Comprehensive Characterization of the Genetic Landscape of African Swine Fever Virus: Insights into Infection Dynamics, Immunomodulation, Virulence and Genes with Unknown Function.

African Swine Fever (ASF) is a lethal contagious hemorrhagic viral disease affecting the swine population. The causative agent is African Swine Fever Virus (ASFV). There is no treatment or commercial vaccine available at present. This virus poses a significant threat to the global swine industry and economy, with 100% mortality rate in acute cases. ASFV transmission occurs through both direct and indirect contact, with control measures limited to early detection, isolation, and culling of infected pigs. ASFV exhibits a complex genomic structure and encodes for more than 50 structural and 100 non-structural proteins and has 150 to 167 open reading frames (ORFs). While many of the proteins are non-essential for viral replication, they play crucial roles in mediating with the host to ensure longevity and transmission of virus in the host. The dynamic nature of ASFV research necessitates constant updates, with ongoing exploration of various genes and their functions, vaccine development, and other ASF-related domains. This comprehensive review aims to elucidate the structural and functional roles of both newly discovered and previously recorded genes involved in distinct stages of ASFV infection and immunomodulation. Additionally, the review discusses the virulence genes and genes with unknown functions, and proposes future interventions.

A nonconjugated radical polymer enables bimodal memory and in-sensor computing operation.

This study reports intrinsic multimodal memristivity of a nonconjugated radical polymer with ambient stability. Organic memristive devices represent powerful candidates for biorealistic data storage and processing. However, there exists a substantial knowledge gap in realizing the synthetic biorealistic systems capable of effectively emulating the cooperative and multimodal activation processes in biological systems. In addition, conventional organic memristive materials are centered on conjugated small and macromolecules, making them synthetically challenging or difficult to process. In this work, we first describe the intrinsic resistive switching of the radical polymer that resulted in an exceptional state retention of >105 s and on/off ratio of >106. Next, we demonstrate its bimodal cooperative switching, in response to the proton accumulation as a biological input. Last, we expand our system toward an advanced in-sensor computing system. Our research demonstrates a nonconjugated radical polymer with intrinsic memristivity, which is directly applicable to future electronics including data storage, neuromorphics, and in-sensor computing.

The adaptation of 3T3 cells to simulated microgravity by retrieving the major cell cycle-related protein expression during long-term in vitro proliferation.

The present study aimed to assess the effects of simulated microgravity (SMG) on 3T3 cell proliferation and the expression of cell cycle regulators. 3T3 cells were induced to SMG by Gravite® for 8 days, while the control group was treated with 1G condition. The result showed that the SMG condition causes a decrease in proliferative activity in 3T3 cells. In the SMG group, the expression of cell cycle-related proteins was lower than the control on day 3. However, these proteins were upregulated in 3T3 cells of the SMG group on day 5, suggesting that these cells were rescued from the arrest and retrieved a higher proliferation. A down-regulation of cell cycle-related proteins was observed in 3T3 cells of both SMG and control groups on day 7. In conclusion, SMG results in the attenuation of cell proliferation during the initial exposure to SMG, but the cells will adapt to this condition and retrieve normal proliferation by increasing the expression of cell cycle regulators.

Intracorporeal evaluation of hyaluronic acid fillers with varied rheological properties and correlations with aesthetic outcomes.

BACKGROUND: Understanding the differences in soft tissue filler rheology and how these properties can impact clinical results is a fundamental concepts for any injector. This study aimed to assess the tissue integration characteristics of hyaluronic acid (HA) fillers manufactured with different technologies (Non-Animal Stabilized HA [HA-N] or Optimal Balance Technology [HA-O]) using ultra-high-frequency ultrasound. METHODS: Twelve female participants with mild-to-moderate midface volume loss and temporal hollowing were enrolled and treated with HA-N and/or HA-O. Participants were seen at five visits (screening/baseline [treatment], and Weeks 1 [optional touch-up], 4, 6, and 8 [follow-up visits]). Ultrasound was used to evaluate the degree of product integration. RESULTS: On ultrasound, HA-N presented with distinct borders, minimal tissue integration, and a capacity to displace tissues. Conversely, HA-O tended to spread horizontally within the same tissue plane and integrated within tissues. The volumizing capacity of the HA-O fillers was dependent on particle size. CONCLUSION: HA-N is suited for deep injections in areas such as the upper lateral cheek and under the muscle of the temporal region when a lifting effect is desired; HA-O is best suited for subcutaneous injections, in areas of dynamic movement or for patients with thin skin; and can be injected subcutaneously or supraperiosteally when a volumizing effect is desired.

Deep Learning - Methods to Amplify Epidemiological Data Collection and Analyses.

Deep learning is a subfield of artificial intelligence and machine learning based mostly on neural networks and often combined with attention algorithms that has been used to detect and identify objects in text, audio, images, and video. Serghiou and Rough (Am J Epidemiol. 0000;000(00):0000-0000) present a primer for epidemiologists on deep learning models. These models provide substantial opportunities for epidemiologists to expand and amplify their research in both data collection and analyses by increasing the geographic reach of studies, including more research subjects, and working with large or high dimensional data. The tools for implementing deep learning methods are not quite yet as straightforward or ubiquitous for epidemiologists as traditional regression methods found in standard statistical software, but there are exciting opportunities for interdisciplinary collaboration with deep learning experts, just as epidemiologists have with statisticians, healthcare providers, urban planners, and other professionals. Despite the novelty of these methods, epidemiological principles of assessing bias, study design, interpretation and others still apply when implementing deep learning methods or assessing the findings of studies that have used them.

Exploring medical first responders' perceptions of mass casualty incident scenario training: a qualitative study on learning conditions and recommendations for improvement.

OBJECTIVE: Despite participating in scenario training, many medical first responders (MFRs) perceive themselves as inadequately prepared to respond to mass casualty incidents (MCIs). The objective of this study was to conduct a comprehensive examination of traditional MCI scenario training methods, focusing on their inherent strengths and limitations. An investigation into the perceptions of MFRs who had participated in MCI scenario training was carried out to identify potential areas for improvement and provide recommendations for refining MCI training protocols. DESIGN: Qualitative inductive approach using semistructured interviews that took place between October 2021 and February 2022. Data were analysed with qualitative content analysis. SETTING: MCI scenario training involving four organisations (three emergency medical services and one search-and-rescue organisation) tasked with responding to MCIs, collectively representing four European Union countries. PARTICIPANTS: 27 MFRs (17 emergency medical services personnel and 10 search-and-rescue volunteers) were recruited to participate in the study. RESULTS: Two categories and seven associated subcategories (shown in parentheses) were identified as influencing the learning outcomes for MFRs: Training in a context mirroring real-world incidents (conducting incident scene risk assessment, realistic representation in casualties, incorporating scenario variety into the curriculum, interagency collaboration, role alignment when training incident site management) and use of a pedagogical framework (allowing for mistakes, the importance of post-training evaluation). CONCLUSIONS: This study reaffirms the value of traditional MCI scenario training and identifies areas for enhancement, advocating for realistic scenarios, interagency collaboration, improved incident site management skills and thorough post-training evaluation. It suggests a shift in MCI training conceptualisation and delivery. The potential of virtual reality technologies as a valuable addition to training methods is explored, with a note on the need for further research to ascertain the long-term effectiveness of these technologies. However, the selection of a training method should consider programme goals, target population and resources.

Expression of the Discoidin Domain Receptor Family Depended on Glucose and Their High Expression in Arterial Tissues in the Rat Model of Type 2 Diabetes.

The active form of discoidin domain receptors (DDRs) is expressed in cell surface and regulated post-translationally by glucose. The DDR2 and DDR1 transfected in HEK293 cells were expressed mainly in their active forms with sizes of 130 and 120 kDa, respectively. DDRs were observed predominantly as 100 kDa proteins in glucose-depleted culture conditions. However, transfection of endothelial growth factor receptor (EGFR) in HEK293 cells resulted in the expression of only one form regardless of glucose concentration. Vascular smooth muscle cells, HT1080s, and MDA-MB-231 cancer cells expressed DDRs in their active forms in high glucose concentrations, which did not occur with EGFR. In diabetic rats, DDRs were expressed at high levels in arterial tissue but EGFR was not highly expressed. Taken together, these results suggest that DDRs expression depends on glucose concentration it may cooperate in the development of atherosclerosis and kidney fibroblasts, promoting nephropathy in diabetic rats.

Compact machine learning model for the accurate prediction of first 24-hour survival of mechanically ventilated patients.

Background: The field of machine learning has been evolving and applied in medical applications. We utilised a public dataset, MIMIC-III, to develop compact models that can accurately predict the outcome of mechanically ventilated patients in the first 24 h of first-time hospital admission. Methods: 67 predictive features, grouped into 6 categories, were selected for the classification and prediction task. 4 tree-based algorithms (Decision Tree, Bagging, eXtreme Gradient Boosting and Random Forest), and 5 non-tree-based algorithms (Logistic Regression, K-Nearest Neighbour, Linear Discriminant Analysis, Support Vector Machine and Naïve Bayes), were employed to predict the outcome of 18,883 mechanically ventilated patients. 5 scenarios were crafted to mirror the target population as per existing literature. S1.1 reflected an imbalanced situation, with significantly fewer mortality cases than survival ones, and both the training and test sets played similar target class distributions. S1.2 and S2.2 featured balanced classes; however, instances from the majority class were removed from the test set and/or the training set. S1.3 and S 2.3 generated additional instances of the minority class via the Synthetic Minority Over-sampling Technique. Standard evaluation metrics were used to determine the best-performing models for each scenario. With the best performers, Autofeat, an automated feature engineering library, was used to eliminate less important features per scenario. Results: Tree-based models generally outperformed the non-tree-based ones. Moreover, XGB consistently yielded the highest AUC score (between 0.91 and 0.97), while exhibiting relatively high Sensitivity (between 0.58 and 0.88) on 4 scenarios (1.2, 2.2, 1.3, and 2.3). After reducing a significant number of predictors, the selected calibrated ML models were still able to achieve similar AUC and MCC scores across those scenarios. The calibration curves of the XGB and BG models, both prior to and post dimension reduction in Scenario 2.2, showed better alignment to the perfect calibration line than curves produced from other algorithms. Conclusion: This study demonstrated that dimension-reduced models can perform well and are able to retain the important features for the classification tasks. Deploying a compact machine learning model into production helps reduce costs in terms of computational resources and monitoring changes in input data over time.

Survival trends among patients with metastatic non-small cell lung cancer before and after the approval of immunotherapy in the United States: A Surveillance, Epidemiology, and End Results database-based study.

BACKGROUND: In 2015, the US Food and Drug Administration approved nivolumab as the first immunotherapy for patients with advanced non-small cell lung cancer (NSCLC). However, population-based survival benefit studies after the introduction of immunotherapy in lung cancer are lacking. This study examined overall survival (OS) and cancer-specific survival in patients with NSCLC in the pre immunotherapy and immunotherapy eras. METHODS: This study used the Surveillance, Epidemiology, and End Results database, which spanned 17 registries from 2000 to 2020. Two cohorts were delineated: preimmunotherapy (2010-2014) and immunotherapy (2015-2020), which coincided with nivolumab's approval. RESULTS: This study included 191,802 patients, 90,807 in the preimmunotherapy era and 100,995 in the immunotherapy era. OS was significantly higher in the immunotherapy era, as shown by Kaplan-Meier curves (1-year OS, 40.1% vs. 33.5%; 3-year OS, 17.8% vs. 11.7%; 5-year OS, 10.7% vs. 6.8%; median OS, 8 vs. 7 months; p < .001 by log-rank test). Similarly, cancer-specific survival improved in the immunotherapy era (1-year survival, 44.0% vs. 36.8%; 3-year survival, 21.7% vs. 14.4%; 5-year survival, 14.3% vs. 9.0%; median OS, 10 vs. 8 months; p < .001 by log-rank test). Survival rates were significantly better in the immunotherapy era, as confirmed by multivariate analysis with a Cox proportional hazards model after adjusting for age, sex, race, income, and geographical area (adjusted hazard ratio, 0.830; 95% CI, 0.821-0.840; p < .001). CONCLUSIONS: In summary, the survival rate of patients with metastatic NSCLC has improved since the introduction of immunotherapy.

Leveraging computer vision for predicting collision risks: a cross-sectional analysis of 2019-2021 fatal collisions in the USA.

OBJECTIVE: The USA has higher rates of fatal motor vehicle collisions than most high-income countries. Previous studies examining the role of the built environment were generally limited to small geographic areas or single cities. This study aims to quantify associations between built environment characteristics and traffic collisions in the USA. METHODS: Built environment characteristics were derived from Google Street View images and summarised at the census tract level. Fatal traffic collisions were obtained from the 2019-2021 Fatality Analysis Reporting System. Fatal and non-fatal traffic collisions in Washington DC were obtained from the District Department of Transportation. Adjusted Poisson regression models examined whether built environment characteristics are related to motor vehicle collisions in the USA, controlling for census tract sociodemographic characteristics. RESULTS: Census tracts in the highest tertile of sidewalks, single-lane roads, streetlights and street greenness had 70%, 50%, 30% and 26% fewer fatal vehicle collisions compared with those in the lowest tertile. Street greenness and single-lane roads were associated with 37% and 38% fewer pedestrian-involved and cyclist-involved fatal collisions. Analyses with fatal and non-fatal collisions in Washington DC found streetlights and stop signs were associated with fewer pedestrians and cyclists-involved vehicle collisions while road construction had an adverse association. CONCLUSION: This study demonstrates the utility of using data algorithms that can automatically analyse street segments to create indicators of the built environment to enhance understanding of large-scale patterns and inform interventions to decrease road traffic injuries and fatalities.

Advanced dual-atom catalysts on graphitic carbon nitride for enhanced hydrogen evolution via water splitting.

In this comprehensive investigation, we explore the effectiveness of 55 dual-atom catalysts (DACs) supported on graphitic carbon nitride (gCN) for both alkaline and acidic hydrogen evolution reactions (HER). Employing density functional theory (DFT), we scrutinize the thermodynamic and kinetic profiles of these DACs, revealing their considerable potential across a diverse pH spectrum. For acidic HER, our results identify catalysts such as FePd-gCN, CrCr-gCN, and NiPd-gCN, displaying promising ΔGH* values of 0.0, 0.0, and -0.15 eV, respectively. This highlights their potential effectiveness in acidic environments, thereby expanding the scope of their applicability. Within the domain of alkaline HER, this study delves into the thermodynamic and kinetic profiles of DACs supported on gCN, utilizing DFT to illuminate their efficacy in alkaline HER. Through systematic evaluation, we identify that DACs such as CrCo-gCN, FeRu-gCN, and FeIr-gCN not only demonstrate favorable Gibbs free energy change (ΔGmax) for the overall water splitting reaction of 0.02, 0.27, and 0.38 eV, respectively, but also feature low activation energies (Ea) for water dissociation, with CrCo-gCN, FeRu-gCN, and FeIr-gCN notably exhibiting the Ea of just 0.42, 0.33, and 0.42 eV, respectively. The introduction of an electronic descriptor (φ), derived from d electron count (Nd) and electronegativity (ETM), provides a quantifiable relationship with catalytic activity, where a lower φ corresponds to enhanced reaction kinetics. Specifically, φ values between 4.0-4.6 correlate with the lowest kinetic barriers, signifying a streamlined HER process. Our findings suggest that DACs with optimized φ values present a robust approach for the development of high-performance alkaline HER electrocatalysts, offering a pathway towards the rational design of energy-efficient catalytic systems.

Pharmacological and behavioural effects of tryptamines present in psilocybin-containing mushrooms.

BACKGROUND AND PURPOSE: Demand for new antidepressants has resulted in a re-evaluation of the therapeutic potential of psychedelic drugs. Several tryptamines found in psilocybin-containing "magic" mushrooms share chemical similarities with psilocybin. Early work suggests they may share biological targets. However, few studies have explored their pharmacological and behavioural effects. EXPERIMENTAL APPROACH: We compared baeocystin, norbaeocystin and aeruginascin with psilocybin to determine if they are metabolized by the same enzymes, similarly penetrate the blood-brain barrier, serve as ligands for similar receptors and modulate behaviour in rodents similarly. We also assessed the stability and optimal storage and handling conditions for each compound. KEY RESULTS: In vitro enzyme kinetics assays found that all compounds had nearly identical rates of dephosphorylation via alkaline phosphatase and metabolism by monoamine oxidase. Further, we found that only the dephosphorylated products of baeocystin and norbaeocystin crossed a blood-brain barrier mimetic to a similar degree as the dephosphorylated form of psilocybin, psilocin. The dephosphorylated form of norbaeocystin was found to activate the 5-HT2A receptor with similar efficacy to psilocin and norpsilocin in in vitro cell imaging assays. Behaviourally, only psilocybin induced head twitch responses in rats, a marker of 5-HT2A-mediated psychedelic effects and hallucinogenic potential. However, like psilocybin, norbaeocystin improved outcomes in the forced swim test. All compounds caused minimal changes to metrics of renal and hepatic health, suggesting innocuous safety profiles. CONCLUSIONS AND IMPLICATIONS: Collectively, this work suggests that other naturally occurring tryptamines, especially norbaeocystin, may share overlapping therapeutic potential with psilocybin, but without causing hallucinations.

Developing a PmSLP3-based vaccine formulation that provides robust long-lasting protection against hemorrhagic septicemia-causing serogroup B and E strains of Pasteurella multocida in cattle.

Background: Pasteurella multocida is a bacterial pathogen that causes a variety of infections across diverse animal species, with one of the most devastating associated diseases being hemorrhagic septicemia. Outbreaks of hemorrhagic septicemia in cattle and buffaloes are marked by rapid progression and high mortality. These infections have particularly harmful socio-economic impacts on small holder farmers in Africa and Asia who are heavily reliant on a small number of animals kept as a means of subsistence for milk and draft power purposes. A novel vaccine target, PmSLP-3, has been identified on the surface of hemorrhagic septicemia-associated strains of P. multocida and was previously shown to elicit robust protection in cattle against lethal challenge with a serogroup B strain. Methods: Here, we further investigate the protective efficacy of this surface lipoprotein, including evaluating the immunogenicity and protection upon formulation with a variety of adjuvants in both mice and cattle. Results: PmSLP-3 formulated with Montanide ISA 61 elicited the highest level of serum and mucosal IgG, elicited long-lasting serum antibodies, and was fully protective against serogroup B challenge. Studies were then performed to identify the minimum number of doses required and the needed protein quantity to maintain protection. Duration studies were performed in cattle, demonstrating sustained serum IgG titres for 3 years after two doses of vaccine and full protection against lethal serogroup B challenge at 7 months after a single vaccine dose. Finally, a serogroup E challenge study was performed, demonstrating that PmSLP-3 vaccine can provide protection against challenge by the two serogroups responsible for hemorrhagic septicemia. Conclusion: Together, these data indicate that PmSLP-3 formulated with Montanide ISA 61 is an immunogenic and protective vaccine against hemorrhagic septicemia-causing P. multocida strains in cattle.

High-harmonic spin-shearing interferometry for spatially resolved EUV magneto-optical spectroscopy.

We present a method for achieving hyperspectral magnetic imaging in the extreme ultraviolet (EUV) region based on high-harmonic generation (HHG). By interfering two mutually coherent orthogonally-polarized and laterally-sheared HHG sources, we create an EUV illumination beam with spatially-dependent ellipticity. By placing a magnetic sample in the beamline and sweeping the relative time delay between the two sources, we record a spatially resolved interferogram that is sensitive to the EUV magnetic circular dichroism of the sample. This image contains the spatially-resolved magneto-optical response of the sample at each harmonic order, and can be used to measure the magnetic properties of spatially inhomogeneous magnetic samples.

Effect of statin use on liver enzymes and lipid profile in patients with Non-Alcoholic Fatty Liver Disease (NAFLD).

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is an independent risk factor for cardiovascular disease (CVD). Statins are recommended for treatment of dyslipidemia to reduce the overall cardiovascular risk in patients with NAFLD. However, statin treatment was underutilized and the effect of statins on liver enzymes remained unclear in this patient population. OBJECTIVES: This study aimed to provide real-world evidence of the safety and effect of statin use in patients with NAFLD. METHODS: We conducted a cross-sectional survey study of adults with NAFLD using pooled data from the US NHANES database 2009-2018. NAFLD was defined by Fatty Liver Index (FLI) ≥ 60 and United States Fatty Liver Index (USFLI) ≥ 30. Multivariate regression analyses adjusted for baseline clinical and demographic characteristics were performed to compare the liver enzymes and lipid profile between statin and non-statin users. RESULTS: The study included 2,533 adults with NAFLD, representing 22.6 million individuals in the US, with 27% receiving statin treatment between 2009 and 2018. The mean differences of liver enzymes for AST, ALT, ALP, and GGT between statin and non-statin users were -0.86 (p=0.539), -3.49 (p=0.042), -0.25 (p=0.913), and 0.57 (p=0.901), respectively. In individuals with NAFLD and dyslipidemia, total cholesterol and LDL levels were significantly lower in statin users compared to non-statin users (mean difference, -28.9; p<0.001 and -27.7; p<0.001). CONCLUSION: The use of statins was not associated with elevated liver enzymes in patients with NAFLD. Significantly lower levels of ALT, total cholesterol, and LDL were observed in statin users compared to non-statin users.

Microglia and Dendritic Cells as a Source of IL-6 in a Mouse Model of Multiple Sclerosis.

Multiple sclerosis (MS) is a complex autoimmune disease of central nervous system (CNS) characterized by the myelin sheath destruction and compromised nerve signal transmission. Understanding molecular mechanisms driving MS development is critical due to its early onset, chronic course, and therapeutic approaches based only on symptomatic treatment. Cytokines are known to play a pivotal role in the MS pathogenesis with interleukin-6 (IL-6) being one of the key mediators. This study investigates contribution of IL-6 produced by microglia and dendritic cells to the development of experimental autoimmune encephalomyelitis (EAE), a widely used mouse model of MS. Mice with conditional inactivation of IL-6 in the CX3CR1+ cells, including microglia, or CD11c+ dendritic cells, displayed less severe symptoms as compared to their wild-type counterparts. Mice with microglial IL-6 deletion exhibited an elevated proportion of regulatory T cells and reduced percentage of pathogenic IFNγ-producing CD4+ T cells, accompanied by the decrease in pro-inflammatory monocytes in the CNS at the peak of EAE. At the same time, deletion of IL-6 from microglia resulted in the increase of CCR6+ T cells and GM-CSF-producing T cells. Conversely, mice with IL-6 deficiency in the dendritic cells showed not only the previously described increase in the proportion of regulatory T cells and decrease in the proportion of TH17 cells, but also reduction in the production of GM-CSF and IFNγ in the secondary lymphoid organs. In summary, IL-6 functions during EAE depend on both the source and localization of immune response: the microglial IL-6 exerts both pathogenic and protective functions specifically in the CNS, whereas the dendritic cell-derived IL-6, in addition to being critically involved in the balance of regulatory T cells and TH17 cells, may stimulate production of cytokines associated with pathogenic functions of T cells.

Neighborhood built environment, obesity, and diabetes: A Utah siblings study.

Background: This study utilizes innovative computer vision methods alongside Google Street View images to characterize neighborhood built environments across Utah. Methods: Convolutional Neural Networks were used to create indicators of street greenness, crosswalks, and building type on 1.4 million Google Street View images. The demographic and medical profiles of Utah residents came from the Utah Population Database (UPDB). We implemented hierarchical linear models with individuals nested within zip codes to estimate associations between neighborhood built environment features and individual-level obesity and diabetes, controlling for individual- and zip code-level characteristics (n = 1,899,175 adults living in Utah in 2015). Sibling random effects models were implemented to account for shared family attributes among siblings (n = 972,150) and twins (n = 14,122). Results: Consistent with prior neighborhood research, the variance partition coefficients (VPC) of our unadjusted models nesting individuals within zip codes were relatively small (0.5%-5.3%), except for HbA1c (VPC = 23%), suggesting a small percentage of the outcome variance is at the zip code-level. However, proportional change in variance (PCV) attributable to zip codes after the inclusion of neighborhood built environment variables and covariates ranged between 11% and 67%, suggesting that these characteristics account for a substantial portion of the zip code-level effects. Non-single-family homes (indicator of mixed land use), sidewalks (indicator of walkability), and green streets (indicator of neighborhood aesthetics) were associated with reduced diabetes and obesity. Zip codes in the third tertile for non-single-family homes were associated with a 15% reduction (PR: 0.85; 95% CI: 0.79, 0.91) in obesity and a 20% reduction (PR: 0.80; 95% CI: 0.70, 0.91) in diabetes. This tertile was also associated with a BMI reduction of -0.68 kg/m2 (95% CI: -0.95, -0.40). Conclusion: We observe associations between neighborhood characteristics and chronic diseases, accounting for biological, social, and cultural factors shared among siblings in this large population-based study.

Genomic insights unveil the plasmid transfer mechanism and epidemiology of hypervirulent Klebsiella pneumoniae in Vietnam.

Hypervirulent Klebsiella pneumoniae (hvKp) is a significant cause of severe invasive infections in Vietnam, yet data on its epidemiology, population structure and dynamics are scarce. We screened hvKp isolates from patients with bloodstream infections (BSIs) at a tertiary infectious diseases hospital in Vietnam and healthy individuals, followed by whole genome sequencing and plasmid analysis. Among 700 BSI-causing Kp strains, 100 (14.3%) were hvKp. Thirteen hvKp isolates were identified from 350 rectal swabs of healthy adults; none from 500 rectal swabs of healthy children. The hvKp isolates were genetically diverse, encompassing 17 sequence types (STs), predominantly ST23, ST86 and ST65. Among the 113 hvKp isolates, 14 (12.6%) carried at least one antimicrobial resistance (AMR) gene, largely mediated by IncFII, IncR, and IncA/C plasmids. Notably, the acquisition of AMR conjugative plasmids facilitated horizontal transfer of the non-conjugative virulence plasmid between K. pneumoniae strains. Phylogenetic analysis demonstrated hvKp isolates from BSIs and human carriage clustered together, suggesting a significant role of intestinal carriage in hvKp transmission. Enhanced surveillance is crucial to understand the factors driving intestinal carriage and hvKp transmission dynamics for informing preventive measures. Furthermore, we advocate the clinical use of our molecular assay for diagnosing hvKp infections to guide effective management.

Tailored synthesis of pH-responsive biodegradable microcapsules incorporating gelatin, alginate, and hyaluronic acid for effective-controlled release.

In response to escalating environmental concerns and the urgent need for sustainable drug delivery systems, this study introduces biodegradable pH-responsive microcapsules synthesized from a blend of gelatin, alginate, and hyaluronic acid. Employing the coacervation process, capsules were created with a spherical shape, multicore structure, and small sizes ranging from 10 to 20 µm, which exhibit outstanding vitamin E encapsulation efficiency. With substantial incorporation of hyaluronic acid, a pH-responsive component, the resulting microcapsules displayed noteworthy swelling behavior, facilitating proficient core ingredient release at pH 5.5 and 7.4. Notably, these capsules can effectively deliver active substances to the dermal layer under specific skin conditions, revealing promising applications in topical medications and cosmetics. Furthermore, the readily biodegradable nature of the designed capsules was demonstrated through Biochemical Oxygen Demand (BOD) testing, with over 80 % of microcapsules being degraded by microorganisms after one week of incubation. This research contributes to the development of responsive microcapsules and aligns with broader environmental initiatives, offering a promising pathway to mitigate the impact of microplastics while advancing various applications.

Self-Assembly of the Porphyrin Monomer on the Surface of Fe/Graphene Material: a Novel Sensing Material for the Detection of Chloramphenicol Antibiotic in Aqueous solution.

Currently, electrochemical sensors are being developed and widely used in various fields, and new materials are being explored to enhance the precision and selectivity of the sensors. The present investigation involved the fabrication of a Fe/graphene/porphyrin nanocomposite through self-assembly, wherein the individual porphyrin molecules were arranged on the Fe/graphene nanomaterials' surface. The Fe/graphene nanoparticles were synthesized utilizing a green approach, wherein leaf extract was employed as the reducing agent. The resulting materials underwent comprehensive characterization using a range of contemporary techniques, including scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and Raman spectroscopy. The study's findings revealed that the nanocomposites of Fe/graphene/porphyrin comprised zero-valent iron nanoparticles, exhibiting an average particle size ranging from 15 to 60 nm. These nanoparticles were seen to be evenly dispersed across the graphene sheets. The presence of nanostructure porphyrin nanofibers, measuring 20 nm in diameter, was also shown to exhibit strong integration with the surface of the Fe/graphene nanomaterials. The electrochemical properties of the Fe/graphene/porphyrin nanocomposite were also investigated, demonstrating that the prepared material could be effectively employed as a sensing electrode in the electrochemical sensor for detecting Chloramphenicol (CAP) through CV, EIS, and DPV techniques using a three-electrode electrochemical system. Under optimal conditions, Fe/graphene/porphyrin exhibited a high current response when detecting CAPs. Electrochemical sensors created using Fe/graphene/porphyrin nanocomposite have high stability and repeatability, and they hold promise in developing sensors capable of identifying other antibiotic residues in agriculture.