Diabetic gastroparesis: Therapeutic options

Gastroparesis is a condition characterized by delayed gastric emptying and the most common known underlying cause is diabetes mellitus. Symptoms include nausea, vomiting, abdominal fullness, and early satiety, which impact to varying degrees on the patient’s quality of life. Symptoms and deficits do not necessarily relate to each other, hence despite significant abnormalities in gastric emptying, some individuals have only minimal symptoms and, conversely, severe symptoms do not always relate to measures of gastric emptying. Prokinetic agents such as metoclopramide, domperidone, and erythromycin enhance gastric motility and have remained the mainstay of treatment for several decades, despite unwanted side effects and numerous drug interactions. Mechanical therapies such as endoscopic pyloric botulinum toxin injection, gastric electrical stimulation, and gastrostomy or jejunostomy are used in intractable diabetic gastroparesis (DG), refractory to prokinetic therapies. Mitemcinal and TZP-101 are novel investigational motilin receptor and ghrelin agonists, respectively, and show promise in the treatment of DG. The aim of this review is to provide an update on prokinetic and mechanical therapies in the treatment of DG

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Management History: Issues and Ideas for Teaching and Research

This review examines the study of management history and discusses its role in management education. Management history provides a theoretical baseline, a historical perspective, and aframework for building and integrating knowledge. After examining issues in teaching and research, future needs and directions for management history are indicated.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Biometric Gait Recognition

Abstract. Psychological studies indicate that people have a small but statistically significant ability to recognize the gaits of individuals that they know. Recently, there has been much interest in machine vision systems that can duplicate and improve upon this human ability for application to biometric identification. While gait has several attractive properties as a biometric (it is unobtrusive and can be done with simple instrumentation), there are several confounding factors such as variations due to footwear, terrain, fatigue, injury, and passage of time. This paper gives an overview of the factors that affect both human and machine recognition of gaits, data used in gait and motion analysis, evaluation methods, existing gait and quasi gait recognition systems, and uses of gait analysis beyond biometric identification. We compare the reported recognition rates as a function of sample size for several published gait recognition systems.