Identification of Post-cardiac Arrest Blood Pressure Thresholds Associated With Outcomes in Children: An ICU-Resuscitation Study

INTRODUCTION: Though early hypotension after pediatric in-hospital cardiac arrest (IHCA) is associated with inferior outcomes, ideal post-arrest blood pressure (BP) targets have not been established. We aimed to leverage prospectively collected BP data to explore the association of post-arrest BP thresholds with outcomes. We hypothesized that post-arrest systolic and diastolic BP thresholds would be higher than the currently recommended post-cardiopulmonary resuscitation BP targets and would be associated with higher rates of survival to hospital discharge. METHODS: We performed a secondary analysis of prospectively collected BP data from the first 24 h following return of circulation from index IHCA events enrolled in the ICU-RESUScitation trial (NCT02837497). The lowest documented systolic BP (SBP) and diastolic BP (DBP) were percentile-adjusted for age, height and sex. Receiver operator characteristic curves and cubic spline analyses controlling for illness category and presence of pre-arrest hypotension were generated exploring the association of lowest post-arrest SBP and DBP with survival to hospital discharge and survival to hospital discharge with favorable neurologic outcome (Pediatric Cerebral Performance Category of 1-3 or no change from baseline). Optimal cutoffs for post-arrest BP thresholds were based on analysis of receiver operator characteristic curves and spline curves. Logistic regression models accounting for illness category and pre-arrest hypotension examined the associations of these thresholds with outcomes. RESULTS: Among 693 index events with 0-6 h post-arrest BP data, identified thresholds were: SBP \u3e 10th percentile and DBP \u3e 50th percentile for age, sex and height. Fifty-one percent (n = 352) of subjects had lowest SBP above threshold and 50% (n = 346) had lowest DBP above threshold. SBP and DBP above thresholds were each associated with survival to hospital discharge (SBP: aRR 1.21 [95% CI 1.10, 1.33]; DBP: aRR 1.23 [1.12, 1.34]) and survival to hospital discharge with favorable neurologic outcome (SBP: aRR 1.22 [1.10, 1.35]; DBP: aRR 1.27 [1.15, 1.40]) (all p \u3c 0.001). CONCLUSIONS: Following pediatric IHCA, subjects had higher rates of survival to hospital discharge and survival to hospital discharge with favorable neurologic outcome when BP targets above a threshold of SBP \u3e 10th percentile for age and DBP \u3e 50th percentile for age during the first 6 h post-arrest

Feasibility of near infrared spectroscopy for analyzing corn kernel damage and viability of soybean and corn kernels

The current US corn grading system accounts for the portion of damaged kernels, measured by timeconsuming and inaccurate visual inspection. Near infrared spectroscopy (NIRS), a non-destructive and fast analytical method, was tested as a tool for discriminating corn kernels with heat and frost damage. Four classification algorithms were utilized: Partial least squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), k-nearest neighbors (K-NN), and least-squares support vector machines (LS-SVM). The feasibility of NIRS for discriminating normal or viable-germinating corn kernels and soybean seeds from abnormal or dead seeds was also tested. This application could be highly valuable for seed breeders and germplasm-preservation managers because current viability tests are based on a destructive method where the seed is germinated. Heat-damaged corn kernels were best discriminated by PLS-DA, with 99% accuracy. The discrimination of frost-damaged corn kernels was not possible. Discrimination of non-viable seeds from viable also was not possible. Since previous results in the literature contradict the current damage-discrimination results, the threshold of seed damage necessary for NIRS detection should be analyzed in the future. NIRS may accurately classify seeds based on changes due to damage, without any correlation with germination

Feasibility of near infrared spectroscopy for analyzing corn kernel damage and viability of soybean and corn kernels

The current US corn grading system accounts for the portion of damaged kernels, measured by time-consuming and inaccurate visual inspection. Near infrared spectroscopy (NIRS), a non-destructive and fast analytical method, was tested as a tool for discriminating corn kernels with heat and frost damage. Four classification algorithms were utilized: Partial least squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), k-nearest neighbors (K-NN), and least-squares support vector machines (LS-SVM). The feasibility of NIRS for discriminating normal or viable-germinating corn kernels and soybean seeds from abnormal or dead seeds was also tested. This application could be highly valuable for seed breeders and germplasm-preservation managers because current viability tests are based on a destructive method where the seed is germinated. Heat-damaged corn kernels were best discriminated by PLS-DA, with 99% accuracy. The discrimination of frost-damaged corn kernels was not possible. Discrimination of non-viable seeds from viable also was not possible. Since previous results in the literature contradict the current damage-discrimination results, the threshold of seed damage necessary for NIRS detection should be analyzed in the future. NIRS may accurately classify seeds based on changes due to damage, without any correlation with germination.This article is from Journal of Cereal Science 55 (2012): 160–166, doi:10.1016/j.jcs.2011.11.002.</p

Optimized analysis and quantification of glucosinolates from Camelina sativa seeds by reverse-phase liquid chromatography

Gold-of-pleasure or false flax (Camelina sativa L Crantz) is being developed as an alternative oil crop for biodiesel and for food use. The seed meal, which contains three relatively unique glucosinolates, is being evaluated for approval for use as an ingredient in animal feeds and for other uses. The objective of this research was to develop reproducible methods for the isolation of large quantities of pure camelina glucosinolates (glucoarabin, glucocamelinin, and 11-(methylsulfinyl)-undecylglucosinolate) and develop efficient methods for quantifying these compounds. The separation and purification of the camelina glucosinolates were achieved using a combination of reverse phase chromatography, counter-current chromatography and ion exchange chromatography. An efficient reverse phase HPLC separation method was used to quantitate the glucosinolate content in camelina seed and plant extracts. The quanti ration methodology was used to measure glucosinolate levels in seeds from 30 cultivars grown in a U.S. field trial and measure glucosinolates levels in sprouted camelina seeds

Substance use and community violence: a test of the relation at the daily level

Prior research has consistently demonstrated an association between substance use and involvement in violence among individuals with mental illness. Yet little is known about the temporal quality of this relationship, largely because longitudinal data required to address this issue are not readily available. This study examined the relationship between substance use (alcohol, marijuana, and other drug use) and violence at the daily level within a sample of mentally ill individuals at high risk for frequent involvement in violence (N = 132). Results support the serial nature of substance use and violence, with an increased likelihood of violence on days following the use of alcohol or multiple drugs, but not the inverse relationship. Implications for the utility of substance use as a risk marker for the assessment of future violence are discussed

Psychiatric symptoms and community violence among high-risk patients: A test of the relationship at the weekly level

Given the availability of violence risk assessment tools, clinicians are now better able to identify high-risk patients. Once these patients have been identified, clinicians must monitor risk state and intervene when necessary to prevent harm. Clinical practice is dominated by the assumption that increases in psychiatric symptoms elevate risk of imminent violence. This intensive study of patients (N = 132) at high risk for community violence is the first to evaluate prospectively the temporal relation between symptoms and violence. Symptoms were assessed with the Brief Symptom Inventory and threat/control override (TCO) scales. Results indicate that a high-risk patient with increased anger in 1 week is significantly more likely to be involved in serious violence in the following week. This was not true of other symptom constellations (anxiety, depression, TCO) or general psychological distress. The authors found no evidence that increases in the latter symptoms during 1 week provide an independent foundation for expecting violence during the following week

Clean quantum point contacts in an InAs quantum well grown on a lattice-mismatched InP substrate

Strong spin-orbit coupling, the resulting large $g$ factor, and small effective mass make InAs an attractive material platform for inducing topological superconductivity. The surface Fermi level pinning in the conduction band enables highly transparent ohmic contact without excessive doping. We investigate electrostatically defined quantum point contacts (QPCs) in a deep-well InAs two-dimensional electron gas. Despite the 3.3% lattice mismatch between the InAs quantum well and the InP substrate, we report clean QPCs with up to eight pronounced quantized conductance plateaus at zero magnetic field. Source-drain dc bias spectroscopy reveals a harmonic confinement potential with a nearly $5$ meV subband spacing. We find a many-body exchange interaction enhancement for the out-of-plane $g$ factor $|g_{\perp}^*| = 27 \pm 1$, whereas the in-plane $g$ factor is isotropic $|g^*_{x}| = |g^*_{y}| = 12 \pm 2$, close to the bulk value for InAs.Comment: Main text (8 pages, 5 figures), Supplemental Material (10 pages, 10 figures