Nomogram for predicting the risk of anxiety and depression in patients with non-mild burns.

BACKGROUND: Post-burn anxiety and depression affect considerably the quality of life and recovery of patients; however, limited research has demonstrated risk factors associated with the development of these conditions. AIM: To predict the risk of developing post-burn anxiety and depression in patients with non-mild burns using a nomogram model. METHODS: We enrolled 675 patients with burns who were admitted to The Second Affiliated Hospital, Hengyang Medical School, University of South China between January 2019 and January 2023 and met the inclusion criteria. These patients were randomly divided into development (n = 450) and validation (n = 225) sets in a 2:1 ratio. Univariate and multivariate logistic regression analyses were conducted to identify the risk factors associated with post-burn anxiety and depression diagnoses, and a nomogram model was constructed. RESULTS: Female sex, age < 33 years, unmarried status, burn area ≥ 30%, and burns on the head, face, and neck were independent risk factors for developing post-burn anxiety and depression in patients with non-mild burns. The nomogram model demonstrated predictive accuracies of 0.937 and 0.984 for anxiety and 0.884 and 0.923 for depression in the development and validation sets, respectively, and good predictive performance. Calibration and decision curve analyses confirmed the clinical utility of the nomogram. CONCLUSION: The nomogram model predicted the risk of post-burn anxiety and depression in patients with non-mild burns, facilitating the early identification of high-risk patients for intervention and treatment.

A Comprehensive Analysis of LYAR in Colorectal Cancer: Prognostic Marker and Therapeutic Target.

Background: Colorectal cancer (CRC) is a major global health challenge with a need for new biomarkers and therapeutic targets. This work aimed to investigate the biological mechanisms and clinical value of Ly1 antibody reactive (LYAR) in CRC. Methods: We analyzed LYAR mRNA expression across multiple public databases, including genotype-tissue expression, gene expression omnibus, Oncomine, and the cancer genome atlas, alongside in-house immunohistochemical data to evaluate LYAR protein expression in CRC and non-CRC colorectal tissues. Gene set enrichment analysis (GSEA) was used to elucidate LYAR's biological functions, and its impact on the tumor immune microenvironment was assessed using CIBERSORT, ESTIMATE, and single-cell RNA sequencing techniques. In addition, LYAR's association with clinicopathological features and patient prognosis was explored, and its influence on drug sensitivity was investigated using the Connectivity Map database. Results: LYAR was significantly upregulated in CRC tissues compared with non-CRC colorectal counterparts, associated with altered immune cell composition and enhanced RNA processing, splicing, and cell cycle regulation. High LYAR expression correlated with poor disease-free and overall survival, underscoring its prognostic value. GSEA revealed LYAR's involvement in critical cellular processes and pathways, including DNA repair, cell cycle, and mTORC1 signaling. Correlation analysis identified genes positively and negatively associated with LYAR, leading to the discovery of temsirolimus and WYE-354, mTOR inhibitors, as potential therapeutic agents for CRC. Furthermore, LYAR expression predicted increased sensitivity to cetuximab in RAS wild-type metastatic CRC, indicating its utility as a biomarker for treatment responsiveness. Conclusions: LYAR's upregulation in CRC highlights its potential as a biomarker for prognosis and therapeutic targeting, offering insights into CRC pathology and suggesting new avenues for treatment optimization.

Quaternary phosphonium AIEgens nanoparticles as innovative agents for developing latent fingerprints.

Quaternary phosphonium salts, a significant category of organophosphorus compounds, have garnered substantial attention from chemists due to their wide range of applications across various research areas. These compounds are utilized in organic synthesis, catalysis, medicinal chemistry, natural materials, and coordination chemistry. Their versatility and effectiveness in these fields make them valuable tools in scientific research. Despite their extensive use in various applications, the potential of quaternary phosphonium compounds as fluorescent agents for revealing latent fingerprints (LFPs) remains largely unexplored, presenting an exciting opportunity for further research and development in forensic science. In this study, we designed molecules that combine the aggregation-induced emission (AIE) chromophore with triphenylphosphine to create a series of novel AIE amphiphiles, namely TPP1, TPP2, and TPP3. Through precise adjustment of the carbon chain length between the phenoxy group and the terminal triphenylphosphine, we were able to finely tune the nanostructures and hydrophobicity of the materials. TPP3 emerged as the optimal candidate, possessing the ideal particle size and hydrophobicity to effectively bind to LFPs, thus enabling efficient fingerprint visualization with enhanced fluorescence upon aggregation. Our findings introduce an innovative approach to fingerprint visualization, offering high selectivity, superior imaging of level 3 structures, and long-term effectiveness (up to 30 days). Additionally, TPP3's outstanding performance in imaging level 3 structures of LFPs is beneficial for analyzing incomplete LFPs and identifying individuals. By significantly improving the detection and analysis of LFPs, this approach ensures more accurate and reliable identification, making it invaluable for forensic investigations and security measures. The adaptability of these compounds to various fingerprint surfaces highlights their potential in diverse practical applications, enhancing their utility in both forensic science and security fields. This versatility allows for precise fingerprint visualization across different scenarios, making them a critical tool for advancing biometric and security technologies.

Shoutai Wan treatment upregulates the expression of TNFAIP3 and improves T cell immune tolerance at maternal-fetal interface.

Shoutai Wan (STW) is a traditional Chinese medicine formula used to treat various conditions. The objective of this study was to evaluate the impact of STW on the abortion rate in the URSA mouse model and elucidate its underlying molecular mechanisms. Female CBA/J mice were mated with male DBA/2 mice to establish the URSA model. Network pharmacological analysis was employed to investigate the potential molecular mechanisms of STW. Hematoxylin-eosin staining, immunofluorescence, and ELISA were performed to examine placental microenvironmental changes, protein expression related to TNFAIP3 and the NF-κB signaling pathway. Treatment with STW reduced the abortion rate in URSA model mice and improved trophoblast development. TNFAIP3 was identified as a potential target of STW for treating URSA, as STW enhanced TNFAIP3 protein expression while decreasing IL-6 and TNF-α secretion in the placenta. Moreover, STW upregulated TNFAIP3 protein expression and Foxp3 mRNA levels, increased the production of anti-inflammatory cytokines such as IL-10 and TGF-ß1, and decreased p-NF-κB expression in CD4+ cells at the placenta. The findings of this study indicate that STW treatment reduces the abortion rate in the URSA mouse model. These effects are likely mediated by increased TNFAIP3 expression and decreased NF-κB signaling pathway activity at the maternal-fetal interface. These molecular changes may contribute to the regulation of T cell immunity and immune tolerance during pregnancy.

A Shape-Consistent Deep-Learning Segmentation Architecture for Low-Quality and High-Interference Myocardial Contrast Echocardiography.

OBJECTIVE: Myocardial contrast echocardiography (MCE) plays a crucial role in diagnosing ischemia, infarction, masses and other cardiac conditions. In the realm of MCE image analysis, accurate and consistent myocardial segmentation results are essential for enabling automated analysis of various heart diseases. However, current manual diagnostic methods in MCE suffer from poor repeatability and limited clinical applicability. MCE images often exhibit low quality and high noise due to the instability of ultrasound signals, while interference structures can further disrupt segmentation consistency. METHODS: To overcome these challenges, we proposed a deep-learning network for the segmentation of MCE. This architecture leverages dilated convolutions to capture high-scale information without sacrificing positional accuracy and modifies multi-head self-attention to enhance global context and ensure consistency, effectively overcoming issues related to low image quality and interference. Furthermore, we also adapted the cascade application of transformers with convolutional neural networks for improved segmentation in MCE. RESULTS: In our experiments, our architecture achieved the best Dice score of 84.35% for standard MCE views compared with that of several state-of-the-art segmentation models. For non-standard views and frames with interfering structures (mass), our models also attained the best Dice scores of 83.33% and 83.97%, respectively. CONCLUSION: These studies proved that our architecture is of excellent shape consistency and robustness, which allows it to deal with segmentation of various types of MCE. Our relatively precise and consistent myocardial segmentation results provide fundamental conditions for the automated analysis of various heart diseases, with the potential to discover underlying pathological features and reduce healthcare costs.

Improving Nowcasting of Intense Convective Precipitation by Incorporating Dual-Polarization Radar Variables into Generative Adversarial Networks.

The nowcasting of strong convective precipitation is highly demanded and presents significant challenges, as it offers meteorological services to diverse socio-economic sectors to prevent catastrophic weather events accompanied by strong convective precipitation from causing substantial economic losses and human casualties. With the accumulation of dual-polarization radar data, deep learning models based on data have been widely applied in the nowcasting of precipitation. Deep learning models exhibit certain limitations in the nowcasting approach: The evolutionary method is prone to accumulate errors throughout the iterative process (where multiple autoregressive models generate future motion fields and intensity residuals and then implicitly iterate to yield predictions), and the "regression to average" issue of autoregressive model leads to the "blurring" phenomenon. The evolution method's generator is a two-stage model: In the initial stage, the generator employs the evolution method to generate the provisional forecasted data; in the subsequent stage, the generator reprocesses the provisional forecasted data. Although the evolution method's generator is a generative adversarial network, the adversarial strategy adopted by this model ignores the significance of temporary prediction data. Therefore, this study proposes an Adversarial Autoregressive Network (AANet): Firstly, the forecasted data are generated via the two-stage generators (where FURENet directly produces the provisional forecasted data, and the Semantic Synthesis Model reprocesses the provisional forecasted data); Subsequently, structural similarity loss (SSIM loss) is utilized to mitigate the influence of the "regression to average" issue; Finally, the two-stage adversarial (Tadv) strategy is adopted to assist the two-stage generators to generate more realistic and highly similar generated data. It has been experimentally verified that AANet outperforms NowcastNet in the nowcasting of the next 1 h, with a reduction of 0.0763 in normalized error (NE), 0.377 in root mean square error (RMSE), and 4.2% in false alarm rate (FAR), as well as an enhancement of 1.45 in peak signal-to-noise ratio (PSNR), 0.0208 in SSIM, 5.78% in critical success index (CSI), 6.25% in probability of detection (POD), and 5.7% in F1.

2,2'-Bisdinitromethyl-5,5'-bistetrazole: A High-Performance, Multi-Nitro Energetic Material with Excellent Oxygen Balance.

Bistetrazoles are highly sought after for developing innovative high-energy density materials. The 1,1'-substituted bistetrazoles, exemplified by TKX-50, have outstanding performance. However, the research of high-perfomance 2,2'-substituted bistetrazoles remains limited. In this work, dinitromethyl groups were introduced into bistetrazole structures as 2,2'-substituted bistetrazoles (BDBTZ), which was extensively characterized through NMR, thermal analysis, and single crystal X-ray diffraction, exhibiting excellent oxygen balance, moderate sensitivity, acceptable thermal stability, high crystal density, and excellent detonation performance.

Atrial tachyarrhythmia prevention by Shensong Yangxin after catheter ablation for persistent atrial fibrillation: the SS-AFRF trial.

BACKGROUND AND AIMS: Despite advances in technology and techniques, the recurrence rate of persistent atrial fibrillation (AF) following catheter ablation remains high. The Shensong Yangxin (SSYX) capsule, a renowned traditional Chinese medicine formula, is used in the treatment of cardiac arrhythmias. This trial aimed to investigate whether the SSYX can improve clinical outcomes in patients who have undergone catheter ablation for persistent AF. METHODS: A multi-centre, randomized, double-blind, placebo-controlled clinical trial was conducted at 66 centres in China among 920 patients with persistent AF undergoing first ablation. Participants were randomized to oral SSYX, 1.6 g (.4 g/granule) thrice daily (n = 460), or matched placebo (n = 460) for 12 months. The primary endpoint was recurrent atrial tachyarrhythmias lasting for ≥30 s following a blanking period of 3 months. Secondary endpoints included time to first documented atrial tachyarrhythmias, AF burden, cardioversion, stroke/systemic embolism, changes in echocardiographic parameters, and quality-of-life (QoL) score. Analyses were performed according to the intention-to-treat principle. RESULTS: A total of 920 patients underwent randomization (460 assigned to SSYX group and 460 assigned to placebo group). During the follow-up of 12 months, patients assigned to SSYX had a higher event-free rate from recurrent atrial tachyarrhythmias when compared with the placebo group (12-month Kaplan-Meier event-free rate estimates, 85.5% and 77.7%, respectively; hazard ratio, .6; 95% confidence interval .4-.8; P = .001). Patients assigned to receive SSYX had a better QoL score at 12 months compared to those randomized to placebo. There was no significant difference in the incidence of serious adverse events between the two groups. CONCLUSIONS: Treatment with SSYX following radiofrequency catheter ablation for persistent AF reduced the incidence of recurrent atrial tachyarrhythmias and led to clinically significant improvements in QoL during a 12-month follow-up in a Chinese population.

Targeting mitochondrial quality control: new therapeutic strategies for major diseases.

Mitochondria play a crucial role in maintaining the normal physiological state of cells. Hence, ensuring mitochondrial quality control is imperative for the prevention and treatment of numerous diseases. Previous reviews on this topic have however been inconsistencies and lack of systematic organization. Therefore, this review aims to provide a comprehensive and systematic overview of mitochondrial quality control and explore the possibility of targeting the same for the treatment of major diseases. This review systematically summarizes three fundamental characteristics of mitochondrial quality control, including mitochondrial morphology and dynamics, function and metabolism, and protein expression and regulation. It also extensively examines how imbalances in mitochondrial quality are linked to major diseases, such as ischemia-hypoxia, inflammatory disorders, viral infections, metabolic dysregulations, degenerative conditions, and tumors. Additionally, the review explores innovative approaches to target mitochondrial quality control, including using small molecule drugs that regulate critical steps in maintaining mitochondrial quality, nanomolecular materials designed for precise targeting of mitochondria, and novel cellular therapies, such as vesicle therapy and mitochondrial transplantation. This review offers a novel perspective on comprehending the shared mechanisms underlying the occurrence and progression of major diseases and provides theoretical support and practical guidance for the clinical implementation of innovative therapeutic strategies that target mitochondrial quality control for treating major diseases.

Exploring the Analgesic Efficacy and mechanisms of low-dose esketamine in pregnant women undergoing cesarean section: A randomized controlled trial.

Background: Postoperative pain is a prevalent concern following a cesarean section. This study aimed to investigate the effect and mechanism of low-dose (0.1 mg/kg) esketamine on postoperative pain management in pregnant women undergoing cesarean sections, specifically in cases where both patient-controlled intravenous analgesia (PCIA) and patient-controlled epidural analgesia (PCEA) were employed. Methods: Pregnant women intending to undergo elective cesarean section were divided into four subgroups based on the intravenous administration of esketamine and the specific analgesia methods employed: E1 (0.1 mg/kg esketamine + PCEA), E2 (0.1 mg/kg esketamine + PCIA), C1 (saline + PCEA), and C2 (saline + PCIA). The primary outcome was the maximum pain score within 24 h postoperatively. Secondary outcomes included the pressure pain threshold and tolerance at 30 min and 24 h postoperatively, along with the inflammation and adverse event index scores. Results: A total of 118 pregnant women were assigned to the four groups: E1 (n = 29), E2 (n = 29), C1 (n = 30), and C2 (n = 30). Compared with those in the control groups (C1 + C2), the maximum postoperative pain scores within 24 h in the esketamine groups (E1 + E2) were significantly lower (4 [2-5] vs. 4 [4-6], P = 0.002), and the E1 group exhibited superior analgesic effects compared with other groups. No significant differences were observed in postoperative hyperalgesia or inflammation across the four groups. Notably, esketamine combined with PCIA increased the incidence of postoperative nausea and vomiting (7 [25 %] vs. 0 [0 %]; P = 0.005). Conclusion: The administration of low-dose (0.1 mg/kg) esketamine effectively alleviates pain following cesarean section, and the analgesic effect is notably enhanced in combination with PCEA. Importantly, these effects do not appear to be mediated through anti-inflammatory mechanisms or the inhibition of hyperalgesia. Clinical trial registration number: NCT05414006.

Data-driven rapid detection of Helicobacter pylori infection through machine learning with limited laboratory parameters in Chinese primary clinics.

Background: Helicobacter pylori (H. pylori) is a significant global health concern, posing a high risk for gastric cancer. Conventional diagnostic and screening approaches are inaccessible, invasive, inaccurate, time-consuming, and expensive in primary clinics. Objective: This study aims to apply machine learning (ML) models to detect H. pylori infection using limited laboratory parameters from routine blood tests and to investigate the association of these biomarkers with clinical outcomes in primary clinics. Methods: A retrospective analysis with three ML and five ensemble models was conducted on 1409 adults from Hubei Provincial Hospital of Traditional Chinese Medicine. evaluating twenty-three blood test parameters and using the C 14 urea breath test as the gold standard for diagnosing H. pylori infection. Results: In our comparative study employing three different feature selection strategies, Random Forest (RF) model exhibited superior performance over other ML and ensemble models. Multiple evaluation metrics underscored the optimal performance of the RF model (ROC = 0.951, sensitivity = 0.882, specificity = 0.906, F1 = 0.906, accuracy = 0.894, PPV = 0.908, NPV = 0.880) without feature selection. Key biomarkers identified through importance ranking and shapley additive Explanations (SHAP) analysis using the RF model without feature selection include White Blood Cell Count (WBC), Mean Platelet Volume (MPV), Hemoglobin (Hb), Red Blood Cell Count (RBC), Platelet Crit (PCT), and Platelet Count (PLC). These biomarkers were found to be significantly associated with the presence of H. pylori infection, reflecting the immune response and inflammation levels. Conclusion: Abnormalities in key biomarkers could prompt clinical workers to consider H. pylori infection. The RF model effectively identifies H. pylori infection using routine blood tests, offering potential for clinical application in primary clinics. This ML approach can enhance diagnosis and screening, reducing medical burdens and reliance on invasive diagnostics.

Predicting prognosis outcomes of primary central nervous system lymphoma with high-dose methotrexate-based chemotherapeutic treatment using lipidomics.

Background: Primary central nervous system lymphoma (PCNSL) is a rare extranodal lymphomatous malignancy which is commonly treated with high-dose methotrexate (HD-MTX)-based chemotherapy. However, the prognosis outcome of HD-MTX-based treatment cannot be accurately predicted using the current prognostic scoring systems, such as the Memorial Sloan-Kettering Cancer Center (MSKCC) score. Methods: We studied 2 cohorts of patients with PCNSL and applied lipidomic analysis to their cerebrospinal fluid (CSF) samples. After removing the batch effects and features engineering, we applied and compared several classic machine-learning models based on lipidomic data of CSF to predict the relapse of PCNSL in patients who were treated with HD-MTX-based chemotherapy. Results: We managed to remove the batch effects and get the optimum features of each model. Finally, we found that Cox regression had the best prediction performance (AUC = 0.711) on prognosis outcomes. Conclusions: We developed a Cox regression model based on lipidomic data, which could effectively predict PCNSL patient prognosis before the HD-MTX-based chemotherapy treatments.

Controlled Reversible N-Terminal Modification of Peptides and Proteins.

A reversible modification strategy enables a switchable cage/decage process of proteins with an array of applications for protein function research. However, general N-terminal selective reversible modification strategies which present site selectivity are specifically limited. Herein, we report a general reversible modification strategy compatible with 20 canonical amino acids at the N-terminal site by the palladium-catalyzed cinnamylation of native peptides and proteins under biologically relevant conditions. This approach broadens the substrate adaptability of N-terminal modification of proteins and shows a potential impact on the more challenging protein substrates such as antibodies. In the presence of 1,3-dimethylbarbituric acid, palladium-catalyzed deconjugation released native peptides and proteins efficiently. Harnessing the reversible nature of this protocol, practical applications were demonstrated by precise function modulation of antibodies and traceless enrichment of the protein-of-interest for proteomics analysis. This novel on/off strategy working on the N-terminus will provide new opportunities in chemical biology and medicinal research.

Symbiotic biofilms formed by Clostridioides difficile and bacteroides thetaiotaomicron in the presence of vancomycin.

Vancomycin (VAN) treatment in Clostridioides difficile infection (CDI) suffers from a relatively high rate of recurrence, with a variety of reasons behind this, including biofilm-induced recurrent infections. C. difficile can form monophyletic or symbiotic biofilms with other microbes in the gut, and these biofilms protect C. difficile from being killed by antibiotics. In this study, we analyzed the ecological relationship between Bacteroides thetaiotaomicron and C. difficile and their formation of symbiotic biofilm in the VAN environment. The production of symbiotic biofilm formed by C. difficile and B. thetaiotaomicron was higher than that of C. difficile and B. thetaiotaomicron alone in the VAN environment. In symbiotic biofilms, C. difficile was characterized by increased production of the toxin protein TcdA and TcdB, up-regulation of the expression levels of the virulence genes tcdA and tcdB, enhanced bacterial cell swimming motility and c-di-GMP content, and increased adhesion to Caco-2 cells. The scanning electron microscope (SEM) combined with confocal laser scanning microscopy (CLSM) results indicated that the symbiotic biofilm was elevated in thickness, dense, and had an increased amount of mixed bacteria, while the fluorescence in situ hybridization (FISH) probe and plate colony counting results further indicated that the symbiotic biofilm had a significant increase in the amount of C. difficile cells, and was able to better tolerate the killing of the simulated intestinal fluid. Taken together, C. difficile and B. thetaiotaomicron become collaborative in the VAN environment, and targeted deletion or attenuation of host gut B. thetaiotaomicron content may improve the actual efficacy of VAN in CDI treatment.

Ubiquitin-specific protease 38 promotes atrial fibrillation in diabetic mice by stabilizing iron regulatory protein 2.

BACKGROUND: Atrial fibrillation (AF) is a common cardiovascular disease often observed in diabetes mellitus, and there is currently no satisfactory therapeutic option. Ubiquitin-specific protease 38 (USP38) has been implicated in the degradation of numerous substrate proteins in the myocardium. Herein, we aim to investigate the role of USP38 in AF induced by diabetes. METHODS: Cardiac-specific transgenic USP38 mice and cardiac-specific knockout USP38 mice were constructed, and streptozotocin was used to establish diabetic mouse model. Functional, electrophysiological, histologic, biochemical studies were performed. RESULTS: The expression of USP38 was upregulated in atrial tissues of diabetic mice and HL-1 cells exposed to high glucose. USP38 overexpression increased susceptibility to AF, accompanied by aberrant expression of calcium-handling protein, heightened iron load and oxidation stress in diabetic mice. Conversely, USP38 deficiency reduced vulnerability to AF by hampering ferroptosis. Mechanistically, USP38 bound to iron regulatory protein 2 (IRP2), stabilizing it and remove K48-linked polyubiquitination chains, thereby increasing intracellular iron overload, lipid peroxidation, and ultimately contributing to ferroptosis. In addition, reduced iron overload by deferoxamine treatment alleviated oxidation stress and decreased vulnerability to AF in diabetic mice. CONCLUSION: Overall, our findings reveal the detrimental role of USP38 in diabetes-related AF, manifested by increased level of iron overload and oxidation stress.

Manipulation of Exchange Bias in Two-Dimensional van der Waals Ferromagnet Near Room Temperature.

As a host for exchange bias (EB), van der Waals (vdW) magnetic materials have exhibited intriguing and distinct functionalities from conventional magnetic materials. The EB in most vdW systems is far below room temperature, which poses a challenge for practical applications. Here, by using Kerr microscopy, we demonstrate a record-high blocking temperature that approaches room temperature and a huge positive EB field that nears 2 kOe at 100 K in naturally oxidized two-dimensional (2D) vdW ferromagnetic Fe3GaTe2 nanoflakes. Moreover, we realized a reversible manipulation of both the presence/absence and positive/negative signs of EB via a training magnetic field without multiple field cooling processes. Thus, our study clearly reveals the robust, sizable, and sign-tunable EB in vdW magnetic materials up to near room temperature, thereby establishing Fe3GaTe2 as an emerging room-temperature-operating vdW material and paving the way for designing practical 2D spintronic devices.

Association between frozen embryo transfer and childhood allergy: a retrospective cohort study.

RESEARCH QUESTION: Does frozen embryo transfer (FET) increase the risk of allergic diseases in offspring? DESIGN: This study followed up 653 singleton children: 166 born through FET and 487 born through natural conception. Demographic characteristics, perinatal information and allergic diseases of children and their parents were collected through clinical medical systems and questionnaires. Among these 653 children, allergen-specific immunoglobulin E (IgE) testing was performed using peripheral blood samples collected from 207 children: 145 in the FET group and 62 in the natural conception group. The prevalence of allergic diseases and positive rates of allergen-specific IgE testing were compared between the two groups with adjustments for confounding factors. RESULTS: The prevalence of food allergy was significantly higher in children born through FET compared with children born through natural conception (adjusted OR = 3.154, 95% CI 1.895-5.250; P < 0.001). In addition, positive rates of food allergen sensitization were higher in children in the FET group compared with children in the natural conception group (adjusted OR = 5.769, 95% CI 2.859-11.751, P < 0.001). Children in the FET group had a higher positive sensitization rate to at least one allergen compared with children in the natural conception group (adjusted OR = 3.127, 95% CI 1.640-5.961, P < 0.001). No association was observed between FET and other allergic diseases, including asthma (P = 0.136), atopic dermatitis (P = 0.130) and allergic rhinitis (P = 0.922). Allergen sensitization IgE testing indicated no differences between the two groups in terms of positive sensitization rates of other common allergens, including animal and insect allergens (P = 0.627), inhaled outdoor allergens (P = 0.915) and inhaled outdoor allergens (P = 0.544). CONCLUSION: This study suggests that children born through FET have increased risk of developing food allergy in early childhood.

Examination of nonlinear associations between pulse pressure index and incident prediabetes susceptibility: a 5-year retrospective cohort investigation.

Prediabetes and related complications constitute significant public health burdens globally. As an indicator closely associated with abnormal glucose metabolism and atherosclerosis, the utility of Pulse Pressure Index (PPI) as a prediabetes risk marker has not been explored. We performed a retrospective cohort analysis to investigate this putative association between PPI and prediabetes hazard. Our analysis encompassed 183,517 Chinese adults ≥ 20 years registered within the Rich Healthcare Group 2010-2016. PPI was defined as (systolic blood pressure - diastolic blood pressure)/systolic blood pressure. The relationship between PPI and prediabetes risk was assessed via Cox proportional hazards regression modeling. Non-linearity evaluations applied cubic spline fitting approaches alongside smooth curve analysis. Inflection points of PPI concerning prediabetes hazard were determined using two-piecewise Cox models. During a median follow-up of 3 years (2.17-3.96 years), new-onset prediabetes was documented in 20,607 patients (11.23%). Multivariate regression analysis showed that PPI was an independent risk factor for prediabetes, and the risk of prediabetes increased by 0.6% for every 1% increase in PPI (Hazard Ratio [HR]: 1.006, 95% Confidence Interval [CI] 1.004-1.008, P < 0.001). This association was non-significant for PPI ≤ 37.41% yet exhibited a sharp upsurge when PPI surpassed 37.41% (HR: 1.013, 95% CI 1.005-1.021, P = 0.0029). Our analysis unveils a positive, non-linear association between PPI and future prediabetes risk. Within defined PPI ranges, this relationship is negligible but dramatically elevates beyond identified thresholds.