Objective To analyze the molecular epidemiology of Candida tropicalis(C.tropicalis)isolates from bloodstream infections,and to investigate preliminarily the underlying mechanisms of fluconazole resistance.Methods Clinical C.tropicalis isolates were collected from bloodstream infections at West China Hospital,Sichuan University and other hospitals in Sichuan Province.All the collected isolates were identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry,and the antifungal susceptibility test was performed by the broth microdilution method.Multilocus sequence typing(MLST)was conducted using the first generation sequencing technique.Genes associated with drug-resistance were sequenced and the mutation sites were identified.The relative expression levels of genes associated with drug-resistance were analyzed using reverse transcription-quantitative polymerase chain reaction(RT-qPCR).Results A total of 39 C.tropicalis isolates from bloodstream infections were collected.The MLST phylogenetic tree showed that most of the strains clustered in the phylogenetic tree shared identical or similar minimal inhibitory concentrations(MICs).All MLST types were not matched with the isolates in the PubMLST database,representing new diploid sequence types(DSTs).A total of 3 sense mutations,including Ser154Phe,Tyr132Phe,and Tyr257His were identified in ERG11,and were present only in drug-resistant strains.UPC2 contained 4 sense mutations,including Ala251Thr,Gln289Leu,Ser279Glu,and Gln313His,which were also present only in drug-resistant strains.Ser279Glu and Gln313His were previously unreported.There were two sense mutations in ERG3,namely Ser112Gly and Ala48Ser,both being previously unreported,and Ser112Gly was found only in drug-resistant strains.The expression levels of ERG11(14.48 vs 7.109,P=0.003)and UPC2(1.922 vs 0.832,P=0.04)in non-sensitive group(MIC>2 mg/L)were higher than those in sensitive group(MIC≤2 mg/L),and the difference was statistically significant.Conclusion There may be a unique genetic relationship among C.tropicalis isolates from Sichuan province,and the MICs of fluconazole against C.tropicalis are associated with molecular typing.ERG11 mutations were the major mechanism underlying fluconazole resistance in C.tropicalis isolates.The upregulation of ERG11 and UPC2 was associated with fluconazole resistance in C.tropicalis.

Objectives To identify key clinical factors influencing recurrence in osteosarcoma patients,to construct and validate a Nomogram-based recurrence risk prediction model,thereby providing a quantitative tool for clinical decision-making and recurrence prevention/control.Methods Clinical data of 469 osteosarcoma patients admitted to Yunnan Cancer Hospital between 2013～2022 were retrospectively collected.Statistical analysis was performed using R software(version 4.3.2).Potential influencing factors were initially screened via univariate analysis and LASSO regression analysis.Independent predictors of osteosarcoma recurrence were then identified using multivariate logistic regression analysis.Based on the identified independent factors,a Nomogram prediction model for recurrence risk was constructed.The area under the receiver operating characteristic curve(AUC)was used to evaluate the model's discriminative ability.Results Among the entire cohort,68 patients experienced recurrence,yielding a recurrence rate of 14.50%.Multivariate analysis identified the following as independent predictors of recurrence:Primary Tumor Location:Tibial lesions(P=0.009)were associated with a significantly lower recurrence risk compared to femoral lesions(OR=0.297),while lesions in"Other Bones"(P=0.008)carried a significantly higher risk(OR=3.294).Biopsy Method:Needle biopsy(P=0.033)was associated with a significantly lower recurrence risk compared to open biopsy(OR=0.461).Lung Metastasis Status:Patients with lung metastasis(P<0.001)had a significantly higher recurrence risk than those without(OR=11.873).Lymphocyte Count:A higher lymphocyte count(P=0.001)was a protective factor,associated with a lower recurrence risk(OR=0.450).The constructed Nomogram prediction model demonstrated excellent performance:Validation results showed an AUC=0.842(95%CI:0.806～0.875),indicating outstanding discriminative ability.Conclusions This study successfully constructed and validated a Nomogram prediction model for osteosarcoma recurrence risk integrating key clinical factors.The model demonstrates superior discriminative ability and can accurately and quantitatively assess the recurrence risk for individual patients.This tool thus provides critical reference for guiding clinical treatment decisions.

Bronchial asthma （asthma for short） is a common clinical respiratory disease mainly characterized by chronic airway inflammation， with complicated pathogenesis and a long treatment cycle. It is lingering and difficult to be cured， and lack specific drugs. Oxidative stress is a new focus in the research on the pathogenesis of asthma and a potential key target for the treatment. Under physiological conditions， the oxidative and antioxidative systems in the body are in a dynamic balance， and the two antagonize each other to maintain normal life activities. In the case of asthma attack， oxidation products such as reactive oxygen species （ROS）， malondialdehyde （MDA）， and nitric oxide （NO） are produced excessively， while the content of antioxidants such as superoxide dismutase （SOD）， catalase （CAT）， and glutathione （GSH） is reduced. As a result， the oxidation exceeds the removal of oxidation products， which aggravates oxidative stress. In addition， the overproduction of ROS activates oxidative stress-related signaling pathways to produce pro-inflammatory factors， exacerbating inflammation， which leads to lung and airway tissue damage. In recent years， traditional Chinese medicine has garnering increasing attention because of the unique advantages in the treatment of asthma， especially in regulating redox balance， alleviating oxidative stress in asthma patients， and reducing inflammation. On the one hand， by inhibiting the mitogen-activated protein kinase （MAPK） and transcription factor （NF）-κB signaling pathways， traditional Chinese medicine can reduce the content of oxidation products and pro-inflammatory factors from the source. On the other hand， by activating the nuclear factor-erythroid 2-related factor 2 （NrF2） signaling pathway， traditional Chinese medicine can elevate the levels of antioxidant enzymes and enhance the antioxidant system to neutralize the excessive accumulation of oxidation products. Therefore， the adjustment of redox balance state by traditional Chinese medicine may be a new means and a new direction for the prevention and treatment of asthma in the future. This paper summarizes the oxidative stress-related pathways in the pathogenesis of asthma and reviews the latest research progress in the regulation of oxidative stress-related pathways by Chinese medicine extracts and prescriptions in the treatment of asthma， with a view to providing a fuller， more solid， and more scientific theoretical basis for the clinical and basic research on the prevention and treatment of asthma by traditional Chinese medicine.

Background Air pollution is a major public health concern. Air Quality Health Index (AQHI) is a very important air quality risk communication tool. However, AQHI is usually constructed by single-pollutant model, which has obvious disadvantages. Objective To construct an AQHI based on the joint effects of multiple air pollutants (J-AQHI), and to provide a scientific tool for health risk warning and risk communication of air pollution. Methods Data on non-accidental deaths in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces from January 1, 2013 to December 31, 2018 were obtained from the corresponding provincial disease surveillance points systems (DSPS), including date of death, age, gender, and cause of death. Daily meteorological (temperature and relative humidity) and air pollution data (SO₂, NO₂, CO, PM_2.5, PM₁₀, and maximum 8 h O₃ concentrations) at the same period were respectively derived from China Meteorological Data Sharing Service System and National Urban Air Quality Real-time Publishing Platform. Lasso regression was first applied to select air pollutants, then a time-stratified case-crossover design was applied. Each case was matched to 3 or 4 control days which were selected on the same days of the week in the same calendar month. Then a distributed lag nonlinear model (DLNM) was used to estimate the exposure-response relationship between selected air pollutants and mortality, which was used to construct the AQHI. Finally, AQHI was classified into four levels according to the air pollutant guidance limit values from World Health Organization Global Air Quality Guidelines (AQG 2021), and the excess risks (ERs) were calculated to compare the AQHI based on single-pollutant model and the J-AQHI based on multi-pollutant model. Results PM_2.5, NO₂, SO₂, and O₃ were selected by Lasso regression to establish DLNM model. The ERs for an interquartile range (IQR) increase and 95% confidence intervals (CI) for PM_2.5, NO₂, SO₂ and O₃ were 0.71% (0.34%–1.09%), 2.46% (1.78%–3.15%), 1.25% (0.9%–1.6%), and 0.27% (−0.11%–0.65%) respectively. The distribution of J-AQHI was right-skewed, and it was divided into four levels, with ranges of 0-1 for low risk, 2-3 for moderate risk, 4-5 for high health risk, and ≥6 for severe risk, and the corresponding proportions were 11.25%, 64.61%, 19.33%, and 4.81%, respectively. The ER (95%CI) of mortality risk increased by 3.61% (2.93–4.29) for each IQR increase of the multi-pollutant based J-AQHI , while it was 3.39% (2.68–4.11) for the single-pollutant based AQHI . Conclusion The J-AQHI generated by multi-pollutant model demonstrates the actual exposure health risk of air pollution in the population and provides new ideas for further improvement of AQHI calculation methods.

Objective:To study the effect of duodenal papillary morphology on selective biliary cannulation (SBC).Methods:Data of 912 patients with biliopancreatic diseases treated with endoscopic retrograde cholangiopancreatography (ERCP) at the Department of Gastroenterology, Affiliated Hospital of Northwest Minzu University from January 2018 to January 2020 were retrospectively analyzed. Duodenal papillary morphology of patients was classified into 4 types by using Haraldsson's endoscopic classification. The success rate of SBC, the pre-incision rate, the difficult intubation rate and the incidence of post-ERCP pancreatitis (PEP) of different papillary types were analyzed.Results:A total of 912 patients were enrolled in this study, and 86.95% (793/912) duodenal papilla conformed to one type of the classification, of which 77.18% (612/793) were regular type (type Ⅰ), 10.21% (81/793) small nipple type (type Ⅱ), 8.58% (68/793) protruding or drooping type (type Ⅲ), and 4.04% (32/793) wrinkled or ridged type (type Ⅳ). The success rates of SBC in four types of duodenal papilla were 98.86% (605/612), 90.12% (73/81), 88.24% (60/68) and 96.60% (28/32) respectively. The success rate of SBC of type Ⅰ was higher than those of type Ⅱ-Ⅳ (all P<0.008) and there was no significant difference between those of type Ⅱ and type Ⅲ ( P> 0.008). The pre-incision rate in the four types of duodenal papilla were 7.84% (48/612), 32.10% (26/81), 50.00% (34/68) and 25.00% (8/32) respectively. The pre-incision rate of type Ⅰ was lower than those of type Ⅱ-Ⅳ (all P<0.008), and there was no significant difference between those of type Ⅱ and type Ⅲ ( P>0.008). The difficult intubation rate in the four types of duodenal papilla were 12.42% (76/612), 39.51% (32/81), 58.82% (40/68) and 28.12% (9/32) respectively .The difficult intubation rate of type Ⅰ was lower than those of type Ⅱ and type Ⅲ (both P<0.001), and that of type Ⅲ was higher than that of type Ⅳ ( P=0.004) . There was no significant difference between those of type Ⅰ and type Ⅳ or type Ⅱ and type Ⅲ (both P>0.008). The incidences of PEP of the four types were 2.61% (16/612), 12.35% (10/81), 5.88% (4/68) and 6.25% (2/32) respectively. The incidences of PEP of type Ⅱ was higher than that of type Ⅰ ( P<0.001) , and there was no significant difference between those of type Ⅰ and type Ⅳ or type Ⅱ and type Ⅲ (both P>0.008). Conclusion:SBC is affected by duodenal papilla morphology, easiest for type Ⅰ and hard for type Ⅱ and Ⅲ. Attention should be paid to risk of PEP in SBC of type Ⅱ.

Background It is projected that the frequency, density, and duration of compound hot extreme may increase in the 21st century in the context of global warming. Objective To explore the association between compound hot extreme and blood pressure, and identify sensitive populations. Methods This was a cross-sectional study. The study subjects were from six Guangdong Province Chronic Disease and Nutrition Surveys during 2002 through 2015. A questionnaire was administered to the participants with questions about demographic information, drinking and smoking status, and measurements on their height, weight, and blood pressure were also collected. We chose the data of May, September, and October to explore the association between compound hot extreme and blood pressure. Compound hot extreme means a hot day with a proceeding hot night. Daily meteorological data were obtained from China Meteorological Data Service Centre. We employed inverse distance weighting to interpolate the temperature and relative humidity values for each participant. A distributed lag non-linear model was used to estimate the association between compound hot extreme and blood pressure. Stratified analyses by sex, age, area, body mass index (BMI), smoking status, and drinking status were also performed to identify sensitive populations. A sensitivity analysis was conducted by adjusting the degrees of freedom for lag spline and removing relative humidity. Result A total of 10967 participants without history of hypertension were included in this study. The average systolic blood pressure (SBP) was 120.8 mmHg and the average diastolic blood pressure (DBP) was 74.5 mmHg. The proportion of participants who experienced hot day, hot night, or compound hot extreme were 9.34%, 17.95% and 2.90%, respectively. Compared to hot day, hot night and compound hot extreme were related with decreased blood pressure, and the effect of compound hot extreme was stronger: the changes and 95%CI for SBP was −6.2 (−10.3-−2.1) mmHg, and for DBP was −2.7 (−5.2-−0.2) mmHg. Compound hot extreme induced decreased SBP among male, population ≥ 65 years, and those whose BMI < 24 kg·m^-2, and their ORs (95%CIs) were −6.2 (−10.7-−1.6). −19.1 (−33.0-−5.1), and −6.7 (−11.8~−1.6) mmHg, respectively, and also decreased DBP among population ≥ 65 years, and its OR (95%CI) was −8.4 (−15.6-−1.1) mmHg. During compound hot extremes, participants living in rural areas showed decreased SBP and DBP, and the ORs (95%CIs) were −10.5 (−16.6-−4.5) and −4.4 (−7.7-−1.1) mmHg respectively, while those living in urban areas showed increased SBP, and the OR (95%CI) was 9.7 (2.9-16.5) mmHg. A significant decrease in blood pressure [OR (95%CI)] was also found in non-smokers [DBP, −3.7 (−6.6-−0.8) mmHg] and non-drinkers [SBP, −4.8 (−9.4-−0.2) mmHg; DBP, −3.4 (−6.0-−0.9) mmHg]. Conclusion Compound hot extreme is negatively associated with SBP, and being male, aged 65 years and over, and having BMI < 24 kg·m⁻² may be more sensitive to compound hot extreme.

Background In recent years, the incidence of metabolic syndrome (MS) is increasing significantly in China. Some studies have found that temperature is related to single metabolic index, but there is a lack of research on associated mechanism and identifying path of the influence of temperature on MS. Objective Based on the data of Guangdong Province, to investigate the effect of temperature on MS and its pathway. Methods A total of 8524 residents were enrolled by multi-stage random sampling from October 2015 to January 2016 in Guangdong. Basic characteristics, behavioral characteristics, health status, and physical activity level were obtained through questionnaires and physical examinations, and meteorological data were obtained from meteorological monitoring sites. We matched individual data both with the temperature data of the physical examination day and of a lag of 14 d. A generalized additive model was used to explore the exposure-effect relationship between temperature and MS and its indexes, calculate effect values, and explore the effects of single-day lag temperature. Based on the literature and the results of generalized additive model analysis, a path analysis was conducted to explore the pathways of temperature influencing MS. Results The association between daily average temperature on the current day or lag 14 day and MS risk was not statistically significant. When daily average temperature increased by 1 ℃, the change values of fasting blood-glucose (FBG), systolic blood pressure (SBP), diastolic blood pressure (DBP), and high density lipoprotein cholesterol (HDL-C) were −0.033 (95%CI: −0.040-−0.026) mmol·L⁻¹, −0.662 (95%CI: −0.741-−0.583) mmHg, −0.277 (95%CI: −0.323-−0.230) mmHg, and −0.005 (95%CI: −0.007-−0.004) mmol·L⁻¹ respectively. The effects of average daily temperature on FBG, blood pressure, HDL-C, and waist circumference lasted until lag 14 day. The effects of daily average temperature on SBP and DBP were the largest on the current day. Daily average temperature of current day had direct and indirect effects on FBG and SBP. Temperature had an indirect effect on TG, and the intermediate variables were waist circumference and FBG, with an indirect effect value of −0.011 (95%CI: −0.020-−0.002). The indirect effects of daily average temperature on SBP, FBG, and TG were weak. Conclusion There is no significant correlation between temperature and risk of MS, and daily average temperature of current day could significantly affected blood pressure and FBG with a lag effect. Daily average temperature of current day has indirect effects on FBG and TG.

Background Dengue fever is a mosquito-borne disease transmitted by Aedes aegypti and Aedes albopictus. Under the background of climate change, there are great challenges in the prevention and control of dengue fever, posing a serious health risk to the population. Objective To analyze the mechanism of temperature on dengue fever transmission and estimate the risk of dengue fever under different climate change scenarios by establishing a coupled human-mosquito dynamics model using Guangzhou as a research site, and to provide reference for adaptation to climate change. Methods Reported dengue fever cases and meteorological data from January 1, 2015 to December 31, 2019 in Guangzhou were collected from Guangdong Provincial Center for Disease Control and Prevention and China Meteorological Data Service Centre, respectively. The temperature data under three Representative Concentration Pahtyway (RCP2.6, RCP4.5, and RCP8.5) scenarios in 2030s (2031–2040), 2060s (2061–2070), and 2090s (2091–2099) were calculated by five general circulation models (GCMs) provided by the fifth phase of the Coupled Model Intercomparison Project. A dengue fever transmission dynamics (ELPSEI-SEIR) model was constructed to analyze the mechanism of temperature affecting dengue fever transmission by fitting the dengue fever epidemic trend from 2015–2019, and then the daily mean temperature under selected RCP scenarios for 2030s, 2060s, and 2090s was incorporated into the established dynamics model to predict the risk of dengue fever under different climate change scenarios in the future. Results From January 1, 2015 to December 31, 2019, a total of 4 234 cases of dengue fever were reported in Guangzhou, including 3741 local cases and 493 imported cases. The regression results showed that the model well fitted the dengue fever cases in Guangzhou from 2015 to 2019, and the coefficient of determination R2 to evaluate goodness of fit and the root mean squared error were 0.82 and 1.96, respectively. A U-shaped or inverted U-shaped relationship between temperature and mosquito habits could directly affect the number of mosquitoes and the transmission of dengue fever. We also found that temperature increase in most future scenarios could promote the transmission of dengue fever, and the epidemic period was significantly wider than the baseline stage. The epidemic of dengue fever would peak in the 2060s under the scenarios of RCP2.6 and RCP4.5. The estimated incidence of dengue fever was predicated to be highest in the 2030s and then decrease in the following years under RCP8.5, and in the 2090s, the incidence would decrease significantly, but the incidence peak would be earlier in each year, mainly from May to July. Conclusion Temperature can directly affect mosquito population and dengue fever transmission by affecting mosquito habits. The cases of dengue fever will increase under most climate scenarios in the future. However, the epidemic risk of dengue fever may be suppressed, and the epidemic season may be advanced under RCP8.5.

Objective:To identify the threshold of a health warning system based on the association of apparent temperature and years of life lost (YLL).Methods:Daily mortality records and meteorological data were collected from 364 Chinese counties for 2006-2017. Distributed lag nonlinear model and multivariate Meta-analyses were applied to estimate the association between the apparent temperature and YLL rate. A regression tree model was employed to estimate the warning thresholds of the apparent temperature. Stratified analyses were further conducted by age and cause of death.Results:The daily YLL rate was 23.6/10 5. The mean daily apparent temperature was 15.7 ℃. U-shaped nonlinear associations were observed between apparent temperature and YLL rate. The actual temperature-caused YLL rate for the elderly was higher than the young population. The daily excess deaths rate increased with the higher effect levels. Conclusions:Regression tree model was employed to define the warning threshold for meteorological health risk. The present study provides theoretical support for the weather-related health warning system.

Objective: To evaluate the exported risk of novel coronavirus pneumonia (NCP) from Hubei Province and the imported risk in various provinces across China. Methods: Data of reported NCP cases and Baidu Migration Indexin all provinces of the country as of February 14, 2020 were collected. The correlation analysis between cumulative number of reported cases and the migration index from Hubei was performed, and the imported risks from Hubei to different provinces across China were further evaluated. Results: A total of 49 970 confirmed cases were reported nationwide, of which 37 884 were in Hubei Province. The average daily migration index from Hubei to other provinces was 312.09, Wuhan and other cities in Hubei were 117.95 and 194.16, respectively. The cumulative NCP cases of provinces was positively correlated with the migration index derived from Hubei province, also in Wuhan and other cities in Hubei, with correlation coefficients of 0.84, 0.84, and 0.81. In linear model, population migration from Hubei Province, Wuhan and other cities in Hubei account for 71.2%, 70.1%, and 66.3% of the variation, respectively. The period of high exported risk from Hubei occurred before January 27, of which the risks before January 23 mainly came from Wuhan, and then mainly from other cities in Hubei. Hunan Province, Henan Province and Guangdong Province ranked the top three in terms of cumulative imported risk (the cumulative risk indices were 58.61, 54.75 and 49.62 respectively). Conclusion The epidemic in each province was mainly caused by the importation of Hubei Province. Taking measures such as restricting the migration of population in Hubei Province and strengthening quarantine measures for immigrants from Hubei Province may greatly reduce the risk of continued spread of the epidemic.