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.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

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.

OBJECTIVES: To investigate the genomic characteristics and prognostic factors of juvenile myelomonocytic leukemia (JMML) with RAS mutations. METHODS: A retrospective analysis was conducted on the clinical data of JMML children with RAS mutations treated at the Hematology Hospital of Chinese Academy of Medical Sciences, from January 2008 to November 2022. RESULTS: A total of 34 children were included, with 17 cases (50%) having isolated NRAS mutations, 9 cases (27%) having isolated KRAS mutations, and 8 cases (24%) having compound mutations. Compared to children with isolated NRAS mutations, those with NRAS compound mutations showed statistically significant differences in age at onset, platelet count, and fetal hemoglobin proportion (P<0.05). Cox proportional hazards regression model analysis revealed that hematopoietic stem cell transplantation (HSCT) and hepatomegaly (≥2 cm below the costal margin) were factors affecting the survival rate of JMML children with RAS mutations (P<0.05); hepatomegaly was a factor affecting survival in the non-HSCT group (P<0.05). CONCLUSIONS Children with NRAS compound mutations have a later onset age compared to those with isolated NRAS mutations. At initial diagnosis, children with NRAS compound mutations have poorer peripheral platelet and fetal hemoglobin levels than those with isolated NRAS mutations. Liver size at initial diagnosis is related to the prognosis of JMML children with RAS mutations. HSCT can improve the prognosis of JMML children with RAS mutations.
Humans ; Leukemia, Myelomonocytic, Juvenile/therapy* ; Mutation ; Male ; Female ; Child, Preschool ; Retrospective Studies ; Child ; Infant ; GTP Phosphohydrolases/genetics* ; Membrane Proteins/genetics* ; Adolescent ; Hematopoietic Stem Cell Transplantation ; Proportional Hazards Models ; Proto-Oncogene Proteins p21(ras)/genetics* ; Prognosis

Aim To investigate the effect of Rtv(a P-gp inhibitor and inducer)on the pharmacokinetics of Y101(P-gp substrate)via P-gp.Methods In short-term studies,rats received a single dose of Rtv,where-as in long-term studies they received continuous dosing for seven days.Following this treatment,Y101 was o-rally administered to analyze its blood concentration in rats.Subsequently,the mechanism by which Rtv af-fected Y101 pharmacokinetics was investigated through the everted gut sac model(in vitro),cellular uptake studies,and so on.Results Short-term administra-tion of Rtv significantly increased Y101's AUC,liver-to-plasma partition coefficient,the everted gut sac model(in vitro),and cellular accumulation.Although long-term Rtv treatment had no effect on Y101 pharma-cokinetics or hepatic distribution,it markedly reduced Y101 cellular accumulation in Caco-2 cells,concomi-tant with an upregulation of P-gp expression.Conclu-sions Short-term Rtv administration acts as a compet-itive P-gp inhibitor,enhancing Y101 intestinal absorp-tion and hepatic distribution.In contrast,the plasma pharmacokinetics and hepatic distribution of Y101 are not altered after long-term administration of Rtv,po-tentially attributable to Rtv's dual modulatory effects on P-gp involving both induction and inhibition.Hence,the potential Rtv and Y101 interaction should be close-ly monitored in the clinic.

Objective:To compare the differences in repair of rabbit bone defects between allogeneic platelet rich plasma (PRP) gel and autologous PRP gel.Methods:Thirty-six healthy New Zealand white rabbits were selected and randomly divided into an autologous group, an allogeneic group, and a control group ( n=12). A model of bilateral forelimb bone defects was established in each group. The autologous group was repaired with self-made deproteinized bone scaffold materials + autologous bone marrow mesenchymal stem cells (BMSCs) + autologous PRP gel, the allogeneic group with self-made deproteinized bone scaffold materials + autologous BMSCs + allogeneic PRP gel, and the control group with only self-made deproteinized bone scaffold materials + autologous BMSCs. At postoperative 1, 2, and 3 months, 4 animals were euthanized in each group, respectively, for gross observation, X-ray examination, Micro-CT examination, biomechanical testing and histological analysis (HE staining for tissue morphology) to compare the differences in repair of bone defects. Results:The formation of trabecular bone, cortical reconstruction, and medullary recanalization occurred earlier in the autologous and allogeneic groups than in the control group. Micro-CT analysis at postoperative 2 months showed that bone mineral density [(281.51±33.69) mg/mL and (266.13±37.13) mg/mL], bone volume fraction (23.52%±2.81% and 21.91%±1.94%), and trabecular number [(1.68±0.29) mm -1 and (1.63±0.22) mm -1] in the autologous and allogeneic groups were significantly higher than those in the control group [(197.47±18.61) mg/mL, 16.54%±3.06%, and (1.06±0.11) mm -1] ( P<0.05). No significant differences were found among the 3 groups in trabecular thickness [(0.33±0.09) mm, (0.42±0.16) mm, and (0.28±0.13) mm] or in the maximum compressive load ( P>0.05). HE staining revealed a significantly greater number and earlier formation of chondrocytes and osteoblasts in the autologous and allogeneic groups than in the control group. Conclusion:Since allogeneic PRP exhibits similar efficacy in promoting new bone formation compared with autologous PRP in a rabbit bone defect model, it may serve as a viable substitute for autologous PRP.

Objective:To explore the application of flipped classroom in the teaching of Laboratory Quality Management course.Methods:A total of 116 students majoring in Health Inspection and Quarantine in grade 2020 and 2021 were selected as the research subjects.Among them,58 students of grade 2020 received the traditional teaching mode as the control group,and 58 students of grade 2021 received the flipped classroom teaching mode as the experimental group.A self-designed questionnaire was conducted to investigate students'satisfaction with laboratory safety course content,and evaluate the teaching methods and effectiveness of the course.Results:The satisfaction rates of the experimental group with the teaching content on the safe use of instruments and equipment,chemical safety management and waste treatment were significantly higher than those of the control group(P＜0.05).There was no statistically significant difference in the satisfaction rate of the teaching content of safety common sense(P＞0.05).In the evaluation of teaching methods and teaching effects,the satisfaction rates of the experimental group in improving classroom participation,enhancing team assistance ability and classroom activity was higher than those of the control group(P＜0.05).Conclusion:The application of flipped classroom teaching method in teaching of Laboratory Quality Management course can enhance students'laboratory safety awareness,stimulate their learning interest and initiative,and effectively improve their learning efficiency.

Objective:To investigate the effect of traditional Chinese medicine chronic disease management model based on empowerment theory in patients with chronic heart failure(CHF).Methods:A total of 115 CHF patients admitted in Guangdong Provincial Hospital of Chinese Medicine between January 2020 and December 2021 were se-lected.Patients received traditional Chinese medicine chronic disease management model based on empowerment theory according to voluntary principle,and were followed up for 12 months.Exercise capacity,scores of Tradition-al Chinese Medicine Symptom Grading and Quantification Scale,Hospital Anxiety and Depression Scale(HADS)and Minnesota Living with Heart Failure Questionnaire(MLHFQ)were compared between before and after inter-vention.Results:Compared to before intervention,scores of Traditional Chinese Medicine Symptom Grading and Quantification Scale[(6.40±6.11)points vs.(8.88±6.72)points],HADS[(5.95±4.68)points vs.(7.69±5.95)points],MLHFQ[(13.10±10.54)points vs.(25.53±11.16)points]and 3m round-trip movement time[(7.54±1.70)s vs.(8.86±3.65)s]were significantly lower,and right hand grip strength[(27.23±10.49)kg vs.(26.10±9.94)kg]and 6-minute walking distance[(464.79±80.78)m vs.(415.55±79.33)m]were sig-nificantly higher after 12-month intervention(P＜0.05 or＜0.01).Conclusion:The traditional Chinese medicine chronic disease management model based on empowerment theory may improve clinical symptoms of traditional Chi-nese medicine,mental state,exercise capacity and quality of life in patients with chronic heart failure.