Forecasting severe respiratory disease hospitalizations using machine learning algorithms.

Background: Forecasting models predicting trends in hospitalization rates have the potential to inform hospital management during seasonal epidemics of respiratory diseases and the associated surges caused by acute hospital admissions. Hospital bed requirements for elective surgery could be better planned if it were possible to foresee upcoming peaks in severe respiratory illness admissions. Forecasting models can also guide the use of intervention strategies to decrease the spread of respiratory pathogens and thus prevent local health system overload.

Advancements in biotransformation pathway prediction: enhancements, datasets, and novel functionalities in enviPath.

enviPath is a widely used database and prediction system for microbial biotransformation pathways of primarily xenobiotic compounds. Data and prediction system are freely available both via a web interface and a public REST API. Since its initial release in 2016, we extended the data available in enviPath and improved the performance of the prediction system and usability of the overall system.

Subclinical maternal autoimmune disease leading to congenital high degree atrioventricular block: Case report and review of the literature.

Maternal autoimmune disease is the most common cause of congenital heart block (CHB), a rare illness characterized by fibrosis and calcification of the fetal atrioventricular (AV) node due to maternal autoantibodies anti-SSA/Ro and anti-SSB/La. We report the full autopsy and clinical information on a female neonate with high degree AV block and calcification in the AV node, atrial approaches to the AV node, and both right and left bundle branches, born to a 27-year-old female with subclinical autoimmune disease.

AdductHunter: identifying protein-metal complex adducts in mass spectra.

Mass spectrometry (MS) is an analytical technique for molecule identification that can be used for investigating protein-metal complex interactions. Once the MS data is collected, the mass spectra are usually interpreted manually to identify the adducts formed as a result of the interactions between proteins and metal-based species. However, with increasing resolution, dataset size, and species complexity, the time required to identify adducts and the error-prone nature of manual assignment have become limiting factors in MS analysis.

Stellar scintillation statistics and the impact of aperture averaging on space-to-ground optical communications.

Statistical probability distributions characterizing received optical power fluctuations, or scintillation, enable performance predictions of space-to-ground optical communication systems. In this paper, we present measurements of stellar scintillation over a wide range of elevation angles and turbulence conditions collected simultaneously with a 5 cm and 40 cm telescope aperture, which allows a comparison between minimal and significant aperture averaging conditions. The measured data is compared to a reasonable set of candidate probability distribution functions (PDFs), including lognormal, which is most often cited in the literature for weak to moderate scintillation.

De novo network analysis reveals autism causal genes and developmental links to co-occurring traits.

Autism is a complex neurodevelopmental condition that manifests in various ways. Autism is often accompanied by other conditions, such as attention-deficit/hyperactivity disorder and schizophrenia, which can complicate diagnosis and management. Although research has investigated the role of specific genes in autism, their relationship with co-occurring traits is not fully understood.

Combatting over-specialization bias in growing chemical databases.

Background: Predicting in advance the behavior of new chemical compounds can support the design process of new products by directing the research toward the most promising candidates and ruling out others. Such predictive models can be data-driven using Machine Learning or based on researchers' experience and depend on the collection of past results. In either case: models (or researchers) can only make reliable assumptions about compounds that are similar to what they have seen before.

Predictors and Hospital Outcomes in Pregnant Patients Undergoing Extracorporeal Membrane Oxygenation: A Nationwide Study.

Background: Extracorporeal membrane oxygenation (ECMO) is increasingly used in patients with severe cardiorespiratory collapse. Although prior large database reviews of ECMO use in the peripartum population exist, they do not stratify by ECMO indication nor do they include obstetric conditions such as preeclampsia. Our objective was to characterize the incidence, indication-associated mortality, and factors associated with mortality in pregnant patients who underwent ECMO.

A pediatric case of xanthogranulomatous pyelonephritis in the setting of Covid-19 and multi-system inflammatory syndrome (MIS-C).

Xanthogranulmatous pyelonephritis is a rare, chronic inflammatory pathology of the kidney. It most commonly arises in middle-aged females, but there are case reports and series described in the pediatric population. Here, we discuss the case of a 14 year old male who presented with xanthogranulomatous pyelonephritis in the setting of Covid-19 and multi-system inflammatory syndrome (MIS-C).

K-8 Classroom Self-Collection Using XpressCollect Nasal Swab: A Usability and Efficacy Study.

This study demonstrates that students in kindergarten through eighth grade can use the XpressCollect nasal swab to self-collect a specimen under the guidance of a teacher. This phased study was conducted with parents, teachers, and students. Phases 1 and 2 were conducted as interviews with teachers and parents to assess the suitability of the XpressCollect for children in kindergarten through eighth grade.

A Novel Approach for Time Series Forecasting of Influenza-like Illness Using a Regression Chain Method.

Influenza is a communicable respiratory illness that can cause serious public health hazards. Due to its huge threat to the community, accurate forecasting of Influenza-like-illness (ILI) can diminish the impact of an influenza season by enabling early public health interventions. Machine learning models are increasingly being applied in infectious disease modelling, but are limited in their performance, particularly when using a longer forecasting window.

Holistic evaluation of biodegradation pathway prediction: assessing multi-step reactions and intermediate products.

The prediction of metabolism and biotransformation pathways of xenobiotics is a highly desired tool in environmental sciences, drug discovery, and (eco)toxicology. Several systems predict single transformation steps or complete pathways as series of parallel and subsequent steps. Their performance is commonly evaluated on the level of a single transformation step.

Re-envisioning health promotion: Thinking and acting salutogenically towards equity for historically resilient communities.

This paper explores how the salutogenic theory can enable us to re-envision health promotion work with marginalized communities, towards an approach that acknowledges and honours their resilience. We use the three core concepts in Antonovsky's salutogenic model of health - sense of coherence, generalized resistance resources and specific resistance resources - to explore the theory's relevance to health equity, thus presenting new opportunities for how we might radically re-evaluate current health promotion approaches. We conclude that a more equitable health promotion requires increased participation of marginalized communities in shaping their futures and suggest a new model for historically grounded salutogenic health promotion.

A comprehensive comparison of molecular feature representations for use in predictive modeling.

Machine learning methods are commonly used for predicting molecular properties to accelerate material and drug design. An important part of this process is deciding how to represent the molecules. Typically, machine learning methods expect examples represented by vectors of values, and many methods for calculating molecular feature representations have been proposed.

Black Lives Matter in health promotion: moving from unspoken to outspoken.

Racism is a public health crisis. Black communities (including Africans, the African diaspora and people of African descent) experience worse health outcomes as demonstrated by almost any measure of health and wellbeing-e.g.

A machine learning approach to quantify the specificity of colour-emotion associations and their cultural differences.

The link between colour and emotion and its possible similarity across cultures are questions that have not been fully resolved. Online, 711 participants from China, Germany, Greece and the UK associated 12 colour terms with 20 discrete emotion terms in their native languages. We propose a machine learning approach to quantify (a) the consistency and specificity of colour-emotion associations and (b) the degree to which they are country-specific, on the basis of the accuracy of a statistical classifier in (a) decoding the colour term evaluated on a given trial from the 20 ratings of colour-emotion associations and (b) predicting the country of origin from the 240 individual colour-emotion associations, respectively.

Optical communications downlink from a low-earth orbiting 1.5U CubeSat.

In this article, we present the first demonstration of an optical communications downlink from a low-earth orbiting free-flying CubeSat. Two 1.5U vehicles, AC7-B&C, built under NASA's Optical Communications and Sensors Demonstration (OCSD) program were launched in November 2017 and subsequently placed into a 450-km, 51.

A survey of practice of rapid sequence induction for caesarean section in England.

Background: In view of newer techniques of preoxygenation and laryngoscopy and recent obstetric guidelines concerning the management of difficult intubation, we aimed to evaluate the current practice of rapid sequence induction for caesarean section in England.

Methods: In 2017, 316 questionnaire surveys were posted to all 158 hospitals with caesarean section capabilities in England. At each hospital, one questionnaire was to be completed by the obstetric anaesthetic consultant lead and one by an anaesthetic trainee.

Proof of concept study: Testing human volatile organic compounds as tools for age classification of films.

Humans emit numerous volatile organic compounds (VOCs) through breath and skin. The nature and rate of these emissions are affected by various factors including emotional state. Previous measurements of VOCs and CO2 in a cinema have shown that certain chemicals are reproducibly emitted by audiences reacting to events in a particular film.

TLE1 Expression in Malignant Rhabdoid Tumor and Atypical Teratoid/Rhabdoid Tumor.

Malignant rhabdoid tumors (MRT; atypical teratoid/rhabdoid tumor [ATRT] in the central nervous system) are aggressive tumors in infants and children which can overlap with other sarcomas, such as synovial sarcoma (SS). The gold standard for SS diagnosis is characterization of the t(X;18) chromosomal translocation. However, stratification of cases for molecular analysis is not always straightforward or feasible.

Xeroderma Pigmentosum Group C Deficiency Alters Cigarette Smoke DNA Damage Cell Fate and Accelerates Emphysema Development.

Cigarette smoke (CS) exposure is a major risk factor for the development of emphysema, a common disease characterized by loss of cells comprising the lung parenchyma. The mechanisms of cell injury leading to emphysema are not completely understood but are thought to involve persistent cytotoxic or mutagenic DNA damage induced by CS. Using complementary cell culture and mouse models of CS exposure, we investigated the role of the DNA repair protein, xeroderma pigmentosum group C (XPC), on CS-induced DNA damage repair and emphysema.