ObjectiveThis Study was conducted to investigate the interaction mechemisms between gutmicrobiota dysregulation and ischemic stroke by establishing a rat model of ischemic stroke and employing fecal microbiota transplantation (FMT). MethodsA preliminary experiment was conducted to establish an antibiotic-induced pseudo-sterile (ABX) rat model through antibiotic treatment, and a cerebral ischemia model was prepared using the middle cerebral artery occlusion (MCAO) method. Fecal microbiota from stroke patients and healthy individuals were transplanted via FMT, followed by behavioral testing. 16S rRNA sequencing was used to analyze the microbial community, hematoxylin and eosin (HE) staining to observe histopathological status, transmission electron microscopy (TEM) to examine the tight junction structure of the small intestine, and enzyme-linked immunosorbent assay (ELISA) to detect levels of inflammatory factors and intestinal barrier-related markers. Results16S rRNA sequencing of fecal samples showed that compared with the normal control group and the metronidazole group, the abundance and diversity of fecal microorganisms in the quadruple antibiotic group were significantly reduced, indicating successful establishment of the ABX model. After transplanting fecal microbiota from stroke patients into ABX rats, significant changes in gut microbiota composition were observed. Behavioral tests revealed that the MCAO model group showed significant decreases in both horizontal movement and vertical exploration abilities. ELISA results indicated that IL-17 concentration in the ABX+mFMT (antibiotic-treated+model fecal microbiota transplantation) group was lower than in the ABX+cFMT (antibiotic-treated+control fecal microbiota transplantation) group, suggesting that IL-17 may serve as a key inflammatory indicator for evaluating the impact of stroke intervention on gut microbiota. Triphenyltetrazolium chloricle staining (TTC) staining suggested that gut microbiota intervention may increase the risk of stroke. HE staining showed that, except for the control group, all groups exhibited ischemic changes and inflammatory infiltration in brain tissues. TEM revealed that microvilli of small intestinal epithelial cells in the ABX+mFMT group were sparser than those in the ABX+cFMT group, indicating that microbial intervention affects intestinal barrier function. ConclusionThe ABX model established using broad-spectrum antibiotics showed no significant differences in physiological characteristics compared to normal rats, and the findings were consistent with those from germ-free rat models. Stroke prognosis appears to be influenced by intestinal dysbiosis, accompanied by significantly elevated levels of the pro-inflammatory cytokine IL-17, which may exacerbate neural injury via the gut-brain axis. Behavioral experiments indicated that transplantation of gut microbiota from stroke rats impaired cognitive function. Furthermore, IL-17 demonstrated sensitivity to alterations in the gut microbiota, suggesting its potential as a key therapeutic target for stroke intervention.

ObjectiveThis Study was conducted to investigate the interaction mechemisms between gutmicrobiota dysregulation and ischemic stroke by establishing a rat model of ischemic stroke and employing fecal microbiota transplantation (FMT). MethodsA preliminary experiment was conducted to establish an antibiotic-induced pseudo-sterile (ABX) rat model through antibiotic treatment, and a cerebral ischemia model was prepared using the middle cerebral artery occlusion (MCAO) method. Fecal microbiota from stroke patients and healthy individuals were transplanted via FMT, followed by behavioral testing. 16S rRNA sequencing was used to analyze the microbial community, hematoxylin and eosin (HE) staining to observe histopathological status, transmission electron microscopy (TEM) to examine the tight junction structure of the small intestine, and enzyme-linked immunosorbent assay (ELISA) to detect levels of inflammatory factors and intestinal barrier-related markers. Results16S rRNA sequencing of fecal samples showed that compared with the normal control group and the metronidazole group, the abundance and diversity of fecal microorganisms in the quadruple antibiotic group were significantly reduced, indicating successful establishment of the ABX model. After transplanting fecal microbiota from stroke patients into ABX rats, significant changes in gut microbiota composition were observed. Behavioral tests revealed that the MCAO model group showed significant decreases in both horizontal movement and vertical exploration abilities. ELISA results indicated that IL-17 concentration in the ABX+mFMT (antibiotic-treated+model fecal microbiota transplantation) group was lower than in the ABX+cFMT (antibiotic-treated+control fecal microbiota transplantation) group, suggesting that IL-17 may serve as a key inflammatory indicator for evaluating the impact of stroke intervention on gut microbiota. Triphenyltetrazolium chloricle staining (TTC) staining suggested that gut microbiota intervention may increase the risk of stroke. HE staining showed that, except for the control group, all groups exhibited ischemic changes and inflammatory infiltration in brain tissues. TEM revealed that microvilli of small intestinal epithelial cells in the ABX+mFMT group were sparser than those in the ABX+cFMT group, indicating that microbial intervention affects intestinal barrier function. ConclusionThe ABX model established using broad-spectrum antibiotics showed no significant differences in physiological characteristics compared to normal rats, and the findings were consistent with those from germ-free rat models. Stroke prognosis appears to be influenced by intestinal dysbiosis, accompanied by significantly elevated levels of the pro-inflammatory cytokine IL-17, which may exacerbate neural injury via the gut-brain axis. Behavioral experiments indicated that transplantation of gut microbiota from stroke rats impaired cognitive function. Furthermore, IL-17 demonstrated sensitivity to alterations in the gut microbiota, suggesting its potential as a key therapeutic target for stroke intervention.

ObjectiveTo investigate the status of overlapping hepatitis B virus （HBV） infection in patients with chronic hepatitis C virus （HCV） infection and the serological characteristics of such patients. MethodsA total of 8 637 patients with HCV infection who were hospitalized from January 1， 2010 to December 31， 2020 and had complete data of HBV serological markers were enrolled， and the composition ratio of patients with overlapping HBV serological markers was analyzed among the patients with HCV infection. The patients were divided into groups based on age and year of birth， and serological characteristics were analyzed， and the distribution of HBV-related serological characteristics were analyzed across different HCV genotypes. ResultsThe patients with HCV/HBV overlapping infection accounted for 5.85%， and the patients with previous HBV infection accounted for 48.10%； the patients with protective immunity against HBV accounted for 14.67%， while the patients with a lack of protective immunity against HBV accounted for 31.39%. The patients were divided into groups based on age： in the 0 — 17 years group， the patients with protective immunity against HBV accounted for 61.41% （304 patients）； the 18 — 44 years group was mainly composed of patients with previous HBV infection （698 patients， 37.31%）， the 45 — 59 years group was predominantly composed of patients with previous HBV infection （1 945 patients， 50.38%）， and the ≥60 years group was also predominantly composed of patients with previous HBV infection （1 486 patients， 61.66%）. The patients were divided into groups based on the year of birth： in the pre-1992 group， the patients with previous HBV infection accounted for 51.63% （4 112 patients）； in the 1992 — 2005 group， the patients with protective immunity against HBV accounted for 54.72% （168 patients）； in the post-2005 group， the patients with protective immunity against HBV accounted for 64.38% （235 patients）. In this study， 6 301 patients underwent HCV genotype testing： the patients with genotype 1b accounted for the highest proportion of 51.71% （3 258 patients）， followed by those with genotype 2a （1 769 patients， 28.07%）， genotype 3b （63 patients， 1.00%）， genotype 3a （10 patients， 0.16%）， genotype 4 （21 patients， 0.33%）， and genotype 6a （5 patients， 0.08%）. ConclusionWith the implementation of hepatitis B planned vaccination program in China， there has been a significant reduction in the proportion of patients with previous HBV infection among the patients with HCV/HBV overlapping infection， but there is still a relatively high proportion of patients with a lack of protective immunity against HBV.

ObjectiveTo identify potential influencing factors of urate crystal deposition at ankle/foot in patients with hyperuricemia （HUA）， and to analyze the predictive value of inflammatory indicators for urate crystal deposition in patients with different traditional Chinese medicine （TCM） syndromes， so as to provide potential reference for clinical risk assessment and individualized TCM intervention. MethodsA retrospective study was carried out with the enrollment of 231 HUA patients from The Third Affiliated People's Hospital of Fujian University of Traditional Chinese Medicine between January 2021 and December 2024. The enrolled patients were further divided into a crystal deposition-positive group （143 cases） and a crystal deposition-negative group （88 cases） according to the results of dual-energy computed tomography （CT）. Sociodemographic data， living habits， serum uric acid levels， and inflammatory indicators of the enrolled patients were collcted， and TCM syndrome differentiation was performed. Furthermore， univariate analysis was used to compare inter-group differences in clinical characteristics. MMultivariate Logistic regression was applied to identify the influencing factors of urate crystal deposition. In addition， the receiver operating characteristic （ROC） curves were plotted to evaluate the predictive efficacy of inflammatory indicators for crystal deposition across different TCM syndromes. ResultsThere were statistically significant inter-group differences in the proportion of males， age， body mass index， proportion of mental labor， rate of low water intake， and rate of high-sugar beverage consumption （P<0.05），whereas no significant difference in low exercise intensity was found between the two groups. Furthermore， compared with the negative group， the positive group had higher serum uric acid level， neutrophil-to-lymphocyte ratio （NLR）， and platelet-to-lymphocyte ratio （PLR）， but lower systemic immune-inflammation index （SIRI） （P<0.05）. Regarding the distribution of TCM syndromes， the positive group was dominated by the dampness-heat accumulation syndrome （55/143，38.46%）， while the negative group was mainly characterized by the phlegm-turbidity obstruction syndrome （44/88，50.00%）. Multivariate Logistic regression analysis revealed that high-sugar beverage consumption， elevated NLR， and elevated PLR were risk factors for urate crystal deposition ［odd ratio （OR） = 8.002， 5.377， 1.034， respectively； 95% CI 1.572-40.732， 2.179-13.270， 1.013-1.054，all P<0.05］， while SIRI was a protective factor （OR = 0.869， 95% CI 0.778-0.971， P<0.05）. In the positive group， patients with the dampness-heat accumulation syndrome exhibited the highest NLR， while the lowest PLR and SIRI， showing statistically significant differences with those of other syndromes （all P<0.05）. In addition， ROC curve analysis indicated that for the dampness-heat accumulation syndrome， the combined "NLR + PLR" model had an area under the curve （AUC） of 0.901 （95% CI 0.850-0.951， P<0.01）， with a sensitivity of 89.1% and a specificity of 79.5%； for the blood stasis-heat obstruction syndrome， the combined "NLR + PLR" model had an AUC of 0.880 （95% CI 0.825-0.934， P<0.01）， with a sensitivity of 100.0% and a specificity of 67.3%； for the liver-kidney Yin-deficiency syndrome， the single PLR model had an AUC of 0.842 （95% CI 0.731-0.952， P<0.01）， with a sensitivity of 83.3% and a specificity of 84.0%. ConclusionUrate crystal deposition in HUA patients exhibits intimate associations with high-sugar beverage consumption as well as elevated NLR and PLR levels. Meanwhile， TCM syndrome differentiation has potential correlation with inflammatory characteristics. The inflammatory indicator-based prediction model constructed based on TCM syndromes exhibits good predictive value.

ObjectiveTo investigate the key targets of Jianpi Yiqi prescription （JYP） in the treatment of hepatocellular carcinoma （HCC） based on network pharmacology and explore the effect of JYP on the invasion and proliferation of hepatocellular carcinoma cells via protein tyrosine phosphatase， non-receptor type 1 （PTPN1） by bioinformatics analysis and CRISPR/Cas9. MethodsThe potential targets of JYP in the treatment of HCC were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， SwissTargetPrediction， GeneCards， NCBI， and CTD. Additionally， the active components of JYP that could interact with PTPN1 were screened out， and then molecular docking between the targets and active components was performed in Autodock 4.0. UALCAN， HPA， and LinkedOmics were used to analyze the expression of PTPN1 in the HCC tissue， and the relationship of PTPN1 expression with the overall survival （OS） of HCC patients was discussed. CRISPR/Cas9 was used to knock down the expression of PTPN1 in HepG2 and SK-hep-1 cells， and the knockdown effect was examined by sequencing， Real-time PCR， and Western blot. HepG2 cells were classified into blank control， low-， medium-， and high-dose JYP （5.25， 10.5， 21 g·kg^-1）， and PTPN1 knockout groups. Real-time PCR and Western blot were employed to determine the mRNA and protein levels， respectively， of PTPN1 in HepG2 cells of each group. The effects of JYP and PTPN1 knockdown on the proliferation， invasion， and apoptosis of HepG2 cells were detected by Cell Counting Kit-8 （CCK-8）， Transwell， and Annexin V-FITC/PI methods， respectively. ResultsJYP had the most active components targeting PTPN1， and 31 of the active components had the binding energy less than -5.0 kcal·mol^-1 in molecular docking. The mRNA and protein levels of PTPN1 in the HCC tissue were higher than those in the normal tissue （P<0.01）. Compared with that in the normal tissue， the mRNA level of PTPN1 in the HCC tissue was up-regulated at the pathological stages Ⅰ-Ⅲ and grades G₁-G₃ （P<0.01）， and it was not significantly up-regulated at the stage Ⅳ or grade G₄. The mRNA level of PTPN1 in the TP53-mutated HCC tissue was higher than that in the TP53-unmutated HCC tissue （P<0.01）. The high mRNA level of PTPN1 was associated with the OS reduction （P<0.01）. After treatment with the JYP-containing serum or knockdown of PTPN1， HepG2 cells demonstrated decreased proliferation and invasion and increased apoptosis （P<0.01）. ConclusionPTPN1 may be one of the core targets of JYP in the treatment of HCC. It is highly expressed in the HCC tissue and cells， which is associated with the poor prognosis of patients. The expression level of PTPN1 is significantly up-regulated in the HCC tissue of the patients with TP53 mutation. However， TP53 mutation or deletion does not affect the expression of PTPN1 in HCC cells. JYP can significantly down-regulate the expression of PTPN1 to inhibit the proliferation and invasion and promote the apoptosis of HCC cells.

AIM: To investigate the effects of insulin-like growth factor 1(IGF-1)on the secretion of transforming growth factor β2(TGF-β2), matrix metalloproteinase 2(MMP-2)and hypoxia-inducible factor 1α(HIF-1α)in human scleral fibroblasts(HSF)and their mechanism.METHODS: The cells were cultured with IGF-1 and PI3K/AKT pathway inhibitor LY294002, respectively. CCK-8 method was used to detect cell viability and determine the optimal concentration and time of drug action. Cell migration activity was observed by cell scratch method. To determine the effects of IGF-1 on HSF cells and the regulatory role of PI3K/AKT pathway, HSF cells were divided into control group(without drugs), IGF-1(80 μg/L)group, IGF-1+LY294002(80 μg/L+5 mmol/L)group, and LY294002(5 mmol/L)group, and were cultured for 24 h; the protein expression levels of TGF-β2, MMP-2, HIF-1α, PI3K and AKT were detected by Western blot; the fluorescence expression of TGF-β2, MMP-2 and HIF-1α was detected by cellular immunofluorescence.RESULTS: The results of CCK-8 showed that the cell viability of the 80 μg/L IGF-1 group cultured with different concentrations of IGF-1 was the highest(all P<0.05), and the cell viability of the 80 μg/L IGF-1 group at 24 h was the highest under different culture times. Therefore, the concentration of IGF-1 was selected as 80 μg/L for 24 h. The viability of cells cultured with different concentrations of LY294002 gradually decreased from 6 h(all P<0.05). According to the IC50 value, therefore, the concentration of LY294002 was selected as 5 mmol/L for 24 h. The cell scratch results showed that compared with the control group, the cell mobility of 40 μg/L and 80 μg/L IGF-1 groups was increased(all P<0.05). Compared with the control group, cell mobility in the 2.5 and 5 mmol/L LY294002 groups was decreased(all P<0.05). Western blot results showed that compared with the control group, the protein expressions of TGF-β2, MMP-2, HIF-1α, PI3K and AKT in the IGF-1 group were increased, while those in the LY294002 group were decreased(all P<0.05). Compared with the IGF-1 group, the expression levels of TGF-β2, MMP-2, HIF-1α, PI3K and AKT in the IGF-1+LY294002 group were decreased(all P<0.05). The results of cell immunofluorescence showed that compared with the control group, the fluorescence expressions of TGF-β2, MMP-2 and HIF-1α in the IGF-1 group were increased, while those in the LY294002 group were decreased(all P<0.05). Compared with the IGF-1 group, the fluorescence expressions of TGF-β2, MMP-2 and HIF-1α in the IGF-1+LY294002 group were significantly decreased(all P<0.05).CONCLUSION: IGF-1 promoted the proliferation and migration of human HSF. IGF-1 may up-regulate the expression of TGF-β2, MMP-2 and HIF-1α in HSF through the PI3K/AKT signaling pathway, and participate in the occurrence and development of myopia.

The innate immune system can be boosted in response to subsequent triggers by pre-exposure to microbes or microbial products, known as “trained immunity”. Compared to classical immune memory, innate trained immunity has several different features. Firstly, the molecules involved in trained immunity differ from those involved in classical immune memory. Innate trained immunity mainly involves innate immune cells (e.g., myeloid immune cells, natural killer cells, innate lymphoid cells) and their effector molecules (e.g., pattern recognition receptor (PRR), various cytokines), as well as some kinds of non-immune cells (e.g., microglial cells). Secondly, the increased responsiveness to secondary stimuli during innate trained immunity is not specific to a particular pathogen, but influences epigenetic reprogramming in the cell through signaling pathways, leading to the sustained changes in genes transcriptional process, which ultimately affects cellular physiology without permanent genetic changes (e.g., mutations or recombination). Finally, innate trained immunity relies on an altered functional state of innate immune cells that could persist for weeks to months after initial stimulus removal. An appropriate inducer could induce trained immunity in innate lymphocytes, such as exogenous stimulants (including vaccines) and endogenous stimulants, which was firstly discovered in bone marrow derived immune cells. However, mature bone marrow derived immune cells are short-lived cells, that may not be able to transmit memory phenotypes to their offspring and provide long-term protection. Therefore, trained immunity is more likely to be relied on long-lived cells, such as epithelial stem cells, mesenchymal stromal cells and non-immune cells such as fibroblasts. Epigenetic reprogramming is one of the key molecular mechanisms that induces trained immunity, including DNA modifications, non-coding RNAs, histone modifications and chromatin remodeling. In addition to epigenetic reprogramming, different cellular metabolic pathways are involved in the regulation of innate trained immunity, including aerobic glycolysis, glutamine catabolism, cholesterol metabolism and fatty acid synthesis, through a series of intracellular cascade responses triggered by the recognition of PRR specific ligands. In the view of evolutionary, trained immunity is beneficial in enhancing protection against secondary infections with an induction in the evolutionary protective process against infections. Therefore, innate trained immunity plays an important role in therapy against diseases such as tumors and infections, which has signature therapeutic effects in these diseases. In organ transplantation, trained immunity has been associated with acute rejection, which prolongs the survival of allografts. However, trained immunity is not always protective but pathological in some cases, and dysregulated trained immunity contributes to the development of inflammatory and autoimmune diseases. Trained immunity provides a novel form of immune memory, but when inappropriately activated, may lead to an attack on tissues, causing autoinflammation. In autoimmune diseases such as rheumatoid arthritis and atherosclerosis, trained immunity may lead to enhance inflammation and tissue lesion in diseased regions. In Alzheimer’s disease and Parkinson’s disease, trained immunity may lead to over-activation of microglial cells, triggering neuroinflammation even nerve injury. This paper summarizes the basis and mechanisms of innate trained immunity, including the different cell types involved, the impacts on diseases and the effects as a therapeutic strategy to provide novel ideas for different diseases.

Objective This study aims to explore the diagnostic value of medical indicators in identifying diuretic resistance(DR)among patients with heart failure(HF)using machine learning methods such as Least Absolute Shrinkage and Selection Operator(LASSO)regression.An early recognition model for diuretic resistance in heart failure patients is constructed to provide clinicians with timely intervention opportunities and reduce hospitalization duration.Methods 267 heart failure patients from Tianjin Chest Hospital were included in the study.Standard urine output and DR status were employed as dependent factors,whereas 64 clinical indicators were gathered as independent variables.Depending on the kind of dependent variable,two modeling strategies were used.The first method used LASSO regression to fit the model,and 10-fold cross-validation was used to find the ideal regularization parameter.Standard urine output was used to predict diuretic resistance in the test set.Root mean square error(RMSE),coefficient of determination(R2),and classification accuracy were employed to assess the model's performance.In the second method,the most pertinent subset of features in relation to DR status was selected utilizing the max-relevance and min-redundancy(mRMR)algorithm.After that,three machine learning classifiers were used for classification:support vector machines(SVM),random forests(RF),and logistic regression(LR).Accuracy,precision,recall,area under the receiver operating characteristic curve(AUC),and F1-score were used to evaluate the model's performance.Results The optimal LASSO parameter was 0.0161.On the test set,the RMSE was 0.3489,the R2 was 0.7200,and the classification accuracy was 91.36%.The AUCs for mRMR+LR,mRMR+RF,and mRMR+SVM were 0.94,0.89,and 0.95,respectively.Their accuracies were 0.86,0.77,and 0.90;precisions were 0.87,0.80,and 0.90;recalls were 0.86,0.75,and 0.90;and F1-scores were 0.86,0.75,and 0.90,respectively.In the validation set,the LASSO regression model outperformed the other machine learning methods in predictive performance.Conclusion Diuretic resistance in heart failure patients was successfully detected by both the LASSO regression model and mRMR-based machine learning classifiers.The LASSO regression model performed better than the mRMR-based classifiers,providing more accurate scientific evidence for early clinical intervention.

The field(emergency)rapid inspection systems involving in the backpack,chest,vehicle and shelter had their research advances introduced and characteristics and deficiencies analyzed,and some improvement suggestions were put forward accordingly.It's pointed out the backpack,chest,vehicle and shelter be combined effectively to enhance the mobility and flexibility of field(emergency)rapid inspection systems.References were provided for the future enhancement and effecient operation of field(emergency)rapid inspection systems.[Chinese Medical Equipment Journal,2025,46(2):80-86]