Nasal Drug Delivery In Ayurveda: A Narrative Review

Ayurveda is the ancient medical system in India that uses nasal therapy. During COVID -19 pandemic, the ministry of AYUSH provided guidelines to boost immunity. The Nasya (nasal delivery) was one of the recommendations by the AYUSH ministry to boost immunity. Nasya has been still in practice for various ailments like chronic rhinitis, headache, cervical spondylosis, Dyspnea, etc., but the knowledge about how Nasya works is still unclear. This review article discusses the practice and current advances in nasal delivery in modern science. It also discusses the possible mechanism of how Nasya can act and boost immunity and what research can be done in the form of clinical and experimental studies to increase the knowledge and understanding of Nasya. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Automatic COVID-19 Detection from Chest X-Rays using Deep Learning Techniques

COVID-19 emerged in November 2019 in the Wuhan city of China. Since then, it has expanded exponentially and reached every corner of the world. To date, it has infected more than three hundred eighty-five million people and caused more than five million seven hundred deaths. Traditional COVID-19 diagnostic tests lack sensitivity and result in false-negative reports several times. Using X-Rays and CT scans to detect covid-19 can aid the diagnosis process when powered by deep learning techniques. Using deep learning will provide accurate results in a fast and automatic manner. The proposed research work has performed a total of twenty-eight experiments. This research work has experimented with seven different Deep Learning models including, DenseNet201, MobileNetV2, DenseNet121, VGG16, VGG19, InceptionV3, and ResNet50. The performance of each model is tested based on the distinct image enhancement techniques. The four different experiments include raw data, data preprocessed with gamma correction for two different gamma values (0.7 and 1.2), and Contrast Limited Adaptive Histogram Equalization (CLAHE). Gamma Correction with gamma value 1.2 performed the best. Lastly, this research work has created an ensemble of three best-performing algorithms including, DenseNet201, MobileNetV2, DenseNet121, and achieved an accuracy, precision, recall, f1 score, and AUC of 98.34%, 98.61%, 98.78%, 98.2%, and 99.8%, respectively. © 2022 IEEE.

Continuing Cancer Treatment in a "COVID HOTSPOT" in India: Are We Overestimating the Risks?

Context: We describe the treatment of cancer patients carried out in a Government of India-designated, dedicated coronavirus disease (COVID) hospital (DCH) in a COVID hotspot in India. Aims: The aim was to study the change and delay in the management of cancer patients during the pandemic and its complications. Settings and Design: This was an observational cohort study conducted at a tertiary care center, which was also a DCH. Subjects and Methods: Cancer patients receiving cancer surgery, chemotherapy, and radiotherapy in our DCH, during the lockdown, were studied. Results: A total of 864 patients received treatment for cancer in our hospital during the period of March 20, 2020 - May 31, 2020. There were no COVID-related complications. The treatment of 109/864 patients (12.61%) was delayed due to the pandemic and lockdown situation and the treatment plan was changed for 84/864 (9.72%) patients. There were 21 deaths in these 864 patients (2.43%), but only two deaths were COVID related. Symptomatic patients were tested for COVID, and 3/864 patients (0.34%) were detected to be COVID positive. Conclusions: We successfully delivered cancer treatment to patients in our DCH. The percentage of adverse effects, symptomatic COVID infection, and related mortality has been very low in our study. Cancer care can be continued with due diligence even during this pandemic.