ONE STEP QUANTIFICATION ANALYTICAL METHOD AND CHARACTERIZATION OF VALSARTAN BY LC-MS

Objective: To develop precise LC-MS method for the estimation of valsartan impurities and perform validation as per ICH guidelines.Methods: Valsartan (VLN) and its degradation products were analyzed by reverse phase high-performance liquid chromatography (RP-HPLC) using mobile phase water: acetonitrile: glacial acetic acid: phosphate buffer in the ratio of 500:500:1:0.5 v/v/v/v at 225 nm using column nucleosil C18, 125 ×4.0 mm, 5 µm. VLN sample (VLN SPL) thus obtained an unknown major impurity (UIMP) of 0.5 % at 0.38 retention time ratio (RRt) and purity of VLN was found to be 98.70 % respectively.Results: Estimation of VLN SPL total unknown impurities was found to be 1.3% by RP-HPLC. In similarly by liquid chromatography mass spectroscopy (LC-MS) a typical chromatogram of valsartan (VLN) at Rt 9.03 min and UIMP at Rt 3.3 min were recorded at a total run time of 23 min. Assay of VLN SPL was validated as per international council for harmonization (ICH) guidelines. Average % recovery was found to be 100.04 % for VLN SPL.Conclusion: The proposed work clearly indicates that the method can be easily adapted for the routine one step estimation of VLN active pharmaceutical ingredient (API)

Deciphering mollusc shell production: the roles of genetic mechanisms through to ecology, aquaculture and biomimetics

Most molluscs possess shells, constructed from a vast array of microstructures and architectures. The fully formed shell is composed of calcite or aragonite. These CaCO3 crystals form complex biocomposites with proteins, which although typically less than 5% of total shell mass, play significant roles in determining shell microstructure. Despite much research effort, large knowledge gaps remain in how molluscs construct and maintain their shells, and how they produce such a great diversity of forms. Here we synthesize results on how shell shape, microstructure, composition and organic content vary among, and within, species in response to numerous biotic and abiotic factors. At the local level, temperature, food supply and predation cues significantly affect shell morphology, whilst salinity has a much stronger influence across latitudes. Moreover, we emphasize how advances in genomic technologies [e.g. restriction site-associated DNA sequencing (RAD-Seq) and epigenetics] allow detailed examinations of whether morphological changes result from phenotypic plasticity or genetic adaptation, or a combination of these. RAD-Seq has already identified single nucleotide polymorphisms associated with temperature and aquaculture practices, whilst epigenetic processes have been shown significantly to modify shell construction to local conditions in, for example, Antarctica and New Zealand. We also synthesize results on the costs of shell construction and explore how these affect energetic trade-offs in animal metabolism. The cellular costs are still debated, with CaCO3 precipitation estimates ranging from 1-2 J/mg to 17-55 J/mg depending on experimental and environmental conditions. However, organic components are more expensive (~29 J/mg) and recent data indicate transmembrane calcium ion transporters can involve considerable costs. This review emphasizes the role that molecular analyses have played in demonstrating multiple evolutionary origins of biomineralization genes. Although these are characterized by lineage-specific proteins and unique combinations of co-opted genes, a small set of protein domains have been identified as a conserved biomineralization tool box. We further highlight the use of sequence data sets in providing candidate genes for in situ localization and protein function studies. The former has elucidated gene expression modularity in mantle tissue, improving understanding of the diversity of shell morphology synthesis. RNA interference (RNAi) and clustered regularly interspersed short palindromic repeats - CRISPR-associated protein 9 (CRISPR-Cas9) experiments have provided proof of concept for use in the functional investigation of mollusc gene sequences, showing for example that Pif (aragonite-binding) protein plays a significant role in structured nacre crystal growth and that the Lsdia1 gene sets shell chirality in Lymnaea stagnalis. Much research has focused on the impacts of ocean acidification on molluscs. Initial studies were predominantly pessimistic for future molluscan biodiversity. However, more sophisticated experiments incorporating selective breeding and multiple generations are identifying subtle effects and that variability within mollusc genomes has potential for adaption to future conditions. Furthermore, we highlight recent historical studies based on museum collections that demonstrate a greater resilience of molluscs to climate change compared with experimental data. The future of mollusc research lies not solely with ecological investigations into biodiversity, and this review synthesizes knowledge across disciplines to understand biomineralization. It spans research ranging from evolution and development, through predictions of biodiversity prospects and future-proofing of aquaculture to identifying new biomimetic opportunities and societal benefits from recycling shell products.FCT: UID/Multi/04326/2019; European Marine Biological Research Infrastructure Cluster-EMBRIC (EU H2020 research and innovation program) 654008; European Union Seventh Framework Programme [FP7] ITN project 'CACHE: Calcium in a Changing Environment' under REA 60505; NERC Natural Environment Research Council NE/J500173/1info:eu-repo/semantics/publishedVersio

The role of higher order image statistics in masking scene gist recognition

In the present article, we investigated whether higher order image statistics, which are known to be carried by the Fourier phase spectrum, are sufficient to affect scene gist recognition. In Experiment 1, we compared the scene gist masking strength of four masking image types that varied in their degrees of second- and higher order relationships: normal scene images, scene textures, phase-randomized scene images, and white noise. Masking effects were the largest for masking images that possessed significant higher order image statistics (scene images and scene textures) as compared with masking images that did not (phase-randomized scenes and white noise), with scene image masks yielding the largest masking effects. In a control study, we eliminated all differences in the second-order statistics of the masks, while maintaining differences in their higher order statistics by comparing masking by scene textures rather than by their phase-randomized versions, and showed that the former produced significantly stronger gist masking. Experiments 2 and 3 were designed to test whether conceptual masking could account for the differences in the strength of the scene texture and phase-randomized masks used in Experiment 1, and revealed that the recognizability of scene texture masks explained just 1% of their masking variance. Together, the results suggest that (1) masks containing the higher order statistical structure of scenes are more effective at masking scene gist processing than are masks lacking such structure, and (2) much of the disruption of scene gist recognition that one might be tempted to attribute to conceptual masking is due to spatial masking