Vaccination is a groundbreaking approach in preventing and controlling infectious diseases. However, the effectiveness of vaccines can be greatly enhanced by the inclusion of adjuvants, which are substances that potentiate and modulate the immune response. This review is based on extensive searches in reputable databases such as Web of Science, PubMed, EMBASE, Scopus, and Google Scholar. The goal of this review is to provide a thorough analysis of the advances in the field of adjuvant research, to trace the evolution, and to understand the effects of the various adjuvants. Historically, alum was the pioneer in the field of adjuvants because it was the first to be approved for use in humans. It served as the foundation for subsequent research and innovation in the field. As science progressed, research shifted to identifying and exploiting the potential of newer adjuvants. One important area of interest is nano formulations. These advanced adjuvants have special properties that can be tailored to enhance the immune response to vaccines. The transition from traditional alum-based adjuvants to nano formulations is indicative of the dynamism and potential of vaccine research. Innovations in adjuvant research, particularly the development of nano formulations, are a promising step toward improving vaccine efficacy and safety. These advances have the potential to redefine the boundaries of vaccination and potentially expand the range of diseases that can be addressed with this approach. There is an optimistic view of the future in which improved vaccine formulations will contribute significantly to improving global health outcomes.

Artificial intelligence (AI) and microbiome have emerged in recent years as transformative fields with far-reaching implications for various biomedical domains. This paper presents a comprehensive bibliometric analysis examining the intersection of AI and the microbiome (AIM). The study aims to provide information on this interdisciplinary fields research landscape, trends, and emerging topics. Using a systematic approach, data-driven studies were extracted from the Scopus database on 23 November 2023 and analyzed using the VOSviewer and Bibliometrix applications. The regression coefficient of 0.94 and the yearly growth rate of 7.46% in AIM production indicate a consistent increase over time. Identification of essential contributors, organizations, and nations illuminated cooperative networks and research hotspots. The trend themes are the gut microbiome, disease prediction, machine learning, transfer learning, categorization, big data, artificial neural networks, chronic rhinosinusitis, epidemiology, COPD, and bronchoalveolar lavage. These hot issues in AIM reflect the present emphasis on research and developments in our knowledge of the microbiomes function in health, sickness, and individualized treatment. The findings give researchers, policymakers, and industry experts a thorough picture of the research environment and guide future paths in AIMs fascinating and promising subject.

The current study was designed to validate the Arabic version of the Diabetes Self-Management Scale (DSMS) using Rasch and confirmatory factor analyses. This included person and item fit, separation, and reliability; rating scale functionality to evidence substantive validity; unidimensional structure to evidence structural validity; and item technical quality to evidence content validity. The study was conducted between September 2021 and March 2022. Utilizing AMOS-based confirmatory factor analysis (CFA), the study also assured the dimensionality of the DSMS. The participants were 103 diabetic patients in Saudi Arabia with a mean age of 44.72 years (standard deviation = 17.35). The analysis was performed using a trichotomous rating scale, and only one item exhibited a misfit (DSMS14). The item difficulty range was −1.0 to +1.0 logits, while the person’s ability range was −3.0 to +3.0 logits. The first construct proved one Rasch dimension, which was explained and further analyzed using AMOS-CFA for the one-factor model. The DSMS was shown to be beneficial as a screening instrument for patient-reported diabetes self-management, despite several flaws that need to be addressed to improve the scale further.

Background/objectives Neutrophil elastase (NE) is a serine protease primarily produced by neutrophils, playing a pivotal role in various physiological and pathological processes. This study aimed to provide insights into the research landscape surrounding NE and its implications in the post-COVID-19 era. Methods The current study employed a cross-sectional design based on bibliometric analysis. Articles were retrieved from the Scopus database and analyzed quantitatively using VOSviewer and Bibliometrix software to evaluate publication trends, authorship patterns, citation dynamics, and emerging research themes. Results The analysis highlighted countries and institutions significantly contributing to NE research, revealing global trends and hotspots. Collaboration patterns were assessed, showcasing productive partnerships within the field. Key research topics identified include NE’s roles in inflammation, tissue damage, and disease pathogenesis. The COVID-19 pandemic reshaped the thematic map of NE research, driving focus toward NE's involvement in COVID-19 pathophysiology, therapeutic interventions, and its role in complications associated with the disease. Conclusions This bibliometric analysis offers a comprehensive view of NE research, focusing on its functions, pathophysiological roles, and implications for diseases such as lung disorders and COVID-19, providing a foundation for future research directions.

Background: This retrospective study evaluated hematological parameters in coronavirus disease 2019 (COVID-19) patients to gain clinical insights. Methods: Data from the Emergency Department of Samtah General Hospital, Samtah, Saudi Arabia, were analyzed, focusing on the parameters measured during hospital admission. This study was conducted between April 2020 and October 2021. Associations between hematological parameters and COVID-19 outcomes were examined in 153 participants, including 23 deceased individuals. Results: The chi-square test results indicated no significant associations (P >0.05) between sex, body mass index (BMI), age, and disease outcome in the study population. However, a significant association was observed between neutrophil percentage and disease outcome, whereas no significant associations were found for red blood cell count, hemoglobin level, monocyte percentage, eosinophil percentage, and basophil percentage. Cox regression analysis revealed a significant association between neutrophil count (considered a categorical covariate) and survival outcomes (P = 0.030). However, specific neutrophil categories (50-70 and >70) were not significantly associated with survival. Conclusions: Integrating hematological parameters into COVID-19 clinical guidelines and decision-support tools holds promise for enhancing patient care and outcomes.

Sleep deprivation research (SDR) has undergone substantial transformations in the aftermath of the COVID-19 pandemic. This comprehensive study explores the SDR’s evolving trends, hotspots, and conceptual structure in the post-COVID-19 era. Using bibliometric analysis with VOSviewer and Bibliometrix software, we examined the SDR publications from January 2020 to December 2023. Core sources were identified using Bradford law, and a dataset of 4578 English-based data-driven studies was retrieved from the Scopus database. Our analysis revealed a remarkable annual growth rate of 37.92% in SDR from 2020 to 2023, indicating a heightened research focus in this domain. Among prolific authors, Shao emerged as a key contributor, while Sleep ranked prominently as a leading publication venue. The United States and China have emerged as the most impactful countries for advancing SDR research. Uncovering the most cited documents sheds light on various focal points within SDR, including sleep duration, mental health implications, cardiovascular events, the impact of COVID-19 on sleep patterns, dementia, resilience in children, and sleep patterns among preschoolers. Noteworthy keywords that emerged from the analysis encompassed “sleep deprivation,” “depression,” “insomnia,” “COVID-19,” “anxiety,” “fatigue,” and “obesity.” Using a thematic mapping approach, we delineated distinct themes characterized by niche, basic, emerging, and declining patterns. Clusters of SDR research were observed in areas such as “Fatigue,” “Sleep apnea,” “Sleep,” “Sleep deprivation,” “Migraine,” “Caffeine,” and “Recovery.” Furthermore, trending themes in SDR encompassed “Sleep disturbance,” “excessive daytime sleepiness,” and “Gamma-Aminobutyric Acid.” These comprehensive findings provide valuable insights into the current landscape of SDR, illuminating emerging trends, identifying hotspots, and offering directions for future research in this critical field.