Comprehensive Analysis Research Articles

WingSegment: A Computer Vision‐Based Hybrid Approach for Insect Wing Image Segmentation and 3D Printing

This article introduces WingSegment, a MATLAB app‐designed tool employing a hybrid approach of computer vision and graph theory for precise insect wing image segmentation. WingSegment detects cells, junctions, Pterostigma, and venation patterns, measuring geometric features and generating Voronoi patterns. The tool utilizes region‐growing, thinning, and Dijkstra's algorithms for boundary detection, junction identification, and vein path extraction. It provides histograms and box plots of geometric features, facilitating comprehensive wing analysis. WingSegment's efficiency is validated through comparisons with established tools and manual measurements, demonstrating accurate results. The tool further enables exporting detected boundaries as FreeCAD macro files for 3D modeling and printing, supporting finite element analysis. Beyond advancing insect wing morphology understanding, WingSegment holds broader implications for diverse planar structures, including leaves and geocells. This tool not only enhances automated geometric analysis and 3D model generation in insect wing studies but also contributes to the broader advancement of analysis, 3D printing, and modeling technologies across various planar structures.

ENHANCING MEDICATION QUALITY CONTROL IN NIGERIA: A COMPREHENSIVE ANALYSIS OF REGULATORY CHALLENGES AND SOLUTIONS

Medication quality control in Nigeria faces multifaceted challenges rooted in regulatory inefficiencies, infrastructural limitations, and systemic inadequacies. This study undertakes a comprehensive analysis of these challenges while proposing pragmatic solutions to bolster the quality control framework in the Nigerian pharmaceutical sector. Drawing upon extensive literature review and expert insights, the research identifies key regulatory challenges impeding effective medication quality control in Nigeria. These challenges encompass inadequate regulatory capacity, inconsistent enforcement mechanisms, rampant substandard and counterfeit medications, and limited access to essential medicines. Additionally, infrastructural deficiencies such as inadequate laboratory facilities and insufficient human resources further exacerbate the problem, leading to compromised patient safety and public health risks. In response to these challenges, the study proposes a multifaceted approach to enhance medication quality control in Nigeria. This includes strengthening regulatory frameworks through legislative reforms aimed at bolstering enforcement capabilities and harmonizing standards with international best practices. Moreover, improving regulatory capacity through training programs and investment in state-of-the-art laboratory infrastructure is essential to enhance surveillance and detection of substandard medications. Furthermore, fostering collaboration between regulatory agencies, healthcare providers, and pharmaceutical manufacturers is imperative to streamline supply chains and ensure the integrity of medications from production to distribution. Additionally, public awareness campaigns and community engagement initiatives play a pivotal role in empowering consumers to make informed decisions and report instances of substandard medications. By addressing these regulatory challenges and implementing comprehensive solutions, Nigeria can significantly enhance medication quality control, safeguard patient health, and foster a conducive environment for pharmaceutical innovation and growth.
 Keywords: Medical, Medication, Drugs, Quality Control, Nigeria, Regulations, Review.

The Mediating Role of Emotional Arousal and Donation Anxiety on Blood Donation Intentions: Expanding on the Theory of Planned Behavior.

Blood donation is essential in health-care systems worldwide, dealing with the demand for transfusions, and for the treatment of a variety of medical conditions. A major obstacle is raising the rate of blood donations by recruiting and retaining donors in an efficient manner. This paper presents a comprehensive analysis of blood donation, utilizing an enhanced framework based on the theory of planned behavior with an emphasis on emotional arousal (positive and negative), attitudes towards advertisements, and blood donation anxiety, revealing critical psychological and communicative determinants of blood donation intention. To achieve this, a quantitative non-experimental correlational technique was employed to collect data from 414 individuals using an online questionnaire circulated across Greek society. The data were analyzed using structural equation modelling, with a focus on the direct impacts on donation intentions and the role of emotional arousal as a mediator. The findings indicate that attitudes and anxiety have strong direct impacts on the behavioral intention to donate, underlining the important barriers generated by donation anxieties as well as the efficacy of positive attitudes and successful advertising. Furthermore, the study demonstrates emotional arousal as a partial mediator, implying that both cognitive assessments and emotional responses play a role in influencing donation intentions. This study takes on a new approach to give emphasis and provide evidence of the mediating effect of emotional arousal on donation intention, utilizing structural equation modeling. Despite the critical role of marketing as a primary source of blood donors, the implementation of emotional marketing techniques has been one aspect less addressed throughout marketing professionals and communication efforts. Our results demonstrate the significance of emotional arousal on blood donation intentions, thus suggesting a more emotionally resonant approach of attracting potential donors.

Supramolecular nanodrug targeting CDK4/6 overcomes BAG1 mediated cisplatin resistance in oral squamous cell carcinoma

Chemoresistance to cisplatin remains a significant challenge affecting the prognosis of advanced oral squamous cell carcinoma (OSCC). However, the specific biomarkers and underlying mechanisms responsible for cisplatin resistance remain elusive. Through comprehensive bioinformatic analyses, we identified a potential biomarker, BCL2 associated athanogene-1 (BAG1), showing elevated expression in head and neck squamous cell carcinoma (HNSCC). Since OSCC represents the primary pathological type of HNSCC, we investigated BAG1 expression in human tumor tissues and cisplatin resistant OSCC cell lines, revealing that silencing BAG1 induced apoptosis in cisplatin-resistant cells both in vitro and in vivo. This effect led to impaired cell viability of cisplatin resistant OSCC cells and indicated a positive correlation between BAG1 expression and the G1/S transition during cell proliferation. Based on these insights, the administration of a CDK4/6 inhibitor in combination with cisplatin effectively overcame cisplatin resistance in OSCC through the CDK4/6-BAG1 axis. Additionally, to enable simultaneous drug delivery and enhance synergistic antitumor efficacy, we developed a novel supramolecular nanodrug LEE011-FFERGD/CDDP, which was validated in an OSCC orthotopic mouse model. In summary, our study highlights the potential of a combined administration of CDK4/6 inhibitor and cisplatin as a promising therapeutic regimen for treating advanced or cisplatin resistant OSCC.

Single-cell transcriptome analysis upon ECM-remodeling meningioma cells.

Meningiomas are the most common tumours that primarily arise in the central nervous system, but their intratumoural heterogeneity has not yet been thoroughly studied. We aimed to investigate the transcriptome characteristics and biological properties of ECM-remodeling meningioma cells. Single-cell RNA sequencing (ScRNA-seq) data from meningioma samples were acquired and used for analyses. We conducted comprehensive bioinformatics analyses, including screening for differentially expressed genes (DEGs), Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway and Gene Ontology (GO) term enrichment analyses, Gene Set Enrichment Analysis (GSEA), protein-protein interaction (PPI) analysis, and copy number variation (CNV) analysis on single-cell sequencing data from meningiomas. Eighteen cell types, including six meningioma subtypes, were identified in the data. ECM-remodeling meningioma cells (MGCs) were mainly distributed in brain-tumour interface tissues. KEGG and GO enrichment analyses revealed that 908 DEGs were mainly related to cell adhesion, extracellular matrix organization, and ECM-receptor interaction. GSEA analysis demonstrated that homophilic cell adhesion via plasma membrane adhesion molecules was significantly enriched (NES = 2.375, P < 0.001). CNV analysis suggested that ECM-remodeling MGCs showed considerably lower average CNV scores. ECM-remodeling MGCs predominantly localized at the brain-tumour interface area and adhere stably to the basement membrane with a lower degree of malignancy. This study provides novel insights into the malignancy of meningiomas.

Comparative and functional analysis unveils the contribution of photoperiod to DNA methylation, sRNA accumulation, and gene expression variations in short-day and long-day grasses.

Photoperiod employs complicated networks to regulate various developmental processes in plants, including flowering transition. However, the specific mechanisms by which photoperiod affects epigenetic modifications and gene expression variations in plants remain elusive. In this study, we conducted a comprehensive analysis of DNA methylation, small RNA (sRNA) accumulation, and gene expressions under different daylengths in facultative long-day (LD) grass Brachypodium distachyon and short-day (SD) grass rice. Our results showed that while overall DNA methylation levels were minimally affected by different photoperiods, CHH methylation levels were repressed under their favorable light conditions, particularly in rice. We identified numerous differentially methylated regions (DMRs) that were influenced by photoperiod in both plant species. Apart from differential sRNA clusters, we observed alterations in the expression of key components of the RNA-directed DNA methylation pathway, DNA methyltransferases, and demethylases, which may contribute to the identified photoperiod-influenced CHH DMRs. Furthermore, we identified many differentially expressed genes in response to different daylengths, some of which were associated with the DMRs. Notably, we discovered a photoperiod-responsive gene MYB11 in the transcriptome of B.distachyon, and further demonstrated its role as a flowering inhibitor by repressing FT1 transcription. Together, our comparative and functional analysis sheds light on the effects of daylength on DNA methylation, sRNA accumulation, and gene expression variations in LD and SD plants, thereby facilitating better designing breeding programs aimed at developing high-yield crops that can adapt to local growing seasons.

The Sequence Stratigraphy and Sedimentary Evolution of the Guantao Formation in the Binxian Uplift Area, Bohai Bay Basin, China

Due to the influence of multiple tectonic movements in rift basins, the sequence and sedimentary filling modes of continental petroleum reservoirs are complex, which makes it difficult to establish isochronous stratigraphic frameworks and thus affects the accuracy of subsequent predictions of effective sand bodies. Taking the Guantao Formation of the Binxian uplift and the surrounding areas as an example, this study established the sequence stratigraphic framework of the Guantao Formation and discussed the controlling effect of sequence stratigraphy on sedimentary filling. According to a combination method of seismic data, well log data, the wavelet transform technique (WTT), and Integrated Prediction Error Filter Analysis (INPEFA) methods, the Guantao Formation in the study area can be divided into 1 long-term cycle (LNG), 4 mid-term cycles (MNG1–MNG4, from bottom to top), and 11 short-term cycles (SNG1–SNG11, from bottom to top). Based on comprehensive analysis of geological and seismic data, three sedimentary facies can be classified: alluvial fan facies, braided fluvial facies, and meandering fluvial facies. The sequence stratigraphic style of the study area has a significant controlling effect on sedimentation and sand body distribution. Different levels of cycles have different impacts on sedimentary facies/microfacies types, the development degree of each sedimentary microfacies, and sand body distribution. The long-term cycle controls the distribution of sedimentary facies, while the mid-term and short-term cycles control the distribution of sedimentary microfacies. The bottom interface of the Guantao Formation (T1) served as the dominant migration channel in the study area, connecting the reservoir and source rocks. When the base-level was in the low stage (MNG1), a large amount of sand bodies developed, forming favorable reservoirs for petroleum. The interlayers at the top of the long- and mid-term cycles served as seal layers to prevent oil and gas from escaping. The MNG1 cycle has a good combination of reservoir and seal, resulting in the accumulation of oil and gas in the MNG1 strata, which became the main oil- and gas-producing layer in the area. These study results can provide effective guidance for future prediction of the distribution of sand bodies and high-quality reservoirs.

Revolutionizing the Textile and Clothing Industry: Pioneering Sustainability and Resilience in a Post-COVID Era

The COVID-19 pandemic disrupted global supply chains, posing significant challenges to the textile and clothing industry. However, amidst these threats, there is a unique opportunity to rebuild a more sustainable and resilient fashion industry. This paper explores the shift from pre-COVID-19 business models and consumption values towards a renaissance characterized by real sustainability. By examining the transition from eco-efficiency to eco-effectiveness and from cradle-to-grave to cradle-to-cradle approaches, this study emphasizes the need for the active involvement of key stakeholders in co-creating value for all. Through a comprehensive analysis of the post-COVID era, this study aims to understand textile and clothing industry professionals’ perceptions and attitudes towards sustainable design practices and identify challenges in implementing such strategies. The findings contribute to the knowledge of sustainability in the post-COVID era and provide insights and strategies for textile and clothing industry players to thrive in a sustainable and transformed landscape.

Characteristics of chronic lymphocytic leukemia in Japan: Comprehensive analysis of the CLLRSG-01 study.

Chronic lymphocytic leukemia (CLL) is rare in Japan. We conducted the nationwide, prospective observational study CLLRSG-01 to clarify the current state of CLL in Japan and to make accurate international comparisons by preparing naturally air-dried smears like those used in other countries. Of the 201 untreated patients enrolled and evaluated, 119 were diagnosed with CLL and 82 with non-CLL mature B-cell neoplasms, based on the WHO classification. Of the 119 CLL patients, 90 were classified as typical and 29 as atypical according to FAB classification morphology, with the proportion of atypical CLL consistent with reports from other countries. Immunophenotypic analyses by flow cytometry showed that 55% of Japanese CLL patients had a Matutes score of 4 or higher, which is lower than the rate of about 90% in Europeans. Mutated IGHV was identified in 80% of Japanese CLL patients, which is a higher rate than in Western patients. The most frequent IGHV gene was VH3-30 (15%), followed by VH3-23 (12%) and VH4-34 (10%). VH1-69, the most common gene in Western countries, was identified in only one patient. These results indicate that the pattern of immunophenotypes and IGHV gene usage in Japanese CLL patients differs from that in Western patients.

The Legal and Political Implications of AI Bias: An International Comparative Study

Purpose: "The Legal and Political Implications of AI Bias: An International Comparative Study" extensively navigates the intricate terrain of AI governance, with a specific focus on the ethical challenges arising from bias in AI systems. The purpose of this study is to underscore the urgent need for robust regulatory frameworks to address issues of bias, discrimination, and fairness within the realm of AI technologies.&#x0D; Materials and Methods: The research methodology involved a comprehensive analysis of international perspectives on AI bias. This entailed examining existing literature, legal frameworks, and political dynamics surrounding AI governance in various countries. Comparative analysis was conducted to elucidate the diverse approaches adopted by different nations to tackle AI bias and unravel the corresponding legal and political consequences.&#x0D; Findings: The study highlighted the inherent risks associated with biased algorithms and stressed the paramount importance of proactively detecting and mitigating bias to prevent discrimination and promote fairness in AI systems. Additionally, it advocated for comprehensive measures such as risk management strategies, conformity assessments for high-risk AI applications, and the careful handling of sensitive data to identify and rectify biases that could lead to discriminatory outcomes.&#x0D; Implication to Theory, Practice and Policy: The study was informed by theories of ethical governance and legal frameworks in AI development and deployment. It was validated through the comparative analysis of international perspectives, which provided insights into the effectiveness of different regulatory approaches in addressing AI bias. Recommendations to practitioners include implementing risk management strategies, conducting conformity assessments for high-risk AI applications, and ensuring the careful handling of sensitive data to identify and rectify biases. Practitioners are urged to prioritize ethical considerations and advocate for responsible deployment practices to mitigate AI bias effectively. Recommendations to policymakers emphasize the need to prioritize ethical considerations and advocate for responsible deployment practices in AI governance. Policymakers are urged to develop robust regulatory frameworks that promote transparency, accountability, and inclusivity in AI development and deployment to build a more equitable and trustworthy AI ecosystem.&#x0D; In essence, the study provides crucial insights into the complex interplay between legal frameworks, political dynamics, and ethical considerations in addressing AI bias on a global scale. It paves the way for the establishment of fair and unbiased AI systems that benefit society as a whole.

Identification of successful factors for block chain implementation in supply chain based on business life cycle

The implementation of blockchain technology in the supply chain has gained significant attention in recent years due to its potential to enhance transparency, security, and efficiency. However, achieving successful blockchain implementation in the supply chain requires a thorough understanding of the factors that contribute to its success. This research paper aims to identify the successful factors for blockchain implementation in the supply chain through a comprehensive analysis. The identified successful factors are categorized into technological, organizational, external dimensions. Overall, this research paper offers valuable insights into the identification of successful factors for blockchain implementation in the supply chain. It serves as a foundation for future research, providing a comprehensive understanding of the complexities and nuances involved in the successful adoption of blockchain technology in supply chain management.

Kano Model Categorization Methods: Typology and Systematic Critical Overview for Hospitality and Tourism Academics and Practitioners

The Kano model has been widely applied in multiple disciplines, particularly in product or service development and optimization. Although the original categorization framework remains the most applied, modifications and new approaches have recently been developed. Yet, most of the hospitality and tourism studies continue to use the original Kano method when newer and superior methods are available. The new categorization methods also have flaws, which academics and practitioners should be aware of. The present study uses a systematic literature review approach to provide a comprehensive synthesis and critical analysis of the existing Kano model categorization methods structuring them in groups based on categorization procedures and pointing to the strengths, weaknesses, and fit of each method. The manuscript aims to provide the most current systematic roadmap and “how-to” of the existing methods. It also points to the existing knowledge gaps and directions for future research.

Unveiling the structural and bonding properties of AuSi2- and AuSi3- clusters: A comprehensive analysis of anion photoelectron spectroscopy and abinitio calculations.

Silicon clusters infused with transition metals, notably gold, exhibit distinct characteristics crucial for advancing microelectronics, catalysts, and energy storage technologies. This investigation delves into the structural and bonding attributes of gold-infused silicon clusters, specifically AuSi2- and AuSi3-. Utilizing anion photoelectron spectroscopy and abinitio computations, we explored the most stable isomers of these clusters. The analysis incorporated Natural Population Analysis, electron localization function, molecular orbital diagrams, adaptive natural density partitioning, and Wiberg bond index for a comprehensive bond assessment. Our discoveries reveal that cyclic configurations with the Au atom atop the Si-Si linkage within the fundamental Si2 and Si3 clusters offer the most energetically favorable structures for AuSi2- and AuSi3- anions, alongside their neutral counterparts. These anions exhibit notable highest occupied molecular orbital-lowest unoccupied molecular orbital gaps and significant σ and π bonding patterns, contributing to their chemical stability. Furthermore, AuSi2- demonstrates π aromaticity, while AuSi3- showcases a distinctive blend of σ antiaromaticity and π aromaticity, crucial for their structural robustness. These revelations expand our comprehension of gold-infused silicon clusters, laying a theoretical groundwork for their potential applications in high-performance solar cells and advanced functional materials.

Applying the MIMO BP Neural Network and Cloud-Based Monitoring of Thermal Behavior for High-Speed Motorized Spindle Units

Understanding the temperature–working condition relationship is crucial for optimizing machining processes to ensure dimensional accuracy, surface finish quality, and overall spindle longevity. Monitoring and controlling spindle temperature through appropriate cooling systems and operational parameters are essential for efficient and reliable machining operations. This paper presents an in-depth analysis of the thermal equilibrium and deformation characteristics of a high-speed motorized spindle unit utilized in grinding machine tools. Through a series of thermal equilibrium experiments and meticulous data acquisition, the study investigates the nuanced influence of various working conditions, including spindle speeds, coolant types, and coolant flow rates, on spindle temperatures and thermal deformations. Leveraging the power of Artificial Neural Networks (ANNs), predictive models are meticulously developed to accurately forecast spindle behavior. Subsequently, the models are seamlessly transitioned to a cloud computing infrastructure to ensure remote accessibility and scalability, facilitating real-time monitoring and forecasting of spindle performance. The validity and reliability of the predictive models are rigorously assessed through comparison with experimental data, demonstrating excellent agreement and high accuracy in forecasting spindle thermal behavior. Furthermore, the study underscores the critical role of key working condition variables as precise predictors of spindle temperature and thermal deformation, emphasizing their significance in optimizing overall spindle efficiency and performance. This comprehensive analysis offers valuable insights and practical implications for enhancing spindle operation and advancing the field of grinding machine tools.

Ethnopharmacology of five flowers herbal tea, a popular traditional beverage in Hong Kong and South China.

It has been a long-standing tradition of using herbal tea for preventive and therapeutic healthcare in Hong Kong and South China and Five Flowers Tea is one of the most popular herbal teas. Based on the principle of traditional Chinese medicine, the pharmacological functions are to clear heat and dispel dampness in the body. Heat and dampness are thought to contribute to a range of health problems, especially during the hot and humid season in South China and Hong Kong. The most prevalent herbs in the formula contain bioactive compounds including flavonoids, alkaloids and terpenoids, which have a wide range of pharmacological properties including anti-inflammation, antivirus, antidiarrhoea, antibacteria, and antioxidation. However, with the composition varies widely, the ethnopharmacological benefits described may not be delivered uniformly. This study is to provide a comprehensive analysis on the composition of the Five Flowers Tea sold inHong Kong and investigate the rationale behind the selection of herbs used in the formula. This study also provides information on the variation and quality ofthe Five Flowers Tea in the market. Thirty-three Five Flowers Tea samples were collected from various locations in Hong Kong. The size, texture, colour and organoleptic properties were documented. Macroscopic and molecular authentication methods were employed to identify the individual components. Macroscopic identificationrevealed there were 23 herbs belonging to 18 plant families. The most prevalent herb was Bombax ceiba L., followed by Chrysanthemum morifolium. Ten adulterants and the existence of insect Lasioderma serricorne were confirmed byDNA barcoding techniques. This study employed a comprehensive approach to authenticate the herbs in FiveFlowers Tea samplescollected from various locations in Hong Kong. Macroscopic andmolecular methodswere used to identify the herbs and adulterants. The findings revealed the varied composition in Five Flowers Tea and the occurrence of adulterants in some samples. This shows that quality assurance of Five Flowers Tea is essential for the effective use of this popular folk medicine.

Cricket data analytics: Forecasting T20 match winners through machine learning

In the ever-evolving world of cricket, the T20 format has captured the imaginations of fans worldwide, intensifying the anticipation for match outcomes with each passing delivery. This study explores the realm of predictive analytics, leveraging the power of machine learning to alleviate the suspense by forecasting T20 cricket match winners before the first ball is bowled. Drawing on a rich dataset encompassing factors such as past team performance and rankings, a diverse ensemble of predictive models, including logistic regression, support vector machine (SVM), random forest, decision tree, and XGBoost, is meticulously employed. Among these, the random forest Classifier emerges as the standout performer, boasting an impressive prediction accuracy rate of 84.06%. To assess the real-world applicability of our predictive framework, a post-case study is conducted, focusing on the high-stakes World Cup T20 matches of 2022, where England emerges as the triumphant team. The dataset underpinning this study is meticulously curated from ESPN CricInfo, ensuring the robustness of our analysis. Moreover, this paper extends its contribution by offering a comprehensive comparative analysis, scrutinizing performance metrics such as accuracy, precision, recall, and the F1-score across benchmark machine learning models for cricket match prediction. This in-depth evaluation not only validates the efficacy of our models but also sheds light on their superior execution time and statistical robustness, further bolstering their utility in the realm of cricket outcome forecasting.

Medical professional liability insuarance

The aim of the study is to form an integrated approach to understanding the context and legal necessity of medical professional liability insurance.&#x0D; The methodological basis of the study is a set of scientific techniques and methods of scientific knowledge, including dialectical, historical-legal, logical-legal, system-structural, method of forecasting and comparative jurisprudence. Dialectical method has provided opportunities to analyze scientific positions regarding the content and development of medical professional liability insurance. Historical-legal method helps to study the genesis of the development of insurance in specific historical and legal situations, the development of theoretical scientific thought and legislation. The method of comparative law is used to study the legislative and regulatory acts of Ukraine and other countries in the world as well as to clarify the advantages and disadvantages of the mechanism of legal regulation the insurance of medical professional liability in various countries in the world. Systemic and structural methods have helped to clarify the content of the contracts connected with this kind of insurance. Formal-logical method has allowed analyzing the provisions of the legislation of Ukraine in the sphere of this type of insurance.&#x0D; Results. This study contains a comprehensive scientific analysis of modern problems of medical professional liability insurance. The elements of the medical professional liability insurance contract are defined, namely: subject matter, insured, beneficiary, insurance risk, insurance event, conditionals of insurance compensation payment. It is stipulated that medical professional liability insurance contract shall have separate grounds for refusal to pay insurance compensation, inherent only to this type of insurance. It is shown that this type of insurance helps to manage the risks in medical practice activities. The concept of this type of insurance has been researched. The conditions to terminate the medical professional liability insurance have been identified.&#x0D; Conclusions. Having considered the issues of medical professional liability insurance and examined the conditions of the medical professional liability insurance contract, it has been made a conclusion that it is necessary to introduce this type of insurance as mandatory for healthcare institutions and private practitioners. It has been proposed to introduce compulsory medical professional liability insurance by approving necessary alterations the valid legislation.

Identification of potential biomarkers for progression and prognosis of renal clear cell carcinoma by comprehensive bioinformatics analysis.

Clear cell renal cell carcinoma (ccRCC) is the most common pathological type of renal cell carcinoma (RCC), and effective biomarkers will improve diagnosis and treatment. This study investigated NPEPL1 expression in ccRCC through public databases and clinical samples and assessed its correlation with clinicopathological features and patient prognosis. Data from The Cancer Genome Atlas and clinical specimens were gathered, NPEPL1 expression levels were analyzed; a receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of NPEPL1; and clinicopathological data was used to study the correlations between expression and clinical parameters. NPEPL1's prognostic value was appraised using a Kaplan-Meier (K-M) survival curve, Cox regression analysis, and a nomogram model; Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of differently expressed genes between tissues with high and low NPEPL1 expression were used to estimate the underlying mechanisms involved. NPEPL1 was significantly higher-expressed in ccRCC tissue. ROC analysis showed that NPEPL1 had noteworthy diagnostic efficacy. NPEPL1 expression was closely related to clinicopathological parameters, such as T and M stage. K-M analysis showed that overall survival was significantly shortened with high NPEPL1 expression. Cox regression analysis showed that NPEPL1 expression was an independent risk factor predicting overall survival. The nomogram showed a significantly high clinical value in predicting the 1-, 3-, and 5-year survival probabilities in ccRCC. GO and KEGG enrichment analysis suggested that NPEPL1 may promote the occurrence and development of ccRCC via the Ras signaling and other pathways. NPEPL1 expression in ccRCC was higher than that in normal kidney tissues and was significantly associated with advanced clinical stage and poor prognosis. Therefore, NPEPL1 is a promising prognostic biomarker.

Ciliatonoids D–M, highly modified limonoids from the twigs of Toona ciliata

A new ring-intact limonoid, ciliatonoid D (1), five new 7,8-seco limonoids, ciliatonoids E–I (2–6), three new 7,8-seco-29-nor limonoids, ciliatonoids J–L (7–9), and a new 7,8:9,11-diseco limonoid, ciliatonoid M (10), together with eleven known limonoids were isolated from the twigs of Toona ciliata. Their structures were established by comprehensive analyses of spectroscopic, electronic circular dichroism, single-crystal X-ray diffraction data. Compound 6 bears an uncommon 1,30-oxygen bridge. Compound 10 represents a rare example of a structure with 9,11-seco limonoid from Meliaceae. The orientation of the 14,15-epoxy moiety in a known limonoid, toonayunnanae C (12), was revised as in a β-orientation by quantum NMR calculations with ML-J-DP4 probability analysis. Compound 9 and a known analogue, toonanoronoid C (11), were found to show modest in vitro cytotoxicity against HL-60 (human premyelocytic leukemia) and P-388 (murine leukemia) cell lines.

Environmental, Social, and Governance Influence on Corporate Governance: A Comprehensive Analysis

The importance of sustainability practises has increased for firms and investors in light of the rapidly shifting investment and climate change landscapes. The UN has stressed the need for impact and ethical investing as well as sustainable investing with its 17 ambitious development objectives. Because they focus on a company's non-financial issues, such social and environmental concerns, ESG funds have become more well-known. The study examines the potential synergies between corporate governance principles and ESG elements to enhance shareholder value, performance, risk management, and organisational resilience. It also examines the ways in which company type, firm size, and the regulatory environment influence relationships between corporate governance, ESG practises, and financial performance. The research provides valuable insights into the benefits of combining ESG and corporate governance, with a focus on improving financial performance and organisational resilience. It also takes regulatory environment and industry-specific considerations into account.