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Microbial communities in the rhizosphere of three Mentha species: Links to soil properties and essential oil profiles

Mentha species are widely cultivated aromatic plants valued for their essential oils and antimicrobial properties. However, despite their agricultural and pharmacological significance, limited information is available on how different Mentha species influence rhizosphere microbial communities and their relationships with soil physicochemical parameters and essential oil composition. In this study, we examined the rhizosphere microbiota of three closely related taxa – Mentha  ×  villosa B10, M. spicata B17, and M. suaveolens J17 – cultivated under uniform field conditions. Rhizosphere and bulk soils were analyzed for physicochemical properties, microbial composition (16S rRNA, ITS sequencing), essential oils (gas chromatography-mass spectrometry), and arbuscular mycorrhizal colonization. Bacterial communities were dominated by the phyla Actinomycetota, Pseudomonadota, Acidobacteriota, Bacillota, and Chloroflexota, while fungal communities were primarily composed of Ascomycota, Mortierellomycota, Basidiomycota, and Rozellomycota. Rhizosphere soils exhibited higher fungal diversity than bulk soils, with Glomeromycota detected exclusively in rhizosphere. Microbial community composition differed significantly among Mentha taxa: M. spicata B17 displayed the lowest bacterial diversity, the most distinct microbial assemblages, and the highest arbuscular mycorrhiza colonization. Soil properties – particularly humus content, phosphorus, potassium, and sodium – were strongly correlated with bacterial diversity, while fungal communities showed weaker associations. Integration of essential oil data revealed genotype-dependent chemical profiles: Mentha  ×  villosa B10 and M. spicata B17 were characterized by high proportions of L-carvone and limonene, whereas M. suaveolens J17 was dominated by cis-piperitone epoxide and piperitenone oxide. Together, these findings demonstrate that even closely related Mentha cultivars can harbor distinct rhizosphere microbiota, associated with both plant chemical traits and soil characteristics. This study highlights the complex interactions between aromatic plants, soil chemistry, and microbial communities, offering novel insights into plant-soil-microbe interactions in medicinal and aromatic crop systems.

Response of PIP aquaporins to long-term cold stress in two citrus rootstocks

Cold is one of the most impactful abiotic stresses causing significant crop losses. Additionally, it is a major limiting factor, reducing cultivation areas, especially for tropical and subtropical species such as citrus. In this study, we conducted a physiological assessment of water balance, photosynthesis, fluorescence, and transcriptomic data, to further understand the response of aquaporins in the Valencia Delta Seedless variety grafted onto two rootstocks: Citrus macrophylla and Carrizo citrange, considered sensitive and tolerant rootstocks, respectively. After 6 weeks of exposure to 1°C with a photoperiod of 16 hours of light and 8 hours of darkness, measurements were taken of CO 2 assimilation rate, stomatal conductance, substomatal CO 2 concentration, transpiration rate, and photosynthetic apparatus damage (Fv/Fm). In addition, plant water balance was quantified by measuring water potential (Ψw), osmotic potential (Ψπ), and relative water content (RWC%). Finally, gene quantification was performed for three previously selected aquaporins ( PIP1–2, PIP2–2, and PIP2–5 ), which our laboratory has formerly associated with cold acclimation and, consequently, with tolerance. Cold temperatures lead to stomatal closure, reduced transpiration, and a significantly decreased osmotic potential (Ψπ), like what occurs under conditions of extreme drought, as the plant seeks to prevent water loss through transpiration. However, the stem water potential (Ψw) and relative water content (RWC) often remain at levels typical of actively growing plants under adequate irrigation conditions. Gene expression and physiological results suggests that plants grafted onto Carrizo citrange rootstock exhibit a better cold response and increased acclimation, leading to the overexpression of aquaporins PIP1–2 , PIP2–2 , and PIP2–5 .

The prognostic significance of stress hyperglycemic ratio in critically Ill patients with hypertension: A study using the MIMIC-IV database

Background Traditional ABG is susceptible to interference from acute stress and daily fluctuations, making it difficult to accurately assess true acute blood glucose surges. To bridge this gap, we adopted the Stress Hyperglycemia Ratio (SHR), which reflects true acute hyperglycemia by controlling for baseline glucose status. SHR is associated with critical illness and has been shown to associated with in-hospital mortality. However, there is a lack of studies investigating SHR and its prognostic significance in patients with hypertension. Methods This study utilized the Medical Information Mart for Intensive Care IV database (MIMIC-IV) to extract patient information. All subjects were divided into four groups based on the quartiles of SHR. Kaplan-Meier (KM) curves were utilized to assess the relationship between SHR and all-cause mortality at 30, 90, 180, and 365 days. The relationship between the SHR index and prognosis was evaluated using restricted cubic spline (RCS) regression and Cox proportional hazards regression. At the same time, subgroup analyses were performed for gender, age, diabetes, myocardial infarction, congestive heart failure, cerebrovascular disease, and paraplegia. Results A total of 2,140 participants with essential hypertension were included in the study. The KM curve analysis revealed that elevated levels of the SHR index were significantly associated with an increased risk of all-cause mortality at 30, 90, 180, and 365 days (log-rank P  < 0.05). Moreover, multivariate analysis revealed that the SHR index remained significantly associated with mortality risk ( P <  0.001 ) . RCS analysis revealed a nonlinear, inverse U-shaped association between SHR and all-cause mortality ( P  < 0.05). Subgroup analysis showed statistically significant differences in all-cause mortality across gender, age, diabetes, myocardial infarction, heart failure, cerebrovascular disease, and paraplegia. Conclusions In critically ill patients with hypertension, a high level of SHR index is associated with all-cause mortality. The SHR index may be a potential prognostic indicator for assessing illness severity in ICU patients with hypertension.

Psychometric properties of the Thai version of the Illness-Specific Social Support Scale Short Version-8 (ISSS-8) among hematological malignancy patients in the Northeastern region of Thailand: A multicenter study

Social support, which is an essential aspect influencing health, has resulted in the development of several approaches for assessment in cancer patients. The Illness-Specific Social Support Scale Short Version-8 (ISSS-8) effectively evaluates social support among diverse patient demographics; however, its psychometric validity has yet to be established in Asian cultural contexts. The objectives of this study were to translate and culturally adapt the ISSS-8 for the Thai setting and to assess its psychometric properties in patients with hematological malignancies (HMs). This study employed a convenience sampling method to select patients with HMs undergoing hospitalization at three tertiary institutions in Northeastern Thailand. Psychometric testing was conducted following the translation and cross-cultural adaptation of the ISSS-8 into Thai. A total of 350 patients were recruited. Participants were randomly divided into two groups for exploratory factor analysis (EFA) (n = 200) and confirmatory factor analysis (CFA) (n = 150). The EFA of the eight items yielded a loading from a two-factor model comprising Positive Support and Detrimental Interactions, which explained 82.44% of the variance. Cronbach’s alpha (0.80) and item–total correlations (rho = 0.33–0.65) demonstrated acceptable reliability of the ISSS-8, while test–retest reliability was high (ICC = 0.924-–0.934). The average variance extracted (AVE) demonstrated convergent validity for all ISSS-8 subscales, with AVEs ranging from 0.76 to 0.80. Moreover, the total ISSS-8 scale demonstrated a statistically significant but weak positive correlation with the Stanford Inventory of Cancer Patient Adjustment (r = 0.244, p < 0.001), while the Detrimental Interactions subscale was significantly and weak negatively correlated with it (r = 0.237, p < 0.001). These findings suggest that the ISSS-8 captures distinct psychosocial and illness-specific relational constructs that differ from coping self-efficacy and psychological adjustment measured by the SICPA. The ISSS-8 is a short, accurate, and valid instrument for measuring social support in Thai patients with HMs. As a result, healthcare professionals can use the ISSS-8 to assess social support in both research and clinical settings. The findings emphasize the necessity of integrating social support evaluation into cancer management and family-centered care, thereby supporting comprehensive and adaptive healthcare delivery in Thailand.

Surveillance of Escherichia coli clones and their antimicrobial resistance profiles in wastewater and drinking water treatment plants of Barcelona, Spain

Antimicrobial resistance (AMR) is a major global health threat, and environmental reservoirs such as wastewater (WWTPs) and drinking water treatment plants (DWTPs) may facilitate its persistence and spread despite reducing bacterial loads. We investigated 152 antibiotic-resistant Escherichia coli strains collected across treatment stages from two WWTPs and one DWTP in Barcelona, Spain. Strains were characterized through antimicrobial susceptibility testing, whole-genome sequencing, multilocus sequence typing, biofilm assays, and screening of antimicrobial resistance genes (ARGs), virulence factors (VFGs), biocide and heavy-metal tolerance genes (HMTGs). Although E. coli bacterial loads decreased along treatment, AMR remained highly prevalent: 85.5% of strains were multidrug-resistant (MDR), 5.3% extensively drug-resistant, and 11.2% carbapenemase-producers. Strains harboring integrase genes were 2.4 to 11.8 times more likely to harbor ARGs for sulfonamide, aminoglycoside, phenicol, trimethoprim, mercury and quaternary-ammonium compounds. Strains carrying bla CTX-M genes were 3.0 to 20.3 times more likely to carry VFGs, while high-risk clones were 3.2 to 7.0 times more associated with VFGs. Some MDR and high-risk E. coli clones persisted in reclaimed water, and one MDR strain was detected at the DWTP inlet. These findings highlight environmental AMR reservoirs as a public health concern and support a One Health approach integrating antibiotic stewardship and environmental monitoring.

A multiplex dual-probe RT-LAMP assay for rapid subtype-specific detection of respiratory syncytial virus A and B

Respiratory syncytial virus (RSV) is a leading cause of acute respiratory tract infections, particularly in infants, older adults, and immunocompromised individuals. RSV is classified into two major subtypes, RSV A and RSV B, which co-circulate seasonally and exhibit genetic variability, highlighting the need for rapid and subtype-specific diagnostic methods. Although reverse transcription quantitative PCR (RT-qPCR) is the reference standard for RSV detection, its reliance on complex instrumentation limits its applicability in decentralized testing settings. In this study, we developed and evaluated a probe-based reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for rapid detection and differentiation of RSV A and RSV B. The assay incorporates a dual-probe strategy, employing an assimilating probe for RSV A detection to ensure robust signal generation under multiplex conditions, and hybridization-based TaqMan-style probes (HyTaq probes) for RSV B detection and for an internal control targeting the human ACTB gene to ensure reaction validity. Analytical performance was assessed using serially diluted RSV positive clinical specimens and plasmid standards. Clinical performance was evaluated using 91 RSV A positive specimens, 97 RSV B positive specimens, and 120 RSV negative specimens, as defined by the reference diagnosis. The RSV A and RSV B RT-LAMP assays demonstrated sensitivities of 92.31% and 98.97%, respectively, with a specificity of 100% for both targets. No cross-reactivity was observed with a panel of common respiratory viruses. These results indicate that the proposed dual-probe RT-LAMP assay provides a rapid and specific approach for subtype-specific RSV detection, with potential applicability in decentralized diagnostic settings pending further validation.

Diagnostic accuracy of automated hematology analyzer abnormal flags for detecting hematological malignancies: A systematic review and meta-analysis

Background Hematological malignancies including leukemia, lymphoma, and myelodysplastic syndromes, are characterized by clonal proliferation of abnormal blood or bone marrow cells. Early and accurate detection is essential for improving treatment outcomes and survival. Automated hematology analyzers generate abnormal flags that may indicate underlying hematologic malignancies; however, their overall diagnostic accuracy has not been comprehensively evaluated. This systematic review and meta-analysis aimed to assess the diagnostic performance of abnormal flags for detecting hematological malignancies. Methods A systematic search of PubMed, PubMed Central, Scopus, ScienceDirect, and Google Scholar was conducted to identify relevant diagnostic accuracy studies. Methodological quality was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2(QUADAS-2) tool. Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated using a bivariate random-effects model in Stata version 17.0. Heterogeneity was assessed using the I 2 statistic, and subgroup and meta-regression analyses were performed to explore potential sources of variability. Results Twenty-eight studies met the inclusion criteria. The pooled sensitivity and specificity of abnormal hematology analyzer flags for detecting hematological malignancies were 91% (95% CI: 87%–94%) and 89% (95% CI: 84%–92%), respectively, indicating good diagnostic accuracy. Significant heterogeneity was observed across studies (I 2  > 50%). Meta-regression analysis identified the type of abnormal flag as a significant source of heterogeneity in sensitivity (p < 0.001), whereas both the type of abnormal flag and the analyzer platform significantly influenced specificity. Conclusion Automated hematology analyzer abnormal flags showed promising diagnostic performance. However, substantial heterogeneity and differences in analyzer platforms, flag types, and reference standards reduce the certainty and generalizability of pooled estimates. Nevertheless, these findings support the use of abnormal hematology analyzer flags as an effective initial screening tool in routine laboratory practice, particularly in resource-limited settings where rapid and cost-effective diagnostic support is essential. Systematic review registration PROSPERO (CRD42024601908 ).

Integrative multi-omics and machine learning identify CHRNA1 putative circadian-immune hub in COPD

Background Circadian rhythm disruption is increasingly recognized as a contributor to chronic inflammatory disorders; however, its specific significance and underlying mechanisms in chronic obstructive pulmonary disease (COPD) remain unclear. This study aimed to identify circadian rhythm-associated biomarkers in COPD and explore their diagnostic value, immune correlations, and therapeutic potential. Methods This study integrated four lung transcriptomic datasets from the public GEO database (GSE151052, GSE38974, and GSE76925 as the discovery set, and GSE47460 as the validation set). Differentially expressed circadian rhythm‑related genes (DECRRGs) were identified by intersecting differentially expressed genes with circadian rhythm‑related genes. Functional enrichment analyses (GO and KEGG) were performed, and three machine learning algorithms were applied to screen for signature DECRRGs. An exploratory risk stratification model based on multivariate logistic regression was constructed and evaluated. Immune cell infiltration was assessed using CIBERSORT, and single-cell RNA sequencing analysis was conducted to localize the distribution of key circadian rhythm genes within specific lung cell populations. Finally, the expression of a core gene CHRNA1 was validated by qRT-PCR in peripheral blood samples from COPD patients and healthy controls. Results We identified eight circadian rhythm-associated feature genes, among which CHRNA1 emerged as a consistently upregulated hub gene in COPD. An exploratory risk stratification model based on these genes exhibited good discriminatory ability in the discovery cohort (AUC = 0.856, 95% CI: 0.806–0.902). Differential expression of CHRNA1 was validated in an independent cohort and correlated significantly with pro-inflammatory immune infiltration, including increased M1 macrophages and CD8 ⁺ T cells. Single-cell transcriptomics further localized CHRNA1 expression predominantly within B cells in COPD lung tissue. In silico drug screening and ceRNA network analysis predicted potential therapeutics (e.g., amitriptyline, rocuronium bromide) and regulatory miRNAs/lncRNAs. Finally, qRT-PCR confirmed a marked upregulation of CHRNA1 in peripheral blood from COPD patients ( *p*  < 0.0001). Conclusions Our findings suggest that CHRNA1 may serve as a candidate circadian rhythm‑associated immunomodulator in COPD. It demonstrates consistent upregulation across cohorts and shows a significant association with pro‑inflammatory immune infiltration. Single-cell analysis revealed that CHRNA1 is predominantly expressed in pulmonary B cells. The exploratory risk stratification model and predicted therapeutic candidates highlight the translational potential of targeting circadian disruption in COPD, though prospective validation is needed before clinical application.

Sustainable conversion of waste plastics to biofuel: Process insights and fuel characteristics

Plastic consumption has become pervasive in modern society, with over 300 million metric tonnes produced annually worldwide, contributing significantly to municipal waste. In Bangladesh, where annual per capita plastic use has risen to 22 kg as of 2022, innovative solutions for managing plastic waste are urgently needed. This research introduces a novel approach to the pyrolysis of various plastics (PET, PVC, PP, HDPE) within a temperature range of 300 °C to 550 °C to produce pyrolytic bio-oil and biochar. We established optimal conditions for each plastic type—500 °C for PET, PVC, and HDPE, and 450 °C for PP—resulting in maximized yields of high-quality liquid oils (61.3% for PP and 47.23% for HDPE). Unique to this study, we innovatively adjust the pyrolysis process parameters to enhance the yield and quality of the derived bio-oils, tailored specifically to the types of plastics treated. The liquid products were characterized as predominantly consisting of C6–C16 hydrocarbons, aligning them closely with naphtha, gasoline, and diesel specifications, suitable for use as renewable fuels. Furthermore, our research applies FTIR and GC-MS analyses in a novel way to provide a detailed examination of these bio-oils, revealing significant quantities of paraffinic hydrocarbons in PP and olefins and naphthenes in HDPE, contributing to their potential fuel applications. The solid char byproducts were also comprehensively characterized using SEM and XRD, providing insights into their suitability for various industrial applications. This study not only demonstrates the potential of pyrolysis to transform waste plastics into valuable renewable energy resources but also advances the technological framework for sustainable waste management practices, marking a significant leap forward in the efficiency and application of plastic waste conversion technologies.

Reproducibility of fetal global longitudinal strain measured with speckle tracking echocardiography using a fixed cardiac cycle

Fetal speckle tracking echocardiography is an ultrasound-based technique used to assess myocardial velocity and deformation of the fetal heart. Despite its potential, the method has not yet been integrated into routine pregnancy care, partly due to concerns about inconsistent reproducibility. This study aimed to evaluate the intra- and inter-observer reproducibility of global longitudinal strain measurements derived from a fixed fetal cardiac cycle, using speckle tracking echocardiography. Healthy women with singleton pregnancies were enrolled during the second trimester. From enrolment until delivery, four-chamber view clips of the fetal heart were acquired every four weeks. For intra-observer reproducibility, a single observer analyzed the same heart cycle in one DICOM clip twice for global longitudinal strain in the left and right ventricles, with a minimum interval of two weeks between assessments in a blinded manner. For inter-observer reproducibility, two independent observers analyzed the same cardiac cycle within one DICOM clip. A total of 124 women were included, yielding 632 ultrasound clips. Intra-observer reproducibility was poor to moderate for global longitudinal strain for the right and left ventricles. Inter-observer reproducibility demonstrated moderate to good reproducibility for global longitudinal strain in both ventricles. The reproducibility was generally higher in the left ventricle than in the right, and the highest reproducibility was observed before 32 weeks of gestation. In conclusion, speckle tracking echocardiography during pregnancy showed variable reproducibility of strain analysis when performed on a fixed cardiac cycle, with more consistent results in the left ventricle. These findings support the potential utility of fetal speckle tracking echocardiography, while highlighting the need for further refinement of reproducibility before clinical implementation.

Integrative network pharmacology, transcriptomics, and molecular docking identify candidate Centella asiatica constituents and targets in neurodegenerative diseases

Background Neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD), are progressive disorders with limited therapeutic options. Centella asiatica ( C. asiatica ), a medicinal and edible plant, has been reported to exert neuroprotective and anti-neuroinflammatory properties. Yet, the mechanisms underlying its effects against neurodegenerative diseases remain largely unclear. Methods We employed an integrative strategy combining network pharmacology, transcriptomic analyses, machine learning and molecular docking to prioritize disease-associated molecular networks and candidate compound–target relationships in AD, PD and HD. Results Sixteen candidate constituents of C. asiatica met the predefined drug-likeness, gastrointestinal absorption and blood–brain barrier permeability criteria, yielding 370 unique predicted targets. Disease-gene mining identified 983 AD-associated genes, 1,103 PD-associated genes, and 3,316 HD-associated genes. Integration of compound targets, disease-associated genes, and transcriptomic profiles prioritized five hub genes in PD (CCKAR, MAPK8, PSEN2, SLC6A3, and TH), four in AD (APP, PGK1, PIK3CA, and TTR), and four in HD (CHRND, HSP90AA1, PRKCQ, and TH). Enrichment analyses highlighted disease-relevant processes involving neurotransmitter signalling, cAMP and calcium pathways, MAPK-related responses and inflammatory regulation. ROC analyses provided additional support for the discriminatory performance of the prioritized genes in independent datasets, whereas molecular docking identified favourable predicted Vina docking scores and structurally plausible interactions between selected compounds and hub targets. Conclusion This integrative computational analysis prioritizes candidate C. asiatica constituents, putative disease-associated targets, and molecular pathways in AD, PD, and HD. The findings provide a foundation for subsequent biochemical, cellular, and in vivo validation.

Correction: Gold wrist-assisted PFNA reduces internal complications and enhances recovery in obese osteoporotic patients with intertrochanteric femur fractures

In vitro and in vivo antibacterial activities and phytochemical screening of 80% methanol extract from Ehretia cymosa leaves

Antibiotic resistance has emerged as one of the most urgent global health threats, undermining the effective treatment of bacterial infections. In response, scientific interest is increasingly focused on identifying natural and effective antimicrobial agents derived from medicinal plants. In Ethiopia, Ehretia cymosa ( E. cymosa ) is traditionally used to treat wound infections, fever, gastric ulcers, dysentery, and toothache. However, there is limited scientific evidence to support these traditional claims. Hence, the present study aimed to evaluate the in vitro and in vivo antibacterial activities and to screen the phytochemical profile of the 80% methanol extract of E. cymosa leaves. The air-dried and powdered leaves of E. cymosa were extracted using cold maceration with 80% methanol. The antibacterial activity of the crude extract was tested using the disk diffusion method against selected bacterial pathogens commonly associated with infections. An in vivo model of burn followed by infection was established in mice. Qualitative phytochemical screening was also performed. One-way analysis of variance followed by Tukey’s post hoc multiple tests was used to compare the means of all parameters. The leaves of E. cymosa demonstrated significant antibacterial activity (p < 0.001) against the tested bacterial strains in a dose-dependent manner compared with the control. The minimum inhibitory concentration ranged from 6.25 to 75 mg/mL, while the minimum bactericidal concentration against P. aeruginosa and E. coli was 200 mg/mL. In the in vivo model, the extract resulted in faster wound contraction and a shorter epithelialization period against S. aureus than against P. aeruginosa . The plant leaf is also rich in flavonoids, terpenoids, and tannins. The 80% methanol extract of E. cymosa leaves exhibited antibacterial activity in vitro and in vivo, which corroborates the traditional use of the leaves against infectious diseases. Further studies involving the isolation and characterization of the active compounds are recommended.

Entering the new normal - psychosocial work environment and health during the transition from full remote to a hybrid work arrangement in a higher education context

This longitudinal study explored the perceptions of psychosocial work factors, work-related health, and job satisfaction of 745 professional service staff, working in a higher education setting in Sweden, during the transition from full remote work to a hybrid work arrangement over 12-months. The study also explored whether these perceptions differed due to gender and household composition. The questionnaire data were analyzed using linear mixed-effects models with estimated marginal means and Bonferroni-adjusted pairwise comparisons. The results showed that while overall perceptions of psychosocial work factors showed modest changes during the transition, except for social support from colleagues, which significantly increased over time. Professional service staff reported higher levels of stress and exhaustion during the transition, while job satisfaction remained unchanged. The results also highlighted significant gender differences during the transition, as women reported less favourable perceptions of psychosocial work factors and higher levels of stress, while men’s perceptions remained largely stable across these outcomes. Significant overall differences in household composition were also observed, as individuals living in single-person households and in single-parent households reported less favourable perceptions of psychosocial work factors and their work-related health compared to cohabitants and cohabitants with children, though all household groups followed similar trajectories during the transition. The findings suggest that higher education institutions should implement action plans for gender equality and family-supportive practices in hybrid work arrangements to ensure that the benefits of hybrid work are accessible to all employees.

Schisandrins as novel efflux pumps inhibitors and non-antibiotic compounds against multi- and extensively-drug resistant clinical strains of Salmonella typhi: An in-vitro study

Purpose Typhoid is a significant global health challenge due to its high pathogenicity and antimicrobial resistance. Salmonella typhi ( S.typhi ) can switch its lifestyles between biofilm and planktonic phase which allows it to evade host defenses and develop resistance to antibiotics. Salmonella sp. harbors multiple genes encoding efflux-pumps systems whose up-regulation contributes to multi-drug resistance (MDR) and extensive drug-resistance (XDR). To overcome the battle against resistant S. typhi strains, novel non-antibiotics inhibitors are required for inhibitory application. This study assesses the inhibitory effect of lignans against drug resistance of S. typhi . Methods Clinical resistant and sensitive strains of S. typhi were obtained and characterized. The inhibitory effect of lignans, specifically Schisandrin A and B, purified from the plant Schisandra chinensis , are found to be effective non-antibiotic inhibitors were evaluated through standard microbiological techniques like growth curve and time-kill assays. Impact on bacterial morphology was analyzed using scanning electron microscopy (SEM). Our study explores two approaches, such as efflux pumps (EPs) inhibition and antibiofilm assays. Results Using colony-forming unit (CFU) assays, growth curve analysis, and SEM imaging, we observed significant bacteriostatic effects, with Schisandrin B causing notable membrane disruption. Schisandrin B also showed remarkable biofilm inhibition (90.33%) and strong efflux pumps inhibition. Conclusion This study offers a strong basis for future research on addressing antibiotic resistance in clinically relevant pathogens.

Mapping the prevalence of household-scale livestock ownership by animal taxon in low- and middle-income countries: A prediction model using template model builder

Animal husbandry is widely practiced on the household scale in communities in low- and middle-income countries (LMICs) and, while having economic and health benefits, exposes household members to risk of zoonotic infections to an extent that is unclear. While demand for georeferenced information on infectious disease risk factors and drivers is growing, spatial variation in livestock ownership remains poorly characterized at high resolution. This study aimed to use geostatistical methods to model and map the prevalence of livestock husbandry in LMICs for three major animal taxa: poultry, swine, and ruminants. Microdata relating to ownership of livestock animal species were sourced from various population-based survey programs which together cover the majority of LMICs and categorized. These were georeferenced and spatially matched with a panel of time-fixed environmental and demographic spatial covariates, INLA models were fitted to the resulting database, and probabilities for ownership of each livestock taxon predicted based on the model parameter estimates. The results indicated widespread poultry ownership across rural Central America, the Amazon basin, tropical Africa and river basins and forests of East Asia. Swine husbandry is the least widely practiced among the three livestock taxa and concentrated in an undulating belt of higher prevalence extending from central China, through southeast Asia to Northeastern India, though such predictions in data-sparse regions (particularly Muslim-majority areas) represent regional covariate patterns rather than fine-scale measurements. To address non-stationarity in swine spatial structure, region-specific spatial kernels were implemented. Rearing of ruminant livestock appears widespread across subequatorial Africa, Central Asia, the Gobi Desert, the Himalayas, Mongolia and northern India. The models perform impressively by most standard evaluation metrics, and the patterns in their predictions align with external evidence. The distribution of this important risk factor for infectious disease transmission can be modeled using publicly available data sources to generate plausible and potentially actionable predictions over wide geographic areas and identify regions of high exposure to animal disease reservoirs. The resulting predicted prevalence estimates are made available as supplementary files in GIS-compatible format.

Ensemble learning-based online sequential pre-interference extreme learning for concept drifting and class imbalanced data streams

With the rapid development of data-driven technologies, real-time data streams not only exhibit concept drift but are also frequently accompanied by class imbalance problems. To address these challenges, this paper proposes an online sequential pre-interference layer extreme learning machine (OS-PIELM). The proposed model introduces a pre-interference layer between the input layer and hidden layer of the original OS-ELM to enhance nonlinear feature representation through kernel-like transformation of sequential data, thereby improving the discriminative ability of different classes. Furthermore, an adaptive forgetting factor and a Gmean-based concept drift detection mechanism are incorporated into OS-PIELM, together with a dynamic weighting strategy. These components enable the model to effectively handle class imbalance in data streams and enhance its sensitivity to concept drift. Finally, an online ensemble learning framework is constructed with OS-PIELM as the base classifier to further improve the robustness of the proposed method. Extensive experiments on nine synthetic datasets and two real-world datasets demonstrate that the proposed method can effectively address class imbalance in data streams and improve concept drift detection performance.

Anatomical fit of the oneKNEE tibia design using statistical shape modeling

Introduction and aim Modern tibial implants should be designed to achieve an optimal anatomical fit. The aim of this study was to evaluate how well a newly developed tibial implant design (oneKNEE ® – B. Braun Aesculap, Tuttlingen, Germany) matches patient anatomy compared to three existing implant systems, using Statistical Shape Models (SSM). Method SSMs for Caucasian and Asian populations were generated using CT scans of 120 Caucasian and 112 Asian osteoarthritic patients. Border anatomical variations were represented by individual anatomies from 14 Caucasian and 12 Asian patients. Tibial components were positioned in accordance with strict protocols established by senior knee surgeons (YM, NK). The anatomical fit was analyzed across all four implant systems in terms of antero-posterior and medio-lateral dimensions, tibial coverage and cortical bone support. Global tests for homogeneity and Dunnett’s tests were performed. Results Bony coverage for Asian and Caucasian populations ranged from 82.9% to 88.4% for long-established designs and from 85.0% to 91.2% for more recently introduced designs. Among all designs, the oneKNEE ® implant demonstrated superior bony coverage and cortical support, followed by Attune ® (Depuy-Synthes, Warsaw, IN, USA), Columbus ® (B. Braun Aesculap), and PFC Sigma ® (Depuy-Synthes). For average anatomies, oneKNEE ® showed significantly better bony coverage and cortical score compared to Columbus ® and PFC Sigma ® (P < 0.01). In less average anatomies, oneKNEE ® exhibited statistically superior bony coverage compared to PFC Sigma ® , although no significant difference was observed in cortical support. Conclusion Compared with established tibial implant designs, the new design demonstrated improved virtual anatomical fit and coverage metrics based on computational modeling. These findings reflect a theoretical design‑level improvement and require biomechanical and clinical validation.

Spatiotemporal co-circulation of four dengue serotypes across Mexico, 2020–2025: A space-time scan analysis

Background Mexico has experienced escalating dengue transmission driven by the co‑circulation of four antigenically distinct serotypes (DENV‑1 through DENV‑4). Multi‑serotype transmission is epidemiologically relevant, yet its spatiotemporal patterns at sub‑national resolution remain poorly characterized. Methods We analyzed 103,426 PCR‑confirmed, serotyped dengue cases across 1,547 of 2,471 Mexican municipalities from January 2020 to December 2025. Kulldorff’s space‑time scan statistic under a discrete Poisson model was applied independently to each serotype and to all serotypes combined. Co‑circulation was defined as the spatiotemporal overlap of significant clusters from at least two serotypes within the same municipality for ≥ 1 epidemiological week. Results We identified 159 statistically significant clusters across all serotypes combined. DENV‑3 was dominant (64.4% of cases; annual incidence 59.9/100,000), consistent with the reemergence of a long‑absent serotype. The 2024–2025 season produced a nationally synchronized epidemic across geographically distant regions. Co‑circulation of at least two serotypes occurred in 1,545 municipalities; 217 experienced simultaneous clustering of all four serotypes. Active co‑circulation was present in 275 of 311 study weeks. Mean pairwise temporal overlap ranged from 8.0 to 12.0 weeks, with maximum overlaps of 29–30 weeks. Conclusions Four‑serotype co‑circulation was documented at municipal resolution, concentrated in the Gulf coast, the Yucatán Peninsula, and northeastern Mexico. The 217 municipalities with simultaneous clustering of all four serotypes may represent areas of epidemiological interest for further investigation. This municipality‑level spatiotemporal framework offers operationally relevant resolution for tracking multi‑serotype activity and supporting serotype‑aware dengue monitoring at sub‑national scale.

Case-matched retrieval improves textual alignment of LLM-generated radiology impressions

Background Radiology impressions guide clinical care. Large Language Models (LLMs)-drafted impressions can drift into generic, off-style text. Retrieval-augmented generation (RAG) enables context-aware few-shot prompting during inference. Methods This retrospective IRB-approved study included 11,998 CT pulmonary angiography (CTPA) reports. We built a retrieval bank from 11,399 reports and reserved 599 reports for testing. GPT-4o and LLaMA 3.1-70B generated impressions from the “findings” section using three setups: zero-shot, fixed random few-shot, and dynamic retrieval-selected few-shot (top-k semantic matches; k = 3/5/10). We ran temperatures 0, 0.7, 1. We scored outputs against the original impressions with ROUGE and BERTScore F1, report mean scores with 95% confidence intervals, and tested for statistical significance using Wilcoxon signed-rank test. Results Dynamic retrieval-based few-shot prompting outperformed zero-shot and fixed few-shot prompting across all configurations (all p < 0.05). The highest scores were observed at temperature 0 and k = 10. ROUGE-1 F1 increased to 0.44–0.47 for GPT-4o and 0.37–0.50 for LLaMA, versus 0.35–0.37 and 0.25–0.37, respectively, in zero-shot prompting. Lower temperature and larger k were associated with higher similarity scores. Conclusions Dynamic, case-matched retrieval improved alignment of LLM-generated CTPA impressions with reference impressions on automated text-similarity metrics. Scores remained moderate, and radiologists’ verification is still required before clinical deployment.