Nevin Manimala

Eval Program Plann. 2025 Aug 25;113:102689. doi: 10.1016/j.evalprogplan.2025.102689. Online ahead of print.

ABSTRACT

This study presents a data-driven analysis of academic performance, demographic disparities, and predictive modeling among more than 23,000 first-time freshmen at a US public University. We examine multiple factors influencing student outcomes, including GPA, credit accumulation, unit workload, Pell Grant eligibility, minority status, and parent education levels. Our analysis reveals several statistically significant disparities: non-minority students earn more units than minority students in their first two years, and Pell-eligible students accumulate fewer credits than their non-eligible peers. First-generation college students also exhibit lower credit accumulation compared to peers. GPA distributions show that minority students have a lower average GPA compared to non-minority students, with broader variation. Clustering analysis identifies three distinct academic engagement profiles based on GPA and unit load, highlighting heterogeneous performance patterns and the need for differentiated support. We develop and tune predictive models to forecast sophomore credit accumulation and GPA, achieving strong performance using deep learning. These models enable proactive risk identification and support strategic interventions. Our findings set the stage for actionable insights for institutional decision-makers aiming to enhance student retention, success, and academic momentum.

PMID:40897068 | DOI:10.1016/j.evalprogplan.2025.102689

Int J Med Inform. 2025 Aug 31;205:106103. doi: 10.1016/j.ijmedinf.2025.106103. Online ahead of print.

ABSTRACT

BACKGROUND: The development and use of artificial intelligence and machine learning technologies in healthcare have increased, prompting a need for evidence on their safety and value. Economic evaluations support healthcare decision-making and resource allocation. This scoping review aimed to map and synthesize current approaches to evaluating the economic aspects of machine learning based technologies implemented in healthcare.

METHODS: Following the updated JBI guidance for scoping reviews, six databases (PubMed, CINAHL, Cochrane Library, Embase, Scopus, and IEEE Xplore) were searched for studies evaluating the economic aspects of machine learning-based technologies within healthcare. No exclusions were applied to healthcare settings, healthcare professionals or used economic evaluation methods. The results of data extraction were analyzed using descriptive statistics and inductive coding. The reporting of the studies was compared against the CHEERS-AI statement.

RESULTS: A total of 6332 references were retrieved, with 18 studies included in the review. The studies comprised economic evaluations (n = 9), impact evaluations (n = 5), and performance evaluations (n = 4), with cost-effectiveness analysis being the most frequently used economic evaluation method (n = 8). The comparison of the studies to the reporting guidelines revealed gaps in the reporting of details from economic evaluations and the artificial intelligence nature of the technologies. Overall, the study alignment with the CHEERS-AI items on average was 39.6 %, with 64.1 % alignment with economic evaluation details, and 21.3 % alignment with key details related to the artificial intelligence nature of the evaluated technologies.

CONCLUSIONS: The current literature evaluating the economic aspects of machine learning-based technologies implemented in healthcare reveals gaps in coherence and coverage. Frameworks guiding artificial intelligence development should be refined to incorporate components related to system evaluation and post-implementation considerations. Further, multidisciplinary collaboration should be enhanced and promoted.

PMID:40897062 | DOI:10.1016/j.ijmedinf.2025.106103

Ecotoxicol Environ Saf. 2025 Sep 1;303:118962. doi: 10.1016/j.ecoenv.2025.118962. Online ahead of print.

ABSTRACT

BACKGROUND: Hormonal disruption evidence of metal exposure is lacking and contradictory.

OBJECTIVES: To elucidate the association of multiple metals exposure with a comprehensive panel of sex hormones in women across the lifespan.

METHODS: 5492 women aged 3-80 from a national survey were included. Multivariable linear regression, restricted cubic splines, and receiver operating characteristic curves were employed to assess individual metal exposure with sex hormones. Quantile-based g computation was used to explore mixture exposure association. Vitamin D and folate were examined as the modifiers. Integrative bioinformatics analysis was conducted leveraging a network of databases to reveal underlying mechanisms.

RESULTS: Exposure to cadmium, lead (Pb), mercury (Hg), selenium, and manganese was associated with sex hormones. For example, in young adult (20-49 years), Pb was associated with androstenedione [3.89 %, 95 % CI: 0.81, 7.06], estrone sulfate [8.14 %, 95 % CI: 1.54, 15.18], and luteinizing hormone [12.29 %, 95 % CI: 5.01, 20.07]; Hg was associated with estrone sulfate [4.84 %, 95 % CI: 0.62, 9.22]. Metals mixture was mainly associated with young adults’ increased sex hormones with effect ranging from 5.37 % (95 % CI: 1.77, 9.10) to 17.83 % (95 % CI: 9.04, 27.34). Folate modified such associations with hazardous effect appeared in high folate level in young adults, while in low folate level in other age groups. Inflammatory signaling pathways such as TNF and IL-17 may mediate metal-induced sex hormones disturbance.

CONCLUSIONS: Our findings highlight the significant associations, folate modifications, and potential pathways of metal exposure on female sex hormones, which provides insights for prevention avenues and mechanisms.

PMID:40897053 | DOI:10.1016/j.ecoenv.2025.118962

Ultrasonics. 2025 Aug 26;157:107803. doi: 10.1016/j.ultras.2025.107803. Online ahead of print.

ABSTRACT

This study aims to evaluate the clinical utility of quantitative ultrasound (QUS) envelope statistics imaging in predicting the risk of vertebral fractures (VFs) in postmenopausal women, compared to conventional dual-energy X-ray absorptiometry (DXA) measurements, including bone mineral density (BMD) and T-score. A total of 63 postmenopausal women were enrolled. QUS envelope statistics imaging was performed on the L3 vertebra, analyzing parameters including the Nakagami parameter (m), scatterer clustering parameter (α), coherent to diffuse signal ratio (k), and entropy (H) for comparisons with DXA. The data were divided into three tertiles: reference, early VF risk, and high-risk groups. Odds ratios (ORs) were calculated to evaluate the predictive abilities of each parameter for VF risk. Intraclass correlation coefficients (ICCs) and Bland-Altman plots were utilized to evaluate consistency both within subjects and across different operators. There were no significant differences in QUS parameters between subjects with and without VFs overall (p > 0.05). However, compared to DXA, the Nakagami parameter and entropy demonstrated a significant association with early VF risk, as subjects in the second tertile exhibited higher risks of VFs compared to those in the first tertile (ORs: 3.02 for m and 3.30 for H). Bland-Altman analysis indicated mean differences close to zero and ICCs exceeding 0.90 for all QUS parameters. QUS envelope statistics imaging could complement DXA in predicting VFs, particularly in detecting early fracture risk, offering a non-invasive, radiation-free alternative for osteoporosis screening.

PMID:40897038 | DOI:10.1016/j.ultras.2025.107803

J Biomech. 2025 Aug 16;191:112909. doi: 10.1016/j.jbiomech.2025.112909. Online ahead of print.

ABSTRACT

This study assessed the biomechanical effect of a counterforce brace on the common extensor origin (CEO) tendon at the elbow via the measurement of shear wave velocity (SWV) using ultrasound. The counterforce brace was hypothesised to reduce SWV, which is a proxy measure of tendon stiffness, whilst the wrist and finger extensors were contracting at different levels of maximum voluntary contraction (MVC). In this cross-sectional study, nineteen healthy participants (age±SD: 30±9) were included in the study. The counterforce brace was applied with either 0 or 80 mmHg pressure to the forearm. The SWV was measured under four different wrist extensors MVC levels: 0%, 20%, 30%, and 40%. The counterforce brace had no significant effect on CEO tendon SWV at rest (V-statistic = 86, p = 0.74), 20% (V-statistic = 105, p = 0.71), 30% (V-statistic = 87, p = 0.77), or 40% (V-statistic = 94, p = 0.98) of MVC. The Friedman test for repeated measures showed an increase in SWV with greater levels of wrist extension MVC (x² = 7.9, p = 0.048). In conclusion, the counterforce brace does not appear to have a biomechanical effect on the CEO of the elbow during resting conditions or whilst the wrist extensors are contracting. The SWV of the CEO, a proxy for tendon stiffness, increases with greater levels of MVC.

PMID:40897020 | DOI:10.1016/j.jbiomech.2025.112909

Environ Int. 2025 Aug 21;203:109739. doi: 10.1016/j.envint.2025.109739. Online ahead of print.

ABSTRACT

BACKGROUND: Early life exposure to environmental factors can impact skeletal development. We aimed to identify periods of susceptibility to air pollution in early life in relation to bone health outcomes at age six.

METHODS: Data were from the Generation R study, a population-based pregnancy cohort study, The Netherlands. We estimated daily concentrations of nitrogen dioxide (NO2) and particulate matter (PM10, PM2.5 and PM2.5 absorbance) at the home addresses during pregnancy and childhood, using land-use regression models. Bone mineral density and area-adjusted bone mineral content were measured by dual-energy x-ray absorptiometry at age six. We performed distributed lag modelling (DLM) adjusted for several socioeconomic characteristics to assess the associations between bone health and air pollution, using 28-day averaged exposure levels, and identify windows of susceptibility.

RESULTS: Among 5966 children, we identified windows of susceptibility from ∼ 1 to ∼ 4 years of age for PM2.5 and PM2.5 absorbance with bone mineral density (e.g., -10.3; 95 % CI -15.8 to -4.7 per 5 µg/m³ increase in PM2.5) and for all air pollutants with bone mineral content (e.g., -14.6; 95 % CI -20.7 to -8.4 per 5 µg/m³ increase in PM2.5). Also, we identified an association between NO2 and PM2.5 absorbance during pregnancy and higher bone mineral content (e.g., 4.0; 95 % CI 1.4 to 6.6 per 10^-5 m^-1 increase in PM2.5 absorbance). In the sex-stratified analyses, associations across all exposures and outcome measures were in the same direction for both sexes, and similar to the main analyses, but statistically significance was observed only in boys.

CONCLUSIONS: Our findings suggest that exposure to air pollutants during childhood may already lead to poorer bone health outcomes.

PMID:40897019 | DOI:10.1016/j.envint.2025.109739

Talanta. 2025 Aug 30;297(Pt B):128784. doi: 10.1016/j.talanta.2025.128784. Online ahead of print.

ABSTRACT

Tetracycline (TC) is a common antibiotic with broad antibacterial activity, yet its excessive abuse will leave antibiotic residues in animal-derived food, posing some threats to human health. Therefore, developing a simple and effective technology for TC trace analysis is immediately important for food safety. Herein, the sensitive PEC aptasensor within Z-scheme heterojunction, based on Bi/Bi₂MoO₆ and P-doped ultrathin porous g-C₃N₄ (PCN), was constructed by elemental doping strategy, hydrothermal method and surface plasmon resonance (SPR) effect. Benefiting from the Z-scheme electron transmission way, the Bi/Bi₂MoO₆@PCN heterojunction significantly improves both visible-light absorption and the mobility of photogenerated carriers. Thus, the fabricated PEC aptasensor based on Bi/Bi₂MoO₆@PCN heterojunction exhibited outstanding selectivity and stability for TC detection, which displayed a wider linear range of 0.05-350 nM and a lower detection limit of 0.036 nM. In addition, the proposed aptasensor showed the acceptable recoveries (98.41-104.76 %) for TC residue analysis in animal-derived food, including milk, honey and pork. Therefore, it demonstrates that the PEC sensing technology possesses the excellent feasibility and application potential in food analysis.

PMID:40897008 | DOI:10.1016/j.talanta.2025.128784

Arch Gerontol Geriatr. 2025 Aug 26;139:106003. doi: 10.1016/j.archger.2025.106003. Online ahead of print.

ABSTRACT

With growing recognition of psychosocial risks for cognitive impairment, research on social isolation (SI) and loneliness (LON) and their relationship to memory has increased over the past decade. However, most studies have examined SI and LON separately, leaving their combined influence on memory underexplored, particularly in qualitative research. This study presents the qualitative arm of a larger mixed-methods investigation, exploring how SI and LON, separately and together, shape memory in middle-aged and older adults. Ten individuals aged 47 – 81 were recruited through purposive and snowball sampling for semi-structured interviews, analyzed using thematic analysis informed by descriptive phenomenology. Participants generally viewed LON as more damaging to memory than SI, noting that mental stimulation is still possible during isolation, whereas LON often drains the motivation to engage in such activities. Some described SI positively (form of self-care), though extended SI was seen as detrimental due to increased social anxiety (further limits social engagement), disrupted routines, and diminished sense of purpose, all critical for memory. The combination of SI and LON was perceived as most harmful, creating a feedback loop that exacerbates both conditions and increases vulnerability to self-destructive behaviours (smoking, physical inactivity, poor diet). This research identifies distinctive indicators and psychosocial needs of those experiencing SI, LON, or both, supporting more precise screening and intervention triage in clinical and community settings. It underscores the value of targeted, multimodal brain health interventions addressing diverse contributing factors through strategies like social connection, purpose-driven living, cognitively stimulating activities, chronic disease management, and healthy lifestyle habits.

PMID:40896982 | DOI:10.1016/j.archger.2025.106003

Int J Occup Med Environ Health. 2025 Aug 29:208604. doi: 10.13075/ijomeh.1896.02626. Online ahead of print.

ABSTRACT

OBJECTIVES: Environmental intolerance (EI) can negatively impact well-being and daily life, and even lead to disability. Healthcare can detect EI early and conduct interventions. This study explored ways of identifying environmental exposure-related health worries and EI during occupational health (OH) check-ups, and their associations with unselected working-age employees’ perceived work ability, stress and overall health.

MATERIAL AND METHODS: A crosssectional survey was conducted among 355 employees attending OH check-ups at an occupational health services (OHS) unit in Southern Ostrobothnia, Finland. Health worries about environmental exposures were measured using 2 single-item questions, one on exposures in general, the other on indoor air. Cutoffs were set for excessive worries. Environmental intolerance was defined using the Quick Environmental Exposure and Sensitivity Inventory (QEESI). Perceived stress, work ability and health were inquired. The analyses used descriptive statistics, Fisher’s exact test and linear regression.

RESULTS: Participants with EI (N = 25, 7%) reported significantly poorer work ability and health, and higher stress than those without EI. Environmental intolerance was also associated with comorbid diseases such as asthma, migraine, mental disorders and irritable bowel syndrome. Those with excessive health worries about environmental exposure (N = 73, 21%) and indoor air (N = 182, 51%) outnumbered and mostly included those with EI. All the participants’ (N = 355) increased health worry about environmental exposures was independently associated with poorer work ability and health, and higher perceived stress. The health worry questions for identifying EI were sensitively phrased, and the general question demonstrated good specificity.

CONCLUSIONS: The findings show that environmental exposure-related health worries can be detected by and EI identified by single questions. Their interrelation and association with poorer work ability and health suggest they are part of the same continuum of increasing environmental worries and exposure- related reactions. Identifying health worries enables early detection and interventions such as psychoeducation, to prevent any related disability and adverse health outcomes. Int J Occup Med Environ Health. 2025;38(4).

PMID:40891448 | DOI:10.13075/ijomeh.1896.02626

Magn Reson Med. 2025 Sep 2. doi: 10.1002/mrm.70054. Online ahead of print.

ABSTRACT

PURPOSE: $\chi$ -separation is an advanced quantitative susceptibility mapping (QSM) method that is designed to generate paramagnetic ( ${\chi }_{\text{para}}$ ) and diamagnetic ( $\left|{\chi }_{\mathrm{dia}}\right|$ ) susceptibility maps, reflecting the distribution of iron and myelin in the brain. However, vessels have shown artifacts, interfering with the accurate quantification of iron and myelin in applications. To address this challenge, a new vessel segmentation method for $\chi$ -separation is developed.

METHODS: The method comprises three steps: (1) seed generation from $R_2^{*}$ and the product of ${\chi }_{\text{para}}$ and $\left|{\chi }_{\mathrm{dia}}\right|$ maps; (2) region growing, guided by vessel geometry, creating a vessel mask; (3) refinement of the vessel mask by excluding non-vessel structures. The performance of the method was compared to other vessel segmentation methods both qualitatively and quantitatively. To demonstrate the utility of the method, it was tested in two applications: quantitative evaluation of a neural network-based $\chi$ -separation reconstruction method ( $\chi$ -sepnet- $R_2^{*}$ ) and population-averaged region of interest (ROI) analysis.

RESULTS: The proposed method demonstrates superior performance to other vessel segmentation methods, effectively excluding the non-vessel structures, achieving the highest Dice score coefficient against manually segmented vessel masks (3 T: 76.7% for ${\chi }_{\text{para}}$ and 68.7% for $\left|{\chi }_{\mathrm{dia}}\right|$ , 7 T: 76.9% for ${\chi }_{\text{para}}$ and 72.6% for $\left|{\chi }_{\mathrm{dia}}\right|$ ). For the applications, applying vessel masks report notable improvements for the quantitative evaluation of $\chi$ -sepnet- $R_2^{*}$ and statistically significant differences in population-averaged ROI analysis. These applications suggest excluding vessels when analyzing the $\chi$ -separation maps provide more accurate evaluations.

CONCLUSION: The proposed method has the potential to facilitate various applications, offering reliable analysis through the generation of a high-quality vessel mask.

PMID:40891385 | DOI:10.1002/mrm.70054