Pilot Programs in Medical Research

Metallurgical and Materials Transactions A - An Al-5.8 at. pct Mg (5.2 wt pct Mg) alloy was deformed in torsion within the solute drag regime to various strains, up to the failure strain of 10.8....

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There is no data on changes of PCT on the background of ABT in pregnant with not severe CAP. Aim: to study the role of dynamic of PCT in pregnant with not severe CAP as a marker of effective ABT. Materials: we studied PCT levels in 35 pregnant with CAP which formed the main group (age (Med [25–75%]) 25 [19–30] yrs, gestational age 30 [27–33] wks) and in a control group of 15 healthy pregnant (age 31 [25–37] yrs, gestational age 35 [34–37] wks). Methods: in pregnant with CAP PCT was measured on admission, before starting ABT (PCT-1) and on the 5th day of therapy (PCT-2). We used SMRT-CO scale to estimate the severity of CAP and respiratory rate (RR), body temperature (BT) and leukocyte count – to monitor clinical status. Results: on admission all patients had high BT (37,9 [37–38,2]°C ), increased RR (28 [24–31] per min.) and leukocytosis (11,9 [8,3–14,3]*109/l), also they had 2 or less points on the SMRT-CO scale which corresponds to not severe CAP. They were prescribed standard ABT with amoxicillin/clavulonate. On the 5th day of ABT we observed a significant decrease of BT, RR and leukocyte count. Dynamics of PCT is shown in [Table 1][1]. View this table: Table 1 Changes of PCT on the background of ABT Conclusion: dynamics of PCT can be used as a marker of effectiveness of ABT in pregnant with not severe CAP. [1]: #T1

Background and Purpose— Numerous imaging techniques have been developed and applied to evaluate brain hemodynamics. Among these are positron emission tomography, single photon emission computed tomog

Enzyme-linked immune-sorbent assay (ELISA) for the determination of PCT in human serum, plasma, tissue homogenates or cell culture supernatants. For research use only, not for use in diagnostic procedures.

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Complex coacervates are liquid–liquid phase separated systems, typically containing oppositely charged polyelectrolytes. They are widely studied for their functional properties as well as their potential involvement in cellular compartmentalization as biomolecular condensates. Diffusion and partitioning of s

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Increased Temporal Resolution for Dynamic Perfusion CT (PCT) with C-arm Flat-Detector CT, SST15-04, 9008589, Marcel Beister,

While provisional patent applications are never published and cannot become prior art, recent decisions from the U.S. Court of Appeals for the Federal Circuit illustrate that parties can nonetheless m...

Although transcriptomic profiling of kidney tissues or isolated glomeruli has provided insights into broad changes in the pathogenesis of diabetic kidney disease, the presence of multiple cell types in kidney samples limits what can be discerned about changes in specific types of cells. To better elucidate the mechanisms of early diabetic kidney injury, the authors used single-cell RNA sequencing technology to perform a gene expression analysis of individual kidney glomerular cells of a diabetic mouse model. A comparison of gene expression in normal versus diabetic mouse kidney cells at a single-cell level showed dynamic changes in the pattern of expressed genes. This approach may help identify important factors underlying the pathophysiology of diabetic kidney disease progression and point to potential new therapeutic approaches. Background Recent single-cell RNA sequencing (scRNA-seq) analyses have offered much insight into cell-specific gene expression profiles in normal kidneys. However, in diseased kidneys, understanding of changes in specific cells, particularly glomerular cells, remains limited. Methods To elucidate the glomerular cell–specific gene expression changes in diabetic kidney disease, we performed scRNA-seq analysis of isolated glomerular cells from streptozotocin-induced diabetic endothelial nitric oxide synthase (eNOS)–deficient (eNOS−/−) mice and control eNOS−/− mice. Results We identified five distinct cell populations, including glomerular endothelial cells, mesangial cells, podocytes, immune cells, and tubular cells. Using scRNA-seq analysis, we confirmed the expression of glomerular cell–specific markers and also identified several new potential markers of glomerular cells. The number of immune cells was significantly higher in diabetic glomeruli compared with control glomeruli, and further cluster analysis showed that these immune cells were predominantly macrophages. Analysis of differential gene expression in endothelial and mesangial cells of diabetic and control mice showed dynamic changes in the pattern of expressed genes, many of which are known to be involved in diabetic kidney disease. Moreover, gene expression analysis showed variable responses of individual cells to diabetic injury. Conclusions Our findings demonstrate the ability of scRNA-seq analysis in isolated glomerular cells from diabetic and control mice to reveal dynamic changes in gene expression in diabetic kidneys, with variable responses of individual cells. Such changes, which might not be apparent in bulk transcriptomic analysis of glomerular cells, may help identify important pathophysiologic factors contributing to the progression of diabetic kidney disease.