This article reports a rare case of autoinflammatory disease presenting initially with skin induration and swelling after trauma as the initial manifestation, followed by progressive limb weakness. The patient was a middle-aged female who developed skin induration and swelling after trauma, which gradually progressed to limb weakness, dysarthria and bilateral facial paralysis, accompanied by livedo reticularis of the lower extremities, diffuse skin induration of the limbs, and beaded subcutaneous nodules in the right upper limb. The patient had a susceptibility to infection since childhood and a history of chronic livedo reticularis. Skin pathological examination revealed panniculitis. A comprehensive etiological screening for special infections and autoimmune diseases was completed with an unremarkable results, and whole-exome sequencing showed no abnormal findings. Following a multidisciplinary discussion combined with RNA sequencing results, the patient was diagnosed with an autoinflammatory disease, with a suspected type Ⅰ interferonopathy. Treatment with tofacitinib resulted in gradual improvement of clinical symptoms. This case highlights the importance of detailed medical history collection, systematic physical examination and multidisciplinary collaborative diagnosis and treatment, and underscores the pivotal role of molecular diagnosis in the confirmation of rare diseases. It can provide a reference for the clinical diagnosis and management of similar rare cases.

Radiogenomics, an extension of radiomics, explores the relationship between imaging features and underlying gene expression patterns. This field is instrumental in providing reliable imaging surrogates, thus potentially representing an alternative to genetic testing. The rapidly growing area of radiogenomics that utilizes ultrasound (US) imaging seeks to elucidate the connections between US image characteristics and genomic data. In this review, the authors outline the radiogenomics workflow and summarize the applications of US-based radiogenomics. These include the prediction of gene variations, molecular subtypes, and other biological characteristics, as well as the exploration of the relationships between US phenotypes and cancer gene profiles. Although the field faces various challenges, US-based radiogenomics offers promising prospects and avenues for future research.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Radiogenomics, an extension of radiomics, explores the relationship between imaging features and underlying gene expression patterns. This field is instrumental in providing reliable imaging surrogates, thus potentially representing an alternative to genetic testing. The rapidly growing area of radiogenomics that utilizes ultrasound (US) imaging seeks to elucidate the connections between US image characteristics and genomic data. In this review, the authors outline the radiogenomics workflow and summarize the applications of US-based radiogenomics. These include the prediction of gene variations, molecular subtypes, and other biological characteristics, as well as the exploration of the relationships between US phenotypes and cancer gene profiles. Although the field faces various challenges, US-based radiogenomics offers promising prospects and avenues for future research.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Objective To evaluate the efficacy of Puerariae lobatae radix （PLR） and Anemarrhenae Rhizoma （AR） in preventing and treating Alzheimer’s disease （AD） and explore its potential mechanism of action by LC-MS serum metabolomics strategy. Methods The AD rat model was established by administering aluminum chloride （AlCl₃） and D-galactose （D-gal） for 20 weeks. The traditional Chinese medicine intervention group was given the PLR, AR, and PLR-AR extracts for 8 weeks by gavage. The model effect and efficacy were evaluated by Morris water maze test and biochemical indicators including SOD, NO, and MDA; Metabolomics research based on the UHPLC-Q/TOF-MS method was conducted, and relevant metabolic pathways were analyzed through the MetaboAnalyst online website. Results The learning and memory abilities of AD model rats were significantly decreased compared with the control group, and the levels of oxidative stress and lipid peroxides were significantly increased （P<0.05）, while the SOD content was decreased considerably （P<0.01）. The learning and memory abilities of AD model rats were improved, oxidative stress and lipid peroxidation levels were reversed, and serum SOD content was increased significantly after the intervention of PLR-AR, with better effects than single drugs. Through metabolomics, 70 differential metabolites were identified between the AD model group and the control group, mainly involving 10 pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, and unsaturated fatty acid biosynthesis, et.al. The intervention of PLR-AR could adjust 47 metabolites, with 20 metabolites showing significant differences （P<0.05）. The significantly adjusted metabolites involve 6 pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, et al. Conclusion The combination of PLR and AR could significantly improve the learning and memory abilities of AD rat models. The mechanism may be related to the improvement of oxidative stress and lipid peroxidation levels, the increase of serum SOD content, and the regulation of phenylalanine, tyrosine, and tryptophan biosynthesis pathways.

OBJECTIVE: To investigate the therapeutic potential of pseudolaric acid B (PAB) on non-alcoholic fatty liver disease (NAFLD) and its underlying molecular mechanism in vitro and in vivo. METHODS: Eight-week-old male C57BL/6J mice (n=32) were fed either a normal chow diet (NCD) or a high-fat diet (HFD) for 8 weeks. The HFD mice were divided into 3 groups according to a simple random method, including HFD, PAB low-dose [10 mg/(kg·d), PAB-L], and PAB high-dose [20 mg/(kg·d), PAB-H] groups. After 8 weeks of treatment, glucose metabolism and insulin resistance were assessed by oral glucose tolerance test (OGTT) and insulin tolerance test (ITT). Biochemical assays were used to measure the serum and cellular levels of total cholesterol (TC), triglycerides (TG), aspartate aminotransferase (AST), alanine aminotransferase (ALT), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). White adipose tissue (WAT), brown adipose tissue (BAT) and liver tissue were subjected to hematoxylin and eosin (H&E) staining or Oil Red O staining to observe the alterations in adipose tissue and liver injury. PharmMapper and DisGeNet were used to predict the NAFLD-related PAB targets. Peroxisome proliferator-activated receptor alpha (PPARα) pathway involvement was suggested by Kyoto Encyclopedia of Genes and Genomes (KEGG) and search tool Retrieval of Interacting Genes (STRING) analyses. Luciferase reporter assay, cellular thermal shift assay (CETSA), and drug affinity responsive target stability assay (DARTS) were conducted to confirm direct binding of PAB with PPARα. Molecular dynamics simulations were applied to further validate target engagement. RT-qPCR and Western blot were performed to assess the downstream genes and proteins expression, and validated by PPARα inhibitor MK886. RESULTS: PAB significantly reduced serum TC, TG, LDL-C, AST, and ALT levels, and increased HDL-C level in HFD mice (P<0.01). Target prediction analysis indicated a significant correlation between PAB and PPARα pathway. PAB direct target binding with PPARα was confirmed through luciferase reporter assay, CETSA, and DARTS (P<0.05 or P<0.01). The target engagement between PAB and PPARα protein was further confirmed by molecular dynamics simulations and the top 3 amino acid residues, LEU321, MET355, and PHE273 showed the most significant changes in mutational energy. Subsequently, PAB upregulated the genes expressions involved in lipid metabolism and mitochondrial biogenesis downstream of PPARα (P<0.05 or P<0.01). Significantly, the PPARα inhibitor MK886 effectively reversed the lipid-lowering and PPARα activation properties of PAB (P<0.05 or P<0.01). CONCLUSION PAB mitigates lipid accumulation, ameliorates liver damage, and improves mitochondrial biogenesis by binding with PPARα, thus presenting a potential candidate for pharmaceutical development in the treatment of NAFLD.
Animals ; PPAR alpha/metabolism* ; Non-alcoholic Fatty Liver Disease/pathology* ; Male ; Mice, Inbred C57BL ; Lipid Metabolism/drug effects* ; Diterpenes/therapeutic use* ; Organelle Biogenesis ; Diet, High-Fat ; Humans ; Mice ; Liver/metabolism* ; Insulin Resistance ; Mitochondria/metabolism* ; Molecular Docking Simulation

Non-steroidal anti-inflammatory drugs(NSAIDs),commonly utilized analgesics,are extensively employed for managing pain associated with musculoskeletal disorders or injuries.Recent clinical studies have demonstrated a heightened risk of bone stress injuries(BSI)in soldiers and athletes,particularly during high-intensity training,due to NSAID usage.Furthermore,the impact of NSAIDs on fracture healing is well-documented;however,the precise mechanism by which their use during training contributes to an increased incidence of stress bone injuries remains unclear.This article aims to summarize potential mechanisms through an extensive review of domestic and international literature in order to standardize the utilization and clinical management of NSAIDs,optimize pain management strategies,and prevent stress bone injuries or fractures in specific populations such as soldiers and elite athletes.

Objective:To apply quality function deployment(QFD)method to formulate management strategy for usage quality of medical equipment,so as to provide a reference for ensuring the safety of using medical equipment.Methods:A questionnaire about the guarantee for the requirement of usage quality of medical equipment was designed,so as to obtain the information of the users of clinical department of The Affiliated Xinghua Hospital to Kangda College of Nanjing Medical University for the requirement of usage quality of medical equipment in using medical equipment from February to April 2024,and confirm the important degree of the requirement.Then,the QFD method was adopted to convert the requirements of users for medical equipment to the required technical indicators of guaranteeing usage quality of medical equipment,and the priority technical guarantee measures of the important degree were quantitatively obtained.Results:A total of 478 questionnaires were issued,and 442 valid questionnaires were retrieved,and the valid recovery rate of questionnaire was 92.47%.The questionnaire identified and analyzed 12 requirements of three dimensions of users in using medical equipment,and they were converted to the top six technical guarantee measures of the strategy of quality management of using medical equipment,which included equipment function,criticality of equipment mission,type of service provider,compliance of rules and regulations,requirements of maintenance,and service life.Conclusion:QFD method can help medical engineering department to establish a management system of usage quality with quantitative analysis for medical equipment,and enhance the management level for the quality of medical equipment in medical institutions,and realize maximize benefit of medical equipment.

Objective To investigate the predictive value of maximum thickness of carotid plaque combined with triglyceride glucose(TyG)index for early neurological deterioration(END)in elderly patients with hypertension combined with acute cerebral infarction(ACI).Methods A prospective study was conducted on 120 elderly hypertensive patients with concomitant ACI admitted in our hospital between October 2022 and October 2024.According to the occurrence of END or not,they were divided into an END group(48 cases)and a non-END group(72 cases).The clinical data and ultrasound parameters were collected in all patients.Multivariate logistic regression analysis was used to determine the factors influencing the occurrence of END.ROC curve was plotted to assess the predictive value of the maximum thickness of the carotid plaque and the TyG index for END.Results The END group exhibited significantly higher SBP at admission,higher low-density lipoprotein cholesterol,TyG index and thicker maximum thickness of carotid plaque than the non-END group(P＜0.05,P＜0.01).TyG index and maximum thickness of carotid plaque were influencing factors for END occurrence in elderly hypertension patients with ACI.The AUC value of TyG index,carotid plaque maximum thickness and their combination for predicting the occurrence of END was 0.801,0.774 and 0.911,respectively,with the combination showing better predictive efficiency(P＜0.01).Conclusion TyG index and maximum thickness of carotid plaque are influencing factors for END in elderly patients with hypertension combined with ACI,and their combination has better predictive value for END in the patients.