Objective The purpose of this study was to investigate the bacterial communities of biting midges and ticks collected from three sites in the Poyang Lake area,namely,Qunlu Practice Base,Peach Blossom Garden,and Huangtong Animal Husbandry,and whether vectors carry any bacterial pathogens that may cause diseases to humans,to provide scientific basis for prospective pathogen discovery and disease prevention and control. Methods Using a metataxonomics approach in concert with full-length 16S rRNA gene sequencing and operational phylogenetic unit(OPU)analysis,we characterized the species-level microbial community structure of two important vector species,biting midges and ticks,including 33 arthropod samples comprising 3,885 individuals,collected around Poyang Lake. Results A total of 662 OPUs were classified in biting midges,including 195 known species and 373 potentially new species,and 618 OPUs were classified in ticks,including 217 known species and 326 potentially new species.Surprisingly,OPUs with potentially pathogenicity were detected in both arthropod vectors,with 66 known species of biting midges reported to carry potential pathogens,including Asaia lannensis and Rickettsia bellii,compared to 50 in ticks,such as Acinetobacter lwoffii and Staphylococcus sciuri.We found that Proteobacteria was the most dominant group in both midges and ticks.Furthermore,the outcomes demonstrated that the microbiota of midges and ticks tend to be governed by a few highly abundant bacteria.Pantoea sp7 was predominant in biting midges,while Coxiella sp1 was enriched in ticks.Meanwhile,Coxiella spp.,which may be essential for the survival of Haemaphysalis longicornis Neumann,were detected in all tick samples.The identification of dominant species and pathogens of biting midges and ticks in this study serves to broaden our knowledge associated to microbes of arthropod vectors. Conclusion Biting midges and ticks carry large numbers of known and potentially novel bacteria,and carry a wide range of potentially pathogenic bacteria,which may pose a risk of infection to humans and animals.The microbial communities of midges and ticks tend to be dominated by a few highly abundant bacteria.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective:To explore the role of NK cells in allogeneic hematopoietic stem cell micro-transplantation(MST)in the treatment of patients with acute myeloid leukemia(AML).Methods:Data from 93 AML patients treated with MST at our center from 2013-2018 were retrospectively analyzed.The induction regimen was anthracycline and cytarabine combined with peripheral blood stem cells transplantation mobilization by granulocyte colony stimulating factor(GPBSC),followed by 2-4 courses of intensive treatment with medium to high doses of cytarabine combined with GPBSC after achieving complete remission(CR).The therapeutic effects of one and two courses of MST induction therapy on 42 patients who did not reach CR before transplantation were evaluated.Cox proportional hazards regression analysis was used to analyze the impact of donor NK cell dose and KIR genotype,including KIR ligand mismatch,2DS1,haplotype,and HLA-Cw ligands on survival prognosis of patients.Results:Forty-two patients received MST induction therapy,and the CR rate was 57.1％after 1 course and 73.7％after 2 courses.Multivariate analysis showed that,medium and high doses of NK cells was significantly associated with improved disease-free survival(DFS)of patients(HR=0.27,P=0.005;HR=0.21,P=0.001),and high doses of NK cells was significantly associated with improved overall survival(OS)of patients(HR=0.15,P=0.000).Donor 2DS1 positive significantly increases OS of patients(HR=0.25,P=0.011).For high-risk patients under 60 years old,patients of the donor-recipient KIR ligand mismatch group had longer DFS compared to the nonmismatch group(P=0.036);donor 2DS1 positive significantly prolonged OS of patients(P=0.009).Conclusion:NK cell dose,KIR ligand mismatch and 2DS1 influence the therapeutic effect of MST,improve the survival of AML patients.

Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]

Introduction::The triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, a novel biomarker for metabolic syndrome (MetS), has been validated in the general population as being significantly correlated with cardiovascular disease (CVD) risk. However, its capabilities to predict CVD in people living with human immunodeficiency virus (HIV; PLWH) remain underexplored.Methods::We conducted a retrospective cohort study of 16,081 PLWH who initiated antiretroviral therapy (ART) at the Third People’s Hospital of Shenzhen (China) from 2005 to 2022. The baseline TG/HDL-C ratio was calculated as TG (mmol/L) divided by HDL-C (mmol/L). We employed a multivariate Cox proportional hazards model to assess the association between the TG/HDL-C ratio and CVD occurrence, using Kaplan-Meier curves and log-rank tests to compare survival distributions. The increase in prediction risk upon the addition of the biomarker to the conventional risk model was examined through the assessment of changes in net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Nonlinear relationships were investigated using a restricted cubic spline plot, complemented by a two-piecewise Cox proportional hazards model to analyze threshold effects.Results::At the median follow-up of 70 months, 213 PLWH developed CVD. Kaplan-Meier curves demonstrated a significant association between the increased risk of CVD and a higher TG/HDL-C ratio (log-rank P <0.001). The multivariate-adjusted Cox proportional hazards regression model indicated that the CVD hazard ratios (HR) (95% confidence intervals [95% CIs]) for Q2, Q3, and Q4 versus Q1 of the TG/HDL-C ratio were 2.07 (1.24, 3.45), 2.17 (1.32, 3.57), and 2.20 (1.35, 3.58), respectively ( P <0.05). The consideration of the TG/HDL-C ratio in the model, which included all significant factors for CVD incidence, improved the predictive risk, as indicated by the reclassification metrics (NRI 16.43%, 95% CI 3.35%-29.52%, P = 0.014). The restriction cubic spline plot demonstrated an upward trend between the TG/HDL-C ratio and the CVD occurrence ( P for nonlinear association = 0.027, P for overall significance = 0.009), with the threshold at 1.013. Significantly positive correlations between the TG/HDL-C ratio and CVD were observed below the TG/HDL-C ratio threshold with HR 5.88 (95% CI 1.58-21.88, P = 0.008), but not above the threshold with HR 1.01 (95% CI 0.88-1.15, P = 0.880). Conclusion::Our study confirms the effectiveness of the TG/HDL-C ratio as a predictor of CVD risk in PLWH, which demonstrates a significant nonlinear association. These findings indicate the potential of the TG/HDL-C ratio in facilitating early prevention and treatment strategies for CVD among PLWH.

Background::Scleroderma is characterized by inflammation and fibrosis, predominantly occurring in the skin and extending to various parts of the body. The pathophysiology of scleroderma is multifaceted, with the current understanding including endothelial damage, inflammatory cell infiltration, and fibroblast activation in its progression. Nonetheless, the mechanism of cellular interactions and the precise spatial distribution of these cellular events within the fibrotic tissues remain elusive, highlighting a critical gap in our comprehensive understanding of scleroderma’s pathogenesis.Methods::In this study, we administered bleomycin intradermally to the dorsal skin of four individual murine models. Subsequently, skin tissues were harvested at predetermined intervals for comprehensive spatial transcriptomic analysis to determine the spatial dynamics influencing scleroderma pathogenesis. To validate the possible results from bioinformatic analysis, further in vitro and in vivo experiments were conducted. Results::Analysis of the spatial transcriptome revealed significant alterations in cell clusters during the progression of scleroderma. Gene Ontology analysis identified disruptions in lipid metabolism as the disease advanced. Pseudotime analysis provided evidence for a phenotypic transition from adipocytes to fibroblasts. In vitro studies demonstrated increased expression of Col1a1 and α-SMA as the disease progressed. These fibroblasts have been identified as key contributors to the increasing inflammation. Co-culturing TGF-β induced adipocytes with RAW264.7 cells resulted in overexpression of pro-inflammatory cytokines in the RAW264.7 cells. Both in vitro and in vivo experiments confirmed adipocyte loss and fibroblast formation, with transformed fibroblasts showing pronounced pro-inflammatory characteristics, highlighting their crucial role in the disease mechanism. Conclusions::Our study showed the spatial distribution and dynamic alterations of various cell types during scleroderma progression. Crucially, we identified the transformation of adipocytes into fibroblasts as a key factor promoting disease advancement. These emergent fibroblasts intensify inflammation, indicating that research on these cell clusters could reveal key scleroderma mechanisms and guide future therapies.

AIM To investigate the protective effect of Mongolian medicine Naru-3 on rat rheumatoid arthritis(RA)using imaging method.METHODS With the rats divided into the normal group,the model group,the positive medicine group,and the low,medium and high dose Naru-3 groups(0.1,0.2 and 0.4 g/kg),the rat model of collagen-induced arthritis(CIA)was established by immune induction method.After 4 weeks of corresponding drug administration,the rats had their changes of arthritis index(AI)level and body weight observed;their serum levels of VEGF,TNF-α and IL-1 detected by ELISA;their synovial hyperplasia and neovascularization evaluated by high-frequency ultrasound and contrast-enhanced ultrasound(CEUS);their bone destruction of ankle joint evaluated by X-ray and high-resolution micro-CT;and their synovial membrane and expressions of CD31,VEGF,TNF-α and IL-1 β observed by HE and immunohistochemistry.RESULTS Compared with the model group,the Naru-3 groups displayed increased rat weight(P＜0.05);no significantly changed AI score(P＞0.05);and overally decreased levels of serum VEGF,TNF-α,synovial membrane thickness,blood flow signal by power Doppler imaging(PDI)and contrast intensity revealed,X-ray score,and CD31 expression(P＜0.05),in addition to the decreased level of IL-1 and HE score in high-dose group(P＜0.05).CONCLUSION Naru-3 is protective to the joint tissue in rat model of RA through alleviating synovitis,bone erosion and delaying the progress of the disease by inhibiting synovial neovascularization and inflammatory cytokines.

AIM To establish a UPLC-MS/MS method for the simultaneous content determination of gallic acid,protocatechuic acid,neomangiferin,catechin,caffeic acid,mangiferin,isomangiferin,albiflorin,paeoniflorin,vitexin,liquiritin,scutellarin,baicalin,liquiritigenin,timosaponin BⅡ,quercetin,wogonoside,benzoylpaeoniflorin,isoliquiritigenin,honokiol,magnolol,norarecaidine,arecaidine,arecoline,epicatechin,baicalein,glycyrrhizinate and wogonin in Dayuan Drink.METHODS The analysis was performed on a 35℃thermostatic Syncronis C18 column(100 mm×2.1 mm,1.7 μm),with the mobile phase comprising of 0.1%formic acid-acetonitrile flowing at 0.3 mL/min in a gradient elution manner,and electron spray inoization source was adopted in positive and negative ion scanning with select reaction monitoring mode.RESULTS Twenty-eight constituents showed good linear relationships within their own ranges(R2≥0.991 0),whose average recoveries were 95.60%-103.53%with the RSDs of 0.60%-5.45%.CONCLUSION This rapid,simple,selective,accurate and reliable method can be used for the quality control of Dayuan Drink.