The Unsteady Lift Produced by a Flat-Plate Wing Translating Past Finite Obstacles

The unsteady lift of a high-angle-of-attack, flat-plate wing encountering finite-length obstacles is studied using towing-tank force measurements. The wing translates from rest and interacts with a rectangular channel, ceiling, or ground obstacle. Variations with angle of attack, obstacle length, mid-chord height to the obstacle, and starting distance between the wing leading edge (LE) and obstacle (typically 1 chord) are examined. For channels, as the gap height decreases, circulatory-lift peaks attributed to leading-edge vortices (LEVs) are the largest, and from the second peak onward occur earliest. This is likely from wing blockage enhancing the flow speed. The lift reduces while exiting a channel, and is lowest afterward if exiting during a lift peak. For ceilings, the first circulatory-lift maximum increases for smaller LE-to-ceiling gaps, but for gaps of 0.5 chords or less, subsequent peaks are below the no-obstacle case yet still earlier. For grounds, with lower wing height the first circulatory-lift peak is larger but the second peak's behavior varies with angle of attack, and the lift decreases near the ground end. Grounds affect peak timing the least, indicating a reduced influence on the LEV. Changing the starting distance to a channel alters the lift, likely from different LEV timing

Analysis of drug related electrolyte disturbances in emergency medicine department

Background: Electrolytes play an important role in various physiological functions of the body. Electrolyte disturbances are one of the most common problems encountered in critically ill patients. Drugs are also known to cause adverse electrolyte consequences. These drugs could be anti-hypertensive agents, hormones, antipsychotics or steroids. There is paucity of published literature on electrolyte disturbances caused by drugs. The purpose of our study was to evaluate the electrolyte disturbances caused by various drugs in critically ill patients.Methods: Following approval of the Institutional Ethics Committee, data collection was started. Adverse Drug Reactions (ADRs) presenting as an electrolyte disturbance in emergency medicine department or occurring in hospitalized patients in the Intensive care unit (ICU) of our hospital was be collected. ADRs resulting into electrolyte disturbances were identified and analysed in detail for demographic details, types of electrolyte disturbances, seriousness, severity, causality and preventability of ADRs. Fisher's exact test was done to find out the statistical difference between the electrolyte disturbances and different drugs.Results: Total 58 ADRs were reported as an electrolyte disturbance. Mean age of the patients affected was 52.48 years. Highest number of ADRs were observed in the age group of 61 to 70 years. Hypokalemia constituted 32 cases (55.2%) followed by hyponatremia (25.9%), hyperkalemia (6.9%), hypernatremia (6.9%), hypocalcemia (1.7%), hypomagnesemia (1.7%) and hypophosphatemia (1.7%). Insulin was associated with maximum cases of ADRs (27.6%).Conclusions: Electrolyte disturbances constitutes a major chunk of ADRs especially in critically ill patients. The physicians must be well-versed with the dynamics of fluid-electrolyte balance

Characterization Of Probiotic Lactic Acid Bacteria From Honey And Assessment Of Their Effects On Consumption By Type-2- Diabetes Using Wistar Rat

The relevance of probiotic, especially lactic acid bacteria cannot be over emphasized. In this present study three honey sources were serially diluted and cultured on De Man, Rogosa and Sharpe (MRS) agar among which only one of this sources grew on MRS agar. The pure Lactobacilli isolate were subjected to gram staining, biochemical tests, physiological test, molecular analysis using Polymerase Chain Reaction (PCR) techniques and Deoxyribonucleotide (DNA) sequencing. Only one isolate was obtained known as Enterococcus fecalis. The isolate was subjected to probiotic selection and was found fit for consumption, however their effect when consumed by type-2 diabetic are alarming and based on the outcome of this study, diabetic patient are advised not consume honey

Linking chondrocyte and synovial transcriptional profile to clinical phenotype in osteoarthritis.

OBJECTIVES: To determine how gene expression profiles in osteoarthritis joint tissues relate to patient phenotypes and whether molecular subtypes can be reproducibly captured by a molecular classification algorithm. METHODS: We analysed RNA sequencing data from cartilage and synovium in 113 osteoarthritis patients, applying unsupervised clustering and Multi-Omics Factor Analysis to characterise transcriptional profiles. We tested the association of the molecularly defined patient subgroups with clinical characteristics from electronic health records. RESULTS: We detected two patient subgroups in low-grade cartilage (showing no/minimal degeneration, cartilage normal/softening only), with differences associated with inflammation, extracellular matrix-related and cell adhesion pathways. The high-inflammation subgroup was associated with female sex (OR 4.12, p=0.0024) and prescription of proton pump inhibitors (OR 4.21, p=0.0040). We identified two independent patient subgroupings in osteoarthritis synovium: one related to inflammation and the other to extracellular matrix and cell adhesion processes. A seven-gene classifier including MMP13, APOD, MMP2, MMP1, CYTL1, IL6 and C15orf48 recapitulated the main axis of molecular heterogeneity in low-grade knee osteoarthritis cartilage (correlation ρ=-0.88, p<10-10) and was reproducible in an independent patient cohort (ρ=-0.85, p<10-10). CONCLUSIONS: These data support the reproducible stratification of osteoarthritis patients by molecular subtype and the exploration of new avenues for tailored treatments

Development of Non-Natural Flavanones as Antimicrobial Agents

With growing concerns over multidrug resistance microorganisms, particularly strains of bacteria and fungi, evolving to become resistant to the antimicrobial agents used against them, the identification of new molecular targets becomes paramount for novel treatment options. Recently, the use of new treatments containing multiple active ingredients has been shown to increase the effectiveness of existing molecules for some infections, often with these added compounds enabling the transport of a toxic molecule into the infecting species. Flavonoids are among the most abundant plant secondary metabolites and have been shown to have natural abilities as microbial deterrents and anti-infection agents in plants. Combining these ideas we first sought to investigate the potency of natural flavonoids in the presence of efflux pump inhibitors to limit Escherichia coli growth. Then we used the natural flavonoid scaffold to synthesize non-natural flavanone molecules and further evaluate their antimicrobial efficacy on Escherichia coli, Bacillus subtilis and the fungal pathogens Cryptococcus neoformans and Aspergillus fumigatus. Of those screened, we identified the synthetic molecule 4-chloro-flavanone as the most potent antimicrobial compound with a MIC value of 70 µg/mL in E. coli when combined with the inhibitor Phe-Arg-ß-naphthylamide, and MICs of 30 µg/mL in S. cerevesiae and 30 µg/mL in C. neoformans when used alone. Through this study we have demonstrated that combinatorial synthesis of non-natural flavonones can identify novel antimicrobial agents with activity against bacteria and fungi but with minimal toxicity to human cells

Bone Marrow Myeloid Cells Regulate Myeloid-Biased Hematopoietic Stem Cells via a Histamine-Dependent Feedback Loop

Myeloid-biased hematopoietic stem cells (MB-HSCs) play critical roles in recovery from injury, but little is known about how they are regulated within the bone marrow niche. Here we describe an auto-/paracrine physiologic circuit that controls quiescence of MB-HSCs and hematopoietic progenitors marked by histidine decarboxylase (Hdc). Committed Hdc+ myeloid cells lie in close anatomical proximity to MB-HSCs and produce histamine, which activates the H2 receptor on MB-HSCs to promote their quiescence and self-renewal. Depleting histamine-producing cells enforces cell cycle entry, induces loss of serial transplant capacity, and sensitizes animals to chemotherapeutic injury. Increasing demand for myeloid cells via lipopolysaccharide (LPS) treatment specifically recruits MB-HSCs and progenitors into the cell cycle; cycling MB-HSCs fail to revert into quiescence in the absence of histamine feedback, leading to their depletion, while an H2 agonist protects MB-HSCs from depletion after sepsis. Thus, histamine couples lineage-specific physiological demands to intrinsically primed MB-HSCs to enforce homeostasis. Chen et al. show that histidine decarboxylase (Hdc) marks quiescent myeloid-biased HSCs (MB-HSCs). Daughter myeloid cells form a spatial cluster with Hdc+ MB-HSCs and secrete histamine to enforce their quiescence and protect them from depletion, following activation by a variety of physiologic insults

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study.

BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.Cambridge work was funded by a CRUK programme grant awarded to DEN; Swedish work and tissue collections were funded by grants from the Linne Centre for Breast and Prostate Cancer (CRISP, grant 70867901), Karolinska Institutet, the Swedish Research Council (K2010-70X-20430-04-3), and the Swedish Cancer Society (11-0287).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ebiom.2015.07.01

Integration of copy number and transcriptomics provides risk stratification in prostate cancer : a discovery and validation cohort study

Study data are deposited in NCBI GEO (unique identifier number GSE70770).Background : Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods : In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. Findings : We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer ( MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions. Interpretation : For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.Publisher PDFPeer reviewe

A molecular quantitative trait locus map for osteoarthritis

Funder: Medical Research Council Centre for Integrated Research into Musculoskeletal Ageing grant (148985)Funder: Versus Arthritis; Tissue Engineering and Regenerative Therapies Centre (21156)Abstract: Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis

A molecular quantitative trait locus map for osteoarthritis

Funder: Medical Research Council Centre for Integrated Research into Musculoskeletal Ageing grant (148985)Funder: Versus Arthritis; Tissue Engineering and Regenerative Therapies Centre (21156)Abstract: Osteoarthritis causes pain and functional disability for over 500 million people worldwide. To develop disease-stratifying tools and modifying therapies, we need a better understanding of the molecular basis of the disease in relevant tissue and cell types. Here, we study primary cartilage and synovium from 115 patients with osteoarthritis to construct a deep molecular signature map of the disease. By integrating genetics with transcriptomics and proteomics, we discover molecular trait loci in each tissue type and omics level, identify likely effector genes for osteoarthritis-associated genetic signals and highlight high-value targets for drug development and repurposing. These findings provide insights into disease aetiopathology, and offer translational opportunities in response to the global clinical challenge of osteoarthritis