Dietary phenolic compounds as promising therapeutic agents for diabetes and its complications: A comprehensive review.

In the middle of an ever-changing landscape of diabetes care, precision medicine, and lifestyle therapies are becoming increasingly important. Dietary polyphenols are like hidden allies found in our everyday meals. These biomolecules, found commonly in fruits, vegetables, and various plant-based sources, hold revolutionary potential within their molecular structure in the way we approach diabetes and its intimidating consequences. There are currently numerous types of diabetes medications, but they are not appropriate for all patients due to limitations in dosages, side effects, drug resistance, a lack of efficacy, and ethnicity. Currently, there has been increased interest in practicing herbal remedies to manage diabetes and its related complications. This article aims to summarize the potential of dietary polyphenols as a foundation in the treatment of diabetes and its associated consequences. We found that most polyphenols inhibit enzymes linked to diabetes. This review outlines the potential benefits of selected molecules, including kaempferol, catechins, rosmarinic acid, apigenin, chlorogenic acid, and caffeic acid, in managing diabetes mellitus as these compounds have exhibited promising results in in vitro, in vivo, in silico, and some preclinical trials study. This encompassing exploration reveals the multifaceted impact of polyphenols not only in mitigating diabetes but also in addressing associated conditions like inflammation, obesity, and even cancer. Their mechanisms involve antioxidant functions, immune modulation, and proinflammatory enzyme regulation. Furthermore, these molecules exhibit anti-tumor activities, influence cellular pathways, and activate AMPK pathways, offering a less toxic, cost-effective, and sustainable approach to addressing diabetes and its complications.

Metabolome Mining of Curcuma longa L. Using HPLC-MS/MS and Molecular Networking.

Turmeric, Curcuma longa L., is a type of medicinal plant characterized by its perennial nature and rhizomatous growth. It is a member of the Zingiberaceae family and is distributed across the world's tropical and subtropical climates, especially in South Asia. Its rhizomes have been highly valued for food supplements, spices, flavoring agents, and yellow dye in South Asia since ancient times. It exhibits a diverse array of therapeutic qualities that encompass its ability to combat diabetes, reduce inflammation, act as an antioxidant, exhibit anticancer properties, and promote anti-aging effects. In this study, organic extracts of C. longa rhizomes were subjected to HPLC separation followed by ESI-MS and low-energy tandem mass spectrometry analyses. The Global Natural Product Social Molecular Networking (GNPS) approach was utilized for the first time in this ethnobotanically important species to conduct an in-depth analysis of its metabolomes based on their fragments. To sum it up, a total of 30 metabolites including 16 diarylheptanoids, 1 diarylpentanoid, 3 bisabolocurcumin ethers, 4 sesquiterpenoids, 4 cinnamic acid derivatives, and 2 fatty acid derivatives were identified. Among the 16 diarylheptanoids identified in this study, 5 of them are reported for the first time in this species.

Molecular Docking and Dynamics Simulation of Several Flavonoids Predict Cyanidin as an Effective Drug Candidate against SARS-CoV-2 Spike Protein.

The in silico method has provided a versatile process of developing lead compounds from a large database in a short duration. Therefore, it is imperative to look for vaccinations and medications that can stop the havoc caused by SARS-CoV-2. The spike protein of SARS-CoV-2 is required for the viral entry into the host cells, hence inhibiting the virus from fusing and infecting the host. This study determined the binding interactions of 36 flavonoids along with two FDA-approved drugs against the spike protein receptor-binding domain of SARS-CoV-2 through molecular docking and molecular dynamics (MD) simulations. In addition, the molecular mechanics generalized Born surface area (MM/GBSA) approach was used to calculate the binding-free energy (BFE). Flavonoids were selected based on their in vitro assays on SARS-CoV and SARS-CoV-2. Our pharmacokinetics study revealed that cyanidin showed good drug-likeness, fulfilled Lipinski's rule of five, and conferred favorable toxicity parameters. Furthermore, MD simulations showed that cyanidin interacts with spike protein and alters the conformation and binding-free energy suited. Finally, an in vitro assay indicated that about 50% reduction in the binding of hACE2 with S1-RBD in the presence of cyanidin-containing red grapes crude extract was achieved at approximately 1.25 mg/mL. Hence, cyanidin may be a promising adjuvant medication for the SARS-CoV-2 spike protein based on in silico and in vitro research.

Reprogramming natural proteins using unnatural amino acids.

Unnatural amino acids have gained significant attention in protein engineering and drug discovery as they allow the evolution of proteins with enhanced stability and activity. The incorporation of unnatural amino acids into proteins offers a rational approach to engineer enzymes for designing efficient biocatalysts that exhibit versatile physicochemical properties and biological functions. This review highlights the biological and synthetic routes of unnatural amino acids to yield a modified protein with altered functionality and their incorporation methods. Unnatural amino acids offer a wide array of applications such as antibody-drug conjugates, probes for change in protein conformation and structure-activity relationships, peptide-based imaging, antimicrobial activities, etc. Besides their emerging applications in fundamental and applied science, systemic research is necessary to explore unnatural amino acids with novel side chains that can address the limitations of natural amino acids.

Micro Gas Chromatography: An Overview of Critical Components and Their Integration.

Among a number of gas analyzers, portable gas chromatography (GC) systems created by the integration of microfabricated components are promising candidates for rapid and on-site analysis of a number of complex chemical mixtures. This Feature provides a snapshot of the progress made in developing micro gas chromatography (µGC) systems in the last 4 decades. In particular, we discuss the development of microfabricated preconcentrators, separation columns, and detectors. Furthermore, we review different stationary phase materials used to coat the separation columns and the major efforts toward the development of an integrated µGC.

Ionic liquid-coated alumina-pretreated micro gas chromatography columns for high-efficient separations.

These studies demonstrate the influence of an intermediate layer of aluminum oxide on the separation performance of a room temperature ionic liquid (RTIL)-coated gas chromatography silicon microcolumn. A 1 m long semipacked column having 190 µm wide and 240 µm deep rectangular cross-sectional channels with embedded arrays of micro pillars was microfabricated. A thin layer of alumina was then deposited on the surface of the channels via atomic layer deposition. Following the alumina deposition, the channels were coated with an RTIL. The separation performance of the RTIL-coated columns with and without the alumina layer was evaluated by measuring the separation efficiency and peak capacity. A substantial increase in separation efficiency was observed in the presence of the alumina layer. The alumina-pretreated columns, at optimum flow rate, exhibited as high as 8000 plates per meter, which is a 2.1-fold increase as compared to the column with no alumina layer. It is inferred that alumina coating promotes the formation of a more uniform RTIL film, thereby enhancing the separation efficiency. The peak production rates of alumina-RTIL columns for temperature-programmed separation were found to be 0.80-1.1 peaks per second, which is an improvement compared to silicon-RTIL columns. The separation performance of these columns were further evaluated by separating a standard 21-component mixture of hazardous organic compounds, a sample of kerosene, diesel, and B20 biodiesel. These studies open up new possibilities of enhancing the separation efficiency of microcolumns by coating silicon surface with a suitable material prior to depositing an ionic liquid.

Ionic liquid functionalization of semi-packed columns for high-performance gas chromatographic separations.

Gas chromatography columns fabricated using microelectromechanical system (MEMS) technology provide a number of clear advantages. However, successful deposition of stationary phases having a wide application range remains an important technical challenge. In this paper, we report, for the first time, on the deposition of room temperature ionic liquids (RTILs)-a versatile class of stationary phases-inside the channels of semi-packed columns (SPCs) for high-performance gas chromatographic separation of complex chemical mixtures. A 1m long, 240µm deep, 190µm wide column comprising an array circular micropillars of 20µm in diameter and 40µm post spacing was fabricated using MEMS processes. Two RTILs were immobilized inside these columns using a dynamic coating method, and the columns were tested for separation of three different mixtures: a 15-component mixture of hazardous chemical pollutants, an 8-component mixture of fatty acid methyl esters, and a sample of gasoline. These columns displayed sharp and symmetrical peaks, significant selectivity variation between the two columns, and rapid separation times. The columns yielded high separation efficiencies measured by approximately 2300 plates/m under isothermal conditions. This work highlights the potential of RTILs to be used as excellent stationary phases for SPCs, thereby dramatically expanding the range of complex mixtures that could be analyzed using a micro gas chromatograph.

Strategy for tuning the photophysical properties of photosensitizers for use in photodynamic therapy.

A novel approach for tuning spectral properties, as well as minimizing aggregation, in zinc porphyrin and zinc phthalocyanine-based compounds is presented. Particular emphasis is placed on use of these compounds as photosensitizers in photodynamic therapy (PDT). To accomplish this aim, a bulky hydrophobic cation, trihexyltetradecylphosphonium, is paired with anionic porphyrin and phthalocyanine dyes to produce a group of uniform materials based on organic salts (GUMBOS) that absorb at longer wavelengths with high molar absorptivity and high photostability. Nanoparticles derived from these GUMBOS possess positively charged surfaces with high zeta potential values, which are highly desirable for PDT. Upon irradiation at longer wavelengths, these GUMBOS produced singlet oxygen with greater efficiency as compared to the respective parent dyes.

Rational Design of QCM-D Virtual Sensor Arrays Based on Film Thickness, Viscoelasticity, and Harmonics for Vapor Discrimination.

Herein, we demonstrate an alternative strategy for creating QCM-based sensor arrays by use of a single sensor to provide multiple responses per analyte. The sensor, which simulates a virtual sensor array (VSA), was developed by depositing a thin film of ionic liquid, either 1-octyl-3-methylimidazolium bromide ([OMIm][Br]) or 1-octyl-3-methylimidazolium thiocyanate ([OMIm][SCN]), onto the surface of a QCM-D transducer. The sensor was exposed to 18 different organic vapors (alcohols, hydrocarbons, chlorohydrocarbons, nitriles) belonging to the same or different homologous series. The resulting frequency shifts (Δf) were measured at multiple harmonics and evaluated using principal component analysis (PCA) and discriminant analysis (DA) which revealed that analytes can be classified with extremely high accuracy. In almost all cases, the accuracy for identification of a member of the same class, that is, intraclass discrimination, was 100% as determined by use of quadratic discriminant analysis (QDA). Impressively, some VSAs allowed classification of all 18 analytes tested with nearly 100% accuracy. Such results underscore the importance of utilizing lesser exploited properties that influence signal transduction. Overall, these results demonstrate excellent potential of the virtual sensor array strategy for detection and discrimination of vapor phase analytes utilizing the QCM. To the best of our knowledge, this is the first report on QCM VSAs, as well as an experimental sensor array, that is based primarily on viscoelasticity, film thickness, and harmonics.

Virtual colorimetric sensor array: single ionic liquid for solvent discrimination.

There is a continuing need to develop high-performance sensors for monitoring organic solvents, primarily due to the environmental impact of such compounds. In this regard, colorimetric sensors have been a subject of intense research for such applications. Herein, we report a unique virtual colorimetric sensor array based on a single ionic liquid (IL) for accurate detection and identification of similar organic solvents and mixtures of such solvents. In this study, we employ eight alcohols and seven binary mixtures of ethanol and methanol as analytes to provide a stringent test for assessing the capabilities of this array. The UV-visible spectra of alcoholic solutions of the IL used in this study show two absorption bands. Interestingly, the ratio of absorbance for these two bands is found to be extremely sensitive to alcohol polarity. A virtual sensor array is created by using four different concentrations of IL sensor, which allowed identification of these analytes with 96.4-100% accuracy. Overall, this virtual sensor array is found to be very promising for discrimination of closely related organic solvents.

GUMBOS matrices of variable hydrophobicity for matrix-assisted laser desorption/ionization mass spectrometry.

RATIONALE: Detection of hydrophobic peptides remains a major obstacle for matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). This stems from the fact that most matrices for MALDI are hydrophilic and therefore have low affinities for hydrophobic peptides. Herein, 1-aminopyrene (AP) and AP-derived group of uniform materials based on organic salts (GUMBOS) as novel matrices for MALDI-MS analyses of peptides were investigated for hydrophobic and hydrophilic peptides. METHODS: A number of solid-phase AP-based GUMBOS are synthesized with variable hydrophobicity simply by changing the counterions. Structures were confirmed by use of (1)H NMR and electrospray ionization mass spectrometry (ESI-MS). 1-Octanol/water partition coefficients (Ko/w) were used to measure the hydrophobicity of the matrices. A dried-droplet method was used for sample preparation. All spectra were obtained using a MALDI-TOF mass spectrometer in positive ion reflectron mode. RESULTS: A series of AP-based GUMBOS was synthesized including [AP][chloride] ([AP][Cl]), [AP][ascorbate] ([AP][Asc]) and [AP][bis(trifluoromethane)sulfonimide] ([AP][NTf2]). The relative hydrophobicities of these compounds and α-cyano-4-hydroxycinnamic acid (CHCA, a common MALDI matrix) indicated that AP-based GUMBOS can be tuned to be much more hydrophobic than CHCA. A clear trend is observed between the signal intensities of hydrophobic peptides and hydrophobicity of the matrix. CONCLUSIONS: MALDI matrices of GUMBOS with tunable hydrophobicities are easily obtained simply by varying the counterion. We have found that hydrophobic matrix materials are very effective for MALDI determination of hydrophobic peptides and, similarly, the more hydrophilic peptides displayed greater intensity in the more hydrophilic matrix.