Time-of-day dependent performance efficiency in student nurses

A psychological test battery comprising reasoning ability, name and number checking, letter cancellation and associative recall was administered to a group of 70 student nurses at 2-hr intervals from 0800 to 2000 to determine if their performance varied at different times of day. Simultaneously, their oral temperature was recorded. A 7 x 7 latin square design was utilized, and latin square repeated measure analysis of variance was employed. The results indicated variations in oral temperature as the day advanced. While accuracy of performance in cognitive tasks was found to be superior during the early morning, noon or early evening hours, the speed of performance was highest during the period from late-morning to late-evening.     

Seasonal Abundance of Acanthamoeba rhysodes (Singh, 1952) (Protozoa: Gymnamoebia) in a Mangrove Litter-Soil Ecosystem of Gangetic-Estuary,India1,2

Acanthamoeba rhysodes has been found to be a predominant intertidal benthic gymnamoeba in the mangrove ecosystem of Sundarbans of lower deltaic Bengal, facing the Bay. The sampling zones under study were the highest high tide regions, with characteristic mangrove litter-soil, inundated twice per month during the highest ebb of spring tide. Population abundance of this species, both in its trophic and cystic forms in the three distinct seasonal periods of pre-monsoon (March to June), monsoon (July to October), and post-monsoon (November to February) has been surveyed for over two years. These seasonal periods affect the physico-chemical parameters of the habitat substrata, including temperature, pH, and salinity. It has been found that the overall number of organisms per gram of soil attains peak value during the monsoon period. This value comes down in post-monsoon samples and is the least in pre-monsoon ones.     

Two oligosaccharides from Marsdenia roylei

Phytochemical analysis of dried twigs of Marsdenia roylei (family Asclepiadaceae) has resulted in the isolation of a trisaccharide, maryal, and a diglycoside, rolinose. Their structures were determined as O-beta-D-oleandropyranosyl-(1-->4)-O-beta-D-digitoxopyranosyl++ +-(1-->4)-D- cymaral and ethyl O-beta-D-oleandropyranosyl-(1-->4)-O-3-O-methyl-6-deoxy-beta-D- allopyranoside, respectively, by chemical degradation and spectroscopic methods.     

Molecular cloning and characterization of buffalo alpha(s1)-casein gene.

Buffaloes in Indian subcontinent play an important role as the producer of milk and milk products. The alpha(s1)-casein constitutes 38% of the total milk proteins. The present study was carried out to characterize the gene in Murrah breed of Riverine buffalo. Buffalo alpha(s1)-casein cDNA was synthesized by RT-PCR, then cloned using pDRIVE-cloning vector and sequenced. The sequencing revealed that the size of alpha(s1)-casein cDNA was of 645 bp with GC content of 45.58%. The alpha(s1)-casein gene coded 214 amino acids precursor with a signal peptide of 15 amino acid residues. The similarity of buffalo alpha(s1)-casein mRNA sequence with that of cattle, goat, sheep, pig, camel, equine and human were estimated as 97.2, 93, 92.3, 57.2, 59.5, 55.9 and 46.6%, respectively. A similar trend was observed when compared amino acid sequences of these species. In the phylogenetic trees, constructed from the data of the alpha(s1)-casein mRNA as well as protein sequences, it has been observed that buffalo, cattle, goat and sheep formed a cluster with a closer relationship between cattle and buffalo followed by goat and sheep.     

Further simplification of the general analysis of the intercalative drug-DNA interaction

The application of McGhee and von Hippel's general equation [J. Mol. Biol., 86 (1974), 469-489, Eq. (15)] to the analysis of the interaction of intercalative drugs with DNA has been further simplified. The value of n can now be determined mathematically, using a simple function, and without any approximation. It is also established that the summation of squared deviation of (( (nu/c), nu)) points would be minimum for and only for the true set of (K,n,omega) of the interaction system. The method incorporating the simplification has been applied to determine the binding parameters of adriamycin-DNA interaction according to the above general equation.     

Towards a matrix mechanics framework for dynamic protein network

Protein–protein interaction networks are currently visualized by software generated interaction webs based upon static experimental data. Current state is limited to static, mostly non-compartmental network and non time resolved protein interactions. A satisfactory mathematical foundation for particle interactions within a viscous liquid state (situation within the cytoplasm) does not exist nor do current computer programs enable building dynamic interaction networks for time resolved interactions. Building mathematical foundation for intracellular protein interactions can be achieved in two increments (a) trigger and capture the dynamic molecular changes for a select subset of proteins using several model systems and high throughput time resolved proteomics and, (b) use this information to build the mathematical foundation and computational algorithm for a compartmentalized and dynamic protein interaction network. Such a foundation is expected to provide benefit in at least two spheres: (a) understanding physiology enabling explanation of phenomenon such as incomplete penetrance in genetic disorders and (b) enabling several fold increase in biopharmaceutical production using impure starting materials.