Mitochondria, independent double-membrane organelles, are intracellular power plants that feed most eukaryotic cells with the ATP produced via the oxidative phosphorylation (OXPHOS). Consistently, cytochrome c oxidase (COX) catalyzes the electron transfer chain's final step. Electrons are transferred from reduced cytochrome c to molecular oxygen and play an indispensable role in oxidative phosphorylation of cells. Cytochrome c oxidase subunit 6c (COX6C) is encoded by the nuclear genome in the ribosome after translation and is transported to mitochondria via different pathways, and eventually forms the COX complex. In recent years, many studies have shown the abnormal level of COX6C in familial hypercholesterolemia, chronic kidney disease, diabetes, breast cancer, prostate cancer, uterine leiomyoma, follicular thyroid cancer, melanoma tissues, and other conditions. Its underlying mechanism may be related to the cellular oxidative phosphorylation pathway in tissue injury disease. Here reviews the varied function of COX6C in non-tumor and tumor diseases.The outbreak of COVID-19 created unprecedented strain in the healthcare system. Various research revealed that COVID-19 main protease (Mpro) and human angiotensin-converting enzyme 2 (ACE2) are responsible for viral replication and entry into the human body, respectively. Blocking the activity of these enzymes gives a potential therapeutic target for the COVID-19. The objective of the study was to explore phytochemicals from Ageratina adenophora against SARS-CoV-2 through in-silico studies. In this study, 34 phytochemicals of A. adenophora were docked with Mpro and ACE2 through AutoDock Tools-1.5.6 and their binding affinity was studied. Phytochemicals with higher affinity have been chosen for further molecular dynamics simulations to determine the stability with target protein. Molecular dynamics simulations were studied on GROMACS 5.1.4 version. Furthermore, 5-β-glucosyl-7-demethoxy-encecalin (5GDE) and 2-oxocadinan-3,6(11)-dien-12,7-olide (BODO) were found to be potential blockers with excellent binding affinity with Mpro and ACE2 than their native inhibitors remdesivir and hydroxychloroquine respectively. The drug likeness study and pharmacokinetics of the phytoconstituents present in A. adenophora provide an excellent support for the lead drug discovery against COVID-19.The present study discusses a pilot intervention for youth in a predominantly Latinx rural community in the U.S. The intervention incorporated multimodal creative activities into the social cognitive career theory-based healthcare career program. Participants (N = 75) were assessed for healthcare career self-efficacy, outcome expectations, and interests (pre-/post-intervention). Their healthcare career task self-efficacy and interests scores significantly increased overall. By race/ethnicity groups, however, only White students reported an increase in healthcare interests, and only students of color an increase in healthcare career task self-efficacy. This provides preliminary evidence for the effectiveness of the proposed intervention. Implications for services and research are discussed. The widespread access to medically assisted reproduction (MAR) techniques for all women, regardless of any infertility diagnosis, has led to an increased, but as yet unmet, demand for sperm donors in Portugal. For this study, we deployed an online survey to explore men's motivations for donating and their attitudes toward anonymity and donating for specific groups. The study's sample comprised men who were eligible to donate sperm (N = 282). The relationships between these factors and participants' psychological and sociodemographic characteristics were also explored. The results mostly indicated altruistic reasons for donating, positive attitudes toward anonymity, and a greater willingness to donate to infertilewomen. Overall, sexual orientation was not associated with the participants' attitudes and motivations. Age, education level, conscientiousness, empathicconcern, and conservative and religious values were associated with the participants' motivations and attitudes toward sperm donation. Recruitment campaigns should therefore consider the specific motivations, attitudes, and psychosocial characteristics of potential sperm donors.Indeed, parenthood is a universal right, so sperm donation should be encouraged, regardless of recipients' fertility status. Clear information about theidentifiability of sperm donors should also be provided.Recruitment campaigns should therefore consider the specific motivations, attitudes, and psychosocial characteristics of potential sperm donors. Indeed, parenthood is a universal right, so sperm donation should be encouraged, regardless of recipients' fertility status. Clear information about the identifiability of sperm donors should also be provided.COVID-19 pandemic is widely spreading over the entire world and has established significant community spread. Palazestrant order Fostering a prediction system can help prepare the officials to respond properly and quickly. Medical imaging like X-ray and computed tomography (CT) can play an important role in the early prediction of COVID-19 patients that will help the timely treatment of the patients. The x-ray images from COVID-19 patients reveal the pneumonia infections that can be used to identify the patients of COVID-19. This study presents the use of Convolutional Neural Network (CNN) that extracts the features from chest x-ray images for the prediction. Three filters are applied to get the edges from the images that help to get the desired segmented target with the infected area of the x-ray. To cope with the smaller size of the training dataset, Keras' ImageDataGenerator class is used to generate ten thousand augmented images. Classification is performed with two, three, and four classes where the four-class problem has X-ray images from COVID-19, normal people, virus pneumonia, and bacterial pneumonia. Results demonstrate that the proposed CNN model can predict COVID-19 patients with high accuracy. It can help automate screening of the patients for COVID-19 with minimal contact, especially areas where the influx of patients can not be treated by the available medical staff. The performance comparison of the proposed approach with VGG16 and AlexNet shows that classification results for two and four classes are competitive and identical for three-class classification.