Computational expression deconvolution in a complex mammalian organ

BACKGROUND: Microarray expression profiling has been widely used to identify differentially expressed genes in complex cellular systems. However, while such methods can be used to directly infer intracellular regulation within homogeneous cell populations, interpretation of in vivo gene expression data derived from complex organs composed of multiple cell types is more problematic. Specifically, observed changes in gene expression may be due either to changes in gene regulation within a given cell type or to changes in the relative abundance of expressing cell types. Consequently, bona fide changes in intrinsic gene regulation may be either mimicked or masked by changes in the relative proportion of different cell types. To date, few analytical approaches have addressed this problem. RESULTS: We have chosen to apply a computational method for deconvoluting gene expression profiles derived from intact tissues by using reference expression data for purified populations of the constituent cell types of the mammary gland. These data were used to estimate changes in the relative proportions of different cell types during murine mammary gland development and Ras-induced mammary tumorigenesis. These computational estimates of changing compartment sizes were then used to enrich lists of differentially expressed genes for transcripts that change as a function of intrinsic intracellular regulation rather than shifts in the relative abundance of expressing cell types. Using this approach, we have demonstrated that adjusting mammary gene expression profiles for changes in three principal compartments – epithelium, white adipose tissue, and brown adipose tissue – is sufficient both to reduce false-positive changes in gene expression due solely to changes in compartment sizes and to reduce false-negative changes by unmasking genuine alterations in gene expression that were otherwise obscured by changes in compartment sizes. CONCLUSION: By adjusting gene expression values for changes in the sizes of cell type-specific compartments, this computational deconvolution method has the potential to increase both the sensitivity and specificity of differential gene expression experiments performed on complex tissues. Given the necessity for understanding complex biological processes such as development and carcinogenesis within the context of intact tissues, this approach offers substantial utility and should be broadly applicable to identifying gene expression changes in tissues composed of multiple cell types

Comparative Assessment of Microbial Air Contamination in Labor and Postnatal Ward at Mzuzu Central Hospital

Nosocomial infections are rapidly becoming a burden especially in developing countries. Neonates are part of the individuals who are at a high risk and mostly affected. Environmental contamination is one of the key agents of these infections. This study aimed to comparatively assess the microbial air contamination before and after cleaning in the labor and postnatal ward at Mzuzu Central Hospital. A comparative study design was employed, with a sample size of 60 paired culture plates (60 MacConkey agar plates and 60 Blood agar plates). Passive technique of air sampling was used to sample air there after 24 hours of culturing and isolation on blood agar and MacConkey agar for identification and quantification of bacterial colonies. Room observations were also done. There was a significant difference between contaminations before and after cleaning, only when MacConkey agar was used. The microorganisms that were identified include; Staphylococci aureus, Klebsiella, coagulase negative staphylococci and non-hemolytic streptococcus. Factors found to contribute to air contamination were, the size of the rooms, traffic of people in a room and number of people present in a room. This study has identified the hazard that these two wards are containing and suggests interventions to avoid nosocomial infections in the neonates

PHARMACOGNOSTIC AND PHYTOCHEMICAL EVALUATION OF TREMA ORIENTALIS LEAF

Trema orientalis (Ulmaceae) is native to India. This tree species has been of interest to researchers because it is a medicinal plant employed in the Indian indigenous system of medicine. Pharmacognostic standardization, physic-chemical evaluation of the leafs of Trema orientalis was carried out to determine its macro-and micro-scopical characters and also some insoluble ash and sulphated ash values, alcohol-and water-soluble extractive values were determined for phytochemical evaluations. Preliminary phytochemical screening was also done to detect different phytoconstituents. Microscopically, Leaf showed trichomes, Lamina, midrib regions, stomata and calcium oxalate crystals. Powder microscopy showed mesophyll region, abundant xylem vessels with annular thickenings and xylem vessels, Unicellular, multiseriate covering trichomes and glandular trichomes, Rosette and prism shape calcium oxalate crystals, Anomocytic stomata. Total ash was approximately two times and four times more than acid insoluble and water soluble as, respectively Ethanol soluble extractive was approximately two times higher than water soluble extractive. TLC of petroleum ether and ethanol extract showed five spots using Hexane: Ethyl acetate (12:4) and four spot using Choloroform: Ethyl acetate (5:4). Phytochemically, root exhibited phytosterols, Flavanoids, Tannin and phenolic compounds

Clinical characteristics and management of cancer-associated acute venous thromboembolism: findings from the MASTER Registry.

Background: Clinical characteristics and management of acute deep vein thrombosis and pulmonary embolism (PE) have been reported to be different in patients with and without cancer. The aim of this paper was to provide information on clinical characteristics and management of acute venous thromboembolism in patients with cancer by means of a large prospective registry. Design and Methods: MASTER is a multicenter registry of consecutively recruited patients with symptomatic, objectively confirmed, acute venous thromboembolism. Information about clinical characteristics and management was collected by an electronic data network at the time of the index event. Results: A total of 2119 patients were enrolled, of whom 424 (20%) had cancer. The incidence of bilateral lower limb deep vein thrombosis was significantly higher in patients with cancer than in patients without cancer (8.5% versus 4.6%; p<0.01), as were the rates of iliocaval thombosis (22.6% versus 14%; p<0.001), and upper limb deep vein thrombosis (9.9% versus 4.8%; p<0.001). Major bleeding (3.3% versus 1.1%; p=0.001), in-hospital treatment (73.3% versus 66.6%; p=0.02) and inferior vena cava filter implantation (7.3% versus 4.1%; p=0.005) were significantly more frequent in patients with cancer, in whom oral anticoagulants were less often used (64.2% versus 82%; p<0.0001). Conclusions: The clinical presentation of acute venous thromboembolism is different and often more extensive in cancer patients than in patients free from malignancy. Moreover, the management of the acute phase of venous thromboembolism is more problematic in cancer patients, especially because of a higher rate of major bleeding and the need for implantation of inferior vena cava filters

Efficiency of free energy calculations of spin lattices by spectral quantum algorithms

Quantum algorithms are well-suited to calculate estimates of the energy spectra for spin lattice systems. These algorithms are based on the efficient calculation of the discrete Fourier components of the density of states. The efficiency of these algorithms in calculating the free energy per spin of general spin lattices to bounded error is examined. We find that the number of Fourier components required to bound the error in the free energy due to the broadening of the density of states scales polynomially with the number of spins in the lattice. However, the precision with which the Fourier components must be calculated is found to be an exponential function of the system size.Comment: 9 pages, 4 figures; corrected typographical and minor mathematical error

Short Signature rpoB Gene Sequence to Differentiate Species in Mycobacterium abscessus Group

Mycobacterium abscessus group (MAG) are rapidly growing acid-fast bacteria that consist of three closely related species: M. abscessus (Ma), M. bolletii (Mb), and M. massiliense (Mm). Differentiation of these species can be difficult but is increasingly requested owing to recent infectious outbreaks and their differential drug resistance. We developed a novel and rapid pyrosequencing method using short signature sequences (35 to 45 bp) at a hypervariable site in the rpoB gene to differentiate the three MAG species, along with M. chelonae (Mc), and M. immunogenum (Mi). This method was evaluated using 111 M. chelonae-abscessus complex (MCAC) isolates, including six reference strains. All isolates were successfully differentiated to the species level (69 Ma, four Mb, six Mm, 23 Mc, and nine Mi). The species identifications by this method had 100% agreement with Sanger sequencing as well as an in-silico rpoB typing method. This short signature sequencing (SSS) method is rapid (6 to 7 h), accurately differentiates MAG species, and is useful for informing antimicrobial therapy decision. IMPORTANCE Mycobacterium abscessus group (MAG) are rapidly growing acid-fast bacteria that include three species: M. abscessus, M. massiliense, and M. bolletii. These species are among the leading causes of nontuberculosis mycobacteria infections in humans but difficult to differentiate using commonly used methods. The differences of drug resistance among the species shape the treatment regimens and make it significant for them to be differentiated accurately and quickly. We developed and evaluated a novel short signature sequencing (SSS) method utilizing a gene called rpoB to differentiate the three MAG species, as well as other two species (M. chelonae and M. immunogenum). The identification results had 100% agreement with both the reference method of Sanger sequencing and rpoB typing method via a computer-simulated analysis. This SSS method was accurate and quick (6 to 7 h) for species differentiation, which will benefit patient care. The technology used for this method is affordable and easy to operate

Biochemical characterization of patients with dihydrolipoamide dehydrogenase deficiency

Dihydrolipoamide dehydrogenase (DLD; E3) oxidizes lipoic acid. Restoring the oxidized state allows lipoic acid to act as a necessary electron sink for the four mitochondrial keto-acid dehydrogenases: pyruvate dehydrogenase, alpha-ketoglutarate dehydrogenase, branched-chain α-keto-acid dehydrogenase, and 2-oxoadipate dehydrogenase. DLD deficiency (DLDD) is caused by biallelic pathogenic variants i