ABSTRACT
Background/Aims@#The interstitial cells of Cajal (ICC) are located within and around the digestive tract’s muscle layers. They function as intestinal muscle pacemakers and aid in the modification of enteric neurotransmission. The appendix’s unique position requires an appropriate contraction pattern of its muscular wall to adequately evacuate its contents. We investigated the development and distribution of nervous structures and ICC in the human fetal appendix. @*Methods@#Specimens were exposed to anti-c-kit (CD117) antibodies to investigate ICC differentiation. Enteric plexuses were examined using antineuron-specific enolase, and the differentiation of smooth muscle cells was studied with anti-desmin antibodies. @*Results@#During weeks 13-14, numerous myenteric plexus ganglia form an almost uninterrupted sequence throughout the body and apex of the appendix. Fewer ganglia were present at the submucosal border of the circular muscle layer and within this layer. A large number of ganglia appear within the circular and longitudinal muscle layers in a later fetal period. The first ICC subtypes noted were of the myenteric plexus and the submucous plexus. In the later fetal period, the number of intramuscular ICC markedly rises, and this subtype becomes predominant. @*Conclusions@#The ICC and nervous structure distribution in the human fetal appendix are significantly different from all other parts of the small and large intestine. The organization of ICC and the enteric nervous system provides the basis for the specific contraction pattern of the muscular wall of the appendix.
ABSTRACT
The coronavirus disease 2019 (COVID-19) pandemic, caused by Severe Acute Respiratory Syndrome (SARS)-CoV-2, continues to burden medical institutions around the world by increasing total hospitalization and Intensive Care Unit (ICU) admissions1-9 A better understanding of symptoms, comorbidities and medication used for preexisting conditions in patients with COVID-19 could help healthcare workers identify patients at increased risk of developing more severe disease10,11. Here, we have used self-reported data (symptoms, medications and comorbidities) from more than 3 million users from the COVID-19 Symptom Tracker app12 to identify previously reported and novel features predictive of patients being admitted in a hospital setting. Despite previously reported association between age and more severe disease phenotypes13-18, we found that patients age, sex and ethnic group were minimally predictive when compared to patients symptoms and comorbidities. The most important variables selected by our predictive algorithm were fever, the use of immunosuppressant medication, mobility aid, shortness of breath and fatigue. It is anticipated that early administration of preventative measures in COVID-19 positive patients (COVID+) who exhibit a high risk of hospitalization signature may prevent severe disease progression.
ABSTRACT
BackgroundThe global COVID-19 pandemic has caused worldwide disruption with its exponential spread mandating national and international lockdown measures. Hospital-associated transmission has been identified as a major factor in the perpetuation of COVID-19, with healthcare workers at high-risk of becoming infected with SARS-CoV-2 and representing important vectors for spread, but not routinely having their clinical observations monitored or being tested for COVID-19. MethodsA single-center, prospective observational study of 60 healthcare workers will explore how many healthcare workers in high-risk areas develop COVID-19 infection over a thirty day period. High-risk areas are defined as COVID positive wards, the intensive care unit or the accident and emergency department. Healthcare workers (HCWs) will be recruited and have daily self-administered nasopharyngeal SARS-CoV-2 PCR tests. They will also be provided with a wearable medical device to measure their clinical observations during non-working hours, and be asked to complete a daily self-reported symptom questionnaire over the study period. Statistical analysis will assess the proportion of healthcare workers who develop COVID-19 infection as a primary objective, with secondary objectives exploring what symptoms are developed, time-to-event, and deviations in clinical observations. DiscussionAt present clinical observations, symptoms and COVID-19 PCR swabs are not routinely undertaken for healthcare workers. If the CEDiD (COVID-19 Early Detection in Doctors and Healthcare Workers) study is successful, it will provide useful information for workforce decisions in reducing hospital-associated transmission of COVID-19. The data will help in determining whether there are early warning signs for development of COVID-19 infections amongst healthcare workers and may contribute to the evidence base advocating for more regular testing of healthcare workers observations, symptoms and COVID-19 status. Trial registrationClinicalTrials.gov, NCT04363489. Registered on 27th July 2020
