Nevin Manimala

Br J Math Stat Psychol. 2026 Feb 19. doi: 10.1111/bmsp.70037. Online ahead of print.

ABSTRACT

The detection of the number of modes in distributions of ordinal data is relevant for applied researchers across disciplines, from uncovering polarization to detecting incidence groups in clinical symptom scales. Yet, established modality detection methods are either purely descriptive or not developed for ordinal data. In the present paper, we attempt to fill this gap by proposing a recursive modality detection method (ReMoDe) which detects modes in univariate distributions through recursive significance testing. We provide a comprehensive review of existing modality detection methods and outline their potential pitfalls when applied to ordinal scales. Based on a benchmark of 172 simulated ordinal samples of different sample sizes, we demonstrate that ReMoDe outperforms other established modality detection methods. We furthermore present a stability test for our method as well as p-values and approximated Bayes factors for each detected mode. To make our method easily applicable for researchers, we introduce open-source R and Python packages.

PMID:41714803 | DOI:10.1111/bmsp.70037

Commun Med (Lond). 2026 Feb 19. doi: 10.1038/s43856-026-01419-7. Online ahead of print.

ABSTRACT

BACKGROUND: Frailty is an important factor in human aging associated with a broad range of adverse outcomes. Frailty metrics are time intensive to collect making them difficult for larger scale application.

METHODS: We apply machine learning to predict these frailty metrics, associated risk factors, and adverse outcomes from activity data. We use activity data collected using Actigraphy wearable accelerometer sensors, which are devices that measure acceleration along three axes of movement. Models were evaluated using Area Under the receiver operator Curve (AUC), Area Under Precision Recall Curve (AUPRC), Spearman rank test, Mann-Whitney U test, or Kruskal-Wallis test on repeated subsampling of train and test sets. All statistical tests are reported using -log₁₀(P-value).

RESULTS: Machine learning models show strong predictive performance even with small amounts of accelerometry data available. They are also able to better determine adverse outcomes such as hospitalization and mortality than frailty metrics themselves in our geriatric population.

CONCLUSIONS: This approach of wearable activity data-based prediction of frailty offers a surrogate (proxy or estimate) for determining frailty metrics in a scalable manner. It can also be used to determine adverse outcomes such as hospitalizations and mortality, allowing frailty to be used as a metric in other studies or medical practices.

PMID:41714788 | DOI:10.1038/s43856-026-01419-7

Sci Rep. 2026 Feb 19. doi: 10.1038/s41598-026-40725-x. Online ahead of print.

NO ABSTRACT

PMID:41714774 | DOI:10.1038/s41598-026-40725-x

Sci Rep. 2026 Feb 19. doi: 10.1038/s41598-026-39761-4. Online ahead of print.

NO ABSTRACT

PMID:41714752 | DOI:10.1038/s41598-026-39761-4

Nature. 2026 Feb 19. doi: 10.1038/s41586-026-10274-4. Online ahead of print.

ABSTRACT

Epstein-Barr virus (EBV) infects ≈90-95% of the global population^1,2 and persists in B cells as a life-long infection³. Prior EBV-infection is associated with autoimmune and neoplastic disease⁴. Still, the biological basis of host control during EBV persistence remains unclear. Here, we report the identification of non-genetic and genetic factors that are associated with EBV control during persistent infection. Using blood-based genome sequence (GS) data from 486,315 UK Biobank and 336,123 All of Us participants, we identified short read-pairs mapping to the EBV genome in 16.2% and 21.8% of individuals, respectively. EBV-read detection (EBVread+) reflects increased viral load in blood cells, as shown by orthogonal measurements, and was associated with HIV infection, immunosuppressive drug intake, and current smoking. Genome-wide analyses of EBVread+ identified strong associations at the Major Histocompatibility Complex (MHC), including 54 independent HLA-alleles of MHC class I and II, and at 27 genomic regions outside MHC. Epistasis with distinct HLA-alleles of MHC class I was observed at the ERAP2 locus. Analysis of individuals with EBV-associated diseases⁴ revealed a higher polygenic burden of EBVread+ for HLA-alleles at MHC class I in multiple sclerosis (driven by HLA-A*02:01), and at MHC class II in rheumatoid arthritis. Phenome-wide analyses identified a polygenic overlap of EBVread+ with inflammatory bowel disease, hypothyroidism, and type 1 diabetes. Our study establishes by-products of human GS as a surrogate marker of EBV viral load. This will facilitate investigation and treatment for EBV and other persistent viral infections.

PMID:41714741 | DOI:10.1038/s41586-026-10274-4

Skeletal Radiol. 2026 Feb 20. doi: 10.1007/s00256-026-05169-4. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate MRI abnormalities of the pulvinar and ligamentum teres (LT) in patients with atraumatic hip pain, as well as to describe a grading system for pulvinar signal abnormalities and test its reproducibility.

MATERIALS AND METHODS: This retrospective study included 128 patients with atraumatic hip pain and no reported structural abnormalities other than those of the pulvinar and LT on hip MRI, along with 64 asymptomatic controls. MR images were evaluated by two readers and included grading of pulvinar signal abnormalities (normal, grade 1: < 50% fat replacement, grade 2: > 50% fat replacement), LT signal abnormality, LT thickening, and LT tear. Ordinal variables were dichotomized for further analysis. Group differences were analyzed using logistic regression models. Inter-reader agreement was assessed using kappa statistics.

RESULTS: Pulvinar signal abnormalities were significantly associated with a higher odds ratio (OR) of hip pain (OR, 4.28; 95% CI, 1.81-11.49; p = 0.002). No significant group differences were found for LT signal increase, LT thickening, or LT tear (p-value range = 0.43-0.71). Inter-reader and intra-reader agreement for pulvinar signal abnormalities grading were almost perfect (κ = 0.85 [95% CI, 0.76-0.93] and κ = 0.92 [95% CI, 0.64-1.00]).

CONCLUSION: Patients with atraumatic hip pain undergoing MRI demonstrated a significantly higher prevalence of pulvinar signal abnormalities in the absence of other relevant structural pathology. These results underscore the importance of systematically evaluating the pulvinar during hip MRI interpretation. Furthermore, a grading system for pulvinar signal abnormalities was introduced.

PMID:41714735 | DOI:10.1007/s00256-026-05169-4

Sci Rep. 2026 Feb 19. doi: 10.1038/s41598-026-38045-1. Online ahead of print.

NO ABSTRACT

PMID:41714716 | DOI:10.1038/s41598-026-38045-1

Pediatr Res. 2026 Feb 19. doi: 10.1038/s41390-026-04825-8. Online ahead of print.

ABSTRACT

BACKGROUND: Early developmental intervention seeks to enhance functional outcomes in preterm infants by leveraging neuroplasticity. We investigated the relationship between early intervention and neurodevelopmental outcomes in early childhood among preterm infants without severe brain injury.

METHODS: This prospective cohort study enrolled very-low-birth-weight infants (23⁺⁰-32⁺⁶ weeks’ gestation) registered in the Korean Neonatal Network. Neurodevelopment was evaluated at corrected ages 18-24 months and chronological ages 33-45 months using the Bayley Scales of Infant and Toddler Development (Second or Third Edition), the Korean Developmental Screening Test, or both. Infants who began motor-based or language therapy prior to 18-24 months of corrected age were defined as the early intervention group.

RESULTS: Of the 1797 infants who completed follow-up, 518 (28.8%) received early intervention. Compared to infants without early intervention, those with early intervention had lower gestational age and higher rates of prematurity-related complications and post-discharge rehospitalizations. The interaction between the intervention group and assessment time was statistically significant, indicating that early intervention was associated with a reduced risk of motor developmental delays over time (adjusted odds ratio 0.669, 95% confidence interval 0.472-0.949).

CONCLUSION: Early intervention was associated with more favorable motor outcomes, highlighting the importance of timely support for high-risk preterm infants.

IMPACT: Preterm infants with greater medical complexity more commonly received early intervention. Early intervention mitigated the progression of motor developmental delays over time. An enriched early environment may help offset the negative developmental impact of preterm complications.

PMID:41714687 | DOI:10.1038/s41390-026-04825-8

Sci Rep. 2026 Feb 20. doi: 10.1038/s41598-026-39783-y. Online ahead of print.

ABSTRACT

Respiratory syncytial virus (RSV) is a single-stranded RNA virus responsible for a wide range of respiratory tract infections, including those affecting the lungs, airways, and middle ear. Understanding its transmission dynamics remains essential for effective disease control. A bio-inspired stochastic delay model for RSV transmission is proposed and analyzed. The model’s qualitative properties including positivity, boundedness, equilibrium states, and the basic reproduction number are rigorously established through well-posedness theorems. Parameter sensitivity is also examined. To investigate the system’s stochastic behavior, numerical schemes such as Stochastic Euler, Runge-Kutta, and Euler-Maruyama methods are applied. However, these traditional approaches fail to fully preserve the dynamic characteristics of the model. To address these limitations, a stochastic nonstandard finite difference (NSFD) scheme with delay is developed. This approach ensures non-negativity, boundedness, consistency, and unconditional convergence, overcoming issues of instability and divergence often observed in standard stochastic numerical methods. Comparative simulations demonstrate that the NSFD method reliably reproduces the true dynamic states of the model. The proposed stochastic delayed modeling framework enhances our understanding of RSV dynamics and provides a stable computational tool for analyzing complex biological systems. The findings open new avenues for exploring nonlinear stochastic processes in epidemiological and neurobiological modeling.

PMID:41714680 | DOI:10.1038/s41598-026-39783-y

Sci Data. 2026 Feb 19. doi: 10.1038/s41597-026-06852-w. Online ahead of print.

ABSTRACT

In sub-Saharan Africa (SSA), onchocerciasis control has been implemented for many decades, beginning in 1974 under the Onchocerciasis Control Programme in West Africa (OCP) and in 1995 in Central and East Africa (plus Liberia) under the African Programme for Onchocerciasis Control (APOC). Since the establishment of the Expanded Special Project for Elimination of Neglected Tropical Diseases (ESPEN) in 2016, data on mass drug administration (MDA) with ivermectin has been centrally compiled for all endemic countries at implementation unit (IU) level, beginning in 2013. This paper presents HISTONCHO, a dataset collating detailed information on interventions, including vector control, from 1975 through to 2022, using the ESPEN portal (2013-2022), regional and country reports, implementation partners’ records, and published literature. Reconstructing such intervention histories is crucial for an understanding of their evolution, modelling their impact, and tailoring future interventions. We discuss strengths and limitations associated with the ESPEN database, and how HISTONCHO can be improved to support modelling of intervention strategies as well as onchocerciasis control and elimination efforts by endemic country programmes.

PMID:41714664 | DOI:10.1038/s41597-026-06852-w