Accuracy of Xpert Carba-R Assay for the Diagnosis of Carbapenemase-producing Organisms from Rectal Swabs in Asia: a Diagnostic Meta-analysis.

The Cepheid Xpert Carba-R assay has been demonstrated to be reliable for rapid detection of carbapenemase-producing orgnisms (CPO) directly from rectal swabs but the performance of which remains unclear in Asia.We searched PubMed, EMBASE and Cochrane Library databases to identify studies according to predetermined criteria. STATA 13.0 software was used to analyze the tests for sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), area under the summary receiver operating characteristic curves (AUC). QUADAS-2 was used to assess the quality of included studies with RevMan 5.2. A total of 5 unique studies involving 10807 samples met the inclusion criteria. The pooled sensitivity, specificity, PLR, NLR, and the AUC with 95% CIs of Xpert Carba-R were 0.91 (0.72-0.97), 0.99 (0.96-1.00), 71.24 (25.41-199.73), 0.09 (0.03-0.32), 0.99 (0.98-1.00), respectively. Deeks'funnel plot showed no publication bias.The present meta-analysis showed the Xpert Carba-R assay had good sensitivity and perfect specificity for detecting CPOs on rectal swabs.

Clinicopathological features of hepatoid adenocarcinoma and non-hepatoid adenocarcinoma of the stomach: A systematic review and meta-analysis.

BACKGROUND: Hepatoid adenocarcinoma of the stomach (HAS) is an extremely rare and unique malignant gastric tumor with a significantly worse prognosis than non-hepatoid adenocarcinoma of the stomach (non-HAS). The present study explored the clinicopathological features of HAS and non-HAS patients to provide insights into HAS treatment strategies. METHODS: From December 26, 2023, we performed a comprehensive search of the PubMed, Web of Science, Cochrane Library, and Embase.com databases for relevant studies. Two authors independently screened the studies, evaluated their quality, extracted data, and performed the analyses. This study was registered with PROSPERO on January 2, 2024. RESULTS: Nine retrospective studies were included for analysis after screening 833 articles. A total of 350 and 924 patients were enrolled in the HAS and non-HAS groups, respectively. While no significant differences were observed in age, sex, tumor size, T3 or T4 stage, and N2 or N3 stage between the two groups, the HAS group exhibited higher rates of lymph node metastasis (OR = 1.93, 95% CI: 1.19-3.13, p = 0.007), liver metastasis (OR = 3.45, 95% CI: 2.26-5.28, p < 0.001), and vascular invasion (OR = 2.76, 95% CI: 2.05-3.71, p < 0.001). Additionally, the HAS group had lower 3-year survival rates (HR = 2.35, 95% CI: 1.70-3.25, p < 0.001) and 5-year survival rates (HR = 3.63, 95% CI: 1.49-8.88, p = 0.005), but lower rates of lymphatic permeation (OR = 0.68, 95% CI: 0.47-0.99, p = 0.040). CONCLUSION: Based on the current clinical evidence, patients with HAS present distinct clinicopathological features, greater invasiveness, and poorer prognosis than non-HAS patients. Further research is warranted to develop optimal treatment strategies for HAS.

Identification of efficient amine transaminase and applicability in dual transaminases cascade for synthesis of L-phosphinothricin.

L-phosphinothricin (L-PPT) is the most popular broad-spectrum and highly effective herbicide. Transaminases (TAs) play a pivotal role in asymmetric synthesis of L-PPT, yet encounter the challenge of unfavorable reaction equilibrium. In this study, the novel dual transaminases cascade system (DTCS) was introduced to facilitate the synthesis of L-PPT. The specific amine transaminase BdATA, originating from Bradyrhizobium diazoefficiens ZJY088, was screened and identified. It exhibited remarkable activity, good stability, and required only 2.5 equivalents of isopropylamine to transform pyruvate effectively. By coupling BdATA with previously reported SeTA to construct the DTCS for pyruvate removal in situ, the L-PPT yield escalated from 37.37 % to 85.35 %. Three advantages of the DTCS were presented: the removal of pyruvate alleviated by-product inhibition, the use of isopropylamine reduced reliance on excess L-alanine, and no demand for expensive cofactors like NAD(P)H. It demonstrated an innovative idea for addressing the challenges associated with transaminase-mediated synthesis of L-PPT.

Integrated Multi-Omics Analysis Reveals Mountain-Cultivated Ginseng Ameliorates Cold-Stimulated Steroid-Resistant Asthma by Regulating Interactions among Microbiota, Genes, and Metabolites.

Steroid-resistant asthma (SRA), resisting glucocorticoids such as dexamethasone (DEX), is a bottleneck in the treatment of asthma. It is characterized by a predominantly neutrophilic inflammatory subtype and is prone to developing into severe refractory asthma and fatal asthma. Currently, there is a lack of universally effective treatments for SRA. Moreover, since cold stimulation does increase the risk of asthma development and exacerbate asthma symptoms, the treatment of cold-stimulated SRA (CSRA) will face greater challenges. To find effective new methods to ameliorate CSRA, this study established a CSRA mouse model of allergic airway inflammation mimicking human asthma for the first time and evaluated the alleviating effects of 80% ethanol extract of mountain-cultivated ginseng (MCG) based on multi-omics analysis. The results indicate that cold stimulation indeed exacerbated the SRA-related symptoms in mice; the DEX individual treatment did not show a satisfactory effect; while the combination treatment of DEX and MCG could dose-dependently significantly enhance the lung function; reduce neutrophil aggregation; decrease the levels of LPS, IFN-γ, IL-1ß, CXCL8, and IL-17; increase the level of IL-10; alleviate the inflammatory infiltration; and decrease the mucus secretion and the expression of MUC5AC. Moreover, the combination of DEX and high-dose (200 mg/kg) MCG could significantly increase the levels of tight junction proteins (TJs), regulate the disordered intestinal flora, increase the content of short-chain fatty acids (SCFAs), and regulate the abnormal gene profile and metabolic profile. Multi-omics integrated analysis showed that 7 gut microbes, 34 genes, 6 metabolites, and the involved 15 metabolic/signaling pathways were closely related to the pharmacological effects of combination therapy. In conclusion, integrated multi-omics profiling highlighted the benefits of MCG for CSRA mice by modulating the interactions of microbiota, genes, and metabolites. MCG shows great potential as a functional food in the adjuvant treatment of CSRA.

ADAMTS18-fibronectin interaction regulates the morphology of liver sinusoidal endothelial cells.

Liver sinusoidal endothelial cells (LSECs) have a unique morphological structure known as "fenestra" that plays a crucial role in liver substance exchange and homeostasis maintenance. In this study, we demonstrate that ADAMTS18 protease is primarily secreted by fetal liver endothelial cells. ADAMTS18 deficiency leads to enlarged fenestrae and increased porosity of LSECs, microthrombus formation in liver vessels, and an imbalance of liver oxidative stress. These defects worsen carbon tetrachloride (CCl4)-induced liver fibrosis and diethylnitrosamine (DEN)/high-fat-induced hepatocellular carcinoma (HCC) in adult Adamts18-deficient mice. Mechanically, ADAMTS18 functions as a modifier of fibronectin (FN) to regulate the morphological acquisition of LSECs via the vascular endothelial growth factor A (VEGFA) signaling pathways. Collectively, a mechanism is proposed for LSEC morphogenesis and liver homeostasis maintenance via ADAMTS18-FN-VEGFA niches.

CT-Based AI model for predicting therapeutic outcomes in ureteral stones after single extracorporeal shock wave lithotripsy through a cohort study.

OBJECTIVES: Exploring the efficacy of an artificial intelligence (AI) model derived from the analysis of CT images to precisely forecast the therapeutic outcomes of singular-session extracorporeal shock wave lithotripsy (ESWL) in the management of ureteral stones. METHODS: A total of 317 patients diagnosed clinically with ureteral stones were included in this investigation. Unenhanced CT was administered to the participants within the initial fortnight preceding the inaugural ESWL. The internal cohort consisted of 250 individuals from a local healthcare facility, whereas the external cohort comprised 67 participants from another local medical institution. The proposed framework comprises three main components: an automated semantic segmentation model developed using 3D U-Net, a feature extractor that integrates radiomics and autoencoder techniques, and an ESWL efficacy prediction model trained with various machine learning algorithms. All participants underwent thorough postoperative follow-up examinations four weeks hence. The efficacy of ESWL was defined by the absence of stones or residual fragments measuring ≤2 mm in KUB X-ray assessments. Model stability and generalizability were judiciously validated through a fivefold cross-validation approach and a multi-center external test strategy. Moreover, Shapley Additive Explanations (SHAP) values for individual features were computed to elucidate the nuanced contributions of each feature to the model's decision-making process. RESULTS: The semantic segmentation model we constructed exhibited an average Dice coefficient of 0.88 ± 0.08 on the external testing set. ESWL classifiers built using Support Vector Machine (SVM), Random Forest (RF), XGBoost (XB), and CatBoost (CB) achieved AUROC values of 0.78, 0.84, 0.85, and 0.90, respectively, on the internal validation set. For the external testing set, SVM, RF, XB, and CB predicted ESWL with AUROC values of 0.68, 0.79, 0.80, and 0.83, respectively, with the last one being the optimal algorithm. The radiomics features and auto-encoder features made significant contributions to the decision-making process of the classification model. CONCLUSIONS: This investigation unmistakably underscores the remarkable predictive prowess exhibited by a scrupulously crafted AI model using CT images to precisely anticipate the therapeutic results of a singular session of extracorporeal shock wave lithotripsy for ureteral stones.

Exosome-transmitted circular RNA circ-LMO7 facilitates the progression of osteosarcoma by regulating miR-21-5p/ARHGAP24 axis.

The potential function and mechanism of circRNAs in regulating malignant performances of Osteosarcoma (OS) cells have not been well investigated. The expression level of CircLMO7, miR-21-5p and ARHGAP24 were detected by RT-qPCR. The relationship between miR-21-5p and circ-LMO7, as well as between miR-21-5p and ARHGAP24, was predicted and examined through bioinformatics analysis and luciferase reporter gene experiments. Moreover, OS cell growth, invasion, migration, and apoptosis were detected using the cell counting kit-8 (CCK-8), transwell and flow cytometry assays, respectively. ARHGAP24 protein level was measured using western blotting. In present study, we choose to investigate the role and mechanism of circ-LOM7 on OS cell proliferation, migration and invasion. circ-LOM7 was found to be down-regulated in OS tissues and cell lines. Enforced expression of circ-LOM7 suppressed the growth, invasion, and migration of OS cells. In contrast, decreasing circ-LMO7 expression had opposite effects. Furthermore, miR-21-5p was predicted to be sponged by circ-LMO7, and had an opposite role of circ-LMO7 in OS. Moreover, ARHGAP24 served as miR-21-5p's downstream target. Mechanistically, circ-LMO7 was packed in exosomes and acted as a cancer-suppresser on OS by sponging miR-21-5p and upregulating the expression of ARHGAP24. The exosomal circ-LMO7 expression was significantly decreased in OS cell exosomes, and co-culture experiments showed that exosomal circ-LMO7 suppressed the proliferation ability of OS cells. Circ-LMO7 exerts as a tumor suppressor in OS, and the circ-LMO7/miR-21-5P/ARHGAP24 axis is involved in OS progression.

Novel applications of Yinhua Miyanling tablets in ulcerative colitis treatment based on metabolomics and network pharmacology.

BACKGROUND: Yinhua Miyanling tablets (YMT), comprising 10 Chinese medicinal compounds, is a proprietary Chinese medicine used in the clinical treatment of urinary tract infections. Medicinal compounds, extracts, or certain monomeric components in YMT all show good effect on ulcerative colitis (UC). However, no evidence supporting YMT as a whole prescription for UC treatment is available. PURPOSE: To evaluate the anti-UC activity of YMT and elucidate the underlying mechanisms. The objective of the study was to provide evidence for the add-on development of YMT to treat UC. METHODS: First, YMT's protective effect on the intestinal barrier was evaluated using a lipopolysaccharide (LPS)-induced Caco-2 intestinal injury model. Second, the UC mouse model was established using dextran sodium sulfate (DSS) to determine YMT's influence on symptoms, inflammatory factors, intestinal barrier, and histopathological changes in the colon. Third, an integrated method combining metabolomics and network pharmacology was employed to screen core targets and key metabolic pathways with crucial roles in YMT's therapeutic effect on UC. Molecular docking was employed to identify the key targets with high affinity. Finally, western blotting was performed to validate the mechanism of YMT action against UC. RESULTS: YMT enhanced the transepithelial electrical resistance value and improved the expression of proteins of the tight junctions dose-dependently in LPS-induced Caco-2 cells. UC mice treated with YMT exhibited alleviated pathological lesions of the colon tissue in the in vivo pharmacodynamic experiments. The colonic lengths tended to be normal, and the levels of inflammatory factors (TNF-α, IL-6, and iNOS) along with those of the core enzymes (MPO, MDA, and SOD) improved. YMT effectively ameliorated DSS-induced colonic mucosal injury; pathological changes along with ultrastructure damage were significantly alleviated (evidenced by a relatively intact colon tissue, recovery of epithelial damage, repaired gland, reduced infiltration of inflammatory cells and epithelial cells arranged closely with dense microvilli). Seven key targets (IL-6, TNF-α, MPO, COX-2, HK2, TPH, and CYP1A2) and four key metabolic pathways (arachidonic acid metabolism, linoleate metabolism, glycolysis, and gluconeogenesis and tyrosine biosynthesis) were identified to play vital roles in the treatment on UC using YMT. CONCLUSIONS: YMT exerts beneficial therapeutic effects on UC by regulating multiple endogenous metabolites, targets, and metabolic pathways, suggestive of its potential novel application in UC treatment.

The evolution, pathogenicity and transmissibility of quadruple reassortant H1N2 swine influenza virus in China: A potential threat to public health.

Swine are regarded as "intermediate hosts" or "mixing vessels" of influenza viruses, capable of generating strains with pandemic potential. From 2020 to 2021, we conducted surveillance on swine H1N2 influenza (swH1N2) viruses in swine farms located in Guangdong, Yunnan, and Guizhou provinces in southern China, as well as Henan and Shandong provinces in northern China. We systematically analyzed the evolution and pathogenicity of swH1N2 isolates, and characterized their replication and transmission abilities. The isolated viruses are quadruple reassortant H1N2 viruses containing genes from pdm/09 H1N1 (PB2, PB1, PA and NP genes), triple-reassortant swine (NS gene), Eurasian Avian-like (HA and M genes), and recent human H3N2 (NA gene) lineages. The NA, PB2, and NP of SW/188/20 and SW/198/20 show high gene similarities to A/Guangdong/Yue Fang277/2017 (H3N2). The HA gene of swH1N2 exhibits a high evolutionary rate. The five swH1N2 isolates replicate efficiently in human, canine, and swine cells, as well as in the turbinate, trachea, and lungs of mice. A/swine/Shandong/198/2020 strain efficiently replicates in the respiratory tract of pigs and effectively transmitted among them. Collectively, these current swH1N2 viruses possess zoonotic potential, highlighting the need for strengthened surveillance of swH1N2 viruses.

Nonylphenol and its derivatives: Environmental distribution, treatment strategy, management and future perspectives.

In recent years, emerging pollutants, including nonylphenol (NP) and nonylphenol ethoxylate (NPE), have become a prominent topic. These substances are also classified as persistent organic pollutants. NP significantly affects the hormone secretion of organisms and exhibits neurotoxicity, which can affect the human hippocampus. Therefore, various countries are paying increased attention to NP regulation. NPEs are precursors of NPs and are widely used in the manufacture of various detergents and lubricants. NPEs can easily decompose into NPs, which possess strong biological and environmental toxicity. This review primarily addresses the distribution, toxicity mechanisms and performance, degradation technologies, management policies, and green alternative reagents of NPs and NPEs. Traditional treatment measures have been unable to completely remove NP from wastewater. With the progressively tightening management and regulatory policies, identifying proficient and convenient treatment methods and a sustainable substitute reagent with comparable product effectiveness is crucial.

Study on the Anti-Ulcerative Colitis Effect of Pseudo-Ginsenoside RT4 Based on Gut Microbiota, Pharmacokinetics, and Tissue Distribution.

The purpose of this study was to explore the therapeutic effect of the oral administration of pseudo-ginsenoside RT4 (RT4) on ulcerative colitis (UC), and to determine the rate of absorption and distribution of RT4 in mice with UC. Balb/c mice were induced using dextran sulfate sodium salts (DSS) to establish the UC model, and 10, 20, or 40 mg/kg of RT4 was subsequently administered via gavage. The clinical symptoms, inflammatory response, intestinal barrier, content of total short-chain fatty acids (SCFAs), and gut microbiota were investigated. Caco-2 cells were induced to establish the epithelial barrier damage model using LPS, and an intervention was performed using 4, 8, and 16 µg/mL of RT4. The inflammatory factors, transient electrical resistance (TEER), and tight-junction protein expression were determined. Finally, pharmacokinetic and tissue distribution studies following the intragastric administration of RT4 in UC mice were performed. According to the results in mice, RT4 decreased the disease activity index (DAI) score, restored the colon length, reduced the levels of pro-inflammatory cytokines (TNF-α, IL-6, and IL-1ß), and boosted the levels of immunosuppressive cytokine IL-10, increased the content of SCFAs, improved the colonic histopathology, maintained the ultrastructure of colonic mucosal epithelial cells, and corrected disturbances in the intestinal microbiota. Based on the results in caco-2 cells, RT4 reduced the levels of TNF-α, IL-6, and IL-1ß; protected integrity of monolayers; and increased tight-junction protein expression. Additionally, the main pharmacokinetic parameters (Cmax, Tmax, t1/2, Vd, CL, AUC) were obtained, the absolute bioavailability was calculated as 18.90% ± 2.70%, and the main distribution tissues were the small intestine and colon. In conclusion, RT4, with the features of slow elimination and directional distribution, could alleviate UC by inhibiting inflammatory factors, repairing the intestinal mucosal barrier, boosting the dominant intestinal microflora, and modulating the expression of SCFAs.

Identification of a novel thermostable transaminase and its application in L-phosphinothricin biosynthesis.

Transaminase (TA) is a crucial biocatalyst for enantioselective production of the herbicide L-phosphinothricin (L-PPT). The use of enzymatic cascades has been shown to effectively overcome the unfavorable thermodynamic equilibrium of TA-catalyzed transamination reaction, also increasing demand for TA stability. In this work, a novel thermostable transaminase (PtTA) from Pseudomonas thermotolerans was mined and characterized. The PtTA showed a high specific activity (28.63 U/mg) towards 2-oxo-4-[(hydroxy)(methyl)phosphinoyl]butyric acid (PPO), with excellent thermostability and substrate tolerance. Two cascade systems driven by PtTA were developed for L-PPT biosynthesis, including asymmetric synthesis of L-PPT from PPO and deracemization of D, L-PPT. For the asymmetric synthesis of L-PPT from PPO, a three-enzyme cascade was constructed as a recombinant Escherichia coli (E. coli G), by co-expressing PtTA, glutamate dehydrogenase (GluDH) and D-glucose dehydrogenase (GDH). Complete conversion of 400 mM PPO was achieved using only 40 mM amino donor L-glutamate. Furthermore, by coupling D-amino acid aminotransferase (Ym DAAT) from Bacillus sp. YM-1 and PtTA, a two-transaminase cascade was developed for the one-pot deracemization of D, L-PPT. Under the highest reported substrate concentration (800 mM D, L-PPT), a 90.43% L-PPT yield was realized. The superior catalytic performance of the PtTA-driven cascade demonstrated that the thermodynamic limitation was overcome, highlighting its application prospect for L-PPT biosynthesis. KEY POINTS: • A novel thermostable transaminase was mined for L-phosphinothricin biosynthesis. • The asymmetric synthesis of L-phosphinothricin was achieved via a three-enzyme cascade. • Development of a two-transaminase cascade for D, L-phosphinothricin deracemization.

Deep learning, geometric characterization and hydrodynamic modeling for assessing sewer defect impacts on urban flooding: A case study in Guangzhou, China.

Deep learning techniques have offered innovative and efficient tools for accurate and automated detection of sewer defects by leveraging large-scale sewer data and advanced feature learning algorithms. However, there has been a lack of thorough characterization of the geometric properties of segmented defects, let alone systematically calculate the severity level of sewer defects and quantitatively evaluate their impacts on flood conditions in hydrodynamic models. This study proposed a comprehensive framework and related metrics to accurately and automatically detect, segment, characterize, and evaluate the impacts of sewer defects on flooded nodes and volumes by integrating a DeepLabv3+-based segmentation technique, an automated geometric characterization and severity quantification module, and a GIS and SWMM-based hydrodynamic modeling. The results clearly showed in details where and how much the urban flooding was affected by the different defect types. The segmentation model achieved satisfactory detection performance, with mean pixel accuracy (MPA), mean intersection over union (MIoU), and frequency weighted intersection over union (FWIoU) of 0.99, 0.74 and 0.95, respectively. In terms of severity level quantification, there were 98%, 90%, 90% and 83% of predictions consistent with real conditions for falling off, obstacle, disjoint and leakage. It was shown that the number of surcharging manholes and total flood volume (TFV) were greatly affected by sewer defects, with over 16% increase in TFVs under all investigated rainfall events. The results addressed the impacts of sewer defects on urban flooding and demonstrated the powerful tools provided by the proposed framework for decision-making on sewer defect detection and management.

An automatic texture feature analysis framework of renal tumor: surgical, pathological, and molecular evaluation based on multi-phase abdominal CT.

OBJECTIVES: To determine whether the texture feature analysis of multi-phase abdominal CT can provide a robust prediction of benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in renal tumor. METHODS: A total of 1051 participants with renal tumor were split into the internal cohort (850 patients from four different hospitals) and the external testing cohort (201 patients from another local hospital). The proposed framework comprised a 3D-kidney and tumor segmentation model by 3D-UNet, a feature extractor for the regions of interest based on radiomics and image dimension reduction, and the six classifiers by XGBoost. A quantitative model interpretation method called SHAP was used to explore the contribution of each feature. RESULTS: The proposed multi-phase abdominal CT model provides robust prediction for benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in the internal validation set, with the AUROC values of 0.88 ± 0.1, 0.90 ± 0.1, 0.91 ± 0.1, 0.89 ± 0.1, 0.84 ± 0.1, and 0.88 ± 0.1, respectively. The external testing set also showed impressive results, with AUROC values of 0.83 ± 0.1, 0.83 ± 0.1, 0.85 ± 0.1, 0.81 ± 0.1, 0.79 ± 0.1, and 0.81 ± 0.1, respectively. The radiomics feature including the first-order statistics, the tumor size-related morphology, and the shape-related tumor features contributed most to the model predictions. CONCLUSIONS: Automatic texture feature analysis of abdominal multi-phase CT provides reliable predictions for multi-tasks, suggesting the potential usage of clinical application. CLINICAL RELEVANCE STATEMENT: The automatic texture feature analysis framework, based on multi-phase abdominal CT, provides robust and reliable predictions for multi-tasks. These valuable insights can serve as a guiding tool for clinical diagnosis and treatment, making medical imaging an essential component in the process. KEY POINTS: • The automatic texture feature analysis framework based on multi-phase abdominal CT can provide more accurate prediction of benign and malignant, histological subtype, pathological stage, nephrectomy risk, pathological grade, and Ki67 index in renal tumor. • The quantitative decomposition of the prediction model was conducted to explore the contribution of the extracted feature. • The study involving 1051 patients from 5 medical centers, along with a heterogeneous external data testing strategy, can be seamlessly transferred to various tasks involving new datasets.

Optimal timing of surgery for gastric cancer after neoadjuvant chemotherapy: a systematic review and meta-analysis.

BACKGROUND: Following neoadjuvant chemotherapy, surgical resection is one of the most preferred treatment options for locally advanced gastric cancer patients. However, the optimal time interval between chemotherapy and surgery is unclear. This review aimed to identify the optimal time interval between neoadjuvant chemotherapy and surgery for advanced gastric cancer. METHODS: Beginning on November 12, 2022, we searched the PubMed, Cochrane Library, Web of Science databases, and Embase.com databases for relevant English-language research. Two authors independently screened the studies, assessed their quality, extracted the data, and analyzed the results. The primary goal was to investigate the relationship between the time interval to surgery (TTS) and long-term survival outcomes for patients. This study has been registered with PROSPERO (CRD42022365196). RESULTS: After an initial search of 4880 articles, the meta-analysis review ultimately included only five retrospective studies. Ultimately, this meta-analysis included 1171 patients, of which 411 patients had TTS of < 4 weeks, 507 patients had TTS of 4-6 weeks, and 253 patients had TTS of > 6 weeks. In survival analysis, patients with TTS of > 6 weeks had poorer overall survival outcomes than patients with TTS of 4-6 weeks (HR = 1.34, 95% CI: 1.03-1.75, P = 0.03). No significant differences were found in terms of disease-free survival the groups. CONCLUSION: Based on the current clinical evidence, patients with locally advanced gastric cancer may benefit better with a TTS of 4-6 weeks; however, this option still needs additional study.

Endophytic fungi of Lycium barbarum: isolation, determination, bioactivity and separation of compounds.

Lycium barbarum is widely distributed in China and used as a traditional Chinese medicine herb to treat dizziness, abdominal pain, dry cough, headache and fatigue. Several studies have examined the endophytes of L. barbarum from northwest China; however, few have focused on that from eastern China. The objective of this study was to isolate and determine the endophytic fungi of L. barbarum from Shandong province, as well as to obtain and identify active secondary metabolites from the endophytes. In this study, 17 endophytic fungi were isolated from L. barbarum and denoted as GQ-1 to GQ-17, respectively. These fungi were further classified into ten genera based on the morphological and ITS identification. The crude extracts of these fungi were obtained by using liquid fermentation and EtOAc extraction, and their antibacterial, cytotoxic, and antioxidant activities were evaluated. The results showed that GQ-6 and GQ-16 exhibited high inhibitory activity; GQ-6 and GQ-9 showed high cytotoxic activity and GQ-5 exhibited high scavenging capability for DPPH free radicals. Additionally, Cladosporium sp. GQ-6 was used to investigate the secondary metabolites. The crude extracts were purified by using column chromatography, reverse column, and liquid chromatography, and four monomeric compounds were identified, including two known compounds (α-acetylorcinol (1) and cladosporester B (2)) and two new compounds (cladosporacid F (3) and cladosporester D (4)). The anti-fungal and antibacterial activities of these compounds were confirmed, but no cytotoxic activity was observed. In conclusion, endophytic fungi of L. barbarum from eastern China can serve as a potential source of active natural products with antibacterial and antioxidant properties.

Glutathione-dependent redox homeostasis is critical for chlorothalonil detoxification in tomato leaves.

Glutathione plays a critical role in plant growth, development and response to stress. It is a major cellular antioxidant and is involved in the detoxification of xenobiotics in many organisms, including plants. However, the role of glutathione-dependent redox homeostasis and associated molecular mechanisms regulating the antioxidant system and pesticide metabolism remains unclear. In this study, endogenous glutathione levels were manipulated by pharmacological treatments with glutathione synthesis inhibitors and oxidized glutathione. The application of oxidized glutathione enriched the cellular oxidation state, reduced the activity and transcript levels of antioxidant enzymes, upregulated the expression level of nitric oxide and Ca2+ related genes and the content, and increased the residue of chlorothalonil in tomato leaves. Further experiments confirmed that glutathione-induced redox homeostasis is critical for the reduction of pesticide residues. RNA sequencing analysis revealed that miRNA156 and miRNA169 that target transcription factor SQUAMOSA-Promoter Binding Proteins (SBP) and NUCLEAR FACTOR Y (NFY) potentially participate in glutathione-mediated pesticide degradation in tomato plants. Our study provides important clues for further dissection of pesticide degradation mechanisms via miRNAs in plants.

Relay run property of immobilized cholesterol oxidase on magnetic biochar for sterol removal.

This study investigated the biocatalytic performance of immobilized cholesterol oxidase (CHOD) on magnetite-based carbon (MBC) for degrading cholesterol. The results showed that MBC-CHOD exhibited higher activity and good affinity towards substrate compared to free enzyme and other immobilized enzymes. Mass spectra analysis revealed that MBC-CHOD damaged the main structure of cholesterol, benefitting the further biological treatment. The study proposes a Fenton process mechanism by which H2O2 is transferred to free radicals such as ·OH under acidic conditions, promoting further substrate degradation. This suggests that MBC-CHOD has a relay run property leading to high degradation of cholesterol. Molecular docking indicates that cholesterol preferentially binds to TYR-28 residue and LYS-138 residue in CHOD through hydrogen bonds. Overall, MBC-CHOD proved to be a promising candidate for efficient and sustainable cholesterol degradation.

A quantitative analysis framework of placenta accreta spectrum: placenta subtype, intraoperative bleeding, and hysterectomy risk evaluation based on magnetic resonance imaging-anatomical-clinical features.

Background: Placenta accreta spectrum (PAS) is a significant contributor to maternal morbidity and mortality. Our objective was to develop a quantitative analysis framework utilizing magnetic resonance imaging (MRI)-anatomical-clinical features to predict 3 clinically significant parameters in patients with PAS: placenta subtype (invasive vs. non-invasive placenta), intraoperative bleeding (≥1,500 vs. <1,500 mL), and hysterectomy risk (hysterectomy vs. non-hysterectomy). Methods: A total of 125 pregnant women with PAS from 2 medical centers were enrolled into an internal training set and an external testing set. Some 21 MRI-anatomical-clinical features were integrated as input into the framework. The proposed quantitative analytic framework contains mainly 3 classifiers built by extreme gradient boosting (XGBoost) and their testing in external datasets. We also further compared the accuracy of placenta subtype prediction between the proposed model and 4 radiologists. A quantitative model interpretation method called SHapley Additive exPlanations (SHAP) was conducted to explore the contribution of each feature. Results: The placenta subtype (invasive vs. non-invasive), intraoperative bleeding (≥1,500 vs. <1,500 mL), and hysterectomy risk (hysterectomy vs. non-hysterectomy) demonstrated impressive area under the receiver operating characteristic curve (AUROC) values of 0.93, 0.88, and 0.90, respectively, in the internal validation set. Even in the external testing set, these metrics maintained their strength, achieving AUROC values of 0.91, 0.82, and 0.82, respectively. Comparing our proposed framework to the 4 radiologists, our model exhibited superior accuracy, specificity, and sensitivity in predicting placental subtypes within the external testing cohort. The features associated with intraplacental dark T2 bands played a crucial role in the decision-making process of all 3 prediction models. Conclusions: The quantitative analysis framework can provide a robust method for classification of placenta subtype (invasive vs. non-invasive placenta), intraoperative bleeding (≥1,500 vs. <1,500 mL), and hysterectomy risk (hysterectomy vs. non-hysterectomy) based on MRI-anatomical-clinical features in PAS.

Driving Force Analysis of Natural Wetland in Northeast Plain Based on SSA-XGBoost Model.

Globally, natural wetlands have suffered severe ecological degradation (vegetation, soil, and biotic community) due to multiple factors. Understanding the spatiotemporal dynamics and driving forces of natural wetlands is the key to natural wetlands' protection and regional restoration. In this study, we first investigated the spatiotemporal evolutionary trends and shifting characteristics of natural wetlands in the Northeast Plain of China from 1990 to 2020. A dataset of driving-force evaluation indicators was constructed with nine indirect (elevation, temperature, road network, etc.) and four direct influencing factors (dryland, paddy field, woodland, grassland). Finally, we built the driving force analysis model of natural wetlands changes to quantitatively refine the contribution of different driving factors for natural wetlands' dynamic change by introducing the sparrow search algorithm (SSA) and extreme gradient boosting algorithm (XGBoost). The results showed that the total area of natural wetlands in the Northeast Plain of China increased by 32% from 1990 to 2020, mainly showing a first decline and then an increasing trend. Combined with the results of transfer intensity, we found that the substantial turn-out phenomenon of natural wetlands occurred in 2000-2005 and was mainly concentrated in the central and eastern parts of the Northeast Plain, while the substantial turn-in phenomenon of 2005-2010 was mainly located in the northeast of the study area. Compared with a traditional regression model, the SSA-XGBoost model not only weakened the multicollinearity of each driver but also significantly improved the generalization ability and interpretability of the model. The coefficient of determination (R2) of the SSA-XGBoost model exceeded 0.6 in both the natural wetland decline and rise cycles, which could effectively quantify the contribution of each driving factor. From the results of the model calculations, agricultural activities consisting of dryland and paddy fields during the entire cycle of natural wetland change were the main driving factors, with relative contributions of 18.59% and 15.40%, respectively. Both meteorological (temperature, precipitation) and topographic factors (elevation, slope) had a driving role in the spatiotemporal variation of natural wetlands. The gross domestic product (GDP) had the lowest contribution to natural wetlands' variation. This study provides a new method of quantitative analysis based on machine learning theory for determining the causes of natural wetland changes; it can be applied to large spatial scale areas, which is essential for a rapid monitoring of natural wetlands' resources and an accurate decision-making on the ecological environment's security.