The influence of a high and low vitamin content in nutrition.

In the bulk of experiments on animal feeding the Albino Rat has served as the experimental animal. It has been proved that any diet which brings about satisfactory growth in white rats will also cause a young child to grow satisfactorily. Therefore, much attention is given to the breeding of such rats for experimental and scientific use. In the earlier stages of experimental work it was found that a diet which contained sufficient protein material and which yielded the proper number of calories because of the fat, sugar, and starch present, was a satisfactory diet. Later investigations showed that animals fed on diets which corresponded in every respect to the diet mentioned above, did not thrive. The addition of certain mineral salts to the diet served to eliminate the trouble. This showed that a diet, in order to be adequate, must contain certain mineral salts in definite quantities. When the scientists began in intensive study of the protein substances from different sources, they found that they did not all possess the same food value. Some proteins produced normal growth and some did not. Due to this fact, to-day we divide the proteins into three groups – Complete, Partially complete, and Incomplete Proteins. If an animal is fed on a diet, of which the protein quota is made from the incomplete proteins, it will not grow normally. A great many of our foods that nature gives us in abundance have present in them incomplete proteins. Up to this time nothing but the solid constituents of the diet, that is, the fats, carbohydrates and protein had been emphasized. However, the importance of the liquid side of the diet came gradually to be appreciated. Water was quite essential for life and is of material assistance in the body processes as digestion, absorption, and excretion. Through a series of years and by means of many carefully controlled experiments the scientific opinion was to the effect that a diet was adequate if it consisted of the proper amount and kind of carbohydrate, protein, fats, mineral and water. It did not take long, however, for experimenters to find out that diets made up according to the above standard did not always yield satisfactory results. Quite a bit of work was done in these years and there were times when one scientist could not verify the results of another scientist. Finally, in recent years and after much research, it was definitely decided that normal growth could not be obtained on the above mentioned diet. In order that an animal should show normal growth and be free from certain disorders, its diet must contain certain substances which are called accessory food substances or vitamins

Navigating Post-Disaster Repair and Reconstruction

The pressure to rebuild after a disaster can be fierce and unrelenting. Colleges and universities impacted by an event will be pushed to re-open the doors and resume teaching and research quickly. What are the factors to consider? How do you balance the lost revenues, damage to research, faculty pay requirements, housing of students, temporary facilities and alternative transportation, communication, housing, lecture space, research and administrative computing needs? It’s in the best interest of your institution to have a plan for how these repairs or reconstruction efforts will be funded. In addition to the issues of re-engagement you also need to understand the Federal Emergency Management Agency’s (FEMA) Public Assistance Program requirements for reimbursement and eligibility. While FEMA’s program offers reimbursements to most colleges and universities, it comes with requirements and restrictions that need to be understood in order to protect your institution’s investment and assure maximum return on investments. This session will cover the common challenges faced by program participants and offer suggestions on how to avoid common pitfalls. Learning outcomes: Awareness of FEMA’s Public Assistance Program and relevancy to colleges and universities Understanding of common challenges faced by colleges and universities in participating in the program Ideas on how to plan for the financial recovery aspects of disaste

Dilatonic global strings

We examine the field equations of a self-gravitating global string in low energy superstring gravity, allowing for an arbitrary coupling of the global string to the dilaton. Massive and massless dilatons are considered. For the massive dilaton the spacetime is similar to the recently discovered non-singular time-dependent Einstein self-gravitating global string, but the massless dilaton generically gives a singular spacetime, even allowing for time-dependence. We also demonstrate a time-dependent non-singular string/anti-string configuration, in which the string pair causes a compactification of two of the spatial dimensions, albeit on a very large scale.Comment: 18 pages RevTeX, 3 figures, references amende

Vortices and black holes in dilatonic gravity

We study analytically black holes pierced by a thin vortex in dilatonic gravity for an arbitrary coupling of the vortex to the dilaton in an arbitrary frame. We show that the horizon of the charged black hole supports the long-range fields of the Nielsen-Olesen vortex that can be considered as black hole hair for both massive and massless dilatons. We also prove that extremal black holes exhibit a flux expulsion phenomenon for a sufficiently thick vortex. We consider the gravitational back-reaction of the thin vortex on the spacetime geometry and dilaton, and discuss under what circumstances the vortex can be used to smooth out the singularities in the dilatonic C-metrics. The effect of the vortex on the massless dilaton is to generate an additional dilaton flux across the horizon.Comment: 16 pages revtex, published versio

American Gut: an Open Platform for Citizen Science Microbiome Research

McDonald D, Hyde E, Debelius JW, et al. American Gut: an Open Platform for Citizen Science Microbiome Research. mSystems. 2018;3(3):e00031-18

Leading to sustainable organizational unit performance: Antecedents and outcomes of executives' dual innovation leadership

According to ambidexterity theory, organizations must encourage innovation and ensure efficiency to achieve sustained organizational performance. Innovation scholars generally agree that leadership is a key determinant of innovation success, yet it remains unclear whether leader behaviors geared to drive innovation also contribute to efficiency. Building on research on leadership and innovation, we introduce executives' dual innovation leadership, consisting of two leader behaviors: fostering idea generation and fostering idea realization. The results from structural equation modeling, with data from 194 executives collected at two points in time, indicate the distinct impacts of fostering idea generation versus fostering idea realization on ambidextrous organizational unit outcomes. Moreover, the results reveal the relevance of executives' goal orientations as drivers of engagement in dual innovation leadership. The insights underscore the importance of refining existing leadership constructs in innovation contexts and provide implications for researchers and practitioners on how leadership can promote ambidextrous organizational outcomes

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients

Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death