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RNA integrity numbers (RINs) are a standardized method for semi-quantification of RNA degradation, and are used in quality control prior to transcriptional profiling analysis. Recent work has demonstrated that RINs are associated with downstream transcriptional profiling, and correction procedures are typically employed in bioinformatic analysis pipelines to attempt to control for RIN’s influence on gene expression. However, relatively little work has been done to determine whether RIN’s influence is random, or is specifically targeted to a subset of mRNAs. We tested the hypothesis that RIN would be associated with a robust transcriptional profile seen across multiple studies.To test this, we downloaded subsets of raw transcriptional data from six published studies. We only included control, non-pathological post-mortem human brain tissue (n = 383 samples) in which independent subjects’ RIN values were also reported. A robust set of mRNAs consistently and significantly correlated with RIN across multiple studies, appearing to be selectively degraded as RIN declines. Many of the affected gene expression pathways are related to neurons (e.g., vesicle, mRNA transport, synapse, and mitochondria), suggesting that neuronal synaptic mRNA may be particularly vulnerable to degradation. Subsequent analysis of the relationship between RIN and vulnerable mRNA expression revealed most of the decay occurred over a relatively narrow RIN range of 7.2-8.6, with RIN values > 8.6 showing a ceiling effect, and those < 7.2 showing a floor effect on gene expression. Our data suggests that the RIN effect is pathway selective and non-linear, which may be an important consideration for current bioinformatic RIN correcting procedures, particularly in datasets in which declining RIN is confounded with a pathology under study (e.g., in Alzheimer’s disease).

Isolation and analysis of circulating tumor cells (CTCs) from the blood of patients at risk of metastatic cancers is a promising approach to improving cancer treatment. However, CTC isolation is difficult due to low CTC abundance and heterogeneity. Previously, we reported an ensemble-decision aliquot ranking (eDAR) platform for the rare cell and CTC isolation with high throughput, greater than 90% recovery, and high sensitivity, allowing detection of low surface antigen-expressing cells linked to metastasis. Here we demonstrate a sequential eDAR platform capable of isolating rare cells from whole blood with high purity. This improvement in purity is achieved by using a sequential sorting and flow stretching design in which whole blood is sorted and fluid elements are stretched using herringbone features and the parabolic flow profile being sorted a second time. This platform can be used to collect single CTCs in a multiwell plate for downstream analysis.

Intranasal insulin is a safe and effective method for ameliorating memory deficits associated with pathological brain aging. However, the impact of different formulations and the duration of treatment on insulin’s efficacy and the cellular processes targeted by the treatment remain unclear. Here, we tested whether intranasal insulin aspart, a short-acting insulin formulation, could alleviate memory decline associated with aging and whether long-term treatment affected regulation of insulin receptors and other potential targets. Outcome variables included measures of spatial learning and memory, autoradiography and immunohistochemistry of the insulin receptor, and hippocampal microarray analyses. Aged Fischer 344 rats receiving long-term (3 months) intranasal insulin did not show significant memory enhancement on the Morris water maze task. Autoradiography results showed that long-term treatment reduced insulin binding in the thalamus but not the hippocampus. Results from hippocampal immunofluorescence revealed age-related decreases in insulin immunoreactivity that were partially offset by intranasal administration. Microarray analyses highlighted numerous insulin-sensitive genes, suggesting insulin aspart was able to enter the brain and alter hippocampal RNA expression patterns including those associated with tumor suppression. Our work provides insights into potential mechanisms of intranasal insulin and insulin resistance, and highlights the importance of treatment duration and the brain regions targeted.

This paper describes the dielectrophoretic (DEP) forces generated by a bipolar electrode (BPE) in a microfluidic device and elucidates the impact of faradaic ion enrichment and depletion (FIE and FID) on electric field gradients. DEP technologies for manipulating biological cells provide several distinct advantages over other cell-handling techniques including label-free selectivity, inexpensive device components, and amenability to single-cell and array-based applications. However, extension to the array format is nontrivial, and DEP forces are notoriously short-range, limiting device dimensions and throughput. BPEs present an attractive option for DEP because of the ease with which they can be arrayed. Here, we present experimental results demonstrating both negative DEP (nDEP) attraction and repulsion of B-cells from each a BPE cathode and anode. The direction of nDEP force in each case was determined by whether the conditions for FIE or FID were chosen in the experimental design. We conclude that FIE and FID zones generated by BPEs can be exploited to shape and extend the electric field gradients that are responsible for DEP force.

Ensemble-decision aliquot ranking (eDAR) is a sensitive and high-throughput method to analyze circulating tumor cells (CTCs) from peripheral blood. Here, we report the next generation of eDAR, where we designed and optimized a new hydrodynamic switching scheme for the active sorting step in eDAR, which provided fast cell sorting with an improved reproducibility and stability. The microfluidic chip was also simplified by incorporating a functional area for subsequent purification using microslits fabricated by standard lithography method. Using the reported second generation of eDAR, we were able to analyze 1 mL of whole-blood samples in 12.5 min, with a 95% recovery and a zero false positive rate (n = 15).

Objective This study aims to add clarity to the relationship between deep and periventricular brain white matter hyperintensities (WMHs), cerebral blood flow (CBF), and cerebrovascular risk in older persons. Methods Deep white matter hyperintensity (dWMH) and periventricular white matter hyperintensity (pWMH) and regional gray matter (GM) and white matter (WM) blood flow from arterial spin labeling were quantified from magnetic resonance imaging scans of 26 cognitively normal elderly subjects stratified by cerebrovascular disease (CVD) risk. Fluid-attenuated inversion recovery images were acquired using a high-resolution 3-dimensional (3-D) sequence that reduced partial volume effects seen with slice-based techniques. Results dWMHs but not pWMHs were increased in patients at high risk of CVD; pWMHs but not dWMHs were associated with decreased regional cortical (GM) blood flow. We also found that blood flow in WM is decreased in regions of both pWMH and dWMH, with a greater degree of decrease in pWMH areas. Conclusions WMHs are usefully divided into dWMH and pWMH regions because they demonstrate differential effects. 3-D regional WMH volume is a potentially valuable marker for CVD based on associations with cortical CBF and WM CBF.

The efficient selection and isolation of individual cells of interest from a mixed population is desired in many biomedical and clinical applications. Here we show the concept of using photoswitchable semiconducting polymer dots (Pdots) as an optical ‘painting' tool, which enables the selection of certain adherent cells based on their fluorescence, and their spatial and morphological features, under a microscope. We first develop a Pdot that can switch between the bright (ON) and dark (OFF) states reversibly with a 150-fold contrast ratio on irradiation with ultraviolet or red light. With a focused 633-nm laser beam that acts as a ‘paintbrush' and the photoswitchable Pdots as the ‘paint', we select and ‘paint' individual Pdot-labelled adherent cells by turning on their fluorescence, then proceed to sort and recover the optically marked cells (with 90% recovery and near 100% purity), followed by genetic analysis., Isolation of individual cells from mixed populations is desirable for many biomedical applications. Here the authors use photoswitchable Pdots to allow 'optical painting', where cells of interest are marked based on their visual characteristics, and can then be isolated by fluorescence activated cell sorting.

Background and purpose Vascular dementia (VAD) is a complex diagnosis at times difficult to distinguish from Alzheimer's disease (AD). MRI scans often show white matter hyperintensities (WMH) in both conditions. WMH increase with age, and both VAD and AD are associated with aging, thus presenting an attribution conundrum. In this study, we sought to show whether the amount of WMH in deep white matter (dWMH), versus periventricular white matter (PVH), would aid in the distinction between VAD and AD, independent of age. Methods Blinded semiquantitative ratings of WMH validated by objective quantitation of WMH volume from standardized MRI image acquisitions. PVH and dWMH were rated separately and independently by two different examiners using the Scheltens scale. Receiver operator characteristic (ROC) curves were generated using logistic regression to assess classification of VAD (13 patients) versus AD (129 patients). Clinical diagnoses were made in a specialty memory disorders clinic. Results Using PVH rating alone, overall classification (area under the ROC curve, AUC) was 75%, due only to the difference in age between VAD and AD patients in our study and not PVH. In contrast, dWMH rating produced 86% classification accuracy with no independent contribution from age. A global Longstreth rating that combines dWMH and PVH gave an 88% AUC. Conclusions Increased dWMH indicate a higher likelihood of VAD versus AD. Assessment of dWMH on MRI scans using Scheltens and Longstreth scales may aid the clinician in distinguishing the two conditions.

Circulating tumor cells (CTCs) are shed from a solid tumor into the bloodstream and can seed new metastases. CTCs hold promise for cancer diagnosis and prognosis and to increase our understanding of the metastatic process. However, their low numbers in blood and varied phenotypic characteristics make their detection and isolation difficult. One source of heterogeneity among CTCs is molecular: When they leave the primary tumor, these cells must undergo a molecular transition, which increases their mobility and chance of survival in the blood. During this molecular transition, the cells lose some of their epithelial character, which is manifested by the expression of the cell surface antigen known as epithelial cell adhesion molecule (EpCAM). Some tumors shed CTCs that express high levels of EpCAM; others release cells that have a low level of the antigen. Nevertheless, many CTC isolation techniques rely on the detection of EpCAM to discriminate CTCs from other cells in the blood. We previously reported a high-throughput immunofluorescence-based technology that targets EpCAM to rank aliquots of blood for the presence or absence of a CTC. This technology, termed ensemble decision aliquot ranking (eDAR), recovered spiked-in cancer cells (taken from a model EpCAM(high) cell line) from blood at an efficiency of 95%. In this paper, we evaluated eDAR for recovery of cells that have low EpCAM expression and developed an immunofluorescence labeling strategy that significantly enhances the method's performance. Specifically, we used a cocktail of primary antibodies for both epithelial and mesenchymal antigens as well as a dye-linked secondary antibody. The cocktail allowed us to reliably detect a model EpCAM(low) cell line for triple negative breast cancer, MDA-MB-231, with a recovery efficiency of 86%. Most significantly, we observed an average of 6-fold increase in the number of CTCs isolated from blood samples from breast cancer patients. These findings underscore the importance of benchmarking CTC technologies with model cell lines that express both high and low levels of EpCAM.