ObjectiveTo compare the differences in fungal community composition between lesional and non-lesional scalp areas in patients suffering from severe alopecia areata （AA）， and compare these with healthy scalp areas in control subjects. Additionally， to preliminarily explore the changes in scalp fungal communities in severe AA patients and their potential underlying immunological mechanisms. MethodsA total of 20 severe AA patients and 18 healthy controls were enrolled. Skin swab samples were collected from lesional and non-lesional scalp areas of severe AA patients， as well as from the normal scalp of healthy controls. The fungal internal transcribed spacer （ITS） region was amplified and analyzed using high-throughput sequencing. ResultsThe lesional scalp areas of severe AA patients exhibited higher α-diversity and species richness in fungal communities. Notably， the relative abundance of Ascomycota， along with genera such as Mycosphaerella， Aspergillus， Penicillium， and Wallemia， significantly increased in the bald regions. In contrast， Acremonium and Schizophyllum were more predominant in the non-lesional areas of severe AA patients. ConclusionDistinct region-specific differences in scalp fungal microbiota in severe AA patients suggests that fungal dysbiosis may play a potential role in the pathogenesis of alopecia areata. These findings provide new insights into the disease characteristics of severe AA from the perspective of scalp microecology.

Objective To explore the association between different levels of fluoride exposure and dyslipidemia in elderly people, and to analyze the influencing factors and their interactions. Methods A total of 1 143 elderly people over 60 years old were randomly selected from historical high water fluorosis areas and control areas in Tianjin. Logistic regression model and classification tree model were used to analyze the influencing factors of dyslipidemia, and to analyze the interaction between high fluoride exposure and relevant influencing factors on dyslipidemia. Results The prevalence of elevated low density lipoprotein cholesterol (LDL-C) was 5.69% (65/1 143). There was a significant difference in the prevalence of high LDL-C in different fluoride-exposed areas (2 = 0.092，P = 0.762). Multivariate logistic analysis showed that high fluoride exposure (OR=2.306，95%CI：1.185-4.491) and abdominal obesity (OR=2.274，95%CI：1.299-3.978) were risk factors for high LDL-C, while type B personality (OR=0.529，95%CI：0.308-0.908) was a protective factor for high LDL-C. The results of classification tree model showed that abdominal obesity contributed the most to the prevalence of high LDL-C in the elderly, followed by high fluoride exposure and hyperglycemia. There was a significant multiplicative interaction between high fluoride exposure and abdominal obesity on dyslipidemia (OR=5.191,95%CI：1.609-16.745，P=0.006). Conclusion High fluoride exposure may increase the risk of high LDL-C, and there is a multiplicative interaction between high fluoride exposure and abdominal obesity on dyslipidemia.

Objective:To investigate the main influencing factors of mild cognitive impairment(MCI)in the elderly and explore the interaction between high fluoride exposure and related co-factors on MCI.Methods:A cross-sectional study was conducted from May to December 2024 in four towns in the rural areas of Tianjin(two historically high-fluoride towns and two non-high-fluoride towns). A total of 125 elderly people aged 60 years and above were randomly selected from each township.MCI was diagnosed using the Mini-Mental State Examination(MMSE)and Montreal Cognitive Assessment-Basic(MoCA-B)according to the diagnostic criteria for MCI.Binary logistic regression was used to analyze the influencing factors of MCI, and conditional logistic regression was employed to assess multiplicative and additive interaction effects.Results:A total of 481 participants were included, with 354 in the normal group and 127 in the MCI group, and the incidence of MCI was 26.40%.Univariate analysis showed that MCI was associated with age, annual household income per capita, high fluoride exposure, life stress, depression, and abnormal urinalysis( χ2=4.241, 4.017, 4.552, 7.143, 4.151, 5.113, all P<0.05). Multivariate logistic regression revealed that after adjusting for other confounders, high fluoride exposure( OR=1.816, 95% CI: 1.177-2.802), age ≥70 years( OR=1.584, 95% CI: 1.034-2.428), depression( OR=2.106, 95% CI: 1.042-4.254), and abnormal urinalysis( OR=1.595, 95% CI: 1.041-2.444)increased the risk of MCI.Compared with severe life stress, moderate stress( OR=0.254, 95% CI: 0.082-0.790)reduced the risk of MCI.No multiplicative or additive interaction was found between high fluoride exposure and depression, life stress, or abnormal urinalysis. Conclusions:High fluoride exposure, age ≥70 years, depression, abnormal urinalysis, and severe life stress may increase the risk of MCI in the elderly, but there is no interaction among them.

Objective:To screen the risk factors for non-complete procedural success of transvenous lead extraction(TLE),and to establish a prediction model based on the results and evaluate its predictive efficacy.Methods:A total of 1 029 patients who underwent TLE in Peking University People's Hospital from January 2014 to December 2020 were enrolled and divided into training set(n=720)and validation set(n=309)using the random number method.There were no statistically significant differences among the variables in the training set and the validation set.The training set was divided into the complete procedural success(CPS)group(n=664)and the non-CPS group(n=56).Univariate analysis was employed to screen the relevant indicators of non-CPS,followed by binary logistic regression analysis to identify the independent risk factors of non-CPS.Subsequently,a predictive model and nomogram were constructed.The receiver operating characteristic(ROC)curve analysis was applied to evaluate the ability of the model to distinguish non-CPS from TLE patients in the training set and validation set.The Hosmer-Lemeshow goodness-of-fit test was used to assess the consistency between the predicted risk and the actual risk of the model.Results:Univariate analysis showed that the relevant variables with P<0.1 including the age at the first implantation of the lead,the number of leads extracted,the oldest dwell time of lead extracted,the presence of abandoned leads,non-manual traction for lead extracted,the number of extracted leads>3,bilateral lead implantation,and the indications for TLE.The binary logistic regression analysis revealed that the presence of abandoned leads(OR=2.252,95%CI:1.111-4.564,P=0.024),the oldest dwell time of the extracted leads(OR=1.009,95%CI:1.005-1.012,P<0.001),and the number of extracted leads>3(OR=3.177,95%CI:1.306-7.733,P=0.011)were independent risk factors for non-CPS of TLE.ROC curve analysis revealed that the area under the ROC curve(AUC)of the training set was 0.80(95%CI:0.75-0.85,P<0.001).The AUC of the validation set was 0.81(95%CI:0.72-0.90,P<0.001).The Hosmer-Lemeshow goodness-of-fit test indicated that the P values of both the training set(P=0.089)and the validation set(P=0.136)were greater than 0.05.Conclusions:The presence of abandoned leads,the oldest dwell time of lead extracted,and the number of extracted leads>3 are independent risk factors for non-CPS in patients undergoing TLE.The nomogram model based on the above factors has satisfactory predictive ability.

Objective:To evaluate the incidence and frequency of inappropriate shocks caused by defibrillation lead failure in patients with implantable cardioverter-defibrillators (ICD), and to explore methods for reducing the incidence and frequency of such inappropriate shocks.Methods:This was a single-center retrospective study involving patients treated for defibrillation lead failures at Peking University People′s Hospital between March 2015 and May 2024. Patients were divided into an alarm function group and a non-alarm function group based on whether their ICDs were equipped with lead alarm functions. Clinical data, lead data, and the incidence and frequency of inappropriate shocks were collected and compared between the two groups. A multivariate logistic regression model was used to analyze factors influencing the incidence and frequency of inappropriate ICD shocks. Kaplan-Meier survival curves were plotted to compare the trends in the incidence and frequency of inappropriate shocks over time since ICD implantation between the two groups.Results:A total of 59 patients were enrolled, with a age of (56.7±15.2) years, including 42 males (71%). The lifespan of the failed leads in the entire cohort was 64.0 (36.0, 96.0) months. There were 26 patients in the alarm function group and 33 in the non-alarm function group. The most common manifestations of lead failure were oversensing (85%, 50/59) and abnormal pacing impedance (42%, 25/59). A total of 33 patients (56%, 33/59) experienced inappropriate shock therapy, with an average of 27.3 shocks per patient. The frequency of inappropriate ICD shocks in the non-alarm function group was higher than that in the alarm function group (25.0 (10.0, 60.0) times/year vs. 5.0 (2.8, 7.8) times/year, P=0.001). Multivariate logistic regression analysis showed that oversensing ( OR=2.057, 95% CI 1.125-6.763, P=0.019) was an influencing factor for incidence of inappropriate shocks, while the lead alert function ( OR=0.062, 95% CI 0.005-0.719, P=0.001) was a factor influencing the frequency of inappropriate shocks. Kaplan-Meier survival analysis revealed that the incidence and frequency of inappropriate shocks increased with the duration of ICD implantation in both groups, but the differences were not statistically significant (incidence: log-rank P=0.908; frequency: log-rank P=0.767). Conclusion:The lead alert function can reduce the frequency of inappropriate shocks caused by lead failure.

Objective:To investigate the prevalence of dental fluorosis in children in Tianjin and study its influencing factors.Methods:From January to December 2023, 5 affected villages were selected from each of the drinking water-borne endemic fluorosis (drinking water-borne fluorosis for short) areas of 10 agricultural areas in Tianjin, and 50 children aged 8 - 12 years (gender and age balanced) were selected from each affected village for questionnaire survey and dental fluorosis examination. At the same time, water samples from affected villages and children's one random urine sample were collected to test for fluoride levels in water and urine. Multivariate logistic regression was used to analyze the influencing factors of dental fluorosis prevalence in children, and a restricted cubic spline model was used to analyze the dose-response relationship between the years of water improvement and dental fluorosis prevalence.Results:A total of 50 water samples were collected, with water fluoride levels ranging from 0.05 to 0.85 mg/L. All affected villages had completed the water improvement and the water fluoride levels were qualified. A total of 2 439 urine samples were collected from children, with urinary fluoride levels ranging from 0.05 to 12.56 mg/L and a geometric mean of 0.82 mg/L. A total of 2 439 children were examined for dental fluorosis, with a detection rate of 22.67% (553/2 439). The results of multivariate logistic regression analysis showed that age ( OR = 1.26, 95% CI: 1.15 - 1.37, P < 0.001), father's education level of junior high school or below ( OR = 1.57, 95% CI: 1.04 - 2.38, P = 0.033), and high urinary fluoride (0.74 - 1.58 mg/L: OR = 1.59, 95% CI: 1.19 - 2.13, P = 0.002; 1.59 - 12.56 mg/L: OR = 2.00, 95% CI: 1.48 - 2.70, P < 0.001) were risk factors for dental fluorosis prevalence in children. The total annual household income with 40 000 to 80 000 yuan ( OR = 0.76, 95% CI: 0.58 - 0.99, P = 0.041), father's occupation was self-employed and other occupation ( OR = 0.69, 95% CI: 0.51 - 0.92, P = 0.013), the years of water improvement in affected villages ≥10 years ( OR = 0.39, 95% CI: 0.30 - 0.50, P < 0.001), and the material of the drinking water container at home was stainless steel products ( OR = 0.58, 95% CI: 0.40 - 0.85, P = 0.005), ceramic or glass products ( OR = 0.66, 95% CI: 0.48 - 0.90, P = 0.010) were protective factors for dental fluorosis prevalence in children. By constructing a restricted cubic spline model, it was found that there was a linear dose-response relationship between the prevalence of dental fluorosis in children and the years of water improvement in affected villages ( Poverall < 0.001, Pnonlinear = 0.059). The longer the years of water improvement, the lower the risk of dental fluorosis prevalence. Conclusions:The detection rate of dental fluorosis in children in Tianjin is relatively high. The fluoride reduction and water improvement measures implemented in drinking water-borne fluorosis areas can effectively reduce the risk of dental fluorosis prevalence. Factors such as age, urinary fluoride, economic conditions, and lifestyle also have important impacts on the prevalence of dental fluorosis.

Objective:To investigate the awareness of prevention and treatment knowledge of drinking water-borne endemic fluorosis among children in Tianjin, explore its influencing factors, analyze the needs of children's health education methods, and provide a basis for carrying out health education in school.Methods:From January to December in 2024, a stratified sampling method was employed to select two endemic villages from each of the 10 areas with drinking water-borne endemic fluorosis in Tianjin as survey sites. In each village, no fewer than 50 children aged 8 - 12 (gender and age balanced) were recruited to conduct a questionnaire survey. Multivariate logistic regression analysis was used to analyze the influencing factors of children's awareness of prevention and treatment knowledge.Results:A total of 1 678 valid questionnaires were collected. The overall awareness rate of prevention and control knowledge of drinking water-borne endemic fluorosis among children in Tianjin was 67.62% (11 346/16 780). Children had the highest awareness of the hazards of drinking water-borne endemic fluorosis (83.61%, 1 403/1 678), while their awareness of the clinical manifestations of dental fluorosis was the lowest (44.87%, 753/1 678). Multivariate logistic regression analysis showed that children in higher grades [grades 5 to 6, OR (95% CI) = 1.66 (1.36, 2.03), P < 0.001], with a larger number of permanent residents in the family [≥6 people, OR (95% CI) = 1.58 (1.13, 2.23), P = 0.008], whose mothers had a college education or above [ OR (95% CI) = 1.45 (1.08, 1.95), P = 0.014], and who had received health education [ OR (95% CI) = 1.46 (1.19, 1.78), P < 0.001] had a higher awareness rate of the prevention and control knowledge of drinking water-borne endemic fluorosis. There were statistically significant differences in the demand rates for access to prevention and control knowledge via school teachers, promotional videos, and online/WeChat official accounts among children of different grades ( P < 0.05). Conclusions:The awareness rate of prevention and treatment knowledge of drinking water-borne endemic fluorosis among children in Tianjin is relatively low. Special attention should be paid to children with a small number of permanent residents in the family, mothers with low educational levels, and who have not received health education. At the same time, detailed health publicity services should be carried out for children of different grades.

Objective: To understand the dose response relationship between urinary fluoride and dental fluorosis among children from drinking water borne endemic fluorosis areas in Tianjin, so as to provide a scientific basis for assessing fluoride exposure risk among children from endemic areas and establishing reference values for urinary fluoride. Methods: From January to December 2024, 83 endemic villages were selected in Tianjin. A total of 2 382 children aged 8-12 years from these villages underwent dental fluorosis examination, along with water fluoride and urinary fluoride testing. Additionally, data from areas where the drinking water fluorosis control target was achieved for more than 12 years (10 villages, 50 people per village) were included as controls. A restricted cubic spline model was used to analyze the relationship between urinary fluoride levels and dental fluorosis prevalence, and benchmark dose (BMD) and benchmark dose lower bound (BMDL), as well as reference dose (RfD), were calculated using the benchmark dose method. Results: The prevalence rates of dental fluorosis among children in drinking water borne endemic fluorosis areas and areas of normal fluoride content in water in Tianjin were 10.58%, 7.60%, with a geometric mean urinary fluoride level of 0.72 and 0.60 mg/L,respectively. There were statistically significant differences in both dental fluorosis prevalence and geometric mean urinary fluoride levels between the drinking water borne endemic fluorosis areas group and the areas of normal fluoride content in water ( χ 2/Z = 4.05 , -7.31, both P <0.05). Across different periods of water source improvement, there were statistically significant differences in overall population, male, and female dental fluorosis prevalence rates and geometric mean urinary fluoride levels ( χ 2/H =44.95, 23.96, 21.05; 168.39, 63.93, 107.50, all P <0.01). Significant differences were also observed across age groups among children from drinking water borne endemic fluorosis areas in terms of dental fluorosis prevalence and geometric mean urinary fluoride levels ( χ 2/H =32.14, 79.73, both P <0.01). The results of the restricted cubic spline model showed that the risk of dental fluorosis in different sex, age and overall children in the drinking water borne endemic fluorosis areas increased significantly with rising urinary fluoride concentration(all P-general trend <0.05). The BMD value for the drinking water borne endemic fluorosis areas was 1.72 mg/L, the BMDL was 1.31 mg/L, and the RfD was 1.31 mg/L. Conclusions The prevalence of dental fluorosis among children in the drinking water borne endemic fluorosis areas in Tianjin has been effectively controlled, but it is still higher than that in the areas of normal fluoride content in water. Moreover, urinary fluoride levels and dental fluorosis prevalence among children from drinking water borne endemic fluorosis areas show a clear dose response relationship.

Objective To analyse the mediating effect of the pain beliefs on pain and fear of disease progression in patients with trigeminal neuralgia.Methods A convenience sampling method was employed to select hospitalised 220 patients with trigeminal neuralgia as research objects from 3 Grade IIIA hospitals.The selected study subjects were surveyed with a general information questionnaire,the numeric pain rating scale,pain beliefs and perceptions scale,and fear of disease progression short form.Structural equation model was used to verify the pathways that affected the pain and pain beliefs on fear of disease progression in patients with trigeminal neuralgia.Results A total of 214 patients with trigeminal neuralgia completed the survey.The mean score of fear of disease progression was 33.38±8.47,the mean score of pain was 8.25±1.44,and the mean score of pain beliefs was-2(-9,8).Spearman correlation analysis showed that fear of disease progression was positively correlated with the pain beliefs(r=0.746,P<0.01)and pain(r=0.838,P<0.01),and the pain beliefs were positively correlated with pain intensity(r=0.704,P<0.01).Pain beliefs partially mediated between the pain and fear of disease progression in patients with trigeminal neuralgia,with a mediating effect of 0.442,a direct effect of 0.482,and a total effect of 0.924.The mediating effect accounted for 47.84%of the total effect.Conclusion Patients with trigeminal neuralgia generally have a critical state of psychologicol disfunction of fear of disease progression,with a moderate to severe pain,and moderate pain beliefs.Pain intensity in patients with trigeminal neuralgia not only directly affects fear of disease progression but also indirectly affects it through pain beliefs.

Objective:To investigate the situation of mild cognitive impairment (MCI) in elderly people in fluorosis areas, and analyze its potential influencing factors.Methods:From April to October 2020, a cluster random sampling method was used to select local elderly people aged 60 and older in areas of drinking-water-borne endemic fluorosis in Tianjin, and their general information was collected through face-to-face surveys. Terminal drinking water samples were collected from survey subjects. Water fluoride concentration was measured using ion-selective electrode method. Cognitive function was evaluated using the Mini-Mental State Examination (MMSE), and survey subjects were categorized into MCI group and control group based on MMSE scores. Logistic regression and Chi-squared automatic interaction detection classification tree models were constructed to analyze the influencing factors of MCI.Results:A total of 677 subjects were included, including 160 cases in the MCI group and 517 cases in the control group, with a MCI detection rate of 23.63%. The detection rates of MCI in the high fluoride exposure group and non high fluoride exposure group were 30.82% (94/305) and 17.74% (66/372), respectively, with a statistically significant difference between the groups (χ 2 = 15.88, P < 0.001). The results of univariate analysis showed that MCI was associated with high fluoride exposure, age, per capita annual household income, sleep duration, personality, and interpersonal relationships (χ 2 = 15.88, 16.17, 12.32, 8.91, 14.03, 9.81, P < 0.05). The results of multiple logistic regression analysis showed that moderate interpersonal relationships ( OR = 2.13, 95% CI: 1.08, 4.20) and high fluoride exposure ( OR = 1.91, 95% CI: 1.03, 3.54) were both risk factors for MCI ( P < 0.05). The classification tree model analysis result showed that high fluoride exposure was the primary factor affecting MCI in elderly people in fluorosis areas, followed by per capita annual household income, personality, and age. Conclusions:The detection rate of MCI in the high fluoride exposure group of elderly people in fluorosis areas is higher than that in the non high fluoride exposure group. High fluoride exposure, interpersonal relationships, per capita annual household income, personality, and age are all influencing factors of MCI in elderly people in fluorosis areas.