Objective: To synthesize bio-inspired gold nanoparticles (AuNPs) using the leaf extract of Justicia adhatoda and evaluate the anti-cancer activity on human lung cancer cell line (A549). Methods: Synthesis of AuNPs was done using an aqueous leaf extract of Justicia adhatoda as a green route. The bio-synthesized AuNPs were confirmed and characterized by using various spectral studies such as UV-Vis spectrum, Scanning Electron Microscope with EDAX, Transmission Electron Microscope, Fourier Transmission Infrared Spectroscope analysis and Surface Enhanced Raman Spectroscopy. The cell viability was determined by MTT reduction assay. In addition, cytomorphology and the nuclear morphological study of A549 cell line was observed under fluorescence microscope. Results: UV-Vis spectrum showed surface plasmon resonance peak at 547 nm, scanning electron microscope and transmission electron microscope studies showed the monodispersed spherical shape and its average size in the range of 40.1 nm was noticed. Fourier Transmission Infrared Spectroscope analysis confirmed that the C=O group of amino acids of proteins had strong ability to bind with the surface of nanoparticle. Interestingly, our results also demonstrated inhibited proliferation of A549 cell line by MTT (IC50 value: 80 μg/mL). Cell morphology was observed and cell death was caused by apoptosis as revealed by propidium iodide staining. Conclusions: The current study proves the anticancer potential of bio-synthesized AuNPs. Thus, synthesized AuNPs can be used for the treatment of human lung cancer cell (A549) and it can be exploited for drug delivery in future.

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.