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Portal vein thrombosis associated with peritoneal tuberculosis is an uncommon manifestation of extrapulmonary tuberculosis. We report one such case of a 33-year-old male with a one-year history of dyspepsia, having been on proton pump inhibitors all this time with temporary relief. In view of ongoing symptoms, an endoscopy was done, which at first showed duodenal ulcer. On repeat endoscopy after an interval, there was evidence of mucosa-associated lymphoid tissue (MALT) lymphoma, which prompted a host of investigations in the patient. A positron emission tomography (PET) scan revealed extensive omento-peritoneal involvement along with a hypodense lesion in the liver with interval development of portal vein thrombosis on a CT scan of the abdomen. The biopsy of the hepatic lesion showed granulomatous inflammation. Faced with a diagnostic dilemma, finally, a laparoscopic biopsy was done, which confirmed the diagnosis of peritoneal TB with portal vein thrombosis. This case highlights the importance of keeping a high index of suspicion to include tuberculosis as a differential when presented with a case such as this and to conduct appropriate investigations to establish the correct diagnosis.
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During a cytokine storm, dysregulated proinflammatory cytokines are produced in excess. Cytokine storms occur in multiple infectious diseases, including Coronavirus 2019 (COVID-19). Thus, eliminating cytokine storms to enhance patient outcomes is crucial. Given the numerous cytokines involved, individual therapies might have little effect. Traditional cytokines might be less effective than medicines that target malfunctioning macrophages. Nanomedicine-based therapeutics reduce cytokine production in animal models of proinflammatory illnesses. The unique physicochemical features and controlled nano-bio interactions of nanotechnology show promise in healthcare and could be used to treat several stages of this virus-induced sickness, including cytokine storm mortality. Macrophage-oriented nanomedicines can minimize cytokine storms and associated harmful effects, enhancing patient outcomes. Here, we also discuss engineering possibilities for enhancing macrophage efficacy with nanodrug carriers.
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Over the years, computer scientists are working on building models that aid the scientific community in many ways by cutting laboratory expenses or by saving time. Such models find useful applications in microscopy images as well. Determining the morphology of nanoparticles from Transmission Electron Microscopy images is a manual and cumbersome task. In the past years, scientists have tried to build models to automate the process of nanoparticle segmentation in microscopy images. This study focuses on finding the best segmentation model, which achieves high metrics and is robust to microscopy parameters. For this purpose, eight different models have been compared. The training dataset consists of 150 BF-TEM Platinum nanoparticle images containing 3629 nanoparticles of all kinds. Further, we examine the generalizability of the models on E-TEM Gold nanoparticle images. We also describe essential considerations while choosing a network for segmenting nanoparticle images that generalize well across the Platinum BF-TEM and Gold E-TEM nanoparticles dataset. The layer gradients are visualized to further explain the black-box nature of neural networks.
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BACKGROUND: The objective of the study is to analyze the expression of androgen, estrogen and progesterone receptor in different types of endometrial carcinomas and to correlate the androgen receptor expression with estrogen and progesterone receptor and the clinicopathological parameters like lymphovascular invasion, grade of the tumour, size of tumour and extent of myometrial invasion.. METHODS: It is a cross-sectional analytical study design with a simple random sample of a total of 54 cases of different types of endometrial carcinomas from the year 2017. Immunohistochemical stains androgen receptor, estrogen receptor, and Progesterone receptor were applied in all the cases. The Pearson Chi-square test of independence was applied to measure association and P-value is calculated to check the significance of the results. RESULTS: Androgen receptor expression was observed in 73% of low-grade endometrioid carcinomas, 62.5% of high-grade endometrioid carcinomas, 62% of serous, 20% of clear cell and 18% of carcinosarcomas, respectively. Androgen positive tumours were also positive for estrogen and progesterone in most of the cases, except 3 serous carcinomas and one low-grade endometrioid carcinoma. However, no significant relation was observed between androgen expression and prognostic parameters like the lymphovascular invasion, size of the tumour and myometrial invasion. CONCLUSIONS: Maximum expression of androgen receptor was observed in endometrioid and serous carcinomas, while carcinosarcomas and clear cell carcinomas showed minimum expression with no significant correlation between androgen receptor expression and clinicopathological parameters.