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Abstract Background Chronic enteropathy associated with SLCO2A1 gene (CEAS) results from loss-of-function variants in SLCO2A1, which encodes the prostaglandin transporter (PGT). CEAS follows an autosomal recessive inheritance pattern. To date, approximate 30 pathogenic variants have been reported in CEAS. Methods We performed whole exome sequencing (WES) to screen for potential pathogenic variants in a patient suspected of having CEAS, and confirmed a variant in SLCO2A1 using Sanger sequencing. We established an in vitro minigene model to compare splicing between wild type (WT) and mutant transcripts. Quantitative polymerase chain reaction (qPCR) was used to evaluate SLCO2A1 transcription in the stomach and colon tissues from the patient and a healthy control (HC). The transcripts were further cloned and sequenced. Results The patient had a novel, homozygous, recessive c.929A > G variant in exon 7 of SLCO2A1, which has not been previously reported in CEAS or PHO. This variant altered splicing, resulting in an exon 7‐truncated transcript lacking 16 bases. No normal transcript was detected in the patient’s stomach or colon tissue. qPCR also showed significantly decreased SLCO2A1 transcription compared to HC. Conclusion A previously unreported variant caused defective SLCO2A1 splicing and reduced mRNA levels in a patient with CEAS and PHO. This research enhances understanding of CEAS and PHO pathophysiology and aids genetic counseling and diagnosis.

Abstract Background and aims Chronic enteropathy associated with SLCO2A1 gene is a rare intestinal disease caused by loss-of-function SLCO2A1 mutations, with clinical and genetic characteristics remaining largely unknown, especially in Chinese patients. This study aims to reveal clinical and genetic features of Chinese CEAS patients, highlighting the previously unreported or unemphasized characteristics. Methods We enrolled 12 Chinese patients with chronic enteropathy associated with SLCO2A1 gene admitted to Peking Union Medical College Hospital from January 2018 to December 2022. Clinical and genetic data of these patients were collected and analyzed. Results 58.3% of patients were male, who also had primary hypertrophic osteoarthropathy, whereas female patients did not have primary hypertrophic osteoarthropathy. Apart from common symptoms associated with anemia and hypoalbuminemia, abdominal pain, ileus, diarrhea, and hematochezia were present. 4 of the 5 female patients had early-onset amenorrhea, though the causal relationship remained to be clarified. Endoscopy and computed tomography enterography revealed that lesions can occur in any part of the digestive tract, most commonly in the ileum. Pathology showed multiple superficial ulcers with adjacent vascular dilatation, and loss of SLCO2A1 expression, particularly in gastrointestinal vascular endothelial cells. Genetic analysis confirmed SLCO2A1 mutations in all patients and identified 11 new SLCO2A1 variants for CEAS. Conclusions This study reports new clinical, pathological, and genetic findings in 12 Chinese patients with chronic enteropathy associated with SLCO2A1 gene. This study provides insights into the pathogenesis of this disease. However, studies with larger sample sizes and more in-depth mechanism research are still required.

Abstract Background Eosinophilic gastritis (EoG) has rarely been reported in conjunction with gluten-sensitive enteropathy (GSE). When this does occur, patients typically present with gastrointestinal symptoms. To our knowledge, hypoproteinemia has not been reported as the primary manifestation. Anti-IgE therapy, such as omalizumab, lowers eosinophil counts in the blood, lungs, and gut. Its efficiency in treating active EoG remain unknown. Case presentation We report a 33-month-old boy with a history of food allergy and atopic dermatitis who developed recurrent edema, hypoproteinemia, and eosinophilia at the age of 14 months. The diagnoses of EoG and GSE were confirmed based on the clinical presentation and results of gastrointestinal biopsies and serological testing. Although prednisone and dietary intervention were initially effective, the boy developed prednisone-related facial swelling. After stopping prednisone, his symptoms relapsed. Subsequent treatment with omalizumab, combined with dietary intervention, showed good efficacy and safety. Conclusions To our knowledge, this is the first case of concurrent EoG and GSE that presented primarily with hypoproteinemia. We highlight the rare manifestations of these two diseases to raise clinical suspicion and prevent missed and delayed diagnoses. The pathogenesis of EoG is heterogeneous and complex. Omalizumab showed good efficacy, indicating that IgE-mediated processes may be involved in the pathogenesis of this patient’s diseases.

Ulcerative colitis (UC), characterized by its recurrent nature, imposes a significant disease burden and compromises the quality of life. Emerging evidence suggests that achieving clinical remission is not sufficient for long-term remission. In pursuit of a favorable prognosis, mucosal healing (MH) has been defined as the target of therapies in UC. This paradigm shift has given rise to the formulation of diverse endoscopic and histological scoring systems, providing distinct definitions for MH. Endoscopic remission (ER) has been widely employed in clinical practice, but it is susceptible to subjective factors related to endoscopists. And there’s growing evidence that histological remission (HR) might be associated with a lower risk of disease flares, but the incorporation of HR as a routine therapeutic endpoint remains a debate. The integration of advanced technology has further enriched the definition of deep MH. Up to now, a universal standardized definition for deep MH in clinical practice is currently lacking. This review will focus on the definition of deep MH, from different dimensions, and analyze strengths and limitations, respectively. Subsequent multiple large-scale trials are needed to validate the concept of deep MH, offering valuable insights into potential benefits for UC patients.

Scene-level change detection (SLCD) can provide semantic change information at image level, thus it is of great significance for monitoring land use changes. Supervised SLCD approaches tend to outperform unsupervised ones. However, the existing supervised methods rely on postclassification, which often results in unsatisfactory performance due to classification error accumulation. We therefore formulate SLCD as a similarity learning task, and propose a scene similarity learning network (SSLN) for land use SLCD. To be specific, SSLN is a two-branch network with ResNet as the backbone for feature extraction, where the global feature difference and the multiscale local feature fusion modules are considered in order to better mine the temporal correlation between bitemporal scenes. Then, the trained SSLN is further exploited to obtain the similarity of scene pairs for determining the similarity threshold via threshold traversal algorithm. Finally, the land use scenes are categorized into changed or unchanged by comparing scene similarity with the threshold. Experimental results on the publicly available MtS-WH dataset and our newly released land use scene change detection dataset show that the proposed approach achieves better performance than comparison methods, indicating that our approach is a simple yet effective solution to land use SLCD.

Many management strategies are available for pancreatic neuroendocrine neoplasms with liver metastases. However, a lack of biological, molecular, and genomic information and an absence of data from rigorous trials limit the validity of these strategies. This review presents the viewpoints from an international conference consisting of several expert working groups. The working groups reviewed a series of questions of particular interest to clinicians taking care of patients with pancreatic neuroendocrine neoplasms with liver metastases by reviewing the existing management strategies and literature, evaluating the evidence on which management decisions were based, developing internationally acceptable recommendations for clinical practice, and making recommendations for clinical and research endeavors. The review for each question will be followed by recommendations from the panel.

Abstract Background and aims Common variable immunodeficiency disorder (CVID) patients may have gastrointestinal (GI) involvement and suffer from infections, which are poorly understood. This study aimed to evaluate the clinical, endoscopic, and histopathological features of CVID patients with GI symptoms and determine their correlation with infections. Methods We performed a retrospective study on 21 CVID patients with GI symptoms who underwent endoscopic examination in Peking Union Medical College Hospital from 2000 to 2020. The clinical, infectious, endoscopic, and histopathological features were reassessed. Results Chronic diarrhea was the most prevalent GI symptom, observed in 95.2% of our CVID cohort. Over 85% of patients had low body weight and malabsorption. Small bowel villous atrophy was found in 90.5% of patients under endoscopy and mostly confirmed by histopathology. GI infections were identified in 9 (42.9%) patients. Of these, 7 patients with diffuse and obvious nodular lymphoid hyperplasia (NLH) of small bowel under endoscopy had significantly higher infection rate (85.7% vs 21.4%, p

Remote sensing image retrieval (RSIR) aims to search and retrieve the images of interest from a large remote sensing image archive, which has remained to be a hot topic over the past decade. Benefited from the advent and progress of deep learning, RSIR has been promoted by developing novel approaches, constructing new datasets, and exploring potential applications. To the best of our knowledge, there lacks a comprehensive review of RSIR achievements, including systematic and hierarchical categorization of RSIR methods and benchmark datasets over the past decade. This article, therefore, provides a systematic survey of the recently published RSIR methods and benchmarks by reviewing more than 200 papers. To be specific, in terms of image source, label, and modality, we first group the RSIR methods into some hierarchical categories, each of which is reviewed in detail. Following the categorization of the RSIR methods, we list the benchmark datasets publicly available for performance evaluation and present our newly collected RSIR dataset. Moreover, some of the existing RSIR methods are selected and evaluated on the representative benchmark datasets. The results demonstrate that deep learning-based methods are currently the dominant RSIR approaches and outperform handcrafted feature-based methods by a significant margin. Finally, we discuss the main challenges of RSIR and point out some potential directions for the future RSIR research.

Abstract The standardized diagnosis and management of gastric precancerous conditions and lesions are important to prevent gastric cancer. This guideline, created by 5 traditional Chinese medicine and Western medicine associations, based on the current morbidity and diagnosis and treatment of gastric precancerous conditions and lesions, provides specific key points and strategies for diagnosis and treatment in the following five aspects: definition and epidemiology, diagnosis and stage, surveillance, treatment and efficacy evaluation. It is hoped that these aspects, assessed by integrating Western medicine and traditional Chinese medicine and involving multidisciplinary participation, will play a guiding role in clinical diagnosis and treatment and achieve effective secondary prevention of gastric cancer.

Abstract Background Allied disorders of Hirschsprung’s disease (ADHD) mainly present with bowel obstruction, intestinal dilatation, and chronic constipation, while recurrent spontaneous pneumoperitoneum was rarely reported. We aimed to report a case of recurrent spontaneous pneumoperitoneum caused by ADHD. Case presentation A 59-year-old female patient presented with progressive and severe constipation in the past 30 years. She suffered from abdominal discomfort, which was described as ‘gurgling’ during the last three years. Radiography showed free-air and intestinal dilatation, without any other diseases, and she was identified with recurrent spontaneous pneumoperitoneum. Gastrointestinal transit test indicated gastrointestinal motility disorder, and anorectal manometry confirmed the presence of rectal anus-suppressing reflex. Subtotal colectomy was performed to relieve apparent constipation, and the postoperative pathological examination of the colon demonstrated proliferation of nerve fibers and hyperplasia of myenteric plexuses, as well as a relatively scarcity of ganglion cells in the myenteric plexus. Based on the presentations and the postoperative pathology, she was diagnosed with ADHD. The recurrent spontaneous pneumoperitoneum was regarded as the gas escape from dilated intestines, which was in high pressure. All the symptoms and her mental state were improved after the treatment with gastrointestinal decompression and enteral nutrition. However, during follow-up visits, she had intestinal infection, and suffered from severe diarrhea and water-electrolyte imbalance, and the patient eventually died at 17 months after the diagnosis. Conclusion ADHD could be a rare cause of recurrent spontaneous pneumoperitoneum, and are mainly undiagnosed or misdiagnosed. A full-thickness biopsy of the gastrointestinal tract (especially the small intestine and sigmoid colon) and differential diagnosis are recommended for the definitive diagnosis. While the ADHD have shown a poor prognosis, timely and long-term treatment with intestinal decompression and nutritional therapy could help relieve symptoms and provide a better quality of life for such patients.

Terrace detection and ridge extraction from high-resolution remote sensing imagery are crucial for soil conservation and grain production on sloping land. Traditional methods use low-to-medium resolution images, missing detailed features and lacking automation. Terrace detection and ridge extraction are closely linked, with each influencing the other’s outcomes. However, most studies address these tasks separately, overlooking their interdependence. This research introduces a cutting-edge, multi-scale, and multi-task deep learning framework, termed DTRE-Net, designed for comprehensive terrace information extraction. This framework bridges the gap between terrace detection and ridge extraction, executing them concurrently. The network incorporates residual networks, multi-scale fusion modules, and multi-scale residual correction modules to enhance the model’s robustness in feature extraction. Comprehensive evaluations against other deep learning-based semantic segmentation methods using GF-2 terraced imagery from two distinct areas were undertaken. The results revealed intersection over union (IoU) values of 85.18% and 86.09% for different terrace morphologies and 59.79% and 73.65% for ridges. Simultaneously, we have confirmed that the connectivity of results is improved when employing multi-task learning for ridge extraction compared to directly extracting ridges. These outcomes underscore DTRE-Net’s superior capability in the automation of terrace and ridge extraction relative to alternative techniques.

Leveraging multi-view remote sensing images in scene classification tasks significantly enhances the precision of such classifications. This approach, however, poses challenges due to the simultaneous use of multi-view images, which often leads to a misalignment between the visual content and semantic labels, thus complicating the classification process. In addition, as the number of image viewpoints increases, the quality problem for remote sensing images further limits the effectiveness of multi-view image classification. Traditional scene classification methods predominantly employ SoftMax deep learning techniques, which lack the capability to assess the quality of remote sensing images or to provide explicit explanations for the network’s predictive outcomes. To address these issues, this paper introduces a novel end-to-end multi-view decision fusion network specifically designed for remote sensing scene classification. The network integrates information from multi-view remote sensing images under the guidance of image credibility and uncertainty, and when the multi-view image fusion process encounters conflicts, it greatly alleviates the conflicts and provides more reasonable and credible predictions for the multi-view scene classification results. Initially, multi-scale features are extracted from the multi-view images using convolutional neural networks (CNNs). Following this, an asymptotic adaptive feature fusion module (AAFFM) is constructed to gradually integrate these multi-scale features. An adaptive spatial fusion method is then applied to assign different spatial weights to the multi-scale feature maps, thereby significantly enhancing the model’s feature discrimination capability. Finally, an evidence decision fusion module (EDFM), utilizing evidence theory and the Dirichlet distribution, is developed. This module quantitatively assesses the uncertainty in the multi-perspective image classification process. Through the fusing of multi-perspective remote sensing image information in this module, a rational explanation for the prediction results is provided. The efficacy of the proposed method was validated through experiments conducted on the AiRound and CV-BrCT datasets. The results show that our method not only improves single-view scene classification results but also advances multi-view remote sensing scene classification results by accurately characterizing the scene and mitigating the conflicting nature of the fusion process.

Abstract. Background:. Endoscopic biopsy can underestimate gastric malignancies as low-grade intraepithelial neoplasia (LGIN). Definitively diagnosed LGIN would progress. This study aimed to evaluate predictive factors to identify malignancies misdiagnosed as LGIN by biopsy and LGIN at high risk of progression. Methods:. The clinical records of patients diagnosed with gastric LGIN by endoscopic biopsy who underwent at least two endoscopies during the first year of follow-up between 2007 and 2017 were retrospectively collected. Three endoscopists reviewed photographs of the initial endoscopy, described lesion characteristics, and made endoscopic diagnoses. Logistic regression was used to analyze predictors to identify malignancies underestimated as LGIN. A receiver operating characteristic curve was used to evaluate the diagnostic accuracy of these predictors. Patient clinical outcomes of follow-up >1 year were collected. Kaplan–Meier estimates with log-rank tests and Cox proportional hazards regression were used to analyze predictors of progression. Results:. Overall, 48 of 182 (26.4%) patients were proven to have malignancies. A single lesion, a large lesion size, and marked intestinal metaplasia (IM) were independent predictors of initially misdiagnosed malignancies. The area under the curve of these predictors was 0.871, with a sensitivity of 68.7% and specificity of 92.5%. Twelve of 98 patients (12.2%) progressed during the 33-month median follow-up period. A whitish appearance, irregular margins, marked IM, and histological diagnosis of LGIN more than twice within the first year were predictors for progression. Conclusions:. Lesions diagnosed as LGIN by biopsy with marked IM and other predictors above should be prudently treated for high potential to be malignancies or progress. Endoscopic follow-up with repeated biopsies within the first year is recommended.

Abstract Background Mixed neuroendocrine-non-neuroendocrine neoplasms (MiNEN) of the pancreas are extremely rare. Their pathogenesis and molecular landscape are largely unknown. Here, we report a case of mixed pancreatic intraductal papillary mucinous neoplasm (IPMN) and well-differentiated neuroendocrine tumor (NET) and identify its genetic alterations by next-generation sequencing (NGS). Case presentation A fifty-year-old male was admitted into the hospital for evaluation of a pancreatic lesion detected during a routine examination. Abdominal ultrasound indicated a hypoechoic mass of 2.6 cm at the head of the pancreas. Malignancy was suspected and partial pancreatectomy was performed. Thorough histopathological examination revealed a mixed IPMN-NET. In some areas, the two components were relatively separated, whereas in other areas IPMN and NET grew in a composite pattern: The papillae were lined with epithelial cells of IPMN, and there were clusters of NET nests in the stroma of papillary axis. NGS revealed shared somatic mutations (KRAS, PCK1, MLL3) in both components. The patient has been uneventful 21 months after the surgery. Conclusions Our case provides evidence of a common origin for mixed IPMN-NET with composite growth features. Our result and literature review indicate that KRAS mutation might be a driver event underlying the occurrence of MiNEN. We also recommend the inclusion of mixed non-invasive exocrine neoplasms and neuroendocrine neoplasms into MiNEN.

BackgroundThere are few reports on standard treatment and long-term prognosis in patients with cryptogenic multifocal ulcerative stenosing enteritis (CMUSE), particularly in patients in whom remission could not be induced by steroids. The aim of this study was to evaluate the treatment response and progression-free periods of patients with CMUSE and to identify the factors predictive of steroid resistance.MethodsThis was a retrospective cohort study that included 25 patients with clinically confirmed CMUSE between 1984 and 2021 from the enteropathy clinic of a tertiary care center. For statistical analyses, chi-square test or Fisher’s exact test were used for categorical variables. Survival curves were plotted using the Kaplan–Meier method.ResultsThe overall median progression-free period was 48 months (range, 1–108 months) after comprehensive therapy, and initial manifestation with severe bleeding rather than ileus was associated with the long-term efficacy. Patients with steroid resistance (N = 10, 55.6%) had poor prognosis, and non-responders had more favorable baseline clinical characteristics, with a higher percentage of female patients (60% vs. 12.5%), earlier disease onset (26.5 years vs. 39 years), rapid progression (42 vs. 108 months), severe anemia (80% vs. 50%), and hypoalbuminemia (50% vs. 0%), in accord with lymphangiectasia or angioectasia identified in pathology.ConclusionThere is no guaranteed treatment strategy in the maintenance of long-term clinical remission for CMUSE patients, particularly in whom with steroid resistance. Female patients with early symptoms onset, severe gastrointestinal hemorrhage and hypoalbuminemia seem to have poor long-term prognosis.

BackgroundEndoscopic submucosal dissection (ESD), a minimally invasive surgery used to treat early gastrointestinal malignancies, has been widely embraced around the world. The gross reconstruction of ESD specimens can facilitate a more precise pathological diagnosis and allow endoscopists to explore lesions thoroughly. The traditional method of mapping is time-consuming and inaccurate. We aim to design a topographic mapping system via artificial intelligence to perform the job automatically.MethodsThe topographic mapping system was built using computer vision techniques. We enrolled 23 ESD cases at the Peking Union Medical College Hospital from September to November 2019. The reconstruction maps were created for each case using both the traditional approach and the system.ResultsUsing the system, the time saved per case ranges from 34 to 3,336 s. Two approaches revealed no significant variations in the shape, size, or tumor area.ConclusionWe developed an AI-assisted system that would help pathologists complete the ESD topographic mapping process rapidly and accurately.

Abstract Background Being a rare disease, cryptogenic multifocal ulcerous stenosing enteritis (CMUSE) is easily misdiagnosed as small bowel Crohn’s disease (SBCD). Aims This study was aimed to compare clinical features of CMUSE to SBCD. Methods Fourteen patients with CMUSE and 61 patients with SBCD were retrospectively analyzed. Results Hematochezia was more frequent in CMUSE patients (10, 71.4% vs 23, 37.7%, P = 0.022), while diarrhea was more common in SBCD patients (23, 37.7% vs 0, 0.0%, P = 0.015). More patients with CMUSE developed intestinal stenosis than with SBCD (14, 100% vs 37, 60.7%, P = 0.011). 30 (50.0%) SBCD patients and none CMUSE patients had an elevated erythrocyte sedimentation rate level (P = 0.001). Extra-enteric findings found by computed tomography enterography were significantly more prevalent in SBCD patients than in CMUSE patients (25,71.4% vs 3,25%, P = 0.013). Longitudinal ulcers found by endoscopy were more common in SBCD patients (16, 37.2% vs 0, 0.0%, P = 0.041), while circumferential ulcers were more common in CMUSE patients (6, 54.6% vs 8, 18.6%, P = 0.041). All ulcers observed in CMUSE patients were within mucosal and submucosal layers, but 8 (44.4%) SBCD patients had deep ulcers that reached beyond submucosal layers (P = 0.003). Ulcers were located at strictures in 9 (90.0%) CMUSE patients but only in 1 (5.6%) SBCD patient (P = 0.000). Conclusions Gastrointestinal symptoms, erythrocyte sedimentation rate levels, radiologic, endoscopic and pathologic features help to distinguish CMUSE from SBCD.

The early detection and accurate histopathological diagnosis of gastric cancer are essential factors that can help increase the chances of successful treatment. Here, the authors report on a digital pathology tool achieving high performance on a real world test dataset and show that the system can aid pathologists in improving diagnostic accuracy.

Conventional remote sensing image retrieval (RSIR) system usually performs single-label retrieval where each image is annotated by a single label representing the most significant semantic content of the image. In this scenario, however, the scene complexity of remote sensing images is ignored, where an image might have multiple classes (i.e., multiple labels), resulting in poor retrieval performance. We therefore propose a novel multilabel RSIR approach based on fully convolutional network (FCN). Specifically, FCN is first trained to predict segmentation map of each image in the considered image archive. We then obtain multilabel vector and extract region convolutional features of each image based on its segmentation map. The extracted region features are finally used to perform region-based multilabel retrieval. The experimental results show that our approach achieves state-of-the-art performance in contrast to handcrafted and convolutional neural network features.

Abstract Background Ulcerative colitis (UC)-related post-colectomy enteritis is a very rare condition that is characterized by diffuse small-bowel mucosal inflammation following colectomy and could be very dangerous. In previously reported cases, corticosteroid therapy seemed to be the optimal choice for inducing remission; however, the patient studied herein presented with severe diarrhoea and hypovolemic shock and failed to achieve full remission with corticosteroid therapy. Case presentation We describe the case of a patient with severe pan-enteritis presenting with life-threatening diarrhoea complicated with hypovolemic shock and acute kidney injury after colectomy and ileal pouch anal anastomosis (IPAA) for UC; this patient was successfully treated by ileostomy closure after failing to achieve full remission with corticosteroid therapy. Next, we review other cases of post-colectomy enteritis reported in the literature and propose a flow-chart for its diagnosis and initial treatment. Conclusion Post-colectomy enteritis can be dangerous, and the early awareness of this condition plays a vital role. Additionally, in patients who do not respond well to corticosteroid or immunosuppressant therapy, early closure of the ileostomy and re-establishment of the natural faecal stream could be important considerations.

Background: Transmural healing (TH) is being increasingly recognized for reflecting deep remission in Crohn’s disease (CD). The long-term clinical significance of achieving TH is still not fully known. We aimed to evaluate TH as a predictor of long-term positive outcomes using intestinal ultrasonography (US), with comparison with the established endpoint mucosal healing (MH). Methods: CD patients were consecutively recruited from September 2015 to August 2018 at a single tertiary hospital. All patients were evaluated at baseline and followed up at 6 months prospectively with a guideline-based treatment regimen. Achieving TH/MH or not was evaluated by US/colonoscopy at the first follow-up. Long-term outcomes including steroid-free clinical remission (CR), drug escalation, hospitalization, and surgery, were recorded after at least another 12 months. Results: We identified 77 patients with a median age of 30 years (range, 12–73 years). Twenty-five (32%) patients achieved TH, and 31 (40%) patients achieved MH. TH and MH were poorly correlated (Cohen’s κ = 0.387; p

Background. Patients diagnosed with ulcerative colitis (UC) associated with primary sclerosis cholangitis (PSC) and sessile serrated adenoma (SSA) are rare. The present study aimed to identify the potential causative gene mutation in a patient with UC associated with PSC and SSA. Methods. DNA was extracted from the blood sample and tissue sample of SSA, followed by the whole exome sequencing (WES) analysis. Bioinformatics analysis was utilized to predict the deleteriousness of the identified variants. Multiple sequence alignment and conserved protein domain analyses were performed using online software. Sanger sequencing was used to validate the identified variants. Expression and diagnostic analysis of identified mutated genes was performed in the GSE119600 dataset (peripheral blood samples of PSC and UC) and GSE43841 dataset (tumor samples of SSA). Results. In the present study, a total of 842 single nucleotide variants (SNVs) in 728 genes were identified in the blood sample. Two variants, integrin beta 4 (ITGB4) (c.C2503G; p.P835A) and a mucin 3A (MUC3A) (c.C1019T; p.P340L), were further analyzed. MUC3A was associated with inflammatory bowel disease. Sanger sequence in blood revealed that the ITGB4 mutation was fully cosegregated with the result of WES in the patient. Additionally, a variant, tumor protein p53 gene (TP53) (c.86delA; p.N29Tfs∗15) was identified in the tissue sample of SSA. Compared to that in normal controls, ITGB4 was upregulated in both UC and PSC, MUC3A was, respectively, upregulated and downregulated in PSC and UC, and TP53 was downregulated in SSA. ITGB4 and TP53 had a potential diagnostic value for UC, PSC and SSA. Conclusions. The present study demonstrated that the ITGB4 (c.C2503G; p.P835A) and MUC3A (c.C1019T; p.P340L) mutations may be the potential causative variants in a patient with UC associated with PSC and SSA. TP53 (c.86delA; p.N29Tfs∗15) mutation may be associated with SSA in this patient.

Background: Transducin-like enhancer of split-1 (TLE1), a member of the Groucho/TLE family of transcriptional corepressors, has been reported to be involved in the tumorigenesis of various cancers and function as a clinical prognostic indicator. However, the mechanisms and prognostic significance of TLE1 in pancreatic ductal adenocarcinoma (PDAC) have not been elucidated.Methods: In this study, western blot analyses and real-time polymerase chain reaction (RT-PCR) were employed to evaluate the expression of TLE1 and related proteins in PDAC cell lines. Wound healing, transwell migration and invasion, and Cell Counting Kit-8 (CCK-8) assays were used to determine cell line-specific differences in metastasis and proliferation. Flow cytometry was performed for cell cycle detection. RNA sequencing and bioinformatics were undertaken to explore the molecular mechanisms and potential targeted molecules of TLE1. TLE1 expression in tumor and para-tumor tissues was evaluated by tissue microarray-based immunohistochemistry using a semiquantitative method (H-score) in 262 patients with radical PDAC resection. Correlation, Kaplan–Meier survival, univariate, and multivariate analyses were also performed.Results: Our findings showed that TLE1 expression was common in PDAC cell lines. Upregulation of TLE1 inhibited PDAC cell migration, invasion, and proliferation in vitro by delaying the G0/G1 transition. Immunohistochemistry revealed that TLE1 was specifically expressed in the nucleus and at higher levels in tumor tissues compared with para-tumor tissues. Generally, high TLE1 expression was associated with no vascular invasion. In univariate analyses, high TLE1 expression was associated with longer disease-specific survival (DSS) in all patients and in 16 patient subgroups. In multivariate analyses, TLE1 expression was independently associated with DSS in all patients and four patient subgroups.Conclusion: In conclusion, these results suggest that TLE1 has an inhibitory role in PDAC progression and is a favorable prognostic indicator for patients with resectable PDAC.

Purpose: This study aimed to determine whether detecting elastic fibers in tumor stroma (EFTS) could be used as a new method for predicting the prognosis of gastric cancer (GC) patients.Materials and Methods: EFTS expression was determined by histochemistry in 160 GC patients who underwent gastrectomy. Based on the staining results, the patients were divided into three groups according to their EFTS expression level: low (n = 57), moderate (n = 50), and high (n = 53). The clinicopathological data and 6-year survival data were analyzed among different EFTS groups.Results: The expression of EFTS was closely related to lymphovascular invasion (P = 0.010), blood transfusion in operation (P < 0.001), recurrence rate (P < 0.001), and motility (P < 0.001). High expression of EFTS was also correlated with recurrence-free survival (RFS) and overall survival (OS) in GC patients by Kaplan–Meier curve (P < 0.001 for RFS and P < 0.001 for OS).Conclusions: Multivariate analysis showed that EFTS was an independent prognostic factor for RFS and OS. In conclusion, detecting EFTS to predict the prognosis of GC patients is effective and highly feasible.

Abstract Background Endometriosis is a relatively common condition in women of reproductive age. Malignant transformation of intestinal endometriosis is a very rare event. We report a case in which a patient with a history of endometriosis underwent surgery for malignant intestinal endometriosis. Case presentation A 55-year-old woman complained of rectorrhagia and intermittent abdominal pain. A neoplasm was revealed by colonoscopy, CT scan and F18-FDG PET/CT of the recto-sigmoidal colon. The patient underwent a rectal anterior resection, hysterectomy and bilateral salpingo-oophorectomy for treatment. According to the histological and immunohistochemical presentation, the diagnosis of endometriosis-associated recto-sigmoid cancer was confirmed. The patient was treated with adjuvant chemotherapy for 6 months. During the follow-up appointment 22 months later, there was clinical and radiographic evidence of recurrence in the rectum. The patient received chemotherapy again and will receive another surgery after two more cycles of chemotherapy. Conclusion We report a case of malignant intestinal endometriosis. Although there is no standard therapy for malignant intestinal endometriosis due to the rarity of this disease, surgery and adjuvant chemotherapy seemed to be rational. This case indicates that local recurrence may be a common situation after standard therapy.

Background. IRAK-M, negatively regulating Toll-like receptor, is shown the dual properties in the varied disease contexts. We studied the effect of IRAK-M deficiency on cigarette smoking- (CS-) induced airway inflammation under acute or subacute conditions in a mouse model. Methods. A number of cellular and molecular techniques were used to detect the differences between IRAK-M knockout (KO) and wild type (WT) mice exposed to 3-day or 7-week CS. Results. Airway inflammation was comparable between IRAK-M KO and WT mice under 3-day CS exposure. Upon short-term CS exposure and lipopolysaccharide (LPS) inhalation, IRAK-M KO mice demonstrated worse airway inflammation, significantly higher percentage of Th17 cells and concentrations of proinflammatory cytokines in the lungs, and significantly elevated expression of costimulatory molecules CD40 and CD86 by lung dendritic cells (DCs) or macrophages. Conversely, 7-week CS exposed IRAK-M KO mice demonstrated significantly attenuated airway inflammation, significantly lower concentrations of proinflammatory cytokines in the lungs, significantly increased percentage of Tregs, and lower expression of CD11b and CD86 by lung DCs or macrophages. Conclusions. IRAK-M plays distinctive effect on CS-induced airway inflammation, and influences Treg/Th17 balance and expression of costimulatory molecules by DCs and macrophages, depending on duration and intensity of stimulus.

In our paper [1], we presented a dense labeling dataset that can be used for not only single-label and multi-label remote sensing image retrieval but also pixel-based problems such as semantic segmentation.[...]

Benchmark datasets are essential for developing and evaluating remote sensing image retrieval (RSIR) approaches. However, most of the existing datasets are single-labeled, with each image in these datasets being annotated by a single label representing the most significant semantic content of the image. This is sufficient for simple problems, such as distinguishing between a building and a beach, but multiple labels are required for more complex problems, such as RSIR. This motivated us to present a new benchmark dataset termed “MLRSIR” that was labeled from an existing single-labeled remote sensing archive. MLRSIR contained a total of 17 classes, and each image had at least one of 17 pre-defined labels. We evaluated the performance of RSIR methods ranging from traditional handcrafted feature-based methods to deep-learning-based ones on MLRSIR. More specifically, we compared the performances of RSIR methods from both single-label and multi-label perspectives. These results presented the advantages of multiple labels over single labels for interpreting complex remote sensing images, and serve as a baseline for future research on multi-label RSIR.

The mammalian target of rapamycin (mTOR) signaling pathway in pulmonary fibrosis was investigated in cell and animal models. mTOR overactivation in alveolar epithelial cells (AECs) was achieved in the conditional and inducible Tsc1 knock-down mice SPC-rtTA/TetO-Cre/Tsc1(fx/+) (STT). Doxycycline caused Tsc1 knock-down and consequently mTOR activation in AECs for the STT mice. Mice treated with bleomycin exhibited increased mortality and pulmonary fibrosis compared with control mice. In wild-type C57BL/6J mice, pretreatment with rapamycin attenuated the bleomycin-mediated mortality and fibrosis. Rapamycin-mediated mouse survival benefit was inhibited by chloroquine, an autophagy inhibitor. Autophagosomes were decreased in the lungs after bleomycin exposure. Rapamycin induced the production of autophagosomes and diminished p62. We concluded that mTOR overactivation in AECs and compromised autophagy in the lungs are involved in the pathogenesis of pulmonary fibrosis. The suppression of mTOR and enhancement of autophagy may be used for treatment of pulmonary fibrosis.

Learning powerful feature representations for image retrieval has always been a challenging task in the field of remote sensing. Traditional methods focus on extracting low-level hand-crafted features which are not only time-consuming but also tend to achieve unsatisfactory performance due to the complexity of remote sensing images. In this paper, we investigate how to extract deep feature representations based on convolutional neural networks (CNNs) for high-resolution remote sensing image retrieval (HRRSIR). To this end, several effective schemes are proposed to generate powerful feature representations for HRRSIR. In the first scheme, a CNN pre-trained on a different problem is treated as a feature extractor since there are no sufficiently-sized remote sensing datasets to train a CNN from scratch. In the second scheme, we investigate learning features that are specific to our problem by first fine-tuning the pre-trained CNN on a remote sensing dataset and then proposing a novel CNN architecture based on convolutional layers and a three-layer perceptron. The novel CNN has fewer parameters than the pre-trained and fine-tuned CNNs and can learn low dimensional features from limited labelled images. The schemes are evaluated on several challenging, publicly available datasets. The results indicate that the proposed schemes, particularly the novel CNN, achieve state-of-the-art performance.