Literature Review: Study of Various Techniques for Beam and Polarization Splitting for mm Waves

In this paper, we present the techniques used for splitting the radiation beam and polarization of mm and sub-millimeter waves. First technique is based on H-plane section which splits the square section pipe into two rectangular.Second technique is based on a confocal quasi optical system with wire grid beam splitter. Another is based on grounded Frequency Selective Surface (FSS) array as millimeter wave beam splitter which demonstrates that the reflection phase of coherent mm-wave can be altered by using FSS array with different slot lengths. Last technique is based on Mylar beam splitters over the range of wavelength between 0.08 mm to 2 mm for angles of incidence between 450 and 80?

Study and Analysis of Power and Polarization Splitting techniques for mm waves using COMSOL Multiphysics 5.2a

To test different properties of plasma radiation, different ECE instruments like Michelson interferometer and Radiometer are placed at a distance from the front end optics. To guide the radiation source from the front end optics to the measuring instruments, power/beam splitter box or power switching techniques are used. In this paper, numerical simulation of different techniques for power and polarization splitting unit is analyzed using COMSOL Multiphysics 5.2a software. First technique is of rectangular waveguide power splitter unit, in which the power at the output ports are analyzed. Second technique discussed is based on wire grid polarizer having a unit cell structure. Transmission coefficient for parallel and perpendicular waves are simulated. Lastly, circular waveguide based power splitter unit is designed and analyzed for power distribution at output ports

Assessment of efficacy and safety of artesunate plus sulfadoxine pyrimethamine combination for treatment of uncomplicated falciparum malaria

Background: Resistance of Plasmodium falciparum to antimalarial drugs is common in India. World Health Organization (WHO) recommends artemisinin‑based combination therapy (ACT) to counter the development of resistance in P. falciparum. WHO recommends that ideally antimalarial drug treatment policy or guidelines should be reviewed regularly and updated at least once every 24 months. In consideration to the above recommendation, we planned to conduct the following study. The objective was to determine the efficacy and safety of artesunate + sulphadoxine‑pyrimethamine (AS + SP) in patients with uncomplicated P. falciparum malaria.Methods: The study included 60 patients of uncomplicated P. falciparum. Each patient received AS + SP as per WHO guidelines. Diagnosis was confirmed by peripheral blood film. All patients were followed‑up on days 1, 3, 14, and 28 for detailed clinical and parasitological examination.Results: Of a total 60 patients, 55 patients were followed‑up for 28 days. Remaining 5 patients were lost in follow‑up. As per protocol analysis, 91% (50) of patients had demonstrated adequate clinical and parasitological response. Remaining 9% (5) had treatment failure in which 5.5% (3) had late parasitological failure and 3.6% (2) had late clinical failure. In our study, mean parasite clearance time was 45.2 ± 4.2 hrs.Conclusion: AS + SP is safe and effective drug for the treatment of uncomplicated falciparum malaria. However, the efficacy of this ACT needs to be carefully monitored periodically since treatment failure can occur due to resistance

Development and Optimization of a Machine-Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort

Breast Radiation Therapy; Machine-Learning Prediction; Acute DesquamationRaditeràpia de mama; Predicció d'aprenentatge automàtic; Descamació agudaRadioterapia de mama; Predicción de aprendizaje automático; Descamación agudaPurpose Some patients with breast cancer treated by surgery and radiation therapy experience clinically significant toxicity, which may adversely affect cosmesis and quality of life. There is a paucity of validated clinical prediction models for radiation toxicity. We used machine learning (ML) algorithms to develop and optimise a clinical prediction model for acute breast desquamation after whole breast external beam radiation therapy in the prospective multicenter REQUITE cohort study. Methods and Materials Using demographic and treatment-related features (m = 122) from patients (n = 2058) at 26 centers, we trained 8 ML algorithms with 10-fold cross-validation in a 50:50 random-split data set with class stratification to predict acute breast desquamation. Based on performance in the validation data set, the logistic model tree, random forest, and naïve Bayes models were taken forward to cost-sensitive learning optimisation. Results One hundred and ninety-two patients experienced acute desquamation. Resampling and cost-sensitive learning optimisation facilitated an improvement in classification performance. Based on maximising sensitivity (true positives), the “hero” model was the cost-sensitive random forest algorithm with a false-negative: false-positive misclassification penalty of 90:1 containing m = 114 predictive features. Model sensitivity and specificity were 0.77 and 0.66, respectively, with an area under the curve of 0.77 in the validation cohort. Conclusions ML algorithms with resampling and cost-sensitive learning generated clinically valid prediction models for acute desquamation using patient demographic and treatment features. Further external validation and inclusion of genomic markers in ML prediction models are worthwhile, to identify patients at increased risk of toxicity who may benefit from supportive intervention or even a change in treatment plan

The development and deployment of Common Data Elements for tissue banks for translational research in cancer – An emerging standard based approach for the Mesothelioma Virtual Tissue Bank

<p>Abstract</p> <p>Background</p> <p>Recent advances in genomics, proteomics, and the increasing demands for biomarker validation studies have catalyzed changes in the landscape of cancer research, fueling the development of tissue banks for translational research. A result of this transformation is the need for sufficient quantities of clinically annotated and well-characterized biospecimens to support the growing needs of the cancer research community. Clinical annotation allows samples to be better matched to the research question at hand and ensures that experimental results are better understood and can be verified. To facilitate and standardize such annotation in bio-repositories, we have combined three accepted and complementary sets of data standards: the College of American Pathologists (CAP) Cancer Checklists, the protocols recommended by the Association of Directors of Anatomic and Surgical Pathology (ADASP) for pathology data, and the North American Association of Central Cancer Registry (NAACCR) elements for epidemiology, therapy and follow-up data. Combining these approaches creates a set of International Standards Organization (ISO) – compliant Common Data Elements (CDEs) for the mesothelioma tissue banking initiative supported by the National Institute for Occupational Safety and Health (NIOSH) of the Center for Disease Control and Prevention (CDC).</p> <p>Methods</p> <p>The purpose of the project is to develop a core set of data elements for annotating mesothelioma specimens, following standards established by the CAP checklist, ADASP cancer protocols, and the NAACCR elements. We have associated these elements with modeling architecture to enhance both syntactic and semantic interoperability. The system has a Java-based multi-tiered architecture based on Unified Modeling Language (UML).</p> <p>Results</p> <p>Common Data Elements were developed using controlled vocabulary, ontology and semantic modeling methodology. The CDEs for each case are of different types: demographic, epidemiologic data, clinical history, pathology data including block level annotation, and follow-up data including treatment, recurrence and vital status. The end result of such an effort would eventually provide an increased sample set to the researchers, and makes the system interoperable between institutions.</p> <p>Conclusion</p> <p>The CAP, ADASP and the NAACCR elements represent widely established data elements that are utilized in many cancer centers. Herein, we have shown these representations can be combined and formalized to create a core set of annotations for banked mesothelioma specimens. Because these data elements are collected as part of the normal workflow of a medical center, data sets developed on the basis of these elements can be easily implemented and maintained.</p

Pancreatitis in RYR1-related disorders

Mutations in RYR1 encoding the ryanodine receptor (RyR) skeletal muscle isoform (RyR1) are a common cause of inherited neuromuscular disorders. Despite its expression in a wide range of tissues, non-skeletal muscle manifestations associated with RYR1 mutations have only been rarely reported. Here, we report three patients with a diagnosis of Central Core Disease (CCD), King-Denborough Syndrome (KDS) and Malignant Hyperthermia Susceptibility (MHS), respectively, who in addition to their (putative) RYR1-related disorder also developed symptoms and signs of acute pancreatitis. In two patients, episodes were recurrent, with severe multisystem involvement and sequelae. RyR1-mediated calcium signalling plays an important role in normal pancreatic function but has also been critically implicated in the pathophysiology of acute pancreatitis, particularly in bile acid- and ethanol-induced forms. Findings from relevant animal models indicate that pancreatic damage in these conditions may be ameliorated through administration of the specific RyR1 antagonist dantrolene and other compounds modifying pancreatic metabolism including calcium signalling. These observations suggest that patients with RYR1 gain-of-function variants may be at increased risk of developing acute pancreatitis, a condition which should therefore be considered in the health surveillance of such individuals

Development and Optimization of a Machine-Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort.

Some patients with breast cancer treated by surgery and radiation therapy experience clinically significant toxicity, which may adversely affect cosmesis and quality of life. There is a paucity of validated clinical prediction models for radiation toxicity. We used machine learning (ML) algorithms to develop and optimise a clinical prediction model for acute breast desquamation after whole breast external beam radiation therapy in the prospective multicenter REQUITE cohort study. Using demographic and treatment-related features (m = 122) from patients (n = 2058) at 26 centers, we trained 8 ML algorithms with 10-fold cross-validation in a 50:50 random-split data set with class stratification to predict acute breast desquamation. Based on performance in the validation data set, the logistic model tree, random forest, and naïve Bayes models were taken forward to cost-sensitive learning optimisation. One hundred and ninety-two patients experienced acute desquamation. Resampling and cost-sensitive learning optimisation facilitated an improvement in classification performance. Based on maximising sensitivity (true positives), the "hero" model was the cost-sensitive random forest algorithm with a false-negative: false-positive misclassification penalty of 90:1 containing m = 114 predictive features. Model sensitivity and specificity were 0.77 and 0.66, respectively, with an area under the curve of 0.77 in the validation cohort. ML algorithms with resampling and cost-sensitive learning generated clinically valid prediction models for acute desquamation using patient demographic and treatment features. Further external validation and inclusion of genomic markers in ML prediction models are worthwhile, to identify patients at increased risk of toxicity who may benefit from supportive intervention or even a change in treatment plan. [Abstract copyright: © 2022 The Authors.

CD40 Is Essential in the Upregulation of TRAF Proteins and NF-KappaB-Dependent Proinflammatory Gene Expression after Arterial Injury

Despite extensive investigations, restenosis, which is characterized primarily by neointima formation, remains an unsolved clinical problem after vascular interventions. A recent study has shown that CD40 signaling through TNF receptor associated factor 6 (TRAF6) plays a key role in neointima formation after carotid artery injury; however, underlying mechanisms are not clearly elucidated. Because neointima formation may vary significantly depending on the type of injury, we first assessed the effect of CD40 deficiency on neointima formation in 2 injury models, carotid artery ligation and femoral artery denudation injury. Compared with wild-type mice, CD40 deficiency significantly reduced neointima formation and lumen stenosis in two different models. Further, we investigated the mechanism by which CD40 signaling affects neointima formation after arterial injury. In wild-type mice, the expression levels of CD40, several TRAF proteins, including TRAF1, TRAF2, TRAF3, TRAF5, and TRAF6, as well as total NF-kB p65 and phospho-NF-kB p65, in the carotid artery were markedly upregulated within 3–7 days after carotid ligation. Deficiency of CD40 abolished the injury-induced upregulation of TRAFs including TRAF6 and NF-kB-p65 in the injured vessel wall. Further, CD40−/− mice showed a significant decrease in the recruitment of neutrophils (at 3, 7d) and macrophages (at 7, 21d) into injured artery; this effect was most likely attributed to inhibition of NF-kB activation and marked downregulation of NF-kB-related gene expression, including cytokines (TNFα, IL-1β, IL-6), chemokines (MCP-1), and adhesion molecules (ICAM-1, VCAM-1). Moreover, neutrophil recruitment in a model of thioglycollate-induced peritonitis is impaired in CD40-deficient mice. In vitro data revealed that CD40 deficiency blocked CD40L-induced NF-kB p65 nuclear translocation in leukocytes. Altogether, our data identified for the first time that CD40 is essential in the upregulation of TRAF6, NF-kB activation, and NF-kB-dependent proinflammatory genes in vivo. Our findings firmly established the role for CD40 in neointima formation in 2 distinct injury models