Nevin Manimala

Int J Health Geogr. 2025 Nov 22;24(1):35. doi: 10.1186/s12942-025-00423-9.

ABSTRACT

BACKGROUND: Mental-health geomatics require reliable ways to convert high-frequency GPS trajectories into meaningful place types that support indicators such as homestay, location entropy, and spatial extent of daily activities. Raw coordinates are typically noisy and carry little semantic information. We introduce H3-MOSAIC(H3-based Multimodal OSM-and-Satellite AI for Classification), a multimodal generative framework that fuses OpenStreetMap (OSM) building text and satellite imagery on H3 grids to infer place semantics from high-frequency GPS.

METHODS: Raw GPS was smoothed by minute-level speed filtering, then assigned to Level 10 H3 hexagons. Cells were retained if the mean speed was ≤ 1.2 m/s and the cumulative duration was ≥ 15 min, contiguous cells were merged, and home was defined as the cell with the longest dwell from 23:45 to 06:00. We compared text-only OSM classification with image-based and fused approaches across open-source models (DeepSeek, CLIP, LLaVA, Qwen-VL) and proprietary models (GPT-4o-mini, Gemini-2.5-flash-lite). Performance was assessed by accuracy, Cohen’s kappa, precision, recall, F-measure, and confusion matrices. Day level associations between H3 semantic exposures and stress were examined by a random forest model and explainable methods.

RESULTS: Multimodal methods outperformed single-modality baselines. In the 11-class task, accuracies were: CLIP 0.179, LLaVA 0.269, Qwen-VL 0.565, GPT-4o-mini 0.779, and Gemini-2.5-flash-lite 0.790. In the 5-class consolidation, accuracies rose to 0.702 (Qwen-VL), 0.849 (GPT-4o-mini), and 0.858 (Gemini-2.5-flash-lite). Text-only OSM baselines were lower (≈ 0.60-0.68). Across 3,845 hexagons with OSM text, closed-source models agreed on 79% of labels; disagreements concentrated in mixed-use, office, and green classes. Error modes reflected area-dominant versus keyword-triggered reasoning, hybrid-parcel ambiguity, tag sparsity, and symbolic artifacts. Stabilized semantics support more robust computation of homestay, entropy, and activity space and are suitable for privacy-aware, cross-city reuse. In a day-level case study, minutes at Home related to lower stress; Green showed a U-shaped pattern.

CONCLUSIONS: H3-MOSAIC provides a scalable, auditable pipeline for semantic place detection from high-frequency GPS. Multimodal fusion markedly improves accuracy and consistency. Proprietary models are most robust on hard classes and open-source models are practical for coarse taxonomies. H3 day level exposures show stress patterns consistent with established mental health pathways, supporting face validity. The framework enables downstream exposure analyses with reduced misclassification and improved interpretability.

PMID:41275284 | DOI:10.1186/s12942-025-00423-9

Lipids Health Dis. 2025 Nov 22. doi: 10.1186/s12944-025-02782-5. Online ahead of print.

ABSTRACT

BACKGROUND: Lipid metabolism may be linked to chronic gastritis, but its causal role remains unclear. While current research emphasizes inflammation, mucosal changes, immune regulation, genetics, and the gut microbiota, the contribution of lipid metabolism is understudied. This study aims to evaluate the impact of serum lipids and the mechanistic roles of lipid-lowering drug targets in chronic gastritis.

METHODS: We conducted a cross-sectional study using data from real world. Multivariable logistic regression was performed to assess the association between serum lipid profiles and gastritis. Mendelian randomization (MR) analyses based on genome-wide association study (GWAS) datasets were performed to detect the causal relationship of serum lipids, plasma lipid species, and lipid-lowering drug targets. Experimental validation was conducted using high-fat diet (HFD)-fed mice and chemically induced CAG rat models.

RESULTS: Four thousand sixty one person, including 1,023 patients with chronic atrophic gastritis (CAG), 1,742 with non-atrophic gastritis (NAG), and 1,296 as healthy population were included in the analysis. Through covariates adjustment, TC, ApoA1, and HDL-C showed to be associated with an increased risk of chronic gastritis, whereas TG exhibited a protective effect. MR analysis confirmed a significant inverse causal relationship between TG and gastritis (OR = 0.889, 95% CI: 0.825-0.958). Ten plasma lipid species and lipid-lowering gene targets, including LPL and APOC3, were identified as causally associated with disease risk. Mediation analysis revealed six plasma lipid species as potential intermediaries linking genetic variation to gastritis. In vivo experiments demonstrated progressive hepatic steatosis and mild gastric mucosal changes in HFD-fed mice. Immunohistochemical analysis further revealed a significant reduction in LPL and APOC3 expression in gastric tissue (P < 0.05). In the CAG rat model, histological analysis revealed hepatocyte disarray, edema, and gastric mucosal atrophy. Elevated levels of TNF-α, IL-6, IL-1β and decreased levels of GAS-17 and PG I/II were also observed (P < 0.05). Western blot analyses further confirmed the downregulation of LPL and APOC3 expression in gastric tissue (P < 0.05).

CONCLUSIONS: This study provides genetic and experimental evidence, supporting a causal role of lipid metabolism in chronic gastritis. LPL and APOC3 are implicated in its pathogenesis, highlighting potential lipid-targeted strategies for prevention and treatment.

PMID:41275282 | DOI:10.1186/s12944-025-02782-5

BMC Oral Health. 2025 Nov 22. doi: 10.1186/s12903-025-07362-8. Online ahead of print.

ABSTRACT

BACKGROUNDS: The aim of this study was to compare the gloss values obtained from two different 3D-printed resins and one composite resin following the application of various polishing techniques, and to evaluate their gloss retention after exposure to different aging protocols.

METHODS: Two 3D-printed resins, Varseo Smile Crown (BEGO, Germany) and Saremco Print Crowntec (Saremco Dental, Switzerland) and one composite resin (G-aenial Universal Posterior, A2, GC, Japan) were tested. A total of 280 specimens were fabricated and subjected to four different polishing protocols (Enhance + Twist Dia, Enhance + Polishing paste, Enhance + Twist Dia + Polishing paste, and glazing). An additional group received no polishing and served as the control. Gloss values were measured using a glossmeter (NovoGloss; Rhopoint Instrument, UK) at three time points: after fabrication (T0), after polishing (T1), and after 1- hour aging (T2). After the first measurement, the specimens were subjected to three aging procedures: toothbrushing simulation, exposure to acidic fluoride gel (Elmex Gelée, GABA, Switzerland), and immersion in alcohol (75% ethanol). Distilled water served as the control group. Data were statistically analyzed using paired t-tests, one-way ANOVA, and Tamhane’s T2 post hoc tests, with significance set at p < 0.05.

RESULTS: Initial gloss values of both 3D-printed resins were comparable, with glazing achieving the highest gloss. Regardless of the polishing technique, the composite resin exhibited the highest gloss values, with the Enhance + Polishing paste method yielding the best results. Among all aging procedures, toothbrushing mechanical aging resulted in the most significant gloss reduction for all three materials.

CONCLUSION: For the composite resin, the Enhance + Polishing paste technique provided the highest gloss. For the 3D-printed resins, glazing was the most effective method in achieving higher gloss. Mechanical aging had the greatest detrimental effect on gloss for all tested materials.

PMID:41275278 | DOI:10.1186/s12903-025-07362-8

Cancer Imaging. 2025 Nov 22. doi: 10.1186/s40644-025-00957-y. Online ahead of print.

ABSTRACT

BACKGROUND: New factors predicting response in patients with a PD-L1 tumor proportion score (TPS) ≥ 50% for locally advanced or metastatic non-small cell lung cancer (NSCLC) are needed to better select first-line therapy. Based on the literature, we previously developed a radiomic model predicting the KEAP1/NFE2L2 mutational status.

METHOD: This was a retrospective monocenter study including 94 consecutive patients with advanced or metastatic PD-L1 ≥ 50% NSCLC, treated with pembrolizumab, who underwent a pre-therapeutic FDG-PET/CT and were followed up for 1 year. Seventy-seven patients who did not progress within the first 60 days of treatment were analyzed. Each primary lesion was segmented by 2 physicians on PET and CT scans. Radiomic features were calculated using MIM software on both PET and CT imaging. A previously developed KEAP1/NFE2L2 radiomic prediction model (called MUT_PET) was applied to this cohort using the initial FDG-PET/CT. The primary endpoint was the validation of the MUT_PET model as a predictive factor of PFS via the non-invasive prediction of KEAP1/NEF2L2 mutation.

RESULTS: The main characteristics of this cohort were: median age of 67.0 years [range, 48.0-84.0], sex ratio M/F = 60/17, 74.0% of patients with a histopathology of adenocarcinoma and 85.0% with a stage IV disease. The median follow-up was 20.0 months [range, 15.3-23.9]. Fifty-six (72.2%) patients experienced a disease progression with a median PFS of 11.8 months (CI95% 8.6-15.8) among which 51 (66.2%) died. In univariable analysis, MUT_PET model was statistically significant as a predictive factor of improved PFS (HR = 0.51, CI95% 0.30-0.91, p = 0.02) whereas it was not statistically significant regarding OS (HR = 0.61, CI95% 0.34-1.11, p = 0.10). In multivariable analysis, the MUT_PET model was associated with a HR of 0.6 (CI95% 0.34-1.06, p = 0.08). Combining the MUT_PET prediction, the histology subtype and the existence of liver metastases, a multimodal nomogram was able to predict PFS (chi-test of 39.43, p < 0.0001).

CONCLUSION: In PD-L1 TPS ≥ 50% NSCLC patients treated with pembrolizumab, our results suggest an improved PFS in patients predicted to be KEAP1/NFE2L2 mutated.

PMID:41275271 | DOI:10.1186/s40644-025-00957-y

BMC Health Serv Res. 2025 Nov 22. doi: 10.1186/s12913-025-13694-6. Online ahead of print.

ABSTRACT

BACKGROUND: Chinese government has been adjusting its strategies in response to rapid domestic and international changes to devise effective health policies and enhance public health. However, with the rapid socio-economic development and the COVID-19 outbreak, many researchers have identified issues of inefficiency and uneven distribution in health resource allocation within China. Therefore, how to scientifically allocate and efficiently use Chinese health resources has become an urgent issue.

METHODS: The super-efficiency SBM model and global Malmquist model were used to measure and dynamically monitor the health resource allocation efficiency of 31 provinces in China from 2008 to 2020. Moran’s I was applied to test the spatial autocorrelation of the efficiency, and the spatial Dubin model was constructed to analyze influencing factors. All data were collected from the China Health Statistical Yearbook and China Statistical Yearbook from 2008 to 2020.

RESULTS: The super-efficiency SBM model revealed an average health resource allocation efficiency score of 0.632. The average Malmquist productivity index for the same period was 1.090, indicating a generally positive growth. Moran’s I test showed a notable spatial autocorrelation in efficiency distribution. And the regression results of the spatial Dubin model showed that the efficiency was affected by the dependency ratio, illiteracy rate, per capita disposable income, per capita public health budget expenditure, number of medical insurance participants, and the balance of medical insurance fund revenue and expenditure.

DISCUSSIONS: The results revealed that China’s health resource allocation exhibited low efficiency and regional disparities, primarily driven by uneven regional development. From 2008 to 2020, overall productivity increased by 9%, which were predominantly attributable to technological advancements. Under conditions of strong spatial autocorrelation, the efficiency of health resource allocation was shaped by multiple factors operating through distinct spatial channels.

CONCLUSION: Given the challenges of health resource allocation efficiency in China, it is vital to implement targeted strategies. These include strengthening policy support for inefficiency regions, relying on technological progress and scientific management, fostering cross-regional collaboration to leverage spatial effects, and considering multiple factors for rational health resource allocation to ensure the sustainability of the health services.

PMID:41275267 | DOI:10.1186/s12913-025-13694-6

BMC Oral Health. 2025 Nov 22. doi: 10.1186/s12903-025-07338-8. Online ahead of print.

ABSTRACT

BACKGROUND: To evaluate the temperature values including initial, maximum, and rising caused by light-cured materials used for direct capping during polymerisation.

METHODS: A 3 mm deep, wide, and length class-I cavity was prepared to a premolar tooth, leaving hard tissue at the pulpal floor of 1 mm thickness with a 1 mm diameter of exposure. The sample was placed in a customised mimicry setup in which the temperature was standardised (37 °C) by a double-verified system. Light-curing capping materials (Theracal LC, Theracal PT, Harvard BioCal, and Ultrablend Plus) were placed, polymerised, and temperature values were recorded. Kruskal-Wallis test was used to compare parameters among groups, and Dunn’s test was used to define the group that caused the difference (p < 0.05).

RESULTS: There were statistically significant differences between the materials in terms of initial, maximum, and temperature rising values (p_in=0.014, p_max=0.034, p_tr= 0.016). The values of Theracal PT were measured highest in terms of temperature increase, while no statistically significant difference was observed between other materials during polymerisation.

CONCLUSIONS: Theracal PT caused higher temperature rise, however, it did not exceed 5.6 °C, which is the critical value for the pulp. Theracal PT should be used with caution as its use during direct capping causes high temperature increases, and there is a need for a light-curing regime to be designed for its use.

PMID:41275265 | DOI:10.1186/s12903-025-07338-8

BMC Oral Health. 2025 Nov 22. doi: 10.1186/s12903-025-07310-6. Online ahead of print.

ABSTRACT

OBJECTIVES: The primary aim of this study was to evaluate the impact of cyclooxygenase-2 (COX-2) expression on overall survival (OS), local recurrence-free survival (LRFS), and regional recurrence-free survival (RRFS) in patients diagnosed with advanced oral squamous cell carcinoma (AOSCC).

MATERIALS AND METHODS: COX-2 expression levels were assessed in 191 cases of AOSCC and 50 cases of normal mucosa using immunohistochemistry (IHC). Comparisons were made between COX-2 expression in AOSCC and normal mucosal tissues, as well as its influence on OS, LRFS, and RRFS. The Cancer Genome Atlas (TCGA)- Head and Neck Squamous Cell Carcinoma (HNSC) database was utilized for validation.

RESULTS: In this cohort of 191 patients with AOSCC followed for 1-145 months (median: 68.3 months), AOSCC Patients exhibited significantly higher COX-2 expression compared to normal oral mucosa tissues. Consistent result was obtained from analysis of the AOSCC subgroup from TCGA HNSC cohort. In the subset of AOSCC patients filtered from the TCGA-HNSC database, COX-2 mRNA expression showed no statistically significant association with survival. However, In our cohort of AOSCC patients from IHC analysis, COX-2 expression emerged as an independent prognostic factor for OS, LRFS, and RRFS. Positive COX-2 expression was associated with a markedly increased risk of recurrence and diminished survival outcomes.

CONCLUSIONS: COX-2 is overexpressed in AOSCC and appears to be a potential adverse prognostic factor in our cohort. As a biomarker, COX-2 may offer valuable prognostic insights for AOSCC.

PMID:41275260 | DOI:10.1186/s12903-025-07310-6

Int J Equity Health. 2025 Nov 22. doi: 10.1186/s12939-025-02701-1. Online ahead of print.

NO ABSTRACT

PMID:41275258 | DOI:10.1186/s12939-025-02701-1

BMC Public Health. 2025 Nov 22. doi: 10.1186/s12889-025-25718-1. Online ahead of print.

ABSTRACT

BACKGROUND: Due to their fragile physiologic functions, Over 65% of deaths from complicated severe acute malnutrition occur in the first week of treatment, primarily due to medical complications. To reduce this, early stabilization is crucial, and there is limited evidence regarding stabilization time in Ethiopia.

OBJECTIVE: To assess predictors of time to stabilization among under-five children admitted with severe acute malnutrition to stabilization centers in Ethiopia.

METHOD: A retrospective follow up study was conducted from January 20 to February 29, 2025 on 543 sampled children selected by a simple random sampling from severely malnourished children admitted to selected hospitals in Western Oromia between January 2020 and December 2024. After collecting data using kobotoolbox, it was exported to STATA version 17 for analysis. Kaplan Meier curve and log-rank test were used to estimate the stabilization rate and presence of statistically significant difference in survival and hazard rate between categories of explanatory variables. Proportional hazard assumption was checked using schoenfeld residual test and log-log survival curve. After performing model comparison, the Weibull model was selected and variables with p < 0.25 on bi-variable regression was selected for multivariable weibull regression. Estimating adjusted hazard ratio with their respective 95% confidence interval, P-value of less than 0.05 was used to declare statistically significant association with stabilizing time.

RESULT: Over 5600 child-days of observation, the median time to stabilize from severe acute malnutrition was 11 days, with 86.39% rate of stabilization and 86.6/1000 incidence of stabilization (95% CI: (74.45-89.44)). Immunization status (AHR: 0.66, 95% CI (0.54-0.8)), pneumonia (AHR: 2.17, 95% CI (1.74-2.70)), hospital acquired infections (AHR: 1.34 95% CI (1.09-1.65)) and vitamin A supplementation (AHR: 0.61, 95%CI (0.49-0.77)) were predictors of stabilization time.

CONCLUSION: This study found prolonged time to stabilization of 11 days compared to the recommendation of Ethiopian national management protocol of severe acute malnutrition. To achieve quicker stabilization, health professionals, hospital managers, and all stakeholders must collaboratively address and reduce the burdens stemming from identified predictors.

PMID:41275240 | DOI:10.1186/s12889-025-25718-1

Int J Health Geogr. 2025 Nov 22;24(1):36. doi: 10.1186/s12942-025-00422-w.

ABSTRACT

BACKGROUND: Geospatial studies that consider the relationships between the built environment and health typically rely on researcher-led ‘objective’ measurement of geospatial attributes of the built environment. Some studies can fail to find expected associations between environments and health outcomes where the geospatial measures do not reflect the experiences or perceptions of people themselves. We took a participatory approach to work with older adults with a concern for falling to assess the built environment in order that we could understand how their assessments relate to researcher assessments. We also wanted to assess whether specific demographic characteristics explained differences in assessments of the built environment between participants. Age-friendly environments can contribute to healthy active ageing. Falling and a fear of falling can lead to restricted outdoor activity. Therefore, understanding how the built environment contributes to fear of falling is important for age-friendly environments.

METHODS: The study is a cross-sectional retrospective observational study of the built environment. We worked with older adults in workshop settings to undertake community audits of the built environment in Google Street View. They assessed locations where a fall had occurred. Researchers separately audited the same locations. We used descriptive statistics and ordinal regression cumulative link mixed models to estimate the odds that community members would rank a location one level higher than the researchers.

RESULTS: There are significant differences in researcher and community auditor assessments of locations of attractiveness. Site related and individual attributes explain variation in how difficult locations were rated for walking, and for concern about falling. Only individual attributes explained variation in site attractiveness. Locations with more trip hazards and steeper slopes were rated as being more difficult to walk and were associated with greater concern for falling.

CONCLUSIONS: Attributes of the built environment influence perceptions of difficulty walking and concern or falling at specific locations. Furthermore, there are some differences in how researchers and community auditors assess the same locations, meaning that geospatial studies which rely only on researcher assessments may be prone to bias. Involving older people in geospatial studies that measure age-friendly environments can make measurement more reflective of their experiences.

PMID:41275235 | DOI:10.1186/s12942-025-00422-w