Volume 12 | Issue 3 |

 Abstract

Stress is a pervasive phenomenon in modern society, and it has been strongly linked to a myriad of comorbid conditions. This comprehensive review aims to explore the intricate relationship between stress and its comorbidities, taking into account various aspects such as psychological, physiological, and behavioral factors. The review delves into the multifaceted impact of stress on mental health, including its role in the development and exacerbation of anxiety disorders, depression, and post-traumatic stress disorder. Furthermore, it uncovers the intricate interplay between stress and physical health, shedding light on how chronic stress can contributed to cardiovascular disease, immune system dysregulation, and metabolic disorders. In addition, the review examines the behavioral repercussions of stress, exploring its influence on substance abuse, addictive behaviors, and disrupted sleep patterns. Special attention is a given to the neurobiological pathways through which stress exerts its effects, including the hypothalamic- pituitary-adrenal axis and the sympathetic nervous system. Furthermore, the review discusses the important early intervention and effective stress management strategies in mitigating the risk of comorbid conditions. It highlights the role of cognitive- behavioral therapy, mindfulness-based interventions, pharmacological approaches in addressing stress and its associated comorbidities. By synthesizing evidence from diverse fields, this review presents a comprehensive understanding of the complex relationship between stress and comorbid conditions. It underscores the imperative for tailored interventions that consider the intertwined nature of stress and its comorbidities, aiming to pave the way for more effective therapeutic approaches and improved health outcomes.

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 Keywords

Mental health, sleep disturbances, substance abuse and addiction, chronic pain, stress and memory.

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Plants provide valuable medicinal chemicals with significant potential in the pharmaceutical sector. The study aims to determine the phytochemical composition of therapeutic plants and evaluate their antioxidant and antibacterial properties. This study was undertaken with an objective of testing the antimicrobial and antioxidative properties of Alstonia Scholaris leaves and identifying the bioactive compound . Alstonia scholaris R. Br, a part of the Apocynaceae family, is a plant utilised in conventional medicine. The research aims to qualitatively examine and compare the initial phytochemical components present in the Alstonia scholaris leaves. The qualitative Phytochemical screening indicates the existence of flavonoids, phenolic compounds, alkaloids, phenols, and tannins in the leaf extracts. Analysed the antibacterial and antioxidant activities of Alstonia scholaris leaf extracts in vitro. The antibacterial efficacy of extract of leaves was assessed using an alcoholic extract to ascertain the minimal inhibitory concentration (MIC) for both positive and negative pathogens: Staphylococcus aureus, Escherichia coli, using disk diffusion method. Methanolic extract from leaf of Alstonia scholaris showed potential antioxidant activity and antimicrobial activity. Plant extracts' antioxidant activity was assessed by FRAP. The plant extracts exhibited strong antioxidant action against FRAP. The Alstonia scholaris extracts exhibited notable antibacterial activity, with minimum inhibitory concentration (MIC) values ranging from 31.25 to 1000 ug/ml, and demonstrated bactericidal activity against all tested species. The analysed extracts of medicinal plants in our research have the potential to serve as antioxidants, antibacterial agents, and as sources for creating novel pharmaceuticals.

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Alstonia scholaris R., Microbial activity, Antioxidant activity, Agar well diffusion method

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Now-a-days, an influence of being Entrepreneur and Innovator trend is being occurred in India. This is an auspicious movement to GDP growth and for being self-reliance. This is the effect of Government support of contemporary announced schemes for motivating the people to start their businesses and showing their talent through the stand-up India scheme. As per the education rate of India, a rapid improving rate is being visualized which is the basic requirement of attaining knowledge for the surrounding happening knowledge for everyone who is engaged in this. A matrix is given by Assistant Professor Abhimanyu Gupta which is known as The SHIV Matrix; by this he postulates that Strength, Honest, Intellectuality, and Versatility are the universal characteristics of every person. According to him, if an individual focus by using these characteristics in a matrix form as per given in the work of 'SHIV' matrix then he can optimized his/her skills to generate "Optimum Confident" which is useful for the decision making process. Hence, the main theme of this lesson is "How an individual has significance of the use of the SHIV matrix for being an Omniscient Learner in the competitive era?"

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Innovator Trend, SHIV Matrix, Omniscient Learner, and Optimum Confident.

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Abstract : The endeavour of Indian women to establish themselves is approaching a significant milestone. The Government of India has acknowledged the imperative of supporting women entrepreneurs and fostering women empowerment, leading to the initiation of several schemes. These initiatives are designed not only to provide financial assistance but also to enhance women's role in the economic development of the nation. Availing these schemes is anticipated to bring about positive changes and substantially impact the businesses managed by women. The government's objective is to elevate both the economic and social standing of women through the implementation of these schemes. This paper aims to assess and evaluate the effectiveness of the policies and schemes introduced by the Government of India in this regard.

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Women entrepreneurs, PMEGP, Schemes for Women entrepreneurs.

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Abstract: Cancer is characterized by uncontrolled cell growth and acquisition of metastatic properties. Some common forms include breast cancer, lung cancer, prostate cancer, colorectal cancer, and leukemia. Despite significant advances in research and treatment modalities, cancer remains a significant public health challenge, with millions of new cases diagnosed each year. For effective cancer therapy, it is necessary to improve and develop novel strategies for effective delivery of chemotherapeutics to cancer cells. Conventional chemotherapeutic agents accumulate both in normal and tumor cells due to non-specificity. The ultimate goal of cancer therapy is to reduce systemic toxicity and improve the quality of life. The landscape of cancer treatment has improved significantly over the past four decades. Novel treatment with ONCOS-102, developed by Targovax, is a genetically modified adenovirus designed to selectively infect cancer cells in lungs and stimulate anti-tumor immune responses has been developed in recent years. New approaches, such as Photodynamic therapy(PDT) is a minimally invasive treatment that utilizes a photosensitizing agent, light, and oxygen to selectively destroy oral cancer cells. One photosensitizer that has shown promise in oral cancer treatment is 5-aminolevulinic acid of oral cancer. Immune checkpoint inhibitors, such as anti-PD-1 or anti-PD-L1 antibodies, block this interaction, thereby reactivating T cell-mediated anti-tumor immune responses in Breast cancer. With the development of molecular biology and genomics, targeted therapy research has achieved a breakthrough development, including anti-angiogenesis, immune checkpoint inhibitors, and other treatments that are efficient for treatment of cervical cancer. a novel approach to the development of AR antagonists is to target the amino-terminus domain of the AR. The small molecule AR antagonist EPI-001 inhibits protein-protein interactions necessary for AR transcriptional activity. A promising novel approach for treating gastric cancer involves targeting the human epidermal growth factor receptor 2 (HER2), which is overexpressed in approximately 20% of gastric cancers.

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- Photodynamic therapy, programmed death-ligand 1, human epidermal growth factor receptor 2, Androgen Receptor Signaling Pathway

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In recent years studies on drug utilization (DU) have become a potential tool to be used in the evaluation of health systems. Studies on the process of DU focus on factors related to prescribing, dispensing, administering and taking of medication and its associated events. DU data is available from databases - computerized or otherwise. From these databases different types of information, qualitative or quantitative or referring to a particular population are available. Patient files and computer registries are widely used as instruments for collecting information on DU. Prospective, Concurrent or Retrospective Drug utilization evaluation (DUE) may be used depending upon the timing of data collection. Importance of DUE in Pharmacoepidemiology (PE) have been increasing due to their close association to other areas like - public health, Pharmacovigilance (Pv), Pharmacoeconomics and pharmacogenetics. This review article highlights various aspects, scope, types and future perspectives of DUE.

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 Keywords

Drug utilization (DU), Pharmacoepidemiology (PE), Pharmacoeconomics, Data collection, Drug utilization evaluation (DUE) cycle.

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Leukemia, a widespread and life-threatening cancer that affects people of all ages, is a global health problem. This disorder predominantly affects White Blood Cells (WBCs), altering bone marrow and blood and causing immature lymphocyte proliferation. The accurate and prompt identification of leukemia is critical for successful treatment and increased survival rates. Currently, the diagnosis is based on manual examination of blood samples from microscopic pictures, a slow, time-consuming technique with inadequate accuracy. Furthermore, the visual resemblance between leukemic and normal cells under a microscope adds to the detection problem. Recent years have witnessed the emergence of Convolutional Neural Network (CNN)-based deep learning algorithms, setting new benchmarks in image classification. However, chances to improve their efficacy, learning processes, and overall performance remain, notably in the field of leukemia diagnosis. In this detailed analysis, we dig into several methodologies previously used in the field of blood cancer detection. In addition, we highlight the field by displaying benchmark datasets often used in leukemia detection studies. We want to clarify the intricacies and complexity within this domain through comparative study, thereby driving advancement in leukemia diagnosis and treatment.

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Leukemia Cancer, Deep Learning, Machine Learning, Convolutional Neural Network, Microscopic images.

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The judicial landscape in India is undergoing a significant transformation with regards to the protection and enforcement of the rights of victims. This article delves into the intricate judicial pursuit aimed at safeguarding the rights of victims within the Indian legal framework. Through an analysis of landmark cases, legislative developments, and judicial pronouncements, this study offers insights into the evolving nature of victim rights protection. Key areas of focus include access to justice, compensation, rehabilitation, and participation in legal proceedings. The article highlights the challenges faced by victims in navigating the legal system and the efforts made by the judiciary to address these challenges. Moreover, it explores the role of judicial activism and public interest litigation in advancing the cause of victim rights. By examining the principles of restorative justice and victim-centric approaches, this article underscores the need for a holistic and rights-based approach towards victim protection. Ultimately, it contributes to the ongoing discourse on enhancing the efficacy of legal mechanisms in promoting the rights and dignity of victims in India's evolving socio-legal landscape.

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Victim rights, judicial pursuit, India, access to justice, compensation, rehabilitation, legal proceedings.

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In this paper, we propose the use of CycleGAN for custom outfit generation. CycleGAN is a type of Generative Adversarial Network (GAN) that can learn to map images from one domain to another domain without requiring paired training data. Our goal is to generate new, realistic images of clothing items based on existing images from a different source domain. We propose a novel approach that combines CycleGAN with a fine-tuning step using a small set of paired data. Our approach is able to generate custom outfits that are both realistic and visually appealing, with high-quality details and textures. We evaluate our approach using a clothing dataset and demonstrate that it outperforms other state-of-the-art methods in terms of image quality and visual similarity.

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CycleGAN, GAN.

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The depression is a medical condition and it is among the major mental diseases that affects numerous people worldwide. For this work, the Distress Analysis Interview Corpus-Wizard of Oz interviews (DAJC-WOZ) dataset will be utilized which contains 189 sessions in zip file format and responses from 59 depressed and BO non-depressed patients[1]. This dataset has video, audio and text clips so individual preprocessing techniques are utilized which is given as a source for depression detection level. The inputs are in the form of video, audio and text, so individual preprocessing methods for feature extraction are used with separate techniques. Then, the extracted features from separate techniques are concatenated and given as input for the classification of depression level. The Long-Short Term Memory (LSTM) can be utilized in this research for classifying the depression levels

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