Frontiers in Molecular Biosciences

This study aimed to evaluate the prognostic value of quantitative analysis of {superscript 1}F-FDG positron emission tomography (PET)/computed tomography (CT) metabolic parameters in patients with pancreatic ductal adenocarcinoma (PDAC) after neoadjuvant chemotherapy (NACT). A retrospective analysis was conducted on the clinical and imaging data of 44 patients with pathologically confirmed PDAC who received NACT. All patients completed standard chemotherapy regimens and underwent {superscript 1}F-FDG PET/CT examinations within 2 weeks before and after chemotherapy. Multiple metabolic parameters of lesions were extracted, their percentage changes were calculated, and the optimal cut-off values for each parameter were determined. Kaplan-Meier survival analysis and Cox proportional hazards regression analysis were applied to explore the prognostic value of the metabolic parameters, and the prognostic stratification performance of PET Response Criteria in Solid Tumors (PERCIST) 1.0 was compared with that of Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. PERCIST 1.0 demonstrated significantly superior prognostic stratification compared with RECIST 1.1. A peak standardized uptake value corrected for lean body mass (SULpeak2) > 3.07 and a percentage change in SULpeak between pre- and post-treatment scans ({Delta}SULpeak%) [≤] 37.66% were identified as independent risk factors for poor prognosis. Furthermore, SUL-related parameters exhibited markedly better predictive efficacy than traditional metabolic parameters such as the standardized uptake value and metabolic tumor volume. Quantitative analysis of {superscript 1}F-FDG PET/CT metabolic parameters can effectively predict prognosis in PDAC after NACT, and PERCIST 1.0 is a more optimal criterion for efficacy and prognostic assessment. A post-NACT SULpeak > 3.07 and {Delta}SULpeak% [≤] 37.66% were core independent indicators for predicting poor prognosis in these patients.

BackgroundCYFRA 21-1, a cytokeratin-19 fragment, is a validated serum biomarker for non-small cell lung cancer (NSCLC). However, most studies rely on single time-point measurements, limiting its specificity in differentiating malignancy from benign pulmonary conditions. Inspired by the clinical utility of serial PSA measurements in prostate cancer, we investigated whether longitudinal trends in CYFRA 21-1 could enhance diagnostic and monitoring capabilities in patients with pulmonary nodules Methods and FindingsWe analyzed 132 patients with pulmonary nodules, including 41 with lung cancer and 91 with benign diagnoses. CYFRA 21-1 levels were measured serially using electrochemiluminescence assays. Longitudinal trends were assessed using linear mixed-effects models to estimate biomarker trajectories. Subgroup analyses examined differences between benign, untreated cancer, and post-treatment cancer groups, as well as within-patient changes in a subset of 16 cancer patients with both pre- and post-surgical measurements. Log-transformed data were used for the analysis. At baseline, CYFRA 21-1 levels were significantly higher in malignant versus benign nodules. Over time, CYFRA trajectories diverged: benign cases showed slight increases, whereas cancer patients exhibited greater biomarker volatility. In treated cancer patients, trend of CYFRA levels on the natural log scale decline from -0.00137 pre-surgery to - 0.00263 to post-surgery, and both cancer groups showed significantly higher absolute slopes than the benign group (p < 0.05). While pre- vs post-treatment slope differences did not reach significance (p = 0.211), the general pattern indicated that CYFRA 21-1 is a dynamic marker responsive to tumor presence and removal. ConclusionsCYFRA 21-1 exhibits substantial within-patient variability over time, with trajectories that reflect disease state and treatment. These findings suggest that longitudinal monitoring of CYFRA 21-1--analogous to PSA velocity in prostate cancer-- may offer improved diagnostic and prognostic insight in the evaluation of pulmonary nodules. Further studies in larger cohorts are warranted to validate these findings and explore clinical implementation of CYFRA trajectory analysis.

Molecular Tumour Boards (MTBs) rely on different bioinformatics tools and knowledgebases for variant annotation, oncogenicity classification, and estimation of complex biomarkers to identify actionable alterations. However, the typical bioinformatics workflow to process raw next-generation sequencing (NGS) data into clinically meaningful variants involves multiple steps and is inherently complex, thus requiring repeated manual intervention and causing delays in providing molecularly informed precision oncology. Here, we aimed at overcoming these limitations by developing a fully-automated integrative workflow to support NGS-based analyses within MTBs. Our workflow was established at the Institute of Pathology, University Hospital Erlangen (Germany), and adapted to the fully digitized Pathology department at Gravina Hospital in Caltagirone (Italy), using the Illumina TruSight Oncology 500 HRD assay as case study. A trigger event initiates all the downstream bioinformatics analyses to support variant interpretation. In Erlangen, the trigger event is the automatic detection of new NGS data on the Illumina Connected Analytics cloud-based platform. In Caltagirone, the analyses are manually triggered from the anatomic pathology laboratory information system (AP-LIS). The workflow automatically: (i) generates an intuitive overview of sequencing quality metrics, (ii) performs variant annotation, (iii) classifies variant oncogenicity through a fully-automated implementation of the ClinGen/CGC/VICC guidelines, and (iv) generates homologous recombination deficiency scores with genomic instability plots. In the digitized pathology department, results can be readily opened from the AP-LIS and visualized in the patient gallery. Taken together, our end-to-end fully-automated workflow streamlines NGS-based analyses within MTBs by integrating variant interpretation, oncogenicity classification, and estimation of clinically relevant biomarkers.

Hereditary ataxias are complicated neurological disorders with enormous genetic heterogeneity as well as the diverse genetic mechanism. Among different genetic mechanism, tandem nucleotide repeat expansion (TNRex) are the most common cause for genetic ataxias followed by single nucleotide variations in over 200 genes. The detection and the diagnosis of tandem nucleotide repeats in clinics and laboratories has been at large common in comparison with SNVs owing to the large number of the mutations in the respective genes they are found. The widely used platforms for detection of these mutations are capillary electrophoresis and Next generation sequencing based targeted gene panel or clinical or whole exome sequencing. Long read sequencers have been proven useful for detection of tandem nucleotide repeat expansions. We have evolved a method to detect in one experiment and on single platform the detection of TNRex and SNVs on Oxford Nanopre Technology using adaptive sequencing approach. We were able to optimize the target region sequencing of both TNR loci and SNV-loci and validate the capture of both by detection of FXN-GAA repeats and pathogenic SNVs in SETX

BackgroundInterstitial lung diseases (ILDs), including idiopathic pulmonary fibrosis (IPF) and connective tissue disease-associated ILD (CTD-ILD), share similar features that complicate diagnosis. Tumor markers are often elevated in ILD, yet their diagnostic utility remains unclear. MethodsThis retrospective study included ILD patients hospitalized between 2018 and 2025. Serum levels of alpha-fetoprotein, carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 199, CA125, CA153, neuron-specific enolase (NSE), and cytokeratin 19 fragment (CYFRA 21-1) were analyzed. Arterial blood gases and erythrocyte sedimentation rates (ESRs) were also collected. Statistical analyses involved the Kruskal-Wallis test, Dunns post hoc test, Spearmans correlation, logistic regression, and receiver operating characteristic (ROC) curve analysis. ResultsCEA, CA199, and CA125 levels varied significantly among ILD subtypes (all p < 0.05). NSE differed among CTD-ILD subgroups (p = 0.0409). In IPF, CEA and NSE correlated inversely with PaO2 (r = -0.1556, p = 0.0380; r = -0.2205, p = 0.0031). In CTD-ILD, NSE correlated negatively with PaCO2 (r = -0.1811, p = 0.016), and CYFRA 21-1 with PaO2 (r = -0.1999, p = 0.0078). A diagnostic model incorporating CEA, CA199, sex, age, smoking, PaO2, and ESR differentiated IPF from CTD-ILD with an AUC of 0.833 (95% CI: 0.790-0.876), showing 73.6% sensitivity and 82.4% specificity at a cutoff of 0.569, outperforming single markers. ConclusionCEA, CA199, and CA125 aid in distinguishing ILD subtypes, while CEA, NSE, and CYFRA 21-1 correlate with impaired gas exchange. The combined clinical and biomarker model demonstrated superior performance in discriminating IPF from CTD-ILD, highlighting its clinical potential.

Background and AimsCholedocholithiasis (CDL) is a common condition that can lead to serious complications, requiring effective risk stratification for timely intervention. While current guidelines use clinical predictors, imaging, and laboratory markers for risk assessment, the role of glutamate dehydrogenase (GLDH) in CDL remains poorly understood. This study aims to evaluate its potential as a clinical biomarker for identifying patients with CDL. MethodsThis single-center cohort study identified 23,103 patients who presented to the emergency department of the University Medical Center Hamburg-Eppendorf and underwent routine abdominal laboratory testing between May 2021 and December 2023. Patients were classified into CDL and other diagnoses. To assess the predictive value of age, sex and laboratory markers for CDL, we developed a random forest machine learning model, conducted a backward stepwise logistic regression and performed receiver operating characteristic (ROC) analysis. Results152 patients were diagnosed with CDL and 22,951 with other diagnoses. In the random forest machine learning model, GLDH emerged as the most significant feature for predicting CDL. ROC analysis revealed that GLDH had the highest area under the curve of 0.93 among laboratory markers. At the upper limit of normal, GLDH demonstrated the best sensitivity (92%) compared to aspartate aminotransferase (AST), alanine aminotransferase (ALT) and bilirubin. High GLDH levels exceeding 150 U/L demonstrate the highest specificity (99%) for CDL, outperforming AST, ALT and bilirubin. ConclusionGLDH outperforms AST, ALT and bilirubin as a screening and predictive marker for CDL, supporting its inclusion in clinical guidelines for risk stratification.

This study investigates the efficacy of transformer-based deep learning architectures--specifically, Vision Transformer (ViT), Class Attention in Image Transformers (CaiT), and Data-Efficient Image Transformers (DeiT)--for the binary classification of colorectal polyps using the Minimalist Histopathology Image Analysis Dataset (MHIST). The dataset comprises 3,152 hematoxylin and eosin (H&E)-stained Formalin Fixed Paraffin-Embedded (FFPE) images annotated as either Hyperplastic Polyps (HP) or Sessile Serrated Adenomas (SSA). A rigorous evaluation was conducted using a 5-fold stratified cross-validation methodology, and performance was quantified using metrics including accuracy, precision, recall, F1-score, and AUC-ROC. Experimental results revealed that transformer architectures, particularly CaiT (accuracy of 90.18%, AUC-ROC of 95.52%), outperformed traditional convolutional neural networks (CNNs). The superior performance of CaiT is attributed to its specialized class-attention mechanisms, effectively capturing nuanced morphological differences essential for accurate histopathological classification. These findings underscore the potential of transformer-based models to enhance diagnostic precision, reduce variability in pathological assessment, and facilitate earlier and more reliable colorectal cancer screening.

The ERS/ATS22 interpretative flowchart classifies diffusing capacity (DLco) into 5 scenarios with associated pathophysiology, and has not been tested on large patient groups. We aimed to obtain a more layered DLco interpretation, by interrogating DLco components Kco and VA, and by estimating lung inflation during the DLco test to identify the presence of restriction, which crucially impacts Kco interpretation. By assessing a "low VA" against lung inflation, a novel 9-scenario DLco classification with associated pathophysiology can be obtained. Lung patients from a tertiary center were classified according to the ERS/ATS22 chart and the novel 9-scenario one. Besides a control group of healthy subjects (n=303), disease groups under study were the following : asthma (n=1615), COPD (n=1338), CF (n=108), extrapulmonary restriction (n=122), ILD (n=98), post-COVID (n=193). Except for COPD, the prevalence of "normal DLco" (ERS/ATS22) was generally greater than that of "normal VA and normal Kco" (9-scenario); this discrepancy was most marked in CF (81% vs 56%) and in extrapulmonary restriction (57% vs 37%). With the novel 9-scenario chart, patients from very different diagnostic groups with a "low DLco" due to emphysema, bronchial disease, interstitial damage or incomplete expansion got classified across distinct scenarios, whereas ERS/ATS22 just grouped them together. In conclusion, when "low VA" is evaluated against lung inflation, a differentiation of DLco interpretation can be obtained in various patient groups involving obstruction and/or restriction. This approach can be readily implemented in clinical practice.

ObjectiveTo explore the application value of dual-staining for specific AT sequence binding protein 2 (SATB2) immunohistochemistry and elastic lamina in detecting elastic lamina invasion (ELI) in pT3 colon cancer, and to assess its association with clinicopathological characteristics, staging, and prognosis. MethodsThis retrospective cohort study enrolled 176 pT3 colon cancer patients who underwent radical resection at Affiliated Jinhua Hospital Zhejiang University School of Medicine. The deepest tumor-infiltrated paraffin blocks were collected for SATB2 immunohistochemistry and elastin dual-staining. Correlations between ELI status and clinicopathological characteristics and prognosis were analyzed. Survival data of 74 pT4a stage patients were collected for comparative analysis. ResultsELI (+) was positively associated with high tumor budding grade, vascular invasion, lymph node metastasis, and reduced tumor infiltrating lymphocytes (TILs) (all P < 0.001). No correlations were observed with age, gender, tumor location, histological subtype, tumor grade, or perineural invasion (all P > 0.05). The ELI (+) group exhibited significantly shorter disease-free survival (DFS) and overall survival (OS) compared to ELI (-) group (P < 0.05). Additionally, the ELI (+) group demonstrated inferior OS than the pT4a group, though DFS did not differ significantly. ConclusionDual-staining of SATB2 immunohistochemistry and elastic lamina provides a reproducible and objective method for assessing ELI. ELI correlates with key clinicopathological features and functions as an independent adverse prognostic indicator in pT3 colon cancer.

Background and AimThe optimal second-line therapy following first-line atezolizumab plus bevacizumab (Atezo/Beva) remains unascertained. This study compared second-line durvalumab plus tremelimumab (Dur/Tre) with lenvatinib (Len) after first-line Atezo/Beva in unresectable hepatocellular carcinoma (uHCC). MethodsThis prospectively registered cohort study analyzed patients with uHCC who received Dur/Tre (n = 14) or Len (n = 67) as second-line therapy after first-line Atezo/Beva. Tumor response was assessed by RECIST version 1.1. Progression-free survival (PFS), overall survival (OS), adverse events (AEs), and changes in the albumin-bilirubin (ALBI) score were compared. ResultsThe objective response rate and disease control rate were 7.7% and 15.4% in the Dur/Tre group, and 23.3% and 76.7% in the Len group, respectively; median PFS was 1.7 vs. 4.2 months (p < 0.001) and median OS was 5.3 vs. 14.0 months (p = 0.047) in the Dur/Tre and Len groups, both significantly favoring Len. Multivariable analysis showed that Len treatment and neutrophil-to-lymphocyte ratio [&ge;]3 were independent predictors of longer PFS and worse OS, respectively. Grade [&ge;]3 AEs were more frequent with Len than with Dur/Tre (70.1% vs. 21.4%; p = 0.002). At week 4, the ALBI score did not worsen with Dur/Tre (-2.30 to -2.21; p = 0.318) but worsened with Len (-2.36 to -1.97; p < 0.001). ConclusionsAfter first-line Atezo/Beva, second-line Len achieved superior disease control and longer survival than Dur/Tre. However, grade [&ge;] 3 AEs were more frequent with Len than with Dur/Tre, and careful management of AEs is essential when choosing therapy for individual patients.

BackgroundSome pancreatic cancer patients for curative-intent surgery are found to actually have unresectable disease on laparotomy. This systematic review aimed to identify parameters that can potentially help predict intraoperative resectability status. MethodsLiterature search was done across PubMed, Scopus, Web of Science, and Cochrane Library to identify studies since 2011 assessing for independent association of preoperative parameters with intraoperative pancreatic cancer resectability. Parameters investigated by at least two studies were identified. For discordant findings, meta-analyses using the random effects model were done, incorporating studies that can be pooled. Pooled odds ratios and mean differences were obtained for parameters with binary and continuous values, respectively, with 95% confidence intervals. Subgroup analyses were done for significant heterogeneity. ResultsFrom initially 8,959 articles searched, 18 studies were included, with 13 parameters identified for synthesis. Elevated serum CA19-9 (>35-1000 U/mL) and larger tumor size (>22-40 mm) were shown to independently predict intraoperative unresectability in the most number of studies. For parameters subjected to meta-analyses, abdominal pain, weight loss, lower body mass index (BMI), lower serum transaminases, and preoperative borderline resectability were significantly associated with intraoperative unresectability, while age and sex were not. Subgroup analyses addressing heterogeneity revealed that tumor location in the pancreatic body/tail is significantly associated with actual unresectability whereas poorer performance status was not. Other parameters shown to have predictive value but could not be included in meta-analyses are serum CA125 and imaging-to-surgery time interval. ConclusionSynthesis of studies has shown that elevated serum CA19-9 and larger tumors are independently associated with intraoperative pancreatic cancer unresectability. Other predictive factors include abdominal pain, weight loss, lower BMI, lower serum transaminases, preoperative borderline resectability, and tumor location in the pancreatic body/tail. Staging laparoscopy or neoadjuvant therapy should be considered for potentially resectable pancreatic cancer patients with these attributes. What is already known on this topicAccurate identification of patients with actual resectable pancreatic cancer remains challenging despite resectability criteria. Some parameters beyond resectability criteria have been found to offer clues regarding actual resectability. What this study addsSynthesis of studies has determined which clinical, laboratory, and radiologic parameters outside of resectability criteria may predict intraoperative resectability among pancreatic cancer patients being considered for curative-intent surgery. How this study might affect research, practice, or policyThe findings in this study may aid in deciding which pancreatic cancer patients should undergo staging laparoscopy first instead of directly attempting curative surgery. Research gaps have also been identified.

BackgroundBronchiectasis is a debilitating respiratory condition characterized by chronic cough with expectoration of thick sputum. It accounts for significant morbidity and mortality, especially when associated with exacerbations. Assessing the health-related quality of life (HR-QoL) of patients with bronchiectasis is important to ascertain the impact of the disease on day-to-day life, as well as to gauge the effect of targeted interventions. Conventionally used methods for assessing HR-QoL such as the St. Georges Respiratory Questionnaire (SGRQ) are time-consuming and have limitations in day-to-day application. The Bronchiectasis Health Questionnaire (BHQ) is a novel, compact tool used for assessing the HR-QoL, and has been validated for use in Korean and Turkish populations. MethodsWe attempted to develop and validate the Hindi version of the Bronchiectasis Health Questionnaire (BHQ) in Indian adults with bronchiectasis. We assessed the correlation between the Hindi BHQ (H-BHQ) scores and other measures of lung health including the Hindi version of the COPD Assessment Tool (H-CAT), pulmonary function tests and the bronchiectasis severity index (BSI). In addition, we assessed the correlation between the H-BHQ scores and the number of exacerbations and hospital admissions in the previous year. ResultsA total of 145 subjects with bronchiectasis were included. The mean ({+/-} SD) H-BHQ total score was 49.10 {+/-} 10.3. The H-BHQ score correlated well with the H-CAT score (Correlation coefficient -0.6534, p value < 0.0001) and the mMRC scale (Correlation coefficient of -0.4459,p value < 0.0001). The H-BHQ score also had a moderate correlation with the number of exacerbations and low correlation with hospital admissions in the previous year, with correlation coefficients of -0.4193 (p < 0.0001) and -0.3030 (p < 0.0001), respectively. The correlation between the H-BHQ and the Bronchiectasis Severity Index (BSI) score was weak (Correlation coefficient of -0.3012, p value < 0.01). ConclusionThe H-BHQ offers a simple and convenient method to assess the HR-QoL in patients with bronchiectasis, and correlates well with other measures of respiratory health, including the H-CAT, the mMRC score and the number of exacerbations and hospital admissions in the previous year.

Neuronal intranuclear inclusion disease (NIID) is a neurodegenerative condition characterized by the presence of intranuclear inclusions in neuronal and visceral cells. Patients with NIID can present respiratory symptoms; however, data on pulmonary functions in NIID are lacking. This study investigated the respiratory conditions in NIID patients diagnosed with histopathological and genetic studies. We conducted two spirometries before and after administrating the bronchodilator in NIID patients with asthmatic histories or symptoms. We statistically compared pre- and post-measured values including forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and peak expiratory flow (PEF). Before two spirometries, we also measured fractional concentration of exhaled nitric oxide (FeNO), if possible. Of the 51finally enrolled patients, 17 (33.3%, 95% CI 20.8% to 47.9%) patients had asthmatic histories or symptoms, and 14 patients received two spirometries. After administrating the bronchodilator, FEV1 and PEF significantly increased by 150 mL (6.01%, p = 0.002) and 260 mL/s (6.72%, p = 0.017), respectively. The median (interquartile range) of FeNO measured in nine patients was 15 (10-21) ppb. Patients with NIID have airflow reversibility like asthma. Airway inflammation is less associated with this condition; thus, immunomodulators such as corticosteroid may not improve respiratory symptoms in NIID.

BACKGROUNDEarly detection of colorectal cancer (CRC) is essential for reducing disease-related mortality; however, the invasiveness and resource intensity of colonoscopy limit its widespread use in population screening. Although several non-invasive screening modalities are available, their sensitivity remains suboptimal, particularly for advanced precancerous lesions (APL). Stool-derived host RNA biomarkers represent a promising approach to improve screening performance. However, numerous technical challenges are associated with extracting and quantifying this RNA, including an abundance of PCR inhibitors, a high microbial background, and varying levels of RNA degradation. METHODSWe developed an extraction method for the isolation of host RNA from stool with improved sensitivity of detection and better diagnostic performance than the conventional phenol-chloroform-based extraction. ECB-Extract (Enrichment Capture By hybridization), uses hybridization capture of RNA under denaturing conditions by adding locked nucleic acid bases to the probes. The improved hybridization characteristics allow us to directly isolate host RNA from stool lysate. RESULTSECB-Extract significantly improved PCR inhibitor removal, enabling scale-up of stool input and resulting in increased diagnostic sensitivity. We evaluated ECB-Extract against a conventional phenol-chloroform-based extraction method using the same panel of biomarkers in a pilot clinical cohort (N = 73). Using ECB-Extract, the sensitivity for detecting CRC and Advanced Precancerous Lesions (APL) was 96% and 50%, respectively, compared with 56% and 21% for the phenol-chloroform comparator at 96% specificity. In a larger cohort of 359 samples, ECB-Extract combined with a panel of the eight CRC-associated mRNA biomarkers achieved sensitivities of 95.7% for CRC and 51.2% for APL at a specificity greater than 90%. CONCLUSIONThese results demonstrate that ECB-Extract substantially improves stool host RNA extraction performance and, consequently, enhances diagnostic sensitivity for CRC and APL.

ObjectivesTo evaluate the efficacy and safety of sitafloxacin-containing regimens versus non-sitafloxacin therapy in patients with nontuberculous mycobacterial (NTM) pulmonary disease, focusing on sputum/BALF conversion rate, time of sputum/BALF culture conversion and radiographic improvement. MethodsThis retrospective cohort study analyzed 149 adults (76 control group vs. 73 sitafloxacin group) with NTM pulmonary disease treated between 2021 to 2024. Inclusion criteria: (1) Sitafloxacin group: [&ge;] 3 months of sitafloxacin-based therapy; (2) Both groups: Confirmed diagnosis of NTM pulmonary disease and age [&ge;] 18 years old. Exclusion criteria: extrapulmonary/disseminated NTM, HIV, active tuberculosis, or incomplete clinical data. Primary endpoint: culture conversion rate and time to culture conversion. Secondary endpoints: radiographic improvement and adverse events (AEs). ResultsThe sitafloxacin group demonstrated significantly higher conversion rate (53.8% vs. 22.1%, P 0.001) and faster culture conversion than the control group without sitafloxacin (median 195 vs. 292 days, P 0.001). Radiographic improvement was more frequent with the sitafloxacin group (54.5% vs. 36.1%, P = 0.046). Compared to the control group, the sitafloxacin group exhibited no significant adverse events. ConclusionsSitafloxacin-based regimens accelerate microbiological clearance and promote radiographic healing in NTM pulmonary disease with good safety, positioning it as a viable drug for improved treatment of NTM infections.

BackgroundColorectal cancer (CRC) is a leading cause of cancer mortality. While early detection improves outcomes, current non-invasive tests often lack sensitivity for early-stage CRC and advanced precancerous lesions (APL). Stool-based host messenger RNA (mRNA) biomarkers offer a promising approach, though the most clinically useful candidates remain undefined. MethodsWe screened for mRNA biomarkers by first using bioinformatic analysis of tissue RNA-seq datasets to identify candidate genes with strong and ubiquitous differential expression in CRC versus normal tissues. The top 135 computationally predicted biomarkers were evaluated using "gold standard" RT-PCR on clinical stool samples across two independent cohorts. ResultsSeveral biomarkers, including PPBP, MYC, MMP7, and TGFBI, exhibited strong predictive power. Integrating top-performing markers through machine learning yielded an AUC of 0.98 for CRC and 0.76 for APL detection. The optimized panel demonstrated 98% sensitivity for CRC and 50% for APL, with a specificity of 90%. ConclusionsThis study derives a high-performance mRNA-based stool test for non-invasive CRC screening. Our findings demonstrate that a multi-marker panel achieves exceptional sensitivity and good specificity, providing a viable tool for clinical diagnostics.

Advances in transcriptomics have transformed our understanding of amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disease, revealing disrupted gene expression profiles and highlighting the multi-system biology of ALS. Despite major advances, transcriptomic studies have only begun to capture the complexity and the molecular hierarchy of transcriptomic alterations in ALS. To resolve and characterize the transcriptome in ALS, we performed a comprehensive reanalysis of bulk RNA sequencing from the New York Genome Center ALS Consortium cohort across five post-mortem tissues including motor and frontal cortex, cervical and lumbar spinal cord, and cerebellum. By deploying dual analytical pipelines - one reference-based to model canonical events and one de novo to detect transcript structural novelties - we disentangled the quantitative and qualitative architectures of ALS. Our reference-based analysis revealed that ALS transcriptome is defined primarily by splicing failure rather than changes in gene expression. Aberrant splicing events, particularly intron retention, outnumbered differentially expressed genes by an order of magnitude. This widespread loss of fidelity disproportionately affected RNA-binding proteins, suggesting a collapse in their autoregulatory feedback loops. Deconvolution of these signals identified distinct cellular vulnerabilities: transcriptional disruptions were enriched in glial cells in sporadic cases but in neuronal cells in C9ORF72-positive cases. Furthermore, we observed sex-specific dysregulation, with male patients exhibiting greater disruption in guanosine triphosphatase signaling and ciliary organization pathways. In parallel, our de novo analysis uncovered a significant burden of disease-specific gene fusions that were absent in controls. Whole-genome sequencing of the same individuals, together with a larger reference population confirmed that disease-specific fusions do not arise from genomic structural variants, indicating a transcriptional rather than genomic origin. Investigation into the mechanism of these RNA-based fusions revealed a critical deviation in splice site definition: while canonical splice junctions exhibit a high density of binding motifs for polyA-binding or 3-cleaveage proteins approximately 50 base pairs upstream of the splice donor site (left junction), ALS-specific fusion junctions displayed a dramatic depletion of these motifs in the same region. Functionally, the presence of these sparse disease-specific fusions was strongly correlated with severe splicing outliers in genes governing guanosine triphosphatase activity, converging with the tissue- and male-specific defects identified in our reference-based analysis. Altogether, our results delineated a transcriptome characterized by aberrant splicing with tissue-and sex-specific changes and identified structural-variant-independent RNA fusions as candidate disease modifiers that may amplify pathology. This integrated view provides a mechanistic scaffold for splicing-centered and RNA-structural therapeutic strategies for ALS.

Background/ObjectivesMetabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is a global health crisis, but current diagnostics are limited. Liver biopsy is invasive, magnetic resonance imaging-proton density fat fraction (MRI-PDFF) is expensive, and quantitative ultrasound methods are low-accuracy, especially in patients with a high body mass index (BMI). This study introduces a novel thermo-acoustic (TA) method that generates ultrasound signals based on tissue electrical conductivity, where lean tissue (high in water and electrolytes) absorbs more radio-frequency (RF) energy than fatty tissue, providing a direct molecular contrast for fat. MethodsA prospective, cross-sectional feasibility study compared a new thermo-acoustic fat fraction (TAFF) score with the reference standard MRI-PDFF in 40 subjects with suspected fatty liver disease. Bland Altman analysis, Deming regression, and Binary classification performance were tested. To establish system stability, a dedicated Repeatability and Reproducibility (R&R) study (N = 14) evaluated inter-operator and intra-operator consistency using an Intraclass Correlation Coefficient (ICC) derived from a two-way random-effects ANOVA model. ResultsTAFF estimates demonstrated a substantial correlation (r =0.89) with MRI-PDFF and an average absolute error of 3.04% fat fraction. Classification performance was high, with an Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.92 at the 12% fat fraction threshold and 0.99 at the 20% fat fraction threshold. The R&R study confirmed robust stability (intraclass correlation = 0.89) and a negligible mean inter-operator difference of 0.36%. Estimation errors showed no statistically significant correlation with BMI or other body habitus measurements. ConclusionsThese findings support thermoacoustics potential as an accurate, non-invasive, point-of-care solution that can serve as a new imaging biomarker. By providing predictive values closely aligned with MRI-PDFF across the full MASLD spectrum, TAFF can complement currently available ultrasound methods to address the cost and access constraints of MRI for the assessment, diagnosis, and monitoring of MASLD.

Protocadherin-12 (PCDH12), a cell-adhesion protein belonging to the non-clustered protocadherin family, plays a crucial role in the establishment and regulation of neuronal connections and communication. Bi-allelic loss-of-function (LoF) variants in the PCDH12 gene have been associated with several neurodevelopmental disorders (NDDs) such as diencephalic-mesencephalic junction dysplasia (DMJD) syndrome, cerebral palsy, and cerebellar ataxia, often accompanied by ocular abnormalities. However, genotypes exhibit variable expressivity. Affected individuals sharing the same PCDH12 variant presenting differing phenotypic severities have posed major challenges towards identification of the underlying pathogenic mechanisms. Here, we report three affected individuals from two families, each harbouring non-truncating pathogenic missense variants in PCDH12. The patients are compound heterozygous, with each individual carrying one extracellular [c.1742T>G (p.Val581Gly) and c.1861_2del/insCA (p.Ile621His)] and one intracellular variant [c.3370C>T (p.Arg1124Cys) and c.3445G>A (p.Asp1149Asn] on each allele. The children present with a range of phenotypes similar to those associated with LoF variants. One child exhibited microcephaly and seizures, while the two siblings displayed developmental delays and severe behavioral disorders. All three children experienced some degree of visual impairment. The missense variants provided new insights into the neurodevelopmental consequences of compromised PCDH12 function by distinguishing the specific consequences associated with dysfunction in the extracellular versus intracellular domains of PCDH12. All identified missense variants are predicted to be deleterious and destabilizing. The expression of PCDH12 in HEK293T and HeLa cells demonstrated that PCDH12 is expressed effectively, regardless of the presence of missense variants. However, the extracellular variants p.Val581Gly and p.Ile621His compromised the stability of PCDH12's homophilic adhesion. Additionally, we found evidence of an interaction between PCDH12 and the extracellular domain of the epilepsy-associated PCDH19 protein. PCDH12 extracellular missense variants also negatively impact this interaction. Our study provides evidence that PCDH12 mediates both homophilic and heterophilic interactions. Our findings also highlight the importance of stable PCDH12-mediated adhesion, emphasizing the need to further study the functional consequences of PCDH12 missense variants on brain and visual system development.

ObjectivesTo develop and validate pediatric adaptations of the Venous Excess Ultrasound Score (P-VExUS) for noninvasive estimation of central venous pressure (CVP) in critically ill children. DesignProspective observational study. SettingPICU of a tertiary-care teaching hospital. PatientsFifty-six mechanically ventilated children (median age 7.4 months, median weight 6.0 kg) with central venous catheters. InterventionsNone. Measurements and Main ResultsVenous Doppler ultrasonography of the inferior vena cava, hepatic, portal, and intrarenal veins was performed at the bedside. Two P-VExUS models were tested: (1) a categorical grading system (0-III) and (2) a semiquantitative point-based score (0-7). Both models showed significant associations with CVP. For predicting elevated CVP (>12 mmHg), model 1 achieved an AUROC of 0.74 (95% CI 0.61-0.85) with 45% sensitivity and 98% specificity, while model 2 demonstrated superior accuracy with an AUROC of 0.94 (95% CI 0.84-0.98), sensitivity 82%, and specificity 91% (p < 0.001). For detecting low CVP (<7 mmHg), model 2 also outperformed model 1 (AUROC 0.80 vs. 0.69, p = 0.02). Among individual venous Doppler components, intrarenal veins had the highest discriminative ability (AUROC 0.92), followed by hepatic (0.89) and portal (0.80) veins. ConclusionsTwo pediatric-specific P-VExUS models were feasible and accurate for estimating CVP in critically ill children. The point-based model (model 2) demonstrated superior diagnostic performance, supporting its potential as a noninvasive tool to assess venous congestion at the bedside. Research in ContextO_LIVenous congestion, reflected by elevated central venous pressure (CVP), is associated with adverse outcomes in critically ill children, including mortality and renal dysfunction. C_LIO_LIThe Venous Excess Ultrasound Score (VExUS) is validated in adults, but pediatric-specific adaptations and cutoff values remain poorly defined. C_LIO_LIThere is a need for noninvasive, bedside tools to estimate CVP in children and guide fluid management in the PICU. C_LI What This Study MeansO_LIThis study validates pediatric-specific adaptations of the Venous Excess Ultrasound Score (P-VExUS) for estimating CVP in critically ill children. C_LIO_LIThe semiquantitative point-based model provided more consistent and accurate discrimination of venous congestion compared with categorical grading. C_LIO_LIThese findings highlight the feasibility and potential clinical utility of venous Doppler ultrasonography as a noninvasive bedside tool in the PICU. C_LI