ANTIOXIDANT ACTIVITY AND BIOGENIC SYNTHESIS OF SELENIUM NANOPARTICLES USING THE LEAF EXTRACT OF ALOE VERA

Objective: The objective of this present study were to the biogenic synthesis of selenium nanoparticles using Aloe vera extract and check it's antioxidant potential by ABTS, DPPH and FRAP assays.Methods: In this study we investigated the clove of Aloe vera, which is used for the synthesis of selenium nanoparticles were characterized by using UV-Visible (UV-VIS) spectrophotometer, Transmission electron microscopy (TEM), Fourier transform spectroscopy (FTIR) and Energy dispersive X-Ray spectroscopy (EDAX) and ABTS, DPPH and FRAP assays for checked it's antioxidant potential.Results: The present study was carried out to synthesis of Selenium nanoparticles using extract of Aloe vera. UV-Vis Spectra at 350 nm with Aloe vera extract and observed as hollow and spherical particles in size ranging 7-48 nm which is found more stable more than two months. EDAX analysis was carried out to check the presoak of Selenium in nanoparticles. Results of EDAX, confirmed its present. TEM and SEAD represented addition evidence of formation of nanoparticles whereas SEAD indicates the particles were crystalline in nature. FT-IR analysis was carried out to identify the possible bio molecules and Aloe vera extract-metal ions interaction responsible for formation and stabilization of selenium nanoparticles. FRAP, ABTS and DPPH assay results sequester that Selenium nanoparticles prepared using Aloe vera extract possess more activity than extract alone.Conclusion: The bio molecules of Aloe veraextract acted as stabilizing as well as capping agent leading to the formation of Selenium nanoparticles. Selenite has been proven to have antioxidant activity and is being used as chemoprevention agent in cancer diagnosis but same time it is toxic also. Elemental Selenium i.e. Selenium nanoparticles are less toxic form of selenium.Â

SciReader enables reading of medical content with instantaneous definitions

<p>Abstract</p> <p>Background</p> <p>A major problem patients encounter when reading about health related issues is document interpretation, which limits reading comprehension and therefore negatively impacts health care. Currently, searching for medical definitions from an external source is time consuming, distracting, and negatively impacts reading comprehension and memory of the material.</p> <p>Methods</p> <p><it>SciReader </it>was built as a Java application with a Flex-based front-end client. The dictionary used by <it>SciReader </it>was built by consolidating data from several sources and generating new definitions with a standardized syntax. The application was evaluated by measuring the percentage of words defined in different documents. A survey was used to test the perceived effect of SciReader on reading time and comprehension.</p> <p>Results</p> <p>We present <it>SciReader</it>, a web-application that simplifies document interpretation by allowing users to instantaneously view medical, English, and scientific definitions as they read any document. This tool reveals the definitions of any selected word in a small frame at the top of the application. <it>SciReader </it>relies on a dictionary of ~750,000 unique Biomedical and English word definitions. Evaluation of the application shows that it maps ~98% of words in several different types of documents and that most users tested in a survey indicate that the application decreases reading time and increases comprehension.</p> <p>Conclusions</p> <p><it>SciReader </it>is a web application useful for reading medical and scientific documents. The program makes jargon-laden content more accessible to patients, educators, health care professionals, and the general public.</p

Homage to Rushikesh M. Maru

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68443/2/10.1177_097206349900100102.pd

A proposed syntax for Minimotif Semantics, version 1

<p>Abstract</p> <p>Background</p> <p>One of the most important developments in bioinformatics over the past few decades has been the observation that short linear peptide sequences (minimotifs) mediate many classes of cellular functions such as protein-protein interactions, molecular trafficking and post-translational modifications. As both the creators and curators of a database which catalogues minimotifs, Minimotif Miner, the authors have a unique perspective on the commonalities of the many functional roles of minimotifs. There is an obvious usefulness in standardizing functional annotations both in allowing for the facile exchange of data between various bioinformatics resources, as well as the internal clustering of sets of related data elements. With these two purposes in mind, the authors provide a proposed syntax for minimotif semantics primarily useful for functional annotation.</p> <p>Results</p> <p>Herein, we present a structured syntax of minimotifs and their functional annotation. A syntax-based model of minimotif function with established minimotif sequence definitions was implemented using a relational database management system (RDBMS). To assess the usefulness of our standardized semantics, a series of database queries and stored procedures were used to classify SH3 domain binding minimotifs into 10 groups spanning 700 unique binding sequences.</p> <p>Conclusion</p> <p>Our derived minimotif syntax is currently being used to normalize minimotif covalent chemistry and functional definitions within the MnM database. Analysis of SH3 binding minimotif data spanning many different studies within our database reveals unique attributes and frequencies which can be used to classify different types of binding minimotifs. Implementation of the syntax in the relational database enables the application of many different analysis protocols of minimotif data and is an important tool that will help to better understand specificity of minimotif-driven molecular interactions with proteins.</p

Serosurveillance among COVID-19 Cases in Ahmedabad Using SARS-COV2 IgG Antibodies

Background: Serosurveillance study focusing on antibodies against SARS-CoV2 among the Covid19 cases can add value in the scientific knowledge &amp; help in formulating valid predictions regarding immunity status in the post-covid period. Objectives: To estimate seropositivity among covid19 cases and to identify various factors affecting seropositivity. Methods: During second half of October 2020, a population based serosurvey on Covid19 cases was carried out in Ahmedabad. Covid-Kavach test kits were used and estimated seroprevalence was compared with available demographic and covid19 case related parameters to identify factors affecting seropositivity in the post-covid period. Simple proportions and Z-test were used as appropriate. Results: As on October 2020, the sero-positivity among Covid19 cases in Ahmedabad was 54.51% [95% Confidence Interval (CI) 52.14-56.86%]. Females have higher positivity (54.78%) as compared to males (54.30%) but the difference was statistically not significant (Z=0.19, P=0.84). Among children and elderly, the positivity is high and from young adults to elderly the seropositivity has an increasing trend. Severity of clinical illness and longer duration of hospitalization are associated with higher seropositivity. Conclusion: With 54.51% seropositivity among covid19 cases, it is clear that all the covid19 cases may not have developed IgG antibodies, have undetectable level or might have disappeared during the post-covid period. Comparison of seropositivity with age group and clinical case details clearly suggest close correlation with the severity of clinical symptoms. The seronegative cases indicate the need for further in-depth scientific research to identify the factors affecting immunity and to uncover the reasons behind the same

MimoSA: a system for minimotif annotation

<p>Abstract</p> <p>Background</p> <p>Minimotifs are short peptide sequences within one protein, which are recognized by other proteins or molecules. While there are now several minimotif databases, they are incomplete. There are reports of many minimotifs in the primary literature, which have yet to be annotated, while entirely novel minimotifs continue to be published on a weekly basis. Our recently proposed function and sequence syntax for minimotifs enables us to build a general tool that will facilitate structured annotation and management of minimotif data from the biomedical literature.</p> <p>Results</p> <p>We have built the MimoSA application for minimotif annotation. The application supports management of the Minimotif Miner database, literature tracking, and annotation of new minimotifs. MimoSA enables the visualization, organization, selection and editing functions of minimotifs and their attributes in the MnM database. For the literature components, Mimosa provides paper status tracking and scoring of papers for annotation through a freely available machine learning approach, which is based on word correlation. The paper scoring algorithm is also available as a separate program, TextMine. Form-driven annotation of minimotif attributes enables entry of new minimotifs into the MnM database. Several supporting features increase the efficiency of annotation. The layered architecture of MimoSA allows for extensibility by separating the functions of paper scoring, minimotif visualization, and database management. MimoSA is readily adaptable to other annotation efforts that manually curate literature into a MySQL database.</p> <p>Conclusions</p> <p>MimoSA is an extensible application that facilitates minimotif annotation and integrates with the Minimotif Miner database. We have built MimoSA as an application that integrates dynamic abstract scoring with a high performance relational model of minimotif syntax. MimoSA's TextMine, an efficient paper-scoring algorithm, can be used to dynamically rank papers with respect to context.</p

Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale

Large-scale generative models such as GPT and DALL-E have revolutionized natural language processing and computer vision research. These models not only generate high fidelity text or image outputs, but are also generalists which can solve tasks not explicitly taught. In contrast, speech generative models are still primitive in terms of scale and task generalization. In this paper, we present Voicebox, the most versatile text-guided generative model for speech at scale. Voicebox is a non-autoregressive flow-matching model trained to infill speech, given audio context and text, trained on over 50K hours of speech that are neither filtered nor enhanced. Similar to GPT, Voicebox can perform many different tasks through in-context learning, but is more flexible as it can also condition on future context. Voicebox can be used for mono or cross-lingual zero-shot text-to-speech synthesis, noise removal, content editing, style conversion, and diverse sample generation. In particular, Voicebox outperforms the state-of-the-art zero-shot TTS model VALL-E on both intelligibility (5.9% vs 1.9% word error rates) and audio similarity (0.580 vs 0.681) while being up to 20 times faster. See voicebox.metademolab.com for a demo of the model

Neuroinflammation, Mast Cells, and Glia: Dangerous Liaisons

The perspective of neuroinflammation as an epiphenomenon following neuron damage is being replaced by the awareness of glia and their importance in neural functions and disorders. Systemic inflammation generates signals that communicate with the brain and leads to changes in metabolism and behavior, with microglia assuming a pro-inflammatory phenotype. Identification of potential peripheral-to-central cellular links is thus a critical step in designing effective therapeutics. Mast cells may fulfill such a role. These resident immune cells are found close to and within peripheral nerves and in brain parenchyma/meninges, where they exercise a key role in orchestrating the inflammatory process from initiation through chronic activation. Mast cells and glia engage in crosstalk that contributes to accelerate disease progression; such interactions become exaggerated with aging and increased cell sensitivity to stress. Emerging evidence for oligodendrocytes, independent of myelin and support of axonal integrity, points to their having strong immune functions, innate immune receptor expression, and production/response to chemokines and cytokines that modulate immune responses in the central nervous system while engaging in crosstalk with microglia and astrocytes. In this review, we summarize the findings related to our understanding of the biology and cellular signaling mechanisms of neuroinflammation, with emphasis on mast cell-glia interactions

Exenatide Improves Glucose Homeostasis and Prolongs Survival in a Murine Model of Dilated Cardiomyopathy

There is growing awareness of secondary insulin resistance and alterations in myocardial glucose utilization in congestive heart failure. Whether therapies that directly target these changes would be beneficial is unclear. We previously demonstrated that acute blockade of the insulin responsive facilitative glucose transporter GLUT4 precipitates acute decompensated heart failure in mice with advanced dilated cardiomyopathy. Our current objective was to determine whether pharmacologic enhancement of insulin sensitivity and myocardial glucose uptake preserves cardiac function and survival in the setting of primary heart failure.The GLP-1 agonist exenatide was administered twice daily to a murine model of dilated cardiomyopathy (TG9) starting at 56 days of life. TG9 mice develop congestive heart failure and secondary insulin resistance in a highly predictable manner with death by 12 weeks of age. Glucose homeostasis was assessed by measuring glucose tolerance at 8 and 10 weeks and tissue 2-deoxyglucose uptake at 75 days. Exenatide treatment improved glucose tolerance, myocardial GLUT4 expression and 2-deoxyglucose uptake, cardiac contractility, and survival over control vehicle-treated TG9 mice. Phosphorylation of AMP kinase and AKT was also increased in exenatide-treated animals. Total myocardial GLUT1 levels were not different between groups. Exenatide also abrogated the detrimental effect of the GLUT4 antagonist ritonavir on survival in TG9 mice.In heart failure secondary insulin resistance is maladaptive and myocardial glucose uptake is suboptimal. An incretin-based therapy, which addresses these changes, appears beneficial