Environmentally responsive changes in mucus indicators and microbiota of Chinese sturgeon Acipensersinensis.

The impact of environmental factors on the health of the endangered Chinese sturgeon (Acipenser sinensis) and the potential hazards associated with sample collection for health monitoring pose urgent need to its conservation. In this study, Chinese sturgeons were selected from indoor and outdoor environments to evaluate metabolic and tissue damage indicators, along with a non-specific immune enzyme in fish mucus. Additionally, the microbiota of both water bodies and fish mucus were determined using 16S rRNA high-throughput sequencing. The correlation between the indicators and the microbiota was investigated, along with the measurement of multiple environmental factors. The results revealed significantly higher levels of two metabolic indicators, total protein (TP) and cortisol (COR) in indoor fish mucus compared to outdoor fish mucus (p < 0.05). The activities of acid phosphatase (ACP), alkaline phosphatase (ALP), creatine kinase (CK), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH) were significantly higher in indoor fish, serving as indicators of tissue damage (p < 0.05). The activity of lysozyme (LZM) was significantly lower in indoor fish (p < 0.01). Biomarker analysis at the phylum and genus levels in outdoor samples revealed that microorganisms were primarily related to the catabolism of organic nutrients. In indoor environments, microorganisms displayed a broader spectrum of functions, including ecological niche establishment, host colonization, potential pathogenicity, and antagonism of pathogens. KEGG functional enrichment corroborated these findings. Dissolved oxygen (DO), electrical conductivity (EC), ammonia nitrogen (NH3-N), turbidity (TU), and chemical oxygen demand (COD) exerted effects on outdoor microbiota. Temperature (TEMP), nitrate (NO3-), total phosphorus (TP), and total nitrogen (TN) influenced indoor microbiota. Changes in mucus indicators, microbial structure, and function in both environments were highly correlated with these factors. Our study provides novel insights into the health impacts of different environments on Chinese sturgeon using a non-invasive method.

Tumor microenvironment characteristics association with clinical outcome in patients with resected intestinal-type gastric cancer.

BACKGROUND: Tumor microenvironment (TME) characteristics including tumor stroma ratio (TSR), tumor budding (TB), and tumor-infiltrating lymphocytes (TILs) were examined in resected gastric cancer. These TME features have been shown to indicate metastatic potential in colon cancer, and intestinal-type gastric cancer (IGC) has pathological similarities with that malignancy. METHODS: TSR, TB, and TILs were quantified in routine histological sections from 493 patients with IGC who underwent radical resection at 2 university hospitals in China from 2010 to 2016. TME variables were dichotomized as follows: TSR (50%), TILs (median), TB per international guidelines (4 buds/0.785mm2), and platelet-lymphocyte ratio (PLR) per survival ROC. Association of TME features with patient clinicopathological characteristics, time-to-recurrence (TTR), and cancer-specific-survival (CSS) were examined using univariate and multivariate analysis, including a relative contribution analysis by Cox regression. RESULTS: Patients whose tumors showed high TSR or high TB or low TILs were each significantly associated with increased T and N stage, higher histological grade, and poorer TTR and CSS at 5 years. Only TSR and N stage were independently associated with TTR and CSS after adjustment for covariates. PLR was only independently associated with TTR after adjustment for covariates. Among the variables examined, only TSR was significantly associated with both TTR (HR 1.72, 95% CI, 1.14-2.60, P = .01) and CSS (HR 1.62, 95% CI, 1.05-2.51, P = .03) multivariately. Relative contribution to TTR revealed that the top 3 contributors were N stage (45.1%), TSR (22.5%), and PLR (12.9%), while the top 3 contributors to CSS were N stage (59.9%), TSR (14.7%), and PLR (10.9%). CONCLUSIONS: Among the examined TME features, TSR was the most robust for prognostication and was significantly associated with both TTR and CSS. Furthermore, the relative contribution of TSR to patient TTR and CSS was second only to nodal status.

Effects of Citrobacter freundii on sturgeon: Insights from skin mucosal immunology and microbiota.

Skin mucus analysis has recently been used as a non-invasive method to evaluate for fish welfare. The present research study was conducted to examine the skin mucosal immunity and skin microbiota profiles of sturgeons infected with Citrobacter freundii. Our histology results showed that the thickness of the epidermal layer of skin remained thinner, and the number of mucous cells was significantly decreased in sturgeons after infection (p < 0.05). Total protein, alanine aminotransferase, aspartate aminotransferase, superoxide dismutase, and creatine kinase levels in the mucus showed biphasic pattern (decrease and then increase). Lactate dehydrogenase, lysozyme, and acid phosphatase activities in the mucus showed an increasing trend after infection. Furthermore, 16S rRNA sequencing also revealed that C. freundii infection also affected the diversity and community structure of the skin mucus microbiota. An increase in microbial diversity (p > 0.05) and a decrease in microbial abundance (p < 0.05) after infection were noted. The predominant bacterial phyla in the skin mucus were Proteobacteria, Fusobacteria, Bacteroidetes, Firmicutes, and Actinobacteria. Specifically, the relative abundance of Fusobacteria increased after infection. The predominant bacterial genera in the skin mucus were Cetobacterium, Pelomonas, Bradyrhizobium, Flavobacterium, and Pseudomonas. The relative abundance of Cetobacterium, Pseudomonas, and Flavobacterium increased after infection. Our current research findings will provide new insights into the theoretical basis for future research studies exploring the mechanism of sturgeon infection with C. freundii.

Indexing serum and mucous biochemical parameters of endangered Chinese sturgeon Acipenser sinensis with implications for health assessment.

The Chinese sturgeon (Acipenser sinensis) is a critically endangered aquatic fish. Health monitoring and welfare assessments are critical for the conservation of Chinese sturgeon. In this study, biochemical parameters of serum and skin mucus in Chinese sturgeon were examined to evaluate the potential biomarkers. Serum and mucous samples were obtained from Chinese sturgeon, and the levels of total protein (TP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), lactate dehydrogenase (LDH), creatine kinase (CK), lactic acid (LD), acid phosphatase (ACP), lysozyme (LYZ), glucose (GLU), and cortisol were determined. The concentrations of ALT, AST, cortisol, and LYZ were significantly higher in the mucous group than those in the serum group (p < 0.05). In addition, the concentrations of ALP, ACP, LD, LDH, CK, and TP were significantly higher level in the serum group than those in the mucous group (p < 0.05). Moreover, the correlations between serum and mucous biochemical parameters were established. Statistical analysis showed a positive correlation between serum and skin mucous markers (ACP, cortisol, and LYZ). AST versus ALT in serum and mucus showed a significant positive correlation (p < 0.01). A significant positive correlation was found between cortisol and CK in mucus (p < 0.01). Moreover, LD versus LDH in serum showed a significant but weak positive correlation (p < 0.01). Principal component analysis revealed a complete separation between the serum and mucous groups, with the biomarkers that contributed the most being ALP, TP, ALT, and AST. This study provides baseline data and reference intervals for serum and mucous biochemical parameters in presumably healthy Chinese sturgeons. The current study has important implications for the development of conservation strategies and the conservation status of critically endangered species.

Linking microbial genes to plasma and stool metabolites uncovers host-microbial interactions underlying ulcerative colitis disease course.

Understanding the role of the microbiome in inflammatory diseases requires the identification of microbial effector molecules. We established an approach to link disease-associated microbes to microbial metabolites by integrating paired metagenomics, stool and plasma metabolomics, and culturomics. We identified host-microbial interactions correlated with disease activity, inflammation, and the clinical course of ulcerative colitis (UC) in the Predicting Response to Standardized Colitis Therapy (PROTECT) pediatric inception cohort. In severe disease, metabolite changes included increased dipeptides and tauro-conjugated bile acids (BAs) and decreased amino-acid-conjugated BAs in stool, whereas in plasma polyamines (N-acetylputrescine and N1-acetylspermidine) increased. Using patient samples and Veillonella parvula as a model, we uncovered nitrate- and lactate-dependent metabolic pathways, experimentally linking V. parvula expansion to immunomodulatory tryptophan metabolite production. Additionally, V. parvula metabolizes immunosuppressive thiopurine drugs through xdhA xanthine dehydrogenase, potentially impairing the therapeutic response. Our findings demonstrate that the microbiome contributes to disease-associated metabolite changes, underscoring the importance of these interactions in disease pathology and treatment.

Bowel Stiffness Assessed by Shear-Wave Ultrasound Elastography Predicts Disease Behavior Progression in Patients With Crohn's Disease.

INTRODUCTION: There is a lack of reliable predictors of disease behavior progression in patients with Crohn's disease (CD). Real-time shear-wave elastography (SWE) is a novel method for evaluating tissue stiffness. However, its value for assessing CD has not yet been investigated. We aimed to explore the value of SWE and other ultrasound parameters at diagnosis in predicting CD behavior progression. METHODS: We retrospectively collected data from patients with CD with the nonstenotic nonpenetrating disease (B1 phenotype based on the Montreal classification). All patients underwent intestinal ultrasound at baseline and were followed up. The end point was defined as disease behavior progression to stricturing (B2) or penetrating (B3) disease. Cox regression analysis was performed for the association between baseline characteristics and subsequent end points. In addition, a multivariate nomogram was established to predict the risk of disease behavior progression quantitatively. RESULTS: A total of 130 patients with CD with B1 phenotype were enrolled. Twenty-seven patients (20.8%) developed B2 or B3 disease, with a median follow-up of 33 months. Multivariate analysis identified that SWE was the only independent predictor of disease behavior progression (hazard ratio 1.08, 95% confidence interval 1.03-1.12, P = 0.001). A reverse of the HR appeared at the cutoff 12.75 kPa. The nomogram incorporating SWE and other clinical characteristics showed a good prediction performance (area under the curve = 0.792). DISCUSSION: Intestinal stiffness assessed using SWE is an independent predictor of disease behavior progression in patients with CD. Patients with CD with SWE >12.75 kPa at diagnosis are prone to progress toward stricturing or penetrating diseases.

TRPV4 channel is involved in HSV-2 infection in human vaginal epithelial cells through triggering Ca2+ oscillation.

Herpes simplex virus (HSV) infection induces a rapid and transient increase in intracellular calcium concentration ([Ca2+]i), which plays a critical role in facilitating viral entry. T-type calcium channel blockers and EGTA, a chelate of extracellular Ca2+, suppress HSV-2 infection. But the cellular mechanisms mediating HSV infection-activated Ca2+ signaling have not been completely defined. In this study we investigated whether the TRPV4 channel was involved in HSV-2 infection in human vaginal epithelial cells. We showed that the TRPV4 channel was expressed in human vaginal epithelial cells (VK2/E6E7). Using distinct pharmacological tools, we demonstrated that activation of the TRPV4 channel induced Ca2+ influx, and the TRPV4 channel worked as a Ca2+-permeable channel in VK2/E6E7 cells. We detected a direct interaction between the TRPV4 channel protein and HSV-2 glycoprotein D in the plasma membrane of VK2/E6E7 cells and the vaginal tissues of HSV-2-infected mice as well as in phallic biopsies from genital herpes patients. Pretreatment with specific TRPV4 channel inhibitors, GSK2193874 (1-4 µM) and HC067047 (100 nM), or gene silence of the TRPV4 channel not only suppressed HSV-2 infectivity but also reduced HSV-2-induced cytokine and chemokine generation in VK2/E6E7 cells by blocking Ca2+ influx through TRPV4 channel. These results reveal that the TRPV4 channel works as a Ca2+-permeable channel to facilitate HSV-2 infection in host epithelial cells and suggest that the design and development of novel TRPV4 channel inhibitors may help to treat HSV-2 infections.

Improving and evaluating deep learning models of cellular organization.

MOTIVATION: Cells contain dozens of major organelles and thousands of other structures, many of which vary extensively in their number, size, shape and spatial distribution. This complexity and variation dramatically complicates the use of both traditional and deep learning methods to build accurate models of cell organization. Most cellular organelles are distinct objects with defined boundaries that do not overlap, while the pixel resolution of most imaging methods is n sufficient to resolve these boundaries. Thus while cell organization is conceptually object-based, most current methods are pixel-based. Using extensive image collections in which particular organelles were fluorescently labeled, deep learning methods can be used to build conditional autoencoder models for particular organelles. A major advance occurred with the use of a U-net approach to make multiple models all conditional upon a common reference, unlabeled image, allowing the relationships between different organelles to be at least partially inferred. RESULTS: We have developed improved Generative Adversarial Networks-based approaches for learning these models and have also developed novel criteria for evaluating how well synthetic cell images reflect the properties of real images. The first set of criteria measure how well models preserve the expected property that organelles do not overlap. We also developed a modified loss function that allows retraining of the models to minimize that overlap. The second set of criteria uses object-based modeling to compare object shape and spatial distribution between synthetic and real images. Our work provides the first demonstration that, at least for some organelles, deep learning models can capture object-level properties of cell images. AVAILABILITY AND IMPLEMENTATION: http://murphylab.cbd.cmu.edu/Software/2022_insilico. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Deep Learning System to Predict the Histopathological Results From Urine Cytopathological Images.

Background: Although deep learning systems (DLSs) have been developed to diagnose urine cytology, more evidence is required to prove if such systems can predict histopathology results as well. Methods: We retrospectively retrieved urine cytology slides and matched histological results. High-power field panel images were annotated by a certified urological pathologist. A deep learning system was designed with a ResNet101 Faster R-CNN (faster region-based convolutional neural network). It was firstly built to spot cancer cells. Then, it was directly used to predict the likelihood of the presence of tissue malignancy. Results: We retrieved 441 positive cases and 395 negative cases. The development involved 387 positive cases, accounting for 2,668 labeled cells, to train the DLS to spot cancer cells. The DLS was then used to predict corresponding histopathology results. In an internal test set of 85 cases, the area under the curve (AUC) was 0.90 (95%CI 0.84-0.96), and the kappa score was 0.68 (95%CI 0.52-0.84), indicating substantial agreement. The F1 score was 0.56, sensitivity was 71% (95%CI 52%-85%), and specificity was 94% (95%CI 84%-98%). In an extra test set of 333 cases, the DLS achieved 0.25 false-positive cells per image. The AUC was 0.93 (95%CI 0.90-0.95), and the kappa score was 0.58 (95%CI 0.46-0.70) indicating moderate agreement. The F1 score was 0.66, sensitivity was 67% (95%CI 54%-78%), and specificity was 92% (95%CI 88%-95%). Conclusions: The deep learning system could predict if there was malignancy using cytocentrifuged urine cytology images. The process was explainable since the prediction of malignancy was directly based on the abnormal cells selected by the model and can be verified by examining those candidate abnormal cells in each image. Thus, this DLS was not just a tool for pathologists in cytology diagnosis. It simultaneously provided novel histopathologic insights for urologists.

Deciphering mechanisms and implications of bacterial translocation in human health and disease.

Significant increases in potential microbial translocation, especially along the oral-gut axis, have been identified in many immune-related and inflammatory diseases, such as inflammatory bowel disease, colorectal cancer, rheumatoid arthritis, and liver cirrhosis, for which we currently have no cure or long-term treatment options. Recent advances in computational and experimental omics approaches now enable strain tracking, functional profiling, and strain isolation in unprecedented detail, which has the potential to elucidate the causes and consequences of microbial translocation. In this review, we discuss current evidence for the detection of bacterial translocation, examine different translocation axes with a primary focus on the oral-gut axis, and outline currently known translocation mechanisms and how they adversely affect the host in disease. Finally, we conclude with an overview of state-of-the-art computational and experimental tools for strain tracking and highlight the required next steps to elucidate the role of bacterial translocation in human health.

Identifying complex motifs in massive omics data with a variable-convolutional layer in deep neural network.

Motif identification is among the most common and essential computational tasks for bioinformatics and genomics. Here we proposed a novel convolutional layer for deep neural network, named variable convolutional (vConv) layer, for effective motif identification in high-throughput omics data by learning kernel length from data adaptively. Empirical evaluations on DNA-protein binding and DNase footprinting cases well demonstrated that vConv-based networks have superior performance to their convolutional counterparts regardless of model complexity. Meanwhile, vConv could be readily integrated into multi-layer neural networks as an 'in-place replacement' of canonical convolutional layer. All source codes are freely available on GitHub for academic usage.

Impact of COVID-19 outbreak on the care of patients with inflammatory bowel disease: A comparison before and after the outbreak in South China.

BACKGROUND AND AIMS: Epidemics pose a great challenge to health care of patients. However, the impact of unprecedented situation of COVID-19 outbreak on health care of inflammatory bowel disease (IBD) patients in real-world setting has seldom been investigated. METHODS: We performed an observational study in a tertiary referral IBD center in China. The mode of health care and medication use was compared before and after COVID-19 outbreak. Electronic questionnaire surveys were performed among gastroenterologists and IBD patients to investigate the impact of COVID-19 outbreak on their attitudes towards telemedicine. RESULTS: COVID-19 outbreak resulted in substantial decrease of patients participating in standard face-to-face visit during 1 month post-outbreak (n = 51) than pre-outbreak (n = 249), whereas the participation in telemedicine was significantly higher than comparable period in 2019 (414 vs 93). During the 1 month after COVID-19 outbreak, 39 (39/56, 69.6%) patients had their infliximab infusion postponed with the mean delay of 3 weeks. The immunomodulator use was similar between pre-outbreak and post-outbreak. Six elective surgeries were postponed for a median of 43 days. In post-outbreak period, 193 (193/297, 64.98%) of the surveyed physicians have used telemedicine with an increase of 18.9% compared with 46.13% (137/292) in the pre-outbreak period (P < 0.001); 331 (331/505, 65.54%) of the surveyed IBD patients supported that the use of telemedicine should be increased in future health care. CONCLUSION: COVID-19 outbreak resulted in a great change in health-care access among IBD patients including decrease in standard face-to-face visit and delay of biologics use. There was an increased use and need of telemedicine after COVID-19 outbreak.

Impact of COVID-19 on the Healthcare of Patients With Inflammatory Bowel Disease: A Comparison Between Epicenter vs. Non-epicenter Areas.

Background and Aims: The COVID-19 pandemic poses a great challenge to healthcare. We aimed to investigate the impact of COVID-19 on the healthcare of patients with inflammatory bowel disease (IBD) in epicenter and non-epicenter areas. Methods: Patients with IBD from Hubei province (the epicenter of COVID-19) and Guangdong province (a non-epicenter area), China were surveyed during the pandemic. The questionnaire included change of medications (steroids, immunomodulators, and biologics), procedures (lab tests, endoscopy, and elective surgery), and healthcare mode (standard healthcare vs. telemedicine) during 1 month before and after the outbreak of COVID-19. Results: In total, 324 IBD patients from Guangdong province (non-epicenter) and 149 from Hubei province (epicenter) completed the questionnaire with comparable demographic characteristics. Compared to patients in Guangdong province (non-epicenter), significantly more patients in Hubei (epicenter) had delayed lab tests/endoscopy procedures [61.1% (91/149) vs. 25.3% (82/324), p < 0.001], drug withdrawal [28.6% (43/149) vs. 9.3% (30/324), p < 0.001], delayed biologics infusions [60.4% (90/149) vs. 19.1% (62/324), p < 0.001], and postponed elective surgery [16.1% (24/149) vs. 3.7% (12/324), p < 0.001]. There was an increased use of telemedicine after the outbreak compared to before the outbreak in Hubei province [38.9% (58/149) vs. 15.4% (23/149), p < 0.001], while such a significant increase was not observed in Guangdong province [21.9% (71/324) vs. 18.8% (61/324), p = 0.38]. Approximately two-thirds of IBD patients from both sites agreed that telemedicine should be increasingly used in future medical care. Conclusions: Our patient-based survey study in a real-world setting showed that COVID-19 resulted in a great impact on the healthcare of patients with IBD, and such an impact was more obvious in the epicenter compared to the non-epicenter area of COVID-19. Telemedicine offers a good solution to counteract the challenges in an unprecedented situation such as COVID-19.

Use of the alkaline phosphatase to prealbumin ratio as an independent predictive factor for the prognosis of gastric cancer.

BACKGROUND: Gastric cancer (GC) is characterized by a low 5-year survival rate. The prognosis is still not satisfactory although it has significantly improved due to developments in medicine. Thus, the identification of more efficient indices for the evaluation of GC prognosis is required. We propose, for the first time, that the alkaline phosphatase (ALP) to prealbumin (PA) ratio (APR) can be used as an independent prognostic factor in GC. AIM: To evaluate the prognostic value the APR in GC. METHODS: According to the exclusion strategy, we collected the preoperative serologic examination results and clinical information of 409 GC patients treated in Shandong Provincial Hospital from January to December, 2016. By calculating the APR, the neutrophil and lymphocyte ratio (NLR), C-reactive protein (CRP) and albumin (ALB) ratio, platelet and lymphocyte ratio, lymphocyte and monocyte ratio, and the relationship with clinical information, we verified the role of preoperative APR ratio in the prognosis of GC. In addition, we used a Cox model combined with the APR and tumor stage to demonstrate its efficacy in assessing the prognosis of GC patients. RESULTS: Preoperative APR was an independent prognostic factor for GC. The median age of patients in the APR-high group was greater compared with that in the APR-low group. Patients with a higher APR had a more advanced clinical stage, higher neutrophil to lymphocyte, CRP to ALB, and platelet to lymphocyte ratios, but a lower lymphocyte to monocyte ratio (P < 0.05). The APR-high group also had higher glycoprotein antigen 199 and carbohydrate antigen 125 levels than the APR-low group (P < 0.05). Median overall survival and disease-free survival were significantly longer in the APR-low group than in the APR-high group. In addition, a Cox model based on the APR and tumor stage was more effective in evaluating the prognosis of patients than models based on stage alone or stage plus the NLR. CONCLUSION: A higher APR is an independent and negative prognostic factor for GC. The prognosis of GC can be better evaluated using a Cox model based on the APR and stage.

Twice-FFT demodulation for signal distortion in optical fiber FP acoustic sensor.

A Twice-FFT demodulation method for signal distortion state is proposed and experimentally demonstrated in an optical fiber Fabry-Perot (FP) acoustic sensor. Here the fiber FP acoustic sensor element is build with fiber end face and combination of diaphragms which is composed of a small round aluminum foil and a polymer PET film. The hypotenuse intensity demodulation method is applied to acquire the acoustic signal in time domain assisted with a Photodetector (PD) and an oscilloscope. The first Fast Fourier transform (FFT) processing results show harmonic distortion on the frequency domain spectrum. To demodulate the acoustic frequency and amplitude information, twice-FFT processing is preformed. Experimental results reveal an accuracy up to 95.6% of acoustic signal in the frequency range 2-100 Hz. Our scheme provides a new option for signal demodulation of optical fiber acoustic sensors (OFAS).

Identification of New Therapeutic Targets for Gastric Cancer With Bioinformatics.

We aimed to identify new targets affecting gastric cancer (GC) prognosis. Six target genes were identified from hub genes based on their relationship with important factors affecting tumor progression, like immune infiltration, purity, tumor mutation burden (TMB), and tumor microenvironment (TME) score. The effect of target genes' somatic mutations and copy number alteration (CNA) was examined to determine their effect on GC prognosis. Six target genes (FBN1, FN1, HGF, MMP9, THBS1, and VCAN) were identified. Reduced expression of each target gene, except MMP9, indicated better prognosis and lower grade in GC. FBN1, THBS1, and VCAN showed lower expression in stage I GC. Non-silencing mutations of the six genes played a role in significantly higher TMB and TME scores. THBS1 mutation was associated with earlier stage GC, and VCAN mutation was associated with lower grade GC. However, patients with target gene CNA displayed higher tumor purity. MMP9, THBS1, and VCAN CNA was associated with lower grade GC, while FBN1 CNA reflected earlier T stage. Additionally, the target genes may affect GC prognosis by influencing multiple oncogenic signaling pathways. FBN1, FN1, HGF, MMP9, THBS1, and VCAN may be new GC prognostic targets by affecting tumor purity, TMB, TME score, and multiple oncogenic signaling pathways.

Involvement of digestive system in COVID-19: manifestations, pathology, management and challenges.

The pandemic of novel coronavirus disease (COVID-19) has developed as a tremendous threat to global health. Although most COVID-19 patients present with respiratory symptoms, some present with gastrointestinal (GI) symptoms like diarrhoea, loss of appetite, nausea/vomiting and abdominal pain as the major complaints. These features may be attributable to the following facts: (a) COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and its receptor angiotensin converting enzyme 2 (ACE2) was found to be highly expressed in GI epithelial cells, providing a prerequisite for SARS-CoV-2 infection; (b) SARS-CoV-2 viral RNA has been found in stool specimens of infected patients, and 20% of patients showed prolonged presence of SARS-CoV-2 RNA in faecal samples after the virus converting to negative in the respiratory system. These findings suggest that SARS-CoV-2 may be able to actively infect and replicate in the GI tract. Moreover, GI infection could be the first manifestation antedating respiratory symptoms; patients suffering only digestive symptoms but no respiratory symptoms as clinical manifestation have also been reported. Thus, the implications of digestive symptoms in patients with COVID-19 is of great importance. In this review, we summarise recent findings on the epidemiology of GI tract involvement, potential mechanisms of faecal-oral transmission, GI and liver manifestation, pathological/histological features in patients with COVID-19 and the diagnosis, management of patients with pre-existing GI and liver diseases as well as precautions for preventing SARS-CoV-2 infection during GI endoscopy procedures.