Effect of Argatroban Plus Intravenous Alteplase vs Intravenous Alteplase Alone on Neurologic Function in Patients With Acute Ischemic Stroke: The ARAIS Randomized Clinical Trial.

Importance: Previous studies suggested a benefit of argatroban plus alteplase (recombinant tissue-type plasminogen activator) in patients with acute ischemic stroke (AIS). However, robust evidence in trials with large sample sizes is lacking. Objective: To assess the efficacy of argatroban plus alteplase for AIS. Design, Setting, and Participants: This multicenter, open-label, blinded end point randomized clinical trial including 808 patients with AIS was conducted at 50 hospitals in China with enrollment from January 18, 2019, through October 30, 2021, and final follow-up on January 24, 2022. Interventions: Eligible patients were randomly assigned within 4.5 hours of symptom onset to the argatroban plus alteplase group (n = 402), which received intravenous argatroban (100 µg/kg bolus over 3-5 minutes followed by an infusion of 1.0 µg/kg per minute for 48 hours) within 1 hour after alteplase (0.9 mg/kg; maximum dose, 90 mg; 10% administered as 1-minute bolus, remaining infused over 1 hour), or alteplase alone group (n = 415), which received intravenous alteplase alone. Both groups received guideline-based treatments. Main Outcomes and Measures: The primary end point was excellent functional outcome, defined as a modified Rankin Scale score (range, 0 [no symptoms] to 6 [death]) of 0 to 1 at 90 days. All end points had blinded assessment and were analyzed on a full analysis set. Results: Among 817 eligible patients with AIS who were randomized (median [IQR] age, 65 [57-71] years; 238 [29.1%] women; median [IQR] National Institutes of Health Stroke Scale score, 9 [7-12]), 760 (93.0%) completed the trial. At 90 days, 210 of 329 participants (63.8%) in the argatroban plus alteplase group vs 238 of 367 (64.9%) in the alteplase alone group had an excellent functional outcome (risk difference, -1.0% [95% CI, -8.1% to 6.1%]; risk ratio, 0.98 [95% CI, 0.88-1.10]; P = .78). The percentages of participants with symptomatic intracranial hemorrhage, parenchymal hematoma type 2, and major systemic bleeding were 2.1% (8/383), 2.3% (9/383), and 0.3% (1/383), respectively, in the argatroban plus alteplase group and 1.8% (7/397), 2.5% (10/397), and 0.5% (2/397), respectively, in the alteplase alone group. Conclusions and Relevance: Among patients with acute ischemic stroke, treatment with argatroban plus intravenous alteplase compared with alteplase alone did not result in a significantly greater likelihood of excellent functional outcome at 90 days. Trial Registration: ClinicalTrials.gov Identifier: NCT03740958.

Quality improvement effects of electrolyzed water on rice noodles prepared with semidry-milled rice flours.

To investigate the effects of electrolyzed water treatment on the qualities of rice noodles prepared with semidry- milled rice flour, pasting properties and thermal properties of rice flour, and the cooking and textural properties of rice noodles were determined. Higher peak viscosity and lower melting enthalpy were observed in electrolyzed water (EW) treated rice flour. The hardness, gumminess and chewiness of rice noodle in slightly acidic electrolyzed water treated rice noodles with available chlorine concentration (ACC) 20.32 mg/L were increased significantly (p < 0.05). The cooking loss decreased significantly in strong acidic electrolyzed water treated noodles with ACC 10.09 mg/L treatment (p < 0.05). The results indicated that EW could promote the gelatinization of rice flour, and improve the textural qualities of rice noodles. Therefore EW was appropriate to be used in rice noodle production.

A Prognostic Model Based on Six Metabolism-Related Genes in Colorectal Cancer.

An increasing number of studies have shown that abnormal metabolism processes are closely correlated with the genesis and progression of colorectal cancer (CRC). In this study, we systematically explored the prognostic value of metabolism-related genes (MRGs) for CRC patients. A total of 289 differentially expressed MRGs were screened based on The Cancer Genome Atlas (TCGA) and the Molecular Signatures Database (MSigDB), and 72 differentially expressed transcription factors (TFs) were obtained from TCGA and the Cistrome Project database. The clinical samples obtained from TCGA were randomly divided at a ratio of 7 : 3 to obtain the training group (n = 306) and the test group (n = 128). After univariate and multivariate Cox regression analyses, we constructed a prognostic model based on 6 MRGs (AOC2, ENPP2, ADA, GPD1L, ACADL, and CPT2). Kaplan-Meier survival analysis of the training group, validation group, and overall samples proved that the model had statistical significance in predicting the outcomes of patients. Independent prognosis analysis suggested that this risk score might serve as an independent prognosis factor for CRC patients. Moreover, we combined the prognostic model and the clinical characteristics in a nomogram to predict the overall survival of CRC patients. Furthermore, gene set enrichment analysis (GSEA) was conducted to identify the enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in the high- and low-risk groups, which might provide novel therapeutic targets for CRC patients. We discovered through the protein-protein interaction (PPI) network and TF-MRG regulatory network that 7 hub genes were retrieved from the PPI network and 4 kinds of differentially expressed TFs (NR3C1, MYH11, MAF, and CBX7) positively regulated 4 prognosis-associated MRGs (GSTM5, PTGIS, ENPP2, and P4HA3).

A Prognostic Model Based on the Immune-related Genes in Colon Adenocarcinoma.

Background: Immune-related genes (IRGs) are critically involved in the tumor microenvironment (TME) of colon adenocarcinoma (COAD). Here, the study was mainly designed to establish a prognostic model of IRGs to predict the survival of COAD patients. Methods: The Cancer Genome Atlas (TCGA), Immunology Database and Analysis Portal (ImmPort) database, and Cistrome database were utilized for extracting data regarding the expression of immune gene- and tumor-related transcription factors (TFs), aimed at the identification of differentially expressed genes (DEGs), differentially expressed IRGs (DEIRGs), and differentially expressed TFs (DETFs). Univariate Cox regression analysis was subsequently performed for the acquisition of prognosis-related IRGs, followed by establishment of TF regulatory network for uncovering the possible molecular regulatory association in COAD. Subsequently, multivariate Cox regression analysis was conducted to further determine the role of prognosis-related IRGs for prognostic prediction in COAD. Finally, the feasibility of a prognostic model with immunocytes was explored by immunocyte infiltration analysis. Results: A total of 2450 DEGs, 8 DETFs, and 79 DEIRGs were extracted from the corresponding databases. Univariate Cox regression analysis revealed 11 prognosis-related IRGs, followed by establishment of a regulatory network on prognosis-related IRGs at transcriptional levels. Functionally, IRG GLP2R was negatively modulated by TF MYH11, whereas IRG TDGF1 was positively modulated by TF TFAP2A. Multivariate Cox regression analysis was subsequently performed to establish a prognostic model on the basis of seven prognosis-related IRGs (GLP2R, ESM1, TDGF1, SLC10A2, INHBA, STC2, and CXCL1). Moreover, correlation analysis of immunocyte infiltration also revealed that the seven-IRG prognostic model was positively associated with five types of immunocytes (dendritic cell, macrophage, CD4 T cell, CD8 T cell, and neutrophil), which may directly reflect tumor immune state in COAD. Conclusions: Our present findings indicate that the prognostic model based on prognosis-related IRGs plays a crucial role in the clinical supervision and prognostic prediction of COAD patients at both molecular and cellular levels.

[Determination of degree of esterification in pectic polysaccharides from Angelica sinensis (Oliv.) diels by Fourier transform infrared spectroscopy].

An infrared spectroscopy method for rapid quantitative determination of the degree of esterification (DE) of pectic polysaccharides was developed. Taking pectic polysaccharides from angelica sinensis as samples, the calibration curve was established between DE and the ratio of A1 730/(A1 730 + A1 630). The square of the linear correlation coefficient was 0.822, indicating a good linear relationship between the DE and the absorbent area at 1 730 and 1 630 cm(-1). Using this method, the DE of pectic polysaccharides from angelica sinensis was determined to be between 42.36% and 54.06% for crude and purified samples respectively. The relationship between infrared spectroscopy data and titrimetrically determined DE values was investigated, indicating an excellent reproducibility. This method is characterized by less sample, simple manipulation, higher sensibility, and speedy analysis compared to chemical method and other instrumentations. FTIR shows a good feasibility and can be a rapid, alternative method to titrimetric analysis for DE determination.