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BackgroundSaliva secretion and oral microbiota change in rhythm with our biological clock. Dysbiosis of the oral microbiome and alcohol consumption have a two-way interactive impact, but little is known about whether the oral microbiome undergoes diurnal changes in composition and function during the daytime in patients with alcohol dependence (AD).MethodsThe impact of alcohol consumption on the diurnal salivary microbiome was examined in a case-control study of 32 AD patients and 21 healthy control (HC) subjects. We tested the changes in microbial composition and individual taxon abundance by 16S rRNA gene sequencing.ResultsThe present study is the first report showing that alcohol consumption enhanced the richness of the salivary microbiome and lowered the evenness. The composition of the oral microbiota changed significantly in alcohol-dependent patients. Additionally, certain genera were enriched in the AD group, including Actinomyces, Leptotrichia, Sphaerochaeta and Cyanobacteria, all of which have pathogenic effects on the host. There is a correlation between liver enzymes and oral microbiota. KEGG function analysis also showed obvious alterations during the daytime.ConclusionAlcohol drinking influences diurnal changes in the oral microbiota, leading to flora disturbance and related functional impairment. In particular, the diurnal changes of the oral microbiota may open avenues for potential interventions that can relieve the detrimental consequences of AD.

Objective: This study aimed to evaluate methotrexate efficacy in patients with Crohn’s disease (CD) and ulcerative colitis (UC), and identify predictors of surgery for patients who were initially treated with methotrexate monotherapy.Design: We performed a retrospective analysis of 34,860 patients with inflammatory bowel disease (IBD) in the IBD Bioresource (United Kingdom) prior to 9 November 2021. Logistic regression was used to identify factors associated with methotrexate efficacy. The data were randomly stratified into training and testing sets (7:3). Nomograms were developed based on Cox regression analysis outcomes. The predictive accuracy and discriminative ability were determined using the concordance index (C-index) and calibration curves.Results: Overall, 1,042 patients (CD: 791, UC: 251) were included. Independent factors associated with effective methotrexate monotherapy were younger age at diagnosis, latest therapy period, exclusive upper gastrointestinal tract disease (for CD), and longer duration between diagnosis and methotrexate initiation (for UC). For CD, predictors in the nomogram were gender, treatment era, tolerance, lesion site, perianal involvement, disease behaviour, and biologics requirements (C-index: 0.711 and 0.732 for training and validation cohorts, respectively). For UC, the factors were age at diagnosis and sex (C-index: 0.784 and 0.690 for training and validation cohorts, respectively). Calibration curves demonstrated good agreement between predictions and actual observations.

The aberrant vascular connecting channel that forms between the portal vein and the hepatic artery is the essence of a hepatic arterioportal fistula. Congenital hepatic arterioportal fistula more frequently occurs in early childhood rather than in adults. We describe a rare instance of a large, isolated, congenital hepatic arterioportal fistula that was successfully treated following selective hepatic arteriography and transcatheter embolization. The patient presented with significant variceal bleeding when the fistula was discovered at the age of 73. The patient's condition improved during the brief postoperative follow-up period without a recurrence. Our research suggests that in older patients with portal hypertension and an unclear etiology, selective arteriography and embolization can provide a definitive diagnosis and successfully treat symptoms.

Allicin is the main active ingredient in freshly-crushed garlic and some other allium plants, and its anticancer effect on cancers of digestive system has been confirmed in many studies. The aim of this review is to summarize epidemiological studies and in vitro and in vivo investigations on the anticancer effects of allicin and its secondary metabolites, as well as their biological functions. In epidemiological studies of esophageal cancer, liver cancer, pancreatic cancer, and biliary tract cancer, the anticancer effect of garlic has been confirmed consistently. However, the results obtained from epidemiological studies in gastric cancer and colon cancer are inconsistent. In vitro studies demonstrated that allicin and its secondary metabolites play an antitumor role by inhibiting tumor cell proliferation, inducing apoptosis, controlling tumor invasion and metastasis, decreasing angiogenesis, suppressing Helicobacter pylori, enhancing the efficacy of chemotherapeutic drugs, and reducing the damage caused by chemotherapeutic drugs. In vivo studies further demonstrate that allicin and its secondary metabolites inhibit cancers of the digestive system. This review describes the mechanisms against cancers of digestive system and therapeutic potential of allicin and its secondary metabolites.

Both colorectal and gastric cancer are lethal solid-tumor malignancies, leading to the majority of cancer-associated deaths worldwide. Although colorectal cancer (CRC) and gastric cancer (GC) share many similarities, the prognosis and drug response of CRC and GC are different. However, determinants for such differences have not been elucidated. To avoid genetic background variance, we performed multi-omics analysis, including single-cell RNA sequencing, whole-exome sequencing, and microbiome sequencing, to dissect the tumor immune signature of synchronous primary tumors of GC and CRC. We found that cellular components of juxta-tumoral sites were quite similar, while tumoral cellular components were specific to the tumoral sites. In addition, the mutational landscape and microbiome contributed to the distinct TME cellular components. Overall, we found that different prognoses and drug responses of GC and CRC were mainly due to the distinct TME determined by mutational landscape and microbiome components.

With the development of geo-positioning technologies, the volumes of spatio-textual data are growing rapidly. These data are available in many applications such as location-based services and geo-social networks, and thus, various types of geo-social keyword queries have been intensively studied in the literature. A top-k geo-social keyword (TkGSK) query retrieves the objects by considering spatial, social, and textual constraints between the query and objects. Moreover, the result diversification is becoming a common practice to enhance the quality of the query result. Motivated by these, in this paper, we study the problem of diversified top-k geo-social keyword (DkGSK) query, which considers not only the relevance but also the diversity of the result. We first prove that this problem is NP-hard, and then, we present an exact algorithm with several effective pruning strategies. Also, we develop an approximate algorithm with proved approximation ratio to support the D k GSK query. Considerable experiments on real data sets demonstrate the effectiveness and efficiency of our proposed algorithms.

Predicting motion of surrounding agents is critical to real-world applications of tactical path planning for autonomous driving. Due to the complex temporal dependencies and social interactions of agents, on-line trajectory prediction is a challenging task. With the development of attention mechanism in recent years, transformer model has been applied in natural language sequence processing first and then image processing. In this paper, we present a Spatial-Channel Transformer Network for trajectory prediction with attention functions. Instead of RNN models, we employ transformer model to capture the spatial-temporal features of agents. A channel-wise module is inserted to measure the social interaction between agents. We find that the Spatial-Channel Transformer Network achieves promising results on real-world trajectory prediction datasets on the traffic scenes.

Electric submersible screw pump often works at high speed, which has the characteristics of high speed, high temperature and large rubber deformation. In case of sudden shutdown, the rubber will not shrink at high temperature, which may lead to serious accidents such as pump locking and electrode burning. In the initial stage of pump start-up and restart after pump shutdown, due to the above reasons, it is often difficult to start the pump, which makes the pump unable to work normally. Therefore, this paper studies the clearance value of the electric submersible screw pump, calculates and tests the interference amount and initial interference amount, improves and optimizes the clearance value of the electric submersible screw pump, effectively improves the working efficiency and service life of the electric submersible screw pump, achieves the purpose of improving the quality and efficiency of oilfield production, and has a very important practical significance for the development of the rodless pump market.

A Reverse Top-k Geo-Social Keyword Query (RkGSKQ) aims to find all the users who have a given geo-social object in their top-k geo-social keyword query results. This query is practical in detecting prospective customers for online business in social networks. Existing work on RkGSKQ only explored efficient approaches in answering a single query per time, which could not be efficient in processing multiple queries in a query batch. In many real-life applications, multiple RkGSKQs for multiple query objects can be issued at the same time. To this end, in this paper, we focus on the efficient batch processing algorithm for multiple RkGSKQs. To reduce the overall cost and find concurrently results of multiple queries, we present a group processing framework based on the current state-of-the-art indexing and group pruning strategies to answer multiple RkGSKQs by sharing common CPU and I/O costs. Extensive experiments on three data sets demonstrate the effectiveness and efficiency of our proposed methods.

OBJECTIVE: X-ray luminescence computed tomography (XLCT) has played a crucial role in pre-clinical research and effective diagnosis of disease. However, due to the ill-posed of the XLCT inverse problem, the generalization of reconstruction methods and the selection of appropriate regularization parameters are still challenging in practical applications. In this research, an robust Elastic net-L1L2 reconstruction method is proposed aiming to the challenge. APPROACH: Firstly, our approach consists of L1 and L2 regularization to enhance the sparsity and suppress the smoothness. Secondly, through optimal approximation of the optimization problem, double modification of Landweber algorithm is adopted to solve the Elastic net-L1L2 regulazation. Thirdly, drawing on the ideal of supervised learning, multi-parameter K-fold cross validation strategy is proposed to determin the optimal parameters adaptively. MAIN RESULTS: To evaluate the performance of the Elastic net-L1L2 method, numerical simulations, phantom and in vivo experiments were conducted. In these experiments, the Elastic net-L1L2 method achieved the minimum reconstruction error (with smallest location error (LE), fluorescent yield relative error (FYRE), normalized root-mean-square error (NRMSE)) and the best image reconstruction quality (with largest contrast-to-noise ratio (CNR) and Dice similarity) among all methods. The results demonstrated that Elastic net-L1L2 can obtain superior reconstruction performance in terms of location accuracy, dual source resolution, robustness and \emph{in vivo} practicability. SIGNIFICANCE: It is believed that this study will further benefit preclinical applications with a view to provide a more reliable reference for the later researches on XLCT.

A reasonable condition is suggested to match the displacements and stresses in a hybrid stress element. Based on Hellinger-Reissner principle the displacement and stress modes are assumed to include the complete polynomials in the natural coordinates of an element. The work done by the assumed stresses on the nonconforming strains in an element should vanish. Taking this as a matching condition the dependent stress parameters can be eliminated and a rank sufficient hybrid stress element can be formulated. it contains the minimum number of stress parameters and is invariant for coordinates. Without perturbation a new 4-node (5 stress parameters) plane hybrid stress element has been developed. It can be arranged to satisfy the patch test. To demonstrate the properties of the element the solutions to some example problems are included