The influence of cimetidine on the pharmacokinetics of ftorafur ( FT-207 ) in 9 rats after intragastric administration were investigated with cross-over design. The concentration of ftorafur in serum was determined by reversed-phase HPLC. Its curve of concentration vs time was fit to one compartment opened model. The serum concentrations and areas under the curve ( AUC ) vs time were increased when cimetidine orally administered daily for 5d or single dose. The peak of serum and AUC of ftorafur were increased by 21 .0%(P

The pharmacokinetics and absolute bioavailability of 1-hexyl-carbamoyl-5-fluorouracil ( HCFU ) (10 mg/kg ) after oral and intravenous administration were studied in 5 dogs with cross-over design. The concentration of HCFU in serum was determined by reversed-phase high performanee liquid chromatography. After intravenous administration, the curve of serum HCFU concentration vs time was fit to a two-compartment opened model and the phar-macokinetic parameters were. T1/2?=1 .67 min, T1/2? = 34.55 min, Vc= 0.2525L/kg,C1 = 0.3205 L/kg?h~-1 & AUCiv =1.9375 mmol/min?L~-1. When HCFU tablets were tiken orally, the curve of concentration vs time was fit to an one-compartment opened model and its pharmacokinetie parameters were: T1/2ke=12.13 min, T1/2ke=38.51 min, Tmax=23.46 min,Cmax=8.140?10~-3mmol/L & AUCpo=1.5856 mmol/min?L~-1 . The absolute bioavailability calculated from AUCpo and AUCiv was 0.8214.

Objective: To analyze the spatio-temporal distribution characteristics of pulmonary tuberculosis incidence in Xinjiang, and to provide reference for the prevention and control of pulmonary tuberculosis. Methods: The reported incidence numbers of tuberculosis and population data from various counties, cities(prefectures), and districts in Xinjiang from 2010 to 2022 were collected. Based on spatial-temporal scan statistics, standard deviational ellipse analysis, and centroid migration models, the clustering and migration trends of tuberculosis incidence were evaluated. Utilizing Kriging interpolation techniques, an interpolation analysis of the 2022 incidence rate was conducted on an annual scale, with the reported incidence rate in 2018 serving as a temporal control, to identify hotspots of the spatio-temporal distribution. ArcGIS software was employed to visualize the continuous spatial trends of incidence rate changes. Results: The annual reported incidence rate of tuberculosis in Xinjiang from 2010 to 2022 varied year by year, with fluctuations and increases prior to 2018, peaking in 2018, and then declining annually thereafter. The spatial distribution of the incidence rate exhibited a trend of initial clustering followed by diffusion, with the centroid of incidence shifting towards the northeast, yet the epicenter of the epidemic remained in Aksu Prefecture. The results of spatiotemporal scan statistics analysis revealed that the three-level aggregated areas of the epidemic encompassed a total of 41 prefectures, counties, and cities, with the tuberculosis incidence risk in the primary and secondary aggregated areas being significantly higher than that in other regions(P<0.01). The Kriging interpolation prediction map suggested that the four prefectures in southern Xinjiang continued to be high-risk regions for tuberculosis(incidence rate>300/100 000). The overall incidence rate in the northern region was relatively low, with the lowest rate observed in Urumqi, radiating outwards. Conclusion The incidence rate of tuberculosis in Xinjiang shows an upward trend before 2018, followed by a year-on-year decrease. The centroid of the incidence rate shifts towards the northeast. From 2010 to 2022, the tuberculosis epidemic in Xinjiang exhibits a notable spatiotemporal clustering, particularly prominent in the southwestern region, where the four prefectures constitute high-risk areas for tuberculosis. The prevention and control efforts of tuberculosis in Xinjiang should prioritize the regions with high tuberculosis incidence, intensifying prevention and control measures as well as policy support.

Background The effects of meteorological factors and air pollutants on ischemic heart disease (IHD) hospitalizations in Urumqi have not been fully understood. Objective To investigate the effects of meteorological conditions (temperature, relative humidity) and common air pollutants [fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), ozone (O₃), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO)] on the daily hospitalization volume of IHD, and to provide a scientific basis for the development of targeted prevention and management strategies. Methods Basic information of 90622 IHD hospitalized patients in Urumqi City was collected from January 1, 2014 to December 31, 2022, and daily air pollutant concentration data and meteorological data were collected during the same period. The meteorological data included daily mean temperature, daily maximum temperature, daily minimum temperature, and daily mean relative humidity, and the common air pollutants included PM_2.5, PM₁₀, daily maximum 8-h average concentration of O₃ (O₃_8 h), SO₂, NO₂, and CO. Descriptive statistical analyses (mean, standard deviation, and quartiles) were performed on the collected data. A distribution lag nonlinear model (DLNM) based on time-stratified case-crossover design was established to estimate the lagged effects (RR) as well as the cumulative lagged effects (RR_cum) of daily mean temperature, relative humidity, and different air pollutants on the number of IHD admissions, stratified by gender and age (<60 and ≥60 years). Subsequently, a generalized additive model (GAM) was used to explore the effects of cold waves (≤ P₅ of the daily minimum temperature and lasting ≥3 d) versus heat waves (≥ P₉₅ of the daily maximum temperature and lasting ≥3 d) on IHD hospitalizations and the potential interactions between temperature and the more influential air pollutants [particulate matter (PM) and O₃_8 h] on IHD hospitalizations. Results The maximum number of IHD hospitalizations in a single day in Urumqi from January 1, 2014 to December 31, 2022 was 100, and the average daily number of hospitalized IHD patients was 27. Daily mean temperature, relative humidity, and air pollutants had different nonlinear relationships and hysteresis with IHD hospitalizations. Extremely low temperatures (<P₁: −18 °C) showed the greatest risk to admission for the total IHD population at a cumulative lag of 31 d (lag0-31) (RR_cum=2.092, 95%CI: 1.261,3.471). Female [lag0-31, RR_cum and 95%CI: 3.416 (2.296,5.082)] and people ≥60 years old [lag0-31, RR_cum and 95%CI: 2.356 (1.681,3.303)] were more sensitive to extremely low temperatures. The risk of IHD hospitalization was greatest on lag20 for cold waves (RR=1.242, 95%CI: 1.053, 1.465), and no lagged effect of heat waves on the number of IHD hospitalizations was found. There was a positive interaction (SI >1, P<0.001) between temperature, PM, and O₃_8 h on the risk of IHD hospitalization, especially for low temperature-high PM and O₃_8 h. Conclusion Both low temperature and high pollutant concentrations associate with an increase in IHD hospitalizations with lagged effects in Urumqi from 2014 to 2022, while cold waves associate with a higher risk of IHD admissions. Females and people aged 60 years and older are at high risk.