Floralozone attenuates atherosclerotic vascular injury by regulating AMPKα/SREBP-1c pathway and down-regulating miR-33-5p.

Background: Severe disruption of lipid metabolism in vivo is one of the central mechanisms in the development of atherosclerotic vascular injury (AVI). Reverse cholesterol transport (RCT) plays a pivotal role in eliminating excess cholesterol, preventing lipid deposition in the aorta, and reducing plaque formation associated with AVI. Floralozone (FL) reduces endothelial cell injury in AVI rats by regulating sphingosine-1-phosphate (S1P) expression.

Recent Advances in Silver and Gold Nanoparticles-Based Colorimetric Sensors for Heavy Metal Ions Detection: A Review.

Silvetr and gold nanoparticles-based colorimetric sensors (Ag/Au-NPs-CSns) allow potential prospects for the development of efficient sensors owing to their unique shape- and size-dependent optical properties. In this review, recent (2020) advances in morphology-controllable synthesis, shape/size-dependent performance, sensing mechanism, challenges and prospects of Ag/Au-NPs-CSns for the detection of heavy metals are discussed. The size/shape-controlled synthesis of innovative Ag/Au-NPs-CSns is reviewed critically and the possible role of different parameters like temperature, time, pH, stabilizing/capping agents, reducing agents and concentration/nature of precursors are discussed.

SERS-based lateral flow immunoassay for sensitive and simultaneous detection of anti-SARS-CoV-2 IgM and IgG antibodies by using gap-enhanced Raman nanotags.

The lateral flow immunoassay (LFIA) has played a crucial role in early diagnosis during the current COVID-19 pandemic owing to its simplicity, speed and affordability for coronavirus antibody detection. However, the sensitivity of the commercially available LFIAs needs to be improved to better prevent the spread of the infection. Here, we developed an ultra-sensitive surface-enhanced Raman scattering-based lateral flow immunoassay (SERS-based LFIA) strip for simultaneous detection of anti-SARS-CoV-2 IgM and IgG by using gap-enhanced Raman nanotags (GERTs).

Heavy metal detection in mulberry leaves: Laser-induced breakdown spectroscopy data.

Five copper or chromium stress levels were carried out on mulberry leaf, and 20 samples were collected for each metal stress level. A total of 100 samples (copper or chromium) were processed into uniform pressed pellet. The mulberry leaf pellet was placed on a sample platform of laser-induced breakdown spectroscopy (LIBS) system.

Simultaneously and quantitatively analyze the heavy metals in Sargassum fusiforme by laser-induced breakdown spectroscopy.

As a nutritious and popular seafood among consumers, Sargassum fusiforme is susceptible to the toxic heavy metals because of its strong adsorption properties. In this study, laser-induced breakdown spectroscopy (LIBS) coupled with a simple framework (only remove some noise and low-intensity variables, and then combine with PLS algorithm) was used to establish the detection models to simultaneously and quantitatively analyze the content of heavy metals arsenic (As), chromium (Cd), cadmium (Cr), copper (Cu), mercury (Hg), lead (Pb) and zinc (Zn) in Sargassum fusiforme. As comparisons, three classic variable methods of successive projections algorithm (SPA), uninformative variable elimination (UVE) and variable importance in projection (VIP) were adopted.

Building a stable and accurate model for heavy metal detection in mulberry leaves based on a proposed analysis framework and laser-induced breakdown spectroscopy.

Laser-induced breakdown spectroscopy (LIBS) was used to rapidly detect heavy metals in mulberry leaves. For the purpose of increasing detection stability and accuracy, a novel analysis framework consisting of a Kohonen self-organizing map (SOM), a variable selection method using the successive projection algorithm (SPA) and uninformative variable elimination (UVE), and a consensus modeling strategy was proposed for processing LIBS data to determine copper (Cu) and chromium (Cr) content. Results showed that the best regression model for Cu and Cr content achieved the residual predictive deviation (RPD) values of 10.

Nondestructive measurement of pectin polysaccharides using hyperspectral imaging in mulberry fruit.

Pectin polysaccharide is an important phytochemical with potential biomedical applications. It is commonly measured by time-consuming destructive chemical methods. This work demonstrates the feasibility of using visible and near-infrared hyperspectral imaging (HSI) techniques to rapidly measure pectin polysaccharides in intact mulberry fruits.

Optimization of the benzamide fragment targeting the S' site leads to potent dipeptidyl peptidase-IV inhibitors.

Our recently successful identification of benzoic acid-based DPP-4 inhibitors spurs the further quest for in-depth structure-activity relationships (SAR) study in S' site DPP-4. Thus novel benzamide fragments were designed to target the S' site to compromise lipophilicity and improve oral activity. Exploring SAR by introduction of a variety of amide and halogen on benzene ring led to identification of several compounds, exerting moderated to excellent DPP-4 activities, in which 4'-chlorine substituted methyl amide 17g showed most potent DPP-4 activity with the IC value of 1.

Rapid generation of novel benzoic acid-based xanthine derivatives as highly potent, selective and long acting DPP-4 inhibitors: Scaffold-hopping and prodrug study.

A series of novel xanthine derivatives 2a-l incorporating benzoic acid moieties were rapidly generated by using strategy of scaffold-hopping from our previously reported scaffold uracil to xanthine, a scaffold of approved drug linagliptin. After systematic structure-activity relationship (SAR) study around benzoic acid moieties, 5 novel DPP-4 inhibitors with low picomolar potency range (IC < 1 nM) and excellent selectivity against various DPP-4 homologues were identified, in which the best one, compound 2f, with the IC value of 0.1 nM for DPP-4, showed 22-fold improvement in inhibitory activity compared to lead compound uracil 1, its activity was 45-fold more potent than alogliptin.

Sample Consensus Model and Unsupervised Variable Consensus Model for Improving the Accuracy of a Calibration Model.

In the quantitative analysis of spectral data, small sample size and high dimensionality of spectral variables often lead to poor accuracy of a calibration model. We proposed two methods, namely sample consensus and unsupervised variable consensus models, in order to solve the problem of poor accuracy. Three public near-infrared (NIR) or infrared (IR) spectroscopy data from corn, wine, and soil were used to build the partial least squares regression (PLSR) model.

Feasibility of Laser-Induced Breakdown Spectroscopy and Hyperspectral Imaging for Rapid Detection of Thiophanate-Methyl Residue on Mulberry Fruit.

An effective and rapid way to detect thiophanate-methyl residue on mulberry fruit is important for providing consumers with quality and safe of mulberry fruit. Chemical methods are complex, time-consuming, and costly, and can result in sample contamination. Rapid detection of thiophanate-methyl residue on mulberry fruit was studied using laser-induced breakdown spectroscopy (LIBS) and hyperspectral imaging (HSI) techniques.

Identification of novel uracil derivatives incorporating benzoic acid moieties as highly potent Dipeptidyl Peptidase-IV inhibitors.

Dipeptidyl Peptidase-IV (DPP-4) is a validated therapeutic target for type 2 diabetes. Aiming to interact with both residues Try629 and Lys554 in S' site, a series of novel uracil derivatives 1a-l and 2a-i incorporating benzoic acid moieties at the N position were designed and evaluated for their DPP-4 inhibitory activity. Structure-activity relationships (SAR) study led to the identification of the optimal compound 2b as a potent and selective DPP-4 inhibitor (IC = 1.

Potential of Visible and Near-Infrared Hyperspectral Imaging for Detection of Larvae and Damage on Mulberry Leaves.

Mulberry trees are an important crop for sericulture. Pests can affect the yield and quality of mulberry leaves. This study aims to develop a hyperspectral imaging system in visible and near-infrared (NIR) region (400⁻1700 nm) for the rapid identification of larvae and its damage.

Comparison of different CCD detectors and chemometrics for predicting total anthocyanin content and antioxidant activity of mulberry fruit using visible and near infrared hyperspectral imaging technique.

This study investigated the potential of using hyperspectral imaging technique in tandem with chemometrics for rapid and invasive predicting total anthocyanin content and antioxidant activity of mulberry fruit. Two calibration methods of partial least square regression and least-squares support vector machines and three wavelength selection algorithms of successive projections algorithm, uninformation variable elimination, and competitive adaptive reweighted sampling were applied. The best prediction models for the analysis of total anthocyanin content and antioxidant activity had R of 0.