A MAPPING OF OXIDATIVE ENZYMES IN THE HUMAN BRAIN *

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65177/1/j.1471-4159.1962.tb11860.x.pd

Likelihood-based random-effects meta-analysis with few studies: empirical and simulation studies

Background: Standard random-effects meta-analysis methods perform poorly when applied to few studies only. Such settings however are commonly encountered in practice. It is unclear, whether or to what extent small-sample-size behaviour can be improved by more sophisticated modeling. Methods: We consider likelihood-based methods, the DerSimonian-Laird approach, Empirical Bayes, several adjustment methods and a fully Bayesian approach. Confidence intervals are based on a normal approximation, or on adjustments based on the Student-t-distribution. In addition, a linear mixed model and two generalized linear mixed models (GLMMs) assuming binomial or Poisson distributed numbers of events per study arm are considered for pairwise binary meta-analyses. We extract an empirical data set of 40 meta-analyses from recent reviews published by the German Institute for Quality and Efficiency in Health Care (IQWiG). Methods are then compared empirically as well as in a simulation study, based on few studies, imbalanced study sizes, and considering odds-ratio (OR) and risk ratio (RR) effect sizes. Coverage probabilities and interval widths for the combined effect estimate are evaluated to compare the different approaches. Results: Empirically, a majority of the identified meta-analyses include only 2 studies. Variation of methods or effect measures affects the estimation results. In the simulation study, coverage probability is, in the presence of heterogeneity and few studies, mostly below the nominal level for all frequentist methods based on normal approximation, in particular when sizes in meta-analyses are not balanced, but improve when confidence intervals are adjusted. Bayesian methods result in better coverage than the frequentist methods with normal approximation in all scenarios, except for some cases of very large heterogeneity where the coverage is slightly lower. Credible intervals are empirically and in the simulation study wider than unadjusted confidence intervals, but considerably narrower than adjusted ones, with some exceptions when considering RRs and small numbers of patients per trial-arm. Confidence intervals based on the GLMMs are, in general, slightly narrower than those from other frequentist methods. Some methods turned out impractical due to frequent numerical problems. Conclusions: In the presence of between-study heterogeneity, especially with unbalanced study sizes, caution is needed in applying meta-analytical methods to few studies, as either coverage probabilities might be compromised, or intervals are inconclusively wide. Bayesian estimation with a sensibly chosen prior for between-trial heterogeneity may offer a promising compromise

PROXIMO-DISTAL INCREASE OF ENZYMIC ACTIVITY IN THE DORSAL SPINAL TRACTS *

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65919/1/j.1471-4159.1964.tb06151.x.pd

A QUANTITATIVE MAPPING OF ALKALINE PHOSPHATASE IN THE BRAIN OF THE RHESUS MONKEY *

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65477/1/j.1471-4159.1966.tb07513.x.pd

A COMPARATIVE MAPPING OF ENZYMES INVOLVED IN HEXOSEMONOPHOSPHATE SHUNT AND CITRIC ACID CYCLE IN THE BRAIN *

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66082/1/j.1471-4159.1963.tb05042.x.pd

A COMPARISON OF CHOLINESTERASE DISTRIBUTION IN THE CEREBELLUM OF SEVERAL SPECIES *

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65142/1/j.1471-4159.1964.tb06717.x.pd

Prediction of martensite start temperature by neural network analysis

Commercial steels are nowadays sophisticated alloys formed by a large number of alloying elements. The martensite start ( Ms) temperature of such steels is of vital engineering importance, and its prediction through models allows us to enhance the design and development of industrial products. In the present work, Ms temperature dependence on chemical composition has been examined by neural network analysis. Neural networks represent powerful methods of non-linear regression modelling. The network is a mathematical function which is fitted to experimental data. The influence of alloying elements such as C, Mn, Si, Cr, Ni, Mo, V, Co, W, Al, Nb, Cu, B and N on Ms temperature was analysed. Finally, a new empirical equation for Ms temperature was derived based on the neural network results.Peer Reviewe

Continuously expanding CAR NK-92 cells display selective cytotoxicity against B-cell leukemia and lymphoma

Background aims Natural killer (NK) cells can rapidly respond to transformed and stressed cells and represent an important effector cell type for adoptive immunotherapy. In addition to donor-derived primary NK cells, continuously expanding cytotoxic cell lines such as NK-92 are being developed for clinical applications. Methods To enhance their therapeutic utility for the treatment of B-cell malignancies, we engineered NK-92 cells by lentiviral gene transfer to express chimeric antigen receptors (CARs) that target CD19 and contain human CD3ζ (CAR 63.z), composite CD28-CD3ζ or CD137-CD3ζ signaling domains (CARs 63.28.z and 63.137.z). Results Exposure of CD19-positive targets to CAR NK-92 cells resulted in formation of conjugates between NK and cancer cells, NK-cell degranulation and selective cytotoxicity toward established B-cell leukemia and lymphoma cells. Likewise, the CAR NK cells displayed targeted cell killing of primary pre-B-ALL blasts that were resistant to parental NK-92. Although all three CAR NK-92 cell variants were functionally active, NK-92/63.137.z cells were less effective than NK-92/63.z and NK-92/63.28.z in cell killing and cytokine production, pointing to differential effects of the costimulatory CD28 and CD137 domains. In a Raji B-cell lymphoma model in NOD-SCID IL2R γnull mice, treatment with NK-92/63.z cells, but not parental NK-92 cells, inhibited disease progression, indicating that selective cytotoxicity was retained in vivo. Conclusions Our data demonstrate that it is feasible to generate CAR-engineered NK-92 cells with potent and selective antitumor activity. These cells may become clinically useful as a continuously expandable off-the-shelf cell therapeutic agent