Use of inert gas jets to measure the forces required for mechanical gene transfection

Background

Abnormal blood glucose (BG) concentrations have been associated with increased morbidity and mortality in both critically ill adults and infants. Furthermore, hypoglycaemia and glycaemic variability have both been independently linked to mortality in these patients. Continuous Glucose Monitoring (CGM) devices have the potential to improve detection and diagnosis of these glycaemic abnormalities. However, sensor noise is a trade-off of the high measurement rate and must be managed effectively if CGMs are going to be used to monitor, diagnose and potentially help treat glycaemic abnormalities.

Aim

To develop a tool that will aid clinicians in identifying unusual CGM behaviour and highlight CGM data that potentially need to be interpreted with care.

Methods

CGM data and BG measurements from 50 infants at risk of hypoglycaemia were used. Unusual CGM measurements were classified using a stochastic model based on the kernel density method and historical CGM measurements from the cohort. CGM traces were colour coded with very unusual measurements coloured red, highlighting areas to be interpreted with care. A 5-fold validation of the model was Monte Carlo simulated 25 times to ensure an adequate model fit.

Results

The stochastic model was generated using ~67,000 CGM measurements, spread across the glycaemic range ~2-10?mmol/L. A 5-fold validation showed a good model fit: the model 80% confidence interval (CI) captured 83% of clinical CGM data, the model 90% CI captured 91% of clinical CGM data, and the model 99% CI captured 99% of clinical CGM data. Three patient examples show the stochastic classification method in use with 1) A stable, low variability patient which shows no unusual CGM measurements, 2) A patient with a very sudden, short hypoglycaemic event (classified as unusual), and, 3) A patient with very high, potentially un-physiological, glycaemic variability after day 3 of monitoring (classified as very unusual).

Conclusions

This study has produced a stochastic model and classification method capable of highlighting unusual CGM behaviour. This method has the potential to classify important glycaemic events (e.g. hypoglycaemia) as true clinical events or sensor noise, and to help identify possible sensor degradation. Colour coded CGM traces convey the information quickly and efficiently, while remaining computationally light enough to be used retrospectively or in real-time.     

Cortical potential imaging using L-curve and GCV method to choose the regularisation parameter

Background

The electroencephalography (EEG) is an attractive and a simple technique to measure the brain activity. It is attractive due its excellent temporal resolution and simple due to its non-invasiveness and sensor design. However, the spatial resolution of EEG is reduced due to the low conducting skull. In this paper, we compute the potential distribution over the closed surface covering the brain (cortex) from the EEG scalp potential. We compare two methods – L-curve and generalised cross validation (GCV) used to obtain the regularisation parameter and also investigate the feasibility in applying such techniques to N170 component of the visually evoked potential (VEP) data.

Methods

Using the image data set of the visible human man (VHM), a finite difference method (FDM) model of the head was constructed. The EEG dataset (256-channel) used was the N170 component of the VEP. A forward transfer matrix relating the cortical potential to the scalp potential was obtained. Using Tikhonov regularisation, the potential distribution over the cortex was obtained.

Results

The cortical potential distribution for three subjects was solved using both L-curve and GCV method. A total of 18 cortical potential distributions were obtained (3 subjects with three stimuli each – fearful face, neutral face, control objects).

Conclusions

The GCV method is a more robust method compared to L-curve to find the optimal regularisation parameter. Cortical potential imaging is a reliable method to obtain the potential distribution over cortex for VEP data.

     

Macrophage-specific up-regulation of apolipoprotein E gene expression by STAT1 is achieved via long range genomic interactions

In atherogenesis, macrophage-derived apolipoprotein E (apoE) has an athero-protective role by a mechanism that is not fully understood. We investigated the regulatory mechanisms involved in the modulation of apoE expression in macrophages. The experiments showed that the promoters of all genes of the apoE/apoCI/apoCIV/apoCII gene cluster are enhanced by multienhancer 2 (ME.2), a regulatory region that is located 15.9 kb downstream of the apoE gene. ME.2 interacts with the apoE promoter in a macrophage-specific manner. Transient transfections in RAW 264.7 macrophages showed that the activity of ME.2 was strongly decreased by deletion of either 87 bp from the 5' end or 131 bp from the 3' end. We determined that the minimal fragment of this promoter that can be activated by ME.2 is the proximal -100/+73 region. The analysis of the deletion mutants of ME.2 revealed the importance of the 5' end of ME.2 in apoE promoter transactivation. Chromatin conformational capture assays demonstrated that both ME.2 and ME.1 physically interacted with the apoE promoter in macrophages. Our data showed that phorbol 12-myristate 13-acetate-induced differentiation of macrophages is accompanied by a robust induction of apoE and STAT1 expression. In macrophages (but not in hepatocytes), STAT1 up-regulated apoE gene expression via ME.2. The STAT1 binding site was located in the 174-182 region of ME.2. In conclusion, the specificity of the interactions between the two multienhancers (ME.1 and ME.2) and the apoE promoter indicates that these distal regulatory elements play an important role in the modulation of apoE gene expression in a cell-specific manner.     

Proliferation, differentiation and characterization of osteoblasts from human BM mesenchymal cells

BACKGROUND: The objective of this study was to isolate osteoprogenitor cells (OPC) from BM mesenchymal stromal cells (MSC) and test their capacity to proliferate and differentiate into osteoblasts. METHODS: Human MSC were separated on a Percoll gradient and cultured in DMEM supplemented with 15% human serum, and characterized by flow cytometric analyzes for CD34, CD13, CD90, CD105 and CD117. To induce differentiation, cultured cells were exposed to 10(-7) m dexamethasone (dexa) and/or 10(-3) m sodium beta-glycerophosphate (beta-GlyP) and 1,25-dihydroxyvitamin D3 (calcitriol) or 9-cis-retinoic acid (9-RA). RESULTS: alkaline phosphatase (AP) activity was detected in cells irrespective of the dexa and/or beta-GlyP treatment. Antigenic phenotypes of MSC were CD34- (more than 99%) and CD13+ CD90+ CD105+ CD117+ (c. 50%). The treatment induced extracellular calcium deposition and gene and protein expression of osteonectin (ON) and bone sialoprotein (BSP): beta-GlyP induced an increase (c. 2.2-fold) of the ON gene and dexa augmented (c. 2.7-fold) the gene expression of BSP II. Gene expression of BSP I reached a maximum at 3 weeks of combined treatment. Osteocalcin gene expression was induced only after additional treatment with calcitriol or 9-RA. Ultrastructural analysis revealed the secretory phenotype of OPC. DISCUSSION: Under appropriate treatment, MSC can give rise to OPC that have the capacity to differentiate into osteoblasts characterized by the expression of osteogenic markers, osteoblastic properties and stromal BM cells phenotypes. These cells may represent a promising material to be utilized in orthopedic cellular therapy.     

Nonglutamate pore residues in ion selection and conduction in voltage-gated Ca(2+) channels

High-affinity, intrapore binding of Ca(2+) over competing ions is the essential feature in the ion selectivity mechanism of voltage-gated Ca(2+) channels. At the same time, several million Ca(2+) ions can travel each second through the pore of a single open Ca(2+) channel. How such high Ca(2+) flux is achieved in the face of tight Ca(2+) binding is a current area of inquiry, particularly from a structural point of view. The ion selectivity locus comprises four glutamate residues within the channel's pore. These glutamates make unequal contributions to Ca(2+) binding, underscoring a role for neighboring residues in pore function. By comparing two Ca(2+) channels (the L-type alpha(1C), and the non-L-type alpha(1A)) that differ in their pore properties but only differ at a single amino acid position near the selectivity locus, we have identified the amino-terminal neighbor of the glutamate residue in motif III as a determinant of pore function. This position is more important in the function of alpha(1C) channels than in alpha(1A) channels. For a systematic series of mutations at this pore position in alpha(1C), both unitary Ba(2+) conductance and Cd(2+) block of Ba(2+) current varied with residue volume. Pore mutations designed to make alpha(1C) more like alpha(1A) and vice versa revealed that relative selectivity for Ba(2+) over K(+) depended almost solely on pore sequence and not channel type. Analysis of thermodynamic mutant cycles indicates that the motif III neighbor normally interacts in a cooperative fashion with the locus, molding the functional behavior of the pore.     

Severity of oxidative stress generates different mechanisms of endothelial cell death

The role of reactive oxygen species (ROS) in the pathogenesis of vascular diseases is well established, but few data exist on the mechanisms by which ROS induce endothelial cell (EC) death. We examined the conditions and the mechanisms by which oxidative stress induces EC death, using cultured confluent bovine aortic ECs exposed for 30 min to different concentrations of hydroxyl radicals (HO*) generated by hydrogen peroxide (H(2)O(2)) in the presence of 100 microM ferrous sulfate (FeSO(4)). Cell viability assays, Hoechst DNA staining, TUNEL (TDT-mediated dUTP-biotin nick end-labeling) analysis, agarose gel electrophoresis and annexin V assay were used to determine the effect of HO* on the viability of ECs, and to distinguish between apoptosis and necrosis. The results showed that at concentrations of up to 0.1 mM H(2)O(2)/FeSO(4), the large majority of cells are viable, except for approximately 12.5% death, which occurs by apoptosis. At a concentration of 0.2 mM H(2)O(2), the cell viability is reduced to 66%, while EC apoptosis remained at comparable values (14%). At high oxidative stress (0.5 mM H(2)O(2)), the cell viability was drastically reduced (approximately 39%), and the prevalent form of death was necrosis; apoptosis accounted for only approximately 17%. Together, these data indicate that: (1) HO* induce EC death either by apoptosis or necrosis and (2) the mechanisms of EC death differ as a function of the concentration of HO. Thus, the same insult can cause apoptosis and/or necrosis, as a function of the intensity rather than the nature of the insult.