Revealing Melatonin's Mysteries: Receptors, Signaling Pathways, and Therapeutics Applications.

Melatonin (5-methoxy-acetyl tryptamine) is a sleep-inducing hormone, and the pineal gland produces it in response to the circadian clock of darkness. In the body, MT1 and MT2 receptors are mostly found, having an orthosteric pocket and ligand binding determinants. Melatonin acts by binding on melatonin receptors, intracellular proteins, and orphan nuclear receptors. It inhibits adenyl cyclase and activates phospholipase C, resulting in gene expression and an intracellular alteration environment. Melatonin signaling pathways are also associated with other intracellular signaling pathways, i. e., cAMP/PKA and MAPK/ERK pathways. Relative expression of different proteins depends on the coupling profile of G protein, accounting pharmacology of the melatonin receptor bias system, and mediates action in a Gi-dependent manner. It shows antioxidant, antitumor, antiproliferative, and neuroprotective activity. Different types of melatonin agonists have been synthesized for the treatment of sleeping disorders. Researchers have developed therapeutics that target melatonin signaling, which could benefit a wide range of medical conditions. This review focuses on melatonin receptors, pharmacology, and signaling cascades; it aims to provide basic mechanical aspects of the receptor's pharmacology, melatonin's functions in cancer and neurodegenerative diseases, and any treatments and drugs designed for these diseases. This will allow a basic comparison between the receptors in question, highlighting any parallels and differences that may exist and providing fundamental knowledge about these receptors to future researchers.

Development of Data-driven Machine Learning Models and their Potential Role in Predicting Dengue outbreak.

ABSTRACT: Dengue fever is one of the most widespread vector-borne viral infections in the world, resulting in increased socio-economic burdens. The WHO has reported that 2.5 billion people are infected with dengue fever across the world, resulting in high mortalities in tropical and subtropical regions. The current article endeavors to present an overview of predicting dengue outbreaks through data-based machine-learning models. This artificial intelligence model uses real-world data such as dengue surveillance, climatic variables, and epidemiological data and combines big data with machine learning algorithms to forecast dengue. Monitoring and predicting dengue incidences have been significantly enhanced through innovative approaches. This involves gathering data on various climatic factors, including temperature, rainfall, relative humidity, and wind speed, along with monthly records of dengue cases. The study functions as an efficient warning system, enabling the anticipation of dengue outbreaks. This early warning system not only alerts communities but also aids relevant authorities in implementing crucial preventive measures.

Electronic and Excitonic Properties of MSi2 Z4 Monolayers.

MA2 Z4 monolayers form a new class of hexagonal non-centrosymmetric materials hosting extraordinary spin-valley physics. While only two compounds (MoSi2 N4 and WSi2 N4 ) are recently synthesized, theory predicts interesting (opto)electronic properties of a whole new family of such two-dimensional (2D) materials. Here, the chemical trends of band gaps and spin-orbit splittings of bands in selected MSi2 Z4 (M = Mo, W; Z = N, P, As, Sb) compounds are studied from first-principles. Effective Bethe-Salpeter-equation-based calculations reveal high exciton binding energies. Evolution of excitonic energies under external magnetic field is predicted by providing their effective g-factors and diamagnetic coefficients, which can be directly compared to experimental values. In particular, large positive g-factors are predicted for excitons involving higher conduction bands. In view of these predictions, MSi2 Z4 monolayers yield a new platform to study excitons and are attractive for optoelectronic devices, also in the form of heterostructures. In addition, a spin-orbit induced bands inversion is observed in the heaviest studied compound, WSi2 Sb4 , a hallmark of its topological nature.

Role of poFUT1 and O-fucosylation in placental angiogenesis†.

Trophoblast cells are critical to placental angiogenesis in the first trimester of pregnancy. Dysfunction of trophoblast leads to defective vascular remodeling and impaired angiogenesis, which is believed as the major cause of placental insufficiency and pregnancy failure. Protein O-fucosyltransferase 1 (poFUT1) is mainly responsible for O-fucosylated glycan biosynthesis on glycoproteins, and poFUT1 deficiency causes embryonic lethality in mice. However, the expression and function of poFUT1 in trophoblast-mediated human placental vessel formation remain unclear. In the current study, we showed that fewer blood vessels were observed in the villi and decidua of miscarriage patients than in normal pregnancy women. The expression of poFUT1 was decreased in the trophoblast cells of miscarriage patients compared with normal pregnancy women. Employing HTR/SVneo cells and an in vivo chorioallantoic membrane assay, we demonstrated that poFUT1 promoted the proliferation, migration ability, and angiogenesis potential of trophoblast cells. The results also indicated that poFUT1 upregulated O-fucosylation on uPA, facilitated the binding of uPA and uPAR, activated the RhoA signaling pathway, and further enhanced the angiogenic capacity of trophoblast cells. Our study provides new evidence for a relationship between poFUT1/O-fucosylation and placental angiogenesis. These findings may provide potential diagnostic biomarkers and targeted therapies for miscarriage patients.

Unsteady ternary hybrid-nanofluid flow over an expanding/shrinking cylinder with multiple slips: a Yamada-Ota model implementation.

The primary objective of this investigation is to examine the thermal state of an unsteady ternary hybrid-nanofluid flow over an expanding/shrinking cylinder. The influence of radiation along with a non-uniform thermal source/sink is taken into account to expedite heat distribution. Multiple slips are considered at the cylinder interface. The mathematical model is simplified by incorporating appropriate transformations. A numerical solution is obtained using the bvp4c algorithm. The flow characteristics and behavior of the trihybrid nanoliquid exhibit significant changes when the cylinder expands or contracts. The effects of various emerging parameters are analyzed using graphical representations. The velocity field shows an opposite trend when the unsteadiness and mass transfer parameters are increased. The thermal field improves with higher values of the non-uniform source/sink parameter but deteriorates with an increase in the thermal slip parameter. The drag force increases with higher values of the unsteadiness parameter, while it decreases with amplified values of the mass suction and velocity slip parameters. A strong correlation is observed with previous studies which validates and strengthens the credibility of the present analysis.

Combined impacts of low oscillating magnetic field and Shliomis theory on mono and hybrid nanofluid flows with nonlinear thermal radiation.

Hybrid nanofluids have become a popular choice for various engineering and industrial applications due to their advanced properties. This study focuses on investigating the consequences of a low oscillating magnetic field on the flow of unsteady mono and hybrid nanofluids over a vertically moving permeable disk. Initially, iron oxide nanoparticles are mixed with water to create a mono nanofluid, which is later transformed into a hybrid nanofluid by adding cobalt nanoparticles. The shape of nanoparticles used is brick-shaped, and an external magnetic field is applied to regulate the flow and heat transfer mechanism using ferromagnetic nanoparticles. Additionally, the nonlinear thermal radiative heat flux is considered for the heat transfer phenomenon. The momentum and rotational motion of the magnetic fluid caused by the rotating disk are formulated using the Shliomis fundamental concept. The numerical analysis of the ordinary differential equations (ODEs) is carried out using the bvp4c technique, and the results are presented in tabular form for the surface drag coefficient and heat transmission at the walls. Moreover, the temperature and velocity distributions are illustrated using graphical representations against relevant parameters. The findings highlight that for a constant negative value for the magnetization parameterϒ<0,the heat transfer rate for hybrid nanofluid is witnessed stronger at a volume fractionϕhnf=0.120,whereas a minimal heat transfer rate is observed for positive values of magnetization parameterϒ>0at the same value of volume fraction.

Functionalized graphene oxide-zinc oxide hybrid material and its deployment for adsorptive removal of levofloxacin from aqueous media.

This work reports on the synthesis of aspartic acid-functionalized graphene oxide-zinc oxide, as a functional porous material, and its potential to mitigate levofloxacin (LFXN). The adsorbent was characterized by various techniques, including ultraviolet-visible (UV-Vis), Fourier transform infrared (FT-IR) spectroscopy, powder X-ray diffraction (PXRD), and scanning electron microscopy (SEM). The average crystallite size of the prepared composite was about 17.30 nm. Batch adsorption studies were carried out to elucidate the adsorption process for LFXN. Different parameters, including contact time, LFXN initial concentration, adsorbent concentration, pH, temperature, and ionic strength were studied. The mechanism and kinetics were studied by fitting the data to Freundlich and Langmuir isotherms, pseudo-first-order and pseudo-second-order kinetic models, respectively. The isotherm data was better fitted to Langmuir isotherm (R2 = 0.999) as compared to the Freundlich model. The maximum adsorption capacity obtained at equilibrium was 73.15 mg/g. For kinetic studies, Pseudo first order was better fitted with R2 = 0.87797, confirming the physisorption process. Thermodynamics parameters revealed that the process was exothermic and spontaneous at low temperatures. The adsorption mechanism was studied and the impregnation of LFXN in the adsorbent was confirmed by FTIR studies. This research proved that the designed GO/Asp-ZnO was a novel and promising adsorbent for the removal of LFXN with an efficiency of 95.12% at 30 mg/L LFXN by 0.6 g/L adsorbent in 24 h at pH = 7 and T = 25 °C.

Comparative evaluation of cell-mediated immune response in calves immunized with live-attenuated and killed Theileria annulata vaccines.

Tropical theileriosis is a tick-borne disease caused by the protozoan Theileria annulata and transmitted by numerous species of Ixodid ticks of the genus Hyalomma. The main clinical signs are fever, lymphadenopathy, and anemia responsible for heavy economic losses, including mortality, morbidity, vaccination failure, and treatment cost. Development of poor cell-mediated immunity (CMI) has been observed in the case of many bovine pathogens (bacteria, viruses, and parasites). Quantification of CMI is a prerequisite for evaluating vaccine efficacy against theileriosis caused by T. annulata. The current study evaluated the CMI in calves administered with two types of T. annulata vaccine (live attenuated and killed). We prepared a live attenuated T. annulata vaccine by attenuation in a rabbit model and also prepared killed vaccine from non-attenuated T. annulata. For the evaluation of immune response in experimental groups including control, 20 calves were divided into four different groups (A, B, C, and D). They were either inoculated subcutaneously with live rabbit-propagated-Theileria-infected RBCs (5 × 106) (group A) or with killed T. annulata vaccine (2 × 109 schizonts) with Freund's adjuvant (group B), along with an infected group (group C) and a healthy control group (group D). The protection of vaccinated calves was estimated with challenge infection. Our results showed that with a single shot of live-attenuated and killed vaccine with a booster dose elicited cell-mediated immune responses in immunized calves. We observed a significant elevation in CD4 + and CD8 + T cells in immunized calves. A significant difference in the CD8 + T cell response between the post-challenge stage of killed and live vaccine (p < 0.0001) was observed, whereas no other difference was found at both pre- and post-immunization stages. A similar finding was recorded for the CD4 + T cells at a post-challenge stage, where a significant difference was seen between killed and live vaccine (p < 0.0001). Another significant difference was observed between the CD8 + T cells and CD4 + T cells at the post-challenge stage in the live vaccine group, where there was a significantly higher induction of CD4 + T cell response (p < 0.0001).

A step towards achieving SDG 2030 agenda: Analyzing the predictive power of information globalization amidst technological innovation-environmental stewardship nexus in the greenest economies.

Through the transition of novel ideas, products, technologies, and business models, info-globalization facilitates the flow and expansion of cross-border information and resources. In the meantime, this stimulates the potential of informational globalization and the internet for environmental and other technological advancements, and assists to the realization of cleaner and greener production and consumption. However, prior studies have completely disregarded this facet of globalization. Thus, this novel study evaluates the role of technological innovation (TIN) and information globalization (ING) in predicting ecological footprints (EFP) and carbon emissions (CO2) in the world's top ten greenest economies. Besides, this study also unveils the moderating role of TIN and ING for environmental sustainability. The novel research employs non-parametric causality-in-quantiles approaches on quarterly data from 1994Q1 to 2019Q4 in order to quantify for causality-in-mean and causality-in-variance, since there may be no causation at first moment, but higher-order interdependencies may exist. The findings revealed that TIN and ING possess significant predictive potential for both ecological footprint and carbon emissions, indicating asymmetric predictability over environmental sustainability. Moreover, TIN and ING asserted a significant interaction role when it comes to predicting pollution levels in chosen countries. Overall, it is essential to note that natural resource conservation and pollution mitigation via green and technical innovation become a dilemma since pollution has no boundaries and will always stoke fires beyond them. The provision of financial and R&D assistance, as well as the use of mass and social media to raise awareness not only in their own regions but also in neighboring countries, might contribute to the achievement of SDG 13 and Cope26's ambition of cutting pollution by 2030.

Assessment of the Phytochemical Analysis and Antimicrobial Potentials of Zingiber zerumbet.

Antimicrobial resistance (AMR) has arisen as a global concern in recent decades. Plant extracts used in combination with antibiotics are promising against AMR, synergistically. The purpose of this study was to evaluate the component of the bitter ginger (Zingiber zerumbet) extract in different solvents using high-performance liquid chromatography (HPLC), in addition to evaluate the antibacterial activity of these extracts, in combination with their antibiotic potential against four multi-drug resistant (MDR) bacterial strains (Lactobacillus acidophilus, Streptococcus mutans, Enterococcus faecalis and Staphylococcus aureus). Ethanol and the aqueous extracts of bitter ginger were prepared using a conventional solvent extraction method and were evaluated for their phytochemistry using HPLC, qualitatively and quantitatively. Moreover, the antibiotic susceptibility of the pathogenic isolates was determined. A disc diffusion assay was used to obtain the antimicrobial potential of the extracts alone and with antibiotics. Eight components were identified from the separation of the bitter ginger extract by HPLC. For AMR bacteria, the combination of the antibiotic solution with the bitter ginger crude extracts could improve its susceptibility of these antibiotics. This study indicates that the combination of an antibiotic solution with the bitter ginger crude extract exhibits potent antibacterial activities against MDR bacterial strains. Therefore, they can be used for the treatment of various diseases against the microbial pathogen and can be incorporated into medication for antibacterial therapy.

Deep Learning Models for Classification of Dental Diseases Using Orthopantomography X-ray OPG Images.

The teeth are the most challenging material to work with in the human body. Existing methods for detecting teeth problems are characterised by low efficiency, the complexity of the experiential operation, and a higher level of user intervention. Older oral disease detection approaches were manual, time-consuming, and required a dentist to examine and evaluate the disease. To address these concerns, we propose a novel approach for detecting and classifying the four most common teeth problems: cavities, root canals, dental crowns, and broken-down root canals, based on the deep learning model. In this study, we apply the YOLOv3 deep learning model to develop an automated tool capable of diagnosing and classifying dental abnormalities, such as dental panoramic X-ray images (OPG). Due to the lack of dental disease datasets, we created the Dental X-rays dataset to detect and classify these diseases. The size of datasets used after augmentation was 1200 images. The dataset comprises dental panoramic images with dental disorders such as cavities, root canals, BDR, dental crowns, and so on. The dataset was divided into 70% training and 30% testing images. The trained model YOLOv3 was evaluated on test images after training. The experiments demonstrated that the proposed model achieved 99.33% accuracy and performed better than the existing state-of-the-art models in terms of accuracy and universality if we used our datasets on other models.

Unusual Driver Behavior Detection in Videos Using Deep Learning Models.

Anomalous driving behavior detection is becoming more popular since it is vital in ensuring the safety of drivers and passengers in vehicles. Road accidents happen for various reasons, including health, mental stress, and fatigue. It is critical to monitor abnormal driving behaviors in real time to improve driving safety, raise driver awareness of their driving patterns, and minimize future road accidents. Many symptoms appear to show this condition in the driver, such as facial expressions or abnormal actions. The abnormal activity was among the most common causes of road accidents, accounting for nearly 20% of all accidents, according to international data on accident causes. To avoid serious consequences, abnormal driving behaviors must be identified and avoided. As it is difficult to monitor anyone continuously, automated detection of this condition is more effective and quicker. To increase drivers' recognition of their driving behaviors and prevent potential accidents, a precise monitoring approach that detects abnormal driving behaviors and identifies abnormal driving behaviors is required. The most common activities performed by the driver while driving is drinking, eating, smoking, and calling. These types of driver activities are considered in this work, along with normal driving. This study proposed deep learning-based detection models for recognizing abnormal driver actions. This system is trained and tested using a newly created dataset, including five classes. The main classes include Driver-smoking, Driver-eating, Driver-drinking, Driver-calling, and Driver-normal. For the analysis of results, pre-trained and fine-tuned CNN models are considered. The proposed CNN-based model and pre-trained models ResNet101, VGG-16, VGG-19, and Inception-v3 are used. The results are compared by using the performance measures. The results are obtained 89%, 93%, 93%, 94% for pre-trained models and 95% by using the proposed CNN-based model. Our analysis and results revealed that our proposed CNN base model performed well and could effectively classify the driver's abnormal behavior.

Effects of Shrimp Peptide Hydrolysate on Intestinal Microbiota Restoration and Immune Modulation in Cyclophosphamide-Treated Mice.

The gut microbiota is important in regulating host metabolism, maintaining physiology, and protecting immune homeostasis. Gut microbiota dysbiosis affects the development of the gut microenvironment, as well as the onset of various external systemic diseases and metabolic syndromes. Cyclophosphamide (CTX) is a commonly used chemotherapeutic drug that suppresses the host immune system, intestinal mucosa inflammation, and dysbiosis of the intestinal flora. Immunomodulators are necessary to enhance the immune system and prevent homeostasis disbalance and cytotoxicity caused by CTX. In this study, shrimp peptide hydrolysate (SPH) was evaluated for immunomodulation, intestinal integration, and microbiota in CTX-induced immunosuppressed mice. It was observed that SPH would significantly restore goblet cells and intestinal mucosa integrity, modulate the immune system, and increase relative expression of mRNA and tight-junction associated proteins (Occludin, Zo-1, Claudin-1, and Mucin-2). It also improved gut flora and restored the intestinal microbiota ecological balance by removing harmful microbes of various taxonomic groups. This would also increase the immune organs index, serum levels of cytokines (IFN-ϒ, IL1ß, TNF-α, IL-6), and immunoglobin levels (IgA, IgM). The Firmicutes/Bacteroidetes proportion was decreased in CTX-induced mice. Finally, SPH would be recommended as a functional food source with a modulatory effect not only on intestinal microbiota, but also as a potential health-promoting immune function regulator.

Synthesis of Silver Nanoparticles from Extracts of Wild Ginger (Zingiber zerumbet) with Antibacterial Activity against Selective Multidrug Resistant Oral Bacteria.

Antibiotic resistance rate is rising worldwide. Silver nanoparticles (AgNPs) are potent for fighting antimicrobial resistance (AMR), independently or synergistically. The purpose of this study was to prepare AgNPs using wild ginger extracts and to evaluate the antibacterial efficacy of these AgNPs against multidrug-resistant (MDR) Staphylococcus aureus, Streptococcus mutans, and Enterococcus faecalis. AgNPs were synthesized using wild ginger extracts at room temperature through different parameters for optimization, i.e., pH and variable molar concentration. Synthesis of AgNPs was confirmed by UV/visible spectroscopy and further characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy analysis (EDXA), and Fourier-transform infrared spectroscopy (FTIR). Disc and agar well diffusion techniques were utilized to determine the in vitro antibacterial activity of plant extracts and AgNPs. The surface plasmon resonance peaks in absorption spectra for silver suspension showed the absorption maxima in the range of 400-420 nm. Functional biomolecules such as N-H, C-H, O-H, C-O, and C-O-C were present in Zingiber zerumbet (Z. zerumbet) (aqueous and organic extracts) responsible for the AgNP formation characterized by FTIR. The crystalline structure of ZZAE-AgCl-NPs and ZZEE-AgCl-NPs was displayed in the XRD analysis. SEM analysis revealed the surface morphology. The EDXA analysis also confirmed the element of silver. It was revealed that AgNPs were seemingly spherical in morphology. The biosynthesized AgNPs exhibited complete antibacterial activity against the tested MDR bacterial strains. This study indicates that AgNPs of wild ginger extracts exhibit potent antibacterial activity against MDR bacterial strains.

Comparison of Redo percutaneous mitral valvuloplasty for mitral restenosis with first procedure for de novo mitral stenosis.

Objectives: To evaluate and compare the effects of redo percutaneous mitral valvuloplasty with initial percutaneous mitral valvuloplasty (PMV) in mitral restenosis (MR) and de novo mitral stenosis (MS) patients, respectively. Methods: A retrospective study was conducted at the cardiology department of Ch. Pervaiz Elahi Institute of Cardiology Multan for the period of one year from 6th July 2020 to 6th July 2021. A total of 50 patients were recruited in the study. Out of them, 20 de novo MS patients were placed in one group, while 30 patients with mitral restenosis, after successful initial percutaneous mitral valvuloplasty, were placed in another group. Ante grade trans-septal approach was adopted to perform percutaneous mitral valvuloplasty. The procedure was considered successful in achieving a 50% increase in the area of the mitral valve, without any major complication. Results: Procedural success in first PMV patients was more (18 patients; 90.0%) than in redo PMV patients (26 patients; 86.6%) (Non-significant). The patients in both groups didn't differ significantly in terms of MVA after the procedure, the increase of MVA, the average difference in blood pressure across the mitral valve, and the complications experienced after the complete procedure. However, the final mitral valve area was negatively correlated with the initial area in both groups. Conclusion: Redo PMV for MR when performed after successful initial PMV is effective, has considerable rate of procedural success, which is achieved with a complication rate less as compared to initial PMV for de novo mitral stenosis.

Tuning Valleys and Wave Functions of van der Waals Heterostructures by Varying the Number of Layers: A First-Principles Study.

In van der Waals heterostructures of 2D transition-metal dichalcogenides (2D TMDCs) electron and hole states are spatially localized in different layers forming long-lived interlayer excitons. Here, the influence of additional electron or hole layers on the electronic properties of a MoS2 /WSe2 heterobilayer (HBL), which is a direct bandgap material, is investigated from first principles. Additional layers modify the interlayer hybridization, mostly affecting the quasiparticle energy and real-space extend of hole states at the Γ and electron states at the Q valleys. For a sufficient number of additional layers, the band edges move from K to Q or Γ, respectively. Adding electron layers to the HBL leads to more delocalized K and Q states, while Γ states do not extend much beyond the HBL, even when more hole layers are added. These results suggest a simple and yet powerful way to tune band edges and the real-space extent of the electron and hole wave functions in TMDC heterostructures, potentially affecting strongly the lifetime and dynamics of interlayer excitons.

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.

A Fuzzy Rule-Based System for Classification of Diabetes.

Diabetes is a fatal disease that currently has no treatment. However, early diagnosis of diabetes aids patients to start timely treatment and thus reduces or eliminates the risk of severe complications. The prevalence of diabetes has been rising rapidly worldwide. Several methods have been introduced to diagnose diabetes at an early stage, however, most of these methods lack interpretability, due to which the diagnostic process cannot be explained. In this paper, fuzzy logic has been employed to develop an interpretable model and to perform an early diagnosis of diabetes. Fuzzy logic has been combined with the cosine amplitude method, and two fuzzy classifiers have been constructed. Afterward, fuzzy rules have been designed based on these classifiers. Lastly, a publicly available diabetes dataset has been used to evaluate the performance of the proposed fuzzy rule-based model. The results show that the proposed model outperforms existing techniques by achieving an accuracy of 96.47%. The proposed model has demonstrated great prediction accuracy, suggesting that it can be utilized in the healthcare sector for the accurate diagnose of diabetes.

Studies on effects of umbelliferon derivatives against periodontal bacteria; antibiofilm, inhibition of quorum sensing and molecular docking analysis.

OBJECTIVE: Umbelliferon derivatives are exclusively found in plants of Ferula spp. that are commonly used in curing various health concerns related to oral cavity. Diabetic patient are especially effected with periodontitis and allied complications. METHOD: We investigated various compounds isolated from Ferula narthex exudate against clinical strains obtained from diabetic patients with periodontitis. Further antibiofilm, antiquorum sensing and molecular docking studies and ADMET analysis were performed. RESULTS: The docking target included 2Q0J, 2UV0, 3QP5 and 3QP1. HYDE affinity assessment was performed for the first 30 top ranking docked conformations within these active sites. The binding free energy ΔG, FlexX docking score and the most favorable poses for all the compounds were determined. During in vitro analysis, feselol presented high inhibition of Pseudomonas aeruginosa (MIC 0.01 mg/mL, MBC 0.02 mg/mL). Similarly, Feselol presented significant inhibition against clinical strain S. epidermidis (MIC 0.087 mg/mL, MBC 0.174 mg/mL) and S. aureus (MIC 0.087 mg/mL, MBC 0.087 mg/mL) preceded by 10'-R-acetyl-karatavacinol against S. epidermidis (MIC 0.56 mg/mL, MBC 0.56 mg/mL) and S. aureus (MIC 0.28 mg/mL, MBC 0.28 mg/mL). During antibiofilm inhibition assay, 10' R-acetyl-karatavacinol showed significant inhibition (54% at a final concentration 0.45 mg/mL), whereas slight antiquorum sensing activity was recorded. CONCLUSIONS: The umbelliferon derivatives have significant inhibition of clinical isolates and moderate antibiofilm potential.

Radiative MHD Nanofluid Flow over a Moving Thin Needle with Entropy Generation in a Porous Medium with Dust Particles and Hall Current.

This paper investigated the behavior of the two-dimensional magnetohydrodynamics (MHD) nanofluid flow of water-based suspended carbon nanotubes (CNTs) with entropy generation and nonlinear thermal radiation in a Darcy-Forchheimer porous medium over a moving horizontal thin needle. The study also incorporated the effects of Hall current, magnetohydrodynamics, and viscous dissipation on dust particles. The said flow model was described using high order partial differential equations. An appropriate set of transformations was used to reduce the order of these equations. The reduced system was then solved by using a MATLAB tool bvp4c. The results obtained were compared with the existing literature, and excellent harmony was achieved in this regard. The results were presented using graphs and tables with coherent discussion. It was comprehended that Hall current parameter intensified the velocity profiles for both CNTs. Furthermore, it was perceived that the Bejan number boosted for higher values of Darcy-Forchheimer number.