Nevin Manimala

BMC Public Health. 2026 Jul 13. doi: 10.1186/s12889-026-28512-9. Online ahead of print.

ABSTRACT

BACKGROUND: Hypertension and diabetes are rising causes of morbidity and mortality in sub-Saharan Africa, yet rural community-level data remain limited. National surveys often obscure local variation, hindering targeted prevention.

METHODS: We conducted a population-based cross-sectional study in Kakum-Kombewa, Siaya County, Kenya (Dec 2024-Jun 2025). Multistage sampling identified 816 households, yielding 1,046 adults aged ≥ 18 years. Participants underwent household screening for blood pressure, random blood glucose, and anthropometry. Individuals with screened positive values were referred to linked primary healthcare facilities for diagnostic confirmation. Prevalence was estimated using descriptive statistics, and associations were assessed with chi-square tests and generalized linear models.

RESULTS: The prevalence of known hypertension, diabetes, and comorbidity was 13.9%, 8.7%, and 4.9%, respectively. Diagnostic confirmation identified an additional 4.2% newly confirmed hypertension, 2.3% newly confirmed diabetes, and 2.5% newly confirmed comorbidity, yielding total prevalence estimates of 18.1% (95% CI: 15.8-20.6), 11.0% (95% CI: 9.2-13.1), and 7.4% (95% CI: 5.9-9.2). Risk factors included age ≥ 50 years, overweight/obesity, central adiposity, family history, and physical inactivity. Female sex, central adiposity, low activity, and family history remained significant predictors in multivariable models.

CONCLUSION: This study reveals a substantial burden of both known and previously undiagnosed hypertension and diabetes in rural Western Kenya. Community-based screening, followed by referral and confirmatory testing, was effective in detecting new cases and identifying poor disease control among those with prior diagnoses. Strengthening routine NCD screening and linkage to primary care could improve early detection and management in similar rural settings.

PMID:42437904 | DOI:10.1186/s12889-026-28512-9

BMC Cardiovasc Disord. 2026 Jul 13. doi: 10.1186/s12872-026-06256-z. Online ahead of print.

ABSTRACT

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) is a critical life-support intervention for patients with severe respiratory and circulatory failure. Nevertheless, identifying the optimal timing of ECMO initiation and its correlation with survival, mortality, and complication rates continues to pose significant clinical challenges.

PURPOSE: This study intends to conduct a systematic review of the existing medical literature to clarify ECMO initiation timing and its association with patient outcomes, aiming to furnish evidence-based recommendations for clinical decision-making.

METHODS: We performed systematic searches across PubMed, Embase, Scopus, The Cochrane Library, and Web of Science for eligible cohort and case-control studies. Studies combining ECMO with other extracorporeal life-support modalities were excluded to eliminate survival confounding. Inclusion criteria encompassed adult ECMO recipients with reported initiation timing and at least one outcome measure. Study quality was evaluated using the Newcastle-Ottawa Scale (NOS).

RESULTS: From 1583 identified records, 30 studies were finally included, comprising 2 prospective cohorts, 1 case-control, and 27 retrospective cohorts. ECMO initiation timing was heterogeneously defined across multiple time intervals and clinical scenarios. Of the full set of 30 included studies, 23 performed statistical analyses examining the link between ECMO initiation delay and mortality; 18 of these 23 studies (60% of all 30 included studies) reported that prolonged ECMO initiation time was significantly associated with higher in-hospital or long-term mortality. Five of the 23 mortality-analyzing studies detected no statistically significant timing-mortality correlation, while the remaining 7 studies only reported organ complication outcomes and did not conduct any statistical testing of mortality as an endpoint. Quality appraisal demonstrated only one low-quality study, with all others graded as medium to high quality.

CONCLUSION: For patients with severe ARDS, cardiogenic shock, drug-induced shock, cardiac arrest, or post-cardiotomy shock, early ECMO initiation-such as within 7 days of mechanical ventilation-can effectively decrease mortality and reduce the incidence of neurological, hepatic, and renal complications.

TRIAL REGISTRATION: This study has been registered in the International Prospective Register of Systematic Reviews (PROSPERO: CRD420250652365).

PMID:42437887 | DOI:10.1186/s12872-026-06256-z

BMC Prim Care. 2026 Jul 13. doi: 10.1186/s12875-026-03470-8. Online ahead of print.

ABSTRACT

BACKGROUND: The digital transformation in healthcare has led to an increase in the use of telemedicine and artificial intelligence (AI)based applications. This study aims to examine the associations between e-health literacy, attitudes toward AI, and acceptance of telemedicine, and to test whether attitudes toward AI statistically mediate the association between e-health literacy and acceptance of telemedicine.

METHODS: Our study was conducted between January 1 and March 1, 2026. This cross-sectional study included 277 participants who visited a family health center. Data were collected using a sociodemographic information form, the General Attitude Scale toward Artificial Intelligence in Health Services, the Attitude Scale toward Telemedicine, and the e-Health Literacy Scale. Hierarchical regression analysis and mediation analysis using the bootstrap method (5,000 resamples) were performed.

RESULTS: The mean age of the participants was 30.52 ± 9.95, and 57.4% were female. In the hierarchical regression analysis, e-health literacy (β = 0.28, p < .001) and a positive attitude toward AI (β = 0.23, p = .010) were found to positively predict telemedicine acceptance, while a negative attitude toward AI (β = -0.28, p = .002) was found to negatively predict it. In the mediation analysis, it was determined that e-health literacy has a strong direct effect on telemedicine acceptance (β = 0.545, p < .001), but AI attitudes do not play a mediating role in this relationship (p > .05).

CONCLUSION: E- health literacy is a strong and direct determinant of telemedicine acceptance, independent of attitudes toward AI. Negative attitudes toward AI were associated with lower acceptance of telemedicine services. The results of our study suggest that strategies aimed at improving e- health literacy and addressing AI related concerns may be effective in promoting the widespread adoption of telemedicine, particularly in primary care settings.

PMID:42437877 | DOI:10.1186/s12875-026-03470-8

Cogn Res Princ Implic. 2026 Jul 13. doi: 10.1186/s41235-026-00740-y. Online ahead of print.

ABSTRACT

Educators face persistent challenges in fostering deep understanding of abstract STEM concepts. Theories of embodied cognition propose that grounding abstract ideas in bodily action and perception can enhance learning. Teachers often intuitively use embodied pedagogies such as gesturing and hand-drawing in the classroom, both by performing these themselves or asking students to do these actions, yet the comparative effects of these different types of embodied pedagogies are not well understood. Furthermore, the effect of these pedagogies needs to be put into perspective of students’ varying levels of prior understanding. It is unlikely that a single pedagogy will suit all learners. Building on research examining how embodied pedagogies interact with prior knowledge, we contrasted gesture-based and hand-drawing-based instruction in a college-level introductory statistics and data science course. Students were randomly assigned to view instructional videos that enacted either drawing or gesture then reenacted the demonstrated actions. Results showed that prior knowledge significantly moderated instructional effectiveness: For low-prior-knowledge learners, gesture-based instruction outperformed drawing-based instruction, whereas no difference emerged for high-prior-knowledge learners. The findings of this study contribute to our theoretical understanding of how embodied pedagogies impact learning and offer practical insights for tailoring embodied pedagogies to learners’ prior knowledge in the classroom.

PMID:42437864 | DOI:10.1186/s41235-026-00740-y

Lasers Med Sci. 2026 Jul 13;41(1):149. doi: 10.1007/s10103-026-04940-2.

ABSTRACT

Leishmaniasis, a zoonotic disease caused by parasites of the genus Leishmania, poses a significant medical and veterinary importance worldwide. This study was designed to explore the potential of SERS-based plasmonic substrate combined with advanced multivariate statistical analysis for differentiation of three prevalent Old World Leishmania species. In the present study, we investigated the potential of Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) combined with machine-learning-based analytical approaches for differentiation of three prevalent Old World Leishmania species. Previously characterized ITS1 PCR products corresponding to Leishmania infantum, Leishmania tropica, and Leishmania major were used as target molecules for spectroscopic analysis. Species identity of the samples had been confirmed previously using ITS1 PCR, sequencing, and PCR-RFLP analysis. Raman and SERS spectra were acquired using a HORIBA Raman microspectrometer equipped with a He-Ne laser. Silver nanoparticle-based SERS substrates were synthesized using a modified Tollens’ method to enhance Raman signal intensity. Spectral datasets were preprocessed and analyzed using principal component analysis (PCA), combined with linear discriminant analysis (PCA-LDA). The PCA-LDA technique reduced data dimensionality and facilitated visualization of spectral separation between species. A support vector machine (SVM) classifier was also utilized as an exploratory approach to visualize potential decision boundaries among species based on the SERS data. SVM classifiers on the ITS1 product spectra suggested the potential ability of SERS-derived spectral features to distinguish among three prevalent Old World Leishmania species. The obtained classifications were fully consistent with the previously confirmed molecular identification results. The findings demonstrate that SERS coupled with multivariate statistical analysis and machine-learning approaches can provide a promising analytical framework for species-level differentiation of Leishmania parasites based on ITS1 PCR products. This preliminary study highlights the potential application of Raman/SERS-based molecular profiling for future diagnostic and epidemiological investigations. Broader sampling across geographically diverse isolates and independent validation datasets will be required in future investigations to determine the reproducibility, specificity, and potential translational value of this analytical approach.

PMID:42437820 | DOI:10.1007/s10103-026-04940-2

Intensive Crit Care Nurs. 2026 Jul 12;96:104499. doi: 10.1016/j.iccn.2026.104499. Online ahead of print.

ABSTRACT

BACKGROUND: Patient-ventilator asynchrony is common in critically ill patients receiving mechanical ventilation, and timely recognition is essential for safe ventilatory management. However, factors associated with intensive care professionals’ ability to identify these events have not been systematically synthesized.

OBJECTIVE: To identify and synthesize factors associated with intensive care professionals’ ability to identify patient-ventilator asynchronies through a systematic review and meta-analysis.

METHODS: Two reviewers independently conducted systematic literature searches in PubMed, LILACS, Cochrane Library, ScienceDirect, and EMBASE from database inception to January 2026. Study selection, data extraction, and methodological appraisal were performed independently. Risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Analytical Cross-Sectional Studies. Pooled odds ratios (ORs) with 95% confidence intervals (95% CI) were calculated using random-effects models. Statistical heterogeneity was assessed using the I² statistic, and leave-one-out sensitivity analyses were performed to evaluate the influence of individual studies. Publication bias was explored using funnel plots. Statistical significance was set at p < 0.05. Certainty of evidence was assessed using the GRADE approach.

RESULTS: Twelve studies including 4823 healthcare professionals were included, of which seven contributed data to the meta-analysis. Previous training in mechanical ventilation was significantly associated with a higher likelihood of correctly identifying patient-ventilator asynchronies (OR = 3.49; 95% CI: 1.95-6.25; I² = 83%). Similarly, advanced academic training was also significantly associated with correct identification (OR = 1.83; 95% CI: 1.07-3.16; I² = 28%). In contrast, specific training in asynchronies or waveform interpretation was not significantly associated (OR = 1.75; 95% CI: 0.67-4.56; I² = 68%). No significant association was observed according to profession. Overall, most studies were at low risk of bias, although some methodological limitations were identified, and the certainty of the evidence was low.

CONCLUSION: Previous training in mechanical ventilation and advanced academic training were associated with improved identification of patient-ventilator asynchronies among intensive care professionals. However, the available evidence remains limited and heterogeneous.

IMPLICATIONS FOR CLINICAL PRACTICE: General training in mechanical ventilation is associated with improved recognition of patient-ventilator asynchrony in clinical practice. Specific training in waveform interpretation alone may be insufficient. Standardized and clinically integrated training approaches may support improved detection of asynchrony in intensive care settings.

PMID:42437551 | DOI:10.1016/j.iccn.2026.104499

Musculoskelet Sci Pract. 2026 Jul 12;85:103616. doi: 10.1016/j.msksp.2026.103616. Online ahead of print.

ABSTRACT

Psychological distress, particularly anxiety and depression, is prevalent among KOA patients and may exacerbate functional disability through maladaptive cognitive processes such as pain catastrophizing. This study examined whether pain catastrophizing mediates the relationship between psychological distress and functional disability in KOA patients. We enrolled 90 KOA patients between January 2024 and January 2025. Anxiety (GAD-7), depression (PHQ-9), pain catastrophizing (Pain Catastrophizing Scale, PCS), functional disability (WOMAC), and pain intensity (visual analog scale, VAS) were assessed. Pearson correlation, hierarchical regression, and bootstrap-based mediation analyses were performed. The mean age was 61.77 ± 7.63 years, and 58.9% were female. Anxiety (GAD-7: 8.58 ± 4.68), depression (PHQ-9: 8.92 ± 5.31), and pain catastrophizing (PCS: 23.59 ± 10.43) were moderately elevated. All psychological variables were significantly correlated with WOMAC scores (r = 0.464-0.637, P < 0.001). Hierarchical regression showed psychological variables significantly increased explained variance in functional disability (ΔR² = 0.095, P < 0.001). Mediation analysis revealed pain catastrophizing partially mediated the anxiety-disability relationship (indirect effect = 0.816, 95% CI [0.425, 1.256], proportion mediated = 48.5%) and fully mediated the depression-disability relationship (indirect effect = 1.028, 95% CI [0.557, 1.636], proportion mediated = 65.0%). Within these cross-sectional data, pain catastrophizing statistically mediated the associations of anxiety and depression with functional disability; because temporal precedence cannot be established, these relationships should be interpreted as associational rather than causal. The findings nonetheless identify pain catastrophizing as a potentially modifiable cognitive correlate of disability and support evaluating cognitive-behavioral interventions targeting catastrophizing within comprehensive KOA management.

PMID:42437550 | DOI:10.1016/j.msksp.2026.103616

Water Res. 2026 Jul 5;305:126429. doi: 10.1016/j.watres.2026.126429. Online ahead of print.

ABSTRACT

Per- and polyfluoroalkyl substances (PFAS) pose persistent and widespread risks to aquatic ecosystems, yet their long-term risk dynamics remain poorly quantified. Here, we reconstruct the spatiotemporal evolution of PFAS ecological risk in China’s river networks from 2011 to 2024 by integrating a national historical monitoring database (n = 1,110 sites) with interpretable machine learning and statistical modeling. Ecological risk was quantified using a mixture-based risk index and predicted at 2 km resolution using an XGBoost classifier trained on 19 dynamic environmental and socioeconomic covariates. Model transferability was evaluated using an independent out-of-time field survey conducted in 2024. The model achieved stable predictive performance (AUC = 0.84 for internal testing; AUC = 0.86 for independent external validation), indicating its out-of-time generalization potential in a typical mixed-use watershed. High-risk regions were persistently concentrated in eastern China. Temporal analysis revealed a transient reduction in national high-risk area temporally coincident with the 2019 PFOS ban (-18.5% relative to the 2019 peak), followed by an observed rebound trajectory in 2023-2024, temporally associated with the increasing prevalence of short-chain alternatives. SHAP-SEM analysis suggests that natural hydrogeological conditions are associated with lower baseline vulnerability, whereas anthropogenic pressures are associated with elevated risk, potentially through the attenuation of soil retention capacity. These results provide a decadal-scale, policy-resolved assessment of PFAS ecological risk and provide data-driven insights into the limitations of substance-by-substance regulation.

PMID:42437549 | DOI:10.1016/j.watres.2026.126429

Eur J Radiol. 2026 Jul 9;204:113056. doi: 10.1016/j.ejrad.2026.113056. Online ahead of print.

ABSTRACT

BACKGROUND: To evaluate whether quantitative craniospinal MRI assessment of baseline tumor burden provides prognostic value in patients with recurrent, previously irradiated medulloblastoma undergoing MEMMAT (Metronomic Antiangiogenic) therapy.

METHODS: We analyzed craniospinal MRI of 40 patients with recurrent, previously irradiated medulloblastoma enrolled in the MEMMAT trial (April 1, 2014, and March 31, 2021). Ependymal, leptomeningeal, and local relapse lesions were retrospectively manually segmented on T1-contrast-enhanced (T1CE) and diffusion-weighted imaging (DWI) at baseline and follow-up (best response). Lesion count and volume were quantified. Bland-Altman analyses and intraclass correlation coefficients (ICC) assessed inter-sequence agreement., logistic regression evaluated associations between baseline tumor burden and progressive disease.

RESULTS: Patients achieving Complete Response (n = 6/40) showed mean monthly decreases of – 12.7% in T1CE lesion count and – 12.9% in volume. Partial Response patients (n = 9/40) showed similar declines (-10.3% and – 13.0%). Stable Disease patients (n = 5/40) demonstrated minimal decreases (-0.8% and – 2.3%). Progressive Disease patients (n = 16/40) showed increases of 33.7% in lesion count and 56.2% in volume. Logistic regression indicated trends toward higher baseline tumor burden predicting PD (volume OR 1.18, p = 0.08; lesion count OR 1.05, p = 0.075). Agreement between T1CE and DWI was limited (ICC 0.35 for lesion count, 0.47 for volume), with 23% of patients misclassified using either modality alone. Survival analyses demonstrated significantly shorter overall survival in patients with baseline lesion volumes ≥ 5.5 ml (log-rank p = 0.003), while a similar association for progression-free survival did not reach statistical significance (p = 0.053).

CONCLUSIONS: Combined intracranial and intraspinal T1CE and intracranial DWI assessment improves response evaluation. Exploratory analyses suggested that higher baseline tumor burden may be associated with progression, although the observed associations were of borderline statistical significance and require validation in larger cohorts.

PMID:42437539 | DOI:10.1016/j.ejrad.2026.113056

Biotechnol Bioeng. 2026 Jul 12. doi: 10.1002/bit.70306. Online ahead of print.

ABSTRACT

Microbial inulinases are increasingly recognized as valuable biocatalysts for the sustainable production of high-value products, including fructooligosaccharides, fructose, bioethanol, and organic acids in industries, such as food, pharmaceuticals, and bioenergy. In the last few decades, microbial inulinase research has advanced significantly, from strain selection and fermentation optimization to advanced enzyme engineering and immobilization, improving yields, stability, and reusability. There are still some final bottlenecks, such as low yields, poor thermostability, and high purification costs. This review examines strategies to innovate and overcome these bottlenecks, including novel immobilization strategies that utilize nanomaterials, system-scale bioprocess optimization using artificial intelligence (AI), and bioprospecting extremophiles using metagenomics. The present review discusses how statistical and computational modeling (RSM, ANN, and AI) significantly increases yield and process efficiency, with comments on their relevance to contemporary biorefinery applications. The advanced immobilization approaches significantly enhance operational stability and reusability, allowing for continuous processing. This review situates the development of inulinase as not just an enzymological effort but a multidisciplinary effort involving process engineering and sustainability science. Overall, emphasize is given toward the thought that advancements leaning toward the future will require a synthesis of AI-designed enzyme systems; economical immobilization supports; and incorporation of circular bioeconomy principles through the valorization of agro-wastes. These barriers to knowledge transfer must be resolved if we are to unlock the full bioeconomic potential of microbial inulinase systems.

PMID:42437513 | DOI:10.1002/bit.70306