Subclinical mastitis in dairy cows: somatic cell counts and associated bacteria in Mymensingh, Bangladesh

Subclinical mastitis is an economically important disease of dairy cows and has a prominent place amongst the factors that limit milk production. This study was undertaken to determine the association of somatic cell counts (SCC) and occurrence of bacteria with SCM in smallholder dairy cows in Mymensingh, Bangladesh. A total number of 240 quarters milk samples from apparently healthy lactating cows were subjected to SCC using NucleoCounter® SCC-100 ™ (Chemo Metec). A quarter was considered SCM positive if the quarter had SCC>100 x 103 cells/ml. All subclinical mastitis positive quarter milk samples were subjected to bacteriological examination and isolates were classified into major, minor, uncommon and mixed pathogens. The overall quarter-level prevalence of subclinical mastitis of dairy cows in Mymensingh district was 25% (95% CI, 19.52% to 30.48%). The most frequently isolated bacterial species were Staphylococcus aureus (18.33%) followed by coagulase-negative staphylococci (10%), Enterobacter spp. (6.67%), Escherichia coli (5%), Bacillus spp. (5%) and Pseudomonas aeruginosa (5%). Different bacterial isolates were associated with 90% cases of subclinical mastitis as mono infections or mixed infections. Mono and mixed infections significantly influenced SCC and were the most prominent factors responsible for increasing SCC. Mean SCC was the highest for Bacillus spp. (713.67 x 103 cells/ml) followed by Enterobacter spp. (395.75 x 103 cells/ml), Escherichia coli (386.00 x 103 cells/ml), Staphylococcus aureus (373.82 x 103 cells/ml), coagulase-negative staphylococci (182.67 x 103 cells/ml) and Pseudomonas aeruginosa (138.67 x 103 cells/ml). Major pathogens induced higher SCC (380.72 x 103cells/ml) than minor and other pathogen groups

Multi-Level Canonical Correlation Analysis for Standard-Dose PET Image Estimation

Positron emission tomography (PET) images are widely used in many clinical applications such as tumor detection and brain disorder diagnosis. To obtain PET images of diagnostic quality, a sufficient amount of radioactive tracer has to be injected into a living body, which will inevitably increase the risk of radiation exposure. On the other hand, if the tracer dose is considerably reduced, the quality of the resulting images would be significantly degraded. It is of great interest to estimate a standard-dose PET (S-PET) image from a low-dose one in order to reduce the risk of radiation exposure and preserve image quality. This may be achieved through mapping both standard-dose and low-dose PET data into a common space and then performing patch based sparse representation. However, a one-size-fits-all common space built from all training patches is unlikely to be optimal for each target S-PET patch, which limits the estimation accuracy. In this paper, we propose a data-driven multi-level Canonical Correlation Analysis (mCCA) scheme to solve this problem. Specifically, a subset of training data that is most useful in estimating a target S-PET patch is identified in each level, and then used in the next level to update common space and improve estimation. Additionally, we also use multi-modal magnetic resonance images to help improve the estimation with complementary information. Validations on phantom and real human brain datasets show that our method effectively estimates S-PET images and well preserves critical clinical quantification measures, such as standard uptake value

Chemical Approaches to Synthetic Drug Delivery Systems for Systemic Applications

Poor water solubility and low bioavailability of active pharmaceutical ingredients (APIs) are major causes of friction in the pharmaceutical industry and represent a formidable hurdle for pharmaceutical drug development. Drug delivery remains the major challenge for the application of new small-molecule drugs as well as biopharmaceuticals. The three challenges for synthetic delivery systems are: (i) controlling drug distribution and clearance in the blood; (ii) solubilizing poorly water-soluble agents, and (iii) selectively targeting specific tissues. Although several polymer-based systems have addressed the first two demands and have been translated into clinical practice, no targeted synthetic drug delivery system has reached the market. This Review is designed to provide a background on the challenges and requirements for the design and translation of new polymer-based delivery systems. This report will focus on chemical approaches to drug delivery for systemic applications

Transcriptomic Profiling of Mouse Brain During Acute and Chronic Infections by Toxoplasma gondii Oocysts

Infection by the protozoan Toxoplasma gondii can have a devastating impact on the structure and function of the brain of the infected individuals, particularly immunocompromised patients. A systems biology view of the brain transcriptome can identify key molecular targets and pathways that mediate the neuropathogenesis of cerebral toxoplasmosis. Here, we performed transcriptomic analysis of the brain of mice infected by T. gondii Pru strain oocysts at 11 and 33 days post-infection (dpi) compared to uninfected (control) mice using RNA sequencing (RNA-seq). T. gondii altered the expression of 936 and 2,081 transcripts at 11 and 33 dpi, respectively, and most of these were upregulated in the infected brains. Gene Ontology (GO) enrichment and pathway analysis showed that immune response, such as interferon-gamma (IFN-γ) responsive genes were strongly affected at 11dpi. Likewise, differentially expressed transcripts (DETs) related to T cell activation, cytokine production and immune cell proliferation were significantly altered at 33 dpi. Host-parasite interactome analysis showed that some DETs were involved in immune signaling, metabolism, biosynthesis-related processes and interspecies interaction. These findings should increase knowledge of the mouse brain transcriptome and the changes in transcriptional regulation and downstream signaling pathways during acute and chronic T. gondii infections