Relationship Between Core Compressive Strength and UPV Values for Different Core Slenderness of High Strength Concrete Beam

The compressive strength of core concrete is affected by many parameters and one of them is the strength of the concrete, which affects the strength of the core compressive strength. This is achieved by using correction factors present in several standards such as ASTM C 42/C 42M-04, but this standard was not considered for high and very high strength concrete (HSC). In this study, a beam of (1x 4x 0.2) m constructed with 100 MPa target strength for core samples. Four different core diameters (25-50-75-100) mm and for each diameter different core length-diameter ratios(λ=l/d) (2-1.75-1.5-1.0) were extracted from the beam for assessing the strength in both casting directions. The relationship between the strength of concrete with respect to reference samples and different cores size with different slenderness ratio, length to diameter (λ) were investigated. The Ultrasonic Pulse Velocity (UPV) was conducted for all samples and the relationship between UPV and strength of cores were determined. The results showed that the core strength was increased with the decrease of slenderness ratio. Core samples correction factors to predict the strength of standard cylinder for HSC beam are different from normal strength concrete (NSC) and they have ranged between 1.0 and 1.12 for beam. Relationship between core compressive strength and UPV values are established

Exploring the Efficacy of Deep Learning Techniques in Detecting and Diagnosing Alzheimer’s Disease: A Comparative Study

Transfer learning has become extremely popular in recent years for tackling issues from various sectors, including the analysis of medical images. Medical image analysis has transformed medical care in recent years, enabling physicians to identify diseases early and accelerate patient recovery. Alzheimer’s disease (AD) diagnosis has been greatly aided by imaging. AD is a degenerative neurological condition that slowly deprives patients of their memory and cognitive abilities. Computed tomography (CT) and brain magnetic resonance imaging (MRI) scans are used to detect dementia in AD patients. This research primarily aims to classify AD patients into multiple classes using ResNet50, VGG16, and DenseNet121 as transfer learning along with convolutional neural networks on a large dataset as compared to existing approaches as it improves classification accuracy. The methods employed utilize CT and brain MRI scans for AD patient classification, considering various stages of AD. The study demonstrates promising results in predicting AD phases with MRI, yet challenges persist, including processing large datasets and cognitive workload involved in interpreting scans. Addressing image quality variations is crucial, necessitating advancements in imaging technology and analysis techniques. The different stages of AD are early mental retardation, mild mental impairment, late mild cognitive impairment, and final AD stage. The novel approach gives results with an accuracy of 96.6% and significantly improved outcomes compared to existing models

Exploring the Potential of Convolutional Neural Networks in Classifying Alzheimer’s Stages with Multi-biomarker Approach

Multiple studies have attempted to use a single type of data to predict various stages of Alzheimer’s disease (AD). However, combining multiple data modalities can improve prediction accuracy. In this study, we utilized a combination of biomarkers, including magnetic resonance imaging (MRI), electronic health records, and cerebrospinal fluid (CSF), to classify subjects into three groups based on clinical tests—normal cognitive controls (CN), mild cognitive impairment (MCI), and AD. To determine the significant parameters, we employ a novel technique that utilizes sparse autoencoders to extract features from CSF, clinical data, and convolutional neural networks’ (CNN’s) MRI imaging data. Our results indicate that deep learning methods outperform traditional machine learning models such as decision trees, support vector machines, random forests and K-nearest neighbors. The proposed method significantly outperforms traditional models, achieving an accuracy of 0.87 for CN versus AD, a precision of 0.93 for CN, and a recall of 0.88 for AD on the external test set. The integration of various data modalities and the application of deep learning techniques enhance the prediction accuracy, demonstrating the potential for improved diagnostic tools in clinical settings

Biogenic Silver Nanoparticles Combined with L-Arginine Using Escherichia coli and their Antibacterial and Cytotoxic Activities via ROS Production against A-549 Cells

Background: Silver and its nanoparticles have gained attention owing to their unique physicochemical properties which contribute to their antimicrobial and anticancer properties. The primary focus of this study was the synthesis of silver nanoparticles (AgNPs) using the cell filtrate of Escherichia coli (E. coli) American Type Culture Collection (ATCC) 8739. Methods: Silver nanoparticles were synthesized using E. coli and coated with non-toxic, naturally occurring L-arginine. L-arginine-coated AgNPs (L-AgNPs) were tested for purity, elemental composition, morphology, topology, and stability. Subsequently, they were tested for their antibacterial, apoptotic, reactive oxygen species (ROS), and cytotoxic effects on A549 lung cancer cells using the 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Results: The study revealed the formation of well-defined nanoparticles with a spherical shape, falling within the size range of 8.8 nm to 44.6 nm. The L-AgNPs exhibited significant antibacterial characteristics, with the largest zone of inhibition observed against Salmonella spp. (18.7 ± 0.9 mm) and the smallest against Bacillus cereus (8.7 ± 0.9 mm). The half maximal inhibitory concentration (IC50) value of L-AgNPs against A549 lung cancer cells was 58.67 μg/mL, while against 3T3-L1 cells, it was measured as 98.03 μg/mL via MTT assay. L-AgNPs induced apoptosis, as confirmed by morphological alterations in the cells, membrane blebbing, and chromatin condensation. These nanoparticles also triggered the production of reactive oxygen species (ROS) due to cellular oxidative stress, as indicated by the increased levels of dichlorodihydrofluorescein (DCF). Conclusion: This research demonstrates the potential application of these L-AgNPs in the biotechnology and pharmaceutical industries for their antibacterial and anticancer properties

Anxiolytic, Antidepressant-Like Proprieties and Impact on the Memory of the Hydro-Ethanolic Extract of Origanum majorana L. on Mice

Marjoram (Origanum majorana L.) infusion has been used as folk medicine against depression and anxiety. However, no studies have been carried out yet to prove those activities scientifically. In this study, the anxiolytic, antidepressant-like effects, and memory impact of the hydro-ethanolic extracts of marjoram were evaluated in mice. The hydro-ethanolic extracts (250 and 500 mg/kg) were evaluated for their central nervous effect using six different behavioral tests such as light–dark box (LDB) and open field (OF) for anxiety, forced swim test (FST), and tail suspension test (TST) for depression, and object recognition test (ORT), Morris water maze (MWM) for the impact on memory. The experiments were realized on days 1, 7, 14, and 21 of treatments and compared with bromazepam for anxiety (1 mg/kg) and paroxetine for depression (11.5 mg/kg). The phytochemical screening was performed by HPLC, and the acute and sub-acute toxicities were performed following OCED guidelines (N°423 and 407) with biochemical parameters evaluation and histopathological analysis. Oral administration of marjoram hydro-ethanolic extract induced significant anxiolytic and antidepressant-like effects without memory impairment, increasing the exploration and time spent in the light area in the LDB test in a similar way to that of bromazepam. In the FST and TST, the extract was as effective as paroxetine (11.5 mg/kg, p.o.) in reducing immobility. The phytochemical screening showed the presence of ferulic acid, naringin, hydroxytyrosol, geraniol, and quercetin. This study approves the traditional use of this plant and encourages further investigation on its bioactive compounds

Anxiolytic, Antidepressant-Like Proprieties and Impact on the Memory of the Hydro-Ethanolic Extract of Origanum majorana L. on Mice

Marjoram (Origanum majorana L.) infusion has been used as folk medicine against depression and anxiety. However, no studies have been carried out yet to prove those activities scientifically. In this study, the anxiolytic, antidepressant-like effects, and memory impact of the hydro-ethanolic extracts of marjoram were evaluated in mice. The hydro-ethanolic extracts (250 and 500 mg/kg) were evaluated for their central nervous effect using six different behavioral tests such as light–dark box (LDB) and open field (OF) for anxiety, forced swim test (FST), and tail suspension test (TST) for depression, and object recognition test (ORT), Morris water maze (MWM) for the impact on memory. The experiments were realized on days 1, 7, 14, and 21 of treatments and compared with bromazepam for anxiety (1 mg/kg) and paroxetine for depression (11.5 mg/kg). The phytochemical screening was performed by HPLC, and the acute and sub-acute toxicities were performed following OCED guidelines (N°423 and 407) with biochemical parameters evaluation and histopathological analysis. Oral administration of marjoram hydro-ethanolic extract induced significant anxiolytic and antidepressant-like effects without memory impairment, increasing the exploration and time spent in the light area in the LDB test in a similar way to that of bromazepam. In the FST and TST, the extract was as effective as paroxetine (11.5 mg/kg, p.o.) in reducing immobility. The phytochemical screening showed the presence of ferulic acid, naringin, hydroxytyrosol, geraniol, and quercetin. This study approves the traditional use of this plant and encourages further investigation on its bioactive compounds

Structure-based virtual screening methods for the identification of novel phytochemical inhibitors targeting furin protease for the management of COVID-19

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, is a highly contagious respiratory disease with widespread societal impact. The symptoms range from cough, fever, and pneumonia to complications affecting various organs, including the heart, kidneys, and nervous system. Despite various ongoing efforts, no effective drug has been developed to stop the spread of the virus. Although various types of medications used to treat bacterial and viral diseases have previously been employed to treat COVID-19 patients, their side effects have also been observed. The way SARS-CoV-2 infects the human body is very specific, as its spike protein plays an important role. The S subunit of virus spike protein cleaved by human proteases, such as furin protein, is an initial and important step for its internalization into a human host. Keeping this context, we attempted to inhibit the furin using phytochemicals that could produce minimal side effects. For this, we screened 408 natural phytochemicals from various plants having antiviral properties, against furin protein, and molecular docking and dynamics simulations were performed. Based on the binding score, the top three compounds (robustaflavone, withanolide, and amentoflavone) were selected for further validation. MM/GBSA energy calculations revealed that withanolide has the lowest binding energy of −57.2 kcal/mol followed by robustaflavone and amentoflavone with a binding energy of −45.2 kcal/mol and −39.68 kcal/mol, respectively. Additionally, ADME analysis showed drug-like properties for these three lead compounds. Hence, these natural compounds robustaflavone, withanolide, and amentoflavone, may have therapeutic potential for the management of SARS-CoV-2 by targeting furin

Drug standardization through pharmacognostic approaches and estimation of anticancer potential of chamomile (Matricaria chamomilla L.) using prostate-cancer cell lines : an in-vitro study

Cancer is the major challenge across world and the adenocarcinoma of prostate malignancy is the second most prevalent male cancer. Various medicinal plants are used for the treatment and management of various cancers. Matricaria chamomilla L., is one of the extensively used Unani medicament for the treatment of various type of diseases. In the current study we evaluated most of the parameters prescribed for drug standardization using pharmacognostic approaches. The 2,2 Diphenyl-1-picryl hydrazyl (DPPH) method was utilized for the analysis of antioxidant activity in the flower extracts of M. chamomilla. Moreover, we analyzed the antioxidant and cytotoxic activity of M. chamomilla (Gul-e Babuna) through in-vitro method. DPPH (2,2-diphenyl-1-picryl-hydrazl-hydrate) method was utilized for the analysis of antioxidant activity in the flower extracts of M. chamomilla. CFU and wound healing assay were performed to determine the anti-cancer activity. The results demonstrated that various extracts of M. chamomilla fulfilled most of the parameters of drug standardization and contained good antioxidant and anticancer activities. The ethyl acetate showed higher anticancer activity followed by aqueous, hydroalcoholic, petroleum benzene and methanol by CFU method. Also, the wound healing assay demonstrated that ethyl acetate extract has more significant effect followed by methanol and petroleum benzene extract on prostate cancer cell line (C4-2). The current study concluded that the extract of M. chamomilla flowers could act as good source of natural anti-cancer compounds.CCRUM, New Delhi; Science and Engineering Research Board, Department of Science and Technology, Government of India; SERB research grant; Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia; South African Medical Research Council (SAMRC) and the National Research Foundation (NRF).https://www.jcancer.orgam2024Medical OncologySDG-03:Good heatlh and well-bein

Growth inhibitory effect of Leptospermum scoparium (manuka) chloroform extract on breast and liver cancer cell lines

Objective: Research has demonstrated that Leptospermum scoparium possesses various thera¬peutic benefits. This study set out to determine whether or not L. scoparium extracts had any effect on the ability of HepG2 and MCF-7 breast cancer cells to survive. Materials and Methods: The antiproliferative activity of L. scoparium extracts was explored using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide and lactate dehydrogenase assays. The most active fraction was selected to investigate its effects on apoptosis induction using flow cytometry and quantitative real-time polymerase chain reaction. The constituents of this fraction were characterized using GC-MS analysis. Results: Research demonstrated that the chloroform fraction of L. scoparium (LSCF) significantly impacted the HepG2 and MCF-7 cancer cell lines. Treatment with LSCF led to a notable rise in both early and late apoptotic cells. Furthermore, there was an upregulation in the mRNA levels of P53, Bax, and caspases, while the expression of Bcl-2 mRNA saw a decrease. The analysis of LSCF revealed the primary components to be cis-calamenene, beta-eudesmol, cyclododecane, and alpha-muurolene. Conclusion: The study showed the promising antiproliferative activity of L. scoparium, suggesting its potential application for cancer treatment. [J Adv Vet Anim Res 2024; 11(2.000): 237-246