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Abstract Background Parkinson's disease (PD) represents a growing global health challenge, with prevalence doubling from 2.5 million cases in 1990 to 6.1 million in 2016, and projections suggesting it will exceed 12 million by 2040. This exponential growth has been termed the "Parkinson's pandemic." China and the United States, which together account for nearly half of the global PD population, have developed markedly different approaches to end-of-life (EOL) care, shaped by their distinct healthcare systems and cultural contexts. Understanding these differences is crucial for developing effective global strategies. This systematic review and meta-analysis comprehensively compares advanced-stage PD care between these two nations to quantify disparities and inform evidence-based policy interventions. Methods We conducted a rigorous systematic review following PRISMA 2020 guidelines, searching six databases (PubMed, Embase, Scopus, Web of Science, CNKI, Wanfang) from January 2015 to October 2025. The timeframe was selected to capture contemporary care patterns following major healthcare reforms in both countries (Affordable Care Act implementation in the US; Healthy China 2030 initiative). Inclusion criteria encompassed peer-reviewed studies reporting on advanced PD (Hoehn-Yahr stage ≥ 3) with outcome measures including survival, quality of life (QoL), palliative care access, caregiver burden, rehabilitation utilization, or healthcare costs. The sample size threshold (n ≥ 100) balanced statistical power with inclusivity. Two independent reviewers screened 3,847 records with excellent agreement (Cohen's κ = 0.82–0.89). Quality assessment employed the Newcastle-Ottawa Scale (NOS ≥ 8 indicating high quality) and ROBINS-I for observational studies, with GRADE criteria determining evidence certainty. Meta-analyses utilized random-effects models with comprehensive heterogeneity assessment (I² statistics, meta-regression) and publication bias evaluation (Egger's test, trim-and-fill analysis). Sensitivity analyses included high-quality studies only and examined the influence of large database studies. Results Our analysis of 42 high-quality studies encompassing over 125,000 patients revealed profound and systematic cross-national disparities across multiple domains. In terms of care access, US patients demonstrated significantly higher hospice enrollment rates (28–35% vs. <1% in China, p < 0.001; HIGH certainty evidence) and greater access to specialized neuropalliative programs (15% of US centers vs. <1% in China). These differences translated into measurable quality of life disparities, with Chinese patients scoring 17.6 points worse on the PDQ-39 scale (95% CI 14.2–21.0; MODERATE certainty, I²=68%), a difference exceeding the minimal clinically important difference nearly four-fold. The burden on families showed equally striking patterns: Chinese families provided 94% of EOL care compared to 61% in the US, resulting in significantly higher caregiver depression rates (47% vs. 32%, OR = 1.89, 95% CI 1.45–2.47) and burden scores (Zarit difference: 10.2 points, 95% CI 7.8–12.6). Access to interventions revealed additional gaps, with only 9.2% of Chinese patients receiving physical therapy versus 14.4% in the US (OR = 0.61, 95% CI 0.49–0.76), and a 5.25-fold disparity in deep brain stimulation access (4.2% vs. 0.8%). Economic analysis demonstrated substantial out-of-pocket burden differences: Chinese families paid 58% of total costs ($4,200 annually) versus 12% for US families ($2,800). Meta-regression identified healthcare system characteristics as the primary driver of these disparities (R²=0.42, p < 0.001). Conclusions This comprehensive analysis reveals that systematic differences in healthcare infrastructure, insurance coverage, and cultural care models produce markedly divergent EOL experiences for PD patients in China versus the United States. These findings have immediate policy implications. For China, we recommend: (1) establishing pilot neuropalliative programs in tertiary centers with phased national expansion; (2) developing caregiver support infrastructure including respite care and training programs; (3) leveraging telemedicine platforms to address urban-rural disparities. For the United States, priorities include: (1) addressing racial disparities in rehabilitation access through culturally competent outreach; (2) expanding Medicare coverage for maintenance therapy; (3) earlier integration of neuropalliative care. Implementation science research is urgently needed to test culturally adapted interventions. As global PD prevalence accelerates, lessons from this bilateral comparison provide a framework for other nations confronting similar challenges in neurological care delivery.

Significance: Immune checkpoint inhibitors (ICIs) have transformed cancer therapy by reactivating antitumor immunity and improving outcomes across multiple malignancies. Yet, clinical observations and preclinical studies suggest that ICIs may increase long-term cardiovascular disease risk, including hypertension, atherosclerosis, and thrombosis. The underlying mechanisms remain incompletely defined, highlighting the need for focused investigation into the vascular consequences of immune activation. Recent Advances: ICI-induced immune activation disrupts vascular and immune homeostasis through persistent production of reactive oxygen species (ROS), mitochondrial dysfunction, and accumulation of cell-free DNA (cfDNA). Sustained T-cell activation enhances ROS generation, driving DNA damage and senescence in both endothelial and immune cells. ICIs may also promote endothelial-to-mesenchymal transition (EndoMT) through chronic oxidative and inflammatory signaling, contributing to fibrosis, vascular stiffness, and chronic inflammation. Transforming growth factor-beta, although immunosuppressive in many contexts, can drive profibrotic and EndoMT programs within the vasculature. Other cytokines and regulators, including interleukin-17 and regulator of calcineurin 1, have been implicated in vascular remodeling, atherosclerosis, and hypertension. Critical Issues: The relative roles of ROS, mitochondrial dysfunction, cfDNA-driven inflammation, and EndoMT in ICI-associated vascular senescence remain unclear. While inflammation-induced vascular damage is well-recognized, direct ICI-specific mechanisms require stronger evidence. How senescent endothelial and immune cells influence therapy resistance and remodeling of the tumor microenvironment also remains to be defined. Future Directions: Mitochondrial and cytosolic ROS sources—arising from electron leakage during oxidative phosphorylation and NADPH oxidases activity—shape immune signaling and sustain T-cell activation during checkpoint blockade. The DNA damage response kinases ataxia-telangiectasia mutated and ATM- and Rad3-related, activated by oxidative and replicative stress, engage p53-dependent senescence pathways in endothelial and immune cells. Future studies should evaluate biomarkers such as cfDNA and thrombospondin-1 and explore senescence-targeting or redox-modulating interventions that may alleviate cardiovascular toxicity without diminishing antitumor efficacy. This review outlines mechanistic pathways linking ICIs to vascular dysfunction and senescence, integrating preclinical data with emerging clinical insights. It distinguishes established processes from ICI-specific hypotheses and identifies key gaps requiring clinical validation. Antioxid. Redox Signal. 00, 000–000.

Abstract Background Amyloid related imaging abnormality edema (ARIA‐E) occurs in about 19% of individuals with autosomal dominant Alzheimer disease (ADAD) treated with an anti‐amyloid‐b monoclonal antibody (Salloway et al., 2021). In a previously reported case, ARIA‐E appeared to colocalize with decreases in PiB‐PET uptake (Joseph‐Mathurin, Llibre‐Guerra, et al, 2022), suggesting an association between amyloid‐b (Aβ) removal and ARIA‐E. Here, we compare longitudinal neuroimaging and corresponding neuropathology in an ADAD individual treated with gantenerumab, who experienced multiple ARIA‐E episodes as sulcal effusions that resolved by the end of the four‐year trial. Methods PiB‐PET and MRI were collected pre‐ and post‐randomization (2 and 4 years). The participant consented to brain donation, which was received a year after trial completion. Four tissue samples were taken from the location of the ARIA‐E in the parieto‐occipital left hemibrain as identified by MRI (one block contained the sulcus affected by ARIA‐E; the rest of the coronal section was captured in the remaining three blocks). Area fractions (AFs) of Aβ (10D5 immunohistochemistry (IHC)), tauopathy (PHF1), microglia (Iba1), and astrocytes (GFAP) in one sulcal region of interest (ROI) from each block and PiB‐PET SUVRs of corresponding ROIs were extracted ( n = 4, Figure 1). Additionally, we included PiB‐PET SUVRs corresponding to ARIA‐E findings observed in the right hemisphere at baseline, two‐year, and four‐year visits ( n = 6). Results Overall PiB‐PET uptake increased during the first two years (before ARIA‐E) and decreased during the last two years (including ARIA‐E episodes) (0.03±0.05 vs. ‐0.04±0.04 SUVR/year, p ‐value=0.01, Figure 2). The decrease seemed more pronounced in ARIA‐E ROIs versus normal‐appearing sulcus ROIs (‐0.05±0.04 vs. ‐0.02±0.03 SUVR/year). Lower PiB uptake at last visit appeared associated with lower Aβ AF (estimates=0.03±0.01, p ‐value=0.07). The ARIA‐E ROI had an Aβ AF of 0.009 while normal‐appearing sulcus ROIs had a mean of 0.02+0.003 (Figure 3). AFs for tauopathy, microglia, and astrocytes were within the range of those of normal‐appearing sulcus ROIs, suggesting an Aβ‐specific effect, although unexamined markers may play a role. Conclusions Our preliminary findings indicated that ARIA‐E is associated with longitudinal PiB‐PET decrease and Aβ AF, supporting the link between ARIA‐E, changes in PiB‐PET, and local Aβ removal observed at autopsy. Funding : K01AG080123; U01AG042791; R01AG046179; R01AG053267

Background Costosternal cartilages and the costal margin, collectively termed costal cartilage, are hyaline cartilage connecting ribs to the sternum and to adjacent ribs, respectively. Presence of intact costal cartilage is essential for elasticity of the chest wall. Anecdotally, costal cartilage injuries are underdiagnosed on trauma CT scan in patients with rib fractures. Our aim was to determine a baseline frequency of acute costal cartilage injury among patients presenting with rib fractures. Methods We performed a retrospective cohort study of injured adult patients admitted to Level I/II trauma centers with rib fractures from January 2020 to July 2024. CT images obtained at admission were manually reviewed by chest wall surgeons for presence of costal cartilage injury. Concordance with the original radiology report was obtained. Multivariable regression was used to analyze factors associated with costal cartilage injury and missed cartilage fractures. Results 1441 patients were identified; 197 (14%) had a costal cartilage fracture. A plurality of injuries included falls (n=667, 46%). Median ISS (Injury Severity Score) was 13 (IQR: 9 to 21), median Abbreviated Injury Scale thorax score was 3 (IQR: 3 to 3), and median number of fractured ribs was 3 (IQR: 3 to 7). 294 (21%) patients had radiographic flail segments, and 136 (9%) had sternal fractures. 172 (87%) patients had a costal cartilage fracture missed on initial trauma chest CT. On multivariable analysis, ISS (adjusted OR (aOR) 1.02 (95% CI 1.01 to 1.04), radiographic flail segment (aOR 1.6 (95% CI 1.10 to 2.31)) and presence of sternal fracture (aOR 1.85 (95% CI 1.19 to 2.89)) were associated with costal cartilage fractures. Only the total number of rib fractures was associated with a missed costal cartilage fracture on univariate analysis (OR 1.17 (95% CI 1.01 to 1.36)). Conclusions Costal cartilage injuries are common and frequently are not identified during interpretation of the initial trauma CT. A higher index of suspicion is warranted for costal cartilage fractures among patients with greater injury burden, radiographic flail segment, and sternal fractures. Level of evidence Level III.

BACKGROUND AND OBJECTIVES: Minimum clinically important differences (MCIDs) for patient-reported outcome metrics (PROMs) in patients with cervical spondylotic myelopathy (CSM) lack consensus on the most appropriate calculation method. This retrospective study aimed to identify the optimal MCIDs for commonly used PROMs in CSM. METHODS: The CSM database from the Quality Outcomes Database SpineCORe Study Group was analyzed. Baseline, 3-month, and 24-month PROM values for Neck Disability Index (NDI), 5-dimension Euro-quality of life (EQ-5D) in quality-adjusted life years, modified Japanese Orthopaedic Association (mJOA) score, and neck/arm pain numeric rating scale (NRS) were collected. MCIDs were calculated for each PROM using previously validated techniques. MCID values were compared using the area under the curve (AUC) with the North American Spine Society satisfaction scale as an anchor. RESULTS: A total of 1141 patients with CSM undergoing surgery were included in this analysis. Improvement of ≥30% from baseline was the optimal MCID for NDI and neck/arm NRS. At 24 months, the optimal percentage cutoff MCID for these instruments resulted in AUCs of 0.76, 0.72, and 0.67, similar to the 30% improvement method, with AUCs of 0.73, 0.71, and 0.67, respectively. Numeric cutoffs (0.065 at 3 months; 0.149 at 24 months) were the superior MCIDs for EQ-5D. For mJOA score, a severity-adjusted MCID outperformed other methods, yielding an AUC of 0.67 at 24 months. MCIDs were achieved in 63% of patients for NDI, 59% for neck pain NRS, 61% for arm pain NRS, 52% for EQ-5D, and 59% for mJOA score at 24 months. CONCLUSION: Using the Quality Outcomes Database SpineCORe data set, we defined optimal MCIDs for key PROMs in CSM. A ≥30% improvement from baseline was optimal in NDI and arm/neck NRS. An absolute numeric cutoff was superior for EQ-5D (0.149 at the 24-month follow-up). A severity-adjusted MCID performed best for mJOA score. These redefined benchmarks better capture the treatment impact and guide care decisions for patients with CSM.

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen's kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure 1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure 1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure 2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure 2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.

PURPOSE Manual extraction of treatment outcomes from unstructured oncology clinical notes is a significant challenge for real-world evidence (RWE) generation. This study aimed to develop and evaluate a robust natural language processing (NLP) system to automatically extract cancer treatments and their associated RECIST-based response categories (complete response, partial response, stable disease, and progressive disease) from non–small cell lung cancer (NSCLC) clinical notes. METHODS This retrospective NLP development and validation study used a corpus of 250 NSCLC oncology notes from University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center, annotated by physician experts. An end-to-end NLP pipeline was designed, integrating a rule-based module for entity extraction (treatments and responses) and a machine learning module using biomedical clinical bidirectional encoder representations from transformers for relation classification. The system's performance was evaluated on a held-out test set, with partial external validation for relation extraction on a Mayo Clinic data set. RESULTS The NLP system achieved high overall accuracy. On the UPMC test set (64 notes), the relation classification model attained an area under the receiver operating characteristic curve of 0.94 and an F1 score of 0.92 for linking treatments with documented responses. The rule-based entity extraction demonstrated a macro-averaged F1 score of 0.87 (precision 0.98, recall 0.81). Although precision was high for chemotherapy and most response types (1.00), recall for cancer surgery was 0.45. External validation at Mayo Clinic showed moderate relation extraction F1 scores (range: 0.51-0.64). CONCLUSION The proposed NLP system can reliably extract structured treatment and response information from unstructured NSCLC oncology notes with high accuracy. This automated approach can assist in abstracting critical cancer treatment outcomes from clinical narrative text, thereby streamlining real-world data analysis and supporting the generation of RWE in oncology.

Sustained injury to renal tubular epithelial cells (TECs), driven by excessive autophagy, is a critical mechanism underlying kidney fibrosis. Our previous work identified JLP — a TEC-expressed scaffolding protein — as an endogenous antifibrotic factor that counteracts TGF-β1–induced autophagy and fibrogenesis. However, the mechanism underlying JLP downregulation in renal fibrosis remains unclear. Here, we delineated a TGF-β1/LEF1/β-catenin/JLP axis that governs TEC autophagy through a dichotomous regulatory circuit. Under physiological conditions, low levels of β-catenin and LEF1 with minimal nuclear localization permitted normal JLP expression, which in turn maintained autophagy in check. In contrast, during renal injury, TGF-β1 promoted the expression and nuclear translocation of β-catenin and LEF1, which together suppressed JLP transcription. This loss of JLP-mediated inhibition led to unchecked autophagy and exacerbated fibrotic damage. Analyses of kidney tissues from patients with CKD, murine fibrotic kidneys, and cultured HK-2 cells confirmed consistent JLP downregulation accompanied by upregulation and nuclear accumulation of LEF1 and β-catenin. Therapeutic intervention using the β-catenin/LEF1 inhibitor iCRT3 or LEF1-targeted silencing in murine fibrosis models restored JLP expression, attenuated TEC autophagy, and ameliorated renal fibrosis. These findings revealed an autoregulatory circuit controlling TEC autophagy and fibrogenesis, and supported LEF1 and β-catenin as potential therapeutic targets in CKD.

Abstract Iron-deficiency anemia (IDA) affects nearly one-third of women globally, with heavy menstrual bleeding (HMB) being a significant risk factor among those of reproductive age. Despite the substantial burden of HMB-related IDA, patients often face delays in receiving effective treatment. Oral iron is typically used as first-line therapy, despite frequent gastrointestinal side effects and challenges in treatment adherence. This study evaluated the reproductive life span cost-effectiveness of first-line intravenous (IV) vs oral iron therapy for women with HMB and IDA. We developed a Markov model simulating a cohort of women aged 18 to 51 years, comparing first-line treatment with IV iron dextran, IV ferumoxytol, IV iron sucrose, or oral ferrous sulfate. Costs and quality-adjusted life years (QALYs) were estimated from the societal perspective. IV iron dextran was the cost-effective treatment, yielding 19.26 QALYs at a cost of $157 500, compared with 19.10 QALYs at $152 900 for oral ferrous sulfate. The incremental cost-effectiveness ratio for IV iron dextran was $28 600 per QALY. Treatment with IV ferumoxytol and iron sucrose cost $158 300 and $163 500, respectively, and did not provide additional QALY benefit compared with IV iron dextran, which remained the cost-effective treatment across a range of scenarios and sensitivity analyses. Our findings indicate that first-line treatment with IV iron dextran is the cost-effective strategy for managing IDA in women with HMB at commonly accepted willingness-to-pay thresholds. These results support expanding access to IV iron as a first-line option, and highlight the need to reduce treatment delays and insurance-related barriers.

SUMMARY Artificial intelligence (AI)-based methods are increasingly critical in peptide drug discovery, but their applications are limited in a narrow scope such as antimicrobial peptides. For indications where peptide therapy inherently excels, such as metabolism, endocrinology, and tissue regeneration, AI-based pipeline for therapeutic peptide discovery is long awaited but still unmet. Here, we propose a deep learning-based pipeline, Deepeptide, capable of identifying therapeutic oligopeptides for various metabolism-related indications. Leveraging the intrinsical relationship of ‘disease indication — biological processes — molecular functions’, Deepeptide discovers oligopeptides with indication-ameliorating-related molecular functions as lead candidates for indication of interest. Deepeptide was applied in five representative indications of metabolism, endocrinology, and tissue regeneration: angiogenesis, lipid metabolism, osteogenesis, glucose metabolism, and anti-angiogenesis. Overall, 62% of the identified oligopeptide candidates demonstrated significant bioactivity in vitro, with most of them showing comparable potency to the first-line drugs. Notably, the heptapeptide AP7 exhibited angiogenic potency comparable to VEGF in excisional wound splinting mouse model by promoting cell migration rather than proliferation, and hexapeptide TP6 showed significant dual-efficacy against hyperlipidemia and obesity in high-fat diet mice by inhibiting lipid synthesis and regulating gut microbiota. These findings highlight the potential and generalizability of Deepeptide in therapeutic oligopeptide discovery for metabolic diseases.