Cumulative studies have provided controversial evidence for the prognostic values of bone morphogenetic protein 5 (BMP5) in different types of cancers such as colon, breast, lung, bladder, and ovarian cancer. To address the inconsistent correlation of BMP5 expression with patient survival and molecular function of BMP5 in relation to cancer progression, we performed a systematic study to determine whether BMP5 could be used as a prognostic marker in human cancers. BMP5 expression and prognostic values were assessed using different bioinformatics tools such as ONCOMINE, GENT, TCGA, GEPIA, UALCAN, PrognoScan, PROGgene V2 server, and Kaplan–Meier Plotter. In addition, we used cBioPortal database for the identification and analysis of BMP5 mutations, copy number alterations, altered expression, and protein–protein interaction (PPI). We found that BMP5 is frequently down-regulated in our queried cancer types. Use of prognostic analysis showed negative association of BMP5 down-regulation with four types of cancer except for ovarian cancer. The highest mutation was found in the R321*/Q amino acid of BMP5 corresponding to colorectal and breast cancer whereas the alteration frequency was higher in lung squamous carcinoma datasets (>4%). In PPI analysis, we found 31 protein partners of BMP5, among which 11 showed significant co-expression (p-value < 0.001, log odds ratio > 1). Pathway analysis of differentially co-expressed genes with BMP5 in breast, lung, colon, bladder and ovarian cancers revealed the BMP5-correlated pathways. Collectively, this data-driven study demonstrates the correlation of BMP5 expression with patient survival and identifies the involvement of BMP5 pathways that may serve as targets of a novel biomarker for various types of cancers in human.

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The challenges of a heme protein and enzyme-based H2O2 sensor was subdued by developing a highly sensitive and practically functional amperometric gold nanoparticles (Au NPs)/SnO2 nanofibers (SnO2 NFs) composite sensor. The composite was prepared by mixing multiporous SnO2 NFs (diameter: 120–190 nm) with Au NPs (size: 3–5 nm). The synthesized Au NPs/SnO2 NFs composite was subsequently coated on a glassy carbon electrode (GCE) and displayed a well-defined reduction peak during a cyclic voltammetry (CV) analysis. The SnO2 NFs prevented the aggregation of Au NPs through its multiporous structure and enhanced the catalytic response by 1.6-fold. The SnO2 NFs-supported GCE/Au NPs/SnO2 NFs composite sensor demonstrated a very good catalytic activity during the reduction of hydrogen peroxide (H2O2) that displayed rapid amperometric behavior within 6.5 s. This sensor allowed for highly sensitive and selective detection. The sensitivity was 14.157 µA/mM, the linear detection range was from 49.98 µM to 3937.21 µM (R2 = 0.99577), and the lower limit of detection was 6.67 µM. Furthermore, the developed sensor exhibited acceptable reproducibility, repeatability, and stability over 41 days. In addition, the Au NPs/SnO2 NFs composite sensor was tested for its ability to detect H2O2 in tap water, apple juice, Lactobacillus plantarum, Bacillus subtilis, and Escherichia coli. Therefore, this sensor would be useful due to its accuracy and sensitivity in detecting contaminants (H2O2) in commercial products.

An amperometric enzyme-free hydrogen peroxide (H2O2) sensor was developed by catalytically stabilizing active gold nanoparticles (Au NPs) of 4–5 nm on a porous titanium dioxide nanotube (TiO2 NTs) electrode. The Au NPs were homogeneously distributed on anatase TiO2 NTs with an outer diameter of ~102 nm, an inner diameter of ~60 nm, and a wall of thickness of ~40 nm. The cyclic voltammogram of the composite electrode showed a pair of redox peaks characterizing the electrocatalytic reduction of H2O2. The entrapping of Au NPs on TiO2 NTs prevented aggregation and facilitated good electrical conductivity and electron transfer rate, thus generating a wide linear range, a low detection limit of ~104 nM, and high sensitivity of ~519 µA/mM, as well as excellent selectivity, reproducibility, repeatability, and stability over 60 days. Furthermore, excellent recovery and relative standard deviation (RSD) were achieved in real samples, which were tap water, milk, and Lactobacillus plantarum bacteria, thereby verifying the accuracy and potentiality of the developed nonenzymatic sensor.