Citations

Abstract INTRODUCTION Similarities between frontotemporal lobar degeneration with transactive response DNA‐binding protein of 43 kDa (TDP‐43) (FTLD‐TDP) and limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC) raise questions about whether they represent distinct entities or a single disease spectrum. The literature mostly examined series with disproportionate numbers of LATE‐NC over FTLD‐TDP. METHODS Leveraging a clinicopathological collection of FTLD‐TDP ( N = 148) from the University of California, San Francisco, we compared demographic, clinical, genetic, and neuropathological features of FTLD‐TDP, particularly FTLD‐TDP type A ( N = 39), and LATE‐NC ( N = 42). RESULTS FTLD‐TDP type A cases were younger at onset and death, had shorter disease duration, and frequent genetic causes ( GRN , C9ORF72 ) compared to LATE‐NC, which were mostly sporadic and older. Blinded evaluation of middle frontal gyrus (MFG) TDP‐43 immunostaining alone proved insufficient to reliably differentiate FTLD‐TDP type A from LATE‐NC stage 3. However, factoring in all neuropathologic features, FTLD type A and LATE‐NC could be differentiated with >95% confidence. DISCUSSION These overall findings support distinct diagnostic entities for FTLD‐TDP and LATE‐NC.

Premature ventricular contractions (PVCs) are common arrhythmia encountered in patients with and without structural heart disease. Although often benign and asymptomatic, they may also cause palpitations, exercise intolerance, presyncope, and reduced quality of life, and in some patients can contribute to PVC-induced cardiomyopathy or trigger malignant ventricular arrhythmias. Their clinical significance depends on symptom burden, PVC frequency, ventricular function, and the presence of underlying myocardial disease. Diagnostic evaluation includes electrocardiography, ambulatory rhythm monitoring, echocardiography, exercise testing, and cardiac magnetic resonance imaging for tissue characterization and risk stratification. Management ranges from reassurance and lifestyle modification to pharmacologic therapy and catheter ablation. Beta-blockers and nondihydropyridine calcium channel blockers remain common first-line options, whereas antiarrhythmic drugs may be considered in carefully selected patients. Catheter ablation is an effective treatment for symptomatic PVCs, high PVC burden, and PVC-induced cardiomyopathy, with high procedural success rates and favorable effects on arrhythmic burden and ventricular function. Novel approaches, including electrocardiographic imaging-guided planning, pulsed field ablation, stereotactic radioablation, neuromodulation, and renal denervation, may further expand future therapeutic options. This review summarizes the pathophysiology, clinical implications, diagnostic evaluation, and contemporary management of PVCs, with emphasis on medical therapy, catheter ablation, and emerging treatments.

Abstract Background Spinocerebellar ataxia type 3 (SCA3), the most common autosomal dominant ataxia, is driven by the accumulation of polyglutamine‐expanded (polyQ) ATXN3 proteins. While promising as biomarkers, their longitudinal trajectories across multiple biofluids remain poorly defined. Objectives To quantify polyQ ATXN3 levels in cerebrospinal fluid (CSF), plasma, and urine within a comprehensive cohort, utilizing serial measurements to map protein dynamics. Methods We employed a validated immunoassay to quantify polyQ ATXN3 in 97 symptomatic and 13 presymptomatic SCA3 patients, correlating levels with clinical features, ancestry, disease status, and longitudinal progression. Results Asian participants exhibited lower plasma but elevated urinary polyQ ATXN3 levels relative to other ancestries. While CSF levels were higher in symptomatic patients at baseline, they showed a significant longitudinal decline. Conclusions PolyQ ATXN3 is a viable multi‐biofluid biomarker. Declining CSF levels likely reflect neurodegeneration, supporting its role in tracking progression and emphasizing the need for ancestry‐based adjustment in trials. © 2026 International Parkinson and Movement Disorder Society.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system in which environmental factors play an important role in shaping disease risk, activity, and progression. Over the past decade, human and experimental studies have consistently shown alterations in the gut microbiome across the phenotypic spectrum of MS and have linked these changes to immune dysregulation, barrier dysfunction, neuroinflammation, and demyelination. Additionally, emerging evidence indicates that microbial function, particularly metabolite production plays a more direct role in shaping immune responses and associated neuropathology. Evidence from both human studies and experimental autoimmune encephalomyelitis models supports a functional role for microbial metabolites in shaping neuroimmune responses. Bacterially derived metabolites such as short-chain fatty acids, bile acids, polyamines, phytoestrogen metabolites, and tryptophan-derived compounds can influence T-cell differentiation, glial activation, epithelial integrity, and neuroimmune communication. Recent longitudinal studies also show associations between metabolite profiles and disability worsening. Because disease-modifying therapies, diet, and microbiome-directed interventions can reshape microbial metabolism, microbial metabolites may represent promising therapeutic targets in the gut-immune-brain axis. In this Review , we integrate current evidence to propose a mechanistic framework in which microbial metabolites act as central regulators of mucosal and systemic immunity that influence different aspects of MS biology. We discuss how this perspective shifts gut microbiome research from descriptive associations to biological mechanisms that more directly link the gut to immune responses and downstream neuropathology. We then evaluate therapeutic strategies that target microbial metabolism and outline key priorities for longitudinal, multi-omics, and interventional studies that are needed to enable microbiome-informed precision therapies in MS.

Abstract Background: The dynamic nature of surgical demand poses significant challenges in planning and scheduling resources to staff the surgical suite. Uncertainty in workload often leads to conservative upstream resource allocation, resulting in staffing misallocation. We propose a novel metric, the daily maximum number of open operating rooms (ORs), as an interpretable resource demand proxy to support staff planning. Methods: Using historical surgical data from Mayo Clinic in Rochester, Minnesota, from May 5, 2018 through October 8, 2023 (332,904 surgical cases), we developed a deep learning framework based on a wide-and-deep architecture to predict the daily maximum number of open ORs. The model incorporates features capturing historic OR use trends, seasonality effects, and anesthesia division–specific characteristics. Predictions are generated for forecast horizons of up to 90 business days. Results: Our results demonstrate strong predictive performance, with campus-level root mean square error values ranging from 5 to 7 available ORs across all forecast horizons. Validation across 9 anesthesia divisions confirms the frame- work’s capability to capture complex, nonlinear dependencies within longitudinal surgical datasets. Conclusions: This study introduces a novel operational metric and a robust predictive framework for perioperative resource management. By accurately fore- casting daily maximum open ORs, health care managers can better align staff capacity with anticipated demand, potentially enhancing staff use and improving the patient care experience by minimizing delays.

Introduction Hospital readmissions in the US place a considerable burden on patients and their caregivers. Our study will investigate whether spiritual intervention during a patient’s hospital stay contributes to lower rates of readmissions 30 days after hospital discharge. Methods Two hundred patients receiving palliative care will be randomized into control (n = 100) and intervention groups (n = 100). The control group will receive a standard spiritual support visit, while the intervention group will receive a spiritual intervention consisting of active listening, compassionate presence, assessment of post-discharge resources, and a supportive phone call 5 to 7 days after discharge. The primary outcome will be hospital readmission within 30 days of discharge. Board-certified chaplains will be allowed to use their individual skillsets but within the standardized ACA spiritual care model. Training chaplains to assess patients in the same way will help with this discrepancy as the same form will be used. Discussion We hypothesize that patients who receive spiritual intervention with a supportive phone call will experience fewer hospital readmissions. Spiritual intervention will instill.confidence in those patients at risk of readmission by assuring them that the hospital staff remain concerned about their well-being even after discharge.

Abstract: Cardiovascular disease (CVD) remains the leading cause of death worldwide. While advances in treatment have improved outcomes, the greatest gains in public health will come from primary prevention. Risk stratification is the foundation of CVD prevention. Traditional tools, such as pooled cohort equations (PCEs) and SCORE2, do not capture non-traditional risk factors and individual variability, driving efforts to refine existing approaches. We critically discuss emerging risk determinants for primary CVD prevention. Coronary artery calcium scoring can reclassify CVD risk but has limitations related to cost, access, and unvalidated improvements in clinical endpoints. Biomarkers such as apolipoprotein B and lipoprotein(a) may identify residual risk beyond LDL-C, particularly in patients with lipid discordance, but remain underused due to uncertain thresholds and the lack of prospective triallevel outcome data. Trials of colchicine in primary prevention have yielded mixed results, making the role of targeting inflammation unclear in CVD prevention. Polygenic risk scores can stratify genetic risk but face challenges in sensitivity, specificity, and generalizability. Multiomics approaches, while offering the promise of deeper phenotyping, lack established clinical applications and consensus on when their use is appropriate. Artificial intelligence may allow better prediction across cohorts but requires broader validation. Clonal hematopoiesis of indeterminate potential, a marker of inflammation and age-related CVD risk, lacks evidence supporting routine screening or intervention in younger, asymptomatic individuals. The proliferation of new risk stratification tools poses a key challenge: determining when additional data meaningfully alter clinical decisions. Until robust outcome-based evidence emerges, risk enhancers should guide, but not dictate, therapy in selected patients.

Abstract Background Patients with breast cancer undergoing chemotherapy experience multiple symptoms that cause decrements in quality of life. A deeper understanding of serum metabolites as biomarkers may guide in predicting symptom occurrence and severity. This study evaluated change in serum metabolite levels from before chemotherapy (T1) to after the initial first or second cycle of chemotherapy (T2), after the third cycle of chemotherapy (T3) and finally after a month of chemotherapy completion (T4). Change in metabolite levels were analyzed in association with symptom occurrence. Methods Patients with breast cancer (n = 10) completed study measures at four timepoints. Neuropsychological and gastrointestinal (GI) symptoms were evaluated using the Memorial Symptom Assessment Scale. Dietary intake was assessed using the NHANES Dietary Screener Questionnaire. Serum metabolites were analyzed using gas chromatography-mass spectrophotometry. Results Five patients experienced > 3 GI symptoms at T2 and T3. At all 4 timepoints, ≥ 6 patients experienced moderate to severe neuropsychological symptoms severity. Daily mean intake of fiber, whole grain, and calcium were less than the recommended guidelines. Compared to T1, long chain fatty acid and amino acid derivative levels decreased at T2 and T3 (p < 0.05). Increase in metabolite levels of glucose-6-phosphate (p = 0.02) and 6-phosphogluconate (p = 0.05) at T2 were associated with fatigue occurrence. Conclusions Patients experienced several gastrointestinal and neuropsychological symptoms during chemotherapy and early survivorship. Chemotherapy-induced changes in metabolites involved in cellular energy metabolism may explain patient symptom experience. Metabolite level changes overtime may reflect inadequate dietary intake. Larger sample size studies may guide in building metabolic prediction models for symptom burden.

Abstract Carcinoid heart disease (CHD) is associated with advanced neuroendocrine tumor liver metastases (NETLM) and may preclude surgical cytoreduction. We assessed perioperative and long‐term outcomes of hepatectomy in patients with CHD. We retrospectively analyzed 311 patients undergoing cytoreductive hepatectomy for intestinal NETLM: non‐functional ( n = 163), carcinoid syndrome (CS) without CHD ( n = 110), and CHD ( n = 38), including patients undergoing pre‐hepatectomy valve replacement. CHD patients more frequently had >10 liver metastases (78%) and larger lesions (median 9.5 cm) and required major hepatectomy more often (58%). Major morbidity was higher in CHD (up to 47%), yet 90‐day mortality remained low (≤4%). Median overall survival after hepatectomy was comparable across groups (12.5 vs. 9.1 vs. 11.4 years; p = .19), including matched analyses. With optimal cardiac management, cytoreductive hepatectomy in CHD is feasible and provides long‐term survival comparable to patients without CHD.