After the discovery of insulin at the University of Toronto in 1921-22, Frederick Banting and Charles Best downplayed the contributions of physiology professor John James Rickard Macleod, the director of the laboratory where the discovery was made. Banting and Best, their allies, and to a lesser extent the university promoted a \"fairy tale\" version in which the two young investigators made the discovery on their own, creating the so-called \"Banting and Best myth.\" Over the next 60 years, the myth prevailed and Macleod\'s reputation became increasingly tarnished, with both Banting and Best actively maligning their former mentor. While the publication of Michael Bliss\' The Discovery of Insulin in 1982 placed Macleod\'s reputation on the road to recovery, there are still many lingering issues that have been raised, and Macleod remains misunderstood, misinterpreted, and maligned. This paper, using primary and secondary historical sources, addresses topics that have been repetitively raised by Macleod\'s detractors over the past century.
Résumé. Après la découverte de l’insuline à l’Université de Toronto en 1921–1922, Frederick Banting et Charles Best ont minimisé les contributions du professeur de physiologie John James Rickard Macleod, directeur du laboratoire où la découverte a été faite. En compagnie de leurs alliés et dans une certaine mesure de l’Université, Banting et Best ont propagé un conte de fée dans lequel les deux jeunes chercheurs auraient fait cette découverte par eux-mêmes, donnant ainsi naissance au « mythe Banting et Best ». Au cours des 60 années suivantes, ce mythe a prévalu et la réputation de Macleod a été ternie, Banting et Best s’employant à calomnier leur ancien mentor. Si la publication de The Discovery of Insulin (1982) par Michael Bliss a quelque peu rétabli la réputation de Macleod, celui-ci est encore largement incompris, mal interprété et dénigré. En s’appuyant sur des sources historiques premières et secondaires, cet article aborde les enjeux qui ont été soulevés de manière répétée par les détracteurs de Macleod au cours du XXe siècle.

Lung cancer remains the leading cause of cancer-related deaths worldwide, mainly due to late diagnosis and the presence of metastases. Several countries around the world have adopted nation-wide LDCT-based lung cancer screening that will benefit patients, shifting the stage at diagnosis to earlier stages with more therapeutic options. Biomarkers can help to optimize the screening process, as well as refine the TNM stratification of lung cancer patients, providing information regarding prognostics and recommending management strategies. Moreover, novel adjuvant strategies will clearly benefit from previous knowledge of the potential aggressiveness and biological traits of a given early-stage surgically resected tumor. This review focuses on proteins as promising biomarkers in the context of lung cancer screening. Despite great efforts, there are still no successful examples of biomarkers in lung cancer that have reached the clinics to be used in early detection and early management. Thus, the field of biomarkers in early lung cancer remains an evident unmet need. A more specific objective of this review is to present an up-to-date technical assessment of the potential use of protein biomarkers in early lung cancer detection and management. We provide an overview regarding the benefits, challenges, pitfalls and constraints in the development process of protein-based biomarkers. Additionally, we examine how a number of emerging protein analytical technologies may contribute to the optimization of novel robust biomarkers for screening and effective management of lung cancer.

Acute-on-chronic liver failure (ACLF) has come a long way as a clinical concept within the hepatology and liver transplant communities. Though the term was proposed in 1995, the first recognition of the entity along with a consensus definition emerged in 2009. Subsequently, the entity has sparked great interest, inspired several consensus conferences, and inspired national societies to form professional ACLF affinity groups (eg, special interest group). Multicenter consortia have been established all over the world to study this condition, including the North American Consortium for the Study of End-Stage Liver Disease, Chronic Liver Failure consortium, Asian Pacific Association for the Study of Liver Diseases ACLF Research Consortium, Chronic Liver disease Evolution And Registry for Events and Decompensation, and the LiverHope Consortium. Collectively, these consortia have enrolled tens of thousands of patients with or at risk for ACLF across dozens of countries and characterized in detail the predictors, pathogenesis, and progression of patients with ACLF. Perhaps most importantly, they have produced essential data characterizing the excess morbidity and mortality that patients with ACLF face, making a compelling case for the urgent need for therapeutic strategies for this condition.

Bioactive substances found in plants, microorganisms and animals have fascinated mankind since time immemorial. This review will focus on the progress that has been made over the centuries and our growing insights. The developments relate to both the discovery and characterization of novel bioactive substances, as well as the ceaseless implementation of refined techniques, the use of high-end instruments and breakthroughs in artificial intelligence with deep learning-based computational methods. As these approaches possess great translational potential, with many applications in different fields, such as therapeutic, diagnostic and agrochemical use, there is a good rationale to continue investing in toxinology-related research.

OBJECTIVE: Plant-based diets are associated with a lower risk of chronic diseases. Large-scale proteomics can identify objective biomarkers of plant-based diets, and improve our understanding of the pathways that link plant-based diets to health outcomes. This study investigated the plasma proteome of four different plant-based diets [overall plant-based diet (PDI), provegetarian diet, healthful plant-based diet (hPDI), and unhealthful plant-based diet (uPDI)] in the Atherosclerosis Risk in Communities (ARIC) Study and replicated the findings in the Framingham Heart Study (FHS) Offspring cohort.
METHODS: ARIC Study participants at visit 3 (1993-1995) with completed food frequency questionnaire (FFQ) data and proteomics data were divided into internal discovery (n = 7690) and replication (n = 2543) data sets. Multivariable linear regression was used to examine associations between plant-based diet indices (PDIs) and 4955 individual proteins in the discovery sample. Then, proteins that were internally replicated in the ARIC Study were tested for external replication in FHS (n = 1358). Pathway overrepresentation analysis was conducted for diet-related proteins. C-statistics were used to predict if the proteins improved prediction of plant-based diet indices beyond participant characteristics.
RESULTS: In ARIC discovery, a total of 837 diet-protein associations (PDI = 233; provegetarian = 182; hPDI = 406; uPDI = 16) were observed at false discovery rate (FDR) < 0.05. Of these, 453 diet-protein associations (PDI = 132; provegetarian = 104; hPDI = 208; uPDI = 9) were internally replicated. In FHS, 167/453 diet-protein associations were available for external replication, of which 8 proteins (PDI = 1; provegetarian = 0; hPDI = 8; uPDI = 0) replicated. Complement and coagulation cascades, cell adhesion molecules, and retinol metabolism were over-represented. C-C motif chemokine 25 for PDI and 8 proteins for hPDI modestly but significantly improved the prediction of these indices individually and collectively (P value for difference in C-statistics<0.05 for all tests).
CONCLUSIONS: Using large-scale proteomics, we identified potential candidate biomarkers of plant-based diets, and pathways that may partially explain the associations between plant-based diets and chronic conditions.

Charles Bell was famous for the discovery of the separate motor and sensory roots of the spinal and facial nerves, although in recent years his right to priority has been challenged by historians and scientists. But Charles Bell did discover something even if has not been accorded the status of a scientific fact. Between 1821 and 1823 he unveiled the \'respiratory nervous system\', a distinct system of nerves that acted as the \'organ of the passions\', which he then elaborated upon in his 1824 Essays on the Anatomy and Philosophy of Expression. As Bell and his allies attempted to claim priority in the spinal and facial nerves, the respiratory nerves were pushed to the background, subordinated to the motor and sensory nerves. This essay, therefore, redefines Charles Bell\'s major discovery as the \'respiratory nerves\', providing a detailed description of their anatomy and physiology and the way in which they underwrote Bell\'s theory of the emotions. It also demonstrates how his aesthetics were intertwined with his research programme. It then connects the respiratory nerves to Thomas Dixon\'s assertion that Bell was one of the founders of the modern psychological category of the emotions, providing a deeper and more nuanced genealogy of the emotions, including the impact that Bell had upon William James\'s seminal article \'What is an Emotion?\'

The major human pathogen Streptococcus pneumoniae has been the subject of intensive clinical and basic scientific study for over 140 years. In multiple instances, these efforts have resulted in major breakthroughs in our understanding of basic biological principles as well as fundamental tenets of bacterial pathogenesis, immunology, vaccinology, and genetics. Discoveries made with S. pneumoniae have led to multiple major public health victories that have saved the lives of millions. Studies on S. pneumoniae continue today, where this bacterium is being used to dissect the impact of the host on disease processes, as a powerful cell biology model, and to better understand the consequence of human actions on commensal bacteria at the population level. Herein we review the major findings, i.e., puzzle pieces, made with S. pneumoniae and how, over the years, they have come together to shape our understanding of this bacterium\'s biology and the practice of medicine and modern molecular biology.

Currently, millions of drugs and their licence have been expired or will be expiring in near future. Therefore, existing USFDA approved drug can be used for treating another disease. The above-mentioned approach falls under the category of drug repurposing. Drug repurposing is an alternative strategy for finding new applications of existing USFDA approved drugs. Identification of a novel drug target is one of the go to way for drug repurposing so that new therapeutic applications of USFDA approved drugs could be determined. Recent advances in computational biology and bioinformatics can help to accelerate the same. Drug repurposing can save time and resource as compared to discovery of an entirely new drug molecule. In this chapter, we explore different strategies for discovery of a novel drug target and its uses for drug repurposing to treat disease.

The Internet of Things (IoT) includes billions of sensors and actuators (which we refer to as IoT devices) that harvest data from the physical world and send it via the Internet to IoT applications to provide smart IoT services and products. Deploying, managing, and maintaining IoT devices for the exclusive use of an individual IoT application is inefficient and involves significant costs and effort that often outweigh the benefits. On the other hand, enabling large numbers of IoT applications to share available third-party IoT devices, which are deployed and maintained independently by a variety of IoT device providers, reduces IoT application development costs, time, and effort. To achieve a positive cost/benefit ratio, there is a need to support the sharing of third-party IoT devices globally by providing effective IoT device discovery, use, and pay between IoT applications and third-party IoT devices. A solution for global IoT device sharing must be the following: (1) scalable to support a vast number of third-party IoT devices, (2) interoperable to deal with the heterogeneity of IoT devices and their data, and (3) IoT-owned, i.e., not owned by a specific individual or organization. This paper surveys existing techniques that support discovering, using, and paying for third-party IoT devices. To ensure that this survey is comprehensive, this paper presents our methodology, which is inspired by Systematic Literature Network Analysis (SLNA), combining the Systematic Literature Review (SLR) methodology with Citation Network Analysis (CNA). Finally, this paper outlines the research gaps and directions for novel research to realize global IoT device sharing.

BACKGROUND: Decision-making in healthcare is increasingly complex; notably in hospital environments where the information density is high, e.g., emergency departments, oncology departments, and psychiatry departments. This study aims to discover decisions from logged data to improve the decision-making process.
METHODS: The Design Science Research Methodology (DSRM) was chosen to design an artifact (algorithm) for the discovery and visualization of decisions. The DSRM\'s different activities are explained, from the definition of the problem to the evaluation of the artifact. During the design and development activities, the algorithm itself is created. During the demonstration and evaluation activities, the algorithm was tested with an authentic synthetic dataset.
RESULTS: The results show the design and simulation of an algorithm for the discovery and visualization of decisions. A fuzzy classifier algorithm was adapted for (1) discovering decisions from a decision log and (2) visualizing the decisions using the Decision Model and Notation standard.
CONCLUSIONS: In this paper, we show that decisions can be discovered from a decision log and visualized for the improvement of the decision-making process of healthcare professionals or to support the periodic evaluation of protocols and guidelines.