Research on the osteogenic properties of 3D-printed porous titanium alloy scaffolds loaded with Gelma/PAAM-ZOL composite hydrogels.

Although titanium alloy is the most widely used endoplant material in orthopedics, the material is bioinert and good bone integration is difficult to achieve. Zoledronic acid (ZOL) has been shown to locally inhibit osteoclast formation and prevent osteoporosis, but excessive concentrations of ZOL exert an inhibitory effect on osteoblasts; therefore, stable and controlled local release of ZOL may reshape bone balance and promote bone regeneration. To promote the adhesion of osteoblasts to many polar groups, researchers have applied gelatine methacryloyl (Gelma) combined with polyacrylamide hydrogel (PAAM), which significantly increased the hydrogen bonding force between the samples and improved the stability of the coating and drug release. A series of experiments demonstrated that the Gelma/PAAM-ZOL bioactive coating on the surface of the titanium alloy was successfully prepared. The coating can induce osteoclast apoptosis, promote osteoblast proliferation and differentiation, achieve dual regulation of bone regeneration, successfully disrupt the balance of bone remodelling and promote bone tissue regeneration. Additionally, the coating improves the metal biological inertness on the surface of titanium alloys and improves the bone integration of the scaffold, offering a new strategy for bone tissue engineering to promote bone technology.

Effect of Stroke Etiology on Endovascular Treatment for Acute Basilar-Artery Occlusion: A Post Hoc Analysis of the ATTENTION Randomized Trial.

BACKGROUND: Stroke etiology could influence the outcomes in patients with basilar-artery occlusion (BAO). This study aimed to evaluate the differences in efficacy and safety of best medical treatment (BMT) plus endovascular treatment (EVT) versus BMT alone in acute BAO across different stroke etiologies. METHODS: The study was a post hoc analysis of the ATTENTION trial (Trial of Endovascular Treatment of Acute Basilar-Artery Occlusion), which was a multicenter, randomized trial at 36 centers in China from February 2021 to September 2022. Patients with acute BAO were classified into 3 groups according to stroke etiology (large-artery atherosclerosis [LAA], cardioembolism, and undetermined cause/other determined cause [UC/ODC]). The primary outcome was a favorable outcome (modified Rankin Scale score of 0-3) at 90 days. Safety outcomes included symptomatic intracranial hemorrhage and 90-day mortality. RESULTS: A total of 340 patients with BAO were included, 150 (44.1%) had LAA, 72 (21.2%) had cardioembolism, and 118 (34.7%) had UC/ODC. For patients treated with BMT plus EVT and BMT alone, respectively, the rate of favorable outcome at 90 days was 49.1% and 23.8% in the LAA group (odds ratio, 3.08 [95% CI, 1.38-6.89]); 52.2% and 30.8% in the cardioembolism group (odds ratio, 2.45 [95% CI, 0.89-6.77]); and 37.5% and 17.4% in the UC/ODC group (odds ratio, 2.85 [95% CI, 1.16-7.01]), with P=0.89 for the stroke etiology×treatment interaction. The rate of symptomatic intracranial hemorrhage in EVT-treated patients with LAA, cardioembolism, and UC/ODC was 8.3%, 2.2%, and 3.2%, respectively, and none of the BMT-treated patients. Lower 90-day mortality was observed in patients with EVT compared with BMT alone across 3 etiology groups. CONCLUSIONS: Among patients with acute BAO, EVT compared with BMT alone might be associated with favorable outcomes and lower 90-day mortality, regardless of cardioembolism, LAA, or UC/ODC etiologies. The influence of stroke etiology on the benefit of EVT should be explored by further trials. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04751708.

Application of Fusobacterium nucleatum as a biomarker in gastrointestinal malignancies.

The morbidity and mortality of gastrointestinal (GI) malignancies are among the highest in the world, posing a serious threat to human health. Because of the insidious onset of the cancer, it is difficult for patients to be diagnosed at an early stage, and it rapidly progresses to an advanced stage, resulting in poor treatment and prognosis. Fusobacterium nucleatum (F. nucleatum) is a gram-negative, spore-free anaerobic bacterium that primarily colonizes the oral cavity and is implicated in the development of colorectal, esophageal, gastric, and pancreatic cancers via various intricate mechanisms. Recent development in novel research suggests that F. nucleatum may function as a biomarker in GI malignancies. Detecting the abundance of F. nucleatum in stool, saliva, and serum samples of patients may aid in the diagnosis, risk assessment, and prognosis monitoring of GI malignancies. This editorial systematically describes the biological roles and mechanisms of F. nucleatum in GI malignancies focusing on the application of F. nucleatum as a biomarker in the diagnosis and prognosis of GI malignancies to promote the clinical translation of F. nucleatum and GI tumors-related research.

The effect of social activities on the alienation and family resilience of Chinese caregivers for children with autism: a latent class analysis.

Introduction: Caregivers of children with autism spectrum disorder (ASD) in China often experience alienation due to societal stigma. While this alienation detrimentally impacts their mental well-being, family resilience serves as a protective factor. Previous research has predominantly examined the social support derived from social activities but has neglected to delve into the specific patterns of these activities. The primary objective of this study was twofold: firstly, to gain insights into the various social activities engaged in by caregivers of children with autism in China, and secondly, to ascertain the influence of these social activities on alienation and family resilience. Methods: Between June and August 2023, a cross-sectional survey was carried out across multiple cities in Jilin Province, aiming to gather data from a total of 205 Chinese caregivers of children with autism. Data collection was conducted through the utilization of a structured questionnaire. The assessment of social activity involved the completion of 12 questionnaires, while alienation was evaluated using the Generalized Alienation Scale (GSAS), and family resilience was gauged through the Chinese version of the Family Resilience Scale (FaRE). The classification of social activities was conducted through latent class analysis (LCA), while the impact of these social activities on alienation and family resilience was examined using linear regression analysis. Results: The findings revealed that social activities can be categorized into five types (Low, Self-Recreation, Communication, Web Surfing, High). Communication social activities were found to reduce family resilience(ß=.332, p<0.01), while high social activities were associated with reduced alienation(ß=-.349, p<0.05) and increased family resilience(ß=.417, p<0.01). Conclusion: Supporting these particular types of social activities has the potential to reduce alienation and bolster family resilience among caregivers for children with autism in China.

Identification of N7-methylguanosine-related miRNAs as potential biomarkers for prognosis and drug response in breast cancer.

Objectives: The impact of N7-methylguanosine (m7G) on tumor progression and the regulatory role of microRNAs (miRNAs) in immune function significantly influence breast cancer (BC) prognosis. Investigating the interplay between m7G modification and miRNAs provides novel insights for assessing prognostics and drug responses in BC. Materials and methods: RNA sequences (miRNA and mRNA profiles) and clinical data for BC were acquired from the Cancer Genome Atlas (TCGA) database. A miRNA signature associated with 15 m7G in this cohort was identified using Cox regression and LASSO. The risk score model was evaluated using Kaplan-Meier and time-dependent ROC analysis, categorizing patients into high-risk and low-risk groups. Functional enrichment analyses were conducted to explore potential pathways. The immune system, including scores, cell infiltration, function, and drug sensitivity, was examined and compared between high-risk and low-risk groups. A nomogram that combines risk scores and clinical factors was developed and validated. Single-sample gene set enrichment analysis (ssGSEA) was employed to explore m7G-related miRNA signatures and immune cell relationships in the tumor microenvironment. Additionally, drug susceptibility was compared between risk groups. Results: Fifteen m7G-related miRNAs were independently correlated with overall survival (OS) in BC patients. Time-dependent ROC analysis yielded area under the curve (AUC) values of 0.742, 0.726, and 0.712 for predicting 3-, 5-, and 10-year survival rates, respectively. The Kaplan-Meier analysis revealed a significant disparity in OS between the high-risk and low-risk groups (p = 1.3e-6). Multiple regression identified the risk score as a significant independent prognostic factor. An excellent calibration nomogram with a C-index of 0.785 (95 % CI: 0.728-0.843) was constructed. In immune analysis, low-risk patients exhibited heightened immune function and increased responsiveness to immunotherapy and chemotherapy compared to high-risk patients. Conclusion: This study systematically analyzed m7G-related miRNAs and revealed their regulatory mechanisms concerning the tumor microenvironment (TME), pathology, and the prognosis of BC patient. Based on these miRNAs, a prognostic model and nomogram were developed for BC patients, facilitating prognostic assessments. These findings can also assist in predicting treatment responses and guiding medication selection.

A Head-to-Head Comparison of EQ-HWB and EQ-5D-5L in Patients, Carers, and General Public in China.

OBJECTIVES: This study aimed to understand the psychometric properties of EQ Health and Wellbeing (EQ-HWB) and to examine its relationship with EQ-5D-5L in a sample covering patients, carers, and general public. METHODS: A cross-sectional study was conducted in Guizhou Province, China. The acceptability, convergent validity (using Spearman correlation coefficients), internal structure (using exploratory factor analysis), and known-group validity of EQ-HWB, EQ-HWB-Short (EQ-HWB-S), and EQ-5D-5L were reported and compared. RESULTS: A total of 323 participants completed the survey, including 106 patients, 101 carers, and 116 individuals from the general public. Approximately 7.4% of participants had at least 1 missing response. In the EQ-HWB and EQ-5D-5L items related to activities, there were more level 1 responses. The correlations between EQ-HWB and EQ-5D-5L items ranged from low to high, confirming the convergent validity of similar aspects between the 2 instruments. Notably, EQ-HWB measures 2 additional factors compared with EQ-5D-5L or EQ-HWB-S, both of which share 3 common factors. When the patient group was included, EQ-5D-5L had the largest effect size, but it failed to differentiate between the groups of general public and carers. Both EQ-HWB and EQ-HWB-S demonstrated better known-group validity results when carers were included. CONCLUSIONS: EQ-HWB measures a broader quality of life construct that goes beyond health measured by EQ-5D-5L. By encompassing a broader scope, the impact of healthcare interventions may become diluted, given that other factors can influence well-being outcomes as significantly as health conditions do.

A novel machine learning prediction model for metastasis in breast cancer.

BACKGROUND: Breast cancer (BC) metastasis is the common cause of high mortality. Conventional prognostic criteria cannot accurately predict the BC metastasis risk. The machine learning technologies can overcome the disadvantage of conventional models. AIM: We developed a model to predict BC metastasis using the random survival forest (RSF) method. METHODS: Based on demographic data and routine clinical data, we used RSF-recursive feature elimination to identify the predictive variables and developed a model to predict metastasis using RSF method. The area under the receiver operating characteristic curve (AUROC) and Kaplan-Meier survival (KM) analyses were plotted to validate the predictive effect when C-index was plotted to assess the discrimination and Brier scores was plotted to assess the calibration of the predictive model. RESULTS: We developed a metastasis prediction model comprising three variables (pathological stage, aspartate aminotransferase, and neutrophil count) selected by RSF-recursive feature elimination. The model was reliable and stable when assessed by the AUROC (0.932 in training set and 0.905 in validation set) and KM survival analyses (p < .0001). The C-indexes (0.959) and Brier score (0.097) also validated the good predictive ability of this model. CONCLUSIONS: This model relies on routine data and examination indicators in real-time clinical practice and exhibits an accurate prediction performance without increasing the cost for patients. Using this model, clinicians can facilitate risk communication and provide precise and efficient individualized therapy to patients with breast cancer.

LncRNA MEG3 Reduces the Ratio of M2/M1 Macrophages Through the HuR/CCL5 Axis in Hepatocellular Carcinoma.

Objective: Tumor-associated macrophages play a crucial role in the development of hepatocellular carcinoma (HCC). Our study aimed to investigate the relationship between long coding RNA (lncRNA) maternally expressed gene 3 (MEG3), RNA-binding protein human antigen R (HuR), and messenger RNA C-C motif chemokine 5 (CCL5) in the modulation of M1 and M2 macrophage polarization in HCC. Methods: To induce M1 or M2 polarization, LPS/IFNγ- or IL4/IL13 were used to treat bone marrow derived macrophages (BMDMs). The localization of MEG3 in M1 and M2 macrophages was assessed using fluorescence in situ hybridization assay. Expression levels of MEG3, HuR, CCL5, M1, and M2 markers were measured by RT-qPCR or immunofluorescence staining. Flow cytometry was performed to determine the proportion of F4/80+CD206+ and F4/80+CD68+ cells. RNA pulldown assay was performed to detect the binding of lncRNA MEG3 and HuR. The impacts of HuR on CCL5 stability and activity of CCL5 promoter were evaluated using actinomycin D treatment and luciferase reporter assay. Cell migration, invasiveness, and angiogenesis were assessed using transwell migration and invasion assays and a tube formation assay. A mixture of Huh-7 cells and macrophages were injected into nude mice to explore the effect of MEG3 on tumorigenesis. Results: MEG3 promoted M1-like polarization while dampening M2-like polarization of BMDMs. MEG3 bound to HuR in M1 and M2 macrophages. HuR downregulated CCL5 by inhibiting CCL5 transcription in macrophages. In addition, overexpression of MEG3 suppressed cell metastasis, invasion, and angiogenesis by obstructing macrophage M2 polarization. MEG3 inhibited tumorigenesis in HCC via promotion of M1-like polarization and inhibition of M2-like polarization. Rescue experiments showed that depletion of CCL5 in M2 macrophages reversed MEG3-induced suppressive effect on cell migration, invasion, and tube formation. Conclusion: MEG3 suppresses HCC progression by promoting M1-like while inhibiting M2-like macrophage polarization via binding to HuR and thus upregulating CCL5.

GMFGRN: a matrix factorization and graph neural network approach for gene regulatory network inference.

The recent advances of single-cell RNA sequencing (scRNA-seq) have enabled reliable profiling of gene expression at the single-cell level, providing opportunities for accurate inference of gene regulatory networks (GRNs) on scRNA-seq data. Most methods for inferring GRNs suffer from the inability to eliminate transitive interactions or necessitate expensive computational resources. To address these, we present a novel method, termed GMFGRN, for accurate graph neural network (GNN)-based GRN inference from scRNA-seq data. GMFGRN employs GNN for matrix factorization and learns representative embeddings for genes. For transcription factor-gene pairs, it utilizes the learned embeddings to determine whether they interact with each other. The extensive suite of benchmarking experiments encompassing eight static scRNA-seq datasets alongside several state-of-the-art methods demonstrated mean improvements of 1.9 and 2.5% over the runner-up in area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC). In addition, across four time-series datasets, maximum enhancements of 2.4 and 1.3% in AUROC and AUPRC were observed in comparison to the runner-up. Moreover, GMFGRN requires significantly less training time and memory consumption, with time and memory consumed <10% compared to the second-best method. These findings underscore the substantial potential of GMFGRN in the inference of GRNs. It is publicly available at https://github.com/Lishuoyy/GMFGRN.

Structural Validation and Measurement Invariance Testing of the Chinese Version of the eHealth Literacy Scale Among Undergraduates: Cross-Sectional Study.

BACKGROUND: The eHealth Literacy Scale (eHEALS) was introduced in China in 2013 as one of the most important electronic health literacy measurement instruments. After a decade of development in China, it has received widespread attention, although its theoretical underpinnings have been challenged, thus demanding more robust research evidence of factorial validity and multigroup measurement properties. OBJECTIVE: This study aimed to evaluate the Chinese version of the eHEALS in terms of its measurement properties. METHODS: A cross-sectional survey was conducted in a university setting in China. Item statistics were checked for response distributions and floor and ceiling effects. Internal consistency reliability was confirmed with Cronbach α, split-half reliability, Cronbach α if an item was deleted, and item-total correlation. A total of 5 representative eHEALS factor structures were examined and contrasted using confirmatory factor analysis. The study used the item-level content validity index (I-CVI) and the average of the I-CVI scores of all items on the scale to assess the content validity of the dominance model. Furthermore, the validated dominance model was subsequently used to evaluate the relevance and representation of elements in the instrument and to assess measurement invariance across genders. RESULTS: A total of 972 respondents were identified, with a Cronbach α of .92, split-half reliability of 0.88, and item-total score correlation coefficients ranging from 0.715 to 0.781. Cronbach α if an item was deleted showed that all items should be retained. Acceptable content validity was supported by I-CVIs ≥0.80. The confirmatory factor analysis confirmed that the 3-factor model was acceptable. The measurement model met all relevant fit indices: average variance extracted from 0.663 to 0.680, composite reliability from 0.810 to 0.857, chi-square divided by the df of 4.768, root mean square error of approximation of 0.062, standardized root mean squared residual of 0.020, comparative fit index (CFI) of 0.987, and Tucker-Lewis index of 0.979. In addition, the scale demonstrated error variance invariance (Δnormed fit index=-0.016, Δincremental fit index=-0.012, ΔTucker-Lewis index=0.005, Δcomparative fit index=-0.012, Δrelative fit index=0.005, and Δroot mean square error of approximation=0.005). CONCLUSIONS: A 3-factor model of the Chinese version of the eHEALS fits best, and our findings provide evidence for the strict measurement invariance of the instrument regarding gender.

Integrating unsupervised language model with multi-view multiple sequence alignments for high-accuracy inter-chain contact prediction.

Accurate identification of inter-chain contacts in the protein complex is critical to determine the corresponding 3D structures and understand the biological functions. We proposed a new deep learning method, ICCPred, to deduce the inter-chain contacts from the amino acid sequences of the protein complex. This pipeline was built on the designed deep residual network architecture, integrating the pre-trained language model with three multiple sequence alignments (MSAs) from different biological views. Experimental results on 709 non-redundant benchmarking protein complexes showed that the proposed ICCPred significantly increased inter-chain contact prediction accuracy compared to the state-of-the-art approaches. Detailed data analyses showed that the significant advantage of ICCPred lies in the utilization of pre-trained transformer language models which can effectively extract the complementary co-evolution diversity from three MSAs. Meanwhile, the designed deep residual network enhances the correlation between the co-evolution diversity and the patterns of inter-chain contacts. These results demonstrated a new avenue for high-accuracy deep-learning inter-chain contact prediction that is applicable to large-scale protein-protein interaction annotations from sequence alone.

Depression is associated with heart failure in patients with type 2 diabetes mellitus.

Background: Type 2 diabetes mellitus (T2DM) is associated with an increased risk of heart failure (HF). Depression, a common comorbidity of T2DM, may further increase the risk of heart failure (HF). We investigated the association between depression and incident HF in patients with T2DM. Methods and results: Depressive symptoms were assessed in the ACCORD Health-Related Quality of Life study participants at baseline, 12, 36, and 48 months using the nine-item Patient Health Questionnaire (PHQ-9). The severity of depressive symptoms was categorized as none (0-4 points), mild (5-9 points), or moderate-severe (10-24 points). Cox regression with PHQ-9 as a time-dependent covariate was used to assess the association between depression and incident HF. During the median follow-up of 8.1 years, 104 participants developed HF (incidence: 7.1/1,000 person-years). Half of the participants with moderate-severe depression were relieved and a significant percentage of participants without depression or with mild depression worsened to mild or moderate-severe depression during the follow-up period, respectively. Each unit increase in the PHQ-9 score was associated with a 5% higher risk of HF (hazard ratio [HR]:1.05, 95% confidence interval [CI]: 1.01-1.10). Patients with depression ever (HR: 2.23, 95% CI: 1.25-3.98) or persistent depression (HR: 2.13, 95% CI: 1.05-4.44) had a higher risk of HF than those without depression ever. Conclusion: Depressive symptoms change greatly in T2DM patients, depressive symptoms are an independent risk factor for HF. These results reinforce the importance of continuous evaluation and management of mental health status in T2DM patients with high HF risk.

Anatomical study of the technique of the axis laminar screws and development of guide.

PURPOSE: To develop a bidirectional slide guide to assist screw placement in the axial lamina and to preliminarily discuss the accuracy and feasibility of auxiliary screw placement. METHODS: CT data from 40 randomly selected patients were imported into the software for modelling, and cross-pinning was used to simulate pinning. According to the different crossing methods of the upper and lower laminar screws, they are divided into two groups. In the software, the position of the needlepoint of each screw is accurately measured, and the needle point is kept unchanged to simulate the movable range of the screw tail under the condition that the body does not penetrate the cortical bone. The data were compared by grouping and gender. Finally, the guide was designed by combining the screw exit point and fine adjustment angle data of all patients with the centripetal principle of the slide rail. RESULTS: The needle exit data L1/L2/L3/L4 were 6.44 ± 0.52 mm, 7.05 ± 0.48 mm, 3.55 ± 0.75 mm and 5.09 ± 0.74 mm, respectively, and the fine adjustment angle of the slide rail was 10.51° ± 0.87°. There was no significant difference between the two groups or between men and women (p > 0.05). CONCLUSION: In this experiment, using the data obtained from the simulation of screw insertion, a two-way slide guide was designed to assist the insertion of axial laminar screws. The guide locks the screw outlet point to position and guides the screw inlet point, which improves the accuracy and safety of screw placement.

Molecular Characterization of U6 Promoters from Orange-Spotted Grouper (Epinephelus coioides) and Its Application in DNA Vector-Based RNAi Technology.

The U6 promoter, a typical RNA polymerase III promoter, is widely used to transcribe small RNAs in vector-based siRNA systems. The RNAi efficiency is mainly dependent on the transcriptional activity of the U6 promoter. However, studies have found that U6 promoters isolated from some fishes do not work well in distantly related species. To isolate a U6 promoter with high transcriptional efficiency from fish, in this study, we cloned five U6 promoters in orange-spotted grouper, of which only the grouper U6-1 (GU6-1) promoter contains the OCT element in the distant region. Functional studies revealed that the GU6-1 promoter has high transcriptional ability, which could efficiently transcribe shRNA and result in target gene knockdown in vitro and in vivo. Subsequently, the deletion or mutation of the OCT motif resulted in a significant decrease in promoter transcriptional activity, demonstrating that the OCT element plays an important role in enhancing the grouper U6 promoter transcription. Moreover, the transcriptional activity of the GU6-1 promoter showed little species specificity. It not only works in the grouper but also possesses high transcriptional activity in the zebrafish. Knockdown of the mstn gene in zebrafish and grouper through shRNA driven by the GU6-1 promoter could promote fish growth, suggesting that the GU6-1 promoter can be used as a potential molecular tool in aquaculture practice.

TripletCell: a deep metric learning framework for accurate annotation of cell types at the single-cell level.

Single-cell RNA sequencing (scRNA-seq) has significantly accelerated the experimental characterization of distinct cell lineages and types in complex tissues and organisms. Cell-type annotation is of great importance in most of the scRNA-seq analysis pipelines. However, manual cell-type annotation heavily relies on the quality of scRNA-seq data and marker genes, and therefore can be laborious and time-consuming. Furthermore, the heterogeneity of scRNA-seq datasets poses another challenge for accurate cell-type annotation, such as the batch effect induced by different scRNA-seq protocols and samples. To overcome these limitations, here we propose a novel pipeline, termed TripletCell, for cross-species, cross-protocol and cross-sample cell-type annotation. We developed a cell embedding and dimension-reduction module for the feature extraction (FE) in TripletCell, namely TripletCell-FE, to leverage the deep metric learning-based algorithm for the relationships between the reference gene expression matrix and the query cells. Our experimental studies on 21 datasets (covering nine scRNA-seq protocols, two species and three tissues) demonstrate that TripletCell outperformed state-of-the-art approaches for cell-type annotation. More importantly, regardless of protocols or species, TripletCell can deliver outstanding and robust performance in annotating different types of cells. TripletCell is freely available at https://github.com/liuyan3056/TripletCell. We believe that TripletCell is a reliable computational tool for accurately annotating various cell types using scRNA-seq data and will be instrumental in assisting the generation of novel biological hypotheses in cell biology.

Association of Tirofiban With Functional Outcomes After Thrombectomy in Acute Ischemic Stroke Due to Intracranial Atherosclerotic Disease.

BACKGROUND AND OBJECTIVE: To investigate the efficacy and safety of IV infusion of tirofiban before endovascular thrombectomy for patients with large vessel occlusion due to intracranial atherosclerotic disease. The secondary objective was to identify potential mediators for the clinical effect of tirofiban. METHODS: Post hoc exploratory analysis of the Endovascular Treatment With versus Without Tirofiban for Patients with Large Vessel Occlusion Stroke (RESCUE BT) trial, which was a randomized, double-blinded, placebo-controlled trial at 55 centers in China from October 2018 to October 2021. Patients with occlusion of the internal carotid artery or middle cerebral artery due to intracranial atherosclerosis were included. The primary efficacy outcome was the proportion of patients achieving functional independence (defined as modified Rankin scale 0-2) at 90 days. Binary logistic regression and causal mediation analyses were used to estimate the treatment effect of tirofiban and the potential mediators. RESULTS: This study included 435 patients, of whom 71.5% were men. The median age was 65 (interquartile range [IQR] 56-72) years, with a median NIH Stroke Scale of 14 (IQR 10-19). Patients in the tirofiban group had higher rates of functional independence at 90 days than patients in the placebo group (adjusted odds ratio 1.68; 95% CI 1.11-2.56, p = 0.02) without an increased risk of mortality or symptomatic intracranial hemorrhage. Tirofiban was associated with fewer thrombectomy passes (median [IQR] 1 [1-2] vs 1 [1-2], p = 0.004), which was an independent predictor of functional independence. Mediation analysis showed tirofiban-reduced thrombectomy passes explained 20.0% (95% CI 4.1%-76.0%) of the effect of tirofiban on functional independence. DISCUSSION: In this post hoc analysis of the RESCUE BT trial, tirofiban was an effective and well-tolerated adjuvant medication of endovascular thrombectomy for patients with large vessel occlusion due to intracranial atherosclerosis. These findings need to be confirmed in future trials. TRIAL REGISTRATION INFORMATION: The RESCUE BT trial was registered on the Chinese Clinical Trial Registry: chictr.org.cn, ChiCTR-INR-17014167. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that tirofiban plus endovascular therapy improves 90-day outcome for patients with large vessel occlusion due to intracranial atherosclerosis.

[Meta-analysis of Simotang Oral Liquid in treatment of functional dyspepsia in adults].

This study was conducted to evaluate the efficacy and safety of Simotang Oral Liquid in the treatment of functional dyspepsia in adults. "Simotang Oral Liquid" "Simotang" "Si Mo Tang" "Si Mo Tang Oral Liquid" were used for retrieval of the relevant papers from CNKI, Wanfang, VIP, SinoMed, PubMed, Cochrane Library, Springer Link, and Web of Science from database inception to June 2021. Randomized controlled trial(RCT) of Simotang Oral Liquid in the treatment of functional dyspepsia in adults was screened out for Meta-analysis which was conducted in RevMan 5.3. A total of 16 RCTs were included. Meta-analysis showed that compared with the control group, Simotang Oral Liquid increased the total response rate and lowered the traditional Chinese medicine syndrome scores, serum cholecystokinin(CCK), serum nitric oxide(NO), and incidence of adverse reactions. However, the serum substance P(SP) had no statistical difference between the two groups. Simotang Oral Liquid is effective and safe in the treatment of functional dyspepsia in adults. However, this study has evidence and limitations, so the conclusions need to be further verified by large sample and multicenter clinical studies.

Emerging roles of non-coding RNAs in colorectal cancer oxaliplatin resistance and liquid biopsy potential.

Colorectal cancer (CRC) is one of the most common malignancies of the digestive tract, with the annual incidence and mortality increasing consistently. Oxaliplatin-based chemotherapy is a preferred therapeutic regimen for patients with advanced CRC. However, most patients will inevitably develop resistance to oxaliplatin. Many studies have reported that non-coding RNAs (ncRNAs), such as microRNAs, long non-coding RNAs, and circular RNAs, are extensively involved in cancer progression. Moreover, emerging evidence has revealed that ncRNAs mediate chemoresistance to oxaliplatin by transcriptional and post-transcriptional regulation, and by epigenetic modification. In this review, we summarize the mechanisms by which ncRNAs regulate the initiation and development of CRC chemoresistance to oxaliplatin. Furthermore, we investigate the clinical application of ncRNAs as promising biomarkers for liquid CRC biopsy. This review provides new insights into overcoming oxaliplatin resistance in CRC by targeting ncRNAs.

Learning Cell Annotation under Multiple Reference Datasets by Multisource Domain Adaptation.

Accurate and efficient cell type annotation is essential for single-cell sequence analysis. Currently, cell type annotation using well-annotated reference datasets with powerful models has become increasingly popular. However, with the increasing amount of single-cell data, there is an urgent need to develop a novel annotation method that can integrate multiple reference datasets to improve cell type annotation performance. Since the unwanted batch effects between individual reference datasets, integrating multiple reference datasets is still an open challenge. To address this, we proposed scMDR and scMultiR, respectively, using multisource domain adaptation to learn cell type-specific information from multiple reference datasets and query cells. Based on the learned cell type-specific information, scMDR and scMultiR provide the most likely cell types for the query cells. Benchmark experiments demonstrated their state-of-the-art effectiveness for integrative single-cell assignment with multiple reference datasets.

Obesity is associated with greater cognitive function in patients with type 2 diabetes mellitus.

Background: The impact of obesity on cognitive function in patients with type 2 diabetes mellitus (T2DM) remains controversial. This study aimed to evaluate whether obesity, assessed by body mass index (BMI) was associated with cognitive function among T2DM patients and whether the effect of obesity on cognitive function was through brain structure. Methods: This was a post-hoc analysis of the Action to Control Cardiovascular Risk in Diabetes-Memory in Diabetes (ACCORD-MIND) study. The cognitive test battery included the Digit Symbol Substitution Test (DSST), Mini-Mental State Exam (MMSE), Rey Auditory Verbal Learning Test (RAVLT), and STROOP test, which were administered at baseline, and at 20, 40, and 80 months. A subgroup (n = 614) of the ACCORD-MIND study underwent MRI scanning at baseline and at 40 and 80 months. The total brain volume (TBV), abnormal white matter volume (AWM), abnormal gray matter volume (AGM), and abnormal basal ganglia volume (ABG) were estimated. The outcomes of this study were cognitive function and brain structure. Results: In the adjusted analyses, BMI was positively associated with the MMSE (ß:0.08, 95%CI,0.01-0.16, per standard deviation [SD] increase) and RAVLT scores (ß:0.09, 95%CI,0.01-0.18). It was also associated with a greater TBV (ß:7.48, 95%CI,0.29-14.67). BMI was not associated with the DSST or STROOP scores, and AWM, AGM, ABG. Mediation analysis found that the effect of BMI on MMSE/RAVLT was mediated through TBV. Conclusion: Obesity may be associated with greater cognitive function and the effect of BMI on cognitive function may be mediated by TBV among patients with T2DM. Clinical Trial Registration: http://www.clinicaltrials.gov, identifier NCT00000620.