Browse Articles

The mediating role of professional identity between role models and self-determination in medical students: A multicenter cross-sectional study

Objective This study aimed to investigate self-determination, explore the mediating role of professional identity between role models and self-determination, and detect how role models and professional identity contribute to the development of self-determination among medical students. Methods A multicenter cross-sectional descriptive study involving 289 medical students in China was conducted. The Self-Determination Scale (SDS), Professional Identity Scale (PIS), and Sense of Admiration Scale (SAS) were employed to collect data. The bootstrapping method was used to analyze the mediating effect of professional identity between role models and self-determination. Results The average score on the SDS was 71.21 ( SD  = 11.72), while the mean score on the PIS was 69.49 ( SD  = 11.57), and the mean score on the SAS was 61.48 ( SD  = 10.41). A high level of role model perception had a significant direct effect (40.54%) on the degree of self-determination among medical students. Furthermore, professional identity had a significant positive mediating effect (54.83%) on the relationship between role models and self-determination. Conclusion Medical educators should focus on creating positive role models and enhancing their perceptions of these role models to foster self-determination among medical students. Additionally, strengthening professional identity could indirectly enhance the self-determination of medical students.

Author Correction: Identification of a non-inhibitory aptameric ligand to CRL2ZYG11B E3 ligase for targeted protein degradation

The open-source multi-wavelength non-invasive blood glucose sensing system

Potential association of certain microRNA gene polymorphisms with recurrent pregnancy loss susceptibility in Saudi women

MicroRNA (miRNA) polymorphisms are increasingly recognized as important regulators of reproductive outcomes, but their role in recurrent pregnancy loss (RPL) is still unexplored in specific populations. This case control study investigated six miRNA polymorphisms (miR-10-A > T, miR-125-G > A, miR-146a-C > G, miR-149-T > C, miR-323b-C > T, miR-499-A > G) in 50 Saudi women with idiopathic (≥ 2 losses) and 50 matched controls (≥ 1 live birth, no loss history) using PCR Sanger sequencing. Significant associations were found for heterozygous genotypes of miR-146a-C > G (OR=2.29, 95% Cl:1.02–5.18, *p* = 0.046) and miR-149-T > C (OR=2.67, 95% Cl:1.08–6.61, *p* = 0.034) with higher prevalence in RPL patients versus controls, while other polymorphisms showed no significant association (*p* > 0.05). These results suggest miR-146a and miR-149 can contribute to RPL susceptibility in Saudi women, highlighting their potential as population-specific genetic biomarkers and underscoring the need for further research into miRNA-mediated pregnancy maintenance mechanisms.

Doping-induced magnetic phase transition enables all-electrical spin control in CrSBr

Composite material surface microscopic defect detection and classification combining diffusion models and zero-shot learning

Correction: How fake news can turn against its spreader

Distinct gastrointestinal microbial signatures predict parasite levels in controlled Plasmodium infections in both rhesus macaques and humans

Lipidomics of polarized macrophages in the human adipose tissue

Abstract Macrophages are critical components of the innate immune system that adapt their function based on local microenvironmental cues. In adipose tissue, macrophage polarization is intimately linked to metabolic regulation and inflammation. In this pilot study, we performed lipidomic profiling to characterize the phospholipid composition of pro-inflammatory (PI-ATM) and non-inflammatory (NI-ATM) macrophages isolated from visceral adipose tissue of living kidney donors. Tissue samples were processed, and macrophages were isolated and sorted using CD14 and CD16 markers. Lipids were extracted by methyl tert -butyl ether, and differences in the lipidome were analyzed using the optimized UHPLC-MS method. PI-ATM exhibited a higher abundance of lipids across various lipid classes than NI-ATM. Phosphatidylethanolamines and ether lipids derived from phosphatidylethanolamines and phosphatidylcholines were most frequently found among the significantly altered lipids. The majority of significantly altered lipid species contained an octadecenoic aliphatic chain. These findings suggest that alterations in membrane lipid composition - particularly ether lipids and phosphatidylethanolamines - may play a pivotal role in macrophage polarization and adipose tissue inflammation. Our study provides novel insights into the lipidomic regulation of macrophage function in human adipose tissue and identifies potential targets for therapeutic intervention in metabolic disorders.

Correction: Demand structure prediction and adaptation path of rural teachers in western China under population change

Evidence for high-frequency hearing in a Permian stem reptile

Anisotropic pullout behavior of bauxite slag-geogrid interfaces

Predicting the influence of homologous recombination repair deficiency genes on glioma heterogeneity and patient prognosis using multi-omics analysis and machine learning

Background Glioma is the most common malignant tumor of the central nervous system, and homologous recombination deficiency (HRD) may play a crucial role in its progression. Our study aimed to predict the impact of HRD on glioma heterogeneity and patient prognosis from a multi-omics perspective. Methods We integrated HRD-related gene expression levels and survival information from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Using a combination of machine learning algorithms, we identified the optimal algorithm and constructed the HRD Index model. After validating the model’s accuracy, we assessed the expression heterogeneity of HRD-related genes in vitro using quantitative polymerase chain reaction (qPCR). Multiple omics analyses, including enrichment analysis, genomics, prediction of immune cell subtype infiltration, and drug sensitivity, were employed to demonstrate the heterogeneity and clinical predictive significance of the HRD Index in glioma. Results Through algorithm selection, the LASSO-RSF (Least Absolute Shrinkage and Selection Operator – Random Survival Forest) algorithm identified 7 genes (POLR2F, FANCB, PTEN, PLK3, INO80D, PRMT6, and UNG) to construct the HRD Index. Model validation demonstrated excellent accuracy. qPCR results revealed differential expression of these HRD Index genes among different cell lines. Samples grouped by HRD Index showed potential differences in certain cytokine and receptor pathways, as well as varying gene mutation frequencies between groups. Drug sensitivity analysis indicated that the HRD Index could predict treatment efficacy for specific drugs. Conclusion Our HRD Index model based on these seven genes significantly correlated with clinical prognosis in glioma patients and holds promise for guiding clinical management.

Recombination junctions from antibody isotype switching classify immune and DNA repair dysfunction

Abstract Personalized assessment of immunocompetence and DNA double-strand break (DSB) repair requires methods that are sensitive to genetic and molecular complexity beyond the well-known monogenic disorders. Inspired by decades of research using B cells to study DNA repair processes, here we present SWIBRID (SWItch junction Breakpoint Repertoire IDentification), a tool to systematically profile genomic junctions generated in vivo during antibody class switch recombination (CSR) in B cells. As CSR junctions reflect immune diversity and DNA repair proficiency, SWIBRID detects phenotypic manifestations of deficiencies via a highly scalable, blood-based PCR followed by long-read sequencing and bioinformatic analysis. We show that specific DNA repair defects, including cancer-associated mutations, exhibit distinct CSR junction patterns. Notably, SWIBRID distinguishes different types of DSB repair knockouts and identifies the respective genetic defect in cell lines. In 68 patients, we detect immunodeficiencies and DNA repair defects with high accuracy (area under the curve 0.99 and 0.84, respectively), and identify previously uncharacterized patient groups as well as patient-specific CSR junction signatures. With SWIBRID, we seek to advance the identification of pathogenic defects, support early diagnosis, and address molecular heterogeneity that drives variable clinical outcomes.

Synergistic role of Trichormus variabilis and zeolites in three-layer culturing system for modulating the wastewater effluent community

Spatial patterning of hypertension and its association with comorbidities and risk factors: A cross-sectional study in South India

Introduction Non-communicable diseases (NCDs), particularly hypertension (HTN), pose a significant global health challenge, accounting for a substantial proportion of premature deaths worldwide. In India, HTN prevalence varies widely across states and districts and is influenced by demographic, socioeconomic, and lifestyle factors. This study aims to assess the spatial distribution of HTN and its correlates in South India. Materials and methods This study utilized data from the 5th National Family Health Survey (NFHS-5), a nationally representative cross-sectional survey conducted across India between 2019 and 2021. For this analysis, data from five states and one union territory in South India were used. Bayesian spatial modelling was employed to analyse HTN prevalence at the district level, incorporating demographic, socioeconomic, and lifestyle covariates. Results The study included 304,420 adults, both male and female, aged >18 years. The overall prevalence of pre-HTN and HTN was 28.9% and 31.8%, respectively. HTN prevalence varied across states, with Kerala exhibiting the highest prevalence. Spatial clustering analysis identified districts with significantly higher HTN prevalence, often clustering with neighbouring districts showing similar patterns. Spatial autocorrelation analyses revealed a significant association between HTN and diabetes. Other comorbidities and risk factors were not significantly associated with HTN. Conclusion The findings underscore the spatial heterogeneity of HTN prevalence within South Indian states and districts. The study highlights the need for targeted interventions tailored to local contexts to effectively mitigate the burden of HTN and associated comorbidities.

Humidity-driven ABA depletion determines plant-pathogen competition for leaf water

Abstract Bacterial phytopathogens, such as Pseudomonas syringae pv. tomato ( Pst ) DC3000, induce water-soaked lesions in the leaf apoplast under high humidity, facilitating infection. However, it remains largely unclear how plants regulate their resistance to restrict bacterial infection in response to humidity. Here, we demonstrate that abscisic acid (ABA)-catabolizing ABA 8’-hydroxylase, encoded by CYP707A3 , plays a critical role in this resistance in Arabidopsis thaliana . Elevated humidity induces CYP707A3 expression, which is essential for reducing ABA levels and promoting stomatal opening, thereby limiting bacterial water-soaking and infection following leaf invasion. High humidity also increases cytosolic Ca 2+ levels via the Ca 2+ channels CNGC2 and CNGC4, with partial involvement from CNGC9, activating the calmodulin-binding transcription activator CAMTA3 to drive CYP707A3 induction. However, Pst DC3000 counteracts this defense response using type III secretion effectors, including AvrPtoB, facilitating water-soaking. These findings provide insights into the mechanisms underlying the competition between plants and bacteria for leaf water under elevated humidity.

Forecasting mean deviation in glaucoma patients using an irregular autoregressive time series method

Abstract Accurate forecasting of disease progression is vital in glaucoma management. Ordinary least square regression (OLSR) analyses are not appropriate to perform trend analysis on longitudinally collected perimetry data. This study examines the applicability of an irregular autoregressive of order 1 (IAR (1)) method to model mean deviation (MD) series and investigates if IAR (1) improves validity of the model and results better forecasts then OLSR. Longitudinal data from eyes with progressive glaucoma were used. A total of 1200 MD data from forty-two eyes were included in this study. MD series from the eyes were fitted using both OLSR and an IAR (1) methods. A correlogram was used to determine if errors of the fitted OLSR and IAR (1) were correlated. Predictability of the IAR (1) method was then compared with OLSR using forecast Mean Square Error (MSE). Residuals from the OLSR were correlated and did not satisfy the assumption of normality. On the other hand, the IAR (1) model markedly improved the validity of the model as evidenced by insignificant autocorrelation functions ( p -value > 0.05) and model’s ability to fit heavy-tailed distribution. Compared to the OLSR fit, significantly higher percentages of eyes resulted smaller MSE (62% vs. 38%, P  = 0.02) when fitted with IAR (1) method. The IAR (1) method adequately addresses the shortcomings of OLSR when fitting repeatedly collected perimetry data. The IAR (1) method appears to be statistically more valid method for fitting MD series and more accurately forecasts MD progression when compared with OLSR fit.

Pathways at the Iberian crossroads: Dynamic modeling of the middle–upper paleolithic transition

Archaeological and genomic data provide essential yet static insights into human expansion, offering limited understanding of the underlying dynamic processes. As a complementary alternative, we present a high-resolution model of population dynamics and apply it to reconstructing the Middle-to-Upper Paleolithic Transition (MUPT) in Iberia. Through ensemble simulation, we examine Neanderthal (NEA) persistence, modern human (AMH) arrival, and possible interbreeding. The model maps population networks, mobility, and interactions, showing NEAs were confined mainly in coastal refugia and already declining when AMHs arrived. Heinrich Event 5 likely accelerated NEA extinction through climate stress and demographic collapse. AMHs expanded rapidly into Cantabria, overlapping with NEAs and allowing for possibly 2–6% admixture. New dispersal corridors are predicted, showing AMHs moved along the Atlantic coast from southern France into Cantabria, then inland via the Duero Route into Portugal and central Mesetas. By linking climate, demography, and culture, our dynamic model offers a broader explanatory framework that enhances the interpretive power of archaeological and genomic records.

Thrombopoietin increases susceptibility for EVI1 + KMT2A-MLLT3-driven AML expressing stem cell genes linked to poor outcome

Abstract To address the cellular origin of ecotropic virus integration site 1 (EVI1)-expressing aggressive KMT2A-rearranged acute myeloid leukaemia (AML) we integrate an Evi1-GFP reporter allele in the inducible iKMT2A-MLLT3 mouse model. We observe that a single injection of thrombopoietin (TPO) selectively increases the number of cycling Evi1 + haematopoietic stem cells (HSC) and accelerates AML initiation. Comparison of mouse Evi1 + KMT2-MLLT3 + AML originating from TPO-stimulated HSC with human EVI1 + AML reveals higher expression of HSC genes including IL12Rβ2 and INPP4B linked to poor disease outcome of patients of four large AML cohorts. Knockdown experiments show exclusive MECOM-dependency of human EVI1 high KMT2A-rearranged OCI-AML4 cells while reduction of IL12Rβ2 also impairs clonogenic growth of EVI1 low MOLM-13, THP-1 or HL-60 AML cells. Collectively, we show that exogenous factors like TPO can increase the susceptibility for iKMT2A-MLLT3-driven HSC-originating Evi1 + AML expressing stem cell genes linked to transformation maintenance of cell lines, and poor disease outcome of patients.