Residue profiles of peptides with cholesterol esterase and pancreatic lipase inhibitory activities through virtual screening and sequence analysis.

The detailed characterization of the structural features of peptides targeting cholesterol esterase (CEase) or pancreatic lipase (PPL) will benefit the management of hyperlipidemia and obesity. This study employed the Glide SP (standard precision)-peptide method to predict the binding modes of 202 dipeptides and 203 tripeptides to these targets, correlating residue composition and position with binding energy. Strong preferences for Trp, Phe, and Tyr were observed at all positions of potential inhibitory peptides, whereas negatively charged residues Glu and Asp were disfavored. Notably, Arg and aromatic rings significantly influenced the peptide conformation at the active site. Tripeptide IWR demonstrated the high efficacy, with IC50 values of 0.214 mg/mL for CEase and 0.230 mg/mL for PPL. Five novel IWR scaffold-tetrapeptides exhibited promising inhibitory activity. Non-covalent interactions and energy contributions dominated the formation of stable complexes. Our results provide insights for the development of new sequences or peptide-like molecules with enhanced inhibitory activity.

Physical activity, long-term fine particulate matter exposure and type 2 diabetes incidence: A prospective cohort study.

Background: Despite the adverse effects of ambient fine particulate matter (PM2.5) on type 2 diabetes and the beneficial role of physical activity (PA), the influence of PM2.5 on the relationship between PA and type 2 diabetes remains unclear. Methods: In this prospective study with 71,689 participants, PA was assessed by a questionnaire and was categorized into quartiles for volume and three groups for intensity. Long-term PM2.5 exposure was calculated using 1-km resolution satellite-based PM2.5 estimates. PM2.5 exposure and PA's effect on type 2 diabetes were assessed by cohort-stratified Cox proportional hazards models, individually and in combination. Results: In 488,166 person-years of follow-up, 5487 incident type 2 diabetes cases were observed. The association between PA and type 2 diabetes was modified by PM2.5. Compared with the lowest quartile of PA volume, the highest quartile was associated with reduced type 2 diabetes risk in low PM2.5 stratification (≤65.02 µg/m3) other than in high PM2.5 stratification (>65.02 µg/m3), with the hazard ratio (HR) of 0.75 (95% confidence interval [CI]: 0.66-0.85) and 1.10 (95% CI: 0.99-1.22), respectively. Similar results were observed for PA intensity. High PM2.5 exposure combined with the highest PA levels increased the risk of type 2 diabetes the most (HR = 1.79, 95% CI: 1.59-2.01 for PA volume; HR = 1.82, 95% CI: 1.64-2.02 for PA intensity). Conclusion: PA could reduce type 2 diabetes risk in low-pollution areas, but high PM2.5 exposure may weaken or even reverse the protective effects of PA. Safety and health benefits of PA should be thoroughly assessed for long-term polluted residents.

Vibration-resistant Fizeau interferometry using three-cavity multiplexing.

This study demonstrates a three-cavity multiplexing vibration-resistant Fizeau interferometry (TCM). The method injects a vibration-measurement pass (VMP), which utilizes three-cavity hybrid interference for the transmission of phase and vibration information, to the Fizeau phase-measurement pass (PMP). Moreover, the VMP is demultiplexed using the temporal difference of mixed fringes and synchronous phase-shifting phase extraction of difference fringe to obtain the vibration information, which is then used to calculate the measured phase combined with PMP. The feasibility and performance of the TCM are demonstrated experimentally. To the best of our knowledge, this is the first proposal of the TCM that not only solves the effect of vibration and null-fringe demodulation but also features a common path, simple testing process, and low system complexity.

Discordant High Remnant Cholesterol With LDL-C Increases the Risk of Stroke: A Chinese Prospective Cohort Study.

BACKGROUND: Previous studies focusing on assessing the effects of remnant cholesterol (RC) and low-density lipoprotein cholesterol (LDL-C) on stroke may not consider their mutual influence. We aimed to explore the associations of RC and discordant high RC with LDL-C with stroke, ischemic stroke (IS), and hemorrhagic stroke. METHODS: This prospective cohort study was conducted based on 3 cohorts of the China-PAR (Prediction for Atherosclerotic Cardiovascular Disease Risk in China) project. RC was calculated as non-high-density lipoprotein cholesterol minus LDL-C estimated by Martin/Hopkins equations. Concordant/discordant categories for RC versus LDL-C were determined based on cut-points of 130 mg/dL for LDL-C and equivalent percentile (32.50 mg/dL) for RC. Cox models were used to estimate adjusted hazard ratios and 95% CIs for incident stroke. RESULTS: Among 113 448 participants recruited at baseline, a total of 98 967 participants were eligible for the final analysis (mean age of 51.44 years; 40.45% were men). During 728 776.87 person-years of follow-up, 2859 stroke cases, 1811 IS cases, and 849 hemorrhagic stroke cases were observed. RC was positively associated with stroke and IS, but not hemorrhagic stroke, with adjusted hazard ratios (95% CIs) of 1.06 (1.02-1.10), 1.09 (1.04-1.13), and 0.95 (0.88-1.03) for per SD increase in RC. Compared with low LDL-C/low RC group, low LDL-C/high RC group had higher risks of stroke (adjusted hazard ratio, 1.15 [95% CI, 1.02-1.30]) and IS (1.19, 1.03-1.38), while high LDL-C/low RC group had no increased risk of stroke (1.07 [0.95-1.20]) and IS (1.09 [0.94-1.25]). CONCLUSIONS: Higher RC was associated with increased risks of stroke and IS but not hemorrhagic stroke. Discordantly high RC, not discordantly high LDL-C, conferred higher risks of stroke and IS. Our findings support further lowering RC by interventions to reduce residual IS risk.

Identification of immunotherapy-related subtypes, characterization of tumor microenvironment infiltration, and development of a prognostic signature in gastric carcinoma.

BACKGROUND: Recent advances in immunotherapy have elicited a considerable amount of attention as viable therapeutic options for several cancer types, the present study aimed to explore the immunotherapy-related genes (IRGs) and develop a prognostic risk signature in gastric carcinoma (GC) based on these genes. METHODS: IRGs were identified by comparing immunotherapy responders and non-responders in GC. Then, GC patients were divided into distinct subtypes by unsupervised clustering method based on IRGs, and the differences in immune characteristics and prognostic stratification between these subtypes were analyzed. An immunotherapy-related risk score (IRRS) signature was developed and validated for risk classification and prognosis prediction based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts. Besides, the predictive ability of the IRRS in immunotherapy response was also determined. RESULTS: A total of 63 IRGs were identified, and 371 GC patients were stratified into two molecular subgroups with significantly different prognosis and immune characteristics. Then, an IRRS signature comprised of three IRGs (CENP8, NRP1, and SERPINE1) was constructed to predict the prognosis of GC patients in TCGA cohort. Importantly, external validation in multiple GEO cohorts further confirmed the universal applicability of the IRRS in distinct populations. Furthermore, we found that the IRRS was significantly correlated with patient's responsiveness to immunotherapy, GC patients with low IRRS are more likely to benefit from existing immunotherapy. CONCLUSIONS: The risk score could serve as a robust prognostic biomarker, provide therapeutic benefits for immunotherapy and may be helpful for clinical decision making in GC patients.

Clinical application potential of large language model: a study based on thyroid nodules.

BACKGROUND: Limited data indicated the performance of large language model (LLM) taking on the role of doctors. We aimed to investigate the potential for ChatGPT-3.5 and New Bing Chat acting as doctors using thyroid nodules as an example. METHODS: A total of 145 patients with thyroid nodules were included for generating questions. Each question was entered into chatbot of ChatGPT-3.5 and New Bing Chat five times and five responses were acquired respectively. These responses were compared with answers given by five junior doctors. Responses from five senior doctors were regarded as gold standard. Accuracy and reproducibility of responses from ChatGPT-3.5 and New Bing Chat were evaluated. RESULTS: The accuracy of ChatGPT-3.5 and New Bing Chat in answering Q2, Q3, Q5 were lower than that of junior doctors (all P < 0.05), while both LLMs were comparable to junior doctors when answering Q4 and Q6. In terms of "high reproducibility and accuracy", ChatGPT-3.5 outperformed New Bing Chat in Q1 and Q5 (P < 0.001 and P = 0.008, respectively), but showed no significant difference in Q2, Q3, Q4, and Q6 (P > 0.05 for all). New Bing Chat generated higher accuracy than ChatGPT-3.5 (72.41% vs 58.62%) (P = 0.003) in decision making of thyroid nodules, and both were less accurate than junior doctors (89.66%, P < 0.001 for both). CONCLUSIONS: The exploration of ChatGPT-3.5 and New Bing Chat in the diagnosis and management of thyroid nodules illustrates that LLMs currently demonstrate the potential for medical applications, but do not yet reach the clinical decision-making capacity of doctors.

NUAK2 mediated regulation of Schwann Cell proliferation and migration in peripheral nerve injury via YAP.

NUAK2 is a member of the AMP-activated protein kinase (AMPK) family, which plays an essential role in cellular processes such as apoptosis, proliferation, and cell fate. Recent studies have already shown that silencing of NUAK2 blocks proliferation and promotes apoptosis of human melanoma cells and liver cancer cells. In addition, NUAK2 is involved in the development of glioblastoma via regulating the expression of cancer stem cell-related genes, and it promotes the cell cycle entry in the glioblastoma cells. However, the expression and the role of NUAK2 in the progress of peripheral nerve regeneration after injury are yet to be elucidated. We observed that NUAK2 was upregulated following distal sciatic nerve crush (SNC). Interestingly, we discovered that NUAK2 showed co-localization with S100 (Schwann cell marker). Furthermore, we found that the NUAK2 had a spatiotemporal protein expression, which was consistent with proliferating cell nuclear-antigen (PCNA). The protein level of NUAK2 and YAP was upregulated in the model of TNF-α-induced Schwann cell (SC) proliferation. Furthermore, flow cytometry analysis, CCK-8, transwell assays, and wound healing assays were all performed with the purpose of exploring the role of NUAK2 in the regulation of SC proliferation and migration. More importantly, we found that NUAK2-deficient SCs showed significantly reduced expression of Yes-associated protein (YAP). Bioinformatic analysis identified upstream regulators of NUAK2 and NUAK2-associated genes (e.g., YAP1). Finally, we investigated the recovery changes during regeneration progress through the walking track analysis. Thus, we speculated that NUAK2 was involved in biochemical and physiological responses of SCs after SNC via YAP-driven proliferation and migration, and this study determined the importance of NUAK2 as a potential target in peripheral nerve regeneration.

Toxicokinetics and bioavailability of indoxacarb enantiomers and their new metabolites in rats.

Indoxacarb is a chiral insecticide that consists of two enantiomers, S-(+)-indoxacarb and R-(-)-indoxacarb, of which only S-(+)-indoxacarb has insecticidal activity. Previous enantioselective toxicology studies of indoxacarb focused mostly on simple environmental model organisms. The lack of a toxicology evaluation of indoxacarb conducted in a mammalian system could mean that the extent of the potential health risk posed by the insecticide to humans is not adequately known. In this study, we reported on a new pair of enantiomers, S-IN-RM294 and R-IN-RM294, derived from the metabolic breakdown of S-(+)-indoxacarb and R-(-)-indoxacarb, respectively, in rats. The toxicokinetics of S-(+)-indoxacarb, R-(-)-indoxacarb, S-IN-RM294, and R-IN-RM294 in rats were evaluated to provide a more comprehensive risk assessment of these molecules. The bioavailability and excretion rates of both S-(+)-indoxacarb and R-(-)-indoxacarb were relatively low, which may be due to their faster metabolism and accumulation in the tissues. In addition, there were significant differences in the metabolism and distribution between the two indoxacarb enantiomers and their metabolites in vivo. S-(+)-Indoxacarb was found to be more easily metabolized in the blood compared with R-(-)-indoxacarb, as shown by the differences in pharmacokinetic parameters between oral and intravenous administration. Analysis of their tissue distribution showed that S-(+)-indoxacarb was less likely to accumulate in most tissues. The results obtained for the two metabolites were consistent with those of the two parent compounds. S-IN-RM294 was more readily cleared from the blood and less likely to accumulate in the tissues compared with R-IN-RM294. Therefore, whether from the perspective of insecticidal activity or from the perspective of mammalian and environmental friendliness, the application of optically pure S-(+)-indoxacarb in agriculture may be a more efficient and safer strategy.

Stitching interferometry using alternating calibration of positioning and systematic errors.

Stitching interferometry is an essential technique for the non-contact, high-precision measurement of large apertures or complex optical surfaces. However, the accuracy of full-aperture surface reconstruction is significantly compromised by subaperture positioning and systematic errors. To address this challenge, this study introduces a novel stitching interferometry method utilizing alternating calibration of positioning and systematic errors (SIAC). This method calibrates one type of error while maintaining the other constant, and alternates between these processes to effectively decouple the two errors, facilitating accurate phase stitching. Within this calibration framework, an iterative weighted phase stitching model employing vertical projection for estimating overlapping areas was developed to calibrate positioning errors. Additionally, the rotation measurements of a single subaperture, in conjunction with a global fitting approach, were employed to correct reference errors. Numerical simulations have confirmed the efficacy of SIAC in calibrating these errors. Moreover, experimental measurements were performed on both a plane mirror and gullwing aspheres, with the resulting stitched full-aperture phase distributions and cross-testing outcomes affirming the method's accuracy and practicality. This research provides a novel solution for stitching interferometry, enhancing the precision of optical surface measurements.

The AaERF64-AaTPPA module participates in cold acclimatization of Actinidia arguta (Sieb. et Zucc.) Planch ex Miq.

Actinidia arguta (A. arguta, kiwiberry) is a perennial deciduous vine with a strong overwintering ability. We hypothesized that trehalose metabolism, which plays a pivotal role in the stress tolerance of plants, may be involved in the cold acclimatization of A. arguta. Transcriptome analysis showed that the expression of AaTPPA, which encodes a trehalose-6-phosphate phosphatase (TPP), was upregulated in response to low temperatures. AaTPPA expression levels were much higher in lateral buds, roots, and stem cambia than in leaves in autumn. In AaTPPA-overexpressing (OE) Arabidopsis thaliana (A. thaliana), trehalose levels were 8-11 times higher than that of the wild type (WT) and showed different phenotypic characteristics from WT and OtsB (Escherichia coli TPP) overexpressing lines. AaTPPA-OE A. thaliana exhibited significantly higher freezing tolerance than WT and OtsB-OE lines. Transient overexpression of AaTPPA in A. arguta leaves increased the scavenging ability of reactive oxygen species (ROS) and the soluble sugar and proline contents. AaERF64, an ethylene-responsive transcription factor, was induced by ethylene treatment and bound to the GCC-box of the AaTPPA promoter to activate its expression. AaTPPA expression was also induced by abscisic acid. In summary, the temperature decrease in autumn is likely to induce AaERF64 expression through an ethylene-dependent pathway, which consequently upregulates AaTPPA expression, leading to the accumulation of osmotic protectants such as soluble sugars and proline in the overwintering tissues of A. arguta. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01475-8.

Functions of Basic Helix-Loop-Helix (bHLH) Proteins in the Regulation of Plant Responses to Cold, Drought, Salt, and Iron Deficiency: A Comprehensive Review.

Abiotic stresses including cold, drought, salt, and iron deficiency severely impair plant development, crop productivity, and geographic distribution. Several bodies of research have shed light on the pleiotropic functions of BASIC HELIX-LOOP-HELIX (bHLH) proteins in plant responses to these abiotic stresses. In this review, we mention the regulatory roles of bHLH TFs in response to stresses such as cold, drought, salt resistance, and iron deficiency, as well as in enhancing grain yield in plants, especially crops. The bHLH proteins bind to E/G-box motifs in the target promoter and interact with various other factors to form a complex regulatory network. Through this network, they cooperatively activate or repress the transcription of downstream genes, thereby regulating various stress responses. Finally, we present some perspectives for future research focusing on the molecular mechanisms that integrate and coordinate these abiotic stresses. Understanding these molecular mechanisms is crucial for the development of stress-tolerant crops.

Physiological and Proteomic Responses of the Tetraploid Robinia pseudoacacia L. to High CO2 Levels.

The increase in atmospheric CO2 concentration is a significant factor in triggering global warming. CO2 is essential for plant photosynthesis, but excessive CO2 can negatively impact photosynthesis and its associated physiological and biochemical processes. The tetraploid Robinia pseudoacacia L., a superior and improved variety, exhibits high tolerance to abiotic stress. In this study, we investigated the physiological and proteomic response mechanisms of the tetraploid R. pseudoacacia under high CO2 treatment. The results of our physiological and biochemical analyses revealed that a 5% high concentration of CO2 hindered the growth and development of the tetraploid R. pseudoacacia and caused severe damage to the leaves. Additionally, it significantly reduced photosynthetic parameters such as Pn, Gs, Tr, and Ci, as well as respiration. The levels of chlorophyll (Chl a and b) and the fluorescent parameters of chlorophyll (Fm, Fv/Fm, qP, and ETR) also significantly decreased. Conversely, the levels of ROS (H2O2 and O2·-) were significantly increased, while the activities of antioxidant enzymes (SOD, CAT, GR, and APX) were significantly decreased. Furthermore, high CO2 induced stomatal closure by promoting the accumulation of ROS and NO in guard cells. Through a proteomic analysis, we identified a total of 1652 DAPs after high CO2 treatment. GO functional annotation revealed that these DAPs were mainly associated with redox activity, catalytic activity, and ion binding. KEGG analysis showed an enrichment of DAPs in metabolic pathways, secondary metabolite biosynthesis, amino acid biosynthesis, and photosynthetic pathways. Overall, our study provides valuable insights into the adaptation mechanisms of the tetraploid R. pseudoacacia to high CO2.

Research on Medical Image Segmentation Method Based on Improved U-Net3.

Computer assisted diagnostic technology has been widely used in clinical practice, specifically focusing on medical image segmentation. Its purpose is to segment targets with certain special meanings in medical images and extract relevant features, providing reliable basis for subsequent clinical diagnosis and research. However, because of different shapes and complex structures of segmentation targets in different medical images, some imaging techniques have similar characteristics, such as intensity, color, or texture, for imaging different organs and tissues. The localization and segmentation of targets in medical images remains an urgent technical challenge to be solved. As such, an improved full scale skip connection network structure for the CT liver image segmentation task is proposed. This structure includes a biomimetic attention module between the shallow encoder and the deep decoder, and the feature fusion proportion coefficient between the two is learned to enhance the attention of the overall network to the segmented target area. In addition, based on the traditional point sampling mechanism, an improved point sampling strategy is proposed for characterizing medical images to further enhance the edge segmentation effect of CT liver targets. The experimental results on the commonly used combined (CT-MR) health absolute organ segmentation (CHAOS) dataset show that the average dice similarity coefficient (DSC) can reach 0.9467, the average intersection over union (IOU) can reach 0.9623, and the average F1 score can reach 0.9351. This indicates that the model can effectively learn image detail features and global structural features, leading to improved segmentation of liver images.

Association of genetic variants related to combined lipid-lowering and antihypertensive therapies with risk of cardiovascular disease: 2 × 2 factorial Mendelian randomization analyses.

BACKGROUND: Lipid-lowering drugs and antihypertensive drugs are commonly combined for cardiovascular disease (CVD). However, the relationship of combined medications with CVD remains controversial. We aimed to explore the associations of genetically proxied medications of lipid-lowering and antihypertensive drugs, either alone or both, with risk of CVD, other clinical and safety outcomes. METHODS: We divided 423,821 individuals in the UK Biobank into 4 groups via median genetic scores for targets of lipid-lowering drugs and antihypertensive drugs: lower low-density lipoprotein cholesterol (LDL-C) mediated by targets of statins or proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, lower systolic blood pressure (SBP) mediated by targets of ß-blockers (BBs) or calcium channel blockers (CCBs), combined genetically lower LDL-C and SBP, and reference (genetically both higher LDL-C and SBP). Associations with risk of CVD and other clinical outcomes were explored among each group in factorial Mendelian randomization. RESULTS: Independent and additive effects were observed between genetically proxied medications of lipid-lowering and antihypertensive drugs with CVD (including coronary artery disease, stroke, and peripheral artery diseases) and other clinical outcomes (ischemic stroke, hemorrhagic stroke, heart failure, diabetes mellitus, chronic kidney disease, and dementia) (P > 0.05 for interaction in all outcomes). Take the effect of PCSK9 inhibitors and BBs on CVD for instance: compared with the reference, PCSK9 group had a 4% lower risk of CVD (odds ratio [OR], 0.96; 95%CI, 0.94-0.99), and a 3% lower risk was observed in BBs group (OR, 0.97; 95%CI, 0.94-0.99), while combined both were associated with a 6% additively lower risk (OR, 0.94; 95%CI, 0.92-0.97; P = 0.87 for interaction). CONCLUSIONS: Genetically proxied medications of combined lipid-lowering and antihypertensive drugs have an independent and additive effects on CVD, other clinical and safety outcomes, with implications for CVD clinical practice, subsequent trials as well as drug development of polypills.

Artificial intelligence in judicial adjudication: Semantic biasness classification and identification in legal judgement (SBCILJ).

History reveals that human societies have suffered in terms of social justice due to cognitive bias. Semantic bias tends to amplify cognitive bias. Therefore, the presence of cognitive biases in extensive historical data can potentially result in unethical and allegedly inhumane predictions since AI systems are trained on this data. The innovation of artificial intelligence and its rapid integration across disciplines has prompted questions regarding the subjectivity of the technology. Current research focuses the semantic bias in legal judgment to increase the legitimacy of training data. By the application of general-purpose Artificial Intelligence (AI) algorithms, we classify and detect the semantics bias that is present in the Chinese Artificial Intelligence and Law (CAIL) dataset. Our findings demonstrate that AI models acquire superior prediction power in the CAIL dataset, which is comprised of hundreds of cases, compared to a structured professional risk assessment tool. To assist legal practitioners during this process, innovative approaches that are based on AI may be implemented inside the legal arena. To accomplish this objective, we suggested a classification model for semantic bias that is related to the classification and identification of semantic biases in legal judgment. Our proposed model legal field uses the example of categorization along with the identification of the CAIL dataset. This will be accomplished by identifying the semantics biases in judicial decisions. We used different types of classifiers such as the Support Vector Machine (SVM), Naïve-Bayes (NB), Multi-Layer Perceptron (MLP), and the K-Nearest Neighbour (KNN) to come across the preferred results. SVM got 96.90 %, NB has 88.80 %, MLP has 86.75 % and KNN achieved 85.66 % accuracy whereas SVM achieved greater accuracy as compared to other models. Additionally, we demonstrate that we were able to get a relatively high classification performance when predicting outcomes based just on the semantic bias categorization in judicial judgments that determine the outcome of the case.

Associations between socioeconomic status and rates of blood pressure changes among Chinese older adults: a longitudinal community-based cohort study.

OBJECTIVES: The relationships between socioeconomic status (SES) and blood pressure changes among older adults in China remain unclear. This study aimed to examine the associations between SES and rates of blood pressure changes among Chinese older adults. STUDY DESIGN: Community-based, prospective, longitudinal cohort study. METHODS: This study included 13,541 participants aged ≥65 years from the Chinese Longitudinal Healthy Longevity Survey between 2002 and 2018. SES was assessed by educational level, occupation, household yearly per capita income, and financial support. The estimated annual changes (EACs) of blood pressure were computed as the difference in blood pressure levels between any two adjacent surveys divided by the time interval. Associations between SES and EACs of blood pressure were evaluated using generalised estimating equations. RESULTS: Lower SES was significantly associated with greater annual increases of blood pressure among Chinese older adults. The effect of SES on EACs of blood pressure was more pronounced among non-hypertensive participants. Compared to EACs among non-hypertensive participants with high SES, multivariable-adjusted EACs among those with low SES increased by 0.57 mmHg (95% confidence interval [CI]: 0.16, 0.99), 0.32 mmHg (95% CI: 0.07, 0.57), and 0.40 mmHg (95% CI: 0.13, 0.66) for systolic blood pressure, diastolic blood pressure, and mean arterial pressure, respectively. CONCLUSIONS: This study revealed strong associations between SES and EACs of blood pressure among Chinese older adults, especially in the non-hypertensive population. Findings suggest that prevention strategies for hypertension should pay more attention to the older population with low SES.

Some evidence supporting the use of optically pure R-(-)-diniconazole: Toxicokinetics and configuration conversion on chiral diniconazole.

Diniconazole is a chiral pesticide that exists in two enantiomers, R-(-)-diniconazole and S-(+)-diniconazole, with the R-enantiomer being much more active than the S-enantiomer. Previous enantioselective toxicology studies of diniconazole focused mostly on simple environmental model organisms. In this study, we evaluated the toxicokinetics of the two diniconazole enantiomers in rats and mice to provide a more comprehensive risk assessment. The two enantiomers displayed clear differences in their stereoselective contents in vivo. The t1/2 of R-(-)-diniconazole was 7.06 ± 3.35 h, whereas that of S-(+)-diniconazole was 9.14 ± 4.60 h, indicating that R-(-)-diniconazole was eliminated faster in vivo. The excretion rates of R-(-)-diniconazole and S-(+)-diniconazole were 4.08 ± 0.50 % and 2.68 ± 0.58 %, respectively, indicating more excretion of R-(-)-diniconazole. S-(+)-diniconazole had a higher bioavailability than R-(-)-diniconazole (52.19 % vs. 42.44 %). S-(+)-Diniconazole was also found in relatively high abundance in tissues such as the stomach, large intestine, small intestine, cecum, liver, kidney, brain, and testes, with the abundance being 1.71-2.48-fold that of R-(-)-diniconazole. The selective degradation of both enantiomers in the tissues and their mutual conversion in vivo were not observed, and this could indicate that configuration conversion did not contribute to the differences in the content of enantiomers in the tissues. Instead, such differences were mainly caused by the differences in affinity of each enantiomer for the tissues. Furthermore, investigation of the interconversion between optically pure R-(-)-diniconazole and S-(+)-diniconazole monomers in soil revealed no interconversion. All of the above results indicated no interconversion between R-(-)-diniconazole and S-(+)-diniconazole in vivo and in the soil, and that S-(+)-diniconazole tends to have a greater potential to accumulate in vivo. Thus, if only R-(-)-diniconazole is used as a pesticide, the negative impact on mammals and the environment will be reduced, suggesting that in agriculture, the application of optically pure R-(-)-diniconazole may be a better strategy.

Metabolomics signature of blood pressure salt sensitivity and its link to cardiovascular disease: A dietary salt-intervention trial.

Individuals with a high degree of salt sensitivity (SS) have a greater risk of cardiovascular disease (CVD), but whether SS fosters CVD by influencing metabolomics homeostasis remains unclear. This study aimed to reveal the role of the SS-related metabolomics signature in the development of CVDs, based on the MetaSalt study, which was a dietary salt-intervention trial conducted at four centers in China in 2019. A total of 528 participants were recruited and underwent 3 days of baseline observations, a 10-day low-salt intervention, and a 10-day high-salt intervention. Plasma untargeted metabolomics, lipidomics, and BP measurements were scheduled at each stage. Participants were grouped into extreme SS, moderate SS, and salt-resistant (SR) individuals according to their BP responses to salt. Linear mixed models were used to identify SS-related metabolites and determine the relationship between the SS-related metabolomics signature and arterial stiffness. Mendelian randomization (MR) analyses were applied to establish the causal pathways among the SS-related metabolites, BP, and CVDs. Among the 713 metabolites, 467 were significantly changed after the high-salt intervention. Among them, the changes in 30 metabolites from the low-salt to the high-salt intervention differed among the SS groups. Of the remaining nonsalt-related metabolites, the baseline levels of 11 metabolites were related to SS. These 41 metabolites explained 23% of the variance in SS. Moreover, SS and its metabolomics signature were positively correlated with arterial stiffness. MR analyses demonstrated that the SS-related metabolites may affect CVD risk by altering BP, indicating that the increase in BP was the consequence of the changes in SS-related metabolites rather than the cause. Our study revealed that the metabolomics signature of SS individuals differs from that of SR individuals and that the changes in SS-related metabolites may increase arterial stiffness and foster CVDs. This study provides insight into understanding the biology and targets of SS and its role in CVDs.

Dietary intake changes the associations between long-term exposure to fine particulate matter and the surrogate indicators of insulin resistance.

The relationship of fine particulate matter (PM2.5) exposure and insulin resistance remains inclusive. Our study aimed to investigate this association in the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR). Specifically, we examined the associations between long-term PM2.5 exposure and three surrogate indicators of insulin resistance: the triglyceride-glucose index (TyG), TyG with waist circumference (TyG-WC) and metabolic score for insulin resistance (METS-IR). Additionally, we explored potential effect modification of dietary intake and components. Generalized estimating equations were used to evaluate the associations between PM2.5 and the indicators with an unbalanced repeated measurement design. Our analysis incorporated a total of 162,060 observations from 99,329 participants. Each 10 µg/m3 increment of PM2.5 was associated with an increase of 0.22 % [95 % confidence interval (CI): 0.20 %, 0.25 %], 1.60 % (95 % CI: 1.53 %, 1.67 %), and 2.05 % (95 % CI: 1.96 %, 2.14 %) in TyG, TyG-WC, and METS-IR, respectively. These associations were attenuated among participants with a healthy diet, particularly those with sufficient intake of fruit and vegetable, fish or tea (pinteraction < 0.0028). For instance, among participants with a healthy diet, TyG increased by 0.11 % (95 % CI: 0.08 %, 0.15 %) per 10 µg/m3 PM2.5 increment, significantly lower than the association observed in those with an unhealthy diet. The findings of this study emphasize the potential of a healthy diet to mitigate these associations, highlighting the urgency for improving air quality and implementing dietary interventions among susceptible populations in China.

Arginase 2 is a Diagnostic and Prognostic Marker for Prostate Cancer and Is Associated with Metabolism.

Objective: Metabolism, a basic need and biochemical process for cell survival and proliferation, is closely connected with the pathogenesis and progression of prostate cancer. Methods: A four-gene signature construct that includes CKM (CKM), CD38, Enoyl Coenzyme A(EHHADH), and Arginase 2(ARG2) was created by bioinformatics. Finally, hub genes were validated by IHC and in vitro experiments. Results: The results showed the AUCs of the logistic regression and neural networks diagnostic model for the diagnosis of two subtypes were 0.920 and 0.936, respectively. The risk score demonstrated by univariable and multivariable Cox analysis is an independent predictive component of the prognostic signature for DFS. According to immunohistochemical analyses, ARG2 and CD38 expression levels were considerably under-expressed, but CKM and EHHADH expression levels were significantly overexpressed. Furthermore, The expression of ARG2 was significantly down-regulated in the late Gleason score. Finally, we found that ARG2 is lowly expressed in prostate cancer cells. Furthermore, based on the effect of ARG2 on the malignant phenotype of PCa in vitro, we also found that ARG2 may be a tumor suppressor that plays an important role in inhibiting proliferation, migration, and invasion. Conclusions: These findings suggest that ARG2 has been tentatively identified as a new target for research into how PCa develops in metabolism and for the development of innovative targeted treatments.