Phenotypic studies require large datasets for accurate inference and prediction. Collecting plant data in a farm can be very labor intensive and costly. This paper presents the design, architecture (hardware and software) and deployment of a distributed modular agricultural multi-robot system for row crop field data collection. The proposed system has been deployed in a soybean research farm at Iowa State University.

Tandem mass spectrometry (TMS) has emerged as a critical analytical tool in pharmaceutical sciences, playing a pivotal role in ensuring the rational use of medications. This article explores the applications of TMS across various stages of drug development, quality assurance, and patient care, highlighting its precision and reliability in advancing therapeutic efficacy. TMS facilitates the accurate identification and quantification of drug compounds, ensuring that pharmaceutical products meet high standards of purity and potency. By detecting even trace levels of impurities or contaminants, TMS strengthens the quality control processes critical to patient safety. In the realm of pharmacokinetics and pharmacodynamics, TMS enables detailed monitoring of drug absorption, distribution, metabolism, and excretion (ADME), allowing for a better understanding of drug behavior in the human body. It is also instrumental in therapeutic drug monitoring (TDM), ensuring that medication levels remain within therapeutic windows, thus optimizing dosing regimens and minimizing adverse effects. Additionally, TMS supports personalized medicine approaches by assessing drug interactions and tailoring treatments to individual patients. Through its application in drug discovery, development, and therapeutic monitoring, TMS serves as an indispensable tool for fostering rational medication use, contributing to more effective, safe, and personalized pharmaceutical care.

Existing methods of hyperspectral anomaly detection still face several challenges: 1) Due to the limitations of self-supervision, avoiding the identity mapping of anomalies remains difficult; 2) The ineffective interaction between spatial and spectral features leads to the insufficient utilization of spatial information; 3) Current methods are not adaptable to the detection of multi-scale anomaly targets. To address the aforementioned challenges, we proposed a blind spot network based on multi-scale blind spot convolution for HAD. The multi-scale mask convolution module is employed to adapt to diverse scales of anomaly targets, while the dynamic fusion module is introduced to integrate the advantages of mask convolutions at different scales. The proposed approach includes a spatial-spectral joint module and a background feature attention mechanism to enhance the interaction between spatial-spectral features, with a specific emphasis on highlighting the significance of background features within the network. Furthermore, we propose a preprocessing technique that integrates pixel shuffle down-sampling (PD) operation with spatial spectral joint screening to address the issue of anomalous identity map-ping and facilitate finite-scale mask convolution to adapt to the detection of more scale targets. The proposed approach was assessed on four real hyperspectral datasets comprising anomaly targets of different scales. The experimental results demonstrate the effectiveness and superior performance of the proposed methodology compared with nine state-of-the art methods.

In the framework of maritime surveillance, vessel detection techniques based on spaceborne Synthetic Aperture Radar (SAR) images have promoted extensive applications for the effective understanding of unlawful activities at sea. The paper deal with this topic presenting a novel approach exploiting a cascade application of a pre-screening, and discrimination phase. The latter leverage the SAR spectrum by means of sub-looks analysis. For the first time, the method has been validated with experiments on multi-frequency (C-, X-, and L-band) SAR images. For a future syngergic exploitation of more SAR missions, the developed dataset, composed of Sentinel-1, SAOCOM and COSMO-SkyMed images, is comprehensive of multiple images gathered over the same area with short time lag (below 15 minutes). Finally, the diversified processing chains and the results for each mission product and scenarios are discussed. Being the first dataset of SLC (Single Look Complex) SAR multi-frequency data, the present work intends to encourage additional research in this promising field of research.

COVID-19 pandemic has spurred intense research efforts to identify effective treatments for SARS-CoV-2. In silico studies have emerged as a powerful tool in the drug discovery process, particularly in the search for drug candidates that interact with various SARS-CoV-2 receptors. These studies involve the use of computer simulations and computational algorithms to predict the potential interaction of drug candidates with target receptors. The primary receptors targeted by drug candidates include the RNA polymerase, main protease, spike protein, ACE2 receptor, TMPRSS2, and AP2-associated protein kinase 1. In silico studies have identified several promising drug candidates, including Remdesivir, Favipiravir, Ribavirin, Ivermectin, Lopinavir/Ritonavir, and Camostat mesylate, among others. The use of in silico studies offers several advantages, including the ability to screen a large number of drug candidates in a relatively short amount of time, thereby reducing the time and cost involved in traditional drug discovery methods. Additionally, in silico studies allow for the prediction of the binding affinity of drug candidates to target receptors, providing insight into their potential efficacy. However, it is crucial to consider both the advantages and limitations of these studies and to complement them with experimental validation to ensure the efficacy and safety of identified drug candidates.

Carbamate insecticides have been used for over four decades to control brown planthopper, Nilaparvata lugens, but resistance has been reported in many countries, including Korea. The test results on resistance to fenobucarb showed that the LC₅₀ values were 3.08 for the susceptible strain, 10.61 for the 2015 population, and 73.98 for the 2019 population. Compared to the susceptible strain, the 2015 and 2019 populations exhibited resistance levels 3.4 and 24.2 times higher, respectively. To elucidate the reason for the varying levels of resistance to fenobucarb in these populations, mutations in the ace1 gene, the target site of carbamate, were investigated, but no previously reported mutations were confirmed. Through RNAseq analysis focusing on the expression of detoxification enzyme genes as an alternative resistance mechanism, it was found that the carboxylesterase gene Nl-EST1 was overexpressed 2.4 times in the 2015 population and 4.7 times in the 2019 population compared to the susceptible strain. This indicates a strong correlation between the level of resistance development in each population and the expression level of Nl-EST1. Previously, Nl-EST1 was reported in an organophosphorus insecticide-resistant strain of Sri Lanka 2000. Thus, Nl-EST1 is crucial for developing resistance to organophosphorus and carbamate insecticides. Resistance-related genes such as Nl-EST1 could serve as expression markers for resistance diagnosis, and it can apply to integrated resistance management of N. lugens.

Sodium hypochlorite (NaOCl) is widely used in public healthcare facilities; this exposure can result in the development of bacterial tolerance to disinfectant, which has known links to antibiotic cross-resistance. However, the mechanism through which cross-resistance to antibiotics and disinfectants develops remains ambiguous. Therefore, this study aimed to examine the phenotypic, and transcriptomic changes caused by disinfectant exposure in gram-negative bacteria and determine the cause of cross-resistance to antibiotics. The results demonstrated that the misuse of disinfectants plays an important role in the emergence of disinfectant resistance and in the increase in antibiotic resistance. Antibiotic resistance may occur from exposure of gram-negative bacteria to subminimal inhibitory concentrations (MICs) of NaOCl. Ten passages of gram-negative bacteria in increasingly higher subMICs of NaOCl disinfectant was sufficient to increase the MIC to >2,500 µg/ml NaOCl, particularly in K. pneumoniae and P. aeruginosa. To determine the development of cross-resistance to antibiotics due to NaOCl exposure, the MICs for each antibiotic before and after exposure of each strain to sublethal concentrations of NaOCl were compared. After overnight incubation with a sublethal concentration of NaOCl, a statistically significant increase in MIC was only observed for imipenem (P<0.01). Investigation of the mechanism of cross-resistance by means of transcriptome analysis revealed that 1,250 µg/ml NaOCl-adapted K. pneumoniae and P. aeruginosa strains increased resistance to imipenem due to increased expression of the resistance-nodulation-cell division (RND) efflux pumps, such as AcrAB-TolC and MexAB/XY-OprM. Therefore, we suggest that exposure to NaOCl can influence the expression of RND efflux pump genes, contributing to imipenem cross-resistance.

Plant activators have emerged as promising alternatives to conventional pesticides for crop disease manage-ment due to their unique mode of action. By priming the plant's innate immune system, these compounds can induce systemic acquired resistance against a broad spectrum of pathogens without directly inhibiting their proliferation. Key advantages of plant activators include prolonged defense activity, lower effective dosages, and negligible risk of developing pathogen resistance. Among the various defensive pathways tar-geted, the salicylic acid (SA) signaling cascade has been extensively explored, leading to the successful devel-opment of commercial activators like benzothiadiazole for widespread application in crop protection. While the action sites of many SA-targeting activators have been preliminarily mapped to different steps along the pathway, a comprehensive understanding of their precise mechanisms remains elusive. This review provides a historical perspective on plant activator development and outlines diverse screening strategies employed across multiple levels, from whole-plant bioassays to molecular and transgenic approaches. We expound on the intricate components, biological relevance, and regulatory circuits governing the SA pathway, while criti-cally examining the structural features, bioactivities, and proposed modes of action of classical activators such as benzothiadiazole derivatives, salicylic acid analogs, and other small molecules. Insights from field trials as-sessing their practical applicability are also discussed. Furthermore, we highlight the current status, challenges, and future prospects in the realm of SA-targeting activator development globally, with a focus on recent en-deavors in China. Collectively, this comprehensive review aims to synthesize existing knowledge and provide a roadmap for future research toward developing more potent and mechanistically understood plant activa-tors that fortify crop immunity against disease.

In agriculture, soil-borne fungal pathogens, especially Fusarium oxysporum strains, are posing a serious threat to efforts to achieve global food security. In the search for safer agrochemicals, silica nanoparticles (SiO2NPs) have recently been proposed as a new tool to alleviate pathogen damage including Fusarium wilt. Hollow mesoporous silica nanoparticles (HMSNs), a unique class of SiO2NPs, have been widely accepted as a desired pesticide carrier. However, their role in enhancing the disease resistance and the specific mechanism remain unknown. In this study, three sizes of HMSNs (19, 96 and 406 nm as HMSNs–19, HMSNs–96 and HMSNs–406, respectively) were synthesized and characterized to determine their effects on seed germination, seedling growth, and Fusarium oxysporum f. sp. phaseolus (FOP) suppression in cowpea roots by foliar spray using phenotypes, fresh biomass and disease progression as indicators. The results revealed that three HMSNs exhibited no adverse impacts on seed germination and tended to improve plant growth. Also, they exert their FOP suppression with a size- and concentration-dependent manner. HMSNs–406 possessed the best control effect at a concentration of 1000 mg/L showing an upto 40.00% decline in the disease severity. The Si(OH)4 control was also effective on FOP suppression at a lower concentration of 100 mg/L, whereas its higher concentrations exhibited obviously adverse impacts on FOP control, seed germination and plant growth. Moreover, we conformed that HMSNs posed their Fusarium wilt suppression in cowpea plant by activating SA (salicylic acid)-dependent SAR (systemic acquired resistance) responses rather than directly suppressing FOP. A higher level of SA content and elevated expression of its maker genes of PR-1 and PR-5 in HMSNs–406 treated cowpea roots provided substantial evidences of this mode of action. Other resistance-related genes, as well as defense-responsive enzymes, were also involved in the HMSNs-activated SAR pathway. Overall, for the first time, our results extended a new role of HMSNs as a potent elicitor to serve as a versatile alternative for plant disease protection of low cost, highly efficiency and sustainability.

Culex quinquefasciatus is an important target for vector control because of its ability to transmit pathogens that cause disease. Most populations are resistant to pyrethroids and often to organophosphates, the two most common classes of active ingredients used by public health agencies. A knockdown resistance (kdr) mutation, resulting in a change from a leucine to phenylalanine in the voltage gated sodium channel, is one mechanism contributing to the pyrethroid resistant phenotype. Enzymatic resistance has also been shown to play a very important role. Recent studies have shown strong resistance in populations even when kdr is relatively low which indicates factors other than kdr may be larger contributors to resistance. In this study, we examined on a statewide scale (over 70 populations), the strength of the correlation between resistance in the CDC bottle bioassay and the kdr genotypes and allele frequencies. Spearman correlation analysis showed only moderate (-0.51) and weak (-0.29) correlation between the kdr genotype and permethrin and deltamethrin respectively. The frequency of the kdr allele was an even weaker correlate. These results indicate, in contrast to Aedes aegypti, assessing kdr in populations of Culex quinquefasciatus is not a good surrogate for phenotypic resistance testing.

Drug resistance in tumor cells is a significant roadblock in the clinical management of advanced or recurrent diseases in endometrial cancers. As a part of the tumor-stromal ecosystem, tumor cells are ecologically connected to the cancer-associated fibroblasts (CAFs), which form contributory elements of the tumor microenvironment (TME). We recently reported a novel model of patient-derived CAF-based 2-cell Hybrid Co-Culture (HyCC) to evaluate CAFs' role in developing drug resistance and understanding personalized tumor cell-CAF dialogue. Using our 2-cell HyCC model of patient-derived endometrial CAFs, we present data to demonstrate the direct counter-inhibitory effect of CAFs to combinations of cytotoxic and targeted drugs in developing drug resistance. CAFs derived from resected endometrial tumor samples were first passage-wise characterized before and after freeze-thaw for their positive and negative CAF markers expression pattern. Paclitaxel and its combination with copanlisib, TAK228, lenvatinib, and trametinib were used to test the 3D clonogenic growth of endometrial AN3CA cells on endometrial CAFs. We demonstrate that CAF-mediated resistance to antitumor drugs occurs via direct and indirect contact with CAFs in HyCC. Our data established the strength of the 2-cell HyCC model of patient-derived CAFs in solid tumors and provided a model of resistance to antitumor drugs tailored on a patient-to-patient basis.

Abstract Metabolic syndrome (MetS) is considered a metabolic disorder that has been steadily increasing globally and seems to parallel the increasing prevalence of obesity. It consists of a cluster of risk factors, which traditionally includes obesity and hyperlipidemia, hyperinsulinemia, hypertension, and hyperglycemia. These four core risk factors are associated with insulin resistance (IR) and importantly, the MetS is known to increase the risk for developing cerebrocardiovascular disease and type 2 diabetes mellitus. The MetS had its early origins in IR and syndrome X. It has undergone numerous name changes with additional risk factors and variables being added over the years; however, it still remains the MetS worldwide for the past three decades. This overview continues to add novel insights to the MetS and suggests that leptin resistance with hyperleptinemia, aberrant mitochondrial stress and reactive oxygen species (ROS), impaired folate-mediated one-carbon metabolism with hyperhomocysteinemia, vascular stiffening, microalbuminuria, and visceral adipose tissues extracellular vesicle exosomes be added to the list of associated variables. Notably, the role of a dysfunctional and activated endothelium and deficient nitric oxide bioavailability along with a dysfunctional and attenuated endothelial glycocalyx, vascular inflammation, systemic metainflammation, and the important role ROS and reactive species interactome are discussed. With new insights and knowledge regarding the MetS, comes the possibility of new findings through further research.

Amebiasis is a disease caused by the unicellular parasite Entamoeba histolytica. In most cases, the infection is asymptomatic but when symptomatic, the infection can cause dysentery and invasive extraintestinal complications. In the gut, E.histolytica feeds on bacteria. Increasing evidences support the role of the gut microbiota in the development of the disease. In this review we will discuss the consequences of E.histolytica infection on the gut microbiota. We will also discuss new evidences about the role of the gut microbiota in regulating the resistance of the parasite to oxi-dative stress and its virulence.

A human organism depends on stable glucose blood levels in order to maintain the metabolic needs. Glucose is considered as the most important energy source and glycolysis is postulated as a backbone pathway. However, when glucose supply is limited, ketone bodies and amino acids can be used to produce enough ATP. In contrast, for the functioning of pentose phosphate pathway (PPP) glucose is essential and cannot be substituted by other metabolites. PPP generates and maintains levels of NADPH needed for reduction of oxidized glutathione and protein thiols, synthesis of lipids and DNA as well as for xenobiotic detoxification, regulatory redox signaling and counteracting infections. Flux of glucose into a PPP, particularly under extreme oxidative and toxic challenges is critical for survival, whereas the glycolytic pathway is primarily activated when glucose is abundant, and there is lack of NADP⁺ that is required for activation of glucose-6 phosphate dehydrogenase. An important role of glycogen stores in resistance to oxidative challenges is discussed. Current evidences explain disruptive metabolic effects and detrimental health consequences of chronic nutritional carbohydrate overload and provides new insights into positive metabolic effects of intermittent fasting, caloric restriction, exercise, and ketogenic diet through modulation of redox homeostasis.

Activating mutations in the Epidermal Growth Factor Receptor gene occur as early cancer-driving clonal events in a subset of patients with non-small cell lung cancer (NSCLC) and result in increased sensitivity to EGFR-tyrosine-kinase-inhibitors (EGFR-TKIs). Despite very frequent and often prolonged clinical response to EGFR-TKIs, virtually all advanced EGFR-mutated (EGFRM+) NSCLCs inevitably acquire resistance mechanisms and progress at some point during treatment. Additionally, 20-30% of patients do not respond or respond for a very short time (< 3 months) because of intrinsic resistance. While several mechanisms of acquired EGFR-TKI-resistance have been determined analyzing tumor specimens obtained at disease progression, the factors causing intrinsic TKI-resistance are less understood. However, recent comprehensive molecular-pathological profiling of advanced EGFRM+ NSCLC at baseline has illustrated the co-existence of multiple genetic, phenotypic, and functional mechanisms that may contribute to tumor progression and cause intrinsic TKI-resistance. Several of these mechanisms have been further corroborated by preclinical experiments. Intrinsic resistance can be caused by mechanisms inherent EGFR or by EGFR-independent processes, including genetic, phenotypic or functional tumor changes. This comprehensive review describes the identified mechanisms connected with intrinsic EGFR-TKI-resistance and differences and similarities with acquired resistance and among clinically implemented EGFR-TKIs of different generations. Additionally, the review highlights the need for extensive pre-treatment molecular profiling of advanced NSCLC for identifying inherently TKI-resistant cases and designing potential combinatorial targeted strategies to treat them.

Bacterial antibiotic resistance has become a major global health concern. One of the main reasons for the development of multi-drug resistance properties in bacteria is due to the bacterial efflux pump systems. They are important transport proteins, mainly involved in the removal of toxic substrates like antibiotics from inner cell environment. These pumps are responsible for the intrinsic ability of bacteria to get resistant to the antibiotic. Various types of efflux pumps are present in the Gram-positive and Gram-negative bacteria. Plant-derived products like Capsaicin, Olympicin A, and Indirubicin were found to be inhibitors of an efflux pump in Staphylococcus aureus similarly Ursolic acid derivatives; Daidzein and Lanatoside C were plant-derived inhibitors of an efflux pump in Escherichia coli. In this review detail information have been provided about efflux pump inhibitors that have been found to be effective in the Gram-positive bacteria and Gram-negative bacteria. The aim of this review is to focus on the role of plant-derived compounds as effective efflux pumps inhibitors with reference to mainly Staphylococcus aureus and Escherichia coli.

Metered Dose Inhalers (MDIs) play a crucial role in managing respiratory diseases, but their effectiveness depends on whether the intended dose is delivered to the target, which can be influenced by various factors. Accurate assessment of MDI performance is crucial for optimizing MDI delivery and ensuring drug efficacy. This study numerically examined the role of evaporation dynamics and dosimetry methods in assessing MDI delivery efficiency to different regions in a mouth-lung model extending to G11. Experimentally determined spray exit speed, applied dose, and droplet size distribution were implemented as the initial/boundary conditions. Large eddy simulations (LES) were used to resolve the transient inhalation flows, and a chemical species model was applied to simulate vapor and temperature variations in the airflow. A multi-component model was used to consider the heat and mass transfer between the droplets and airflow. The model was validated against literature data and applied to evaluate the impact of evaporation on pulmonary drug delivery using MDI, in comparison to inert particles. Three methods were used to quantify deposition: based on droplet count, droplet mass, and the drug carried by the droplets. Results demonstrate that evaporation notably alters the spray droplet size distribution and subsequent deposition patterns. Compared to inert particles, evaporation led to significantly more droplets ranging from 1–5 µm entering the pulmonary region. For a given region, large discrepancies were observed in deposition fraction (DF) using different dosimetry methods. In the lower lung, the count-based DF (33.9%) and mass-based DF (2.4%) differed by more than one order of magnitude, while the drug-based DF fell between them (20.5%). This large difference highlights the need to include evaporation in predictive dosimetry, as well as to use the appropriate method to quantify the delivery efficiency of evaporating droplets.

Background: Medication errors often stem from incomplete or incorrect transfer of drug information during reviews. To enhance medication review processes, a collaborative healthcare team, including a pharmacist in the surgical ward, is essential. This study aimed to identify the frequency and the kind of intentional and unintentional discrepancies related to the prescriptions within two surgical wards. Methods: A prospective observational study was conducted among adult patients admitted to two surgical settings. The patients were selected between May 30th and November 30th, 2021. The study followed a three-phase structure: patient selection, medication review to identify discrepancies and DRPs, and the detection of any such issues in the discharge letter. Results: The most frequent types of discrepancies collected were substitutions (60.9%) for the Endocrinological Surgery and omissions for General Surgery (53.4%). In Endocrinological Surgery, 45.9% of cases exhibited class C drug interactions. In General Surgery, class D drug interactions were predominantly observed (54.1%), with 93.3% attributed to drugs carrying an elevated risk of prolonging the QT interval. Conclusions: Frequently, the medication review process is superficially carried out, introducing errors that may adversely affect patient health. This study explores the potential positive impact of involving the clinical pharmacist in identifying and managing discrepancies and DRPs.

Drugs-drugs interactions(DDI) are entities composed of different chemical substructures (functional groups). In existing methods that predict drug–drug interactions based on the usage of substructures, each node is considered the center of a substructure, and adjacent nodes eventually become centers of similar substructures, resulting in redundancy. Furthermore, the significant differ- ences in structure and properties among compounds can lead to unrelated pairings, making it difficult to integrate information. This heterogeneity negatively affects the prediction results. To address these issues, we propose a drug–drug interaction prediction method based on substructure signature learning (DDI-SSL). This method extracts useful information from local subgraphs surrounding drugs and effectively utilizes substructures to assist in predicting drug side effects. Additionally, a deep clustering algorithm is used to aggregate similar substructures, allowing any individual subgraph to be reconstructed using this set of global signatures. Furthermore, we developed a layer-independent collaborative attention mechanism to model the mutual influence between drugs, generating signal strength scores for each class of drugs to mitigate noise caused by heterogeneity. Finally, we evaluated DDI-SSL on a comprehensive dataset and demonstrated improved performance in DDI prediction compared to state-of-the-art methods.

The study aimed to identify clinical pharmacology patterns of prescribed and taken medications in older cardiovascular patients using electronic health records (EHRs) (n = 704) (2019–2022). Medscape Drug Interaction Checker was used to identify pairwise drug-drug interactions (DDIs). Prevalence rates of DDIs were 73.5% and 68.5% among taken and prescribed drugs, respectively. However, total number of DDIs was significantly higher among prescribed medications compared with the list of taken drugs (p < 0.05). Serious DDIs comprised 16% and 7% of all DDIs among prescribed and taken medications, correspondingly (p < 0.05). Median DDI numbers between prescribed versus taken medications were Me = 2, IQR 0-7 and Me = 3, IQR 0-7 per record, respectively. Prevalence of polypharmacy was significantly higher among prescribed medications compared with taken medications (p < 0.05). Women were taking significantly more drugs and had higher rates of polypharmacy and DDIs (p < 0.05). No sex-related differences were observed in the list of prescribed medications. ICD code U07.1 (COVID-19, virus identified) was associated with the highest median DDI number per record. Further research is warranted to improve EHR structure, patient engagement in reporting adverse drug reactions, and genetic profiling of patients to avoid potentially serious DDIs.

Background: This article evaluates the perception of drug use control and strategies in Valencia City (Spain) in a general and clinical population, in two independent studies. Material and Methods: 1071 people participated. In the Study 1 (n= 924) the entire sample came from general population (GP), and in the Study 2 (n=147), 68 were drug users being treated in an Addictive Behaviors Unit (ABU), and 79 people of the GP. The drug use control perception and strategies in both subgroups were compared. The participants filled in the Drug Use Strategies Scale and a Drug Use Survey. Results: A high level of perception of drug control in GP was obtained (72,7% in the Study 1 and 67,5% in the Study 2), and 32.5% in ABU subgroup. People in the PG and drug users in treatment differ in some control strategies. A predictive profile of the perception of control was obtained for the Study 2. Conclusion: The high degree of perception of controlling drug use in the GP, and partially in drug users being treated, and the specific control strategies reported suggests that moderate use and drug control strategies are a great value alternative to bear in mind compared to abstinence.

Flavonoids comprise a large group of structurally diverse polyphenolic compounds of plant origin and are abundantly found in human diet such as fruits, vegetables, grains, tea, dairy products, red wine and so on. Major classes of flavonoids include flavonols, flavones, flavanones, flavanols, anthocyanidins, isoflavones, and chalcones. Owing to their potential health benefits and medicinal significance, flavonoids are now considered as an indispensable component in a variety of medicinal, pharmaceutical, nutraceutical, and cosmetic preparations. However, flavonoids play a significant role in preventing cardiovascular diseases (CVDs), which could be mainly due to their antioxidant, antiatherogenic, and antithrombotic effects. Epidemiological and in vitro/in vivo evidences of antioxidant effects support the cardioprotective function of dietary flavonoids. Further, the inhibition of LDL oxidation and platelet aggregation following regular consumption of food containing flavonoids and moderate consumption of red wine might protect against atherosclerosis and thrombosis. A study suggests that daily intake of 100 mg of flavonoids through diet may reduce the risk of developing morbidity and mortality due to coronary heart disease (CHD) by approximately 10%. This review summarizes dietary flavonoids with their sources and potential health implications in CVDs including various redox-active cardioprotective (molecular) mechanisms with antioxidant effects. Pharmacokinetic (oral bioavailability, drug metabolism), toxicological and therapeutic aspects of dietary flavonoids are also addressed herein with future directions for the discovery and development of useful drug candidates/ therapeutic molecules.

In 2019, Chinese government implemented the first round of National Centralized Drug Procurement (NCDP) pilot (so-called "4+7" policy) in mainland China, achieved a prominent price reduction of 52% on average for 25 bidding winning products. Under cross-price elasticity theory, the price behavior of pharmaceutical enterprises for policy-related drugs might change. This study used drug purchasing data from the Centralized Drug Procurement Survey in Shenzhen 2019, and applied single-group Interruption Time Series (ITS) design to examine the impact of "4+7" policy on the drug price index (DPI) of policy-related drugs. The ITS analysis showed that the DPI of winning (-0.183 per month, p&lt;0.0001) and non-winning (-0.034 per month, p=0.046) products significantly decreased after the implementation of "4+7" policy. No significant difference was found for the immediate change of DPI for alternative drugs (p=0.537), while a significant decrease in change trend was detected in the post-"4+7" policy period (-0.003 per month, p=0.014). The DPI of the overall policy-related drugs significantly decreased (-0.261 per month, p&lt;0.0001) after "4+7" policy. These findings indicate that the price behavior of pharmaceutical enterprises changed under NCDP policy, while the price linkage effect is still limited. It is necessary to further expand the scope of centralized purchased drugs and strengthen the monitoring of related drugs regarding price change and consumption structure.

Nanoprecipitation by liquid anti-solvent precipitation is one of the most versatile methods to produce pure drug nanoparticles (PDNPs) owing to the ability to optimize the properties of the product. Nevertheless, nanoprecipitation shows broad particle size distribution and low physical stability, leading to high batch-to-batch variability and challenging the bench-to-bedside translation. Microfluidics has emerged as a powerful tool to produce PDNPs in a simple, reproducible, and cost-effective manner with excellent control over NP size. In this work, we designed and fabricated T- and Y-shaped Si-made microfluidics device and used it to produce pure NPs of three kinase inhibitors of different lipophilicity and water-solubility, namely imatinib, dasatinib and tofacitinib, without the use of colloidal stabilizers. PDNPs display sizes in the 90-350 nm range (dynamic light scattering) and a rounded shape (high-resolution scanning electron microscopy). Analysis by X-rays diffraction and differential scanning calorimetry confirmed that this method results in highly amorphous NPs. In addition, we show that the flow rate of solvent, the anti-solvent, and the channel geometry of the device play a key role in the size of the generated NPs.

The development of targeted therapeutics for cancer continues to receive intense research attention as laboratories and pharmaceutical companies seek to develop drugs and technologies that improve treatment efficacy and mitigate harmful side effects. In the aftermath of World War I, it was discovered that mustard gas destroys rapidly dividing cells and could be used to treat cancer. Since then, chemotherapy has remained a predominant treatment for cancer; however, the destruction of dividing cells throughout the body yields devastating side effects including off-target damage of the digestive tract, bone marrow, skin, and reproductive tract. Furthermore, the high mutation rate of cancerous cells often renders chemotherapy ineffective long-term. Therapies with improved specificity, localization, and efficacy are redefining cancer treatment. Herein, we define and summarize the principal advancements in targeted cancer treatment and briefly comment on the march towards personalized medicine in the treatment of human cancer.

There are guidelines on lactation following maternal analgo-sedative exposure, but these do not consider the effect of maternal fasting, nor fluid abstention on human milk macronutrient composition. We therefore performed a structured search (PubMed) on ‘human milk composition’ and screened title, abstract and full paper on ‘fasting’ or ‘abstention’ and ‘macronutrient composition’ (lactose, protein, fat, solids, triglycerides, cholesterol). This resulted in 6 papers and one abstract related to religious fasting (n=129 women) and observational studies in lactating women (n=23, healthy volunteers, fasting). These data reflect two different ‘fasting’ patterns: an acute (18-25h) model in 71 (healthy volunteers, Yom Kippur/Ninth of Av) women and a chronic fasting (Ramadan) model in 81 women. Changes were most related to electrolytes and were moderate, with almost no changes in macronutrients during acute fasting. We therefor conclude that neither short term fasting nor fluid abstention (18-25h) affect human milk macronutrient composition, so that women can be reassured when this topic were raised during consulting. Besides the nutritional relevance, this also matters as clinical research samples – especially to estimate analgo-sedative exposure by lactation - are commonly collected after maternal procedural sedation, associated with maternal fasting and physiology-based pharmacokinetic (PBPK) models assume stable human milk composition.

SARS-CoV-2 is the betacoronavirus responsible for the COVID-19 pandemic. It was listed as a potential global health threat by WHO due to high mortality, high basic reproduction number and lack of clinically approved drugs and vaccines for COVID-19. The genomic sequence of the virus responsible for COVID-19, as well as the experimentally determined three dimensional structure of the Main protease (Mpro) are available. The reported structure of the target Mpro was utilized in this study to identify potential drugs for COVID-19 using molecular docking based virtual screening of all approved drugs. The results of this study confirm preliminary reports that some of the drugs approved for treatment of other viral infections have the potential for treatment of COVID-19. Selected antiviral drugs, approved for human therapeutic applications, were ranked for potential effectiveness against COVID-19, based on predicted binding energy to the target Mpro of SARS-CoV-2, and novel candidates for drug repurposing were identified in this study. In addition, potential mechanisms for beneficial off target effects of some drugs in clinical trials were identified by using molecular docking.

Background and Objectives: Acute aortic dissection (AD) is a life-threatening condition and early detection can significantly improve patient outcomes and survival. This study evaluates the clinical benefits of integrating a deep-learning (DL)-based application for automated detection and prioritisation of AD on chest CT angiographies (CTAs), focusing on the reduction of scan-to-assessment (STAT) and interpretation times (IT). Materials and Methods: This retrospective Multi-Reader, Multi-Case (MRMC) study compared AD detection with and without artificial intelligence-(AI) assistance. Ground truth was established by two U.S. board-certified radiologists, while three additional expert radiologists participated as readers. All participants assessed the same CTAs without AI-assistance (pre-AI arm) and, after a 1-month washout period, with the help of the device outputs (post-AI arm). STAT and IT were compared between the two phases. Results: The study included 285 CTAs (95 per reader, per arm), with a mean patient age of 58.5 years ±14.7(SD), 52% men, 37% prevalence. AI assistance significantly reduced STAT for detecting 33 true positive AD cases, from 15.84 minutes (95% CI: 13.37–18.31min) without AI to 5.07 minutes (95% CI: 4.23–5.91min) with AI, a 68% reduction (p<0.01). IT also decreased significantly, from 21.22 seconds (95% CI: 19.87–22.58s) without AI to 14.17 seconds (95% CI: 13.39–14.95s) with AI (p<0.05). Conclusions: Integrating a DL-based algorithm for AD detection on chest CTAs significantly reduces both STAT and IT. By prioritising the most urgent cases, AI ensures faster diagnosis and improves the workflow efficiency in clinical radiology practice, compared to standard First-In First-Out (FIFO) workflow.

The multi-stage, multi-level assembly job shop scheduling problem (MsMlAJSP) is commonly encountered in the manufacturing of complex customized products. Ensuring production efficiency while effectively improving energy utilization is a key focus in the industry. For the energy-efficient MsMlAJSP (EEMsMlAJSP), an improved imperialist competitive algorithm based on Q-learning (IICA-QL) is proposed to minimize the maximum completion time and total energy consumption. In IICA-QL, a decoding strategy with energy-efficient triggers based on problem characteristics is designed to ensure solution quality while effectively enhancing search efficiency. Additionally, an assimilation operation with operator parameter self-adaptation based on Q-learning is devised to overcome the challenge of balancing exploration and exploitation with fixed parameters, thus the convergence and diversity of the algorithmic search is enhanced. Finally, the effectiveness of the energy-efficient strategy decoding trigger mechanism and the operator parameter self-adaptation operation based on Q-learning is demonstrated through experimental results, and the effectiveness of IICA-QL for solving EEMsMlAJSP is verified by comparing with other algorithms.

Deep convolutional neural network (CNN) has shown their great advantages in the single image deraining task. However, most existing CNN-based single image deraining methods still suffer from residual rain streaks and details lost. In this paper, we propose a deep neural network including the Multi-scale feature extraction module and the channel attention module, which are embed in the feature extraction sub-network and the rain removal sub-network respectively. In the feature extraction sub-network, the Multi-scale feature extraction module is constructed by a Multi-layer Laplacian pyramid, and is then integrated multi-scale feature maps by a feature fusion module. In the rain removal sub-network, the channel attention module, which assigns different weights to the different channels, is introduced for preserving image details. Experimental results on visually and quantitatively comparison demonstrate that the proposed method performs favorably against other state-of-the-art approaches

Defect detection in ferromagnetic substrates is often hampered by non-magnetic coating thickness variation when using conventional eddy current testing technique. The lift-off distance between the sample and the sensor is one of the main obstacles for the thickness measurement of non-magnetic coatings on ferromagnetic substrates when using the eddy current testing technique. Based on the eddy current thin-skin effect and the lift-off insensitive inductance (LII), a simplified iterative algorithm is proposed for reducing the lift-off variation effect using a multi-frequency sensor. Compared to the previous techniques on compensating the lift-off error (e.g., the lift-off point of intersection) while retrieving the thickness, the simplified inductance algorithms avoid the computation burden of integration, which are used as embedded algorithms for the online retrieval of lift-offs via each frequency channel. The LII is determined by the dimension and geometry of the sensor, thus eliminating the need for empirical calibration. The method is validated by means of experimental measurements of the inductance of coatings with different materials and thicknesses on ferrous substrates (dual-phase alloy). The error of the calculated coating thickness has been controlled to within 3 % for an extended lift-off range of up to 10 mm.

Porous ceramics can be realized by different methods and are used for manifold applications, like cross-flow-membranes or wall-flow-filters, porous burners, solar receivers, structural design elements or catalytic supports. Within this paper three different alternative process routes are presented, which can be used to manufacture porous ceramic components with different properties or even graded porosity. The first process route bases on additive manufacturing (AM) of macro porous ceramic components, the second on AM of a polymeric template, which is used to manufacture porous ceramic components via replica technique. Finally, the third process route bases on an AM technology, which allows the manufacturing of multi-material or multi-property ceramic components, like components with dense and porous volumes in one complex shaped component.

Polycystic ovary syndrome (PCOS) is the predominant endocrine disorder among women of re-productive age and represents the leading cause of anovulatory infertility, which imposes a con-siderable health and economic burden. Currently, medications used to treat PCOS can lead to certain adverse reactions, such as affecting fertility and increasing the risk of venous thrombosis. Drug delivery systems utilizing nanomaterials, characterized by prolonged half-life, preci-sion-targeted delivery, enhanced bioavailability, and reduced toxicity, are currently being em-ployed in the management of PCOS. This innovative approach is gaining traction as a favored strategy for augmenting the therapeutic efficacy of medications. Consequently, this paper dis-cusses the roles of nanoparticles, nanocarriers, and targeted ligands within nanomaterial-based drug delivery systems, aiming to identify optimal methodologies for treating PCOS using nano-materials. Additionally, prospective research avenues concerning nanomaterial-based delivery systems in the context of PCOS, as well as the implications of existing insights on the advancement of novel therapies for PCOS, are highlighted.

Objective: Evaluation of individuals with intravenous drug addiction who developed infective endocarditis (IE) is required for a better understanding of the management that can be applied in these cases. This study aimed to shed light on the complex interplay between intravenous drug use and IE with the ultimate goal of improving patient care and outcomes Method: The study examined the clinical outcomes of 43 patients admitted with infective endocarditis (IE) associated with injection drug use. Data was collected over an average follow-up period of 12 months, providing a substantial timeframe to assess the long-term effects of different treatment approaches. The research focused on comparing the outcomes between two distinct groups: patients who received medical treatment alone and those who underwent surgical intervention in addition to medical management. Results This study included 43 intravenous drug users who were diagnosed with infective endocarditis (IE). The mean age of the patient cohort was 31 ± 9 years with a predominance of males (74.4%). All cases involved native valve IE, with the aortic valve being the most commonly affected (62.9%), followed by the tricuspid (30.2%) and mitral valves (6.9 %). Multiple valve involvement was observed in 13.9% of the cases. The study population had a high prevalence of comorbidities, particularly HIV infection (65.1%) and hepatitis C infection (25.5%). The study also revealed that 19.3% of the patients had previously experienced IE. Mortality rates were slightly higher in patients with recurrent IE (23.2%) than in those who experienced their first episode. Transthoracic echocardiography proved to be a highly effective diagnostic tool for detecting vegetation in 95% of the cases. Microbiological analysis identified Staphylococcus aureus as the predominant causative organism, isolated from blood cultures in 55.8% of the cases. These findings highlight the complex nature of IE in intravenous drug users, emphasizing the importance of comprehensive management strategies that address both cardiac manifestations and underlying comorbidities in this high-risk population. Conclusions: Injection drug use–associated infective endocarditis presents a significant challenge in modern healthcare, with patients facing a high risk of complications and poor clinical outcomes despite current therapeutic approaches. This persistent issue underscores the complexity of treating individuals with both infectious diseases and substance use disorders. The multifaceted nature of these cases often involves immediate cardiac infection, as well as concurrent medical, psychological, and social challenges that can complicate treatment and recovery.

DNA - the repository of genetic information harbours sequences rich in Guanine that adopt non-B form four-stranded DNA secondary structures termed as G-quadruplexes (G4s). Such non-canonical structures tend to impede the progression of routine replisome and are implicated to have crucial roles in replication, transcription and epigenetic regulation while also ensuring genomic stability. It is now fully established that G4s are enzymatically unfolded by helicases, thus, preventing transient yet apparent impediments to the vital replisome progression. This unfolding of G-quadruplex ensures genetic and epigenetic stability. Given the importance of G4 biology for multiple human parasites such as, Mycobacterium tuberculosis, research efforts probing parasitic G4 biology is gaining momentum with the hope to enable therapeutic intervention. We herein shed light on G4s, conditions that lead to their formation and the mechanisms employed by cells to cause their unfolding. Towards the end, potential drug discovery avenues that arise from targeting parasitic helicases and G4 biology are summarized.

Extracellular vesicles (EVs) are natural carriers of biomolecules that play a crucial role in cell-to-cell communication and tissue homeostasis under normal and pathological conditions, including inflammatory diseases and cancer. Since the discovery of the pro-regenerative and immune-modulating properties of EVs, EV-based therapeutics have entered clinical trials for conditions such as myocardial infarction and autoimmune diseases, among others. Due to their unique advantages—such as superior bioavailability, substantial packaging capacity, and the ability to traverse biological barriers—EVs are regarded as a promising platform for targeted drug delivery. However, achieving sufficient accumulation of therapeutic agents at the target site necessitates a larger quantity of EVs per dose compared to using EVs as standalone drugs. This challenge can be addressed by administering larger doses of EVs, increasing the drug dosage per administration, or enhancing the selective accumulation of EVs at target cells. In this review, we will discuss methods to improve the isolation and purification of EVs, approaches to enhance cargo packaging—including proteins, RNAs, and small-molecule drugs—and technologies for displaying targeting ligands on the surface of EVs to facilitate improved targeting. Ultimately, this guide can be applied to the development of novel classes of EV-based therapeutics and to overcoming existing technological challenges.

Toxoplasma gondii is a protozoan and the etiologic agent of toxoplasmosis causes high mortality in immunocompromised individuals and newborns. Despite the medical importance of toxoplasmosis, few drugs are available for its treatment, which are associated with side events and parasite resistance. Here, we show a screening of molecules present in Covid-Box as a way of discovering new hits with anti-T. gondii activity. Covid-Box contains 160 molecules with known or predicted activity against SARS-CoV-2. Our analysis selected 23 Covid-Box molecules that can inhibit the tachyzoite forms of the RH strain of T. gondii in vitro by more than 70% at 1 µM after seven days of treatment. The inhibitory curves showed that most of these molecules inhibited the proliferation of tachyzoites with IC50 values below 0.80 µM; Cycloheximide and (-)-Anisomycin were the most active drugs, with IC50 values of 0.02 μM. Cell viability assays showed that the compounds are not toxic at active concentrations, and most are highly selective for parasites. Overall, all 23 compounds were selective, and for three of them (Apilimod, Midostaurin, and Salinomycin), this is the first report of activity against T. gondii. To better understand the effect of the drugs, we analyzed the effect of six of them on the ultrastructure of T. gondii using transmission electron microscopy. The main changes observed in parasite morphology after treatment with the selected drugs were changes in cell division and parasite organelles.

Multiple Myeloma (MM), is a hematological malignancy and poses significant therapeutic challenges. This review synthesizes evidence from pivotal clinical trials to guide induction treatment for transplant-eligible (TE), newly diagnosed MM (NDMM) patients. Emphasizing the evolution from three-drug to four-drug induction therapies, we highlight the integration of monoclonal antibodies, particularly CD38 recombinant monoclonal antibody agents, into treatment regimens. Our analysis includes a comprehensive literature review of research from major databases and conferences conducted between 2010 and 2024, culminating in the detailed evaluation of 47 studies. The findings underscore the superiority of quadruple regimens in TE NDMM, notably those incorporating daratumumab, in achieving superior responses including progression-free survival (PFS), minimal residual disease (MRD) negativity, overall response rate (ORR), and overall survival (OS) when compared to triple-drug regimens. As treatment regimens evolve with additional agents, the improved outcomes with treatment-related adverse events should be carefully balanced. This review advocates for a paradigm shift towards quadruple induction therapies for TE NDMM, offers a detailed insight into the current landscape of MM treatment, and reinforces a new standard of care.

As the world population grows, fulfilling the need for biomaterials in the healthcare system becomes increasingly important. Biomaterials, which include metals, polymers, ceramics, and composites, play an important role in the creation of medical devices that improve people's lives. The European Society for Biomaterials described biomaterials as non-biological materials used in medical devices to interact with biological systems. This definition has developed to encompass materials that treat, assess, or replace tissues or bodily functions. Biocompatibility, as defined by the FDA, is a key feature of biomaterials, as is the requirement to fulfil design requirements such as mechanical performance, geometry, and electrical control. Over the last decade, advances in regenerative medicine and tissue engineering have boosted biomaterials' usage in medical applications dramatically. Despite its promise, scientists, engineers, and physicians continue to face significant challenges due to the complexity of biomaterials. Biomaterials have various benefits, including biodegradability, non-toxicity, and biocompatibility, making them extremely useful for replacing, sustaining, or improving biological activities in damaged tissues. They are used in a wide range of applications, including tissue engineering implants, human tissue healing and regeneration, medication delivery systems, and biosensors. This study gives insights into the fundamental characteristics, case studies, and ethical issues associated with the usage and use of biomaterials, further examining their potential and significance in healthcare and medicine.

Lithium is the superior first-line treatment for bipolar disorder (BD). Yet the percentage of patients receiving lithium is abysmally low, especially in the USA. Since psychiatrists have failed to place lithium in its appropriate role, we make the case that patients with BD themselves need to be better educated about the unique characteristics and preeminence of the drug so that it can be used more often and appropriately. Lithium has a highly unfavorable popular reputation among would-be patients and many psychiatrists. Thus, a direct appeal to patients with BD appears appropriate to try to remediate this situation. The unique assets of lithium are underappreciated or not well known. Conversely, the side effects profile of lithium are overestimated. Here, we make the case that lithium’s image needs to be revised not only with better and more accurate information but with a wholesale re-naming and rebranding of the drug. We will not only outline the unique qualities and new information about the side effects of the drug but attempt to change some of the terminology conventionally used to refer to lithium so that its use may be appropriately applied earlier and at an increased frequency for patients with BD.

Feline infectious peritonitis (FIP) is a severe and invariably fatal disease affecting both domestic and wild felines with limited effective therapeutic options available. By considering the significant immunomodulatory effects of vitamin E observed in both animal and human models under physiological and pathological conditions, we have provided a full in-silico investigation of vitamin E and related compounds and their effect on the crystal structure of feline infectious peritonitis virus 3C-like protease (FIPV-3CLpro). This work revealed the β-tocotrienol and δ-tocotrienol analogues as inhibitor candidates for this protein, suggesting their potential as possible drug compounds against FIP or their supplementary use with current medicines against this disease.

Cancer is a highly heterogeneous disease and remains a global health challenge affecting millions of human lives worldwide. Despite advancements in conventional treatments like surgery, chemotherapy, and immunotherapy, the rise of multidrug resistance, tumor recurrence, and severe side effects necessitates innovative therapeutic approaches. The complex nature of the tumor microenvironment (TME) further compromises the efficacy of traditional chemotherapy drugs. Recently, stimulus-responsive nanomedicines designed to target TME characteristics (e.g., pH, redox, enzymes) have gained attention for their potential to enhance anticancer efficacy while minimizing adverse effects. Among various nanocarriers, hydrogels are an interesting class of nanocarriers used in cancer therapy due to their high water content, adjustable mechanical characteristics, and ability to respond to external/internal stimuli. These properties make hydrogels an ideal nanocarrier for controlled drug release within the TME. This review comprehensively surveys the latest advancements in stimulus-responsive hydrogels for cancer therapy, exploring various stimuli-responsive mechanisms, including biological (e.g., pH, redox), chemical (e.g., enzymes, glucose), and physical (e.g., temperature, light), as well as dual- or multi-stimuli responsiveness. This review will offer novel perspectives on the development of stimulus-responsive hydrogels for cancer therapy.

Skin inflammation associated with chronic diseases has the direct action of keratinocytes in its immunopathogenesis, leading to a series of immune responses. However, there are still no highly targeted treatments, and the development of more specific therapies is highly desirable. In the present work, nanocapsules containing quinizarin (QZ/NC) were developed, evaluating their act in a model of the keratinocytes inflammatory process in vitro with the action of Photodynamic Therapy, analyzing the permeation in a 3D skin model. Physicochemical, stability, cytotoxicity and permeation analyses of the nanomaterials were carried out. The nanocapsules showed desirable physicochemical characteristics and were stable during the analysis period, without spectroscopic modifications. The cell viability test carried out showed no cytotoxicity at the lowest QZ/NC concentrations. The permeation and cellular uptake studies showed the permeation of QZ/NC in 3D skin models and the intracellular incorporation and internalization of the drug, enhancing its action in the drug delivery technique. Promising results were presented using the model developed to induce the inflammatory process in vitro and applying the synthesized nanomaterial in conjunction with PDT, where a decrease in the levels of cytokines analyzed was observed, representing a possible new therapeutic approach for inflammatory skin diseases.

Cohort studies have identified several genetic determinants that could predict the clinical response to allopurinol. However, they have not been commonly used for genome-wide investigations to identify genetic determinants on allopurinol metabolism and concentrations. We conducted a genome-wide association study of a prior cross-sectional investigation of patients from the Montreal Heart Institute Biobank undergoing allopurinol therapy. Four endpoints were investigated, namely plasma concentrations of oxypurinol, the active metabolite of allopurinol, allopurinol, and allopurinol-riboside, as well as allopurinol daily dosing. A total of 439 participants (mean age 69.4 years; 86.4% male) taking allopurinol (mean daily dose 194.5 mg) and who had quantifiable oxypurinol concentrations were included in the genome-wide analyses. Participants presented multiple comorbidities and received concomitant cardiovascular medications. No association achieved the predefined genome-wide threshold values for any of the endpoints (all p&gt;5 × 10-8). Our results are consistent with prior finding regarding the difficulty in identifying genetic determinants of drug concentrations or pharmacokinetics of allopurinol and its metabolites, and allopurinol daily dosing. Given the size of this genome-wide study, collaborative investigations involving larger and diverse cohorts may be required to further identify pharmacogenomic determinants of allopurinol and measure their clinical relevance to personalize allopurinol therapy.

Paracetamol, also known as acetaminophen, is one of the most widely used over-the-counter analgesics and antipyretics globally. While generally considered safe when used as directed, excessive or prolonged use of paracetamol can lead to adverse effects on various organ systems within the human body. This comprehensive review explores the physiological mechanisms underlying paracetamol toxicity, its effects on different organs, risk factors for overdose, diagnostic methods, and potential management strategies.

mRNA-lipid nanoparticle (LNP) medicinal products can be considered a platform technology because the development process is similar for different diseases and conditions, with similar noncoding mRNA sequences and lipid nanoparticles and essentially unchanged manufacturing and analytical methods utilised often for different products. It is critical not to lose the momentum built using the platform approach during the development, regulatory approval and rollout of vaccines for SARS-CoV-2 and its variants. This Review proposes a set of modifications to existing regulatory requirements for mRNA products, based on a platform perspective for quality, manufacturing, preclinical and clinical data. For the first time, we address development and potential regulatory requirements when the mRNA sequences and LNP composition vary in different products as well. In addition, we propose considerations for self-amplifying mRNA, individualised oncology mRNA products and mRNA therapeutics. Providing a predictable development pathway for academic and commercial groups, so they can know in detail what product characterisation and data are required to develop a dossier for regulatory submission, has many potential benefits. These include reduced development and regulatory costs; faster consumer/patient access and more agile development of products in the face of pandemics; and for rare diseases where alternatives may not exist or to increase survival and the quality of life in cancer patients. Therefore, achieving consensus around platform approaches is both urgent and important. This approach with mRNA can be a template for similar platform frameworks for other therapeutics and vaccines to enable more efficient development and regulatory review.

Antibody-drug conjugates (ADCs), a groundbreaking advancement in cancer therapy, synergistically combine the precision of monoclonal antibodies with the potent destruction capabilities of cytotoxic drugs, signifying a new era in the targeted oncological treatments. This comprehensive paper delves into the evolving field of antibody-drug conjugates (ADCs) and their pivotal role in cancer therapy. We have conducted an in-depth exploration of the structural components of ADCs, including target antigens, monoclonal antibodies, chemical linkers, and cytotoxic payloads, each playing a crucial role in determining the efficacy and safety profile of these novel therapies. A detailed market analysis reveals the leading pharmaceutical companies shaping the ADC landscape, reflecting the growing interest and potential in this therapeutic approach. We further dissect the engineering intricacies of ADCs, focusing on their ability to target specific cancer cell antigens while minimizing off-target effects, thus offering a more focused treatment with reduced systemic side effects compared to traditional chemotherapy. This approach holds promise in a heightened therapeutic index and decreased toxicity. The mechanisms and effector functions of ADCs are explored, highlight- ing their multifaceted strategy in combating cancer. We include a comprehensive look at how ADCs operate from initial blood circulation to the induction of apoptosis in cancer cells. We also review several key ADCs currently in use or under investigation, offering insights into their unique mechanisms of action, pharmacokinetics, and clinical implications. The discussion extends to drug creation modalities, focusing on innovative conjugation techniques that enhance ADC homogeneity and therapeutic efficacy. In conclusion, the paper underscores the transformative potential of ADCs in the realm of cancer treatment, marking a shift towards more precise and targeted therapeutic approaches. By offering a thorough analysis of ADC technology, this paper sheds light on the prospects of these groundbreaking therapies in the ongoing fight against cancer.

Cancer is among the leading causes of death worldwide. Therefore, timely diagnosis and appropriate treatment are very important. There are many disadvantages that come with traditional cancer treatments, such as chemotherapy and radiotherapy. In these treatments, the specific drug concentration affects not only the tumor site but also healthy tissues or organs. One of the foremost promising uses of nanotechnology is in the field of medical technology and specific site targeting can be achieved due to manipulation of materials at a nanometric scale. Nanotechnology offers specific benefits in terms of cancer therapy by enhancing it and reducing its adverse effects by guiding drugs to selectively target cancer cells. In addition, the use of minute amounts of medicine can lead to cost savings. Furthermore, nanoparticles can also be used as imaging agents to improve cancer diagnostics, therapeutics, and treatment management. Thus, this review has focused on the different types of nanoparticles used in cancer therapy, their action mechanisms, and their benefits and applications in diagnosis, imaging, and treatment. This review sums up the parameters that need to be considered when designing systems for cancer therapy while considering the desired characteristics of the nanoparticles from the biological point of view.

(1) Background: Hemispherotomy is the generally accepted treatment for hemispheric drug resistant epilepsy (DRE). Lateral or vertical approaches are performed according to the surgeon's preference. Multiples technical variations have been proposed since Delalande first described his vertical technique. We propose a sub-insular variation of the vertical parasagittal hemispherotomy (VPH) and describe our case series of patients operated on with this procedure. (2) Methods: a continuous series of patients operated on by the senior author (CR) with the modified sub-insular VPH was retrospectively analyzed. We report the demographic pre-operative characteristics, epilepsy and functional outcome as well as the surgical complications.(3) Results: Twenty-five patients were operated on between August 2008 and August 2023, twenty-three of them have at least a 3-month follow-up. On this last group 86,3% of patients were seizure-free. Only two patients developed post-operative hydrocephalus (8.7%), all patients with autonomous preoperative walk and 86,3% of the total series were able to walk without assistance (86.3%) and perform adapted social activities at last follow-up.(4) Conclusion: The modified vertical parasagittal sub-insular hemispherotomy is a successful surgical technique for hemispheric DRE with seizure freedom rates similar to the biggest series reported in the literature. Compared to other series, patients operated with our modified technique had a lower rate of postoperative hydrocephalus and excellent long-term motor and cognitive outcome.

Skin cancer is a disease that reflects most malignant neoplasms worldwide, whose rate of involvement has increased significantly in recent decades. Treatments that offer efficient results with attenuation of adverse reactions and greater patient compliance have been the subject of many systematic investigations. This review aims to qualitatively present published works that showed new strategies to increase the penetration power of natural substances through the skin in the topical treatment against skin cancer. In this sense, nanoengineering mechanisms, the iontophoresis technique, and photodynamic therapy using natural products (NP) contribute to new knowledge about substance carrier strategies in topical treatments against skin cancer.

The prevalence of antiviral drugs (AVTs) has seen a substantial increase in response to the COVID-19 pandemic, leading to heightened concentrations of these pharmaceuticals in wastewater systems. The hydrophilic nature of AVTs has been identified as a significant factor contributing to the low degradation efficiency observed in wastewater treatment plants. This characteristic often necessitates the implementation of additional treatment steps to achieve complete degradation of AVTs. Semiconductor-based photocatalysis has garnered considerable attention due to its promising potential in achieving efficient degradation rates and subsequent mineralization of pollutants, leveraging the inexhaustible energy of sunlight. However, in recent years, there have been few comprehensive reports that have thoroughly summarized and analyzed the application of photocatalysis for the removal of AVTs. This review commences by summarizing the types and occurrence of AVTs. Furthermore, it places a significant emphasis on delivering a comprehensive summary and analysis of the characteristics pertaining to the photocatalytic elimination of AVTs. Ultimately, the review sheds light on the identified research gaps and key concerns, offering invaluable insights to steer future investigations in this field.

Background: The clinical outcomes of antiretroviral drugs may be modified by drug interactions; thus, it is important to update the drug interactions in people living with HIV. Aim: To update clinically relevant drug interactions in people living with HIV on antiretroviral therapy. Methods: A systematic review in Medline/PubMed database from July 2017 to December 2022, using the Mesh terms: Anti-retroviral agents and drug interactions or herb-drug interactions or food-drug interactions. Publications with drug interactions in humans, in English or Spanish, and with full text were retrieved. The clinical relevance of drug interaction was grouped into 5 levels according to gravity and probability of occurrence. Results: 361 articles were identified and 148 were included, which allowed the identification of 894 drug interaction pairs. Among these 894 drug pairs, 355 have not been identified previously; and 89 (25.1%) and 72 (20.2%) were of levels 1 and 2, respectively. In addition, for 197 (55.5%) pairs the mechanism was pharmacokinetic. The non-nucleoside reverse transcriptase inhibitors (NNRTIs) and the protease inhibitors (PIs) with 91 (25.6%) and 76 (21.4%) pairs, respectively were more frequent. Conclusions: In people living with HIV on antiretroviral therapy, we identify 355 new drug interaction pairs, of them 161 (45.3%) are assessed as levels 1 and 2 and thus, clinically relevant; a figure that is lower compared to 2014-2107 update. The pharmacokinetic mechanism is the most frequently identified. The non-nucleoside reverse transcriptase inhibitors (NNRTIs) and the protease inhibitors (PIs) are the antiretroviral groups with the highest number of clinically relevant drug interactions.

Drug-resistant tuberculosis (DR-TB) is still a major public health concern in South Africa. Mutations in M. tuberculosis can cause varying levels of phenotypic resistance to anti-TB medications. There have been no prior studies on gene mutations and the genotyping of DR-TB in the rural Eastern Cape Province; hence we aimed to identify DR-TB mutations, genetic diversity and allocated lineages among patients in this area. Using Xpert® MTB/RIF, we assessed the rifampin-resistance of sputum samples collected from 1157 patients suspected of having tuberculosis. GenoType MTBDR plus VER 2.0 was used for the detection of mutations causing resistance to anti-TB medications. The next step was to spotlight type 441 isolates. The most prevalent rifampin resistance-conferring mutations were in rpoB codon S531L, in INH-resistant strains, katG gene at codon S315TB and the inhA gene at codon C-15TB had highest mutations; 54.5% and 24.7%, respectively. In addition, 24.6% of strains showed mutations in both the rpoB and inhA genes, while 69.9% of strains showed mutations in both the katG and rpoB genes. Heteroresistance was seen in 17.9% of all cases in the study. According to spoligotyping analysis, Beijing families predominated. Investigating the evolutionary lineages of M. tuberculosis isolates can be done using the information provided by the study's diversity of mutations. In locations where these mutations have been discovered, decision-making regarding standardization of treatment regimens or individualized treatment may be aided by the detection frequency of rpoB, katG, and inhA mutations in various study areas.

Antibody-drug conjugates (ADCs) have provided new therapeutic options and significant promise for patients with cancers, particularly where existing treatments are limited. Substantial effort in ADC development is underway globally, with 13 ADCs currently approved and many more in development [1]. Therapeutic benefits of ADCs leverage the ability to selectively target cancer cells through antibody binding, resultant relative sparing of non-malignant tissues, and the targeted delivery of a cytotoxic payload. Consequently, this drug class has demonstrated activity in multiple malignancies refractory to standard therapeutic options [1-4]. Despite this, limitations exist, including narrow therapeutic windows, unique toxicity profiles, development of therapeutic resistance, and appropriate biomarker selection [5-7]. This review will describe the development of ADCs, their mechanisms of action, pivotal trials, and approved indications and identify common themes. Current challenges and opportunities will be discussed for this drug class in cancer therapeutics at a time when significant developments in antibody therapies, immunotherapy and targeted agents are occurring.

Drug induced liver injury (DILI) is the most common cause of acute liver failure and 5-10% of patients hospitalized for jaundice are diagnosed with DILI. For a diagnosis of DILI to be made, there should be exclusion of other etiologies of liver injury and the use of a precipitator drug, latency of symptoms, and resolution of liver injury once the offending drug is identified and discontinued. In our case report, we present a patient with idiosyncratic hepatocellular pattern DILI after two doses of ocrelizumab for treatment of multiple sclerosis. Ocrelizumab was given 16 and 27 days prior to the onset of icterus, jaundice, and fatigue, in a patient without the evidence of prior exposure to hepatitis B virus. At presentation labs revealed severe acute hepatocellular liver injury with R factor of 30.42, marked hyperbilirubinemia, and transient hypoalbuminemia. No evidence of latent or active hepatitis B infection was detected. Drug dechallenge led to return of liver chemistries to near-normal levels 31 days after the onset of her symptoms. This case indicates DILI diagnosis associated with the use of ocrelizumab, and warrants careful monitoring of liver functions in patients even in the absence of hepatitis B.

Autoimmune disorders and some types of blood cancer originate when B lymphocytes malfunction. In particular, when B cells produce antibodies recognizing the body’s proteins, it leads to various autoimmune disorders. And when B cells of various developmental stages transform into cancer cells, it results in blood cancers, including multiple myeloma, lymphoma, and leukemia. Thus, new methods of targeting B cells are required for various patient groups. Here, we used protein kinase inhibitors alectinib, brigatinib, ceritinib, crizotinib, entrectinib, and lorlatinib previously approved as drugs treating anaplastic lymphoma kinase (ALK)-positive lung cancer cells. We hypothesized that the same inhibitors will efficiently target leukocyte tyrosine kinase (LTK)-positive, actively protein-secreting mature B lymphocytes, including plasma cells. We isolated CD19-positive human B cells from the blood of healthy donors and used two alternative methods to stimulate cell maturation toward plasma cells. Using cell proliferation and flow cytometry assays, we found that ceritinib and entrectinib eliminate plasma cells from B cell populations. Alectinib, brigatinib, and crizotinib also inhibited B cell proliferation, while lorlatinib had no or limited effect on B cells. More generally, we concluded that several drugs previously developed to treat ALK-positive malignant cells can be also used to treat LTK-positive B cells.

Increasing environmental distress is associated with a growing asthma incidence and, with no treatments available, montelukast (MTK) – an antagonist of the cysteinyl leukotrienes receptor 1 – is widely used in the management of symptoms among adults and children. Recently, new molecular targets have been identified and MTK has been proposed for repurposing in other therapeutic applications, with several ongoing clinical trials. The proposed applications include neuroinflammation control, which could be explored in some neurodegenerative disorders, such as Alzheimer’s and Parkinson’s diseases (AD and PD). However, this drug has been associated with an increasing number of reported neuropsychiatric adverse drug reactions. Besides, and despite being on the market since 1998, MTK metabolism is still poorly understood and the mechanisms underlying neuropsychiatric ADRs remain unknown. We review the role of MTK as modulator of leukotriene pathways and systematize the knowledge about MTK metabolism. Known toxic effects of MTK are discussed, and repurposing applications are presented comprehensively, with a focus on AD and PD.

Therapeutic Drug Monitoring (TDM) is potentially a useful tool that can be employed to increase the efficacy and decrease the toxicity of antifungal drugs. The aim of this narrative review is to provide an overview of the current use of TDM in clinical practice, and to present the evidence available regarding its use in proactive clinical settings for preventing and managing treatment failure. This review also presents the existing evidence regarding the association of various clinical outcomes with specific thresholds of drug concentrations in everyday practice. Articles concerning the use of TDM of triazoles in the treatment of fungal infections were retrieved through an electronic search using PubMed. In clinical practice, TDM has an increasingly important role in the management of antifungal drugs as a consequence of the improvement in the knowledge of the pharmacokinetics and pharmacodynamics of these drugs. The currently available evidence shows a direct exposure-response relationship for triazoles, though the PK/PD profile is unpredictable. Current guidelines and treatment consensus statements recommend the proactive TDM of voriconazole, posaconazole, and itraconazole to optimize dosage regimens and improve outcomes for adult and pediatric patients.

The treatment of peptides has played an important role in clinical practice since the discovery of insulin therapy in the 1920s. Over 60 peptide drugs are approved in the United States (US and other regional mar-kets, and peptides continue to undergo drug discovery steadily. Peptide research and development has lev-eraged a wider range of structures known from other plant sources, via pharmacology and medicinal molecular biology, beyond its conventional focus on individual endogenous peptides. We build a comprehensive database of peptides that have met scientific studies with more than 150 constantly evolving peptides. Here we provide a simple overview of the peptide-based drug therapy environment, comprising evolutionary points of view, structural properties, operational thresholds, and explanation of the therapeutic area.

BACKGROUND: From March to April 2020, Spain was the center of the SARS-CoV-2 pandemic, particularly Madrid with approximately 30% of the cases in Spain. The aim of this study is to report the suspected serious adverse drug reactions (SADRs) in COVID-19 patients versus non-COVID-19 patients detected by the prospective pharmacovigilance program based on automatic laboratory signals (ALSs) in the hospital (PPLSH) during that period. We also compared the results with the suspected SADRs detected during the same period for 2019. METHODS: All ALSs that reflected potential SADRs (including neutropenia, pancytopenia, thrombocytopenia, anemia, eosinophilia, leukocytes in cerebrospinal fluid, hepatitis, pancreatitis, acute kidney injury, rhabdomyolysis and hyponatremia were prospectively monitored in hospitalized patients during the study periods. We analyzed the incidence and the distribution of causative drugs for the COVID-19 patients. RESULTS: The incidence rate of SADRs detected in the COVID-19 patients was 760.63 (95% CI 707.89–816.01) per 10,000 patients, 4.75-fold higher than the SADR rate for non-COVID-19 patients (160.15 per 10,000 patients,95% CI 137.09–186.80), and 5.84-fold higher than the SADR rate detected for the same period in 2019 (130.19 per 10,000 patients, 95% CI 109.53–154.36). The most frequently related drugs were tocilizumab (59.84%), dexketoprofen (13.93%), azithromycin (8.43%), lopinavir-ritonavir (7.35%), dexamethasone (7.62%), and chloroquine/hydroxychloroquine (6.91%). CONCLUSIONS: The incidence rate of SADRs detected by the PPSLH in patients with COVID-19 was 4.75-fold higher than that of the non-COVID-19 patients. Caution is recommended when using medications for COVID-19 patients, especially drugs that are hepatotoxic, myotoxic, and those that induce thromboembolic events.

Most recently, an outbreak of severe pneumonia caused by the infection of 2019-nCoV, a novel coronavirus first identified in Wuhan, China, imposes serious threats to public health. Many important aspects about 2019-nCoV remain largely unknown, among which, the limitation of antiviral therapies represents one of the most critical problems. More recently, it was confirmed that human ACE2 is the receptor for the entry of 2019-nCoV into lower respiratory tract epithelial cells. Give this observation, it is thus expected that the virus could be inhibited if we decrease the expression of ACE2. Here by screening two databases, Connectivity Map (CMap) and our JeaMoon Map (JMap), we identified a number of candidate agents that decrease ACE2 expression. CMap analysis identified 5 compounds, among which, Azathioprine is a possible therapeutic strategy for anti-2019-nCoV. Moreover, JMap analysis revealed a number of comounds, biologics, and traditional Chinese medicine, among which, Andrographis, Urtica, Sambucus, Astragalus, valproic acid, butyrate, and epoxomicin represent the most significant and possible strategies for anti-2019-nCoV therapies. This study provides a number of clues and possible therapeutic strategies for 2019-nCoV prevention and treatment.

Many approaches have been developed over time to counter the bioavailability limitations of poorly soluble drugs. With advances in nanotechnology in recent decades, science and industry have been approaching this issue through the formulation of drugs as nanocrystals, which consist of pure drugs and a minimum of surface active agents required for stabilization. They are carrier-free submicron colloidal drug delivery systems with a mean particle size in the nanometer range, typically between 10 and 800 nm. By reducing particle size to nanoscale, the particle surface area available for the molecule dissolution in the direction of dissolution medium is increased, and thus bioavailability is enhanced. This approach has proven successful, as demonstrated by the number of such drug products on the market. R&D and industry have offered many technological solutions to reduce the particle size to nanoscale, and also devised solutions for the handling of particle of nanodimensions, such as methods to accurately measure nanoparticle size and techniques to prevent physicochemical and stability related problems, such as aggregation. The present work provides an overview of the more recent achievements in improving the bioavailability of poorly soluble drugs according to their administration route, and describes the methods developed to overcome physicochemical and stability related problems.

Currently, drug screening is primarily based on human cell culture for initial high-throughput screening, and subsequently, rodent model to confirm the biological effects. However, the mammalian system is known for time-consuming and highly-cost to be difficult to perform high-throughput drug screening, which exists a critical gap between in vitro cell-based models and the in vivo mammalian models. Therefore, the zebrafish could bridge this gap in preclinical toxicity screening along the drug development pipeline because of its efficiency. We aimed to develop an in vivo zebrafish platform for rapid drug screening. Zebrafish, due to its high genomic conservation with mammals and rapid development and differentiation, it has many advantages, such as short life span, large number of offspring and low cost, easy manipulation for generating transgenic species, to serve as animal model for disease-based research. In 96-well microplates, zebrafish embryos were incubated with small molecular compounds that affected bone mineralization. The level of osteogenic mineralization was evaluated by fluorescent dye staining and quantified by image analysis software. Quantitative real time-PCR (qRT-PCR) was performed to evaluate the biological pathways involved in bone metabolism at the molecular level. The system was validated by demonstrating that response to alendronate and Dorsomorphin in zebrafish. In our study, we screened for 24 compounds within the CYCU-1120~1152 chemical library and identified 3 compounds, pentamidine (CYCU-1140), BML-267 (CYCU-1147), and alendronate (CYCU-1152), increased embryonic mineralization; while 6 compounds, RWJ-60475 (CYCU-1126), levamisole HCL (CYCU-1128), tetramisole HCL (CYCU-1129), fenvalerate (CYCU-1132), NSC-663284 (CYCU-1138), and BML-267ester (CYCU-1148), were inhibitory to bone mineralization. We also found that alendronate enhanced the level of bone mineralization by inhibiting osteoclast-related genes. To sum up, our research showed that zebrafish may have potential to be a drug-screening and mechanism-analysis platform for bone mineralization.

In vitro studies show that diclofenac inhibits enzymatic steroid glucuronidation. This study was designed to investigate the influence of diclofenac on the excretion of stanozolol and 3'-hydroxystanozolol via analyses in hair, blood and urine in vivo in a rat study. Brown Norway rats were administered with stanozolol (weeks 1-3) and diclofenac (weeks 1-6). Weekly assessment of steroid levels in hair was complemented with spot urine and serum tests. Levels of both stanozolol and 3'-hydroxystanozolol steadily increased in hair during stanozolol treatment and decreased post-treatment, but remained readily detectable for 6 weeks. In contrast, compared to control rats, diclofenac significantly reduced urinary excretion of 3’-hydroxystanozolol which was undetectable in most samples. This is the first report of diclofenac altering steroid metabolism in vivo, detrimentally affecting detection in urine, but not in hair which holds considerable advantages over urinalysis for anti-doping tests.

Europium (Eu)-doped fluorapatite (FA) nanorods has a similar biocompatibility with hydroxyapatite (HA) in terms, attracted much attention as cell imaging biomaterials due to their luminescent property. Here, we will discuss the new feature of europium doped fluorapatite (Eu-FA) nanorods as anticancer drug carrier. Eu-FA nanorods was prepared using a hydrothermal method. The morphology, crystal structure, fluorescence and composition are investigated. The specific crystal structure, enabling an effective loading of drug molecules. Doxorubicin (DOX), used as an anticancer model drug, was shown to be effectively loaded onto the surface of the nanorods. The DOX release was fairly pH-dependent, occurring more rapidly at pH 5.5 than pH 7.4 was observed. The intracellular penetration of the DOX-loaded Eu-FA nanorods (Eu-FA/DOX) can be imaged in situ due to the self-fluorescence property. Treatment of melanoma A375 cells with Eu-FA/DOX elicited a more effective apoptosis rate than direct DOX treatment. Overall, Eu-FA show great promise for tracking and treating tumor, may potentially useful as a multifunctional carrier system to effectively load and sustainably deliver drugs.

Background: Previously, our laboratory has provided evidence that pre-administration of the antioxidant, lipoic acid covalently bonded to various naturally occurring antioxidants, enhanced neuroprotective capacity compared to the administration of lipoic acid on its own. The naturally occurring compound scopoletin, a coumarin derivative, has been shown in various in vitro studies to have both antioxidant and anti-inflammatory mechanism of actions. To date, the effect of scopoletin on neuronal cell death in an in vivo model of ischemia or ischemia-reperfusion has not been investigated. Therefore, the present investigation was designed to determine if scopoletin on its own, or a co-drug consisting of lipoic acid and scopoletin covalent bond, named UPEI-400, would be capable of demonstrating a similar neuroprotective efficacy. Methods: Using a rodent model of stroke in male rats (anesthetized with Inactin®; 100 mg/kg, iv), the middle cerebral artery was permanently occluded for 6 hours (pMCAO), or in separate animals, occluded for 30 min followed by 5.5 hrs of reperfusion (ischemia/reperfusion; I/R). Results: Pre-administration of either scopoletin or UPEI-400 significantly decreased infarct volume in the I/R model (p<0.05), but not in the pMCAO model of stroke. However, UPEI-400 was ~1000 times more potent as compared to scopoletin on its own. The optimal dose of UPEI-400 was then injected during the occlusion and at several time points during reperfusion and significant neuroprotection was observed for up to 150 mins following the start of reperfusion (p<0.05). Conclusion: The data suggest that synthetic combination of scopoletin with lipoic acid (UPEI-400) is a more effective neuroprotectant that either compound on their own. Also, since UPEI-400 was only effective in a model of I/R, it is possible that it may act to enhance neuronal antioxidant capacity and/or upregulate anti-inflammatory pathways to prevent the neuronal cell death.

Since the domestication of plants, pathogenic fungi have consistently threatened crop production, evolving genetically to develop increased virulence under various selection pressures. Understanding their evolutionary trends is crucial for predicting and designing control measures against future disease outbreaks. This paper reviews the evolution of fungal pathogens from natural habitats to agricultural settings, focusing on eight significant phytopathogens: Pyricularia oryzae, Botrytis cinerea, Puccinia spp., Fusarium graminearum, F. oxysporum, Blumeria graminis, Zymoseptoria tritici, and Colletotrichum spp. Also, we explore the mechanism used to understand evolutionary trends in these fungi. The studied pathogens have evolved in agroecosystems through either (1) introduction from elsewhere or (2) local origins involving co-evolution with host plants, host shifts, or genetic variations within existing strains. Genetic variation, generated via sexual recombination and various asexual mechanisms, often drives pathogen evolution. While sexual recombination is rare and mainly occurs at the center of origin of the pathogen, asexual mechanisms such as mutations, parasexual recombination, horizontal gene or chromosome transfer, and chromosomal structural variations are predominant. Farming practices like mono-cropping resistant cultivars and prolonged use of fungicides with the same mode of action can drive the emergence of new pathotypes. Furthermore, host range does not necessarily impact pathogen adaptation and evolution. Although halting pathogen evolution is impractical, its pace can be slowed by managing selective pressures, optimizing farming practices, and enforcing quarantine regulations. The study of pathogen evolution has been transformed by advancements in molecular biology, genomics, and bioinformatics, utilizing methods like next-generation sequencing, comparative genomics, transcriptomics and population genomics. However, continuous research remains essential to monitor how pathogens evolve over time and to develop proactive strategies that mitigate their impact on agriculture.

The genus Aeromonas is widely distributed in aquatic environments. It is frequent as a fish pathogen, but has also been described associated to human infections. Most human cases are caused by A. caviae, A. veronii biovar sobria, and A. hydrophila, though A. dhakensis is becoming increasingly important. Transmission happens primarily by ingestion or contact with aquatic collections, or by consumption of contaminated food, especially of aquatic origin. Increasing resistance has been described in Aeromonas to penicillins, including their combinations with classical b-lactamase inhibitors, cephalosporins and carbapenems. Among the b-lactam antibiotics, only the 4th generation cephalosporins remain almost uniformly active. In addition, the simultaneous presence of resistance genes to 3rd generation cephalosporins and carbapenems in the same isolates is increasing. Recently, the presence of mobile genes linked to colistin resistance has also been described, in some cases with resistance percentages higher than 30%. Most likely, this evolution of colistin resistance is linked to its use in aquaculture, and, together with the evolution of b-lactam resistance, may be turning this genus into a reservoir of resistance genes that may affect other species much more frequently linked to human infections, such as Enterobacterales.

The aim of this study was to evaluate patients' knowledge and perception of the use of systemic antibiotics in the treatment of endodontic infections and to determine the possible contribution of patients to the development of bacterial resistance. Five hundred and fifty patients were asked to respond to a survey on the perception of systemic antibiotic use in the treatment of endodontic infections and antibiotic resistance during January 2022 and March 2023. Data were analyzed using descriptive statistics and Pearson's Chi-square test. 514 patients were included in the study, 65.9% of whom were women. While 34.6% of the population studied thought that it was always necessary to take antibiotics prior to endodontics, 49.4% considered that they were necessary after endodontics, regardless of the clinical symptoms (p&gt;0.05). The prevalence of self-medication was 17.3% and women self-medicate more than men, with significant differences (p&lt;0.05), although they have greater knowledge of antibiotic resistance than men (p&gt;0.05). Forty-four percent of the population expect to take antibiotics when faced with dental pain, mainly women (p&lt;0.05). The general population is contributing to the serious problem of bacterial resistance. It is necessary to promote educational strategies focused on the correct use of antibiotics in the community.

A lignin modified salt resistance branched high-performance water reducer was prepared via free radical polymerization. The water reducing agent was identified through Fourier transform infrared analysis, thermal gravimetric analysis, and scanning electron microscopy. The experiment conducted on cement paste demonstrates that the water-reducing efficiency can reach a maximum of 44%. Additionally, the significant spatial steric hindrance of the application enhances the dispersal capability of the water-reducing agent, resulting in effective water reduction and reduced viscosity. In addition, its compressive strength is the highest after 3-day curing and 3, 7, 28-day standard curing, and it has the best overall performance both in water and saline water prepared systems.The application in oil cement slurry shows that it exhibits good dispersibility in fresh water, saline water, and substitute ocean water. In the Halfaya and Missan Oilfields of Iraq, BHPWR was used in slurry with a density of 2.28g cm-3 for casing the 244.5 mm salt paste layer of five wells. Cementing results exceeded expectations with over 85% excellent and 100% qualified.

Antibiotic resistance is a persistent and growing concern. Our objective was to analyze antibiotic prescribing in the United States (US) in the Medical Expenditure Panel System (MEPS) and to Medicaid patients. We obtained total MEPS prescriptions for eight antibiotics from 2013 to 2020. We extracted prescribing rates per 1,000 Medicaid enrollees for two years, 2018 and 2019, for four broad spectrum (azithromycin, ciprofloxacin, levofloxacin, and moxifloxacin) and four narrow spectrum (amoxicillin, cephalexin, doxycycline, and trimethoprim/sulfamethoxazole) antibiotics. Antibiotics in MEPS decreased from 2013 to 2020 by -38.7% with a larger decline for broad (-53.7%) than narrow (-23.5%) spectrum. Antibiotic prescriptions in Medicaid decreased by -6.7%. Amoxicillin was the predominant antibiotic followed by azithromycin, cephalexin, trimethoprim/sulfamethoxazole, doxycycline, ciprofloxacin, levofloxacin, and moxifloxacin. Substantial geographic variation in antibiotic prescribing existed with 2.8-fold between the highest (Kentucky = 855/1,000) and lowest (Oregon = 299) states. The South prescribed 52.2% more antibiotics (580/1,000) than the West (381/1,000). There were significant correlations across states in antibiotic prescribing. This study identified sizable disparities by geography in prescribing rates of eight antibiotics with over three-fold state level differences. Areas with high antibiotic prescribing rates, particularly for outpatients, may benefit from stewardship programs to reduce potentially unnecessary prescribing.

This article describes the challenges, pharmacological strategies, and recommendations for managing multidrug-resistant breast cancer in Sub-Saharan Africa (SSA). By examining the current breast cancer treatment landscape, region-specific challenges, and promising pharmacological interventions, the objective is to bring to light the insufficient research on breast cancer and its multidrug resistance in this part of the world and guide healthcare professionals, policymakers, and researchers in developing evidence-based strategies for improved breast cancer care in SSA. Breast cancer is the leading cause of cancer morbidity in SSA, necessitating continuous advancements in its management. This overview explores the evolution of breast cancer treatment, including surgery, targeted therapy, immunotherapy, radiotherapy, and chemotherapy. Despite these advancements, multidrug resistance poses a significant challenge, impacting treatment efficacy and patient outcomes.The article provides insights into various breast cancer treatment modalities, emphasizing surgery, targeted therapy, immunotherapy, radiotherapy, and chemotherapy. Each approach is discussed in detail, highlighting its significance in managing breast cancer. The effectiveness of these treatments is contingent on timely diagnosis and intervention. Multidrug resistance is examined as a critical obstacle in breast cancer treatment, elucidating its impact on treatment failure and patient outcomes. Mechanisms such as the efflux system, enhanced DNA repair, apoptosis inhibition, alterations in drug targets, and the tumor microenvironment contribute to multidrug resistance, emphasizing the need for a multifaceted understanding.The unique challenges faced in SSA regarding multidrug-resistant breast cancer are delineated. These include the lack of comprehensive data, late presentation and diagnosis, poor genomic studies, limited access to specialized care, financial constraints, inadequate infrastructure, and psychosocial support issues. Addressing these challenges is crucial for devising effective strategies. In response to multidrug resistance, the article discusses contemporary treatment strategies such as P-glycoprotein inhibitors, combined chemotherapy, and immunotherapy. Notable advancements, including the use of Tariquidar and synergistic effects of combined chemotherapy, are highlighted, presenting promising avenues for overcoming resistance.The article proposes recommendations to enhance breast cancer management in SSA, encompassing strengthening primary healthcare services, creating specialized oncology facilities and long-term monitoring and data collection. Breast cancer management in SSA is multifaceted, marked by challenges and evolving solutions. Multidrug resistance remains a significant hurdle, demanding a holistic approach. Promising advancements in pharmacological interventions offer hope, while comprehensive recommendations serve as a roadmap for progress. By implementing these strategies, SSA can substantially improve multidrug-resistant breast cancer care and overall patient well-being.

During the bioassay, on leaf sections of the A. roylei species, a significantly higher number of T. tabaci females was recorded compared to the cv. Tęcza of the A. cepa species and the cv. Kroll of the A. fistulosum species, in each observation period. Significantly more thrips settled on cv. Kroll compared to Alibaba and Bila. Regarding the results obtained on A. cepa, significantly fewer females were found on cv. Bila compared to cv. Tęcza. Opposite results were observed in a combination of cvs. Tęcza - Alibaba, where significantly more insects settled on leaves of cv. Alibaba. Statistically significant differences of cultivars/species were found in the number of hatched larvae on the leaves of the tested cultivars/species of onion. The significantly lowest number of larvae hatched from eggs laid on A. roylei compared to A. fistulosum and cultivars of A. cepa, except for Bila.

Non-judicious antimicrobial use (AMU) is a major driver of antimicrobial resistance (AMR). In human hospitals, cumulative antibiograms are often used by clinicians to evaluate local susceptibility rates and to select the most appropriate empiric therapy with the aim of minimizing inappropriate AMU. However, use of cumulative antibiograms to guide empiric antimicrobial therapy in veterinary hospitals in the United States is limited, and there are no specific guidelines or standardized methods available for the construction of antibiograms in veterinary clinical settings. The objective of this methods article is to describe the approaches that were used to construct antibiograms from clinical samples collected from dogs seen at a veterinary teaching hospital. Laboratory data for 563 dogs for the period January 1, 2015 to December 31, 2015 was utilized. We used the Clinical and Laboratory Standards Institute (CLSI) guidelines for use in the construction of the antibiograms in human healthcare settings as the basis for the veterinary antibiograms. One general antibiogram, and antibiograms, stratified by hospital section, anatomic region of sample collection/ by sample type, were created and the challenges encountered in preparing these antibiograms are highlighted. The approaches described could be useful in guiding veterinary antibiogram development for empiric therapy.

The presence of Staphylococcus aureus in six dry-cured meat-processing facilities was investigated. S. aureus was detected in 3.8% of surfaces from five facilities. Prevalence was clearly higher during processing (4.8%) than after cleaning and disinfection (1.4%). Thirty eight isolates were typified by PFGE and MLST. Eleven sequence types (STs) were defined by MLST. ST30 (32%) and ST12 (24%), were the most abundant. Enterotoxin genes were detected in 53% of isolates. The enterotoxin A gene (sea) was present in all ST30 isolates, seb in one ST1 isolate and sec in two ST45 isolates. Sixteen isolates harbored the enterotoxin gene cluster (egc) with four variations in the sequence. The toxic shock syndrome toxin gene (tst) was detected in 82% of isolates. Regarding the antimicrobial resistance, twelve strains were susceptible to all the antibiotics tested (31.6%). However, 15.8% were resistant to three or more antimicrobials, and therefore multidrug-resistant. Our results showed that, in general, efficient cleaning and disinfection procedures were applied. Nonetheless, the presence of S. aureus with virulence determinants and resistance to antimicrobials, and particularly multidrug resistant MRSA ST398 strains might represent a potential health hazard for consumers, even though the pathogen was not isolated from final products.

Abstract: Vulvovaginal candidiasis (VVC) is a mucous membrane infection, with an increased rate of antifungal resistance of Candida species. The in vitro efficacy of farnesol alone or in combination with traditional antifungals, against resistant Candida strains recovered from women with VVC was assessed. In this study, 80 Candida isolats were identified by multi-plex PCR. Antifungal sus-ceptibility of amphotericin B (AMB), fluconazole (FLU), itraconazole (ITZ), voriconazole (VOR), clotrimazole (CTZ) and farnesol was tested by M27-A3/S4 broth micro dilution method. The combinations of farnesol with each antifungal were calculated based on the fractional inhibitor concentration index (FICI). C. glabrata was the predominant species (48.75%) isolated from vaginal discharges, followed by C. albicans (43.75%), C. parapsilosis (3.75%), mixed infection of C. albicans and C. glabrata (2.5%), C. albicans and C. parapsilosis (1%). C. albicans and C. glabrata isolates had lower susceptibility to FLU (31.4% and 23.0%, respectively) and CTZ (37.1% and 33.3%, respectively). Importantly, there was ‟synergismˮ between farnesol-FLU and farnesol-ITZ against C. albicans and C. parapsilosis (FICI= 0.5 and 0.35, respectively), reverting the original azole resistant profile. These findings indicate that farnesol is able to revert to the resistance profile of azole by enhancing the activity of FLU and ITZ in resistant isolates, which is a promising result.

Antibiotic resistance, particularly beta-lactam resistance, is a major problem worldwide. Imipenemase or IMP-type metallo-beta-lactamase (MBL) has become a more prominent enzyme, especially in Asia, since it was discovered in the 1990s in Japan. There are currently more than 91 variants of IMP-type enzymes. The most commonly identified variant of IMP-type enzymes is IMP-1 variant. IMP-type MBLs have been identified in more than 10 species in Enterobacterales. Pseudomonas aeruginosa is the most frequent carrier of IMP-type enzymes worldwide. In Asia, IMP-type MBLs have been distributed in many countries in the region. This work investigated a variety of currently available IMP-type MBLs in both global level and regional level. Out of 88 variants of IMP-type MBLs reported worldwide, only 32 variants were found to have susceptibility profiles. Most of the IMP-type MBLs were resistant to Carbapenems, especially Imipenem and Meropenem, followed by the 3rd generation cephalosporins, and interestingly, monobactams. Our results comprehensively indicated the distribution of IMP-type MBLs in Asia and raised the awareness of the situation of antimicrobial resistance in the region.

Bacterial resistance to antibiotics is a growing global concern, threatening human and environ-mental health, particularly among urban populations. Wastewater treatment plants (WWTPs) are thought to be “hotspots” for antibiotic resistance dissemination. The conditions of WWTPs, in conjunction with the persistence of commonly used antibiotics, may favor the selection and trans-fer of resistance genes among bacterial populations. WWTPs provide an important ecological niche to examine the spread of antibiotic resistance. We used heterotrophic plate count methods to identify phenotypically resistant cultivable portions of these bacterial communities and charac-terized the composition of the culturable subset of these populations. Resistant taxa were more abundant in raw sewage and wastewater before the biological aeration treatment stage. While some antibiotic resistant bacteria (ARB) were detectable downstream of treated wastewater re-lease, these organisms are not enriched relative to effluent-free upstream water, indicating effi-cient removal during treatment. Combined culture-dependent and culture-independent analyses revealed a stark difference in community composition between culturable fractions and the envi-ronmental source material, irrespective of culturing conditions. Higher proportions of the envi-ronmental populations were recovered than predicted by the widely accepted 1% culturability paradigm. These results represent baseline abundance and compositional data for ARB commu-nities for reference in future studies addressing the dissemination of antibiotic resistance associ-ated with urban wastewater treatment ecosystems.

Phytopathogenic oomycetes are known to infect a host plant successfully due to their ability to secrete a set of protein effectors. Of interest to many researchers are effectors with the N-terminal RxLR motif (Arginine-any amino acid-Leucine-Arginine). Owing to the genome sequencing, we can now comprehend the high level of diversity among oomycete effectors, and similarly, their conservation within and among species core RxLR effectors (CREs). Currently, there are a couple of putative CREs that have been identified in oomycetes. The functional characterization of these CREs proposes their virulence role with the potential of targeting central cellular processes that are conserved across diverse plant species. This could be harnessed in engineering plants for broad-spectrum and durable resistance.

When we were working on improving the resistance to deep abrasion of porcelain stoneware tiles, several tiles which had a very high resistance to abrasion were found in the market. The abraded volume of these tiles, measured via ISO 10545-6 method, was conspicuously less than 75 mm³. These values were well below the standard limit (<175 mm³) and reported values in the literature (>110 mm³). We determined the chemical, physical and microstructural characteristics of these tiles and other commercially available ones to find the relationship between the abrasion resistance and the technical specifications. We also characterized the samples by Vickers microhardness (VH), X-ray diffraction (XRD), mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM). It was observed that the high resistance to abrasion could be due to the presence of an adequate glassy phase capable of wetting all the hard crystalline phases in the matrix such as quartz and mullite. Therefore, the resistance to deep abrasion could be improved by increasing the amount of “vitreous” matrix, without altering the content of "hard" phases considerably well-bonded to the matrix.

Urinary tract infections are a major cause of morbidity and mortality in Mozambique. They are sometimes treated empirically with nitrofurantoin. However, little is known about this antibiotic’s performance and bacterial resistance in the country. This study analyzed the results of nitrofurantoin sensitivity tests requested in the Central Hospital of Maputo during 2012 and 2013. As result, 181 samples were tested and most cases (66.9%) showed absolute sensitivity but there were considerable cases of resistance (29.8%). Morganella morganii was the only bacteria presenting no absolute or intermediate resistance. The sensitivity was also high in the case of Escherichia coli (90%) and Gram-negative bacteria (66.7%). Serratia marcescens was mostly resistant (64.3%). The remaining bacteria showed inconclusive results. Thus they shall be subjected to a sensitivity test before prescription. Factors such as seasonality, patients’ sex and urine transparency did not seem to be reliable indicators of microbial resistance in the urine. Yet, a longer time span (over 5 years) might be sufficient for the sensitivity profile to change.

Lead optimization in drug discovery is a crucial phase where initial hits are refined into compounds with improved pharmacological properties. While traditional methods rely on manual experimentation and modifications, AI-driven techniques have revolutionized this process by leveraging big data and predictive modeling. This review explores how AI-driven approaches accelerate lead optimization, showcasing examples like deep neural networks and reinforcement learning. Integration of multi-omic data and experimental validation further enhances AI-driven strategies. The future lies in refining these AI methods, democratizing tools, and interdisciplinary collaboration to streamline drug discovery and address medical needs efficiently.

Antimicrobial peptides (AMPs) have emerged as a promising solution to tackle bacterial infections and combat antibiotic resistance. However, their clinical application has been hindered by their vulnerability to protease degradation and toxicity towards mammalian cells. To overcome these challenges, our study aims to develop a method to enhance the stability and safety of AMPs, applicable to effective drug-device combination products. KR12 antimicrobial peptide was chosen and in order to further enhance its delivery and efficacy, HIV TAT protein-derived cell-penetrating peptide (CPP) was fused to form CPP-KR12. A new product, CPP-KR12@Si, was developed by forming silica nanoparticles with self-entrapped CPP-KR12 peptide using the biomimetic silica precipitability due to its cationic nature. Peptide delivery from CPP-KR12@Si to bacteria and cells was delivered at a slightly delayed rate with improved stability against trypsin treatment and a reduction in cytotoxicity over CPP-KR12. Finally, the antimicrobial potential of CPP-KR12@Si/bone graft substitute (BGS) combination product was demonstrated, which is coated with CPP-KR12 in the form of nanoparticles on the surface of BGS. Self-entrapped AMP in silica nanoparticles is a safe and effective AMP delivery method that will be useful for developing a drug/device combination product for tissue regeneration.

As cancer remains resistant to several modes of treatment, novel therapeutics are still under active investigation to overcome treatment inefficacy in cancer. Given the high attrition rate of de novo drug discovery, drug screening, and drug repurposing have offered time- and cost-effective alternative strategies for the identification of potentially effective therapeutics. In contrast to large-scale drug screens, computational approaches for drug repurposing leverage the increasing amounts of biomedical data to predict candidate therapeutic agents prior to testing in biological models. Current studies in drug repurposing for cancer therapy prediction have increasingly focused on the prediction of combination therapies, as combination therapies have numerous advantages over monotherapies. These include increased effect from synergistic interactions, reduced toxicity from lowered drug doses, and a reduced risk of resistance due to multiple non-overlapping mechanisms of action. This review provides a summary of several classes of computational methods used for drug combination therapy prediction in cancer research, including networks, regression-based machine learning, classifier machine learning models, and deep learning approaches, with the goal of presenting current progress in the field, particularly to non-computational cancer biologists. We conclude by discussing the need for further advancements in technologies that incorporate disease mechanisms, drug characteristics, multi-omics data, and clinical considerations to generate effective patient-specific drug combinations, as holistic data integration will inevitably result in optimal targeted therapeutics for cancer.

This paper presents a computational approach designed to construct and query a literature-based knowledge graph for predicting novel drug therapeutics. The main objective is to offer a platform that discovers drug combinations from FDA-approved drugs and accelerates their investigations by domain scientists. Specifically, the paper introduced the following algorithms: (1) an algorithm for constructing the knowledge graph from drug, gene, and disease mentions in the biomedical literature; (2) an algorithm for vetting the knowledge graph from drug combinations that may pose a risk of drug interaction; (3) and two querying algorithms for searching the knowledge graph by a single drug or a combination of drugs. The resulting knowledge graph had 844 drugs, 306 gene/protein features, and 19 disease mentions. The original number of drug combinations generated was 2,001. We queried the knowledge graph to eliminate noise generated from chemicals that are not drugs. This step resulted in 614 drug combinations. When vetting the knowledge graph to eliminate the potentially risky drug combinations, it resulted in predicting 200 combinations. Our domain expert manually eliminated extra 54 combinations which left only 146 combination candidates. Our three-layered knowledge graph, empowered by our algorithms, offered a tool that predicted drug combination therapeutics for scientists who can further investigate from the viewpoint of drug targets and side effects.

Phage therapeutics offer a potentially powerful approach to combat multidrug-resistant bacterial infections. However, to be effective, phage therapy must overcome existing and developing phage resistance. While phage cocktails can reduce this risk by targeting multiple receptors in a single therapeutic, bacteria have mechanisms of resistance beyond receptor modification. A rapidly growing body of knowledge describes a broad and varied arsenal of antiphage systems encoded by bacteria to counter phage infection. We sought to understand the types and frequencies of antiphage systems present in a highly diverse panel of Pseudomonas aeruginosa clinical isolates utilized to characterize novel antibacterials. Using web-server tool PADLOC (Prokaryotic Antiviral Defense Locator), putative antiphage systems were identified in these P. aeruginosa clinical isolates based on sequence homology to a validated and curated catalog of known defense systems. Coupling this host bacterium sequence analysis with host range data for 70 phages, we observed a correlation between existing phage resistance and the presence of higher numbers of antiphage systems in bacterial genomes. We were also able to identify antiphage systems that were more prevalent in highly phage-resistant P. aeruginosa strains, suggesting their importance in conferring the resistance.

Antimicrobial resistance (AMR) is a growing public health issue worldwide that affects the world economy. The concern associated with this issue increased during the COVID-19 pandemic. The misuse of antibiotics during the COVID-19 pandemic will have catastrophic implications for the control of AMR. In 2019, the coronavirus illness COVID-19 first appeared in China. COVID-19 infection is a surface-to-surface communicable disease. It is considered the most vital global health disaster of the century. It has rapidly spread around the world and is the greatest challenge for humankind. This chapter discusses the origin, symptoms, transmission, treatment, and recommendations of the COVID-19 disease.

A novel group of conjugative plasmids of Pseudomonas is characterized. The prototype plasmid pPPUT-Tik1-1 (153663 bp), isolated from a permafrost strain of P. putida Tik1, carries a defective mercury transposon Tn501 and a streptomycin resistance transposon Tn5393. Ten plasmids and 34 contigs with backbone regions closely related to pPPUT-Tik1-1 have been found in Gene Bank. Two of these plasmids isolated from clinical strains of P. putida and P. fulva are almost identical to the ancient plasmid. A characteristic feature of this group of plasmids is the presence of two genes encoding the initiators of replication (repA1 and repA2). None of these genes has high similarity with plasmid replication genes belonging to known incompatibility groups. It has been demonstrated that while pPPUT-Tik1-1-like plasmids have homologous backbone regions they significantly differ by the molecular structure and the functional burden of their accessory regions. Some of the pPPUT-Tik1-1-related plasmids carry determinants of antibiotic resistance and/or heavy metal salts. Some plasmids are characterized by the ability to degrade xenobiotics. Plasmids related to pPPUT-Tik1-1 are characterized by a narrow host range and are found in various species of Pseudomonas genus. A group of shortened plasmids containing the same replication module, but without conjugation genes, were also found. These plasmids also contain other structural changes that strongly distinguish them from plasmids related to pPPUT-Tik1-1. The data obtained indicate the need for a complex approach to the classification of plasmids.

This paper presents a concise exploration of several analytical methods for extracting the parameters of the single-diode model (SDM) of a photovoltaic (PV) module under standard test conditions (STC). The paper investigates six methods and presents the detailed mathematical analysis leading to the development of each method. To evaluate the performance of these methods, MATLAB-based software has been developed and deployed to synthesize the results of each method when used to extract the SDM parameters of various PV test modules of different PV technologies. Similar software has also been developed to extract the same parameters using well-established numerical and iterative techniques. A comparison is subsequently made between the synthesized results and those obtained using numerical and iterative methods. The comparison indicates that in spite of the fact that analytical methods may involve fair amount of approximations, their accuracy can be comparable to that of their numerical and iterative counterparts, with the added advantage of significant reduction in computational complexity, and without the initialization and convergence difficulties, which are normally associated with numerical methods.

Abstract: This paper outlines the methodology and results for a two species finite volume scalar computational drug transport model developed for simulating the mass transport of Poly(lactic-co-glycolic acid (PLGA) ) from a half-embedded single strut implanted in a coronary arterial vessel wall. The mathematical drug transport model incorporates the convection-diffusion equation in scalar form (dimensionless) with a two species (free-drug and bound-drug) mass transport setup including reversible equilibrium reaction source terms for the free and bound-drug states to account for the pharmaco-kinetic reactions in the arterial wall. The relative reaction rates of the added source terms control the interconversion of drug between the free and bound-drug states. The model is solved by a 2-D finite-volume method for discretizing and solving the free and bound drug transport equations with anisotropic vascular drug diffusivities. This model is an improvement over our previously developed model using the finite-difference method. A dimensionless characteristic scaling pre-analysis was conducted a priori to evaluate the significance of implementing the reaction source terms in the transport equations. This paper reports the findings of an investigation of the interstitial flow profile into the arterial wall and the free and bound drug diffusion profiles with a parametric study of varying polymer drug concentration (low and high), tortuosity, porosity, and Peclet and DamKöhler numbers over the course of 400 hours (16.67 days). The results also reveal how a single species drug delivery model that neglects both a reversible binding reaction source term and the porosity and tortuosity of the arterial wall cannot accurately predict the distribution of both the free and bound drug.

In CNS drug discovery, estimation of brain exposure of lead compounds is critical for their optimization. Compounds need to cross the blood-brain barrier (BBB) to reach the pharmacological targets in the CNS. The BBB is a complex system involving passive and active mechanisms of transport and efflux transporters such as P-glycoproteins (P-gp) and breast cancer resistance protein (BCRP), which play an essential role in CNS penetration of small molecules. Several in vivo, in vitro and in silico methods are available to estimate human brain penetration. Preclinical species are used as in vivo models to understand the unbound brain exposure by deriving the Kp,uu parameter, the brain/plasma ratio of exposure corrected with the plasma and brain free fraction. MDCK-mdr1 (Madin Darby canine kidney cells transfected with the MDR1 gene encoding for the human P-gp) assay is the most commonly used in vitro assay to estimate compound permeability and human efflux. The in silico methods to predict brain exposure, such as CNS MPO, CNS BBB scores and various Machine Learning models, help save costs and speed up compound discovery and optimization at all stages. These methods enable the screening of virtual compounds and building of a CNS penetrable compounds library as well as optimization of lead molecules for CNS penetration. Therefore, it is crucial to understand these methods' reliability and ability to predict CNS penetration. We review the in silico, in vitro and in vivo data and their correlation with each other and assess published in silico approaches to predict the BBB penetrability of compounds.

In this article, we introduce some multi-messenger studies of blazars. Main contents contain the following parts, 1. the subclasses of blazars and the observational characteristics, 2. emission variabilities from the multi-messenger observations, 3. the physical origin for the multi-messenger studies. Based on mid-IR observations collected from the $WISE$ database, we collect two sources (BZQ J1700+6830 and BZQ J1842+6809) to analyze the mid-IR variabilities. \\ (1) For BZQ J1700+6830, the period is $P\approx$ 42 hr at the four bands ($W1$, $W2$, $W3$, $W4$); for BZQ J1842+6809, the period is $P\approx$ 123 hr at the two bands ($W1$, $W2$). \\ (2) Using the periodicities, we calculate that the central black hole mass ($BH$) should be $M = (5.44\sim33.0)\times10^8M_{\odot}$ for BZQ J1700+6830 and $M = (1.13\sim6.88)\times10^9M_{\odot}$ for BZQ J1842+6809.\\ (3) For the two sources, during the flaring stage, we find anti-clockwise variation trends based on the time-based relations built by the spectral indices ($\alpha$) and flux densities ($F$).\\ (4) We calculate the Doppler factor ($\delta$) when the sources are in the dimming or brightening stages, and find that with the frequency increasing, the Doppler factor become stronger.

The paper considers new effects of the nanoscale state of matter, which open up prospects for the creation of electronic devices using new physical principles. The contact of chemically homogeneous different sizes hydrated nanoparticles of yttrium-stabilized zirconium oxide (ZrO2 – x %mol Y2O3, x=0, 3, 4, 8; YSZ) with particle sizes of 7.5 nm and 7,5 nm; 7.5 nm and 9 nm; 7.5 nm and 11 nm; 7.5 nm and 14 nm in the form of compacts obtained using high hydrostatic pressure (HP-compacts of 300MPa) was studied at direct and alternating current. A unique size effect of the nonlinear (semiconductor) dependence of the electrical properties (in the region U <2.5 V, I ≤ 2.7 mA) of the contact of different-sized YSZ nanoparticles of the same chemical composition is revealed, which indicates the possibility of creating semiconductor structures of a new type based on chemically homogeneous nanostructured systems. The electronic structure of the near-surface regions of nanoparticles of a special type of oxide materials and the possibility, on this basis, to obtain specifically rectifying properties of the contacts were studied theoretically. Models of surface states of the Tamm type are constructed, but considering the Coulomb long-range action. The discovered variance and its dependence on the curvature of the surface of nanoparticles made it possible to study the conditions for the formation of a contact potential difference in cases of nanoparticles of the same radius (synergistic effect), different radii (doped and undoped variants), as well as to discover the possibility of describing a group of powder particles from material within the Anderson model. The established effect makes it possible to solve the problem of diffusion instability of semiconductor heterojunctions and opens up prospects for creating electronics devices with a fundamentally new level of properties for use in various fields of the national economy and breakthrough critical technologies.

Fluorescence microscopy provides an unparalleled tool for imaging biological samples. However, producing high-quality volumetric images quickly and without excessive complexity remains a challenge. Here, we demonstrate a simple multi-camera structured illumination microscope (SIM) capable of simultaneously imaging multiple focal planes, allowing for the capture of 3D fluorescent images without any axial movement of the sample. This simple setup allows for the acquisition of many different 3D imaging modes, including 3D time lapses, high-axial-resolution 3D images, and large 3D mosaics.

Our work uses Iterative Boltzmann Inversion (IBI) to study the coarse-grained interaction between 20 amino acids and the representative carbon nanotube CNT55L3. IBI is a multi-scale simulation method that has attracted the attention of many researchers in recent years. It can effectively modify the coarse-grained model derived from the Potential of Mean Force (PMF). IBI is based on the distribution result obtained by All-Atom molecular dynamics simulation, that is, the target distribution function, the PMF potential energy is extracted, and then the initial potential energy extracted by the PMF is used to perform simulation iterations using IBI. Our research results have gone through more than 100 iterations, and finally, the distribution obtained by coarse-grained molecular simulation (CGMD) can effectively overlap with the results of all-atom molecular dynamics simulation (AAMD). In addition, our work lays the foundation for the study of force fields for the simulation of the coarse-graining of super-large proteins and other important nanoparticles.

Multi-morbidity and polypharmacy are common in older people and pose a challenge for health and social care systems especially in context of global population ageing. They are complex and interrelated concepts in the care of older people that require early detection and patient centred decision making that are underpinned by the principles of multidisciplinary led comprehensive geriatric assessment (CGA). Personalised care plans need to remain responsive and adaptable to the needs of a patient, enabling an individual to maintain their independence.

This paper presents a new and enhanced fusion module for the Multi-Sensor Precipitation Estimator (MPE) that would objectively blend real-time satellite quantitative precipitation estimates (SQPE) with radar and gauge estimates. This module consists of a preprocessor that mitigates systematic bias in SQPE, and a two-way blending routine that statistically fuses adjusted SQPE with radar estimates. The preprocessor not only corrects systematic bias in SQPE, but also improves the spatial distribution of precipitation based on SQPE and makes it closely resemble that of radar-based observations. It uses a more sophisticated radar-satellite merging technique to blend preprocessed datasets, and provides a better overall QPE product. The performance of the new satellite-radar-gauge blending module is assessed using independent rain gauge data over a 5-year period between 2003-2007, and the assessment evaluates the accuracy of newly developed satellite-radar-gauge (SRG) blended products versus that of radar-gauge products (which represents MPE algorithm currently used in the NWS operations) over two regions: I) inside radar effective coverage and II) immediately outside radar coverage. The outcomes of the evaluation indicate a) ingest of SQPE over areas within effective radar coverage improve the quality of QPE by mitigating the errors in radar estimates in region I; and b) blending of radar, gauge, and satellite estimates over region II leads to reduction of errors relative to bias-corrected SQPE. In addition, the new module alleviates the discontinuities along the boundaries of radar effective coverage otherwise seen when SQPE is used directly to fill the areas outside of effective radar coverage.

Technological advancements and evolving government regulations are driving the adoption of construction equipment powered by renewable energy sources, aiming to significantly reduce emissions. Electrifying non-road mobile machinery (NRMM), particularly self-propelled Rough-Terrain Variable Reach Trucks (RTVRT) with telescopic booms, presents stability challenges. Replacing diesel engines with electric motors and battery packs shifts the centre of gravity, necessitating precise load capacity determinations via load charts to ensure safe operation. This paper introduces a virtual model developed using multi-physic modelling with Bond Graph methodology. The model encompasses crucial components, including the chassis, rear axle, telescopic boom, attachment fork, and wheels, requiring three-dimensional treatment for spatial dynamics resolution. An illustrative example, supported by experimental data, demonstrates the model's capabilities. Special focus is placed on calculating ground wheel reaction forces and hydraulic self-leveling of the attachment fork. Numerical results validate the BG-3D simulation model of the telehandler with 20-Sim as a promising tool for estimating stability limits with satisfactory precision and predicting dynamic behavior across various operating conditions. Moreover, the paper explores potential extensions of the model, such as integrating the virtual vehicle model with a platform of variable inclination in subsequent phases which aims to evaluate telehandler longitudinal and lateral stability, aligning with the ISO 22915 standard and operator safety.

Bioelectrocatalysis provides the intrinsic catalytic-functions of redox enzymes to non-specific electrode reactions and is the most important and basic concept for biosensors. This review starts by describing fundamental characteristics of bioelectrocatalytic reactions in mediated and direct electron transfer types from a theoretical viewpoint and summarizes amperometric biosensors based on multi-enzymatic cascades and for multi-analyte detection. The review also introduces prospective aspects of two new concepts of biosensors: mass-transfer-controlled (pseudo)steady-state amperometry at microelectrodes with enhanced enzymatic activity without calibration curves and potentiometric coulometry at enzyme/mediator-immobilized biosensors for absolute determination.

This article proposes the use of a multi-scale and multi-sensor approach to collect and modelling 3D data concerning wide and complex areas in order to obtain a variety of metric information in the same 3D archive, based on a single coordinate system. The employment of these 3D georeferenced products is multifaceted and the fusion or integration among different sensors data, scales and resolutions is promising and could be useful for the generation of a model that could be defined as hybrid. The correct geometry, accuracy, radiometry and weight of the data models are hereby evaluated comparing integrated processes and results from Terrestrial Laser Scanner (TLS), Mobile Mapping System (MMS), Unmanned Aerial Vehicle (UAV), terrestrial photogrammetry, using Total Station (TS) and Global Navigation Satellite System (GNSS) as topographic survey. The entire analysis underlines the potentiality of the integration and fusion of different solutions and is a crucial part of the “Torino 1911” project whose main purpose is mapping and virtually reconstructing the 1911 Great Exhibition settled in the Valentino Park in Turin (Italy).