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Diabetes mellitus (DM) and its complications are a severe public health concern due to the high incidence, morbidity, and mortality rates. The present study aims to synthesize and characterize silver nanoparticles (AgNPs) using the aqueous leaf extract of Psidium guajava (PGE) for investigating its antidiabetic activity. Psidium guajava silver nanoparticles (PGAg NPs) were prepared and characterized by various parameters. The in vivo study was conducted using PGE and PGAg NPs in Streptozotocin (STZ)-induced diabetic rats to assess their antidiabetic properties. STZ of 55 mg/kg was injected to induce diabetes. The PGE, PGAg NPs at a dose of 200 and 400 mg/kg and standard drug Metformin (100 mg/kg) were administered daily to diabetic rats for 21 days through the oral route. Blood glucose level, body weight changes, lipid profiles, and histopathology of the rats’ liver and pancreas were examined. In the diabetic rats, PGE and PGAg NPs produced a drastic decrease in the blood glucose level, preventing subsequent weight loss and ameliorating lipid profile parameters. The histopathological findings revealed the improvements in pancreas and liver cells due to the repercussion of PGE and PGAg NPs. A compelling effect was observed in all doses of PGE and PGAg NPs; however, PGAg NPs exhibited a more promising result. Thus, from the results, it is concluded that the synthesized PGAg NPs has potent antidiabetic activity due to its enhanced surface area and smaller particle size of nanoparticles.

Dementia affects the patient’s memory and leads to language impairment. Research has demonstrated that speech and language deterioration is often a clear indication of dementia and plays a crucial role in the recognition process. Even though earlier studies have used speech features to recognize subjects suffering from dementia, they are often used along with other linguistic features obtained from transcriptions. This study explores significant standalone speech features to recognize dementia. The primary contribution of this work is to identify a compact set of speech features that aid in the dementia recognition process. The secondary contribution is to leverage machine learning (ML) and deep learning (DL) models for the recognition task. Speech samples from the Pitt corpus in Dementia Bank are utilized for the present study. The critical speech feature set of prosodic, voice quality and cepstral features has been proposed for the task. The experimental results demonstrate the superiority of machine learning (87.6 percent) over deep learning (85 percent) models for recognizing Dementia using the compact speech feature combination, along with lower time and memory consumption. The results obtained using the proposed approach are promising compared with the existing works on dementia recognition using speech.

We demonstrate experimentally the feasibility of continuous variable quantum key distribution (CV-QKD) in dense-wavelength-division multiplexing networks (DWDM), where QKD will typically have to coexist with several co-propagating (forward or backward) C-band classical channels whose launch power is around 0 dBm. We have conducted experimental tests of the coexistence of CV-QKD multiplexed with an intense classical channel, for different input powers and different DWDM wavelengths. Over a 25 km fiber, a CV-QKD operated over the 1530.12 nm channel can tolerate the noise arising from up to 11.5 dBm classical channel at 1550.12 nm in the forward direction (9.7 dBm in backward). A positive key rate (0.49 kbits s−1) can be obtained at 75 km with classical channel power of respectively −3 and −9 dBm in forward and backward. Based on these measurements, we have also simulated the excess noise and optimized channel allocation for the integration of CV-QKD in some access networks. We have, for example, shown that CV-QKD could coexist with five pairs of channels (with nominal input powers: 2 dBm forward and 1 dBm backward) over a 25 km WDM-PON network. The obtained results demonstrate the outstanding capacity of CV-QKD to coexist with classical signals of realistic intensity in optical networks.

Due to their biological activities, both in plants and in humans, there is a great interest in finding natural sources of phenolic compounds or ways to artificially manipulate their levels. During the last decade, a significant amount of these compounds has been reported in the vegetative organs of the vine plant. In the roots, woods, canes, stems, and leaves, at least 183 phenolic compounds have been identified, including 78 stilbenes (23 monomers, 30 dimers, 8 trimers, 16 tetramers, and 1 hexamer), 15 hydroxycinnamic acids, 9 hydroxybenzoic acids, 17 flavan-3-ols (of which 9 are proanthocyanidins), 14 anthocyanins, 8 flavanones, 35 flavonols, 2 flavones, and 5 coumarins. There is great variability in the distribution of these chemicals along the vine plant, with leaves and stems/canes having flavonols (83.43% of total phenolic levels) and flavan-3-ols (61.63%) as their main compounds, respectively. In light of the pattern described from the same organs, quercetin-3-O-glucuronide, quercetin-3-O-galactoside, quercetin-3-O-glucoside, and caftaric acid are the main flavonols and hydroxycinnamic acids in the leaves; the most commonly represented flavan-3-ols and flavonols in the stems and canes are catechin, epicatechin, procyanidin B1, and quercetin-3-O-galactoside. The main stilbenes (trans-ε-viniferin, trans-resveratrol, isohopeaphenol/hopeaphenol, vitisin B, and ampelopsins) accumulate primarily in the woods, followed by the roots, the canes, and the stems, whereas the leaves, which are more exposed to environmental stresses, have a low concentration of these compounds. Data provided in this review could be used as (i) a metabolomic tool for screening in targeted and untargeted analyses and (ii) a reference list in studies aimed at finding ways to induce naturally occurring polyphenols on an industrial scale for pant and human disease control.

The stationary life of plants has led to the evolution of a complex gridded antioxidant defence system constituting numerous enzymatic components, playing a crucial role in overcoming various stress conditions. Mainly, these plant enzymes are superoxide dismutase (SOD), catalase (CAT), peroxidase (POX), glutathione peroxidase (GPX), glutathione reductase (GR), glutathione S-transferases (GST), ascorbate peroxidase (APX), monodehydroascorbate reductase (MDHAR), and dehydroascorbate reductase (DHAR), which work as part of the antioxidant defence system. These enzymes together form a complex set of mechanisms to minimise, buffer, and scavenge the reactive oxygen species (ROS) efficiently. The present review is aimed at articulating the current understanding of each of these enzymatic components, with special attention on the role of each enzyme in response to the various environmental, especially abiotic stresses, their molecular characterisation, and reaction mechanisms. The role of the enzymatic defence system for plant health and development, their significance, and cross-talk mechanisms are discussed in detail. Additionally, the application of antioxidant enzymes in developing stress-tolerant transgenic plants are also discussed.

Rapid and precise analytical tools are essential for monitoring food safety and screening of any undesirable contaminants, allergens, or pathogens, which may cause significant health risks upon consumption. Substantial developments in analytical techniques have empowered the analyses and quantitation of these contaminants. However, conventional techniques are limited by delayed analysis times, expensive and laborious sample preparation, and the necessity for highly-trained workers. Therefore, prompt advances in electrochemical biosensors have supported significant gains in quantitative detection and screening of food contaminants and showed incredible potential as a means of defying such limitations. Apart from indicating high specificity towards the target analytes, these biosensors have also addressed the challenge of food industry by providing high analytical accuracy within complex food matrices. Here, we discuss some of the recent advances in this area and analyze the role and contributions made by electrochemical biosensors in the food industry. This article also reviews the key challenges we believe biosensors need to overcome to become the industry standard.

This study investigated the inequality in citation distribution of the publications produced by top ten universities ranked under the National Institutional Ranking Framework (NIRF) 2024. The analysis aimed to understand the extent of evenness in the distribution of citations across academic publications which is crucial for accurately assessing scholarly impact. Using the affiliation organisation field in the advanced document search in Scopus, a search for publication and citation data of each university was carried out. The search results were refined for the period 2021-2023 to align period of publication and citation data with that of NIRF rank data. The resultant dataset of 56791 publications garnering 725925 citations for period 2021-2023 was exported from Scopus database. Data was analysed using Microsoft Excel. Calculations and visualisations were performed using R statistical analysis software. Gini coefficient, an index to measure the degree of inequality, was used to discover the degree of inequality of citations across publications. The overall Gini coefficient value of 0.6458 revealed a high degree of citation inequality among universities, indicating the concentration of higher number of citations within a small number of publications. Gini coefficient values of open access and non-open access publications were 0.6683 and 0.6152 respectively, highlighting a higher degree of citation inequality among open access publications. No significant association was found between research and publication practices score and Gini coefficient values. In-depth understanding of citation inequality can provide deeper insights on the characteristics of citations in terms of evenness of their distribution and can help uncover a phenomenon where a small number of publications bear the ‘burden’ of enhancing the citation impact of the entire institution.

Videolaryngoscope is regarded as the standard of care for airway management in well-resourced setups however the technology is largely inaccessible and costly in middle and low-income countries. An improvised and cost-effective form of customized videolaryngoscope was proposed and studied for patient care in underprivileged areas however there were no distinct conclusions on its performances. The study follows PRISMA guidelines for systematic review and the protocol in International Prospective Register for Systematic Reviews. The primary aim was to assess the first attempt success of customized videolaryngoscope for endotracheal intubation. The secondary objective was to evaluate the number of attempts, laryngoscopic view in terms of Cormack Lehane score and Percentage of glottic opening, use of external laryngeal maneuver and stylet and, the airway injuries after the endotracheal intubation. Five studies were analyzed for risk of bias using the National Institute of Health Quality Assessment Tool for cross-sectional studies. Most of the studies had a poor to a fair level of evidence with only one study with a good level of evidence. Certainty of evidence was \"very low\" for all eligible studies when graded using the Grading of Recommendation, Assessment, Development and Evaluation approach for systematic review. The certainty of the evidence regarding performance of custom-made videolaryngoscope compared to conventional laryngoscope was very low and the study was performed in small numbers with fair to the poor risk of bias. It was difficult to establish and do further analysis regarding whether the customized form of videolaryngoscope will improve the first attempt success rate for tracheal intubation, reduce the number of attempts, improve the laryngoscopic view, require fewer external aids and reduce the incidences of airway injury with the given low-grade evidence. Some properly conducted randomised clinical trials will be required to further analyze the outcome and make the strong recommendations.

Polyherbal formulation (PHF) enhances therapeutic efficacy and minimizes side effects by reducing individual herb dosages. Allopolyherbal formulation (APHF) combines polyherbal extracts with allopathic medication, effectively reducing the latter’s required dose and mitigating associated adverse effects. The current study intends to assess the anti-diabetic effects of PHF and APHF in-vivo. Dried raw powders of Cassia auriculata leaf, Centella asiatica leaf, and Zingiber officinale rhizome were extracted by cold maceration process using 70% ethanol. These extracts were combined in three different ratios to make PHF. PHF was subjected to qualitative and quantitative phytochemical investigations. APHF has been prepared by combining a potent ratio of PHF with metformin in three different ratios. The compatibility of APHF has been confirmed by differential scanning calorimetry (DSC). In vivo activity was also evaluated in streptozotocin-induced diabetic albino rats. PHF (3 different ratios at a dose of 200–400 mg/kg b.w), APHF (combination of PHF and metformin in 3 different ratios, 200 + 22.5, 200 + 45, and 200 + 67.5 mg/kg b.w), and metformin (90 mg/kg b.w) were administered to albino rats for 21 consecutive days. Blood glucose levels were estimated on the 1st, 7th, 14th, and 21st days of treatment. On the 21st day, blood was collected by cardiac puncture for biochemical analysis. The liver and pancreas were isolated and subjected to histopathological analysis. PHF and APHF showed significant anti-diabetic and antihyperlipidemic efficacy. In comparison to PHF, APHF had the most promising action. The current study demonstrated that PHF and APHF are safe and efficacious drugs in the treatment of diabetes mellitus as they help to replace or lower the dose of metformin, thereby decreasing the risks of metformin.

The most common denture material used for dentistry is poly-methyl-methacrylate (PMMA). Usually, the polymeric PMMA material has numerous biological, mechanical and cost-effective shortcomings. Hence, to resolve such types of drawbacks, attempts have been made to investigate fillers of the PMMA like alumina (Al 2 O 3 ), silica (SiO 2 ), zirconia (ZrO 2 ) etc. For the enhancement of the PMMA properties a suitable additive is required for its orthopedic applications. Herein, the main motive of this study was to synthesize a magnesium oxide (MgO) reinforced polymer-based hybrid nano-composites by using heat cure method with superior optical, biological and mechanical characteristics. For the structural and vibrational studies of the composites, XRD and FT-IR were carried out. Herein, the percentage of crystallinity for all the fabricated composites were also calculated and found to be 14.79–30.31. Various physical and optical parameters such as density, band gap, Urbach energy, cutoff energy, cutoff wavelength, steepness parameter, electron–phonon interaction, refractive index, and optical dielectric constant were also studied and their values are found to be in the range of 1.21–1.394 g/cm 3 , 5.44–5.48 eV, 0.167–0.027 eV, 5.68 eV, 218 nm, 0.156–0.962, 4.273–0.693, 1.937–1.932, and 3.752–3.731 respectively. To evaluate the mechanical properties like compressive strength, flexural strength, and fracture toughness of the composites a Universal Testing Machine (UTM) was used and their values were 60.3 and 101 MPa, 78 and 40.3 MPa, 5.85 and 9.8 MPa-m 1/2 respectively. Tribological tests of the composites were also carried out. In order to check the toxicity, MTT assay was also carried out for the PM0 and PM15 [(x)MgO + (100 − x) (C 5 O 2 H 8 ) n ] (x = 0 and 15) composites. This study provides a comprehensive insight into the structural, physical, optical, and biological features of the fabricated PMMA-MgO composites, highlighting the potential of the PM15 composite with its enhanced density, mechanical strength, and excellent biocompatibility for denture applications.