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A Bayesian active learning platform for scalable combination drug screens

Gestational diabetes mellitus causes genome hyper-methylation of oocyte via increased EZH2

Energy management strategy for methanol hybrid commercial vehicles based on improved dung beetle algorithm optimization

In order to solve the problem of poor adaptability and robustness of the rule-based energy management strategy (EMS) in hybrid commercial vehicles, leading to suboptimal vehicle economy, this paper proposes an improved dung beetle algorithm (DBO) optimized multi-fuzzy control EMS. First, the rule-based EMS is established by dividing the efficient working areas of the methanol engine and power battery. The Tent chaotic mapping is then used to integrate strategies of cosine, Lévy flight, and Cauchy Gaussian mutation, improving the DBO. This integration compensates for the traditional dung beetle algorithm’s tendency to fall into local optima and enhances its global search capability. Subsequently, fuzzy controllers for the driving charging mode and hybrid driving mode are designed under this rule-based EMS. Finally, the improved DBO is used to obtain the optimal control of the fuzzy controller by taking the fuel consumption of the whole vehicle and the fluctuation change of the battery state of charge (SOC) as the optimization objectives. Compared to traditional rule-based energy management strategies, the optimized fuzzy control using the enhanced DBO continuously adjusts the torque distribution between the engine and motor based on the vehicle’s real-time state, resulting in a 9.07% reduction in fuel consumption and a 3.43% decrease in battery SOC fluctuations.

The prevalence of multidrug resistance in Staphylococcus hominis isolated from clinical materials

Prediction of microvascular invasion in hepatocellular carcinoma using a preoperative serum C-reactive protein-based nomogram

Soft cluster-rectangle method for eliciting criteria weights in multi-criteria decision-making

Coordinatively stiffen and toughen polymeric gels via the synergy of crystal-domain cross-linking and chelation cross-linking

Remote epitaxy and exfoliation of vanadium dioxide via sub-nanometer thick amorphous interlayer

Correction: Validation of the Strengths and Difficulties Questionnaire (SDQ) emotional subscale in assessing depression and anxiety across development

Four-dimensional anatomical spinal reconstruction using pre-bent rods in thoracic adolescent idiopathic scoliosis

PEGDA-based HistoBrick for increasing throughput of cryosectioning and immunohistochemistry in organoid and small tissue studies

RUNX1 promotes proliferation of cervical cancer through TGFB2-MAPK pathway

Stabilization of oxygen vacancy ordering and electrochemical-proton-insertion-and-extraction-induced large resistance modulation in strontium iron cobalt oxides Sr(Fe,Co)Oy

Atomically distributed Al-F3 nanoparticles towards precisely modulating pore size of carbon membranes for gas separation

A generalised catalytic model to assess changes in risk for multiple reinfections with SARS-CoV-2

Background Monitoring trends in multiple infections with SARS-CoV-2, following several pandemic waves, provides insight into the biological characteristics of new variants, but also necessitates methods to understand the risk of multiple reinfections. Objectives We generalised a catalytic model designed to detect increases in the risk of SARS-CoV-2 reinfection, to assess the population-level risk of multiple reinfections. Methods The catalytic model assumes the risk of reinfection is proportional to observed infections and uses a Bayesian approach to fit model parameters to the number of nth infections among individuals that occur at least 90 days after a previous infection. Using a posterior draw from the fitted model parameters, a 95% projection interval of daily nth infections is calculated under the assumption of a constant nth infection hazard coefficient. An additional model parameter was incorporated for the increased reinfection risk detected during the Omicron wave. The generalised model’s performance was then assessed using simulation-based validation. Key findings No additional increase in the risk of third infection was detected after the increase detected during the Omicron wave. Using simulation-based validation, we show that the model can successfully detect increases in the risk of third infections under different scenarios. Limitations Even though the generalised model is intended to detect the risk of nth infections, it is validated specifically for third infections, with its applicability for four or more infections being unconfirmed. Furthermore, the method’s sensitivity to low counts of nth infections, limits application in settings with small epidemics, limited testing coverage or early in an outbreak. Conclusions The catalytic model was successfully adapted to detect increases in the risk of nth infections, enhancing our capacity to identify future changes in the risk of nth infections by SARS-CoV-2 or other similar pathogens.

Analysis of user behavior and satisfaction under the elderly adaptation mode of an APP based on the fuzzy-IPA model

Age-related morphological changes of the pubic symphyseal surface: using three-dimensional statistical shape modeling

AbstractComputational analysis of the pubic symphyseal surface is widely used for accurate age estimation, offering quantitative precision through the detection of subtle morphological changes. However, these methods often lack insights into the underlying morphological changes across different age groups. To bridge this gap, the study utilizes statistical shape modeling (SSM), a versatile tool capable of describing diverse morphological variations within populations. This study aimed to elucidate the direction and extent of these morphological changes, identify the contributing factors, and pinpoint key variations crucial for distinguishing between age groups. Computed tomography (CT) scans of 252 subjects from the National Forensic Service of South Korea were employed, subjected to preprocessing and landmark-based alignment. Through this approach, the study visualized and validated significant age-related morphological changes and highlighted the shape variations essential for differentiating between consecutive age groups. This study holds significance in elucidating the intricate nature of age-related morphological changes in the pubic symphyseal surface. Thus, these findings can serve as valuable cornerstones for enhancing age-at-death estimation techniques in forensic anthropology.

Epidemiological characteristics of imported malaria related to international travel in the Republic of Korea from 2009 to 2018

General (hetero)polyaryl amine synthesis via multicomponent cycloaromatization of amines

Functional large-conductance calcium and voltage-gated potassium channels in extracellular vesicles act as gatekeepers of structural and functional integrity

Abstract Extracellular vesicles (EVs) are associated with intercellular communications, immune responses, viral pathogenicity, cardiovascular diseases, neurological disorders, and cancer progression. EVs deliver proteins, metabolites, and nucleic acids into recipient cells to effectively alter their physiological and biological response. During their transportation from the donor to the recipient cell EVs face differential ionic concentrations, which can be detrimental to their integrity and impact their cargo content. EVs are known to possess ion channels and transporters in their membrane but neither the function nor the role of these channels in EVs is known. In this study, we discover a functional calcium-activated large-conductance potassium channel (BKCa) in the membrane of EVs. Furthermore, we establish that BKCa is essential for the structural and functional integrity of EVs. Together, these findings establish the critical role of ion channels such as BKCa in functioning as gatekeepers and maintaining EV-mediated signaling.