A simple technique for estimation ofDrechslera nodulosa (Berk. & Curt.) Subram. and Jain propagules in soil

Summary A baiting technique was developed to estimate the population ofDrechslera nodulosa (Berk. and Curt.) Subram. and Jain in soil by using susceptible ragi (Eleusine coracana Gaertn.) culms. The number of lesions developed on baited culms were reduced with the reduction in concentration ofD. nodulosa propagules in both sterilized and unsterilized soils. Based on this a standard correlation (concentrationvs infection probability) was established which was found to be quite efficient method to estimate the population in soil and to bait even when the inoculum level was 4 propagules per g of soil.     

Phylogeny of snakes (Serpentes): Combining morphological and molecular data in likelihood,Bayesian and parsimony analyses

Abstract

The phylogeny of living and fossil snakes is assessed using likelihood and parsimony approaches and a dataset combining 263 morphological characters with mitochondrial (2693 bp) and nuclear (1092 bp) gene sequences. The ‘no common mechanism’ (NCMr) and ‘Markovian’ (Mkv) models were employed for the morphological partition in likelihood analyses; likelihood scores in the NCMr model were more closely correlated with parsimony tree lengths. Both models accorded relatively less weight to the molecular data than did parsimony, with the effect being milder in the NCMr model. Partitioned branch and likelihood support values indicate that the mtDNA and nuclear gene partitions agree more closely with each other than with morphology. Despite differences between data partitions in phylogenetic signal, analytic models, and relative weighting, the parsimony and likelihood analyses all retrieved the following widely accepted groups: scolecophidians, alethinophidians, cylindrophiines, macrostomatans (sensu lato) and caenophidians. Anilius alone emerged as the most basal alethinophidian; the combined analyses resulted in a novel and stable position of uropeltines and cylindrophiines as the second‐most basal clade of alethinophidians. The limbed marine pachyophiids, along with Dinilysia and Wonambi, were always basal to all living snakes. Other results stable in all combined analyses include: Xenopeltis and Loxocemus were sister taxa (fide morphology) but clustered with pythonines (fide molecules), and Ungaliophis clustered with a boine‐erycine clade (fide molecules). Tropidophis remains enigmatic; it emerges as a basal alethinophidian in the parsimony analyses (fide molecules) but a derived form in the likelihood analyses (fide morphology), largely due to the different relative weighting accorded to data partitions.     

Exploiting nonsystematic covariate monitoring to broaden the scope of evidence about the causal effects of adaptive treatment strategies

In studies based on electronic health records (EHR), the frequency of covariate monitoring can vary by covariate type, across patients, and over time, which can limit the generalizability of inferences about the effects of adaptive treatment strategies. In addition, monitoring is a health intervention in itself with costs and benefits, and stakeholders may be interested in the effect of monitoring when adopting adaptive treatment strategies. This paper demonstrates how to exploit nonsystematic covariate monitoring in EHR‐based studies to both improve the generalizability of causal inferences and to evaluate the health impact of monitoring when evaluating adaptive treatment strategies. Using a real world, EHR‐based, comparative effectiveness research (CER) study of patients with type II diabetes mellitus, we illustrate how the evaluation of joint dynamic treatment and static monitoring interventions can improve CER evidence and describe two alternate estimation approaches based on inverse probability weighting (IPW). First, we demonstrate the poor performance of the standard estimator of the effects of joint treatment‐monitoring interventions, due to a large decrease in data support and concerns over finite‐sample bias from near‐violations of the positivity assumption (PA) for the monitoring process. Second, we detail an alternate IPW estimator using a no direct effect assumption. We demonstrate that this estimator can improve efficiency but at the potential cost of increase in bias from violations of the PA for the treatment process.     

Ethanol inhibits Kv7.2/7.3 channel open probability by reducing the PI(4,5)P2 sensitivity of Kv7.2 subunit

Ethanol often causes critical health problems by altering the neuro-nal activities of the central and peripheral nerve systems. One of the cellular targets of ethanol is the plasma membrane proteins including ion channels and receptors. Recently, we reported that ethanol elevates membrane excitability in sympathetic neurons by inhibiting Kv7.2/7.3 channels in a cell type-specific manner. Even though our studies revealed that the inhibitory effects of ethanol on the Kv7.2/7.3 channel was diminished by the increase of plasma membrane phosphatidylinositol 4,5-bisphosphate (PI (4,5)P₂), the molecular mechanism of ethanol on Kv7.2/7.3 channel inhibition remains unclear. By investigating the kinetics of Kv7.2/7.3 current in high K⁺ solution, we found that ethanol inhibited Kv7.2/7.3 channels through a mechanism distinct from that of tetraethylammonium (TEA) which enters into the pore and blocks the gate of the channels. Using a non-stationary noise analysis (NSNA), we demonstrated that the inhibitory effect of ethanol is the result of reduction of open probability (P_O) of the Kv7.2/7.3 channel, but not of a single channel current (i) or channel number (N). Finally, ethanol selectively facilitated the kinetics of Kv7.2 current suppression by voltage-sensing phosphatase (VSP)-induced PI(4,5)P₂ depletion, while it slowed down Kv7.2 current recovery from the VSP-induced inhibition. Together our results suggest that ethanol regulates neuronal activity through the reduction of open probability and PI(4,5)P₂ sensitivity of Kv7.2/7.3 channels.