Citations

With rapid industrial expansion, air pollution’s adverse neurological effects have gained increasing attention. Children face a greater risk of neurological damage because of their higher breathing rates, developing brains, and limited ability to detoxify harmful substances. Fine particulate matter has been identified as a primary neurotoxic contributor affecting developing brains. Strong evidence connects environmental pollutant exposure to the prevalence of Autism Spectrum Disorder (ASD), a neurodevelopmental condition marked by lasting difficulties with social communication and interaction. This study explores the association between long-term PM2.5 exposure and ASD symptom exacerbation, investigating underlying mechanisms. We hypothesize that long-term PM2.5 exposure exacerbates ASD symptoms through neuroinflammatory activation, leading to neuronal damage and impaired synaptic plasticity. Our investigation employs three complementary approaches: First, integrated analysis combining Global Burden of Disease data with Mendelian randomization demonstrates a significant association between PM2.5 exposure and increased ASD severity risk. Second, utilizing the China High-Resolution Air Pollution Database in conjunction with cohort studies, we provide evidence that ambient air pollution substantially influences autism severity, with PM2.5 identified as the predominant environmental determinant. Third, through network toxicology, single-cell transcriptomics, and animal experimentation, we demonstrate that chronic PM2.5 exposure exacerbates valproic acid-induced autism-like behaviors in murine models, identifying CTNNB1, PTEN, CCR2, AKT1, and mTOR as potential core mediating genes. Importantly, these findings represent preliminary results. Several potential confounding factors such as co-exposure to other pollutants and socioeconomic variables have not been fully addressed. While our multi-modal approach provides converging lines of evidence, further validation in larger, more diverse populations with refined control of confounders will be essential to establish causality and elucidate mechanisms. Nonetheless, these early insights advance our understanding of PM2.5-induced neurotoxicity in the context of ASD and offer timely, albeit preliminary, evidence to inform public health policy.

Abstract This study examined in vitro glenohumeral instability under two simulated biomechanical models of rotator cuff tear: 1) tendon-defect model and 2) muscle-unloaded model. The results indicated that rotator cuff tear significantly increased the joint instability. Significant difference also existed between the two tested models. The tendon-defect model underestimated the joint instability in most simulated shoulder positions.

Abstract The stress environment of the extracellular matrix of the supraspinatus tendon, including the stress distribution and concentration, was evaluated by using a finite element model. Stress riser was found around the insertion at the articular side of the tendon. Compressive and shear stresses were observed at the articular side which corresponded to the region associated with fibrocartilaginous matrix. This area corresponded well with the critical zone of potential tear observed clinically.

Abstract A methodology was developed for potential determination of the material properties of inhomogeneous and anisotropic biomembranes. Mathematical estimations and computer simulations were performed to determine the effect of load and displacement errors on the property values. The results indicated that the material properties were particularly sensitive to displacement errors. The determination of non-dominant components requires more accurate experimental measurements.

Abstract Objectives To implementation an automated multi-institutional pipeline that delivers breast-cancer risk integrated with polygenic risk scores, monogenic variants, family history, and clinical factors, emphasizing operational challenges and their solutions. Materials and Methods A five-stage process was executed at ten sites. Data streams from REDCap surveys, PRS and monogenic reports, and MeTree pedigrees were normalized and forwarded through a REDCap plug-in to the CanRisk API. Results Integrated risk was returned to >10 000 women; 3.6% were ≥25 % lifetime risk and 0.9% carried pathogenic variants. Pipeline generated score aligns well with manual generated ones. Major barriers such as heterogeneous pedigree formats, missing data, edge-case handling, and evolving model versions were identified and resolved through mapping rules, imputations, and iterative testing. Discussion Cross-platform data harmonization and stakeholder alignment were decisive for success. Borderline-risk communication and model-version drift remain open issues. Conclusion Large-scale PRS-integrated breast-cancer risk reporting is feasible but requires robust interoperability standards and iterative governance.

ABSTRACTSurgical biopsy of brainstem tumors carries a risk of neurological injury. We performed magnetic resonance spectroscopy (MRS) of 2‐hydroxyglutarate (2HG) and glycine in patients with brainstem tumors to assess the feasibility of detecting and quantifying 2HG in the brainstem to obviate the need for a diagnostic biopsy and to establish the clinical significance of glycine MRS in brainstem tumors in vivo. Twenty adult patients with radiographically identified presumed brainstem gliomas were prospectively enrolled in the study. Proton MRS was obtained at 3T with a protocol tailored for detection of 2HG and glycine (TE 97‐ms PRESS). Spectra were fit using LCModel software and in‐house basis signals of metabolites and lipids. The metabolite concentrations were quantified with reference to water and examined with respect to clinical outcomes, including postgadolinium MRI and overall survival time. MRS data from 19 patients were included in subsequent analysis, excluding suboptimal data from one patient. Tumors with elevated 2HG (> 1.9 mM, N = 8) and undetectable 2HG (< 0.3 mM, N = 11) were clearly distinguishable. Tumors with elevated glycine (> 1.5 mM, N = 4) showed rapid progression. Kaplan–Meier survival analyses with metabolite measures demonstrated that tumors with 2HG higher than 1.0 mM were significantly associated with a favorable prognosis (p = 0.01). In contrast, tumors with glycine higher than 2.5 mM showed a strong association with poor survival (p = 0.0005). The data confirm detection of 2HG in brainstem tumors at a concentration that is consistent with an IDH mutation and expected good prognosis, whereas elevated glycine in brainstem tumors portends rapid tumor progression and a worse prognosis.

Abstract Sex differences in cancer outcome, including that of glioblastoma (GBM), are shaped by biological, hormonal, and immunological factors and impact disease progression, treatment responses, survival, and tumor microenvironment (TME) interactions. Platelets regulate the immune responses and tumor progression in many cancers, but it is not clear how they contribute to these sex-based differences by affecting the dynamics of the TME. Here, we show that GBM patients exhibit heightened platelet reactivity driven by PAR4 signaling. In murine GBM models, both pharmacological inhibition of PAR4 using BMS986120 and genetic deletion of PAR4 significantly prolong survival in females but not males. This survival advantage is estrogen dependent: it is preserved in chromosomal male-hormonal female mice within the four-core genotype model and is rescued in ovariectomized mice treated with estrogen. The survival benefit is TME specific and is mediated by platelet-driven enhancement of CD8⁺ T cell infiltration into the tumor. Inhibition of platelet PAR4 signaling increases calcium signaling through an estrogen-dependent interaction between PAR4 and estrogen receptor β (ERβ)—a receptor interaction not previously described. PAR4-activated platelets within the TME suppress CD8⁺ T cell function, and depletion of CD8⁺ T cells abolishes both the tumor-induced platelet reactivity and the survival benefit conferred by PAR4 inhibition. These findings establish platelet-mediated PAR4 signaling as a critical driver of tumor progression and identify sex-specific immune responses as key to therapeutic efficacy.

Background: Lung cancer ranks as the leading cause of cancer-related mortality worldwide. The complexity of tumor delineation, crucial for radiation therapy, requires expertise often unavailable in resource-limited settings. Artificial Intelligence (AI), particularly with advancements in deep learning (DL) and natural language processing (NLP), offers potential solutions yet is challenged by high false positive rates. Purpose: The Oncology Contouring Copilot (OCC) system is developed to leverage oncologist expertise for precise tumor contouring using textual descriptions, aiming to increase the efficiency of oncological workflows by combining the strengths of AI with human oversight. Methods: Our OCC system initially identifies nodule candidates from CT scans. Employing Language Vision Models (LVMs) like GPT-4V, OCC then effectively reduces false positives with clinical descriptive texts, merging textual and visual data to automate tumor delineation, designed to elevate the quality of oncology care by incorporating knowledge from experienced domain experts. Results: The deployment of the OCC system resulted in a 35.0% reduction in the false discovery rate, a 72.4% decrease in false positives per scan, and an F1-score of 0.652 across our dataset for unbiased evaluation. Conclusions: OCC represents a significant advance in oncology care, particularly through the use of the latest LVMs, improving contouring results by (1) streamlining oncology treatment workflows by optimizing tumor delineation and reducing manual processes; (2) offering a scalable and intuitive framework to reduce false positives in radiotherapy planning using LVMs; (3) introducing novel medical language vision prompt techniques to minimize LVM hallucinations with ablation study; and (4) conducting a comparative analysis of LVMs, highlighting their potential in addressing medical language vision challenges.

ABSTRACTBackgroundPercutaneous transluminal angioplasty and stenting (PTAS) in patients with carotid stenosis may have potential effects on brain parenchyma. However, current studies on parenchymal changes are scarce due to the need for advanced imaging modalities. Consequently, the alterations in brain parenchyma following PTAS remain an unsolved issue.PurposeTo investigate changes to the brain parenchyma using magnetic resonance elastography (MRE).Study TypeProspective.Population13 patients (6 women and 7 men; 39 MRI imaging sessions) with severe unilateral carotid stenosis patients indicated for PTAS were recruited between 2021 and 2024.Field Strength/SequenceNoncontrast MRI sequences including MRE (spin echo) were acquired using 3 T scanners.AssessmentAll patients underwent MRE before (preprocedural), within 24 h (early postprocedural) and 3 months after (delayed postprocedural) PTAS. Preprocedural and delayed postprocedural ultrasonographic peak systolic velocity (PSV) was recorded. MRE stiffness and damping ratio were evaluated via neural network inversion of the whole brain, in 14 gray matter (GM) and 12 white matter (WM) regions.Statistical TestsStiffness and damping ratio differences between each pair of MR sessions for each subject were identified by paired sample t tests. The correlations of stiffness and damping ratio with stenosis grade and ultrasonographic PSV dynamics were evaluated by Pearson correlation coefficients. The statistical significance was defined as p < 0.05.ResultsThe stiffness of lesion side insula, deep GM, and deep WM increased significantly from preprocedural to delayed postprocedural MRE. Increasing deep GM stiffness on the lesion side was positively correlated with the DSA stenosis grade significantly (r = 0.609). The lesion side insula stiffness increments were positively correlated with PSV decrements significantly (r = 0.664).Data ConclusionRegional brain stiffness increased 3 months after PTAS. Lesion side stiffness was positively correlated with stenosis grades in deep GM and PSV decrements in the insula.Evidence Level2.Technical EfficacyStage 2.