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To characterize bacterial infections and antibiotic utilization in hospitalized cancer patients with coronavirus disease 2019 (COVID-19).
Retrospective cohort study.
Tertiary cancer center in New York City.
Hospitalized cancer patients ≥18 years with COVID-19 between March 1, 2020, and May 31, 2020.
Patients were classified with mild COVID-19 (ie, with room air), moderate COVID-19 (ie, using nasal cannula oxygen), or severe COVID-19 (ie, using high-flow oxygen or mechanical ventilation). The primary outcome was bacterial infection rate within 30 days of COVID-19 onset. Secondary outcomes included the proportion of patients receiving antibiotics and antibiotic length of therapy (LOT).
Of 358 study patients, 133 had mild COVID-19, 97 had moderate COVID-19, and 128 had severe COVID-19. Of 358 patients, 234 (65%) had a solid tumor. Also, 200 patients (56%) had 245 bacterial infections, of which 67 (27%) were microbiologically confirmed. The proportion of patients with bacterial infection increased with COVID-19 severity: mild (n = 47, 35%) versus moderate (n = 49, 51%) versus severe (n = 104, 81%) (P < .0001). Also, 274 (77%) received antibiotics for a median of 4 days. The median antibiotic LOTs were 7 days with 1 infection and 20 days with multiple infections (P < .0001). Antibiotic durations were 1 day for patients with mild COVID-19, 4 days for patients with moderate COVID-19, and 8 days for patients with severe COVID-19 (P < .0001).
Hospitalized cancer patients with COVID-19 had a high rate of bacterial infection. As COVID-19 severity increased, the proportion of patients diagnosed with bacterial infection and given antibiotics increased. In mild COVID-19 cases, antibiotic LOT was short, suggesting that empiric antibiotics can be safely avoided or discontinued in this group.
Introduction: Technological Advancement and Human Dignity
Given the rapid technological growth of artificial intelligence (AI) through advancements in machine learning, what was once thought impossible is quickly becoming a reality. It is no longer so far-fetched that humanlike machines will soon be a part of everyday life. People today are divided on whether these continued advancements in AI technologies will lead to the best of times or the worst of times for humankind. History continues to teach that a utopian or dystopian future is largely determined by a society's ability to identify and defend human dignity. Given AI's potential for dehumanization, if we are to avoid the mistakes of our past, our future will depend on people's ability to correctly see the difference between machines and humans.
By developing the work of Michael Polanyi and Alan Turing, the following chapter challenges reductionist perspectives in AI studies that are dehumanizing and explores an alternative foundation that can help navigate the technological future, while upholding the inherent dignity of being human. First (Section 1), a brief history of AI's ontological development is developed within Polanyi and Turing's interactions through tacit knowledge and the imitation game. Second (Section 2), it is demonstrated that Turing's imitation game, as expressed in strong AI, undermines the inherent nature of dignity in that it is intrinsically dehumanizing. Third (Section 3), Polanyi's machine ontology is developed as an alternative to the imitation game. Fourth (Section 4), Polanyi's non-reductive approach is contrasted with Turing's reductive approach to explore which best provides a foundation for the nature of human dignity.
Artificial Intelligence: Polanyi vs. Turing's Machine Ontology
For a time, Michael Polanyi and Alan Turing both worked at Manchester University in the United Kingdom. Polanyi was a scientist-turned-philosopher and Turing was a mathematician-turned-computer scientist. They both had a keen interest in AI studies and regularly discussed the philosophy of ‘intelligent machines’ (Hodges 2009, 13). Turing was focused on technological advancement, and Polanyi was concerned with the philosophies behind these advancements.
Navigators have been taught for centuries to estimate the location of their craft on a map from three lines of position, for redundancy. The three lines typically form a triangle, called a cocked hat. How is the location of the craft related to the triangle? For more than 80 years navigators have also been taught that, if each line of position is equally likely to pass to the right and to the left of the true location, then the likelihood that the craft is in the triangle is exactly 1/4. This is stated in numerous reputable sources, but was never stated or proved in a mathematically formal and rigorous fashion. In this paper we prove that the likelihood is indeed 1/4 if we assume that the lines of position always intersect pairwise. We also show that the result does not hold under weaker (and more reasonable) assumptions, and we prove a generalisation to $n$ lines.
Ghrelin showed antidepressant-like effects in mice. Furthermore, ghrelin influences sleep and the activity of hypothalamic-pituitary-adrenal (HPA) and somatotropic axis in healthy humans as indicated by increased cortisol and growth hormone (GH) plasma levels. Both sleep and the activity of these endocrine axes are disturbed in depression.
To study the effect of ghrelin on psychopathology, sleep and secretion of cortisol and GH in patients with major depression.
Depressive symptoms as assessed by a validated self rating scale (’Befindlichkeits-Skala’, [well-being scale]), secretion profiles of cortisol and GH and sleep-EEGs were determined in 14 unmedicated patients with major depression (7 women) twice, receiving 50 μg ghrelin or placebo at 2200, 2300, 0000, and 0100 hours.
Overall, depressive symptoms did not change significantly after ghrelin administration (placebo: 37 ± 8; ghrelin: 33 ± 10, p = 0.178). However, there was an improvement at trend level in men (placebo: 36 ± 9 to ghrelin: 30 ± 9, p = 0.093) but not in women. In men, ghrelin was associated with less time awake (placebo: 149.0 ± 11.1; ghrelin: 88.0±12.2 min, p = 0.029) and more non-REM sleep (placebo: 263.2 ± 24.1; ghrelin: 304.9 ± 14.1 min, p = 0.027), in women with less REM sleep (placebo: 108.6 ± 15.7; ghrelin: 74.1 ± 13.8 min, p = 0.031) and longer REM latency (placebo: 49.9 ± 6.5; ghrelin: 85.6 ± 14.1 min, p = 0.019). In both sexes, ghrelin caused strong transient increases of GH and cortisol.
Our study may provide an initial indication that ghrelin can exert antidepressant effects in patients with major depression. Ghrelin strongly affected sleep and secretion of GH and cortisol in a partly different way as previously reported in healthy subjects.
Sleep studies in patients with major depression receiving the new selective norepinephrine and serotonin reuptake inhibitor (SNRI) duloxetine are lacking.
Polysomnography in 10 patients with major depression (7 males, 39.9 ± 7.6 years, HAMD-21 score: 23.6 ± 5.6) was recorded twice, before and after 7-14 days of treatment with duloxetine.
A significant (p < 0.01) increase from baseline to endpoint was found for amount of stage 3 sleep (21.0 ± 10.7 to 37.4 ± 20.1 minutes) and REM latency (58.5 ± 31.1 to 193.6 ± 72.6 minutes). Amount of REM sleep significantly (p < 0.01) decreased from 94.8 ± 34.5 to 51.5 ± 42.5 minutes.
These results partly differ from those in healthy subjects receiving duloxetine.
Gene × environment (G × E) interactions in eating pathology have been increasingly investigated, however studies have been limited by sample size due to the difficulty of obtaining genetic data.
To synthesize existing G × E research in the eating disorders (ED) field and provide a clear picture of the current state of knowledge with analyses of larger samples.
Complete data from seven studies investigating community (n = 1750, 64.5% female) and clinical (n = 426, 100% female) populations, identified via systematic review, were included. Data were combined to perform five analyses: 5-HTTLPR × Traumatic Life Events (0–17 events) to predict ED status (n = 909), 5-HTTLPR × Sexual and Physical Abuse (n = 1097) to predict bulimic symptoms, 5-HTLPR × Depression to predict bulimic symptoms (n = 1256), and 5-HTTLPR × Impulsivity to predict disordered eating (n = 1149).
The low function (s) allele of 5-HTTLPR interacted with number of traumatic life events (P < .01) and sexual and physical abuse (P < .05) to predict increased likelihood of an ED in females but not males (Fig. 1). No other G × E interactions were significant, possibly due to the medium to low compatibility between datasets (Fig. 1).
Early promising results suggest that increased knowledge of G × E interactions could be achieved if studies increased uniformity of measuring ED and environmental variables, allowing for continued collaboration to overcome the restrictions of obtaining genetic samples.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
Organisms (fauna, flora and microorganisms) are components of the Earth that respond to but also affect their geomorphic environment. Indeed, most of Earth's landscapes are defined, at least partly, by biota (Goudie and Viles, 2010; Corenblit et al., 2011; Holtmeier, 2015; Phillips, 2016). The Earth Critical Zone (ECZ; i.e., “heterogeneous, near surface environment in which complex interactions involving rock, soil, water, air, and living organisms regulate the natural habitat and determine the availability of life-sustaining resources”; NRC, 2001) that concentrates most of life on Earth supports strong feedbacks between biota and abiota. Here, feedbacks relate to organisms’ effects upon their geomorphic environment and their responses to the modification they induce themselves on their geomorphic environment. The responses of the organisms to the changes of the geomorphic environment concern ecosystems at various levels, from genes to landscape via populations and communities.
Feedbacks between organisms and their physical environment within the ECZ is a focus for geomorphologists, ecologists and evolutionary biologists attempting to establish top-down and bottom-up eco-evolutionary connections between the different levels of ecosystems and their biotic and abiotic components. The goal of this chapter is to exemplify how feedbacks between organisms and geomorphology within stressful and disturbed environments can generate biogeomorphic ecosystems (sensu Balke et al., 2014 and Corenblit et al., 2015b). A biogeomorphic ecosystem is an ecosystem in which organisms and geomorphic components (i.e., surface matter and energy fluxes, landforms and soils) strongly interact and adjust reciprocally. Biogeomorphic ecosystems keep their integrity (form and function) under stressful and disturbed conditions within specific domains of stability from the feedbacks between organisms and their geomorphic environment. Stress is defined here as predictable external constraints which limit the rate of organic production (Grime, 2002); it relates for example to water deficit. A disturbance is defined as any relatively discrete event in time that disrupts ecosystem, community, or population structure and changes resources, substrate availability, or the physical environment (Pickett and White, 1985).
Disinhibition of REM sleep is a characteristic finding in patients with major depression. REM disinhibition includes shortened REM latency, prolonged first REM periods, and increased REM density (measure of the frequency of rapid eye movements). REM latency, but not REM density, is influenced by age. REM-sleep changes appear to be closely related to the development and the course of depression. A relationship between REM-sleep changes before treatment and treatment outcome is suggested by several studies. REM density is elevated in healthy subjects who have a high genetic load for affective disorders. Most antidepressants suppress REM sleep in patients, normal controls, and laboratory animals. REM-sleep suppression appears to be a distinct hint for the antidepressive properties of a substance, whereas it is not absolutely required. REM-sleep variables during treatment with antidepressants appear to predict the course of the illness. The noradrenergic locus coeruleus and the serotonergic dorsal raphe nuclei, the cholinergic nuclei, and the nucleus of the solitary tract (NTS) are involved in sleep and mood regulation. Hyperaldosteronism has been demonstrated in major depression. Subchronic aldosterone administration can induce anxiety-like behavior. Because of the unusual presence within the brain of both mineralocorticoid receptors and 11-β hydroxysteroid dehydrogenase (11-β HSD), the NTS can act as the gate of the influence of peripheral aldosterone into the brain. Importantly, aldosterone secretion is closely related to the REM/non-REM cycle and is sensitive to sleep manipulations. Hypersecretion of corticotropin-releasing hormone (CRH), the key hormone of the hypothalamo–pituitary–adrenocortical system appears to participate in the pathophysiology of REM-sleep disinhibition. This is supported by increased time spent in REM sleep in mice overexpressing corticotropin-releasing hormone (CRH) in the brain. Furthermore CRH-receptor-type 1 antagonism seems to induce normalization of the REM-sleep changes related to the depression.
A multiscale approach was adopted for the calculation of confined states in self-assembled semiconductor quantum dots (QDs). While results close to experimental data have been obtained with a combination of atomistic strain and tight-binding (TB) electronic structure description for the confined quantum states in the QD, the TB calculation requires substantial computational resources. To alleviate this problem an integrated approach was adopted to compute the energy states from a continuum 8-band k.p Hamiltonian under the influence of an atomistic strain field. Such multiscale simulations yield a roughly six-fold faster simulation. Atomic-resolution strain is added to the k.p Hamiltonian through interpolation onto a coarser continuum grid. Sufficient numerical accuracy is obtained by the multiscale approach. Optical transition wavelengths are within 7% of the corresponding TB results with a proper splitting of p-type sub-bands. The systematically lower emission wavelengths in k.p are attributable to an underestimation of the coupling between the conduction and valence bands.
This report is on activities of the Division at the General Assembly in Rio de Janeiro. Summaries of scientific activities over the past triennium have been published in Transactions A, see Melrose et al. (2008), Klimchuk et al. (2008), Martinez Pillet et al. (2008) and Bougeret et al. (2008). The business meeting of the three Commissions were incorporated into the business meeting of the Division. This report is based in part on minutes of the business meeting, provided by the Secretary of the Division, Lidia van Driel-Gesztelyi, and it also includes reports provided by the Presidents of the Commissions (C10, C12, C49) and of the Working Groups (WGs) in the Division.