Endophytic Fungi as Alternative and Reliable Sources for Potent Anticancer Agents

In comparison with other natural sources like plants, highly diverse microorganisms are narrowly explored, especially with respect to their limitless potentials as repositories of exceptionally bioactive natural products. Of these organisms, fungi inhabiting tissues of plant in a noninvasive relationship (endophytic fungi) have proven undeniably useful and unmatchable as sources of potent bioactive molecules against several diseases such as cancer and related ailments. In general terms, endophytic fungi are highly prevalent organisms found in the tissue (intracellular or intercellular) of plants and at least for reasonable portion of their lives. It has been proven that virtually every plant, irrespective of habitat and climate, plays host to wide varieties of endophytes. Endophytic fungi produce metabolites produced by different biosynthetic pathways to that of the host plant, and this robustness equips them to synthesize unlimited structural entities and scaffolds of diverse classes. Interestingly too, the cohabitation/culture of these fungi with certain bacteria offers even stronger hopes for anticancer drug discovery. The endless need for potent drugs has necessitated the search of bioactive molecules from several sources, and endophytic fungi appear to be a recipe. This chapter is an attempt to present the current trend of research with these very promising organisms

Modulatory effects of Saccharomyces cerevisiae var. boulardii on experimentally induced benign prostatic hyperplasia in rats

25-32Benign prostatic hyperplasia (BPH) is an age-related non-neoplastic disease of the prostate gland in men that has become a global health issue in recent years. Due to the side effects of conventional treatment options, attention is now focused on phytotherapeutics for its management. We investigated the possible protective effect of Saccharomyces cerevisiae var. boulardii in a rat model of testosterone propionate (TP) induced BPH. Rats were divided into five groups: Gr. I, untreated control group; Gr. II, TP group; Gr. III, TP + finasteride; Gr. IV, TP + S. cerevisiae var. boulardii; and Gr. V, S. cerevisiae var. boulardii group. Treatments were given daily for 28 days. At the end of the experiment, all rats were weighed and the prostatic indices, prostate specific antigen, serum testosterone concentration as well as the histological and histomorphometric changes were evaluated. Saccharomyces cerevisiae var. boulardii significantly (P <0.05) reduced prostate weight, prostatic index, serum prostate specific antigen, prostatic epithelial thickness and increased luminal diameter. Thus, the results of this study suggest that S. cerevisiae var. boulardii is a potential pharmacological candidate for management of benign prostatic hyperplasia

Skin Tone Analysis for Representation in Educational Materials (STAR-ED) using machine learning

Abstract Images depicting dark skin tones are significantly underrepresented in the educational materials used to teach primary care physicians and dermatologists to recognize skin diseases. This could contribute to disparities in skin disease diagnosis across different racial groups. Previously, domain experts have manually assessed textbooks to estimate the diversity in skin images. Manual assessment does not scale to many educational materials and introduces human errors. To automate this process, we present the Skin Tone Analysis for Representation in EDucational materials (STAR-ED) framework, which assesses skin tone representation in medical education materials using machine learning. Given a document (e.g., a textbook in .pdf), STAR-ED applies content parsing to extract text, images, and table entities in a structured format. Next, it identifies images containing skin, segments the skin-containing portions of those images, and estimates the skin tone using machine learning. STAR-ED was developed using the Fitzpatrick17k dataset. We then externally tested STAR-ED on four commonly used medical textbooks. Results show strong performance in detecting skin images (0.96 ± 0.02 AUROC and 0.90 ± 0.06 F1 score) and classifying skin tones (0.87 ± 0.01 AUROC and 0.91 ± 0.00 F1 score). STAR-ED quantifies the imbalanced representation of skin tones in four medical textbooks: brown and black skin tones (Fitzpatrick V-VI) images constitute only 10.5% of all skin images. We envision this technology as a tool for medical educators, publishers, and practitioners to assess skin tone diversity in their educational materials

Exacerbation of Autoantibody-Mediated Hemolytic Anemia by Viral Infection

Strong enhancement of the pathogenicity of an antierythrocyte monoclonal antibody was observed after infection of mice with lactate dehydrogenase-elevating virus. While injection of the antierythrocyte antibody alone induced only moderate anemia, concomitant infection with this virus, which is harmless in most normal mice, led to a dramatic drop in the hematocrit and to death of infected animals. In vitro and in vivo analyses showed a dramatic increase in the ability of macrophages from infected mice to phagocytose antibody-coated erythrocytes. These results indicate that viruses can trigger the onset of autoimmune disease by enhancing the pathogenicity of autoantibodies. They may explain how unrelated viruses could be implicated in the etiology of autoantibody-mediated autoimmune diseases