Citations

Abstract INTRODUCTION Plasma phosphorylated tau at threonine 217 (p‐tau217) has emerged as one of the most promising blood‐based biomarkers for Alzheimer's disease (AD). While rare, heterophilic antibodies (HAb) are a persistent potential confounding factor in immunoassays. METHODS Potential HAb interference in the Lumipulse G pTau217 assay in samples exhibiting concentrations > 10 pg/mL were investigated. Samples were subjected to HAb blocking reagent (HBT), and in some cases, polyethylene glycol (PEG) precipitation and serial dilutions. RESULTS In 14 of the 15 suspected HAb cases, HBT treatment greatly reduced measured p‐tau217 concentrations. and in one of three specimens selected for further investigation, reduced Aβ42 concentrations PEG precipitation in the three selected samples also reduced p‐tau217 concentrations, while serial dilution yielded mixed effects. Control specimens were unaffected by sample treatment or dilutions. DISCUSSION HAb may result in falsely elevated p‐tau217 and p‐tau217/Aβ42 ratio. HAb interference should be considered in cases of unusually high p‐tau217 concentrations prior to clinical interpretation. Highlights Potential heterophile antibody (HAb) interference in the Lumipulse p‐tau217 immunoassay was investigated. Investigation was performed using HAb blocking reagent, and in some cases also using PEG precipitation . Patients with p‐tau217 concentrations > 10 pg/mL exhibited positive HAb interference in 14 of 15 cases. HAb interference can lead to falsely positive p‐tau217/Aβ42 ratios.

Parkinson’s Disease (PD) is a neurodegenerative disorder in which gait abnormalities serve as key indicators of motor impairment and disease progression. Although wearable sensor-based gait analysis has advanced, existing methods still face challenges in modeling multi-sensor spatial relationships, extracting adaptive multi-scale temporal features, and effectively integrating time–frequency information. To address these issues, this paper proposes a multi-sensor gait neural network that integrates biomechanical priors with time–frequency collaborative learning for the automatic assessment of PD gait severity. The framework consists of three core modules: (1) BGS-GAT (Biomechanics-Guided Graph Attention Network), which constructs a sensor graph based on plantar anatomy and explicitly models inter-regional force dependencies via graph attention; (2) AMS-Inception1D (Adaptive Multi-Scale Inception-1D), which employs dilated convolutions and channel attention to extract multi-scale temporal features adaptively; and (3) TF-Branch (Time–Frequency Branch), which applies Real-valued Fast Fourier Transform (RFFT) and frequency-domain convolution to capture rhythmic and high-frequency components, enabling complementary time–frequency representation. Experiments on the PhysioNet multi-channel foot pressure dataset demonstrate that the proposed model achieves 0.930 in accuracy and 0.925 in F1-score for four-class severity classification, outperforming state-of-the-art deep learning models.

Abstract Rapid and profound reduction of free light chains (FLCs) improves outcomes in AL amyloidosis; however, early FLC kinetics with daratumumab‐based frontline therapy remain undefined. We retrospectively analyzed 315 patients treated with daratumumab–bortezomib–cyclophosphamide–dexamethasone (Dara–VCd) or Dara–Vd at eight centers. Involved FLC (iFLC), the difference between iFLC and uninvolved FLC (dFLC), and hematologic response (≥very good partial response [VGPR]) were assessed at baseline and at 1, 3, and 6 months, and correlated with light chain isotype, disease burden (bone‐marrow plasma‐cell percentage [%BMPC], baseline dFLC), and cytogenetics. Hematological ≥VGPR increased from 49.8% at 1 month to 66.0% at 3 months. The kappa isotype showed slower responses, with higher iFLC/dFLC and lower ≥VGPR at each time point compared to lambda. Higher %BMPC or baseline dFLC predicted persistently elevated iFLC/dFLC and reduced ≥VGPR. The t(11;14) translocation was associated with lower baseline FLC but similar subsequent kinetics. BMPC < 10% and dFLC < 18 mg/dL independently predicted early ≥VGPR (in ≤1 month). Early ≥VGPR conferred superior hematologic event‐free survival (heme‐EFS) and overall survival (OS) versus later responders (P < 0.001). At a 3‐month landmark, achieving dFLC < 1 mg/dL further stratified prognosis, conferring longer heme‐EFS and OS (P < 0.01). Frontline Dara‐based therapy elicits rapid, deep responses in AL amyloidosis; early ≥VGPR (within 1 month) and dFLC < 1 mg/dL by 3 months predict durable EFS and OS, whereas higher baseline disease burden delays hematologic response.

Abstract Variants in the cystic fibrosis transmembrane conductance regulator ( CFTR ) gene, which causes cystic fibrosis, have become increasingly well‐characterized in recent decades. However, clinicians remain challenged by CFTR variants that result in variable expressivity and reduced penetrance, including the variant R117H (c.350G>A) and the intron 9 poly‐thymidine (poly‐T) and poly‐thymidine‐guanosine (TG) tracts, highlighting a knowledge gap that impacts the delivery of accurate information to patients and families. To address this gap, we developed an educational resource that provides descriptive likelihoods of specific phenotypes that may result from genotypes including R117H and the poly‐T and TG tracts. Development of the resource was grounded in an extensive literature review, clinical expertise, and publicly available CFTR variant databases, with feedback incorporated from CF clinicians, genetic counselors, and CF content experts. Genotypes were determined to have very low, low, moderate, high, or very high likelihood of resulting in CF, CFTR‐related disorder (CFTR‐RD), no symptoms, or the designation of CFTR‐related metabolic syndrome/CF‐screen positive, inconclusive diagnosis (CRMS/CFSPID) following CF newborn screening. The resource described in this report is intended to help clinicians navigate the uncertainty surrounding potential diagnostic scenarios to present accurate assessments to patients and families, a critical component of CF genetic testing and counseling.

ABSTRACT Background Sampling techniques have poor accuracy for classifying biliary strictures as benign or malignant. Previously, a cholangioscopy artificial intelligence (AI) outperfromed sampling techniques based solely on analysis of previously recorded cholangioscopy footage. The aim of this trial was to compare the performance of a real-time cholangioscopy AI to both sampling techniques and human observers for the task of biliary stricture classification. Methods A cholangioscopy AI computer connected directly to a cholangioscope console. The computer analyzed the cholangioscopy video stream during procedures for suspected biliary strictures. The primary outcome of the study was comparison of the performance of cholangioscopy AI to sampling techniques – brush cytology and transpapillary forceps biopsy – for biliary stricture classification. Secondary outcomes included comparison of the AI classification performance to that of human observers (separated into junior-level and experienced-level cohorts) who reviewed the cholangioscopy footage. Results A total of 41 patients were enrolled in the trial and had biliary strictures analyzed by cholangioscopy AI. For the classification of strictures, the AI had greater classification accuracy than standard sampling techniques (87.8% versus 67.4%; p = 0.043). Additionally, the cholangioscopy AI was significantly more accurate for biliary stricture classification than both junior-level (87.8% versus 61.5%; p = 0.001) and experienced endoscopists (87.8% versus 63.15%; p = 0.011). Conclusions This trial demonstrates that sampling techniques and human assessment of biliary strictures are flawed and there may be a benefit to the use of a cholangioscopy AI system to aid in biliary stricture classification.

Abstract Microglia are essential for maintaining brain homeostasis, including the sleep-wake cycle, but the underlying mechanisms remain unclear. Here, using in vivo two-photon imaging in both head-fixed and freely moving mice with simultaneous electroencephalogram–electromyogram (EEG–EMG) recording, we investigated microglial process dynamics and their interactions with locus coeruleus (LC) noradrenergic (NE) axons in the frontal cortex across sleep-wake states. During sleep or chemogenetic suppression of LC neurons, microglia enhanced their surveillance and increased interactions with NE axons. Correlative electron microscopy at nanometer resolution identified structural contacts between microglial process endings and NE boutons. Mechanistically, microglia-bouton interaction is primed by NE–β2-adrenergic receptor (β2AR) signaling, leading to enhanced Ca²⁺ activity in NE axons. These findings suggest that microglial interactions with NE axons promote cortical norepinephrine transmission and maintain stable wakefulness.

Abstract Background and Aims Celiac disease (CeD) is a chronic digestive autoimmune disorder affecting approximately 1% of the worldwide population. It is driven by T cells activated by specific HLA-DQ2 or HLA-DQ8 molecules leading to the destruction of intestinal villi. We aimed to characterize shared CeD-specific T cells in patients on and off a gluten-free diet (GFD) from a large cohort of cases and controls. Methods We performed bulk TCRβ immune sequencing of the peripheral blood of 1,604 biopsy-confirmed CeD patients (1,339 on GFD, 265 on normal diet) and 1,100 controls. We identified over 300 TCRβs enriched in CeD cases versus controls in an HLA-aware manner, controlling for CeD risk alleles. Results CeD-associated TCRβs were found to be more predictive of disease than previously characterized gliadin and glutenin-binding TCRs in a validation cohort. Furthermore, the clonal breadth of these TCRβs was associated with increased intestinal damage. Immune sequencing of the peripheral blood also uncovered repertoire-level differences between CeD patients and controls. CeD patients displayed significantly higher productive clonality compared to age-matched controls as well as expansion of TCRβs specific to cytomegalovirus (CMV) and Epstein-Barr Virus (EBV). Conclusions These findings underscore the value of unbiased immune repertoire sequencing to identify novel biomarkers for autoimmune disease and to discover new disease mechanisms which can improve both diagnosis and treatment of disease.

Abstract Pick’s disease (PiD) is a rare cause of sporadic frontotemporal dementia, neuropathologically defined by the presence of Pick bodies consisting of aggregates of 3-repeat tau. Given the genetic aetiology of PiD remains unresolved, we assembled the Pick’s disease International Consortium (PIC) to identify susceptibility loci through a genome-wide association study (GWAS). A GWAS was conducted in 294 autopsy confirmed PiD cases and 1,055 controls. Lead variants were annotated using the Functional Mapping and Annotation of GWAS (FUMA) platform, followed by co-localisation analyses using the METABRAIN dataset and statistical finemapping using FINEMAP and SuSiE. After exclusion of 3 cases of MAPT mutations, no variants were associated with risk of PiD at genome-wide significance ( p < 5 × 10 -8 ). The strongest association was on chromosome 4 (4p13, lead SNP rs112161979, OR = 7.53, 95% Confidence Interval (CI) = 3.62-15.65, p = 6.37 × 10 -8 ) followed by chromosome 11 (11p15.4, lead SNP rs66481907, OR = 2.10, 95% CI = 1.54-2.84, p = 1.83 × 10 -6 ). rs112161979 is an intronic SNP in the KCDT8 gene, encoding a potassium channel tetramerization domain that acts as an auxiliary subunit for GABA B receptors, whilst rs66481907 is an intronic SNP in TRIM22 , encoding an E3 ubiquitin-protein ligase. Our GWAS provides the first evidence of possible genetic risk for PiD that implicate the modulation of GABA B receptor signalling and inflammation, in disease pathogenesis. Replication of these findings will be important, but our results suggest that, if present, the genetic risk of PiD beyond MAPT mutations is low.

ABSTRACT Introduction Metabolic dysfunction‐associated steatotic liver disease (MASLD) and steatohepatitis (MASH) represent a spectrum of liver conditions that can gradually progress to cirrhosis. Sodium‐glucose co‐transporter‐2 (SGLT‐2) inhibitors have shown benefits in reducing hepatic steatosis and liver‐related events in MASLD. This study aims to assess whether SGLT‐2 inhibitors are associated with a reduced risk of all‐cause mortality and disease‐specific outcomes in patients with MASH cirrhosis and type 2 diabetes (T2D). Methods A retrospective cohort study was performed using TriNetX. Patients with T2D and MASH cirrhosis on SGLT‐2 inhibitors were matched 1:1 with other glucose‐lowering drugs (oGLDs) based on demographics, comorbidities and medications. Primary outcomes included all‐cause mortality, hepatic decompensation and major adverse liver outcomes (MALO). Cox‐proportional hazards models were used to estimate hazard ratios (HRs) with 95% confidence interval (CI). Results A total of 51 427 patients with MASH cirrhosis and T2D were identified, of which 6833 (13.28%) were on SGLT‐2 inhibitors. Patients on SGLT‐2 inhibitors ( n = 6449, mean age 63.7 years, 52.9% female) were matched with 6449 individuals (mean age 63.9 years, 53.5% female) on oGLDs. The SGLT‐2 inhibitors cohort had statistically significantly lower risk of all‐cause mortality (HR: 0.58, 95% CI: 0.53–0.63), hepatic decompensation (HR: 0.85, 95% CI: 0.81–0.90) and MALO (HR: 0.88, 95% CI: 0.83–0.93). Conclusion SGLT‐2 inhibitors are associated with a reduced risk of all‐cause mortality in patients with MASH cirrhosis and T2DM, which may be partly attributable to a lower risk of hepatic decompensation and subsequent events. Further studies are warranted as SGLT‐2 inhibitors may serve as an adjunctive therapy for patients with MASH cirrhosis.