Browse Articles

Gender discrimination and personal and professional development fostered by allopathic medical schools in the United States

Background Despite prevalent gender discrimination in medical education, its influence on personal and professional development, foundational competencies in medical training per the Association of American Medical Colleges (AAMC), remains unclear. This retrospective cross-sectional study assesses how experiences of gender discrimination in medical school influence personal and professional identity formation (PPIF) among males and females. Methods Deidentified student-level data were procured from the AAMC data warehouse for 37,610 MD students who matriculated in 2014–2015 and took the Graduation Questionnaire (GQ) between 2016–2020. Gender discrimination frequency was categorized as ‘Never’, ‘Isolated’, and ‘Recurrent’ from GQ responses to questions about denial of opportunities, offensive remarks, and lower evaluations due to gender. Students self-reported their sex as male, female or declined to answer. PPIF was assessed using two separate GQ metrics assessing student agreement on a 5-point Likert scale that their medical school fostered and nurtured their development as a person and a future physician, respectively, and dichotomized. Results Female students experienced higher rates of isolated (12.6%) and recurrent (20.1%) gender discrimination than males (4.3% isolated, 6.2% recurrent). Females reported slightly lower personal (71.2%) but similar professional development (92.2%) rates compared to males (73.4% personal, 91.2% professional). Both sexes experiencing gender discrimination had lower likelihoods of PPIF than their counterparts without these experiences. If recurrent discrimination occurred, the aRR (95%CI) of professional development was 0.89 (0.87–0.90) for females and 0.78 (0.74–0.81) for males, while for personal development, it was 0.69 (0.67–0.71) for females and 0.61 (0.58–0.66) for males. Compared to females, males showed sharper declines in professional development as discrimination frequency increased from never to isolated (aRR = 0.93, 95% CI [0.92–0.94], p < 0.001) and isolated to recurrent (aRR = 0.95, 95% CI [0.93–0.97], p < 0.001). Conclusions Gender discrimination negatively influences PPIF for both female and male medical students. Efforts to combat discrimination in medical training and promote holistic student development should be considered. Future work is needed to understand the influence of gender discrimination on the comprehensive development of gender-diverse medical students.

Correlation analysis of blood metabolites and periventricular leukomalacia in preterm infants two weeks postnatally

Artificial intelligence in the diagnosis of deep vein thrombosis: A scoping review

Deep vein thrombosis (DVT) is the formation of thrombi in the deep venous system, most often in the lower extremities. Although usually not life-threatening, DVT requires timely diagnosis to prevent complications such as pulmonary embolism and post-thrombotic syndrome. The growing demand for image interpretation has generated interest in applying artificial intelligence (AI) to automated DVT detection. This scoping review analyzes the performance of artificial intelligence in diagnosing DVT using computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US). We conducted a search across seven databases from inception to May 2025 using terms related to deep vein thrombosis, artificial intelligence, and machine learning. Eligible studies were limited to those evaluating DVT diagnosis using CT, MRI, or ultrasound. Two independent reviewers selected eligible studies, and quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Eleven studies published between 2021 and 2025 met the inclusion criteria. Some of the AI algorithms included RetinaNet, Deep R-Belief Neural Networks, and Sooty Tern Optimization. US-based models were the most studied algorithms, with sensitivities and specificities ranging from 68 to 100% and 70–100%, respectively. The MRI-based model achieved sensitivities, specificities, and accuracies of 95% to 97%. One CT-based model demonstrated a sensitivity of 83%. Studies evaluated across multiple imaging datasets showed high sensitivities, specificities, and precision of 96% or higher. Future research should prioritize multicenter validation and integration of clinical factors. In addition, explainable frameworks capable of integrating multiple imaging datasets must be developed with attention to workflow efficiency and cost-effectiveness to support clinical translation. The results indicate that AI is best situated as a supplementary tool rather than a replacement for expert interpretation in DVT diagnosis.

Retraction Note: Nano-Bio Soil Improvement (NBSI) with Micro-, Nano-, and Pico- Typha latifolia: a green material approach

Correction: Quantum-inspired pedestrian mobility modeling: Applying probabilistic spatial simulation to urban walkability and thermal comfort in Sri Lanka

Anti‐CRISPR Protein Regulates CRISPR/Cas12a Fusogenic‐Nanovesicle‐Based Platform for Extracellular Vesicle‐Encapsulated Non‐Nucleic Acid Target In‐Vesicle Detection

ABSTRACT The detection of non‐nucleic acid targets encapsulated in extracellular vesicles (EVs) faces two major challenges: (1) difficulties in efficient isolation and the risk of content degradation, and (2) the low abundance of target molecules encapsulated in EVs always leads to failed signal transduction and inadequate output signal intensity. To overcome these limitations, we propose a high‐efficiency in‐vesicle analysis strategy that integrates targeting probe delivery and regulation by protein signal amplification. By applying aptamer‐mediated membrane fusion and “locked‐activated” CRISPR‐Cas12a‐AcrVA1 (LACA) for protein signal regulation, we fabricated a yly12‐aptamer‐functionalized self‐assembled nanovesicle which encapsulate LACA‐system (yly12‐lipo@Cas12a nanovesicle) as an in‐vesicle bioanalytical platform. Leveraging the high specificity of the aptamer and the regulatory function of AcrVA1 in selectively modulating Cas12a activity, the platform enables highly specifiec and sensitive detection, offering advantages of simple operation and versatility across platforms within only 2.5 h. Clinical analysis demonstrated effective differentiation between patients and healthy controls, yielding high diagnostic performance with an AUC of 0.965. The proposed platform shows great potential for EV‐carrying protein biomarker analysis and has broad prospects for the disease's diagnosis in clinical settings.

Analysis of decision support system of basketball sports competition based on machine learning and IoT

Emotional demands and burnout: Differential moderating effect of job resources and age

This study, based on the Job Demands–Resources (JD-R) model, investigates how perceived and contact-related emotional demands contribute to burnout, and whether job resources -deep acting, meaning of work, work control, and social support at work-buffer these effects. A cross-sectional online survey was conducted among professionals in healthcare, care, and human service roles ( N =  1,506). Structural Equation Modelling (PLS-SEM) was used to examine moderating effects of job resources on the relationships between emotional demands and the burnout dimensions of exhaustion and disengagement. Both types of emotional demands were positively associated with both burnout dimensions. While job resources were generally negatively associated with exhaustion and disengagement, they did not moderate the effects of emotional demands in the expected buffering direction. Instead, meaning of work and social support amplified the relationships between contact-related and perceived emotional demands, respectively, and exhaustion. Exploratory analyses revealed no significant linear or curvilinear age-based moderation, suggesting that these moderation patterns function similarly across age groups. Overall, the findings indicate that while job resources may reduce general burnout, they are not universally protective in emotionally demanding work. This study highlights the need to refine the JD-R assumption that resources consistently buffer job demands and underscores the importance of identifying alternative resources and targeted interventions in emotionally demanding roles.

Yang Yao

Highly Regioselective Trifluoromethylation of Unprotected Phenols and Anilines Enabled by an Engineered P450 Peroxizyme System

ABSTRACT The trifluoromethyl (CF 3 ) group is a pivotal motif in pharmaceuticals, agrochemicals, and functional materials, yet achieving direct and regioselective aromatic C─H trifluoromethylation—especially for phenols and anilines—remains a formidable challenge. Here, we transform a dual‐functional small molecule (DFSM)‐facilitated P450BM3 peroxizyme into a versatile biocatalytic platform that enables highly ortho ‐selective trifluoromethylation of diverse phenols and anilines. Through protein engineering, we achieve up to 98% ortho ‐selectivity for phenol—the first highly selective enzymatic trifluoromethylation reported. The system exhibits broad substrate scope and functional‐group tolerance, delivering >99% regioselectivity and over 6700 turnovers for leading substrates. Mechanistic studies confirm a radical pathway and reveal that selectivity is engineered via synergistic mutations‐DFSM interactions that pre‐organize substrates in a confined active site. This work establishes a programmable strategy to bridge biocatalysis and organofluorine chemistry, offering a sustainable route to valuable fluorinated building blocks.

Effects of chin supported maxillary protraction on symphsis morphology

Interpretable machine learning via symbolic classification of radiomic texture and morphological features for pediatric pneumonia detection from chest X-rays

Explainable artificial intelligence in medical imaging is currently dominated by post-hoc tools that rationalise the decisions of otherwise opaque deep networks, without providing, most of the time, a robust and transparent decision rule. This paper presents an interpretable mathematical model for pneumonia detection in pediatric chest radiographs. We propose a symbolic classification framework that evolves a non-linear closed-form diagnostic formula directly from a compact set of clinically grounded radiomic markers, including entropy, solidity, and fractal dimension. To our knowledge, this is the first single-formula symbolic classifier reported for pediatric pneumonia detection on the specific dataset. The symbolic classifier achieved 87% accuracy and AUC = 0.93 under 10-fold cross-validation. When the selected closed-form equation was applied to the filtered independent hold-out test set, it achieved 79.1% accuracy and AUC = 0.89. The equation has been further validated and re-calibrated on an independently acquired external dataset. With a parameter count several orders of magnitude smaller than that of competing deep learning models, and an auditable closed-form expression, the proposed model provides a lightweight, transparent baseline suited to resource-constrained inference and regulatory audit. The proposed framework can be applied in complementary ways to existing deep learning pipelines, as an intrinsically interpretable alternative that broadens the methodological repertoire for clinically transparent diagnosis.

Electrostatic Field Effects in Covalent Organic Frameworks for Photocatalytic CO ₂ ‐to‐CO Conversion beyond 1000 mmol g _Co ⁻¹ h ⁻¹

ABSTRACT Covalent Organic Frameworks (COFs) with unique π‐structures and exceptional stability are promising candidates for photocatalytic CO 2 conversion. However, most reported COFs exhibit significant recombination of photo‐generated charges and holes, along with low CO 2 chemisorption, leading to suboptimal photocatalytic performance. Here, we designed covalently linked two‐dimensional cobalt (II) porphyrin layers and introduced various tetra‐alkylammonium cations (─CH 2 N + (CH 3 ) 3 , ─CH 2 CH 2 N + (CH 3 ) 3 , or ─CH 2 CH 2 CH 2 N + (CH 3 ) 3 ). The tetra‐alkylammonium cations within the ionic covalent organic framework (iCOF) stabilize the intermediates of the photoreduction reaction and accelerate the reaction kinetics through electrostatic field interactions, thereby facilitating the conversion of *CO 2 to *CO. Molecular dynamics simulations further indicate that tetra‐alkylammonium side chains increase CO 2 residence time in the pores, thereby enhancing interaction with catalytically active sites. Furthermore, the electrostatic field effects of the tetra‐alkylammonium cations increase the charge density at the Co center, stabilize CO 2 reaction intermediates, and facilitate proton transfer. Remarkably, these advantageous effects synergistically contribute to the photocatalytic CO 2 ‐to‐CO conversion. The CoTph‐3C‐N + COF achieves an impressive CO initial production rate of 1006 mmol g Co −1 h −1 and a quantum efficiency of 5.67% at 420 nm, which is 17 times that of the pristine COF. This strategy offers a novel approach to designing various photocatalytic systems aimed at efficient chemical transformations.

Validated analytical workflow for quantifying proline metabolism related amino acids in HaCaT cells with LC-Q-TOF-MS

Abstract It is known that altered amino acid metabolism can influence immunological responses, thus studying the molecular mechanisms underlying these changes requires analytical methods for reliably determining the quantities of individual analytes. To address the ongoing need for quantitative assessment of amino acid composition, a validated method for determining their quantities was proposed. This study presents the development and validation of a novel method for the quantitative analysis of selected amino acids using high-performance liquid chromatography coupled with a quadrupole time-of-flight (Q-TOF) mass spectrometer equipped with an electrospray ionization source. The method has been satisfactorily validated in terms of linearity, range, precision, accuracy, and stability. Its applicability to biological matrices was demonstrated by the successful quantification of amino acids in HaCaT cell lysates. Owing to the use of a robust, state-of-the-art analytical platform based on Q-TOF technology, which enables high-resolution mass detection, the method is readily adaptable for the inclusion of additional analytes and can be extended to other complex biological samples. The applicability of the method for the simultaneous determination of selected amino acids was demonstrated, and the method successfully applied to the HaCaT cell lysates.

Do South Korean adults have insufficient levels of physical activity? Domain patterns and associations with self-rated health

Objectives The study aimed to evaluate domain-specific physical activity (PA) patterns in South Korea, where the prevalence of insufficient PA is high, and assess their association with self-rated health (SRH). Methods Data from 32,005 South Korean adults aged 20–79 from the Korean National Health and Nutrition Examination Survey (2016–2021) were analyzed. Domain-specific PA (leisure-time (LTPA), transportation-related (TPA), and work-related (OPA)) were measured using the Global Physical Activity Questionnaire. PA was categorized into <10, 10–149, and ≥150 min/week, labeled as “inactive,” “insufficient,” and “meeting PA guidelines (PAG).” Each individual’s primary PA domain was defined by the domain with the largest proportion of their total PA time. Logistic regression was used to examine associations between PA patterns and good SRH. Results In total, 46.3% met PAG, while 30.8% were inactive. TPA was the primary domain for 59.0% of non-inactive individuals. This emphasis on TPA was pronounced among women, the elderly, and those with insufficient PA. Only 8.7% had ≥ 10 minutes of continuous OPA per week, and 19% met PAG through LTPA alone. LTPA showed a clear positive dose-response relationship with good SRH. TPA showed a weak positive association, while OPA showed an inverse association. Conclusions The high prevalence of insufficient PA among Korean adults is likely primarily attributed to low levels of OPA. TPA is the primary PA domain. Only LTPA showed clear health benefits regarding SRH, but a large proportion did not meet PAG through LTPA. Monitoring domain-specific PA patterns is needed for developing effective PA promotion strategies in Korea.

A Synthetic Epitope‐Binding Receptor Enables In Situ Recruitment of Endogenous Bioactive Ligand for Tissue Regeneration

ABSTRACT In tissue engineering, tissue repair efficacy highly relies on the delivery of growth factor through scaffold biomaterials. However, the lack of controllability in use of these exogenous bioactive ligands raises significant ethical and safety concerns. In this context, we propose a ligand‐recruiting scaffold system for endogenous growth factor delivery, based on molecularly imprinted polymers (MIPs) featuring tailor‐made recognition toward target ligand. As a proof of concept, the osteogenic growth peptide (OGP), an endogenous growth factor for bone repair and regeneration, was selected as target ligand for MIPs design. The nonactive N‐terminal epitope of OGP (OGP 1‐9 ) was used as the template, and subsequently MIPs with tailor‐made recognition sites toward the OGP 1‐9 epitope was synthesized via a solid‐phase imprinting strategy. Due to specific epitope‐binding ability, the MIPs exhibited receptor‐like high affinity toward full‐length OGP while leaving its bioactive C‐terminal OGP 10‐14 exposed. Upon integration into scaffold biomaterial, the MIPs could enhance in situ osteogenic activity through epitope recognition‐mediated recruitment of endogenous OGP, thereby leading to improved bone tissue repair in vivo. This work demonstrates the potential of MIPs‐mediated ligand recognition for in situ recruitment of endogenous growth factors and provides new ideas for on‐demand design of growth factor‐free tissue engineering scaffolds.

Interplay of electron–phonon coupling, dissipative phonon bath, and electron–electron interaction in a triangular quantum-dot trimer

Identifying potential inhibitors for wild-type EGFR tyrosine kinase through a cross-talk pathway strategy and an in-silico drug repurposing method

Wild-type epidermal growth factor receptor (EGFRwt) is commonly implicated in tumor growth, yet most of the approved EGFR-targeted therapies are against mutant receptor isoforms, and patients with EGFRwt-dependent cancers have limited treatment options. We herein explored the potential to inhibit EGFRwt with five top screened hits retrieved from Food and Drug Administration (FDA)-approved kinase inhibitors library, originally developed for MET-overexpressing cancers for potential drug repurposing approach. Induced-fit docking showed that all five molecules bound the ATP-binding pocket of EGFRwt, with compound D4 emerging as the top candidate due to key interactions with ASP855 (DFG motif) and MET793 (hinge region), underscoring its favorable engagement. To further assess this interaction, we then conducted 100 ns molecular dynamics (MD) simulations, confirming the structural stability of the EGFRwt–D4 complex, with stable root-mean-square deviation (RMSD) values and maintained secondary structure elements. Free energy of binding calculations using the Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA) method supported these findings, with D4 showing the most favourable interaction, dominated by Van Der Waals and electrostatic contributions from key catalytic amino acid. Our research, with further experimental validation, could be helpful to support that certain MET inhibitors, especially D4, are promising competitive inhibitors of EGFRwt, offering potential for the development of new therapeutic strategies targeting EGFRwt-driven cancers.

Terminal Hydroxylated Side‐Chains Enhance Ionic‐Electronic Coupling Efficiency in Small‐Molecule Semiconductors

ABSTRACT Small‐molecule semiconductors play a crucial role in organic electronics. However, when employed as organic mixed ionic‐electronic conductors (OMIECs), their limited ionic transport capabilities will obstruct efficient ionic‐electronic coupling. To address this issue, we propose a universal strategy by introducing terminal hydroxylated ethylene glycol (EG‐OH) side chains onto small‐molecule semiconductors. The 4Cl‐PDI‐EG‐OH, synthesized using this strategy, exhibits higher transconductance, faster response time, and better stability than the common ethylene glycol (EG)‐based 4Cl‐PDI‐EG in organic electrochemical transistors (OECTs). X‐ray single‐crystal diffraction and spectroscopic studies reveal that the terminal hydroxyl interlocking promotes the formation of ordered side‐chain arrangements, broadening the ionic transport channels. Concurrently, this induces the formation of short‐range charge‐transfer (CT)‐coupled J‐aggregates ( J CT ) within the backbones, maintaining efficient carrier mobility, thus achieving high‐efficiency ionic‐electronic coupling. Further applying this strategy to representative small‐molecule skeletons yields significant performance improvements. Specifically, BTP‐EG‐OH exhibits a remarkable transconductance of 101.9 mS, which is comparable to that of many high‐performance polymer‐based OECTs. This study shows that the EG‐OH side chain represents a superior choice compared to the currently common EG side chain for developing high‐performance small‐molecule OMIECs.

Circularly Polarized Luminescent and Melt‐Processable Copper(I)‐Organic Glasses Based on 2,2′‐Bis(diphenylphosphino)‐1,1′‐binaphthyl

ABSTRACT The melting and vitrification behavior of metal–organic materials endows them with high processability, enabling the formation of bulk solids with potential in optical applications. Nevertheless, obtaining metal–organic glasses with chiroptical properties, such as circularly polarized luminescence (CPL), remains challenging due to the limited thermal and mechanical stability of current chiral metal‐organic materials. Here, we report a pair of homochiral copper(I) cyanide complexes based on 2,2′‐bis(diphenylphosphino)‐1,1′‐binaphthyl (BINAP) that can be readily vitrified by either melt‐quenching or desolvation. Structural analysis reveals that vitrification disrupts only the intermolecular stacking of the complexes, while preserving the local coordination environment. The resulting melt‐quenched glasses are CPL‐active and exhibit yellow–orange triplet excited state decay via thermally activated delayed fluorescence (TADF) at room temperature, which is environment‐dependent due to an additional 3 BINAP↔ 3 (Cu→BINAP) CT (CT = charge transfer) equilibrium. Centimeter‐sized monoliths and thin films can be fabricated by molding and thermal annealing, highlighting their excellent processability. Moreover, the glasses can be recrystallized by solvent vapor treatment, which triggers distinct changes in luminescent properties. These results establish BINAP‐based copper(I) cyanide complexes as a versatile platform for the design of CPL‐active metal–organic glasses and point to their promise in optoelectronic applications.