A Rare Case of a Non- Functioning Pancreatic Neuroendocrine Tumor

Pancreatic neuroendocrine tumors (PNET) are very rare and represent about 1–2% of all pancreatic tumors. Non-functional PNET (NF-PNET) is incidentally discovered in most cases. Most NF-PNETs are found at an advanced stage because patients are mostly asymptomatic. We present a case of 32-yr-old female who initially presented with increasing abdominal girth, decreased mobility, and lower extremity swelling up to the hip and was found to have an advanced NF-PNET with metastatic disease to the pelvis and liver. There have been few studies directed toward early detection and management; Computed tomography (CT) is the imaging modality of choice as well as the use of several screening biomarkers. Surgical treatment is preferred, but this option is not available for advanced disease leaving only palliative chemotherapy and radiation

A Mathematical Investigation on Tumor-Immune Dynamics: The Impact of Vaccines on the Immune Response

Mathematical models analyzing tumor-immune interactions provide a framework by which to address specific scenarios in regard to tumor-immune dynamics. Important aspects of tumor-immune surveillance to consider is the elimination of tumor cells from a host’s cell-mediated immunity as well as the implications of vaccines derived from synthetic antigen. In present studies, our mathematical model examined the role of synthetic antigen to the strength of the immune system. The constructed model takes into account accepted knowledge of immune function as well as prior work done by de Pillis et al. All equations describing tumor-immune growth, antigen presentation, immune response, and interaction rates were numerically simulated with MATLAB. Here, our work shows that a robust immune response can be generated if the immune system recognizes epitopes that are between 8 to 11 amino acids long. We show through mathematical modeling of how synthetic tumor vaccines can be utilized to mitigate a developing cancer

Dense Colon Scarring After Infliximab for Acute Severe Ulcerative Colitis

Introduction: Infliximab is a monoclonal antibody against tumor necrosis factor alpha used in the treatment of ulcerative colitis. It has been shown to be efficacious in patients with moderate to severe ulcerative colitis and/or those who have failed intravenous steroids. We present a unique finding of profoundly dense colonic scarring after a year of infliximab therapy in a patient with acute severe ulcerative colitis. Case: A female in her early 60s presented to the hospital with a three month history of rectal bleeding and intermittent fevers. A colonoscopy was done which demonstrated severe Mayo 3 left-sided colitis, consistent with a diagnosis of acute severe ulcerative colitis. After failing mesalamine and intravenous methylprednisolone, she was started on infliximab resulting in marked symptom improvement. She then had a repeat colonoscopy one year later which showed no active ulcerative colitis with a mayo score 0 but profound scarring correlating to the severe initial ulcerations from the previous year. Discussion: During normal pathogenesis of ulcerative colitis, inflammation and ulceration causes the bowel walls to swell and thicken with scar tissue. After treatment with monoclonal antibodies, the mucosa should normally heal without evidence of scar tissue or fibrosis. Despite being at high risk for colectomy, this patient responded well to infliximab. However, further studies and follow ups are needed to determine if the scar tissue in this patient has long term effects. Research is ongoing on how to prevent fibrosis in inflammatory bowel disease

A Mathematical Investigation on Tumor-Immune Dynamics: The Impact of Vaccines on the Immune Response

Mathematical models analyzing tumor-immune interactions provide a framework by which to address specific scenarios in regard to tumor-immune dynamics. Important aspects of tumor-immune surveillance to consider is the elimination of tumor cells from a host’s cell-mediated immunity as well as the implications of vaccines derived from synthetic antigen. In present studies, our mathematical model examined the role of synthetic antigen to the strength of the immune system. The constructed model takes into account accepted knowledge of immune function as well as prior work done by de Pillis et al. All equations describing tumor-immune growth, antigen presentation, immune response, and interaction rates were numerically simulated with MATLAB. Here, our work shows that a robust immune response can be generated if the immune system recognizes epitopes that are between 8 to 11 amino acids long. We show through mathematical modeling of how synthetic tumor vaccines can be utilized to mitigate a developing cancer

Recurrent Renal Cell Carcinoma Post Radical Nephrectomy: A Case Report

This is a case of a 73-year-old Caucasian male presenting with an asymptomatic right adrenal mass. Renal Cell Carcinoma (RCC) constitutes 80 to 85% of primary renal neoplasms. At presentation, up to 25% of patients with RCC will have evidence of metastases or locally advanced disease. [1] Patients will rarely present with any symptoms since the majority of patients are incidentally diagnosed due to radiologic procedures performed for other indications. RCC is considered the most lethal of urologic cancers because a patient without intervention who has stage IV metastatic disease has a 5-year survival rate of 23% in comparison to 96% for stage I disease.[14] RCC has several treatment options. The standard of care for localized RCC is surgical resection. Since our patient has metastatic disease, adjuvant therapy is the ideal treatment method. This includes surgical resection prior to chemotherapy or immunotherapy. Current focus is on therapeutics that target vascular endothelial growth factor receptor (VEGF-R) and mammalian target of rapamycin (mTOR). [15] Since this patient presented with a solitary metastatic RCC lesion, the treatment of choice is surgical resection if feasible. With adrenalectomy(solitary metastatic lesion), the patient’s 5-year survival rate at is estimated to be 51%, whereas the 5-year survival rate with adjuvant targeted therapy is estimated to be 18%. [16] Current research indicates that there is no improvement in survival outcome with adjuvant therapy after resection of a solitary metastatic RCC lesion. [15

A Case of T-cell Lymphoma Found in the Liver

Elevation in liver enzymes can be due to a variety of reasons such as toxins, drugs, autoimmune process, sepsis, malignant infiltration, alcoholic hepatitis, viral hepatitis, and other causes. In this case study, our patient presented with an obstructive pattern of liver test abnormalities. The patient demonstrated alkaline phosphatase levels \u3e1000, with AST and ALT levels \u3c200. His T-bilirubin initially was 1.5 and increased to 12.4 by the end of his hospital stay. Workup to exclude other causes of liver injury was performed and eventually a liver biopsy was needed to establish etiology. The biopsy revealed a malignant infiltration of likely Peripheral T-Cell Lymphoma

Amiodarone Induced Epididymo-Orchitis

Amiodarone has a well-established and extensive side effect profile: pulmonary fibrosis, thyroid toxicity, corneal deposits, skin discoloration. However, in some rare instance, epididymitis/orchitis is a side effect of amiodarone. Amiodarone toxicity was first studied in (1, 2) Symptoms range from testicular pain to swelling and erythema (1,2) The mechanism of how this toxicity occurs is unknown. In this case report, we will discuss the case of an elderly patient who developed epididymitis and orchitis after several years of tolerating amiodarone without any adverse events. Our patient underwent a full workup with testicular ultrasound, evaluation by urology and cardiology specialists. Then his amiodarone was discontinued with complete resolution of symptoms

A Rare Manifestation of a Bleeding Tubulovillous Duodenal Polyp Presenting as an Upper Gastrointestinal Hemorrhage

• Duodenal polyps are a group of polyps that are fairly uncommon to find on endoscopic evaluation (1). • They are histologically classified according to mucin phenotype into intestinal and gastric subtypes; the intestinal-type polyps are morphologically subdivided into tubular and tubulovillous adenomas (2) • We present a case of a 76-year-old male with recurrent hematemesis who was found to have an intestinal-type pedunculated tubulovillous adenoma (TVA) in the descending duodenum • An isolated occurrence of non-ampullary sporadic duodenal adenomas (SDA)’s are a rare finding and presentation as an upper GI hemorrhage is extremely uncommon (3) • Furthermore, our patient’s polyp was pedunculated which is atypical because most SDA’s are morphologically flat or sessile (4) • The purpose of this case is to present a rare cause of upper gastrointestinal bleeding and to depict characteristics of an isolated duodenal TVA and its treatment options

GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection

Integrating real-time artificial intelligence (AI) systems in clinical practices faces challenges such as scalability and acceptance. These challenges include data availability, biased outcomes, data quality, lack of transparency, and underperformance on unseen datasets from different distributions. The scarcity of large-scale, precisely labeled, and diverse datasets are the major challenge for clinical integration. This scarcity is also due to the legal restrictions and extensive manual efforts required for accurate annotations from clinicians. To address these challenges, we present \textit{GastroVision}, a multi-center open-access gastrointestinal (GI) endoscopy dataset that includes different anatomical landmarks, pathological abnormalities, polyp removal cases and normal findings (a total of 27 classes) from the GI tract. The dataset comprises 8,000 images acquired from B{\ae}rum Hospital in Norway and Karolinska University Hospital in Sweden and was annotated and verified by experienced GI endoscopists. Furthermore, we validate the significance of our dataset with extensive benchmarking based on the popular deep learning based baseline models. We believe our dataset can facilitate the development of AI-based algorithms for GI disease detection and classification. Our dataset is available at \url{https://osf.io/84e7f/}