1.Establishment and application of ultra-fast real-time PCR for Brucella detection
Zhen-na XU ; Zhi-peng WU ; Wei-bin HONG ; Zhi-shen GUAN ; Qi-ming LIN ; Zuan-lan MO ; Yi-fei YE ; Hai-yan XIE ; Min LI ; Yan-qiu ZHU ; Xiao-jun LI ; Xian-peng ZHANG
Chinese Journal of Zoonoses 2025;41(3):278-283
This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20%to 0.91%,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100%compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.
2.Constructing A Risk Warning Model for Severe Mycoplasma Pneumoniae Pneumonia Children Based on Clinical Multi Parameters
Wan-ting MO ; Ping-ming GAO ; Rui-ping WAN ; Hui-wen XIAN ; Dan-xia LIN
Progress in Modern Biomedicine 2025;25(3):511-518
Objective:To construct a risk warning model for severe mycoplasma pneumoniae pneumonia(SMPP)children based on clinical data,laboratory indicators and imaging indicators.Methods:162 Mycoplasma pneumoniae pneumonia(MPP)children who were admitted in Foshan Women and Children Hospital from January 2021 to December 2023 were selected,64 SMPP children were included in severe group,the remaining 98 children were included in mild group.The general data,laboratory indicators and imaging indicators of the children were collected.The influencing factors for the occurrence of SMPP were analyzed by univariate and multivariate logistic regression models,and a risk warning model for the occurrence of SMPP children was constructed based on multivariate logistic regression model.The predictive value of the risk warning model for the occurrence of SMPP were analyzed by receiver operating characteristic(ROC)curve.Results:The proportion of 3 years old ≤ age<6 years old,course of disease,body temperature,fever course,C-reactive protein(CRP),erythrocyte sedimentation rate(ESR),lactate dehydrogenase(LDH),cyanosis of lips,positive triconcave sign,pleural effusion,lesion site was the lower lobe,abnormal electrocardiogram and extrapulmonary manifestations in severe group were significantly higher than those in mild group(P<0.05),there were no significant differences in gender,white blood cell count(WBC),neutrophil ratio and procalcitonin(PCT)between the two groups(P>0.05).Multivariate logistic regression analysis model showed that,3 years old ≤age<6 years old,high body temperature,long fever course,CRP elevated,ESR elevated,LDH elevated,cyanosis of lips,positive triconcave sign,pleural effusion,lesion site was the lower lobe,abnormal electrocardiogram and extrapulmonary manifestations were risk factors for the occurrence of SMPP(P<0.05).ROC curve analysis showed that,the area under the curve(AUC)of the risk warning model was 0.829,the sensitivity was 84.82%,and the specificity was 78.15%,the actual prediction curve of the risk warning model was in good agreement with the prediction curve,the decision curve showed that,the threshold probability range of the model was 4.61%~88.14%.Conclusion:The risk warning model based on clinical multi parameters such as general data,laboratory indicators and imaging indicators has certain predictive value for the occurrence of SMPP.
3.Constructing A Risk Warning Model for Severe Mycoplasma Pneumoniae Pneumonia Children Based on Clinical Multi Parameters
Wan-ting MO ; Ping-ming GAO ; Rui-ping WAN ; Hui-wen XIAN ; Dan-xia LIN
Progress in Modern Biomedicine 2025;25(3):511-518
Objective:To construct a risk warning model for severe mycoplasma pneumoniae pneumonia(SMPP)children based on clinical data,laboratory indicators and imaging indicators.Methods:162 Mycoplasma pneumoniae pneumonia(MPP)children who were admitted in Foshan Women and Children Hospital from January 2021 to December 2023 were selected,64 SMPP children were included in severe group,the remaining 98 children were included in mild group.The general data,laboratory indicators and imaging indicators of the children were collected.The influencing factors for the occurrence of SMPP were analyzed by univariate and multivariate logistic regression models,and a risk warning model for the occurrence of SMPP children was constructed based on multivariate logistic regression model.The predictive value of the risk warning model for the occurrence of SMPP were analyzed by receiver operating characteristic(ROC)curve.Results:The proportion of 3 years old ≤ age<6 years old,course of disease,body temperature,fever course,C-reactive protein(CRP),erythrocyte sedimentation rate(ESR),lactate dehydrogenase(LDH),cyanosis of lips,positive triconcave sign,pleural effusion,lesion site was the lower lobe,abnormal electrocardiogram and extrapulmonary manifestations in severe group were significantly higher than those in mild group(P<0.05),there were no significant differences in gender,white blood cell count(WBC),neutrophil ratio and procalcitonin(PCT)between the two groups(P>0.05).Multivariate logistic regression analysis model showed that,3 years old ≤age<6 years old,high body temperature,long fever course,CRP elevated,ESR elevated,LDH elevated,cyanosis of lips,positive triconcave sign,pleural effusion,lesion site was the lower lobe,abnormal electrocardiogram and extrapulmonary manifestations were risk factors for the occurrence of SMPP(P<0.05).ROC curve analysis showed that,the area under the curve(AUC)of the risk warning model was 0.829,the sensitivity was 84.82%,and the specificity was 78.15%,the actual prediction curve of the risk warning model was in good agreement with the prediction curve,the decision curve showed that,the threshold probability range of the model was 4.61%~88.14%.Conclusion:The risk warning model based on clinical multi parameters such as general data,laboratory indicators and imaging indicators has certain predictive value for the occurrence of SMPP.
4.Current status and suggestions on regulation of traditional Chinese medicine raw materials and preparations under regulatory system of drugs.
Li-Ping QU ; Yong-Dan XU ; Wei-Jing HE ; Ding-Kun ZHANG ; Nan YANG ; Min-Xian SONG ; Zhi-Qiang MIN ; Ting-Mo ZHANG
China Journal of Chinese Materia Medica 2025;50(3):824-832
At present, the cause of traditional Chinese medicine(TCM) in China has entered a new period of high-quality development. How to strengthen the foundation for the TCM industry from the source is an important issue that deserves the attention of the authorities, industry, and academia. This study systematically analyzed the regulatory system of TCM raw materials and preparations. The study took the TCM industry chain and the product life cycle as a clue and focused on the dimensions of TCM resource protection and plant cultivation(farming), production and quality supervision of TCM raw materials and preparations, and their market access and distribution. It analyzed the current situation of the regulation of TCM raw materials and preparations under the regulatory system of drugs, discussed the main problems, and put forward corresponding suggestions. The results can provide an important reference value for the subsequent improvement of the regulatory system of drugs and the construction of a prominent regulatory system of drugs in accordance with TCM characteristics.
Drugs, Chinese Herbal/economics*
;
Medicine, Chinese Traditional/standards*
;
China
;
Quality Control
;
Humans
;
Plants, Medicinal/chemistry*
5.Phenotypic Function of Legionella pneumophila Type I-F CRISPR-Cas.
Ting MO ; Hong Yu REN ; Xian Xian ZHANG ; Yun Wei LU ; Zhong Qiu TENG ; Xue ZHANG ; Lu Peng DAI ; Ling HOU ; Na ZHAO ; Jia HE ; Tian QIN
Biomedical and Environmental Sciences 2025;38(9):1105-1119
OBJECTIVE:
CRISPR-Cas protects bacteria from exogenous DNA invasion and is associated with bacterial biofilm formation and pathogenicity.
METHODS:
We analyzed the type I-F CRISPR-Cas system of Legionella pneumophila WX48, including Cas1, Cas2-Cas3, Csy1, Csy2, Csy3, and Cas6f, along with downstream CRISPR arrays. We explored the effects of the CRISPR-Cas system on the in vitro growth, biofilm-forming ability, and pathogenicity of L. pneumophila through constructing gene deletion mutants.
RESULTS:
The type I-F CRISPR-Cas system did not affect the in vitro growth of wild-type or mutant strains. The biofilm formation and intracellular proliferation of the mutant strains were weaker than those of the wild type owing to the regulation of type IV pili and Dot/Icm type IV secretion systems. In particular, Cas6f deletion strongly inhibited these processes.
CONCLUSION
The type I-F CRISPR-Cas system may reduce biofilm formation and intracellular proliferation in L. pneumophila.
Legionella pneumophila/pathogenicity*
;
CRISPR-Cas Systems
;
Biofilms/growth & development*
;
Phenotype
;
Bacterial Proteins/metabolism*
;
Gene Deletion
6.Correlation and predictive value of obesity measurement indicators and cerebrovascular function scores in healthy physical examination population
Dianhua DU ; Chunwei WU ; Lan MO ; Xuelin ZHANG ; Wen WU ; Yiping WANG ; Xian WU ; Bo WANG ; Shaohui FENG
Chinese Journal of Health Management 2025;19(4):286-291
Objective:To analyze the correlation and predictive value of obesity measurement indicators and cerebrovascular function scores in healthy physical examination population.Methods:It was a cross-sectional analysis that employed a simple random sampling method to select 3 496 individuals who underwent healthy physical examinations and cerebrovascular function tests at the Physical Examination Center of the Affiliated Hospital of Guizhou Medical University from January to December 2022. The general information, physical examination data, biochemical examination results, human component analyses, and cerebrovascular function integral data were collected. Based on cerebrovascular function scores, the participants were divided into high-risk group (0-24 points, 70 cases), medium-risk group (25-49 points, 317 cases), low-risk group (50-74 points, 787 cases), and normal group (≥75 points, 2 322 cases). Spearman correlation analysis and receiver operating characteristic (ROC) curve analyses were utilized to assess the correlation and predictive value of obesity measurement indicators and cerebrovascular function integrals.Results:Among the 3 496 subjects included in the analysis, 2 018 were male and 1 478 were female, with an average age of (46.4±7.9) years. The age, systolic blood pressure, diastolic blood pressure, body mass index, waist-to-hip ratio, body fat ratio, body fat content, visceral fat area, fasting blood glucose, total cholesterol, low-density lipoprotein, homocysteine all exhibited an increasing trend as the cerebrovascular function integral value decreased (all P<0.05). The skeletal muscle content in the low-risk group was significantly higher than those in the high-risk group, medium-risk group, and normal group [45.00 (36.80, 50.60) vs 44.10 (36.98, 50.45), 44.50 (37.80, 50.20), and 42.75 (36.30, 48.60) kg, respectively] ( P<0.05). The triglyceride level in the medium-risk group was higher when compared to those in the high-risk group, low-risk group, and normal group[1.87 (1.29, 2.70) vs 1.71 (1.24, 2.80), 1.75 (1.18, 2.70), and 1.43 (1.00, 2.14) mmol/L] ( P<0.05). The high-density lipoprotein level in the normal group was higher than the high-risk group, medium-risk group, and low-risk group[1.26 (1.05, 1.51) vs 1.16 (0.94, 1.36), 1.15 (0.99, 1.39), and 1.16 (0.97, 1.39) mmol/L, respectively] ( P<0.05). The increases in systolic blood pressure, diastolic blood pressure, body mass index, and body fat content were all moderately negatively correlated with the cerebrovascular function score ( rs=-0.347, -0.335, -0.370, and -0.340, respectively, all P<0.05). The increase in age ( OR=1.012, 95% CI: 1.002-1.022), systolic blood pressure ( OR=1.027, 95% CI: 1.017-1.036), diastolic blood pressure ( OR=1.028, 95% CI: 1.014-1.042), body mass index ( OR=1.157, 95% CI: 1.083-1.237), body fat rate ( OR=1.021, 95% CI: 1.007-1.035), and fasting blood glucose ( OR=1.072, 95% CI: 1.020-1.127) were all positively correlated with the decrease of the cerebrovascular function score; conversely, the increase in skeletal muscle content ( OR=0.967, 95% CI: 0.951-0.982) was negatively correlated with the decrease in cerebrovascular function score (all P<0.05). The area under the curve for the combined prediction of cerebrovascular function integral value by age, systolic blood pressure, diastolic blood pressure, body mass index, body fat rate, skeletal muscle content, and fasting blood glucose was 0.754. Conclusions:As the body mass index and body fat content increase and the skeletal muscle content decreases in the healthy physical examination population, the likelihood of abnormal cerebrovascular function integral values rises; the combination of age, systolic blood pressure, diastolic blood pressure, body mass index, body fat percentage, skeletal muscle content, and fasting blood glucose indicators can predict the increased risk of cerebrovascular function integral values.
7.Risk Prediction Performance of Blood Biomarkers for Bipolar Disorder With Psychotic Symptoms
Zijun NI ; Junping YIN ; Xiaoying WANG ; Yuting ZHOU ; Xian MO ; Lu SUN ; Wei ZHANG
Journal of Sichuan University (Medical Sciences) 2025;56(5):1351-1356
Objective To investigate biological markers associated with psychotic symptoms in patients with bipolar disorder(BD)based on electronic medical records of patients,and to develop an interpretable risk prediction model that supports the identification of high-risk individuals and that facilitates decision-making for providing clinical intervention in a timely manner.Methods A total of 2 352 patients diagnosed with BD and admitted to West China Hospital,Sichuan University were enrolled using the electronic medical records system of the hospital.The participants were divided into two subgroups,the bipolar disorder depression(BDD)group and the bipolar disorder mania(BDM)group.The logistic regression algorithm was used to train and validate the prediction model,and interpretability methods were used to analyze the contribution of each feature to individuals and the effect of the features on specific target prediction decisions.Results The logistic regression model demonstrated robust predictive performance across the BD,BDD,and BDM cohorts,with areas under the curve(AUC)of the receiver operating characteristic curves always exceeding 81.6%.The core predictive features included platelet distribution width(PDW),fibrinogen(FIB),platelet large cell ratio(P-LCR),activated partial thromboplastin time(APTT),prothrombin time(PT),and triglyceride(TG).The logistic regression model exhibited strong interpretability and was combined with nomograms for intuitive risk quantification and individualized prediction.Conclusion The logistic regression model enables rapid and simple screening of BD patients with psychotic symptoms.Distinct patterns of changes observed in blood biomarkers of BDD and BDM subgroups enrich the understanding of the underlying pathophysiological mechanisms and highlight the importance of considering subtypes in the intervention and management of patients.
8.Establishment and application of ultra-fast real-time PCR for Brucella detection
Zhen-na XU ; Zhi-peng WU ; Wei-bin HONG ; Zhi-shen GUAN ; Qi-ming LIN ; Zuan-lan MO ; Yi-fei YE ; Hai-yan XIE ; Min LI ; Yan-qiu ZHU ; Xiao-jun LI ; Xian-peng ZHANG
Chinese Journal of Zoonoses 2025;41(3):278-283
This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20%to 0.91%,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100%compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.
9.Correlation and predictive value of obesity measurement indicators and cerebrovascular function scores in healthy physical examination population
Dianhua DU ; Chunwei WU ; Lan MO ; Xuelin ZHANG ; Wen WU ; Yiping WANG ; Xian WU ; Bo WANG ; Shaohui FENG
Chinese Journal of Health Management 2025;19(4):286-291
Objective:To analyze the correlation and predictive value of obesity measurement indicators and cerebrovascular function scores in healthy physical examination population.Methods:It was a cross-sectional analysis that employed a simple random sampling method to select 3 496 individuals who underwent healthy physical examinations and cerebrovascular function tests at the Physical Examination Center of the Affiliated Hospital of Guizhou Medical University from January to December 2022. The general information, physical examination data, biochemical examination results, human component analyses, and cerebrovascular function integral data were collected. Based on cerebrovascular function scores, the participants were divided into high-risk group (0-24 points, 70 cases), medium-risk group (25-49 points, 317 cases), low-risk group (50-74 points, 787 cases), and normal group (≥75 points, 2 322 cases). Spearman correlation analysis and receiver operating characteristic (ROC) curve analyses were utilized to assess the correlation and predictive value of obesity measurement indicators and cerebrovascular function integrals.Results:Among the 3 496 subjects included in the analysis, 2 018 were male and 1 478 were female, with an average age of (46.4±7.9) years. The age, systolic blood pressure, diastolic blood pressure, body mass index, waist-to-hip ratio, body fat ratio, body fat content, visceral fat area, fasting blood glucose, total cholesterol, low-density lipoprotein, homocysteine all exhibited an increasing trend as the cerebrovascular function integral value decreased (all P<0.05). The skeletal muscle content in the low-risk group was significantly higher than those in the high-risk group, medium-risk group, and normal group [45.00 (36.80, 50.60) vs 44.10 (36.98, 50.45), 44.50 (37.80, 50.20), and 42.75 (36.30, 48.60) kg, respectively] ( P<0.05). The triglyceride level in the medium-risk group was higher when compared to those in the high-risk group, low-risk group, and normal group[1.87 (1.29, 2.70) vs 1.71 (1.24, 2.80), 1.75 (1.18, 2.70), and 1.43 (1.00, 2.14) mmol/L] ( P<0.05). The high-density lipoprotein level in the normal group was higher than the high-risk group, medium-risk group, and low-risk group[1.26 (1.05, 1.51) vs 1.16 (0.94, 1.36), 1.15 (0.99, 1.39), and 1.16 (0.97, 1.39) mmol/L, respectively] ( P<0.05). The increases in systolic blood pressure, diastolic blood pressure, body mass index, and body fat content were all moderately negatively correlated with the cerebrovascular function score ( rs=-0.347, -0.335, -0.370, and -0.340, respectively, all P<0.05). The increase in age ( OR=1.012, 95% CI: 1.002-1.022), systolic blood pressure ( OR=1.027, 95% CI: 1.017-1.036), diastolic blood pressure ( OR=1.028, 95% CI: 1.014-1.042), body mass index ( OR=1.157, 95% CI: 1.083-1.237), body fat rate ( OR=1.021, 95% CI: 1.007-1.035), and fasting blood glucose ( OR=1.072, 95% CI: 1.020-1.127) were all positively correlated with the decrease of the cerebrovascular function score; conversely, the increase in skeletal muscle content ( OR=0.967, 95% CI: 0.951-0.982) was negatively correlated with the decrease in cerebrovascular function score (all P<0.05). The area under the curve for the combined prediction of cerebrovascular function integral value by age, systolic blood pressure, diastolic blood pressure, body mass index, body fat rate, skeletal muscle content, and fasting blood glucose was 0.754. Conclusions:As the body mass index and body fat content increase and the skeletal muscle content decreases in the healthy physical examination population, the likelihood of abnormal cerebrovascular function integral values rises; the combination of age, systolic blood pressure, diastolic blood pressure, body mass index, body fat percentage, skeletal muscle content, and fasting blood glucose indicators can predict the increased risk of cerebrovascular function integral values.
10.Expert consensus on odontogenic maxillary sinusitis multi-disciplinary treatment
Lin JIANG ; Wang CHENGSHUO ; Wang XIANGDONG ; Chen FAMING ; Zhang WEI ; Sun HONGCHEN ; Yan FUHUA ; Pan YAPING ; Zhu DONGDONG ; Yang QINTAI ; Ge SHAOHUA ; Sun YAO ; Wang KUIJI ; Zhang YUAN ; Xian MU ; Zheng MING ; Mo ANCHUN ; Xu XIN ; Wang HANGUO ; Zhou XUEDONG ; Zhang LUO
International Journal of Oral Science 2024;16(1):1-14
Odontogenic maxillary sinusitis(OMS)is a subtype of maxillary sinusitis(MS).It is actually inflammation of the maxillary sinus that secondary to adjacent infectious maxillary dental lesion.Due to the lack of unique clinical features,OMS is difficult to distinguish from other types of rhinosinusitis.Besides,the characteristic infectious pathogeny of OMS makes it is resistant to conventional therapies of rhinosinusitis.Its current diagnosis and treatment are thus facing great difficulties.The multi-disciplinary cooperation between otolaryngologists and dentists is absolutely urgent to settle these questions and to acquire standardized diagnostic and treatment regimen for OMS.However,this disease has actually received little attention and has been underrepresented by relatively low publication volume and quality.Based on systematically reviewed literature and practical experiences of expert members,our consensus focuses on characteristics,symptoms,classification and diagnosis of OMS,and further put forward multi-disciplinary treatment decisions for OMS,as well as the common treatment complications and relative managements.This consensus aims to increase attention to OMS,and optimize the clinical diagnosis and decision-making of OMS,which finally provides evidence-based options for OMS clinical management.

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