Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Autophagy, a highly conserved cellular degradation mechanism, maintains intracellular homeostasis by removing damaged organelles and abnormal proteins. Its dysregulation is closely associated with various diseases. Autophagy-related protein 12 (ATG12), a core member of the ubiquitin-like protein family, covalently binds to ATG5 through a ubiquitin-like conjugation system to form the ATG12-ATG5-ATG16L1 complex. This complex directly regulates the formation and maturation of autophagosomes, making ATG12 a key molecule in the initiation of autophagy. Recent studies have revealed that ATG12 functions extend far beyond the classical autophagy context. It promotes apoptosis by binding to anti-apoptotic proteins of the Bcl-2 family (e.g., Bcl-2 and Mcl-1) and enhances host antiviral immunity by regulating the NF-κB and interferon signaling pathways. Moreover, ATG12 deficiency can lead to mitochondrial biogenesis impairment, energy metabolism disorders, and substrate-dependent metabolic shifts, underscoring its pivotal role in cellular metabolic homeostasis. At the disease level, dysregulation of ATG12 expression is closely linked to tumorigenesis and cancer progression. By modulating the dynamic balance between autophagy and apoptosis, ATG12 influences cancer cell proliferation, metastasis, and chemoresistance. Notably, ATG12 is abnormally overexpressed in multiple cancers, including breast, liver, and gastric cancer, highlighting its potential as a therapeutic target. Furthermore, in neurodegenerative diseases such as Parkinson’s disease, ATG12 mitigates protein toxicity by enhancing mitochondrial autophagy. In cardiovascular diseases, it alleviates ischemia-reperfusion injury by regulating cardiomyocyte autophagy and apoptosis, demonstrating its broad regulatory role across various pathological conditions. Genetic studies further underscore the clinical significance of ATG12. Polymorphisms in the ATG12 gene (e.g., rs26537 and rs26538) have been significantly associated with the risk of head and neck squamous cell carcinoma, hepatocellular carcinoma, and atrophic gastritis. Notably, the risk allele of rs26537 enhances ATG12 promoter activity, leading to its overexpression and promoting tumorigenesis. These findings provide a molecular basis for individualized risk assessment and targeted interventions based on ATG12 genotype. Despite significant progress, many aspects of ATG12 biology remain unclear. The precise regulatory mechanisms of its post-translational modifications (e.g., ubiquitination and acetylation) are yet to be fully elucidated. Additionally, the molecular pathways underlying its non-canonical functions, such as metabolic regulation and immune modulation, require further investigation. Moreover, the functional heterogeneity of ATG12 in different tumor microenvironments and its role in drug resistance warrant in-depth exploration. Future research should integrate advanced technologies such as cryo-electron microscopy, single-cell sequencing, and organoid models to decipher the intricate regulatory network of ATG12. Additionally, developing small-molecule inhibitors or gene-editing tools targeting its protein interaction interfaces (e.g., the ATG12-ATG3 binding domain) may help overcome current therapeutic challenges. Through interdisciplinary collaboration and clinical translation, ATG12 holds promise as a next-generation molecular target for precision intervention in autophagy-related diseases. This review summarizes the structure and function of ATG12, its role in autophagy initiation, its physiological functions, and its involvement in disease pathogenesis. Furthermore, it discusses future research directions and potential challenges, emphasizing ATG12’s potential as a biomarker and therapeutic target in autophagy-related diseases.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Tuberculosis (TB) is a chronic infectious disease caused by Mycobacterium tuberculosis, which is primarily transmitted through the respiratory tract, and remains one of the diseases with the highest mortality rate of single-pathogen infections globally. The cell wall polysaccharides of M. tuberculosis are critical for maintaining bacterial structure, mediating pathogenesis, and enabling immune evasion. Lipoarabinomannan (LAM), a key polysaccharide component, has revolutionized non-invasive diagnostic technologies as a TB biomarker, while polysaccharide-based vaccines have emerged as innovative strategies for TB prevention. This review systematically examines the composition, subcellular distribution, and functional roles of M. tuberculosis cell wall polysaccharides in bacterial metabolism, drug resistance, and immune regulation. A particular emphasis is placed on recent advancements in LAM-based diagnostics and vaccine development. Future studies should utilize advanced technologies to precisely characterize the structural features of TB polysaccharides and explore their biological functions, providing a foundation for targeted diagnostic and therapeutic innovations. This article aims to provide reference for advancing both basic research and clinical applications related to M. tuberculosis.

Arginine methylation is a critical post-translational modification that plays multifaceted biological functions. However, the manipulation of protein arginine methylation largely depends on genetic or pharmaceutic inhibition of the regulatory enzymes, protein arginine methyltransferases (PRMTs), or non-methylation substitution of corresponding arginine residue to lysine or alanine of protein of interest (POI), which inevitably affects other substrates, or disrupts the structure of POI. Thus, it urges an approach to specifically modulate the arginine methylation of a POI under physiological conditions. To this end, we report the discovery of a methylation tagging system (MeTAG), that enables targeted modification of protein arginine methylation. Through bridging the methyltransferase PRMT5 proximity to a POI, MeTAG facilitates the arginine methylation of POIs, including known arginine methylated proteins, androgen receptor (AR) and protein kinase B (AKT), as well as a neo-substrate E1A binding protein (p300), in a reversible and PRMT5-dependent manner. Moreover, MeTAG can regulate downstream signaling in a methylation dependent manner, leading to downregulation of PSMA mRNA level and activation of AKT. Therefore, MeTAG represents a feasible approach to modulate protein methylation and thereby perturbs protein function in biological and therapeutic contexts.

OBJECTIVES: To evaluate the association of GGN repeat polymorphism of androgen receptor (AR) with ovarian reserve and ovarian response in controlled ovarian stimulation (COS). METHODS: This genetic association study was conducted among a total of 361 women aged ≤40 years with basal FSH≤12 U/L undergoing the GnRH-agonist long protocol for COS in a university-affiliated IVF center. GGN repeat in the AR gene was analyzed with Sanger sequencing. The primary endpoint was the number of antral follicle counts (AFCs), and the secondary endpoints were stimulation days, total dose of gonadotropin (Gn) used, total number of retrieved oocytes, ovarian sensitivity index, and follicular output rate. RESULTS: The GGN repeat in exon 1 of the AR gene ranged from 13 to 24, and the median repeat length was 22. Based on the genotypes (S for GGN repeats <22, L for GGN repeats ≥22), the patients were divided into 3 groups: SS, SL, and LL. Generalized regression analysis indicated that the number of AFCs in group SS was significantly lower than those in group SL (adjusted β=1.8, 95% CI: 0.2-3.4, P=0.024) and group LL (adjusted β=1.5, 95% CI: 0.2-2.7, P=0.021). No significant difference was observed in the number of AFCs between group SL and group LL (P>0.05). Generalized regression analysis indicated no significant differences in ovarian stimulation parameters among the 3 groups, either before or after adjusting for confounding factors (P>0.05). CONCLUSIONS GGN repeat length on the AR gene is associated with AFC but not with ovarian response in Chinese women, indicating that AR gene polymorphisms may affect ovarian reserve.
Adult ; Female ; Humans ; Genotype ; Ovarian Follicle/cytology* ; Ovarian Reserve/genetics* ; Ovulation Induction/methods* ; Polymorphism, Genetic ; Receptors, Androgen/genetics* ; East Asian People/genetics*

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*

The accurate prediction of drug absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties represents a crucial step in early drug development for reducing failure risk. Current deep learning approaches face challenges with data sparsity and information loss due to single-molecule representation limitations and isolated predictive tasks. This research proposes molecular properties prediction with parallel-view and collaborative learning (MolP-PC), a multi-view fusion and multi-task deep learning framework that integrates 1D molecular fingerprints (MFs), 2D molecular graphs, and 3D geometric representations, incorporating an attention-gated fusion mechanism and multi-task adaptive learning strategy for precise ADMET property predictions. Experimental results demonstrate that MolP-PC achieves optimal performance in 27 of 54 tasks, with its multi-task learning (MTL) mechanism significantly enhancing predictive performance on small-scale datasets and surpassing single-task models in 41 of 54 tasks. Additional ablation studies and interpretability analyses confirm the significance of multi-view fusion in capturing multi-dimensional molecular information and enhancing model generalization. A case study examining the anticancer compound Oroxylin A demonstrates MolP-PC's effective generalization in predicting key pharmacokinetic parameters such as half-life (T0.5) and clearance (CL), indicating its practical utility in drug modeling. However, the model exhibits a tendency to underestimate volume of distribution (VD), indicating potential for improvement in analyzing compounds with high tissue distribution. This study presents an efficient and interpretable approach for ADMET property prediction, establishing a novel framework for molecular optimization and risk assessment in drug development.
Deep Learning

CD20 is a surface marker protein of B-cell lymphoma, and its extracellular region is the target of specific antibodies and drugs. To obtain a cheap and easily modified specific preparation targeting CD20, we optimized the gene of CD20 extracellular region according to codon degeneracy to facilitate its expression in Escherichia coli. The optimized gene was cloned into pGEX-4T-1 vector, and the recombinant vector was transformed into E. coli BL21(DE3) for expression. The purified protein was identified by SDS-PAGE and Western blotting. Systematic evolution of ligands by exponential enrichment (SELEX) was employed to screen the ssDNA aptamer that specifically binds to the fusion protein, and the affinity of the aptamer to CD20 was detected by flow cytometry. Then, the cytotoxicity test was carried out to examine the inhibitory effect of the aptamer on B lymphoma cells. In this study, we established the prokaryotic expression method of CD20 and obtained the aptamer specifically binding to the extracellular region of CD20, which laid a foundation for the development of therapeutic drugs targeting CD20.
Humans ; Escherichia coli/metabolism* ; SELEX Aptamer Technique/methods* ; Aptamers, Nucleotide/genetics* ; Antigens, CD20/metabolism* ; Ligands