Quantification of the Heat-Related Risk and Burden of Hospitalizations for Cause-Specific Injuries and Contribution of Human-Induced Climate Change: A Time-Stratified Case-Crossover Study in China.

BACKGROUND: Although ambient temperature has been linked with injury incidence, there have been few nationwide studies to quantify the temperature-related risk and burden of cause-specific injury hospitalizations. Additionally, the impact of human-induced climate change to injury burden remains unknown. OBJECTIVES: Our objectives are to examine the associations between ambient temperature and injury hospitalizations from various causes and to quantify the contribution of human-induced warming to the heat-related burden. METHODS: We collected injury hospitalization data from a nationwide hospital-based registry in China during 2000-2019. Using a time-stratified case-crossover design, we investigated the associations between daily mean temperature (°C) and cause-specific injury hospitalizations. We also quantified the burden of heat-related injuries under the scenarios with and without anthropogenic forcing, using the Detection and Attribution Model Intercomparison Project to assess the contribution of human-induced warming. RESULTS: Our study included a total of 988,087 patients with hospitalization records for injuries. Overall, compared to the temperature at minimum risk of hospitalization (-12.1°C), the relative risk of hospitalization at extreme hot temperature (30.8°C, 97.5th percentile) was 1.18 [95% confidence interval (CI): 1.14, 1.22], with an approximately linear association between temperature and hospitalization. Vulnerability to heat-related injuries was more pronounced among males, young (<18 years of age) or middle-aged (45-64 years of age) individuals, and those living in the North. The heat-related attributable fraction increased from 23.2% in the 2000s to 23.6% in the 2010s, with a corresponding increase in the contribution of human-induced change over time. In the 2010s, the heat-related attributable fractions for specific causes of injury ranged from 12.4% to 54.4%, with human-induced change accounting for 6.7% to 10.6% of the burden. DISCUSSION: This nationwide study presents new evidence of significant associations between temperature and cause-specific injury hospitalizations in China and highlights the increasing contribution of human-induced warming to the injury burden. https://doi.org/10.1289/EHP14057.

Study on Dynamic Mechanical Properties of Sandwich Beam with Stepwise Gradient Polymethacrylimide (PMI) Foam Core under Low-Velocity Impact.

Different PMI foam materials of 52, 110, and 200 kg/m3 were used to design stepwise gradient cores to improve the impact resistance of the sandwich beam. The stepwise gradient core consists of three layers arranged in positive gradient, negative gradient, and sandwich-core (e.g., 200/52/200). These sandwich beams were subjected to the impact of a steel projectile under impact momentum of 10 to 20 kg·m/s, corresponding to impact energy in the range of 12.5 to 50 J. During the test, the impact force was recorded by an accelerometer, and the different failure modes were also obtained. Subsequently, the influence of the layer arrangement on the energy absorption and load transfer mechanism between the different layers was analyzed. The results showed that the top layer with a large density can improve the impact force, but the middle/bottom layer with a low density promoted specific energy absorption. Thus, based on these two points, the negative gradient core (200/110/52) had an excellent specific energy absorption because it can transfer and expand the area to bear the load layer by layer, which improved the energy absorption in each layer. Combined with the failure modes, the load transfer and deformation mechanisms between the layers were also discussed. The present work provided a valuable method to design an efficient lightweight sandwich structure in the protection field.

A Theoretical Benchmark of the Geometric and Optical Properties for 3d Transition Metal Nanoclusters via Density Functional Theory.

Understanding structure-property relationships in atomically precise metal nanoclusters is vital in finding selective and tunable catalysts. In this study, density functional theory (DFT) was used to benchmark seven exchange correlation functionals at different basis sets for 17 atomically precise nanoclusters against experimentally determined geometries, band gaps, and optical gaps. The set contains both monometallic and bimetallic clusters that possess at least two types of 3d transition metals (specifically, Cu, Ni, Fe, or Co). The benchmark highlights that PBE0 is a good functional to use regardless of the basis set, and Minnesota functionals do well with respect to specific metals. Further, while long-range corrected functionals overestimate band and optical gaps, they model absorption features better than the other considered functionals. The study additionally looks at the photoinduced hydrogen evolution reaction (HER) and the CO2 reduction mechanism on nanoclusters reported from the literature.

GestaltMML: Enhancing Rare Genetic Disease Diagnosis through Multimodal Machine Learning Combining Facial Images and Clinical Texts.

Individuals with suspected rare genetic disorders often undergo multiple clinical evaluations, imaging studies, laboratory tests and genetic tests, to find a possible answer over a prolonged period of time. Addressing this "diagnostic odyssey" thus has substantial clinical, psychosocial, and economic benefits. Many rare genetic diseases have distinctive facial features, which can be used by artificial intelligence algorithms to facilitate clinical diagnosis, in prioritizing candidate diseases to be further examined by lab tests or genetic assays, or in helping the phenotype-driven reinterpretation of genome/exome sequencing data. Existing methods using frontal facial photos were built on conventional Convolutional Neural Networks (CNNs), rely exclusively on facial images, and cannot capture non-facial phenotypic traits and demographic information essential for guiding accurate diagnoses. Here we introduce GestaltMML, a multimodal machine learning (MML) approach solely based on the Transformer architecture. It integrates facial images, demographic information (age, sex, ethnicity), and clinical notes (optionally, a list of Human Phenotype Ontology terms) to improve prediction accuracy. Furthermore, we also evaluated GestaltMML on a diverse range of datasets, including 528 diseases from the GestaltMatcher Database, several in-house datasets of Beckwith-Wiedemann syndrome (BWS, over-growth syndrome with distinct facial features), Sotos syndrome (overgrowth syndrome with overlapping features with BWS), NAA10-related neurodevelopmental syndrome, Cornelia de Lange syndrome (multiple malformation syndrome), and KBG syndrome (multiple malformation syndrome). Our results suggest that GestaltMML effectively incorporates multiple modalities of data, greatly narrowing candidate genetic diagnoses of rare diseases and may facilitate the reinterpretation of genome/exome sequencing data.

LRG1 promotes the apoptosis of pulmonary microvascular endothelial cells through KLK10 in chronic obstructive pulmonary disease.

INTRODUCTION: Cigarette smoking is one of the most important causes of COPD and could induce the apoptosis of pulmonary microvascular endothelial cells (PMVECs). The conditional knockout of LRG1 from endothelial cells reduced emphysema in mice. However, the mechanism of the deletion of LRG1 from endothelial cells rescued by cigarette smoke (CS) induced emphysema remains unclear. This research aimed to demonstrate whether LRG1 promotes the apoptosis of PMVECs through KLK10 in COPD. METHODS: Nineteen patients were divided into three groups: control non-COPD (n=7), smoker non-COPD (n=7), and COPD (n=5). The emphysema mouse model defined as the CS exposure group was induced by CS exposure plus cigarette smoke extract (CSE) intraperitoneal injection for 28 days. Primary PMVECs were isolated from the mouse by magnetic bead sorting method via CD31-Dynabeads. Apoptosis was detected by western blot and flow cytometry. RESULTS: LRG1 was increased in lung tissue of COPD patients and CS exposure mice, and CSE-induced PMVECs apoptosis model. KLK10 was over-expressed in lung tissue of COPD patients and CS exposure mice, and CSE-induced PMVECs apoptosis model. LRG1 promoted apoptosis in PMVECs. LRG1 knockdown reversed CSE-induced apoptosis in PMVECs. The mRNA and protein expression of KLK10 were increased after over-expressed LRG1 in PMVECs isolated from mice. Similarly, both the mRNA and protein levels of KLK10 were decreased after LRG1 knockdown in PMVECs. The result of co-immunoprecipitation revealed a protein-protein interaction between LRG1 and KLK10 in PMVECs. KLK10 promoted apoptosis via the down-regulation of Bcl-2/Bax in PMVECs. KLK10 knockdown could reverse CSE-induced apoptosis in PMVECs. CONCLUSIONS: LRG1 promotes apoptosis via up-regulation of KLK10 in PMVECs isolated from mice. KLK10 promotes apoptosis via the down-regulation of Bcl-2/Bax in PMVECs. There was a direct protein-protein interaction between LRG1 and KLK10 in PMVECs. Our novel findings provide insights into the understanding of LRG1/KLK10 function as a potential molecule in COPD.

SAMP: Identifying Antimicrobial Peptides by an Ensemble Learning Model Based on Proportionalized Split Amino Acid Composition.

It is projected that 10 million deaths could be attributed to drug-resistant bacteria infections in 2050. To address this concern, identifying new-generation antibiotics is an effective way. Antimicrobial peptides (AMPs), a class of innate immune effectors, have received significant attention for their capacity to eliminate drug-resistant pathogens, including viruses, bacteria, and fungi. Recent years have witnessed widespread applications of computational methods especially machine learning (ML) and deep learning (DL) for discovering AMPs. However, existing methods only use features including compositional, physiochemical, and structural properties of peptides, which cannot fully capture sequence information from AMPs. Here, we present SAMP, an ensemble random projection (RP) based computational model that leverages a new type of features called Proportionalized Split Amino Acid Composition (PSAAC) in addition to conventional sequence-based features for AMP prediction. With this new feature set, SAMP captures the residue patterns like sorting signals at around both the N-terminus and the C-terminus, while also retaining the sequence order information from the middle peptide fragments. Benchmarking tests on different balanced and imbalanced datasets demonstrate that SAMP consistently outperforms existing state-of-the-art methods, such as iAMPpred and AMPScanner V2, in terms of accuracy, MCC, G-measure and F1-score. In addition, by leveraging an ensemble RP architecture, SAMP is scalable to processing large-scale AMP identification with further performance improvement, compared to those models without RP. To facilitate the use of SAMP, we have developed a Python package freely available at https://github.com/wan-mlab/SAMP.

Ruthenium red alleviates post-resuscitation myocardial dysfunction by upregulating mitophagy through inhibition of USP33 in a cardiac arrest rat model.

Cardiac arrest (CA) remains a leading cause of death, with suboptimal survival rates despite efforts involving cardiopulmonary resuscitation and advanced life-support technology. Post-resuscitation myocardial dysfunction (PRMD) is an important determinant of patient outcomes. Myocardial ischemia/reperfusion injury underlies this dysfunction. Previous reports have shown that ruthenium red (RR) has a protective effect against cardiac ischemia-reperfusion injury; however, its precise mechanism of action in PRMD remains unclear. This study investigated the effects of RR on PRMD and analyzed its underlying mechanisms. Ventricular fibrillation was induced in rats, which were then subjected to cardiopulmonary resuscitation to establish an experimental CA model. At the onset of return of spontaneous circulation, RR (2.5 mg/kg) was administered intraperitoneally. Our study showed that RR improved myocardial function and reduced the production of oxidative stress markers such as malondialdehyde (MDA), glutathione peroxidase (GSSG), and reactive oxygen species (ROS) production. RR also helped maintain mitochondrial structure and increased ATP and GTP levels. Additionally, RR effectively attenuated myocardial apoptosis. Furthermore, we observed downregulation of proteins closely related to mitophagy, including ubiquitin-specific protease 33 (USP33) and P62, whereas LC3B (microtubule-associated protein light chain 3B) was upregulated. The upregulation of mitophagy may play a critical role in reducing myocardial injury. These results demonstrate that RR may attenuate PRMD by promoting mitophagy through the inhibition of USP33. These effects are likely mediated through diverse mechanisms, including antioxidant activity, apoptosis suppression, and preservation of mitochondrial integrity and energy metabolism. Consequently, RR has emerged as a promising therapeutic approach for addressing post-resuscitation myocardial dysfunction.

Mechanistic insights into cardiovascular effects of ultrafine particle exposure: A longitudinal panel study.

BACKGROUND: Ultrafine particle (UFP) has been linked with higher risks of cardiovascular diseases; however, the biological mechanisms remain to be fully elucidated. OBJECTIVES: This study aims to investigate the cardiovascular responses to short-term UFP exposure and the biological pathways involved. METHODS: A longitudinal panel study was conducted among 32 healthy, non-smoking young adults in Shanghai, China, who were engaged in five rounds of follow-ups between December 2020 and November 2021. Individual exposures were calculated based on the indoor and outdoor real-time measurements. Blood pressure, arterial stiffness, targeted biomarkers, and untargeted proteomics and metabolomics were examined during each follow-up. Linear mixed-effect models were applied to analyze the exposure and health data. The differential proteins and metabolites were used for pathway enrichment analyses. RESULTS: Short-term UFP exposure was associated with significant increases in blood pressure and arterial stiffness. For example, systolic blood pressure increased by 2.10 % (95 % confidence interval: 0.63 %, 3.59 %) corresponding to each interquartile increase in UFP concentrations at lag 0-3 h, while pulse wave velocity increased by 2.26 % (95 % confidence interval: 0.52 %, 4.04 %) at lag 7-12 h. In addition, dozens of molecular biomarkers altered significantly. These effects were generally present within 24 h after UFP exposure, and were robust to the adjustment of co-pollutants. Molecular changes detected in proteomics and metabolomics analyses were mainly involved in systemic inflammation, oxidative stress, endothelial dysfunction, coagulation, and disturbance in lipid transport and metabolism. DISCUSSION: This study provides novel and compelling evidence on the detrimental subclinical cardiovascular effects in response to short-term UFP exposure. The multi-omics profiling further offers holistic insights into the underlying biological pathways.

Exploring the relationship between illness perception, self-management and quality of life among HIV-positive men who have sex with men.

AIMS: This study aimed to explore the mediating effect of self-management (SM) on the relationship between illness perception and quality of life (QOL) among Human immunodeficiency virus (HIV)-positive men who have sex with men (MSM). DESIGN: A cross-sectional study. METHODS: We explored the effect of illness perception and self-management on QOL using the multiple regression model. Moreover, we conducted a simple mediation analysis to examine the role of SM in the relationship between illness perception and QOL. In addition, a parallel mediation analysis was performed to investigate the differences in domains of SM on the relationship between illness perception and QOL. RESULTS: Among 300 Chinese HIV-positive MSM, the mean score of SM was 39.9 ± 6.97, with a range of 14.0-54.0. The higher score in SM indicated a higher level of HIV SM. SM was negatively related to illness perception (r = -0.47) while positively related to QOL (r = 0.56). SM partially mediated the relationship between illness perception and QOL, accounting for 25.3% of the total effect. Specifically, both daily self-management health practices and the chronic nature of the self-management domain played a parallel role in mediating the relationship between illness perception and QOL. CONCLUSION: Our study demonstrated that SM was a significant factor influencing QOL among HIV-positive MSM. Focusing on daily self-management health practices and the chronic nature of self-management could be the potential key targets for enhancing HIV self-management strategies. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: This study emphasized the role of SM in the well-being of HIV-positive MSM and underscored the importance of developing interventions that integrate SM strategies to improve QOL in this population. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Silicon Nitride Surface Enabled Propane Dehydrogenation Catalyzed by Supported Organozirconium.

Mesoporous silicon nitride (Si3N4) is a nontraditional support for the chemisorption of organometallic complexes with the potential for enhancing catalytic activity through features such as the increased Lewis basicity of nitrogen for heterolytic bond activation, increased ligand donor strength, and metal-ligand orbital overlap. Here, tetrabenzyl zirconium (ZrBn4) was chemisorbed on Si3N4, and the resulting supported organometallic species was characterized by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS), Dynamic Nuclear Polarization-enhanced Solid State Nuclear Magnetic Resonance (DNP-SSNMR), and X-ray Absorption Spectroscopy (XAS). Based on the hypothesis that the nitride might enable facile heterolytic C-H bond activation along the Zr-N bond, this material was found to be a highly active (1.53 molpropene molZr-1 h-1 at 450 °C) and selective (99% to propylene) catalyst for propane dehydrogenation. In contrast, the homologous silica supported complex exhibited negligible activity under these conditions.

Odontogenic and anti-inflammatory effects of magnesium-doped bioactive glass in vital pulp therapy.

This study aimed to investigate the effects of magnesium-doped bioactive glass (Mg-BG) on the mineralization, odontogenesis, and anti-inflammatory abilities of human dental pulp stem cells (hDPSCs). Mg-BG powders with different Mg concentrations were successfully synthesized via the sol-gel method and evaluated using X-ray diffraction, Fourier-transform infrared spectroscopy, scanning electron microscopy, and transmission electron microscopy. Apatite formation was observed on the surfaces of the materials after soaking in simulated body fluid. hDPSCs were cultured with Mg-BG powder extracts in vitro, and no evident cytotoxicity was observed. Mg-BG induced alkaline phosphatase (ALP) expression and mineralization of hDPSCs and upregulated the expression of odontogenic genes, including those encoding dentin sialophosphoprotein, dentin matrix protein 1, ALP, osteocalcin, and runt-related transcription factor 2. Moreover, secretion of inflammatory cytokines (interleukin [IL]-4, IL-6, IL-8, and tumor necrosis factor-alpha) was substantially suppressed by Mg-BG. Collectively, the results of this study suggest that Mg-BG has excellent in vitro bioactivity and is a potential material for vital pulp therapy for inflamed pulps.

A novel design of copper selenide/zinc selenide/Nitrogen-doped carbon derived from MOF for sulfadiazine adsorption: Performance and mechanism.

Herein, a novel copper selenide/zinc selenide/Nitrogen-doped carbon (Cu2Se/ZnSe/NC) sphere was constructed via a combination of cation exchange, selenization and carbonization approaches with zinc-based metal-organic frameworks (ZIF-8) as precursor for sulfadiazine (SDZ) removal. Compared with the ZnSe/NC, the defective Cu2Se/ZnSe interface in the optimizing Cu-ZnSe/NC2 sample caused a remarkably improved adsorption performance. Notably, the adsorption capacity of 129.32 mg/g was better than that of mostly reported adsorbents for SDZ. And the adsorption referred to multiple-layer physical-chemical process that was spontaneous and exothermic. Besides, the Cu-ZnSe/NC2 displayed fast adsorption equilibrium of about 20 min and significant anti-interference ability for inorganic ions. Specially, the adsorbent possessed excellent stability and reusability, which could also be applied for rhodamine B (RhB), methylene blue (MB), and methyl orange (MO) dyes removal. Ultimately, the charge redistribution of Cu2Se/ZnSe interface greatly contributes the superior adsorption performance for SDZ, in which electrostatic attraction occupied extremely crucial status as compared to π-π electron-donor-acceptor (π-π EDA) interaction and hydrogen bonding (H-bonding), as revealed by the density function theory (DFT) calculations and experimental results. This study can provide a guideline for design of high-efficient adsorbent with interfacial charge redistribution.

Endothoracic lymphatic plexus­hemiazygos vein anastomosis for chylothorax complicated with hepatocellular carcinoma: A case report.

For patients with hepatocellular carcinoma and cirrhosis, the rupture of thin lymphatic vessel walls leads to a profuse outflow of lymph fluid. Typically, chyloperitoneum tends to precede the development of chylothorax in patients with cancer. The present study describes the case of a male patient with hepatocellular carcinoma who developed chylothorax without chyloperitoneum. Computed tomography showed lymphatic system developmental abnormalities with a large volume of leaked lymph fluid. Multiple thoracic duct ligations (TDLs) failed, but a side-to-end lymphatic venous anastomosis (LVA) surgery resolved the symptoms. To the best of our knowledge, there are no reports of chylothorax occurrence after cirrhosis further complicated by congenital lymphatic abnormalities in the English-language literature. In conclusion, LVA could be appropriate to treat chylothorax when TDL is ineffective as a remedial or even prophylactic intervention.

Assessing the Utility of Large Language Models for Phenotype-Driven Gene Prioritization in Rare Genetic Disorder Diagnosis.

Phenotype-driven gene prioritization is a critical process in the diagnosis of rare genetic disorders for identifying and ranking potential disease-causing genes based on observed physical traits or phenotypes. While traditional approaches rely on curated knowledge graphs with phenotype-gene relations, recent advancements in large language models have opened doors to the potential of AI predictions through extensive training on diverse corpora and complex models. This study conducted a comprehensive evaluation of five large language models, including two Generative Pre-trained Transformers series, and three Llama2 series, assessing their performance across three key metrics: task completeness, gene prediction accuracy, and adherence to required output structures. Various experiments explored combinations of models, prompts, input types, and task difficulty levels. Our findings reveal that even the best-performing LLM, GPT-4, achieved an accuracy of 16.0%, which still lags behind traditional bioinformatics tools. Prediction accuracy increased with the parameter/model size. A similar increasing trend was observed for the task completion rate, with complicated prompts more likely to increase task completeness in models smaller than GPT-4. However, complicated prompts are more likely to decrease the structure compliance rate, but no prompt effects on GPT-4. Compared to HPO term-based input, LLM was also able to achieve better than random prediction accuracy by taking free-text input, but slightly lower than with the HPO input. Bias analysis showed that certain genes, such as MECP2, CDKL5, and SCN1A, are more likely to be top-ranked, potentially explaining the variances observed across different datasets. This study provides valuable insights into the integration of LLMs within genomic analysis, contributing to the ongoing discussion on the utilization of advanced LLMs in clinical workflows.

[Deep Learning-Based Key Frame Recognition Algorithm for Adrenal Vascular in X-Ray Imaging].

Adrenal vein sampling is required for the staging diagnosis of primary aldosteronism, and the frames in which the adrenal veins are presented are called key frames. Currently, the selection of key frames relies on the doctor's visual judgement which is time-consuming and laborious. This study proposes a key frame recognition algorithm based on deep learning. Firstly, wavelet denoising and multi-scale vessel-enhanced filtering are used to preserve the morphological features of the adrenal veins. Furthermore, by incorporating the self-attention mechanism, an improved recognition model called ResNet50-SA is obtained. Compared with commonly used transfer learning, the new model achieves 97.11% in accuracy, precision, recall, F1, and AUC, which is superior to other models and can help clinicians quickly identify key frames in adrenal veins.

Bruton's tyrosine kinase inhibitors in Refractory or Relapsing Primary Central Nervous System Lymphoma: A meta-analysis and systematic review.

BACKGROUND: Primary central nervous system lymphoma (PCNSL) is an aggressive lymphoma that primarily affects the central nervous system. Current treatments, such as surgery, chemotherapy, and whole-brain radiotherapy, often fail to achieve satisfactory results. The prognosis for patients with refractory or relapsed (R/R) PCNSL is bleak. The optimal treatment for refractory or relapsed PCNSL is poorly defined due to a limited number of studies in this setting. Bruton's tyrosine kinase (BTK) inhibitors, as part of targeted therapy regimens, have undergone testing in several clinical trials against PCNSL and have shown promising results in the treatment of R/R PCNSL. In this meta-analysis, we aim to explore and critically appraise the evidence regarding the efficacy of BTK inhibitors in the treatment of refractory or relapsed PCNSL. METHODS: A systematic search was conducted on multiple databases including PubMed, Embase, Cochrane library, Wanfang Data Knowledge Service Platform, and CNKI, covering the period up to November 2023. The inclusion criteria for studies were patients with refractory or relapsed (R/R) primary central nervous system lymphoma (PCNSL) who received Bruton's tyrosine kinase (BTK) inhibitors, and reported data on overall response (OR) and complete remission (CR). The pooled rates were calculated using a random-effects or fixed-effects model with a double arcsine transformation, and 95% confidence intervals (CI) were determined for all outcomes. RESULTS: In total, eleven studies involving 185 patients were identified and included in the meta-analysis. The pooled complete remission (CR) rate of BTK inhibitors-based treatment for refractory or relapsed (R/R) primary central nervous system lymphoma (PCNSL) was found to be 50%. Subgroup analysis revealed that the CR rates for BTK inhibitor monotherapy, BTK inhibitor combined with chemotherapy, and BTK inhibitor combined with radiotherapy for R/R PCNSL were 7%, 68%, and 80%, respectively. The overall response rate (ORR) for BTK inhibitors-based treatment for R/R PCNSL was 70%. Subgroup analysis showed that the ORR rates for BTK inhibitor monotherapy and BTK inhibitor combined with chemotherapy for R/R PCNSL were 55% and 83%, respectively. The most common adverse events reported were hematological AEs, including neutropenia, anemia, and thrombocytopenia. Severe nonhematological AEs included rash, febrile neutropenia, increased levels of aspartate aminotransferase, and increased blood bilirubin. CONCLUSIONS: BTK inhibitors can be regarded as a safe and effective treatment option for refractory or relapsed (R/R) primary central nervous system lymphoma (PCNSL), thereby providing a potential new avenue for R/R PCNSL treatment. However, it is important to note that further large-sample prospective randomized controlled trials are needed to validate these findings and establish their wider applicability.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection. METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model. RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability. CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

The impact of educational and medical systems on autistic children from multilingual American homes: A systematic review.

LAY ABSTRACT: Research has found that autistic children can navigate multilingual schools and communities without harming their language skills or school success. However, they may encounter specific challenges within the United States, where educational and healthcare systems are insufficiently equipped to meet their needs. This review examined 46 US-based studies on the topic and findings reveal persistent deficit-based ideas about multilingualism and autism (e.g., professionals recommending that autistic students only speak and learn in English) accompanied by patterns of unequal identification of autism among multilingual children. These findings highlight issues of disproportionality and inadequate access to educational and healthcare resources. However, recent studies indicate that incorporating a child's native language in education not only enhances learning and behavioral outcomes but also boosts cognitive functions like problem-solving and planning. Taken as a whole, current research suggests that intentionally addressing linguistic diversity will allow educational and medical systems to better serve autistic children.

Retagliptin as add-on therapy to metformin in Chinese patients with type 2 diabetes inadequately controlled with metformin: A multicentre, randomized, double-blind, placebo-controlled, phase 3 trial.

AIM: To evaluate the efficacy and safety of retagliptin in Chinese patients with type 2 diabetes (T2D) inadequately controlled with metformin. MATERIALS AND METHODS: This multicentre, phase 3 trial consisted of a 16-week, randomized, double-blind, placebo-controlled period, where patients with HbA1c levels between 7.5% and 11.0% were randomized to receive either once-daily (QD) retagliptin 100 mg (n = 87) or placebo (n = 87), both as an add-on to metformin. The primary endpoint was the change in HbA1c from baseline to week 16. RESULTS: At week 16, the least squares mean change in HbA1c from baseline, compared with placebo, was -0.82% (95% CI, -1.05% to -0.58%) for the retagliptin 100 mg QD group (P < .0001) per treatment policy estimand. Significantly higher proportions of patients in the retagliptin 100 mg QD group achieved HbA1c levels of less than 6.5% (11.5%) and less than 7.0% (26.4%) compared with those receiving placebo (0% and 4.6%; P = .0016 and P < .0001, respectively) at week 16. Retagliptin 100 mg QD also lowered fasting plasma glucose and 2-hour postprandial plasma glucose levels. The incidence of adverse events (AEs) during the treatment period was similar between the two groups. However, slightly higher proportions of increased lipase and increased amylase in the retagliptin 100 mg QD group were observed. No patients discontinued treatment permanently because of AEs, and no episodes of severe hypoglycaemia were reported. CONCLUSIONS: Retagliptin 100 mg QD as an add-on therapy to metformin offers a new therapeutic option for treating Chinese patients with T2D inadequately controlled by metformin alone, and is generally well tolerated.