Combining Antigen-Based Therapy with GABA Treatment Synergistically Prolongs Survival of Transplanted ß-Cells in Diabetic NOD Mice

Antigen-based therapies (ABTs) very effectively prevent the development of type 1 diabetes (T1D) when given to young nonobese diabetic (NOD) mice, however, they have little or no ability to reverse hyperglycemia in newly diabetic NOD mice. More importantly, ABTs have not yet demonstrated an ability to effectively preserve residual ß-cells in individuals newly diagnosed with type 1 diabetes (T1D). Accordingly, there is great interest in identifying new treatments that can be combined with ABTs to safely protect ß-cells in diabetic animals. The activation of γ-aminobutyric acid (GABA) receptors (GABA-Rs) on immune cells has been shown to prevent T1D, experimental autoimmune encephalomyelitis (EAE) and rheumatoid arthritis in mouse models. Based on GABA's ability to inhibit different autoimmune diseases and its safety profile, we tested whether the combination of ABT with GABA treatment could prolong the survival of transplanted ß-cells in newly diabetic NOD mice. Newly diabetic NOD mice were untreated, or given GAD/alum (20 or 100 µg) and placed on plain drinking water, or water containing GABA (2 or 6 mg/ml). Twenty-eight days later, they received syngenic pancreas grafts and were monitored for the recurrence of hyperglycemia. Hyperglycemia reoccurred in the recipients given plain water, GAD monotherapy, GABA monotherapy, GAD (20 µg)+GABA (2 mg/ml), GAD (20 µg)+GABA (6 mg/ml) and GAD (100 µg)+GABA (6 mg/ml) about 1, 2-3, 3, 2-3, 3-8 and 10-11 weeks post-transplantation, respectively. Thus, combined GABA and ABT treatment had a synergistic effect in a dose-dependent fashion. These findings suggest that co-treatment with GABA (or other GABA-R agonists) may provide a new strategy to safely enhance the efficacy of other therapeutics designed to prevent or reverse T1D, as well as other T cell-mediated autoimmune diseases

An analysis of photoemission and inverse photoemission spectra of Si(111) and sulphur-passivated InP(001) surfaces

Photoemission (PES) and inverse-photoemission spectra (IPES) for the sulphur-passivated InP(001) surface are compared with theoretical predictions based on density-functional calculations. As a test case for our methods, we also present a corresponding study of the better known Si(111) surface. The reported spectra for InP(001)-S agree well with the calculated ones if the surface is assumed to consist of a mixture of two phases, namely, the fully S-covered $(2\times2)$-reconstructed structure, which contains four S atoms in the surface unit-cell, and a $(2\times2)$ structure containing two S and two P atoms per unit cell. The latter has recently been identified in total-energy calculations as well as in core-level spectra of S-passivated Si(111)-$(2\times1)$ is in excellent agreement with the calculations. The comparison of the experimental-PES with our calculations provides additional considerations regarding the nature of the sample surface. It is also found that the commonly-used density-of-states approximation to the photo- and inverse- photoemission spectra is not valid for these systems.Comment: Submitted to Phys. Rev. B; 6 postscript formatted pages; 7 figures in gif format; postscript figures available upon reques

Chemical Explosion, Covid-19, and Environmental Justice: insights From Low-Cost air Quality Sensors

OBJECTIVES: to examine the impact of the Intercontinental Terminals Company (ITC) fire and COVID-19 on airborne particulate matter (PM) concentrations and the PM disproportionally affecting communities in Houston using low-cost sensors. METHODS: We compared measurements from a network of low-cost sensors with a separate network of monitors from the Environmental Protection Agency (EPA) in the Houston metropolitan area from Mar 18, 2019, to Dec 31, 2020. Further, we examined the associations between neighborhood-level sociodemographic status and air pollution patterns by linking the low-cost sensor data to EPA environmental justice screening and mapping systems. FINDINGS: We found increased PM levels during ITC fire and pre-COVID-19, and lower PM levels after the COVID-19 lockdown, comparable to observations from the regulatory monitors, with higher variations and a greater number of locations with high PM levels detected. In addition, the environmental justice analysis showed positive associations between higher PM levels and the percentage of minority, low-income population, and demographic index. IMPLICATION: Our study indicates that low-cost sensors provide pollutant measures with higher spatial variations and a better ability to identify hot spots and high peak concentrations. These advantages provide critical information for disaster response and environmental justice studies. SYNOPSIS: We used measurements from a low-cost sensor network for air pollution monitoring and environmental justice analysis to examine the impact of anthropogenic and natural disasters

Oral Treatment with γ-Aminobutyric Acid Improves Glucose Tolerance and Insulin Sensitivity by Inhibiting Inflammation in High Fat Diet-Fed Mice

Adipocyte and β-cell dysfunction and macrophage-related chronic inflammation are critical for the development of obesity-related insulin resistance and type 2 diabetes mellitus (T2DM), which can be negatively regulated by Tregs. Our previous studies and those of others have shown that activation of γ-aminobutyric acid (GABA) receptors inhibits inflammation in mice. However, whether GABA could modulate high fat diet (HFD)-induced obesity, glucose intolerance and insulin resistance has not been explored. Here, we show that although oral treatment with GABA does not affect water and food consumption it inhibits the HFD-induced gain in body weights in C57BL/6 mice. Furthermore, oral treatment with GABA significantly reduced the concentrations of fasting blood glucose, and improved glucose tolerance and insulin sensitivity in the HFD-fed mice. More importantly, after the onset of obesity and T2DM, oral treatment with GABA inhibited the continual HFD-induced gain in body weights, reduced the concentrations of fasting blood glucose and improved glucose tolerance and insulin sensitivity in mice. In addition, oral treatment with GABA reduced the epididymal fat mass, adipocyte size, and the frequency of macrophage infiltrates in the adipose tissues of HFD-fed mice. Notably, oral treatment with GABA significantly increased the frequency of CD4+Foxp3+ Tregs in mice. Collectively, our data indicated that activation of peripheral GABA receptors inhibited the HFD-induced glucose intolerance, insulin resistance, and obesity by inhibiting obesity-related inflammation and up-regulating Treg responses in vivo. Given that GABA is safe for human consumption, activators of GABA receptors may be valuable for the prevention of obesity and intervention of T2DM in the clinic

Inferring Geographic Coordinates of Origin for Europeans Using Small Panels of Ancestry Informative Markers

Recent large-scale studies of European populations have demonstrated the existence of population genetic structure within Europe and the potential to accurately infer individual ancestry when information from hundreds of thousands of genetic markers is used. In fact, when genomewide genetic variation of European populations is projected down to a two-dimensional Principal Components Analysis plot, a surprising correlation with actual geographic coordinates of self-reported ancestry has been reported. This substructure can hamper the search of susceptibility genes for common complex disorders leading to spurious correlations. The identification of genetic markers that can correct for population stratification becomes therefore of paramount importance. Analyzing 1,200 individuals from 11 populations genotyped for more than 500,000 SNPs (Population Reference Sample), we present a systematic exploration of the extent to which geographic coordinates of origin within Europe can be predicted, with small panels of SNPs. Markers are selected to correlate with the top principal components of the dataset, as we have previously demonstrated. Performing thorough cross-validation experiments we show that it is indeed possible to predict individual ancestry within Europe down to a few hundred kilometers from actual individual origin, using information from carefully selected panels of 500 or 1,000 SNPs. Furthermore, we show that these panels can be used to correctly assign the HapMap Phase 3 European populations to their geographic origin. The SNPs that we propose can prove extremely useful in a variety of different settings, such as stratification correction or genetic ancestry testing, and the study of the history of European populations

Nanotechnology for catalysis and solar energy conversion

This roadmap on Nanotechnology for Catalysis and Solar Energy Conversion focuses on the application of nanotechnology in addressing the current challenges of energy conversion: 'high efficiency, stability, safety, and the potential for low-cost/scalable manufacturing' to quote from the contributed article by Nathan Lewis. This roadmap focuses on solar-to-fuel conversion, solar water splitting, solar photovoltaics and bio-catalysis. It includes dye-sensitized solar cells (DSSCs), perovskite solar cells, and organic photovoltaics. Smart engineering of colloidal quantum materials and nanostructured electrodes will improve solar-to-fuel conversion efficiency, as described in the articles by Waiskopf and Banin and Meyer. Semiconductor nanoparticles will also improve solar energy conversion efficiency, as discussed by Boschloo et al in their article on DSSCs. Perovskite solar cells have advanced rapidly in recent years, including new ideas on 2D and 3D hybrid halide perovskites, as described by Spanopoulos et al 'Next generation' solar cells using multiple exciton generation (MEG) from hot carriers, described in the article by Nozik and Beard, could lead to remarkable improvement in photovoltaic efficiency by using quantization effects in semiconductor nanostructures (quantum dots, wires or wells). These challenges will not be met without simultaneous improvement in nanoscale characterization methods. Terahertz spectroscopy, discussed in the article by Milot et al is one example of a method that is overcoming the difficulties associated with nanoscale materials characterization by avoiding electrical contacts to nanoparticles, allowing characterization during device operation, and enabling characterization of a single nanoparticle. Besides experimental advances, computational science is also meeting the challenges of nanomaterials synthesis. The article by Kohlstedt and Schatz discusses the computational frameworks being used to predict structure–property relationships in materials and devices, including machine learning methods, with an emphasis on organic photovoltaics. The contribution by Megarity and Armstrong presents the 'electrochemical leaf' for improvements in electrochemistry and beyond. In addition, biohybrid approaches can take advantage of efficient and specific enzyme catalysts. These articles present the nanoscience and technology at the forefront of renewable energy development that will have significant benefits to society

The clinicopathologic observation, c-KIT gene mutation and clonal status of gastrointestinal stromal tumor in the sacrum

<p>Abstract</p> <p>Background</p> <p>It is very rare that gastrointestinal stromal tumor (GIST) occurs in the sacrum. Only one case of GIST occuring in the sacral region, with intracranial metastasis, has been reported in the literature. Moreover, only few cases have been published in literature about its clonal origin.</p> <p>Case presentation</p> <p>In this report, we present a rare case of GIST occuring in the sacrum and describe its clinicopathologic features, c-KIT gene mutation and clonal status. Microscopically, the lesion was composed of spindle cells arranged in cords, knitted and whirlpool patterns. Trabecula of bone were found in the lesion. The cytoplasm of tumor cells were abundant, and the nuclei were fusiform. Mitotic figures were rare. Immunohistochemically, the tumor cells showed positive reactivity for CD117 and CD34. On mutation analysis, a c-KIT gene mutation was found in exon 11. The result of clonal analysis demonstrated that the GIST was monoclonal.</p> <p>Conclusion</p> <p>In summary, we showed that tumor material, phenotypically identical with GISTs was found in the sacrum. It is difficult to differentiate GISTs from other spindle cell tumors, hence the need for immunohistochemistry, the examination of c-KIT gene amplification and sequencing.</p

Enzyme classification with peptide programs: a comparative study

<p>Abstract</p> <p>Background</p> <p>Efficient and accurate prediction of protein function from sequence is one of the standing problems in Biology. The generalised use of sequence alignments for inferring function promotes the propagation of errors, and there are limits to its applicability. Several machine learning methods have been applied to predict protein function, but they lose much of the information encoded by protein sequences because they need to transform them to obtain data of fixed length.</p> <p>Results</p> <p>We have developed a machine learning methodology, called peptide programs (PPs), to deal directly with protein sequences and compared its performance with that of Support Vector Machines (SVMs) and BLAST in detailed enzyme classification tasks. Overall, the PPs and SVMs had a similar performance in terms of Matthews Correlation Coefficient, but the PPs had generally a higher precision. BLAST performed globally better than both methodologies, but the PPs had better results than BLAST and SVMs for the smaller datasets.</p> <p>Conclusion</p> <p>The higher precision of the PPs in comparison to the SVMs suggests that dealing with sequences is advantageous for detailed protein classification, as precision is essential to avoid annotation errors. The fact that the PPs performed better than BLAST for the smaller datasets demonstrates the potential of the methodology, but the drop in performance observed for the larger datasets indicates that further development is required.</p> <p>Possible strategies to address this issue include partitioning the datasets into smaller subsets and training individual PPs for each subset, or training several PPs for each dataset and combining them using a bagging strategy.</p

Overexpression of LCMR1 is significantly associated with clinical stage in human NSCLC

<p>Abstract</p> <p>Background</p> <p>Lung cancer is one of the most common human cancers and the leading cause of cancer death worldwide. The identification of lung cancer associated genes is essential for lung cancer diagnosis and treatment.</p> <p>Methods</p> <p>Differential Display-PCR technique was used to achieve the novel cDNA, which were then verified by real-time PCR. Northern blot was utilized to observe the expression of LCMR1 in different human tissues. 84 cases human NSCLC tissues and normal counterparts were analyzed for the expression of LCMR1 by immunohistochemistry.</p> <p>Results</p> <p>A novel 778-bp cDNA fragment from human large cell lung carcinoma cell lines 95C and 95D was obtained, and named <it>LCMR1 </it>(Lung Cancer Metastasis Related protein 1). LCMR1 was differentially expressed in different human tissues. LCMR1 was strongly overexpressed in NSCLC and its expression was significantly associated with clinical stage.</p> <p>Conclusion</p> <p>Our data indicated that <it>LCMR1</it>, strongly overexpressed in NSCLC, might have applications in the clinical diagnosis and treatment of lung cancer.</p