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Derek J Van Booven,1 Manish Kuchakulla,2 Raghav Pai,2 Fabio S Frech,2 Reshna Ramasahayam,2 Pritika Reddy,2 Madhumita Parmar,2 Ranjith Ramasamy,2,3 Himanshu Arora1– 3 1John P Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; 2Department of Urology, Miller School of Medicine, University of Miami, Miami, FL, USA; 3The Interdisciplinary Stem Cell Institute, Miller School of Medicine, University of Miami, Miami, FL, USACorrespondence: Himanshu Arora Email Hxa287@miami.eduAbstract: The diagnosis and management of prostate cancer involves the interpretation of data from multiple modalities to aid in decision making. Tools like PSA levels, MRI guided biopsies, genomic biomarkers, and Gleason grading are used to diagnose, risk stratify, and then monitor patients during respective follow-ups. Nevertheless, diagnosis tracking and subsequent risk stratification often lend itself to significant subjectivity. Artificial intelligence (AI) can allow clinicians to recognize difficult relationships and manage enormous data sets, which is a task that is both extraordinarily difficult and time consuming for humans. By using AI algorithms and reducing the level of subjectivity, it is possible to use fewer resources while improving the overall efficiency and accuracy in prostate cancer diagnosis and management. Thus, this systematic review focuses on analyzing advancements in AI-based artificial neural networks (ANN) and their current role in prostate cancer diagnosis and management.Keywords: prostate cancer, active surveillance, clinical trials, artificial intelligence

Daniel C Gonzalez,1 Kajal Khodamoradi,1 Raghav Pai,1 Kristopher Guarch,2 Zachary M Connelly,3 Emad Ibrahim,1 Himanshu Arora,1 Ranjith Ramasamy1 1Department of Urology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA; 2Florida International University, Miami, FL 33199, USA; 3Louisiana State University Health Shreveport, Shreveport, LA 71103, USA; 4The Interdisciplinary Stem Cell Institute, University of Miami, Miller School of Medicine, Miami, FL 33136, USACorrespondence: Ranjith RamasamyDepartment of Urology, Miller School of Medicine, University of Miami, 1120 NW 14th St, #1551, Miami, FL 33136, USATel +1 (305)-243-7200Email Ramasamy@miami.eduBackground: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a virus that is present in most bodily fluids. However, whether SARS-CoV-2 is present in the semen remains underexplored. Thus, we systematically reviewed the existing studies on the presence of SARS-CoV-2 in semen.Methods: A literature search of the PubMed, Embase, Cochrane, Web of Science, Google Scholar, and Ovid databases was performed for articles from the dates of their inception to August 2020 using the following keywords: COVID-19, SARS-CoV2, seminal, semen, and sperm. After excluding non-human studies and articles that were not in the English language, we identified 19 relevant studies. The full text of the articles were reviewed and a total of eight articles remained after applying our selection criteria.Results: After reviewing the presence of SARS-CoV-2 in the eight different studies using semen samples, only one reported the presence of the virus. Six out of 160 total semen samples with SARS-CoV-2 positive demonstrated the presence of viral RNA, of which 2 were from males in the recovery phase and 4 from the acute phase of the infection.Conclusion: The novel nature of SARS-CoV-2 has limited the number and size of studies on semen. Nevertheless, the current literature, while limited, has confirmed the presence of SARS-CoV-2 in semen in one out of the eight reported studies and totaling 4.3% of the population screened. Taken together, the risk of the presence of SARS-CoV-2 in semen appears to be extremely low and likely negligible in recovered men. Future studies need to focus on whether complete viral particles can be seen in semen and the possibility of sexual transmission.Keywords: COVID-19, coronavirus, semen, semen parameters

Harleen Arora, Fleta N Bray, Jessica Cervantes, Leyre A Falto Aizpurua Department of Dermatology and Cutaneous Surgery, University of Miami-Miller School of Medicine, Miami, FL, USA Abstract: Benign familial chronic pemphigus or Hailey–Hailey disease is caused by an ­autosomal dominant mutation in the ATP2C1 gene leading to suprabasilar acantholysis. The disease most commonly affects intertriginous areas symmetrically. The chronic nature of the disease and multiple recurrences make the disease bothersome for patients and a treatment challenge for physicians. Treatments include topical and/or systemic agents and surgery including laser. This review summarizes the available treatment options. Keywords: familial benign chronic pemphigus, corticosteroids, dermabrasion, Hailey–Hailey disease, laser

In this study, we propose a family of iterative procedures with no derivatives for calculating multiple roots of one-variable nonlinear equations. We also present an iterative technique to approximate the multiplicity of the roots. The new class is optimal since it fits the Kung-Traub hypothesis and has second-order convergence. Derivative-free methods for calculating multiple roots are rarely found in literature, especially in the case of one-step methods, which are the simplest ones in terms of their structure. Moreover, this new family contains almost all the existing single-step derivative-free iterative schemes as its special cases, with an additional degree of freedom. Several results are used to confirm its theoretical order of convergence. Through the complex discrete dynamics analysis, the stability of the suggested class is illustrated, and the most stable methods are found. Several test problems are included to check the performance of the proposed methods, whether the multiplicity of the roots is estimated or known, comparing the numerical results with those obtained by other methods. [ABSTRACT FROM AUTHOR]