Title Of Article Research Articles

Continuing Medical Education Questions: October 2023.

Article Title: Performing High Quality, Safe, Cost-Effective and Efficient Basic Colonoscopy in 2023: Advice From Two Experts.

Feature importance in the age of explainable AI: Case study of detecting fake news & misinformation via a multi-modal framework

In recent years, fake news has become a global phenomenon due to its explosive growth and ability to leverage multimedia content to manipulate user opinions. Fake news is created by manipulating images, text, audio, and videos, particularly on social media, and the proliferation of such disinformation can trigger detrimental societal effects. False forwarded messages can have a devastating impact on society, spreading propaganda, inciting violence, manipulating public opinion, and even influencing elections. A major shortcoming of existing fake news detection methods is their inability to simultaneously learn and extract features from two modalities and train models with shared representations of multimodal (textual and visual) information. Feature engineering is a critical task in the fake news detection model's machine learning (ML) development process. For ML models to be explainable and trusted, feature engineering should describe how many features used in the ML models contribute to making more accurate predictions. Feature engineering, which plays an important role in the development of an explainable AI system by shaping the features used in the ML models, is an interconnected concept with explainable AI as it affects the model's interpretability. In the research, we develop a fake news detector model in which we (1) identify several textual and visual features that are associated with fake or credible news; specifically, we extract features from article titles, contents, and, top images; (2) investigate the role of all multimodal features (content, emotions and manipulation-based) and combine the cumulative effects using the feature engineering that represent the behavior of fake news propagators; and (3) develop a model to detect disinformation on benchmark multimodal datasets consisting of text and images. We conduct experiments on several real-world multimodal fake news datasets, and our results show that on average, our model outperforms existing single-modality methods by large margins that do not use any feature optimization techniques.

Opioid Impacts on Cardiovascular Health.

The prevalence of opioid use in the current opioid epidemic era has led to a public health emergency due to the ties to mortality and morbidity. Studies have investigated opioids' impacts on different aspects of cardiovascular health, although there seems to be a lack of a current concise review. Therefore, the aim of this literature review is to provide a summary of the most recent studies from the past decade that postulate a connection between opioids and their impact on cardiovascular health while highlighting conflicting areas among published research. For this literature review, three databases, PubMed (NLM), EMBASE, and Web of Science (Core Collection), were searched for full peer-reviewed articles written in English about human subjects and published between 2013 and 2023 inclusive. The following initial approach was to search for terms in the title of articles: "opioid AND ("vascular" OR "artery" OR "vein" OR "heart rate" OR "infarct" OR "stroke" OR "aortic" OR "cardiovascular disease"). After assessing for duplicate articles from the three databases, the remaining articles were assessed for inclusion eligibility. In the present review, a brief description of the overall role of opioid receptors is provided followed by the literature findings. These findings indicate potentially important negative impacts of opioid use on cardiovascular health in a number of areas. These include opioid-associated increases in the following: (1) vascular aging based on demonstrated increases in arterial stiffness, (2) opioid-related reductions in heart rate variability (HRV) and its implications on morbidity and mortality, (3) opioid's impacts on coronary artery and coronary heart disease (CHD), (4) opioids as a risk factor for atrial fibrillation (AF) and (5) opioid use as a risk factor for vascular occlusion processes. In addition to these broad cardiovascular effects, other aspects of concern are related to the potential impacts of withdrawal from opioid use, which, when done rapidly, are associated with increases in blood pressure and a decrease in HRV.

A bibliometric analysis of halal tourism: future research agenda

Purpose Over the past few decades, a large number of research studies have examined tourism. However, studies that examine halal tourism are still limited. Therefore, the purpose of this study is to conduct a bibliometric analysis related to halal tourism based on the results of empirical research studies that have been published. Design/methodology/approach The approach in this study uses a systematic literature review related to halal tourism as a reference in “Article Title, Abstract and Keywords” based on the Scopus database from 1997 to 2023. The analysis was conducted on January 8, 2023. The data that has been collected will be analyzed bibliometrically using VOSviewer. Findings The research findings show that research related to halal tourism is still relatively rare, especially in countries/locations where the majority of the population is non-Muslim. This can be seen from the majority of previous studies conducted in Muslim-majority countries/locations, such as Malaysia and Indonesia. Future research should be conducted in countries/locations where the majority of the population is non-Muslim. Research limitations/implications This study relies on research in halal tourism literature in the Scopus database. Future studies can combine with the Web of Science database to expand generalization. Practical implications The results of this study include implications for managing and developing sustainable halal tourism in the future for practitioners. Social implications The results of this study provide a strategic perspective to practitioners and society in general to find out how the concept of sustainable halal tourism development in the future is in accordance with Islamic sharia. Originality/value Research related to halal tourism is currently starting to develop in various countries, both with a majority Muslim and non-Muslim population. In addition, until now research related to halal tourism is still limited literature that discusses.

Compounds inpress article titles and their contribution to the realization of the communicative function. An analysis on the example of the online version of the „Süddeutsche Zeitung” newspaper

Compounds inpress article titles and their contribution to the realization of the communicative function. An analysis on the example of the online version of the „Süddeutsche Zeitung” newspaper

Continuing Medical Education Questions: January 2024.

Article Title: American College of Gastroenterology Monograph on Microbiome Therapeutics.

Biomarkers for Prediabetes, Type 2 Diabetes, and Associated Complications

Purpose: Diabetes mellitus is a chronic disorder caused by high blood glucose levels due to insulin resistance or insufficient insulin production in pancreatic β-cells. Due to its fastest-growing public health concerns worldwide, it is important to evaluate metabolic profile abnormalities before pre-diabetes or T2DM to anticipate and prevent disease progression. The purpose of the study was to examine the metabolite biomarkers by systematic review and meta-analysis to support early detection of pre-diabetes and T2DM.
 Methodology: Studies published from the earliest online through May 31, 2023, were searched in the Cochrane Library, EMBASE, PubMed, and Scopus. Article titles, abstracts, and complete texts were reviewed after duplicate records were eliminated. Two writers (Long and Yang) created the following inclusion criteria for the publications before literature screening: The study was conducted on humans, did not involve gestational diabetes mellitus (GDM), type 1 diabetes mellitus (T1DM), or subjects under 18 years old, included a diabetic or prediabetes group, and followed international diagnostic guidelines (American Diabetes Association, 2013).
 Findings: The study aimed to review the biomarkers that have been utilized for diabetes in previous research. The comparison of the biomarkers mentioned in the provided information revealed a complex interplay of factors influencing the risk and management of Type 2 Diabetes (T2D). These biomarkers encompass genetic, lifestyle, environmental, and insulin-related factors, each with varying degrees of accuracy and specificity in predicting T2D risk or guiding its management.
 Recommendations: The research will help in spreading awareness among people regarding the identification of diabetes as understanding biomarker-based screening's economic impact can inform healthcare policies. Future studies should validate these biomarkers' diagnostic capacities across varied populations and circumstances. Assessment of these biomarkers' predictive usefulness should be done over time via longitudinal research. Understanding biomarker alterations and diabetes progression improves risk prediction.

Current Applications of Artificial Intelligence in Sarcoidosis.

Sarcoidosis is a complex disease which can affect nearly every organ system with manifestations ranging from asymptomatic imaging findings to sudden cardiac death. As such, diagnosis and prognostication are topics of continued investigation. Recent technological advancements have introduced multiple modalities of artificial intelligence (AI) to the study of sarcoidosis. Machine learning, deep learning, and radiomics have predominantly been used to study sarcoidosis. Articles were collected by searching online databases using keywords such as sarcoid, machine learning, artificial intelligence, radiomics, and deep learning. Article titles and abstracts were reviewed for relevance by a single reviewer. Articles written in languages other than English were excluded. Machine learning may be used to help diagnose pulmonary sarcoidosis and prognosticate in cardiac sarcoidosis. Deep learning is most comprehensively studied for diagnosis of pulmonary sarcoidosis and has less frequently been applied to prognostication in cardiac sarcoidosis. Radiomics has primarily been used to differentiate sarcoidosis from malignancy. To date, the use of AI in sarcoidosis is limited by the rarity of this disease, leading to small, suboptimal training sets. Nevertheless, there are applications of AI that have been used to study other systemic diseases, which may be adapted for use in sarcoidosis. These applications include discovery of new disease phenotypes, discovery of biomarkers of disease onset and activity, and treatment optimization.

The 100 Most Cited Kluver-Bucy Research Articles: A Bibliometric Analysis.

Kluver-Bucy Syndrome (KBS) is a rare neuropsychiatric disorder characterized by hyperorality, hypersexuality, bulimia, visual agnosia, and amnesia due to lesions affecting bilateral temporal lobes.It is attributed to a multitude of causes, including stroke, herpes simplex encephalitis, Alzheimer's disease, and head trauma.Current treatments for KBS include symptomatic management with antipsychotics, mood stabilizers, carbamazepine, and selective serotonin reuptake inhibitors. The bibliometric analysis was done to reflect the relevance and understanding of KBS in recent literature.The SCOPUS database was utilized to conduct a search for all articles with the terms "Kluver-Bucy" and "Kluver Bucy" from January 1, 1955 (the first available articles from the search) to February 1, 2023. The parameters included in this analysis were article title, citation numbers, citations per year, authors, institutions, publishing journals, country of origin, Source Normalized Impact per Paper, and Scopus CiteScore. Since 1937, when Kluver-Bucy Syndrome was first defined, the publications on KBS have steadily increased, with up to six publications a year in 2002. The most common institutions were SUNY Upstate Medical University, VA Medical Center, and the State University of New York (SUNY) System. Seven of these papers were published in Neurology. Almost 75% of the articles were published in journals of medicine and neuroscience. This is the first bibliometric analysis to evaluate the most influential publications about Kluver-Bucy Syndrome. A majority of the research is case-based and there is a dearth of clinical trials to identify the exact pathophysiology and physiotherapy management, possibly owing to the rarity of the disease. Our research suggests that there may be a significant overlap between Sanfilippo syndrome and KBS, suggesting that refined guidelines for establishing diagnosis may be required for children. Our study could bring a renewed interest in this field and lead to additional research focused on understanding the pathophysiology of KBS in order to promote the development of novel diagnostics and treatment.

A cyber risk prediction model using common vulnerabilities and exposures

The cyber risk from malicious external attackers is a significant socio-economic problem. Cyber risk prediction is particularly difficult, given the constantly changing attack vectors. This study presents a model that automatically predicts cyber risks. The model is only based on common vulnerabilities and exposures (CVE) data and supervised prediction algorithms. This approach eliminates expert opinion bias in cyber risk prediction. Our supervised data-driven model, CyRiPred, CVE data into cyber risk groups by mapping the textual description field of the database into relevant Wikipedia article titles. Then CyRiPred aggregates the occurrence and severity of extracted topics for the desired time unit and produces a time series fed to supervised regressors for prediction. The risks are calculated using predicted occurrence and impact. Finally, the cyber risks are ranked by their score, and the top ten risks are presented. The proposed model is evaluated, and the results are discussed.

Artificial Intelligence Advances in Transplant Pathology.

Transplant pathology plays a critical role in ensuring that transplanted organs function properly and the immune systems of the recipients do not reject them. To improve outcomes for transplant recipients, accurate diagnosis and timely treatment are essential. Recent advances in artificial intelligence (AI)-empowered digital pathology could help monitor allograft rejection and weaning of immunosuppressive drugs. To explore the role of AI in transplant pathology, we conducted a systematic search of electronic databases from January 2010 to April 2023. The PRISMA checklist was used as a guide for screening article titles, abstracts, and full texts, and we selected articles that met our inclusion criteria. Through this search, we identified 68 articles from multiple databases. After careful screening, only 14 articles were included based on title and abstract. Our review focuses on the AI approaches applied to four transplant organs: heart, lungs, liver, and kidneys. Specifically, we found that several deep learning-based AI models have been developed to analyze digital pathology slides of biopsy specimens from transplant organs. The use of AI models could improve clinicians' decision-making capabilities and reduce diagnostic variability. In conclusion, our review highlights the advancements and limitations of AI in transplant pathology. We believe that these AI technologies have the potential to significantly improve transplant outcomes and pave the way for future advancements in this field.

Continuing Medical Education Questions: September 2023.

Article Title: Incidence of hepatic decompensation after nucleos(t)ide analog withdrawal: Results from a large, international, multi-ethnic cohort of patients with chronic hepatitis B (RETRACT-B study).

The Association Between Maternal Nutritional Status During Pregnancy and Caries Experience in Their Offspring: A Literature Review

Previous studies have discovered intergenerational linkage between maternal nutritional status and the subsequent health of their offspring. This literature review aimed to explore the connection between the nutritional status of mothers during pregnancy and the occurrence of dental caries in their children. PubMed and Scopus were used for searching articles, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) protocol. The process involved eliminating duplicate articles, and further refinement included articles published within the timeframe of 2013-2023 and those published in the English language. Review articles, studies involving animals, letters to the editor, book sections, and conference proceedings were excluded. Articles that did not provide information on the variables of interest and sample details were also excluded. Data extraction included author names, article titles, publication years, study designs, indicators of maternal nutritional status, type of dentition under consideration, and the reported outcomes. After meticulous removal of duplicate articles and careful application of the inclusion and exclusion criteria, 7 articles met the study's eligibility criteria. The study results collectively indicated that lower levels and intake of maternal plasma vitamin D, reduced maternal plasma folate levels, inadequate gestational weight gain, and overall poor maternal nutritional status were associated with an increased risk of dental caries in their children. It is crucial for mothers to maintain a diet that guarantees the adequate nutrition of the developing fetus.

Institute of Euthanasia: Between a Person’s Right to Life and the Right to a Dignified Death: Problems and Challenges in the Implementation of Human Rights of Choice in Lithuania

Abstract The title of the scientific article is the problem of euthanasia as a possibility for the implementation of natural human rights in Lithuania and foreign countries. The purpose of this paper is to analyze the relationship between the individual’s right to life and the prohibition of torture in the implementation of euthanasia as one of the natural human rights in Lithuania and foreign countries. This work has theological and comparative methods. The theological method, which leads to the first part of the work, analyzing international and national legal acts regulating natural human rights. The comparative method compares the legal regulations and social differences between countries that have legalized and those that have not legalized euthanasia. The main conclusion of the article - the legalization of euthanasia is one of the possibilities to implement the prohibition of torture in the context of natural human rights. The practical significance of this scientific article is particularly important for states that have not legalized euthanasia, because the main conclusion of this article is proving the obligation of states to legalize euthanasia in order to provide suitable conditions for the realization of natural human rights. The originality of this scientific article is based on the fact that the compatibility of euthanasia in the context of human rights and freedoms and the equating of the illegalization of euthanasia to torture at the national and international level have not been analyzed in any scientific articles. The value of the article is proven by the fact that the authors used only the latest scientific editions of national and international legal acts and the latest and most comprehensive literature.

Automatic classification of experimental models in biomedical literature to support searching for alternative methods to animal experiments

Current animal protection laws require replacement of animal experiments with alternative methods, whenever such methods are suitable to reach the intended scientific objective. However, searching for alternative methods in the scientific literature is a time-consuming task that requires careful screening of an enormously large number of experimental biomedical publications. The identification of potentially relevant methods, e.g. organ or cell culture models, or computer simulations, can be supported with text mining tools specifically built for this purpose. Such tools are trained (or fine tuned) on relevant data sets labeled by human experts. We developed the GoldHamster corpus, composed of 1,600 PubMed (Medline) articles (titles and abstracts), in which we manually identified the used experimental model according to a set of eight labels, namely: “in vivo”, “organs”, “primary cells”, “immortal cell lines”, “invertebrates”, “humans”, “in silico” and “other” (models). We recruited 13 annotators with expertise in the biomedical domain and assigned each article to two individuals. Four additional rounds of annotation aimed at improving the quality of the annotations with disagreements in the first round. Furthermore, we conducted various machine learning experiments based on supervised learning to evaluate the corpus for our classification task. We obtained more than 7,000 document-level annotations for the above labels. After the first round of annotation, the inter-annotator agreement (kappa coefficient) varied among labels, and ranged from 0.42 (for “others”) to 0.82 (for “invertebrates”), with an overall score of 0.62. All disagreements were resolved in the subsequent rounds of annotation. The best-performing machine learning experiment used the PubMedBERT pre-trained model with fine-tuning to our corpus, which gained an overall f-score of 0.83. We obtained a corpus with high agreement for all labels, and our evaluation demonstrated that our corpus is suitable for training reliable predictive models for automatic classification of biomedical literature according to the used experimental models. Our SMAFIRA - “Smart feature-based interactive” - search tool (https://smafira.bf3r.de) will employ this classifier for supporting the retrieval of alternative methods to animal experiments. The corpus is available for download (https://doi.org/10.5281/zenodo.7152295), as well as the source code (https://github.com/mariananeves/goldhamster) and the model (https://huggingface.co/SMAFIRA/goldhamster).

Homology in the Rate and Pattern of Eruption of Primate Dentition: A Narrative Review

Adult antemolar dentition of mammals may consist of both permanent and retained deciduous teeth. Certain animals, such as Homo sapiens and Tarsius, develop sequence homology of three sets of teeth. A technique for reconsidering dental homologies is presented, and a model of tooth loss is given, following a reassessment of dental homologies in most primates. An essential component of the theory of evolution is the study of homology and the discovery of related species, particularly phylogenetic reconstruction. Scopus, PubMed, Web of Science and Google Scholar were the electronic databases utilized to gather pertinent information that satisfied the eligibility requirements. The databases' key terms led to the discovery of 125 articles in total. Eighteen articles were discarded based solely on the article's title and abstract, and eighty-seven articles were eliminated because of duplication or irrelevant themes. There is a relationship between dental morphology and tooth function, however, physical similarities do not always imply homology. A conclusion was derived that, diet, life history, and phylogeny are the primary factors that influence the rate of tooth eruption.

An overview of the studies on microbial air contamination in operating theatres and related issues over time: a useful tool for a multidisciplinary approach.

Background and aim Surgical site infection (SSI) is a major complication following surgery associated with increased morbidity and mortality, as well as increased health and not health costs. A variety of factors affect airborne contamination in operating theatres (OT). Following the Medical Research Council study showing a correlation between microbial air contamination and SSI incidence in prosthetic joint surgery ultraclean OTs have been recommended for this type of surgery, while OTs supplied by turbulent airflow plants are recommended for other types of surgery. The aim of this study was to illustrate the studies on this topic. Methods Scopus was considered for articles published until January 2023 on OTsandaircontamination in article title or abstract or keywords. Many issues were deepened: "microbial", "bacterial", "fungi", "viruses", "surgical site/wound infection", "monitoring/sampling", "air changes", "behaviour", "door openings", "particles", turbulent flow", "unidirectional flow". Results Total papers published were 907 and 249 papers faced monitoring/sampling. A total of 313 papers investigated airborne bacterial contamination and 63 papers investigated fungal air contamination. There were 218 papers that have evaluated particle contamination in OTs. Many other issues were deepened. Conclusions This study shows a picture of the studies on biological air contamination in OTs and related issues over time. We think that the results of our study will provide a useful tool to increase awareness towards a better sharing of aims, approaches, and results, above all in the interest of the patients, but also of the health services of the different countries. (www.actabiomedica.it).

EXAM SURVEILLANCE USING MACHINE LEARNING

Recent publications on video surveillance systems in conferences and journals show that researchers are paying attention. This review's objectives are to look at the most recent works that have been published in journals, suggest a new classification scheme for video surveillance systems, and look into each component of that scheme. Using the article's title and keyword, this paper presents a thorough and organized analysis of the prior literature on video surveillance systems from 2010 to 2011. The review was taken from six online digital libraries. The architecture of video surveillance systems, which consists of six layers: the Concept and Foundation Layer, Network Infrastructure Layer, Processor Layer, Communication Layer, Application Layer, and User Interaction Layer, serves as the foundation for the suggested classification framework. This analysis demonstrates that while real-time aspects of the problem are the subject of many publications and studies, the use of extracted and retrieved information for forensic video surveillance has received less attention. Key Words: CCTV, video surveillance system, exam surveillance, student activity recognition, frameworks, datasets, network infrastructure layer, processing layer, communication layer, application layer, and user interaction layer.

Syntactic structures of Turkish research article titles in medicine and engineering

The title is of vital importance to research articles as it summarizes the content in several words and grabs the attention of readers. When selecting articles pertinent to their research, the prevalence of online publication leads readers to use online search engines like Google Scholar, which generally displays the first few words of a title, making the title highly important. This study aimed to investigate some key features, such as length, style, syntactic structure and punctuation marks of titles in Turkish research articles in medicine and engineering. To this end, we selected 1,200 titles in four leading journals publishing research articles in these disciplines. As a tool to collect data, document analysis was used in the study to analyze such features of titles and in analyzing the data, descriptive analysis technique was used. The study revealed that both medicine and engineering have almost the equivalent title length. Titles in both disciplines are dominated by single-unit ones and both single-unit and compound titles are predominated by nominal group construction. The results also suggested some disciplinary differences: Compound titles were more common in medicine than in engineering. Medical titles appear to have used more varied syntactic structures in forming titles. Moreover, medical titles have shown a high degree of complexity in terms of punctuation usage. The differences might be attributed to disciplinary practices set out in these two fields. The results of the present study will provide novice writers with ample opportunity to construct their titles as best they can while maintaining their effort to build and enhance their academic writing skills.

Characteristics and changes in Japanese public administration research: statistical content analyses of article titles in Public Administration Review Quarterly (1978–2019)

The objective of this study is to understand features of Japan’s public administration research and the changes it has undergone, by using content analyses. To this end, this study quantitatively explains research trends in postwar administrative studies in Japan by statistically analyzing article titles from the Public Administration Review Quarterly over the course of nearly 40 years. Co-occurrence network and correspondence analyses revealed the changes in research interests. There was substantially more research on administrative reforms through the postwar Showa and Heisei eras. The configuration of the correspondence analysis indicates that the first dimension is concerned with administrative reforms, the second with historical events or administrative systems, and the third with evaluations and kaizen. The co-occurrence network analysis show that two extracted compound words—the United States and the United Kingdom—were very common in studies during the Showa era (1978–1988). This suggests that Japan’s public administration was influenced by the West during this period. Japan’s policies and institutions became a feature of these studies during the Heisei era (1989–2018). The results of this analysis is partially similar to the author’s previous studies on another Japanese administrative studies journal. One commonality of the results of the analysis is that the dimension related to administrative reform was found in the correspondence analysis. In this study, the first principal component was administrative reform, and Moteki’s (Hiroshima Law J 43:205–235, 2020) correspondence analysis also found “reform,” “policy evaluation” and “governance” as characteristic extracted terms in the 2000s.