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.

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.

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]

Aim To explore the effect of astragalosideⅣ(AS-Ⅳ)on lipopolysaccharide(LPS)-induced po-larization and migration of RAW 264.7 macrophages and the underlying mechanism.Methods 1 mg·L-1 LPS was used to construct cell migration model.Scratch assay was utilized to determine cell migration rate.Immunofluorescence staining was utilized to de-tect the expression and location of F4/80,iNOS and Arg-1.CCK-8 assay was used to determine the viabili-ty of RAW 264.7 cells.Griess assay was used to measure NO content.Molecular docking was used to analyze the interaction between AS-Ⅳ and the core tar-gets such as cGAS and STING protein.Western blot was employed to detect the expression of iNOS,Arg-1,cGAS,STING,NF-κB p65 and p-NF-κB p65 protein.Results AS-Ⅳ significantly inhibited the migration and M1 polarization of RAW 264.7 cells induced by LPS.Moreover,AS-Ⅳ could interact with cGAS and STING protein,especially cGAS.Further Western blot assay showed that AS-Ⅳ significantly downregulated the expression of iNOS,cGAS,STING and p-NF-κB p65 protein.Conclusions AS-Ⅳ could promote mac-rophage M1 to M2 polarization,thereby inhibited mac-rophage migration through restraining the cGAS/STING/NF-κB signaling pathway,which provides a new therapeutic target for AS-Ⅳ to improve the early inflammatory response of AS.

Objective To explore the effectiveness of an integrated laparoscopic simulation training course (best essential surgical technique training, BEST) in enhancing laparoscopic peritoneal suturing techniques in surgical residents.Methods As an integrated two-stage program, the BEST course applied basic laparoscopic training system with simple molds in phase Ⅰ training, and then adopted advanced laparoscopic training system, 3D Laparoscope and ex-vivo animal models in phase Ⅱ training. The laparoscopic suturing techniques were practiced in phase Ⅱ training. From August 2021 to July 2024, surgical residents in the second year of the national standardized training program were divided into pilot and control groups based on whether they had undergone the BEST course. Two cases of laparoscopic peritoneal suture were performed by the surgical residents under supervision in the department of gastrointestinal surgery. The operative time, quality of suture, and independent completion rate were compared between the two groups.Results A total of 33 surgical residents (19 in pilot group and 14 in control group) were included in this study, and a total of 66 cases of laparoscopic peritoneal suture were performed (38 in pilot group and 28 in control group). The operative time was significantly shorter in pilot group than that in control group (15.7 min vs. 17.5 min, P=0.025). The quality of suture was significantly better in pilot group compared to control group (P=0.023). In pilot group, all peritoneal sutures were performed by residents independently, whereas in control group, 3 cases (10.7%) were assisted by the supervisor, and the independent completion rate was different significantly (P=0.039).Conclusions The BEST course can help improve surgical residents′ laparoscopic peritoneal suturing techniques and could be promoted in the national standardized training program for surgical residents.

Objective To establish a chromatography-tandem mass spectrometry method for detecting chlorfenapyr and its metabolite tralopyril in blood,and to investigate the toxicokinetics in rats.Methods Chlorfenapyr(8 mg/kg)was administered orally to rats,and blood samples were collected from rats'canthus vein at 5 min,15 min,30 min,1 h,3 h,6 h,12 h,24 h and 48 h after administration.The blood samples were extracted using 100 μL of 5%formic acid solution and 400 μL of acetonitrile.Chlorfena-pyr was qualitatively and quantitatively detected by triple quadrupole gas chromatography-tandem mass spectrometry(GC-MS/MS)and tralopyril was detected by triple quadrupole liquid chromatography-tandem mass spectrometry(LC-MS/MS).The DAS 3.0 software was used to fit the toxicokinetic equa-tions and calculate the toxicokinetic parameters.Results Chlorfenapyr was detectable from 5 min to 24 h with a peak time of 1 h.Tralopyril was detectable from 15 min to 48 h with a peak time of 3 h.The toxicokinetic process of chlorfenapyr in rat blood conformed to a first-order absorption one-compartment open model,with the toxicokinetic equation described as C=e-0.265t-e-0.175t.Tralopyril con-formed to the first-order absorption three-compartment model,and the toxicokinetic equation was C=47 361.069e-2.209t-35 404.962e-1.486t+11 956.363e-0.512t.In the equations,C stands for the concentration of the target substance in the blood,e is the natural constant(≈2.718 28),and t stands for time.Conclu-sion This study optimized the detection method for chlorfenapyr and its metabolite tralopyril in blood.The toxicokinetic equations and parameters of chlorfenapyr and tralopyril can provide a reference for the estimation of oral intake time of chlorfenapyr.

Objective To investigate serum levels of food intake inhibitory factor-1(Nesfatin-1)and Klotho and their predictive value for secondary mild cognitive impairment(MCI)in elderly patients with type 2 diabetes mellitus(T2DM).Methods A total of 118 elderly patients with T2DM diagnosed and treated in the hospital from April 2023 to March 2024 were selected as the T2DM group,and they were divided into the non-MCI group(n=71)and the MCI group(n=47)according to the Montreal Cognitive Assessment(Mo-CA)scale.In addition,110 healthy people in the same hospital during the same period were selected as the control group.The clinical data of the patients were collected.Serum Nesfatin-1 and Klotho levels were detec-ted by enzyme-linked immunosorbent assay.Spearman and Pearson correlation analysis were used to analyze the correlation of serum Nesfatin-1 and Klotho levels with MoCA score and related clinical indicators in elder-ly patients with T2DM.Multivariate Logistic regression analysis was used to analyze the influencing factors for secondary MCI in elderly patients with T2DM.Receiver operating characteristic(ROC)curve was used to evaluate the predictive value of serum Nesfatin-1 and Klotho levels for secondary MCI in elderly patients with T2DM.Results Compared with control group,the serum levels of Nesfatin-1 and Klotho were significantly decreased in T2DM group(P<0.05).The serum levels of Nesfatin-1 and Klotho in MCI group were signifi-cantly lower than those in non-MCI group(P<0.05).Compared with the non-MCI group,the levels of fast-ing plasma glucose(FPG),insulin resistance index(HOMA-IR),reactive oxygen species(ROS)and C-reac-tive protein(CRP)were significantly increased in the MCI group(all P<0.05),and were negatively correla-ted with serum Nesfatin-1 and Klotho levels(all P<0.05).The serum levels of Nesfatin-1 and Klotho were positively correlated with MoCA score(P<0.05).Increased levels of FPG and ROS and decreased levels of Nesfatin-1 and Klotho were risk factors for secondary MCI in T2DM patients(P<0.05).The area under the curve of serum Nesfatin-1,Klotho and their combination for predicting secondary MCI in T2DM patients was 0.803,0.829 and 0.932,respectively.The combined prediction of serum nesfatin-1 and Klotho was better than each index alone(Zcombined-Nesfatin-1=3.421,P=0.001,Zcombined-Klotho=2.980,P=0.003).Conclusion The serum lev-els of Nesfatin-1 and Klotho are decreased in T2DM patients,which are significantly correlated with secondary MCI in T2DM patients,and both of them have high predictive value for secondary MCI in T2DM patients.

To explore the value of general information and rapid laboratory tests obtained from the emergency department in the early diagnosis and prevention of young patients with acute myocardial infarction and acute myocarditis, in order to prevent the disease from progressing to a critical stage. This study employs a retrospective observational study, compiling clinical data from young patients diagnosed with acute myocardial infarction or acute myocarditis who were admitted to the Department of Cardiology or Emergency Department of the Second Affiliated Hospital of Soochow University from January 2015 to September 2024. Demographic information and laboratory test results from both the outpatient and emergency departments were retrieved. The acute myocardial infarction group comprised 267 patients (257 males, 10 females) aged 23-44 ys, while the acute myocarditis group included 134 patients (93 males, 41 females) aged 18-44 ys. A comparative analysis of the clinical data between the two groups was conducted, encompassing variables such as age, gender, comorbidities, high-risk factors, emergency blood routine tests, high-sensitivity C-reactive protein levels, coagulation profiles, renal function tests, NT-proBNP levels, myocardial injury markers, electrocardiogram readings, blood pressure, and heart rate. The results showed that:Compared with the young myocarditis group, the myocardial infarction group was older (ys)[38(35, 42) vs 30(25, 37), U=7 893, P<0.001], more male [257(96.3%) vs 93(69.4%), χ2=57.95, P<0.001], more smoking [211(79.0%) vs 38(28.4%), χ2=97.32, P<0.001], drinking history [125(46.8%) vs 22(16.4%), χ2=35.51, P<0.001], family history of coronary heart disease [45(16.9%) vs 3(2.2%), χ2=18.09, P<0.001], hypertension [100(37.5%) vs 12(9.0%), χ2=36, P<0.001] and diabetes [42(15.7%) vs 4(3.0%), χ2=14.27, P<0.001]. Systolic blood pressure (mmHg)[126(114, 144) vs 119(101, 126), U=11 389.50, P<0.001], diastolic blood pressure (mmHg)[80(70, 93) vs 72(62, 81), U=12 220.50, P<0.001], total white blood cell count (10 9/L)[11.3(9.2, 14.1) vs 8.5(6.6, 11.2), U=10 825.50, P<0.001], hemoglobin (g/L)[157(147, 166) vs 143(129, 154), U=9 404.50, P<0.001], platelet count (10 9/L)[244(206, 297) vs 207(173, 253), U=11 680, P<0.001], uric acid (μmol/L)[380(315, 446) vs 347(265, 412), U=14 805.50, P=0.005], ST segment elevation [204(76.4%) vs 57(42.5%), χ2=73.03, P<0.001] and Q wave formation [76(28.5%) vs 17(12.7%), χ2=12.47, P<0.001] in ECG were higher than those in myocarditis group. The duration of onset (hs) [6(3, 25) vs 48(24, 73), U=27911, P<0.001], heart rate (beats/min)[82(74, 92) vs 92(78, 103), U=22 347, P<0.001], D-dimer (μg/ml)[0.23(0.17, 0.51) vs 0.61(0.30, 1.38), U=25 806, P<0.001], High-sensitivity troponin T/99th percentile upper reference limit [5(1, 36) vs 16(8, 39), U=22 577, P<0.001], NT-proBNP (pg/ml) [204(64, 644) vs 824(189, 4 043), U=25 134, P<0.001], C-reactive protein (mg/L)[6(3, 9) vs 24(6, 55), U=26 349.50, P<0.001] and body temperature (℃) [36.50(36.30, 36.60) vs 37.35(36.50, 38.50), U=26 961, P<0.001] were significantly lower than those in myocarditis group, the symptoms of chest pain in myocardial infarction group was significantly higher than those in myocarditis group [262(98.1%) vs 83(61.9%), χ2=97.24, P<0.001], and the history of prodromal infection [12(4.5%) vs 112(83.6%), χ2=261.26, P<0.001], syncope [11(4.1%) vs 18(13.4%), χ2=11.53, P<0.001] and shock [6(2.2%) vs 22(16.4%), χ2=27.59, P<0.001] in myocardial infarction group were significantly lower than those in myocarditis group. With acute myocardial infarction as the target outcome, 8 influencing factors selected by LASSO regression, and 5 independent influencing factors were found after multiple Logistic regression, those were age ( OR=1.21, 95% CI: 1.12-1.31; P<0.001), pre-infection ( OR=0.02, 95% CI: 0.01-0.06; P<0.001), body temperature ( OR=0.37, 95% CI: 0.18-0.77; P=0.008), chest pain ( OR=26.75, 95% CI: 5.87-121.81; P<0.001) and white blood cell count ( OR=1.27, 95% CI: 1.12-1.44; P<0.001). Younger age, high body temperature and pre-infection are independent predictors for acute myocarditis, while chest pain and elevated white blood cell count are independent predictors for acute myocardial infarction. The five influencing factors selected by multivariate logistic regression and their combined diagnostic model were subjected to ROC analysis. The AUC reached 0.969, sensitivity reached 0.940 and specificity reached 0.925. Calibration curve and decision curve analysis(DCA) demonstrate that the model possesses excellent clinical application value. In conclusion, age, chest pain, pre-infection, body temperature and white blood cell count were independent factors in distinguishing acute myocardial infarction and acute myocarditis in young people. The clinical differential diagnosis model based on 5 independent factors may has high efficiency and good clinical practicability.