The mediating effect of positive expectations in the relationship between social support and post-traumatic stress disorder symptoms among parents of children with acute lymphoblastic leukemia.

PURPOSE: Parents of children with cancer are exposed to risks of developing post-traumatic stress disorder (PTSD) symptoms, but few studies have explored PTSD symptoms of Chinese parents of children with acute lymphoblastic leukemia (ALL). Our study aimed to examine the association between social support and PTSD symptoms and to examine the mediating effect of positive expectations in this relationship among parents of children with ALL. METHODS: A cross-sectional study was conducted of consecutive parents of children with ALL in the Shengjing Hospital of China Medical University. A total of 177 parents eligible for this study completed questionnaires on PTSD symptoms, perceived social support, optimism and general self-efficacy anonymously. Asymptotic and resampling strategies were used to examine how positive expectations mediated the association between perceived social support and PTSD symptoms. RESULTS: Mean score of PTSD symptoms was 37.64 ± 14.44; 29.4% of the sample scored 44 and above, 19.8% scored 50 and above. After adjusting for covariates, perceived social support was negatively associated with the total score of PTSD symptoms (ß = -0.209, p < 0.01). Positive expectations were found to mediate the relationship between perceived social support and PTSD symptoms, especially for the symptoms of avoidance and hyperarousal. CONCLUSIONS: Optimism and general self-efficacy fully mediated the association between perceived social support and PTSD symptoms. Therefore, social support and positive expectations should be included in PTSD preventions and treatments targeting Chinese parents of children with ALL.

Vehicle Lane-Changing scenario generation using time-series generative adversarial networks with an Adaptative parameter optimization strategy.

Connected and automated vehicles (CAVs) hold promise for enhancing transportation safety and efficiency. However, their large-scale deployment necessitates rigorous testing across diverse driving scenarios to ensure safety performance. In order to address two challenges of test scenario diversity and comprehensive evaluation, this study proposes a vehicle lane-changing scenario generation method based on a time-series generative adversarial network (TimeGAN) with an adaptive parameter optimization strategy (APOS). With just 13.3% of parameter combinations tested, we successfully trained a satisfactory TimeGAN and generate a substantial number of lane-changing scenarios. Then, the generated scenarios were evaluated for diversity, fidelity, and utility, demonstrating their effectiveness in capturing a wide range of driving situations. Furthermore, we employed a Lane-Changing Risk Index (LCRI) to identify the rare adversarial cases in scenarios. Compared to real scenarios, our approach generates 27 times more adversarial cases with 1.8 times higher average risk, highlighting its potential for uncovering critical safety vulnerabilities. This study paves the way for more comprehensive and effective CAV testing, ultimately contributing to safer and more reliable autonomous driving technologies.

Medium- to long-term clinical efficacy of total hip arthroplasty with structural bone grafting for dysplasia of the hip.

BACKGROUND: Patients with dysplasia of the hip (DDH) have different degrees of bone defects above and outside the acetabulum, and anatomically reconstructing the acetabular centre of rotation is difficult in primary total hip arthroplasty (THA). METHODS: From April 2012 to December 2022, 64 patients (64 hips) with DDH treated with THA with structural bone graft in the superolateral acetabulum were selected. The Oxford hip score(OHS), Barthel index (BI), leg length discrepancy, Wibegr central edge-angle(CE), gluteus medius muscle strength, vertical and horizontal distance of the hip rotation center, coverage rate of the bone graft and complications were used to evaluate the clinical effectiveness of the patients. RESULTS: All patients were followed up for an average of 7.3±1.9 years. The OHS improved significantly after the operation (P<0.001). The postoperative BI was significantly greater than that before operation (P<0.001). The postoperative leg length discrepancy was significantly lower than that before the operation (P<0.001). Postoperative bedside photography revealed that the height and horizontal distance to the hip rotation center were significantly lower after surgery than before surgery (P<0.001). The postoperative CE was significantly greater than that before surgery (P<0.001). No acetabular component loosening or bone graft resorption was found during the postoperative imaging examination. CONCLUSIONS: The use of biological acetabular cup combined with structural bone graft in the superolateral acetabulum in THA for DDH can obtain satisfactory medium and long-term clinical and radiological results.

Preparation of Polyoxymethylene/Exfoliated Molybdenum Disulfide Nanocomposite through Solid-State Shear Milling.

In this paper, the solid-state shear milling (S3M) strategy featuring a very strong three-dimensional shear stress field was adopted to prepare the high-performance polyoxymethylene (POM)/molybdenum disulfide (MoS2) functional nanocomposite. The transmission electron microscope and Raman measurement results confirmed that the bulk MoS2 particle was successfully exfoliated into few-layer MoS2 nanoplatelets by the above simple S3M physical method. The polarized optical microscope (PLM) observation indicated the pan-milled nanoscale MoS2 particles presented a better dispersion performance in the POM matrix. The results of the tribological test indicated that the incorporation of MoS2 could substantially improve the wear resistance performance of POM. Moreover, the pan-milled exfoliated MoS2 nanosheets could further substantially decrease the friction coefficient of POM. Scanning electron microscope observations on the worn scar revealed the tribological mechanism of the POM/MoS2 nanocomposite prepared by solid-state shear milling. The tensile test results showed that the pan-milled POM/MoS2 nanocomposite has much higher elongation at break than the conventionally melt-compounded material. The solid-state shear milling strategy shows a promising prospect in the preparation of functional nanocomposite with excellent comprehensive performance at a large scale.

Relationship between HLA genetic variations, COVID-19 vaccine antibody response, and risk of breakthrough outcomes.

The rapid global distribution of COVID-19 vaccines, with over a billion doses administered, has been unprecedented. However, in comparison to most identified clinical determinants, the implications of individual genetic factors on antibody responses post-COVID-19 vaccination for breakthrough outcomes remain elusive. Here, we conducted a population-based study including 357,806 vaccinated participants with high-resolution HLA genotyping data, and a subset of 175,000 with antibody serology test results. We confirmed prior findings that single nucleotide polymorphisms associated with antibody response are predominantly located in the Major Histocompatibility Complex region, with the expansive HLA-DQB1*06 gene alleles linked to improved antibody responses. However, our results did not support the claim that this mutation alone can significantly reduce COVID-19 risk in the general population. In addition, we discovered and validated six HLA alleles (A*03:01, C*16:01, DQA1*01:02, DQA1*01:01, DRB3*01:01, and DPB1*10:01) that independently influence antibody responses and demonstrated a combined effect across HLA genes on the risk of breakthrough COVID-19 outcomes. Lastly, we estimated that COVID-19 vaccine-induced antibody positivity provides approximately 20% protection against infection and 50% protection against severity. These findings have immediate implications for functional studies on HLA molecules and can inform future personalised vaccination strategies.

New Indole Alkaloids from the Fungus Talaromyces assiutensis JTY2.

Three new indole alkaloids, named talatensindoids A-C (1-3), together with two known biogenetically related indole alkaloids tryptamine (4) and L-tryptophan (5) were isolated from the Talaromyces assiutensis JTY2 based on the guidance of OSMAC approach. The structures of these indole alkaloids were determined by comprehensive spectroscopic analyses. The absolute configuration of 3 was confirmed by X-ray crystallographic analysis. Compound 1 represent the rare example of a chlorine-substituted indole alkaloid from natural products. The inhibitory activity of compounds 1-5 against two phytopathogenic fungi and three phytopathogenic bacteria was evaluated. Compound 1 exhibited broad spectrum antibacterial activities.

Lipopolysaccharide promotes cancer cell migration and invasion through METTL3/PI3K/AKT signaling in human cholangiocarcinoma.

Purpose: As a major structural component of the outer membrane of Gram-negative bacteria, lipopolysaccharide (LPS) has been detected in the blood circulation and tissues in patients with chronic diseases and cancers, which plays a critical role in the tumor formation and progression. However, the biological role of LPS in human intrahepatic cholangiocarcinoma remains unclear. The aims of this study were to investigate the role of LPS in the malignant progression of intrahepatic cholangiocarcinoma. Methods: The cell migration and invasion capacities of cholangiocarcinoma cell lines were evaluated by Boyden chamber assays. Expression levels of the key molecules involved in the PI3K/AKT signaling and METTL3 were detected by qPCR and western blot. The molecular mechanism by which LPS promotes the malignant behaviors was investigated by using siRNAs, plasmids and small molecule inhibitors. Results: In vitro experiments showed that exogenous LPS treatment promoted cell migration and invasion capacities in both QBC939 and HUCCT1 cell lines, while did not affect cell proliferation and apoptosis. Mechanistically, exogenous LPS treatment had been proved to induce the increased expression of METTL3 and activate the downstream PI3K/AKTsignaling pathway. In addition, suppression of METTL3 expression reduced cell proliferation, migration and invasion capacities in both cell lines. Furthermore, inhibition of METTL3 expression or inhibition of PI3K/AKT signaling decreased LPS-induced cell migration and invasion capacities. Moreover, knockdown of METTL3 or inhibition of METTL3 significantly inhibited LPS-induced activation of the PI3K/AKT signaling. Conclusion: In general, these results suggest that the LPS-METTL3-PI3K/AKT signal axis promotes cell migration and invasion in ICC, which contributes to a reduced overall survival in patients with ICC. It may broaden the horizon of cancer therapy with potential therapeutic targets.

The Role of FveAFB5 in Auxin-Mediated Responses and Growth in Strawberries.

Auxin is a crucial hormone that regulates various aspects of plant growth and development. It exerts its effects through multiple signaling pathways, including the TIR1/AFB-based transcriptional regulation in the nucleus. However, the specific role of auxin receptors in determining developmental features in the strawberry (Fragaria vesca) remains unclear. Our research has identified FveAFB5, a potential auxin receptor, as a key player in the development and auxin responses of woodland strawberry diploid variety Hawaii 4. FveAFB5 positively influences lateral root development, plant height, and fruit development, while negatively regulating shoot branching. Moreover, the mutation of FveAFB5 confers strong resistance to the auxinic herbicide picloram, compared to dicamba and quinclorac. Transcriptome analysis suggests that FveAFB5 may initiate auxin and abscisic acid signaling to inhibit growth in response to picloram. Therefore, FveAFB5 likely acts as an auxin receptor involved in regulating multiple processes related to strawberry growth and development.

Nomogram for predicting surgical site infections in elderly patients after open lumbar spine surgery: A retrospective study.

The aim of this study is to develop a nomogram to assess the risk of surgical site infection in elderly patients undergoing open lumbar spine surgery and explore related risk factors. We reviewed the records of 578 elderly patients who had undergone open lumbar spine surgery. The clinical parameters were subjected to lasso regression and logistic regression analyses. Subsequently, a nomogram was constructed to predict the risk of postoperative surgical site infection and validated using bootstrap resampling. A total of 578 patients were included in the analysis, of which 17 were diagnosed as postoperative surgical site infection. Following the final logistic regression analysis, obesity, hypoalbuminemia and drinking history were identified as independent risk factors and subsequently incorporated into the nomogram. The nomogram demonstrated excellent discrimination, with an area under the receiver-operating characteristic curve of 0.879 (95% CI 0.769 ~ 0.989) after internal validation. The calibration curve exhibited a high level of consistency. Decision curve analysis revealed that this nomogram had greater clinical value when the risk threshold for surgical site infection occurrence was >1% and <89%. We had developed a nomogram for predicting the risk of postoperative surgical site infection in elderly patients who had undergone open lumbar spine surgery. Validation using bootstrap resampling demonstrated excellent discrimination and calibration, indicating that the nomogram may hold potential clinical utility as a simple predictive tool for healthcare professionals.

PS2MS: A Deep Learning-Based Prediction System for Identifying New Psychoactive Substances Using Mass Spectrometry.

The rapid proliferation of new psychoactive substances (NPS) poses significant challenges to conventional mass-spectrometry-based identification methods due to the absence of reference spectra for these emerging substances. This paper introduces PS2MS, an AI-powered predictive system designed specifically to address the limitations of identifying the emergence of unidentified novel illicit drugs. PS2MS builds a synthetic NPS database by enumerating feasible derivatives of known substances and uses deep learning to generate mass spectra and chemical fingerprints. When the mass spectrum of an analyte does not match any known reference, PS2MS simultaneously examines the chemical fingerprint and mass spectrum against the putative NPS database using integrated metrics to deduce possible identities. Experimental results affirm the effectiveness of PS2MS in identifying cathinone derivatives within real evidence specimens, signifying its potential for practical use in identifying emerging drugs of abuse for researchers and forensic experts.

Impact of Immunomodulatory Therapy on COVID-19 Vaccine Response in Patients with Autoimmune Inflammatory Rheumatic Diseases.

Coronavirus disease 2019 (COVID-19) vaccination is essential for patients with autoimmune inflammatory rheumatic diseases (AIIRD) to reduce the risk of morbidity and mortality associated with serious COVID-19 infection. With endemicity, waning of vaccine- and infection-acquired immunity, and development of SARS-CoV-2 variants, the need for additional doses of vaccines against serious illness in high-risk immunocompromised persons remains imperative. This review examines how immunomodulatory therapies affect vaccine-induced immune response in patients with AIIRD. Glucocorticoids, methotrexate, azathioprine, calcineurin inhibitors, mycophenolate mofetil, tumor necrosis factor inhibitors, and abatacept have been shown to variably attenuate both humoral and cellular immune responses to vaccination. Janus kinase inhibitors reduce humoral immune response. In contrast, sulfasalazine, leflunomide, belimumab, interleukin (IL)-17, IL-12/23, IL-6, and IL-1 inhibitors appear favorable, with mild or no impact on vaccine response. Although rituximab is known to profoundly diminish humoral immune response, cellular immunity is relatively preserved. Administering a third and subsequent vaccine dose or temporally coordinating the dosing of immunomodulatory drugs may improve vaccine effectiveness. Further research is needed to personalise vaccination strategies for AIIRD patients, considering their specific immunomodulatory treatments.

Abnormal levels of expression of microRNAs in peripheral blood of patients with traumatic brain injury are induced by microglial activation and correlated with severity of injury.

BACKGROUND: Microglia play a crucial role in regulating the progression of traumatic brain injury (TBI). In specific, microglia can self-activate and secrete various substances that exacerbate or alleviate the neuroimmune response to TBI. In addition, microRNAs (miRNAs) are involved in the functional regulation of microglia. However, molecular markers that reflect the dynamics of TBI have not yet been found in peripheral tissues. METHODS: Paired samples of peripheral blood were collected from patients with TBI before and after treatment. Next-generation sequencing and bioinformatics analysis were used to identify the main pathways and biological functions of TBI-related miRNAs in the samples. Moreover, lipopolysaccharide-treated human microglia were used to construct a cellular immune-activation model. This was combined with analysis of peripheral blood samples to screen for highly expressed miRNAs derived from activated microglia after TBI treatment. Quantitative reverse-transcriptase polymerase chain reaction was used to determine the expression levels of these miRNAs, allowing their relationship with the severity of TBI to be examined. Receiver operating characteristic (ROC) curves were constructed to analyse the clinical utility of these miRNAs for determining the extent of TBI. RESULTS: Sequencing results showed that 37 miRNAs were differentially expressed in peripheral blood samples from patients with TBI before and after treatment, with 17 miRNAs being upregulated and 20 miRNAs being downregulated after treatment. The expression profiles of these miRNAs were verified in microglial inflammation models and in the abovementioned peripheral blood samples. The results showed that hsa-miR-122-5p and hsa-miR-193b-3p were highly expressed in the peripheral blood of patients with TBI after treatment and that the expression levels of these miRNAs were correlated with the patients' scores on the Glasgow Coma Scale. ROC curve analysis revealed that abnormally high levels of expression of hsa-miR-122-5p and hsa-miR-193b-3p in peripheral blood have some clinical utility for distinguishing different extents of TBI and thus could serve as biomarkers of TBI. CONCLUSION: Abnormally high levels of expression of hsa-miR-122-5p and hsa-miR-193b-3p in the peripheral blood of patients with TBI were due to the activation of microglia and correlated with the severity of TBI. This discovery may help to increase understanding of the molecular pathology of TBI and guide the development of new strategies for TBI therapy based on microglial function.

Scoring method of English composition integrating deep learning in higher vocational colleges.

Along with the progress of natural language processing technology and deep learning, the subjectivity, slow feedback, and long grading time of traditional English essay grading have been addressed. Intelligent English automatic scoring has been widely concerned by scholars. Given the limitations of topic relevance feature extraction methods and traditional automatic grading methods for English compositions, a topic decision model is proposed to calculate the topic relevance score of the topic richness in English composition. Then, based on the Score of Relevance Based on Topic Richness (TRSR) calculation method, an intelligent English composition scoring method combining artificial feature extraction and deep learning is designed. From the findings, the Topic Decision (TD) model achieved the best effect only when it was iterated 80 times. The corresponding accuracy, recall and F1 value were 0.97, 0.93 and 0.95 respectively. The model training loss finally stabilized at 0.03. The Intelligent English Composition Grading Method Integrating Deep Learning (DLIECG) method has the best overall performance and the best performance on dataset P. To sum up, the intelligent English composition scoring method has better effectiveness and reliability.

The Influence of Mindful Parenting on Children's Creative Tendencies: The Chain Mediating Effect of Parent-Child Intimacy and Connectedness to Nature.

(1) Objectives: The aim of this study was to examine the relationship between mindful parenting and children's creative tendencies and to investigate the mediating role of parent-child intimacy and connectedness to nature in the relationship between mindful parenting and children's creative tendencies. (2) Methods: In this cross-sectional study, nearly 800 mothers of children aged 3-6 were enrolled. General sociodemographic data, the Mindfulness in Parenting Questionnaire (MIPQ), the Creativity Assessment Packet (CAP), the Child-Parent Relationship Scale-Short Form (CPRS-SF), and the Connectedness to Nature Index-Parents of Preschool Children (CNI-PPC) were all included in the questionnaire survey. (3) Results: There were significant positive correlations among mindful parenting, parent-child intimacy, connectedness to nature, and children's creative tendencies. Mindful parenting had a positive predictive effect on children's creative tendencies. Parent-child intimacy played a mediating role between mindful parenting and children's creative tendencies. Connectedness to nature played a mediating role between mindful parenting and children's creative tendencies. The correlation between mindful parenting and children's creative tendencies may be impacted by the chain mediation effects of parent-child intimacy and connectedness to nature. (4) Conclusions: By promoting parent-child intimacy and connectedness to nature, and by utilizing the chain mediating effects of both, mindful parenting positively impacted children's creative tendencies.

Cultivation of microalgae-bacteria consortium by waste gas-waste water to achieve CO2 fixation, wastewater purification and bioproducts production.

The cultivation of microalgae and microalgae-bacteria consortia provide a potential efficient strategy to fix CO2 from waste gas, treat wastewater and produce value-added products subsequently. This paper reviews recent developments in CO2 fixation and wastewater treatment by single microalgae, mixed microalgae and microalgae-bacteria consortia, as well as compares and summarizes the differences in utilizing different microorganisms from different aspects. Compared to monoculture of microalgae, a mixed microalgae and microalgae-bacteria consortium may mitigate environmental risk, obtain high biomass, and improve the efficiency of nutrient removal. The applied microalgae include Chlorella sp., Scenedesmus sp., Pediastrum sp., and Phormidium sp. among others, and most strains belong to Chlorophyta and Cyanophyta. The bacteria in microalgae-bacteria consortia are mainly from activated sludge and specific sewage sources. Bioengineer in CBB cycle in microalgae cells provide effective strategy to achieve improvement of CO2 fixation or a high yield of high-value products. The mechanisms of CO2 fixation and nutrient removal by different microbial systems are also explored and concluded, the importance of microalgae in the technology is proven. After cultivation, microalgae biomass can be harvested through physical, chemical, biological and magnetic separation methods and used to produce high-value by-products, such as biofuel, feed, food, biochar, fertilizer, and pharmaceutical bio-compounds. Although this technology has brought many benefits, some challenging obstacles and limitation remain for industrialization and commercializing.

Spectra-Based Machine Learning for Predicting the Statistical Interaction Properties of CO Adsorbates on Surface.

Theoretical analyses of small-molecule adsorption on heterogeneous catalyst surfaces often rely on simplified models of molecular adsorption with the most favorable configuration. Given that real-world experimental tests frequently entail multiple molecules interacting with the surface, there is a pressing need for a comprehensive multimolecule adsorption model to bridge the gap between theory and experiment. Using machine learning, we predict the average values of important adsorption properties from conformationally averaged, calculated infrared and Raman spectra and compare these values to those theoretically derived from the conformationally averaged ensemble. Remarkably, our approach yields excellent predictions even when faced with large and indeterminate numbers of surface molecules. These quantitative spectra-averaged property relationships provide a theoretical framework for extracting key interaction properties from the spectra of real chemical environments.

Identification of potential crucial genes shared in psoriasis and ulcerative colitis by machine learning and integrated bioinformatics.

BACKGROUND: Mounting evidence suggest that there are an association between psoriasis and ulcerative colitis (UC), although the common pathogeneses are not fully understood. Our study aimed to find potential crucial genes in psoriasis and UC through machine learning and integrated bioinformatics. METHODS: The overlapping differentially expressed genes (DEGs) of the datasets GSE13355 and GSE87466 were identified. Then the functional enrichment analysis was performed. The overlapping genes in LASSO, SVM-RFE and key module in WGCNA were considered as potential crucial genes. The receiver operator characteristic (ROC) curve was used to estimate their diagnostic confidence. The CIBERSORT was conducted to evaluate immune cell infiltration. Finally, the datasets GSE30999 and GSE107499 were retrieved to validate. RESULTS: 112 overlapping DEGs were identified in psoriasis and UC and the functional enrichment analysis revealed they were closely related to the inflammatory and immune response. Eight genes, including S100A9, PI3, KYNU, WNT5A, SERPINB3, CHI3L2, ARNTL2, and SLAMF7, were ultimately identified as potential crucial genes. ROC curves showed they all had high confidence in the test and validation datasets. CIBERSORT analysis indicated there was a correlation between infiltrating immune cells and potential crucial genes. CONCLUSION: In our study, we focused on the comprehensive understanding of pathogeneses in psoriasis and UC. The identification of eight potential crucial genes may contribute to not only understanding the common mechanism, but also identifying occult UC in psoriasis patients, even serving as therapeutic targets in the future.

Chromosome-scale genome assembly of Lepus oiostolus (Lepus, Leporidae).

Lepus oiostolus (L. oiostolus) is a species endemic to the Qinghai-Tibet Plateau. However, the absence of a reference genome limits genetic studies. Here, we reported a high-quality L. oiostolus genome assembly, with scaffolds anchored to 24 chromosomes and a total assembled length of 2.80 Gb (contig N50 = 64.25 Mb). Genomic annotation uncovered 22,295 protein-coding genes and identified 49.84% of the sequences as transposable elements. Long interspersed nuclear elements (LINEs) constitute a high proportion of the genome. Our study is at the first time to report the chromosome-scale genome for the species of the L. oiostolus. It provides a valuable genomic resource for future research on the evolution of the Leporidae.

Effects of admission hyperglycemia and intravenous thrombolysis allocation in acute basilar artery occlusion after endovascular treatment: Analysis of the ATTENTION registry.

This study was to investigate the admission hyperglycemia and modified effect of intravenous thrombolysis (IVT) on clinical outcomes in acute basilar artery occlusion (BAO) patients receiving endovascular treatment (EVT). We prospectively recruited acute BAO patients from 48 stroke centers across 22 Chinese provinces in the ATTENTION registry from 2017 to 2021. Hyperglycemia on admission was defined as glucose ≥7.8 â€‹mmol/L. We performed multivariable logistic regression analysis to evaluate the correlation of hyperglycemia on admission with the primary outcome defined as a modified Rankin scale (mRS) score of <4 â€‹at 90 days, and the secondary outcomes defined as successful recanalization, mRS 0-1 and 0-2 â€‹at 90 days. Safety outcomes were symptomatic intracranial hemorrhage (sICH) and mortality within 90 days. There were 1195 patients with acute BAO treated with EVT of whom 519 had hyperglycemia on admission. Hyperglycemia on admission was inversely associated with favorable neurological outcomes (mRS 0-3: adjusted odd ratio [aOR] 0.69, 95 â€‹% confidence intervals [CI] 0.54-0.89, P â€‹= â€‹0.004; mRS 0-1: aOR 0.67, 95 â€‹% CI 0.50-0.90, P â€‹= â€‹0.008; mRS 0-2: aOR 0.73, 95 â€‹% CI 0.56-0.95; P â€‹= â€‹0.02). Hyperglycemia on admission was not correlated to sICH nor successful recanalization. In the subgroup of BAO patients treated with direct EVT, those with hyperglycemia on admission had a higher mortality rate, and overall worse clinical outcomes at 90 days than patients without hyperglycemia. A significant interaction was observed between IVT and hyperglycemia on admission (Pinteraction â€‹= â€‹0.017). In patients with acute BAO treated with EVT, hyperglycemia on admission was associated with worse functional outcomes at 90 days but was not correlated with sICH nor successful recanalization. The effect of admission hyperglycemia appears to be modified by IVT allocation. Unique identifier: ChiCTR2000041117.