Volume 14 | Issue 7 |

 Abstract

ABSTRACT Background Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancer cases and remains one of the leading causes of cancer-related mortality worldwide. Recent advances in immune checkpoint inhibitor therapy targeting PD-1/PD-L1 pathways have improved survival outcomes; however, only a subset of patients demonstrates durable clinical responses. Emerging evidence indicates that lung microbiome dysbiosis plays an important role in tumor progression, immune regulation, inflammatory pathways, and response to immunotherapy. Aim To assess the role of lung microbiome dysbiosis in NSCLC progression and its association with immunotherapy response among patients receiving immune checkpoint inhibitor therapy. Methods A prospective observational study was conducted among 100 diagnosed NSCLC patients receiving immunotherapy. Bronchoalveolar lavage (BAL) samples were collected for microbial profiling using 16S rRNA sequencing. Clinical characteristics, tumor stage, PD-L1 expression, inflammatory biomarkers, and immunotherapy response were assessed. Treatment response was evaluated according to RECIST 1.1 criteria. Data were analyzed using SPSS version 26.0. Results Among 100 NSCLC patients, lung microbiome dysbiosis was identified in 62% of cases. Advanced tumor stage (III-IV) was significantly associated with reduced microbial diversity (p<0.01). Patients with balanced lung microbiota showed a higher immunotherapy response rate (63.2%) compared with dysbiosis patients (32.3%). Increased abundance of Proteobacteria and reduced Firmicutes were associated with poor progression-free survival and resistance to immune checkpoint inhibitors. Conclusion Lung microbiome dysbiosis significantly influences NSCLC progression and immunotherapy response. Microbial profiling may serve as a potential biomarker for predicting treatment outcomes and developing microbiome-targeted therapeutic approaches.

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Keywords: Non-small cell lung cancer, Lung microbiome, Dysbiosis, Immunotherapy, Immune checkpoint inhibitors, PD-1, PD-L1

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Colon-targeted drug delivery has effective approach to address the clinical need for localized treatment of colonic diseases while reducing systemic side effects and improving therapeutic outcomes. Advances in understanding colonic anatomy, physiology, gastrointestinal transit, and the role of microbiota have enabled the development of site-specific delivery strategies such as pH-dependent, time-controlled, enzyme-responsive, and microbiota-activated systems. The use of advanced carrier systems, including polymers, micro- and nanoparticles, lipid-based carriers, and hybrid platforms, has further enhanced drug stability, controlled release, and targeting precision. These technologies have shown significant therapeutic benefits in the management of inflammatory bowel disease, Crohn's disease, colorectal cancer, and microbiome-related and systemic applications. Despite promising preclinical and clinical outcomes, challenges such as formulation stability, physiological variability, regulatory complexity, and scalable manufacturing remain. Emerging trends focusing on smart multi-responsive systems, integration with microbiome-based therapies, and personalized medicine are expected to overcome existing limitations and drive the future clinical translation of colon-specific drug delivery systems.

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Colon-Targeted Drug Delivery, pH-Dependent, Microbiota-Activated, Crohn's Disease, Colorectal Cancer, Inflammatory Bowel Disease (IBD).

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This research paper evaluates and compares the portfolio performance of selected large-cap and mid-cap mutual fund schemes in India. The study uses secondary data for the period 2021-2025 and compares five large-cap schemes with five mid-cap schemes. Performance is examined through return measures, risk measures and risk-adjusted measures such as portfolio return, compound annual growth rate, average return, standard deviation, coefficient of variation, beta, Sharpe ratio, Treynor ratio, Jensen alpha, Sortino ratio, correlation, regression, CAPM and the Fama-French three factor model. The results indicate that mid-cap schemes generally generated higher returns than large-cap schemes, but they were also exposed to higher volatility. Invesco India Mid Cap Fund, Quant Mid Cap Fund and Motilal Oswal Midcap Fund showed strong performance on several risk-adjusted indicators. Among large-cap schemes, Nippon India Large Cap Fund and HDFC Large Cap Fund performed better than the other selected large-cap funds. The study concludes that investors should not select funds only on the basis of return, but should also consider risk, market sensitivity and downside protection before making investment decisions.

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Mutual Funds, Large-Cap Funds, Mid-Cap Funds, Portfolio Performance, Risk-Return Analysis, Sharpe Ratio, Jensen Alpha, CAPM, Fama-French Model.

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Keywords: Biomedical waste management, digital learning, compliance audit, housekeeping personnel, infection prevention, healthcare waste, hospital training, quasi-experimental study.

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ABSTRACT Background Lung cancer development is a complex process influenced by genetic, environmental, inflammatory, and immunological factors. Chronic allergic airway inflammation, characterized by increased Th2 immune responses, eosinophilic activity, and altered cytokine expression, may influence the lung microenvironment and contribute to cancer initiation. Recent evidence suggests that lung microbiome dysbiosis can modify immune surveillance, inflammatory pathways, and tumor-promoting mechanisms. Understanding the relationship between allergic airway inflammation, lung microbiota alterations, and immune crosstalk may help identify early biomarkers for lung cancer prevention and targeted therapy. Objective To assess the impact of allergic airway inflammation on lung cancer initiation and evaluate the association between lung microbiome alterations and immune response among selected participants. Methods A quantitative observational comparative study was conducted among 100 participants divided into two groups: 50 participants with allergic airway inflammation (asthma/allergic airway disease) and 50 healthy controls. Participants were selected using purposive sampling. Clinical history, inflammatory biomarkers, microbiome profiles, and immune response parameters were assessed. Airway inflammation was evaluated using serum IgE levels, eosinophil count, and inflammatory cytokines (IL-4, IL-5, IL-13). Lung microbiome composition was analyzed using 16S rRNA sequencing of respiratory samples. Immune activity was assessed through inflammatory markers and immune regulatory pathways. Data were analyzed using SPSS version 26.0. Descriptive statistics, chi-square test, independent t-test, and correlation analysis were applied. Results Among participants with allergic airway inflammation, significant changes in airway microbiome composition were observed compared with controls. Reduced microbial diversity and increased abundance of inflammatory-associated bacterial species were identified. Higher levels of Th2-associated cytokines were found among allergic participants. Participants with chronic allergic inflammation showed: o Increased eosinophilic airway activity o Higher IgE concentration o Altered microbiome diversity o Enhanced inflammatory signaling pathways Microbiome imbalance showed a significant positive association with inflammatory markers (p<0.05), suggesting that allergic inflammation may contribute to a tumor-supportive lung microenvironment. Conclusion The findings indicate that allergic airway inflammation may influence lung cancer initiation through alteration of microbiome-immune interactions. Persistent inflammatory responses and microbial dysbiosis may contribute to impaired immune surveillance and early carcinogenic changes. Targeting microbiome regulation and inflammatory pathways may provide future opportunities for lung cancer prevention and immunotherapy strategies.

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Keywords: Allergic airway inflammation, lung cancer initiation, microbiome dysbiosis, immune crosstalk, Th2 immunity, cytokines

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In Karnataka, organic farming is ecologically and economically feasible. Shivamogga district is a significant organic agricultural zone due to its favourable agro-climatic conditions, diverse planting pattern, and growing farmer awareness. Demographics, education, landholding, income, employment, marketing, certification, government assistance, and restraints of organic farmers in Shivamogga district are examined in this research. Organic farming has increased farmers' income, soil fertility, chemical input resistance, and sustainable lives, according to the research. However, certification fees, marketing inefficiencies, price volatility, workforce shortages, and insufficient institutional backing continue to hinder organic agricultural growth. The report suggests boosting market links, certification, financial aid, and extension services to promote sustainable organic agriculture. Studies in Shivamogga and Karnataka found that bigger, better-educated farmers embrace organic farming more easily, despite institutional obstacles.

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Keywords: Organic farming, Socio-economic conditions, Sustainable agriculture, Organic certification, Shivamogga District, Karnataka.

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The organizational culture is essential in influencing the attitude of employees, behavior, and performance in healthcare institutions. When it comes to the agency of private hospitals, where the quality of service and the commitment of employees is directly related to patient outcomes, it becomes necessary to comprehend the causes of job satisfaction. This paper focuses on the issue of organizational culture as a predictor of job satisfaction among healthcare professionals working in the Kerala based private hospitals. The quantitative research design was used, and the primary data were gathered using structured questionnaires on 300 healthcare employees (doctors, nurses, and administrative workers). The dimensions used to evaluate organizational culture included leadership support, communication climate, teamwork orientation and organizational values, whereas job satisfaction was evaluated using standardized levels of satisfaction. The data were analyzed using statistical tools such as descriptive analysis, correlation and multiple regression. The results demonstrate that there is significant positive correlation between job satisfaction and organizational culture and the predictors have been shown as leadership support and teamwork. The researchers find that organization culture that is supportive and collaborative leads to employee satisfaction, lower turnover intention, and better quality of service delivery in privately owned hospitals. The findings have significant implications to hospital managers wishing to enhance organizational performance by using culture-based approaches.

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Organizational Culture; Job Satisfaction; Private Hospitals; Healthcare Employees; Leadership Support; Teamwork; Communication Climate; Kerala; Employee Engagement; Hospital Management

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The rapid growth of digital platforms has led to a very large amount of customer interaction data being generated every second. This situation creates strong opportunities for organizations to engage with customers in real time. However, many existing analytics systems face problems related to scalability, high processing delay, and difficulty in using advanced artificial intelligence models on streaming data. To address these challenges, this paper proposes a simple and practical analytical framework for real-time customer engagement by combining big data technologies with AI-based analytics. The proposed framework is organized into four clear layers: data ingestion, data processing, analytics, and decision support. In the data ingestion layer, streaming data from digital platforms such as social media are collected using distributed messaging systems. The data processing layer handles large volumes of data through scalable big data frameworks that support real-time computation. The analytics layer applies machine learning and deep learning models to perform sentiment analysis, predict customer engagement levels, and identify behavioral patterns. The decision support layer converts analytical outputs into timely insights that can help organizations take quick and informed actions. The framework is evaluated using real-world social media datasets. Performance is measured using engagement prediction accuracy, sentiment classification results, system latency, and response time. The experimental findings show that the proposed approach provides better scalability and faster insights compared to traditional batch-based analytics methods. Overall, this study demonstrates the usefulness of integrating big data and AI for building efficient real-time customer engagement systems and offers a foundation for future research

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Big Data Analytics, Real-Time Data Processing, Customer Engagement, Artificial Intelligence, Machine Learning, Streaming Data Analytics, Decision Support Systems

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In this study, the researcher have focused on the impact of financial ratio on the profitability of an Indian bank with special reference to State Bank of India. The researcher has strictly focused on this bank because, it is the largest and oldest commercial bank in the history of India with a glorious past of over 100+ years. Not only this, currently SBI acts as the bank with largest number of customers in the world. As per latest reports by Reserve Bank of India, sand many other financial institutions, the customer base of SBI exceeds 52 crores, comprising of both domestic and international customers. SBI solely accounted for 1.1% of 6.7% share in India's global economy incremental growth in FY25. The research aims to analyze how key ratios like liquidity ratio (cash ratio, credit deposit ratio), solvency ratio, and capital adequacy ratio- affect the overall profitability of the bank. Various analysis tools such as regression, and correlation are used to prove the study. The study is solely based on secondary data collected from annual reports of SBI, RBI, and other financial institutions. The research adopts a descriptive, and analytical research design to intercept the financial health of bank. The study focuses on quantitative aspect rather than qualitative aspect. The study will be useful for investors, bank management, consulting aspirants, financial analyst, and policy makers. Overall, the research contributes to the existing knowledge by providing insights into financial ratio analysis in assessing and enhancing the profitability of a major public sector bank.

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Financial ratios, profitability, analysis, State Bank of India

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?-carboline; chloroquine; hybrid; synthesis; malaria; fluorimetric probes.

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