Analysis of status and influencing factors of mental health in patients with systemic lupus erythematosus.

BACKGROUND: Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disorder with varied clinical courses and prognoses, not only did the patients suffer from physical impairment, but also various physical and psychiatric comorbidities. Growing evidence have suggested that mental disorders in SLE patients, can lead to various adverse consequences. AIM: To explored the features and influencing factors of mental health in patients with SLE and clarifying the correlations between mental health and personality characteristics and perceived social support. The results would provide a basis for psychological intervention in patients with SLE. METHODS: The clinical data of 168 patients with SLE admitted at the First Affiliated Hospital of Hainan Medical University between June 2020 and June 2022 were collected. Psychological assessment and correlation analysis were conducted using the Symptom Checklist-90 (SCL-90) and Perceived Social Support Scale, and the collected data were compared with the national norms in China. The relevant factors influencing mental health were identified by statistical analysis. A general information questionnaire, the Revised Life Orientation Test, and Short-Form 36-Item Health Survey were employed to assess optimism level and quality of life (QoL), respectively. RESULTS: Patients with SLE obtained higher scores for the somatization, depression, anxiety, and phobic anxiety subscales than national norms (P < 0.05). A correlation was identified between total social support and total SCL-90 score or each subscale (P < 0.05). The factors significantly affecting patients' mental health were hormone dosage and disease activity index (DAI) (P < 0.05). The average optimism score of patients with SLE was 14.36 ± 4.42, and 30 cases were in the middle and lower levels. A positive correlation was found between optimism level and QoL scores. CONCLUSION: Patients with SLE develop psychological disorders at varying degrees, which are significantly influenced by hormone dosage and DAI. Patients' mental health should be closely monitored during clinical diagnosis and treatment and provided adequate support in establishing positive, healthy thinking and behavior patterns and improving their optimism level and QoL.

Machine Learning-Based Prediction of Large-for-Gestational Age Infants in Mothers with Gestational Diabetes Mellitus.

CONTEXT: Large-for-gestational-age (LGA), one of the most common complications of gestational diabetes mellitus (GDM), has become a global concern. The predictive performance of common continuous glucose monitoring (CGM) metrics for LGA is limited. OBJECTIVE: We aimed to develop and validate an artificial intelligence (AI) based model to determine the probability of women with GDM giving birth to LGA infants during pregnancy using CGM measurements together with demographic data and metabolic indicators. METHODS: A total of 371 women with GDM from a prospective cohort at a university hospital were included. CGM was performed during 20-34 gestational weeks, and glycemic fluctuations were evaluated and visualized in women with GDM who gave birth to LGA and non-LGA infants. A convolutional neural network (CNN)-based fusion model was developed to predict LGA. Comparisons among the novel fusion model and three conventional models were made using the area under the receiver-operating characteristic curve (AUCROC) and accuracy. RESULTS: Overall, 76 (20.5%) out of 371 GDM women developed LGA neonates. The visualized 24-h glucose profiles differed at midmorning. This difference was consistent among subgroups categorized by pregestational BMI, therapeutic protocol and CGM administration period. The AI based fusion prediction model using 24-h CGM data and 15 clinical variables for LGA prediction (AUCROC 0.852, 95% CI 0.680-0.966, accuracy 84.4%) showed superior discriminative power compared with the three classic models. CONCLUSIONS: We demonstrated better performance in predicting LGA infants among women with GDM using the AI based fusion model. The characteristics of the CGM profiles allowed us to determine the appropriate window for intervention.

Association between composite dietary antioxidant and bone mineral density in children and adolescents aged 8-19 years: findings from NHANES.

Dietary antioxidants may have beneficial effects on bone health, but it remains uncertain in children and adolescents. This study investigates the association of composite dietary antioxidant index (CDAI) with bone mineral density (BMD) in children and adolescents aged 8-19 years from the National Health and Nutrition Examination Survey (NHANES) 2007-2010. The study assessed the relationship between CDAI and BMD in 2994 individuals aged 8-19 years (average age 13.48 ± 3.32 years) from the NHANES 2007-2010. Multivariate linear regression analyses were utilized to detect the association between CDAI and total spine, femur neck, and total femur BMD, adjusting for confounders including age, race/ethnicity, sex, poverty income ratio (PIR), body mass index (BMI), serum phosphorus and calcium. Stratified analyses and interaction tests were performed to examine the stability of the results. The weighted characteristics showed that subjects in the fourth CDAI quartile were more likely to be older, men, and Non-Hispanic White. They have higher values of serum total calcium and phosphorus. After adjusting all confounders, CDAI was positively associated with the total spine (ß = 0.0031 95% CI 0.0021-0.0040), total femur (ß = 0.0039 95% CI 0.0028-0.0049), and femur neck BMD (ß = 0.0031 95% CI 0.0021-0.0040) in children and adolescents. Furthermore, we found no interaction effects between different race/ethnicity, age, and sex groups. Our findings suggest that dietary intake of multiple antioxidants was positively associated with BMD in children and adolescents. These findings provide valuable evidence for improving bone health in the early stages of life. However, more prospective studies are required to validate our findings and their causal relationship.

Association between Life's Essential 8 and Infertility as Well as the Mediating Effects of Oxidative Stress and Inflammatory Factors Among U.S. Women Aged 18-45 Years.

Management of cardiovascular disease in pregnancy is important, yet the association between cardiovascular health and infertility is rarely reported. In this study, we aimed to explore the association between Life's Essential 8 (LE8), a novel cardiovascular health (CVH) measure, and infertility, and to investigate potential mediating mechanisms. This study investigated cross-sectional data from the 2013-2018 National Health and Nutrition Examination Survey. LE8 score (ranging from 0 to 100) was calculated as the unweighted average of eight CVH metrics. The association between LE8 and infertility was explored through weighted multiple logistic regression. Restricted cubic splines were used to explore nonlinear correlation. In addition, mediation analysis was conducted to investigate the role of oxidative stress and inflammatory markers systematically. After strict exclusion criteria, 1703 American women aged 18-45 years were included. After full adjustment, the LE8 score showed a negative correlation with infertility [per 1 SD increase, OR = 0.675, 95% CI: 0.553-0.824], with a linear dose-response relationship (non-linear P = 0.122). Similar linear negative correlations were found between health factor scores and infertility, with higher body mass index and glucose scores having a significantly lower risk of infertility. Stratified analyses showed a stronger inversed relationship between LE8 and infertility in younger populations. Moreover, mediation analysis revealed that uric acid concentration and lymphocyte count mediated the effect of LE8 on infertility (P < 0.05). LE8 and its subscale scores were linearly and negatively associated with infertility, which may be mediated in part through uric acid and lymphocyte count. Focusing on weight management and glycemic control can effectively reduce the risk of infertility.

The associations of maternal liver biomarkers in early pregnancy with the risk of gestational diabetes mellitus: a prospective cohort study and Mendelian randomization analysis.

Background: Associations of liver function with the risk of gestational diabetes mellitus (GDM) remain unclear. This study aimed to examine the relationship and the potential causality between maternal liver biomarkers and the risk of subsequent GDM, as well as to evaluate the interaction between liver biomarkers and lipids on GDM risk. Methods: In an ongoing Zhoushan Pregnant Women Cohort, pregnant women who finished the first prenatal follow-up record, underwent liver function tests in early pregnancy, and completed the GDM screening were included in this study. Logistic regression models were used to investigate the association, and the inverse-variance weighted method supplemented with other methods of two-sample Mendelian randomization (MR) analysis was applied to deduce the causality. Results: Among 9,148 pregnant women, 1,668 (18.2%) developed GDM. In general, the highest quartile of liver function index (LFI), including ALT, AST, GGT, ALP, and hepatic steatosis index, was significantly associated with an increased risk of GDM (OR ranging from 1.29 to 3.15), especially an elevated risk of abnormal postprandial blood glucose level. Moreover, the causal link between ALT and GDM was confirmed by the MR analysis (OR=1.28, 95%CI:1.05-1.54). A significant interaction between AST/ALT and TG on GDM risk was observed (P interaction = 0.026). Conclusion: Elevated levels of LFI in early pregnancy were remarkably associated with an increased risk of GDM in our prospective cohort. Besides, a positive causal link between ALT and GDM was suggested.

Isolation, identification, and degradation mechanism by multi-omics of mesotrione-degrading Amycolatopsis nivea La24.

Mesotrione is a herbicide used in agricultural production; however, its stability and long-term residues pose ecological risks to soil health and subsequent crops. In this research, the strain Amycolatopsis nivea La24 was identified as capable of completely degrading 50 mg∙L-1 mesotrione within 48 h. It exhibited a broad adaptability to various environment and could degrade three sulfonylurea herbicides (nicosulfuron, chlorimuron-methyl, and cinosulfuron). Non-target metabonomic and mass spectrometry demonstrated that La24 strain broke down the mesotrione parent molecule by targeting the ß-diketone bond and nitro group, resulting in the production of five possible degradation products. The differentially expressed genes were significantly enriched in fatty acid degradation, amino acid metabolism, and other pathways, and the differentially metabolites in glutathione metabolism, arginine/proline metabolism, cysteine/methionine metabolism, and other pathways. Additionally, it was confirmed by heterologous expression that nitroreductase was directly involved in the mesotrione degradation, and NDMA-dependent methanol dehydrogenase would increase the resistance to mesotrione. Finally, the intracellular response of La24 during mesotrione degradation was proposed. This work provides insight for a comprehensive understanding of the mesotrione biodegradation mechanism, significantly expands the resources for pollutant degradation, and offers the potential for a more sustainable solution to address herbicide pollution in soil.

Weight change patterns across adulthood are associated with the risk of osteoarthritis: a population-based study.

BACKGROUND: Body weight has been recognized as a driving factor of osteoarthritis. Few studies had investigated the association between weight status across adulthood and risk of osteoarthritis (OA). This study investigates the association of weight change patterns across adulthood (lasting at least 25 years) with the risk of OA from the National Health and Nutrition Examination Survey (NHANES) 2013-2018. METHODS: The study assessed the relationship between weight change across adulthood and OA in 7392 individuals aged > 50 spanning a minimum of 25 years. Multivariate linear regression analyses were utilized to detect the association between weight change patterns and self-reported OA. Restricted cubic splines (RCS) were used to examine the nonlinear relationship between absolute weight change and OA risk. RESULTS: From 10 years ago to survey, the risk of OA was 1.34-fold (95% CI 1.07-1.68) in people changed from obese to non-obese, 1.61-fold (95% CI 1.29-2.00) in people change from non-obese to obese, and 1.82-fold (95% CI 1.49-2.22) in stable obese people compared with people who were at stable normal weight. Similar patterns were also observed at age 25 years to baseline and age 25 years to 10 years before the baseline. The dose-response association of RCS found a U-shaped relationship between absolute weight change and OA risk. CONCLUSIONS: The study suggests that weight patterns across adulthood are associated with the risk of OA. These findings stressed important to maintain a normal weight throughout adulthood, especially to prevent ignored weight gain in early adulthood to reduce OA risk later.

Soil Organic Matter and Total Nitrogen Reshaped Root-Associated Bacteria Community and Synergistic Change the Stress Resistance of Codonopsis pilosula.

The stress resistance of medicinal plants is essential to the accumulation of pharmacological active ingredients, but the regulation mechanism of biological factors and abiotic factors on medicinal plants is still unclear. To investigate the mechanism of soil nutrient and microecology on the stress resistance of C. pilosula, rhizosphere soil and roots were collected across the four seasons in Minxian, Gansu, and their physicochemical properties, as well as root-associated microorganisms, were examined. The results showed that the bacterial α-diversity indexes increased in the endosphere and rhizosphere from summer to autumn. At the same time, the community composition and function changed considerably. The stability of the endophytic bacterial community was higher than that rhizospheric bacteria, and the complexity of the endophytic bacterial community was lower than rhizospheric bacteria. Soil organic matter (OM), water content (WC), total potassium (TK), and total nitrogen (TN) have been identified as the key factors affecting bacterial community diversity and stress resistance of C. pilosula. WC, TN, and OM showed significant differences from summer to autumn (P < 0.5). Four key soil physiochemical factors changed significantly between seasons (P < 0.01). TN and OM change the stress resistance of C. pilosula mainly by changing the activity of antioxidant enzymes. Changes of OM and endophytic bacterial diversity affect the accumulation of soluble sugars to alter stress resistance. These four key soil physicochemical factors significantly influenced the diversity of endophytic bacteria. WC and OM were identified as the most important factors for endophytic and rhizospheric bacteria, respectively. This study provided the research basis for the scientific planting of C. pilosula.

Amplifying colorectal cancer progression: impact of a PDIA4/SP1 positive feedback loop by circPDIA4 sponging miR-9-5p.

OBJECTIVE: Colorectal cancer (CRC) is a prevalent malignant tumor with a high fatality rate. CircPDIA4 has been shown to have a vital role in cancer development by acting as a facilitator. Nevertheless, the impact of the circPDIA4/miR-9-5p/SP1 axis on development of CRC has not been studied. METHODS: Western blot, immunohistochemistry, and reverse transcription-quantitative polymerase chain reaction assays were used to analyze gene expression. The CCK-8 assay was used to assess cell growth. The Transwell assay was used to detect invasion and migration of cells. The luciferase reporter and RNA immunoprecipitation tests were used to determine if miR-9-5p and circPDIA4 (or SP1) bind to one another. An in vivo assay was used to measure tumor growth. RESULTS: It was shown that circPDIA4 expression was greater in CRC cell lines and tissues than healthy cell lines and tissues. CircPDIA4 knockdown prevented the invasion, migration, and proliferation of cells in CRC. Additionally, the combination of circPDIA4 and miR-9-5p was confirmed, as well as miR-9-5p binding to SP1. Rescue experiments also showed that the circPDIA4/miR-9-5p/SP1 axis accelerated the development of CRC. In addition, SP1 combined with the promoter region of circPDIA4 and induced circPDIA4 transcription. CircPDIA4 was shown to facilitate tumor growth in an in vivo assay. CONCLUSIONS: The circPDIA4/miR-9-5p/SP1 feedback loop was shown to aggravate CRC progression. This finding suggests that the ceRNA axis may be a promising biomarker for CRC patient treatment.

CoH-catalyzed asymmetric remote hydroalkylation of heterocyclic alkenes: a rapid approach to chiral five-membered S- and O-heterocycles.

Saturated heterocycles, which incorporate S and O heteroatoms, serve as fundamental frameworks in a diverse array of natural products, bioactive compounds, and pharmaceuticals. Herein, we describe a unique cobalt-catalyzed approach integrated with a desymmetrization strategy, facilitating precise and enantioselective remote hydroalkylation of unactivated heterocyclic alkenes. This method delivers hydroalkylation products with high yields and excellent stereoselectivity, representing good efficiency in constructing alkyl chiral centers at remote C3-positions within five-membered S/O-heterocycles. Notably, the broad scope and good functional group tolerance of this asymmetric C(sp3)-C(sp3) coupling enhance its applicability.

Dynamic observation and risk factors analysis of deep vein thrombosis after hip fracture.

OBJECTIVE: To dynamically observe the occurrence of deep vein thrombosis (DVT) after a hip fracture and analyze of the risk factors affecting the dynamic alteration of DVT. METHODS: Data of patients with hip fractures from January 1, 2017 to August 31, 2021 were collected. Patients were divided into DVT and non-DVT groups according to their daily Doppler ultrasonography findings. Survival analysis was used to describe dynamic changes in DVT occurrence with time. Log-rank tests were used to compare the influence of individual factors of patients with DVT occurrence, and a Cox proportional hazards regression model was used to identify the risk factors affecting the dynamic alteration of DVT occurrence. RESULTS: A total of 331 patients were included: 148(44.7%) had preoperative DVT, and 143 (96.6%) had DVT in the first 3days after admission. The probability of DVT was 0.42 on Day 1, 0.11 on Day 2, 0.10 on Day 3, 0.08 on Day 4, 0.20 on Day 5, and 0.00 on Day 6-7, with a median survival time of 3.30 d. Age>70 years, intertrochanteric fracture, admission hemoglobin<130g/L, and admission hematocrit<40% had a significantly higher occurrence rate of DVT. A hematocrit level of <40% (Hazard Ratio 2.079, 95% Confidence Interval:1.148-3.764, P = 0.016) was an independent risk factor for DVT. CONCLUSION: DVT after hip fractures mainly occurred in the first three days after admission, the trend was stabilized within one week, and day 1 had the highest rate of DVT incidence. Age, fracture type, HGB level, and Hct level affected dynamic occurrence of DVT. At constant other factors, Hct<40% was 2.079-fold incidence in the risk of preoperative DVT formation than those with Hct≥40% after hip fracture.

MRISegmentator-Abdomen: A Fully Automated Multi-Organ and Structure Segmentation Tool for T1-weighted Abdominal MRI.

BACKGROUND: Segmentation of organs and structures in abdominal MRI is useful for many clinical applications, such as disease diagnosis and radiotherapy. Current approaches have focused on delineating a limited set of abdominal structures (13 types). To date, there is no publicly available abdominal MRI dataset with voxel-level annotations of multiple organs and structures. Consequently, a segmentation tool for multi-structure segmentation is also unavailable. METHODS: We curated a T1-weighted abdominal MRI dataset consisting of 195 patients who underwent imaging at National Institutes of Health (NIH) Clinical Center. The dataset comprises of axial pre-contrast T1, arterial, venous, and delayed phases for each patient, thereby amounting to a total of 780 series (69,248 2D slices). Each series contains voxel-level annotations of 62 abdominal organs and structures. A 3D nnUNet model, dubbed as MRISegmentator-Abdomen (MRISegmentator in short), was trained on this dataset, and evaluation was conducted on an internal test set and two large external datasets: AMOS22 and Duke Liver. The predicted segmentations were compared against the ground-truth using the Dice Similarity Coefficient (DSC) and Normalized Surface Distance (NSD). FINDINGS: MRISegmentator achieved an average DSC of 0.861$\pm$0.170 and a NSD of 0.924$\pm$0.163 in the internal test set. On the AMOS22 dataset, MRISegmentator attained an average DSC of 0.829$\pm$0.133 and a NSD of 0.908$\pm$0.067. For the Duke Liver dataset, an average DSC of 0.933$\pm$0.015 and a NSD of 0.929$\pm$0.021 was obtained. INTERPRETATION: The proposed MRISegmentator provides automatic, accurate, and robust segmentations of 62 organs and structures in T1-weighted abdominal MRI sequences. The tool has the potential to accelerate research on various clinical topics, such as abnormality detection, radiotherapy, disease classification among others.

Research on domain ontology construction based on the content features of online rumors.

Online rumors are widespread and difficult to identify, which bring serious harm to society and individuals. To effectively detect and govern online rumors, it is necessary to conduct in-depth semantic analysis and understand the content features of rumors. This paper proposes a TFI domain ontology construction method, which aims to achieve semantic parsing and reasoning of the rumor text content. This paper starts from the term layer, the frame layer, and the instance layer, and based on the reuse of the top-level ontology, the extraction of core literature content features, and the discovery of new concepts in the real corpus, obtains the core classes (five parent classes and 88 subclasses) of the rumor domain ontology and defines their concept hierarchy. Object properties and data properties are designed to describe relationships between entities or their features, and the instance layer is created according to the real rumor datasets. OWL language is used to encode the ontology, Protégé is used to visualize it, and SWRL rules and pellet reasoner are used to mine and verify implicit knowledge of the ontology, and judge the category of rumor text. This paper constructs a rumor domain ontology with high consistency and reliability.

The microRNA408-plantacyanin module balances plant growth and drought resistance by regulating reactive oxygen species homeostasis in guard cells.

The conserved microRNA (miRNA) miR408 enhances photosynthesis and compromises stress tolerance in multiple plants, but the cellular mechanism underlying its function remains largely unclear. Here, we show that in Arabidopsis (Arabidopsis thaliana), the transcript encoding the blue copper protein PLANTACYANIN (PCY) is the primary target for miR408 in vegetative tissues. PCY is preferentially expressed in the guard cells, and PCY is associated with the endomembrane surrounding individual chloroplasts. We found that the MIR408 promoter is suppressed by multiple abscisic acid (ABA)-responsive transcription factors, thus allowing PCY to accumulate under stress conditions. Genetic analysis revealed that PCY elevates reactive oxygen species (ROS) levels in the guard cells, promotes stomatal closure, reduces photosynthetic gas exchange, and enhances drought resistance. Moreover, the miR408-PCY module is sufficient to rescue the growth and drought tolerance phenotypes caused by gain- and loss-of-function of MYB44, an established positive regulator of ABA responses, indicating that the miR408-PCY module relays ABA signaling for regulating ROS homeostasis and drought resistance. These results demonstrate that miR408 regulates stomatal movement to balance growth and drought resistance, providing a mechanistic understanding of why miR408 is selected during land plant evolution and insights into the long-pursued quest of breeding drought-tolerant and high-yielding crops.

Association of systemic chronic inflammation during pregnancy in different periods and its trajectories with preterm birth.

PROBLEM: Systemic chronic inflammation (SCI) is a prevalent characteristic observed in various diseases originating from different tissues, while the association of SCI with preterm birth (PTB) remains uncertain. This study aimed to analyze the association between a nonspecific biomarker of SCI and PTB, while also exploring the trajectories of SCI in pregnant women at risk of PTB. METHOD OF STUDY: The study used data from the Electronic Medical Record System (EMRS) of a hospital in Zhejiang, China and 9226 pregnant women were included. The duration of pregnancy was categorized into four distinct periods: the first, early-second, late-second, and third trimester. Latent class trajectory modeling (LCTM) was used to identify the trajectories of SCI during pregnancy. RESULTS: The elevated WBC counts in the late-second (OR = 1.14, 95% CI: 1.06-1.23) and third (OR = 1.16, 95% CI: 1.09-1.24) trimester were both positively associated with an evaluated risk of PTB. Moreover, significant dose-response relationships were observed. There were three distinct SCI trajectories found: progressing SCI (2.89%), high SCI (7.13%), and low SCI (89.98%). Pregnant women with progressive SCI had the highest risk of PTB (OR = 3.03, 95% CI: 1.47-6.25). CONCLUSIONS: In conclusion, elevated SCI after 23 weeks was a risk factor for PTB in healthy women, even if the SCI indicator was within normal range. Pregnant women with progressive SCI during pregnancy had the highest risk of PTB.

Phase 2 Study of Preoperative Tislelizumab in Combination with Low-dose Nab-Paclitaxel in Patients with Muscle-invasive Bladder Cancer.

BACKGROUND AND OBJECTIVE: Combinations of immune checkpoint inhibitors and nab-paclitaxel have achieved significant therapeutic effects in the treatment of advanced urothelial carcinoma. Our aim was to assess the efficacy and safety of tislelizumab combined with low-dose nab-paclitaxel in patients with muscle-invasive bladder cancer (MIBC). METHODS: TRUCE-01 was a single-arm phase 2 study that included 62 patients with T2-4a N0/X M0 MIBC tumors with predominant urothelial carcinoma histology. Eligible patients received three 21-d cycles of intravenous 200 mg tislelizumab on day 1 plus intravenous 200 mg nab-paclitaxel on day 2, followed by surgical assessment. The primary study endpoint was a clinical complete response (cCR). Treatment-related adverse event (TRAE) profiles were recorded according to Common Terminology Criteria for Adverse Events version 5.0. KEY FINDINGS AND LIMITATIONS: The safety analysis included all 62 patients and the efficacy analysis included 48 patients. The primary efficacy endpoint (cCR) was met by 25 patients (52%) patients. Among the 62 patients in the safety analysis, six (9.7%) had grade ≥3 TRAEs. CONCLUSIONS: Tislelizumab combined with low-dose nab-paclitaxel showed promising antitumor effectiveness and was generally well tolerated, which makes it an excellent preoperative therapy option for MIBC. PATIENT SUMMARY: We found that a combination of the drugs tislelizumab and low-dose nab-paclitaxel had satisfactory efficacy and safety for preoperative treatment of muscle-invasive bladder cancer.

A non-invasive method to determine core temperature for cats and dogs using surface temperatures based on machine learning.

BACKGROUND: Rectal temperature (RT) is an important index of core temperature, which has guiding significance for the diagnosis and treatment of pet diseases. OBJECTIVES: Development and evaluation of an alternative method based on machine learning to determine the core temperatures of cats and dogs using surface temperatures. ANIMALS: 200 cats and 200 dogs treated between March 2022 and May 2022. METHODS: A group of cats and dogs were included in this study. The core temperatures and surface body temperatures were measured. Multiple machine learning methods were trained using a cross-validation approach and evaluated in one retrospective testing set and one prospective testing set. RESULTS: The machine learning models could achieve promising performance in predicting the core temperatures of cats and dogs using surface temperatures. The root mean square errors (RMSE) were 0.25 and 0.15 for cats and dogs in the retrospective testing set, and 0.15 and 0.14 in the prospective testing set. CONCLUSION: The machine learning model could accurately predict core temperatures for companion animals of cats and dogs using easily obtained body surface temperatures.

Type II diabetes mellitus increases the risk of inflammatory bowel disease in a prospective cohort study.

BACKGROUND: Inflammatory bowel disease is a common digestive disorder and diabetes can lead to intestinal dysfunction. Patients with inflammatory bowel disease in combination with diabetes present a higher rate of hospitalization and consumption of medical resources, yet the association between type 2 diabetes and Inflammatory bowel disease remains unknown. METHODS: We studied 313,008 participants from the UK Biobank, including 5891 patients with type 2 diabetes at baseline. Multivariate Cox proportional risk models were constructed to examine the risks associated with type 2 diabetes and inflammatory bowel disease and its subtypes (Crohn's disease, ulcerative colitis). Potential confounders including sociodemographic, lifestyle, physical body indicators, psychological state, hypertension, and thyroid-related disorders were adjusted. Propensity score matching was also performed to analyze their sensitivity. RESULTS: Of a total of 313,008 participants included in the study, 5891 (1.88 %) were diagnosed with type 2 diabetes mellitus at baseline and 1829 (0.58 %) of the entire cohort developed inflammatory bowel disease during follow-up, with a median follow-up time of 13.72 years. Patients with type 2 diabetes had a higher cumulative risk of inflammatory bowel disease compared to the non-type 2 diabetes population (inflammatory bowel disease: 1.24% vs. 0.57%, p < 0.001; Crohn's disease: 0.46% vs. 0.15%, p < 0.001; ulcerative colitis: 0.73% vs. 0.35%, p < 0.001). Multivariate Cox regression analysis showed that type 2 diabetes was independently associated with inflammatory bowel disease (Hazard Ratio: 1.61 [95% Confidence Interval: 1.26-2.06], p < 0.001), Crohn's disease (Hazard Ratio: 2.10 [95% Confidence Interval: 1.39-3.17], p < 0.001) and ulcerative colitis (Hazard Ratio: 1.58 [95% Confidence Interval: 1.15-2.18], p = 0.005). In a propensity-matched analysis, type 2 diabetes still showed its ability to predict the risk of inflammatory bowel disease (Hazard Ratio: 2.09 [95% Confidence Interval: 1.55-2.83], p < 0.001), Crohn's disease (Hazard Ratio: 3.49 [95% Confidence Interval: 2.00 to 6.09], p < 0.001), and ulcerative colitis (Hazard Ratio: 1.76 [95% Confidence Interval: 1.20 to 2.56], p = 0.003) of robustness. CONCLUSION: In patients with type 2 diabetes mellitus, the risk of inflammatory bowel disease is higher, and the presence of gastrointestinal symptoms in patients with type 2 diabetes requires vigilance for the possibility of inflammatory bowel disease in clinical practice.

Associations of maternal liver biomarkers in the first trimester with the risk of hypertensive disorders of pregnancy.

This study aimed to evaluate the association between maternal liver biomarkers in early pregnancy and the risk of hypertensive disorders of pregnancy (HDP), as well as to evaluate interaction between liver enzymes and BMI on the development of HDP. Pregnant women in our study were recruited from the Zhoushan Pregnant Women Cohort. Participants who had their first prenatal follow-up and the blood pressure follow-up records, and measured liver biomarkers in the first trimester were eligible for inclusion in the study. A total of 10,610 pregnant women were included in the analysis, and 305 (2.87%) developed the HDP. There were positive associations between AST, GGT, ALP, HSI and SBP, as well as between ALT, GGT, ALP, HSI and DBP. In addition, AST/ALT level was negatively associated with DBP. The highest quartile of GGT, ALP, AST/ALT and HSI were significantly associated with 1.71-fold (95% Cl: 1.23-2.41), 1.53-fold (95% Cl: 1.10-2.14), 0.62-fold (95% Cl: 0.43-0.90) and 1.67-fold (95% Cl: 1.05-2.67) increased risk of HDP, respectively. There was no significant association between ALT, AST and HDP. These associations remained consistent in pregnant women with liver enzymes within the clinical reference range. Besides, we found an interaction between GGT and BMI (Pinteraction = 0.013) in the development of HDP. In summary, the level of GGT, ALP, AST/ALT and HSI were associated with the subsequent risk of HDP, even within the clinical reference range. And there was an interaction between liver biomarkers and BMI in the development of HDP. Our study showed the level of GGT, ALP, AST/ALT and HSI were associated with the subsequent risk of HDP. And there was an interaction between GGT and BMI in the risk of HDP.