The cardioprotective effect of Mn-superoxide dismutase is lost at high doses in the postischemic isolated rabbit heart

The loss of protection by human recombinant (hr) Cu,Zn-superoxide dismutase (SOD) at higher doses reported previously may have been due to the weak peroxidase activity of this enzyme. To test this possibility we studied the dose-response relationship of hrMn-SOD, which lacks peroxidase activity. Isolated, buffer perfused rabbit hearts were subjected to 1 h of global ischemia followed by 1 h of reperfusion, and the percent recovery of developed tension (relative to preischemic) was measured via a left ventricular balloon connected through a pressure transducer to a polygraph recorder. The coronary effluent was assayed for lactate dehydrogenase (LDH) release. While hrMn-SOD almost completely protected against loss of function and LDH release at 2 and 5 mg/L (p < 0.01), it exacerbated the damage at 50 mg/L concentration (p < 0.05 against controls), thus giving an even sharper bell-shaped curve than seen with the hrCu,Zn-SOD. Therefore we conclude that, first, while the hrMn-SOD protects the reperfused heart at lower doses, it may exacerbate the damage at higher doses. Second, that the lack of protection seen at higher doses of hr-Cu,Zn-SOD is unlikely to be due only to its peroxidase activity.     

ROC graphs for assessing the ability of a diagnostic marker to detect three disease classes with an umbrella ordering

Receiver operating characteristic (ROC) curves and the area under these curves are commonly used to assess the ability of a continuous diagnostic marker (e.g., DNA methylation markers) to correctly classify subjects as having a particular disease or not (e.g., cancer). These approaches, however, are not applicable to settings where the gold standard yields more than two disease states or classes. ROC surfaces and the volume under the surfaces have been proposed for settings with more than two disease classes. These approaches, however, do not allow one to assess the ability of a marker to differentiate two disease classes from a third disease class without requiring a monotone order for the three disease classes under study. That is, existing approaches do not accommodate an umbrella ordering of disease classes. This article proposes the construction of an ROC graph that is applicable for an umbrella ordering. Furthermore, this article proposes that a summary measure for this umbrella ROC graph can be used to summarize the classification accuracy, and corresponding variance estimates can be obtained using U-statistics theory or bootstrap methods. The proposed methods are illustrated using data from a study assessing the ability of a DNA methylation marker to correctly classify lung specimens into three histologic classes: squamous cell carcinoma, large cell carcinoma, and nontumor lung.     

Adjusting O'Brien's test to control type I error for the generalized nonparametric Behrens-Fisher problem

O'Brien (1984, Biometrics 40, 1079-1087) introduced a simple nonparametric test procedure for testing whether multiple outcomes in one treatment group have consistently larger values than outcomes in the other treatment group. We first explore the theoretical properties of O'Brien's test. We then extend it to the general nonparametric Behrens-Fisher hypothesis problem when no assumption is made regarding the shape of the distributions. We provide conditions when O'Brien's test controls its error probability asymptotically and when it fails. We also provide adjusted tests when the conditions do not hold. Throughout this article, we do not assume that all outcomes are continuous. Simulations are performed to compare the adjusted tests to O'Brien's test. The difference is also illustrated using data from a Parkinson's disease clinical trial.     

A new hepatoma cell line for toxicity testing at repeated doses

Many cell models that are used to assess basic cytotoxicity show a good correlation with acute toxicity. However, their correlation with the toxicity seen following chronic in vivo exposure is less evident. The new human hepatoma cell line HBG BC2 possesses the capacity of being reversibly differentiated in vitro and of maintaining a relatively higher metabolic rate when in the differentiated state (3 weeks) as compared to HepG2 cells, and thus may allow the conduct of repeated toxicity testing on cells in culture. In order to evaluate the genetic background of HBG BC2 cells, the expression of selected genes was analyzed in untreated cultures and, in addition, the behavior of HBG BC2 cultures under conditions of repeated treatment was studied with acetaminophen as a test substance and coupled with the use of standard staining techniques to demonstrate toxicity. Results showed that cultures of HBG BC2 cells retained a capacity to undergo apoptosis and proliferation, allowing probable replacement of damaged cells in the culture monolayer. MTT reduction was used to evaluate the toxicity of acetaminophen, acetylsalicylic acid, perhexiline, and propranolol, after both single and repeated (3 times/week for 2 weeks) administration. Under the conditions of repeated treatment, cytotoxicity was observed at lower doses as compared to single administration. In addition, the lowest nontoxic doses were in the same range as plasma concentrations measured in humans under therapeutic use. Our results suggest that the new human hepatoma HBG BC2 cell line is of interest for the evaluation of cell toxicity under conditions of repeated administration.     

Order-restricted inference for clustered ROC data with application to fingerprint matching accuracy

Receiver operating characteristic (ROC) curve is commonly used to evaluate and compare the accuracy of classification methods or markers. Estimating ROC curves has been an important problem in various fields including biometric recognition and diagnostic medicine. In real applications, classification markers are often developed under two or more ordered conditions, such that a natural stochastic ordering exists among the observations. Incorporating such a stochastic ordering into estimation can improve statistical efficiency (Davidov and Herman, 2012). In addition, clustered and correlated data arise when multiple measurements are gleaned from the same subject, making estimation of ROC curves complicated due to within-cluster correlations. In this article, we propose to model the ROC curve using a weighted empirical process to jointly account for the order constraint and within-cluster correlation structure. The algebraic properties of resulting summary statistics of the ROC curve such as its area and partial area are also studied. The algebraic expressions reduce to the ones by Davidov and Herman (2012) for independent observations. We derive asymptotic properties of the proposed order-restricted estimators and show that they have smaller mean-squared errors than the existing estimators. Simulation studies also demonstrate better performance of the newly proposed estimators over existing methods for finite samples. The proposed method is further exemplified with the fingerprint matching data from the National Institute of Standards and Technology Special Database 4.     

Nonparametric maximum likelihood estimation for competing risks survival data subject to interval censoring and truncation

We derive the nonparametric maximum likelihood estimate (NPMLE) of the cumulative incidence functions for competing risks survival data subject to interval censoring and truncation. Since the cumulative incidence function NPMLEs give rise to an estimate of the survival distribution which can be undefined over a potentially larger set of regions than the NPMLE of the survival function obtained ignoring failure type, we consider an alternative pseudolikelihood estimator. The methods are then applied to data from a cohort of injecting drug users in Thailand susceptible to infection from HIV-1 subtypes B and E.     

Dopamine and glutamate in individuals at high risk for psychosis: a meta‐analysis of in vivo imaging findings and their variability compared to controls

Dopaminergic and glutamatergic dysfunction is believed to play a central role in the pathophysiology of schizophrenia. However, it is unclear if abnormalities predate the onset of schizophrenia in individuals at high clinical or genetic risk for the disorder. We systematically reviewed and meta‐analyzed studies that have used neuroimaging to investigate dopamine and glutamate function in individuals at increased clinical or genetic risk for psychosis. EMBASE, PsycINFO and Medline were searched form January 1, 1960 to November 26, 2020. Inclusion criteria were molecular imaging measures of striatal presynaptic dopaminergic function, striatal dopamine receptor availability, or glutamate function. Separate meta‐analyses were conducted for genetic high‐risk and clinical high‐risk individuals. We calculated standardized mean differences between high‐risk individuals and controls, and investigated whether the variability of these measures differed between the two groups. Forty‐eight eligible studies were identified, including 1,288 high‐risk individuals and 1,187 controls. Genetic high‐risk individuals showed evidence of increased thalamic glutamate + glutamine (Glx) concentrations (Hedges’ g=0.36, 95% CI: 0.12‐0.61, p=0.003). There were no significant differences between high‐risk individuals and controls in striatal presynaptic dopaminergic function, striatal D2/D3 receptor availability, prefrontal cortex glutamate or Glx, hippocampal glutamate or Glx, or basal ganglia Glx. In the meta‐analysis of variability, genetic high‐risk individuals showed reduced variability of striatal D2/D3 receptor availability compared to controls (log coefficient of variation ratio, CVR=–0.24, 95% CI: –0.46 to –0.02, p=0.03). Meta‐regressions of publication year against effect size demonstrated that the magnitude of differences between clinical high‐risk individuals and controls in presynaptic dopaminergic function has decreased over time (estimate=–0.06, 95% CI: –0.11 to –0.007, p=0.025). Thus, other than thalamic glutamate concentrations, no neurochemical measures were significantly different between individuals at risk for psychosis and controls. There was also no evidence of increased variability of dopamine or glutamate measures in high‐risk individuals compared to controls. Significant heterogeneity, however, exists between studies, which does not allow to rule out the existence of clinically meaningful differences.