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DECIPHERING THE GENETIC LINKS BETWEEN PSYCHOLOGICAL STRESS, AUTOPHAGY, AND DERMATOLOGICAL HEALTH: INSIGHTS FROM BIOINFORMATICS, SINGLE-CELL ANALYSIS, AND MACHINE LEARNING IN PSORIASIS AND ANXIETY DISORDERS
Get PDFThe relationship between psychological stress, altered skin immunity, and autophagy-related genes (ATGs) is currently unclear. Psoriasis is a chronic skin inflammation of unclear etiology that is characterized by persistence and recurrence. Immune dysregulation and emotional disturbances are recognized as significant risk factors. Emerging clinical evidence suggests a possible connection between anxiety disorders, heightened immune system activation, and altered skin immunity, offering a fresh perspective on the initiation of psoriasis. The aim of this study was to explore the potential shared biological mechanisms underlying the comorbidity of psoriasis and anxiety disorders. Psoriasis and anxiety disorders data were obtained from the GEO database. A list of 3254 ATGs was obtained from the public database. Differentially expressed genes (DEGs) were obtained by taking the intersection of DEGs between psoriasis and anxiety disorder samples and the list of ATGs. Five machine learning algorithms used screening hub genes. The ROC curve was performed to evaluate diagnostic performance. Then, GSEA, immune infiltration analysis, and network analysis were carried out. The Seurat and Monocle algorithms were used to depict T-cell evolution. Cellchat was used to infer the signaling pathway between keratinocytes and immune cells. Four key hub genes were identified as diagnostic genes related to psoriasis autophagy. Enrichment analysis showed that these genes are indeed related to T cells, autophagy, and immune regulation, and have good diagnostic efficacy validated. Using single-cell RNA sequencing analysis, we expanded our understanding of key cellular participants, including inflammatory keratinocytes and their interactions with immune cells. We found that the CASP7 gene is involved in the T-cell development process, and correlated with γδ T cells, warranting further investigation. We found that anxiety disorders are related to increased autophagy regulation, immune dysregulation, and inflammatory response, and are reflected in the onset and exacerbation of skin inflammation. The hub gene is involved in the process of immune signaling and immune regulation. The CASP7 gene, which is related with the development and differentiation of T cells, deserves further study. Potential biomarkers between psoriasis and anxiety disorders were identified, which are expected to aid in the prediction of disease diagnosis and the development of personalized treatments
APPLYING HYPERGRAPHS TO STUDIES IN QUANTITATIVE BIOLOGY: Received: 05th June 2024 Revised: 10th June 2024, 11th June 2024 Accepted: 10th June 2024
No full textThe objective of this research is to demonstrate hypergraph versatility and applicability for modeling diverse biological systems. The inherent structure of hypergraphs allows for encoding of higher-order feature interactions, providing a flexible framework for efficient models that can enhance our understanding of physical phenomena and one that can be generalized across various datasets. By adopting innovative methods including centrality measure and populations of models rather than singular instances, biases and overfitting tendencies are mitigated, again presenting promise for application across a broad spectrum of biological systems. Furthermore, emphasis is placed on the significance of probabilistic distribution analysis in elucidating threshold selection and feature relevance while maintaining high levels of accuracy. Our results demonstrate the advantages of hypergraph models on two different datasets; with the first on gene expression and the identification of outlier genes and the second on classifying starch grains. There is significant scope in the application of the hypergraph to a wider class of biological systems, with the potential to improve understanding of the biological processes
ASSESSMENT OF BACTERIA STREPTOMYCES TERMITUM WICCB66 AND STREPTOMYCES INDIAENSIS WICCB67 FOR LOW DENSITY POLYETHYLENE DEGRADATION
Get PDFGiven its extended earthly persistence and detrimental effects on ecosystems, plastic waste disposal is one of the most concerning problems in the waste management industry. Plastics, which are strong, durable, and lightweight, have a big impact on society all over the world. Most of the waste is dumped, and only 7% of it is recycled. Plastic poses a serious threat to the ecosystem, thus getting rid of it is crucial. Biodegradation is one of the most efficient methods for plastic decomposition when compared to other degradation processes. This is because of the eco-friendly, cost-effective, and non-polluting method. Bacteria are crucial for biodegradation because they act on plastic by secreting a degrading enzyme, which then converts the polymer's high molecular weight into a monomer. The bacteria strain that breaks down plastic was introduced into low density polyethylene (LDPE). Thus, this study is aimed to evaluate and compared the polyethylene plastic degrading bacteria. The LDPE plastic are compared in terms of biomass and weight after incubated with bacteria for 30 days. The bacteria used are Streptomyces termitum WICC-B66 and Streptomyces indiaensis WICC-B67. From the results, both bacteria strain simultaneously grow and then started to decline with time. Moreover, the results shown both bacteria able to degrade LDPE plastic but Streptomyces indiaensis WICC-B67 poses the higher degradability rate with 0.83%. In conclusion, Streptomyces termitum WICC-B66 and Streptomyces indiaensis WICC-B67 were able to degrade LDPE plastic with Streptomyces indiaensis WICC-B67 gave higher degradability rate
FACTORS AFFECTING THE DECISION MAKING TO CHOOSE DANCE SCHOOL IN BANGKOK METROPOLITAN AREA
Get PDFThis study investigates factors influencing the decision-making process of individuals choosing dance schools in the Bangkok Metropolitan Area. Using a mixed-methods approach, the research combines quantitative surveys and qualitative interviews to identify key determinants such as location, reputation, cost, curriculum, and instructor qualifications. Findings reveal that while cost and location are significant, the reputation of the school and instructor qualifications play crucial roles. The study aims to provide insights for dance school administrators to better understand their target market and improve their offerings. Objectives include studying the demographic characteristics of those who choose dance schools in Bangkok, examining consumer behavior toward the dance school industry, and analyzing the importance of the marketing mix (product, price, distribution channel, promotion, process, image, and presentation) for prospective students. Methods involve a quantitative approach with descriptive research and surveys. Cluster 1 is diverse in gender, with many young adults and middle-aged respondents, including students, private company officers, and lower to mid-income earners. Consumer behavior in this cluster shows a balanced interest in various dance courses, lower study expenses, a preference for evening study times, and a high preference for weekend study times. Cluster 2 is predominantly female, younger, and more diverse in occupation and income levels, with higher education levels and higher income earners. This cluster focuses on finding special skills and talents, with a strong preference for specific dance courses (especially K-pop Dance), more diverse and higher study expenses, balanced study times throughout the day, and varied main study times, including weekends and combined times. In conclusion, the importance of the marketing mix (7Ps) segments consumers into two clusters in this study
IMPACT MODEL OF SOME FACTORS ON ORGANIZATIONAL PERFORMANCE
Get PDFThis research explores the effects of human resource management practices, organizational culture, organizational innovation, and intellectual capital on organizational performance, with a focus on enterprises in Vietnam. Utilizing foundational theories such as the Resource-Based View and Dynamic Capability Theory, the study integrates these elements to provide a comprehensive understanding of their combined impact. The methodology employs Structural Equation Modeling to analyze data collected from representative firms, ensuring robust insights. Findings demonstrate that human resource management practices significantly influence employee satisfaction and productivity, while an innovation-oriented organizational culture enhances adaptability and creativity. Furthermore, investment in intellectual capital drives competitive advantage, and organizational innovation directly contributes to improved performance outcomes. These results offer critical implications for both academic research and practical applications, providing strategies for business leaders to enhance operational effectiveness and sustain competitive performance in dynamic markets
DETERMINANTS OF THE ORGANIZATIONAL PERFORMANCE OF BUSINESSES IN NINH THUAN PROVINCE
Get PDFThis research explores the critical factors influencing organizational performance in businesses based in Ninh Thuan Province, Vietnam. Leveraging key theoretical frameworks, including Resource-Based View and Dynamic Capability Theory, the study evaluates the impacts of human resource management practices, organizational culture, organizational innovation, intellectual capital, and organizational citizenship behavior (OCB). Using Structural Equation Modeling, data from 412 senior and middle-level managers were analyzed to validate the proposed hypotheses. The findings highlight that organizational culture exerts the most significant influence on performance, followed closely by OCB, intellectual capital, HRM practices, and organizational innovation. These results underscore the interplay between these factors, emphasizing the need for a robust organizational culture, strategic HRM, and proactive engagement in intellectual capital development. The study provides a comprehensive foundation for managerial strategies aimed at improving organizational efficiency, fostering innovation, and ensuring sustainable growth in competitive markets
BIOCHEMICAL AND TRANSCRIPTOMIC ANALYSIS OF DISEASE RESISTANCE AND EARLY-MATURITY RELATED GENES IN NMR-191 AND NMR-192 RICE MUTANT LINES
Get PDFMalaysia's rice industry has revealed that the rice production was unable to supply the food demand where nearly 30% was imported from other countries. This is due to the fact that rice cultivation in Malaysia faces concerns about rice blast disease, Magnaporthe oryzae attack, and having a long maturation period. As such, generation of new rice mutant lines that possess improved disease resistance and early maturity characteristics through mutation breeding techniques are of great importance. This study aimed to analyze the biochemical characteristics as well as to validate the presence of disease resistance and early maturity-related genes in rice mutant lines. After the rice seeds of the parent line Pongsu Seribu 2 (PS2) and mutant lines (NMR191 and NMR192) were grown for 14 days, the plant samples underwent biochemical tests including total soluble protein content, specific activity of peroxidase, chlorophyll content and proline content. The RNA extraction and sequencing were also conducted for the purpose of transcriptomic profiling analysis to determine the presence of disease resistance and early maturity genes in the samples. The biochemical analyses showed a significant increase in the total soluble protein content, chlorophyll content, and proline content in the mutant line NMR191 and NMR192 compared to the parent line, while the specific activity of peroxidase in the mutant lines was significantly lower compared to the parent line. The transcriptomic profiling analysis revealed that Os07g0129300, Os12g0270300, and Os03g0235000 were the disease-resistance genes whereas Os03g0195300, Os01g0704100, Os11g0143200, Os06g0569900, and Os06g0568600 were the early maturity genes found in NMR191 and NMR192. This study validates that NMR191 and NMR192 could be better varieties than the parent line due to the presence of their early maturity and disease resistance traits
MINI-REVIEW OF NUCLEAR-FACTOR-KAPPA-B IN SILICO STUDIES: Received: 23rd August 2024 Revised: 1st September 2024, 8th September 2024 Accepted: 26th August 2024
No full textThis mini-review provides a concise overview of the advancements in computer-assisted methodologies and research related to nuclear factor kappa B (NF-kB) over the past decade. Applying computer-aided or in silico methods to investigating the NF-kB complex offers intriguing options for identifying treatment targets for various disorders involving the NF-kB protein. Compared to traditional in vivo and in vitro investigations, in silico research has multiple advantages, including improved precision, increased efficiency, and eliminating the requirement for human and animal participants. This method creates a framework for evaluating the efficacy of potential treatments against specific molecular targets, allowing for the prediction of their efficacy based on the structural properties of compounds before synthesis for subsequent in vitro and in vivo testing. Targeting the NF-kB protein is critical because it plays a role in many disorders involving immunological and inflammatory responses, stress responses, cellular proliferation, and apoptosis. These findings are essential for guiding future research into the role of the NF-kB protein in human disorders and identifying possible therapeutic targets.
This mini-review provides a concise overview of the advancements in computer-assisted methodologies and research related to nuclear factor kappa B (NF-kB) over the past decade. Applying computer-aided or in silico methods to investigating the NF-kB complex offers intriguing options for identifying treatment targets for various disorders involving the NF-kB protein. Compared to traditional in vivo and in vitro investigations, in silico research has multiple advantages, including improved precision, increased efficiency, and eliminating the requirement for human and animal participants. This method creates a framework for evaluating the efficacy of potential treatments against specific molecular targets, allowing for the prediction of their efficacy based on the structural properties of compounds before synthesis for subsequent in vitro and in vivo testing. Targeting the NF-kB protein is critical because it plays a role in many disorders involving immunological and inflammatory responses, stress responses, cellular proliferation, and apoptosis. These findings are essential for guiding future research into the role of the NF-kB protein in human disorders and identifying possible therapeutic targets
ANALYZING PUBLIC HEALTH CONCERNS THROUGH TEXT MINING AND SOCIAL NETWORK ANALYSIS: A CASE STUDY OF COVID-19 PUBLIC OPINION ANALYSIS FROM ONLINE COMMUNITY FORUMS IN TAIWAN
Get PDFIn the past, many quantitative studies in public health relied on traditional descriptive statistical data and less on analyzing unstructured text data. However, in the era of close online communication, a huge amount of text information related to public health issues is generated in online communities every day. COVID-19 pandemic should be one of the most important public health events in Taiwan since 2020. Many people express their views and feelings on the epidemic issue in online forums. In this research, the aim is to apply text mining and social network analysis to analyze the sentiment and topics related to COVID-19 in PTT, the most popular online community forum of social media in Taiwan. We used topic modeling to extract COVID-19 related topics and keywords, as well as sentiment analysis to explore the attitudes and emotional tendencies of the online community towards various issues, and data visualization methods such as word clouds and network graphs to present the research results. Additionally, we plan to conduct cluster analysis on the authors and accounts of the articles to determine if there is a phenomenon of specific groups influencing the COVID-19 public opinion. The expected outcome of this research is to provide a reference for the implementation of public health policies and to promote the value of sentiment analysis in public health management.
After conducting text mining analysis on the articles published in the COVID-19 forum of PTT in 2021, especially the period of Taiwan's COVID-19 escalation from June to August 2021. The overall discussion volume and sentiment can be roughly divided into three peaks. The first peak started to rise in mid-May and reached its peak in mid-June. The second peak occurred in mid-July, and the negative sentiment was significantly higher than the positive sentiment. The last peak occurred in late August and had the highest discussion volume among the three peaks. In each peak of sentiment, negative sentiment was mostly higher than positive sentiment. Our suggestion is to focus on the following research results that Public health managers can use daily text mining results by our way to assist in judging public reactions under current epidemic policies, and the positive and negative sentiment levels in sentiment analysis can reflect whether policies may lead to a crisis outbreak. Observing the subsequent changes in sentiment can avoid affecting the implementation effectiveness of the next policy or causing a more serious public opinion crisis. This research hopes to promote the value of sentiment analysis in public health management by visualizing the complex online forum opinions into easy-to-understand charts, which can serve as a reference for decision-makers in judging online public opinion
THE IMPACT OF INFORMATION TRANSPARENCY ON FIRM PERFORMANCE: EVIDENCE FROM CHINA
Get PDFNowadays, with the concern of the public for corporate social responsibility, firms are increasingly concerned with social responsibility, and they need to know whether social responsibility is favourable for their profit. The study focuses on 3,536 Chinese firms and collects the data of them from 2006 to 2021. The study analyses the data with the method of regression to find the relationship between information transparency and ROA, as well as the moderating effects of voluntary disclosure and company loss. We also run regressions with a lagged score of information transparency instead of the current score as a robust check. After analysis, we find that a high level of information transparency is significantly beneficial for a great firm performance. Additionally, this relationship exhibits an increasing marginal effect in the firms in which information disclosure is voluntary and the firms that are facing losses. The findings of this study provide useful guidance for firm managers about whether to develop high information transparenc