Nevin Manimala

J Epidemiol Glob Health. 2025 Nov 26. doi: 10.1007/s44197-025-00486-8. Online ahead of print.

ABSTRACT

BACKGROUND: Neonatal sepsis remains a major cause of preventable neonatal mortality globally, yet diagnosis remains difficult in low-resource settings due to the inaccessibility and the long turnaround time of blood culture. Clinical prediction models can support the early detection and management of sepsis.

OBJECTIVE: To develop and internally validate a diagnostic prediction model for the diagnosis of neonatal sepsis in a low-resource setting, Ethiopia.

METHODS: An institution-based cross-sectional study was conducted from January 2022 to December 2024. We collected data through medical record review among 607 newborns with suspected sepsis. Predictors were selected using the least absolute shrinkage and selection operator (LASSO) and then subjected to multivariable logistic regression. Model performance was assessed by discrimination and calibration. Ten-fold cross-validation was performed to assess the model’s internal validity, and clinical utility was assessed by decision curve analysis. External validation was not performed. The R statistical software was used for data analysis.

RESULTS: The proportion of sepsis was 36.1% (95% CI: 32.3, 39.9). The final model incorporated maternal anemia, fever, antibiotic use during pregnancy, temperature abnormality, presence of a focus of infection, invasive procedure before admission, leukocytosis, leukopenia, and thrombocytopenia. The model demonstrated an area under the receiver operating characteristic curve (AUROC) of 0.87(95% CI: 0.84, 0.90) and good calibration. The model achieved a sensitivity of 86.8%, specificity of 71.1%, negative predictive value of 90.5%, and a positive likelihood ratio of 3.0. The decision curve analysis showed a higher net benefit than the “treat-all” or “treat-none” strategies.

CONCLUSIONS: We developed a diagnostic prediction model for neonatal sepsis, demonstrating good discrimination, high sensitivity, and negative predictive value, with a modest positive likelihood ratio, reflecting its utility for ruling in or out sepsis. The model can be incorporated into routine neonatal care practices and quality improvement initiatives following external validation.

PMID:41299099 | DOI:10.1007/s44197-025-00486-8

Nat Aging. 2025 Nov 26. doi: 10.1038/s43587-025-01016-8. Online ahead of print.

ABSTRACT

Aging and age-related diseases share convergent pathways at the proteome level. Here, using plasma proteomics and machine learning, we developed organismal and ten organ-specific aging clocks in the UK Biobank (n = 43,616) and validated their high accuracy in cohorts from China (n = 3,977) and the USA (n = 800; cross-cohort r = 0.98 and 0.93). Accelerated organ aging predicted disease onset, progression and mortality beyond clinical and genetic risk factors, with brain aging being most strongly linked to mortality. Organ aging reflected both genetic and environmental determinants: brain aging was associated with lifestyle, the GABBR1 and ECM1 genes, and brain structure. Distinct organ-specific pathogenic pathways were identified, with the brain and artery clocks linking synaptic loss, vascular dysfunction and glial activation to cognitive decline and dementia. The brain aging clock further stratified Alzheimer’s disease risk across APOE haplotypes, and a super-youthful brain appears to confer resilience to APOE4. Together, proteomic organ aging clocks provide a biologically interpretable framework for tracking aging and disease risk across diverse populations.

PMID:41299092 | DOI:10.1038/s43587-025-01016-8

Cell Death Differ. 2025 Nov 26. doi: 10.1038/s41418-025-01623-3. Online ahead of print.

ABSTRACT

Ferroptosis-an iron-dependent form of cell death triggered by phospholipid peroxidation-has emerged as a promising therapeutic avenue in cancer treatment. Although neuroblastoma (NB) has been identified as a ferroptosis susceptible cancer, our studies reveal striking heterogeneity in ferroptosis sensitivity across high-risk NB models. Through a targeted metabolic compound screen, we identified stearoyl-CoA desaturase 1 (SCD1)-a key enzyme in monounsaturated fatty acid (MUFA) synthesis-as a robust ferroptosis-sensitizing target. Genetic and pharmacological inhibition of SCD1 restored ferroptosis sensitivity in resistant NB cells. Notably, high SCD1 expression correlates with poor patient prognosis. Co-treatment with arachidonic acid (AA), a polyunsaturated fatty acid (PUFA), further enhanced ferroptotic cell death via increased PUFA/MUFA ratio. Nevertheless, neither baseline lipidomic profiles nor transcriptomes of key ferroptosis regulators reliably predicted ferroptosis sensitivity. To overcome AA’s poor solubility, we engineered AA-loaded lipid nanoparticles (AA-LNPs), which selectively accumulated in high-risk NB tumors and synergized with SCD1 inhibition. This dual-sensitization strategy, termed LipidSens, significantly suppressed tumor growth and induced ferroptosis in cell-derived xenograft mouse models without systemic toxicity. Together, these findings establish MUFA synthesis blockade and PUFA enrichment as a tumor-targeted, ferroptosis-enhancing strategy, and offer a nanomedicine-based therapeutic platform for high-risk NB.

PMID:41299087 | DOI:10.1038/s41418-025-01623-3

Eur Radiol. 2025 Nov 27. doi: 10.1007/s00330-025-12206-8. Online ahead of print.

NO ABSTRACT

PMID:41299042 | DOI:10.1007/s00330-025-12206-8

Eur Radiol. 2025 Nov 27. doi: 10.1007/s00330-025-12182-z. Online ahead of print.

NO ABSTRACT

PMID:41299041 | DOI:10.1007/s00330-025-12182-z

Environ Monit Assess. 2025 Nov 27;197(12):1377. doi: 10.1007/s10661-025-14827-4.

ABSTRACT

Concern over agricultural nutrient contamination is rising in arid Central Asia where a shortage of freshwater resources under climate change exacerbates water supply problems. This study assesses how nutrient loading in the Zarafshan River Basin is affected by the application of nitrogen, phosphorus, and potassium (NPK) fertilizers. We evaluated fertilizer use and river nutrient concentrations using QSWAT hydrological modeling, GIS-based spatial analysis, and long-term water quality data. The model was calibrated and validated for discharge using SWAT-CUP on a monthly time step. The model results were evaluated using the R² and NSE statistical coefficients, which were 0.78 and 0.76 during the calibration period, and 0.75 and 0.73 during the validation period, respectively, which proved the model’s accuracy. While P and K correlations were weak and not statistically significant, N fertilizer application demonstrated a statistically significant, moderate positive correlation with TN_min (mineral total nitrogen) in river water (ρ = 0.30, p < 0.05). For nutrient export, 37.1% of the basin was in high-risk zones. Modeled monthly averages for the upstream and downstream nitrogen (NO₃) loads were 598 kg and 60,318 kg/month per subbasin, respectively. These results highlight nitrogen, in contrast to phosphorus and potassium, as one of the dominant contributors to non-point source pollution, demanding targeted nutrient management in agricultural zones.

PMID:41299005 | DOI:10.1007/s10661-025-14827-4

Sports Med. 2025 Nov 27. doi: 10.1007/s40279-025-02359-3. Online ahead of print.

ABSTRACT

BACKGROUND: This study simulated the effect of reducing contact training duration on overall in-season head acceleration event (HAE) exposure within men’s and women’s rugby union.

METHODS: Players (n = 982) from two professional men’s and two semi-professional women’s competitions wore instrumented mouthguards in training and match-play for one season. Generalised linear mixed models were used to estimate the in-season weekly HAE exposures per position, sex and contact type. Simulation of modelled estimates evaluated the impact of reducing contact load guidelines by 25%, 50% and 75% (scenario 1), and replacing full contact training with controlled contact (scenario 2) or non-contact (scenario 3) training for different seasonal match exposures. Previously established contact load guidelines were used as a reference point.

RESULTS: HAEs were decreased by a maximum of 3.2 per week (0-95 HAEs per season; 0-23%). In scenario 1, the decrease in HAEs was disproportionately smaller than the reduction in contact training duration (e.g. 23.7% reduction in overall rugby minutes for 7% decrease in HAEs). Scenario 2 decreased HAEs similarly to scenario 1 but with no reduction in contact time. Scenario 3 decreased HAEs proportionally with contact time reductions (e.g. 8.9% decrease in HAEs >10 g for 9.6% reduction in overall rugby minutes).

CONCLUSIONS: HAEs were reduced in all scenarios, but the reduction was relatively small due to the low overall rate of HAEs in training. Policymakers should be aware of the tradeoffs involved in any change. Managing individuals with higher HAE exposures may be more appropriate than reducing contact training guidelines.

PMID:41298988 | DOI:10.1007/s40279-025-02359-3

Int J Clin Oncol. 2025 Nov 27. doi: 10.1007/s10147-025-02926-8. Online ahead of print.

ABSTRACT

BACKGROUND: Systematic pelvic and aortic lymphadenectomy in stage IIB-IVB patients with epithelial ovarian cancer, undergoing complete abdominal macroscopic resection with normal lymph nodes, was revealed to have no prognostic significance for survival in the LION trial. However, the proportion of patients with ovarian clear cell carcinoma (OCCC) in the LION trial was only 2.2%, so the significance of systematic retroperitoneal lymphadenectomy in patients with OCCC remains unclear.

METHODS: We conducted an ancillary analysis of 619 patients enrolled in a randomized phase III trial (JGOG 3017) in patients with OCCC. Of these, 89 were stage IIB to IVB, underwent a complete macroscopic resection, and had no grossly enlarged lymph nodes intraoperatively. Patients were divided into two groups: group A with lymphadenectomy and group B without lymphadenectomy. The Kaplan-Meier method was used to calculate progression-free survival (PFS) and overall survival (OS) and the log-rank test and Cox proportional hazard model were used to compare the two groups.

RESULTS: Among the 89 patients, 77 (86.5%) underwent a lymphadenectomy (group A), while 12 (13.5%) did not (group B). Three-year PFS were 62.3% in group A and 58.3% in group B (p = 0.7705). Three-year OS were 73.0% in group A and 65.6% in group B (p = 0.6346). No significant differences were observed between two groups.

CONCLUSION: This study did not demonstrate a definitive survival benefit from systematic lymphadenectomy in advanced OCCC patients with complete resection and clinically negative nodes. Given the small sample size, these results should be interpreted with caution and regarded as exploratory.

PMID:41298960 | DOI:10.1007/s10147-025-02926-8

Forensic Sci Int. 2025 Nov 21;379:112743. doi: 10.1016/j.forsciint.2025.112743. Online ahead of print.

ABSTRACT

Considerations on the drivers of bone diagenesis have received a lot of attention, yet there is still more to understand, particularly in relation to chemical changes that can occur post-mortem, and the rate at which these occur. The physicochemical composition of bone is altered during the post-depositional period, leading to a more thermodynamically stable crystal lattice, thus increasing the long-term survivability of the bone. Research has shown the potential for soft tissue trauma to affect the decomposition process, but the effect of bone trauma and fractures on diagenesis has not yet been considered. Most bone diagenesis research uses destructive analytical techniques, resulting in the loss of samples and the inability to perform repeat analyses. Presented here is a study investigating changes in the physicochemical composition of disarticulated Sus scrofa ribs, with and without fractures, using non-destructive analytical techniques. The aim was to explore the timescales in which physicochemical changes occur and to investigate the potential influence of bone fractures. Intact (control) or fractured (blunt-force or sharp-force) bone samples were deposited on a grassy surface for up to 240 days. Physicochemical changes to the bone sections were analysed using scanning electron microscopy – energy dispersive spectroscopy and Fourier transform infrared spectroscopy with attenuated total reflectance. It was hypothesised that physicochemical changes could be quantified in < 240 days using these techniques, and that the presence of fractures would affect the observed changes. Statistically significant (p < 0.05) losses in Na, K, and Mg and increases in crystallinity were seen over time, as well as significant changes in carbonate content and a significant loss of proteins. Differences physicochemical composition were observed between the undamaged and fractured samples, and the samples with BFT appeared to be the least affected for many elemental and IR parameters indicating BFT could potentially inhibit physicochemical change. The analysis of Na and K showed potential for PMI estimation, as these changed significantly over time, but as these were influenced by the presence of bone fractures, more research is needed fully understand how different variables can affect physicochemical change in bone, particularly the presence of bone fractures/damage.

PMID:41297088 | DOI:10.1016/j.forsciint.2025.112743

Comput Methods Programs Biomed. 2025 Nov 14;274:109167. doi: 10.1016/j.cmpb.2025.109167. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Cosinor analysis allows for the fitting of a cosine curve to describe cyclical variation in periodic data. The analysis provides an intuitive set of estimates that includes the MESOR (Midline Estimating Statistic of Rhythm), i.e., the mid-point of the fitted outcome, the amplitude, i.e., one-half the distance between the MESOR and the peak for normally distributed outcomes, and the acrophase, i.e. the time at which the outcome reaches its peak. Traditionally, most published cosinor analyses were generated though a two-stage approach in which a curve was fit to each individual’s data and differences in the estimated cosinor parameters were compared in downstream analyses. More recently multilevel cosinor modeling software has been developed which allows for the simultaneous modeling of data from multiple individuals. In addition to simplifying the model building process, the advantage of multilevel vs. two-stage cosinor analysis includes the option to fit more complex models and, likely, an improvement in fit for each individual’s data. However, to our knowledge, there are no SAS procedures or macros that assist users with this analytical approach.

METHODS: In this paper we introduce multilevel cosinor models and SAS macros we have developed to perform these analyses. In addition, we compare model fit between the multilevel and two-stage methods.

RESULTS: The SAS macros presented in this paper allow users to select the best random variable specification for the unconditional cosinor model and add a dichotomous grouping variable to detect differences in parameters across groups. At each step of model building, parameter estimates, measures of model fit and graphical output help the user understand the model derived and its appropriateness for their data. Results of cross-validation analyses are presented that illustrate the superior fit of the multilevel over the single-level approach for the dataset utilized in the examples.

CONCLUSIONS: Multilevel cosinor analysis extends the single subject cosinor model by allowing for more convenient model selection and may provide a better fit for each individual’s data. We are hopeful that this manuscript will introduce more researchers to this analytical technique and allow them to apply it in their own research.

PMID:41297072 | DOI:10.1016/j.cmpb.2025.109167