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Antibody libraries are the heartbeat of any phage display campaign to isolate monoclonal antibodies. Naïve antibody libraries have been used to identify monoclonal antibodies against a collection of different targets from small molecules to large protein targets. The fundamental requirements of a good naïve library generation is the availability of a diverse collection of antibody genes as the genetic source. The antibody gene pool used for naïve antibody libraries is the IgM repertoire derived from healthy donors. The obtained antibody genes will then be cloned as single-chain fragment variable (scFv), as it is a common format used for its smaller size and preference for phage display. The protocol will encompass the library cloning process which involves the use of a two-step cloning method, followed by bio-panning selection.

Dialects, in their remarkable diversity, serve as repositories of rich historical and cultural heritage. The Guanzhong dialect, native to the Guanzhong region of Shaanxi, is characterized by distinct phonetics, vocabulary, and cultural nuances. With the rapid advancement of speech emotion recognition (SER) technology, research into emotion analysis for dialectal speech has gained traction. However, this field remains challenged by limited dialect-specific datasets, an inadequate representation of emotional features in speech, and subpar model performance. The core objective of research is to achieve an accurate recognition of emotions in dialect environments, overcome the limitations of scarce dialect data, and meet the emotional interaction needs of specific groups of people. This work presents a dual contribution: first, there is the construction of a high-fidelity Guanzhong dialect SER dataset through systematic data collection, noise reduction preprocessing, and the annotation of four emotional categories (joy, sadness, anger, neutral), which establishes a robust foundation for subsequent research. Second, there is the development of FCAL-Net, which is a novel framework integrating multi-dimensional feature fusion. This approach leverages the CAM (convolutional attention module) to enhance CNN's local temporal feature extraction, couples it with Bi-LSTM for global contextual modeling, and demonstrates superior performance. The experimental results validate an accuracy of 77.67% in emotion classification, outperforming traditional CNN (12.31% improvement), Bi-LSTM (7.23%), Wav2vec 2.0 (8.08%), and Conformer (4.61%) baselines-highlighting its efficacy in addressing core challenges in dialectal SER.

We conducted Alliance clinical trial A231701CD that provided breast cancer patients a decision aid (DA) before their surgical consultation with the goal of improving engagement in decision-making. We report a mixed-methods analysis from patients who received the DA to understand patients' experiences in preparing for their consultation. Patients were included in this analysis if they were randomized to the DA arm (n = 331) and agreed to receive the DA (n = 195). Data collection included surveys before and after the consultation that assessed whether patients reviewed the DA and found it helpful, and reasons for non-review. We interviewed a subset of patients who had low engagement and experienced a preparatory barrier. We used descriptive statistics to summarize survey responses and content analysis to analyze interview data. Seventy-three percent (n = 143) reviewed the DA before the consultation. The majority (93%) said they would recommend receiving information via email. The most common reasons for non-review were logistical. Additional barriers included wanting to hear information directly from the surgeon, feeling they were already informed, wanting to stay in denial about their cancer, and perceiving information would be scary. Interviewees shared suggestions for clinics to optimize patients' review of information, such as explaining how preparing benefits patients and acknowledging emotion around cancer diagnoses. Our study highlights that breast cancer patients want information prior to the consultation, but patient-centered challenges can lead to non-review. When sharing pre-consult information, clinics should communicate how reviewing information can help patients feel less overwhelmed and improve their discussion with the surgeon. ClinicalTrials.gov Identifier: NCT03766009 (12/4/2018).

The soil microbiome plays a pivotal role in carbon sequestration, particularly through the degradation of lignocellulosic biomass such as paddy straw, which is often disposed of through environmentally harmful practices like open-field burning. This study investigates the isolation and characterization of novel lignocellulolytic bacterial strains capable of efficiently degrading paddy straw, thereby contributing to sustainable carbon management. A diverse collection of 27 bacterial isolates was obtained from soil samples, demonstrating significant cellulase, laccase, and lignin-degrading activities. Detailed biochemical and phenotypic analyses revealed distinct metabolic profiles and carbon source utilization patterns among the isolates. Notably, strains SH2A, AK17, AK15, U6, and SH2 achieved up to 94% degradation of paddy straw within 25 days, with isolate GS5A exhibiting an 18% reduction in recalcitrant lignin content in paddy straw within just 10 days leading to enhanced bioavailability of structural polysaccharides, and accelerating microbial-mediated degradation processes. Enzyme kinetic studies indicated optimal laccase activity at temperatures of 45-55 °C and pH levels of 4-7, with isolates TR32, SH2A, and AK17 producing laccase activities exceeding 90 U/L. Molecular characterization via 16 S rRNA sequencing identified these isolates as belonging to genera such as Pseudomonas, Enterobacter, Acinetobacter, and Klebsiella, known for their lignocellulolytic enzyme production. The findings underscore the potential of these bacterial strains exhibiting rapid lignin degradation enabling faster and more effective paddy straw decomposition compared to previously reported strains. Thereby leading faster carbon sequestration through effective biomass management, contributing to the development of a circular bio-economy and sustainable agricultural practices.

The analysis of human movement data in sports science is often challenged by the inherent variability in movement speed and rhythm, which results in gait time-series data of inconsistent lengths (dynamic dimensionality). This poses a significant obstacle for traditional optimization algorithms in constructing accurate motion templates for performance analysis and rehabilitation. To address this, we propose a novel Dynamic Dimension Warping (DDW) algorithm specifically designed for efficient search in dynamic multidimensional spaces. DDW integrates a Cross-Dimensional Mapping (CDM) mechanism, fusing Dynamic Time Warping and Euclidean distance to enable comparison between variable-length sequences, and an Optimal Dimension Collection (ODC) method to break fixed-dimension constraints. When applied to the task of optimizing human gait templates from experimental data, DDW demonstrated superior performance against 31 benchmark algorithms, reducing average fitness to 9.16 (41% below mean) and achieving rapid convergence within 10 generations. The algorithm also attained global optima in 52.17% of classical function tests, confirming its robustness. This work establishes DDW as an effective optimization framework for complex, dynamic-dimensional problems, with direct methodological value for gait analysis and biomechanical motion assessment.

Perioperative and postoperative complications after major urologic oncologic surgeries are common and clinically significant. Standardised complication grading and reporting are critical for benchmarking, quality improvement, and patient counselling. Our aim was to provide a comprehensive global assessment of complications following radical cystectomy (RC), radical and partial nephrectomy (RN and PN), radical prostatectomy (RP), radical nephroureterectomy (RNU), and retroperitoneal lymph node dissection (RPLND). This international, multicentre observational study included 130&#xa0;034 procedures (29&#xa0;098 RC, 75&#xa0;001 RP, 24&#xa0;476 major kidney surgery, 1459 RPLND) from 180 centres in 33 countries worldwide. Complications were graded using the Clavien-Dindo classification and quantified via the Comprehensive Complication Index, with descriptive analysis of complications at 30&#xa0;d and 90&#xa0;d. Complication rates varied by procedure. RC had the highest morbidity, with 30-d grade I-II complication in 40% and grade III-V in 16%, and a 90-d mortality rate of 2.3%. RP had low complication rates (grade I-II: 10-15%; grade III-V: 5-8%; mortality <0.05%), although extended pelvic lymph node dissection increased the incidence of high-grade events to 10%. Morbidity and mortality were generally low after PN; 90-d mortality was higher with open RN, reaching 1.7%. RNU and RPLND had moderate rates of major complications (up to 14%) and low mortality (<1%). Retrospective data collection, potential heterogeneous reporting of complications between centres, and incomplete follow-up in some cases may affect the generalisability of the results. This standardised global data set is the largest assessment of perioperative morbidity across urologic oncologic procedures to date, and provides important real-world evidence. RC remains the most morbid procedure, while RP had markedly lower complication rates. Standardised reporting and international benchmarking are essential to improve surgical safety and guide quality improvement worldwide.

This study compared two widely used biomechanical models-Plug-in Gait (PiG) and Conventional Gait Model 2.3 (CGM2.3)-during overground walking (WALK) and single-leg squats (SLS) in 24 healthy adults. Data was collected using a 20-camera Vicon system and force plates. Static trials were analyzed with medial knee and ankle markers to align joint axes across models. Kinematic and kinetic outputs were compared using root mean square differences (RMSD) and statistical parametric mapping (SPM) paired t-tests. During WALK, PiG produced greater internal rotation at the knee (RMSD 17.8&#xb0;, p&#x2009;<&#x2009;0.001) and hip (RMSD 5.0&#xb0;, p&#x2009;<&#x2009;0.001), and smaller sagittal-plane flexion angles (RMSD 2.6&#xb0; knee, 2.3&#xb0; hip) compared with CGM2.3. In single-leg squats, these discrepancies increased to 29.1&#xb0; and 9.0&#xb0;, respectively, with sagittal-plane differences of 4.4&#xb0; at the knee and 5.1&#xb0; at the hip. CGM2.3 yielded higher knee flexion moments (31% in WALK, 104% in SLS), while PiG produced higher frontal-plane knee moments (28% and 89%). The differences were most pronounced at deeper flexion angles. These results demonstrate that biomechanical outcomes differ systematically between models, emphasizing the impact of model selection on joint kinematics and kinetics in human movement analysis.

This study focuses on the vessel normalization window of anlotinib to preliminarily explore the optimal intervention timing for combining anlotinib with whole brain radiotherapy (WBRT) in treating brain metastases from non-small cell lung cancer (NSCLC). We aimed to explore the feasibility of combining anlotinib with WBRT based on the hypothesized vascular normalization window, and to investigate potential associations with intracranial tumor control, iPFS, and quality of life in patients with NSCLC brain metastases. This study was designed as a prospective, non-randomized, single-center cohort study. From Feb 8, 2024, to Sep 30, 2025, a total of 38 patients with NSCLC brain metastases diagnosed by the Department of Oncology, the Fifth Affiliated Hospital of Chengdu University of Traditional Chinese Medicine, were prospectively recruited. Anlotinib was used as the intervention measure in this study. According to whether the patients received anlotinib or not, they were divided into the experimental group (anlotinib combined with WBRT) and the control group (sole WBRT), with 19 patients in each group. In the experimental group, the vascular normalization time window of anlotinib, which is 5 to 7 days, was precisely utilized. The specific medication regimen was to start taking 8&#xa0;mg of anlotinib 5 days before the initiation of WBRT and continue the medication until the end of WBRT. In contrast, the control group received only WBRT. The primary and secondary endpoint indicators of the patients in both groups were followed up regularly. The primary endpoint indicators included the intracranial objective response rate (iORR) and iPFS, while the secondary endpoint indicators included the intracranial disease control rate (iDCR), quality of life, and adverse reactions. The Kaplan-Meier method was used to draw the survival curve.Meanwhile, the clinical characteristics of the patients in both groups, such as gender, age, primary tumor site, T stage, N stage, and the number of brain metastases, were collected. Univariate analysis was used to screen out the prognostic factors that might affect iPFS. Then, the factors with statistical differences (P < 0.10) in the univariate analysis were taken as independent variables, and further Cox multivariate regression analysis was carried out to explore the independent prognostic factors affecting iPFS. The test standard P value was < 0.05. From Feb 8, 2024, to Sep 30, 2025, a total of 38 patients diagnosed with brain metastases from NSCLC by the Oncology Department of the Fifth Affiliated Hospital of Chengdu University of Traditional Chinese Medicine were prospectively recruited and included in the statistical analysis. The median follow-up time was 15.2 months (95% CI: 9.02-21.37). The results showed that the experimental group had better iORR (57.90% vs. 15.79%, P = 0.017) and iDCR (100% vs. 73.68%, P = 0.046) compared to the control group, with statistically differences. Compared with the control group, the experimental group showed a advantage in iPFS (6.7 months vs. 4.27 months, P = 0.038), and the median iPFS was extended by an additional 2.43 months. The results of subgroup analysis showed that the iPFS of patients with &#x2265; 3 brain metastases and patients with < 3 brain metastases were 6.3 months and 6.7 months, respectively, and there was no significant difference between the two groups (P = 0.723). The iPFS was longer in patients with less than 3 metastases than those with more than 3 metastases (11.73 months vs. 3.17 months, P = 0.035). After WBRT, the iPFS of NSCLC patients with brain metastases who received anti-tumor therapy was improved compared with those who did not receive anti-tumor therapy (8.67 months vs. 3.80 months, P = 0.040). In terms of quality of life, the experimental group showed better outcomes in functional status, symptom domains, and overall health compared to the control group over time. Regarding adverse reactions, the main ones included decreased appetite, fatigue, nausea and vomiting, hypertension, Myelosuppression, dizziness, headache, and abnormal liver function indicators. Grade &#x2265; 3 adverse reactions primarily included anemia, agranulocytosis, leukopenia, thrombocytopenia, cognitive impairment and abnormal liver function indicators, most of which were tolerable after symptomatic treatment. Univariate regression analysis of the overall population indicated that antitumor therapy after WBRT (P = 0.078) and the number of organ metastases (P = 0.038) were clinically relevant factors affecting iPFS. Further multivariate Cox regression analysis revealed that antitumor therapy after WBRT (P = 0.047) and the number of organ metastases (P = 0.028) were independent prognostic factors influencing iPFS. In this exploratory cohort, low-dose (8&#xa0;mg) anlotinib administered 5-7 days prior to WBRT was associated with higher iORR, iDCR, and longer iPFS relative to WBRT alone in patients with NSCLC brain metastases. This combination regimen showed a manageable safety profile and trends toward improved quality of life. Subgroup analyses suggested that patients with < 3 organ metastases or those receiving post-WBRT antitumor therapy tended to have prolonged iPFS. Multivariate Cox regression identified post-WBRT antitumor therapy and number of organ metastases as potential independent prognostic factors for iPFS in this cohort. These findings are hypothesis-generating and require validation in larger randomized controlled trials.

Very preterm (VP) infants undergo rapid brain development while hospitalized in the neonatal intensive care unit (NICU). Meaningful auditory experiences enhance brain development, yet understanding VP infants' auditory environment remains a challenge. We examined the trajectories of auditory exposures of VP infants before term-equivalent age. This was a prospective, observational study of 25 VP infants born &#x2264;32 weeks and 6 days gestation in a hybrid-design NICU. We collected 128 auditory recordings using language environment analysis (LENA) devices, with up to six consecutive weekly recordings per infant. We performed repeated-measure correlations between auditory measurements and postmenstrual age (PMA) and assessed relationships with room type and parental presence using stratification. Between 31 and 39 weeks PMA, VP infants experienced primarily silence (63.2% of recorded time) and electronic sounds (14.5%), with overall limited meaningful language exposure (3.9%). With advancing PMA and transitioning from single-family rooms to semi-private bays, meaningful language increased (r&#x2009;=&#x2009;0.54, p&#x2009;<&#x2009;0.001) and noise exposure decreased (r&#x2009;=&#x2009;-0.59, p&#x2009;<&#x2009;0.001). Higher parental presence appeared to positively correlate with language exposure. VP infants experience reduced meaningful auditory exposures during NICU hospitalization. Further work should examine how modifiable NICU environment factors could be leveraged to optimize auditory experiences during a sensitive period. NICU auditory environments remain suboptimal for preterm infants, with a predominance of silence and limited meaningful experiences. In this hybrid-design NICU, meaningful language exposures monitored longitudinally increased with advancing postmenstrual age and as infants transitioned from single-family rooms to semi-private bays. Modifiable factors, including NICU designs, models of care, and parental presence, may play a role in optimizing auditory exposures of preterm infants. A better understanding of factors influencing the auditory experience can facilitate the design of effective interventions in the NICU.

Patients who are referred for genetic counseling and/or genetic testing may conduct web searches to try to gather more information prior to their appointment. However, little is known about the reading level of such resources or the suitability of the information they provide. This study aims to determine the readability and suitability of top-ranked webpages after general searches about genetic counseling and if there is a difference in these metrics depending on which type of organization (i.e., government, non-profit) authored the webpage. Twenty webpages were identified using Google. Searches of the questions "What is a genetic counselor?", "What is genetic testing?", "Why do I need genetic testing?", and "What happens at a genetic counseling appointment?" were completed and the top 5 pages were taken from each. These webpages were then analyzed using the readability tools of Flesch-Kincaid (FK) and Standardized Measure of Gobbledygook (SMOG). Both FK and SMOG provide an assessment of readability based on grade level with the goal of this study to find resources under grade level 8. Additionally, the webpages were analyzed using the Suitability Assessment of Materials (SAM) on 6 categories. To complete the SAM analysis, two reviewers completed the tool for each webpage. Sponsor type was determined based on the primary goal of the group that supported or published the webpage. When comparing between questions, the average FK scores for the webpages were between 8th and 12th grade and the average SMOG scores were between 11th and 14th grade. Most webpages rated as adequate on the SAM scale. The results of this study highlight the continued need for evaluation of patient resources, especially those on the internet, to ensure they are meeting the needs of the rising number of individuals being referred to genetic services.

Acute gastroenteritis (AGE) in children is primarily associated with pathogens such as Human Rotavirus A (HRVA), Human norovirus (HNoV), Human adenovirus (HAdV), Human astrovirus (HAstV), Human parechovirus (HPeV) and increasingly, Human enteroviruses (EVs). EVs are non-enveloped RNA viruses belonging to the Picornaviridae family, comprising over 100 subtypes classified into four species. Despite their clinical relevance, the prevalence of EVs in AGE remains underexplored in India, resulting in limited data on their epidemiology and molecular diversity. A total of 450 stool samples were collected from hospitalized children under five years of age with AGE in Pune, India, between 2017 and 2023. Molecular characterization was subsequently performed to identify and confirm the types of EVs present. EVs were detected in 11.3% (51/450) of AGE cases. HRVA remained the most frequently detected pathogen overall. Among EV-positive cases, 58.8% were viral mono-infections, while 41.2% occurred as co-infections with other enteric viruses. EVs detection was highest in children below two years of age and occurred year-round, with a marked increase during the monsoon months. Molecular characterization identified 16 distinct EVs genotypes among 28 genotyped samples, predominantly belonging to EV-B species, followed by EV-A and EV-C. Phylogenetic analysis demonstrated clustering with contemporary global strains, indicating sustained circulation and genetic diversity. Replication-competent EVs were successfully isolated from representative samples, confirming the presence of viable viruses in clinical specimens. Although rotavirus remained the predominant viral pathogen associated with pediatric AGE, EVs were consistently detected across multiple years and age groups, either as viral mono-infections or in combination with other enteric viruses. These findings suggest that non-polio EVs may contribute to the viral etiology of pediatric gastroenteritis, although their precise etiological role requires further investigation. Continued molecular surveillance and broader diagnostic approaches may help clarify their epidemiological relevance and contribution to gastroenteritis in settings with high disease burden.

Lung nodule detectionis necessary for lung cancer treatment, which is crucial for treating the patients. However, the current dataset comprises only a limited amount of lung Computed Tomography (CT) images, with a significant imbalance between non-nodule and nodule samples. This disparity reduces the performance of neural networks and makes training more difficult. Early detection of lung tumor is crucial for identifying patients with ahigh chance of effective treatment, and this relies heavily on the preciserecognition of malignant lung nodules in CT scans. Recently, Deep Neural Network (DNN)techniques have been successfully employed to address various computer vision challenges, demonstrating their potential in this domain. Yet, low training values present significant challenges in the diagnosis of malignant nodules. The size and shape of a lump are crucial factors in determining malignancy in lung cancer. Therefore, it is important to address limitations of conventional techniques through the application of deep learning strategies. The developed lung nodule classification framework contains three main stages: image collection, segmentation, and classification. Initially, a substantial number of CT images used for validation are gathered from publicly available sources. These images are processed through a segmentation module, where effective segmentation is performed using a 3D Trans-DenseUnet++ (3D-TDUnet++) model. This segmentation process segregates the lung nodules from nearby tissues and also ignores inappropriate background structures, which helps the suggested approachfocus only on the region of interest. Also, it enhances the feature extraction process and reduces noise from images, which strengthens the classification accuracy and overall reliability of the developed method. After segmentation, the attained segmented images is further given into the classification phase by using an Adaptive DenseNet combined with a Long Short-Term Memory (LSTM) layer (ADNet-LSTM).This synergy of the classification-based deep learning model empowers an automated differentiation between malignant and benign lung nodules, which yields an accurate and efficient clinical decision-making process. It efficiently reduces the manual effort, improves the early detection process and also enhances the detection consistency. Additionally, the parameters of an ADNet-LSTM are optimized with the help of Intensified Fitness-based Red-Tailed Hawk Algorithm (IF-RTHA). Furthermore, some experimental validations are performed over the developed models with several performance metrics to ensure model's reliability. The accuracy of the IF-RTH-ADNet-LSTM model is 94.98% higher than the existing works, such as RAN, Densenet, LSTM, and ADNet-DenseNet, as 90.21%, 92.38%, 91.68%, and 92.87% using the lung nodule dataset. Thus, it is revealed that the offered lung nodule classification framework performed well for evaluating the malignancy risk of lung nodules found on CT images and also it has the efficiency to provide better decisions for clinicians.

To characterize the occurrence levels and distribution of disinfection byproducts in drinking water of Chengdu in China, evaluate health risks to the adult population via oral, dermal, and inhalation exposure routes, and identify key health risk drivers. From 2023 to 2025, water samples were collected from 118 centralized water supply units across 23 districts to detect trihalomethanes and haloacetic acid disinfection byproducts, analyze differences in detection and concentration levels across water periods, regions, and water supply scales, and applied the US EPA health risk assessment model to assess exposure risks of trichloromethane, bromodichloromethane, dibromochloromethane, tribromomethane, dichloroacetic acid, and trichloroacetic acid through oral and dermal routes. All 4464 samples had disinfection byproduct concentrations met national standards, with 100.0% pass rate. Trichloromethane had the highest detection rate (86.0%) and median concentration (9.00 &#xb5; g/L). Concentrations of trichloromethane, bromodichloromethane, dichloroacetic acid, and trichloroacetic acid were higher in the wet season than in the dry season. Trichloromethane and bromodichloromethane concentrations were higher in urban versus rural samples, whereas dibromochloromethane and dichloroacetic acid were higher in rural areas. Detection rates and concentrations in large centralized water supply units exceeded those in small units (P&#x2009;<&#x2009;0.05). The health risk assessment showed that the cumulative non-carcinogenic risk (HI&#x2009;<&#x2009;1) was within acceptable limits, and the cumulative carcinogenic risk (TCR&#x2009;=&#x2009;4.15&#x2009;&#xd7;&#x2009;10&#x207b;&#x2075;) fell within the commonly used regulatory benchmark range but warrants continued attention. Trichloromethane contributed the largest share (26.5%). Disinfection byproduct concentrations in Chengdu's drinking water comply with national standards, and the associated non&#x2011;carcinogenic health risks are low. The cumulative carcinogenic risk is within the commonly accepted benchmark range but is sufficiently elevated to justify continued surveillance and source&#x2011;control measures, with trichloromethane and trichloroacetic acid as priority compounds.

Most studies on the impact of vitamin D on sex hormones focus on specific populations, such as older males, Asian males, or those with certain health conditions. Limited evidence exists on the relationship between vitamin D and sex hormones in American women. This cross-sectional analysis used National Health and Nutrition Examination Survey (NHANES) data to explore the association between serum vitamin D levels and sex hormones levels in women. Data from NHANES (2021-2023) were analyzed. Participants were categorized by serum vitamin D levels: Deficient (<50 nmol/L), Insufficient (50-74.99 nmol/L), and Adequate (&#x2009;&#x2265;&#x2009;75 nmol/L). One-way ANOVA and Chi-square tests were used for comparisons, and linear regression evaluated associations. Our analysis specifically focused on a subset of 3181 women aged 18 years and older (18-80 years). Women in the adequate vitamin D group had lower body mass index (BMI) (29.16 vs. 32.10&#x2009;kg/m&#xb2;, p&#x2009;<&#x2009;0.001), lower total testosterone (24.10 vs. 32.28&#x2009;ng/dL, p&#x2009;<&#x2009;0.001), progesterone (139.05 vs. 229.73&#x2009;ng/dL, p&#x2009;<&#x2009;0.001), estrone sulfate (687.10 vs. 1023.08&#x2009;pg/mL, p&#x2009;<&#x2009;0.001), and dehydroepiandrosterone sulfate (DHEAS) (66.41 vs. 100.56&#x2009;&#xb5;g/dL, p&#x2009;<&#x2009;0.001) compared to the deficient vitamin D group. They also had higher sex hormone-binding globulin (SHBG) (70.37 vs. 58.55 nmol/L, p&#x2009;<&#x2009;0.001), follicle-stimulating hormone (FSH) (50.30 vs. 23.99 mIU/mL, p&#x2009;<&#x2009;0.001), and luteinizing hormone (LH) (26.39 vs. 16.64 mIU/mL, p&#x2009;<&#x2009;0.001) compared to the deficient vitamin D group. Linear regression revealed that higher serum vitamin D was inversely associated with 17&#x3b1;-hydroxyprogesterone (Beta&#x2009;=&#x2009;-0.85, P&#x2009;=&#x2009;0.023), androstenedione (Beta&#x2009;=&#x2009;-0.181, p&#x2009;<&#x2009;0.001), anti-M&#xfc;llerian hormone (Beta&#x2009;=&#x2009;-0.238, p&#x2009;<&#x2009;0.001), DHEAS (Beta&#x2009;=&#x2009;-0.204, p&#x2009;<&#x2009;0.001), total testosterone (Beta&#x2009;=&#x2009;-0.080, P&#x2009;=&#x2009;0.042), while showing a positive association with follicle-stimulating hormone (Beta&#x2009;=&#x2009;0.260, p&#x2009;<&#x2009;0.001) and luteinizing hormone (Beta&#x2009;=&#x2009;0.208, p&#x2009;<&#x2009;0.001). Serum vitamin D levels were negatively associated with testosterone and estradiol in American women, particularly in older individuals.

Canine distemper virus (CDV) is a highly contagious, multi-host pathogen that spreads readily among susceptible animals and often causes mass mortality. Yanbian Prefecture, located at the border area of China, Russia, and North Korea, represents a critical region for pathogen surveillance due to its unique geographical characteristics and animal trade activities; however, little is known about the prevalent CDV strains in this area or their pathogenic mechanisms. In this study, a CDV strain, designated CDV-Yanbian (CDV-YB), was successfully isolated from an anal swab sample collected from a suspected infected dog in Yanbian Prefecture and identified as the Asia-1 genotype through genetic analysis. To further elucidate the molecular mechanisms underlying CDV-host interactions, we examined the expression changes of inflammation-related signaling pathway genes and the occurrence of pyroptosis in canine adipose-derived mesenchymal stem cells (ADMSCs) following CDV infection using RT-qPCR and Western blot. Our results revealed that CDV infection activated the Janus kinase 2 - Signal transducer and activator of transcription 3 (JAK2-STAT3), mitogen-activated protein kinase (MAPK), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-&#x3ba;B), and phosphatidylinositol 3-kinase-Akt (PI3K-Akt) pathways and upregulated NLR family pyrin domain containing 3 (NLRP3) inflammasome activation. Furthermore, inhibition of the JAK2-STAT3 pathway using AG490 reduced NLRP3 inflammasome activation. Taken together, our findings demonstrate that CDV activates multiple inflammatory signaling pathways and, via the JAK2-STAT3 pathway, upregulates NLRP3 inflammasome activation in host cells, and pyroptosis was also observed. These findings provide a foundation for understanding CDV pathogenesis and informing future research on this important virus.

Ficus natalensis (Natal fig), an evergreen tree of the family Moraceae, is widely distributed across tropical and temperate regions and cultivated in Egypt. Members of the Moraceae family are traditionally employed as expectorants, hypoglycemic agents, and mild laxatives, with reported neuroprotective, analgesic, anti-inflammatory, and antihypertensive effects. The present study aimed to profile the secondary metabolites of F. natalensis fruit using ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS) and test its anti-inflammatory potential. A total of 160 metabolites were annotated in both positive and negative ionization modes, belonging to diverse phytochemical classes such as phenolics (41), flavonoids (21), acids (26), glycosides (11), terpenoids, coumarins (4), iridoids (3), fatty acids/ester (22), sterols (8), sugar derivatives (6), and terpenoids (18). The anti-inflammatory activity of F. natalensis fruit methanolic extract was investigated using nitric acid (NO) inhibition assay, revealing an IC50 of 28.54&#x2009;&#xb1;&#x2009;1.66&#xa0;&#xb5;g/mL, compared to resveratrol as a standard anti-inflammatory with an IC50 value of 10.21&#x2009;&#xb1;&#x2009;0.68&#xa0;&#xb5;g/mL. Major bioactive constituents, including ellagic acid, gallic acid, betulinic acid, and quercetin derivatives, were identified and may underline the observed anti-inflammatory effect. The current findings highlight F. natalensis fruit as a rich source of bioactive metabolites with potential anti-inflammatory effect.

This data paper presents a dataset, of 12,361 observations compiled from the Happiness Meanders project, which explores cultural variations in individual and family well-being, ideal and actual happiness, emotional experiences and expressions, and cultural models of selfhood across 48 countries. Participants were recruited through academic networks. Data were collected using standardised scales, including the Satisfaction with Life Scale, the Interdependent Happiness Scale, the Cultural Models of Selfhood Scale, and the Emotional Experience and Expression inspired by Affect Valuation Index. The dataset underwent thorough technical validation, including checks for variable consistency, handling missing data, and identifying potential response biases. A filter for data quality was applied, with potentially unreliable data flagged for exclusion. This dataset offers a valuable resource for examining cultural influences on emotional dynamics (frequence of experience and expression), individual and family oriented evaluations of happiness, ideal and actual evaluation of happiness, cultural models of selfhood, and can support further research in cross-cultural psychology and related social sciences.

Self-perceived health, defined as an individual's subjective evaluation of their overall health status, is a widely recognized indicator of health among older adults and is strongly associated with objective health outcomes. Identifying epidemiological and health-related determinants of poor self-perceived health among older individuals is essential to improve targeted interventions and resource allocation. This community-based cross-sectional study included 10,321 older adults aged 65 years and over. The data were obtained from the 2023 Turkey Elderly Profile Survey conducted between 23 October and 18 December 2023. The survey was carried out by the Turkish Statistical Institute (TUIK) in collaboration with the Ministry of Family and Social Services to inform aging-related policies. Data were collected on sociodemographic characteristics, lifestyle behaviors, clinical conditions, depressive symptoms, and self-perceived health. Univariable and multivariable logistic regression analyses were undertaken to identify factors associated with poor self-perceived health. The mean age of the study population was 72.8&#x2009;&#xb1;&#x2009;6.4 years (range: 65-115 years); 45.5% (n&#x2009;=&#x2009;4,698) of participants were male and 54.5% (n&#x2009;=&#x2009;5,623) were female. The prevalence of participants rating their health status as "bad" was 77.2%. In the multivariable analysis, age&#x2009;&#x2265;&#x2009;75 years (aOR&#x2009;=&#x2009;1.25, 95% CI: 1.09-1.42, p&#x2009;=&#x2009;0.001), female gender (aOR&#x2009;=&#x2009;1.19, 95% CI: 1.06-1.34, p&#x2009;=&#x2009;0.004), the presence of chronic disease (aOR&#x2009;=&#x2009;8.31, 95% CI: 7.42-9.30, p&#x2009;<&#x2009;0.001), hearing impairment (aOR&#x2009;=&#x2009;1.88, 95% CI: 1.46-2.43, p&#x2009;<&#x2009;0.001), visual impairment (aOR&#x2009;=&#x2009;1.80, 95% CI: 1.39-2.33, p&#x2009;<&#x2009;0.001), and not having a spouse (aOR&#x2009;=&#x2009;1.15, 95% CI: 1.01-1.31, p&#x2009;=&#x2009;0.036) were associated with increased odds of poor self-perceived health. Mild and severe depression (aOR&#x2009;=&#x2009;2.08, 95% CI: 1.84-2.36, p&#x2009;<&#x2009;0.001; aOR&#x2009;=&#x2009;5.89, 95% CI: 4.41-7.88, p&#x2009;<&#x2009;0.001, respectively) were also significantly associated with increased odds of poor self-perceived health. Conversely, having a medium (aOR&#x2009;=&#x2009;0.77, 95% CI: 0.64-0.92, p&#x2009;=&#x2009;0.004) or high education level (aOR&#x2009;=&#x2009;0.62, 95% CI: 0.52-0.74, p&#x2009;<&#x2009;0.001), and engaging in physical activity (aOR&#x2009;=&#x2009;0.67, 95% CI: 0.60-0.75, p&#x2009;<&#x2009;0.001) were associated with decreased odds of poor self-perceived health. Poor self-perceived health among community-dwelling older adults is highly prevalent and strongly influenced by demographic, lifestyle, clinical, and psychosocial factors. Public health strategies aimed at improving subjective health perceptions should address modifiable determinants, including chronic disease management, physical activity promotion, and mental health interventions.

The conservation of stream salamanders relies on effective monitoring of these cryptic species in freshwater habitats increasingly affected by human activities. Environmental DNA (eDNA) and environmental RNA (eRNA) offer non-invasive alternatives to conventional active search methods. However, knowledge gaps remain regarding how eDNA and eRNA (collectively environmental nucleic acids; eNA) signals vary across space and time under natural field conditions, limiting their integration into monitoring programs. We evaluated eNA signals in small headwater streams in Quebec (Canada), focusing on the northern two-lined salamander (Eurycea bislineata) and the spring salamander (Gyrinophilus porphyriticus). We collected water samples over three consecutive days during fall and winter, and we assessed eNA detection and concentration using species-specific qPCR assays targeting mitochondrial markers. Detection rates of eDNA were consistently high across seasons, highlighting its suitability for rapid presence-absence surveys. In contrast, eRNA detection rates were lower in the fall, but increased with repeated sampling. In winter, eRNA detection rates were near zero, consistent with salamanders' markedly reduced metabolic rate during overwintering, suggesting that mitochondrial eRNA primarily represents metabolically active individuals rather than species presence alone. The concentrations of eNA were positively associated with salamander abundance in fall. Our results demonstrate the value of eNA-based approaches for the monitoring of stream salamanders under natural field conditions.