Objective To investigate the seroprevalence of antibody against Toxoplasma gondii among patients with hematological malignancies, and compare it with that among health individuals, so as to provide insights into unraveling the pathogenesis of hematological malignancies. Methods A total of 225 patients with hematological malignancies in Department of Hematology, Xuzhou Central Hospital and 300 healthy individuals in the same hospital were enrolled from 2017 to 2024. Blood samples were collected from all subjects, and the serum IgG and IgM antibodies against T. gondii were detected using chemiluminescent immunoassay. Demographic and clinical features were collected from patients with hematological malignancies, including gender, age, contact with cats, consumption of raw or undercooked meat, type of malignancy, clinical symptoms, blood transfusion and treatment, and the seroprevalence of anti-T. gondii antibody was compared among patients with different characteristics. Results The age (t = 0.72, P > 0.05) and gender (χ² = 0.93, P > 0.05) were compared between patients with hematological malignancies and healthy individuals. The seroprevalence of T. gondii infection was 20.89% among patients with hematological malignancies and 4.33% among healthy individuals (χ² = 34.81, P < 0.01), and the seroprevalence of anti-T. gondii IgG antibody was 20.89% among patients with hematological malignancies and 4.33% among healthy individuals (χ² = 34.81, P < 0.01), while there was no significant difference in the seroprevalence of anti-T. gondii IgM antibody between patients with hematological malignancies and healthy individuals (1.33% vs. 0; corrected χ² = 2.02, P > 0.05). The seroprevalence of T. gondii infection was 23.08% among patients with leukemia, 16.67% among patients with lymphoma, 19.23% among patients with multiple myeloma, 24.00% among patients with myeloproliferative neoplasm, and 26.09% among patients with myelodysplastic syndrome (χ² = 1.44, P > 0.05), and was all higher than among healthy individuals (corrected χ² = 23.92, 10.74, 13.76, 12.84 and 14.54; all P values < 0.01). In addition, there were no significant differences in the detection of anti-T. gondii antibody among patients with hematological malignancies in terms of gender, age, contact with cats, consumption of raw or undercooked meat, chemotherapy or blood transfusion (χ² = 0.76, 1.97, 0, 2.81, 2.38 and 0.66; all P values > 0.05). Conclusions There is a high risk of T. gondii infection among patients with hematological malignancies, and intensified surveillance of T. gondii infection is recommended among patients with hematological malignancies.

Methamphetamine abuse is a major public health problem in the world,and in recent years,methamphetamine is also the most abused synthetic drug in China.The neurotoxic or addiction mechanism of methamphetamine has not been fully clarified,and there is still a lack of specific withdrawal methods and drugs for methamphetamine abuse.Mitochondria are not on-ly the organelles to which methamphetamine directly produces toxic effects,but also participate in regulating the neurotoxic damage process of methamphetamine.Mitochondrial quality is the regulatory basis for maintaining mitochondrial homeostasis and is regulated by three main mechanisms,which are mitochon-drial biogenesis,mitochondrial dynamic,and mitophagy.This review summarizes the research progress of mitochondrial quality control in methamphetamine-induced neurotoxicity,which may provide theoretical support for further research on the mechanism of methamphetamine neurotoxicity and development the mito-chondria-targeting drugs.

Modern Chinese medicine studies have confirmed that the interaction between traditional Chinese medicine(TCM)and intestinal flora is the key to the treatment of diseases with tradi-tional Chinese medicine.This interplay includes such activities as:traditional Chinese medicine can be metabolized by intestinal flora into effective components with different biological activities from its precursors;TCM chemicals improve the composition of gut microbiota,consequently ameliorating its dysfunction as well as associated pathological conditions;and gut microbiota mediate the interactions between the multiple chemicals in TCM.There-fore,it becomes an important way to understand the modern sci-entific connotation of traditional Chinese medicine theory to study the pharmacological mechanism of the efficacy of traditional Chi-nese medicine by targeting Gut microbiota.

Aim To explore the potential genes and mechanism of alisol B in the treatment of non-small cell lung cancer(NSCLC).Methods The proliferation and migration of NSCLC cells were detected by CCK-8 and Transwell.Genes of NSCLC and alisol B were col-lected through TCGA and compound gene prediction database,and their intersection genes were obtained.The network of protein-protein interaction(PPI)was constructed by using String database,and the top 20 key nodes were screened out,and the prognosis-related proteins related to the prognosis of NSCLC were screened out by using R language,and the intersection of them was obtained.The potential mechanism of ali-sol B on NSCLC was explored by KEGG and GO en-richment analysis and the relationship between related genes and immune cells,which was verified by cell-lev-el experiments.Results Alisol B inhibited the cell activity and migration ability of NSCLC cells.Five im-portant genes were identified by network pharmacologi-cal analysis:CCNE1,CDK1,COL1A1,COL1A2 and COL3A1.The results of cell experiment showed that al-isol B down-regulated the expression of Cyclin E1,CDK1 and COL1A2 in NSCLC cells.In addition,alisol B could inhibit the expression of COL1A2 and M2 macrophage marker CD206 in macrophages.Conclu-sions Alisol B may inhibit the proliferation of tumor cells by down-regulating CDK1 and Cyclin E1,and may affect the function of macrophages by inhibiting COL1A2,thus regulating the tumor immune microenvi-ronment and inhibiting NSCLC.

Sepsis-associated encephalopathy (SAE) is the most common neurological complication of sepsis, with an incidence of up to 70% in sepsis, and contributes to the increased mortality and disability in sepsis. To date, the exact pathogenesis of SAE is not clear. Most of current researches indicated that blood-brain barrier (BBB) dysfunction, active neuroinflammation, glial cell over activation as well as cerebral microcirculation dysfunction contributed to the pathophysiology of SAE. BBB, as a complex cellular structure between the central nervous system and the peripheral system, strictly controls the entrance and discharge of substances and plays an important role in maintaining the balance between biochemical system and immune system of central system. During the progress of sepsis, inflammatory cytokines and reactive oxygen species resulting from peripheral system directly or indirectly resulted in the damage to the integrity and structure of BBB, which helped above species easily enter into the central system. Above these damages caused glial cell activation (microglia and astrocyte), the imbalance of neurotransmitters, mitochondrial dysfunction and neural apoptosis, which also reversely contributed to the damage to the integrity and permeability of BBB via decreasing the expression of tight junctional protein between cells. Therefore, this review focuses on the structural and functional changes of BBB in SAE, and how these changes lead to the development of SAE, in order to seek a BBB-targeted therapy for SAE.

AIM To study the flavonoids from the leaves of Cinnamomum camphora(L.)Presl.and their antioxidant activities.METHODS The 95％ethanol extraction from the leaves of C.camphora was isolated and purified by liquid-liquid extraction,macroporous adsorption resin chromatography,HW-40C gel column chromatography,molecular exclusion chromatography and preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antioxidant activity was determined by DPPH method.RESULT Ten flavonoids were isolated and identified as(2R,3S)-7-methoxy-5-O-β-D-glucopyranosyl-afzelechin(1),quercetin-3-O-sambubioside(2),quercetin-3-O-β-D-apiosyl-(1→2)-β-D-glucoside(3),quercetin-3-O-robibioside(4),kaempferol-3-O-β-D-rutinoside-7-O-β-D-glucoside(5),kaempferol-3-O-α-L-rhamnoside-7-O-β-D-glucoside(6),5,3'-di-O-methyl-epicatechin(7)、cinchonain Ⅱb(8)、quercetin-3,4'-di-O-β-D-glucoside(9)、(-)-epicatechin(10).The IC50 value of compound 8 scavenging DPPH free radical was 4.8 μg/mL.CONCLUSION Compound 1 is a new compound,and compound 2-6 are obtained from Cinnamomum genus for the first time,compound 7-9 are first isolated from this plant.Compound 8 shows good antioxidant activities..

Objective To develop an intelligent horizontal rotating cell culture device with high modularity,easy operation,easy disinfection,low cost and high stability.Methods The cell culture device consisted of a rotating culture module,a dirve module,a control module and control software,with the shells of all the modules being manufactured by 3D printing.The rotating culture module was composed of a tubular electrospun scaffold,a cell culture chamber,a magnetic coupling rotor and polypropylene pipeline;the drive module was made up of a N20 reduction motor and a magnetic coupling rotor;the control module included an ESP-8266 chip and a printed circuit board;the control software was developed with Blinker IoT platform and C++language.The device was used to culture human intrahepatic bile duct epithelial cells to verify its effects.Results Light microscopy and scanning electron microscopy images showed that a uniform and continuous cell layer was formed on the surface of the tubular electrospun scaffold.Conclusion The intelligent horizontal rotating cell culture device achieves uniform growth of cells on the inner surface of tubular electrospun scaffolds,and can be used as an effective platform for cell culture on tubular scaffolds.[Chinese Medical Equipment Journal,2024,45(9):41-45]

A boy,aged 14 years,was admitted due to recurrent cough and expectoration for more than 1 month,with aggravation and fever for 2 days. After admission,he presented with tachypnea and a significant reduction in transcutaneous oxygen saturation,and emergency chest CT examination showed large patchy exudation and consolidation of both lungs. The boy was given tracheal intubation and invasive mechanical ventilation immediately,and his condition was improved after active symptomatic treatment. On the 10th day of hospitalization,the boy experienced fever again,and the laboratory tests showed positive results for Epstein-Barr virus and Mycoplasma antibody IgM,along with pancytopenia,elevated triglycerides,decreased fibrinogen,and increased levels of ferritin and soluble CD25. The boy was diagnosed with hemophagocytic lymphohistiocytosis. Bone marrow biopsy showed the presence of atypical lymphocytes,and aggressive natural killer cell leukemia was considered according to clinical manifestations and flow cytometry immunophenotype. Therefore,the possibility of hemophagocytic lymphohistiocytosis should be suspected in case of severe infection with pancytopenia and rapid disease progression,and hematological malignancies should also be ruled out. Bone marrow biopsy should be performed as early as possible to make a confirmed diagnosis and perform timely treatment.

Objective To explore the prediction of hospital indoor microbial concentration in air based on real-time indoor air environment monitoring data and machine learning algorithms.Methods Four locations in a hospital were selected as monitoring sampling points from May 23 to June 5,2022.The"internet of things"sensor was used to monitor a variety of real-time air environment data.Air microbial concentration data collected at each point were matched,and the gradient boosting decision tree(GBDT)was used to predict real-time indoor microbial concentra-tion in air.Five other common machine learning models were selected for comparison,including random forest(RF),decision tree(DT),k-nearest neighbor(KNN),linear regression(LR)and artificial neural network(ANN).The validity of the model was verified by the mean absolute error(MAE),root mean square error(RMSE)and mean absolute percentage error(MAPE).Results The MAPE value of GBDT model in the outpa-tient elevator room(point A),bronchoscopy room(point B),CT waiting area(point C),and nurses'station in the supply room(point D)were 22.49％,36.28％,29.34％,and 26.43％,respectively.The mean performance of the GBDT model was higher than that of other machine learning models at three sampling points and slightly lower than that of the ANN model at only one sampling point.The mean MAPE value of GBDT model at four sampling points was 28.64％,that is,the predicted value deviated from the actual value by 28.64％,indicating that GBDT model has good prediction results and the predicted value was within the available range.Conclusion The GBDT machine learning model based on real-time indoor air environment monitoring data can improve the prediction accuracy of in-door air microbial concentration in hospitals.

Objective To understand the prevalence characteristics of influenza and changes of influenza virus strains,and provide reference for the prevention and control of influenza in the province.Methods Surveillance da-ta about influenza in Hunan Province from 2014 to 2023 were exported from China Influenza Surveillance Informa-tion System.Differences in the percentage of influenza-like illness(ILI)cases(percentage of influenza-like cases[ILI％]in outpatient and emergency department visits)among different years and different populations,as well as the positive rate of influenza virus in ILI specimens were compared.Results From 2014 to 2023,over 2.65 million cases of ILI were reported,with an ILI％of 4.70％.ILI％among different years presented statistically significant differences(P＜0.001).People aged 0-14 years old were the main population with ILI,accounting for 82.90％.The positive rate of influenza virus in ILI specimens was 14.14％,the positive rate of influenza virus among diffe-rent years and age groups were both significantly different(both P＜0.001).The main prevalent influenza strains from 2014 to 2023 included types A(H1N1),A(H3N2),B(Victoria),and B(Yamagata),alternating among di-fferent years.However,type B(Yamagata)strains were not detected from 2020 to 2023.There were basically two influenza prevalence seasons every year,namely winter-spring and summer.Conclusion People＜15 years old are the main population of influenza,and the prevalence peaks are in winter-spring and summer.From 2021 to 2023,the prevalence alternates mainly among 3 types:A(H1N1),A(H3N2),and B(Victoria).