Three-dimensional nano-structured silver on gold interdigitated microband array electrode for nitrate determination

414-419<span style="font-size:9.0pt;mso-ansi-language: EN-US" lang="EN-US">A new type of micro amperometric sensing chip based on gold interdigitated microband array (Au-IDA) electrode for trace nitrate determination has been developed. The Au-IDA microelectrode is fabricated with micro-electro-mechanical systems technology. Three-dimensional (3D) nano-structured dendritic silver is electrochemically deposited on the Au-IDA microelectrode surface, which shows superior electrocatalysis property in facilitating nitrate reduction. The results show that the sensing chip has a sensitivity of 9.5 nA/μ<span style="font-size:9.0pt; mso-ansi-language:EN-US" lang="EN-US">mol/L, limit of detection of 10 μmol/L, detection dynamic range of 10-1000 μmol/L , and linear range of 25-1000 μmol/L nitrate (R2=0.9998). Interference analysis with 9 kinds of ions (NO2−<span style="font-size:9.0pt; mso-ansi-language:EN-US" lang="EN-US">, F<span style="font-size:9.0pt; mso-fareast-font-family:" ms="" mincho";mso-ansi-language:en-us"="" lang="EN-US">−, PO43−, H2PO4<span style="font-size:9.0pt; mso-fareast-font-family:" ms="" mincho";mso-ansi-language:en-us"="" lang="EN-US">−, SO42−, CO32−, NH4+, Na+ and K+) commonly found in surface water indicates that the proposed microchips have good selectivity to NO3−<span style="font-size:9.0pt;mso-ansi-language: EN-US" lang="EN-US">. It is noteworthy that the proposed 3D nano-structured dendritic silver modified Au-IDA microelectrode could be used for nitrate analysis in neutral media which is important for field and real-time monitoring nitrate ions in natural water. </span

Differential Responses of Retinal Neurons and Glia Revealed via Proteomic Analysis on Primary and Secondary Retinal Ganglion Cell Degeneration.

To explore the temporal profile of retinal proteomes specific to primary and secondary retinal ganglion cell (RGC) loss. Unilateral partial optic nerve transection (pONT) was performed on the temporal side of the rat optic nerve. Temporal and nasal retinal samples were collected at 1, 4 and 8 weeks after pONT (n = 4 each) for non-biased profiling with a high-resolution hybrid quadrupole time-of-flight mass spectrometry running on label-free SWATHTM acquisition (SCIEX). An information-dependent acquisition ion library was generated using ProteinPilot 5.0 and OneOmics cloud bioinformatics. Combined proteome analysis detected 2531 proteins with a false discovery rate of &lt;1%. Compared to the nasal retina, 10, 25 and 61 significantly regulated proteins were found in the temporal retina at 1, 4, and 8 weeks, respectively (p &lt; 0.05, FC ≥ 1.4 or ≤0.7). Eight proteins (ALDH1A1, TRY10, GFAP, HBB-B1, ALB, CDC42, SNCG, NEFL) were differentially expressed for at least two time points. The expressions of ALDH1A1 and SNCG at nerve fibers were decreased along with axonal loss. Increased ALDH1A1 localization in the inner nuclear layer suggested stress response. Increased GFAP expression demonstrated regional reactivity of astrocytes and Muller cells. Meta-analysis of gene ontology showed a pronounced difference in endopeptidase and peptidase inhibitor activity. Temporal proteomic profiling demonstrates established and novel protein targets associated with RGC damage

Human tear proteome dataset in response to daily wear of water gradient contact lens using SWATH-MS approach

Water Gradient Contact Lens (WGCL) is a new generation material that combines the benefits of Silicone hydrogel (SiHy) and traditional hydrogel contact lenses by modifying the materials between the core and the surface. However, its impact on tear proteome has not been explored. Tears were collected on healthy young adults using Schirmer's strip at baseline, 1-week, and 1-month of WGCL lens wear (n=15) and age-matched untouched controls (n=10). Equal amounts of tears samples from individuals of WGCL and control groups were randomly pooled to form representative equal parts at each condition (n=3 for WGCL wear and age-matched untouched control group) at each condition (baseline, 1-week, and 1-month). Tears were prepared using the S-Trap sample preparation followed by the analysis of a TripleTOF 6600 mass spectrometer. Using Information-dependent acquisition (IDA), a total of 725 tear proteins (6760 distinct peptides) were identified in the constructed spectral library at 1% FDR. Using data-independent acquisition (SWATH-MS), data were analyzed and processed using PeakView (v2.2, SCIEX), with the top differentially expressed proteins at each time point (baseline, 1-week, and 1-month) presented. All acquired raw data (IDA and SWATH-MS) were submitted and published on the Peptide Atlas public repository (http://www.peptideatlas.org/) for general release (Data ID PASS01589)

A four-gene signature-derived risk score for glioblastoma: prospects for prognostic and response predictive analyses

Objective: Glioblastoma (GBM) is the most common primary malignant brain tumor regulated by numerous genes, with poor survival outcomes and unsatisfactory response to therapy. Therefore, a robust, multi-gene signature-derived model is required to predict the prognosis and treatment response in GBM. Methods: Gene expression data of GBM from TCGA and GEO datasets were used to identify differentially expressed genes (DEGs) through DESeq2 or LIMMA methods. The DEGs were then overlapped and used for survival analysis by univariate and multivariate COX regression. Based on the gene signature of multiple survival-associated DEGs, a risk score model was established, and its prognostic and predictive role was estimated through Kaplan-Meier analysis and log-rank test. Gene set enrichment analysis (GSEA) was conducted to explore high-risk score-associated pathways. Western blot was used for protein detection. Results: Four survival-associated DEGs of GBM were identified: OSMR, HOXC10, SCARA3, and SLC39A10. The four-gene signature-derived risk score was higher in GBM than in normal brain tissues. GBM patients with a high-risk score had poor survival outcomes. The high-risk group treated with temozolomide chemotherapy or radiotherapy survived for a shorter duration than the low-risk group. GSEA showed that the high-risk score was enriched with pathways such as vasculature development and cell adhesion. Western blot confirmed that the proteins of these four genes were differentially expressed in GBM cells. Conclusions: The four-gene signature-derived risk score functions well in predicting the prognosis and treatment response in GBM and will be useful for guiding therapeutic strategies for GBM patients