Origin and radiation of the house mouse: clues from nuclear genes

Although quite a lot is known about the genetic structure of the polytypic species Mus musculus at the periphery of its range, the centre of origin and dispersion of the species remains unknown. To investigate the amount of genetic subdivision that occurs in the central parts of its range, we analysed the genetic variation in four new samples of mice coming from Iran, Pakistan, northern and southern India using 35 autosomal protein loci and restriction fragment length polymorphisms of three genes of the Vβ gene complex of the immune system. The variation was then compared with that found in the subspecies occupying the peripheral regions of the species range. The two samples from the northern part of the Indian subcontinent were shown to be more heterozygous than the samples from any of the other regions. They also contain the majority of the alleles that exist in the differentiated subspecies at the periphery of the species range. A neighbour-joining analysis on Nei's genetic distances and a factorial analysis of correspondences on the allelic composition of each sample both place the Pakistani and Indian populations in a phylogenetically and genetically central position compared to the peripheral subspecies. These results suggest that the populations in this geographically central area have retained most of the ancestral polymorphisms, which in turn indicates that the Indian subcontinent is probably the cradle of the species. The nature of the genetic relationships between the various populations throughout the species range and the possibility that they form an incipient ring species are also discussed. Our results are in agreement with the classical model of geographic differentiation where genetic divergence in allopatry is considered to be the prime cause of subspecies formation that may eventually lead to partial reproductive isolation on secondary contact.     

Protocol for in vitro propagation of Excoecaria agallocha L., a medicinally important mangrove species

An in vitro propagation protocol has been developed for Excoecaria agallocha L. (Euphorbiaceae), a mangrove species. Nodal segments were used for axillary shoot proliferation. One shoot from each node of binodal explants was observed 3 weeks after inoculation. The best axillary sprouting was seen on a newly formulated medium containing BA, Zeatin and IBA in concentrations of 13.3 μM, 4.65 μM and 1.23 μM, respectively. The new medium, first used in this study, has a specific composition of major nutrients, MS micronutrients and iron compounds. Nodal segments from rooted cuttings and seedlings responded better than those of mature tree explants. Multiple shoot induction was complemented with efficient shoot elongation, and repeated subculture of binodal segments from axillary shoots resulted in 10–12 shoots per explant in 3 months. Rooting was achieved by growing shoots in the new medium with 0.23 μM IBA. Regenerated plants were successfully acclimatized to the natural environment, and about 85% of plantlets survived under ex vitro conditions. This is the first report of micropropagation in the genus Excoecaria and also in mangrove tree species. Received: 11 August 1997 / Revision received: 10 February 1998 / Accepted: 2 March 1998     

Classification of Leukemia and Leukemoid Using VGG-16 Convolutional Neural Network Architecture

Leukemoid reaction like leukemia indicates noticeable increased count of WBCs (White Blood Cells) but the cause of it is due to severe inflammation or infections in other body regions. In automatic diagnosis in classifying leukemia and leukemoid reactions, ALL IDB2 (Acute Lymphoblastic Leukemia-Image Data Base) dataset has been used which comprises 110 training images of blast cells and healthy cells. This paper aimed at an automatic process to distinguish leukemia and leukemoid reactions from blood smear images using Machine Learning. Initially, automatic detection and counting of WBC is done to identify leukocytosis and then an automatic detection of WBC blasts is performed to support classification of leukemia and leukemoid reactions. Leukocytosis is commonly observed both in leukemia and leukemoid hence physicians may have chance of wrong diagnosis of malignant leukemia for the patients with leukemoid reactions. BCCD (blood cell count detection) Dataset has been used which has 364 blood smear images of which 349 are of single WBC type. The Image segmentation algorithm of Hue Saturation Value color based on watershed has been applied. VGG16 (Visual Geometric Group) CNN (Convolution Neural Network) architecture based deep learning technique is being incorporated for classification and counting WBC type from segmented images. The VGG16 architecture based CNN used for classification and segmented images obtained from first part were tested to identify WBC blasts.     

Deciphering the ovarian cancer ascites fluid peptidome

Background

Conventional proteomic approaches have thus far been unable to identify novel serum biomarkers for ovarian cancer that are more sensitive and specific than the current clinically used marker, CA-125. Because endogenous peptides are smaller and may enter the circulation more easily than proteins, a focus on the low-molecular-weight region may reveal novel biomarkers with enhanced sensitivity and specificity. In this study, we deciphered the peptidome of ascites fluid from 3 ovarian cancer patients and 3 benign individuals (ascites fluid from patients with liver cirrhosis).

Results

Following ultrafiltration of the ascites fluids to remove larger proteins, each filtrate was subjected to solid phase extraction and fractionated using strong cation exchange chromatography. The resultant fractions were analyzed using an Orbitrap mass spectrometer. We identified over 2000 unique endogenous peptides derived from 259 proteins. We then catalogued over 777 peptides that were found only in ovarian cancer ascites. Our list of peptides found in ovarian cancer specimens includes fragments derived from the proteins vitronectin, transketolase and haptoglobin.

Conclusions

Peptidomics may uncover previously undiscovered disease-specific endogenous peptides that warrant further investigation as biomarkers for ovarian cancer.     

Rapid determination of the synthetic pyrethroid insecticide, deltamethrin, in rat plasma and tissues by HPLC

Deltamethrin (DLM), [(S)-alpha-cyano-d-phenoxybenzyl-(1R,3R)-e-(2,2 dibromovinyl)-2,2-dimethylcyclo-propane-1-carboxylate], is a pyrethroid insecticide widely used in agriculture and households. There are several methods for analysis of DLM in biological fluids and tissues, but these methods are time consuming. They generally involve the extraction of DLM with lipid-soluble solvents such as n-pentane, n-hexane, diethylether or acetone, and subsequent evaporation of the solvent. A more rapid and sensitive high-performance liquid chromatography (HPLC) method to analyze DLM in plasma and tissues (liver, kidney, and brain) was developed and validated according to U.S. Food and Drug Administration (U.S. FDA) and International Conference on Harmonization (ICH) of Technical Requirements for Registration of Pharmaceuticals for Human Use guidelines. The limit of detection (S/N of 3/1) for DLM was 0.01 microg/ml for plasma, liver, kidney and brain. The method performances were shown to be selective for DLM and linear over the concentration range 0.01-20.0 microg/ml. For five replications of samples at 0.05, 0.1, 0.2, 1.5 and 4.0 microg/ml, intraday precision and accuracy values were in the range of 0.7-13.1% relative standard deviation (%R.S.D.) and 1.8-14.1%Error, respectively. Interday (n = 15) precision and accuracy values at 0.05, 0.1, 0.2, 1.5, and 4.0 microg/ml were in the range of 3.2-15.2% (%R.S.D.) and 3.7-14.8%Error, respectively. The absolute recoveries of DLM ranged from 93 to 103% for plasma, 95 to 114% for liver, 97 to 108% for kidney, and 95 to 108% for brain. This method can be quite useful for DLM pharmacokinetic and tissue distribution studies, for which multiple plasma and tissue samples have to be analyzed quickly with high reproducibility.     

Indole-3-piperazinyl derivatives: novel chemical class of 5-HT(6) receptor antagonists

N₁-Arylsulfonyl-3-piperazinyl indole derivatives were designed and identified as a novel class of 5-HT₆ receptors ligands. All the compounds have high affinity and antagonist activity towards 5-HT₆ receptor. The compound 7a (K_i = 3.4 nM, functional assay IC₅₀ = 310 nM) shows enhanced cognitive effect when tested in NORT and Morris water maze models. Synthesis, SAR and PK profile of these novel compounds constitute the subject matter of this Letter.