Machine Learning Applications in the Neuro ICU: A Solution to Big Data Mayhem?

The neurological ICU (neuro ICU) often suffers from significant limitations due to scarce resource availability for their neurocritical care patients. Neuro ICU patients require frequent neurological evaluations, continuous monitoring of various physiological parameters, frequent imaging, and routine lab testing. This amasses large amounts of data specific to each patient. Neuro ICU teams are often overburdened by the resulting complexity of data for each patient. Machine Learning algorithms (ML), are uniquely capable of interpreting high-dimensional datasets that are too difficult for humans to comprehend. Therefore, the application of ML in the neuro ICU could alleviate the burden of analyzing big datasets for each patient. This review serves to (1) briefly summarize ML and compare the different types of MLs, (2) review recent ML applications to improve neuro ICU management and (3) describe the future implications of ML to neuro ICU management

The developmental effects of media-ideal internalization and self-objectification processes on adolescents’ negative body-feelings, dietary restraint, and binge eating

Despite accumulated experimental evidence of the negative effects of exposure to media-idealized images, the degree to which body image, and eating related disturbances are caused by media portrayals of gendered beauty ideals remains controversial. On the basis of the most up-to-date meta-analysis of experimental studies indicating that media-idealized images have the most harmful and substantial impact on vulnerable individuals regardless of gender (i.e., “internalizers” and “self-objectifiers”), the current longitudinal study examined the direct and mediated links posited in objectification theory among media-ideal internalization, self-objectification, shame and anxiety surrounding the body and appearance, dietary restraint, and binge eating. Data collected from 685 adolescents aged between 14 and 15 at baseline (47 % males), who were interviewed and completed standardized measures annually over a 3-year period, were analyzed using a structural equation modeling approach. Results indicated that media-ideal internalization predicted later thinking and scrutinizing of one’s body from an external observer’s standpoint (or self-objectification), which then predicted later negative emotional experiences related to one’s body and appearance. In turn, these negative emotional experiences predicted subsequent dietary restraint and binge eating, and each of these core features of eating disorders influenced each other. Differences in the strength of these associations across gender were not observed, and all indirect effects were significant. The study provides valuable information about how the cultural values embodied by gendered beauty ideals negatively influence adolescents’ feelings, thoughts and behaviors regarding their own body, and on the complex processes involved in disordered eating. Practical implications are discussed

Integrating Models of Diffusion and Behavior to Predict Innovation Adoption, Maintenance, and Social Diffusion

This study documents an investigation into the adoption and diffusion of eave tubes, a novel mosquito vector control, during a large-scale scientific field trial in West Africa. The diffusion of innovations (DOI) and the integrated model of behavior (IMB) were integrated (i.e., innovation attributes with attitudes and social pressures with norms) to predict participants’ (N = 329) diffusion intentions. The findings showed that positive attitudes about the innovation’s attributes were a consistent positive predictor of diffusion intentions: adopting it, maintaining it, and talking with others about it. As expected by the DOI and the IMB, the social pressure created by a descriptive norm positively predicted intentions to adopt and maintain the innovation. Drawing upon sharing research, we argued that the descriptive norm may dampen future talk about the innovation, because it may no longer be seen as a novel, useful topic to discuss. As predicted, the results showed that as the descriptive norm increased, the intention to talk about the innovation decreased. These results provide broad support for integrating the DOI and the IMB to predict diffusion and for efforts to draw on other research to understand motivations for social diffusion

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie

A three gene DNA methylation biomarker accurately classifies early stage prostate cancer

Background: We identify and validate accurate diagnostic biomarkers for prostate cancer through a systematic evaluation of DNA methylation alterations. Materials and methods: We assembled three early prostate cancer cohorts (total patients = 699) from which we collected and processed over 1300 prostatectomy tissue samples for DNA extraction. Using real-time methylation-specific PCR, we measured normalized methylation levels at 15 frequently methylated loci. After partitioning sample sets into independent training and validation cohorts, classifiers were developed using logistic regression, analyzed, and validated. Results: In the training dataset, DNA methylation levels at 7 of 15 genomic loci (glutathione S-transferase Pi 1 [GSTP1], CCDC181, hyaluronan, and proteoglycan link protein 3 [HAPLN3], GSTM2, growth arrest-specific 6 [GAS6], RASSF1, and APC) showed large differences between cancer and benign samples. The best binary classifier was the GAS6/GSTP1/HAPLN3 logistic regression model, with an area under these curves of 0.97, which showed a sensitivity of 94%, and a specificity of 93% after external validation. Conclusion: We created and validated a multigene model for the classification of benign and malignant prostate tissue. With false positive and negative rates below 7%, this three-gene biomarker represents a promising basis for more accurate prostate cancer diagnosis

Cytokine Combination Therapy with Erythropoietin and Granulocyte Colony Stimulating Factor in a Porcine Model of Acute Myocardial Infarction

PurposeErythropoietin (EPO) and granulocyte colony stimulating factor (GCSF) have generated interest as novel therapies after myocardial infarction (MI), but the effect of combination therapy has not been studied in the large animal model. We investigated the impact of prolonged combination therapy with EPO and GCSF on cardiac function, infarct size, and vascular density after MI in a porcine model.MethodsMI was induced in pigs by a 90&nbsp;min balloon occlusion of the left anterior descending coronary artery. 16 animals were treated with EPO+GCSF, or saline (control group). Cardiac function was assessed by echocardiography and pressure-volume measurements at baseline, 1 and 6&nbsp;weeks post-MI. Histopathology was performed 6&nbsp;weeks post-MI.ResultsAt week 6, EPO+GCSF therapy stabilized left ventricular ejection fraction, (41 ± 1% vs. 33 ± 1%, p &lt; 0.01) and improved diastolic function compared to the control group. Histopathology revealed increased areas of viable myocardium and vascular density in the EPO+GCSF therapy, compared to the control. Despite these encouraging results, in a historical analysis comparing combination therapy with monotherapy with EPO or GCSF, there were no significant additive benefits in the LVEF and volumes overtime using the combination therapy.ConclusionOur findings indicate that EPO+GCSF combination therapy promotes stabilization of cardiac function after acute MI. However, combination therapy does not seem to be superior to monotherapy with either EPO or GCSF

LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

Discrepancies between the medical record and the reports of patients with acute coronary syndrome regarding important aspects of the medical history

<p>Abstract</p> <p>Background</p> <p>Many critical treatment decisions are based on the medical history of patients with an acute coronary syndrome (ACS). Discrepancies between the medical history documented by a health professional and the patient's own report may therefore have important health consequences.</p> <p>Methods</p> <p>Medical histories of 117 patients with an ACS were documented. A questionnaire assessing the patient's health history was then completed by 62 eligible patients. Information about 13 health conditions with relevance to ACS management was obtained from the questionnaire and the medical record. Concordance between these two sources and reasons for discordance were identified.</p> <p>Results</p> <p>There was significant variation in agreement, from very poor in angina (kappa < 0) to almost perfect in diabetes (kappa = 0.94). Agreement was substantial in cerebrovascular accident (kappa = 0.76) and hypertension (kappa = 0.73); moderate in cocaine use (kappa = 0.54), smoking (kappa = 0.46), kidney disease (kappa = 0.52) and congestive heart failure (kappa = 0.54); and fair in arrhythmia (kappa = 0.37), myocardial infarction (kappa = 0.31), other cardiovascular diseases (kappa = 0.37) and bronchitis/pneumonia (kappa = 0.31). The odds of agreement was 42% higher among individuals with at least some college education (OR = 1.42; 95% CI, 1.00 - 2.01, p = 0.053). Listing of a condition in medical record but not in the questionnaire was a common cause of discordance.</p> <p>Conclusion</p> <p>Discrepancies in aspects of the medical history may have important effects on the care of ACS patients. Future research focused on identifying the most effective and efficient means to obtain accurate health information may improve ACS patient care quality and safety.</p

Operation Moonshot: rapid translation of a SARS-CoV-2 targeted peptide immunoaffinity liquid chromatography-tandem mass spectrometry test from research into routine clinical use

OBJECTIVES: During 2020, the UK's Department of Health and Social Care (DHSC) established the Moonshot programme to fund various diagnostic approaches for the detection of SARS-CoV-2, the pathogen behind the COVID-19 pandemic. Mass spectrometry was one of the technologies proposed to increase testing capacity. METHODS: Moonshot funded a multi-phase development programme, bringing together experts from academia, industry and the NHS to develop a state-of-the-art targeted protein assay utilising enrichment and liquid chromatography tandem mass spectrometry (LC-MS/MS) to capture and detect low levels of tryptic peptides derived from SARS-CoV-2 virus. The assay relies on detection of target peptides, ADETQALPQRK (ADE) and AYNVTQAFGR (AYN), derived from the nucleocapsid protein of SARS-CoV-2, measurement of which allowed the specific, sensitive, and robust detection of the virus from nasopharyngeal (NP) swabs. The diagnostic sensitivity and specificity of LC-MS/MS was compared with reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) via a prospective study. RESULTS: Analysis of NP swabs (n=361) with a median RT-qPCR quantification cycle (Cq) of 27 (range 16.7-39.1) demonstrated diagnostic sensitivity of 92.4% (87.4-95.5), specificity of 97.4% (94.0-98.9) and near total concordance with RT-qPCR (Cohen's Kappa 0.90). Excluding Cq>32 samples, sensitivity was 97.9% (94.1-99.3), specificity 97.4% (94.0-98.9) and Cohen's Kappa 0.95. CONCLUSIONS: This unique collaboration between academia, industry and the NHS enabled development, translation, and validation of a SARS-CoV-2 method in NP swabs to be achieved in 5 months. This pilot provides a model and pipeline for future accelerated development and implementation of LC-MS/MS protein/peptide assays into the routine clinical laboratory

Predicting the environmental suitability and population at risk of podoconiosis in Africa

Podoconiosis is a type of tropical lymphedema that causes massive swelling of the lower limbs. The disease is associated with both economic insecurity, due to long-term morbidity-related loss of productivity, and intense social stigma. The geographical distribution and burden of podoconiosis in Africa are uncertain. We applied statistical modelling to the most comprehensive database compiled to date to predict the environmental suitability of podoconiosis in the African continent. By combining climate and environmental data and overlaying population figures, we predicted the environmental suitability and human population at risk of podoconiosis in Africa. Environmental suitability for podoconiosis was predicted in 29 African countries. In the year 2020, the total population in areas suitable for podoconiosis is estimated at 114.5 million people, (95% uncertainty interval: 109.4–123.9) with 16.9 million in areas suitable for both lymphatic filariasis and podoconiosis. Of the total 5,712 implementation units (typically second administrative-level units, such as districts) defined by the World Health Organization in Africa, 1,655 (29.0%) were found to be environmentally suitable for podoconiosis. The majority of implementation units with high environmental suitability are located in Angola (80, 4.8%), Cameroon (170, 10.3%), the DRC (244, 14.7%), Ethiopia (495, 29.9%), Kenya (217, 13.1%), Uganda (116, 7.0%) and Tanzania (112, 6.8%). Of the 1,655 environmentally suitable implementation units, 960 (58.0%) require more detailed community-level mapping. Our estimates provide key evidence of the population at risk and geographical extent of podoconiosis in Africa, which will help decision-makers to better plan more integrated intervention programmes