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A genome-wide coverage-based pipeline for the identification of host-derived candidate DNA biomarkers from cell-free blood.

We have created a new data-analysis pipeline for the discovery of host-specific candidate DNA biomarkers derived from sequencing data of cell-free blood. Unlike approaches that rely on specific molecular or genetic signatures, our method leverages the coverage distribution of cell-free DNA sequences mapped to a reference genome, applying statistical analyses to identify informative short genomic regions for biomarker discovery. The pipeline is applicable to diverse diseases and can be used to analyze cell-free DNA sequences from plasma or serum to identify candidate biomarkers that are characteristic of disease states in mammals. Core functionalities were developed in Java and integrated with open-source software tools for the preprocessing of raw sequencing data, complemented by Python scripts for the machine-learning analysis and statistical validation. The pipeline is designed for HPC use and users can access the pipeline through a Galaxy workflow, which offers a user-friendly web interface for input selection prior to execution and analysis progress monitoring. Performance tests, carried out using duplicate sets of COVID-19 samples and controls, showed linear scalability of execution time with an increasing dataset size, as well as a substantial reduction in execution time through parallelized computation, whereby each HPC node is used to process the data of one chromosome. Further statistical tests confirmed the quality of the pipeline's results by showing that the set of identified candidate biomarkers remained stable across varying dataset sizes.

Biomarkers

Dynamic evolution of chaperone-mediated autophagy is associated with tumor microenvironment remodeling and prognostic stratification in lung adenocarcinoma: insights from single-cell transcriptomics, ensemble machine learning, and experimental validation.

BACKGROUND: Lung adenocarcinoma (LUAD) shows prognostic heterogeneity, and tumor-node-metastasis (TNM) staging is limited for individualized management. Chaperone-mediated autophagy (CMA) maintains proteostasis, but its role during adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA)-invasive adenocarcinoma (IAC) progression remains unclear. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE189357 and bulk transcriptomes from The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GEO) cohorts were integrated. CMA activity, cell-cell communication, weighted gene co-expression network analysis (WGCNA), tumor-normal differential expression, machine-learning survival modeling, tumor microenvironment (TME) features, drug sensitivity, and EPC1 function were analyzed. RESULTS: CMA-high tumor epithelial cells increased from AIS (58.1%) to MIA (65.7%) but declined in IAC (44.4%; p < 0.001). CMA-low cells preferentially received fibroblast-derived extracellular matrix cues. A CMA-negatively correlated module identified 69 core genes. Random survival forest (RSF) performed best among 117 machine-learning combinations (mean concordance index > 0.873). High-risk patients had worse survival across cohorts, and the risk score was independently associated with overall survival (hazard ratio = 16.013, 95% confidence interval: 9.579-26.768, p < 0.001). High-risk tumors showed proliferative activation and M0 macrophage enrichment, whereas low-risk tumors showed stronger immune-related signaling. EPC1 overexpression suppressed malignant phenotypes in A549 cells. CONCLUSION: CMA dynamics are associated with stromal and immune remodeling during LUAD progression. A CMA-based model provides robust prognostic stratification and may offer a basis for future TME-guided studies.

Chaperone-mediated autophagy

Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integrating global proteomics, acetylomics, and succinylomics to dissect the molecular dynamics during platelet storage. METHODS: We performed quantification of global proteomics, acetylome and succinylome based on TMT-labeled LC-MS/MS analysis, combined with antibody-affinity enrichment and purification. Dynamic molecular changes and functional transformation of platelet were also characterized under proper conditions stored for 1, 3, 5, 7&#x2009;days, respectively. RESULTS: We systematically characterized 3,609 proteins, 1,308 acetylation sites, and 1,947 succinylation sites across multiple storage time points (D1, D3, D5, D7). We distinct temporal patterns of post-translational modifications, with succinylation showing more extensive coverage than acetylation in platelets. Pathway enrichment analysis revealed extensive metabolic reprogramming involving complement activation, energy metabolism, and cellular detoxification processes. The identification of specific motif patterns provided mechanistic insights into the functional specificity of these modifications. Random forest machine learning identified 20 core regulatory proteins representing critical nodes in PSL development. Furthermore, we employed real - time quantitative polymerase chain reaction (RT - QPCR) to measure the expression levels of key genes related to platelet function and PTM - associated pathways. CONCLUSION: By mapping the interplay between proteomic abundance shifts and PTM dynamics, this study provides a multidimensional understanding of PSL, establishing a foundational framework for optimizing storage protocols and enhancing transfusion safety.

Blood Platelets

Targeting ncRNA control networks with engineered exosomes to overcome therapy resistance in thyroid cancer.

Papillary thyroid cancer (PTC) is the most prevalent endocrine malignancy, accounting for over 90% of thyroid cancers. While differentiated thyroid cancers (DTCs) typically have favorable outcomes, a significant subset progresses to radioactive iodine-refractory (RAIR) disease, characterized by impaired iodine uptake and a 10-year survival rate below 10%. Genetic alterations and dysregulated signaling pathways underlie this transition. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), circular RNAs (circRNAs), and long non-coding RNAs (lncRNAs), play critical regulatory roles in tumor biology and may be transported via exosomes, facilitating intercellular communication and contributing to RAIR-PTC. This systematic review, conducted according to PRISMA 2020 guidelines, evaluated the role of exosomal ncRNAs in RAIR-PTC. A comprehensive search of PubMed, PubMed Central, and Google Scholar identified studies published within the past 15 years in English. Following stringent quality appraisal, studies with a non-bias score above 40% were included. Of 961 identified publications, 96 high-quality studies met inclusion criteria. Evidence indicates that therapy resistance in RAIR-PTC is driven by convergent ncRNA regulatory networks that suppress sodium-iodide symporter (NIS) expression and activate oncogenic pathways, most notably MAPK, PI3K/AKT/mTOR, and Wnt/&#x3b2;-catenin signaling. Multiple ncRNAs converge on key regulatory nodes, forming redundant circuits that sustain dedifferentiation, metabolic adaptation, and impaired iodide transport. Several consistently dysregulated ncRNAs directly or indirectly regulate NIS expression and trafficking, highlighting actionable targets. Exosomes emerge as biologically compatible, programmable delivery vehicles capable of transporting therapeutic ncRNA payloads independent of endogenous packaging mechanisms. These findings support a precision therapeutic paradigm in which engineered exosomes reprogram ncRNA networks to restore iodine-handling pathways and overcome therapy resistance in RAIR-PTC.

Humans

Proteomic and phosphoproteomic profiles of time-dependent dynamic changes in LPS-induced macrophage polarization.

The temporal proteomic and phosphoproteomic reprogramming during early M1 macrophage polarization (0-6&#xa0;h) remains poorly understood. We performed time-resolved proteomic and phosphoproteomic analyses of LPS-stimulated RAW264.7 macrophages at seven time points within 6&#xa0;h. Time-clustering of differentially expressed molecules revealed two patterns: initial change with partial recovery, and sustained dysregulation. Upregulated proteins and phosphorylation sites were enriched in the Rho GTPase signaling pathway, T-cell receptor signaling pathway, NF-&#x3ba;B cascade, osteoclast differentiation pathway, and antiviral immune pathway. Downregulated pathways were associated with cell cycle regulation, chromatin remodeling, RNA metabolism, and mRNA processing, indicating resource reallocation to prioritize acute inflammatory responses. Kinase-substrate network analysis confirmed the mitogen-activated protein kinase (MAPK), cyclin-dependent kinase (CDK), protein kinase B (AKT), and ribosomal S6 kinase (RSK) families as core upstream phosphorylation regulators. Integrated analysis revealed synergistic and antagonistic relationships between proteomic and phosphoproteomic changes. This study provides a temporal molecular atlas of M1 polarization, delineating inflammatory signaling dynamics and offering a basis for therapeutic target discovery in inflammatory diseases. SIGNIFICANCE: Macrophage M1 polarization is a central event in innate immune defense against pathogenic invasion, yet its dysregulation is a pivotal driver of the onset and progression of a broad spectrum of inflammation-associated disorders, spanning autoimmune diseases, infectious conditions and inflammatory bone diseases, making the dissection of its molecular regulatory mechanisms an urgent research priority in immunology and translational medicine. Dynamic molecular events within 0-6&#xa0;h after LPS stimulation are critical for initiating and shaping M1 inflammatory activation, yet systematic time-resolved proteomic and phosphoproteomic profiling remains insufficient.In this study, we comprehensively characterized temporal proteome and phosphoproteome changes at seven consecutive time points during macrophage polarization, clarified two distinct dynamic molecular patterns, identified core signaling pathways and key kinase regulators involved in inflammatory reprogramming, and uncovered the leading role of post-translational phosphorylation modifications in initiating polarization. This work delineates the time-series molecular atlas of early macrophage activation, provides novel insights into the temporal regulatory mechanism of inflammatory signaling networks, and lays a solid experimental foundation for exploring new intervention targets and regulatory nodes in clinical translational research.

Lipopolysaccharides

Dual Transcranial Direct Current Stimulation Modulates Hierarchical Functional Network Organization in Post-Stroke Cognitive Impairment: A Randomized Controlled Trial.

OBJECTIVE: To evaluate the clinical efficacy of dual transcranial direct current stimulation (tDCS) in patients with post-stroke cognitive impairment (PSCI) and to explore the effects on the hierarchical organization of functional brain networks, ranging from regional synchronization to inter-regional connectivity and global network topology. METHODS: In this randomized, double-blind, sham-controlled trial, 74 PSCI patients received conventional therapy alongside either active dual-tDCS (n&#x2009;=&#x2009;38) or sham stimulation (n&#x2009;=&#x2009;36). Active tDCS targeted the dorsolateral prefrontal cortex (DLPFC) via anodal-left/cathodal-right nodes (2.0&#x2009;mA, 20&#x2009;min/day, 20 sessions). The primary outcome was the Montreal Cognitive Assessment (MoCA). Secondary outcomes included the Mini-Mental Status Examination (MMSE), Stroop Test (ST), Trail Making Test (TMT), Wechsler Memory Scale (WMS), and Barthel Index (BI). A subgroup of 36 participants (18 per group) underwent resting-state functional magnetic resonance imaging (rs-fMRI) to analyze regional homogeneity (ReHo), functional connectivity (FC), and network topology. Partial correlations assessed the association between neuroimaging alterations and clinical improvements. RESULTS: The tDCS group showed significantly greater improvements in MoCA scores (tDCS: 5.74&#x2009;&#xb1;&#x2009;2.76 vs. sham: 2.69&#x2009;&#xb1;&#x2009;2.69; t&#x2009;=&#x2009;4.799, p&#x2009;<&#x2009;0.001) as well as in attention and memory domains compared to the sham group. The rs-fMRI changes included increased ReHo in the right middle temporal gyrus (MTG) and the left inferior frontal gyrus (IFG), and reduced FC between the right MTG-left superior frontal gyrus and left IFG-cerebellum (p&#x2009;<&#x2009;0.05, FWE-corrected). Additionally, small-worldness and global efficiency increased (p&#x2009;<&#x2009;0.05) with these alterations correlating with clinical recovery. Adverse events were rare and self-limiting. CONCLUSION: Dual-tDCS over bilateral DLPFC safely improves cognitive recovery in PSCI. These clinical gains are associated with rs-fMRI alterations, specifically in regional synchronization, inter-regional connectivity, and global topology, which suggest a potential biomarker for monitoring tDCS efficacy, offering a rationale for precision neuromodulation in stroke rehabilitation.

Humans