Mechanism Of Action Of American Ginseng And Its Components In The Treatment Of Ulcerative Colitis

Inflammatory bowel diseases (IBD), mainly ulcerative colitis (UC), Crohn’s disease (CD), are chronic, idiopathic, inflammatory diseases of the gastrointestinal tract affecting millions of people worldwide. The incidence of IBD is steadily increasing in the modern world due to changes in dietary habits and other environmental influences that originated from industrialization. The etiology is poorly understood but is believed to be a combination of genetic predisposition, environmental factors, and overactive immune system. UC is characterized by inflammation and ulceration of colonic mucosa and rectum and has a higher incidence than CD. Aside from severely affecting the quality of life of the patients, IBD also increases the risk of developing colorectal cancer (CRC). Hence, it is imperative to find a treatment that not only treats colitis but can also act as a chemopreventive agent. Current medications that include aminosalicylates, TNFα inhibitors, and corticosteroids help patients cope with the symptoms and induce temporary remission, but are paired with a risk of serious side effects and people become refractory. Many patients, therefore, turn to unconventional treatments for relief and plant-based products provide a safe, alternative option. Many studies have shown that American Ginseng (AG), an herb native to North America is effective in the treatment of diabetes, cancer, cardiovascular diseases, and neurodegenerative diseases. Our lab has previously shown that AG treats colitis and prevents colon cancer in mice. This indicates the potential for AG to become part of mainstream medicine like other drugs that have natural antecedents, e.g., taxol, vincristine, digoxin, etc. Drug discovery from plant products involves phytochemical and biological characterization of plants used in alternative medicine. This dissertation aims to address these issues by identifying the bioactive component of AG and elucidating the mechanism of action in the treatment of UC and prevention of CRC. We used bioassay-guided fractionation to identify the most potent fraction of AG. A hexane fraction of AG (HAG) has shown remarkable anti-inflammatory and anti-cancer properties both in vitro and in vivo. Sub-fractionation of HAG revealed that Panaxynol (PA), a polyacetylene is the most abundant compound in this fraction and also showed antiinflammatory potential in vitro as indicated by suppression of iNOS, an inflammation marker. PA effectively suppressed DSS induced colitis in mice and showed potential as a chemopreventive agent. PA targets macrophages (mФ) for DNA damage and apoptosis while it requires \u3e10X dosage to sustain cause similar effects in other cell types. AG has been shown to decrease oxidative stress and Nuclear factor (erythroidderived 2)-like 2 (NFE2L2 or Nrf2)-a transcription factor that is a master regulator of antioxidant response), we hypothesized that AG, HAG, and PA treat colitis by activating the Nrf2 pathway. AG, HAG, and PA decreased oxidative stress and activated the Nrf2 pathway in vitro and in vivo. Accordingly, in vivo experiments indicate that AG, HAG, and PA were not very effective in the treatment of DSS induced colitis in Nrf2 knockout mice. We further delineated the mechanism of action of AG in the absence of inflammation using gene expression profiling of primary peritoneal mФ by microarray. We found that AG and its compounds showed distinct immunomodulatory properties, as shown by the activation of both pro-inflammatory cytokines and anti-inflammatory molecules. These results will bring AG a step closer to being used as a conventional drug for the treatment of colitis and pave the way for its use in the treatment of other inflammatory and autoimmune diseases with a similar genesis

Magnetization Measurements on Single Crystals of Superconducting Ba0.6K0.4BiO3

Extensive measurements of the magnetization of superconducting single crystal samples of Ba0.6K0.4BiO3} have been made using SQUID and cantilever force magnetometry at temperatures ranging between 1.3 and 350 K and in magnetic fields from near zero to 27 T. Hysteresis curves of magnetization versus field allow a determination of the thermodynamic critical field, the reversibility field, and the upper critical field as a function of temperature. The lower critical field is measured seperately and the Ginzburg-Landau parameter is found to be temperature dependent. All critical fields have higher T = 0 limits than have been previously noted and none of the temperature dependence of the critical fields follow the expected power laws leading to possible alternate interpretation of the thermodynamic nature of the superconducting transition.Comment: 33 pages, 11 figures, accepted for publication in Philosophical Magazine B on 7 August 1999. This paper supplies the experimental details for the argument presented in our PRL 82 (1999) p. 4532-4535 (also at cond-mat/9904288

Social Media Advertisement Outreach: Learning the Role of Aesthetics

Corporations spend millions of dollars on developing creative image-based promotional content to advertise to their user-base on platforms like Twitter. Our paper is an initial study, where we propose a novel method to evaluate and improve outreach of promotional images from corporations on Twitter, based purely on their describable aesthetic attributes. Existing works in aesthetic based image analysis exclusively focus on the attributes of digital photographs, and are not applicable to advertisements due to the influences of inherent content and context based biases on outreach. Our paper identifies broad categories of biases affecting such images, describes a method for normalization to eliminate effects of those biases and score images based on their outreach, and examines the effects of certain handcrafted describable aesthetic features on image outreach. Optimizing on the describable aesthetic features resulting from this research is a simple method for corporations to complement their existing marketing strategy to gain significant improvement in user engagement on social media for promotional images.Comment: Accepted to SIGIR 201

Nonlinear Dynamics, Bifurcation Maps, Signal Encryption and Decryption using Acousto-Optic Chaos under a Variable Aperture Illumination

Bragg cell nonlinear dynamics and bifurcation properties under first-order feedback with variable aperture are examined. Chaotic encryption and recovery of low-bandwidth signals, and optimal performance are evaluated for fixed and variable apertures

A PROSPECTIVE STUDY ON HYPONATREMIA IN CHILDREN WITH THE LOWER RESPIRATORY TRACT INFECTIONS ADMITTED IN PICU

Objective: The present study has been undertaken to study hyponatremia in children with lower respiratory tract infections. The other objectives of the study were to evaluate the clinical and laboratory characteristics of children with hyponatremia and explore the relationship between hyponatremia and outcome about the duration of hospital stay and recovery/death. Methods: The study included children aged 2 months to 5 years who were referred to the PICU, GITAM Institute of Medical Sciences and Research, Visakhapatnam from October 2018 to September 2019 with the lower respiratory tract infections were included in the study. A thorough clinical examination and detailed history have been completed and recorded into a prestructured pro forma. Hematological investigations have been done in all cases. Chest X-ray has been done in all cases to delineate the radiological features of LRTI. A venous blood sample was collected and sent to the biochemistry lab to evaluate serum sodium and was estimated by the ion-selective electrode method analyzed by the radiometer. Results: 872 children were admitted to the pediatric intensive care unit during the study period. Among them, 100 children in the age group of 2 months to 5 years suffering from the lower respiratory tract infection were included in the study. Out of 100 cases of the lower respiratory tract infections, 59 cases were Pneumonia, and 41 cases were severe Pneumonia. Out of 100 cases, 68 cases accounting for 68% have normal sodium levels, 32 cases accounting to 32% had hyponatremia, and none had hypernatremia. Thus, third of the cases suffering from the lower respiratory tract infections had hyponatremia. The mean CRP in children with hyponatremia was 7.38 mg/dl, higher than children with normal sodium levels, that is, 2.30 mg/dl; this was also statistically significant (p<0.001). All 32 cases of hyponatremia and 68 cases of normonatremia recovered and were discharged. There was no mortality. Conclusion: Children with hyponatremia had a longer duration of hospital stay. Serum sodium levels are an important biomarker and should be measured in all children hospitalized for the lower respiratory tract infections

Role of Micro RNA 148/152 Family in Cancer Progression

Micro RNA are small single stranded RNA that regulate the expression of various genes. MiRNA guide the mRNA disintegrating RISC complex to the complimentary sequence in the target mRNA. Each micro RNA has multiple targets and can play a different biological role depending on the population of targets at the particular stage of the cell or a physiological state. Several miRNA show elevated or decreased levels of expression in various cancers because of their role in tumor initiation and progression. MiRNA belonging to mir148/152 family are examples of such MicroRNA. This family includes miR148a, miR148b and miR152. MiR148a and miR152 are down-regulated in various cancers while there is no significant change in the expression of miR148b. Prior studies indicate a role for miR152 and mir148a in suppressing tumor growth in various cancers. However, the mechanism of action and targets remain to be identified. Interestingly, miR148b and miR152 are encoded within the first intron of COPZ1 and COPZ2 genes respectively. This study started with the understanding of the role of miR152 in cancer progression. COPZ2 gene expression is lower in malignant tissues of different tumor types when compared to benign tumors suggesting a similar expression pattern for miR152. We have identified several candidate targets for miR152 in the TGF-β pathway including DNMT1, LTBP1, SERPINE1 and the Rho GEF -LARG. This data led to the hypothesis that miR152 expression correlates with tumor progression and that miR152 suppresses epithelial to mesenchymal transition (EMT) and EMT related events through regulation of specific EMT mediators and effectors. However, all the members belonging to this family have the same seed sequence that binds to the target genes, suggesting that they play similar roles and have common targets. In this thesis, I have verified LTBP1 and PAI1 as novel, common targets for the miR148/152 family. Additionally, reintroduction of these microRNA into prostate cancer cell lines can decrease the migratory capabilities and increase the adhesive characteristics. This biological role of these miRNA can be exploited in the form of replacement miRNA in cancer therapy

A pilot study on the prevalence of DNA palindromes in breast cancer genomes

Background DNA palindromes are a unique pattern of repeat sequences that are present in the human genome. It consists of a sequence of nucleotides in which the second half is the complement of the first half but appearing in reverse order. These palindromic sequences may have a significant role in DNA replication, transcription and gene regulation processes. They occur frequently in human cancers by clustering at specific locations of the genome that undergo gene amplification and tumorigenesis. Moreover, some studies showed that palindromes are clustered in amplified regions of breast cancer genomes especially in chromosomes (chr) 8 and 11. With the large number of personal genomes and cancer genomes becoming available, it is now possible to study their association to diseases using computational methods. Here, we conducted a pilot study on chromosomes 8 and 11 of cancer genomes to identify computationally the differentially occurring palindromes. Methods We processed 69 breast cancer genomes from The Cancer Genome Atlas including serum-normal and tumor genomes, and 1000 Genomes to serve as control group. The Biological Language Modelling Toolkit (BLMT) computes palindromes in whole genomes. We developed a computational pipeline integrating BLMT to compute and compare prevalence of palindromes in personal genomes. Results We carried out a pilot study on chr 8 and chr 11 taking into account single nucleotide polymorphisms, insertions and deletions. Of all the palindromes that showed any variation in cancer genomes, 38% of what were near breast cancer genes happened to be the most differentiated palindromes in tumor (i.e. they ranked among the top 25% by our heuristic measure). Conclusions These results will shed light on the prevalence of palindromes in oncogenes and the mutations that are present in the palindromic regions that could contribute to genomic rearrangements, and breast cancer progression

On Monetizing Personal Wearable Devices Data: A Blockchain-based Marketplace for Data Crowdsourcing and Federated Machine Learning in Healthcare

Machine learning advancements in healthcare have made data collected through smartphones and wearable devices a vital source of public health and medical insights. While wearable device data helps to monitor, detect, and predict diseases and health conditions, some data owners hesitate to share such sensitive data with companies or researchers due to privacy concerns. Moreover, wearable devices have been recently available as commercial products; thus large, diverse, and representative datasets are not available to most researchers. In this article, we propose an open marketplace where wearable device users securely monetize their wearable device records by sharing data with consumers (e.g., researchers) to make wearable device data more available to healthcare researchers. To secure the data transactions in a privacy-preserving manner, we use a decentralized approach using Blockchain and Non-Fungible Tokens (NFTs). To ensure data originality and integrity with secure validation, our marketplace uses Trusted Execution Environments (TEE) in wearable devices to verify the correctness of health data. The marketplace also allows researchers to train models using Federated Learning with a TEE-backed secure aggregation of data users may not be willing to share. To ensure user participation, we model incentive mechanisms for the Federated Learning-based and anonymized data-sharing approaches using NFTs. We also propose using payment channels and batching to reduce smart contact gas fees and optimize user profits. If widely adopted, we believe that TEE and Blockchain-based incentives will promote the ethical use of machine learning with validated wearable device data in healthcare and improve user participation due to incentives.

A Novel Neural Network Classifier for Brain Computer Interface

Brain computer interfaces (BCI) provides a non-muscular channel for controlling a device through electroencephalographic signals to perform different tasks. The BCI system records the Electro-encephalography (EEG) and detects specific patterns that initiate control commands of the device. The efficiency of the BCI depends upon the methods used to process the brain signals and classify various patterns of brain signal accurately to perform different tasks. Due to the presence of artifacts in the raw EEG signal, it is required to preprocess the signals for efficient feature extraction. In this paper it is proposed to implement a BCI system which extracts the EEG features using Discrete Cosine transforms. Also, two stages of filtering with the first stage being a butterworth filter and the second stage consisting of an moving average 15 point spencer filter has been used to remove random noise and at the same time maintaining a sharp step response. The classification of the signals is done using the proposed Semi Partial Recurrent Neural Network. The proposed method has very good classification accuracy compared to conventional neural network classifiers. Keywords: Brain Computer Interface (BCI), Electro Encephalography (EEG), Discrete Cosine transforms(DCT), Butterworth filters, Spencer filters, Semi Partial Recurrent Neural network, laguarre polynomia

Optimization using evolutionary metaheuristic techniques: a brief review

Optimization is necessary for finding appropriate solutions to a range of real life problems. Evolutionary-approach-based meta-heuristics have gained prominence in recent years for solving Multi Objective Optimization Problems (MOOP). Multi Objective Evolutionary Approaches (MOEA) has substantial success across a variety of real-world engineering applications. The present paper attempts to provide a general overview of a few selected algorithms, including genetic algorithms, ant colony optimization, particle swarm optimization, and simulated annealing techniques. Additionally, the review is extended to present differential evolution and teaching-learning-based optimization. Few applications of the said algorithms are also presented. This review intends to serve as a reference for further work in this domain