搜索结果：Biomarker research

Alzheimer's disease (AD) commences with the preclinical stage where individuals remain cognitively unimpaired but already have AD pathology. As fluid and neuroimaging biomarker research progresses, AD has become defined biologically rather than based on traditional clinical symptoms. While the diagnosis of AD has been conceptually advanced by the AT(N) classification framework according to core biomarker profiles of amyloid-β (A), tau (T) and neurodegeneration (N), solely relying on biological diagnosis at an asymptomatic stage has limitations with potential ethical and psychosocial issues. Accelerated long-term forgetting (ALF) characterized by higher forgetting rates over longer delays (a week to months) captures substantial interest as one of the sensitive mnemonic measures. Remarkably, ALF assays have been increasingly applied to detecting subtle cognitive declines in preclinical AD individuals who are still normal on standard memory tests, which typically use ∼ 30 min delays to assess classical hippocampal amnesia. The findings suggest that ALF may reflect the impairment of systems memory consolidation, a process that is required to gradually transform memory traces temporarily stored in the hippocampus into cortical networks for long-term storage. This review provides an overview of recent progress in ALF research including the underlying mechanisms and fluid-based or brain imaging biomarkers, which have been explored not only in individuals at risk for developing AD but also in relevant animal models. The findings have important implications for how we can optimize the earlier and precise identification of patients at a preclinical stage of AD that is essential for designing effective preventive interventions.

This study was conducted to investigate cerebrospinal fluid neurobiomarker levels in elderly individuals with cognitive impairment and their correlation with clinical symptoms such as cognitive abilities, psychiatric symptoms, and self-care abilities. We collected data from 250 elderly patients suffering from cognitive impairment, with all participants being admitted to hospital. Neurobiomarker levels were tested by single-molecule immunoassay after cerebrospinal fluid specimens were obtained by lumbar puncture. Two trained neurologists jointly examined and questioned the rated patients, applying various scales. Aβ42, t-tau and p-tau181 not only affect elderly patients' cognition but also are correlated with neuropsychiatric symptoms (depression, anxiety), while α-synuclein (α-syn) is significantly associated with elderly patients' mental status such as anxiety and depression. Meanwhile, self-care ability is affected by the multiplicity of multiple biomarkers such as p-tau181, α-syn, and t-tau/Aβ42. This study reveals the associations between cerebrospinal fluid biomarkers and cognitive, psychiatric, and self-care symptoms in elderly individuals with cognitive impairment. Aβ, tau, and α-syn each have characteristic association patterns, providing biomarker references for clinical assessment. Longitudinal studies are still needed to verify causality and clinical translation value.

Bicuspid aortic valve (BAV) is associated with early aortopathy that may precede overt aortic dilatation. Functional assessment of aortic biomechanics and extracellular matrix (ECM) biomarkers may provide additional insight beyond conventional diameter-based evaluation. In this prospective case-control study, 40 children with BAV and 40 healthy controls underwent echocardiographic assessment of ascending aortic elastic properties and left ventricular global longitudinal strain (GLS). ECM-related biomarkers were measured using ELISA. Children with BAV demonstrated significantly impaired aortic elastic properties, including lower aortic strain (14.79&#x2009;&#xb1;&#x2009;2.41 vs 21.03&#x2009;&#xb1;&#x2009;2.94) and distensibility (2.3 [2.0-3.15] vs 4.7 [4.1-5.7] &#xd7;10&#x207b;&#xb3; mmHg&#x207b;&#xb9;, p&#x2009;<&#x2009;0.001) and higher aortic stiffness index despite preserved GLS (p&#x2009;>&#x2009;0.05). Ascending aortic Z-scores were significantly higher in the BAV group. Serum MMP-2, MMP-9, and MMP-2/TIMP-1 ratio levels were elevated in children with BAV and were associated with impaired aortic elastic parameters. TGF-&#x3b2;1 levels did not differ between groups but demonstrated modest correlations with aortic biomechanics within the BAV cohort. In children with BAV, impaired aortic biomechanics and ECM remodeling appear to precede before overt myocardial dysfunction. Integrated functional imaging and biomarker assessment may enhance detection of BAV-related aortopathy. Functional impairment of aortic biomechanics and extracellular matrix remodeling are detectable in children with bicuspid aortic valve before overt aortic dilatation or myocardial dysfunction. This study integrates aortic strain-based functional imaging with circulating ECM biomarkers, providing pediatric evidence that biomechanical deterioration precedes structural aortopathy. Early functional aortic assessment may improve risk stratification and longitudinal surveillance strategies in pediatric patients with bicuspid aortic valve.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous lung disease traditionally characterized by neutrophilic inflammation. However, a distinct Type 2 (T2) inflammatory endotype is present in 20-40% of patients. This review examines the pathophysiology and clinical consequences of T2 inflammation in COPD, focusing on established and emerging biomarkers to identify this treatable trait and guide targeted therapies. Orchestrated by Th2 cells and innate lymphoid cells, T2 inflammation involves signature cytokines IL-4, IL-5, and IL-13, which drive eosinophilic tissue infiltration, mucus hypersecretion, airway hyperreactivity, and accelerated remodeling. These processes correlate with increased exacerbation risk and more rapid lung function decline. Blood eosinophil count (BEC) is the most validated and accessible biomarker, with established thresholds guiding the use of inhaled corticosteroids and biologics. Fractional exhaled nitric oxide (FeNO) and serum IgE offer complementary predictive value, and combining biomarkers may enhance the identification of responders to specific targeted agents. Clinical trials of biologics, such as dupilumab and mepolizumab, have validated the therapeutic potential of targeting T2 pathways in selected populations, though variable success with other agents highlights unique aspects of COPD pathophysiology and persistent knowledge gaps. Precision medicine, informed by a nuanced interpretation of reliable T2 biomarkers, is crucial for optimizing outcomes in this significant patient subgroup.

Septic arthritis (SA) is a rapidly progressive joint disease that can lead to cartilage damage if not treated promptly. A prompt and accurate distinction between SA and inflammatory arthritis (IA) is essential for establishing an optimal treatment plan. Progranulin (PRGN), an anti-inflammatory glycoprotein involved in various autoimmune diseases, has rarely been studied as a diagnostic biomarker for infectious arthritis. However, its precise role in this context remains unclear. This study aimed to evaluate the diagnostic utility of synovial fluid PRGN (SF-PRGN) in distinguishing SA from IA and osteoarthritis (OA). This single-center, cross-sectional study included 59 patients who underwent synovial fluid aspiration and were categorized into three groups: SA (n&#x2009;=&#x2009;23), IA (n&#x2009;=&#x2009;18), and OA (n&#x2009;=&#x2009;18). SA was diagnosed based on a positive synovial fluid culture or fulfillment of clinical criteria suggestive of infection. SF-PRGN levels were measured using ELISA, and synovial fluid C-reactive protein (SF-CRP) levels were determined using an immunoturbidimetric assay. Mean SF-PRGN levels were higher in the SA (339.77&#x2009;&#xb1;&#x2009;142.16 ng/mL) and IA (300.52&#x2009;&#xb1;&#x2009;159.60 ng/mL) groups than in the OA group (133.44&#x2009;&#xb1;&#x2009;41.77 ng/mL), indicating a statistically significant difference between the inflammatory and non-inflammatory groups (p&#x2009;<&#x2009;0.05). However, the SF-PRGN did not significantly differentiate between SA and IA (p&#x2009;=&#x2009;0.803). In contrast, SF-CRP levels were markedly elevated in SA (61.91&#x2009;&#xb1;&#x2009;46.84&#xa0;mg/L) and demonstrated strong discriminatory power between SA and IA (p&#x2009;<&#x2009;0.001; AUC: 0.795, p&#x2009;<&#x2009;0.0001). Although SF-PRGN levels are elevated in inflammatory arthritis, they lack specificity for SA. SF-CRP exhibited superior diagnostic accuracy in differentiating SA from IA. These findings underscore the need for further research on reliable biomarkers of SA in larger patient cohorts. Clinical trial number not applicable.

Oral squamous cell carcinoma (OSCC) is often preceded by oral potentially malignant disorders (OPMDs). Despite this known association, the transition from an OPMD to OSCC is complex, unpredictable, and non-linear, making early detection and intervention challenging for clinicians. Histopathological grading, the current standard for risk stratification, is not reliably predictive of malignant transformation (MT), and is subject to significant inter- and intra-observer variability. This scoping review evaluates emerging evidence on the integration of artificial intelligence (AI) and machine learning (ML) with molecular and histopathologic biomarkers to enable individualized risk assessment for MT. Ten retrospective studies incorporating AI/ML algorithms were analyzed, utilizing biomarkers ranging from gene expression panels, biochemical and protein-based markers like S100A7 to image-derived histomorphometric features. These models demonstrated promising predictive accuracy, with histology-derived features showing the greatest clinical feasibility. However, variability in methodologies, lack of prospective validation, and inconsistent demographic reporting limit the generalizability of the findings. This review highlights the need for multimodal biomarker integration, prospective clinical trials, and validation across broader populations. Ultimately, AI/ML-enhanced tools hold significant potential to inform personalized surveillance and treatment decisions in OPMD, but their clinical readiness requires further refinement and robust validation.

Cervical cancer remains a leading cause of cancer-related mortality among women worldwide, with mortality disproportionately concentrated in low-and middle-income countries (LMICs), where screening infrastructure is limited. Although persistent high-risk human papillomavirus (hrHPV) infection drives nearly all cervical cancers through a prolonged preinvasive window, making the disease both preventable and detectable, current screening modalities face biological and operational limitations that constrain their global impact. Cytology-based methods suffer from moderate sensitivity and subjective interpretations. HPV DNA testing is highly sensitive, it lacks specificity for transforming infections and shifts the diagnostic burden toward triage and colposcopy. Meanwhile, visual inspection methods are accessible, they offer limited reproducibility. In this review, we adopt a target-centric diagnostic framework that organizes cervical cancer screening not by detection platform but by the biological class of the marker being interrogated. We first examined the molecular pathogenesis of cervical carcinogenesis, including HPV genotype-specific biology, viral integration dynamics, oncogene-driven transformation, and epigenetic consolidation, to establish the biological rationale for each biomarker category. We then systematically evaluated conventional screening modalities and their limitations before reviewing emerging diagnostic technologies across four target domains: HPV-derived markers (DNA, mRNA, capsid proteins), host cell-cycle regulators (p16INK4a, Ki-67), non-protein biomarkers (biothiols, volatile metabolites), and marker-free platforms (Raman/FT-IR spectroscopy, AI-assisted cytopathology). Particular emphasis is placed on point-of-care (POC) deployability, noninvasive sampling strategies, and the integration of multilayered risk stratification into scalable screening pathways. By mapping diagnostic innovation onto the biological continuum of cervical carcinogenesis, this review provides a conceptual foundation for developing next-generation screening approaches that align molecular precision with global accessibility, thereby supporting progress toward the World Health Organization goal of cervical cancer elimination.

Heavy metals and trace elements can act as endocrine-disrupting chemicals and have been linked to thyroid, glucose, lipid, and hepatic abnormalities. We aimed to explore associations between routinely measured metal concentrations and biochemical/endocrinological parameters in a large occupational screening dataset from T&#xfc;rkiye. Records from 37,763 individuals evaluated at a national occupational and environmental diseases hospital between November 2021 and October 2023 were retrospectively reviewed; after prespecified exclusions, 34,595 unique participants were included. Metal measurements were performed in whole blood, serum, and urine samples as requested in routine surveillance; for each analyte, results were categorized as within or above the interpretive limit by the laboratory information system. Primary comparisons focused on arsenic, cadmium, lead, manganese, and zinc because of occupational relevance and sample size. Routine biochemistry, lipid profile, and thyroid function tests were extracted when available, and estimated glomerular filtration rate (eGFR, CKD&#x2011;EPI) was calculated. Among participants with available thyroid function tests (n&#x2009;=&#x2009;9,956), thyroid dysfunction was observed in 14.3% (subclinical hypothyroidism 11.9%). Among participants with available fasting glucose and/or HbA1c data (n&#x2009;=&#x2009;20,738), diabetes mellitus and prediabetes criteria were met in 12.8% and 10.0%, respectively. In univariable comparisons, several metals above the interpretive limit were associated with differences in metabolic biomarkers, including lower HDL with elevated cadmium, lower HDL/LDL with elevated manganese, and higher ALT/AST and triglycerides with elevated zinc. Elevated metal strata differed in age and sex distribution. After within-metal false discovery rate correction, only a limited subset of biomarker differences remained significant. Among tested participants, thyroid dysfunction and dysglycemia were observed, and selected metal measurements above interpretive limits were associated with lipid and liver enzyme patterns. Given the clinically driven testing and limited covariate data, these findings should be interpreted as exploratory surveillance signals rather than workforce-level prevalence estimates. Heavy metal exposure may exert endocrine-disrupting effects on workers in relevant industries, particularly on thyroid function and glycemic regulation, suggesting that periodic surveillance of these parameters is warranted in exposure-prone workforces.

Schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD) are highly prevalent psychiatric disorders characterized by substantial clinical overlap and biological heterogeneity, complicating diagnosis and therapeutic stratification. The identification of robust, minimally invasive biomarkers remains a critical unmet need. In this study, we applied an integrative systems biology framework to identify convergent and disorder specific blood and tissue based molecular signatures across SCZ, MDD, and BD. Disorder associated genes were systematically curated from multiple biomedical repositories and integrated with transcriptomic profiles from independent GEO datasets encompassing brain tissue, peripheral blood, and disease relevant cellular models. Comparative analyses revealed 4607 genes shared across all three disorders, of which 4348 were detectable in blood. These shared genes were significantly enriched for immune regulation, stress response, metabolic control, and neurotransmitter related pathways. Protein-protein interaction network analysis enabled the prioritization of key genes, with PFKFB3, ATF3, LGALS3, and TIMP1 emerging as central, biologically coherent nodes that were consistently validated across independent differential expression datasets and confirmed for blood level detectability using the Human Protein Atlas. Regulatory network reconstruction further identified disease relevant miRNA-gene interactions, with enrichment of blood expressed miRNAs highlighting the miR-17&#x223c;92 cluster and its paralogs as dominant post transcriptional regulators. Notably, the prioritized gene and miRNA signatures demonstrated enrichment across pathways associated with metabolic, cardiovascular, neurological, and oncological disorders, highlighting potential molecular overlap between psychiatric and systemic disorders. Collectively, these findings identify clinically accessible candidate gene and miRNA biomarkers with mechanistic relevance, supporting their prioritization for future experimental and clinical investigation.

Identifying children at highest risk for deterioration during evaluation for septic shock in emergency department (ED) settings remains challenging. Soluble CD25 (sCD25), a hemophagocytic lymphohistiocytosis (HLH) diagnostic criterion, has been associated with sepsis mortality in ICU settings. This study aimed to determine whether sCD25 is associated with adverse outcomes in children undergoing initial septic shock evaluation in a pediatric ED. We also sought to compare sCD25 in patients with septic shock, infection without sepsis, and HLH. Children with HLH demonstrated significantly higher sCD25 levels [25,800&#xa0;pg/mL (IQR: 1620-42,300)] compared with those with septic shock [5200&#xa0;pg/mL (IQR: 2500-20,600)] or infection [5500&#xa0;pg/mL (IQR: 2200-12,500)]. No statistical differences were observed between septic shock and infection groups; however, a subset of septic shock patients exhibited sCD25 elevations comparable to HLH patients. These patients experienced severe outcomes, including 100% PICU admission, 50% vasoactive support requirement, and prolonged hospitalization (16&#xa0;days). Bloodstream infections were associated with the highest sCD25 levels. These findings suggest sCD25 elevation may be associated with adverse outcomes in children with septic shock. Larger studies are warranted to validate sCD25 as a prognostic marker for children with septic shock.

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Helicobacter pylori (H. pylori) infection is a major risk factor for gastric cancer (GC), yet the key genes mediating this carcinogenesis remain unclear. This study aimed to identify H. pylori-related genes in GC and elucidate their molecular functions. Transcriptomic data from TCGA and GEO databases were analyzed using weighted gene co-expression network analysis (WGCNA), LASSO regression, and multivariate Cox analysis to construct a prognostic model. The immune landscape was also assessed. Validation involved RT-qPCR and immunohistochemistry (IHC). An in vitro H. pylori co-culture system was used to assess time-dependent changes in gene and protein expression via RT-qPCR, IHC, and Western blotting. A four-gene risk model (PDCD1, KYNU, CYTL1, and FZD2) was identified, demonstrating strong predictive capacity for overall survival as an independent prognostic factor. High-risk patients exhibited reduced immune cell infiltration. CellMiner analysis identified potential therapeutic agents targeting these genes. Among them, KYNU showed significant upregulation in GC tissues. Notably, in the co-culture system, KYNU expression markedly increased at both mRNA and protein levels following H. pylori infection in a time-dependent manner. The H. pylori-associated risk model represents a novel independent prognostic indicator for GC. Particularly, KYNU emerged as a pivotal gene in H. pylori-mediated GC, offering insights into disease progression and serving as a promising therapeutic target.

A Pre-atrial fibrillation (Pre-AF) status has been postulated to exist when there are structural or electrical findings predisposing to AF, but it is not well described in relation to prognosis. This prospective cohort study aims to sub-classify Pre-AF by structural, electrical and biomarker parameters and quantify associations with major adverse events. Prospective cohort study of individuals with high risk of developing AF (according to the FIND-AF risk score), who underwent echocardiographic, ECG and biomarker assessment. Pre-AF sub-classes were specified as follows: Pre-AF 1 (one of echocardiographic, ECG or biomarker parameters); Pre-AF 2 (two parameters); and Pre-AF 3 (three parameters). Individuals were followed up for a composite primary outcome of major adverse cardiovascular, cerebrovascular and cognitive events (incident AF, heart failure, ischaemic stroke/TIA, myocardial infarction, dementia or cardiovascular death). Of 254 participants (mean age 74.9 (+/- 5.8) years, 50% women), 82 (32.3%) were classified as Pre-AF 1, 90 (35.4%) as Pre-AF 2, and 82 (32.3%) as Pre-AF 3. Higher Pre-AF sub-class was associated with higher NT-pro BNP (84.0 ng/L vs 186.1 ng/L vs 558.2 ng/L, p<0.001) and larger left atrial volume (29.0 ml/m2 vs 39.8 ml/m2 vs 46.1 ml/m2, p < 0.001). Over a median follow-up of 24.4 months (IQR 19.6-26.3 months), the primary outcome was 23.2% (19/82) for Pre-AF 3, 11.1% (10/90) for Pre-AF 2 and 4.9% (4/82) for Pre-AF 1 (log-rank p = 0.002). Sub-classification of Pre-AF using ECG, echocardiography and NT-proBNP has prognostic implications but is not specifically associated with diagnosis of incident AF in routine care.

Nasopharyngeal carcinoma (NPC) represents a highly prevalent and aggressive malignancy endemic to Southeast Asia. Early and accurate diagnosis is critical to improving survival outcomes; however, the absence of robust, stage-specific biomarkers remains a key obstacle to clinical implementation of early screening strategies. We performed untargeted serum proteomic profiling using mass spectrometry in 15 treatment-na&#xef;ve early-stage NPC patients and 15 VCA-IgA-positive healthy controls. Bioinformatics analyses were conducted to identify differentially expressed proteins (DEPs). Machine learning (random forest combined with recursive feature elimination) was employed to prioritize candidate biomarkers, which were subsequently verified using enzyme-linked immunosorbent assay (ELISA) in independent sample cohorts. In total, 1,428 serum proteins were identified, among which 1,410 were reliably quantified. We observed 31 upregulated and 189 downregulated proteins in NPC patients relative to controls. Spearman correlation analysis revealed significant associations: LTA4H (leukotriene A4 hydrolase) levels correlated with serum cell infiltration (r&#x2009;=&#x2009;0.383, p&#x2009;=&#x2009;0.032) and CD8&#x2009;+&#x2009;T-cell abundance (r&#x2009;=&#x2009;0.408, p&#x2009;=&#x2009;0.021); both SULT1A3 (sulfotransferase family 1&#xa0;A member 3) and FGL1 (fibrinogen-like protein 1) levels were positively associated with M1 macrophage infiltration (r&#x2009;=&#x2009;0.510, p&#x2009;=&#x2009;0.003 and r&#x2009;=&#x2009;0.430, p&#x2009;=&#x2009;0.015, respectively). In a preliminary validation cohort (n&#x2009;=&#x2009;80), ELISA yielded AUC values of 0.631 (95% CI: 0.515-0.736, p&#x2009;=&#x2009;0.04) for LTA4H, 0.787 (95% CI: 0.681-0.871, p&#x2009;<&#x2009;0.001) for SULT1A3, and 0.688 (95% CI: 0.575-0.787, p&#x2009;=&#x2009;0.002) for FGL1. In large-scale independent validation, SULT1A3 achieved an AUC of 0.826 (95% CI: 0.766-0.876; sensitivity&#x2009;=&#x2009;78.89%, specificity&#x2009;=&#x2009;75.47%) in cohort 1 (n&#x2009;=&#x2009;196) and 0.796 (95% CI: 0.723-0.857; sensitivity&#x2009;=&#x2009;76.67%, specificity&#x2009;=&#x2009;76.67%) in cohort 2 (n&#x2009;=&#x2009;150). Through an integrated workflow combining proteomic screening, machine learning prioritization, and multi-stage ELISA validation, we identified SULT1A3 as a candidate serum-based biomarker for early detection of NPC. Preliminary findings suggest that SULT1A3 may have potential utility in clinical screening, though further validation in independent, multi&#x2011;center cohorts is required.

Despite promising outcomes in CAR T-cell therapy for relapsed/refractory multiple myeloma (RRMM), nearly all patients eventually relapse. Resistance and relapse may be driven by CAR T-cell and tumor-intrinsic factors. Here, we developed a mechanistic quantitative systems pharmacology (QSP) model of multiple myeloma growth and CAR T-cell therapy using measurable biomarkers to predict and identify factors associated with response and relapse. The model incorporates key components to explore disease dynamics and CAR T-cell expansion. Our model reproduced published pharmacokinetics and biomarker response data from anti-BCMA and anti-GPRC5D CAR T-cell therapies. We then validated the model using clinical biomarker data from a total of 29 real-world RRMM patients treated with commercial anti-BCMA CAR T. Virtual trial simulations, exploring the impact of variable baseline disease and CAR T characteristics on response, predicted that factors associated with worse outcomes are intrinsic to tumor cells (disease burden, low-antigen expression) and CAR T cells (low CAR T-induced killing rate). Interestingly, simulations suggested that a lower baseline percentage of normal plasma cells is associated with higher overall response. The developed model was also used to predict the outcome of BCMA-targeted and GPRC5D-targeted combination CAR T-cell treatment. Sequential combination therapy simulations predicted a better response in scenarios starting with anti-GPRC5D CAR T infusion, followed by anti-BCMA CAR T infusion. Our model can serve as a framework to investigate response mechanisms as well as multi-antigen targeting, and to optimize clinical trial design and dosing regimens.

Social surveys are increasingly incorporating DNA collection to unlock research opportunities in social and medical sciences. Saliva sampling is emerging as a common and practical method - particularly well-suited to self-completion surveys where interviewers or other trained professionals are not present. However, a number of methodological challenges in the collection of saliva samples remain unsolved. We analyse data from a cohort study of young adults in England: the Next Steps Age 32 survey to explore these methodological challenges. Approximately 57 per cent of eligible cohort members consented to provide a saliva sample and 27 per cent returned a sample to the laboratory, resulting in genotyped data for 24 per cent. Both consent and sample return were significantly associated with participant characteristics - such as white ethnicity - as well as survey-related factors, including engagement with study materials, prior wave participation and consent to health data linkage. Experimental evidence also indicates that higher monetary incentives (&#xa3;10 versus &#xa3;5) increased both consent rates (57.8 per cent versus 53 per cent) and sample returns (29.8 per cent versus 20.6 per cent). Analysis of non-consent reasons revealed that many responses were vague, while 26.9 per cent mentioned they were uncomfortable with the task, found it intrusive or expressed privacy concerns. We conclude with recommendations for improving biosample collection in survey practice. Our work contributes to the growing literature on integrating biomarker collection into large-scale, mixed-mode, multi-purpose social research.

The neutrophil to high-density lipoprotein cholesterol ratio (NHR) is emerging as a potential composite biomarker integrating aspects of inflammation and lipid metabolism in the context of acute ischemic stroke (AIS). However, its clinical utility remains uncertain due to limited and inconsistent evidence across studies. A comprehensive systematic search was conducted in PubMed, Embase, and the Cochrane Library up to September 2025 to identify studies examining the association between NHR and adverse outcomes or mortality in AIS patients. Heterogeneity among studies was evaluated through sensitivity and subgroup analyses, and potential publication bias was explored using Egger's test, recognizing the limited power due to the small number of included studies. A meta-analysis including 4,138 patients from five studies suggested a possible association between higher NHR and adverse outcomes in AIS (OR 1.89, 95% CI: 1.18-3.02; I&#xb2; = 82%), although substantial heterogeneity limits confidence in the pooled estimate. Sensitivity analyses yielded similar trends, but findings should be interpreted cautiously. Subgroup analyses indicated stronger associations for patients undergoing reperfusion therapy (OR 2.80, 95% CI: 1.79-4.38) and at 3-month follow-ups (OR 2.24, 95% CI: 1.51-3.32), while no significant associations were observed with conventional treatment or 1-month follow-ups. The pooled area under the curve (AUC) was 0.63, reflecting limited predictive performance. Only a single study examined mortality, reporting no significant association with NHR (OR 1.5; 95% CI: 0.47-4.74). Elevated NHR is associated with adverse outcomes in AIS, supporting its potential as a prognostic biomarker. However, evidence for mortality prediction is limited, and further prospective studies are needed.

The upper frequency limit of human brain activity remains unknown. Using ultrahigh sampling rate (&#x2265;20&#x2009;kHz) intracranial microelectroencephalography, this study aimed to systematically explore and quantitatively characterize brain field oscillations beyond the established high-frequency oscillation range (>2&#x2009;kHz), and to determine their relationship to epileptogenic tissue. We analyzed intracranial electroencephalographic recordings from 15 patients with drug-resistant epilepsy, comprising 466 microcontacts and 434 macrocontacts implanted in mesiotemporal structures across four international epilepsy centers. A custom spectrogram-based detector optimized for ultrahigh frequencies was developed to identify ultrafast oscillations (UFOs; >2&#x2009;kHz). UFO rates were assessed in epileptic (successfully resected) and nonepileptic hippocampi and compared with established electrophysiological biomarkers, including interictal epileptiform discharges, ripples, and fast ripples. Statistical comparisons were performed using mixed-effects models to account for intersubject and interelectrode variability. We identified a previously undescribed class of short-duration oscillatory events spanning 2-8&#x2009;kHz. UFOs occurred at significantly higher rates in epileptic compared with nonepileptic mesiotemporal regions, with the strongest differentiation observed in the 2-3-kHz band. Two distinct UFO phenotypes were consistently observed: (1) spindlelike, narrow-band oscillations and (2) sharp-onset, rapidly decaying bursts. Both forms were prevalent within epileptic hippocampi but were exceedingly rare in nonepileptic structures. UFOs exhibited pronounced temporal intermittency and spatial focality and frequently arose independently of ripples, fast ripples, and very high-frequency oscillations, indicating that they represent a distinct electrophysiological phenomenon. Macrocontacts detected UFOs only exceptionally, highlighting the necessity of microelectrode recordings to capture activity in this ultrahigh-frequency regime. These findings substantially extend the known frequency range of human brain field activity and identify ultrafast oscillations as a novel biomarker of neuronal hyperexcitability. UFOs likely reflect pathological microcircuit dynamics inaccessible to conventional clinical recordings and provide new insights into the organization and pathophysiology of epileptogenic networks.

In a first-in-human trial (NI006-101), the monoclonal antibody cliramitug, targeting misfolded transthyretin, demonstrated a favorable safety profile and time- and dose-dependent reductions in surrogate markers of cardiac amyloid burden over the course of 12 months in patients with amyloid transthyretin cardiomyopathy (ATTR-CM). Here we evaluate the long-term safety and efficacy of cliramitug in a subgroup of participants of the NI006-101 trial who continued treatment in a second open-label extension (OLE2) and further explore dose- and time-dependent effects on amyloid depletion, cardiac biomarkers and cardiac structure and function. Twenty-three participants (20 receiving background treatment with tafamidis, all male) entered OLE2 and received a median of 10 additional infusions, increasing the maximum total exposure to 24 infusions and extending the median follow-up to 29.3 months. Thirteen participants initially treated with &#x2264;10&#x2009;mg kg-1 were up-titrated to 30&#x2009;mg kg-1 during OLE2. Treatment adherence was high (98%), with no treatment-related serious adverse events or discontinuations. Continued treatment and up-titration in participants with lower prior exposure led to further reductions in cardiac extracellular volume on MRI and tracer uptake on bisphosphonate scintigraphy. Improvements were also observed in NT-proBNP and troponin T levels, left ventricular relaxation, filling pressures and wall thickness. Increases in Kansas City Cardiomyopathy Questionnaire scores suggested potential quality-of-life benefits. Consistent with results from the original trial, cliramitug showed favorable long-term safety and further reductions in cardiac amyloid burden following up-titration to 30&#x2009;mg kg-1. These time- and dose-dependent improvements across structural, functional and biomarker endpoints support the therapeutic potential of amyloid-depleting therapy with cliramitug in ATTR-CM. ClinicalTrials.gov: NCT04360434 .