Bifidobacteria have long been recognized as bacteria with probiotic and therapeutic features. The aim of this work is to characterize the Bifidobacterium asteroides BA15 and BA17 strains, isolated from honeybee gut. An in-depth assessment was carried out on safety properties (antibiotic resistance profiling, β-haemolytic, DNAse and gelatinase activities and virulence factor presence) and other properties (antimicrobial activity, auto-aggregation, co-aggregation and hydrophobicity). Based on phenotypic and genotypic characterization, both strains satisfied all the safety requirements. More specifically, genome analysis showed the absence of genes encoding for glycopeptide (vanA, vanB, vanC-1, vanC-2, vanD, vanE, vanG), resistance to tetracycline (tet-M, tet-L and tetO), and virulence genes (asa1, gelE, cylA, esp, hyl).

Senna alata (Linn) Roxb. plant is widely used to manage various infections in folkloric medicine. Methicillin-resistant Staphylococcus aureus (MRSA) infection continues to be a major global public health problem. This study aims to investigate the bioactive components of S. alata leaves active against MRSA. The leaves of S. alata were sequentially extracted and fractionated using standard methods and screened for activities against MRSA. The diethyl ether active thin layer chromatography (TLC) spot was subjected to infrared (IR) and gas chromatography-mass spectroscopic (GC-MS) studies. The aqueous extract and diethyl ether fraction of S. alata leaves elicited the highest activity against the MRSA. The GC-MS analysis of the fraction produced 15 eluates; only the sub-fraction 13 was effective. The TLC analysis of the sub-fraction 13 revealed three spots; only the second spot produced activity. The GC-MS result of the spot showed six peaks. The spectral results for peak 3 match the data from the IR study suggestive of 9-octadecenoic acid methyl ester. Senna alata leaves possess bioactive compounds closely related to 9-octadecenoic acid methyl ester with potent antibacterial activity against MRSA.

The problem of drug resistance in terms of antifungal therapy, unknown until a few years ago, is assuming increasing importance. Particularly in immunosuppressed patients and subject to chemotherapy and radiotherapy. In the last years the use of essential oils as approach to improving the effectiveness of antifungal agents and reducing the antibiotic resistant has been proposed. Our research aimed to evaluate the antifungal activity of Colombian essential oil of Ruta graveolens (REO) against clinical strains of Candida albicans, Candida parapsilopsis, C. glabrata and Candida tropicalis. The data obtained showed that Candida tropicalis and Candida albicans were most sensible strains showing minimum inhibitory concentrations (MIC) of 0.5 and 1.0 µg/ml of REO. The Time Kill Kinetics assay demonstrated that REO showed fungicide effect against C. tropicalis and fungistatic effect against C. albicans. In addition, the 40% of the biofilm formed by C. albicans was eradicated using 1% of REO after 1 hour of exposure.

Accurately predicting drug-drug interactions (DDIs) is crucial for preventing adverse drug events in clinical settings. However, existing methodologies often rely on complex models built from diverse data sources, posing challenges in computational drug discovery. To address the need for precise computational methods in predicting unknown DDIs, this study introduces a novel Deep Neural Network (DNN)-based approach. By leveraging a wide range of drug-related information, including substructure, targets, side effects, pathways, and indications, our method calculates multiple drug similarities. These similarities are then synthesized using a nonlinear fusion method to extract high-level features. Subsequently, a tailored neural network is deployed for interaction prediction. Comparative evaluation against three prominent machine learning classifiers—Extreme Gradient Boosting (XGBoost), Adaptive Gradient Boosting (AdaBoost), and Light Gradient-Boosting Machine (LGBM)—using three benchmark datasets demonstrates the superior performance of DNN. It achieves outstanding accuracy, precision, recall, and F1-score metrics, all reaching 94.6% in cross-validation. Additionally, case studies involving numerous drug pairs confirm the reliability of DNN in accurately predicting unknown DDIs. These findings underscore DNN as a potent and reliable method for DDI prediction, with promising implications for drug discovery and healthcare applications.

Background & Aim: Drug sustainability (DS) is a surrogate marker for treatment efficacy. We aimed to compare the DS of two main biologics used to treat moderate-to-severe ulcerative colitis (UC), infliximab (IFX) and vedolizumab (VDZ), in a real-world setting. Methods: We conducted a retrospective cohort study at a tertiary medical center in Israel. We included patients treated between Dec 1st, 2017, and May 1st, 2021, who were followed for up to 300 weeks. DS was defined as corticosteroid, surgical, and hospitalization-free treatment. Results: 217 patients with UC were included. VDZ had a significantly longer median DS of 265.6 weeks compared to IFX's 106.5 weeks (p=0.001) in treatment-naïve patients, even when adjusting for disease severity (HR 0.55 95 CI 0.3-0.98, p=0.042). In treatment-experienced patients, DS was comparable between IFX and VDZ (p=0.593). Conclusion: VDZ showed significantly longer DS in treatment-naïve patients with UC compared to IFX, also when adjusted for disease severity. There was no difference in DS between VDZ and IFX in treatment-experienced patients and patients switching from one drug to another. VDZ may be a suitable first-line treatment for biologic-naïve patients with moderate-to-severe UC.

The worldwide outbreak of SARS-CoV-2 in early 2020 caused numer- ous deaths and unprecedented measures to control its spread. We employed our Computational Analysis of Novel Drug Opportunities (CANDO) multiscale therapeutic discovery, repurposing, and design platform to identify small molecule inhibitors of the virus to treat its resulting indication, COVID-19. Initially, few experimental studies existed on SARS-CoV-2, so we optimized our drug candidate prediction pipelines using results from two independent high-throughput screens against prevalent human coronaviruses. Ranked lists of candidate drugs were generated using our open source cando.py software based on viral protein inhibition and proteomic interaction similarity. For the former viral protein inhibition pipeline, we computed interaction scores between all compounds in the corresponding candidate library and eighteen SARS-CoV proteins using an interaction scoring protocol with extensive parameter optimization which was then applied to the SARS-CoV-2 proteome for prediction. For the latter similarity based pipeline, we computed interaction scores between all compounds and human protein structures in our libraries then used a consensus scoring approach to identify candidates with highly similar proteomic interaction signatures to multiple known anti-coronavirus actives. We published our ranked candidate lists at the very beginning of the COVID-19 pandemic. Since then, 51 of our 276 predictions have demonstrated anti-SARS-CoV-2 activity in published clinical and experimental studies. These results illustrate the ability our platform to rapidly respond to emergent pathogens and provide greater evidence that treating compounds in a multitarget context more accurately describes their behavior in biological systems.

Although marketing authorization holders (MAHs) are involved in monitoring medication safety, it was unclear how they experience their role and current monitoring activities in pregnancy. Therefore, a qualitative study using online focus groups with MAHs and the Belgian umbrella organisation of MAHs was conducted in June-July 2021. In total, 38 representatives of nine organisations participated. Overall, participants reported multiple difficulties with data collection, including underreporting, collection of incomplete information and loss to follow-up. The limited number of high-quality data collected, the unknown denominator and the lack of comparator data complicate MAHs’ data processing activities, preventing them to timely provide evidence in the pregnancy label. Three ‘conflicts’ inherent to the specific position of MAHs were identified explaining the difficulties they experience, i.e., 1) mistrust from patients and healthcare professionals (HCPs); 2) MAHs’ legal obligations and regulatory framework; 3) MAHs’ position outside the healthcare context. To overcome these barriers, MAHs suggested that data registration should occur in close collaboration with patients and HCPs, organized within the healthcare context and performed by using a user-friendly system. In conclusion, the reported difficulties and underlying conflicts of MAHs highlight the need for more effective, collaborative data collection strategies to generate new evidence on this topic.

Mitral regurgitation (MR) is a broadly diffuse valvular heart disease (VHD) with a significant impact on healthcare system and patient’s prognosis. Transcatheter mitral valve interventions (TMVI) are now well-established techniques included in the therapeutic armamentarium for managing patients with mitral regurgitation, either primary or functional MR. Even if guidelines give indications regarding the correct management of this VHD, the wide heterogeneity of patient’s clinical background, valvular and heart’s anatomy make each patient a unique case, in which the appropriate device’s selection requires a multimodality imaging evaluation and a multidisciplinary discussion. Proper pre-procedural evaluation plays a pivotal role to judge the feasibility of TMVI, as well as a cooperative works between imagers and interventionalist is crucial for procedural success. This manuscript aims to provide an exhaustive overview of the main parameters that need to be evaluated for appropriate device selection, pre-procedural planning, intraprocedural guidance and post-operative assessment in the setting of TMVI. In addition, it tries to give some insights about next perspective of structural cardiovascular imaging.

The aim of this work was to classify the business incubators in Spain according to the four phases of startups incubation. Taking into account that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis have been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors, finally the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3 called activity monitoring and control and was related to phase 3 or basic incubation variables. Clusters analysis facilitates the grouping of incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small Business Incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factor 1 and 2. Factor 3 although positive is susceptible to improvement. They are the largest incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.

Polycystic ovary syndrome (PCOS) is a multisystem disorder that presents with a variety of phenotypes involving metabolic, endocrine, reproductive, and psychological symptoms and signs. Women with PCOS are at increased risk of pregnancy complications including implantation failure, miscarriage, gestational diabetes, fetal growth restriction, preterm labour, and preeclampsia (PE). This may be attributed to the presence of specific susceptibility features associated with PCOS before and during pregnancy, such as chronic systemic inflammation, insulin resistance (IR), and hyperandrogenism, all of which have been associated with an increased risk of pregnancy complications. Many of the features of PCOS are reversible following lifestyle interventions such as diet and exercise, and pregnant women following a healthy lifestyle have been found to have a lower risk of complications, including PE. This review summarizes the evidence investigating the risk of PE and the role of nutritional factors in women with PCOS. The findings suggest that the beneficial aspects of lifestyle management of PCOS, as recommended in the evidenced-based international guidelines, extend to improved pregnancy outcomes. Identifying high-risk women with PCOS will allow targeted interventions, early pregnancy screening, and increased surveillance for PE. Women with PCOS should be included in risk assessment algorithms for PE.

As for their large surface area and pore volume, three-dimensional covalent organic frameworks (3D COFs) have emerged as competitive porous materials. However, due to the structural dynamic behavior particularly for imine-linked 3D COFs, potentially unlock their potential for gas storage application. Herein, we showed a pre-locked linker strategy introduces breaking dynamic behavior in 3D COFs. A predesigned planar linker based 3,8-diamino-6-phenylphenanthridine (DPP) was prepared to produce non-dynamic 3D JUC-595, as benzylideneamine moiety in DPP locked the linker flexibility and restrict the molecular-bond rotation of the imine linkages. Upon solvent inclusion and release, the PXRD profile of JUC-595 remained intake, while JUC-594 with flexible benzidine linker experienced crystal transformation due to framework contraction-expansion. As a result, the activated JUC-595 achieved higher surface areas (754 m² g-1) than that of JUC-594 (548 m² g-1). Furthermore, improved CO2 and CH4 storages were also seen in JUC-595 compared with JUC-594. Impressively, JUC-595 recorded high normalized H2 storage capacity that surpass other reported high surface area 3D COFs. This works shows important insight on manipulating structural properties of 3D COF to tune the gas storage performance.

Artificial intelligence (AI)-based models hold the potential to transform higher education if adopted properly and ethically. A prime example is ChatGPT with earlier studies indicating its widespread adoption in academia and by university students. The current study aimed to identify the factors influencing the attitude towards ChatGPT and its usage among university students in Arab countries. A previous survey instrument termed Technology Acceptance Model Edited to Assess ChatGPT Adoption (TAME-ChatGPT) was administered online using a convenience-based approach among the contacts of the authors. Confirmatory factor analysis (CFA) for the survey constructs was done using root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), comparative fit index (CFI), and Tucker-Lewis index (TLI). The final study sample comprised a total of 2240 participant divided as follows: Iraq (n=736, 32.9%), Kuwait (n=582, 26.0%), Egypt (n=417, 18.6%), Lebanon (n=263, 11.7%), and Jordan (n=242, 10.8%). A total of 1048 respondents heard of ChatGPT before the study (46.8%), of which 551 used ChatGPT (52.6%). The mean scores of TAME-ChatGPT constructs showed that the ease of ChatGPT use, positive attitude towards technology and social influence, higher perceived usefulness, the influence of behavioral/cognitive factors, low perceived risks and low anxiety were the determinants of positive attitude to ChatGPT and its use. For both the attitude and usage scales of TAME-ChatGPT, CFA collectively yielded satisfactory fit indices as indicated by low RMSEA and SRMR together with high CFI and TLI. Multivariate analysis showed that attitude to ChatGPT use was significantly influenced by country of residence, age, university type, and the latest grade point average of the students. The current study confirmed the validity of TAME-ChatGPT as a survey instrument to assess the possible determinants of ChatGPT use among university students in Arab countries. The study findings highlighted that successful adoption of ChatGPT in higher education could be dependent on perceived ease of use, usefulness, positive attitudes to technology, social influence, behavioral/cognitive factors, lower anxiety, and minimal perceived risks. The utility of ChatGPT in higher education requires policies that should be tailored for various settings, considering the differences observed in attitude towards ChatGPT among participating students in this study.

The pre-chamber technologies can improve the ignition performance of IC engines by more than two orders in magnitude and thereby substantial economic benefits. Compared with the common pre-chamber, a plug-and-play passive scheme is suitable for quick retrofit, which is getting more attention from the automobile industry. Good scavenging is the precondition for improving turbulent jet ignition performance for a passive pre-chamber. Therefore, detailed evaluations of the scavenging process and turbulent jet ignition deserve investigations for new pre-chamber schemes. In this paper, the effects of design parameters on ignition processes of plug-and-play passive pre-chamber were numerically studied, allowing for the lateral angle, orifice diameter, and vertical angle design. Seven pre-chamber schemes were evaluated, and four optimal ones were selected for bench tests. The characteristics of the scavenging process, turbulent jet ignition, and main-chamber combustion were investigated and analyzed. The results show that allowing for the trade-off between ignition energy and scavenging efficiency, the volume ratio of the pre-chamber to clearance is recommended to be 0.2~0.7%, and the corresponding area-volume ratio is 0.003~0.006 mm-1. Compared with the original natural gas engine, the pre-chamber retrofit can save up to 13.2% fuel consumption, which presents a significant improvement in fuel economy.

Artificial intelligence, a key technological tool in the era of the 4th Industrial Revolution, is being actively applied to education beyond industry, economy, and culture. In the future society, understanding and using artificial intelligence technology will be considered an essential skill for everyone, and the professionalism of AI education for pre-service teachers nurturing future talents is also important. This study verifies the effectiveness of pre-service teachers after undergoing a 15-week extension program consisting of AI Literacy Education (10 weeks), AI-Linked Subjet Education (3 weeks), and Micro-teaching (2 weeks) which was designed to enhance the AI ​​education professionalism of pre-service teachers. The AI Literacy Education section consisted of understanding AI, AI ethics, and basic programming, and the education was conducted through both experience and practice. After that, the pre-service teachers analyzed the curriculum of the 5th and 6th grades of an elementary school, and developed a subject-related education program using AI tools in three stages. Using the developed program, micro-teaching classes were conducted twice. The study results are as follows. First, there was a change in the positive perception of AI (p<.05). Second, the understanding of AI educational technology tools was improved and the recognition of the usefulness of developing a curriculum-related program was expanded. Third, the importance of teacher competency development was learned through the micro-teaching, and the students' understanding of the learning process was expanded.

The aim of this study was to investigate the potential of converting potato peel waste into bio ethanol using an in-house produced multi-enzyme preparation. To achieve this, a variety of pre-treatment strategies, including thermal, chemical, and thermo-chemical methods, were applied to the potato peels. These included boiling for 30 and 60 min, steam at varying pressures and times, and different concentrations of chemicals such as H2SO4, HNO3, CH3COOH, HCl, NaOH, Ca(OH)2, KOH, NH3, and H2O2, either alone or in combination with steam. The pre-treated potato peels were then enzymatically hydrolyzed using a crude multi-enzyme cocktail derived from solid-state fermentation of wheat bran by a natural variety of Aspergillus niger P-19, containing cellulases, hemicellulases, pectinase, and amylases. The most effective pre-treatment combination was found to be 3% H2SO4 followed by steam under pressure and enzymatic hydrolysis using the crude multi-enzyme preparation. This combination resulted in the highest yield of reducing sugars (141.04 ±12.31 g/l) with a 98.49% carbohydrate conversion at a 20% substrate loading, giving an ethanol yield of 43.2 g/l. Furthermore, supplementing the medium with peptone, (NH4)(H2PO4), and ZnSO4 at 0.1%w/v each with 22% and 24% solid, respectively, resulted in appreciable yields of 51.67 and 54.75 g/l, further enhancing the ethanol yield.

This communication investigates possible anomalies in the lithosphere atmosphere and ionosphere on the occasion of the ML=3.3 earthquake that occurred on 1st January 2023 close to Guidonia Montecelio (Rome, Italy). This earthquake followed another event on 23 December 2022 of magnitude ML=3.1 with a very close epicentre (distance less than 1km). Seismological investigations clearly show an acceleration of seismicity in the last six months in the area. Two solutions of fitting time to failure power law on the Cumulative Benioff strain curve are the more likelihood: the ML3.3 of 1 January is the mainshock of seismic sequence or incoming earthquakes of a magnitude of about 4.1 provides a slightly better fit of the seismic data. Further investigation are necessary to assess if the accumulated stress have been totally released or not. No atmospheric anomalies related to this seismic activity have been identified even if some SO2 emissions could come from tectonic or volcanic sources in the South-Tyrrhenian Sea. Swarm satellites' magnetic data shows an anomalous track on 16 December 2022, which is temporally compatible with the seismic acceleration but other sources for the anomalous signal are also possible.

We transformed the existing learning program Language Shower, which is used in some Norwegian day-care centers in the Grorud district of Oslo municipality, into a digital solution using an app for smartphone or tablet with the option for further enhancement of presentation by a NAO robot. The solution was tested in several iterations and multiple day-care centers over several weeks. Measurements of the children’s progress across learning sessions indicate a positive impact of the program using a robot as compared to the program without robot. In-situ observations and interviews with day care center staff confirmed the solution’s many advantages, but also revealed some important areas for improvement. In particular, the speech recognition needs to be more flexible and robust, and special measures have to be in place to handle children speaking simultaneously.

Dietary components are important for the structural and functional development of the brain. Among these, docosahexaenoic acid,22:6n-3 (DHA) is critically required for the structure and development of the growing fetal brain in utero. DHA is the major n-3 long-chain fatty acid in brain gray matter representing about 15% of all fatty acids in the human frontal cortex. DHA affects neurogenesis, neurotransmitter, synaptic plasticity & transmission, and signal transduction in the brain. Studies in animals and humans show that adequate levels of DHA in neural membranes are important for cortical astrocyte maturation and vascular coupling, and helps cortical glucose uptake and metabolism. In addition, specific metabolites of DHA are bioactive molecules that protect tissues from oxidative injury and stress in the brain. A low DHA level in the brain results in behavior changes and is associated with learning problems and memory deficits. In humans, the third trimester-placental supply of maternal DHA to the growing fetus is critically important as the growing brain obligatory requires DHA during this window period. Besides, DHA is also involved in the early placentation process, essential for placental development. This underscores the critical importance of maternal DHA intake for the structural and functional development of the brain. This review describes DHA's multiple roles during gestation, lactation, and the consequences of its lower intake during pregnancy and postnatally on the children's brain development and function.

How, if at all, consciousness can be part of the physical universe remains a baffling problem. This article outlines a new, developing philosophical theory of how it could do so, and offers a preliminary mathematical formulation of a physical grounding for key aspects of the theory. Because the philosophical side has radical elements, so does the physical-theory side. The philosophical side is radical, first, in proposing that the productivity or dynamism in the universe that many believe to be responsible for its systematic regularities is actually itself a physical constituent of the universe, along with more familiar entities. Indeed, it proposes that instances of dynamism can themselves take part in physical interactions with other entities, this interaction then being “meta-dynamism” (a type of meta-causation). Secondly, the theory is radical, and unique, in arguing that consciousness is necessarily partly constituted of meta-dynamic auto-sensitivity, in other words it must react via meta-dynamism to its own dynamism, and also in conjecturing that some specific form of this sensitivity is sufficient for and indeed constitutive of consciousness. The article proposes a way for physical laws to be modified to accommodate meta-dynamism, via the radical step of including elements that explicitly refer to dynamism itself. Additionally, laws become, explicitly, temporally non-local in referring directly to quantity values holding at times prior to a given instant of application of the law. The approach therefore implicitly brings in considerations about what information determines states. Because of the temporal non-locality, and also because of the deep connections between dynamism and time-flow, the approach also implicitly connects to the topic of entropy insofar as this is related to time.

Pre-diabetes is a serious health condition where blood sugar levels are higher than normal, but not high enough yet to be diagnosed as type 2 diabetes. Pre-diabetes puts one at an increased risk of developing type 2 diabetes and heart disease Methodology: A cross-sectional study was carried out on 384 patients aged 20-70 years old, attending the dental clinics to assess the risk for diabetes, using the FINDRISC questionnaire, HbA1c blood test and a periodontal examination. Results: The mean age of participants was 38.90±10.74. 32.3% were categorized as no risk, 46.6% low risk, while 19% and 2.1% moderate and high risk of developing diabetes respectively. Tests for serum HbA1c Level showed 46.1 % had normal HbA1c followed by 18.0% and 3.6 % were pre-diabetic and diabetic respectively. 19.3% of participants had periodontal pockets measuring more than 4mm and 15.9% measuring more than 6mm. Conclusion: The study has proven to be useful in identifying patients at high-risk of developing diabetes. Controlling and managing periodontal disease could be a new aspect to include in the standards for diabetes care. Dental settings could be a successful platform to carry out the screening and risk stratification of pre-diabetic patients.

High oxidative stress in cells due to inflammation process or excessive cell proliferation would produce oxidants or free radicals with biomarkers, one of which is malondialdehyde (MDA). Passion fruit seed’s contain high antioxidant and are expected to decrease the level of cholesterol and MDA. The objective is to identify the effect of passion fruit seed’s ethanol extract in Wistar rats that have been fed with atherogenic feed. The method was preclinical trial (post-test control group design) in rats, by administering passion fruit seed’s ethanol extract for 14 days. This study used 26 male rats aged two months, divided into 5 groups. The result showed significant difference in MDA level which was found in group that was given passion fruit seed extract 10mg/kg BW with positive control group that was given standard feed. Passion fruit seed’s extract showed significant difference in level of triglyceride, which was found in negative control group that was given atherogenic feed with group that was given passion fruit seed’s extract 5mg/kg BW (mean±standard deviation: 1.09±0.30 mg/dL vs 0.77±0.25mg/dL; p=0.048). This study showed that passion fruit seed’s ethanol extract had significant lowering effect in level of MDA, total cholesterol, and triglyceride for 14 days.

Background. Specific clinical risk factors that may be associated with ambulatory outcome following thrombolysis therapy in ischemic stroke patients with pre-stroke depression is not fully understood. This was investigated. Methods. Multivariate analyses were performed to identify predictors of functional ambulatory outcomes. Patient demographics and clinical risk factors served as predictive variables, while improvement or no improvement in ambulatory outcome was considered as the primary outcome. Results. A total of 595 of these patients received rtPA of which 310 patients presented with pre-stroke depression, 217 had no improvement in functional outcome, while 93 patients presented with an improvement in functional outcome. Carotid artery stenosis (OR= 11.577, 95% CI, 1.281 – 104.636, P=0.029) and peripheral vascular disease (OR= 18.040, 95% CI, 2.956-110.086, P=0.002) were more likely to be associated with an improvement in ambulation. Antihypertensive medications (OR= 7.810, 95% CI, 1.401 –43.529, P=0.019),previous TIA (OR= 0.444, 95% CI, 0.517 –0.971, P=0.012), and congestive heart failure (OR= 0.217, 95% CI, 0.318 –0.402, P=0.030) were associated with a no improvement in ambulation. Conclusion. After adjustment for covariates, more clinical risk factors were associated with no improvement when compared with improvement in functional outcome following thrombolysis therapy in an acute ischemic stroke population with pre-stroke depression.

This economic evaluation aims to support policy-making on the combined use of pre-exposure prophylaxis (PrEP) with HIV vaccines by evaluating the potential cost-effectiveness of implementation that would support the design of clinical trials for assessment of combined product safety and efficacy. The target study population is a cohort of men who have sex with men (MSM) in the United States. Policy strategies considered include standard HIV prevention, daily oral PrEP, HIV vaccine, and their combination. We constructed a Markov model based on clinical trial data and published literature. We used a payer perspective, monthly cycle length, a lifetime horizon, and a 3% discount rate. We assumed a price of $500 per HIV vaccine series in the base case. HIV vaccines dominated standard care and PrEP. At current prices,PrEP was not cost-effective alone or in combination. A combination strategy had the greatest health benefit but was not cost-effective (ICER=$463,448/QALY) as compared to vaccination alone. Sensitivity analyses suggest a combination may be valuable for higher-risk men with good adherence. Vaccine durability and PrEP drug prices were key drivers of cost-effectiveness. Results suggest that boosting potential may be key to HIV vaccine value.

Movement disorders can be associated with various drugs and systemic diseases, posing diagnostic challenges for clinicians. This review explores the spectrum of movement disorders associated with pharmacological agents and medical conditions. Drug-induced movement disorders encompass a broad range of conditions resulting from exposure to medications that affect several neurotransmitters. Neuroleptic medications can lead to tardive dyskinesia, characterized by involuntary, repetitive movements. Antipsychotics and antiemetics, including metoclopramide, may induce acute dystonic reactions. Other drugs, such as dopamine receptor-blocking agents, can contribute to drug-induced parkinsonism. Beyond medications, movement disorders can also arise secondary to systemic diseases. Metabolic disorders like Wilson's disease, characterized by copper accumulation, may manifest as chorea or dystonia. Inflammatory conditions such as rheumatoid arthritis and systemic lupus erythematosus can result in secondary movement disorders due to autoimmune-mediated processes affecting the central nervous system. Movement disorders linked to drugs or systemic diseases often necessitate a thorough clinical evaluation, including detailed medication histories and comprehensive systemic assessments. Neuroimaging, laboratory investigations, and, in some cases, cerebrospinal fluid analyses and electrodiagnostic studies help in establishing accurate diagnoses. Management involves addressing the underlying cause, modifying medications, and employing symptomatic treatments.

Skin wounds and their infections by antibiotic resistant bacteria (ARB)are very common in small animals, posing the risk of acquiring ARB by pet owners or antibiotic resistance gene (ARG) transfer to the owners’ microbiota. The aim of this study was to identify the most common pathogens infecting wounds of companion animals, assess their antibiotic resistance and determine the ARGs using culture-based, molecular and proteomic methods. A total of 136 bacterial strains were isolated from wound swabs. Their species was identified using chromogenic media, followed by MALDI-TOF spectrometry. Disk diffusion was used to test the antibiotic resistance and twelve ARGs were detected using PCRs. The dominant species included Staphylococcus pseudintermedius (9.56%), E. coli and E. faecalis (both n=11, 8.09%). Enterobacterales were mostly resistant to amoxicillin/clavulanic acid (68.3% strains), all Pseudomonas were resistant to ceftazidime, piperacillin/tazobactam, imipenem and tylosin, Acinetobacter was mostly resistant to tylosin (55.5%), all Enterococcus were resistant to imipenem, 39.2% of Staphylococci were resistant to clindamycin. Among ARGs, strA (streptomycin resistance), sul3 (sulfonamide resistance) and blaTEM, an ESBL determinant, were the most frequent. The risk of ARB and ARD transfer between animals and humans causes the need to search for new antimicrobial therapies in the future veterinary medicine.

Urinary tract infections (UTIs) caused by pathogens, particularly E. coli, have spontaneously become resistant to antimicrobial drugs in recent years. Therefore, regular monitoring and alternative strategies for the antimicrobial agent are crucial for combating antimicrobial resistance and bacterial biofilms. Here, we report a new cobalt iron oxide-conjugated tin oxide nanocomposite that can kill bacteria and treat multidrug-resistant E. coli posing UTIs. Following the isolation and identification of E. coli, we tested 57/134 samples against sixteen commonly used antibiotics phenotypically using the disk diffusion method to determine their sensitivity pattern. Of the 57 E. coli isolates, 66% (38/57) were multidrug-resistant. The E. coli isolates were resistant to cephradine (70.17%), ceftriaxone (59.64%), and azithromycin (59.64%), followed by cefixime (54.38%), cefuroxime sodium (52.63%), and co-trimoxazole (50.87%). X-ray diffraction results showed the crystallite sizes were about 5.68 and 8.84 nm in pure SnO2 nanoparticles and 95% SnO2-5% CoFe2O4 nanocomposite, respectively. Energy-dispersive X-ray spectroscopy and Fourier transform infrared determined the fundamental structure of the nanocomposite, encompassing Co, Fe, Sn, and O. Moreover, FTIR measurements implied that the distinct functional groups in both SnO2 and CoFe2O4 nanoparticles existed in a 95% SnO2-5% CoFe2O4 nanocomposite. Field emission scanning electron microscope analysis uncovered that the SnO2-CoFe2O4 nanocomposite had a size of roughly 24 nm and was spherical. In addition, the biosynthesized SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite were evaluated for their antibacterial activity. At a minimum 100 µg/mL concentration, SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite showed high antibacterial activity. The SnO2 nanoparticles and SnO2-CoFe2O4 nanocomposite demonstrated antibacterial activity on multidrug-resistant E. coli at 10 ± 0.7 and 16 ± 0.8 mm zone of inhibition, respectively. In conclusion, the new SnO2-CoFe2O4 nanocomposite might be a potential candidate for treating UTIs caused by drug-resistant E. coli in the foreseeable future.

Drought stress imposes substantial constraints on the growth and production of wheat (Triticum aestivum L.), a globally important cereal crop that is essential for food security. To mitigate these adverse effects, researchers are intensifying their efforts to comprehend how different genotypes respond to drought stress, aiding in the development of sustainable breeding and management strategies. This review summarized past and recent research on genotype-dependent responses of wheat to drought stress, encompassing morphological, physiological, biochemical, molecular, genetic, and epigenetic reactions in plants. Screening of drought-affected features at early developmental stages can provide valuable insights into the adult growth stages that are closely linked to plant productivity. The review underscores the importance of identifying key traits associated with drought resistance, and the potential of leveraging wheat diversity to select cultivars with desirable agronomic characteristics. It also highlights recent advancements in investigating Bulgarian wheat genotypes with varying levels of drought tolerance, specifically in detecting essential features contributing to drought tolerance. Cultivating drought-resistant wheat genotypes and understanding stress stability determinants could markedly contribute to enhancing wheat production and ensuring stable yields under changing climate conditions.

: Introduction: Discovering compounds with antibacterial activity is crucial in the current fight against antibiotic-resistance. Material and Methods: We generate two QSAR model to design six new heteroaryl drug candidates; we assessed the antibacterial properties of the compounds against nine ATCC strains, the majority being part of the ESKAPE group, that include Enterococcus faecalis, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and also Salmonella enterica and Escherichia coli. We performed a synergic assay in which we combined PB4, a compound that we have previously tested in published studies, with GC-VI-70, one of the new compounds with the best cytotoxicity/MIC profile. We tested sub-MIC concentrations of PB4 with five antibiotics (linezolid, gentamycin, ampicillin, erythromycin, rifampin and imipenem) to examine the synergic effect on the ATCC strains. To evaluate compounds’ cytotoxicity, we performed a 24-hour and 48-hour 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay on Colorectal Adenocarcinoma (CaCo-2) cells. The antibiotics were tested, alone and in combination with PB4. Results: PB4 lowered the MIC measured for GC-VI-70 and for the various antibiotics employed in clinical use, and all the compounds presented in this study have cytotoxic activity against cells. Conclusions: These compounds show promising use in combination with antibiotics to improve their effectiveness at low concentrations, to prevent unwanted cytotoxic effects.

The incidence of carbapenem-resistant Enterobacteriaceae (CRE) has been increasing considerably annually since being first reported in 2008. Gyeonggi Province has the largest number of healthcare facilities in South Korea, which contribute to its regional vulnerability to CRE infections. Thus, there is a need to obtain up to date information on the occurrence of CRE infections in the Gyeonggi Province to take corrective measures. Therefore, in this study, we aimed to investigate the overall trends of CRE occurrence in Gyeonggi Province over the past 4 years and the epidemiological characteristics of CRE-related mortality. Patients admitted to a healthcare facility in Gyeonggi Province from January 2018 to December 2021 with positive blood cultures to CRE were included in the study and investigated. Additionally, the risk factors for CRE-related death were determined using data from CRE-positive patients who died within 30 days of last blood sampling. Older adults aged 70 and over accounted for the highest percentage of both survivors and non-survivors with CRE bacteremia. The number of non-survivors was higher in tertiary hospitals and among patients in intensive care unit. There were no significant differences in the mortality risk according to the use of antibiotics. Moreover, non-survivors were predominant among patients with hypertension, malignant tumor, and those having two or more underlying diseases. Klebsiella pneumoniae was the most common CRE strain in both survivors and non-survivors. Among the survivors, carbapenemase-producing Enterobacteriaceae was detected in 151 cases (71.2%) and 49 cases (23.1%) in the KPC and NDM groups, respectively. Among the non-survivors, it was detected in 25 cases (86.2%) and 5 cases (17.2%) in the KPC and NDM groups, respectively. The endemicity of CRE in South Korea has been proposed for several years; our results have suggested endemicity of CRE in the Gyeonggi Province. Despite the strengthened infection control policies in healthcare facilities during the pandemic, there has been an increasing trend in the isolation of CRE strains in South Korean long-term care hospitals and hospitals within Gyeonggi Province. Factors such as history of hospitalization and underlying diseases have been identified as risk factors for CRE-related deaths. However, to address this issue strictly, it is important to establish infection control infrastructure tailored based on each type of healthcare facility, and elaborate specific government support measures, accordingly.

The increasing prevalence of methicillin-resistant S. aureus (MRSA) in the dairy industry has become a fundamental concern. Endolysins are bacteriophage-derived peptidoglycan hydrolases that induce the rapid lysis of host bacteria. We investigated endolysin candidates with lytic activity against MRSA and evaluated the lytic activity of the endolysin candidate against S. aureus and MRSA. To identify endolysins, we used the following bioinformatic strategy: (1) retrieval of genetic information, (2) annotation, (3) selection of MRSA, (4) selection of endolysin candidates, and (5) evaluation of protein solubility. We then characterized the endolysin candidate under various conditions. Approximately 67% of S. aureus was detected as MRSA and a total of 114 putative endolysins were found. The 114 putative endolysins were divided into three groups based on their combination of conserved domains. Considering the protein solubility, we selected putative endolysins 177 and 117. Putative endolysin 117 was successfully overexpressed and renamed LyJH1892. LyJH1892 lysed approximately 85% of S. aureus. LyJH1892 showed more potent lytic activity against MRSA than normal S. aureus (relative lytic activity &gt; 125%). LyJH1892 showed broad lytic activity against coagulase-negative Staphylococci (CNS). In conclusion, These findings provide a rapid and useful strategy for the development of specific endolysins against antibiotic-resistant bacterial strains.

In this study, we discuss the properties of absolute vacuum space and how these properties can play a vital role in creating a mechanism in which the very first particle gets created simultaneously everywhere and we find the limit in which when the absolute vacuum volume reaches will lead to the collapse that leads to the creation of the first particle. This discussion is made following to the elementary dimensions theory study that was peer-reviewed at the end of 2020, everything in the universe is made from four elementary dimensions, these dimensions are the three spatial dimensions (X, Y, and Z) and the Vacuum resistant as the factor of change among the four, time itself wasn’t considered as the fourth dimension, rather time corresponds to a factor of change, and during the research it was found out that the Vacuum resistant is the factor of change in the Absolute Vacuum space, where time is a hypothetical concept, that represents changes during certain events compared to a constant change rate event.Therefore, time does exist, but as a factor of change, and as the Vacuum resistant in the absolute vacuum space, Time= factor of change= Vacuum resistant. In the study, the internal and external vacuum resistant volume equivalent is found, External Vacuum resistant=3.2857602*10^15 *mass. This equation is used to identify the amount of Free external vacuum resistant created during nuclear fission and fusion: Initial mass of the excited nucleuses mass of the created new nucleuses+ 3.2857602*10^15 * the lost Mass. In elementary dimensions, the energy created during nuclear reactions is equivalent to the free External vacuum resistant created through nuclear reactions, and mass is equivalent to the internal Vacuum resistant.

Infections by methicillin-resistant Staphylococcus aureus (MRSA) are continuously expanding within the community. Chicken meat is usually contaminated by MRSA, and this contaminated chicken meat is an important source of foodborne infections in humans. In this study, a cross-sectional supershop survey was conducted to determine the prevalence and antimicrobial resistance pattern of MRSA in 113 domestic frozen chicken meat samples purchased from nine branded supershops available in five divisional megacities of Bangladesh. The study also focused on the determination of methicillin resistance gene in MRSA isolates. S. aureus was identified by standard culture-based and molecular methods, and subjected to antimicrobial susceptibility testing. MRSA was screened by cefoxitin disk diffusion test. Methicillin resistance gene was identified by PCR. Of samples, 54.9% were positive for S. aureus, and, of these, 37.1% isolates were identified as MRSA. All the isolates were multidrug resistant (MDR): 52.2% were resistant to 6−8 antimicrobial classes, and 47.8% isolates to 9−12 classes. Three (3.2%) isolates of S. aureus were possible extensively drug resistant. The highest rates of resistance were observed against cefoxitin (100%), followed by nalidixic acid, ampicillin and oxacillin (97.7%), colistin (91.3%), amoxicillin-clavulanic acid and amoxicillin (87%), penicillin-G and cloxacillin (82.6%), oxytetracycline (78.3%) and cefixime (73.9%). Screening of methicillin resistance gene revealed that 43.5% isolates of MRSA were positive for mecA gene. The high prevalence of MDR MRSA in frozen chicken meat samples in this study emphasizes the need for better sanitary education of food handlers in hygienic practices focusing on their potential role as reservoirs and spreaders of MRSA.

Resistance to hormone therapy and disease progression is the major challenge in clinical management of prostate cancer (PC). Drugs currently used in PC therapy initially show a potent antitumor effect. Nevertheless, PC gradually develops resistance, relapses and spreads. Most patients develop, indeed, castrate-resistant PC (CRPC), which is almost incurable. The nerve growth factor (NGF) acts on a variety of non-neuronal cells by activating the NGF tyrosine-kinase receptor, TrkA. NGF signaling is deregulated in PC. In androgen-dependent PC cells, TrkA mediates the proliferative action of NGF through its cross talk with the androgen receptor (AR). Epithelial PC cells, however, acquire the ability to express NGF and TrkA, as the disease progresses, indicating a role for NGF/TrkA axis in PC progression and androgen-resistance. We here report that once activated by NGF, TrkA mediates proliferation, invasiveness and epithelial-mesenchyme transition (EMT) in various CRPC cells. NGF promotes organoid growth in 3D models of CRPC cells, and specific inhibition of TrkA impairs all these responses. Thus TrkA represents a new biomarker to target in CRPC.

In California, an average of 41,900 patients are diagnosed annually with Staphylococcus bacterial infection; out of these, 24,090 patients have methicillin-resistant Staphylococcus aureus (MRSA) infection and 17,810 patients have methicillin-sensitive Staphylococcus aureus (MSSA) infection. The aim of this paper is to find out whether there is a significant difference in strain dominancy and in what direction. The paper gathered and analyzed data for period of five years of infection rate due to Staphylococcus aureus. This study indicates that a significant difference in dominancy exists, the MRSA infection rate (an average of five years period) is 1.35 times higher than the MSSA infection rate (P-value < 0.05, CI: 95%), but the gap between the two infection rates is decreasing. The infection rate of both MRSA and MSSA is in a path of decline.

The release of drugs from core/shell nanoparticles (NPs) is a crucial factor in ensuring high re-producibility, stability, and quality control. It serves as the scientific basis for the development of nanocarriers. Several factors, such as composition, composition ratio, ingredient interactions, and preparation methods, influence the drug release from these carrier systems. The objective of our study was to investigate and discuss the relationship between modifications of core/shell NPs as multifunctional drug delivery systems and the properties and kinetics of drug release using an in vitro drug release model. In this paper, we prepared four core/shell NPs consisting of a super-paramagnetic iron oxide NPs (Fe3-δO4) core encapsulated by a biocompatible thermo-responsive copolymer, poly(2-(2-methoxy) ethyl methacrylate-oligo (ethylene glycol) methacrylate) or P(MEO2MAx-OEGMA100-x) (where x and 100-x represent the molar fractions of MEO2MA and OEGMA, respectively), and loaded with doxorubicin (DOX). Colloidal behavior measurements in water and PBS as a function of temperature showed an optimization of the lower critical solu-tion temperature (LCST) depending on the molar fractions of MEO2MA and OEGMA used to form each NPs. In vitro studies of doxorubicin release as a function of temperature demonstrated a high control of release based on the LCST. A temperature of approximately 45°C for 60 h was sufficient to release 100 % of the DOX loaded in the NPs for each sample. In conclusion, external stimuli can be used to modulate the drug release behavior. Core/shell NPs hold great promise as a technique for multifunctional drug delivery systems.

The multifactorial nature of some diseases, and in particular neurodegenerative diseases such as Alzheimer’s disease, frequently requires the use of several drugs. These drug cocktails are not without drawbacks in terms of increased adverse effects, drug-drug interactions or adherence to treatment. The concept of pleiotropic drugs, which combine, within a single molecule, several activities directed against distinct therapeutic targets, makes it possible to overcome some of these problems. In addition, these pleiotropic drugs, generally, lead to the expression of a synergy of effects, sometimes greater than that observed with a combination of drugs. This article will review, through recent examples, the different kinds of pleiotropic drugs being studied or already present on the market of medicines.

With opioid overdose rates on the rise, we aim to develop a county-level risk stratification, specifically focusing on access to Medications for Opioid Use Disorder (MOUD) and high overdose rates. We examined over 15 million records from the South Carolina Prescription Tracking System (SCRIPTS) across 46 counties. Additionally, we incorporated data from opioid treatment programs, healthcare professionals prescribing naltrexone, clinicians with buprenorphine waivers, and county-level overdose fatality statistics. To assess the risk of opioid misuse, we classified counties into high-risk and low-risk categories based on prescription rates, overdose fatalities, and treatment service availability. Utilizing statistical methods, we compared prescription patterns and outcomes between these groups. Our study shows that between 2017 and 2021, opioid prescriptions decreased from 64,223 to 41,214 per 100,000 residents, while fentanyl-related overdose deaths increased by 312%. High-risk counties have significantly higher rates of fentanyl prescriptions and rely more on out-of-state doctors. They also exhibit higher instances of doctor shopping and had fewer medical doctors per capita, with limited access to MOUD. To effectively combat the opioid crisis, we advocate for improved local healthcare infrastructure, broader treatment access, stricter management of out-of-state prescriptions, and vigilant tracking of prescription patterns. Tailored local strategies are essential for mitigating the opioid epidemic in these communities.

This study proposes an innovative pharmacovigilance approach, VIGI-4, leveraging ChatGPT Teams Pro version. Our method involves aggregating data from all phase 4 studies published in February 2024 to identify adverse reactions. These results are categorized by disease state alphabetically, demonstrating the method's capacity to generate structured and easily navigable outputs. The results section is tailored to exemplify the valuable, actionable insights attainable through our workflow. This research emphasizes the game-changing potential of integrating advanced technologies such as ChatGPT into pharmacovigilance, signaling a new era in safeguarding drug safety.

Background: The Coronavirus Disease 2019 (COVID-19) pandemic presented a new challenge in modern medicine. The development of vaccines was followed by massive population vaccinations. A few reports on post-vaccination allergic reactions have made patients and medical personnel uneasy as to anti-COVID-19 vaccines’ allergising potential. Most of the studies in this area to date have been small, and some that were based on global databases skipped most of the allergic diseases and concentrated only on anaphylaxis. We aimed to analyse the incidence of serious allergic reactions based on the EudraVigilance (EV) database, regardless of the reported symptoms and allergy mechanism. Methods: The total number of administrated vaccine doses was extracted on the 5th October 2023 from Vaccine Tracker and included all administrations since vaccinations began in the European Economic Area (EEA). Data on serious allergic reactions to COVID-19 vaccines was extracted from the EudraVigilance database with the same time point. The code names of 147 allergic symptoms or diseases were used. Results: The frequency of serious allergic reactions per 100,000 administered vaccine doses was 1.53 for Comirnaty, 2.16 for Spikevax, 88.6 for Vaxzevria, 2.11 for Janssen, 7.9 for Novavax, 13.3 for VidPrevtyn Beta and 3.1 for Valneva. The most prevalent reported reactions were oedema (0.46) and anaphylaxis (0.40). Only 6% of these reactions were delayed hypersensitivity-oriented. Conclusions: The overall frequency of potential serious allergic reactions to COVID-19 is very rare. Therefore, COVID-19 vaccines seem to be safe for human use. The lowest frequency of allergic reaction was observed for Comirnaty and the highest for Vaxzevria.

This report provides a comprehensive overview of occupational asthma and respiratory hypersensitivity, focusing on some chemicals used in the workplace Includes numerous case studies and research papers related to occupational exposure methacrylates, such as HEMA-HPMA, and respiratory hypersensitivity are discussed And the relationship is explored The book also examines asthma pathophysiology, emerging drug delivery systems used to treat asthma, and the potential of nanoparticles , dendrimers and micellar systems have to improve pulmonary drug delivery in detail The worldwide prevalence of asthma is highlighted, with higher rates in high-GDP countries. The book highlights the need to improve asthma diagnosis, treatment and biomarkers, particularly in rural and low-income countries where the disease is often underdiagnosed and inadequately treated, and discusses the role of inflammation in asthma, in particular secondary inflammation characterized by specific cytokines and inflammation cells In addition, the paper explores various drug delivery methods, such as parenteral and parenteral drugs, pressurized inhalers (pMDIs), dry powder inhalers ( DPIs), nebulizers, nanoparticles, liposomes, micellar systems, microparticles , dendrimers, and gene therapy . These systems aim to increase pulmonary delivery of drugs and improve clinical outcomes. The potential of dendrimer bilirubin-based nanoparticles and micellar systems in the treatment of asthma and lung inflammatory diseases, including asthma, has been discussed in summary, this paper provides an overview of occupational asthma and respiratory hypersensitivity, and this discussion highlights the association between methacrylate exposure and respiratory hypersensitivity.

Animal trypanosomiasis (AT) is a complex of veterinary diseases known under various names such as nagana, surra, dourine and mal de caderas, depending on the country, the infecting trypanosome species and the host. AT is caused by parasites of the genus Trypanosoma, and the main species infecting domesticated animals are T. brucei brucei, T. b. rhodesiense, T. congolense, T. vivax, T. evansi and T. equiperdum. AT transmission, again depending on species, is through tsetse flies or common Stomoxys and tabanid flies or through copulation. Therefore, the geographical spread of all forms of AT together is not restricted to the habitat of a single vector like the tsetse fly and currently includes almost all of Africa, and most of South America and Asia. The disease is a threat to millions of companion and farm animals in these regions, creating a financial burden in the billions of dollars to developing economies as well as serious impacts on livestock rearing and food production. Despite the scale of these impacts, control of AT is neglected and under-resourced, with diagnosis and treatments being woefully inadequate and not improving for decades. As a result, neither the incidence of the disease, nor the effectiveness of treatment is documented in most endemic countries, although it is clear that there are serious issues of resistance to the few old drugs that are available. In this review we particularly look at the drugs, their application to the various forms of AT, and their mechanisms of action and resistance. We also discuss the spread of veterinary trypanocide resistance and its drivers, and highlight current and future strategies to combat it.

Intermolecular interactions are the fabrics underlying almost all processes in living organisms, where two cornerstone concepts, intermolecular binding affinity (K d ) and binding energy (ΔG), have long been established to physically describe the strengths of biomolecular interactions, e.g., drug-target K d and ΔG to describe the strength of drug-target interaction. The past two-three years saw a big step forward in the use of artificial intelligence (AI) in structural biology (e.g., AlphaFold for protein structure prediction) and drug discovery & design. In light of the roles of K d and ΔG in drug discovery & design, the speed of this AI progress raises a question of what’s next for its practical application in the pharmaceutical industry, in addition to a system-wide account of biomolecular structures and motions. Last August, the concept of a general intermolecular binding affinity calculator (GIBAC) was for the first time coined and proposed in an MDPI-published preprint. Here, this article puts forward an updated conceptual and practical framework of GIBAC, including its inception, definition, construction, practical applications, technical challenges and limitations, and future directions. Moreover, this article argues that the time is now ripe for the construction of such an accurate, precise and efficient GIBAC to be on the agenda of the entire drug discovery & design community, to ensure its applicability & reliability, and to enhance its value in drug R&D in future.

Background: Chronic Hepatitis B Virus (HBV) infection is a global health concern, associated with severe liver diseases, necessitating ongoing research on novel drug candidates. This study aims to identify potential drug candidates targeting HBV core protein (HBcAg) and disrupting capsid assembly, a critical step in the virus's life cycle. Methods: HBcAg in complex with HBV inhibitors were obtained from the Protein Data Bank (PDB). CavityPlus server was used for analysis of druggable cavity. Structure-based pharmacophores were extracted from identified cavities, and potential allosteric ligand binding sites were assessed using CavPharmer, CorrSite, and CovCys. LigandScout was employed for ligand-based pharmacophore screening against an FDA-approved library. The ZINC database was screened with features extracted from CavPharmer. Molecular docking studies were conducted using Autodock Vina. Lead compounds were selected based on docking scores, binding modes, and interactions within the druggable cavity. Results: Strong druggable pockets were found for Ciclopirox, while Compound 24, NVR10-001E2, and others showed medium to weak pockets. Ligand-based pharmacophores varied in size and complexity. Screening revealed potential hits matching these pharmacophores, including Ciclopirox olamine, Voriconazole, Enasidenib, and Statins. A large compound database search yielded additional hits like ZINC86859997 and ZINC63280172. Docking analyses confirmed these hits' potential, highlighting their interactions with critical HBc protein residues, offering promising leads for hepatitis B drug development. Conclusions: Voriconazole, Enasidenib, and Lovastatin have shown promises. These hits displayed favorable interactions with crucial HBc protein residues, indicating their potential as lead compounds The mechanism of action of statins with anti-HBV activities also highlighted. This comprehensive approach offers valuable insights into targeting HBc protein for antiviral drug discovery.

Esophageal cancer is a formidable challenge in the realm of cancer treatment. Conventional methods such as surgery, chemotherapy, and immunotherapy have demonstrated limited success rates in managing this disease. In response, targeted drug therapies have emerged as a promising strategy to improve outcomes for patients. These therapies aim to disrupt specific pathways involved in the growth and development of esophageal cancer cells. This review explores various drugs used to target specific pathways, including cetuximab and monoclonal antibodies (gefitinib) that target the epidermal growth factor receptor (EGFR), trastuzumab that targets human epidermal growth factor receptor 2 (HER-2), drugs targeting the vascular endothelial growth factor receptor (VEGFR), mTOR inhibitors, and cMET inhibitors. Additionally, the article discusses the impact of drug resistance on the effectiveness of these therapies, highlighting factors such as cancer stem cells, cancer-associated fibroblasts, immune-inflammatory cells, cytokines, hypoxia, and growth factors. While drug targeting approaches do not provide a complete cure for esophageal cancer due to drug resistance and associated side effects, they offer potential for improving patient survival rates.

Artificial intelligence AI or machine learning has proven to be a potential activity in the health and biomedical sciences. Previous research it has found that AI can learn new data and transform it into the useful knowledge. In the field of pharmacology, the aim is to design more efficient and novel vaccines using this method which are also cost effective. The underlying fact is to predict the molecular mechanism and structure for increased likelihood of developing new drugs. Clinical, electronic and high resolution imaging datasets can be used as inputs to aid the drug development niche. Moreover, the use of comprehensive target activity has been performed for repurposing a drug molecule by extending target profiles of drugs which also include off targets with therapeutic potential providing a new indication.

Introduction: Valproic acid (VPA) is an antiepileptic drug extensively used for treating partial and generalised seizures, acute mania and as prophylaxis for bipolar disorder. Drug-induced liver injury (DILI) persists as a significant issue related to fatal outcomes by VPA. The aim of this study was to increase our knowledge about this condition and to better identify patients affected. Methods: We conducted an observational retrospective case-control study that identified cases of DILI by VPA from the Pharmacovigilance Programme from our Laboratory Signals at La Paz University Hospital from January 2007 to December 2019. From the Therapeutic VPA Monitoring Programme, two control groups were assigned, VPA-tolerant patients and the other with patients who developed mild VPA-related hepatitis but who did not meet the DILI criteria, matched for date, age and sex. Results: A total of 60 patients were included in the study: 15 cases of DILI, 30 VPA-tolerant controls and 15 controls with mild hepatitis. Mean age for the cases was 45.7 years, 4(26.7%) were women and 5(33.34%) were children under 18 years, of them 3(20%) were fatal. Polytherapy with other antiepileptic drugs (p=0.047) and alcohol consumption (p<0.001) were associated with a greater risk of developing DILI by VPA. A diagnosis of epileptic seizure was more frequently related to DILI when compared with the VPA-tolerant controls (p<0.001). The cases developed hepatocellular hepatitis (p<0.001), while the mild hepatitis controls had a higher rate of cholestatic hepatitis (p<0.001). The laboratory lactate dehydrogenase values were statistically higher (even at baseline) in patients with DILI than in both control groups (p= 0.033 and p=0.039). Conclusions: VPA hepatotoxicity remains a considerable problem. This study offers interesting findings for characterising VPA-induced liver injury and at-risk patients.

The Novel Coronavirus (COVID-19) is a positive-sense single-stranded RNA ((+)ssRNA) virus. The COVID-19 Main Proteases play very important role in the propagation of the Novel Coronavirus (COVID-19). It has already killed more than 8000 people around the world and thousands of people are getting infected every day. Therefore, it is very important to identify a potential inhibitor against COVID-19 Main Proteases to inhibit the propagation of the Novel Coronavirus (COVID-19). We have applied a drug repurposing approach of computational methodology, depending on the synergy of molecular docking and virtual screening techniques, aimed to identify possible potent inhibitors against Novel Coronavirus (COVID-19) from FDA approved antiviral compounds and from the library of active phytochemicals. On the basis of recently resolved COVID-19 Main Protease crystal structure (PDB:6LU7), the library of 100 FDA approved antiviral compounds and 1000 active components of Indian Medicinal Plants extracted for screening against COVID-19 Main Protease. The compounds were further screened using Pyrex virtual screening tool and then best inhibitors, top 19 compounds optimally docked to the COVID-19 Main Protease structure to understand the participation of specific amino acids with inhibitors at active sites. Total 19 best compounds were identified after screening based on their highest binding affinity with respect to the other screened compounds. Out of 19, 6 best compounds were further screened based on their binding affinity and best ADME properties. Nelfinavir exhibited highest binding energy -8.4 kcal/mol and strong stability with the TRP207, ILE281, LEU282, PHE3, PHE291, GLN127, ARG4, GLY283, GLU288, LYS5, LYS137, TYR126, GLY138, TYR126, SER139 and VAL135 amino acid residues of COVID-19 Main Protease participating in the interaction at the binding pocket. In addition to Nelfinavir (-8.4), Rhein (-8.1), Withanolide D (-7.8), Withaferin A (-7.7), Enoxacin (-7.4), and Aloe-emodin (-7.4) also showed good binding affinity and best ADME properties. Our findings suggest that these compounds can be used as potential inhibitors against COVID-19 Main Protease, which could be helpful in inhibiting the propagation of the Novel Coronavirus (COVID-19). Moreover, further in vitro and in vivo validation of these findings would be very helpful to bring these inhibitors to next level study.

The similarities between exosomes and liposomes, together with the high organotropism of several types of exosomes, have recently prompted the development of engineered-exosomes or exosome-mimetics, which may be artificial (liposomal) or cell-derived vesicles, as advanced platforms for targeted drug delivery. Here we provide the current state-of-the-art of using exosome or exosome-inspired systems for drug delivery. We review the various approaches investigated and the shortcomings of each approach. Finally the challenges identified up-to-date in this field are summarized.

Traditional methods for discovery and development of new drugs can be a very time-consuming and expensive process because it includes several stages such as compound identification, pre-clinical and clinical trials before the drug is approved by the US Food and Drug Administration (FDA). Therefore, drug repurposing, namely using currently FDA-approved drugs as therapeutics for other diseases than what they are originally prescribed for, is emerging to be a faster and more cost-effective alternative to current drug discovery methods. In this paper, we have described a three-step in silico protocol for analyzing transcriptomics data using online databases and bioinformatics tools for identifying potentially repurposable drugs. The efficacy of this protocol was evaluated by comparing its predictions with the findings of two case studies of recently reported repurposed drugs: HIV treating drug Zidovudine for the treatment of Dry Age-Related Macular Degeneration and the antidepressant Imipramine for Small-Cell Lung Carcinoma. The proposed protocol successfully identified the published findings, thus demonstrating the efficacy of this method. In addition, it also yielded several novel predictions that have not yet been published, including the finding that Imipramine could potentially treat Severe Acute Respiratory Syndrome (SARS), a disease that currently does not have any treatment or vaccine. Since this in-silico protocol is simple to use and does not require advanced computer skills, we believe any motivated participant with access to these databases and tools would be able to apply it to large datasets to identify other potentially repurposable drugs in the future.

Land cover mapping, essential for understanding global land use patterns, relies on satellite imagery for monitoring changes, assessing ecosystem health, and supporting conservation ef- forts. However, significant challenges remain in managing large, complex satellite imagery datasets, acquiring specialized datasets due to high costs and labor intensity, and a lack of comparative studies for optimal deep learning model selection. Additionally, a scarcity of aerial datasets specifically tailored for agricultural areas exists. This study addresses these gaps by presenting a method for semantic segmentations of land covers in agricultural areas using satellite images and deep learning models with pre-trained backbones. We introduce an efficient methodology for preparing semantic segmentation datasets and contribute the "Land Cover Aerial Imagery" (LICAID) dataset for semantic segmentation. The study focuses on the Franciacorta area, Lombardy Region, leveraging the rich diversity of the dataset to effectively train and evaluate the models. We conduct a comparative study, employing cutting-edge deep learning-based segmentation models (U-Net, SegNet, DeepLabV3) with various pre-trained backbones (ResNet, Inception, DenseNet, EfficientNet) on our dataset acquired from Google Earth Pro. Through meticulous data acquisition, preprocessing, model selection, and evaluation, we demonstrate the effectiveness of these techniques in accurately delineating land cover classes. Integrating pre-trained feature extraction networks significantly improves performance across various metrics. Additionally, addressing challenges such as data availability, computational resources, and model interpret-ability is essential for advancing the field of remote sensing and supporting sustainable environmental stewardship worldwide.

Based on a constant volume combustion chamber, the initial ambient pressure effect on combustion performance and flame propagation of the active and passive pre-chamber ignition systems were studied. Compared with the passive pre-chamber, the active pre-chamber can significantly expand the lean combustion limit, enhance the ignition and combustion performance, and speed up the combustion of the main combustion chamber. At slightly lean combustion conditions, the heat release performance has a positive correlation with the initial ambient pressure. As the premixed λ increases, the heat release performance and the initial ambient pressure begin to become negatively correlated. Ignition delay can be minimized by controlling the excess air coefficient in the pre-chamber close to the stoichiometric ratio. The high ambient pressure in the constant volume chamber greatly reduces the mixture entrainment ability of the jet flame at lean combustion conditions, thereby reducing the combustion speed and peak heat release rate.

Hemangioblasts give rise to endothelial progenitor cells (EPCs), which also express the cell surface markers CD133 and C-kit. They may differentiate into the outgrowth endothelial cells (OECs) that control neovascularization in the developing embryo. Reduced levels of EPC in circulation have been linked to human cardiovascular disorders, according to numerous studies. Furthermore, preeclampsia and senescence have been linked to levels of EPCs produced from cord blood. Uncertainties surround how preeclampsia affects the way EPCs function. It is reasonable to speculate that preeclampsia may have an impact on the function of fetal EPCs during the in utero period; however, given the present literature's suggestion that maternal vasculopathies, including preeclampsia, damage fetal circulation. Additionally, the differentiation potential and general activity of EPCs may serve as an indicator of the health of the fetal vascular system since they promote neovascularization and repair during pregnancy. Thus, the purpose of this review is to compare, through assessment of their quantity, differentiation potency, angiogenic activity, and senescence, the angiogenic function of fetal EPCs obtained from cord blood for normal and pregnancy problems. This will shed light on the relationship between the angiogenic function of fetal EPCs and pregnancy complications, which could have an effect on the management of long-term health issues like metabolic and cardiovascular disorders in offspring with abnormal vasculature development.

Based on the teaching material of "Robotics" course, this paper studied the automatic knowledge graph construction, including knowledge points extraction and knowledge point relation extraction. We proposed a new method of extracting the first-level, second-level, and third-level knowledge points as well as their prerequisite relations of knowledge points in the textbook. For the problem of insufficient knowledge of the pre-trained language model in the specific field, methods such as incremental pre-training and optimization of cost functions are employed to integrate subject knowledge into the pre-trained language model, thus improving its effectiveness. To overcome the problem that the traditional method of relationship extraction can not be applied directly to the extraction of teaching materials, a new scheme for knowledge point relationship extraction based on keyword relationship is proposed. The experimental data from textbooks shows that the F1 score of knowledge point extraction reaches 93%, considerably improved compared to the traditional model. Consequently, the knowledge point entity extraction and relationship extraction methods based on the pre-trained model can effectively extract structured information and facilitate the automatic construction of knowledge graphs.

Red raspberry fruit production is increasing worldwide due to the growing consumer interest in foods with high antioxidant properties. However, raspberries are very perishable fruit with a short shelf life. Chitosan applications have shown promising results in promoting the storage of different berry fruit. This work aimed at analysing the effects of chitosan applied in pre- and/or post-harvest on the quality and antioxidant properties of raspberry fruit during the cold storage and room temperature conditions (i.e., 6 d at 4 °C and 3 d at 20 °C, respectively). Pre-harvest chi-tosan applications reduced fruit weight loss during cold storage and room temperature condi-tions but also reduced fruit decay at room temperature conditions. Furthermore, pre-harvest treatments with chitosan increased the total phenol and anthocyanin contents and promoted the highest total antioxidant activity with respect to other treatments. Of note, after the cold storage, post-harvest chitosan application drastically reduced the development of fungi that cause fruit decay, thus minimizing the potential risk of mycotoxin production. Overall, this study demon-strates that applications of chitosan in pre-harvest are sufficient to ensure the goal of maintaining and/or increasing the quality and antioxidant properties of fruit during cold storage and room temperature conditions.

Earnings management and financial distress are two critical facets of financial management in corporations that have lately been the focus of thorough research from both scholars and practitioners. The purpose of the research is to evaluate the influence of financial distress on the earnings management of companies listed at the NSE during the pre- and post-COVID eras. Multiple linear regression was applied in this study to examine the causal association between earnings management and financial distress. To assess the effect of financial distress on earnings management, the study analyzed data from 37 listed companies during the pre-COVID and post-COVID periods. The methodology also takes into account control factors like firm size, GDP, and inflation. The pre-COVID research indicates a significant positive correlation between financial strain and earnings management. In contrast, the correlation between financial distress and earnings management is not statistically significant in the post-COVID analysis. However, research shows that firm size has a statistically significant negative influence on managing earnings. The results of this study show that smaller firms are more inclined to engage in earnings management during the post-COVID era than bigger ones.

Neuromonitoring of the efferent nerve impulses transmission in the spinal cord tracts during surgical scoliosis treatment makes it possible to assess whether the functional status is deteriorating, affecting the procedure's safety. Is there any relationship between pre- and intraoperative motor evoked potentials recordings and does idiopathic scoliosis (IS) surgical correction improve directly the spinal efferent transmission? This study aimed to compare the results of surface recorded electromyography (EMG), electroneurography (ENG, M and F-waves), and especially motor evoked potentials (MEP) from tibialis anterior (TA) muscle bilaterally in 353 girls with the right idiopathic scoliosis (types 1A-4C according to Lenke classification). It has not yet been documented whether the results of MEPs recordings induced by transcranial single magnetic stimulus (TMS, pre – and postoperatively) and trains of electrical stimuli (TES; intraoperatively in T0-before surgery, T1 – after pedicle screws implantation, T2 – after scoliosis curvature distraction and derotation following two rods implantation) can be compared for diagnostic verification of improvement of the spinal neural transmission. The study also attempted to determine whether the constant level of optimal anesthesia during the certain surgical steps of scoliosis treatment affects the parameters of MEPs recorded during neuromonitoring procedures. No neurological deficits have been observed postoperatively. Values of amplitudes but not latencies in MEPs recordings evoked with TMS in IS patients compared before and after surgery indicated a slight improvement in the efferent transmission of neural impulses within the fibers of the spinal tracts postoperatively. Results of all neurophysiological studies in IS patients were significantly asymmetrical and recorded worse on the concave side, suggesting greater neurological motor deficits at p=0.04. This asymmetry had been significantly reduced following IS surgery. The surgeries in IS patients brought significant improvement (p=0.04) in parameters of amplitudes of sEMG recordings, however reflecting still the consequences of the neurogenic injury of TA muscle motor units. ENG studies results indicated the symptoms of the axonal type injury in peroneal motor fibers improved only on the concave side at p=0.04 in parallel with the significant improvement of F-waves parameters, which suggests that surgeries might result in the lumbar ventral roots decompression. There were not detected significant differences in amplitudes or latencies of MEPs induced with TMS or TES comparing the parameters recorded preoperatively (one day before surgery) and intraoperatively in T0. The amplitudes of TES evoked MEPs increased gradually at p=0.04 in the subsequent periods (T1 and T2) of observation. The significant reduction of MEPs latency at p=0.05 was observed only at the end of the IS surgery. Studies on the possible connections between the level of anesthesia fluctuations and the required TMS stimulus strength, as well as the MEPs amplitude changes measured in T0-T2 revealed lack of relationships. It is not likely that they could be the factors influencing the efferent transmission in spinal pathways beside the surgical procedures. Considering that MEPs amplitude parameter reflects the number of axons excited from the motor cortex and transmitting the efferent impulses via spinal descending tracts in the white matter, pre- (TMS evoked) and intraoperative (TES evoked) recordings are reliable for evaluating the patient’s neurological status before and during surgical scoliosis correction procedures. The results of this study indicate an agreement between preoperative and early-intraoperative evaluations with these both diagnostic methods. An increase of MEPs amplitude parameters recorded on both sides after scoliosis surgery proves immediate improvement of the total efferent spinal cord transmission. Considering comparative pre- and postoperative sEMG and ENG recordings it can be concluded that surgeries might directly result in the additional lumbar ventral roots decompression. Our results of the tests on the possible variability of the anesthesia level on the parameters of intraoperative recorded MEPs show no clear relationships. We can conclude that MEPs parameters changes are determined by the surgery procedures during neuromonitoring, not the anesthesia conditions if they are kept stable, which influences a decrease in the number of false-positive neuromonitoring warnings. Further studies on a larger population of patients with long-lasting observation postoperatively are required to confirm the presented conclusions on the direct influences of scoliosis surgery on improvement of the motor function in patients with IS.

During the few years, various algorithms have been developed to extract features from high-resolution satellite imagery. For the classification of these extracted features, several complex algorithms have been developed. But these algorithms do not possess critical refining stages of processing the data at the preliminary phase. Various satellite sensors have been launched such as LISS3, IKONOS, QUICKBIRD, and WORLDVIEW etc. Before classification and extraction of semantic data, imagery of the high resolution must be refined. The whole refinement process involves several steps of interaction with the data. These steps are pre-processing algorithms that are presented in this paper. Pre-processing steps involves Geometric correction, radiometric correction, Noise removal, Image enhancement etc. Due to these pre-processing algorithms, the accuracy of the data is increased. Various applications of these pre-processing of the data are in meteorology, hydrology, soil science, forest, physical planning etc. This paper also provides a brief description of the local maximum likelihood method, fuzzy method, stretch method and pre-processing methods, which are used before classifying and extracting features from the image.

Surimi-based products occupy an important position in the aquatic product processing industry. To enhance the quality and flavor of surimi-based products, the effects of pre-emulsified safflower seed oil on the texture, water-holding capacity (WHC), microstructure, and flavor of Nemipterus virgatus surimi gel was evaluated. The texture and whiteness of gel were improved, and the WHC increased (P &lt; 0.05) as the content of safflower seed oil increased up to 2 mL per 100 g surimi. Furthermore, the drops of pre-emulsified safflower seed oils with an average diameter of less than 0.10 μm were evenly distributed in gel matrix. Microstructure and infrared spectroscopy analyses indicated that low-content pre-emulsified safflower seed oil acted as filler particles to occupy void spaces, resulting in gel exhibiting a dense network structure. Volatile analysis showed the gel containing pre-emulsified oil enriched volatile compounds, mainly resulting from oxidation and decomposition of oils by the activation of lipoxygenase, which synergistically contributes to unique flavors of gel. Consequently, low-content pre-emulsified safflower seed oil can used to enhance the quality and flavor of N. virgatus surimi-based products. These findings are especially relevant to the current growing interest in low-fat and high-protein diets.

The prevalence of corona virus and the novel COVID-19 disease in the entire globe has exacerbated different impact on socioeconomic spectrum in the world, including water use pattern. Thus a research was conducted to examine the comparative use of water during pre- and post-COVID-19 lockdown pattern among post-primary schools in Iwo, Osun State, Nigeria. A survey was conducted among fifteen schools which were randomly selected, but with eight public and seven private schools for the investigation. Both descriptive and inferential statistical techniques were used in data analysis. The results revealed that the major source of water to the schools investigated is ground water which is obtained through hand-dug wells and boreholes. It was further discovered that there was increase in water use during post-COVID-19 lockdown era as a result of the directive by the government that clean water should be provided for hand-washing by all schools regardless of the owner to curtail the spread of COVID-19 disease in the country. One sample t-test also revealed that there was a significant difference in water use at (p<0.01) level. It is recommended that the government and other stakeholders in water sector to ensure that all-time and non-seasonal dependent source of water be provided rather than ground water source which is susceptible to variations in water yields from seasonal variations. This will enable continuous clean water supply, for all purposes, including COVID-19 protocols.

Shells, probably like no other product of nature, have played an important role in the history of mankind. The pre-Hispanic civilizations of Ibero-America also used certain type of shells profusely in their religious ceremonies, in particular, in Ecuador there were two species of main importance, the Spondylus princeps and the Spondylus calcifer broadly employed to manufacture ornaments that possess a strong symbolic, religious and social meaning and that were almost exclusively used by ruling classes. Among these ornaments, the faces carved on the Spondylus shells are little known. In the present study, we chose a total of fifteen (15) pieces from the Pastor Restrepo Lince´s archaeomalacology collection to understand the possible uses of these objects, through the interpretation of the gestures represented on the faces, their dimensions, and their geographical distribution in pre-Hispanic Ecuador. To achieve the proposed objective, we approach the present investigation from the perspective of the formal analysis of concepts, which is a mathematical theory of representation of knowledge, finding that these faces carved in Spondylus, were used daily or in special ceremonial occasions and that its use was common in all the regional cultures of ancient Ecuador, from the oldest such as Valdivia, and for more than 2000 years, indicating a long tradition of the use of Spondylus as an object of great symbolic and economic value until the arrival of the Spanish

There is a confusion in the original design concept for the tensioning of longitudinally connected reinforcement of CRTSII slab ballastless track. In order to clarify the effect of tension value of longitudinal reinforcement on mechanical characteristics of ballastless track, a three dimensional finite element model considering the nonlinear interaction between the track slab and CA mortar of CRTSII slab ballastless track was established. The mechanical characteristics of the track structure under longitudinal tension load and temperature gradient load of the longitudinal joint were calculated. A method of applying pre-stress to post-pouring concrete was proposed according to the concept of pre-stress loss of pretensioning pre-stressed concrete, reasonable tensile force value was proposed after the crack width and the reinforcement stress of the ballastless track in the operation stage were checked and calculated according to the concrete design principle. When the tension force is greater than 300 kN, it’s harmful to the bonding between the slab and mortar layer, which is prone to interlayer damage. In order to adding pre-stress to concrete of wide joints to ensure the longitudinal stability of ballastless track and the reinforcement stress and crack width to meet the design requirements. It is suggested that the tension force value should be 230 kN, and the temperature difference between reinforcement and concrete should be 30 °C before the initial curdle of wide joint concrete.

MicroRNAs (miRNAs) are crucial regulatory RNAs, originated from hairpin precursors. For the past decade, researchers are focusing extensively on miRNA profiles in various plants. However studies on precursor miRNAs (pre-miRNAs) global profiling stay static even in model plants. Here, for the first time in a non-model plant, Abelmoschus esculentus with negligible genome information, we are reporting the global profiling to characterize the miRNAs and their associated pre-miRNAs by applying next generation sequencing approach. Preliminarily we performed sRNA (small RNA) sequencing with five biological replicates of leaf samples to attain 207,285,863 reads and data analysis using miRPlant keyed out 128 known and 845 novel miRNA candidates. With the objective to seize their associated hairpin precursors, we accomplished pre-miRNA sequencing to attain 83,269,844 reads. The paired end reads are merged, adaptor trimmed and the resulting 40-241 nt (nucleotide) sequences were picked out for analysis by using perl scripts from miRGrep tool and in-house built shell script for Minimum Fold Energy Index (MFEI) calculation. Applying stringent criteria of dicer cleavage pattern and perfect stem loop structure revealed precursors for 57 known miRNAs of 15 families and 18 novel miRNAs. Quantitative Real Time (qRT) PCR was performed to determine the expression of selected miRNAs.

The proliferation of SARS-COV-2 through enhanced viral replication and its subsequent triggering of cytokine storm, are some of the hallmark phenotypes in severe COVID-19 patient cases. Cyclosporine, an immunosuppressant drug and Selinexor, an inhibitor of nuclear transporter protein, both have been successfully demonstrated to be effective against SARS-COV-2 infection by targeting those functions individually. However, the highly multifactorial pathology of SARS-COV-2 infection hinders any mono-therapeutic strategy to become an optimal option. In this study, we assess the potential efficacy of the Cyclosporine-Selinexor combination on an integrated interactome by adopting a network-medicine-based repositioning technique, where disease proximity, functional proximity and their topological separation are evaluated, followed by a robust statistical significance test. Results have shown that both drug target modules are highly proximal to the SARS-COV-2 disease modules in terms of network topology and functional associations, in a statistically significant manner, individually. Functional enrichment of both drug modules and SARS-COV-2 infected modules has shown that two drugs target the functions related to viral replication and cytokine storm during infection. Moreover, a high degree of network separation been those two drug target modules has been observed, revealing ``complementary exposure`` patterns, rendering this drug combination as an effective one against SARS-COV-2 infection. We hope that our results will encourage researchers to further investigate the potency of Cyclosporine and Selinexor combination in vivo or in vitro, and ultimately lead that up to clinical trials to treat SARS-COV-2 patients.

Hypertension (HTN) is the foremost contributor to cardiovascular diseases (CVD), which remain a leading cause of death. However, adherence to the properly prescribed dosage form is critical and challenging for patients with chronic diseases such as HTN to prevent illness progression and death. The study’s objective was to develop AMB-loaded subcutaneous implants to reduce the frequency of administration, thus improving patient compliance during HTN management. AMB subcutaneous implants were prepared using continuous hot melt extrusion technology using PCL and PLGA with dimensions of 7.5 cm (length) by 2 mm (diameter). The implants were characterized for thermal characteristics, drug-excipient incompatibilities, surface morphology, fracturability, in vitro release, and stability studies. DSC showed that the drug was in the crystalline state in the fabricated implants. Scanning Electron Microscopy (SEM) revealed a smooth surface. The lead formulation presented good drug content, showed an extended drug release profile over 30 days, and followed zero-order release kinetics with a mean dissolution time of 15 days. The formulation was stable over 30 days in accelerated stability conditions (the last time point was tested, 40℃/75% RH), and the release profile was similar to the initial drug release profile. The lead formulation showed good fracturability during textural analysis. Therefore, the hot melt extruded implants could be an alternative management strategy for conventional amlodipine besylate (AMB) formulation.

The primary purpose of this study was to determine the prevalence of drug-drug interaction (DDI) and duplicate therapy in chronic patients in a completely random study population engaged in digital health apps. In this cross-sectional study, polypharmacy checks for 100 completely anonymous patients were analyzed for the occurrence of DDIs and duplicate therapy. Logistic regression models were used to identify factors associated with DDIs and duplicate therapy. DDIs and duplicate therapy prevalence were 34% and 33%, respectively. Chi-Square test discovered a significant association between the DDIs and duplicate therapy variables. Logistic regression models showed a strong association between the number of medications taken and higher odds of DDIs occurring in our population only. In conclusion, our study shows that polypharmacy is a determining factor for the occurrence of unwanted DDIs, and the prevalence of duplicate therapy and DDIs is around 33%, increasing an issue regarding patient safety and its burden to the healthcare system.

Overt hyperthyroidism during pregnancy is associated with risk of maternal-fetal complications. The antithyroid drugs (ATD) have a potential risk for teratogenic effects and fetal–neonatal hy-pothyroidism. This study evaluated ATD treatment and thyroid function control during preg-nancy, and pregnancy outcome in women with hyperthyroidism. Patients and methods: retro-spective analysis of 36 single fetus pregnancies in 29 consecutive women (median age 30.3 ± 4.7 years) with hyperthyroidism diagnosed before or during pregnancy; a control group of 39 healthy euthyroid pregnant women was used. Results: 26 women had Graves’ disease (GD, 33 pregnan-cies), 1 had a hyperfunctioning autonomous nodule, 2 had gestational transient thyrotoxicosis (GTT). Methimazole (MMI) was administered in 22 pregnancies (78.5%), Propylthiouracil (PTU) in 2 (7.1%), switch from MMI to PTU in 4 (14.2%), no treatment in 8 pregnancies (3 with subclinical hyperthyroidism, 5 euthyroid with previous GD remission before conception). One spontaneous abortion at 5 weeks (3.4% of pregnancies) and 1 premature delivery at 32 weeks with perinatal death in 24h (3.4%) were recorded in 2 of the 8 pregnancies of GD patients diagnosed shortly before (< 6 weeks) or during gestation. In women treated more than 6 months until conception (20 pregnancies): a) median ATD doses were lower than those in women diagnosed shortly before or during pregnancy; b) ATD was withdrawn in 40% of pregnancies in trimester (T) I, all on MMI < 10 mg/day (relapse in 14.2%), and in up to 55% in TIII; c) TSH level was below normal in 37%, 35% and 22% of pregnancies in T I, II and III respectively; FT4 was increased in 5.8% (T I) and sub-normal in 11.75% in TII and III; d) one fetal death due to a true umbilical cord knot was recorded. Hyperthyroidism relapsed postpartum in 83% of GD patients (at median 3 ± 2.6 months). One child had neonatal hyperthyroidism (3.3% of live children in GD women) and a small atrial sept defect (4% of live children in ATD treated women). Mean birth weight did not differ from that of the control group. Conclusion. In hyperthyroid women with long-term ATD control before con-ception, drugs could be withdrawn in TI in a third of them, and fetal complications were rare. Frequent serum TSH and FT4 monitoring is needed in order to maintain optimal thyroid function during pregnancy.

In this paper we propose the generation of synthetic small and more sophisticated molecule structures that optimize the binding affinity to a target (ASYNT-GAN). To achieve this we leverage on three important achievements in A.I.: Attention, Deep Learning on Graphs and Generative Adversarial Networks. Similar to text generation based on parts of text we are able to generate a molecule architecture based on an existing target. By adopting this approach, we propose a novel way of searching for existing compounds that are suitable candidates. Similar to question and answer Natural Language solutions we are able to find drugs with highest relevance to a target. We are able to identify substructures of the molecular structure that are the most suitable for binding. In addition, we are proposing a novel way of generating the molecule in 3D space in such a way that the binding is optimized. We show that we are able to generate compound structures and protein structures that are optimised for binding to a target.

HIV treatment strategies against viral enzymes are continuously hampered by viral drug resistance. Recent findings show that viral substrate Gag contributes to HIV-1 Protease Inhibitor (PI) resistance, leading to demands for new strategies in HIV treatment where Gag is recognized as a drug target. To successfully target Gag, there is a need of in-depth understanding of the Gag polyprotein and the effects of Gag mutations. Here, we propose new strategies in designing novel Gag inhibitors against existing and novel emerging Gag mutations via a structural understanding of the Gag-Protease relationship in PI resistance. In this review, we discuss the role of both novel and previously reported mutations, revealing insights to how they aid in PI resistance, and how new Gag inhibitors can be designed.

Vancomisin resistant enterococcus(VRE), is a resistant microorganism which colonizates and causes infections in hospitalized patients. It was aimed to show the spread of vancomycin-resistant Enterococcus (fVREfm) step-by-step in all intensive care units, which started with the growth of vancomycin-resistant Enterococcus faecium (VREfm) on 02.12.2021 in the blood culture of a patient hospitalized in the anesthesia intensive care unit of our hospital and was found to have reached epidemic size in the surveys. Rectal swab samples were taken from all patients hospitalized in intensive care units, VRE colonization was determined and the VanA and VanB resistance genes associated with vancomycin resistance of VREfm isolates were determined by PCR method, and clonal association analysis was performed by Arbitrarily Primed-PCR (AP-PCR) and Pulsed-Field Gel Electrophoresis. In our study, VRE was detected in 61 of 2601 rectal swab samples. 54 (85.52%) of the VRE isolates were Enterococcus faecium, 3 (4.91%) was Enterococcus faecalis, 3 (4.91%) was Enterococcus gallinorum, 1 (1.63%) was Enterococcus casseliflavus. It was determined that all of the 54 VREfm isolates, which were the most detected among all VRE isolates, carried the vanA gene. In the clonal association analysis of the isolates by AP-PCR and PFGE methods, it was found that they had 12 different genotypes, 48 of them were included in any cluster, the clustering rate was 88.8%, and the largest cluster was genotype 1 cluster with 36 isolates. Of the 54 patients with VREfm isolated recently, 18.51 percent of the clinical samples were isolated before the survey, and 9.24% were isolated after the survey. It was determined that 100% of VREfm isolates were resistant to ampicillin, levofloxacin, ciprofloxacin, high-level gentamicin, trimethoprim-sulfamethoxazole, teicoplanin, 7.4% to tigecycline and 1.85% to linezolid. In our study, in the clonal association analysis performed by isolating VREfm in rectal swab samples, it was found that 88.8% of the samples were indistinguishably similar and the increase in the number of VREfm infections after the index case in our hospital was associated with the epidemic. VREfm infections cause long term hospitalization, costs and also deaths, which shows the seriousness of the event, and the importance of the combination of epidemiological and molecular analysis in epidemic research.

Although the beneficial health effects of prebiotics have been demonstrated in numerous research papers, its incorporation into daily food remains unfamiliar to consumers. This work evaluates the resistant maltodextrin (RMD) addition in the sensory attributes of pasteurized orange juice, together with the physico-chemical properties and the aromatic profile. RMD addition moderately improved almost all sensory attributes evaluated by panellists. It also proportionally increased °Brix together with density and decreased acidity. Colour changes were registered with higher RMD concentrations. Orange pulp presence affected the volume particle size distribution analysis while RMD addition did not exercised any effect. The aroma volatile compounds were also analysed. Pulp-added samples marked higher alcohol and aldehydes quantity, whereas pulp-free samples registered higher terpenes and terpenoids values. Ketones and acids were also quantified. RMD had a moderate impact on volatile compounds quantifications, playing the orange pulp presence a much more decisive role. A correlation analysis was also performed to relate instrumental and sensorial determinations for all samples. This work proves that the addition of RMD to orange juice is technologically feasible while also achieving a good response at the sensory level.

The increased emergence of multidrug-resistant Helicobacter pylori influences the prevention of stomach cancer. Zingiber officinale is a plant usually used in folk medicine to treat a variety of diseases involving infections, nausea, vomiting, peptic ulcer, dyspepsia, and inflammation. This study was conducted to evaluate the ability of Z. officinale extract to combat resistant H. pylori. The disc diffusion, microdilution, and microplate assays were performed to evaluate the susceptibility to antibiotics, and the antibacterial and antibiofilm activities of the Z. officinale extracts. Using the checkerboard method, the combined effects of the gentamicin and Z. officinale extract were investigated. In addition, anti-inflammatory activity and GC-MS analysis were determined by the modified protocol. According to the findings, H. pylori isolates exhibited resistance rates of 56.33, 50.0, and 45.85 for metronidazole, gentamicin, and tetracycline, respectively. The methanolic extract of Z. officinale had the strongest effectiveness against resistant H. pylori isolates with MIC of 20.0 to 50.0 µg/ml against both H. pylori isolates and the stranded strain NCTC 11637. Z. officinale extract suppress the biofilm formed by H. pylori isolates with a percentage of 92.96% at 50.0µg/ml, compared with 97.19% for gentamicin at the same concentration. According to FICI values, combination of methanolic Z. officinale extract to gentamicin increases bacterial sensitivity to such drugs. Moreover, the Z. officinale extract exhibits strong anti-inflammatory activity. The GC-MS analysis of Z. officinale extract exhibits 17 different chemical compounds. Conclusions: The Z. officinale extract contain the anti-inflammatory compound gingerol as the main constituent which inhibits the growth of H. pylori and its biofilm, are a promising natural therapeutic alternative or enhance antibiotics activity

Staphylococcus aureus (S. aureus) is a major human pathogen that requires new antibiotics with unique mechanism. A new pleuromutilin derivative, 14-O-[(4,6-Diaminopyrimidine-2-yl) thioacetyl] mutilin (DPTM), has been synthesized and proved as a potent antibacterial agent using in vitro and in vivo assays. In the present study, DPTM was further in vitro evaluated against Methicillin-resistant Staphylococcus aureus (MRSA) isolated from dairy farms and outperformed tiamulin fumarate, a pleuromutilin drug used for veterinary. Moreover, a murine skin wound model caused by MRSA infection was established and the healing effect of DPTM was investigated. The results showed that DPTM could promote the healing of MRSA skin infection, reduce the bacterial burden of infected skin MRSA and decrease the secretion of IL-6 and TNF-α inflammatory cytokines in plasma. These results provided the basis for further in-depth drug targeted studies of DPTM as a novel antibacterial agent.

Necrotizing pneumonia due to Methicillin-Resistant Staphylococcus Aureus (MRSA) is devastating and difficult to treat in preterm infants. We report a case of severe MRSA necrotizing pneumonia in a preterm infant. As an add-on rescue therapy to vancomycin, linezolid rapidly cured this case after the failure of vancomycin plus rifampicin. This rapid cure suggests that adjunctive rather than rescue linezolid may be considered in such cases.

Average of 41,900 patients are diagnosed annually with staphylococcus bacterial infection in California, 24,089 patients have Methicillin-resistant Staphylococcus Aureus (MRSA) and 17,810 patients have Methicillin-Sensitive Staphylococcus (MSSA). This paper demonstrates that there is a difference in mortality rate due to staphylococcus infection between males and females (P-value<0.05, CI 95%). Male patient diagnosed with S. aureus has 1.3 chance of mortality incidence than female patient. In addition, MRSA infection rate is 1.4 times MSSA infection (P-value<0.05, CI 95%), but the gap of infection is decreasing; however, mortality of both infections combined are more than threefold greater compared to three decades ago.

Functional genomics, a multidisciplinary subject, investigates the functions of genes and their products in biological systems to better understand diseases and find new drugs. Drug repurposing is an economically efficient approach that entails discovering novel therapeutic applications for already-available medications. Genomics enables the identification of illness and therapeutic molecular characteristics and interactions, which in turn facilitates the process of drug repurposing. Techniques like gene expression profiling and Mendelian randomization are helpful in identifying possible medication candidates. Progress in computer science allows for the investigation and modelling of gene expression networks that involve large amounts of data. The integration of data from DNA, RNA, and protein activities has resemblance to pharmacogenomics, which is of utmost importance in the development of cancer drugs. Functional genomics in drug discovery, particularly for cancer, is still not thoroughly investigated, despite the existence of a significant amount of literature on the subject. Next-generation sequencing and proteomics present highly intriguing opportunities. Publicly available databases and mining techniques facilitate the development of cancer treatments based on functional genomics. Expanding the study and application of functional genomics has great promise to advance the process of discovering and repurposing drugs, especially in the field of oncology.

Melatonin is a ubiquitous molecule found in living organisms, ranging from bacteria to plants and mammals. It possesses various properties, partly due to its robust antioxidant nature and partly owed to its specific interaction with melatonin receptors present in almost all tissues. Melatonin regulates different physiological functions and contributes to the homeostasis of the entire organism. In the human eye, a small amount of melatonin is also present, produced by cells in the anterior segment and the posterior pole, including the retina. In the eye, melatonin may provide antioxidant protection along with regulating physiological functions of ocular tissues, including intraocular pressure (IOP). Therefore, it is conceivable that the exogenous administration of sufficiently high amounts of melatonin to the eye could be beneficial in several instances: for the treatment of eye pathologies like glaucoma, due to the IOP-lowering and neuroprotection effects of melatonin; for the prevention of other dysfunctions, such as dry eye and refractive defects (cataract and myopia) mainly due to its antioxidant properties; for diabetic retinopathy due to its metabolic influence and neuroprotective effects; for macular degeneration due to the antioxidant and neuroprotective properties; and for uveitis, mostly owing to anti-inflammatory and immunomodulatory properties. This paper reviews the scientific evidence supporting the use of melatonin in different ocular districts and provides data suggesting that the topical administration of melatonin as eye drops is a real possibility. This way, its distribution and concentration in different ocular tissues may support its pleiotropic therapeutic effects.

BRAF is one of the most frequently mutated oncogenes, with an overall frequency of about 50%. Targeting BRAF and its effector mitogen-activated protein kinase kinase 1/2 (MEK1/2) is now a key therapeutic strategy for BRAF-mutant tumors, and therapies based on dual BRAF/MEK inhibition showed significant efficacy in a broad spectrum of BRAF tumors. Nonetheless, BRAF/MEK inhibition therapy is not always effective for BRAF tumor suppression, and significant challenges remain to improve its clinical outcomes. First, certain BRAF tumors have an intrinsic ability to rapidly adapt to the presence of BRAF and MEK1/2 inhibitors by bypassing drug effects via rewired signaling, metabolic, and regulatory networks. Second, almost all tumors initially responsive to BRAF and MEK1/2 inhibitors eventually acquire therapy resistance via an additional genetic or epigenetic alteration(s). Overcoming these challenges requires identifying the molecular mechanism underlying tumor cell resistance to BRAF and MEK inhibitors and analyzing their specificity in different BRAF tumors. This review aims to update this information.

The paradigm of molecular communications is applied to the concrete case for delivering electrically charged nanoparticles to tumor. Once them have been injecetd in blood it is expecetd an optimal outcome as to reduce toxicity and minimal dispersion of drugs in the blood stream. With a fraction of nanoparticles arrives to surface of tumor, the scattered part of injected ones can minimize the success of scheme of drug delivery. In this paper is presented a theory based at the sequence electrodynamics-diffusion-Bayes theorem. The resulting probability of Bayes at the end of sequence, might be telling us that dynamical processes based in the injection of electrically charged nanoparticles might be dictated by stochastic formalism more that biochemical approaches by which makes impossible to know the success or fail of drug delivery dynamics. Illustrations demonstrating the transition of a linear to nonlinear scenario are presented

Nanosystems-based antifungal agents have emerged as an effective strategy to address issues related to drug resistance, drug release, and toxicity. Among the different materials used for drug delivery, multifunctional polymers have proven to be ideal due to their versatility. This review provides an overview of the various types of nanoparticles used in antifungal drug delivery systems, with a particular emphasis on the types of polymers used. The review focuses on the application of drug delivery systems and the release behavior of these systems. Furthermore, the review summa-rizes the critical physical properties and relevant information utilized in antifungal polymer nanomedicine delivery systems, and briefly discusses the application prospects of these systems.

Both Stevens Johnson Syndrome (SJS) and toxic epidermal necrolysis (TEN) are main injurious cutaneous medication reactions that mostly affect the epidermis and mucus membranes. TEN and SJS affecting nearly 1 or 2/1,000,000 people per year, and can recognized as medical crises since they may be deadly. Mucocutaneous discomfort, hemorrhagic erosions, erythema, and more or less severe epidermal separation that appear as ulcer and patches of dermic loss are their defining characteristics. The sole difference between TEN and SJS at this time is the degree of skin detachment, making them two extremes of a spectrum of severe cutaneous adverse drug reactions (cADRs). In the majority of cases, drugs are considered as the principal reason of SJS/TEN, but herpes simplex virus and Mycoplasma pneumoniae infections are also recognized causes, along with lesser number of cases in which the cause is still unknown. Among the drugs with a "high" likelihood of producing TEN/SJS are carbamazepine (CBZ), trimethoprim-sulfamethoxazole, phenytoin, aminopenicillins, allopurinol, cephalosporins, other sulfonamide antibiotics, quinolones, phenobarbital, and NSAIDs of the oxicam variety. There is strong genetic evidence for SJS and TEN in Han Chinese due to the substantial association between the human leukocyte antigen (HLA-B*1502) and SJS brought on by CBZ. The diagnosis is made mostly based on clinical symptoms and the histological study of a dermal biopsy. Pemphigus vulgaris, bullous pemphigoid, linear IgA dermatosis, paraneoplastic pemphigus, disseminated fixed bullous drug eruption, acute generalized exanthematous pustulosis (AGEP), and staphylococcal scalded skin syndrome (SSSS) are among the differential diagnoses. The management of patients with SJS/TEN is complicated by the high risk of mortality, necessitating early diagnosis, estimation of the SCORTEN prognosis, identification and discontinuation of the causative drug, specialized supportive care, and high-dose injectable Ig therapeutic interventions. The reported fatality rates for SJS are 1-5% on average and 25-35% for TEN; it can be even higher in patients who are elderly or who have a significant amount of epidermal detachment on their skin. More than 50% of TEN patients who survive the disease experience long-term consequences.

Nanotechnology is making significant transformation to our world, especially in healthcare and the treatment of diseases. It is widely used in different medical applications, such as in treatment and detection. Targeting diseased cell with nanomedicines is one of the numerous applications of nanotechnology. Targeted drug delivery systems for delivering various types of drugs to specific sites are such a dynamic area in pharmaceutical biotechnology and nanotechnology. Compared to conventional drugs, nanomedicines have a higher absorption and bioavailability rate, improving efficacy and minimizing side effects. There are several drug delivery systems including metallic nanoparticles, polymers, liposomes, and microspheres, but one of the most important is the niosomes, which are produced by nonionic surfactants. Because of the amphiphilic nature and structure, hydrophilic or hydrophobic drugs can be loaded into niosome structures. Other compounds, including cholesterol, can also be applied to the niosomes' backbone to rigidize the structure. Several variables such as the type of surfactant in niosome production, the preparation method, and the hydration temperature can affect the structure of the niosomes. Nevertheless, in-silico design of drug delivery formulations requires molecular dynamic simulation tools, molecular docking, and ADME (absorption; distribution; excretion; metabolism) properties, which evaluate physicochemical features of formulation and ADME attitudes before synthesis, investigating the interaction between nano-carriers and specific targets. Hence, experimenting in-vitro and in-vivo is essential. In this review, the basic aspects of niosomes are described including their structure, characterization, preparation methods, optimization with in-silico tools, factors affecting their formation, and limitations.

Drug discovery has been initially attributed to coincidence or trial and error where the traditional approach was complex, lengthy, and expensive. Conventional drug discovery methods require the costly random screening of synthesized compounds or natural products. Another downside for this approach is the wide dependency on the experimental use of animals for in vi-vo testing. Currently, in silico modeling has become a vital tool for drug discovery and repurposing, and molecular docking is being used to find the best matching between a ligand and a molecule. Practical application of in silico docking will predict the biomolecular interactions between the drug and the target host. Beauvericin (BEA) is an emerging mycotoxin produced by the entomopathogenic fungus Beauveria bassiana. Originally investigated for its pesticide capability, BEA is now considered as a molecule of interest for its potentially diverse biotechnological applications in the pharmacological industry and the field of medicine. In this manuscript, we will provide an overview of the repurposing of BEA into a potentially superior therapeutic molecule in a broad range of diseases. Furthermore, considerable attention has been given to the fundamental role of in silico techniques to i) further investigate the spectrum of this secondary metabolite and ii) elucidate the pathways of BEA for its promising therapeutic action

With increasing awareness amongst physicians and improved radiological imaging techniques, the peritoneal cavity is increasingly recognized as an important metastatic site in various malignancies. Prognosis of these patients is usually poor as traditional treatment including surgical resection or systemic treatment is relatively ineffective. Intraperitoneal delivery of chemotherapeutic agents is thought to be an attractive alternative as this results in high tumor tissue concentrations with limited systemic exposure. The addition of hyperthermia aims to potentiate the anti-tumor effects of chemotherapy, resulting in the concept of heated intraperitoneal chemotherapy (HIPEC) for the treatment of peritoneal metastases as it was developed about 3 decades ago. With increasing experience, HIPEC has become a safe and accepted treatment offered in many centers around the world. However, standardization of the technique has been poor and results from clinical trials have been equivocal. As a result, the true value of HIPEC in the treatment of peritoneal metastases remains a matter of debate. The current review aims to provide a critical overview of the theoretical concept and preclinical and clinical study results, to outline areas of persisting uncertainty, and to propose a framework to better define the role of HIPEC in the treatment of peritoneal malignancies.

The influence of lignin modification on drug release and pH-dependent releasing behaviour of oral solid dosage form was investigated using three different formulations. The first formulation contains microcrystalline cellulose (MCC101) as excipient and paracetamol as active pharmaceutical ingredient (API). The second formulation includes Alcell lignin and MCC 101 as excipient and paracetamol, and the third formulation consists of carboxylated Alcell lignin, MCC 101 and paracetamol. Direct compaction was carried out in order to prepare the tablets. Lignin can be readily chemically modified due to the existence of different functional groups in its structure. The focus of this investigation is on lignin carboxylation and its influence on paracetamol control release behaviour at varying pH. Results suggest that carboxylated lignin tablets had the highest drug release, which is linked to their faster disintegration and lower tablet hardness.

Objective: To evaluate the status of receiving education on rational drug use, the criteria in medical drug selection, and level of knowledge of dentists working in a dentistry faculty in Turkey. Material and Methods: This was a descriptive study based on a questionnaire. One hundred seventeen (74%) dentists volunteered to participate in the study. The questionnaire consisted of 20 questions investigating sociodemographic features and rational drug use. Results: The mean age of the dentists was 30.8 ± 7.2 years, and 62.4% were men. The mean period of professional experience was 8.9±7.1 years. The most frequently used resources of references while prescribing medicine were Vademecum (medical drug guide) (61.5%), the internet (59.0%), and colleagues (49.6%). The most frequently reported condition described as ‘good’ was drug indications (43.6%). The dentists had a moderate level of information about posology, and administration route (48.7%), pharmacologic features (48.7%), and contraindications (46.2%). The number of dentists who stated that they considered cost while prescribing was low [always (6%), and frequently (15.4%)]. Rational drug use education had been received by 23.9% of the dentists. Conclusions: The dentists were found to have a lack of adequate and effective education on rational use of drugs. Regular and continuous education before and after graduation is a necessity for dentists and for their patients.

Same-day desensitization (SDD) is a procedure in which desensitization to the drug suspected of causing the hypersensitivity reaction (HR) is performed on the same day as the patient's reaction. In rapid drug desensitization (RDD), desensitization to the suspected drug is performed after an allergological study. The aim of the study was to analyze the diagnostic capacity of the allergist in Oncology Day Hospital (ODH) to establish the phenotype of the HR, in the context of SDD, based exclusively on clinical biomarkers. This is a study of patients treated with desensitization on the same day they had a HR. Later an allergological study (clinical history, skin test, risk assessment, serological biomarkers, drug provocation test if applicable) was performed prior to the following administrations. A total of 35 successful SDDs were performed. A high concordance (91.5% of patients) was found between the phenotype suspected by the allergist after the initial assessment of the patient prior to SDD and the final phenotype after subsequent allergological study performed in the Allergy Department. The presence of the allergist at the ODH allows, in addition to initial treatment according to phenotype, desensitization on the day of the reaction. This will lead to personalized and precision allergology.

In this study, a simple machine learning-based quantitative structure-activity relationship (QSAR) model was developed to predict the inhibitory potency (pIC50 values) of FLT3 tyrosine kinase inhibitors, pivotal in treating Acute Myeloid Leukemia (AML). Distinctively, our model leverages an extensive and diverse dataset, 14 times larger than those employed in prior studies within this field, enabling an unparalleled scope of compound analysis. This vast dataset, combined with further exploration of molecular descriptors, enabled predictions of extraordinary precision, covering a broader spectrum of FLT3 inhibitors than was previously possible. The Random Forest Regressor (RFR) algorithm, selected for its superior predictive performance, was trained with 1080 inputs and validated through comprehensive external and internal methods. It achieved an remarkable coefficient of determination (R^2) of 0.941 and a standard deviation of 0.235 on a test set of 270 compounds, highlighting the efficacy of model in predicting FLT3 inhibitory activity. Key molecular descriptors were identified, enhancing our understanding of structural requirements for inhibitor potency. Additionally, we developed a user-friendly computational tool that enables the rapid prediction of pIC50 values. Utilizing this tool, potential FLT3 inhibitors were identified through ligand-based virtual screening. This study represents a major advancement in FLT3 inhibitor discovery by utilizing a simple QSAR-machine learning model. It enables more efficient and precise identification of potential drug candidates at an early stage, promising a faster development of targeted therapies and streamlining the ligand-based drug design process.

The clinical practice implies a research translation that helps the use of scientific data and thera-peutic evidence for patient benefits. This review critically summarizes the potential impact of cannabinoids in concomitance with other drugs in the following chronic diseases as Epilepsy, Au-tism Spectrum Disorders (ASD), Oncology, Multiple Sclerosis, and Chronic Pain. The potential in-teractions can change the predicted clinical outcomes of therapeutic protocols and need to be evaluated. Some of the effects would be additive, synergistic or antagonistic, but can also enroll changes in absorption, distribution, metabolism, particularly via cytochrome P450 (CYP) isoen-zymes (e.g CYP2C9 and CYP3A4) and excretion. For instance, the combination of canna-bis-derived compounds and the antifungal drug ketoconazole, a CYP3A4 inhibitor, increases plasma concentration of Δ-9-tetrahydrocannabinol (THC) and CBD (CBD). Opposable, rifampic-in, a CYP3A4 inducer, stands out for the approximately 20-40% reduction in plasma THC levels and 50% to 60% for CBD. Other CYP3A4 inhibitors and inducers are likely to have a similar effect on plasma concentrations if co-administered. Indeed, pharmacokinetic interactions have been also reported with antiseizure drugs. Moreover, pharmacodynamic interactions between cannabinoids and drugs with sympathomimetic effects (eg tachycardia, hypertension), central nervous system depressants (eg drowsiness, ataxia), and anticholinergics (eg tachycardia and drowsiness) are also expected. Even though pending further studies, there is currently clinical evidence supporting drug interaction with cannabinoids, demanding doctors evaluate the risk of drug combinations with cannabinoids. The tables herein provided were designed to facilitate the identification of bi-orelevant interactions that may compromise therapeutic efficacy and toxicity.

Urothelial cell carcinoma (UCC, bladder cancer) remains a difficult to treat malignancy with rising incidence worldwide. In the U.S., UCC is the sixth most incident neoplasm and ~90% of diagnoses are made in those &gt;55 years of age, ~four times more commonly observed in men than women. The most important risk factor for developing bladder cancer is tobacco smoking, which accounts for ∼50% of cases followed by occupational exposure to aromatic amines and ionizing radiation. The standard of care for advanced UCC includes platinum-based chemotherapy and programmed cell death (PD-1) or programmed cell death ligand 1 (PD-L1) inhibitors, administered as frontline, second-line, or maintenance therapy. UCC is highly aggressive and remains generally incurable since these cancers are associated with intrinsic and acquired drug resistance. UCC is highly lethal in the metastatic state and characterized by genomic instability, high PD-L1 expression, DNA damage-response mutations, and high tumor mutational burden. Although immune checkpoint inhibitors (ICIs) achieve long-term durable responses in other cancers, their ability to achieve similar results with metastatic UCC (mUCC) is not as well-defined. Here, we discuss the novel therapies to improve the management of mUCC.

Gastro-retentive floating microspheres were developed as a result of the recent advancements in floating delivery systems for drugs (FDDS), which included the uniform dispersion of multiparticulate dosage forms along the GIT. This could lead to more consistent drug absorption and a lower risk of local irritation. Microballoons (MB), a multi-unit extended release with a sphere-shaped cavity encased in a tough polymer shell, have been developed as a dosage form with exceptional buoyancy in the stomach. This preparation for constrained intestinal absorption is made to float on top of gastric acid, that has a relative density lower than 1.By using enteric acrylic polymers and the emulsion solvent diffusion method, microballoons are prepared and filled to drug in one‘s outer polymer casings. Enteric acrylic plastics are used to generate microballoons that are drug-loaded in one‘s external polymer casings and dissipate in a solution of dichloromethane and ethanol. Cavity development in microparticles seems to be particularly correlated with dichloromethane evaporation. Microballoons with a drug distributed or dispersed all through the particle-matrix have the potential for a controlled drug release and float continuously for more than 12 hours in vitro out over the surface of an acidified dissolution medium with surfactant. The drug is released slowly and at the desired rate as the microballoons glide over the components of the stomach, increasing gastro-retention time and lowering fluctuations in plasma concentration.

Sex differences are essential factors in disease etiology and manifestation in many diseases such as cardiovascular disease, cancer, and neurodegeneration (1). The biological influence of sex differences (including genomic, epigenetic, hormonal, immunological, and metabolic differences between males and females) and the lack of biomedical studies considering sex differences in their study design has led to several policies. For example, the National Institute of Health’s (NIH) sex as a biological variable (SABV) and Sex and Gender Equity in Research (SAGER)) policies to motivate researchers to consider sex differences (2). However, drug repurposing, a promising alternative to traditional drug discovery by identifying novel uses for FDA-approved drugs, lacks sex-aware methods that can improve the identification of drugs that have sex-specific responses (1,3–5). Sex-aware drug repurposing methods either select drug candidates that are more efficacious in one sex or deprioritize drug candidates based on if they are predicted to cause a sex-bias adverse event (SBAE), unintended therapeutic effects that are more likely to occur in one sex. Computational drug repurposing methods are encouraging approaches to develop for sex-aware drug repurposing because they can prioritize sex-specific drug candidates or SBAEs at lower cost and time than traditional drug discovery. Sex-aware methods currently exist for clinical, genomic, and transcriptomic information (3,6,7). They have not expanded to other data types, such as DNA variation, which has been beneficial in other drug repurposing methods that do not consider sex (8). Additionally, some sex-aware methods suffer from poorer performance because a disproportionate number of male and female samples are available to train computational methods (3). However, there is development potential for several different categories (i.e., data mining, ligand binding predictions, molecular associations, and networks). Low-dimensional representations of molecular association and network approaches are also especially promising candidates for future sex-aware drug repurposing methodologies because they reduce the multiple hypothesis testing burden and capture sex-specific variation better than the other methods (9,10). Here we review how sex influences drug response, the current state of drug repurposing including with respect to sex-bias drug response, and how model organism study design choices influence drug repurposing validation.

NF-κB is a central mediator of inflammation, response to DNA damage and oxidative stress. As a result of its central role in so many important cellular processes, NF-κB dysregulation has been implicated in the pathology of important human diseases. NF-κB activation causes inappropriate inflammatory responses in diseases including rheumatoid arthritis (RA) and multiple sclerosis (MS). Thus, modulation of NF-κB signaling is being widely investigated as an approach to treat chronic inflammatory diseases, autoimmunity and cancer. The emergence of COVID-19 in late 2019, the subsequent pandemic and the huge clinical burden of patients with life-threatening SARS-CoV-2 pneumonia led to a massive scramble to repurpose existing medicines to treat lung inflammation in a wide range of healthcare systems. These efforts continue and these efforts continue to be con-troversial. Drug repurposing strategies are a promising alternative to de-novo drug development, as they minimize drug development timelines and reduce the risk of failure due to unexpected side effects. Different experimental approaches have been applied to identify existing medicines which inhibit NF-κB that could be repurposed as anti-inflammatory drugs.

Elevated levels of oxidative stress in the corneal epithelium contribute to the progression of dry eye disease pathology. Previous studies have shown that antioxidant therapeutic intervention is a promising avenue to reduce disease burden and slow disease progression. In this study, we evaluated the pharmacological efficacy of Xanthohumol in preclinical models for dry eye disease. Xanthohumol is a naturally occurring prenylated chalconoid that promotes the transcription of phase II antioxidant enzymes. Xanthohumol exerted a dose-response in preventing tert-butylhydroxide-induced loss of cell viability in human corneal epithelial (HCE-T) cells and resulted in a significant increase in expression of nuclear factor erythroid 2-related factor 2 (Nrf2), the master regulator of the endogenous antioxidant system. Xanthohumol-encapsulating poly(lactic-co-glycolic acid) nanoparticles (PLGA NP) were cytoprotective against oxidative stress in vitro, and significantly reduced corneal fluorescein staining in the mouse desiccating stress/ scopolamine model for dry eye disease in vivo by reducing oxidative stress-associated DNA damage in corneal epithelial cells. PLGA NP represent a safe and efficacious drug delivery vehicle for hydrophobic small molecules to the ocular surface. Optimization of NP-based antioxidant formulations with the goal to minimize instillation frequency may represent future therapeutic options for dry eye disease and related ocular surface disease.

We use state-of-the-art computer-aided drug design (CADD) techniques to identify prospective inhibitors of the main protease enzyme, 3CLpro of the SARS-CoV-2 virus causing COVID-19. From our screening of over one million compounds including approved drugs, investigational drugs, natural products, and organic compounds, and a rescreening protocol incorporating enzyme dynamics via ensemble docking, we have been able to identify a range of prospective 3CLpro inhibitors. Importantly, some of the identified compounds had previously been reported to exhibit inhibitory activities against the 3CLpro enzyme of the closely related SARS-CoV virus. The top- ranking compounds are characterized by the presence of multiple bi- and monocyclic rings, many of them being heterocycles and aromatic, which are flexibly linked allowing the ligands to adapt to the geometry of the 3CLpro substrate site and involve a high amount of functional groups enabling hydrogen bond formation with surrounding amino acid residues, including the catalytic dyad residues H41 and C145. Among the top binding compounds we identified several tyrosine kinase inhibitors, which include a bioflavonoid, the group of natural products that binds best to 3CLpro. Another class of compounds that decently binds to the SARS-CoV-2 main protease are steroid hormones, which thus may be endogenous inhibitors and might provide an explanation for the age-dependent severity of COVID-19. Many of the compounds identified by our work show a considerably stronger binding than found for reference compounds with in vitro demonstrated 3CLpro inhibition and anticoronavirus activity. The compounds determined in this work thus represent a good starting point for the design of inhibitors of SARS-CoV-2 replication.

Endocannbinoids system (ECS) engrossed a considerable interest as potential therapeutic targets in various carcinomas and cancer related conditions alongside with neurodegenerative diseases. Cannabinoids are implemented in several physiological processes such as appetite stimulation, energy balance, pain modulation and the control of chemotherapy induced nausea and vomiting (CINV). However, pharmacokinetics and pharmacodynamics interactions could be perceived in drug combinations, so in this short review we tried to shed the light over the potential drug interactions of medicinal cannabis. Hitherto, few data have been provided to the healthcare practitioners about the drug-drug interactions of cannabinoids with other prescription medications. In general, cannabinoids are usually well tolerated, but the bidirectional effects may be expected with concomitant administered agents via affected membrane transporters (glycoprotein p, breast cancer resistance proteins) and metabolizing enzymes (Cytochrome P450 and UDP- glucuronosyltransferases). The caveats should be undertaken to closely monitor the responses of cannabis users with certain drugs to guard their safety, especially for the elderly and people with chronic diseases or kidney and liver conditions.

There are dozens of approved, investigational and experimental antiviral agents. Many of these agents cause serious side effects, which can be revealed only after drug administration. Identification of the side effects prior to drug administration is challenging. Here we describe an ex vivo approach for studying immuno- and neuro-modulatory properties of antiviral agents, which could be associated with potential side effects of these therapeutics. The approach combines drug toxicity/efficacy tests and transcriptomics, which is followed by cytokine and metabolite profiling. We demonstrated the utility of this approach with several examples of antiviral agents. We also showed that the approach can utilize different immune stimuli and cell types. It can also include other omics techniques, such as genomics and epigenomics, to allow identification of individual markers associated with adverse reactions to antivirals with immuno- and neuro-modulatory properties.

Machine reading comprehension is a crucial area of research in natural language processing, aiming to enable machines to read and understand text as humans do, and to answer questions related to the text content. The pre-trained language model, represented by BERT, has achieved superior results compared to traditional models in many NLP tasks, leading to the rise of the pre-trained paradigm in the field of natural language processing. This paper addresses the issue that the pre-trained language model lacks the ability to extract long-distance semantic relations and make efficient use of linguistic features. Firstly, the recent developments of the pre-trained language model are described. Then, two feature maps are used to intuitively express the structured long-distance semantic correlation features, and the traditional sequence structure features are integrated. The influence of different feature map construction methods on machine reading comprehension is compared. Finally, the application of the pre-trained language model in machine reading comprehension is summarized and prospected. By fusing graph structure features, the model can learn more abundant language knowledge, thus further improving its reasoning ability.

The COVID-19 pandemic period, from 2020 - 2022 had a significant impact on maternal infant health with mothers impacted more than their infants. We questioned whether there have been any lingering effects from the pandemic. We examined intermediate and long-term pandemic effects of maternal and neonatal outcomes before, during and after the COVID-19 pandemic period. We reviewed mother-infant pairs from three epochs: 1) the pre-COVID-19 period, 2) the COVID-19 pandemic period, and 3) the post-pandemic period. The Case Mix Index (CMI) for the neonates from all 3 epochs were detailed. Post-pandemic we noted a rising trend of LGA infants (10%), and an increase in SGA infants (13%). For women in 2023 we noted an increase in hypertension, preeclampsia, diabetes, and a higher BMI than the pre- pandemic period. There have also been more congenital anomalies (9%), and neonatal CMI increased in the post-pandemic period. Well after the pandemic period, maternal-infant health continues to be affected. For women, increase in hypertension and diabetes during pregnancy is concerning. For the infants, being LGA or SGA may have long-term consequences. The post-pandemic increase in infants with congenital anomalies compared to the pre-pandemic era is an area that needs ongoing review.

The approach to the personal experience and previous ideas about Physical Education of future Primary Education teachers is a starting point of great interest for the teaching of the subject of Didactics of Physical Education. The study aims to investigate these prior beliefs and to verify to what extent this initial perception changes after taking the course on “Didactics of Physical Education”. A concurrent mixed-methods study was conducted, which included two data collection procedures: (1) a pre-experimental design with a single group featuring pre-test and post-test; (2) the analysis of students' autobiographical accounts of their school experience with physical education. The participants were students enrolled in the Bachelor’s degree program in Primary Education at the University of Santiago de Compostela (USC) who undertook the course last year. The results obtained reveal that after taking the subject of Didactics of Physical Education, students give greater value to more positive concepts of learning, socializing, participating, and playing, among others. Similarly, in the post-test, the assessment of concepts such as competitiveness and physical fatigue diminished. In their autobiographical memories, students associate good memories with relationships with classmates and the playful and socializing nature of the subject; and among the bad memories, they highlight the content related to physical performance, competitiveness, and lack of attention to the diversity of students and their individual characteristics.

The present study analyzed the effect of temperature, pH, retention time, pretreatment and mixing ratio on the anerobic digestion process. The parameters during the anaerobic co digestion of cow manure and food waste were then optimized using the Taguchi experimental design method. ANOVA is carried out to find the significant parameters which influence the biogas production. Experimental tests were carried out at laboratory scale reactors kept at different temperatures (28 °C, 35 °C, and 50 °C). The specific methanogenic Performance (SMP) during anerobic digestion at higher temperatures was characterized with the analysis of acetate, propionate, butyrate, hydrogen, glucose, and formate. The improvement of biogas production with different pre-treatment i.e., ultrasonic, autoclave, and microwave techniques also analysed. The results showed that reactor that maintained at 35 °C showed the highest biogas production. While the reactor that maintained at lower temperature (28 °C) produced the lower volume of biogas. As the retention time increases, the amount of biogas produced increases. Methanogenic activities of microorganisms reduced at higher temperature conditions (65 °C). Biogas production increased by 28.1%, 20.23%, and 13.27 % when the of substrates treated with ultrasonic, autoclave, and microwave, respectively, compared to the untreated substrate. The optimized condition for the highest biogas production during anaerobic co digestion of food waste and cow manure is temperature of 35 °C, pH of 7 and mixing ratio (CM: FW=1.5:0.5). ANOVA showed that temperature is the most important input parameter affecting biogas production, followed by mixing ratio.