High mobility group box 1 (HMGB1) is secreted from activated immune cells, necrotic cells, and certain cancers. Previous studies have reported that different patterns of post-translational modification, particularly acetylation and oxidation, mediate HMGB1 release and confer distinct extracellular HMGB1 signaling activity. Here we report that cisplatin but not carboplatin induces secretion of HMGB1 from human A549 non-small cell lung cancer (NSCLC) cells. Cisplatin-mediated HMGB1 secretion was dose-dependent and was regulated by nuclear exportin 1 (XPO1) also known as chromosomal maintenance 1 (CRM1) rather than adenosine diphosphate (ADP)-ribosylation, acetylation, or oxidation. HMGB1, as well as lysine acetylation and cysteine disulfide oxidation of secreted HMGB1, were monitored by sensitive and specific assays using immunoprecipitation, stable isotope dilution, differential alkylation, and nano liquid chromatography parallel reaction monitoring/high-resolution mass spectrometry (nano-LC-PRM/HRMS). A major fraction of the HMGB1 secreted by low dose cisplatin treatment of A549 NSCLC cells was found to be in the fully reduced form. In contrast, mainly oxidized forms of HMGB1 were secreted by dimethyl sulfoxide (DMSO)-mediated apoptosis. These findings suggest that inhibition of XPO1 could potentiate the anti-tumor activity of cisplatin by increasing the nuclear accumulation of HMGB1 protein, an inhibitor of cisplatin DNA-adduct repair. Furthermore, low-dose cisplatin therapy could modulate the immune response in NSCLC through the established chemokine activity of extracellular reduced HMGB1. This could potentially enhance the efficacy of subsequent immunotherapy treatment.

(1) Background: The COVID-19 pandemic had a devastating impact on the world, causing widespread illness and death. It is essential to focus on prevention strategies to limit the spread of the disease. Despite the advent of vaccines, maintaining a vigilant approach to prevention remains paramount. While vaccines are essential, they do not guarantee absolute immunity, and their protective effect may diminish over time; (2) Methods: We reviewed effective strategies to prevent COVID-19 transmission. We focused on me-ta-analyses (MA), literature reviews (LR) and the health care context. Various prevention measures and interventions were reviewed. Both es-tablished practices and unresolved issues were considered; (3) Results: Standard precautions (SP) as the cornerstone of infection control, with hand hygiene and mask use as key components. Debate about the relative importance of droplet versus aerosol transmission led to differences in recommendations between agencies at the onset of the pandemic. We have clarified the role of personal protective equipment (PPE), including eye protection. The effectiveness of masks in pre-venting transmission is reviewed. The use of surgical masks is recommended to prevent droplet transmission, while eye protection is recommended in combination with masks. Although data show some risk reduction, the clear superiority of N95/FFP2 over surgical masks remains unproven. In terms of room occupancy, ventilation is critical in reducing the risk of transmission in poorly ventilated environments. The use of negative pressure isolation rooms (NPIRs) is being investigated. The presence of viral RNA on surfaces does not necessarily indicate infectivity, and the risk of transmission by surface contact is low if surfaces are properly maintained and hand hygiene is practised regularly. Testing for SARS-CoV-2 in asymptomatic persons in healthcare settings may help prevent transmission; (4) Conclusions: Prevention of SARS-CoV-2 transmission requires a multifaceted approach, including reducing particle emissions from infected persons by wearing masks, eliminating aerosols by ventilation, ensuring physical separation, and protecting exposed persons with masks and eye protection.

This study aimed to identify and differentiate the factors that may affect the incidence of temporomandibular joint (TMJ) dysfunction in children with type 1 diabetes. We analyzed the TMJ symptoms, clinical and laboratory parameters of type 1 diabetes in a cohort of 101 consecutive patients. The participants were evaluated regarding the presence of pain in the masticatory muscles, TMJ sounds, mouth opening, maximum mouth opening, lateral and protrusive excursions, and Fonseca scores. The overall cohort showed a mean Fonseca score of 20 ± 13.89, referred to mild TMJ dysfunction. Of patients, 34.65% presented at least one clinical symptom and were defined as having dysfunction. The most frequently recorded symptom was TMJ sounds, presented in 16.8% of children. In subjects with dysfunction compared to those without dysfunction, a significant difference was found at height standard deviation scores, Fonseca scores and maximum mouth opening (p<0.001). HbA1c levels, diabetes duration, age and gender did not reveal any significant differences between the patients with and without dysfunction. Type 1 diabetes is often associated with limited mouth opening and mild TMJ dysfunction. This dysfunction may reflect a more chronic condition and possibly exceeds the prevalence of cheiroartropathy. This study could be a starting point towards enhancing our understanding of clinically evident TMJ involvement in type 1 diabetes.

Lead-based ternary chalcogenide thin films of the (PbTe)1-x(PbS)x system were obtained by plasma-enhanced chemical vapor deposition technique (PECVD) under conditions of a nonequilibrium low-temperature argon plasma of an RF discharge (40.68 MHz) at a reduced pressure (0.01 Torr). High-purity elements were directly used as starting materials – Pb, S and Te. Plasma-chemical synthesis was carried out on the surface of of c-sapphire and silicon substrate. The physicochemical properties of the films were studied by various analytical methods. The dependence of the Seebeck coefficient, resistivity, and power factor on the structural properties and composition has been studied. The thermoelectric characteristics were found to be dependent on the film composition. Upon the selection of optimal sulfur concentration one can increase the power factor as compared to single phase PbS ot PbTe films.

Infection with the porcine reproductive and respiratory syndrome virus type 1 (PRRSV-1) has serious economic consequences for the pig industry. Swine practitioners and other agricultural advisors often describe an increase in antibiotic use when PRRSV-1 is circulating. Our objective was to assess the impact of PRRSV-1 stabilization programmes on reducing antibiotic use. The study was carried out on 19 French farrow-to-finish farms that successfully implemented a PRRSV-1 stabilization protocol between 2007 and 2019. For each farm, antibiotic consumption (expressed in mg/PCU and ALEA) were compared one year before (P1) and one year after (P2) the implementation of such a protocol and the change between P1 and P2 were calculated in percentages. Data were then analysed by level of consumption. Antibiotic use decreased significantly between P1 and P2 if expressed in mg/PCU and showed a decreased tendency in terms of exposure (ALEA). Concerning the change from P1 to P2, our results showed that the higher consumption levels in P1, the greater antibiotic reduction in P2. This study highlights the ability of a stabilization protocol against PRRSV-1 to reduce antibiotic use, especially on farms that have high consumption. These hopeful results show that further investigations about the relationship between PRRSV-1 and antibiotic usage could be beneficial.

HAX1 is a multifunctional protein involved in the antagonism of apoptosis in cellular response to oxidative stress. In the present study we identified HAX1 as novel binding partner for Che-1/AATF, a pro-survival factor which plays a crucial role in fundamental processes, including response to multiple stresses and apoptosis. HAX1 and Che-1 proteins show extensive colocalization in mitochondria and we demonstrated that their association is strengthened after oxidative stress stimuli. Interestingly, in MCF-7 cells, resembling luminal estrogen receptor (ER) positive breast cancer, we found that Che-1 depletion correlates with decreased HAX1 mRNA and protein levels, and this event is not significantly affected by oxidative stress induction. Furthermore, we observed an enhancement of the previously reported interaction between HAX1 and estrogen receptor alpha (ERα) upon H2O2 treatment. These results indicate the two anti-apoptotic proteins HAX1 and Che-1 as coordinated players in cellular response to oxidative stress with a potential role in estrogen sensitive breast cancer cells.

Background: Visceral leishmaniasis affects approximately 12 million people worldwide. Current existing drugs cause several side effects and resistance, the identification of new therapeutic targets for the development of new drugs is necessary. The vesicular trafficking in the parasite flagellar pocket is essential for parasite survival and proliferation, but little is known about the proteins involved in the endocytic/secretory pathways. In this work, we are describing the characterization of a transporter cargo protein SFT-2/Got-1 like in Leishmania infantum. Material and Methods: Using bioinformatics tools, the putative Got-1 protein A4HSK3 was characterized structurally and phylogenetically. Molecular biology was used to clone and express the protein and confocal fluorescence to determine its subcellular localization. Results: The Got-1 like protein presents four alpha helix TM conserved domains (aa38-aa147) characteristics of the Got-1/SFT-2 family proteins and an important Pen-2 conserved motif LGDYXXF located in the extracellular loop. Confocal microscopy suggests that Got-1/SFT-2 like is localized in the flagellar pocket, and is partially co-localized with the L. infantum presenilin-like protein. Phylogenetically, the Leishmania sp Got-1 like is contained in a subgroup of proteins clearly detached from the other Trypanosomatidae, such as T. cruzi and T. brucei. Conclusions: Our data show the presence of an important transported proteins, and its colocalization with the presenilin aspartyl protease in the flagellar pocket of the L. infantum open new perspectives to identify novel targets, which can be an alternative therapeutic strategy against leishmaniasis.

HIV-1, like other viruses, represents an open thermodynamic system. This is why it is important to know its thermodynamic properties. Virus-host interactions are performed at the membrane as antigen-receptor binding. Antigen-receptor binding represents a chemical reaction, similar to protein-ligand interactions. The driving force for antigen-receptor binding is Gibbs energy of binding. Knowing Gibbs energy of binding, it is possible to estimate the rate of virus binding and entry into host cells. In this paper, binding equilibrium constants and standard Gibbs energies of binding between the HIV-1 gp120 antigen and the CD4 receptor have been reported at 4°C, 22°C and 37°C.

The glucose-insulin regulatory system and its glucose oscillations is a recurring theme in the literature because of its impact on human lives, mostly the ones affected by diabetes mellitus. Several approaches were proposed, from mathematical to data-based models, with the aim of modeling the glucose oscillation curve. Having such a curve, it is possible to predict, when injecting insulin in type 1 diabetes (T1D) individuals. However, the literature presents prediction horizons no longer than 6 hours, which could be a problem considering their sleeping time. This work presents Tesseratus, a model that adopts a multi-agent approach to combine machine learning and mathematical modeling to predict the glucose oscillation up to 8 hours. Tesseratus uses the pharmacokinetics of insulins and data collected from T1D individuals. Its outcome can support endocrinologists while prescripting daily treatment for T1D individuals, and provide personalized recommendations for such individuals, to keep their glucose concentration in the ideal range. Tesseratus brings pioneering results for prediction horizons of 8 hours for nighttime, in an experiment with seven real T1D individuals. It is our claim that Tesseratus will be a reference for classification of glucose prediction model, supporting the mitigation of short- and long-term complications in the T1D individuals.

Emerging RNA virus infections are a growing concern among domestic bird and poultry industries due to the severe impact it can have on the flock health and economic livelihoods. Avian paramyxoviruses (APMV) are pathogenic, negative sense RNA viruses that cause serious infections in the respiratory and central nervous system. APMV was detected in multiple avian species during the 2017 migration season in Ukraine, and studied using PCR, virus isolation, and sequencing. Of the 4090 wild bird samples, eleven swabs were isolated in chicken embryos and identified for APMV serotype by hemagglutinin inhibition test: APMV-1, APMV-4, APMV-6, APMV-7. At a variety of sites in Ukraine we characterized the virulence of the virus and further analyzed and predicted the potential risks of spillover to immunologically naïve populations. RNA was extracted and amplified using a multiplex-tiling primer approach to encompass full cDNA genomes. Full-length APMV-1 (n=5) and APMV-6 (n=2) genomes were sequenced on an Oxford Nanopore MinION device in Ukraine. All APMV-1 and APMV-6 fusion (F) proteins possessed a monobasic cleavage site, suggesting these APMV were likely low virulence, annually circulating strains. Utilization of this low-cost method will identify gaps in viral evolution and circulation in this understudied but important critical region for Eurasia.

We have developed a self-consistent model for predicting velocity of 1/2[111] screw dislocation in binary iron--carbon alloys gliding by a high-temperature Peierls mechanism. The methodology of modelling includes: (i) Kinetic Monte-Carlo (kMC) simulation of carbon segregation in dislocation core and determination the total carbon occupancy of the core binding sites; (ii) Determination of kink-pair formation enthalpy of a screw dislocation in iron---carbon alloy; (iii) KMC simulation of carbon drag and determination of maximal dislocation velocity at which the atmosphere of carbon atoms can follow a moving screw dislocation; (iv) Self consistent calculation of average velocity of screw dislocation in binary iron--carbon alloys gliding by a high-temperature kink-pair mechanism under constant strain rate. We conduct a quantitative analysis of the conditions of stress and temperature at which screw dislocation glide in iron--carbon alloy is accomplished by a high-temperature kink-pair mechanism. We estimate the dislocation's velocity at which screw dislocation brakes away from the carbon cloud and thermally-activated smooth dislocation propagation is interrupted by sporadic bursts controlled by athermal dislocation activity.

Bistable rhodopsins have two stable forms which can be interconverted by light. Due to their ability to act as photoswitches, these proteins are considered as ideal candidates for applica-tions such as optogenetics. In this work we analyze a recently crystalized bistable rhodopsin, namely the jumping spider rhodopsin-1 (JSR1). This rhodopsin exhibits identical absorption maxima for the parent and the photoproduct form, which impedes its broad application. We have performed hybrid QM/MM simulations to study three isomers of the retinal chromo-phore: the 9-cis, 11-cis and all-trans configurations. The main aim was to gain insight into the specific interactions of each isomer and their impact on the absorption maximum in JSR1. The absorption spectra were computed using sampled snapshots from a QM/MM molecular dy-namics trajectory and compared to experimental counterparts. The chromophore-protein in-teractions were analyzed by visualizing the electrostatic potential of the protein and projecting it onto chromophore. It was found that the distance between a nearby tyrosine (Y126) residue plays a larger role in the predicted absorption maximum than the primary counterion (E194). Geometric differences between the isomers were also noted including a structural change in the polyene chain of the chromophore as well as changes in the nearby hydrogen bond network.

Let $G$ be a group with identity $e$ and $R$ be a commutative $G$-graded ring with nonzero unity $1$. Graded semi-primary and graded $1$-absorbing primary ideals have been investigated and examined by several authors as generalizations of graded primary ideals. However, these three concepts are different. In this article, we characterize graded rings over which every graded semi-primary ideal is graded $1$-absorbing primary and graded rings over which every graded $1$-absorbing primary ideal is graded primary.

Surface soil moisture (SSM) is a significant factor affecting crop growth. This paper presents a method for retrieving SSM over wheat-covered areas using synergy dual-polarization C-band Sentinel-1 synthetic aperture radar and Sentinel-2 optical data. Firstly, a modified water cloud model (WCM) was proposed to remove the influence of vegetation from the backscattering coefficient of the radar data. The vegetation fraction was then introduced in this WCM, and the vegetation water content (VWC) was calculated using multiple linear regression model. Subsequently, the support vector regression technique was used to retrieve the SSM. This approach was validated using in-situ measurements of the wheat field in Hebi, in the north of Henan Province. The key findings of this study are as follows: (1) Based on vegetation indices obtained from Sentinel-2; the proposed VWC estimation model can effectively eliminate the influence of vegetation; (2) compared with vertical transmit and horizontal receive polarization, vertical transmit and vertical receive polarization is better for detecting changes in SSM at different growth stages of wheat; and, (3) the validation results indicated that the proposed approach, based on Sentinel-1 and Sentinel-2 data, successfully retrieved SSM in the study area.

Current therapeutic protocols for the treatment of HIV infection consist of the combination of diverse anti-retroviral drugs in order to reduce the selection of resistant mutants and to allow for the use of lower doses of each single agent to reduce toxicity. However, avoiding drugs interactions and patient compliance are issues not fully accomplished so far. In this respect the identification of single agents with multitarget potential might represent the ideal solution. Accordingly, a small library of biphenylhydrazo 4-arylthiazoles derivatives has been synthesised and evaluated to investigate the ability of the new derivatives to simultaneously inhibit both associated functions of HIV reverse transcriptase. All compounds were active towards the two functions, although at different concentrations. The substitution pattern on the biphenyl moiety appears relevant to determine the activity.

Background: Brain oxidative lipid damage and inflammation are common in neurodegenerative diseases such as Alzheimer’s disease (AD). Paraoxonase-1 and 3 (PON1 and PON3) protein expression have been described in tissues with no PON1 and PON3 gene expression. In the present study, we aimed to examine differences in PON1 and PON3 protein expression in the brain of a mouse model of AD. Methods: We used peroxidase-based and fluorescence-based immunohistochemistry in 5 brain regions (olfactory bulb, forebrain, posterior midbrain, hindbrain and cerebellum) of transgenic (Tg2576) mice with the Swedish mutation (KM670/671NL) responsible for a familial form of AD and corresponding wild-type mice. Results: We found intense PON1 and PON3 positive staining in star-shaped cells surrounding Aβ plaques in all Tg2576 mouse brain regions studied. Although we could not co-localize PON1 and PON3 with astrocytes, brain star-shaped cells, we found some co-localization of PON3 with microglia. Conclusions: These results suggest that 1) PON1 and PON3 cross the blood-brain barrier in discoidal HDLs and are transferred to specific brain cell types, and 2) PON1 and PON3 play an important role in preventing oxidative stress and lipid peroxidation in particular cell types, likely astrocytes and microglia, in AD pathology, and potentially in other neurodegenerative diseases

In recent years, there have been frequent reports on the adverse effects of synthetic cannabinoid (SC) abuse. SCs cause psychoactive effects, similar to those caused by marijuana, by binding and activating cannabinoid receptor 1 (CB1R) in the central nervous system. The aim of this study was to establish a reliable quantitative structure-activity relationship (QSAR) model to correlate the structures and physicochemical properties of various SCs with their CB1R-binding affinities. We prepared 15 SCs and their derivatives (tetrahydrocannabinol [THC], naphthoylindoles, and cyclohexylphenols) and determined their binding affinity to CB1R, which is known as a dependence-related target. We calculated the molecular descriptors for dataset compounds using an R/CDK (R package integrated with CDK, version 3.5.0) toolkit to build QSAR regression models. These models were established and statistical evaluations were performed using the mlr and plsr packages in R software. The most reliable QSAR model was obtained from the partial least squares regression method via external validation. This model can be applied in vivo to predict the addictive properties of illicit new SCs. Using a limited number of dataset compounds and our own experimental activity data, we built a QSAR model for SCs with good predictability. This QSAR modeling approach provides a novel strategy for establishing an efficient tool to predict the abuse potential of various SCs and to control their illicit use.

Fire is a significant threat to human life and civil infrastructures. Builders and architects are hankering for safer and sustainable alternatives of concrete that do not compromise with their design intent or fire safety requirements. The aim of the present work is to improve the residual compressive performance of concrete in the post-fire exposure, by incorporating by-products from urban residues. Based on sustainability and circular economy motivations, the attention is focused on rubber tire fly ash, aged brick powder, and plastic (PET) bottle residuals used as partial sand replacement. The selected by-products from urban residues are used for the preparation of Cement-Based Composites (CBCs) in two different proportions (10 % and 15 %). The thermal CBC behaviour is thus investigated under realistic fire scenarios (i.e., Direct Flame (DF) for 1 hour (1h)), by following the ISO 834 standard provisions, but necessarily resulting in non-uniform thermal exposure for the cubic specimens. The actual thermal exposure is further explored with a Finite Element (FE) model, giving evidence of thermal boundaries effects. The post-fire residual compressive strength of heated concrete and CBC samples is hence experimentally derived, and compared to unheated specimens in ambient conditions. From the experimental study, the enhanced post-fire performance of CBCs with PET bottle residual is generally found superior to other CBCs or concrete. The structure-property relation is also established, with the support of Scanning Electron Microscopy (SEM) micrographs. Based on existing empirical models of literature for the prediction of the compressive or residual compressive strength of standard concrete, newly developed empirical relations for both concrete and CBCs are assessed.

The main objective of this study is to develop a Hapke photometric model that is suited for Chang’E-1 (CE-1) Interference Imaging Spectrometer (IIM) data. We first divided the moon into three areas including ‘maria’, ‘new highland’ and old ‘highland’ with similar photometry characteristic based on the Hapke parameters of the moon derived from Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) multispectral data. Then, we selected the sample data in the ‘maria’ area and obtained a new set of Hapke model’s parameters that can best fit these data. Result shows that photometric correction using Hapke model with these new derived parameters can eliminate the effect of variations in viewing and luminating geometry, especially ‘opposition surge’, more efficiently than the empirical model. The corrected mosaic shows no significant artifacts along the tile boundaries, and more detailed information of the image can be exhibited due to a better correction of ‘opposition surge’ at small phase angle (g <15°).

The process of viral integration into the host genome is an essential step of the HIV-1 life cycle. The viral Integrase (IN) enzyme catalyses integration. IN is an ideal therapeutic enzyme targeted by several drugs; raltegravir (RAL), elvitegravir (EVG), dolutegravir (DTG) and bictegravir (BIC) having been approved by the USA Food and Drug Administration (FDA). Due to high HIV-1 diversity, it is not well understood how specific naturally occurring polymorphisms (NOPs) in IN may affect the structure/function and binding affinity of Integrase Strand Transfer Inhibitors (INSTIs). In this study, we applied computational methods of molecular modelling and docking to analyse the effect of NOPs on the full-length IN structure and INSTI binding. We identified 16 NOPs within the Cameroonian derived CRF02_AG IN sequences and further identified 17 NOPs within HIV-1C South African sequences. The NOPs in the IN structures did not show any effect on INSTI binding. INSTIs displayed similar binding affinities to each IN structure. All INSTIs are clinically effective against diverse HIV-1 strains from INSTI treatment naïve populations. This study supports the use of second-generation INSTI DTG as part of first-line combination antiretroviral therapy (cART) regimens, due to DTG possessing a stronger genetic barrier to the emergence of drug resistance.

Background: CCL11 (eotaxin) is a chemokine with an important role in allergic conditions. Recent evidence indicates that CCL11 plays a role in brain disorders as well. Aims: This paper reviews the associations between CCL11 and aging, neurodegenerative, neuroinflammatory and neuropsychiatric disorders.Methods: Electronic databases were searched for original articles examining CCL11 in neuropsychiatric disorders.Results: CCL11 is rapidly transported from the blood to the brain through the brain-blood barrier. Age-related increases in CCL11 are associated with cognitive impairments in executive functions, episodic and semantic memory and, therefore, this chemokine was described as an “endogenous cognition deteriorating chemokine” (ECDC) or “accelerated brain-aging chemokine” (ABAC). In schizophrenia, increased CCL11 is not only associated with impairments in cognitive functions, but also with key symptoms including formal thought disorders. Some patients with mood disorders and premenstrual syndrome show increased plasma CCL11 levels. In diseases of old age, CCL11 is associated with lowered neurogenesis and neurodegenerative processes and, as a consequence, increased CCL11 increases risk towards Alzheimer's Disease. Polymorphisms in the CCL11 gene are associated with stroke. Increased CCL11 also plays a role in neuroinflammatory disease including multiple sclerosis. In animal models, neutralization of CCL11 may protect against nigrostriatal neurodegeneration. Increased production of CCL11 may be attenuated by glucocorticoids, minocycline, resveratrol and anti-CCL11 antibodies.Conclusion: Increased CCL11 production during inflammatory conditions may play a role in human disease including age-related cognitive decline, schizophrenia, mood disorders and neurodegenerative disorders. Increased CCL11 production is a new drug target in the treatment and prevention of those disorders.

The effectiveness of immunotherapy for cervical adenocarcinoma (CA) has not been demonstrated yet. It may be possible for us to use programmed cell death 1 (PD-1), programmed cell death-ligand 1 (PD-L1), and CD8 as biomarkers of response to immune therapy in CA patients. In the present study, we aimed to investigate whether the expression levels of PD-1, PD-L1, and CD8 can predict the prognosis of CA patients and their response to ICI therapy. The levels of the PD-1, PD-L1, and CD8 proteins were analyzed by immunohistochemical analysis from formalin-fixed, paraffin-embedded tumor samples. The correlation between the expression levels and patient prognosis was analyzed by the Kaplan–Meier method and univariate and multivariate Cox proportional hazard regression model. We observed a significant inverse-correlation between the PD-1 and CD8 expression (p=0.001, chi square test). We also found a significant inverse-correlation between the PD-L1 and CD8 expression (p=0.027). The overall survival was significantly worse in patients with positive PD-1 expression (p=0.027). Similarly, the progression-free survival was also worse (p=0.087). Our results demonstrate that a high level of PD-1 expression is associated with a poor prognosis in CA patients. Further research is necessary to identify the molecular mechanisms that mediate this association.

Knowledge of the spatio-temporal occurrence of avalanche activity is critical for avalanche forecasting and hazard mapping. We present a near-real time automatic avalanche monitoring system that outputs detected avalanche polygons within roughly 10 min after Sentinel- 1 SAR data download. Our avalanche detection algorithm has an average probability of detection of 67.2 % with a false alarm rate averaging 45.9, with maximum POD's over 85 % and minimum FAR's of 24.9 % compared to manual detection of avalanches. The high variability in performance stems from the dynamic nature of snow in the Sentinel-1 data. After tuning parameters of the detection algorithm, we processed five years of Sentinel-1 images acquired over a 150 x 100 km large area in Northern Norway, with the best setup. Compared to a dataset of field-observed avalanches, 77.3 % were manually detectable. Using these manual detections as benchmark, the avalanche detection algorithm achieved an accuracy of 79 % with high POD's in cases of medium to large wet snow avalanches. For the first time, we can present a dataset of spatiotemporal avalanche activity over several winters from a large region. This unique dataset allows for research into the relationship between avalanche activity and triggering meteorological factors, mapping of avalanche prone areas and near-real time avalanche activity monitoring to assist public avalanche forecasting. Currently, the Norwegian Avalanche Warning Service is using our processing system for pre-operational use in three regions in Norway.

The maintenance of high quality standards for prolonging shelf life of fruit and maintaining sensory and nutritional quality is a priority the horticultural products. The aim of this work was to test the effectiveness of a single treatment of edible coating based on Aloe arborescens and a combined treatment of 1-Methylcycyclopropene and edible coating to prolong the shelf-life of "Settembrina" white flesh peach fruit. White flesh peach fruit were harvested at the commercial ripening stage and treated with edible coating (EC) or 1-MCP +EC and stored for 28 days at 1°C. After 7, 14, 21 and 28 days fruits were removed from cold storage, transferred at 20°C and then analyzed immediately (cold out) and after 6 days (shelf life) to evaluate the combined effect of cold storage and room temperature. Weight loss, physical, chemical and sensory parameters were measured. Fruit treated with EC and 1-MCP +EC kept their marketing values better than CTR after 14 days of storage and 6 days of simulated shelf life, in terms of flesh firmness, total soluble solids and titratable acidity as well as sensory parameters. After 21 days of storage, all treatments showed a deterioration of the quality parameters. The single and combined application of Aloe-based coating (with 1-MCP) slowed down the maturation processes of the fruit, limited the weight loss and preserved its organoleptic characteristics.

Interaction of an electromagnetic field with matter in a laser cavity without the assumption of a fixed direction of the transverse electric field, described by the two-level Maxwell-Bloch equations, is studied. By using a perturbative nonlinear analysis, performed near the laser threshold, we report on the derivation of the laser (3+1)D vectorial complex cubic-quintic complex Ginzburg-Landau equation. Furthermore, we study the modulational instability of the plane waves both theoretically using the linear stability analysis, and numerically, using direct simulations via the split-step Fourier method. The linear theory predicts instability for any amplitude of the primary waves. Our numerical simulations confirm the theoretical predictions of the linear theory as well as the threshold of the amplitude of perturbations. The system understudy shows a deep dependence on the laser cavity parameters, for which there appear wave patterns in accordance with the predictions from the gain spectrum.

Aim: The purpose of this examination is determining predictors to oral health behaviors predict in Iranian students in district 1 Tehran based on the health belief model with added commitment to plan construct. Methods: This cross-sectional study were randomly selected conducted on 351 eligible four grade female students in the first district of Tehran, Iran in 2017. The random Multi‑stage random cluster sampling method was used to recruit students. The inclusion criteria were being graded, four female students (aged 9-11 years), or education at the fourth grade of one of the elementary schools studied in the first district of Tehran and, The health of the student from a physical and psychological of view. Logistic regression analysis was used to identify the variables that predict oral health behaviors. To assess the predictors of oral health behaviors, all the expanded Health Belief Model constructs with the construct of “Commitment to Plan of Action” from “Health Promotion Model were examined as risk factors to see if they influence on the probability of brushing behavior and dental floss behavior occurrence and were interpreted through odds ratio (OR). SPSS version 19 was used to analyze the data. Results: Totally 308 four grade female students with mean age of 9.32 ± 0.81 years old took part in the study. The total 31.8% of the students reported that they were brushing behavior less than twice a day and 55.2% students claimed, use of dental floss behavior once a week or less than once a day. The results indicated that perceived self-efficacy (OR=1.46, 95% CI=0.57-3.78, P<0.001), Commitment to plan (OR=1.13, 95% CI=1.04-1.23, P<0.001) and Cues to action (OR=1.42, 95% CI=1.14–1.76, P=0.002) were the significant predicting variables which is the key factor of brushing twice a day, and use of dental floss once a day or more (OR=1.02, 95% CI=0.23-3.53, P=0.003). Conclusion: This study has shown the effectiveness of the health belief model with added commitment to plan construct to predict oral health behavior in female students. So, it seems that the model as a framework for designing training programs to improve students to improve oral health behavior can be used.

Programmed cell death protein 1 (PD-1) is a biomarker on the surface of cells that has a role in promoting self-tolerance by suppressing the inflammatory activity of T cells. In this work, one peptide of PD-1 was used as the template in molecular imprinting. The magnetic peptide-imprinted poly(ethylene-co-vinyl alcohol) composite nanoparticles (MPIP NPs) were characterized by dynamic light scattering (DLS), high-performance liquid chromatography (HPLC), Brunauer-Emmett-Teller (BET) analysis and superconducting quantum interference device (SQUID) analysis. Natural killer-92 (NK-92) cells were added to these composite nanoparticles and then incubated with human hepatoma (HepG2) cells. The viability and apoptosis pathway of HepG2 were then studied using cell counting kit-8 (CCK8) and the quantitative real-time polymerase chain reaction (qRT-PCR), respectively. These nanoparticles were found significantly enhance the activity of natural killer cells toward HepG2 cells by increasing expression of NK-kB, caspase 8 and especially caspase 3.

The inhibition of heat shock protein 90 (Hsp90) a molecular chaperone for multiple oncogenic client proteins is considered as a promising approach to overcome radioresistance. Since most Hsp90 inhibitors activate HSF-1 that induces the transcription of cytoprotective and tumor-promoting stress proteins such as Hsp70 and Hsp27, a combined approach consisting of HSF-1 knockdown (k.d.) and Hsp90 inhibition was investigated. A specific HSF-1 k.d. was achieved in H1339 lung cancer cells using RNAi-Ready pSIRENRetroQ vectors with puromycin resistance. The Hsp90 inhibitor NVP-AUY922 was evaluated at low concentrations - ranging from 1-10nM - in control and HSF-1 k.d. cells. Protein expression (i.e., Hsp27/Hsp70, HSF-1, pHSF-1) and transcriptional activity was assessed by Western blot analysis and luciferase assays and radiosensitivity was measured by proliferation, apoptosis (Annexin V, active caspase 3), clonogenic cell survival, alkaline comet, γH2AX, 53BP1 and Rad51 foci assays. The k.d. of HSF-1 resulted in a significant reduction of basal and NVP-AUY922-induced Hsp70/Hsp27 expression levels. A combined approach consisting of HSF-1 k.d. and low concentrations of the Hsp90 inhibitor NVP-AUY922 potentiates radiosensitization which involves an impaired homologous recombination mediated by Rad51. Our findings are key for clinical applications of Hsp90 inhibitors with respect to adverse hepatotoxic effects.

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

A balanced chromosomal translocation disrupting DISC1 (Disrupted in Schizophrenia 1) gene has been linked to psychiatric diseases, such as major depression, bipolar disorder and schizophrenia. Since the discovery of this translocation, many studies have focused on understating the role of the truncated isoform of DISC1, hypothesizing that the gain of function of this protein could be behind the neurobiology of mental conditions, but not so many studies have focused in the mechanisms impaired due to its loss of function. For that reason, we perform an analysis on the cellular proteome of primary neurons in which DISC1 was knocked down with the goal of identifying relevant pathways directly affected by DISC1 loss of function. Using an unbiased proteomic approach, we found that the expression of 31 proteins related to neurodevelopment (e.g. CRMP-2, stathmin) and synaptic function (e.g. MUNC-18, NCS-1) is regulated by DISC1 in primary mouse neurons. Hence, this study reinforces the idea that DISC1 is a unifying regulator of both neurodevelopment and synaptic function, thereby providing a link between these two key anatomical and cellular circuitries.

The rapid urbanization that takes place in developing regions such as Sub-Saharan Africa is associated with a large range of environmental and social issues. In this context, remote sensing is essential to provide accurate and up-to-date spatial information to support risk assessment and decision making. However, mapping urban areas remains a challenge because of their heterogeneity, especially in developing regions where the highest rates of misclassification are observed. Nevertheless, urban areas located in arid climates --- which are among the most vulnerables to anthropogenic impacts, suffer from the spectral confusion occurring between built-up and bare soil areas when using optical imagery. Today, the increasing availability of satellite imagery from multiple sensors allow to tackle the aforementioned issues by combining optical data with Synthetic Aperture Radar (SAR). In this paper, we assess the complementarity of the Landsat 8 and Sentinel-1 sensors to map built-up areas in twelve Sub-Saharan African urban areas, using a pixel-level supervised classification based on the Random Forest classifier. We make use of textural information extracted from SAR backscattering data in order to reduce the speckle noise and to introduce contextual information at the pixel level. Results suggest that combining both optical and SAR features consistently improves classification performances, mainly by enhancing the differentiation between built-up and bare lands. However, the fusion was less beneficial in mountainous case studies, suggesting that including features derived from a Digital Elevation Model (DEM) could improve the reliability of the proposed approach. As suggested by previous studies, combining features computed from both VV and VH polarizations consistently led to better classification performances. On the contrary, introducing textures computed from different spatial scales did not improve the classification performances.

Lung adenocarcinoma with EGFR-TKI (epidermal growth factor receptor-tyrosine kinase inhibitor) resistance was reported to harbor higher ability of invasion and migration than those sensitive to EGFR-TKI, but the function of MMPs (matrix metalloproteinases) has not been explored in EGFR-TKI resistant lung adenocarcinoma. In this study, the correlation between immunohistochemical status of MMP-1 and clinicopathological factors were analyzed in 89 lung adenocarcinoma. We performed microarray, migration assay and invasion assay using EGFR-TKI sensitive cell lines and EGFR-TKI resistant cell lines. To clarify the mechanism of MMP-1 induction, we treated lung adenocarcinoma cells with EGF and rapamycin, performed phosphorylation antibody array and analyzed the correlation between MMP-1 expression and EGFR or mTOR (mammalian target of rapamycin) pathway. As a result, we firstly demonstrated that MMP-1 played an important role in migration and invasion abilities of EGFR-TKI resistant lung adenocarcinoma, and that mTOR pathway could be associated with an induction of MMP-1. We demonstrated the significant positive correlation between MMP-1 status in lung adenocarcinoma cells and the history of smoking, and the subtype of invasive mucinous adenocarcinoma. In conclusion, This study provides insights into the development of a possible alternative therapy manipulating MMP-1 and mTOR signaling pathway in EGFR-TKI resistant lung adenocarcinoma.

Many studies, which try to analyze conditions for debris flow development, ignore the type of initiation. Therefore this paper deals with the following questions: What type of hydro-mechanical triggering mechanisms for debris flows can we distinguish in upstream channels of debris flow prone gullies? Which are the main parameters controlling the type and temporal sequence of these triggering processes and what is their influence on the meteorological thresholds for debris flow initiation? A series of laboratory experiments were carried out in a flume, 8 m long and with a width of 0.3 m. to detect the conditions for different types of triggering mechanisms. The flume experiments show a sequence of hydrological processes triggering debris flows, namely erosion and transport by intensive overland flow and by infiltrating water causing failure of channel bed material. On the basis of these experiments an integrated hydro-mechanical model was developed, which describes Hortonian and Saturation overland flow, maximum sediment transport, through flow and failure of bed material. The model was calibrated and validated using process indicator values measured during the experiments in the flume. Virtual model simulations, carried out in a schematic hypothetical source area of a catchment show that slope angle and hydraulic conductivity of the bed material determine the type and sequence of these triggering processes. It was also clearly demonstrated that the type of hydrological triggering process and the influencing geometrical and hydro-mechanical parameters may have a great influence on rainfall intensity-duration threshold curves for the start of debris flows.

Keywords: Marine Coasts; Protected Areas; Defense and Conservation; Asbestos Cement Materials; Wastes; Contamination; Human Health Risk; Medical Geology.

The negative energy solutions of the Klein-Gordon and Dirac equations have been used to define the antiparticle with the positive energy from the Feynman - Stueckelberg interpretation in the standard model based on the 4-D Minkowski space with the relative time. The negative energy solutions of the Klein-Gordon and Dirac equations are used to define the antiparticles with the negative energy in the present 3-D quantized space model. Note that all the present results are based on the 4-D Euclidean space with the absolute time (t) and relative time (t_l). Then the particle with the positive energy and antiparticle with the negative energy have the 4-D P₄ = TCP = T_cP symmetry. The continuity equations are derived from the Klein-Gordon, Dirac and Schrodinger equations. The Klein-Gordon and Schrodinger equations with the potential barriers are solved. The Klein paradox is explained by using the pair production of the electron with the positive energy and positron with the negative energy under the P₄ = _TcP symmetry, The effective velocity ( c_eff=√2 " c " ) and effective energy ("Etl =" √2 E ) along the relative time axis (ctl) give the relative time momentum of "p_tl"=E_tl/c_eff =(√2 E)/(√2 c)=E/c=p_t=p_x. This indicates that the photons with the energy of E have the constant photon velocity of c and the constant photon momentum of "ptl"=E_tl/c_eff =(√2 E)/(√2 c)=E/c=p_t=p_x. For the negative energy particles, the space momentum directions are opposite to the particle velocity directions because the energy is negative. And the matter collapse to the photons at the very high particle velocity is discussed from the length expansion. It is, for the first time, proposed that the gamma ray burst is originated from the matter collapse to the photons near the black hole. Also, the wave function collapse is explained from the length expansion. The wave function collapse takes place when the measurement makes the particle velocity to be zero. It is concluded that the negative energy solutions of the Klein-Gordon and Dirac equations support the existence of the partner antimatter universe with the negative energy and negative time direction. Our matter universe has the positive energy and the positive time direction.

This study aimed to evaluate the impact of the built environment (i.e., walk, transit, and bike scores) on the location and transportation or “alternative transportation” credit (LTc1) in Leadership in Energy and Environmental Design for Existing Buildings version 4 (LEED-EB-v4) Platinum (n1 = 24), Gold (n2 = 112), Silver (n3 = 46), and Certified (n4 = 34) office buildings in the USA. Spearman’s test was used to estimate the correlation between built environment scores and LTc1 scores for each certification level. The Wilcoxon–Mann–Whitney test was used to estimate pairwise comparison between unpaired Platinum, Gold, Silver, and Certified groups. The Platinum, Gold, and Silver certification levels showed positive and significant correlations between the built environment and LTc1 (0.44 ≤ r ≤ 0.74, p ≤ 0.0312). By contrast, Certified certification levels showed a non-significant correlation (0.18 ≤ r ≤ 0.33, p ≥ 0.0579). Pairwise comparison showed that Platinum and Gold groups outperformed Certified groups in terms of built environment and LTc1 scores (Cliff’s δ ≥ 0.37, p ≤ 0.0099). Thus, for LEED-EBv4-certified projects located in downtown areas, LTc1 can be seen as a significant lever to achieve high levels of LEED certification.

For polymicrobial infections, AtbFinder utilizes a novel paradigm of the population response to antibiotics, enabling bacterial growth in the form of a mixed microbial community and selecting the antibiotics targeting not only the principal pathogen, but also those bacteria that support their growth. TGV medium allowed culturing a more diverse set of bacteria from polymicrobial biospecimens, compared with that achieved with the standard media and enabled, already within 4h, accurate selection of the antibiotics that completely eliminated all cultivatable bacteria from clinical samples. In conclusion, AtbFinder system may be a valuable tool in improving antibiotic selection, enabling targeted empirical therapy and accurate antibiotic replacement, which is especially important in high-risk patients.

Cartilage regeneration requires a balance of anabolic and catabolic processes. This study examined the susceptibility of fibromodulin (FMOD) and lumican (LUM) to degradation by MMP-13, ADAMTS-4 and ADAMTS-5, the three major degradative proteinases in articular cartilage in osteoarthritis (OA). Immunolocalisation of FMOD and LUM in foot sections of developmental cartilages demonstrated prominent localisations in metatarsal and phalangeal foetal rudiment cartilages and growth plate. An MMP-13 neoepitope antibody (TsYG11) demonstrated localisation of MMP-13 cleaved FMOD in the hypertrophic chondrocytes of the metatarsal growth plate. FMOD was more prominently localised in the superficial cartilage of normal and fibrillated zones in OA cartilage, TsYG11 positive FMOD was located deeper in the cartilage samples. Ab TsYG11 also identified FMOD fragmentation in Western blots of extracts of normal and fibrillated cartilage and total knee replacement OA cartilage. The C-terminal anti-FMOD used in this study (PR-184) failed to identify FMOD fragmentation due to C terminal processing, an equivalent Ab to the C-terminus of LUM (pAb PR-353) identified 3 prominent LUM fragments in OA human knee cartilages. In-vitro digestion of human knee cartilage with MMP-13, ADAMTS-4 and ADAMTS-5 generated equivalently sized FMOD fragments of 54, 45 and 32kDa to those in blots of OA cartilage, LUM was not less susceptible to fragmention in in-vitro digestions however Ab PR-353 detected N-terminally processed LUM fragments of 39, 38 and 22 kDa in 65-80 year old OA knee cartilage. FMOD and LUM were differentially processed during in-vitro digestions with MMP-13, ADAMTS-4 and ADAMTS-5 with FMOD susceptible to degradation by MMP-13, ADAMTS-4 and to a lesser extent ADAMTS-5 however LUM was less susceptible to fragmentation. FMOD was processed by MMP-13 in metatarsal and phalangeal foetal rudiment developmental cartilages and growth plate indicating a role in skeletogenesis.

Background: Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality in both sexes globally. This is not unconnected with the heterogeneity and plasticity of CRC stem cells (CRC-SCs) which stealthily exploit niche-related and (epi)genetic factors to facilitate metastasis, chemoresistance, tumor recurrence, and disease progression. Despite accumulating evidence of the role of dysregulated microRNAs in malignancies, the therapeutic efficacy of pharmacological-targeting of CRC-SC-associated microRNAs is relatively under-explored. Experimental approach: In this present study, we employed relatively new bioinformatics approaches, analyses of microarray data, western blot, RT-PCR, and functional assays to show that hsa-miR-324-5p expression is significantly suppressed in CRC cells, and inversely correlates with the aberrant expression of SOD2. Results: This converse hsa-miR-324-5p/SOD2 relationship is associated with enhanced oncogenicity, which is effectively inhibited by 4-AAQB as evidenced by inhibited cell viability and proliferation, as well as, attenuated migration, invasion and clonogenicity in 4-AAQB-treated DLD1 and HCT116 cells. We also showed that 4-AAQB-induced re-expression of hsa-miR-324-5p, akin to short-interfering RNA reduced SOD2 expression, correlates with the concurrent down-regulation of SOD2, N-cadherin, vimentin, c-Myc, and BcL-xL2, with concomitant up-regulation of E-cadherin and BAX2 proteins. Enhanced expression of hsa-miR-324-5p in the CRC cells suppressed their tumorigenicity in vitro and in vivo. Additionally, 4-AAQB synergistically potentiates FOLFOX anticancer effect by eliciting the re-expression of SOD2-suppressed hsa-miR-324 and inhibiting SOD2-mediated tumorigenicity. Conclusion: Our findings highlight the pre-clinical anti-CSC efficacy of 4-AAQB, with or without FOLFOX in CRC, and suggest a potential novel therapeutic strategy for CRC patients.

The rationalization of single molecule magnets’ (SMMs) magnetic properties by quantum mechanical approaches represents a major task in the field of the Molecular Magnetism. The fundamental interpretative key of molecular magnetism is the phenomenological Spin Hamiltonian and the understanding of the role of its different terms by electronic structure calculations is expected to steer the rational design of new and more performing SMMs. This paper deals with the ab initio calculation of isotropic and anisotropic exchange contributions in the Fe(III) dimer [Fe₂(OCH₃)₂(dbm)₄]. This system represents the building block of one of the most studied Single Molecule Magnets ([Fe₄RC(CH₂O)₃)₂(dpm)₆] where R can be an aliphatic chain or a phenyl group just to name the most common functionalization groups) and its relatively reduced size allows the use of a high computational level of theory. Calculations were performed using CASSCF and NEVPT2 approaches on the X-ray geometry as assessment of the computational protocol, which has then be used to evinced the importance of the outer coordination shell nature through organic ligand modelization. Magneto-structural correlations as function of internal degrees of freedom for isotropic and anisotropic exchange contributions are also presented, outlining for the first time the extremely rapidly changing nature of the anisotropic exchange coupling.

Overweight/obesity and cardiovascular diseases are associated with high rates of mobility and mortality. We investigated inflammatory lesions and ionic transporters in the left ventricle of male rats chronically fed a high-fat diet (HL). They developed moderate overweight with early expansion of visceral adiposity. The inflammatory markers interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-), Na+-transporting ATPases, sarco-endoplasmic reticulum Ca2+-ATPase (SERCA2a), and the abundance of Angiotensin II receptors were studied together with lipid and glycemic profiles, and the left ventricle echocardiographic parameters fractional shortening (FS) and ejection fraction (EF). HL rats doubled IL-6 and TNF-, which returned to normal levels when signaling coupled to Angiotensin II type 2 receptors (AT2R) was supraregulated by Ang-(3–4) administration. The decreased glucose tolerance was accompanied by significantly reduced plasma triglycerides due to intense hepatic steatosis (Crisóstomo et al. Metabolism Open. 2022, 14, 100176). AT2R (and AT1R) abundance did not change. (Na++K+)ATPase and ouabain-resistant Na+-ATPase were downregulated and upregulated, respectively, normalized with Ang-(3–4). SERCA2a lost its most critical regulatory property, inhibition by excess substrate. The ultrasound showed no changes in FS and EF. We conclude that very moderate overweight can cause silent initial molecular tissue damage in heart, which can evolve to cause systolic dysfunction.

A biobased and conductive ink composed of elastomeric vinyl acetate-vinyl laurate copolymer (PVAc-VL) and carbon nanofibers (CNF) has been developed to create stretchable and flexible tactile devices (taxels) for robotics and prosthetics applications. The ink can be sprayed onto elastomeric surfaces (Ecoflex) to produce an electronic skin for applications such as the iCub robot and the Hannes prosthetic hand. Electron microscopy analysis confirms good dispersion of the CNF within the ink, and the ink remains conductive even after 150 mechanical cycles of stretching up to 25% and unloading. Compression tests up to 50% deformation show a small influence on the coating, and stretching cycles allow for rearrangement of the CNF, improving the electrical behaviour due to mechanical energy dissipation. The measured electrical performance exhibits a twofold increase in the R/R0 ratio, succeeded by a rapid decline (recovery), and eventually stabilizes near the initial value, indicating enhanced electronic performance.

The quest for surgical advancements regarding the enhancement of the submental and cervicofacial regions has witnessed a remarkable upsurge in recent years. Informed patients are actively seeking sophisticated plastic surgery techniques to achieve comprehensive rejuvenation in these specific areas. Common complaints expressed by these patients include sagging of the jawline, the emergence of deep perioral wrinkles, and the formation of "marionette lines" within the lower third of the face. Furthermore, the manifestation of age-related signs, including neck laxity, submental adipose accumulation, "witch's chin" deformity, and weakened platysma musculature, are common within this anatomical region. This literature review aims to summarize the recent technical improvements, historical evolution, indications, postoperative care, and challenges for facial rejuvenation of the lower third of the face and neck. Lastly, the application of minimally invasive procedures as part of a comprehensive approach to an aging face will also be discussed.

Retinal pigment epithelium (RPE) replacement therapy is evolving as a feasible approach to treat age-related macular degeneration (AMD). In majority of the preclinical studies, RPE cells are transplanted as cell suspension into immunosuppressed animal eyes and transplant effects were monitored only short-term. We investigated long-term effects of human iPSC derived RPE transplants in immunodeficient Royal College of Surgeons (RCS) rat model, in which RPE dysfunction lead to photoreceptor degeneration. iPSC-RPE cultured as polarized monolayer on nanoengineered ultrathin parylene C scaffold was transplanted into the subretinal space of 28-day old immunodeficient RCS rat pups and evaluated after 1, 4 and 11 months. Assessment at early time points showed good iPSC-RPE survival. The transplants remained as a monolayer, expressed RPE specific markers, performed phagocytic function and contributed to vision preservation. At 11-month post-implantation, RPE survival was observed only in 50% of the eyes that were concomitant with vision preservation. Loss of RPE monolayer characteristics at the 11month time point was associated with peri-membrane fibrosis, immune reaction through activation of macrophages (CD 68 expression) and transition of cell fate (expression of mesenchymal markers). The overall study outcome supports the therapeutic potential of RPE grafts despite the loss of some transplant benefits during long-term observations.

Influenza B virus (IBV) is a major respiratory pathogen of humans, particularly in the elderly and children and vaccines are the most effective way to control it. In previous work, incorporation of two mutations (E580G, S660A) along with the addition of a HA epitope tag in the PB1 segment of B/Brisbane/60/2008 (B/Bris) resulted in an attenuated strain that was safe and effective as a live attenuated vaccine. A third attempted mutation (K391E) in PB1 was not always stable. Interestingly, viruses that maintained the K391E mutation were associated with the mutation E48K. To explore the contribution of the E48K mutation for stability of the K391E mutation, a vaccine candidate was generated by inserting both mutations along with attenuating mutations E580G and S660A in PB1 of B/Bris (B/Bris PB1att 4M). Serial passage of the B/Bris PB1att 4M vaccine candidate in eggs and MDCK indicated high stability. In silico structural analysis revealed a potential interaction between amino acids at positions 48 and 391. In mice, B/Bris PB1att 4M was safe and provided complete protection against homologous challenge. These results confirm the compensatory effect of mutation E48K to stabilize the K391E mutation, resulting in a safer, yet still protective, IBV LAIV vaccine.

There is increased concern that the quality, generalizability, and reproducibility of biomedical research can be influenced by the sex of animals used. We studied the differences between male and female mice in response to invasive pulmonary mucormycosis including susceptibility to infection, host immune reaction, and responses to antifungal therapy. We used diabetic ketoacidotic (DKA) or neutropenic mice infected with either Rhizopus delemar or Mucor circinelloides. The only difference detected was that when DKA mice were infected with M. circinelloides, female mice were more resistant to infection than male mice (median survival time of 5 vs. 2 days for female and male mice, respectively). However, a 100% lethality was detected among infected animals of both sexes. Treatment with either liposomal amphotericin B (L-AMB) or posaconazole (POSA) protected mice from infection and eliminated the difference seen between infected but untreated female and male mice. Treatment with L-AMB consistently outperformed POSA in prolonging survival and reducing tissue fungal burden of DKA and neutropenic mice infected with R. delemar or M. circinelloides, in both mouse sexes. Although little difference was detected in cytokine levels among both sexes, mucormycosis infection in the DKA mouse model induced more inflammatory cytokines/chemokines involved in neutrophil (CXCL1) and macrophage (CXCL2) recruitment vs. uninfected mice. As expected, this inflammatory response was reduced in the neutropenic mouse model. Our studies show that there are few differences between female and male DKA or neutropenic mice infected with mucormycosis with no effect on the outcome of treatment or host immune response.

For decades, fossil fuels have been the backbone of reliable energy systems, offering unmatched energy density and flexibility. However, as the world shifts toward renewable energy, overcoming the limitations of intermittent power sources requires a bold reimagining of energy storage and integration. Power-to-X (PtX) technologies, which convert excess renewable electricity into storable energy carriers, offer a promising solution for long-term energy storage and sector coupling. Recent advancements in machine learning (ML) have revolutionized PtX systems by enhancing efficiency, scalability, and sustainability. This review provides a detailed analysis of how ML techniques, such as deep reinforcement learning, data-driven optimization, and predictive diagnostics, are driving innovation in Power-to-Gas, Power-to-Liquid, and Power-to-Heat systems. While ML applications have shown great potential in optimizing operational decisions and managing uncertainties in renewable energy integration, challenges such as data quality, real-time processing, and scalability remain. Addressing these gaps presents important future research opportunities. These advancements are critical to decarbonizing hard-to-electrify sectors such as heavy industry, transportation, and aviation, aligning with global sustainability goals.

Study of differential equation theory has come a long way with applications in the various fields. In 1961, Zygmund and Calderón introduced the notion of derivatives on metric Lr which proved to be better in applications than approximate derivatives. But most of the studies involved are on fuzzy set theory, so it seems likely that intuitionistic fuzzy Lr - norm - based derivatives deserve study. In the study, the fuzzy derivative is extended to intuitionistic fuzzy derivatives with respect.to Lr - norm - based derivatives using intuitionistic fuzzy number valued functions. The efficacy of the proposed method is established by proving the associated theorems along with numerical examples. Further, the Cauchy problem is also studied with respect to intuitionistic fuzzy setting.

The exploring comprehensive review of cutting-edge techniques for securing cloud-stored data and managing sensitive information in the context of smart cities through the application of Ciphertext-Policy Attribute-Based Encryption (CP-ABE). It highlights the innovative integration of blockchain technology with CP-ABE, which introduces a decentralized and tamper-resistant key management system, thereby enhancing the overall security framework in cloud environments where data sharing is prevalent. Introducing an online/offline multi-authority CP-ABE scheme, characterized by hidden policies, offers significant advancements in protecting user attributes and access structures, ensuring that sensitive information remains confidential even during encryption and decryption processes. This dual approach not only fortifies security but also optimizes the efficiency of data-sharing mechanisms. Furthermore, the paper delves into implementing hidden sensitive policies and keyword search techniques within smart city infrastructures, which are designed to facilitate secure and efficient data retrieval. These techniques ensure that while data remains accessible to authorized users, privacy is rigorously maintained. Collectively, these approaches represent significant strides in bolstering the security and confidentiality of data in both cloud-based and smart city applications, addressing the growing demand for robust and efficient data management solutions in increasingly interconnected environments.

Thermodynamics of protein-ligand interactions seems to be associated to a narrow range of Gibbs Free Energy. As a consequence, a linear enthalpy-entropy relationship showing an apparent Enthalpy-Entropy compensation (EEC) is frequently observed associated to the study of protein-ligand interactions. This EEC affects negatively the design and discovery of new and more efficient drugs capable of binding protein-targets with a higher affinity. Originally attributed to experimental errors, compensation between H and TS values is a real observable fact, although its molecular origin has remained obscure and controversial. Herein we show the results of a data search of G values of 2558 protein-ligand interactions and 3025 “in vivo” ligand concentrations from the Protein Data Bank bind Database and the Metabolome Data Base (2020). These results, together with the mechano-statistical interpretation of the thermodynamic properties leads to the conclusion that the EEC has no basis in statistical thermodynamics. It can be plausibly explained as a consequence of the narrow range of G associated to protein-ligand interactions. The Gaussian distribution of the G values matches very well with that of ligands. These results suggest the hypothesis that the set of G values for the protein-ligand interactions is the result of the evolution of proteins. The conformation versatility of present proteins and the exchange of thousands (even millions) of minute amounts of energy with the environment may have functioned as a homeostatic mechanism to make G of proteins adaptive to changes in availability of ligands, and therefore achieve the maximum regulatory capacity of the protein function. Finally, a plausible strategy to avoid the EEC is suggested.

Nowadays, one of the greatest challenges in Data Meshes revolves around detecting and creating Data Domains and Data Products for providing the ability to adapt easily and quickly to changing business needs. This requires a disciplined approach to identify, differentiate and prioritize distinct data sources according to their content and diversity. The current paper tackles this highly com-plicated issue and suggests a standardized approach that integrates the concept of Data Blueprints with Data Meshes. In essence, a novel standardization framework is proposed that creates Data Products using a metadata semantic enrichment mechanism, the latter also offering Data Domain readiness and alignment. The approach is demonstrated using real-world data produced by mul-tiple sources in a poultry meat production factory. A set of functional attributes is used to compare qualitatively the proposed approach against existing data structures utilized in storage architectures with quite promising results. Finally, experimentation with different scenarios varying in data product complexity and granularity suggests successful performance.

Entrepreneurial activities in economic and social domains are considered one of the conditional pillars for successful transformation of resource-rich countries to sustainable, knowledge-based and diversified economies. However, there is no, and cannot be, a single recipe for such a transformation as every country or region needs to develop its own strategy, policy toolbox and implementation plan depending on its historical and present socio-economic make up and trajectory. This paper advances the qualitative findings of a previously published work to delve deeper into the complexities of entrepreneurship within resource-based economies, with a particular focus on Qatar. Employing a mixed methodology that blends explanatory and quantitative analysis, this paper aims to validate and refine the entrepreneurship framework proposed previously, ensuring its relevance and adaptability to Qatar's unique economic and cultural context, and its extendibility to similar resource-rich country settings. It systematically focuses on discovering various social, economic, and environmental dimensions critical to fostering entrepreneurship in resource-rich countries. These include examining government policies, cultural and social factors, financial support mechanisms, innovation ecosystem, technology adaptation, and digitization. A primary component of this study is the methodological approach, which includes collecting and analyzing quantitative data through a survey developed based on previous findings on qualitative explorations. This approach allows for an objective assessment of the effectiveness of the proposed recommendations. The paper presents a set of detailed recommendations aimed at various stakeholders, including government bodies, supporting agencies, and entrepreneurs themselves. These recommendations encompass integrating entrepreneurship education into academic curricula, increasing easy access to business and market information, simplifying, unifying and streamlining policies and procedures, and adapting them into the legal system. Other important and unique recommendations include establishing a country-wide entrepreneurship free-zone (Ent-Q) and facilitating its operations though an online digital platform (Ryadah), allocating certain percentage of governmental ministries’, agencies’ as well as large corporations’ budgets into innovative small business development programs and preferred purchasing from small business. These initiatives are validated to become effective tools and avenues to create a conducive entrepreneurial environment, facilitating transformation into a diversified, knowledge-based and sustainable economy. The expected outcomes of implementing these recommendations include an increase in the efficiency of entrepreneurship-related policymaking, a rise in the number, quality and impact of entrepreneurs, and the sustained diversification of the economy into non-oil/gas sectors and actors. In conclusion, this paper provides a comprehensive set of strategies and recommendations expected to significantly contribute to the nurturing and growth of entrepreneurship in resource-based economies.

The limits for recording weak signals for electrochemical seismic sensors are determined by their self-noise. At the same time, the noise nature is complex and not fully understood. In this work, for the first time, in addition to the frequency dependences of the noise amplitude, the difference in the phases of the noise currents of the cathodes of an electrochemical sensor has been studied. It has been established that at low frequencies the cathode currents change in an-tiphase. As the frequency increases, the phase difference becomes random. At the same time, the frequency at which the phase difference changes depend on the interelectrode distance; the clos-er the electrodes are located to each other, the greater it is. Physically, this effect is explained by the transition from noise caused by the integral flow of the working fluid to noise associated with vortex flows, the size of which depends on frequency. Thus, a new way of studying noise makes it possible to identify its physical nature and develop new methods of reduction.

This research emphasizes a meta-heuristic Modified Ant Lion Optimizer (MALO) optimization approach for simultaneous utilization of DSTATCOM devices and distributed Photovoltaic (PV) sources with network reconfiguration in a radial power distribution scheme. In a radial power distribution network with network reconfiguration majority of the research is based on Constant Power model analysis. However, it is noticed that load models have a substantial impact on the distributed PV sources and the D-STATCOM device's optimal size and position. The effect of the Constant Power (CP) and Polynomial (ZIP) with load growth load models for the simultaneous insertion of distributed PV sources and DSTATCOM devices with network reconfiguration examined in this research work for power system planning. The penetration levels of distributed PV sources considered for the investigation are 25%, 50%, 75%, and 100%. The principal objective of this research is to reduce network total power losses, enhance the voltage magnitude profile at all buses, and reduce the overall operating cost while adhering to equality and inequality constraints. The proposed algorithm verified on 118-node test systems. The investigation is carried out for planning network upgradation to a High Voltage Distribution System(HVDS) on 317 nodes in the rural Bangalore Electricity Supply Company Limited(BESCOM) radial distribution scheme. Simulated results obtained by this method are validated with the BAT algorithm and available techniques in the literature.

ShK domain-containing proteins are peptides found in different parasitic and venomous organisms. From a previous transcriptomic dataset from Bursaphelenchus xylophilus, a plant-endoparasitic nematode that infects forest tree species, we identified 96 transcripts potentially as ShK domain-containing proteins with unknown function in the nematode genome. This study aimed to characterize and explore the functional role of genes encoding ShK domain-containing proteins in B. xylophilus biology. We selected and functionally analyzed nine candidate genes specific from B. xylophilus. In situ hybridization revealed expression of one B. xylophilus ShK in the pharyngeal gland cells, suggesting their delivery into host cells. Most of the transcripts are highly expressed during infection and showed a significant upregulation in response to peroxide products compared to the nematode catalase enzymes. We reported for the first time, the potential involvement of ShK domain genes in oxidative stress, suggesting that these proteins may have an important role protecting or modulating the reactive oxygen species (ROS) activity of the host plant during parasitism.

In this paper, existence and stability results of non-local integro-differential equation with Hilfer derivative of order ω∈(1,2) have been investigated. In this derivative is applied in RLC circuit equation of various fractional order. To proposed problem the existence solutions are derived using Schaefer’s fixed point theorem and the Banach contraction principle is using for uniqueness results. To demonstrate the effectiveness and applicability of our theoretical conclusions and two-step Lagrange polynomial interpolation were used to solve four numerical results.

The Sakha people have a long history of use of medicinal plants in traditional medicine and healing practices. This article explores the use and naming practices found with 10 plants that grow in far northeastern Russia, in the Arctic and Subarctic zones of the Republic of Sakha (Yakutia). A field survey of 2500 participants was used to identify the most widely used medicinal plants, their names, and uses. Findings were double-checked with published resources. A small set of criteria are used in naming practices. These practices are based on the plant’s appearance, its habit, or in some way are related to their use, indexing the disease, or the diseased organ, or the result of healing. We find robust knowledge and practice of traditional medicine across the Sakha population, and deep knowledge of plants among Sakha herbalists, healers and shamans.

(1) Background: A history of TB is a known risk factor for long-term respiratory impairment affecting lung functions in both restrictive and obstructive lung disease. (2) Methods: We analyzed data from the NHANES 1 Epidemiologic Follow-up Study (NHEFS), a longitudinal study conducted on non-institutionalized adult US population, ages 25-74 years. Approximately 93 percent (n=13,383) of the cohort was successfully traced by the end of the survey period and was available for analysis. The final adjusted model included age groups, gender, family income, lifetime smoking, BMI, and frequency of alcohol consumption as potential confounders. (3) Results: Estimated hazards ratio of developing Emphysema during follow-up in individuals that had a past diagnosis of TB was 54% lower (95% CI = 0.35, 0.61) as compared to individuals with no past TB, after controlling for potential confounders and using proportional hazards regression appropriate to the complex sample design. The association, however, was not statistically significant (HR = 0.862, p-value = 0.38) when only self-reported history of TB was considered as the exposure. (4) Conclusion: Tuberculosis (self-reported or LTBI) was strongly (but inversely) associated with Emphysema incidence. The association was not statistically significant with only self-reported history of TB as exposure.

In this paper a more flexible extension of the Fréchet distribution is introduced. The new distribution is defined by means of the stochastic representation as the quotient of two independent random variables, a Fréchet distribution and the power of a random variable with uniform distribution in the interval (0,1). We will call this new extension the Slash Fréchet distribution and one of its main characteristics is that its tails are heavier than the Fréchet distribution. The general density of this distribution and some basic properties are determined. Its moments, skewness coefficients and kurtosis are calculated. In addition, the estimation of the model parameters is obtained by the method of moments and maximum likelihood. Finally, two applications with real data are performed by fitting the new model and comparing it with the Fréchet distribution.

Egyptians face a significant challenge in meeting the growing population's water needs for agriculture and food production. To address this, policymakers and researchers have implemented the National Great Project for Lining and Rehabilitation of All Open Canals of the Irrigation Network to reduce irrigation water losses through seepage, evaporation, and evapotranspiration. The current field study evaluates water losses from the Al Maanna canal network in Assiut governorate, Middle Egypt, using empirical formulas and field ponding methods. The obtained results indicated that the Moleth-Worth formula is more compatible and gives results that are in good agreement with the field measurements carried out. The estimated seepage losses from the existing, distorted Al Maanna canal network using the Moleth-Worth formula and field ponding method were about 2.07 and 2.20 million m3/month, respectively. Also, the calculated maximum evaporation and evapotranspiration losses were about 0.086 and 1.133 million m3/month, respectively. Consequently, the total water losses might be about 3.42 million m3/month, representing nearly 13.63% of the Al Maanna canal’s total discharge. After completing the lining process, seepage losses from lined canals were determined to be only about 0.472 million m3/month using the ponding method, while evaporation and evapotranspiration losses will be significantly decreased after canal rehabilitation. Hence, lining the Al Maanna canal network can decrease the total water losses by about 84%, which is sufficient to recommend and encourage the lining processes where the value of the gained quantities of water exceeds all the implementation expenses, in addition to other moral, cultural, and environmental gains.

In this review, our goal is to design and test quantum-like algorithms for Artificial Intelligence (AI) in open systems to structure a human-machine team to be able to reach its maximum performance. Unlike the laboratory, in open systems, teams face complexity, uncertainty and conflict. All task domains have complexity levels, some have low, and others high levels. Complexity in this new domain is affected by the environment and the task, which are both affected by uncertainty and conflict. We contrast the individual and interdependence approaches to teams. The traditional and individual approach focuses on building teams and systems by aggregating the best available information for individuals, their thoughts, behaviors and skills. Its concepts are characterized chiefly by one-to-one relations between mind and body, a summation of disembodied individual mental and physical attributes, and degrees of freedom corresponding to the number of members in a team; however, this approach is characterized by the many researchers who have invested in it for almost a century with few effects that can be generalized to human-machine interactions; by the replication crisis of today (e.g., the invalid scales for self-esteem, implicit racism, and honesty); and by its many disembodied concepts. In contrast, our approach is based on the quantum-like nature of interdependence. It allows us to theorize about the bistability of mind and body, but it proposes a measurement problem and a non-factorable nature. Bistability addresses team structure and performance; the measurement problem solves the replication crisis; and the non-factorable aspect of teams reduces the degrees of freedom and the information derivable from teammates to match findings by the National Academies of Science. We begin with a review of the science of teams and a focus on human-machine team research in the laboratory versus the open; justifications for rejecting traditional social science while supporting our approach; a full understand of the complexity of the domain, tasks in the domain, and how teams address both; the mathematics involved; a review of results from our model versus the open field; a discussion of the results; conclusions; and the path forward to successfully advance the science of interdependence and autonomy.

Microarray gene expression-based detection and classification of medical conditions have been prominent in research studies over the past few decades. However, extracting relevant data from the high-volume microarray gene expression with inherent nonlinearity and inseparable noise components raises significant challenges during data classification and disease detection. So, this paper proposes a two-level strategy involving feature extraction and selection methods before the classification step. The feature extraction step utilizes Short Term Fourier Transform (STFT), and the feature selection step employs Particle Swarm Optimization (PSO) and Harmonic Search (HS) metaheuristic methods. The classifiers employed are Non-Linear Regression, Gaussian Mixture Model, Softmax Discriminant, Naive Bayes, SVM (Linear), SVM (Polynomial), and SVM (RBF). The two-level extracted relevant features are compared with raw data classification results, including Convolutional Neural Network (CNN) Methodology. Among the methods, STFT with PSO feature selection and SVM (RBF) classifier produced the highest accuracy of 94.47%.

The proliferation of the Internet of Things (IoT) has revolutionized traditional services, giving rise to emerging smart infrastructures by connecting the physical and digital worlds. Sensory data is essential in IoT-based systems for providing context-aware and location-based services. Hence, the accurate localization of IoT devices is paramount. Anchor misplacement can significantly affect location information and coverage services in IoT. We study the effect of anchor misplacement in typical IoT settings where sensors are randomly deployed, can be mobile and may belong to multiple providers. We identify sensing coverage holes formed by anchor misplacement and analyze their presence and impact. To mitigate the impact of anchor misplacement on network reliability, we propose a framework to identify the affected sensor nodes and then identify and remove misplaced anchor nodes. The validity of our approach is verified, and its effectiveness is demonstrated by several experiments with different network topologies and parameters. Our results are promising and can be utilized in multiple coverage applications, such as smart agriculture systems and habitat monitoring, regardless of the sensors or deployment types. It also sheds light on best practices and methods for a reliable design of IoT-based systems.

The cosmetic industry recognizes the importance of natural sources for functional active constit-uents in meeting consumer expectations for safer and more sustainable beauty care products. Ma-rine macroalgae have emerged as promising resources, offering diverse bioactive constituents with potential applications in cosmetics. In this study, we investigated the biochemical profile of Padina boergesenii, a marine macroalga, using various methods to assess its potential as a cosmetic ingre-dient. The Fourier Transform Infrared (FTIR) analysis revealed the presence of distinct bioactive functional groups associated with numerous skin-beneficial compounds. Furthermore, the ethanolic and methanolic extracts of P. boergesenii were subjected to Gas Chromatography-Mass Spectrom-etry (GC-MS) analysis, which identified a total of six and fifteen significant phytocompounds, re-spectively. Additionally, a comprehensive phytochemical profiling of P. boergesenii was performed using High-Resolution Liquid Chromatography-Mass Spectrometry Quadrupole Time-of-Flight (HRLCMS-Q-TOF), highlighting the presence of various terpenoids, alkaloids, peptides, fatty acids, derivatives, and coumarins with potential cosmetic applications. To further assess its potential as a cosmetic ingredient, P. boergesenii was subjected to several additional estimations. Pigment estima-tion revealed the presence of specific pigments, while the determination of total phenol content and total protein content highlighted the richness of these bioactive components. The antioxidant analysis using the DPPH method demonstrated the antioxidant potential of P. boergesenii extracts, suggesting their ability to combat oxidative stress-related skin damage. Moreover, the tyrosinase inhibition assay indicated the inhibitory effect of P. boergesenii extracts on tyrosinase activity, which is relevant for addressing hyperpigmentation concerns. Furthermore, the elemental composition of P. boergesenii was evaluated using Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES), revealing that silicon (Si) exhibited the highest concentration among the measured elements, while copper (Cu) displayed the lowest concentration. Additionally, HRLCMS-Q-TOF analysis was employed to quantify 21 amino acids, with aspartic acid exhibiting the highest con-centration (2034.99 nmol/mL), and tyrosine demonstrating the lowest concentration (233.26 nmol/mL). The accuracy of all the measured elements and amino acids was deemed acceptable. Taken together, the findings of this study highlight the potential of P. boergesenii as an effective ingredient for enhancing skin health. The incorporation of seaweed-based bioactive components, such as P. boergesenii, into cosmetic products is increasingly common due to their beneficial effects on the skin. Further exploration of the potential applications of P. boergesenii in the cosmetics in-dustry is warranted to harness its valuable bioactive properties.

We are already more than year away from the pandemic period, followed by a year within a global economic crisis and a war in Ukraine, with the marks and the changes caused in all parameters of life becoming clear now including food choice motives of citizens worldwide. In this study we investigate the changes in food choice motives caused by the pandemic to college students in Greece in the 10 key food motives namely health, convenience, sensory, appeal, nutritional quality, moral concerns, weight control, mood and stress, familiarity, price, and shopping frequency and behavior. A self-response questionnaire survey was carried out in January to February 2023 on a sample of 1017 college students’ participants through the Google platform. Basic statistical tools, combined with cross and Chi-square tests were used in order to analyze the collected data. The results show that students exhibit quiet and very important preferences on health, convenience, weight control, and mood and stress. Food choices related to sensory appeal, nutritional quality, and familiarity is of less importance for the students, similarly to ethical concerns expect the environmental impact of the food which is high to their concern. The motive which continues to have the highest concern for students before and after the pandemic is price looking for value for money food (88.8%), not to be expensive (80.7%), and be cheap (78.7%). The shopping frequency and behavior motives, which were changed during the pandemic, have now returned to the motives of the pre pandemic period, with purchase of foods from supermarket (29%), local grocery (37.6%), and only 12.3% via online, and 20.4% by delivery, weekly or every two weeks. They prefer to cook at home full meals is now very high reaching 74.4%, avoiding eating at a restaurant or fast food (only 27% positives answers). Our findings indicate that students have already returned to their food choice motives of the period before COVID-19 except the home cooking food which is now high in their preference.

Untargeted and targeted approaches are the traditional metabolomics workflows acquired for a wider understanding of the metabolome under focus. Both approaches have their strengths and weaknesses. The untargeted, for example, is maximizing the detection and accurate identification of thousands of metabolites, while the targeted is maximizing the linear dynamic range and quantification sensitivity. These workflows, however, are acquired separately, so researchers compromise either a low-accuracy overview of total molecular changes (i.e., untargeted analysis) or a detailed yet blinkered snapshot of a selected group of metabolites (i.e., targeted analysis) by selecting one of the workflows over the other. In this review, we present a novel single injection simultaneous quantitation and discovery (SQUAD) metabolomics that combines targeted and untargeted workflows. It is used to identify and accurately quantify a targeted set of metabolites. It also allows data retro-mining to look for global metabolic changes that were not part of the original focus. This offers a way to strike the balance between targeted and untargeted approaches in one single experiment and address the two’s limitations. This simultaneous acquisition of hypothesis-led and discovery-led datasets allows scientists to gain more knowledge about biological systems in a single experiment.

Objective: To investigate commonalities and variations in the learning outcomes, curriculum content, assessment methods and competencies in undergraduate orthodontic curricula globally. Methods: This scoping review followed the updated methodological guidance proposed by the Joanna Briggs Institute and reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). A search on electronic databases PubMed, Scopus and Embase was conducted for the last 25 years. Google Scholar was used to identify eligible unpublished and grey literature. Results: The total number of reports identified was 231. After removal of 62 duplicates, 169 reports were included in the title and abstract screening. Finally, 17 studies were included in the review which included 13 cross-sectional surveys, three expert panel proceedings and one discussion paper. Marked variations were reported in undergraduate orthodontic curricula and competency assessments at the level of individual countries, regionally as well as globally. The challenges of imparting competency in orthodontic treatment during undergraduate dental education are also acknowledged. Conclusion: Lack of consistency in undergraduate orthodontic education is evidenced by several Delphi studies to develop consensus on orthodontic teaching in undergraduate programs. A common message emanating from the available studies on undergraduate orthodontic education seems to emphasize a focus on assessment and diagnosis of orthodontic treatment needs of patients and a basic understanding of contemporary treatment options to facilitate patient referral.

Working memory (WM) is a brain system for short-term storage and manipulation of information and plays an important role in complex cognitive tasks. In the synaptic theory of WM memorized elements are stored in the form of short-term potentiated connections in a sample population of neurons. In this paper, we show that such populations can be formed due to the mechanisms of spike-timing-dependent plasticity (STDP) – the phase dependence associated with the ratio of the pulse times of the interacting neurons. We propose a WM model considering two types of plasticity: short-term plasticity and STDP. We have shown formation of neuronal clusters encoding items in the WM model, that can be formed by external stimulation of a group of neurons due to the mechanisms of STDP and hold and reactivated by short-term plasticity mechanisms. The dynamic formation of neuronal clusters instead of pre-formed clusters gives additional flexibility to the model.

In this work, we adapt the fine-tuning algorithm of the Naïve Bayesian (FTNB) classifier to make it more suitable for imbalanced datasets. In particular, we boost misclassified instance probability terms by an amount that is disproportional to the harmonic mean of actual and predicted classes. The intuition is that discriminative attributes when the instance is misclassified would have small probability term pair values in both the actual class due to data scarcity and the predicted class due to weak correlation. Conversely, if both values are relatively high, then the attribute has good data coverage (support) and it should not be a cause for misclassification. Since the harmonic average is dominated by the smaller value and we have an imbalanced dataset, we should enact a large update if both or either term probabilities of actual and predicted classes are small. We used several benchmark datasets (60 different balanced and imbalanced datasets) to determine if the poor performance of the NB classifier is due to the scarcity of data and compared the performance of the proposed algorithm with NB, original FTNB, and other relatively new SOTA Ensemble Imbalanced Classifiers. Our empirical results reveal that the new proposed algorithm significantly outperforms all other classifiers.

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by progressive cognitive decline. The two cardinal neuropathological hallmarks of AD include buildup of cerebral β amyloid (Aβ) plaques and neurofibrillary tangles of hyperphosphorylated tau. The current disease-modifying treatments are still not effective enough to lower the rate of cognitive decline. The paucity of early detection and disease progression biomarkers also seems to present a major obstacle to AD drug development. The current established readouts based on expression levels of amyloid beta, tau and phospho tau have shown many discrepancies in patient samples when linked to disease progression. There is an urgent need to identify diagnostic and disease progression biomarkers from blood, CSF or other biofluids that can facilitate early detection of the disease and provide pharmacodynamic readouts for new drugs being tested in clinical trials. Advances in proteomic approaches using state-of-the-art mass spectrometry, are now being increasingly applied to study AD disease mechanisms, identify drug targets and novel disease biomarkers. In this report, we describe applications of the quantitative proteomic approaches for understanding AD pathophysiology, summarize the current knowledge gained from proteomic investigations of AD and discuss development and validation of new predictive and diagnostic disease biomarkers.

Enzymatically active nanocomposites are a perspective class of bioactive materials that finds their application in numerous fields of science and technology ranging from biosensors and therapeutic agents to industrial catalysts. Key properties of such systems are their stability and activity under various conditions, the problems that are addressed in any research devoted to this class of materials. Сomprehension ща the principles that affect these properties play the most important role in the development of the field, especially when it takes to a new class of bioactive systems. Recently, a new class of enzymatically doped magnetite-based sol-gel systems emerged and paved the way for a variety of potent bioactive magnetic materials with improved thermal stability. Such systems already showed themself as perspective industrial and therapeutic agents, but are still under intense investigation and many aspects are still unclear. Here we made a first attempt to describe the interaction of biomolecules with magnetite-based sol-gel materials and to investigate facets of protein structure rearrangements occurring within the pores of magnetite sol-gel matrix using dedicate Fourier-transform infrared spectroscopy.

This article discusses a transformer-free, high-efficiency DC-DC converter besides renewable energy applications. The traditional buck-boost, classic Zeta, Sepic, and Cuk converter does have the benefits of a simple design, low cost, as well as the capacity to execute voltage step-up and step-down. Conversely, because of the detrimental consequences of the parasitic constraints of the device, the voltage conversion gain of the traditional DC-DC converter is much more restricted and the efficiency is also significantly smaller, whereas this proposed converter does have a higher voltage gain and efficiency because it is used in a single power switch, resulting in reduced switching losses and voltage stress. The said converter's design is very simple, which simplifies the operation control and reduces switching and conduction losses, leading to an efficiency of 97.4 percent. This converter seems to have the same capabilities as the Zeta converter, including continuous desired output current and desired buck-boost operation. Such an article offers the operation principle and steady evaluation, as well as a comparison with other existing high step-up configurations. The proposed converter employs a fuzzy logic controller, which improves the voltage level as well as reduces the time taken to set the voltage output of a conventional PI and ANN controller, especially in comparison to the FLC controller. For deployment, Experimental Result and MATLAB/Simulink has been used, and the modeling results indicate that the proposed controller performance has improved

Acute inflammation is a physiological response to injury or infection, with a cascade of steps that ultimately leads to recruitment of immune cells to clear invading pathogens and heal wounds. However, chronic inflammation arising from continued presence of the initial trigger, or dysfunction of signalling and/or effector pathways, is harmful to health. While successful ageing in older adults including centenarians is associated with low levels of inflammation, elevated inflammation increases the risk of poor health and death [1–3]. Hence inflammation has been described as one of seven pillars of ageing. Age-associated sterile, chronic, and low-grade inflammation is commonly termed inflammageing - it is not simply a consequence of increasing chronological age, but is also a marker of biological ageing, multimorbidity and mortality risk. While inflammageing was initially thought to be caused by “continuous antigenic load and stress”, reports from the last two decades describe a much more complex phenomenon also involving cellular senescence and ageing of the immune system. In this review, we explore the sources and consequences of inflammageing and highlight potential interventions. In particular, we assess the contribution of cellular senescence to age-associated inflammation, identify patterns of pro- and anti-inflammatory markers characteristic of inflammageing, describe alterations in the ageing immune system that lead to elevated inflammation, and finally assess the ways that diet, exercise and pharmacological interventions can reduce inflammageing and thus improve later life health.

Background: Shared value creation in Base of the Pyramid (BoP) communities is a crucial process towards building sustainable societies. BoP communities in developing countries represent more than four billion people who live on low incomes with limited access to basic products and services. Current or emerging technologies offer promising solutions for organisations pursuing manufacturing opportunities in BoP communities. This study seeks to explore the literature on how BoP communities may become active participants in sustainably manufacturing products using micro-manufacturing factories. The research question posed is: What are the core concepts that need to be taken into consideration for creating shared value through micro-manufacturing factories in BoP communities? Method: A Systematised Literature review (SLR) was completed following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) method for data selection criteria and analysis. The SLR is used to explore the state of literature with regards to creating manufacturing shared value in BoP communities with the objective to identify study gaps and to explore shared value creation concepts. Results: Literature indicates BoP initiatives that have pursued to engage BoP communities through various innovation strategies. The findings of the review is organised under three strategic pillars: Capability building strategy, Implementation process, and Growth strategy. The capability building strategy defines the users’ intention to create shared value in BoP communities with Micro-manufacturing factories (MMF). It is followed by the implementation process which guides the users to create manufacturing shared value in BoP communities. This is followed by a growth strategy to scale for impact.

Coupled Delft3D-object model has been developed to predict object’s mobility and burial on sandy seafloor. The Delft3D model is used to predict seabed environment such as currents, waves (peak period, significant wave height, wave direction), water level, sediment transport, and seabed change, which are taken as the forcing term to the object model consisting of three components: (a) object‘s physical parameters such as diameter, length, mass, and rolling moment, (b) dynamics of rolling cylinder around its major axis, and (c) empirical sediment scour model with re-exposure parameterization. The model is compared with the observational data collected from a field experiment from 21 April to 23 May 2013 off the coast of Panama City, Florida funded by the Department of Defense Strategic Environmental Research and Development Program. The experimental data contain both objects’ mobility using sector scanning and pencil beam sonars and simultaneous environmental time series data of the boundary layer hydrodynamics and sediment transport conditions. Comparison between modeled and observed data clearly show the model capability.

Inter-industry has various capital structures to take advantage of growth opportunities due to agency differences and information asymmetric problems. This research aims to analyze: (1) the differences in leverage between industries; (2) the impact of shareholders-debtholders conflict and information asymmetric on growth opportunities. The findings show that there are differences in leverage between industries. However, they are relatively stable and not excessive for assets to prevent conflicts between managers and shareholders and debtholders. Equity is also not used to utilize growth because it is used to reduce the discretionary power (dilution) of shareholders. As a result, the use of opportunities and growth is limited.

Monitoring volatile organic compounds (VOCs) places a crucial role in environmental pollutants control and indoor air quality. In this study, a metal-oxide (MOx) sensor detector (used in a commercially available monitor) was employed to delineate the composition of air containing three common VOCs (ethanol, acetone and hexane) under various concentrations. Experiments with a single component and double components were conducted to investigate how the solvents interact with the metal oxide sensor. The experimental results revealed that the affinity between VOC and sensor was in the following order: acetone > ethanol > n-hexane. A mathematical model was developed, based on the experimental findings and data analysis, to convert the output resistance value of the sensor into concentration values, which in turn can be used to calculate a VOC-based air quality index. Empirical equations were established based on inferences of vapor composition versus resistance trends, and on an approach of using original and diluted air samples to generate two sets of resistance data per sample. The calibration of numerous model parameters allowed matching simulated curves to measured data. As such, the predictive mathematical model enabled quantifying not only the total concentration of sensed VOCs, but also estimating the VOC composition. This first attempt to obtain semi-quantitative data from a single MOx sensor, despite remaining selectivity challenges, is aimed at expanding the capability of mobile air pollutants monitoring devices.

We emphasize the point that, standard model of cosmology is basically a model of classical general relativity and it seems inevitable to have a revision with reference to quantum model of cosmology. Utmost important point to be noted is that, ‘Spin’ is a basic property of quantum mechanics and ‘rotation’ is a very common experience. In this context, we propose five assumptions in line with Planck mass as the baby universe. We appeal that, 1) Universe can be modeled as a time-reversed black hole (a white hole) with rotation and light speed expansion, and 2) ‘Light speed expanding cosmic space’ can be called as ‘Flat space’. With reference to light speed expansion, if one is willing to re-define cosmic red shift as [z/(1+z)], without considering Lambda cosmology model of matter density fractions, light travel distances can be reproduced with a marginal error of +8.6% at z =1.2, (i.e. traditional light travel distance is 8.6% higher than our estimate), 0% at z = 11.5 and -5.5% at z = 1200.( i.e. traditional light travel distance is 5.5% lower than our estimate). Advantages of our model are, 1) A quantum model of cosmology can be developed with unification of general theory of relativity and quantum mechanics. 2) Tension in estimating the current Hubble parameter can be eliminated via scaled Hawking’s black hole temperature formula with great confidence. 3) Galactic dark matter and visible matter can be studied in a unified manner. 4) Galactic light travel distances can be estimated very easily without matter density fractions. 5) Big Bang and Inflation like non-general relativistic concepts can be relinquished with further study.

The main purpose of this paper is to propose a novel optimization model with a new machine learning approach in the first section to achieve the best results in financial institutions in the second section. Since the constancy of efficacy derived from parametric and non-parametric is not significant, this paper provides a scientific assessment at the optimization section and proposes a novel combined parametric and non-parametric model which will be a new experiment in literature perception. A scientific assessment of banks based on a combination of the efficiency measurement method of CCR(Charnes, Cooper and Rhodes model) or CRS(Constant Return to Scale) BCC(Banker, Charnes, and Cooper model) or VRS (Variable Return to Scale) in Data Envelopment Analysis (DEA), as well as Stochastic Frontier Approach (SFA) for 65 banks during Feb to July 2020, are introduced. For analyzing the performance of the parametric and non-parametric approaches we have considered the linear regression and Unreplicated Linear Functional Relationship (ULFR). At the machine learning section, a novel four-layers data mining filtering pre-processes for selected supervised classification as well as unsupervised clustering algorithms to increase the accuracy and to remove unrelated attributes and data are applied. For the four kinds of preprocessing approaches of unsupervised attributes, supervised attributes, supervised instances, and unsupervised instances, we have chosen discretization, attribute selection, stratified remove folds, and resample filters respectively. Based on the nature of the suggested financial institution's dataset and attributes, the most appropriate preprocessing filter in each layer to achieve the highest performance is suggested. Finally, the superior bank, best performance model, and the most accurate algorithm are introduced. The results indicate that the bank number 56 is the superior bank. Among the proposed techniques, the novel recommended CVS compared with CCR-BCC and SFA models, has a more positive correlation with profit risk, and show a higher coefficient of determination values. Sequential Minimal Optimization(SMO) algorithm receives the highest accuracy in all four suggested filtering layers.

Cellular therapy has emerged as an attractive option for the treatment of cancer, and adoptive transfer of chimeric antigen receptor (CAR) expressing T cells has gained FDA approval in hematologic malignancy. However, limited efficacy has been observed utilizing CAR-T therapy in solid tumors. Natural killer (NK) cells are crucial for tumor surveillance and exhibit potent killing capacity of aberrant cells in an antigen-independent manner. Adoptive transfer of unmodified allogeneic or autologous NK cells has shown limited clinical benefit due to factors including low cell number, low cytotoxicity and failure to migrate to tumor sites. To address these problems, immortalized and autologous NK cells have been genetically engineered to express high affinity receptors (CD16), CARs directed against surface proteins (PD-L1, CD19, Her2, etc.) and endogenous cytokines (IL-2 and IL-15) that are crucial for NK cell survival and cytotoxicity, with positive outcomes reported by several groups both preclinically and clinically. With a multitude of NK cell-based therapies currently in clinic trials, it is likely they will play a crucial role in next-generation cell therapy-based treatment. In this review we will highlight the recent advances and limitations of allogeneic, autologous and genetically enhanced NK cells used in adoptive cell therapy.

Graph theory plays significant role in every field of science as well as technology. Every situation can be articulated in terms of suitable graphs by using various approaches of graph theory. Considering the recent pandemic in the world and the precautions taken for prevention of the COVID 19, it is the most appropriate way to exercise the graph models with theoretical as well as practical aspects to control this epidemic. This paper defines the variable set, variable graphs and their types with respect to variable vertex sets and variable edge sets. Depending upon the nature of the pandemic, there are four types of Virus graphs. Virus graph I and III are not so perilous for all living beings. Although, Virus graphs II and IV are extremely hazardous for the harmony of the world. In view of different aspects for expand of pandemic, growth types of virus graphs are divided in 1-1, 1-P and 1-all growth types. The COVID19 initially was in Virus graph-I type, but presently it is in Virus graph-II types. We present the table involving the number of infected people after n days with respect to different values of P and growth rates with I0 = 100. Moreover, the country wise starting dates of stages of the virus graph-I and II are specified. The concept of cut sets is applicable for prevention of COVID19 and the whole world is using the same analogy.

Surface Plasmon Resonance (SPR) is an attracting property of certain transition metals when they are synthesized in nano-range giving rise to promising optical applications. However, most SPR and associated applications are limited to the noble metal nanoparticles, which limits their potential due to high production cost. We report surface plasmon resonance in copper-copper oxide core-shell quantum dots synthesized via chemical route studied by using UV-Visible spectrophotometry. Tuning of the plasmonic resonance with respect to the particle diameter is achieved by an inexpensive all chemical route. Photoluminescence measurements also support the data. This size reduction leads to remarkable changes in its optical response as compared to the bulk metal. The results point towards applications of these materials in tunable SPR based biosensors.

Mutations in the calcium channel gene Transient Receptor Potential cation channel subfamily V member 4 (TRPV4) cause autosomal dominant skeletal dysplasia, with phenotypes ranging from mild to perinatal lethality. A recent report detailed murine thrombocytosis in the absence of functional TRPV4, but no prior reports have described platelet count abnormalities in the context of human TRPV4 disease. Here, we report a case of prolonged thrombocytosis in the context of TRPV4-associated metatropic dysplasia that was lethal in the infantile period.

Diffuse intrinsic pontine glioma (DIPG) is an aggressive pediatric brainstem tumor with a 5-year survival of <1%. Up to 80% of DIPG tumors contain a specific K27M mutation in one of two genes encoding histone H3 (H3K27M). Furthermore, p53 mutations found in >70-80% of H3K27M DIPG, and mutant p53 status is associated with a decreased response to radiation treatment and worse overall prognosis. Recent evidence indicates that H3K27M mutation disrupts tri-methylation at H3K27 leading to aberrant gene expression. Jumonji family histone demethylases collaborates with H3K27 mutation in DIPG by erasing H3K27 trimethylation and thus contributing to derepression of genes involved in tumorigenesis. Since the first line treatment for pediatric DIPG is fractionated radiation, we investigated the effects of Jumonji demethylase inhibition with GSK-J4, and mutant p53 targeting/oxidative stress induction with APR-246, on radio-sensitization of human H3K27M DIPG cells. Both APR-246 and GSK-J4 displayed growth inhibitory effects as single agents in H3K27M DIPG cells. Furthermore, both of these agents elicited mild radiosensitizing effects in human DIPG cells (sensitizer enhancement ratios (SERs) of 1.12 and 1.35, respectively; p<0.05). Strikingly, a combination of APR-246 and GSK-J4 displayed a significant enhancement of radiosensitization, with SER of 1.50 (p<0.05) at sub-micro-molar concentrations of the drugs (0.5 μM). The molecular mechanism of the observed radiosensitization appears to involve DNA damage repair deficiency triggered by APR-246/GSK-J4, leading to the induction of apoptotic cell death. Thus, a therapeutic approach of combined targeting of mutant p53, oxidative stress induction, and Jumonji demethylase inhibition with radiation in DIPG warrants further investigation.

Wearable sensors have the potential to enable comprehensive patient characterization and optimized clinical intervention. Critical to realizing this vision is accurate estimation of biomechanical time-series in daily-life, including joint, segment, and muscle kinetics and kinematics, from wearable sensor data. The use of physical models for estimation of these quantities often requires many wearable devices making practical implementation more difficult. However, regression techniques may provide a viable alternative by allowing the use of a reduced number of sensors for estimating biomechanical time-series. Herein, we review 46 articles that used regression algorithms to estimate joint, segment, and muscle kinematics and kinetics. We present a high-level comparison of the many different techniques identified and discuss the implications of our findings concerning practical implementation and further improving estimation accuracy. In particular, we found that several studies report the incorporation of domain knowledge often yielded superior performance. Further, most models were trained on small datasets in which case nonparametric regression often performed best. No models were open-sourced, and most were subject-specific and not validated on impaired populations. Future research should focus on developing open-source algorithms using complementary physics-based and machine learning techniques that are validated in clinically impaired populations. This approach may further improve estimation performance and reduce barriers to clinical adoption.

Motivation: 16S rRNA gene amplicon based sequencing has significantly expanded the scope of metagenomics research by enabling microbial community analyses in a cost-effective manner. The possibility to infer functional potential of a microbiome through amplicon sequencing derived taxonomic abundance profiles has further strengthened the utility of 16S sequencing. In fact, a surge in 'inferred function metagenomic analysis' has recently taken place, wherein most 16S microbiome studies include inferred functional insights in addition to taxonomic characterization. Tools like PICRUSt, Tax4Fun, Vikodak and iVikodak have significantly eased the process of inferring function potential of a microbiome using the taxonomic abundance profile. A platform that can enable hosting of inferred function 'metagenomic studies' with comprehensive metadata driven search utilities (of a typical database), coupled with on-the-fly comparative analytics between studies of interest, can be a major improvement to the state of art. ReFDash represents an effort in the proposed direction. Methods: This work introduces ReFDash - a Repository of Functional Dashboards. ReFDash, developed as a significant extension of iVikodak (function inference tool), provides three broad unique offerings in inferred function space - (i) a platform that hosts a database of inferred function data being continously updated using public 16S metagenomic studies (ii) a tool to search studies of interest and compare upto three metagenomic environments on the fly (iii) a community initiative wherein users can contribute their own inferred function data to the platform. ReFDash therefore provides a first-of-its-kind community-driven frame-work for scientific collaboration, data analytics, and sharing in this area of microbiome research. Results: Overall, the ReFDash database is aimed at compiling together a global ensemble of 16S-derived Functional Metagenomics projects. ReFDash currently hosts close to 50 ready-to-use, re-analyzable functional dashboards representing data from approximately 18,000 microbiome samples sourced from various published studies. Each entry also provides direct downloadable links to associated taxonomic files and metadata employed for analysis. Conclusion: The vision behind ReFDash is creation of a framework, wherein users can not only analyze their microbiome datasets in functional terms, but also contribute towards building an information base by submitting their functional analyses to ReFDash database. ReFDash web-server may be freely accessed at https://web.rniapps.net/iVikodak/refdash/

The combination of calcium phosphates (CaP) with bioactive glasses (BG) has received an increased interest in the field of bone tissue engineering. In the present work, biphasic calcium phosphates (BCP) obtained by hydrothermal transformation (HT) of cuttlefish bone (CB) were coated with a Sr-, Mg- and Zn-doped sol-gel derived BG. The scaffolds were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The initial CB structure was maintained after HT and the scaffold functionalization did not jeopardize the internal structure. The results of in vitro bio-mineralization after immersing the BG coated scaffolds in simulated body fluid (SBF) showed extensive formation of bone-like apatite onto the surface of the scaffolds. Overall, the functionalized CB derived BCP scaffolds revealed promising properties for their use in bone tissue engineering field.

In this paper, we introduce a new class of Laguerre-based Hermite-Fubini numbers and polynomials and investigate some properties of these polynomials. We establish summation formulas of these polynomials by summation techniques series. Furthermore, we derive symmetric identities of Laguerre-based Hermite-Fubini numbers and polynomials by using generating functions.

The VLSI industry is facing parasitic effects that trouble development in the nanoscale domain. However, instead of replacing the traditional MOSFET design, it would be more advantageous to apply different doping profiles and discerning which deal with specific parasitic effects the best. With a review of Gaussian doping, Uniform doping, and Delta doping profiles and analysis of the FET technology characteristics that use these doping profiles, a comparison can be made among them for integrated circuit design engineers. These doping profiles are compared based on how well they perform against non-ideal and ideal environments. Also, both digital and analog performance are measured to ensure the uniqueness of each doping profile that is present. After getting a list of benefits from each doping profile, it is derived to determine which doping profile works best against a host of parasitic effects and what type of application do these doping profiles have

The unexploited unification of quantum physics, general relativity and biology is a keystone that paves the way towards a better understanding of the whole of Nature. Here we propose a mathematical approach that introduces the problem in terms of group theory. We build a cyclic groupoid (a nonempty set with a binary operation defined on it) that encompasses the three frameworks as subsets, representing two of their most dissimilar experimental results, i.e., 1) the commutativity detectable both in our macroscopic relativistic world and in biology; 2) and the noncommutativity detectable both in the microscopic quantum world and in biology. This approach leads to a mathematical framework useful in the investigation of the three apparently irreconcilable realms. Also, we show how cyclic groupoids encompassing quantum mechanics, relativity theory and biology might be equipped with dynamics that can be described by paths on the twisted cylinder of a Möbius strip.

Abstract: Yeast – especially Saccharomyces cerevisiae – have long been a preferred workhorse for the production of numerous recombinant proteins and other metabolites. S. cerevisiae is a noteworthy aroma compound producer, and has also been exploited to produce foreign bioflavour compounds. In the past few years, important strides have been made in unlocking the key elements in the biochemical pathways involved in the production of many aroma compounds. The expression of these biochemical pathways in yeast often involves the manipulation of the host strain to direct the flux towards certain precursors needed for the production of the given aroma compound. This review highlights recent advances in the bioengineering of yeast – including S. cerevisiae – to produce aroma compounds and bioflavours. To capitalise on recent advances in synthetic yeast genomics, this review presents yeast as a significant producer of bioflavours in a fresh context and proposes new directions for combining engineering and biology principles to improve the yield of targeted aroma compounds.

This study was conducted to search for green technology that can extract metabolites from neem leaves for use in the development of botanical pesticide against Bactrocera dorsalis (Hendel) (Diptera:Tephritidae). Rice wine, rice wash, vinegar and distilled water were used as solvents and hot infusion, maceration, hot continuous reflux (Soxhlet), and fermentation were the methods employed. The different leaf extracts prepared by green technology were evaluated for their potentials as pesticide against B. dorsalis. Vinegar extract via Soxhlet extraction (V-S) for eight (8) h registered to have the highest mortality but not significantly different from vinegar - fermentation (V-F), rice wash - Soxhlet (RWa-S), vinegar - maceration (V-M), distilled water - fermentation (DW-F), and rice wash - fermentation (RWa-F) extracts. Phythochemicals present in the extracts are affected by the solvent-extraction interaction. Among the sixteen solvent-extraction interactions, the use of rice wash and fermentation is the most economical method in extracting the extracting the active components of neem leaves against B. dorsalis. Rice wash is a waste that can be utilized in the development of a biopesticide from neem leaves for pest management of B. dorsalis. This is the first report that rice wash is used as extracting solvent in green synthesis.

Since the detection of the first COVID-19 patient, 2 years have passed, during which more than 287,862,000 people fell ill globally, of which about 1.9% died. Implementation of SARS-CoV-2 control programs required efforts from almost all countries. An important direction in the fight against COVID-19 was the formation of herd immunity, the main tool for managing the pandemic. Study goal: to assess the seroprevalence of antibodies (Abs) to SARS-CoV-2 nucleocapsid (Nc) and receptor binding domain (RBD) in the St. Petersburg population during the COVID-19 pandemic. Materials and methods. A longitudinal cohort randomized monitoring study of Ab seroprevalence (SARS-CoV-2 Nc, RBD) was organized and conducted according to a unified methodology developed by Rospotrebnadzor with the participation of the St. Petersburg Pasteur Institute. For this purpose, a cohort of 1000 volunteers was formed who participated in all five stages of seromonitoring. The cohort was divided into 7 age groups: 1-17; 18-29; 30-39; 40-49; 50-59; 60-69; 70; and older (70+) years. Seropositivity levels (Nc, RBD) were assessed by quantitative and qualitative enzyme immunoassays. During the 2nd year of monitoring, some volunteers were vaccinated with the GamCOVIDVac (84%) or EpiVacCorona (11.6%) vaccines approved in Russia. Statistical processing was carried out using the Excel 2010 software package. Confidence intervals for shares and percentages (95% CI) were calculated using the method of A. Wald and J. Wolfowitz with adjustment (A. Agresti, B.A. Coull). The statistical significance of differences was calculated by z-test, using the appropriate online calculator (p<0.05), unless indicated. Results. There was a trend towards: an increase in Nc seropositivity in stages 1-3 of seromonitoring, with a decrease in stages 4-5 among children and adults. The share of RBD seropositive steadily increased during all 5 stages of seromonitoring. The most frequently found were low anti-RBD Abs levels (22.6-220 BAU/ml). High Ab levels were recorded statistically significantly less frequently. Asymptomatic forms were observed in 84-88% of SARS-CoV-2 seropositive volunteers. By the 5th stage of monitoring, this indicator significantly decreased to 69.8% (95% CI: 66.1-73.4). The monitoring revealed a statistically significant increase in anti-RBD Abs, alongside a statistically significant decrease in the proportion of Nc seropositive. This dynamic was especially characteristic of persons vaccinated with GamCOVIDVac. Conclusion. Prior to the use of specific vaccines, a seroprevalence of anti-Nc Abs was noted. After the introduction of the GamCOVIDVac vaccine in adults, a decrease in the level of anti-Nc Abs was noted due to an increase in the proportion of RBD seropositive persons.

The hydrothermal synthesis of aluminophosphate molecular sieve type AlPO4-11 was processed from chemicals containing psueudobohemite, 85% phosphoric acid, water, and di-isopropylamine as templating agent. The crystallization of the samples was studied by taking samples in times from 2 to 74 hours. The obtained white powder products have been characterized by XRD patterns, FT-IR spectra, thermogravimetric data, scanning electron microscopy and pH measurement of the mother liquor. The pore volume, as determined from TG and DTG curves, was ca. 0.17 cm3g-1. The crystallization process of the aluminophosphate exhibited in its initial phase a behavior of first order reaction with a specific velocity constant of ca. 0.25 h-1, as determined from XRD and FT-IR data.

Distance Learning has become the new standard, especially after the pandemic and due to the technological advances, that are incorporated into the teaching procedure. At the same time, the augmented use of the internet has blurred the borders between distance and conventional learning. Students interact mainly through LMSs, leaving their digital traces that can be leveraged to improve the educational process. This work aims to propose a model that can capture the students' behaviors based on the clickstream data associated with the discussion forum and additionally to suggest interpretable patterns that will support education administrators and tutors in the decision-making process. To achieve our goal, we use Social Network Analysis (SNA) as networks represent complex interactions in a meaningful and easily interpretable way. Moreover, simple or complex network metrics are becoming available to provide valuable insights into the students’ social interaction. This study concludes that by leveraging the imprint of these actions in an LMS and using metrics of SNA, differences can be spotted in the communicational patterns that go beyond simple participation recording. Although HITS and PageRank algorithms were created with completely different targeting, it is shown that they can also reveal methodological features in students’ communicational approach.

Neisseria meningitidis (N. meningitidis) serogroup B (MenB) is the leading cause of invasive meningococcal disease worldwide. The pathogen has a wide range of virulence factors, which are potential vaccine components. Studying the genetic variability of antigens within a population, especially their long-term persistence, is necessary to develop new vaccines and predict the effectiveness of existing ones. The multicomponent 4CMenB vaccine (Bexsero), used since 2014, contains three major genome-derived recombinant proteins: factor H-binding protein (fHbp), Neisserial Heparin-Binding Antigen (NHBA) and Neisserial adhesin A (NadA). Here, we assessed the prevalence and sequence variations of these vaccine antigens in a panel of 5667 meningococcal isolates collected worldwide over the past 10 years and deposited in the PubMLST database. Using multiple amino acid sequence alignments and machine learning methods, we estimated the potential strain coverage by fHbp and NHBA vaccine variants (51 and about 30%, respectively); the NadA antigen sequence was found in only 17.8% of MenB genomes analyzed, but cross-reactive variants were present in less than 1% of isolates. Based on our findings, we proposed various strategies to improve the 4CMenB vaccine and broaden coverage of N. meningitidis strains.

As digital technologies rapidly integrate into Health Professions Education (HPE), gaining a comprehensive understanding of cyberethics becomes crucial. This scoping review aimed to explore the pedagogy of cyberethics within HPE, with an emphasis on its definitions, conceptualizations, theoretical foundations, and interventions. Drawing from 37 documents spanning 2012-2022, primarily originating from the U.S. and encompassing both peer-reviewed and grey literature, the study highlighted a significant gap in the explicit definition and conceptualization of cyberethics. Additionally, the evident lack of specific theoretical frameworks in the majority of these documents could hamper the progression and replicability of research. Among the reviewed articles, only four introduced cyberethics educational interventions, indicating a substantial avenue for future research. While the study utilized comprehensive search methods, limitations such as language biases and the potential omission of pertinent documents were present. Future investigations should broaden the cyberethics discourse to encompass emerging technologies and their ethical implications within HPE. Crafting comprehensive, culturally sensitive, and inclusive guidelines is pivotal in nurturing ethical digital practices in the health care community.

Chenodeoxycholic acid (CA) is a naturally occurring bile acid that is produced in the liver from cholesterol. Three CA complexes using Zn(II), Mg(II), and Ca(II) ions were synthesized to examine the chelation tendencies of CA towards these metal ions. The complexation reaction of CA with the metal ions under investigation was conducted with a 1:1 molar ratio (CA to metal) at 60-70°C in natural media (pH 7-8), which consisted of a binary solvent of MeOH and H2O (1:1). The resulting CA complexes were characterized using analytical data (metal, H, C, and Cl, analysis) and spectral data (UV-visible, FT-IR, and 1H NMR) to elucidate the complexes’ structures. The results suggested that CA in anion form utilized oxygen atoms of the carboxylate group (-COO−) to capture Zn(II), Mg(II), and Ca(II) ions. This produced complexes with the general compositions of [Zn(CA)(H2O)Cl], [Mg(CA)(H2O)Cl]H2O, and [Ca(CA)(H2O)Cl]2H2O, respectively. The Kirby-Bauer disc diffusion assay was then used to explore the bioactivity of the CA complexes toward three fungal species, three Gram-positive bacteria, and two Gram-negative bacteria. The Ca(II) and Mg(II) complexes exhibited marked inhibitory effects on the cell growth of the fungal species Aspergillus niger with potency equal to 127% and 116% of the activity of the positive control, respectively. The Zn(II) and Ca(II) complexes strongly inhibited the growth of Penicillium sp., while the Zn(II) and Mg(II) complexes showed strong growth inhibition towards the Gram-negative species Pseudomonas aeruginosa.

The chemical reaction between the quinolone antibiotic oxolinic acid (OA) and Fe(III), Zn(II), Ca(II), and Mg(II) ions results in the formation of metal-based complexes with the following formulas: [Fe(OA)(H2O)2Cl2]2H2O, [Zn(OA)(H2O)Cl]2H2O, [Ca(OA)(H2O)Cl], and [Mg(OA)(H2O)Cl]. We used analytical (C, N, H, Cl, metal analysis) and spectral (FT-IR, 1H NMR, UV-visible) data to structurally characterize the synthesized metal-based complexes of the OA molecule. We found that the OA molecule utilizes the two oxygen atoms of the carboxylate group and the pyridone C=O group to bind the investigated metal ions. The morphological properties of the synthesized OA complexes were assessed using X-ray powder diffractometry (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The biological properties, specifically antibacterial and antifungal activity, of the synthesized complexes were evaluated in vitro using the Kirby-Bauer disc diffusion protocol with five bacterial and three fungal strains. The complex containing Ca(II) ions exhibited remarkable antibacterial and antifungal activity against all tested microbial strains, surpassing or equaling the potency of the standard drugs (streptomycin for antibacterial assays and ketoconazole for antifungal assays).

Urbanization affects all elements of the pre-urban environment, including soils, hydrology, vegetation, and microclimate. Recently, Saudi Arabia has experienced rapid urbanization and growth. Thus, the country's biodiversity has been threatened. In Riyadh, beetle assemblages were assessed along a rural-suburban-urban gradient. A total of 2,791 individuals from 94 species belonging to seven families were collected at 15 sites along three different gradients of urbanization in Wadi Hanifa. Tenebrionidae dominated abundance (60.1%) and richness (38%). Beetle abundance, evenness, and diversity were not different among habitats; however, species richness was higher in rural habitats. DCA and CCA analyses showed distinct differences among sites along gradients. Urbanization intensity, soil variables, and land cover were significantly correlated with DCA axis 1, while elevation and flora were significantly correlated with DCA axis 2. The most critical operating environmental variables in Wadi Hanifa were buildings, elevation, soil organic carbon, litter cover, and litter depth, as well as plants such as Launaea capitata, Lycium shawii, Alhagi graecorum, and Heliotropium currasavicum. Ten species in our study are associated with urban habitats, six with suburban habitats, and seven with rural habitats. Consequently, expanding urban areas may negatively affect the richness and composition of beetles and may result in the loss of some native species.