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Abstract Background Endocrine function in patients with type 2 diabetes (T2DM) typically differs from those with normal glucose tolerance (NGT). However, few epidemiologic studies have explored how these differences impact the association between exposure to polychlorinated biphenyls (PCBs) and vitamin D levels. Methods This study included 1,705 subjects aged 18–79 years from the Henan Rural Cohort [887 NGT and 818 T2DM]. Linear regression was applied to evaluate the associations between PCB exposure and vitamin D levels. Quantile g-computation regression (QG) and Bayesian kernel machine regression (BKMR) were applied to evaluate the impact of PCB mixtures on vitamin D levels. Interaction effects of ΣPCBs with HOMA2-%β and HOMA2-IR on vitamin D levels were assessed. Results Plasma ΣPCBs was positively associated with 25(OH)D2 in the NGT group (β = 0.060, 95% CI: 0.028, 0.092). Conversely, in T2DM group, ΣPCBs was negatively associated with 25(OH)D3 and 25(OH)D (β = -0.049, 95% CI: -0.072, -0.026; β = -0.043, 95% CI: -0.063, -0.023). Similarly, both QG and BKMR analysis revealed a negative association between PCB mixture exposure and vitamin D levels in the T2DM group, contrary to the results observed in the NGT groups. Furthermore, the negative association of ΣPCBs with 25(OH)D2 and 25(OH)D disappeared or changed to a positive association with the increase of HOMA2-%β levels. Conclusions These findings suggest that decreased β cell function may exacerbate the negative effects of PCB exposure on vitamin D levels. Recognizing T2DM patients’ sensitivity to PCBs is vital for protecting chronic disease health.

Background and aims: There is no evidence on the longitudinal and causal associations between multiple pesticides and the incidence of type 2 diabetes mellitus (T2DM) in the Chinese rural population, and whether physical activity (PA) modified these associations remains unclear. Here, we aimed to investigate the longitudinal and causal associations between pesticides mixture and T2DM, and determine whether PA modified these associations. Methods: A total of 925 subjects with normal glucose and 925 subjects with impaired fasting glucose (IFG) were enrolled in this case-cohort study. A total of 51 targeted pesticides were quantified at baseline. Logistic regression, quantile g-computation, and Bayesian kernel machine regression (BKMR) were used to assess the individual and combined effects of pesticides on IFG and T2DM. Mendelian randomization (MR) analysis was employed to obtain the causal association between pesticides and T2DM. Results: After 3-year follow-up, one-unit increment in ln-isofenphos, ln-malathion, and ln-deltamethrin were associated with an increase conversion of IFG to T2DM (FDR-P

Abstract Epoxides, as a prominent small ring O-heterocyclic and the privileged pharmacophores for medicinal chemistry, have recently represented an ideal substrate for the development of single-atom replacements. The previous O-to-C replacement strategy for epoxides to date typically requires high temperatures to achieve low yields and lacks substrate range and functional group tolerance, so achieving this oxygen-carbon exchange remains a formidable challenge. Here, we report a silver-catalyzed direct conversion of epoxides into trifluoromethylcyclopropanes in a single step using trifluoromethyl N-triftosylhydrazones as carbene precursors, thereby achieving oxygen-carbon exchange via a tandem deoxygenation/[2 + 1] cycloaddition. The reaction shows broad tolerance of functional groups, allowing routine cheletropic olefin synthesis in a strategy for the net oxygen-carbon exchange reaction. The utility of this method is further showcased with the late-stage diversification of epoxides derived from bioactive natural products and drugs. Mechanistic experiments and DFT calculations elucidate the reaction mechanism and the origin of the chemo- and stereoselectivity.

Objectives: This study aimed to delineate the ability of a plasmid, pS130–4, which harboured both hypervirulence and multidrug resistance genes, to disseminate within Klebsiella pneumoniae, as well as its potential formation mechanism. Methods: We employed whole-genome sequencing to decipher the genetic architecture of pS130–4. Its capability to conjugate and transfer was assessed through a series of experiments, including plasmid stability, competitive growth, and growth curve analysis. Its expression stability was further evaluated using drug sensitivity, larval survival, and biofilm formation tests. Results: pS130–4 contained four intact modules typical of self-transmissible plasmids. BLAST analysis revealed a sequence identity exceeding 90% with other plasmids from a variety of hosts, suggesting its broad prevalence. Our findings indicated the plasmid's formation resulted from IS26-mediated recombination, leading us to propose a model detailing the creation of this conjugative fusion plasmid housing both blaKPC-2 and hypervirulence genes. Our conjugation experiments established that pS130–4, when present in the clinical strain S130, was self-transmissible with an estimated efficiency between 10−5 and 10−4. Remarkably, pS130–4 showcased a 90% retention rate and did not impede the growth of host bacteria. Galleria mellonella larval infection assay demonstrated that S130 had pronounced toxicity when juxtaposed with high-virulence control strain NTUH-K2044 and low-toxicity control strain ATCC700603. Furthermore, pS130–4′s virulence remained intact postconjugation. Conclusion: A fusion plasmid, encompassing both hypervirulence and multidrug resistance genes, was viable within K. pneumoniae ST11-KL64 and incurred minimal fitness costs. These insights underscored the criticality of rigorous monitoring to pre-empt the escalation and distribution of this formidable super-plasmid.

Background: Plasma polybrominated diphenyl ethers (PBDE) were used as flame retardants widely, however, epidemiological evidence for the association between PBDEs and type 2 diabetes mellitus (T2DM) is inconsistent. Moreover, the combined effects of PBDEs and blood lipid indicators on impaired fasting glucose (IFG) and T2DM remains largely unknown in rural areas lacking good waste recycling infrastructure. Methods: In this study, a total of 2607 subjects aged 18–79 years were included from the Henan Rural Cohort. Generalized linear and logistic regression models were applied to evaluate the associations of various PBDE pollutants on IFG and T2DM. Quantile g-computation regression and PBDE pollution score created by the adaptive elastic net were applied to evaluate the impact of PBDEs mixtures on IFG and T2DM. Interaction effects of individual PBDE pollutants and blood lipid indicators on IFG and T2DM were assessed by using Interaction plots. Results: The geometric mean concentrations (detection rates) were 0.09 ng/mL (100.0%), 0.12 ng/mL (97.8%), 0.22 ng/mL (94.7%), 0.16 ng/mL (99.2%) and 0.28 ng/mL (100.0%) for PBDE-28, PBDE-47, PBDE-99, and PBDE-153 respectively. However, PBDE-28, PBDE-99, PBDE-100, and ΣPBDEs were positively associated with IFG (odds ratios (ORs) (95% confidence intervals (CIs)): 1.14 (1.06, 1.23), 1.16 (1.04, 1.29), 1.25 (1.14, 1.37), and 1.27 (1.08, 1.50)). Similarly, PBDE-28, PBDE-47, PBDE-99, PBDE-100, and ΣPBDEs were positively associated with T2DM (ORs (95% CIs): 1.30 (1.10, 1.54), 1.13 (1.06, 1.22), 1.27 (1.13, 1.43), 1.27 (1.15, 1.40), and 1.30 (1.10, 1.54)). Moreover, five PBDE mixtures or jointly as PBDE pollution score, were significantly associated with an increased risk of T2DM (P

This study aimed to explore the epidemic, clinical characteristics, and molecular and virulence attributes of Klebsiella pneumoniae serotype K54 (K54-Kp). A retrospective study was conducted on 328 strains of Klebsiella pneumoniae screened in a Chinese hospital from January 2016 to December 2019. The virulence genes and antibiotic resistance genes (ARGs) were detected by PCR, and a drug sensitivity test was adopted to detect drug resistance. Multilocus sequence typing (MLST) and PFGE were performed to determine the clonal correlation between isolates. Biofilm formation assay, serum complement-mediated killing, and Galleria mellonella infection were used to characterize the virulence potential. Our results showed that thirty strains of K54-Kp were screened from 328 strains of bacteria, with an annual detection rate of 2.29%. K54-Kp had a high resistance rate to antibiotics commonly used in the clinic, and patients with hepatobiliary diseases were prone to K54-Kp infection. MLST typing showed 10 sequence typing, mainly ST29 (11/30), which concentrated in the B2 cluster. K54-Kp primarily carried virulence genes of aerobactin, silS, allS, wcaG, wabG, and mrkD, among which the terW gene was closely related to ST29 (p

Background: Although it has been reported that herbicides exposure is related to adverse outcomes, available evidence on the associations of quantitatively measured herbicides with type 2 diabetes mellitus (T2DM) and prediabetes is still scant. Furthermore, the effects of herbicides mixtures on T2DM and prediabetes remain unclear among the Chinese rural population. Aims: To assess the associations of plasma herbicides with T2DM and prediabetes among the Chinese rural population. Methods: A total of 2626 participants were enrolled from the Henan Rural Cohort Study. Plasma herbicides were measured with gas chromatography coupled to triple quadrupole tandem mass spectrometry. Generalized linear regression analysis was employed to assess the associations of a single herbicide with T2DM, prediabetes, as well as indicators of glucose metabolism. In addition, the quantile g-computation and environmental risk score (ERS) structured by adaptive elastic net (AENET), and Bayesian kernel machine regression (BKMR) were used to estimate the effects of herbicides mixtures on T2DM and prediabetes. Results: After adjusting for covariates, positive associations of atrazine, ametryn, and oxadiazon with the increased odds of T2DM were obtained. As for prediabetes, each 1-fold increase in ln-transformed oxadiazon was related to 8.4% (95% confidence interval (CI): 1.033, 1.138) higher odds of prediabetes. In addition, several herbicides were significantly related to fasting plasma glucose, fasting insulin, and HOMA2-IR (false discovery rates adjusted P value < 0.05). Furthermore, the quantile g-computation analysis showed that one quartile increase in multiple herbicides was associated with T2DM (OR (odds ratio): 1.099, 95%CI: 1.043, 1.158), and oxadiazon was assigned the largest positive weight, followed by atrazine. In addition, the ERS calculated by the selected herbicides from AENET were found to be associated with T2DM and prediabetes, and the corresponding ORs and 95%CIs were 1.133 (1.108, 1.159) and 1.065 (1.016, 1.116), respectively. The BKMR analysis indicated a positive association between mixtures of herbicides exposure and the risk of T2DM. Conclusions: Exposure to mixtures of herbicides was associated with an increased risk of T2DM among Chinese rural population, indicating that the impact of herbicides exposure on diabetes should be paid attention to and measures should be taken to avoid herbicides mixtures exposure.

Aims: To evaluate the associations between residential greenness and glucocorticoid levels and whether air pollutants and sex modify the relationship between greenness and glucocorticoid level in Chinese rural adults. Methods: We collected cross-sectional survey data from 6055 participants from the Henan Rural cohort. The three-year average residential greenness for participants was assessed using normalized difference vegetation index (NDVI) values from a satellite platform. Liquid chromatography-tandem mass spectrometry was employed to quantify the concentrations of glucocorticoids, which were measured by morning blood draw after at least 8 hr of fasting. A random forest model was employed to obtain the average concentrations of PM1, PM2.5, and PM10. A general linear regression model was performed to estimate the associations of NDVI500−m values with cortisol, 11-deoxycortisol, and cortisone. Furthermore, interaction plots were used to present the interaction effects of particulate matter, sex, and green space on glucocorticoid levels. Results: After adjusting for multiple variables, an elevated average NDVI500−m value in the total population was associated with a decrease in cortisol levels (β = −0.063, 95 % confidence interval (CI): − 0.118, − 0.008), and 11-deoxycortisol levels (β = −0.118, 95 % CI: −0.190, −0.047), as well as an increase in cortisone levels (β = 0.130, 95 % CI: 0.079, 0.181). By adding the interaction terms of air pollutants and residential greenness into the regression model, interaction effects between air pollutants and residential greenness were found (cortisol, PM2.5: P interaction=:0.018; PM10: P interaction=0.016; 11-deoxycortisol, all pollutants: P interaction< 0.001), suggesting that the protective effect of residential greenness on serum glucocorticoids disappeared accompanying with increased concentrations of particulate matter. Moreover, trends towards modification in the association between green space and glucocorticoid levels were also evident by sex, but these did not reach statistical significance (for all glucocorticoids: P interaction> 0.05). Conclusion: Long-term exposure to green space was negatively correlated with cortisol and 11-deoxycortisol levels, and positively correlated with cortisone levels. There may be sex differences in these associations. Moreover, the protective effect of residential greenness on serum glucocorticoids was altered by high levels of particulate matter.

This study proposes a rapid and non-destructive technique for determining the age of Potentilla griffithii individuals in the field by observing the sequence of leaf scars. Based on two- to three-year-old P. griffithii seedlings, planted in a common garden in the western Sichuan Plateau, China, the study found that the rates of basal leaf production were consistent, with leaves growing from March to April and falling off from October to December, leaving behind basal leaf scars. Thus, the age of individuals in situ could be determined by counting the leaf scars. Through this method, we determined the age structure and growth strategy of P. griffithii populations in two typical habitats in the western Sichuan Plateau. In open land habitats, the age structure of P. griffithii populations was relatively younger compared to understory habitats. In open land, P. griffithii tends to allocate more photosynthate terminal organs (leaves and fine roots) to absorbing more resources, as well as to its reproductive organs (flower stems and aggregate fruits), to expand the population. The P. griffithii population in the understory habitat is in its middle-age stage and concentrates more photosynthate in the coarse root part (e.g., the high coarse root mass fraction (FRMF)) to support the plant. Additionally, we found a significant correlation between P. griffithii plant age and various traits in open land habitats. Therefore, we conclude that plant age can be used as a good predictor of plant growth condition in open land. These results allow for predicting ecological processes, based on the ages and traits of P. griffithii plants, providing a theoretical basis to support the large-scale breeding of P. griffithii.

ObjectiveCollege students are one of the most vulnerable populations to the COVID-19 pandemic's mental health effects. During the coronavirus disease 2019 (COVID-19) outbreak, we wanted to see how common depressive symptoms were among college students and what factors contributed to that.MethodsBetween 21 and 27 May 2021, 140,259 college students from three cities in Henan Province, China, were involved. The Patient Health Questionnaire-9 was used to determine depressive symptoms (PHQ-9). Multiple logistic regression analysis was used to calculate odds ratios (ORs) and 95% CIs for potential depressive symptom factors.ResultsMild depressive symptoms and above are present in 21.12% of college students. Women had a higher prevalence of mild depressive symptoms than men (61.38 vs. 59.75%), and depressive symptoms were most prevalent among rural students and least prevalent among city students (21.44 vs. 20.29%). Participants with depressive symptoms are also more likely to have a poor-behavioral status. From none-to-severe depressive symptoms, 78.88, 15.78, 2.80, 1.67, and 0.88% had them. Gender, residential location, and behavioral status were found to be associated with depressive symptoms after adjusting for potential confounders.ConclusionThis cross-sectional study identified the factors that influence the prevalence of depression in college students. It found that the government should pay more attention to mental health issues affecting college students in combating the COVID-19 epidemic normalization.

BackgroundPesticides are widely used in agricultural production to control insect pests and regulate plant growth in China, which may result in the presence of some pesticide residues in the vegetables. However, few studies of monitoring pesticides have been conducted in Henan Province. The aim of this study was to evaluate the level of pesticide residues in commonly consumed vegetables in the regions of Henan Province.MethodsIn this study, we collected 5,576 samples of 15 different vegetables in 17 areas from Henan Province during 2020. Eight kinds of pesticides were analyzed by gas chromatography-mass spectrometry (GC-MS), including procymidone, lambda-cyhalothrin, cypermethrin, pendimethalin, isocarbophos, isazophos, fenthion and deltamethrin. The chi-square test was used to compare the detection rates of pesticide residues in different regions.ResultsOf all the pesticides above, procymidone, lambda-cyhalothrin, cypermethrin, pendimethalin and isocarbophos were detected in vegetables, the detection rates were 27.0%, 16.2%, 11.4%, 3.5%, and 1.9%, respectively. However, isazophos, fenthion, and deltamethrin were not detected. In addition, procymidone, lambda-cyhalothrin, and cypermethrin were detected in urban areas, while pendimethalin was detected in rural areas. The detection rates of cypermethrin and pendimethalin in rural were 19.8% and 5.4%, respectively, which in urban were at relatively lower levels (13.7% and 1.9%, respectively) (P < 0.05). Compared the differences of pesticide detection rates among five areas of Henan province, we found that there were statistical differences in the detection rates of procymidone, cypermethrin and lambda-cyhalothrin in different regions (all P < 0.05).ConclusionThe results have revealed that the pesticide residues are present. Higher detection rates and more types of pesticides were found in rural areas than urban areas. In addition, there were higher detection rates in Eastern Henan. The findings provided valuable information on the current pesticide residues status, which can be a reference of pesticide supervision and management.

To explore the independent and combined effects of ESRα methylation and progesterone on impaired fasting glucose (IFG) and type 2 diabetes mellitus (T2DM), a case-control study including 901 subjects was conducted. Generalized linear models were performed to assess the independent and combined effects of ESRα methylation and progesterone on IFG or T2DM. Methylation level of cytosine-phosphoguanine (CpG) 1 in the estrogen receptor α (ESRα) gene was positively related to IFG in both men (odds ratio (OR) (95% confidence interval (CI)): 1.77 (1.05, 3.00)) and postmenopausal women (OR (95% CI): 1.82 (1.09, 3.04)), whereas the association between CpG 1 and T2DM was not significant. Positive associations of progesterone with IFG and T2DM were observed in both men (OR (95% CI): 2.03 (1.18, 3.49) and 3.00 (1.63, 5.52)) and postmenopausal women (OR (95% CI): 2.13 (1.27, 3.56) and 3.30 (1.85, 5.90)). Participants with high CpG 1 methylation plus high progesterone had an increased risk of IFG and T2DM, both in men and postmenopausal women. ESRα methylation and progesterone were positively associated with IFG, and the positive association between progesterone and T2DM was also found. Importantly, we firstly found the combined effects of ESRα methylation and progesterone on IFG and T2DM.

BackgroundThe reliability and validity of recalled body shape were unknown in China. This study was conducted to examine the reliability and validity of recalled body shape as well as the responsiveness of obesity classification by recalled body shape among the Chinese rural population.MethodsA total of 166 people from the Henan rural cohort were enrolled. The Spearman's correlation coefficient (SCC), intraclass correlation coefficient (ICC), and Cronbach's α were calculated to assess the reliability and validity of recalled body shape. Additionally, the receiver operator characteristic curve (ROC) was performed to assess the responsiveness.ResultsThe SCC between the twice recalled body shape ranged from 0.383 to 0.578, and the ICC ranged from 0.357 to 0.615. Besides, the Cronbach's α of the recalled body shape questionnaire was 0.845. At the age of 20–70, the SCC between recalled body shape and actual body mass index (BMI) and waist circumference (WC) ranged from 0.563 to 0.699 and 0.409 to 0.661, respectively. Furthermore, above the age of 20, the area under the curve (AUC) of classifying general obesity and abdominal obesity by recalled body shape ranged from 0.833 to 0.960 and 0.686 to 0.870, respectively.ConclusionThe results indicated that recalled body shape had moderate reliability, validity, and discriminative degree for earlier obesity among the Chinese rural population.

Background and Aims. The effects of cortisol on cardiovascular diseases (CVD) and CVD risk are unknown, especially in patients with type 2 diabetes mellitus (T2DM). Furthermore, it is unclear whether 25 (OH)D can alter the associations of cortisol with CVD and CVD risk factors. Thus, the present study was to investigate the associations of serum cortisol with CVD and CVD risk factors and whether 25 (OH)D altered these associations among patients with T2DM. Materials and methods. A total of 762 patients diagnosed with T2DM were recruited. The levels of serum cortisol and 25 (OH)D were measured with a liquid chromatography-tandem mass spectrometry. Logistic regression and linear regression were used to assess the association of cortisol with CVD and multiple cardiovascular risk factors. Modification analyses were performed to identify whether 25 (OH)D altered the above associations. Results. A 1 SD increase in cortisol was associated with a higher prevalence of stroke (odds ratio (OR): 1.25, 95% confidence interval (CI): 1.05, 1.50). Elevated cortisol was associated with related cardiovascular risk factors, including deceased ß cell function, high-density lipoprotein-cholesterol (HDL-C), and fasting insulin, as well as increased triglycerides (TG), low-density lipoprotein-cholesterol (LDL-C), fasting plasma glucose (FPG), and glycated hemoglobin (HbA1c). In addition, modification analyses suggested that the associations of cortisol with ß cell function, fasting insulin, FPG, and HbA1c were modified by 25 (OH)D. Conclusions. Serum cortisol was associated with the prevalence of stroke and cardiovascular risk factors, and the associations of cortisol with cardiovascular risk factors were moderated by 25 (OH)D, suggesting that T2DM patients with exposure to lower 25 (OH)D levels and higher cortisol levels were more susceptible to have higher cardiovascular risk factors.

Diamide insecticides are a class of insecticides with high efficiency, a broad spectrum, and environmental and ecological safety. However, their effect on the environment cannot be ignored, especially the chronic environmental effects of sublethal doses. In this study, we evaluated the influence of cyantraniliprole on zebrafish and provided data for evaluating the risk of cyantraniliprole in water. An acute toxicity test was used to obtain LC50, while 1/10 LC50 was selected to study the toxicity of the sublethal dose of cyantraniliprole on the transcription and metabolism of zebrafish liver. Our results showed that after exposure to a sublethal dose of cyantraniliprole for 30 days, the expression of various functional genes (elovl6, cpt1ab, eci1, fabp6, etc.) was abnormal and the content of various metabolites (Taurine, 1-Acyl-sn-glycero-3-phosphocholine, phosphatidylserine, betaine, sarcosine, etc.) was altered. In addition, transcriptional and metabolic correlation analysis revealed that sublethal doses of cyanobacteria could affect the fatty acid metabolism-related pathways of zebrafish liver (fatty acid elongation, metabolism, and degradation), as well as the PPAR pathway related to fat and the ABC pathway related to drug metabolism and transport. In conclusion, sublethal doses of cyantraniliprole caused abnormal liver metabolism in zebrafish by affecting fatty acid metabolism, up-regulating the PPAR pathway and down-regulating related genes and metabolites in the ABC pathway, which eventually led to liver damage.

A high-quality leaf-area index (LAI) is important for land surface process modeling and vegetation growth monitoring. Although multiple satellite LAI products have been generated, they usually show spatio-temporal discontinuities and are sometimes inconsistent with vegetation growth patterns. A deep-learning model was proposed to retrieve time-series LAIs from multiple satellite data in this paper. The fusion of three global LAI products (i.e., VIIRS, GLASS, and MODIS LAI) was first carried out through a double logistic function (DLF). Then, the DLF LAI, together with MODIS reflectance (MOD09A1) data, served as the training samples of the deep-learning long short-term memory (LSTM) model for the sequential LAI estimations. In addition, the LSTM models trained by a single LAI product were considered as indirect references for the further evaluation of our proposed approach. The validation results showed that our proposed LSTMfusion LAI provided the best performance (R2 = 0.83, RMSE = 0.82) when compared to LSTMGLASS (R2 = 0.79, RMSE = 0.93), LSTMMODIS (R2 = 0.78, RMSE = 1.25), LSTMVIIRS (R2 = 0.70, RMSE = 0.94), GLASS (R2 = 0.68, RMSE = 1.05), MODIS (R2 = 0.26, RMSE = 1.75), VIIRS (R2 = 0.44, RMSE = 1.37) and DLF LAI (R2 = 0.67, RMSE = 0.98). A temporal comparison among LSTMfusion and three LAI products demonstrated that the LSTMfusion model efficiently generated a time-series LAI that was smoother and more continuous than the VIIRS and MODIS LAIs. At the crop peak growth stage, the LSTMfusion LAI values were closer to the reference maps than the GLASS LAI. Furthermore, our proposed method was proved to be effective and robust in maintaining the spatio-temporal continuity of the LAI when noisy reflectance data were used as the LSTM input. These findings highlighted that the DLF method helped to enhance the quality of the original satellite products, and the LSTM model trained by the coupled satellite products can provide reliable and robust estimations of the time-series LAI.

Background: Population-based studies on the associations of long-term exposure to particulate matter (PM) with androgen and progesterone are still scant. Residential greenness is benefits health by promoting physical activity, reducing air pollution, and improving mental health, but it remains unclear whether it is related to androgen and progesterone levels among humans. Aims: This study aimed to explore the individual and interactive effects of PM and residential greenness on serum testosterone and progesterone levels among rural Chinese adults. Methods: A total of 6017 subjects were recruited from the baseline of the Henan Rural Cohort Study in 2016. Serum testosterone and progesterone were measured with liquid chromatography-tandem mass spectrometry. Particulate matters (PM) (PM1, PM2.5, and PM10) were assessed by machine learning algorithms. Residential greenness was assessed using the normalized difference vegetation index (NDVI) within 500-m, 1000-m, and 3000-m buffers around participants’ residences. The effects of air pollutants and residential greenness and their interaction on serum testosterone and progesterone levels were assessed using linear mixed-effects models with township as a random intercept. Results: After adjusting for potential confounding factors, a 1 μg/m3 increase in PM2.5 or PM10 was associated with a 0.037 or 0.030 ng/ml increase in serum testosterone, respectively, in females and with a 0.111 or 0.182 ng/ml decrease in serum progesterone, respectively, in males. A 1 μg/m3 increase in PM1, PM2.5 or PM10 was associated with a 0.222, 0.306, or 0.295 ng/ml decrease in serum progesterone, respectively, among females. Moreover, a 0.1-unit increase in NDVI was associated with a 0.310 ng/ml increase in serum testosterone and a 0.170 ng/ml increased in serum progesterone in males, as well as with a 0.143 ng/ml increase in serum progesterone in females. Interaction effects of PM and residential greenness on serum testosterone and progesterone levels were observed, indicating that the effects of residential greenness on serum testosterone and progesterone were modified by high levels of PM. In addition, physical activity significantly mediated 2.92% of the estimated association between greenness and testosterone levels. Conclusions: Our study suggested that long-term exposure to PM was positively associated with serum testosterone in males but negatively associated with progesterone levels in both genderssin. In addition, positive associations of residential greenness with serum testosterone and progesterone levels were observed, but they were modified by high levels of PM. Furthermore, the estimated effects of residential greenness on testosterone levels were partly mediated by physical activity.

Nucleobases, nucleosides, nucleotides and amino acids, as crucial nutrient compositions, play essential roles in determining the flavor, function and quality of Chrysanthemi Flos. The quality of Chrysanthemi Flos from different geographical origins is uneven, but there have been no reports about the screening of their quality markers based on nutritional ingredients. Here, we developed a comprehensive strategy integrating ultra performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (UPLC–MS/MS) and multivariate statistical analysis to explore quality markers of Chrysanthemi Flos from different geographical origins and conduct quality evaluation and discrimination of them. Firstly, a fast, sensitive, and reliable UPLC–MS/MS method was established for simultaneous quantification 28 nucleobases, nucleosides, nucleotides and amino acids of Chrysanthemi Flos from nine different regions in China. The results demonstrated that Chrysanthemi Flos from nine different cultivation regions were rich in the above 28 nutritional contents and their contents were obvious different; however, correlation analysis showed that altitude was not the main factor for these differences, which required further investigation. Subsequently, eight crucial quality markers for nine different geographical origins of Chrysanthemi Flos, namely, 2′-deoxyadenosine, guanosine, adenosine 3′,5′-cyclic phosphate (cAMP), guanosine 3′,5′-cyclic monophosphate (cGMP), arginine, proline, glutamate and tryptophan, were screened for the first time using partial least squares discriminant analysis (PLS-DA) and the plot of variable importance for projection (VIP). Moreover, a hierarchical clustering analysis heat map was employed to intuitively clarify the distribution of eight quality markers in the nine different regions of Chrysanthemi Flos. Finally, based on the contents of selected eight quality markers, support vector machines (SVM) model was established to predict the geographical origins of Chrysanthemi Flos, which yielded excellent prediction performance with an average prediction accuracy of 100%. Taken together, the proposed strategy was suitable to discover the quality markers of Chrysanthemi Flos and could be used to discriminate its geographical origin.

Infection caused by carbapenem-resistant hypervirulent Klebsiella pneumoniae (CR-hvKP) has become a tricky health care threat in China and KPC-2 enzyme is a main factor mediating resistance to carbapenems of K. pneumoniae. Here, we report the characterization of the genetic environment of the blaKPC-2 gene in CR-hvKP clinical isolates from South China. Forty-five non-duplicated CR-hvKP isolates collected in Jiangxi Province from 2018 to 2019 were analyzed. Each of them were multidrug-resistant due to the presence not only of blaKPC-2 gene but also of other resistance determinants, including Metallo-β-lactamases (NDM-1), extended-spectrum β-lactamases (TEM-1, CTX-M-14, SHV-1), and plasmid-mediated quinolone resistance determinants (qnrS, aac(6′)-Ib-cr). After plasmid analyses of PCR-based replicon typing (PBRT), mapping PCR, amplicon sequencing, and whole-genome sequencing (WGS) were used to analyze the genetic environment of the blaKPC-2 gene. PCR analysis of pLVPK-like plasmids, Southern Blot, and mouse lethality assay were used to characterize the virulence phenotype of K. pneumoniae. Multilocus sequence typing (MLST) analysis showed ST11 CR-hvKP was the predominant clone. In conclusion, this is the first analysis of diverse genetic structures blaKPC-2 gene in CR-hvKP isolates from south China. Both the NTEKPC-I on the IncF plasmids and pLVPK-like virulence plasmids make contributions to the formation of CR-hvKP especially ST11 which need more attention.

Background: Although short-term exposure to particulate matter (PM) was associated with increased glucocorticoids (GCs) levels, available evidence on associations of long-term exposure to PM and GCs levels is still scant. Previous studies has showed that meat intake is associated with sex hormones levels, but it is unknown whether meat intake is associated with GCs levels. Furthermore, the role of meat intake in the associations between PM and GCs levels remains unclear. Aims: The aims of this study were to explore the associations of long-term exposure to PM and GCs levels among Chinese rural adults, and the role of meat intake in these associations. Materials and methods: A total of 6223 subjects were recruited from the Henan Rural Cohort Study. Serum GCs levels were measured with liquid chromatography-tandem mass spectrometry. The concentrations of PM (PM1 and PM2.5) for each subject were assessed with machine learning algorithms. The food frequency questionnaire (FFQ) was used to obtain each participant’ information on meat intake. The effects of PM and meat intake on GCs levels were assessed using generalized linear models. In addition, modification analyses were performed to identify the role of meat intake played in the associations of PM with serum GCs levels. Results: Per 1 μg/m3 increment in PM1 or PM2.5 concentration was associated with a 0.364 ng/ml (95% confidence interval (CI): 0.234, 0.494) or 0.227 ng/ml (95%CI: 0.110, 0.343) increase in serum cortisone, respectively. In addition, the moderation effects of total meat intake and red meat intake on the associations of long-term exposure to PM1 or PM2.5 with serum cortisone were observed (P

The main feature of grassland degradation is the change in the vegetation community structure. Hyperspectral-based grassland community identification is the basis and a prerequisite for large-area high-precision grassland degradation monitoring and management. To obtain the distribution pattern of grassland communities in Xilinhot, Inner Mongolia Autonomous Region, China, we propose a systematic classification method (SCM) for hyperspectral grassland community identification using China’s ZiYuan 1-02D (ZY1-02D) satellite. First, the sample label data were selected from the field-collected samples, vegetation map data, and function zoning data for the Nature Reserve. Second, the spatial features of the images were extracted using extended morphological profiles (EMPs) based on the reduced dimensionality of principal component analysis (PCA). Then, they were input into the random forest (RF) classifier to obtain the preclassification results for grassland communities. Finally, to reduce the influence of salt-and-pepper noise, the label similarity probability filter (LSPF) method was used for postclassification processing, and the RF was again used to obtain the final classification results. The results showed that, compared with the other seven (e.g., SVM, RF, 3D-CNN) methods, the SCM obtained the optimal classification results with an overall classification accuracy (OCA) of 94.56%. In addition, the mapping results of the SCM showed its ability to accurately identify various ground objects in large-scale grassland community scenes.

Biocontrol formulations prepared from biocontrol bacteria are increasingly applied in sustainable agriculture. Notably, inoculants prepared from Bacillus strains have been proven efficient and environmentally friendly alternatives to chemical bactericides. The bacterium Bacillus velezensis HAB-2 (formerly classified as B. amyloliquefaciens HAB-2) is used as a biological control agent in agricultural fields. In this study, we reported a high-quality genome sequence of HAB-2 using third-generation sequencing technology (PacBio RS II). The 3.89 Mb genome encoded 3,820 predicted genes. Comparative analysis among the genome sequences of reference strains B. velezensis FZB42, B. amyloliquefaciens DSM7 and B. subtilis 168 with the HAB-2 genome revealed obvious differences in the variable part of the genomes, while the core genome shared by FZB42 and HAB-2 was similar (96.14%). However, there were differences in the prophage region among the four strains. The numbers of prophage regions and coding genes in HAB-2 and FZB42 were smaller than the other two strains. The HAB-2 genome showed superior ability to produce secondary metabolites and harbored 13 gene clusters involved in synthesis of antifungal and antibacterial acting secondary metabolites. Furthermore, there were two unique clusters: one cluster which encoded lanthipeptide was involved in mersacidin synthesis and another cluster which encoded ladderane was shown to direct an unknown compound. Multidomain enzymes, such as non-ribosomal peptide synthetase and polyketide synthase, control the biosynthesis of secondary metabolites and rely on 4′-phosphopantetheinyl transferases (PPTases). Key genes lpaH2 and a encoded PPTases in HAB-2 encoded 224 and 120 amino acids, respectively. The genomic features revealed that HAB-2 possesses immense potential to synthesize antimicrobial acting secondary metabolites by regulating and controlling gene clusters. The prophage regions and genes encoding PPTases may provide novel insight for the bacteriostatic mechanism of Bacillus in the biological control of plant diseases.

ObjectivesTo establish a rapid molecular diagnostics of hvKp using the peg-344 loop-mediated isothermal amplification technique (LAMP).MethodsIn all, 28 K. pneumoniae strains isolated from the blood of patients were used for the peg-344 LAMP. K. pneumoniae NTUH-K2044 and K. pneumoniae ATCC700603 were used as positive control and negative control, respectively. For comparison, all the results were detected in a polymerase chain reaction (PCR), which was considered the gold standard for the detection of the gene. Mouse lethality assay, and Serum killing assay were also used to determine the virulence phenotype of K. pneumoniae.ResultsWe determined the specificity and sensitivity of the primers for peg-344 detection in the LAMP reactions. This LAMP assay was able to specifically differentiate hvKp from classical K. pneumoniae (cKp) at 65°C, which was 100-fold more sensitive than a PCR assay for peg-344 detection. The virulence phenotype of K. pneumoniae detected by LAMP was as precise as by Mouse lethality assay and Serum killing assay.ConclusionThe LAMP assay is easy to perform and rapid. Therefore, it can be routinely applied to differentiate hvKp from cKp in the clinical laboratory.

Background: Obesity is an important risk factor for hypertension. Previous studies have explored the association between body fat percentage (BFP) and hypertension, but evidence on the consistency of the association remains uncertain and limited. The aim of this study was to explore the relationship between BFP and hypertension in a Chinese rural population.Methods: The present cross-sectional study including 38,913 eligible individuals was conducted in rural areas of Henan province. BFP was measured by bioelectrical impedance methods using Omron body fat and weight measurement device. Logistic regression models and restricted cubic spline regression models were performed to investigate the relationship between BFP and hypertension. Receiver operating characteristic (ROC) analyses were used to compare the discriminating power of adiposity indices.Results: The age-standard prevalence of hypertension was 23.74 and 17.87% in males and females, respectively. Compared with the first quartile of BFP, the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for hypertension in the highest BFP quartile were 3.30 (95% CI: 2.85, 3.83) in males and 2.66 (95% CI: 2.36, 2.99) in females, and the adjusted ORs increased along with increasing BFP levels. The areas under ROC and 95% CIs of BFP were 0.673 (0.665, 0.682) in males and 0.696 (0.689, 0.703) in females, respectively.Conclusions: BFP was significantly positively associated with the prevalence of hypertension in both males and females in the Chinese rural population. Controlling of body fat should be emphasized in rural areas of China.Clinical Trial Registration: Registration number: ChiCTR-OOC-15006699. http://www.chictr.org.cn/showproj.aspx?proj=11375

Cities are beginning to monitor atmospheric carbon dioxide (CO _2 ) to assess the efficacy of their climate policies. However, changes in anthropogenic CO _2 emissions must be separated from biospheric CO _2 fluxes which have a large seasonal cycle. Urban vegetation (e.g. lawns, trees along street and in parks, etc) in developed land covers is often omitted in regional biogenic CO _2 flux models. We set up a biosphere model to estimate the regional biogenic CO _2 fluxes in New York City (NYC) and assess the importance of vegetation within developed land covers. The model incorporates a high-resolution (30 m) land cover map which identifies the mixture of impervious surfaces and vegetation that is ubiquitous across developed land covers. We designed three model scenarios to evaluate the role of developed land covers in regional biogenic CO _2 fluxes by assuming (a) there is no vegetation versus scenarios where all remotely sensed vegetation in developed land covers is either (b) grassland or (c) deciduous forest. Despite relatively low tree canopy cover in NYC, the regional biogenic CO _2 fluxes are surprisingly large when vegetation within the developed land covers is included. Furthermore, the types of vegetation within the developed land covers are crucially important for estimating regional biogenic CO _2 fluxes, demonstrated by a doubling in estimates of total biogenic CO _2 flux when this vegetation is assumed to be grassland compared to forest. Using a Lagrangian atmospheric transport model, we find that the regional biogenic CO _2 uptake offsets up to 40% of atmospheric CO _2 enhancements attributed to anthropogenic emissions in summer afternoons and completely balances on-road traffic in one of the most congested cities in the United States. Accurate characterization of the vegetation and biogenic carbon fluxes in cities are essential to the development of effective atmospheric monitoring tools. Future measurements should focus on constraining CO _2 fluxes in urban grasslands (i.e. lawns).

Estimating the carbon (C), nitrogen (N), and phosphorus (P) contents of a large-span grassland transect is essential for evaluating ecosystem functioning and monitoring biogeochemical cycles. However, the field measurements are scattered, such that they cannot indicate the continuous gradient change in the grassland transect. Although remote sensing methods have been applied for the estimation of nutrient elements at the local scale in recent years, few studies have considered the effective estimation of C, N, and P contents over large-span grassland transects with complex environment including a variety of grassland types (i.e., meadow, typical grassland, and desert grassland). In this paper, an information enhancement algorithm (involving spectral enhancement, regional enhancement, and feature enhancement) is used to extract the weak information related to C, N, and P. First, the spectral simulation algorithm is used to enhance the spectral information of Sentinel-2 imagery. Then, the enhanced spectra and meteorological data are fused to express regional characteristics and the fractional differential (FD) algorithm is used to extract sensitive spectral features related to C, N, and P, in order to construct a partial least-squares regression (PLSR) model. Finally, the C, N, and P contents are estimated over a West–East grassland transect in Inner Mongolia, China. The results demonstrate that: (i) the contents of C, N, and P in large-span transects can be effectively estimated through use of the information enhancement method involving spectral enhancement, regional feature enhancement, and information enhancement, for which the estimation accuracies (R2) were 0.88, 0.78, and 0.85, respectively. Compared with the estimation results of raw Sentinel-2 imagery, the RMSE was reduced by 3.42 g/m2, 0.14 g/m2, and 13.73 mg/m2, respectively; and (ii) the continuous change trend and spatial distribution characteristics of C, N, and P contents in the west–east transect of the Inner Mongolia Plateau were obtained, which showed decreasing trends in C, N, and P contents from east to west and the characteristics of meadow > typical grassland > desert grassland. Thus, the information enhancement algorithm can help to improve estimates of C, N, and P contents when considering large-span grassland transects.

Objective. The aim of the study was to investigate the independent and combined effects of the cortisol-to-cortisone ratio (F/E) and 11-deoxycortisol on prediabetes and type 2 diabetes mellitus (T2DM) among different genders. Methods. A case-control study was performed including 2676 participants from the Henan Rural Cohort Study. Liquid chromatography-tandem mass spectrometry was used to assess serum cortisol, cortisone, and 11-deoxycortisol. Conditional logistic regression was performed to estimate the associations between hormones and outcomes. Results. After adjusting for multiple variables, the negative associations of F/E and 11-dexyocortisol with T2DM were observed in females (T3 vs. T1: OR=0.56, 95% CI: 0.39-0.80 for F/E; T3 vs. T1: OR=0.44, 95% CI: 0.27-0.73 for 11-dexyocortisol). However, only 11-dexyocortisol showed a negative association with prediabetes both in males and females. Compared with the combination of low F/E and 11-dexyocortisol, the combination of middle F/E and high 11-dexyocortisol was significantly associated with prediabetes (OR=0.29, 95% CI: 0.12-0.71) in males. Furthermore, the combination of high F/E and 11-dexyocortisol was associated with the lowest odds of prediabetes (OR=0.39, 95% CI: 0.21-0.73) and T2DM (OR=0.25, 95% CI: 0.12-0.52) in females. Conclusions. Serum F/E level was negatively associated with T2DM only in females whereas serum 11-deoxycortisol level was negatively associated with prediabetes in males and with prediabetes and T2DM in females. Additionally, their combination has a synergistic effect on T2DM.

Numerous studies have investigated the associations between serum vitamin D or testosterone and diabetes; however, inconsistencies are observed. Whether there is an interaction between vitamin D and testosterone and whether the lipid profile (total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C)) mediates the association between vitamin D and diabetes is unclear. To investigate the effect of vitamin D and testosterone on impaired fasting glucose (IFG) or type 2 diabetes mellitus (T2DM), 2659 participants from the Henan Rural Cohort were included in the case-control study. Generalized linear models were utilized to estimate associations of vitamin D with IFG or T2DM and interactive effects of vitamin D and testosterone on IFG or T2DM. Principal component analysis (PCA) and mediation analysis were used to estimate whether the lipid profile mediated the association of vitamin D with IFG or T2DM. Serum 25(OH)D3, 25(OH)D2, and total 25(OH)D levels were negatively correlated with IFG (odds ratios (ORs) (95% confidence intervals (CIs)): 0.99 (0.97, 1.00), 0.85 (0.82, 0.88), and 0.97 (0.96, 0.98), respectively). Similarity results for associations between serum 25(OH)D2 and total 25(OH)D with T2DM (ORs (95%CIs): 0.84 (0.81, 0.88) and 0.97 (0.96, 0.99)) were observed, whereas serum 25(OH)D3 was negatively correlated to T2DM only in the quartile 2 (Q2) and Q3 groups (both p < 0.05). The lipid profile, mainly TC and TG, partly mediated the relationship between 25(OH)D2 or total 25(OH)D and IFG or T2DM and the proportion explained was from 2.74 to 17.46%. Furthermore, interactive effects of serum 25(OH)D2, total 25(OH)D, and testosterone on T2DM were observed in females (both p for interactive 2 was higher than 10.04 ng/mL or total 25(OH)D was higher than 40.04 ng/mL. Therefore, ensuring adequate vitamin D levels could reduce the prevalence of IFG and T2DM, especially in females with high levels of testosterone.

Leaf area index (LAI) is an essential vegetation parameter that represents the light energy utilization and vegetation canopy structure. As the only in-operation hyperspectral satellite launched by China, GF-5 is potentially useful for accurate LAI estimation. However, there is no research focus on evaluating GF-5 data for LAI estimation. Hyperspectral remote sensing data contains abundant information about the reflective characteristics of vegetation canopies, but these abound data also easily result in a dimensionality curse. Therefore, feature selection (FS) is necessary to reduce data redundancy to achieve more reliable estimations. Currently, machine learning (ML) algorithms have been widely used for FS. Moreover, the same ML algorithm is usually conducted for both FS and regression in LAI estimation. However, no evidence suggests that this is the optimal solution. Therefore, this study focuses on evaluating the capacity of GF-5 spectral reflectance for estimating LAI and the performances of different combination of FS and ML algorithms. Firstly, the PROSAIL model, which coupled leaf optical properties model PROSPECT and the scattering by arbitrarily inclined leaves (SAIL) model, was used to generate simulated GF-5 reflectance data under different vegetation and soil conditions, and then three FS methods, including random forest (RF), K-means clustering (K-means) and mean impact value (MIV), and three ML algorithms, including random forest regression (RFR), back propagation neural network (BPNN) and K-nearest neighbor (KNN) were used to develop nine LAI estimation models. The FS process was conducted twice using different strategies: Firstly, three FS methods were conducted to search the lowest dimension number, which maintained the estimation accuracy of all bands. Then, the sequential backward selection (SBS) method was used to eliminate the bands having minimal impact on LAI estimation accuracy. Finally, three best estimation models were selected and evaluated using reference LAI. The results showed that although the RF_RFR model (RF used for feature selection and RFR used for regression) achieved reliable LAI estimates (coefficient of determination (R2) = 0.828, root mean square error (RMSE) = 0.839), the poor performance (R2 = 0.763, RMSE = 0.987) of the MIV_BPNN model (MIV used for feature selection and BPNN used for regression) suggested using feature selection and regression conducted by the same ML algorithm could not always ensure an optimal estimation. Moreover, RF selection preserved the most informative bands for LAI estimation so that each ML regression method could achieve satisfactory estimation results. Finally, the results indicated that the RF_KNN model (RF used as feature selection and KNN used for regression) with seven GF-5 spectral band reflectance achieved the better estimation results than others when validated by simulated data (R2 = 0.834, RMSE = 0.824) and actual reference LAI (R2 = 0.659, RMSE = 0.697).

Rehmannia glutinosa Libosch (RG), is officially listed in the Chinese Pharmacopoeia and is widely used in China. The leaves of RG (LR) is an important vegetative organ of the plant. At present, the total glycosides of RG (TLR) were extracted from RG, and developed a national second class of new drugs to the Dihuangye total glycoside capsule (DTG). Additionally, DTG has the effect of nourishing yin and tonifying kidney, promoting blood circulation and blood cooling, and applicable to chronic glomerulonephritis mild to Qi and Yin Deficiency. Moreover, diabetic nephropathy (DN) rats model was induced by intraperitoneal injection of a small dose of streptozotocin (45 mg/kg) and high-fat diet and plus 5% glucose drinking water. Over 15 days, after oral administration TLR and DTG in DN rats, samples from serum, urine and kidney were collected for biochemical indicators measurements, pathological analysis, western blotting and metabolomics. Therefore, the analytical results of biochemical indicators, histopathological observations and western blotting showed that TLR and DTG exhibited a significant effect in renal protection. And 27 endogenous metabolites (12 in serum and 15 in urine) could be tentatively identified in the process of DN in rats using metabolomics method. Those endogenous metabolites were chiefly involved in sphingolipid metabolism; pentose, glucuronate interconversion; terpenoid backbone biosynthesis; purine metabolism and retinol metabolism. After drug intervention, these endogenous metabolites turned back to normal level some extent (P < 0.05). Furthermore, TLR and DTG prevent high glucose-induced glomerular mesangial cells (GMCs) by inhibiting TGF-β1 and Wnt/β-catenin signaling pathway, providing a powerful supports to develop a new therapeutic agent for DN. This study paved the way for further exploration of the pathogenesis of DN, early diagnosis and the evaluation of curative effect.

Anatase TiO2 with {001} facets is much more active than that with {101} facets, which has been verified via experiments and theoretical calculations. Graphene has garnered much attention since it was initially synthesized, due to its unique properties. In this study, reduced graphene oxide (RGO)/{001} faceted TiO2 composites were fabricated via a solvothermal method. The composites were characterized by scanning electron microscopy, transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectrophotometry, photoluminescence and Raman analysis. The results revealed that the graphene oxide was reduced during the preparation process of the {001} faceted TiO2, and combined with the surface of {001} TiO2. The photocatalytic activities of the composites were evaluated through the degradation of basic violet, under both white light (λ > 390 nm) and visible light (λ = 420 nm) irradiation. The results indicated that the photocatalytic activities of the {001} faceted TiO2 were significantly improved following the incorporation of RGO, particularly under visible light irradiation. Theoretical calculations showed that the band structure of the {001} faceted TiO2 was modified via graphene hybridization, where the separation of photoinduced electron–hole pairs was promoted; thus, the photocatalytic activity was enhanced.

Jujubae Fructus, the dried fruit of Ziziphus jujuba, has been used as Chinese medicine and food for centuries. Triterpenic acids have been found to be the major bioactive constituents in Jujubae Fructus responsible for their hepatoprotective activity in previous phytochemical and biological studies, while few pharmacokinetic studies have been conducted. To reveal the kinetics of the triterpenic acids under the pathological liver injury state, an established ultra-performance liquid chromatography coupled with a mass spectrometry method was applied for the simultaneous quantitation of seven triterpenic acids (ceanothic acid, epiceanothic acid, pomonic acid, alphitolic acid, maslinic acid, betulinic acid, and betulonic acid) in plasma samples of normal and acute liver injury rats induced by CCl4. The results showed that there were significant differences (p < 0.05) in the pharmacokinetic parameters of seven triterpenic acids between model and normal groups. The AUC0–t and AUC0–∞ of epiceanothic acid (5227 ± 334 μg⋅h/L vs. 1478 ± 255 μg⋅h/L and 6127 ± 423 μg⋅h/L vs. 1482 ± 255 μg⋅h/L, respectively) and pomonic acid (4654 ± 349 μg⋅h/L vs. 1834 ± 225 μg⋅h/L and 4776 ± 322 μg⋅h/L vs. 1859 ± 230 μg⋅h/L, respectively) in model rats were significantly higher than those in normal rats, and the CLz/F of them were significantly decreased (0.28 ± 0.02 L/h/kg vs. 1.36 ± 0.18 L/h/kg and 19.96 ± 1.30 L/h/kg vs. 53.15 ± 5.60 L/h/kg, respectively). In contrast, the above parameters for alphitolic acid, betulinic acid and betulonic acid exhibited the quite different trend. This pharmacokinetic research might provide useful information for the clinical usage of triterpenic acids from Jujubae Fructus.

Venenum Bufonis, a well-known traditional Chinese medicine, has been widely used in Asia and has gained popularity in Western countries over the last decade. Venenum Bufonis has obvious side effects that have been observed in clinical settings, but few studies have reported on its cardiotoxicity. In this work, the cardiotoxicity of Venenum Bufonis was investigated using a 11H NMR-based metabolomics approach. The 1H NMR profiles of the serum, myocardial extracts and liver extracts of specific-pathogen-free rats showed that Venenum Bufonis produced significant metabolic perturbations dose-dependently with a distinct time effect, peaking at 2 hr after dosing and attenuating gradually. Clinical chemistry, electrocardiographic recordings, and histopathological evaluation provided additional evidence of Venenum Bufonis-induced cardiac damage that complemented and supported the metabolomics findings. The combined results demonstrated that oxidative stress, mitochondrial dysfunction, and energy metabolism perturbations were associated with the cardiac damage that results from Venenum Bufonis.

This paper deals with a generalized KdV–mKdV equation with time delay. By employing the geometrical singular perturbation theory and the linear chain trick, we establish the existence result of solitary wave solutions when the average delay is sufficiently small, for a special convolution kernel.