Chemotherapy can affect testis development of young boys with cancer, reducing the chances of fatherhood in adulthood. Studies using experimental models are needed to determine the damage caused by individual chemotherapy drugs in order to predict the risk of infertility and direct patients towards appropriate fertility preservation options. Here, we investigated the individual role of two drugs, cisplatin and doxorubicin, using an in vitro culture model of prepubertal (postnatal day 5) mouse testis that supports induction and maintenance of full spermatogenesis. Twenty-four hour exposure with either drug at clinically-relevant doses (0.25, 0.5 or 0.75 μg/mL for cisplatin, or 0.01, 0.03 or 0.05 μg/mL for doxorubicin), induced an acute significant loss of spermatogonial stem cells (SSCs; PLZF+), proliferating SSCs (PLZF+BrdU+), total germ cells (MVH+), and spermatocytes (SCP3+) one week after chemotherapy exposure. By the time of the first (Week 4) and second (Week 8) waves of spermatogenesis, there was no longer any effect on SSC or proliferating SSC numbers in drug-exposed testis compared to untreated tissue however, the populations of total germ cells and spermatocytes were still lower in the higher-dose cisplatin treated groups, along with a reduced frequency of round and elongated spermatids in both cisplatin- and doxorubicin-treated testis fragments. Overall, this study details a direct impairment of germ cell development following acute chemotherapy-induced damage during the prepubertal phase, most likely due to an effect on SSCs, using an in vitro culture system that successfully recapitulates key events of mouse spermatogenesis.SARS-CoV-2 infection was announced as a pandemic in March 2020. Since then, several scientists have focused on the low prevalence of smokers among hospitalized COVID-19 patients. These findings led to our hypothesis that the Nicotinic Cholinergic System (NCS) plays a crucial role in the manifestation of COVID-19 and its severe symptoms.  https://www.selleckchem.com/ATM.html  Molecular modeling revealed that the SARS-CoV-2 Spike glycoprotein might bind to nicotinic acetylcholine receptors (nAChRs) through a cryptic epitope homologous to snake toxins, substrates well documented and known for their affinity to the nAChRs. This binding model could provide logical explanations for the acute inflammatory disorder in patients with COVID-19, which may be linked to severe dysregulation of NCS. In this study, we present a series of complexes with cholinergic agonists that can potentially prevent SARS-CoV-2 Spike glycoprotein from binding to nAChRs, avoiding dysregulation of the NCS and moderating the symptoms and clinical manifestations of COVID-19. If our hypothesis is verified by in vitro and in vivo studies, repurposing agents currently approved for smoking cessation and neurological conditions could provide the scientific community with a therapeutic option in severe COVID-19.Von Hippel-Lindau disease predisposes to develop renal cell carcinoma (RCC). Treatment is frequently challenging due to presence of bilateral tumors and high risk of recurrence. We present the case of a VHL-patient with bilateral recurrence of clear-cell RCC after bilateral partial nephrectomy and autotransplantation on one side. Recurrence on the transplanted kidney was treated with repeat partial nephrectomy with good oncological and functional outcomes. This approach is feasible in centres with wide experience in partial nephrectomy and renal transplantation when minimally invasive tumor ablation is not indicated.SARS-COV-2 has created one of the most massive pandemics in modern history. There is a rapid accumulation of data on its epidemiology, clinical course, diagnosis, management, and complications. One of the sequelae of COVID-19 pneumonia and acute respiratory distress syndrome (ARDS) is pulmonary fibrosis. There is a dearth of accurate data on the prevalence of pulmonary fibrosis post-COVID-19. We report a patient who developed dyspnea secondary to pulmonary fibrosis after successful treatment of COVID-19 pneumonia.Patients with primary immunodeficiency disease (PID) are not only vulnerable to mycobacterial disease, but are also more likely to develop adverse events following BCG vaccination. These events can range from regional disease (BCGitis) to disseminated disease (BCGosis). Chronic granulomatous disease (CGD), which is characterized by impaired leukocyte phagocytic function, is one of the many inherited PIDs that increase the body's susceptibility to recurrent bacterial and fungal infections. Here, we report a 6-year-old boy with no significant past medical history who presented with progressive lymphadenopathy six years after BCG vaccination. He was later diagnosed with CGD on further evaluation.In the United States, C. gattii is considered to be endemic to the Pacific Northwest and although uncommon, additional cases have been documented in other regions including the Southeastern United States. While it has been hypothesized in the past that C. gattii may be endemic to the Southeastern United States, there remains a paucity of evidence. Here, we present a patient with no history of HIV/AIDS and no organ transplant and document the course of his disease and presentation. There were no adverse long-term neurological outcomes in this patient and the combination of steroid use, antifungal agents, and cerebrospinal fluid drainage resulted in his discharge from the hospital after 12 days. This patient's subacute presentation with vague neurological symptoms highlights the importance of understanding the treatment of rare causes of meningitis.Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began to surpass other established mature models on some important benchmarks. Later, it was widely used in academia and industry. Ranging from image analysis to natural language processing, it fully exerted its magic and now become the state-of-the-art machine learning models. Deep neural networks have great potential in medical imaging technology, medical data analysis, medical diagnosis and other healthcare issues, and is promoted in both pre-clinical and even clinical stages. In this review, we performed an overview of some new developments and challenges in the application of machine learning to medical image analysis, with a special focus on deep learning in photoacoustic imaging. The aim of this review is threefold (i) introducing deep learning with some important basics, (ii) reviewing recent works that apply deep learning in the entire ecological chain of photoacoustic imaging, from image reconstruction to disease diagnosis, (iii) providing some open source materials and other resources for researchers interested in applying deep learning to photoacoustic imaging.