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Crohn\'s disease is a type of inflammatory bowel disease (IBD) that typically presents in the second or third decade of life. There are various pharmaceutical therapies that have been developed to treat the disease\'s symptoms. However, some patients still do not find relief with these medications and turn to other therapies such as diet modification. The underlying cause of Crohn\'s disease involves multiple factors such as uncontrolled inflammation and several genetic variants. While most current medication therapies control the symptoms that occur due to this uncontrolled level of inflammation, an anti-inflammatory diet (AID) may actually lower the level of inflammation in the gut and therefore reduce the amount of disease symptoms in Crohn\'s disease. Some such diets include the IBD-AID, Crohn\'s disease exclusion diet, and the Groningen AID (GrAID). This report describes a case of treatment-resistant Crohn\'s disease in a patient who was given all categories of pharmaceutical therapies including prednisone, budesonide, sulfasalazine, olsalazine, 6-mercaptopurine, methotrexate, mesalamine, and adalimumab. These only gave temporary relief of symptoms and eventually failed for various reasons including allergic reaction, insufficient symptom control, and antibody formation against the medication. This prompted the patient to independently research AIDs instead. In conclusion, for patients whose disease is refractory to different treatments, or who develop antibodies to the medication, AIDs may offer a solution to reduce disease symptoms and progression. Education of healthcare professionals and patients alike is vital in order for Crohn\'s patients to gain the benefits from dietary therapy.

BACKGROUND: Primary sclerosing cholangitis (PSC) is a progressive immune-mediated liver disease, for which no medical therapy has been shown to slow disease progression. However, the horizon for new therapies is encouraging, with several innovative clinical trials in progress. Despite these advancements, there is considerable heterogeneity in the outcomes studied, with lack of consensus as to what outcomes to measure, when to measure and how to measure. Furthermore, there has been a paradigm shift in PSC treatment targets over recent years, moving from biochemistry-based endpoints to histological assessment of liver fibrosis, imaging-based biomarkers and patient-reported outcome measures. The abundance of new interventional trials and evolving endpoints pose opportunities for all stakeholders involved in evaluating novel therapies. To this effect, there is a need to harmonise measures used in clinical trials through the development of a core outcome set (COS).
METHODS: Synthesis of a PSC-specific COS will be conducted in four stages. Initially, a systematic literature review will be performed to identify outcomes previously used in PSC trials, followed by semistructured qualitative interviews conducted with key stakeholders. The latter may include patients, clinicians, researchers, pharmaceutical industry representatives and healthcare payers and regulatory agencies, to identify additional outcomes of importance. Using the outcomes generated from the literature review and stakeholder interviews, an international two-round Delphi survey will be conducted to prioritise outcomes for inclusion in the COS. Finally, a consensus meeting will be convened to ratify the COS and disseminate findings for application in future PSC trials.
BACKGROUND: Ethical approval has been granted by the East Midlands-Leicester Central Research Ethics Committee (Ref: 24/EM/0126) for this study. The COS from this study will be widely disseminated including publication in peer-reviewed journals, international conferences, promotion through patient-support groups and made available on the Core Outcomes Measurement in Effectiveness Trials (COMET) database.
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OBJECTIVE: There are no previous studies in which computer-aided diagnosis (CAD) diagnosed colorectal cancer (CRC) subtypes correctly. In this study, we developed an original CAD for the diagnosis of CRC subtypes.
METHODS: Pretraining for the CAD based on ResNet was performed using ImageNet and five open histopathological pretraining image datasets (HiPreD) containing 3 million images. In addition, sparse attention was introduced to improve the CAD compared to other attention networks. One thousand and seventy-two histopathological images from 29 early CRC cases at Kyoto Prefectural University of Medicine from 2019 to 2022 were collected (857 images for training and validation, 215 images for test). All images were annotated by a qualified histopathologist for segmentation of normal mucosa, adenoma, pure well-differentiated adenocarcinoma (PWDA), and moderately/poorly differentiated adenocarcinoma (MPDA). Diagnostic ability including dice sufficient coefficient (DSC) and diagnostic accuracy were evaluated.
RESULTS: Our original CAD, named Colon-seg, with the pretraining of both HiPreD and ImageNET showed a better DSC (88.4%) compared to CAD without both pretraining (76.8%). Regarding the attentional mechanism, Colon-seg with sparse attention showed a better DSC (88.4%) compared to other attentional mechanisms (dual: 79.7%, ECA: 80.7%, shuffle: 84.7%, SK: 86.9%). In addition, the DSC of Colon-seg (88.4%) was better than other types of CADs (TransUNet: 84.7%, MultiResUnet: 86.1%, Unet++: 86.7%). The diagnostic accuracy of Colon-seg for each histopathological type was 94.3% for adenoma, 91.8% for PWDA, and 92.8% for MPDA.
CONCLUSIONS: A deep learning-based CAD for CRC subtype differentiation was developed with pretraining and fine-tuning of abundant histopathological images.

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Nausea and vomiting during pregnancy are very common; however, when persistent symptoms lead to severe malnutrition, other conditions should be considered. We present a patient with severe postprandial nausea and vomiting resulting in 120 lb weight loss. She was treated for presumed hyperemesis gravidarum but diagnosed with achalasia type 1 upon further work-up. The pregnancy was further complicated by fetal growth restriction, shortened cervix and preterm premature rupture of membranes, and resulted in delivery at 26 weeks of gestation. Postpartum, she underwent a peroral endoscopic myotomy procedure and has returned to normal body mass index.The differential for nausea/vomiting is broad, and major medical conditions can manifest for the first time during pregnancy. Severe malnutrition adversely affects maternal and fetal health. Further work-up should be pursued when symptoms cannot otherwise be explained.

Artificial intelligence (AI) applications are used in gastroenterology for automatic imaging diagnostic methods such as ultrasonography, computer tomography, magnetic resonance imaging, but also in endoscopy, capsule endoscopy and biopsy followed by automatic digital pathology evaluation. The accuracy of AI-based systems is superior to human expertise. Furthermore, in reality, a very small percentage of the patients are being investigated by a human expert in endoscopy, so implementing AI in this investigation would only increase the diagnostic accuracy. The existence of an unimaginable number of digital images and different types of medical information made possible the analysis and training of convolutional neural network (CNN), which consists of multilayers of artificial neural networks (ANN) with step-by-step minimal processing, creating a fundamental resource for any AI-based system to learn by itself how to automatically perform medical tasks, which were performed only by human experts in the past. The main objectives for AI applications used in gastroenterology are to improve the medical procedures with enhanced precision, to reduce the number of medical errors and to perform repetitive tasks.

A woman in her 60s presented to the emergency department with excruciating, deep left shoulder pain and was found to have a right-sided Morgagni hernia, a rare type of congenital diaphragmatic hernia (CDH). She did not have chest pain, palpitations, shortness of breath, cough, abdominal pain, constipation, diarrhoea, nausea, vomiting or other symptoms classically associated with CDHs in adults. Laparoscopic robotic-assisted repair with mesh placement was performed, and the patient\'s recovery was uncomplicated, with no recurrence of shoulder pain. Our patient\'s presentation was unusual due to the absence of symptoms typically seen with CDHs in adults, and the presence of contralateral, left-sided shoulder pain with a right-sided Morgagni hernia.

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