BMC Endocr Disord. 2026 Feb 28. doi: 10.1186/s12902-026-02211-3. Online ahead of print.
NO ABSTRACT
PMID:41764469 | DOI:10.1186/s12902-026-02211-3
Tag: pubmed
BMC Health Serv Res. 2026 Feb 28. doi: 10.1186/s12913-026-14265-z. Online ahead of print.
ABSTRACT
BACKGROUND: In diverse healthcare teams, insufficient cultural awareness can lead to communication challenges, interpersonal conflict, and staff turnover, negatively impacting patient care and organizational performance. Culturally competent environments foster inclusive team climates, enhance collaboration, and contribute to higher job satisfaction-key factors in staff retention and the delivery of effective care. This study aims to explore team climate, job satisfaction, cultural competence, and intent to stay among healthcare professionals working in multicultural healthcare teams.
METHODS: A quantitative, cross-sectional research design (n = 490) utilizing descriptive, bivariate, and multivariate statistical analyses. The electronic survey consisted of three standardized instruments: the Team Climate Inventory, the Kuopio University Hospital Job Satisfaction Scale, and the Cross-Cultural Competence of Healthcare Professionals, all using a 5-point Likert scale. Additionally, one item assessed intention to stay.
RESULTS: A total of 490 healthcare professionals participated in this survey. The participants rated their team climate (M = 3.72, SD = 0.74), job satisfaction (M = 3.76, SD = 0.62), and cultural competence (M = 3.59, SD = 0.55) as moderate. One quarter of the respondents were not satisfied with their current profession. We observed correlations between cultural competence (r = 0.316), team climate (r = 0.709), and job satisfaction. Team climate (r = 0.342) and job satisfaction (r = 0.452) also showed a correlation with the intention to stay. Furthermore, women evaluated their cultural competence higher than men (p < 0.001). Intention to stay was statistically significantly related to team climate (p < 0.001), job satisfaction (p < 0.001), and cultural competence (p = 0.015). Educational level had a statistical association (p = 0.003) with job satisfaction.
CONCLUSIONS: These findings highlight the importance of supportive work environments and international collaboration in fostering retention and inclusivity. Future research should investigate the directionality of the relationships between team climate, job satisfaction, cultural competence, and intention to stay using more advanced multivariate approaches. This could further support organizations in their efforts to foster well-being in multicultural healthcare teams.
PMID:41764467 | DOI:10.1186/s12913-026-14265-z
BMC Med Educ. 2026 Feb 28. doi: 10.1186/s12909-026-08914-4. Online ahead of print.
NO ABSTRACT
PMID:41764461 | DOI:10.1186/s12909-026-08914-4
BMC Vet Res. 2026 Feb 28. doi: 10.1186/s12917-026-05381-3. Online ahead of print.
ABSTRACT
BACKGROUND: Salmonella enterica and Escherichia coli-associated enteric disturbances contribute to health and productivity losses in poultry and pose zoonotic concerns. In the context of antimicrobial resistance, phytogenic feed additives may offer antibiotic-sparing strategies by modulating the intestinal microbiota. We evaluated a fenugreek (Trigonella foenum-graecum) and turmeric (Curcuma longa) extract combination for its microbiota-modulating effects in a controlled dual-challenge model.
MATERIALS AND METHODS: A total of 270 Bábolna Tetra-SL chicks were allocated to six groups: low-, medium-, or high-dose phytobiotic; enrofloxacin; infected control; and non-infected control. Birds were orally challenged on days 3-4 post-hatch with clinical isolates of S. enterica and E. coli (both phenotypically susceptible to enrofloxacin). Cloacal swab samples were collected on days 1, 7, and 42 and profiled by V3-V4 16 S rRNA gene amplicon sequencing. Alpha diversity and beta diversity were assessed in QIIME2 using non-parametric and permutation-based approaches.
RESULTS: Alpha diversity increased with age across groups. On day 42, the medium-dose phytobiotic group exhibited the most balanced community profile among treated groups, whereas enrofloxacin was associated with the strongest early community disruption followed by partial recovery by day 42. Beta diversity ordinations and clustering indicated clear time-driven separation, with treatment-associated differences observed within time points and supported by permutation-based multivariate statistics.
CONCLUSIONS: A fenugreek-turmeric phytobiotic modulated cloacal microbiota structure in chickens under a controlled dual-challenge model. Medium-dose supplementation was associated with the most balanced community configuration at the end of the trial, while enrofloxacin induced marked early perturbation. These findings support further evaluation of phytogenic additives as components of antibiotic-reduction strategies in poultry production.
PMID:41764458 | DOI:10.1186/s12917-026-05381-3
BMC Plant Biol. 2026 Feb 28. doi: 10.1186/s12870-026-08434-9. Online ahead of print.
ABSTRACT
BACKGROUND: Genotypic differences in nitrogen use efficiency strongly influence sorghum growth and yield, highlighting the need for precise and reliable prediction of cultivar responses to nitrogen (N) availability. This study investigates the impact of two N treatments on sorghum cultivars, using artificial intelligence (AI) models for prediction.
RESULTS: A randomized complete block design with two treatments: 0 kg N ha– 1 (0 N) and 238 kg N ha– 1 (238 N) was used. Six hybrid sorghum cultivars (Gustav, Estyphon, Foehn, Vegga, Aday1 and Beydarı) were evaluated for different traits. Statistical analysis included two-way ANOVA and factorial regression to assess treatment effects. Significant treatment effects were observed. Beydarı and Estyphon exhibited larger stem diameter and leaf area under 238 N, while Aday1 had the smallest values under 0 N. Gustav showed the highest panicle width, panicle weight, and grain yield under 238 N. Stomatal conductance showed an opposite trend, decreasing with N supplementation. Machine learning models, specifically Random Forest (RF) and Light Gradient-Boosting Machine (LightGBM), were used to model the interaction, achieving R2 values ranging from 0.759 to 0.966 for RF and 0.729 to 0.980 for LightGBM, indicating strong predictive accuracy.
CONCLUSION: LightGBM consistently achieved R2 values greater than 0.92 for key traits, such as stomatal conductance, panicle width, and grain yield, demonstrating its potential to optimize N management. Gustav performed best under high N, whereas cultivar responses to low N were genotype-specific, captured effectively by the machine learning models. These findings highlight the role of AI models in predicting cultivar performance and supporting sustainable agricultural decisions.
PMID:41764445 | DOI:10.1186/s12870-026-08434-9
Bioinformatics. 2026 Mar 1:btag090. doi: 10.1093/bioinformatics/btag090. Online ahead of print.
ABSTRACT
MOTIVATION: Understanding the functional roles of lipids is essential for interpreting metabolic phenotypes in health, disease, and dietary interventions. However, lipidomic analyses typically focus on individual lipid species, making it difficult to extract mechanistic and systems-level insights. We therefore asked how quantitative lipidomic data can be translated into biologically structured and function-oriented interpretations.
RESULTS: Here, we present a major update to LipidOne (lipidone.eu), introducing the novel analytical module: Functional Lipid Analysis (FLA). FLA computes 42 indices describing lipid functions related to membrane structure, energy storage, and signaling. Indices are derived from lipid classes and fatty acyl-, alkyl-, and alkenyl-chain composition, statistically compared across experimental groups, and explored using multivariate and visualization tools. Each index is semantically annotated and linked to predicted protein mediators, enabling pathway- and network-based interpretation. Application to published datasets confirmed previous conclusions while uncovering additional biologically coherent functional insights.
AVAILABILITY AND IMPLEMENTATION: New FLA module is freely available through LipidOne.eu web platform. The LipidOne FLA core R script (v1.0.0) is archived on Zenodo (DOI: 10.5281/zenodo.18468230). The LipidOne web platform is available at https://lipidone.eu.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
PMID:41764409 | DOI:10.1093/bioinformatics/btag090
J Water Health. 2026 Feb;24(2):128-147. doi: 10.2166/wh.2026.145. Epub 2026 Feb 6.
ABSTRACT
This study assessed the health risks associated with groundwater contamination by metals and metalloids in the Tabalaopa-Aldama aquifer, located in the arid region of northern Mexico. A total of 40 drinking water wells were sampled and analyzed for elements including arsenic, aluminum, uranium, iron, nickel, and zinc. The results revealed that a significant proportion of the wells exceeded national and international permissible limits for these contaminants. To evaluate the potential impact on public health, three complementary indices were applied: the health risk index, the hazard quotient, and the water quality index. The integrated analysis demonstrated high consistency among the indices, particularly highlighting arsenic, iron, and nickel as critical contaminants. Multivariate statistical techniques further identified key patterns and groupings, revealing that contaminant levels are influenced by geological and hydrological factors such as well depth and flow rate. The integration of the results from these indices through multivariate statistical methods – specifically Principal Component Analysis (PCA) and cluster analysis – provided a valuable assessment of the concordance and divergences between the indices. This allowed for more robust identification of high-risk areas and contributed to better-informed decision-making for targeted water quality management and public health protection.
PMID:41764387 | DOI:10.2166/wh.2026.145
Clin Gerontol. 2026 Mar 1:1-20. doi: 10.1080/07317115.2026.2629563. Online ahead of print.
ABSTRACT
OBJECTIVES: To examine the association between work beyond the traditional retirement age and mental health outcomes among older Canadians (65+ years) and to assess whether these associations vary by sex.
METHODS: A subsample of (N = 65,033) older adults was drawn from repeated national Canadian Community Health Surveys between 2013 to 2018. Firth’s logistic regression model was applied to identify factors associated with self-reported mood and anxiety disorders. Prevalence estimates and adjusted odds ratios with 95% confidence intervals are reported.
RESULTS: The prevalence of self-reported mood and anxiety disorders were 6.9% and 5.3% respectively. We found that paid full-time work was positively associated with self-reported mood disorder (OR = 0.61, 95% CI: 0.50-0.73) and self-reported anxiety disorder (OR = 0.65, 95% CI: 0.52-0.81). Older age (75+) was positively associated with self-reported mood disorder (OR = 0.56, 95% CI: 0.51-0.62) and self-reported anxiety disorder (OR = 0.62, 95% CI: 0.55-0.69). High work-related stress was a significant negative associated factor for both mental disorders [(OR = 1.46, 95% CI: 1.16-1.82), and (OR = 1.38, 95% CI: 1.07-1.77, respectively)]. Being female, single, a current smoker, and multimorbidity were statistically significant negative associated factors for both self-reported mood and anxiety disorders. Although females reported higher prevalence of self-reported mood and anxiety disorders, the significant factors associated with these conditions were largely similar across both sexes.
CONCLUSIONS: Our findings emphasize the positive mental health benefits of paid work past age 65+ and its obvious financial benefit.
CLINICAL IMPLICATIONS: This research supports the idea of “active aging” and emphasize the need for further research to explore the motivations behind continued employment and their differential impact on mental health.
PMID:41764384 | DOI:10.1080/07317115.2026.2629563
Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-026-42144-4. Online ahead of print.
ABSTRACT
Afghan refugees face persistent poverty, social marginalization, and restricted access to healthcare in Pakistan, making them one of the world’s largest and longest-displaced groups. Health disparities have been made worse by decades of instability, especially among marginalized groups living in informal urban settlements and refugee camps. With an emphasis on how income, education, and legal status affect health outcomes and healthcare access, this study explores the socioeconomic determinants and health burdens among Afghan refugees residing in Pakistan. Between January and June 2025, 250 Afghan refugee families (n = 1460 people) in the provinces of Balochistan and Khyber Pakhtunkhwa were surveyed. To guarantee proportionate representation from camp-based and urban populations, stratified random sampling was employed. Data were gathered via structured questionnaires using a cross-sectional methodology, and SPSS v.27 was used for analysis. Multiple logistic regression, chi-square tests, and descriptive statistics were used to find predictors of poor health outcomes. Undocumented status (OR = 3.11, p < 0.001) and low income (OR = 2.34, p < 0.001) were found to be significant risk variables. Results show that poor health outcomes are strongly correlated with socioeconomic deprivation. Reducing health disparities among Afghan refugees in Pakistan requires bolstering social protection systems, livelihood initiatives, and inclusive healthcare access.
PMID:41764346 | DOI:10.1038/s41598-026-42144-4
Sci Rep. 2026 Feb 28. doi: 10.1038/s41598-026-41837-0. Online ahead of print.
NO ABSTRACT
PMID:41764340 | DOI:10.1038/s41598-026-41837-0