Although α-Klotho has gained attention as a promising biomarker of aging, its association with frailty and broader aging-related outcomes beyond chronic kidney disease–mineral and bone disorder remains incompletely characterized. This systematic review and meta-analysis aimed to investigate the association between circulating α-Klotho levels and aging-related outcomes, including frailty, effects of physical activity and exercise interventions, body composition, cognitive and neuropsychiatric status, sarcopenia, and bone mineral density (BMD). A comprehensive literature search was performed across multiple electronic databases, including Ovid MEDLINE, Web of Science, Scopus, PubMed, and the Cochrane Library, to identify relevant studies published up to April 30, 2025. Pooled analyses were conducted using random-effects models, with effect estimates synthesized as mean differences, odds ratios, or correlation coefficients, and heterogeneity assessed using the I2 statistic. Risk of bias was assessed using design-specific tools, including the Newcastle–Ottawa Scale, the Risk of Bias 2 tool (RoB2) of the Cochrane collaboration, and the Joanna Briggs Institute (JBI) checklists. A total of 109 studies met the inclusion criteria and were included. In our meta-analysis, higher circulating α-Klotho levels were significantly associated with lower odds of frailty (OR = 0.61, 95
Neuromyelitis optica spectrum disorder (NMOSD) is a rare autoimmune CNS disease that frequently causes severe optic neuritis, yet the molecular mechanisms driving retinal damage remain incompletely understood, especially across different NMOSD subgroups. Müller glial cells, which maintain retinal water–ion homeostasis through AQP4 and Kir4.1 channels, may represent a primary retinal target of circulating NMOSD-related autoantibodies and serum factors. We investigated how sera from AQP4-IgG+, MOG-IgG+, and double-seronegative (DSN) NMOSD patients affect the expression and localization of key Müller cell biomarkers. Human MIO-M1 Müller cells were stimulated with complement-inactivated patient or healthy control sera, and protein/mRNA levels of AQP4, Kir4.1, CRALBP, VEGF, and IL-6 were evaluated using immunofluorescence, Western blotting, and RT-qPCR. AQP4 membrane localization and internalization were assessed using WGA and EEA1 colocalization analyses. AQP4-IgG+ sera uniquely induced a marked reduction in AQP4 and Kir4.1 protein expression, together with mild AQP4 internalization and reduced membrane association. Despite protein loss, AQP4 and Kir4.1 transcripts were significantly upregulated, indicating a compensatory transcriptional response to antibody-mediated depletion. MOG-IgG + sera produced no major changes in the examined markers. In contrast, DSN sera selectively increased VEGF expression at both protein and mRNA levels, suggesting an alternative, antibody-independent mechanism of Müller cell activation. IL-6 expression showed non-significant changes across groups. These findings demonstrate subgroup-specific retinal glial responses to patient sera, with AQP4-IgG mediating early complement-independent loss of the AQP4–Kir4.1 water–ion channel complex, and DSN sera engaging distinct VEGF-related pathways. Our study establishes Müller cells as active contributors to NMOSD-associated retinal pathology and provides a foundation for exploring subgroup-tailored changes.
Potassium citrate is widely used as oral alkali therapy for the prevention of recurrent nephrolithiasis. Despite its long-standing clinical use, systematically collected real-world safety data remain limited. We performed a pharmacovigilance analysis to characterize adverse event reports associated with potassium citrate using the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS). FAERS reports submitted between 2014 and 2025 listing potassium citrate as the primary suspect drug were analyzed. Duplicate records were removed, and adverse events were coded using the Medical Dictionary for Regulatory Activities (MedDRA) at both the system organ class and standardized event term levels (preferred terms, PTs). Disproportionality analyses were conducted using reporting odds ratio, proportional reporting ratio, bayesian confidence propagation neural network, and multi-item gamma poisson shrinker methods. A total of 408 unique reports were included. Most reports involved adults and were physician-reported from the United States. Disproportionality analysis identified potential safety issues (signals), defined as drug event associations reported more frequently than expected in FAERS and therefore warranting further evaluation, although not establishing causality. The strongest associations involved product-related issues, laboratory investigations, and gastrointestinal disorders. When these potential safety issues were described using standardized MedDRA event terms most reflected formulation- and administration-related problems, including tablet residue in stool, abnormal solubility, swallowing difficulty, throat irritation, and foreign body sensations. Reports of rash were infrequent. This first FAERS-based analysis of potassium citrate highlights that most reported adverse events are related to formulation and administration characteristics rather than drug toxicity. These findings support the overall tolerability of potassium citrate while underscoring the importance of adherence, patient education, and formulation-specific considerations in clinical practice. As a spontaneous reporting system, FAERS is valuable for hypothesis generation, label expansion, and post-marketing surveillance, but it is not suitable for estimating the incidence or absolute risk of adverse events.
3D medical image classification is crucial for improving diagnostic accuracy and treatment planning, but it encounters challenges due to the complexity and variability of volumetric data. While 3D Convolutional Neural Networks offer potential solutions, designing effective architectures is complex and resource-intensive. Neural Architecture Search automates this process, optimizing network designs for specific tasks, thereby improving model performance. This study introduces a novel extension of the PBC-NAS method for 3D medical image classification, aiming to balance prediction accuracy and model complexity. We focus on optimizing neural network architectures using Neural Architecture Search for six different 3D datasets from MedMNIST3D, including OrganMNIST3D, NoduleMNIST3D, FractureMNIST3D, AdrenalMNIST3D, VesselMNIST3D, and SynapseMNIST3D, which are derived from real-world clinical imaging datasets. We have compared our method with state-of-the-art handcrafted networks, AutoML frameworks and recent NAS studies in terms of prediction performance and model complexity. The proposed NAS methods demonstrate superior performance compared to state-of-the-art handcrafted networks and AutoML frameworks. Our proposed model (Ours #3 ^† ) achieves the highest average Area Under the Curve (AUC) of 0.915 and accuracy (ACC) of 0.847 (best result across three independent runs), outperforming all handcrafted networks and AutoML frameworks. Compared to other NAS-based methods, all proposed models achieve higher average AUC scores, and it is important to note that they do not rely on data augmentation, pre-processing, or feature selection, unlike the competing NAS methods which do use data augmentation during training. The study also highlights significant reductions in computational complexity, with FLOPs reduced by up to 45.51 times and parameters by up to 211 times compared to ResNet models. An ablation study reveals that while fine-tuning a model optimized for one dataset can achieve competitive results on other datasets, dataset-specific NAS is crucial for optimal performance. Despite this, the ablation results still outperform ResNets and AutoML frameworks in terms of average AUC and ACC. The study concludes that the proposed NAS approach effectively optimizes neural network architectures for complex 3D medical image classification tasks, achieving state-of-the-art performance without data augmentation.
INTRODUCTION:Leptomeningeal carcinomatosis (LMC) is a rare and highly fatal complication of solid malignancies and is extremely uncommon in gastric cancer, particularly as an isolated metastatic lesion. This study presents a rare case of LMC in a patient diagnosed with gastric signet-ring cell carcinoma and reviews cases reported in PubMed over the last 10 years. n METHOD: We present a 43-year-old male patient diagnosed with poorly differentiated gastric signet-ring cell carcinoma and elevated CA19-9 levels. His initial staging was consistent with locally advanced disease (CT4aN2M0). The patient received neoadjuvant FLOT chemotherapy, followed by total gastrectomy. In addition, articles published in PubMed over the last 10 years were systematically reviewed to identify cases of LMC associated with gastric cancer. RESULT:The final pathology from the gastrectomy revealed ypT3N3 disease. Three weeks after surgery, the patient developed new-onset headaches and progressive confusion, with a Mini-Mental State Examination score of 23/30. Contrast-enhanced brain MRI did not reveal any mass lesion but showed subtle hyperintensity in the cerebral peduncle region. CSF cytology confirmed LMC, demonstrating malignant signet-ring cells. After detailed consultation, the patient declined targeted therapy and transitioned to home palliative care, passing away two weeks after the diagnosis. The literature review identified 18 cases of LMC associated with gastric cancer. Clinical presentations were largely non-specific, including headache, nausea/vomiting, and confusion. Outcomes were uniformly poor, with survival typically measured in weeks. CONCLUSION:In patients with gastric cancer, clinicians should maintain a high index of suspicion for LMC when new neurological symptoms are detected, even in the absence of other metastatic disease on systemic workup. Cerebrospinal fluid cytology remains as an important test for confirming the diagnosis.
