The entrancing role of dietary polyphenols against the most frequent aging-associated diseases.

Aging, a fundamental physiological process influenced by innumerable biological and genetic pathways, is an important driving factor for several aging-associated disorders like diabetes mellitus, osteoporosis, cancer, and neurodegenerative diseases including Alzheimer's and Parkinson's diseases. In the modern era, the several mechanisms associated with aging have been deeply studied. Treatment and therapeutics for age-related diseases have also made considerable advances; however, for the effective and long-lasting treatment, nutritional therapy particularly including dietary polyphenols from the natural origin are endorsed. These dietary polyphenols (e.g., apigenin, baicalin, curcumin, epigallocatechin gallate, kaempferol, quercetin, resveratrol, and theaflavin), and many other phytochemicals target certain molecular, genetic mechanisms. The most common pathways of age-associated diseases are mitogen-activated protein kinase, reactive oxygen species production, nuclear factor kappa light chain enhancer of activated B cells signaling pathways, metal chelation, c-Jun N-terminal kinase, and inflammation. Polyphenols slow down the course of aging and help in combatting age-linked disorders. This exemplified in the form of clinical trials on specific dietary polyphenols in various aging-associated diseases. With this context in mind, this review reveals the new insights to slow down the aging process, and consequently reduce some classic diseases associated with age such as aforementioned, and targeting age-associated diseases by the activities of dietary polyphenols of natural origin.

Dysregulation of exosomal miRNAs and their related genes in head and neck cancer patients.

Aim: The present study aimed to figure out the potential role of exosomal microRNAs, and their targeted genes in HNC detection/diagnosis.Methods: In the present study, exosomes were extracted from the serum samples of 400 HNC patients and 400 healthy controls. Exosomes were characterized using TEM, NTA, TEM-immunogold labeling and ELISA. Quantitative PCR was used to measure the expression level of exosomal miRNA-19a, miRNA-19b and targeted genes SMAD2 and SMAD4 in HNC patients and controls.Results: The deregulation of miR-19a (p < 0.01), miR-19b (p < 0.03), SMAD2 (p < 0.04) and SMAD4 (p < 0.04) was observed in HNC patients vs controls.Conclusion: ROC curve and Kaplan-Meier analysis showed the good diagnostic/prognostic value of selected exosomal microRNAs and related genes in HNC patients.

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Insight into the wheat residues-derived adsorbents for the remediation of organic and inorganic aquatic contaminants: A review.

Wheat is a major grain crop of the world that provides a stable food for human consumption. Large amounts of by-products/waste materials are produced after the harvesting and processing of wheat crop. Such materials can cause an environmental issue if not disposed of properly. Several studies have shown that wheat residues can be efficient precursors for adsorbents because of their availability, renewability, lignocellulosic composition, and surface active groups enriched structure. In the literature, there are few review articles that address wheat residues-based adsorbents. However, these reviews were specific in terms of adsorbate or adsorbent and did not provide detailed information about the modification, properties, and regeneration of these adsorbents. This article extensively reviews the utilization of wheat biomass/waste including straw, bran, husk, and stalk as precursors for raw or untreated, chemically treated, carbonaceous, and composite adsorbents against various environmental pollutants. The influences of inlet pollutant amount, adsorbent dose, pH, temperature, and time on the performance of adsorbents against pollutants were considered. The maximum uptakes, equilibrium time, and adsorption nature were identified from isotherms, kinetic, and thermodynamic studies. The highest adsorbed amounts of most tested contaminants were 448.20, 322.58, and 578.13 mg/g for lead, chromium, and copper, 1374.6 and 1449.4 mg/g for methylene blue and malachite green, and 854.75, 179.21, and 107.77 mg/g for tetracycline, phosphate, and nitrate, respectively. For the studied adsorbate/adsorbent systems the adsorption mechanism and regeneration were also discussed. Significant results and future directions are finally presented.

Biochar-based functional materials for the abatement of emerging pollutants from aquatic matrices.

Biochar has emerged as a versatile and efficient multi-functional material, serving as both an adsorbent and catalyst in removing emerging pollutants (EPs) from aquatic matrices. However, pristine biochar's catalytic and adsorption capabilities are hindered by its poor surface functionality and small pore size. Addressing these limitations involves the development of functionalized biochar, a strategic approach aimed at enhancing its physicochemical properties and improving adsorption and catalytic efficiencies. Despite a growing interest in this field, there is a notable gap in existing literature, with no review explicitly concentrating on the efficacy of biochar-based functional materials (BCFMs) for removing EPs in aquatic environments. This comprehensive review aims to fill this void by delving into the engineering considerations essential for designing BCFMs with enhanced physiochemical properties. The focus extends to understanding the treatment efficiency of EPs through mechanisms such as adsorption or catalytic degradation. The review systematically outlines the underlying mechanisms involved in the adsorption and catalytic degradation of EPs by BCFMs. By shedding light on the prospects of BCFMs as a promising multi-functional material, the review underscores the imperative for sustained research efforts. It emphasizes the need for continued exploration into the practical implications of BCFMs, especially under environmentally relevant pollutant concentrations. This holistic approach seeks to contribute to advancing knowledge and applying biochar-based solutions in addressing the challenges posed by emerging pollutants in aquatic ecosystems.

Versatile Magnetic Mesoporous Carbon Derived Nano-Adsorbent for Synchronized Toxic Metal Removal and Bacterial Disinfection from Water Matrices.

Contamination of water resources by toxic metals and opportunistic pathogens remains a serious challenge. The development of nano-adsorbents with desired features to tackle this problem is a continuously evolving field. Here, magnetic mesoporous carbon nanospheres grafted by antimicrobial polyhexamethylene biguanidine (PHMB) are reported. Detailed mechanistic investigations reveal that the electrostatic stabilizer modified magnetic nanocore interfaced mesoporous shell can be programmatically regulated to tune the size and related morphological properties. The core-shell nano-adsorbent shows tailorable shell thickness (≈20-55 nm), high surface area (363.47 m2 g-1 ), pore volume (0.426 cm3 g-1 ), radially gradient pores (11.26 nm), and abundant biguanidine functionality. Importantly, the nano-adsorbent has high adsorption capacity for toxic thallium (Tl(I) ions (≈559 mg g-1 ), excellent disinfection against Staphylococcus aureus and Escherichia coli (>99.99% at 2 and 2.5 µg mL-1 ), ultrafast disinfection kinetics rate (>99.99% within ≈4 min), and remarkable regeneration capability when exposed to polluted water matrices. The Tl(I) removal is attributed to surface complexation and physical adsorption owing to open ended mesopores, while disinfection relies on contact of terminal biguanidines with phospholipid head groups of membrane. The significance of this work lies in bringing up effective synchronic water purification technology to combat pathogenic microorganisms and toxic metal.

Nitrogen-Doped Porous Nickel Molybdenum Phosphide Sheets for Efficient Seawater Splitting.

Hydrogen is emerging as an alternative clean fuel; however, its dependency on freshwater will be a threat to a sustainable environment. Seawater, an unlimited source, can be an alternative, but its salt-rich nature causes corrosion and introduces several competing reactions, hindering its use. To overcome these, a unique catalyst composed of porous sheets of nitrogen-doped NiMo3 P (N-NiMo3 P) having a sheet size of several microns is designed. The presence of large homogenous pores in the basal plane of these sheets makes them catalytically more active and ensures faster mass transfer. The introduction of N and Ni into MoP significantly tunes the electronic density of Mo, surface chemistry, and metal-non-metal bond lengths, optimizing surface energies, creating new active sites, and increasing electrical conductivity. The presence of metal-nitrogen bonds and surface polyanions increases the stability and improves anti-corrosive properties against chlorine chemistry. Ultimately, the N-NiMo3 P sheets show remarkable performance as it only requires overpotentials of 23 and 35 mV for hydrogen evolution reaction, and it catalyzes full water splitting at 1.52 and 1.55 V to achieve 10 mA cm-2 in 1 m KOH and seawater, respectively. Hence, structural and compositional control can make catalysts effective in realizing low-cost hydrogen directly from seawater.

Role of exosomal miRNA-19a/19b and PTEN in brain tumor diagnosis.

Aim: The current study was designed to evaluate the diagnostic significance of the exosomal miRNAs miR-19a and miR-19b and the PTEN gene in brain tumor patients versus controls. Methods: Exosomes were extracted from the serum samples of 400 brain tumor patients and 400 healthy controls. The exosomes were characterized by scanning electron microscopy, dynamic light scattering and ELISA. Quantitative PCR was used to analyze selected exosome miRNAs and gene expression levels. Results: Analysis showed significant deregulated expression of miR-19a (p < 0.0001), miR-19b (p < 0.0001) and PTEN (p < 0.001) in patients versus controls. Spearman correlation showed a significant correlation among the selected exosomal miRNAs and the PTEN gene. Conclusion: Receiver operating characteristic curve analysis showed the good diagnostic value of exosomal miRNAs and the PTEN gene in brain tumor patients.

Oscillatoria limnetica Mediated Green Synthesis of Iron Oxide (Fe2O3) Nanoparticles and Their Diverse In Vitro Bioactivities.

Iron oxide nanoparticles (Fe2O3-NPs) were synthesized using Oscillatoria limnetica extract as strong reducing and capping agents. The synthesized iron oxide nanoparticles IONPs were characterized by UV-visible spectroscopy, Fourier transform infrared (FTIR), X-ray diffractive analysis (XRD), scanning electron microscope (SEM), and Energy dispersive X-ray spectroscopy (EDX). IONPs synthesis was confirmed by UV-visible spectroscopy by observing the peak at 471 nm. Furthermore, different in vitro biological assays, which showed important therapeutic potentials, were performed. Antimicrobial assay of biosynthesized IONPs was performed against four different Gram-positive and Gram-negative bacterial strains. E. coli was found to be the least suspected strain (MIC: 35 µg/mL), and B. subtilis was found to be the most suspected strain (MIC: 14 µg/mL). The maximum antifungal assay was observed for Aspergillus versicolor (MIC: 27 µg mL). The cytotoxic assay of IONPs was also studied using a brine shrimp cytotoxicity assay, and LD50 value was reported as 47 µg/mL. In toxicological evaluation, IONPs was found to be biologically compatible to human RBCs (IC50: >200 µg/mL). The antioxidant assay, DPPH 2,2-diphenyl-1-picrylhydrazyly was recorded at 73% for IONPs. In conclusion, IONPs revealed great biological potential and can be further recommended for in vitro and in vivo therapeutic purposes.

Role of genetic variations of DNA damage response pathway genes and heat-shock proteins in increased head and neck cancer risk.

Aim: The present study was designed to evaluate the role of DNA damage response pathway genes and heat-shock proteins in head and neck cancer (HNC) risk. Methods: For this purpose, two study cohorts were used. Cohort 1 (blood samples of 250 HNC patients and 250 controls) was used for polymorphism screening of selected genes using tetra-primer amplification refractory mutation system-polymerase chain (Tetra-ARMS PCR). Cohort 2 (200 HNC tumors and adjacent controls) was used for expression analysis, using quantitative PCR. Results: Analysis showed that mutant allele frequency of selected polymorphisms was found associated with increased HNC risk. Expression analysis showed the significant deregulation of selected genes in patients. Conclusion: The present study showed that selected genes (CHK1, CHK2, HSP70 and HSP90) can act as good diagnostic/prognostic markers in HNC.

The present study is designed to identify the selected genes of DNA damage response pathway and heat-shock proteins as diagnostic/prognostic markers of head and neck cancer (HNC). To do this, DNA was isolated from blood samples and RNA isolated from the tissue samples of HNC patients. The mutation and expression level of selected genes was tested, and selected genes showed good diagnostic/prognostic values for HNC patients.

Cd diminution through microbial mediated degraded lignocellulose maize straw: Batch adsorption and bioavailability trails.

Lignocellulose degraded maize straw (LMS) was prepared with the interaction of soil-indigenous microorganisms and further deployed to attenuate the Cd contamination in polluted soil. The Lignocellulose degrading ratio was determined and results revealed the significant degradation of cellulose, hemicellulose and lignin by 33.03, 26.7 and 15.97% respectively as compared to pristine maize straw (PS). Moreover, LMS was also categorized through FE-SEM, FTIR, BET analysis, elemental analysis and XPS technique and the analytical results indicated that lignocellulose structure in maize straw was successfully degraded and was involved in metal-ion complexation. Batch sorption trials revealed that Cd2+ sorption onto LMS was explained well by Langmuir isotherm and pseudo-second-order kinetic model. The LMS showed maximum adsorption capacities (9.84 mg g-1) for Cd2+ as compared to PS (3.30 mg g-1). Moreover, the soil incubation trials (60 days) depicted the availability of Cd decreased by 11.03 and 34.7% with PS and LMS application respectively. The addition of LMS significantly decreased the exchangeable fractions of Cd and ensued an increase in organic matter and Fe-Mn oxides bound fractions. This work clarified the LMS as a promising amendment for effective remediation of Cd-contaminated matrices.

Promising role of polymeric nanoparticles in the treatment of rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic inflammatory illness caused by an autoimmune disorder of synovial membrane resulting in synovial membrane dysfunction. The available treatment particularly focuses on inhibiting macrophage proliferation and reducing the generation of pro-inflammatory cytokines. However, therapeutic success of current treatment options at targeted site is limited; therefore, development of promising therapeutic strategy is the need of time that may provide better targeted delivery of drug with added safety. In development of precision medicine to manage RA, nanotechnology is a viable option to be considered. Recent research using nanoparticles for the treatment of RA, particularly polymeric nanoparticles, has been discussed in this article. Using polymeric nanoparticles as a therapeutic method has shown considerable promise of enhancing treatment success over standard medications used in routine. It is exclusively evident that the viability of using nanoparticles is mainly owed due to their biocompatibility, chemical stability, controlled drug release, and selective drug delivery to inflamed tissues in RA model animals. The current analysis focuses on the critical design characteristics of RA-targeted nanotechnology-based strategies in quest of better therapeutic strategies for RA, and to identify leading polymer as the most effective medications in RA therapy.

Uncovering the Anticancer Potential of Polydatin: A Mechanistic Insight.

Polydatin or 3-O-ß-d-resveratrol-glucopyranoside (PD), a stilbenoid component of Polygonum cuspicadum (Polygonaceae), has a variety of biological roles. In traditional Chinese medicine, P. cuspicadum extracts are used for the treatment of infections, inflammation, and cardiovascular disorders. Polydatin possesses a broad range of biological activities including antioxidant, anti-inflammatory, anticancer, and hepatoprotective, neuroprotective, and immunostimulatory effects. Currently, a major proportion of the population is victimized with cervical lung cancer, ovarian cancer and breast cancer. PD has been recognized as a potent anticancer agent. PD could effectively inhibit the migration and proliferation of ovarian cancer cells, as well as the expression of the PI3K protein. The malignancy of lung cancer cells was reduced after PD treatments via targeting caspase 3, arresting cancer cells at the S phase and inhibiting NLRP3 inflammasome by downregulation of the NF-κB pathway. This ceases cell cycle, inhibits VEGF, and counteracts ROS in breast cancer. It also prevents cervical cancer by regulating epithelial-to-mesenchymal transition (EMT), apoptosis, and the C-Myc gene. The objective of this review is thus to unveil the polydatin anticancer potential for the treatment of various tumors, as well as to examine the mechanisms of action of this compound.

Role of mitochondrial sirtuins in rheumatoid arthritis.

AIM: Current study is intended to evaluate the expression and epigenetic variations of mitochondrial situins in 306 rheumatoid arthritis (RA) cases and compared with age/gender matched controls. MATERIALS AND METHODS: The expression level was measured using the quantitative Real time PCR (qPCR) and epigenetic analysis was performed by measuring deacetylation activity. Oxidative stress was also measured in present study using the enzyme linked immunoassay (ELISA). The obtained results were evaluated by means of the student t-test, spearman correlation and ROC curve analysis. RESULTS: Expression analysis showed the significant downregulation of SIRT3 (p < 0.0001), SIRT4 (p < 0.0001) and SIRT5 (p < 0.0001) in RA cases when compared with controls. Downregulation of mitochondrial sirtuins was significantly associated with positive anti-CCP status, increased ESR level and with increased CRP levels. Epigenetic analysis showed significant increased histone deacetylation in RA patients compared to controls. Co-expression analysis showed the significant negative association between expression level of mitochondrial sirtuins and deacytylation level (SIRT3 r = -0.438, p < 0.0001; SIRT4 r = -0.424, p < 0.0001; SIRT5 r = -0.282, p < 0.0001). ROC curve analysis exhibited that downregulation of mitochondrial sirtuins (SIRT3 AUC = 0.91, p < 0.001; SIRT4 AUC = 0.92, p < 0.001; SIRT5 AUC = 0.85, p < 0.001) was act as the good diagnostic marker for detection/diagnosis of arthritis. CONCLUSIONS: The results show that significant deregulation of mitochondrial sirtuins was associated with increased arthritis risk and can be act as an indicator of advance clinical outcome.

Inducible knockdown of Mycobacterium smegmatis MSMEG_2975 (glyoxalase II) affected bacterial growth, antibiotic susceptibility, biofilm, and transcriptome.

Tuberculosis (TB) causes millions of deaths each year across the globe. Multiple drug-resistant (MDR) and extensively drug-resistant (XDR) mycobacterial strains have made the treatment extremely difficult. To overcome this hurdle, the development of new drug targets and an effective treatment strategy are desperately needed. This can be achieved by deciphering the role of essential genes and enzymes which are involved in cell survival. One such enzyme is glyoxalase II. The glyoxalase system (glyoxalase I and glyoxalase II) has a pivotal role in cellular survival and detoxification by converting methylglyoxal (MG) into lactate. Otherwise, the increased concentration of MG then modifies DNA, proteins, and lipids, resulting in abnormalities and cell death. Interestingly, the function and physiological role of glyoxalase II have remained undetermined in mycobacteria. In this study, the functional activity of MSMEG_2975 (putative glyoxalase II) after heterologous cloning and expression was determined. And the knockdown strain Mycobacterium smegmatis KD for MSMEG_2975 was constructed with tetracycline-inducible vector pMIND. The inducible knockdown of MSMEG_2975 affected bacterial growth, biofilm formation, transcriptome, and enhanced the susceptibility to antibiotics. This work represents mycobacterial glyoxalase II as a potential drug target against mycobacterial pathogens and indicates the crucial regulatory role of glyoxalase II in mycobacteria.

Combination of natural antivirals and potent immune invigorators: A natural remedy to combat COVID-19.

The flare-up in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in December 2019 in Wuhan, China, and spread expeditiously worldwide has become a health challenge globally. The rapid transmission, absence of anti-SARS-CoV-2 drugs, and inexistence of vaccine are further exacerbating the situation. Several drugs, including chloroquine, remdesivir, and favipiravir, are presently undergoing clinical investigation to further scrutinize their effectiveness and validity in the management of COVID-19. Natural products (NPs) in general, and plants constituents specifically, are unique sources for various effective and novel drugs. Immunostimulants, including vitamins, iron, zinc, chrysin, caffeic acid, and gallic acid, act as potent weapons against COVID-19 by reinvigorating the defensive mechanisms of the immune system. Immunity boosters prevent COVID-19 by stimulating the proliferation of T-cells, B-cells, and neutrophils, neutralizing the free radicals, inhibiting the immunosuppressive agents, and promoting cytokine production. Presently, antiviral therapy includes several lead compounds, such as baicalin, glycyrrhizin, theaflavin, and herbacetin, all of which seem to act against SARS-CoV-2 via particular targets, such as blocking virus entry, attachment to host cell receptor, inhibiting viral replication, and assembly and release.

Latest Research Trends in Fall Detection and Prevention Using Machine Learning: A Systematic Review.

Falls are unusual actions that cause a significant health risk among older people. The growing percentage of people of old age requires urgent development of fall detection and prevention systems. The emerging technology focuses on developing such systems to improve quality of life, especially for the elderly. A fall prevention system tries to predict and reduce the risk of falls. In contrast, a fall detection system observes the fall and generates a help notification to minimize the consequences of falls. A plethora of technical and review papers exist in the literature with a primary focus on fall detection. Similarly, several studies are relatively old, with a focus on wearables only, and use statistical and threshold-based approaches with a high false alarm rate. Therefore, this paper presents the latest research trends in fall detection and prevention systems using Machine Learning (ML) algorithms. It uses recent studies and analyzes datasets, age groups, ML algorithms, sensors, and location. Additionally, it provides a detailed discussion of the current trends of fall detection and prevention systems with possible future directions. This overview can help researchers understand the current systems and propose new methodologies by improving the highlighted issues.

Recent updates on immunological, pharmacological, and alternative approaches to combat COVID-19.

The pandemic coronavirus disease 2019 (COVID-19) is instigated by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that is mainly transmitted via the inhalation route and characterized by fever, coughing and shortness of breath. COVID-19 affects all age groups with no single cure. The drug discovery, manufacturing, and safety studies require extensive time and sources and, therefore, struggled to match the exponential spread of COVID-19. Yet, various repurposed drugs (antivirals, immune-modulators, nucleotide analogues), and convalescent plasma therapy have been authorized for emergency use against COVID-19 by Food and Drug Administration under certain limits and conditions. The discovery of vaccine is the biggest milestone achieved during the current pandemic era. About nine vaccines were developed for human use with varying claims of efficacy. The rapid emergence of mutations in SARS-CoV-2, suspected adverse drug reactions of current therapies in special population groups and limited availability of drugs in developing countries necessitate the development of more efficacious, safe and cheap drugs/vaccines for treatment and prevention of COVID-19. Keeping in view these limitations, the current review provides an update on the efficacy and safety of the repurposed, and natural drugs to treat COVID-19 as well as the vaccines used for its prophylaxis.

Finger Gesture Spotting from Long Sequences Based on Multi-Stream Recurrent Neural Networks.

Gesture spotting is an essential task for recognizing finger gestures used to control in-car touchless interfaces. Automated methods to achieve this task require to detect video segments where gestures are observed, to discard natural behaviors of users' hands that may look as target gestures, and be able to work online. In this paper, we address these challenges with a recurrent neural architecture for online finger gesture spotting. We propose a multi-stream network merging hand and hand-location features, which help to discriminate target gestures from natural movements of the hand, since these may not happen in the same 3D spatial location. Our multi-stream recurrent neural network (RNN) recurrently learns semantic information, allowing to spot gestures online in long untrimmed video sequences. In order to validate our method, we collect a finger gesture dataset in an in-vehicle scenario of an autonomous car. 226 videos with more than 2100 continuous instances were captured with a depth sensor. On this dataset, our gesture spotting approach outperforms state-of-the-art methods with an improvement of about 10% and 15% of recall and precision, respectively. Furthermore, we demonstrated that by combining with an existing gesture classifier (a 3D Convolutional Neural Network), our proposal achieves better performance than previous hand gesture recognition methods.

Inception learning super-resolution.

An efficient network for super-resolution, which we refer to as inception learning super-resolution (ILSR), is proposed. We adopt the inception module from GoogLeNet to exploit multiple features from low-resolution images, yet maintain fast training steps. The proposed ILSR network demonstrates low computation time and fast convergence during the training process. It is divided into three parts: feature extraction, mapping, and reconstruction. In feature extraction, we apply the inception module followed by dimensional reduction. Then, we map features using a simple convolutional layer. Finally, we reconstruct the high-resolution component using the inception module and a 1×1 convolutional layer. Experimental results demonstrate that the proposed network can construct sharp edges and clean textures, and reduce computation time by up to three orders of magnitude compared to state-of-the-art methods.

The impact of liquidity risk and credit risk on bank profitability during COVID-19.

The COVID-19 outbreak caused a massive setback to the stability of financial system due to emergence of several other risks with COVID, which significantly influenced the continuity of profitable banking operations. Therefore, this study aims to see that how differently the liquidity risk and credit risk influenced the banking profitability during Covid-19 (Q12020 to Q42021) than before COVID (Q12018 to Q42019). The study employs pooled OLS, and OLS fixed & random effects models, to analyze the panel data on a sample of 37 banks currently operating in Pakistan. The results depict that liquidity risk has a positive and significant relationship with return on assets and return on equity, but insignificant relationship with net interest margin. Credit risk has a negative and significant relationship with return on assets, return on equity, and net interest margin. The study also applies quantile regression to address the normality issue in data. The quantile regression results are consistent with pooled OLS, and OLS fixed and random effects results. The study makes valuable suggestions for regulators, policymakers, and others users of financial institutional data. The current study will help to set policies for efficient management of LR and CR.