Objective:To explore the impact of plant and animal dietary behaviors on type 2 diabetes mellitus (T2DM) in older adults aged ≥65 in 18 longevity areas of China.Methods:The subjects were 5 223 older adults over 65 years old from the Healthy Ageing and Biomarkers Cohort Study (HABCS) in 18 longevity areas in China. Through a questionnaire survey and physical examination, information about their demographic characteristics, lifestyles, daily activities, self-health status, current diseases, and fasting venous blood were collected. Food Frequency and Questionnaire (FFQ) was used to collect data on food intake frequency. Based on the prior method, the plant-based diet index (PDI) and animal-based diet index (ADI) of 5 223 older adults were calculated. Subjects were divided into three groups (low-level group: PDI<39 or ADI<31, middle-level group: 39≤PDI≤42 or 31≤ADI≤34, high-level group: PDI>42 or ADI>34) by tertiles of PDI and ADI. Multivariate logistic regression was used to analyze the association between PDI and ADI and the risk of T2DM.Results:The average age of 5 223 subjects was (84.8±11.5) years, with the median ( Q1, Q3) of PDI about 41(38, 43) and the median ( Q1, Q3) of ADI about 33 (30, 35). The prevalence rate of T2DM was 16.41% (857/5 223). After adjusting for covariates, multivariate logistic regression showed that PDI was negatively associated with T2DM. Compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 0.83 (0.69-0.99). ADI was positively associated with T2DM, and compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 1.28 (1.06-1.55). For every one-point increase in PDI and ADI, the risk of T2DM decreased by 2% and increased by 3%, respectively, with the OR (95% CI) of 0.98 (0.96-1.00) and 1.03 (1.01-1.06), respectively. Conclusion:In Chinese older adults ≥65 years in 18 longevity areas, higher adherence to the plant-based behavior may be negatively associated with the risk of T2DM, while higher adherence to the animal-based behavior may be positively associated with the risk of T2DM.

Objective:To investigate the distribution of iodine and other chemical elements in soil, grain and vegetables in different water iodine areas of Xi'an City, and to provide theoretical basis for prevention and treatment of iodine related diseases and water improvement measures.Methods:From September to November 2021, a stratified cluster sampling method was used to select three survey villages in Xi'an, namely Yehu Village, Xingbei Village, and Quanzhong Village, where the iodine level of residents' drinking water < 10, 10 - 100, and > 100 μg/L. Drinking water samples were collected from seven survey sites based on the source of domestic drinking water to determine the iodine level of the water. At the same time, soil samples of cultivated land, residents' grains (wheat, corn), and vegetables were collected from survey villages to determine the content of 14 elements including calcium, iron, magnesium, chromium, nickel, copper, zinc, cadmium, lead, arsenic, mercury, selenium, iodine, and fluoride.Results:The iodine level in the water of 7 survey sites in three survey villages was 5.80, 6.40, 25.51, 42.20, 53.90, 111.65, and 177.63 μg/L, respectively. A total of 70 samples of soil, 65 samples of wheat, 76 samples of corn, and 141 samples of vegetables were collected. Among them, the levels of various elements in vegetables and grains were lower than those in the soil. Only calcium and fluoride were higher in vegetables than in grains, while iron, chromium, copper, zinc, selenium, and iodine were lower in vegetables than in grains. According to the range of water iodine level, there were statistically significant differences in the content of calcium, iron, chromium, nickel, copper, zinc, mercury, iodine, and fluoride in soils from different water iodine regions ( Fcalcium, iron, chromium, nickel = 42.04, 13.55, 12.22, 11.20, Hcopper, zinc, mercury, iodine, fluoride = 14.27, 9.19, 14.72, 25.14, 16.50, P < 0.05). The comparison of magnesium, zinc, cadmium, arsenic, and selenium content in wheat showed statistically significant differences ( Fadmium, selenium = 6.34, 3.31, Hmagnesium, zinc, arsenic = 6.12, 11.55, 6.23, P < 0.05). The comparison of calcium, iron, magnesium, chromium, nickel, copper, zinc, cadmium, lead, arsenic, mercury, iodine, and fluoride content in corn showed statistically significant differences ( Fmagnesium, chromium, nickel, copper, zinc, iodine = 18.89, 13.76, 17.86, 24.17, 28.46, 15.96, Hcalcium, iron, cadmium, lead, arsenic, mercury, fluoride = 11.57, 40.53, 26.50, 33.05, 33.73, 36.01, 29.21, P < 0.05). The comparison of calcium, iron, magnesium, chromium, zinc, cadmium, lead, arsenic, mercury, and selenium content in vegetables showed statistically significant differences ( H = 23.93, 8.12, 10.03, 7.01, 16.09, 18.36, 23.07, 6.51, 27.67, 7.86, P < 0.05). Conclusions:There are significant differences in the distribution of 14 elements in soil, grain, and vegetables in different water iodine regions. In addition to drinking water, precise guidance should also be provided based on the iodine content in soil, grain, and vegetables in different water iodine areas.

Objective:To develop and validate a predictive model for delayed emergence in patients undergoing thoracoscopic radical lung cancer surgery with general anesthesia.Methods:A total of 1 468 patients admitted to the anesthesia recovery room after thoracoscopic radical lung cancer surgery at the First Affiliated Hospital of Zhejiang University School of Medicine from August 2020 to August 2021 were selected via convenience sampling. Patients who underwent surgery between August 2020 and June 2021 ( n=1 213) were assigned to the modeling group, while those from July to August 2021 ( n=255) were used as the validation group. Logistic regression analysis was used to identify risk factors for delayed emergence and to establish a predictive model. The performance of the model was evaluated using the area under the receiver operating characteristic curve ( AUC) and the Hosmer-Lemeshow goodness-of-fit test. Results:Among the modeling group, 200 patients experienced delayed emergence, with an incidence of 16.49% (200/1 213). Logistic regression analysis revealed that the use of reversal agents, use of neostigmine, albumin level, presence of shivering, pain score≥4 points, extubation time, partial pressure of CO 2, partial pressure of oxygen, serum potassium level, and intraoperative fentanyl dosage were significant influencing factors ( P<0.05). The predictive model demonstrated good performance with an AUC of 0.864 [95% CI (0.828, 0.899) ], a Hosmer-Lemeshow test χ 2=5.299 ( P=0.725), cut-off value of 0.442, sensitivity of 0.794, and specificity of 0.769. In the validation group, delayed emergence occurred in 44 cases (17.25%). The model showed good validation performance with an AUC of 0.852 [95% CI (0.826, 0.878) ], Hosmer-Lemeshow χ 2=5.912 ( P=0.336), cut-off value of 0.754, sensitivity of 0.674, and specificity of 0.877. Conclusions:The predictive model constructed in this study demonstrates strong performance and can assist clinicians in the early identification of patients at risk of delayed emergence following thoracoscopic radical lung cancer surgery under general anesthesia.

Objective:To explore the impact of plant and animal dietary behaviors on type 2 diabetes mellitus (T2DM) in older adults aged ≥65 in 18 longevity areas of China.Methods:The subjects were 5 223 older adults over 65 years old from the Healthy Ageing and Biomarkers Cohort Study (HABCS) in 18 longevity areas in China. Through a questionnaire survey and physical examination, information about their demographic characteristics, lifestyles, daily activities, self-health status, current diseases, and fasting venous blood were collected. Food Frequency and Questionnaire (FFQ) was used to collect data on food intake frequency. Based on the prior method, the plant-based diet index (PDI) and animal-based diet index (ADI) of 5 223 older adults were calculated. Subjects were divided into three groups (low-level group: PDI<39 or ADI<31, middle-level group: 39≤PDI≤42 or 31≤ADI≤34, high-level group: PDI>42 or ADI>34) by tertiles of PDI and ADI. Multivariate logistic regression was used to analyze the association between PDI and ADI and the risk of T2DM.Results:The average age of 5 223 subjects was (84.8±11.5) years, with the median ( Q1, Q3) of PDI about 41(38, 43) and the median ( Q1, Q3) of ADI about 33 (30, 35). The prevalence rate of T2DM was 16.41% (857/5 223). After adjusting for covariates, multivariate logistic regression showed that PDI was negatively associated with T2DM. Compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 0.83 (0.69-0.99). ADI was positively associated with T2DM, and compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 1.28 (1.06-1.55). For every one-point increase in PDI and ADI, the risk of T2DM decreased by 2% and increased by 3%, respectively, with the OR (95% CI) of 0.98 (0.96-1.00) and 1.03 (1.01-1.06), respectively. Conclusion:In Chinese older adults ≥65 years in 18 longevity areas, higher adherence to the plant-based behavior may be negatively associated with the risk of T2DM, while higher adherence to the animal-based behavior may be positively associated with the risk of T2DM.

Objective:To investigate the distribution of iodine and other chemical elements in soil, grain and vegetables in different water iodine areas of Xi'an City, and to provide theoretical basis for prevention and treatment of iodine related diseases and water improvement measures.Methods:From September to November 2021, a stratified cluster sampling method was used to select three survey villages in Xi'an, namely Yehu Village, Xingbei Village, and Quanzhong Village, where the iodine level of residents' drinking water < 10, 10 - 100, and > 100 μg/L. Drinking water samples were collected from seven survey sites based on the source of domestic drinking water to determine the iodine level of the water. At the same time, soil samples of cultivated land, residents' grains (wheat, corn), and vegetables were collected from survey villages to determine the content of 14 elements including calcium, iron, magnesium, chromium, nickel, copper, zinc, cadmium, lead, arsenic, mercury, selenium, iodine, and fluoride.Results:The iodine level in the water of 7 survey sites in three survey villages was 5.80, 6.40, 25.51, 42.20, 53.90, 111.65, and 177.63 μg/L, respectively. A total of 70 samples of soil, 65 samples of wheat, 76 samples of corn, and 141 samples of vegetables were collected. Among them, the levels of various elements in vegetables and grains were lower than those in the soil. Only calcium and fluoride were higher in vegetables than in grains, while iron, chromium, copper, zinc, selenium, and iodine were lower in vegetables than in grains. According to the range of water iodine level, there were statistically significant differences in the content of calcium, iron, chromium, nickel, copper, zinc, mercury, iodine, and fluoride in soils from different water iodine regions ( Fcalcium, iron, chromium, nickel = 42.04, 13.55, 12.22, 11.20, Hcopper, zinc, mercury, iodine, fluoride = 14.27, 9.19, 14.72, 25.14, 16.50, P < 0.05). The comparison of magnesium, zinc, cadmium, arsenic, and selenium content in wheat showed statistically significant differences ( Fadmium, selenium = 6.34, 3.31, Hmagnesium, zinc, arsenic = 6.12, 11.55, 6.23, P < 0.05). The comparison of calcium, iron, magnesium, chromium, nickel, copper, zinc, cadmium, lead, arsenic, mercury, iodine, and fluoride content in corn showed statistically significant differences ( Fmagnesium, chromium, nickel, copper, zinc, iodine = 18.89, 13.76, 17.86, 24.17, 28.46, 15.96, Hcalcium, iron, cadmium, lead, arsenic, mercury, fluoride = 11.57, 40.53, 26.50, 33.05, 33.73, 36.01, 29.21, P < 0.05). The comparison of calcium, iron, magnesium, chromium, zinc, cadmium, lead, arsenic, mercury, and selenium content in vegetables showed statistically significant differences ( H = 23.93, 8.12, 10.03, 7.01, 16.09, 18.36, 23.07, 6.51, 27.67, 7.86, P < 0.05). Conclusions:There are significant differences in the distribution of 14 elements in soil, grain, and vegetables in different water iodine regions. In addition to drinking water, precise guidance should also be provided based on the iodine content in soil, grain, and vegetables in different water iodine areas.

Objective:To develop and validate a predictive model for delayed emergence in patients undergoing thoracoscopic radical lung cancer surgery with general anesthesia.Methods:A total of 1 468 patients admitted to the anesthesia recovery room after thoracoscopic radical lung cancer surgery at the First Affiliated Hospital of Zhejiang University School of Medicine from August 2020 to August 2021 were selected via convenience sampling. Patients who underwent surgery between August 2020 and June 2021 ( n=1 213) were assigned to the modeling group, while those from July to August 2021 ( n=255) were used as the validation group. Logistic regression analysis was used to identify risk factors for delayed emergence and to establish a predictive model. The performance of the model was evaluated using the area under the receiver operating characteristic curve ( AUC) and the Hosmer-Lemeshow goodness-of-fit test. Results:Among the modeling group, 200 patients experienced delayed emergence, with an incidence of 16.49% (200/1 213). Logistic regression analysis revealed that the use of reversal agents, use of neostigmine, albumin level, presence of shivering, pain score≥4 points, extubation time, partial pressure of CO 2, partial pressure of oxygen, serum potassium level, and intraoperative fentanyl dosage were significant influencing factors ( P<0.05). The predictive model demonstrated good performance with an AUC of 0.864 [95% CI (0.828, 0.899) ], a Hosmer-Lemeshow test χ 2=5.299 ( P=0.725), cut-off value of 0.442, sensitivity of 0.794, and specificity of 0.769. In the validation group, delayed emergence occurred in 44 cases (17.25%). The model showed good validation performance with an AUC of 0.852 [95% CI (0.826, 0.878) ], Hosmer-Lemeshow χ 2=5.912 ( P=0.336), cut-off value of 0.754, sensitivity of 0.674, and specificity of 0.877. Conclusions:The predictive model constructed in this study demonstrates strong performance and can assist clinicians in the early identification of patients at risk of delayed emergence following thoracoscopic radical lung cancer surgery under general anesthesia.

Objective:To investigate the current situation and related factors of children's growth and development in drinking-water-borne endemic fluorosis areas after water improvement, and provide a basis for improving the control strategies.Methods:The stratified random sampling method was used to select children aged 7 to 13 in villages with different years of water improvement in Xi'an from November 2019 to June 2020. The height and weight of children were measured, and body mass index (BMI) was calculated. The height development level of children was graded according to the "Standard for Height Level Classification among Children and Adolescents Aged 7 - 18 Years" (WS/T 612-2018), and the physical development (BMI) level of children was determined according to the "Comprehensive Evaluation of Development Level for Children and Adolescents" (GB/T 31178-2014). At the same time, according to the standard of "Diagnosis of Dental Fluorosis" (WS/T 208-2011), the diagnosis of dental fluorosis in children was performed. The serum fluoride level was determined by ion selective electrode method, and the levels of other chemical elements (calcium, iron, magnesium, copper, zinc, iodine, selenium, lead, arsenic, cadmium, chromium, mercury, nickel) in blood were determined by inductively coupled plasma mass spectrometry.Results:A total of 469 children were included in the investigation. After water improvement, 67.38% (316/469) of the children in the disease area were at the moderate level of height development, 7.89% (37/469) were at the medium to upper and upper levels, and 24.73% (116/469) were at the medium to lower and lower levels. The BMI of the children in the emaciation group was 8.53% (40/469), while it was 10.87% (51/469) in the overweight group and 8.74% (41/469) in the obesity group. There was statistically significant difference in the distribution of height development level of children in areas with different water improvement years ( P = 0.005), but no statistically significant difference in BMI distribution ( P = 0.154). There was no significant difference in height development level and BMI distribution of children with or without dental fluorosis ( P > 0.05). There were significant differences in serum levels of iron and zinc among children with different height development levels ( P < 0.05). There were significant differences in serum levels of magnesium, copper, iodine and chromium among children with different BMI ( P < 0.05). Conclusion:The growth and development of children in drinking-water-borne endemic fluorosis area after water improvement are not correlated with the prevalence of dental fluorosis, but may be related to the levels of chemical elements such as iron, magnesium, copper, and iodine in the body.

Objective To investigate the pathogenic distribution characteristics and drug resistance of opportunistic Candida in patients with pulmonary tuberculosis on the Qinghai-Tibet Plateau.Methods 3 012 hospitalized cases of pulmonary tuberculosis at Qinghai Province Fourth People's Hospital from March 1,2020 to December 31,2020 were analyzed,sputum samples were collected,Candida identification was carried by VITEK-32-YBC automatic bacterial analysis system,and the detected Candida was tested for drug sensitivity.Results Among the 3 012 cases of pulmonary tuberculosis in this investigation,283 cases of pulmonary tuberculosis patients with Candida infection,accounting for 9.40%.Among them,Candida albicans was the main type of Candida,accounting for 79.86%of the total.Conclusion The prevalence rate of pulmonary tuberculosis complicated with Candida infection was high in Qinghai-Tibet Plateau.Therefore,the selection of antimicrobial drugs should be based on a comprehensive analysis of the patient's condition,in order to select the best and most effective drugs for treatment.

Objective:To explore the impact of sleep duration, physical exercise, and their interactions on the risk of dyslipidemia in older adults aged ≥80 (the oldest old) in China.Methods:The study subjects were the oldest old from four rounds of Healthy Aging and Biomarkers Cohort Study (2008-2009, 2011-2012, 2014 and 2017-2018). The information about their demographic characteristics, lifestyles, physical examination results and others were collected, and fasting venous blood samples were collected from them for blood lipid testing. Competing risk model was used to analyze the causal associations of sleep duration and physical exercise with the risk for dyslipidemia. Restricted cubic spline (RCS) function was used to explore the dose-response relationship between sleep duration and the risk for dyslipidemia. Additive and multiplicative interaction model were used to explore the interaction of sleep duration and physical exercise on the risk for dyslipidemia.Results:The average age of 1 809 subjects was (93.1±7.7) years, 65.1% of them were women. The average sleep duration of the subjects was (8.0±2.5) hours/day, 28.1% of them had sleep duration for less than 7 hours/day, and 27.2% had sleep for duration more than 9 hours/day at baseline survey. During the 9-year cumulative follow-up of 6 150.6 person years (follow-up of average 3.4 years for one person), there were 304 new cases of dyslipidemia, with an incidence density of 4 942.6/100 000 person years. The results of competitive risk model analysis showed that compared with those who slept for 7-9 hours/day, the risk for dyslipidemia in oldest old with sleep duration >9 hours/day increased by 22% ( HR=1.22, 95% CI: 1.07-1.39). Compared with the oldest old having no physical exercise, the risk for dyslipidemia in the oldest old having physical exercise decreased by 33% ( HR=0.67, 95% CI: 0.57-0.78). The RCS function showed a linear positive dose-response relationship between sleep duration and the risk for hyperlipidemia. The interaction analysis showed that physical exercise and sleep duration had an antagonistic effect on the risk for hyperlipidemia. Conclusion:Physical exercise could reduce the adverse effects of prolonged sleep on blood lipids in the oldest old.

ObjectiveTo investigate the feasibility of applying electronic nose technology to rapidly identify Bletillae Rhizoma and its approximate decoction pieces. MethodA total of 134 batches of Bletillae Rhizoma and its approximate decoction pieces， including 45 batches of Bletillae Rhizoma， 30 batches of Gastrodiae Rhizoma， 30 batches of Polygonati Odorati Rhizoma and 29 batches of Bletillae Ochraceae Rhizoma， were collected as test samples. The olfactory sensory data of the samples were collected by PEN3 electronic nose as the independent variable（X）. Based on the identification results of the 2020 edition of Chinese Pharmacopoeia and local standards， as well as the high performance liquid chromatography（HPLC） fingerprint and original purchase information of 134 batches of the decoction pieces， the benchmark data Y of the identification model were obtained， and four chemometric methods of principal component analysis-discriminant analysis（PCA-DA）， partial least squares-discriminant analysis（PLS-DA）， least square-support vector machine（LS-SVM） and K-nearest neighbor（KNN） were used to establish the binary identification model for 45 batches of Bletillae Rhizoma and 89 batches of non-Bletillae Rhizoma and the quadratic identification model of the four kinds of decoction pieces， that is， Y=F（X）. ResultAfter leave-one-out cross validation， the positive discrimination rates of the above four models were 97.01%， 97.01%， 98.51% and 97.01% in the binary identification， and 97.76%， 89.55%， 98.51% and 97.01% in the quadratic identification， respectively. The highest positive discrimination rate could reach 98.51% for the binary and quadratic identification models， and LS-SVM algorithm is both the optimal one， the most suitable kernel functions were chosen as radial basis function and linear kernel function， respectively. The optimal models discriminated well with no unclassified samples. ConclusionElectronic nose technology can accurately and rapidly identify Bletillae Rhizoma and its approximate decoction pieces， which can provide new ideas and methods for rapid quality evaluation of other decoction pieces.