DeepCare: A Deep Dynamic Memory Model for Predictive Medicine

Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, recorded in electronic medical records, are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors in space, models patient health state trajectories through explicit memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces time parameterizations to handle irregular timed events by moderating the forgetting and consolidation of memory cells. DeepCare also incorporates medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden -- diabetes and mental health -- the results show improved modeling and risk prediction accuracy.Comment: Accepted at JBI under the new name: "Predicting healthcare trajectories from medical records: A deep learning approach

Outcome analysis of intracorneal ring segments for the treatment of keratoconus based on visual, refractive, and aberrometric impairment

PURPOSE: To analyze the outcomes of intracorneal ring segment (ICRS) implantation for the treatment of keratoconus based on preoperative visual impairment. DESIGN: Multicenter, retrospective, nonrandomized study. METHODS: A total of 611 eyes of 361 keratoconic patients were evaluated. Subjects were classified according to their preoperative corrected distance visual acuity (CDVA) into 5 different groups: grade I, CDVA of 0.90 or better; grade II, CDVA equal to or better than 0.60 and worse than 0.90; grade III, CDVA equal to or better than 0.40 and worse than 0.60; grade IV, CDVA equal to or better than 0.20 and worse than 0.40; and grade plus, CDVA worse than 0.20. Success and failure indices were defined based on visual, refractive, corneal topographic, and aberrometric data and evaluated in each group 6 months after ICRS implantation. RESULTS: Significant improvement after the procedure was observed regarding uncorrected distance visual acuity in all grades (P < .05). CDVA significantly decreased in grade I (P < .01) but significantly increased in all other grades (P < .05). A total of 37.9% of patients with preoperative CDVA 0.6 or better gained 1 or more lines of CDVA, whereas 82.8% of patients with preoperative CDVA 0.4 or worse gained 1 or more lines of CDVA (P < .01). Spherical equivalent and keratometry readings showed a significant reduction in all grades (P ≤ .02). Corneal higher-order aberrations did not change after the procedure (P ≥ .05). CONCLUSIONS: Based on preoperative visual impairment, ICRS implantation provides significantly better results in patients with a severe form of the disease. A notable loss of CDVA lines can be expected in patients with a milder form of keratoconus

Dynamical Boson Stars

The idea of stable, localized bundles of energy has strong appeal as a model for particles. In the 1950s John Wheeler envisioned such bundles as smooth configurations of electromagnetic energy that he called {\em geons}, but none were found. Instead, particle-like solutions were found in the late 1960s with the addition of a scalar field, and these were given the name {\em boson stars}. Since then, boson stars find use in a wide variety of models as sources of dark matter, as black hole mimickers, in simple models of binary systems, and as a tool in finding black holes in higher dimensions with only a single killing vector. We discuss important varieties of boson stars, their dynamic properties, and some of their uses, concentrating on recent efforts.Comment: 79 pages, 25 figures, invited review for Living Reviews in Relativity; major revision in 201

Visual, Motor and Attentional Influences on Proprioceptive Contributions to Perception of Hand Path Rectilinearity during Reaching

We examined how proprioceptive contributions to perception of hand path straightness are influenced by visual, motor and attentional sources of performance variability during horizontal planar reaching. Subjects held the handle of a robot that constrained goal-directed movements of the hand to the paths of controlled curvature. Subjects attempted to detect the presence of hand path curvature during both active (subject driven) and passive (robot driven) movements that either required active muscle force production or not. Subjects were less able to discriminate curved from straight paths when actively reaching for a target versus when the robot moved their hand through the same curved paths. This effect was especially evident during robot-driven movements requiring concurrent activation of lengthening but not shortening muscles. Subjects were less likely to report curvature and were more variable in reporting when movements appeared straight in a novel “visual channel” condition previously shown to block adaptive updating of motor commands in response to deviations from a straight-line hand path. Similarly, compromised performance was obtained when subjects simultaneously performed a distracting secondary task (key pressing with the contralateral hand). The effects compounded when these last two treatments were combined. It is concluded that environmental, intrinsic and attentional factors all impact the ability to detect deviations from a rectilinear hand path during goal-directed movement by decreasing proprioceptive contributions to limb state estimation. In contrast, response variability increased only in experimental conditions thought to impose additional attentional demands on the observer. Implications of these results for perception and other sensorimotor behaviors are discussed

Serotype-specific mortality from invasive Streptococcus pneumoniae disease revisited

BACKGROUND: Invasive infection with Streptococcus pneumoniae (pneumococci) causes significant morbidity and mortality. Case series and experimental data have shown that the capsular serotype is involved in the pathogenesis and a determinant of disease outcome. METHODS: Retrospective review of 464 cases of invasive disease among adults diagnosed between 1990 and 2001. Multivariate Cox proportional hazard analysis. RESULTS: After adjustment for other markers of disease severity, we found that infection with serotype 3 was associated with an increased relative risk (RR) of death of 2.54 (95% confidence interval (CI): 1.22–5.27), whereas infection with serotype 1 was associated with a decreased risk of death (RR 0.23 (95% CI, 0.06–0.97)). Additionally, older age, relative leucopenia and relative hypothermia were independent predictors of mortality. CONCLUSION: Our study shows that capsular serotypes independently influenced the outcome from invasive pneumococcal disease. The limitations of the current polysaccharide pneumococcal vaccine warrant the development of alternative vaccines. We suggest that the virulence of pneumococcal serotypes should be considered in the design of novel vaccines

Detrended Fluctuation Analysis in the prediction of type 2 diabetes mellitus in patients at risk: Model optimization and comparison with other metrics

[EN] Complexity analysis of glucose time series with Detrended Fluctuation Analysis (DFA) has been proved to be useful for the prediction of type 2 diabetes mellitus (T2DM) development. We propose a modified DFA algorithm, review some of its characteristics and compare it with other metrics derived from continuous glucose monitorization in this setting. Several issues of the DFA algorithm were evaluated: (1) Time windowing: the best predictive value was obtained including all time-windows from 15 minutes to 24 hours. (2) Influence of circadian rhythms: for 48-hour glucometries, DFA alpha scaling exponent was calculated on 24hour sliding segments (1-hour gap, 23-hour overlap), with a median coefficient of variation of 3.2%, which suggests that analysing time series of at least 24-hour length avoids the influence of circadian rhythms. (3) Influence of pretreatment of the time series through integration: DFA without integration was more sensitive to the introduction of white noise and it showed significant predictive power to forecast the development of T2DM, while the pretreated time series did not. (4) Robustness of an interpolation algorithm for missing values: The modified DFA algorithm evaluates the percentage of missing values in a time series. Establishing a 2% error threshold, we estimated the number and length of missing segments that could be admitted to consider a time series as suitable for DFA analysis. For comparison with other metrics, a Principal Component Analysis was performed and the results neatly tease out four different components. The first vector carries information concerned with variability, the second represents mainly DFA alpha exponent, while the third and fourth vectors carry essentially information related to the two "pre-diabetic behaviours" (impaired fasting glucose and impaired glucose tolerance). The scaling exponent obtained with the modified DFA algorithm proposed has significant predictive power for the development of T2DM in a high-risk population compared with other variability metrics or with the standard DFA algorithm.This study has been funded by Instituto de Salud Carlos III through the project PI17/00856 (Co-funded by the European Regional Development Fund, A way to make Europe). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Colás, A.; Vigil, L.; Vargas, B.; Cuesta Frau, D.; Varela, M. (2019). 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Experimental Evolution of Resistance to Artemisinin Combination Therapy Results in Amplification of the mdr1 Gene in a Rodent Malaria Parasite

Background: Lacking suitable alternatives, the control of malaria increasingly depends upon Artemisinin Combination Treatments (ACT): resistance to these drugs would therefore be disastrous. For ACTs, the biology of resistance to the individual components has been investigated, but experimentally induced resistance to component drugs in combination has not been generated. Methodology/Principal Findings: We have used the rodent malaria parasite Plasmodium chabaudi to select in vivo resistance to the artesunate (ATN) + mefloquine (MF) version of ACT, through prolonged exposure of parasites to both drugs over many generations. The selection procedure was carried out over twenty-seven consecutive sub-inoculations under increasing ATN + MF doses, after which a genetically stable resistant parasite, AS-ATNMF1, was cloned. AS-ATNMF1 showed increased resistance to ATN + MF treatment and to artesunate or mefloquine administered separately. Investigation of candidate genes revealed an mdr1 duplication in the resistant parasites and increased levels of mdr1 transcripts and protein. There were no point mutations in the atpase6 or ubp1genes. Conclusion: Resistance to ACTs may evolve even when the two drugs within the combination are taken simultaneously and amplification of the mdr1 gene may contribute to this phenotype. However, we propose that other gene(s), as ye

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT