Analyzing Collective Motion with Machine Learning and Topology

We use topological data analysis and machine learning to study a seminal model of collective motion in biology [D'Orsogna et al., Phys. Rev. Lett. 96 (2006)]. This model describes agents interacting nonlinearly via attractive-repulsive social forces and gives rise to collective behaviors such as flocking and milling. To classify the emergent collective motion in a large library of numerical simulations and to recover model parameters from the simulation data, we apply machine learning techniques to two different types of input. First, we input time series of order parameters traditionally used in studies of collective motion. Second, we input measures based in topology that summarize the time-varying persistent homology of simulation data over multiple scales. This topological approach does not require prior knowledge of the expected patterns. For both unsupervised and supervised machine learning methods, the topological approach outperforms the one that is based on traditional order parameters.Comment: Published in Chaos 29, 123125 (2019), DOI: 10.1063/1.512549

Beckman Access versus the Bayer ACS:180 and the Abbott AxSYM cardiac Troponin-I real-time immunoassays: an observational prospective study

BACKGROUND: Reliability of cardiac troponin-I assays under real-time conditions has not been previously well studied. Most large published cTnI trials have utilized protocols which required the freezing of serum (or plasma) for delayed batch cTnI analysis. We sought to correlate the presence of the acute ischemic coronary syndrome (AICS) to troponin-I values obtained in real-time by three random-mode analyzer immunoassay systems: the Beckman ACCESS (BA), the Bayer ACS:180 (CC) and the Abbott AxSYM (AX). METHODS: This was an observational prospective study at a university tertiary referral center. Serum from a convenience sampling of telemetry patients was analyzed in real-time for troponin-I by either the BA-CC (Arm-1) or BA-AX (Arm-2) assay pairs. Presence of the AICS was determined retrospectively and then correlated with troponin-I results. RESULTS: 100 patients were enrolled in Arm-1 (38 with AICS) and 94 in Arm-2 (48 with AICS). The BA system produced 51% false positives in Arm-1, 44% in Arm-2, with negative predictive values of 92% and 100% respectively. In Arm-1, the BA and the CC assays had sensitivities of 97% and 63% and specificities of 18% and 87%. In Arm-2, the BA and the AX assays had sensitivities of 100% and 83% and specificities of 11% and 78%. CONCLUSIONS: In real-time analysis, the performance of the AxSYM and ACS:180 assay systems produced more accurate troponin-I results than the ACCESS system

Age-Related Differences in Biomarkers of Acute Inflammation During Hospitalization for Sepsis

To evaluate age-related differences in inflammation biomarkers during the first 72 hours of hospitalization for sepsis

Emergency department spirometric volume and base deficit delineate risk for torso injury in stable patients

BACKGROUND: We sought to determine torso injury rates and sensitivities associated with fluid-positive abdominal ultrasound, metabolic acidosis (increased base deficit and lactate), and impaired pulmonary physiology (decreased spirometric volume and PaO(2)/FiO(2)). METHODS: Level I trauma center prospective pilot and post-pilot study (2000–2001) of stable patients. Increased base deficit was < 0.0 in ethanol-negative and ≤ -3.0 in ethanol-positive patients. Increased lactate was > 2.5 mmol/L in ethanol-negative and ≥ 3.0 mmol/L in ethanol-positive patients. Decreased PaO(2)/FiO(2 )was < 350 and decreased spirometric volume was < 1.8 L. RESULTS: Of 215 patients, 66 (30.7%) had a torso injury (abdominal/pelvic injury n = 35 and/or thoracic injury n = 43). Glasgow Coma Scale score was 14.8 ± 0.5 (13–15). Torso injury rates and sensitivities were: abdominal ultrasound negative and normal base deficit, lactate, PaO(2)/FiO(2), and spirometric volume – 0.0% & 0.0%; normal base deficit and normal spirometric volume – 4.2% & 4.5%; chest/abdominal soft tissue injury – 37.8% & 47.0%; increased lactate – 39.7% & 47.0%; increased base deficit – 41.3% & 75.8%; increased base deficit and/or decreased spirometric volume – 43.8% & 95.5%; decreased PaO(2)/FiO(2 )– 48.9% & 33.3%; positive abdominal ultrasound – 62.5% & 7.6%; decreased spirometric volume – 73.4% & 71.2%; increased base deficit and decreased spirometric volume – 82.9% & 51.5%. CONCLUSIONS: Trauma patients with normal base deficit and spirometric volume are unlikely to have a torso injury. Patients with increased base deficit or lactate, decreased spirometric volume, decreased PaO(2)/FiO(2), or positive FAST have substantial risk for torso injury. Increased base deficit and/or decreased spirometric volume are highly sensitive for torso injury. Base deficit and spirometric volume values are readily available and increase or decrease the suspicion for torso injury

What should an ideal spinal injury classification system consist of? A methodological review and conceptual proposal for future classifications

Since Böhler published the first categorization of spinal injuries based on plain radiographic examinations in 1929, numerous classifications have been proposed. Despite all these efforts, however, only a few have been tested for reliability and validity. This methodological, conceptual review summarizes that a spinal injury classification system should be clinically relevant, reliable and accurate. The clinical relevance of a classification is directly related to its content validity. The ideal content of a spinal injury classification should only include injury characteristics of the vertebral column, is primarily based on the increasingly routinely performed CT imaging, and is clearly distinctive from severity scales and treatment algorithms. Clearly defined observation and conversion criteria are crucial determinants of classification systems’ reliability and accuracy. Ideally, two principle spinal injury characteristics should be easy to discern on diagnostic images: the specific location and morphology of the injured spinal structure. Given the current evidence and diagnostic imaging technology, descriptions of the mechanisms of injury and ligamentous injury should not be included in a spinal injury classification. The presence of concomitant neurologic deficits can be integrated in a spinal injury severity scale, which in turn can be considered in a spinal injury treatment algorithm. Ideally, a validation pathway of a spinal injury classification system should be completed prior to its clinical and scientific implementation. This review provides a methodological concept which might be considered prior to the synthesis of new or modified spinal injury classifications

The impact of body mass index and gender on the development of infectious complications in polytrauma patients

Purpose The aim was to test the impact of body mass index (BMI) and gender on infectious complications after polytrauma. Methods A total of 651 patients were included in this retrospective study, with an Injury Severity Score (ISS) C16 and age C16 years. The sample was subdivided into three groups: BMI\25 kg/m2, BMI 25–30 kg/m2, and BMI[30 kg/m2, and a female and a male group. Infectious complications were observed for 31 days after admission. Data are given as mean ± standard errors of the means. Analysis of variance, Kruskal–Wallis test, v2 tests, and Pearson’s correlation were used for the analyses and the significance level was set at P\0.05. Results The overall infection rates were 31.0 % in the BMI\25 kg/m2 group, 29.0 % in the BMI 25–30 kg/m2 group, and 24.5 % in the BMI[30 kg/m2 group (P = 0.519). The female patients developed significantly fewer infectious complications than the male patients (26.8 vs. 73.2 %; P\0.001). The incidence of death was significantly decreased according to the BMI group (8.8 vs. 7.2 vs. 1.5 %; P\0.0001) and the female population had a significantly lower mortality rate (4.1 vs. 13.4 %; P\0.0001). Pearson’s correlations between the Abbreviated Injury Scale (AIS) score and the corresponding infectious foci were not significant. Conclusion Higher BMI seems to be protective against polytrauma-associated death but not polytrauma-associated infections, and female gender protects against both polytrauma- associated infections and death. Understanding gender-specific immunomodulation could improve the outcome of polytrauma patients

Longitudinal Assessment of the Effect of Atrasentan on Thoracic Bioimpedance in Diabetic Nephropathy:A Randomized, Double-Blind, Placebo-Controlled Trial

BACKGROUND: Fluid retention is a common adverse event in patients who receive endothelin (ET) receptor antagonist therapy, including the highly selective ETA receptor antagonist, atrasentan. OBJECTIVE: We performed longitudinal assessments of thoracic bioimpedance in patients with type 2 diabetes mellitus and nephropathy to determine whether a decrease in bioimpedance accurately reflected fluid retention during treatment with atrasentan. STUDY DESIGN: We conducted a randomized, double-blind, placebo-controlled study in 48 patients with type 2 diabetes mellitus and nephropathy who were receiving stable doses of renin angiotensin system inhibitors and diuretics. METHODS: Patients were randomized 1:1:1 to placebo, atrasentan 0.5 mg, or atrasentan 1.25 mg once daily for 8 weeks. Thoracic bioimpedance, vital signs, clinical exams, and serologies were taken at weeks 1, 2, 4, 6, and 8, with the exception of serum hemoglobin, which was not taken at week 1, and serum brain natriuretic peptide, which was only taken at baseline, week 4, and week 8. RESULTS: Alterations in bioimpedance were more often present in those who received atrasentan than in those who received placebo, though overall differences were not statistically significant. Transient declines in thoracic bioimpedance during the first 2 weeks of atrasentan exposure occurred before or during peak increases in body weight and hemodilution (decreased serum hemoglobin). CONCLUSIONS: We conclude that thoracic bioimpedance did not reflect changes in weight gain or edema with atrasentan treatment in this study. However, the sample size was small, and it may be of interest to explore the use of thoracic bioimpedance in a larger population to understand its potential clinical use in monitoring fluid retention in patients with chronic kidney disease who receive ET receptor antagonists

Dynamics, Networks, and Information: Methods for Nonlinear Interactions in Biological Systems

In this dissertation, we investigate complex, non-linear interactions in biological systems.This work is presented as two independent projects. The mathematics and biology in each differ, yet there is a unity in that both frameworks are interested in biological responses that cannot be reduced to linear causal chains, nor can they be expressed as an accumulation of binary interactions. In the first part of this dissertation, we use mathematical modeling to study tumor-immune dynamics at the cellular scale.Recent work suggests that LSD1 inhibition reduces tumor growth, increases T cell tumor infiltration, and complements PD1/PDL1 checkpoint inhibitor therapy. In order to elucidate the immunogenic effects of LSD1 inhibition, we create a delay differential equation model of tumor growth under the influence of the adaptive immune response in order to investigate the anti-tumor cytotoxicity of LSD1-mediated T cell dynamics. We fit our model to the B16 mouse model data from Sheng et al. [DOI:10.1016/j.cell.2018.05.052] Our results suggest that the immunogenic effect of LSD1 inhibition accelerates anti-tumor cytoxicity. However, cytotoxicity does not seem to account for the slower growth observed in LSD1 inhibited tumors, despite evidence suggesting immune-mediation of this effect. In the second part, we consider the partial information decomposition (PID) of response information within networks of interacting nodes, inspired by biomolecular networks.We specifically study the potential of PID synergy as a tool for network inference and edge nomination. We conduct both numeric and analytic investigations of the \Imin and \Ipm PIDs, from [arXiv:1004.2515] and [DOI:10.3390/e20040297], respectively. We find that the $I_\text{PM}$ synergy suffers from issues of non-specificity, while $I_{\text{min}}$ synergy is specific but somewhat insensitive. In the course of our work, we extend the $I_\text{PM}$ and $I_{\text{min}}$ PIDs to continuous variables for a general class of noise-free trivariate systems. The $I_\text{PM}$ PID does not respect conditional independence, while$I_{\text{min}}$ does, as demonstrated through asymptotic analysis of linear and non-linear interaction kernels. The technical results of this chapter relate the analytic and information-theoretic properties of our interactions, by expressing the continuous PID of noise-free interactions in terms of the partial derivatives of the interaction kernel