Tag: pubmed

Environ Monit Assess. 2026 Jul 24;198(8):871. doi: 10.1007/s10661-026-15715-1.

ABSTRACT

The presence of polyfluoroalkyl substances (PFASs) in US drinking water has generated concerns about their toxicity and ability to be monitored. In 2024, the US Environmental Protection Agency (USEPA) set Maximum Contaminant Levels (MCLs) for six PFAS compounds and introduced a Hazard Index (HI) for four others under the Safe Drinking Water Act. In May 2026, the USEPA proposed revisions to several of these parameters. However, these revisions had not been approved at the time of publication of this manuscript. The main objective of this study was to examine PFAS occurrence in US. public water systems (PWSs), focusing on identifying monitoring limitations and challenges in meeting MCL regulations. This study analyzed 1.98 million records from 10,777 PWSs through February 2026 and examined how PFAS monitoring unfolds across public water systems nationwide. The focus was on exceedances, the quality of the data, frequency, locations, types of water sources, and the environmental risk impact assessments of the size of the population served. Results show that 8838 exceedances were recorded based on the 2026 proposed MCL, impacting between 37.2 to 81.3 million users and 11.54 to 25.22 million cubic meters/day of water supply. The proposed 2026 MCL revisions result in only marginal reductions in the number of affected PWS (1.4 to 1.7%) and population served (0.5 to 0.7%) relative to the 2024 standards. About 38% of samples for several PFAS compounds collected between 2013 and 2016 had Minimum Reporting Levels (MRL) above current MCLs, limiting their regulatory value. The analysis, based on the environmental quality standards, created accurate HI assessments for PWSs. That said, many exceedances remain undetected due to low sample quality and frequency. Larger PWSs exhibit higher exceedance rates relative to current MCL thresholds, likely due to greater urban contamination and the increased complexity of their water supply systems. Groundwater influenced by surface water shows higher exceedance rates for PFOA and PFOS MCLs.

PMID:42493659 | DOI:10.1007/s10661-026-15715-1

Cerebellum. 2026 Jul 24;25(4):116. doi: 10.1007/s12311-026-02062-7.

ABSTRACT

Ankylosing spondylitis (AS) is a chronic immune-mediated inflammatory disease primarily affecting the axial skeleton and is frequently associated with postural instability, impaired balance, and altered motor control. The cerebellum plays a central role in sensorimotor integration; however, cerebellar volumetric alterations in AS remain insufficiently elucidated. This study aimed to investigate cerebellar and cerebellar lobular volumetric changes in individuals with AS using a fully automated magnetic resonance imaging (MRI) segmentation method. This retrospective study included 15 patients with AS and 15 age- and sex-matched healthy controls (HC). Brain MRI data were analyzed using the automated CERES pipeline of the volBrain platform. All cerebellar volumetric measures were normalized to intracranial volume (ICV). Group comparisons were performed using appropriate parametric and non-parametric tests, and multiple comparisons were controlled using the false discovery rate (FDR) method. Compared with the control group, nominal differences (p < 0.05) were observed in several cerebellar regions, including Lobule V, Lobule VI, and Lobule VIIIA. Similarly, nominal differences were identified in the gray matter volumes of Lobule I-II and Lobule VIIIA. However, none of these findings remained statistically significant after FDR correction (all q > 0.05). Cerebellar volumetric differences in AS appear to be subtle and do not remain significant after correction for multiple comparisons. These findings suggest that previously reported differences may reflect inter-individual variability rather than robust disease-specific structural alterations. Further studies with larger cohorts and multimodal approaches are warranted.

PMID:42493658 | DOI:10.1007/s12311-026-02062-7

Bull Math Biol. 2026 Jul 23;88(8):142. doi: 10.1007/s11538-026-01709-0.

ABSTRACT

The mitochondrial dicarboxylate carrier SLC25A10 mediates reversible exchange among succinate, malate, and phosphate, contributing to mitochondrial metabolic regulation. Structural studies establish a ping-pong mechanism, but most mathematical models still assume sequential binding, lacking mechanistic justification and overlooking the alternation of a single binding site. Here, we present the first mechanistically derived and thermodynamically consistent model of SLC25A10 based on a ping-pong framework. The model incorporates competitive binding of succinate, malate, and phosphate, heteroexchange, reversibility, and electroneutrality, and is calibrated using experimental datasets from intact mitochondria and reconstituted proteoliposomes. To estimate kinetic parameters and quantify their uncertainty, we employed Bayesian inference, enabling statistically rigorous calibration to uptake and competition assays. The model introduces new terms that quantify which substrate and from which side of the membrane is most likely to start the transport cycle. Beyond reproducing experimentally observed exchange kinetics, the model resolves non-equilibrium transport dynamics that are difficult to access directly in classical uptake assays. In particular, the simulations reveal a two-phase response in which an initial phosphate-driven high-flux uptake regime for malate and succinate is followed by a slower redistribution phase in which the two dicarboxylates continue to readjust primarily against each other. The model also predicts that mitochondrial morphology modulates early transport behaviour, with matrix swelling increasing and matrix condensation decreasing the initial SLC25A10 flux magnitude. More broadly, the framework provides a quantitative basis for studying how substrate competition, thermodynamic driving forces, and compartment geometry shape SLC25A10-mediated exchange, and it offers a transferable modelling strategy for other carriers in the SLC25 family.

PMID:42493647 | DOI:10.1007/s11538-026-01709-0

J Math Biol. 2026 Jul 24;93(2):21. doi: 10.1007/s00285-026-02422-1.

ABSTRACT

Oropouche virus (OROV) is a vector-borne arbovirus that has caused more than 500,000 infections across South America, Central America, and the Caribbean. Its primary vector, the midge species Culicoides paraensis, acquires the virus from wild reservoir hosts and transmits it to humans during blood feeding. As outbreaks within the Amazon basin continue to occur and confirmed cases steadily increase, a proper understanding of the interplay between climatic variables, vector behavior, and OROV transmission is needed to develop effective public health interventions. In this paper, we develop a novel mathematical model of Oropouche virus spread in Amazonas, Brazil using ordinary differential equations (ODEs). First, we derive the basic reproductive number at baseline to assess the potential for disease persistence. We then incorporate seasonal forcing and fit the model to weekly incidence data from the 2023-2024 outbreak using least squares optimization. With our model structure, we evaluated multiple candidate seasonality functions and implementations, including precipitation-based forcing functions and others intended to model general seasonality or the right-skewed incidence curve. Among these, quantitative results show that the seasonal variation in OROV transmission is best explained (in the sense of minimum $l^2$ error) by an exponentially decaying pulse applied to midge recruitment, which captures the incidence data with a relative $l^2$ error of 11.94%. While moderate levels of observational noise can affect the relative ranking of seasonal mechanisms, the exponential pulse remained the best-performing forcing function to describe the observed incidence data.

PMID:42493628 | DOI:10.1007/s00285-026-02422-1

Br J Cancer. 2026 Jul 23. doi: 10.1038/s41416-026-03560-5. Online ahead of print.

ABSTRACT

BACKGROUND: Limited knowledge exists on the association between hospital contacts before a childhood cancer diagnosis and the risk of early mortality.

METHODS: We conducted a register-based cohort study including 14,089 children with cancer diagnosed in 1989 – 2014 in Denmark and Sweden. Odds ratios (ORs) and 95% confidence intervals (CIs) of early mortality (deaths within 0-90 days) were estimated by nights in hospital up to two years prior cancer diagnosis and diagnoses within specific main diagnostic categories using logistic regression.

RESULTS: Children hospitalized ≥14 nights within 2 years-14 days and 3 months-14 days before cancer diagnosis faced elevated ORs of early mortality (4.6, 95% CI 3.2-6.4; 4.4, 2.9-6.7). The association was not explained by maternal education. Early mortality was associated with diagnoses within several diagnostic categories prior to cancer diagnosis, including infectious (OR 1.5, 95% CI 1.1-2.0) and endocrine diseases (OR 1.6, 95% CI 1.02-2.5), blood (OR 3.3, 95% CI 2.1-5.1) and digestive disorders (OR 1.9, 95% CI 1.4-2.6), and symptoms with no specific diagnosis (OR 1.4, 95% CI 1.1-8).

CONCLUSION: Children with increased time in hospital before cancer diagnosis had a higher risk for early mortality, which indicates underlying health vulnerabilities or pre-existing fragility in this population.

PMID:42493601 | DOI:10.1038/s41416-026-03560-5

J Expo Sci Environ Epidemiol. 2026 Jul 23. doi: 10.1038/s41370-026-00950-y. Online ahead of print.

ABSTRACT

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are a diverse group of organofluorine compounds used in industrial and consumer applications. The primary route of human exposure to PFAS is ingestion of contaminated food and drinking water, representing a significant and sometimes unavoidable exposure for many populations. Ecotoxicological and epidemiological studies have established associations between PFAS exposures and adverse health effects. Fetal and childhood development is a particularly susceptible window of exposure.

OBJECTIVE: We characterized PFAS exposures for pregnant women in Suriname who identified as Indigenous or Tribal Peoples, and we examined regional variations in exposure patterns between urban, rural, and remote populations.

METHODS: We measured 24 PFAS analytes in the blood serum of 100 pregnant Tribal and Indigenous women living in Suriname. Samples were collected from December 2016 to July 2019 and were purposively selected for laboratory analysis. We assessed differences in serum concentrations visually and statistically by location and ethnicity.

RESULTS: Ten unique PFAS were detected in at least one sample. The median total PFAS across all participants was 1.05 ng/mL (IQR: 0.73-1.45 ng/mL). The most frequently detected PFAS were PFOS (DF = 100%, median concentration ( $\tilde{x}$ ) = 0.59 ng/mL), PFOA (DF = 86%, $\tilde{x}$ = 0.15 ng/mL), PFNA (DF = 84%, $\tilde{x}$ = 0.09 ng/mL), PFUnDA (DF = 72%, $\tilde{x}$ = 0.09 ng/mL), and PFHxS (DF = 71%, $\tilde{x}$ = 0.06 ng/mL). Median total PFAS concentrations were highest for participants in the remote interior district, although differences among the districts were not statistically significant (p = 0.37) and should be interpreted cautiously due to limited statistical power. Indigenous Peoples tended to have higher total PFAS in their blood serum ( $\tilde{x}$ = 1.25 ng/mL) compared to Tribal Peoples ( $\tilde{x}$ = 0.84 ng/mL, p < 0.01), although we did not assess potential confounding variables.

SIGNIFICANCE: Our analysis revealed mostly long-chain legacy PFAS with possibly different exposure risks for secluded interior communities compared to urban-coastal populations, indicating a need for contaminant source assessments.

IMPACT: Our study adds to the growing literature around PFAS exposures for people living in remote areas. Suriname aims to reduce environmental contamination from persistent organic pollutants through the Stockholm Treaty. Our study provides data needed for policymakers and communities to make informed decisions about their environmental health.

PMID:42493588 | DOI:10.1038/s41370-026-00950-y

Sleep Med. 2026 Jul 17;147:109147. doi: 10.1016/j.sleep.2026.109147. Online ahead of print.

NO ABSTRACT

PMID:42492132 | DOI:10.1016/j.sleep.2026.109147

Eur J Radiol. 2026 Jul 20;204:113092. doi: 10.1016/j.ejrad.2026.113092. Online ahead of print.

ABSTRACT

Early detection of pulmonary embolism (PE) is critical for clinical outcomes, yet existing deep-learning models often fail to generalize across institutions. The recently released Google CT Foundation model, pre-trained on a large, diverse CT corpus, produces compact volumetric embeddings that may transfer to downstream tasks without fine-tuning. We evaluate a classification pipeline that pairs these frozen embeddings with three lightweight heads – Multi-Layer Perceptron (MLP), Random Forest (RF), and a stacking ensemble – for central PE detection, training on the public RSNA CTPA dataset and externally validating on the Stanford INSPECT cohort. The pipeline first reproduces the published data-size scaling behavior of the foundation model on other medical pathologies. The highest point-estimate test AUC of 0.79 was obtained by the RF trained on a balanced training set of 408 CT studies and evaluated on the held-out RSNA test set of 144 studies; paired DeLong tests showed that this advantage over the MLP and stacking heads was not statistically significant. Direct comparison to specialized state-of-the-art PE pipelines is task-mismatched – those target any-PE rather than central PE – so the result anchors a non-fine-tuned baseline rather than a deficit. In a low-data regime, hard vascular segmentation did not improve performance. On the external INSPECT cohort, AUC dropped by 0.17 and specificity at the transferred operating point collapsed, so simple global threshold recalibration does not restore deployability-frozen generalist embeddings alone do not guarantee cross-institutional reliability.

PMID:42492117 | DOI:10.1016/j.ejrad.2026.113092

JMIR Ment Health. 2026 Jul 23;13:e92021. doi: 10.2196/92021.

ABSTRACT

BACKGROUND: Parents of very preterm infants admitted to the neonatal intensive care unit (NICU) experience high levels of psychological distress, yet access to timely, evidence-based mental health support is limited by staffing and resource constraints. Digital mental health interventions offer a scalable approach to addressing this gap; however, their effectiveness has not been well established in NICU caregiver populations, particularly during periods of acute stress.

OBJECTIVE: This study aims to evaluate the effectiveness of a self-guided digital acceptance and commitment therapy (ACT)-based intervention combined with NICU-specific education (NICU parent acceptance and commitment therapy [NPACT]). The study explored the intervention’s effects on stress among parents and primary caregivers of very preterm infants, compared to a digital education-only intervention, and active control.

METHODS: We conducted a 3-arm, single-center, randomized controlled cluster trial in a tertiary NICU. Parents and primary caregivers of very preterm infants (<32 wk’ gestational age,<1 wk old) were randomized by family cluster to (1) NPACT (ACT+ education), (2) a digital education-only intervention, or (3) active control. Digital interventions were delivered via a web-based platform over 2 weeks. The primary outcome was NICU-related stress on the Parent Stressor Scale: Neonatal Intensive Care Unit (PSS:NICU) at 2 weeks postrandomization. Secondary outcomes included caregiver anxiety, depression, perceived stress, and selected neonatal outcomes. Engagement and perceived helpfulness were assessed for digital interventions.

RESULTS: A total of 102 caregivers from 68 family clusters (79 infants; mean gestational age 28.1, SD 2.2 wk) were enrolled. There were no statistically significant between-group differences in the mean PSS:NICU scores at 2 weeks (NPACT 3.0, SD 0.9; education-only 2.5, SD 1; active control 2.6, SD 0.9; adjusted mean difference for NPACT vs active control 0.04, 95% CI -0.39 to 0.47). No between-group differences were observed for secondary psychological outcomes at any time point. However, caregivers in both digital intervention groups had higher odds of full breastfeeding at discharge compared with active control. Engagement with the digital interventions was high, with 97% (28/29) of NPACT participants and 76% (19/25) of education-only participants completing at least 5 of 7 modules, and both interventions were rated as very helpful.

CONCLUSIONS: In this trial, an unguided digital mental health intervention delivered during NICU admission did not reduce NICU-specific parental stress or other psychological outcomes relative to active control. However, the intervention was highly used by caregivers. These findings suggest that while a brief digital mental health intervention can be successfully implemented in a high-stress clinical setting with caregivers, its capacity to reduce acute psychological distress may be limited. Secondary findings indicate potential benefits of the digital intervention on breastfeeding, generating hypotheses for future research. Digital mental health interventions in neonatal settings may be most effective when integrated within hybrid models of care and/or delivered beyond the acute admission phase.

PMID:42492071 | DOI:10.2196/92021

JMIR Res Protoc. 2026 Jul 23;15:e88520. doi: 10.2196/88520.

ABSTRACT

BACKGROUND: Infections with respiratory viruses such as SARS-CoV-2 and influenza are significant international public health concerns. While patients with cancer remain the most vulnerable group, they show poor vaccine response in general. Immunological data in this population are limited and mainly focus on serological parameters. However, in these patients, cellular, and especially T-cell, responses often seem to be induced more reliably than humoral responses.

OBJECTIVE: To gain further insights into vaccine-induced immunity, the RESPONSE study will analyze the effect of early and late booster vaccination on humoral and cellular responses, with special focus on T cell-induced immune responses. In addition, we aim to investigate factors influencing humoral and cellular vaccine-induced immunity in patients with hematological and oncological malignancies, including state of disease, treatment, and demographic factors.

METHODS: Humoral immune responses will be assessed by measuring binding and neutralizing antibodies using standardized assays. Cellular immunity will be evaluated using functional assays such as flow cytometry and FluoroSpot, as well as in-depth analyses using additional exploratory assays as appropriate. Immune responses will be correlated with clinical parameters, including disease status, treatment, and demographic factors.

RESULTS: This study was initiated following ethics approval and is currently recruiting participants. Enrollment commenced on March 25, 2025, and is ongoing, whereas biosample collection and follow-up visits are nearing completion for most participants. Final data cleaning, dataset integration, and statistical analyses of adaptive immune responses are planned from the third quarter of 2026 onward.

CONCLUSIONS: This study intends to lay a foundation for a structured translational research platform on vaccination to aim for best protection from infection by different respiratory pathogens. Long-term objectives are reaching best possible protection from vaccine-preventable disease with a first focus on influenza infection. In addition, we plan to investigate vaccine-induced immune responses to the recently approved respiratory syncytial virus vaccine using this platform and possibly extend this to further vaccines in the future. Urgent questions, such as the influence of different targeted therapies on vaccine immune response, will be part of these projects.

TRIAL REGISTRATION: ClinicalTrials.gov NCT06612515; https://clinicaltrials.gov/study/NCT06612515.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/88520.

PMID:42492070 | DOI:10.2196/88520