BACKGROUND:Buqi Huoxue Compounds have significant clinical efficacy in treating ischemic stroke with Qi deficiency and phlegm stasis;however,the exact mechanism of action is not clear. OBJECTIVE:To observe the effect of Buqi Huoxue Compounds on the expression of vascular endothelial growth factor,basic fibroblast growth factor,brain-derived neurotrophic factor and autophagy related protein Beclin1 and p62 in a rat model of cerebral ischemia/reperfusion. METHODS:Forty male Sprague-Dawley rats were randomly divided into sham operation group,model group,Buqi Huoxue Compounds group and autophagy inhibitor group,with 10 rats in each group.In the latter three groups,a rat model of cerebral ischemia/reperfusion injury was established.The Buqi Huoxue Compounds group was intragastrically given Buqi Huoxue Compounds(6.49 g/kg,administered three times a day)2 hours after reperfusion;the autophagy inhibitor group was intragastrically given Buqi Huoxue Compounds(6.49 g/kg,administered three times a day)2 hours after reperfusion and intraperitoneally given 3-methyladenine 2 hours before gavage and at days 1-3 of gavage.The sham operation group and model group were given equal amounts of saline by gavage for 7 consecutive days.Neurological function,cerebral infarct volume,brain tissue morphology and expression of vascular endothelial growth factor,basic fibroblast growth factor,brain-derived neurotrophic factor and autophagy-related proteins Beclin1 and p62 in the ischemic cortical region of rats were detected at 24 hours after the final administration. RESULTS AND CONCLUSION:Zea-Longa scoring results showed that the neurological function of rats was severely damaged after modeling and neurological deficit of rats in the Buqi Huoxue Compounds group was less than that in the model group and the autophagy inhibitor group(P＜0.05).TTC staining showed that cerebral infarct foci were observed in the model group,Buqi Huoxue Compounds group,and autophagy inhibitor group,and the cerebral infarct volume in the Buqi Huoxue Compounds group was lower than that in the model group and the autophagy inhibitor group(P＜0.05).The results of hematoxylin-eosin staining in ischemic brain tissues showed that there were large gaps between nerve cells in the model group and cell arrangement was not neat,and cytoplasmic agglutination and pyknosis were observed.Immunohistochemical staining results showed that vascular endothelial growth factor was mostly expressed in neuronal cells,glial cells and capillary endothelium;basic fibroblast growth factor and brain-derived neurotrophic factor were mostly expressed in neuronal cells and glial cells;and there was no significant difference in the expression of vascular endothelial growth factor,basic fibroblast growth factor,and brain-derived neurotrophic factor among the four groups(P＞0.05).The results of western blot assay showed that compared with the sham operation group,Beclin1 protein expression was decreased(P＜0.05)and p62 protein expression was elevated(P＜0.05)in the model group;compared with the model group,Beclin1 protein expression was increased(P＜0.05)and p62 protein expression was reduced(P＜0.05)in the Buqi Huoxue Compounds group;compared with the Buqi Huoxue Compounds group,Beclin1 protein expression was decreased(P＜0.05)and p62 protein expression was elevated(P＜0.05)in the autophagy inhibitor group.To conclude,Buqi Huoxue Compounds attenuate cerebral ischemia-reperfusion injury in rats by promoting autophagy.

Anti-tumor drug research and development in non-small cell lung cancer (NSCLC) is rapidly developing, and the clinical application of high-throughput sequencing technology is also becoming widespread. Accordingly, researchers are focusing on human epidermal growth factor receptor-2 (HER-2) gene as a rare target of NSCLC, and a series of exploratory studies has been performed. Traditional chemotherapy and immunotherapy are unsatisfactory in the HER-2 mutant population, whereas the survival improvement of anti-HER-2 monoclonal antibodies and pan-HER inhibitors is limited. The development of antibody drug conjugate (ADC) ushers in a turning point for HER-2-mutated NSCLC, and new ADC drugs represented by trastuzumab deruxtecan are making a breakthrough. It opens up a new era of precision therapy for advanced HER-2-mutated NSCLC. Additionally, novel HER-2 inhibitors show very encouraging initial efficacy and safety, and clinical trials are ongoing. This review focuses on the latest progress of research on HER-2-mutated NSCLC.

ObjectiveTo investigate the demyelination induced by Angiostrongylus cantonensis （AC） infection in the brain of Balb/c mice and analyze the untargeted metabolomic changes in the corpus callosum， aiming to elucidate the underlying mechanisms. MethodsBalb/c mice were randomly assigned to a control group （n=6） and an infection group （n=6）. The infection group was orally administered 30 third-stage larvae of AC， while the control group received an equal volume of saline. Body weight， visual function， and behavioral scores were measured on post-infection 3， 6， 9， 12， 15， 18， and 21 days to assess neurological alterations. After 21 days， brain tissues were harvested for immunofluorescence staining， hematoxylin-eosin （HE） staining， and transmission electron microscopy to examine morphological changes in brain myelin and retina. Metabolomics analysis was performed， and differential metabolites were identified using volcano plots and heatmaps. The distribution of fold changes and bar charts were used to profile the key metabolites. These differential metabolites were then subjected to Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis and regulatory network analysis. ResultsOn the 9th day after AC infection， Balb/c mice showed a decline in neurological behavioral scores （P<0.05）. By day 15， visual scores decreased （P<0.05）， and by day 21， significant weight loss （P＜0.001） and mortality were observed. Concurrently， transmission electron microscopy and immunofluorescence staining revealed significant myelin damage in the corpus callosum and a marked reduction in oligodendrocytes （P<0.001）. HE staining showed severe retinal ganglion cell damage. Metabolomic analysis revealed that glycerophospholipids were the most abundant differential metabolites， with steroids and sphingolipids being relatively less abundant. Cholesteryl ester CE （20：2） was significantly upregulated （P<0.001）， while phosphatidylmethanol （18：0_18：1） was significantly downregulated （P<0.01）. KEGG enrichment and regulatory network analyses demonstrated that the differential metabolites were mainly enriched in metabolic pathways like steroid biosynthesis， bile secretion， and cholesterol metabolism， and were involved in key metabolic pathways such as sphingolipid metabolism， neural signal regulation， and glycerophospholipid metabolism. ConclusionsAC infection affects the metabolic state of mice via multiple pathways， modifying the levels of metabolites crucial for myelination and myelin stability. Demyelination may be closely linked to the disruption of these key metabolic pathways， particularly the dysregulation of cholesterol and sphingolipid metabolism， potentially playing a central role in demyelination onset. Furthermore， alterations in phospholipid metabolism and abnormal nerve signaling regulation may exacerbate myelin damage.

Objective: To summarize the laboratory findings of a case of hemolytic disease of the fetus and newborn (HDFN) caused by Rh system anti-c antibodies and to review the literature, so as to explore the characteristics of anti-c HDFN. Methods: The ABO blood type, Rh blood type, direct antiglobulin test (DAT) results, and the presence of unexpected antibodies and their titers were determined by serological methods. The cases of anti-c HDFN in our laboratory in China and abroad were statistically analyzed, and the incidence of severe HDFN caused by anti-c, anti-D and anti-E was compared. Results: The blood type of the child was B (Rh CcDee) with a positive DAT. Anti-c antibody was detected in both serum and eluate, with a serum antibody titer of 4. The mother’s blood type was AB (Rh CCDee) with a negative DAT, and anti-c antibody was detected in the serum with a titer of 128. Among 20 cases of anti-c HDFN, 17 were DAT positive, and 9 (45%, 9/20) underwent blood transfusion or exchange transfusion. The incidence of severe HDFN was 47.60% (10/21) for anti-c, 47.60% (10/21) for anti-D and 31.30% (5/16) for anti-E. Conclusion: Maternal pregnancy and/or blood transfusion are the main reasons for the production of Rh alloantibodies such as anti-c. The prevention and management of anti-c should be similar to that of anti-D. Rh antigen-matched (five antigens of Rh blood group) transfusion is necessary for women of childbearing age to avoid antibody production, and Rh typing and antibody screening during prenatal examination is recommended to ensure early detection, intervention and treatment.

Objective To explore the potential causal relationship between occupational pneumoconiosis (hereinafter referred to as "pneumoconiosis") and five mental disorders (depression, bipolar disorder, schizophrenia, insomnia and anxiety) using the two-sample Mendelian randomization (MR) method. Methods Single nucleotide polymorphisms (SNPs) loci associated with pneumoconiosis and five mental disorders were screened from Genome-Wide Association Studies. Inverse variance weighting (IVW), weighted median (WM) and MR-Egger regression methods were used to evaluate the significance of the causal relationship between pneumoconiosis and five mental disorders. Sensitivity analysis was used to evaluate the accuracy and reliability of the research results. Results After matching data of pneumoconiosis and the five mental disorders, 16 SNPs were ultimately included as instrumental variables in this study. The result of MR analysis revealed a positive causal relationship between pneumoconiosis and both depression [IVW: odds ratio (OR) and 95% confidence interval (CI) was 1.017 (1.000-1.035), P<0.05] and bipolar disorder [IVW: OR(95%CI)was 1.046(1.009-1.083), P<0.05; WM: OR (95%CI) was 1.055(1.007-1.105), P<0.05]. Result of sensitivity analysis indicated there was no heterogeneity and horizontal pleiotropy in the above results. There was no causal association observed between pneumoconiosis and schizophrenia, insomnia, or anxiety disorders (all P>0.05). Conclusion This study provides genetic evidence supporting a positive causal relationship between pneumoconiosis and both depression and bipolar disorder.

ObjectiveFunctional near-infrared spectroscopy (fNIRS), a novel non-invasive technique for monitoring cerebral activity, can be integrated with upper limb rehabilitation robots to facilitate the real-time assessment of neurological rehabilitation outcomes. The rehabilitation robot is designed with 3 training modes: passive, active, and resistance. Among these, the resistance mode has been demonstrated to yield superior rehabilitative outcomes for patients with a certain level of muscle strength. The control modes in the resistance mode can be categorized into dynamic and static control. However, the effects of different control modes in the resistance mode on the motor function of patients with upper limb hemiplegia in stroke remain unclear. Furthermore, the effects of force, an important parameter of different control modes, on the activation of brain regions have rarely been reported. This study investigates the effects of dynamic and static resistance modes under varying resistance levels on cerebral functional alterations during motor rehabilitation in post-stroke patients. MethodsA cohort of 20 stroke patients with upper limb dysfunction was enrolled in the study, completing preparatory adaptive training followed by 3 intensity-level tasks across 2 motor paradigms. The bilateral prefrontal cortices (PFC), bilateral primary motor cortices (M1), bilateral primary somatosensory cortices (S1), and bilateral premotor and supplementary motor cortices (PM) were examined in both the resting and motor training states. The lateralization index (LI), phase locking value (PLV), network metrics were employed to examine cortical activation patterns and topological properties of brain connectivity. ResultsThe data indicated that both dynamic and static modes resulted in significantly greater activation of the contralateral M1 area and the ipsilateral PM area when compared to the resting state. The static patterns demonstrated a more pronounced activation in the contralateral M1 in comparison to the dynamic patterns. The results of brain network analysis revealed significant differences between the dynamic and resting states in the contralateral PFC area and contralateral M1 area (F=4.709, P=0.038), as well as in the contralateral PM area and ipsilateral M1 area (F=4.218, P=0.049). Moreover, the findings indicated a positive correlation between the activation of the M1 region and the increase in force in the dynamic mode, which was reversed in the static mode. ConclusionBoth dynamic and static resistance training modes have been demonstrated to activate the corresponding brain functional regions. Dynamic resistance modes elicit greater oxygen changes and connectivity to the region of interest (ROI) than static resistance modes. Furthermore, the effects of increasing force differ between the two modes. In patients who have suffered a stroke, dynamic modes may have a more pronounced effect on the activation of exercise-related functional brain regions.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

ObjectiveTo investigate the clinical features and outcomes of recompensation in patients with autoimmune hepatitis （AIH）-related decompensated cirrhosis， to identify independent predictive factors， and to construct a nomogram prediction model for the probability of recompensation. MethodsA retrospective cohort study was conducted among the adult patients with AIH-related decompensated cirrhosis who were admitted to The Fifth Medical Center of PLA General Hospital from January 2015 to August 2023 （n=211）. The primary endpoint was achievement of recompensation， and the secondary endpoint was liver-related death or liver transplantation. According to the outcome of the patients at the end of the follow-up， the patients were divided into the recompensation group （n=16） and the persistent decompensation group（n=150）.The independent-samples t test was used for comparison of normally distributed continuous data with homogeneity of variance， and the Mann-Whitney U rank sum test was used for comparison of non-normally distributed continuous data with heterogeneity of variance； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups； the Kaplan-Meier method was used for survival analysis； the Cox proportional-hazards regression model was used to identify independent predictive factors， and a nomogram model was constructed and validated. ResultsA total of 211 patients were enrolled， with a median age of 55.0 years and a median follow-up time of 44.0 months， and female patients accounted for 87.2%. Among the 211 patients， 61 （with a cumulative proportion of 35.5%） achieved recompensation. Compared with the persistent decompensation group， the recompensation group had significantly higher white blood cell count， platelet count （PLT）， total bilirubin （TBil）， alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， total bile acid， prothrombin time， international normalized ratio （INR）， SMA positive rate， Model for End-Stage Liver Disease （MELD） score， Child-Pugh score， and rate of use of glucocorticoids （all P0.05）， as well as significantly lower age at baseline， number of complications， and death/liver transplantation rate （all P0.05）. At 3 and 12 months after treatment， the recompensation group had continuous improvements in AST， TBil， INR， IgG， MELD score， and Child-Pugh score， which were significantly lower than the values in the persistent decompensation group （all P0.05）， alongside with continuous increases in PLT and albumin， which were significantly higher than the values in the persistent decompensation group （P0.05）. The multivariate Cox regression analysis showed that baseline ALT （hazard ratio ［HR］=1.067， 95% confidence interval ［CI］： 1.010 — 1.127， P=0.021）， IgG （HR=0.463，95%CI：0.258 — 0.833， P=0.010）， SMA positivity （HR=3.122，95%CI：1.768 — 5.515， P0.001）， and glucocorticoid therapy （HR=20.651，95%CI：8.744 — 48.770， P0.001） were independent predictive factors for recompensation， and the nomogram model based on these predictive factors showed excellent predictive performance （C-index=0.87，95%CI：0.84 — 0.90）. ConclusionAchieving recompensation significantly improves clinical outcomes in patients with AIH-related decompensated cirrhosis. Baseline SMA positivity， a high level of ALT， a low level of IgG， and corticosteroid therapy are independent predictive factors for recompensation. The predictive model constructed based on these factors can provide a basis for decision-making in individualized clinical management.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.