Numerical simulation of Orion CEV re-entry vehicle at low altitude

Aerothermodynamics analysis of Orion Crew Exploration Vehicle (CEV) re-entry vehicle at low altitude has been studied numerically. At low altitude continuum approximation is valid due to high density region. The Favre averaging (density weighted averaging) procedure is applied to obtain the governing equations. The Favre averaged Navier-stokes along with Spalart-Allmaras turbulent model are used to compute flow field in high density region using open source CFD code SU2

Management of Hypertension and Diabetes in Obesity: Non-Pharmacological Measures

Obesity has become a global epidemic over the past few decades because of unhealthy dietary habits and reduced physical activity. Hypertension and diabetes are quite common among obese individuals and there is a linear relationship between the degree of obesity and these diseases. Lifestyle interventions like dietary modifications and regular exercise are still important and safe first-line measures for treatment. Recently, bariatric surgery has emerged as an important and very effective treatment option for obese individuals especially in those with comorbidities like hypertension and diabetes. Though there are few effective drugs for the management of obesity, their efficacy is only modest, and they should always be combined with lifestyle interventions for optimal benefit. In this paper we aim to outline the non-pharmacological measures for the management of hypertension and diabetes in obesity

Multidrug and extensively drug-resistant tuberculosis from a general practice perspective

Despite intensive efforts to eradicate the disease, tuberculosis continues to be a major threat to Indian society, with an estimated prevalence of 3.45 million cases in 2006. Emergence of multidrug-resistant tuberculosis has complicated eradication attempts in recent years. Incomplete and/inadequate treatment are the main causes for development of drug resistance. Directly observed therapy, short-course (DOTS) is the World Health Organization (WHO) strategy for worldwide eradication of tuberculosis, and our country achieved 100% coverage for DOTS through the Revised National Tuberculosis Control Program in 2006. For patients with multidrug-resistant tuberculosis, the WHO recommends a DOTS-Plus treatment strategy. Early detection and prompt treatment of multidrug-resistant tuberculosis is crucial to avoid spread of the disease and also because of the chances of development of potentially incurable extensively drug-resistant tuberculosis in these cases. This review discusses the epidemiologic, diagnostic, and therapeutic aspects of multidrug-resistant tuberculosis, and also outlines the role of primary care doctors in the management of this dangerous disease

Tumor metabolism in pheochromocytomas: clinical and therapeutic implications

Pheochromocytomas and paragangliomas (PPGLs) have emerged as one of the most common endocrine tumors. It epitomizes fascinating crossroads of genetic, metabolic, and endocrine oncology, providing a canvas to explore the molecular intricacies of tumor biology. Predominantly rooted in the aberration of metabolic pathways, particularly the Krebs cycle and related enzymatic functionalities, PPGLs manifest an intriguing metabolic profile, highlighting elevated levels of oncometabolites like succinate and fumarate, and furthering cellular malignancy and genomic instability. This comprehensive review aims to delineate the multifaceted aspects of tumor metabolism in PPGLs, encapsulating genetic factors, oncometabolites, and potential therapeutic avenues, thereby providing a cohesive understanding of metabolic disturbances and their ramifications in tumorigenesis and disease progression. Initial investigations into PPGLs metabolomics unveiled a stark correlation between specific genetic mutations, notably in the succinate dehydrogenase complex (SDHx) genes, and the accumulation of oncometabolites, establishing a pivotal role in epigenetic alterations and hypoxia-inducible pathways. By scrutinizing voluminous metabolic studies and exploiting technologies, novel insights into the metabolic and genetic aspects of PPGLs are perpetually being gathered elucidating complex interactions and molecular machinations. Additionally, the exploration of therapeutic strategies targeting metabolic abnormalities has burgeoned harboring potential for innovative and efficacious treatment modalities. This review encapsulates the profound metabolic complexities of PPGLs, aiming to foster an enriched understanding and pave the way for future investigations and therapeutic innovations in managing these metabolically unique tumors

A Cloud-based Deep Learning Framework for Remote Detection of Diabetic Foot Ulcers

This research proposes a mobile and cloud-based framework for the automatic detection of diabetic foot ulcers and conducts an investigation of its performance. The system uses a cross-platform mobile framework which enables the deployment of mobile apps to multiple platforms using a single TypeScript code base. A deep convolutional neural network was deployed to a cloud-based platform where the mobile app could send photographs of patient's feet for inference to detect the presence of diabetic foot ulcers. The functionality and usability of the system were tested in two clinical settings: Salford Royal NHS Foundation Trust and Lancashire Teaching Hospitals NHS Foundation Trust. The benefits of the system, such as the potential use of the app by patients to identify and monitor their condition are discussed

Exercise Induced Systemic Venous Hypertension in the Fontan Circulation

Increasingly end-organ injury is being demonstrated late after institution of the Fontan circulation, particularly liver fibrosis and cirrhosis. The exact mechanisms for these late phenomena remain largely elusive. Hypothesizing that exercise induces precipitous systemic venous hypertension and insufficient cardiac output for the exercise demand, i.e. a possible mechanism for end-organ injury, we sought to demonstrate the dynamic exercise responses in systemic venous (SVP) and concurrent end organ perfusion. Ten stable Fontan patients and 9 control subjects underwent incremental cycle ergometry based cardiopulmonary exercise testing. SVP was monitored in the right upper limb and regional tissue oxygen saturation was monitored in the brain and kidney using Near Infrared Spectroscopy. SVP rose profoundly in concert with workload in the Fontan group, described by the regression equation 15.97+0.073 Watts per mm Hg. In contrast SVP did not change in healthy controls. Regional renal (p<0.01) and cerebral tissue saturations (p<0.001) were significantly lower and fell more rapidly in Fontan patients. We conclude that in a stable group of adult patients with Fontan circulation high intensity exercise was associated with systemic venous hypertension and reduced systemic oxygen delivery. This physiologic substrate has the potential to contribute to endorgan injury

Diabetic foot ulcers segmentation challenge report: benchmark and analysis

Monitoring the healing progress of diabetic foot ulcers is a challenging process. Accurate segmentation of foot ulcers can help podiatrists to quantitatively measure the size of wound regions to assist prediction of healing status. The main challenge in this field is the lack of publicly available manual delineation, which can be time consuming and laborious. Recently, methods based on deep learning have shown excellent results in automatic segmentation of medical images, however, they require large-scale datasets for training, and there is limited consensus on which methods perform the best. The 2022 Diabetic Foot Ulcers segmentation challenge was held in conjunction with the 2022 International Conference on Medical Image Computing and Computer Assisted Intervention, which sought to address these issues and stimulate progress in this research domain. A training set of 2000 images exhibiting diabetic foot ulcers was released with corresponding segmentation ground truth masks. Of the 72 (approved) requests from 47 countries, 26 teams used this data to develop fully automated systems to predict the true segmentation masks on a test set of 2000 images, with the corresponding ground truth segmentation masks kept private. Predictions from participating teams were scored and ranked according to their average Dice similarity coefficient of the ground truth masks and prediction masks. The winning team achieved a Dice of 0.7287 for diabetic foot ulcer segmentation. This challenge has now entered a live leaderboard stage where it serves as a challenging benchmark for diabetic foot ulcer segmentation

Deep learning in diabetic foot ulcers detection: A comprehensive evaluation

There has been a substantial amount of research involving computer methods and technology for the detection and recognition of diabetic foot ulcers (DFUs), but there is a lack of systematic comparisons of state-of-the-art deep learning object detection frameworks applied to this problem. DFUC2020 provided participants with a comprehensive dataset consisting of 2,000 images for training and 2,000 images for testing. This paper summarizes the results of DFUC2020 by comparing the deep learning-based algorithms proposed by the winning teams: Faster R–CNN, three variants of Faster R–CNN and an ensemble method; YOLOv3; YOLOv5; EfficientDet; and a new Cascade Attention Network. For each deep learning method, we provide a detailed description of model architecture, parameter settings for training and additional stages including pre-processing, data augmentation and post-processing. We provide a comprehensive evaluation for each method. All the methods required a data augmentation stage to increase the number of images available for training and a post-processing stage to remove false positives. The best performance was obtained from Deformable Convolution, a variant of Faster R–CNN, with a mean average precision (mAP) of 0.6940 and an F1-Score of 0.7434. Finally, we demonstrate that the ensemble method based on different deep learning methods can enhance the F1-Score but not the mAP