The COVID-19 pandemic has caused unprecedented negative impacts in the modern era, including economic, social, and public health losses. On the other hand, the potential effects that the input of SARS-CoV-2 in the aquatic environment from sewage may represent on non-target organisms are not well known. In addition, it is not yet known whether the association of SARS-CoV-2 with other pollutants, such as microplastics (MPs), may further impact the aquatic biota. Thus, we aimed to evaluate the possible ecotoxicological effects of exposure of male adults Poecilia reticulata, for 15 days, to inactivated SARS-CoV-2 (0.742 pg/L; isolated SARS.CoV2/SP02.2020.HIAE.Br) and polyethylene MP (PE MPs) (7.1 × 104 particles/L), alone and in combination, from multiple biomarkers. Our data suggest that exposure to SARS-CoV-2 induced behavioral changes (in the open field test), nephrotoxic effect (inferred by the increase in creatinine), hepatotoxic effect (inferred by the increase in bilirubin production), imbalance in the homeostasis of Fe, Ca, and Mg, as well as an anticholinesterase effect in the animals [marked by the reduction of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) activity]. On the other hand, exposure to PE MPs induced a genotoxic effect (assessed by the comet assay), as well as an increase in enzyme activity alpha-amylase, alkaline phosphatase, and carboxylesterases. However, we did not show synergistic, antagonistic, or additive effects caused by the combined exposure of P. reticulata to SARS-CoV-2 and PE MPs. Principal component analysis (PCA) and values from the "Integrated Biomarker Response" index indicate that exposure to SARS-CoV-2 was determinant for a more prominent effect in the evaluated animals. Therefore, our study sheds light on the ecotoxicity of the new coronavirus in non-target organisms and ratifies the need for more attention to the impacts of COVID-19 on aquatic biota.
Tuberculosis (TB) remains a major global health burden. Antitubercular drugs (ATDs) such as isoniazid (INH), rifampicin (RIF), pyrazinamide (PZA), and ethambutol are used as first-line therapy in TB patients. Drug-induced liver injury is one of the common side effects that leads to the discontinuation of ATDs in TB patients. Therefore, this review discusses the molecular pathogenesis of ATDs induced liver injury. The biotransformation of INH, RIF, and PZA in the liver liberates several reactive intermediates, leading to peroxidation of the hepatocellular membrane and oxidative stress. INH + RIF administration decreased the expression of bile acid transporters such as the bile salt export pump and multidrug resistance-associated protein 2 and induced liver injury by sirtuin 1 and farnesoid X receptor pathway. INH inhibits the nuclear translocation of Nrf2 by interfering with its nuclear importer, karyopherin β1, thereby inducing apoptosis. INF + RIF treatments alter Bcl-2 and Bax homeostasis, mitochondrial membrane potential, and cytochrome c release, thereby triggering apoptosis. RIF administration enhances the expression of genes involved in fatty acid synthesis and hepatocyte fatty acid uptake (CD36). RIF induces the expression of peroxisome proliferator-activated receptor -γ and its downstream proteins and perilipin-2 by activating the pregnane X receptor in the liver to increase fatty infiltration into the liver. ATDs administration induces oxidative stress, inflammation, apoptosis, cholestasis, and lipid accumulation in the liver. However, ATDs toxic potentials are not elaborately studied at the molecular level in clinical samples. Therefore, future studies are warranted to explore ATDs induced liver injuries at the molecular level in clinical samples whenever possible.
Biomaterials are feasible resources that aids to replace damaged structures in our bodies. The most biologically active flora is Aloe vera which has many bioactive compounds that are anti-inflammatory, antimicrobial, and have ECM mimicking protein content which helps in the healing of wounds and also acts as an ECM factor for stem cell homing and differentiation. The Aloe vera containing 10 w / v of gelatin was lyophilized. Scaffolds had sharper morphology, greater hydrophilic properties, and a Young’s modulus of 6.28 MPa and 15.9 MPa of higher tensile strength are desirable. In tissue engineering and regenerative medicine, biologically active scaffolds have been producing hopeful outcomes in both restoration and replacement, respectively. The objective of the present investigation is to test the idea that incorporating gelatin to Aloe vera scaffolds might enhance their structure, good biocompatibility, and possibly even bioactivity. The SEM picture of the composite scaffold revealed pore walls. The scaffolds had linked pores with diameters ranging from 93 to 296 μm. Aloe vera and the matrix interact well, according to the FTIR study, which could lead to a reduction in the amount of water-binding sites and a reduction in the material’s ability to absorb water. Aloe vera with 10% gelatin (AV/G) scaffold was investigated for different biological reactions of human gingival tissue mesenchymal stem cells (MSCs) in terms of cell proliferation, morphology, and cell migration. The results demonstrated the potential of the AV/G scaffold as a biomaterial that offers new insight in the field of tissue engineering.
The creatine shuttle translocates the energy generated by oxidative phosphorylation to the cytoplasm via mitochondrial creatine kinase (MTCK) and creatine kinase B (CKB) in the cytoplasm. It is not apparent how the creatine shuttle is related to cancer. Here, we analyzed the expression and function of CKB and MTCK in colorectal cancer (CRC) and investigated the role of the creatine shuttle in CRC. Compared with normal mucosa, 184 CRC tissues had higher levels of CKB and MTCK, and these levels were associated with histological grade, tumor invasion, and distant metastasis. CK inhibitor dinitrofluorobenzene (DNFB) on CRC cell lines HT29 and CT26 inhibited cell proliferation and stemness to less than 2/3 and 1/20 of their control levels, respectively. In this treatment, the production of reactive oxygen species increased, mitochondrial respiration decreased, and mitochondrial volume and membrane potential decreased. In a syngeneic BALB/c mouse model using CT26 cells pretreated with DNFB, peritoneal metastasis was suppressed to 70%. Phosphorylation of EGFR, AKT, and ERK1/2 was inhibited in DNFB-treated tumors. High ATP concentrations prevented EGFR phosphorylation in HT29 cells following DNFB treatment, CKB or MTCK knockdown, and cyclocreatine administration. Despite not being immunoprecipitated, CKB and EGFR were brought closer together by EGF stimulation. These findings imply that blocking the creatine shuttle decreases the energy supply, suppresses oxidative phosphorylation, and blocks ATP delivery to phosphorylation signals, preventing signal transduction. These findings highlight the critical role of the creatine shuttle in cancer cells and suggest a potential new cancer treatment target.
This study investigates a fuzzy controller technique for autonomous robot navigation in both the static and dynamic environmental conditions and an excessive number of pathways to the destination. The design and implementation of a novel obstacle avoidance technique for autonomous robots are developed using the fuzzy controller-based multi-agent system. This method allows the Robot to identify dynamic or static unidentified objects while directing the Robot to prevent collisions and advance toward the objective. The Robot is capable of moving in a variety of environments. The Robot may communicate and travel in dynamic space by perceiving its surroundings and pursuing a free-collision route. This study covers creating a multi-agent system that includes fuzzy logic to regulate the robotic movements along a path reactive for effective Navigation. This project aims to develop an algorithm that allows the Robot to do distinct tasks to accomplish a unified objective, autonomous Navigation in a slightly unfamiliar environment. Under such a situation, the usage of a multi-agent system is advantageous. As a result, we created a framework made up of four agents responsible for sensing, Navigation, dynamic, and static obstacle avoidance. These agents communicate with one another via a coordinating mechanism.
The p-GaN layer adjacent to the quantum well is proposed for InGaN/GaN Light Emitting Diode (LED), it enhances the output optical power and internal quantum efficiency. The physical simulator Technology Computer-Aided Design (TCAD) is used to analyze the performance of the proposed LED. In the simulation, physics-based models are used to obtain optical properties such as luminous power and recombination rate. The suggested InGaN/GaN LED outperformed conventional LEDs in terms of internal quantum efficiency and luminous power. At the injection current of 700 mA, the output luminous power and internal quantum efficiency in the proposed LED are improved by 24% and 18%, respectively. Furthermore, the suggested InGaN/GaN LED has a smaller Auger recombination than conventional LEDs. Thus, the proposed p-GaN layer technique in GaN LED is a promising one for future solid-state lighting applications due to its high internal quantum efficiency of 90% at 100 mA injection current.
Fig leaf, an environmentally friendly byproduct of fruit plants, has been used for the first time to treat of methylene blue dye. The fig leaf-activated carbon (FLAC-3) was prepared successfully and used for the adsorption of methylene blue dye (MB). The adsorbent was characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and the Brunauer–Emmett–Teller (BET). In the present study, initial concentrations, contact time, temperatures, pH solution, FLAC-3 dose, volume solution, and activation agent were investigated. However, the initial concentration of MB was investigated at different concentrations of 20, 40, 80, 120, and 200 mg/L. pH solution was examined at these values: pH3, pH7, pH8, and pH11. Moreover, adsorption temperatures of 20, 30, 40, and 50 °C were considered to investigate how the FLAC-3 works on MB dye removal. The adsorption capacity of FLAC-3 was determined to be 24.75 mg/g for 0.08 g and 41 mg/g for 0.02 g. The adsorption process has followed the Langmuir isotherm model (R² = 0.9841), where the adsorption created a monolayer covering the surface of the adsorbent. Additionally, it was discovered that the maximum adsorption capacity (Qm) was 41.7 mg/g and the Langmuir affinity constant (KL) was 0.37 L/mg. The FLAC-3, as low-cost adsorbents for methylene blue dye, has shown good cationic dye adsorption performance. Graphical Abstract
Some of the most significant computational ideas in neuroscience for learning behavior in response to reward and penalty are reinforcement learning algorithms. This technique can be used to train an artificial intelligent (AI) agent to serve as a virtual assistant and a helper. The goal of this study is to determine whether combining a reinforcement learning-based Virtual AI assistant with play therapy. It can benefit wheelchair-bound youngsters with Down syndrome. This study aims to employ play therapy methods and Reinforcement Learning (RL) agents to aid children with Down syndrome and help them enhance their abilities like physical and mental skills by playing games with them. This Agent is designed to be smart enough to analyze each patient's lack of ability and provide a specific set of challenges in the game to improve that ability. Increasing the game's difficulty can help players develop these skills. The agent should be able to assess each player's skill gap and tailor the game to them accordingly. The agent's job is not to make the patient victorious but to boost their morale and skill sets in areas like physical activities, intelligence, and social interaction. The primary objective is to improve the player's physical activities such as muscle reflexes, motor controls and hand-eye coordination. Here, the study concentrates on the employment of several distinct techniques for training various models. This research focuses on comparing the reinforcement learning algorithms like the Deep Q-Learning Network, QR-DQN, A3C and PPO-Actor Critic. This study demonstrates that when compared to other reinforcement algorithms, the performance of the AI helper agent is at its highest when it is trained with PPO-Actor Critic and A3C. The goal is to see if children with Down syndrome who are wheelchair-bound can benefit by combining reinforcement learning with play therapy to increase their mobility.
Building cracks spoil the aesthetic view of the structure along with degrading the strength of the structure. It leads to the failure of the structure as a whole. Propagation of cracks in the concrete surface increases the chance of permeability due to moisture content in the atmosphere which might corrode the internal reinforcements. To overcome this situation, a solution in the form of fibre-reinforced self-healing concrete was suggested in this research work. Steel fibre was added by varying 0%,1%,2%,3%,4% and 5% interms of volume of concrete to prolong fatigue life and decrease the crack width under fatigue loading. Bacteria (Bacillus subtilis) are used to heal the cracks by producing calcium carbonate (CaCO3) as a result. Bacterial concrete with fibre (BCF) was cast by M30 mix as per Indian Standard Code. Studied concrete's mechanical and microstructural properties like compression strength test, flexural strength test, split tensile strength test, SEM images, EDS, XRD and FTIR methods. From microstructural studies, it is clear that there is sufficient self-healing material in broken concrete, hence the efficiency of BCF's self-healing property is commendable and the ability of the generated BCF concrete to regain strength.
Focusing on natural fibers are the prominent substitution for synthetic fiber and reinforced into polymer matrices found unique properties such as lightweight, cost-effectiveness, and good mechanical and wear properties. Incompatibility and low adhesive behavior are the primary drawbacks found during the fabrication of natural fiber-bonded polymer matrix composites. The constant weight percentage (10 wt%) of sisal and hemp fiber is treated with a 5% NaOH solution for improving adhesive behavior and bonded with epoxy. The prepared sisal/hemp/epoxy combination is blended with 0 wt%, 3 wt%, 6 wt%, and 9 wt% silica nanoparticles, which results in reduced voids (1.32%) and increased flexural strength (56.98 MPa). Based on the compositions of fiber and reinforcement, the density of the composite varied. Samples 3-6 wt% of silica nanoparticle-blend sisal/hemp/epoxy composite offered maximum tensile and impact strength of 52.16 MPa and 2.1 J. An optical microscope analyzed the tensile fracture surface, and the failure nature was reported. The dry sliding wear performance of composite samples is tested by pin-on-disc setup with a 10 N-40 N load of 10 N interval at 0.75 m/sec. Sample 3 found good wear resistance compared to others.
The range of diagnostic equipment has been widened and improved by the quick development of biomedical research technologies. The creation of multifunctional instruments that become essential for biomedical operations has been discovered by several research organizations to be made possible by optical imaging, acoustic image analysis, and magnetic resonance imaging. One of the most crucial tools is hyperspectral photoacoustic (PA) imaging, which combines optical and ultrasonic technology. In this study, the reconstruction of the PA pictures employs a new deployment of deep learning methods. This enabled us to train and evaluate our deep-learning approach under several imaging situations in addition to firmly establishing the contextual information. This study presents an optimization approach that blends multispectral optical acoustic imaging with detailed transfer learning-based diagnostic imaging. The particle swarm-convolutional neural network (PS-CNN) technique aims to reconstruct and categorize the presence of cancer using ultrasonic pictures. In image processing, the technique of bilateral filtration (BF) is commonly employed to remove noise. Additionally, the biological images are separated using portable LED Net frameworks. It is also possible to employ a feature extraction technique with the PS optimization methodology. Last but not least, biological images employ a CNN model to assign suitable classification. Using a standard dataset, the PS-CNN technology’s efficacy is confirmed, and testing findings revealed that it performs superior to other methods.
The transition metal oxide-based nanomaterial attracted researchers for its various applications due to its interesting physical, chemical, and optical properties. Copper oxide thin films with different oxidation states were prepared on various transparent, nontransparent nature conducting substrates from the acidic and alkaline medium by electrodeposition technique. The deposition parameters such as potential, bath temperature, solution pH, and deposition time determine the physical, chemical, and optical properties. The complexing agents such as sodium thiosulfate, lactic acid, citric acid, and triethanolamine determine the stability of cuprous and cupric ions in the deposited films. Optical properties reported that the deposited films have direct band gap value 1.3 and 3.7 eV represents the absorbance of the deposited films in the visible region of solar spectrum. The absorbance of light in visible region, good electrical conductivity, and various nanostructure morphologies with the environment-friendly constituents are the distinctive properties of copper metal oxides.
The primary goal of this paper is to design a Multi-Converter Unified Power Quality Conditioner (MC-UPQC). The proposed method is solved based on the Synchronous Reference Frame (SRF) theory. The MC-UPQC involves two series Voltage Source Converters (VSCs) for power transfer between feeders to eliminate voltage sag, swell, interruption, and transient response in the system. The proposed model adopts control strategies based on an optimized Fuzzy Logic Controller (FLC) in SRF, utilizing a hybrid metaheuristic algorithm called Beetle Swarm-based Butterfly Optimization Algorithm (BS-BOA), which combines Beetle Swarm Optimization (BSO) and Butterfly Optimization Algorithm (BOA) for membership limit optimization and control rule generation. The major benefit of the optimized FLC-based MC-UPQC is its quick behavior in minimizing Total Harmonic Distortion (THD) in source and load side voltages and currents. Simulation and MATLAB environment are used for the entire system implementation. The comparative analysis of the proposed controller for MC-UPQC is performed against conventional controllers to validate its effectiveness. Quantitative data related to the main research outcomes, such as THD of source voltage and current, and dynamic behavior of the system, are included. The main benefit of the study is the significant reduction in THD and improved dynamic performance of the system.
In vehicular networks, several automation protocols are invented in artificial intelligence-based systematic processes. But best of our knowledge, none of the methods discussed effective sound detection systems and sound transducers based on real-time scenarios. In this research, an effective sound detection system and sound transducer for an intelligent sound adjustment system in commercial car vehicles using proposed sound prototyping development are developed to create an impact of a sound detection system. This Intelligent sound adjustment system enables six models for vehicle wearable sensor systems with Value Line MSP430 LaunchPad™ Development Kit. This model reduces and maintains a balanced sound system inside the car based on unique circumstances such as Acoustic source localization, Microphone with Super cardioid, and Mass comparison. This Proposed Analysis of an Intelligent sound adjustment system in commercial car vehicles works based on Value Line MSP430 LaunchPad™ Development Kit connected with "Acoustic source localization," "Microphone with Super cardioid" for creating a vehicle wearable sensor system. This system can find a nearby vehicle, especially an ambulance, and the siren sound of an ambulance. However, sensors are car wearable devices for accessing ambulance sound and predicting exclusive sound patterns of an ambulance by comparing and predicting sound from a real-time sound to a sound database. Proposed connected development kit to sound system used to control sound. According to experimental findings, an effective sound detection system in commercial car vehicles using proposed sound prototyping achieves a recognition accuracy equivalent to that of edge Value Line MSP430 LaunchPad™ Development systems already in use while significantly decreasing data traffic by 93.5 and computational delay by 92%. Findings indicate that Intelligent sound adjustment system fault detection accuracy ranges from 99.82 percent on average to 97.92 percent at its peak. Compared to traditional federated learning, a microphone with super-cardioid considerably reduces energy usage by 68.5 with a minimum accuracy loss of up to 97.3%. Acoustic source localization is built and utilized to find sound faults at the end. This technique offers a fresh concept for arc sound detection systems and performs well.
Asiatic acid (AA) is a natural aglycone of pentacyclic triterpenoids and is abundantly present in many edible and medicinal plants, including Centella Asiatica, which is a reputed herb for wound healing and neuropsychiatric disorders in many traditional medicine formulations. Asiatic acid has various pharmacological functions such as antioxidant and anti-inflammatory and controls apoptosis, which in numerous diseases credits to its medicinal impact. In preclinical trials, asiatic acid demonstrated potent antihypertensive, neuroprotective, cardioprotective, antidiabetic, antimicrobial, and antitumor behaviors. It has been shown to influence multiple enzymes, receptors, growth factors, transcription factors, apoptotic proteins, and cell signaling cascades in several in vitro and in vivo experiments. This review aims to reflect the current therapeutic potential reports and the underlying pharmacological and molecular mechanisms of asiatic acid. In various diseases, studies display Asiatic acid’s polypharmacological properties, therapeutic ability, and molecular pathways. With the available research data, asiatic acid appears to be a significant multi-targeted, natural-origin polypharmacological agent for further pharmaceutical production and clinical use. Provided advantageous pharmacokinetics, protection, and effectiveness, along with commonly used modern drugs. Asiatic acid may be a potential agent or adjuvant, with a pharmacological justification for its usage in therapeutics.
This paper deals with the study of the reaction–diffusion epidemic model perturbed with time noise. It has various applications such as disease in population models of humans, wildlife, and many others. The stochastic SIR model is numerically investigated with the proposed stochastic backward Euler scheme and proposed stochastic implicit finite difference (IFD) scheme. The stability of the proposed methods is shown with Von Neumann criteria and both schemes are unconditionally stable. Both schemes are consistent with systems of the equations in the mean square sense. The numerical solution obtained by the proposed stochastic backward Euler scheme and solutions converges towards an equilibrium but it has negative and divergent behavior for some values. The numerical solution gained by the proposed IFD scheme preserves the positivity and also solutions converge towards endemic and disease-free equilibrium. We have used two problems to check our findings. The graphical behavior of the stochastic SIR model is much adjacent to the classical SIR epidemic model when noise strength approaches zero. The three-dimensional plots of the susceptible and infected individuals are drawn for two cases of endemic equilibrium and disease-free equilibriums. The results show the efficacy of the proposed stochastic IFD scheme.
The entire human race is struggling with the spread of COVID-19. Worldwide, the wearing of face masks is indispensable to prevent such spread. Despite numerous studies reporting on the fabrication of face masks and surgical masks to reduce spread and thus human deaths, this novel work is considered the marine waste of microplastics, namely Polypropylene (PP) polymer, used to fabricate non-woven fabric masks through the melt-blown process. This experimental work aims to maximize the mask's quality and minimize its fabrication cost by optimizing the melt-blown process parameters and using microplastics. The melt-blown process was used to make masks. Parameters such as extruder temperature, hot air temperature, melt flow rate, and die-to-collector distance (DCD) were investigated as independent variables. The quality of the mask was investigated in terms of bacterial filtration efficiency (BFE), particle filtration efficiency (PFE), and differential pressure. The Taguchi L16 orthogonal array and Taguchi analysis were employed for experimental design and statistical optimization, respectively. The results reveal that the higher BFE and PFE are recorded at 96.7 % and 98.6 %, respectively. The surface morphological investigation on different layers ensured the fine and uniform porosity of the layers and exhibited minimum breath resistance (a low differential pressure of 0.00152 kPa/cm2). Hence the chemically treated marine waste microplastics improved the masks' performance.
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Saveetha Nagar, Thandalam, 602105, Chennai, Tamilnadu, India
Head of institution
Dr. E.N Ganesh