ObjectiveTo study the effect of Taikong Yangxin Pills on the metabolism of simulated weightless rats based on metabolomics and discuss the metabolism mechanism. MethodsIn the simulated space capsule environment on the ground， the rat model of simulated weightlessness was established by the tail suspension method. Rats were randomly grouped as follows： out-of-capsule control， in-capsule control， model， and high （3.0 g·kg^-1） and low （1.5 g·kg^-1） doses of Taikong Yangxin Pills， and they were administrated with corresponding drugs by gavage for 28 days. The serum levels of endogenous metabolites in rats were determined by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry （UPLC-Q-TOF/MS）. The obtained data were processed by principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA） to screen for differential metabolites and potential biomarkers. MetaboAnalyst 5.0 was used for pathway enrichment analysis to explain the metabolic regulation mechanism of the drug. ResultsCompared with the out-of-capsule control group， the in-capsule control group showed elevated levels of thirteen metabolites， including 14-hydroxyhexadecanoic acid， linoleic acid， and α-linolenic acid （P<0.05）， which suggested that the space capsule environment mainly affected the metabolism of α-linolenic acid and linoleic acid in the rats. Compared with the in-capsule control group， the model group showed lowered levels of fourteen metabolites， including 4-imidazolone-5-propionic acid， isocitric acid/citric acid， and L-tyrosine （P<0.05）， which were recovered after the treatment with Taikong Yangxin pills （P<0.05）. The pathway enrichment analysis revealed that weightlessness induced by tail suspension and drug intervention mainly involved the phenylalanine， tyrosine， and tryptophan biosynthesis， tyrosine metabolism， histidine metabolism， and citric acid cycle. ConclusionThe simulated space capsule environment and simulated weightlessness induced by tail suspension can both affect the metabolism level of rats. Taikong Yangxin pills can ameliorate the metabolic abnormality in the rat model of weightlessness by regulating various amino acids and energy metabolism-related pathways.

[Objective] To explore the influencing factors of quality monitoring index on the nucleic acid pooling detection mode and continuously improve the detection quality of nucleic acid laboratory. [Methods] The quality monitoring indicators (NAT reactive rate, NAT resolution reactive rate, NAT invalid batch rate, NAT invalid result rate, equipment failure rate) and causes of invalidity in our laboratory from January 1, 2020 to December 31, 2022 were retrospectively analyzed. The quality monitoring indicators of the laboratory during 2020 to 2022 were compared longitudinally. The quality monitoring indicators of the laboratory in 2022 were compared horizontally with the overall level in Shandong for the same period to find the differences. [Results] From 2020 to 2022, a total of 218 686 samples were detected, the NAT reactive rate was 0.15‰ (32 samples in total), the resolution reactive rate was 39.02%, the invalid batch rate was 1.06%, the invalid result rate was 1.18%, and the equipment failure rate was 3.58%. There were no differences in the NAT reactive rate, NAT resolution reactive rate and NAT invalid batch rate among different years (P>0.05), but there were differences in the invalid result rate (P<0.05). Equipment failure was the main cause of invalid results (56.53%). Compared with other laboratories in Shandong, there were differences in the NAT reactive rate and invalid result rate (P<0.05). There were differences in the reaction rate, resolution rate and invalid result rate among different reagents (P<0.05). Compared with other two laboratories using the same manufacturer's reagent, there were differences in the reactive rate and invalid result rate (P<0.05), but no difference in the resolution rate and invalid batch rate (P>0.05). [Conclusion] Establishing quality indexes for process control and regular analysis can timely detect potential risks in laboratory operation. The use of quality indicators to implement self-comparison and inter-laboratory comparison can help the laboratory systematically and scientifically evaluate its own operating status and formulate corresponding quality management strategies, thereby improving the laboratory's testing capacity and ensure the safety of blood use.

ObjectiveTo elucidate the chemical composition of Danshenyin and its blood components in rats after oral administration. MethodsUltra performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry（UPLC-Q-TOF-MS/MS） coupled with PeakView 1.2 software was used to systematically characterize and identify the components of Danshenyin aqueous extract and its migratory components in rat blood after oral administration based on the retention time， quasi-molecular ion peaks， secondary fragmentation ions， and literature reports， and a preliminary compounds identification of Salviae Miltiorrhizae Radix et Rhizoma aqueous extract， the co-decoction of Santali Albi Lignum and Amomi Fructus was carried out to attribute the chemical constituents of the aqueous extract of Danshenyin. ResultsA total of 73 compounds， including 21 phenolic acids， 23 diterpenes， 6 flavonoids， 7 organic acids， 3 volatile oils and 13 others， were identified from the aqueous extract of Danshenyin. And 36 prototypes and 15 metabolites were identified in rat plasma， the major metabolic pathways included reduction， hydration， hydroxylation， demethylation， methylation， sulfation and others， these metabolites were mainly derived from tanshinones and salvianolic acids. ConclusionThe main blood components of the aqueous extract of Danshenyin are salvianolic acids and tanshinones， which may be the material basis of the efficacy. This study can provide reference for pharmacological research， quality control， and clinical application of Danshenyin.

Objective To analyze the status and risk factors of Helicobacter pylori (Hp) infection in permanent residents in a certain area. Methods The clinical data of 6 792 permanent residents surveyed from January 2021 to December 2023 were retrospectively analyzed. All subjects underwent 13C-urea breath test，and relevant general information was collected to analyze Hp infection status. According to whether Hp infection occurred, they were divided into positive group (n=4 283) and negative group (n=2 509). The differences in general information, living habits, and dietary habits between the two groups of subjects were analyzed, and multivariate logistic regression analysis was conducted. Results Among the 6 792 permanent residents surveyed from January 2021 to December 2023, 4283 were positive for 13C-urea breath test, accounting for 63.05% of the total. There were statistically significant differences in age distribution, gender, BMI, tableware cleaning, personal hygiene products use, chopsticks use, and raw food and vegetable cleaning between the positive group and the negative group (P<0.05). The single factors of Hp infection were substituted into multivariate logistic regression analysis equation, and it was found that age ≥45 years old, male, BMI≥24, no use of detergents to clean utensils, sharing personal hygiene products, not using public chopsticks, having a habit of eating raw food, and not cleaning vegetables before eating were independent risk factors for Hp infection. Conclusion The positive rate of Hp infection in this area is relatively high, and the infection factors are related to age, gender, and some lifestyle and dietary habits.

Objective To analyze the trends in the disease burden of schistosomiasis in China from 1992 to 2021, and to project the disease burden of schistosomiasis in China from 2022 to 2030, so as to provide insights into the elimination of schistosomiasis in China. Methods The prevalence, age-standardized prevalence, disability-adjusted life year (DALYs) rate and age-standardized DALYs rate of schistosomiasis, as well as the years lost due to disability (YLDs) rate and age-standardized YLDs rate of anemia attributable to Schistosoma infections in China, the world and different socio-demographic index (SDI) regions were captured from the Global Burden of Disease Study 2021 (GBD 2021) data resources, and the trends in the disease burden due to schistosomiasis were evaluated with estimated annual percentage change (EAPC) and its 95% confidence interval (CI). In addition, the age, period and cohort effects on the prevalence of schistosomiasis were examined in China using an age-period-cohort (APC) model, and the disease burden of schistosomiasis was predicted in China from 2022 to 2030 using a Bayesian age-period-cohort (BAPC) model. Results The age-standardized prevalence and DALYs rate of schistosomiasis, and the age-standardized YLDs rate of anemia attributable to Schistosoma infections were 761.32/10⁵, 5.55/10⁵ and 0.38/10⁵ in China in 2021. These rates were all lower than the global levels (1 914.30/10⁵, 21.90/10⁵ and 3.36/10⁵, respectively), as well as those in the medium SDI regions (1 413.61/10⁵, 12.10/10⁵ and 1.93/10⁵, respectively), low-medium SDI regions (2 461.03/10⁵, 26.81/10⁵ and 4.48/10⁵, respectively), and low SDI regions (5 832.77/10⁵, 94.48/10⁵ and 10.65/10⁵, respectively), but higher than those in the high SDI regions (59.47/10⁵, 0.49/10⁵ and 0.05/10⁵, respectively) and high-medium SDI regions (123.11/10⁵, 1.20/10⁵ and 0.12/10⁵, respectively). The prevalence and DALYs rate of schistosomiasis were higher among men (820.79/10⁵ and 5.86/10⁵, respectively) than among women (697.96/10⁵ and 5.23/10⁵, respectively) in China in 2021, while the YLDs rate of anemia attributable to Schistosoma infections was higher among women (0.66/10⁵) than among men (0.12/10⁵). The prevalence of schistosomiasis peaked at ages of 30 to 34 years among both men and women, while the DALYs rate of schistosomiasis peaked among men at ages of 15 to 19 years and among women at ages of 20 to 24 years. The age-standardized prevalence of schistosomiasis showed a moderate decline in China from 1992 to 2021 relative to different SDI regions [EAPC = -1.51%, 95% CI: (-1.65%, -1.38%)], while the age-standardized DALYs rate [EAPC = -3.61%, 95% CI: (-3.90%, -3.33%)] and age-standardized YLDs rate of anemia attributable to Schistosoma infections [EAPC = -4.16%, 95% CI: (-4.38%, -3.94%)] appeared the fastest decline in China from1992 to 2021 relative to different SDI regions. APC modeling showed age, period, and cohort effects on the trends in the prevalence of schistosomiasis in China from 1992 to 2021, and the prevalence of schistosomiasis appeared a rise followed by decline with age, and reduced with period and cohort. BAPC modeling revealed that the age-standardized prevalence and age-standardized DALYs rate of schistosomiasis, and age-standardized YLDs rate of anemia attributable to Schistosoma infections all appeared a tendency towards a decline in China from 2022 to 2030, which reduced to 722.72/10⁵ [95% CI: (538.74/10⁵, 906.68/10⁵)], 5.19/10⁵ [95% CI: (3.54/10⁵, 6.84/10⁵)] and 0.30/10⁵ [95% CI: (0.21/10⁵, 0.39/10⁵)] in 2030, respectively. Conclusions The disease burden of schistosomiasis appeared a tendency towards a decline in China from 1992 to 2021, and is projected to appear a tendency towards a decline from 2022 to 2030. There are age, period and cohort effects on the prevalence of schistosomiasis in China. Precision schistosomiasis control is required with adaptations to current prevalence and elimination needs.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.