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Objective: To evaluate the associations between biological aging, metabolic heterogeneity of obesity, and rheumatoid arthritis (RA)., Methods: This prospective cohort study analyzed 268,184 individuals from the UK Biobank. Biological age was estimated using phenotypic age (PhenoAge), Klemera-Doubal methods (KDM-BA), and telomere length. We calculated KDM-BA acceleration and PhenoAge acceleration after subtracting the effect of chronological age by regression residual. The metabolic heterogeneity of obesity can be evaluated by four BMI metabolic phenotypes, namely metabolically unhealthy normal weight (MUNW), metabolically healthy normal weight (MHNW), metabolically unhealthy overweight/obesity (MUOO), and metabolically healthy overweight/obesity (MHOO). Cox models were employed to estimate the associations between biological aging, metabolic heterogeneity of obesity, and RA risk., Results: A total of 2842 patients experienced RA during a mean follow-up time of 12.21 years. A standard deviation (SD) increase in KDM-BA acceleration and PhenoAge acceleration was associated with an increased risk of RA by 13% (hazard ratio = 1.13; 95% CI, 1.09-1.17) and 39% (HR = 1.39; 95% CI, 1.34-1.44), respectively. A SD increase in telomere length was associated with a reduced risk of RA by 5% (HR = 0.95; 95% CI, 0.91-0.98). Compared to the MHNW group, the MUOO group was associated with a 51% increase in the risk of incident RA. In the joint effect analysis, compared to the MHNW + KDM-BA younger subgroup, the HR (95% CI) for RA was 1.68 (1.48, 1.90) in the MUOO + KDM-BA older subgroup., Conclusion: Accelerated biological aging may heighten the susceptibility to RA, particularly in individuals with obesity or metabolic dysfunction. Key Points •Accelerated biological aging increases the risk of developing RA. •Overweight/obese people with a healthy metabolism have a higher risk of RA than those with normal weight and healthy metabolism. •The BMI metabolic phenotype has a strong modifying effect on the association between KDM-BA/PhenoAge and RA risk., (© 2024. The Author(s), under exclusive licence to International League of Associations for Rheumatology (ILAR).)

Osteoarthritis (OA) is a threat to public health issue with high morbidity and disability worldwide. However, unequivocal evidence on the link between air pollution and OA remains little, especially in multi-study sites. This study aimed to explore the relationship between short-term exposure to main air pollutants and the risk of OA outpatient visits in multi-study sites. A multi-city time-series analysis was performed in Anhui Province, Central-Eastern China from January 1, 2015, to December 31, 2020. We used a two-stage analysis to assess the association between air pollution and daily OA outpatient visits. City-specific associations were estimated with a distributed lag nonlinear model and then pooled by random-effects or fixed-effects meta-analysis. Stratified analysis was conducted by gender, age, and season. Additionally, the disease burden of OA attributable to air pollutant exposure was calculated. A total of 35,700 OA outpatients were included during the study period. The pooled exposure-response curves showed that PM 2.5 and PM 10 concentrations below the reference values could increase the risk of OA outpatient visits. Concretely, per 10 ug/m 3 increase in PM 2.5 concentration was linked to an elevated risk of OA outpatient visits at lag 2 and lag 3 days, where the effect reached its highest value on lag 2 day (RR: 1.023, 95%CI: 1.005-1.041). We observed that a 10 μg/m 3 increase in PM 10 was positively correlated with OA outpatient visits (lag2 day, RR: 1.011, 95%CI: 1.001-1.025). Nevertheless, no statistical significance was discovered in gaseous pollutants (including SO 2 , O 3 , and CO). Additionally, a significant difference was found between cold and warm seasons, but not between different genders or age groups. This study reveals that particulate matter is an important factor for the onset of OA in Anhui Province, China. However, there is no evidence of a relationship of gaseous pollutants with OA in this area., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

With the deepening of research on the correlation between meteorological factors and autoimmune diseases, the relationship between climate change and dermatomyositis (DM) has come to our attention. This study aimed to explore the short-term correlation between meteorological factors and DM outpatient visits. Daily records of hospital outpatient visits for DM, air pollutants, and meteorological factor data in Hefei from January 1, 2018 to December 31, 2021 were obtained. The mean temperature (MT), relative humidity (RH), diurnal temperature range (DTR), and temperature change between neighboring days (TCN) were used to quantify environmental temperature and humidity and their variations. And we performed a time series analysis using a generalized linear model (GLM) in combination with a distributed lag nonlinear model (DLNM). Furthermore, gender and age were further stratified for the analysis. The sensitivity analysis was also performed. A total of 4028 DM outpatient visits were recorded during this period. There were statistically significant associations of low temperature (5th, 1.5 °C), low RH (1st, 48.6%), high RH (99th, 99%), high DTR (75th, 12.6°c), and low TCN (10th, -2.7 °C) that were associated with risk of DM outpatient visits, with lag days of 30, 16, 16, 10, and 14, respectively. Moreover, women were more susceptible to high RH exposure and low TCN exposure, while the elderly were more susceptible to low temperature. This study concluded that exposure to low temperature, extreme RH, and temperature changes (especially high DTR and low TCN) was associated with an increased risk of DM outpatient visits., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Evidence suggests a possible association between ambient air pollutants and oral diseases. Nevertheless, information regarding the relationship between air pollutants and pulpitis is scarce and inconclusive. In view of this, the present study aimed to investigate the relationship between short-term exposure to air pollution and outpatient visits for pulpitis. Daily data on outpatient visits for pulpitis, air pollutants, and meteorological data in Hefei, China, was collected from January 1, 2015 to December 31, 2021. The association between exposure to air pollutants and pulpitis outpatient visits was evaluated using distributed lag non-linear model (DLNM) and a generalized linear model (GLM). Furthermore, stratified analyses were performed by gender, age and season. A total of 93,324 records of outpatient visits for pulpitis were included in this study. The results showed that exposure to NO 2 , PM 2.5 , and CO were positively correlated with an increased risk of pulpitis outpatient visits. Each 10 μg/m 3 increase in NO 2 and PM 2.5 concentration, at lag 0-2 day, was associated with a 2.4% (relative risk (RR) = 1.024, 95% confidence interval (CI): 1.014-1.035) and 0.5% (RR = 1.005, 95% CI: 1.000-1.010) increase in pulpitis outpatient visits, respectively. With a 1 mg/m 3 increase in CO concentration, the risk of pulpitis outpatient visits increased by 9.1% (RR = 1.091, 95% CI: 1.031-1.154, lag 0-1 day). Intriguingly, exposure to O 3 was associated with a decreased risk of pulpitis outpatient visits (RR = 0.990, 95% CI: 0.984-0.995, lag 0-5 day). Subgroup analysis revealed that in the warm season, exposure to PM 2.5 , O 3 , and CO was related with a significantly higher outpatient risk of pulpitis than in the cold season. Additionally, the influence of PM 2.5 and CO exposure at age < 65 years was significantly stronger than at age ≥ 65 years. In conclusion, exposure to ambient NO 2 , PM 2.5 , and CO is associated with an increase in pulpitis outpatient visits in Hefei, China. Conversely, exposure to O 3 reduces the risk of outpatient visits for pulpitis. Age and season are effect modifiers of these associations., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Meteorological variables are regarded as risk factors for inflammatory diseases, but their associations with uveitis, one of the leading causes accounting for blindness worldwide with an estimated prevalence of 38-714 cases/100,000 person-years, have not been thoroughly investigated. The present study explored the short-term association between meteorological variables and hospital admissions for uveitis in Hefei City, China. Daily data on uveitis hospital admissions and meteorological variables including mean temperature (MT) (°C), diurnal temperature range (DTR) (°C), and relative humidity (RH) (%), from 2014 to 2020, were collected. A time-series study using generalized linear model combined with distributed lag non-linear model was applied. Totally, 1911 admissions for uveitis including 894 first admissions and 1017 readmissions were reported during the study period. The associations of high percentile of MT (75th, 24.5℃) and low percentile of DTR (25th, 5.4℃) with uveitis admissions were observed to be statistically significant from lag9 (RR = 1.041, 95%CI: 1.002-1.081) to lag11 (RR = 1.053, 95%CI: 1.003-1.104) and lag4 (RR = 1.053, 95%CI: 1.019-1.088) to lag5 (RR = 1.052, 95%CI: 1.020-1.085), respectively. Moreover, a significant association between low percentile of RH (1th, 44%) and uveitis admissions appeared at lag0-8 (RR = 1.869, 95%CI: 1.017-3.434) and lasted until lag0-13 (RR = 2.539, 95%CI: 1.102-5.850) in the cumulative lag structure. Subgroup analyses indicated that males and the young seemed to be more sensitive to high MT exposure, while females appeared to be more vulnerable to low DTR exposure. Interestingly, both the young and the elderly are susceptible to low DTR and low RH exposure. Furthermore, high MT and low DTR exposure were associated with increased risk of first admission for uveitis. In summary, exposure to high-value of MT and low-value of DTR and RH may increase the hospital admissions for uveitis, especially for the status of first admission., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Previous studies have found that non-optimal temperature influences the development of gout, but the results have been inconsistent. The present study aimed to explore the effects of high temperature and high temperature variation on hospitalizations for gout in Anqing, China. We collected daily data on air pollutants, meteorological factors, and hospitalizations for gout between 1January 2016 and 31 December 2020 in Anqing City, China. We used Poisson generalized linear regression model and a distributed lag non-linear model (DLNM) to explore the relationship of high temperature, diurnal temperature range (DTR), and temperature change between neighboring days (TCN) with hospitalizations for gout. Stratified analysis by gender (male, female) and age (<65 years, ≥65 years) was conducted. Hospitalizations for gout attributed to high temperature, high DTR, and high TCN were also quantified. A total of 8675 hospitalized patients with gout were reported during the study period. We observed that exposure to high temperature was linked with an increased risk of hospitalizations for gout (lag 0, RR: 1.081, 95% confidence interval (CI): 1.011, 1.155). Exposure to high DTR was also associated with increased risk of hospitalizations for gout (lag9, RR: 1.017, 95% CI: 1.001,1.035). A large drop in temperature between neighboring days was associated an increased risk of hospitalizations for gout (lag 0-2 days, RR: 1.234, 95% CI: 1.017, 1.493). Stratified analysis results revealed that older adults and men were more sensitive to high-level DTR exposure than their counterparts. Nearly 15% of hospitalizations for gout could be attributable to high temperature (attributable fraction: 14.93%, 95% CI: 5.99%, 22.11%). This study suggests that high temperature and high temperature variation may trigger hospitalizations for gout, indicating that patients with gout need to take proactive actions in the face of days with non-optimal temperature., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The optimal dose of warfarin depends on polymorphisms in the VKORC1 (the vitamin K epoxide reductase complex subunit (1) and CYP2C9 (cytochrome P450 2C9) genes. To minimize the risk of adverse reactions, warfarin dosages should be adjusted according to results from rapid and simple monitoring methods. However, there are few pharmacogenetic-guided warfarin dosing algorithms that are based on large cohorts from the Chinese population, especially patients with atrial fibrillation. This study aimed to validate a pharmacogenetic-guided warfarin dosing algorithm based on results from a new rapid electrochemical detection method used in a multicenter study. Three SNPs (CYP2C9 *2, *3 and VKORC1 c.-1639G > A) were genotyped by electrochemical detection using a sandwich-type format that included a 3' short thiol capture probe and a 5' ferrocene-labeled signal probe. A total of 1285 samples from four clinical hospitals were evaluated. Concordance rates between the results from the electrochemical DNA biosensor and the sequencing test were 99.8%. The results for gene distribution showed that most Chinese patients had higher warfarin susceptibility because mutant-type and heterozygotes were present in the majority of subjects (99.4%) at locus c.-1639G > A. When the International Warfarin Pharmacogenetics Consortium algorithm was used to estimate therapeutic dosages for 362 patients with AF and the values were compared with their actual dosages, the results revealed that 56.9% were similar to actual dosages (within the 20% range). A novel electrochemical detection method of CYP2C9 *2, *3and VKORC1 c.-1639G > A alleles was evaluated. The warfarin dosing algorithm based on data gathered from a large patient cohort can facilitate the reasonable and effective use of warfarin in Chinese patients with AF.

This mini-review introduces a general understanding of the use of a milli-whistle as a gas chromatography (GC) detector in gas analysis, including our research on the methodology and theory associated with a number of different related applications. The milli-whistle is connected to the outlet of a GC capillary, and when the eluted gases and the GC carrier gas pass through it, a sound with a fundamental frequency is produced. The sound wave can be picked up by a microphone or an accelerometer, and after a fast Fourier transform, the online data obtained for frequency-change vs. retention time constitute a new method for detecting gases. The first part of this review discusses the fundamentals of the milli-whistle. Some modifications are also discussed, including various types of whistles and an attempt to maximize the sensitivity and stability of the method. The second part then focuses on several practical applications, including an analysis of hydrogen released from ammonia borane, inorganic gases produced from fireworks, the CO2/O2 ratio from expired human breath and a purity test for alcohols. These studies show that the GC-whistle method has great potential for use as a fast sampling ionization method, and for the direct analysis of biological and chemical samples at under ambient conditions.

The sex pheromone components from the corn borer spreading widely in China,Ostrinia furnacalis Guenée, have been identified as (E)-and (Z)-12-tetradecenyl acetates (E andZ12-14∶ Ac). The ratio ofE isomer toZ isomer was 53 ∶ 47. Traps containing 1 × 10(-7)-1 × 10(-5) g of these compounds captured more males than did live females or their tip extract (3-6 female equivalents). Tetradecyl acetate (14 ∶ Ac) was also identified in the tip extract. Its quantity was about 1.8 times the sum of the other two isomers. However, including this compound in its natural ratio in pheromone traps resulted in a decrease in trap catches (P< 0.05).