Hepatic fibrosis is a reversible pathological process in various chronic liver diseases and is closely associated with the development and progression of severe liver diseases such as liver cirrhosis and hepatocellular carcinoma， and it has emerged as a significant global health challenge. In recent years， studies have shown that histone lactylation， a newly discovered epigenetic modification， actively participates in regulating the progression of hepatic fibrosis. This article systematically reviews the core regulatory effect of histone lactylation modification in the interaction between inflammatory microenvironment and hepatic fibrosis， in order to clarify the cascade regulatory mechanism of “inflammation-hepatic fibrosis” and provide new insights for early diagnosis， targeted intervention， and prevention of malignant transformation in hepatic fibrosis.

Liver fibrosis is a critical pathological process in the progression of chronic liver diseases and is mainly driven by the activation of hepatic stellate cells， and it is characterized by excessive deposition of extracellular matrix. Programmed cell death is widely observed in liver fibrosis and plays diverse roles in different types of cells. It is not only a mechanism for maintaining cellular homeostasis through metabolism， but it can also regulate the development and progression of diseases. Ferroptosis has recently emerged as a research focus due to its close association with lipid metabolism. This article systematically reviews the related concepts of lipid metabolism， ferroptosis， and liver fibrosis， analyzes the bridging role and dual regulatory function of ferroptosis in lipid metabolism and liver fibrosis， and further highlights the clinical application value of targeting ferroptosis in hepatic stellate cells for the treatment of liver fibrosis， in order to provide new perspectives for the mechanistic studies on liver fibrosis and the optimization of related clinical intervention strategies.

ObjectiveTo carry out a health technology assessment （HTA） of acupuncture for secondary dysmenorrhea （SD） caused by adenomyosis and endometriosis， in order to provide a reference for relevant medical decision-making. MethodsFrom the perspective of the health system， the assessment covers seven areas， including the technical characteristics， safety， effectiveness， economics， ethical fairness， organizational adaptability， and impact on patients and society. The results are reported accordingly. ResultsThe operational specifications of acupuncture are standardized， and the conditions for its use are clearly defined. Acupuncture has a lower overall incidence of adverse events. The main adverse events are localized pain， subcutaneous bleeding， and dizziness， with most symptoms being mild， all of which have corresponding standard treatments. No reports on occupational or environmental safety were found， and the safety operation specifications are available for reference. Compared with conventional Western medicine， acupuncture demonstrates higher effectiveness. Acupuncture may improve the quality of life scores of patients， though no significant difference was observed. The cost of acupuncture is higher than that of conventional Western medicine， but its overall economic value is greater. The informed consent information is relatively comprehensive. Most patients are aware of the potential benefits and risks of acupuncture and voluntarily opt for it. The treatment process fully respects patient privacy and human rights. The clinical application of acupuncture follows the current acupuncture medical service model， with no special requirements for the level of medical institutions. Patient accessibility and affordability are suitable. Patient satisfaction is high. Most patients indicated they would choose acupuncture again for SD. The main barriers to choosing acupuncture are psychological factors （such as fear of acupuncture）， cost， and transportation issues. Nearly 70% of patients receiving acupuncture treatment benefit from medical insurance reimbursement， with reimbursement rates generally above 50%， indicating strong social security support. ConclusionThe implementation of HTA for acupuncture in the treatment of SD， using the standards for traditional Chinese medicine （TCM）， is feasible. The implementation steps are clear， the data sources for each evaluation domain are adequate， the analysis methods are practical， and the evaluation results are comprehensive. Experts recommend that the findings be used as a reference for relevant medical decision-making.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Sigma-1 receptor (σ ₁R) has become a focus point of drug discovery for central nervous system (CNS) diseases. A series of novel 1-phenylethan-1-one O-(2-aminoethyl) oxime derivatives were synthesized. In vitro biological evaluation led to the identification of 1a, 14a, 15d and 16d as the most high-affinity (K _i < 4 nmol/L) and selective σ ₁R agonists. Among these, 15d, the most metabolically stable derivative exhibited high selectivity for σ ₁R in relation to σ ₂R and 52 other human targets. In addition to low CYP450 inhibition and induction, 15d also exhibited high brain permeability and excellent oral bioavailability. Importantly, 15d demonstrated effective antipsychotic potency, particularly for alleviating negative symptoms and improving cognitive impairment in experimental animal models, both of which are major challenges for schizophrenia treatment. Moreover, 15d produced no significant extrapyramidal symptoms, exhibiting superior pharmacological profiles in relation to current antipsychotic drugs. Mechanistically, 15d inhibited GSK3β and enhanced prefrontal BDNF expression and excitatory synaptic transmission in pyramidal neurons. Collectively, these in vivo proof-of-concept findings provide substantial experimental evidence to demonstrate that modulating σ ₁R represents a potential new therapeutic approach for schizophrenia. The novel chemical entity along with its favorable drug-like and pharmacological profile of 15d renders it a promising candidate for treating schizophrenia.

Combined with elastic network model (ENM), the perturbation response scanning (PRS) has emerged as a robust technique for pinpointing allosteric interactions within proteins. Here, we proposed the PRS analysis of drug-target networks (DTNs), which could provide a promising avenue in network medicine. We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework, for drug repurposing of multiple sclerosis (MS). First, the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes. Then, based on topological analysis and functional annotation, the neurotransmission module was identified as the "therapeutic module" of MS. Further, perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis, giving a list of repurposable drugs for MS. Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of serotonin 2B receptor (HTR2B). Finally, we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex. These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS. As a useful systematic method, our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

This article introduces Professor LIU Xing's clinical experience in treatment of peripheral facial paralysis at the recovery and sequelae stages with the combination of acupotomy, cupping and herbal medication. Based on the analysis of etiology and pathogenesis of peripheral facial paralysis, Professor LIU believes that "invasion of pathogenic wind to collaterals and obstruction of qi and blood" is crucial. Therefore, the treatment focuses on "dispelling wind and harmonizing blood". The compound therapeutic mode is proposed, with acupotomy, cupping and herbal decoction involved, in which, "three-step sequential method of acupotomy" is predominated. Firstly, in the prone position, five "feng" (wind) points are stimulated in patient, Fengfu (GV16), Fengchi (GB20), Yifeng (TE17), Bingfeng (SI12) and Fengmen (BL12). Secondly, in the lateral position, three-facial points are stimulated (FaceⅠneedle: Yangbai [GB14]-Yuyao [EX-HN4]; Face Ⅱ needle: Sibai [ST2]-Quanliao [SI18]; Face Ⅲ needle: Jiache [ST6]-Dicang [ST4]) to restore the deviated facial muscles. Finally, in the supine, two Dantian points are stimulated on the forehead and chest, respectively (upper Dantian: Yintang [GV24⁺], middle Dantian: Danzhong [CV17]), to regulate qi and blood. As the adjunctive therapies, cupping is used to remove stasis, and herbal decoction is to harmonize the body interior. In view of holistic regulation, the treatment is administered in accordance with the affected meridians, so as to expel wind, remove obstruction in collaterals and regulate qi and blood.
Humans ; Facial Paralysis/drug therapy* ; Drugs, Chinese Herbal/administration & dosage* ; Acupuncture Therapy ; Male ; Female ; Middle Aged ; Adult ; Combined Modality Therapy ; Acupuncture Points ; Cupping Therapy ; Aged ; Young Adult

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

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