Survivability and behavior of probiotic bacteria encapsulated by internal gelation in non-dairy matrix and In Vitro GIT conditions.

The primary objective of this investigation was to assess the viability of free and encapsulated Lactobacillus plantarum probiotics in mango juice and under simulated gastrointestinal conditions. Specifically, the probiotics were encapsulated using sodium alginate and alginate-soy protein isolate through the internal gelation method, and the obtained probiotics were characterized for various attributes. Both free and encapsulated probiotics were exposed to challenging conditions, including thermal stress, low temperature, and simulated gastrointestinal conditions. Additionally, both types of probiotics were incorporated into mango juice, and their survival was monitored over a 28-day storage period. Following viability under simulated gastrointestinal conditions, the count of free and encapsulated probiotic cells decreased from initial levels of 9.57 log CFU/mL, 9.55 log CFU/mL, and 9.53 log CFU/mL, 9.56 log CFU/mL to final levels of 6.14 log CFU/mL, 8.31 log CFU/mL, and 6.24 log CFU/mL, 8.62 log CFU/mL, respectively. Notably, encapsulated probiotics exhibited a decrease of 1.24 log CFU and 0.94 log CFU, while free cells experienced a reduction of 3.43 log CFU and 6.24 log CFU in mango juice over the storage period. Encapsulated probiotics demonstrated higher viability in mango juice compared to free probiotics throughout the 28-day storage period. These findings suggest that mango juice can be enriched with probiotics to create a health-promoting beverage.

Characterization of carbonated beverage fortified with chamomile herbal extract.

The current study was planned to provide nutrient dense carbonated beverage fortified with chamomile herbal extract that was rich in healthy nutrients and best to use. Infusion method was used to prepare chamomile herbal extract. After adding flavor and sugar syrup, carbonation was done. Different treatments were prepared (T0, T1, T2, T3, T4, and T5). The antioxidant potential, physiochemical properties, and sensory attributes of beverage were assessed. Results showed that addition of chamomile enhanced the antioxidant and physiochemical properties of beverage. The DPPH activity, total phenolic content, and total flavonoid content were observed as 49.23 ± 0.03 (%), 136.92 ± 0.06 (mg GAE/L), and 1989.47 ± 0.07 (mg QE/L), respectively, among T5 with 12% of chamomile extract. Moreover, the acidity increases from T0 to T5 (0.191 ± 0.01 to 0.220 ± 0.01). Furthermore, the overall acceptability of T4 was highest among sensory attributes.

BAU-Insectv2: An agricultural plant insect dataset for deep learning and biomedical image analysis.

"BAU-Insectv2" represents a novel agricultural dataset tailored for deep learning applications and biomedical image analysis focused on plant-insect interactions. This dataset encompasses a diverse collection of high-resolution images capturing intricate details of plant-insect interactions across various agricultural settings. Leveraging deep learning methodologies, this study aims to employ convolutional neural networks (CNN) and advanced image analysis techniques for precise insect detection, classification, and understanding of insect-related patterns within agricultural ecosystems. We mainly focus on addressing insect-related issues in South Asian crop cultivation. The dataset's extensive scope and high-quality imagery provide a robust foundation for developing and validating models capable of accurately identifying and analyzing diverse plant insects. The dataset's utility extends to biomedical image analysis, fostering interdisciplinary research avenues across agriculture and biomedical sciences. This dataset holds significant promise for advancing research in agricultural pest management, ecosystem dynamics, and biomedical image analysis techniques.

Exploring the serotonin-probiotics-gut health axis: A review of current evidence and potential mechanisms.

Modulatory effects of serotonin (5-Hydroxytryptamine [5-HT]) have been seen in hepatic, neurological/psychiatric, and gastrointestinal (GI) disorders. Probiotics are live microorganisms that confer health benefits to their host. Recent research has suggested that probiotics can promote serotonin signaling, a crucial pathway in the regulation of mood, cognition, and other physiological processes. Reviewing the literature, we find that peripheral serotonin increases nutrient uptake and storage, regulates the composition of the gut microbiota, and is involved in mediating neuronal disorders. This review explores the mechanisms underlying the probiotic-mediated increase in serotonin signaling, highlighting the role of gut microbiota in the regulation of serotonin production and the modulation of neurotransmitter receptors. Additionally, this review discusses the potential clinical implications of probiotics as a therapeutic strategy for disorders associated with altered serotonin signaling, such as GI and neurological disorders. Overall, this review demonstrates the potential of probiotics as a promising avenue for the treatment of serotonin-related disorders and signaling of serotonin.

Copper nitroprusside: An innovative approach for targeted cancer therapy via ROS modulation.

The clinical application of nanomaterials for chemodynamic therapy (CDT), which generate multiple reactive oxygen species (ROS), presents significant challenges. These challenges arise due to insufficient levels of endogenous hydrogen peroxide and catalytic ions necessary to initiate Fenton reactions. As a result, sophisticated additional delivery systems are required. In this study, a novel bimetallic copper (II) pentacyanonitrosylferrate (Cu(II)NP, Cu[Fe(CN) 5 NO]) material was developed to address these limitations. This material functions as a multiple ROS generator at tumoral sites by self-inducing hydrogen peroxide and producing peroxynitrite (ONOO-) species. The research findings demonstrate that this material exhibits low toxicity towards normal liver organoids, yet shows potent antitumoral effects on High Grade Serous Ovarian Cancer (HGSOC) organoid patients, regardless of platinum resistance. Significantly, this research introduces a promising therapeutic opportunity by proposing a single system capable of replacing the need for H2O2, additional catalysts, and NO-based delivery systems. This innovative system exhibits remarkable multiple therapeutic mechanisms, paving the way for potential advancements in clinical treatments.

Biological activities, therapeutic potential, and pharmacological aspects of blackcurrants (Ribes nigrum L): A comprehensive review.

Blackcurrant possesses various health-endorsing attributes owing to its polyphenol profile. Recent studies have demonstrated its therapeutic potential against various health disorders. Various bioactives present in blackcurrants have different functional and pharmacological aspects including anti-inflammatory, antioxidant, and antimicrobial properties. The most dominant and important bioactive include anthocyanins, flavonols, phenolic acids, and polyunsaturated fatty acids. Food formats derived from blackcurrants comprise pomace, juice, powder, and extracts. All these food formats have industrial, prebiotic, and pharmacological benefits. In the current article, the nutritional composition, industrial applications, and therapeutic potential are discussed in the recent literature. Moreover, novel extraction techniques for the extraction of bioactive compounds present in blackcurrants and their safety concerns have been elaborated.

Characterization and valorization of soybean residue (okara) for the development of synbiotic ice cream.

There is an increasing challenge in probiotic viability and stability during food product formulation, processing, and storage. However, synbiotic functional foods have promising potential to deliver the targeted benefits. This study aimed to isolate the okara from soybean residue, and obtained okara flour was further characterized using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM). Synbiotic ice cream was developed by fortification with Lactobacillus rhamnosus GG and okara at different concentrations (1-3%). Additionally, the synbiotic ice cream was subjected to physicochemical and sensory attributes over 60 days of storage. High viability of L. rhamnosus GG (8.17 log CFU/mL) was observed during storage at 3% okara. Moreover, adding okara at 2% or higher improved viscosity, reduced overrun, and maintained probiotic viability. When compared to the control (ice cream without okara), synbiotic ice cream exhibited a higher protein content and a lower fat level. The synergistic combination of probiotics and okara in ice cream is a potentially novel approach for developing functional ice cream. The addition of okara is not only helpful in increasing the nutritional value of the ice cream but will also be a way forward to minimize agricultural waste. Synbiotic ice cream developed in this study may be considered a potential functional food rich in protein and low in fat.

A Federated Learning Model Based on Hardware Acceleration for the Early Detection of Alzheimer's Disease.

Alzheimer's disease (AD) is a progressive illness with a slow start that lasts many years; the disease's consequences are devastating to the patient and the patient's family. If detected early, the disease's impact and prognosis can be altered significantly. Blood biosamples are often employed in simple medical testing since they are cost-effective and easy to collect and analyze. This research provides a diagnostic model for Alzheimer's disease based on federated learning (FL) and hardware acceleration using blood biosamples. We used blood biosample datasets provided by the ADNI website to compare and evaluate the performance of our models. FL has been used to train a shared model without sharing local devices' raw data with a central server to preserve privacy. We developed a hardware acceleration approach for building our FL model so that we could speed up the training and testing procedures. The VHDL hardware description language and an Altera 10 GX FPGA are utilized to construct the hardware-accelerator approach. The results of the simulations reveal that the proposed methods achieve accuracy and sensitivity for early detection of 89% and 87%, respectively, while simultaneously requiring less time to train than other algorithms considered to be state-of-the-art. The proposed algorithms have a power consumption ranging from 35 to 39 mW, which qualifies them for use in limited devices. Furthermore, the result shows that the proposed method has a lower inference latency (61 ms) than the existing methods with fewer resources.

Loading of zinc and iron in grains of different wheat genotypes in the calcareous and floodplain soils of Bangladesh.

Major malnutrition in Bangladesh is zinc (Zn) and iron (Fe) deficiency as most people commonly depend on cereals, chiefly rice and wheat. The main objectives are to enhance Zn and Fe concentrations through the use of selected varieties and the application of respective fertilizers. Field experiments were conducted at Bangladesh Agricultural University (BAU) farm, Mymensingh (AEZ 9, non-calcareous soil) and at Bangladesh Institute of Nuclear Agriculture (BINA) substation, Ishwardi (AEZ 11, calcareous soil) for two consecutive wheat seasons (2014-15 and 2015-16) with 10 varieties and 15 advanced lines. Varieties BARI Gom 25, 27, 28 & 29 and breeding lines Vijay, HPYT-5, 15 & 21 and BL-1883 have been recognized as Zn-enriched wheat varieties (24-30 µg g-1). Among the genotypes, Zn further increased by 4-8 µg g-1 due to Zn fertilization. Concerning Fe-enriched wheat genotypes (24-30 µg g-1), five varieties viz. Shatabdi, Prodip, BARI Gom 25 & 28 and Sufi, and four lines such as HPYT-12, BL-1883, BL-1040 and Fery-60 have been identified. The grain Fe concentration of wheat genotypes increased when Fe was added, the increment being 6-12 µg g-1. A positive relationship between Zn and N is observed with increased protein content. The grain yield of wheat was increased by 3.8-25.7% due to Zn application over the varieties and locations but Fe addition had no effect. The result of the current study showed that a potential breeding line with appropriate fertilization can improve Zn and Fe levels in wheat grain, without incurring loss to wheat yield.

Probing the functional and therapeutic properties of postbiotics in relation to their industrial application.

Functional foods are gaining significant research attention of researchers due to their health-endorsing properties due to their bioactive components either living cells (probiotics) or nonviable cells (prebiotics). The term "postbiotic" specifies the soluble substances, such as enzymes, peptides, teichoic acids, muropeptides derived from peptidoglycans, polysaccharides, cell surface proteins, and organic acids, that are secreted by living bacteria or released after bacterial lysis. Due to various signaling molecules which may have antioxidant, immunomodulatory, antiinflammatory, antihypertensive, and antiproliferative activities, postbiotics offer great potential to be used in pharmaceutical, food, and nutraceutical industries, to promote health and ailment prevention. This recent review is a landmark of information relevant to the production of postbiotics along with salient features to use in various fields ranging from food to immunomodulation and selective and effective therapy. It also puts forward the concept that postbiotics are way more effective than probiotics in the veterinary, food as well as medical field which ultimately helps in reducing the disease burden along with human health.

Detection of Cardiovascular Disease from Clinical Parameters Using a One-Dimensional Convolutional Neural Network.

Heart disease is a significant public health problem, and early detection is crucial for effective treatment and management. Conventional and noninvasive techniques are cumbersome, time-consuming, inconvenient, expensive, and unsuitable for frequent measurement or diagnosis. With the advance of artificial intelligence (AI), new invasive techniques emerging in research are detecting heart conditions using machine learning (ML) and deep learning (DL). Machine learning models have been used with the publicly available dataset from the internet about heart health; in contrast, deep learning techniques have recently been applied to analyze electrocardiograms (ECG) or similar vital data to detect heart diseases. Significant limitations of these datasets are their small size regarding the number of patients and features and the fact that many are imbalanced datasets. Furthermore, the trained models must be more reliable and accurate in medical settings. This study proposes a hybrid one-dimensional convolutional neural network (1D CNN), which uses a large dataset accumulated from online survey data and selected features using feature selection algorithms. The 1D CNN proved to show better accuracy compared to contemporary machine learning algorithms and artificial neural networks. The non-coronary heart disease (no-CHD) and CHD validation data showed an accuracy of 80.1% and 76.9%, respectively. The model was compared with an artificial neural network, random forest, AdaBoost, and a support vector machine. Overall, 1D CNN proved to show better performance in terms of accuracy, false negative rates, and false positive rates. Similar strategies were applied for four more heart conditions, and the analysis proved that using the hybrid 1D CNN produced better accuracy.

Mechanical Properties of Protein-Based Food Packaging Materials.

The quality and safety of food products greatly depend on the physiochemical properties of the food packaging material. There is an increasing trend in the utilization of protein-based biopolymers for the preparation of edible films and coating due to their film-forming properties. Various studies have reported the preparation of protein-based edible films with desirable mechanical and barrier properties. The mechanical attributes of the protein-based food packaging materials can be enhanced by incorporating various components in the film composition such as plasticizers, surfactants, crosslinkers, and various bioactive compounds, including antimicrobial and antioxidant compounds. This review article summarizes the recent updates and perspective on the mechanical attributes such as Tensile Strength (TS), Elongation at Break (EAB), and Young's Modulus (YM) of edible films based on different proteins from plants and animal sources. Moreover, the effects of composite materials such as other biopolymers, bioactive compounds, essential oils, and plasticizers on the mechanical properties of protein-based edible films are also discussed.

RhoA rescues cardiac senescence by regulating Parkin-mediated mitophagy.

Heart failure is one of the leading causes of death worldwide. RhoA, a small GTPase, governs actin dynamics in various tissue and cell types, including cardiomyocytes; however, its involvement in cardiac function has not been fully elucidated. Here, we generated cardiomyocyte-specific RhoA conditional knockout (cKO) mice, which demonstrated a significantly shorter lifespan with left ventricular dilation and severely impaired ejection fraction. We found that the cardiac tissues of the cKO mice exhibited structural disorganization with fibrosis and also exhibited enhanced senescence compared with control mice. In addition, we show that cardiomyocyte mitochondria were structurally abnormal in the aged cKO hearts. Clearance of damaged mitochondria by mitophagy was remarkably inhibited in both cKO cardiomyocytes and RhoA-knockdown HL-1 cultured cardiomyocytes. In RhoA-depleted cardiomyocytes, we reveal that the expression of Parkin, an E3 ubiquitin ligase that plays a crucial role in mitophagy, was reduced, and expression of N-Myc, a negative regulator of Parkin, was increased. We further reveal that the RhoA-Rho kinase axis induced N-Myc phosphorylation, which led to N-Myc degradation and Parkin upregulation. Re-expression of Parkin in RhoA-depleted cardiomyocytes restored mitophagy, reduced mitochondrial damage, attenuated cardiomyocyte senescence, and rescued cardiac function both in vitro and in vivo. Finally, we found that patients with idiopathic dilated cardiomyopathy without causal mutations for dilated cardiomyopathy showed reduced cardiac expression of RhoA and Parkin. These results suggest that RhoA promotes Parkin-mediated mitophagy as an indispensable mechanism contributing to cardioprotection in the aging heart.

Vascular smooth muscle RhoA counteracts abdominal aortic aneurysm formation by modulating MAP4K4 activity.

Whether a small GTPase RhoA plays a role in the pathology of abdominal aortic aneurysm (AAA) has not been determined. We show here that RhoA expression is reduced in human AAA lesions, compared with normal areas. Furthermore, incidence of AAA formation is increased in vascular smooth muscle cell (VSMC)-specific RhoA conditional knockout (cKO) mice. The contractility of the aortic rings and VSMCs from RhoA cKO mice is reduced, and expression of genes related to the VSMC contractility is attenuated by loss of RhoA. RhoA depletion activates the mitogen-activated protein (MAP) kinase signaling, including MAP4K4, in the aorta and VSMCs. Inhibition of MAP4K4 activity by DMX-5804 decreases AAA formation. Set, a binding protein to active RhoA, functions as an activator of MAP4K4 by sequestering PP2A, an inhibitor of MAP4K4, in the absence of RhoA. In conclusion, RhoA counteracts AAA formation through inhibition of MAP4K4 in cooperation with Set.

Evaluation of safety and anti-obesity effects of DWP16001 in naturally obese dogs.

BACKGROUND: The aim of this study was to investigate the anti-obesity effects of DWP16001, a sodium-glucose cotransporter-2 (SGLT2 inhibitor), in naturally obese dogs. A total of 20 dogs were divided into four equal groups: one obese control (OC group), and three treated groups; DWP0.2 group, DWP0.5 group, and DWP1 group. OC group fed with food for maintenance and treated groups were fed with food for maintenance with 0.2 mg/kg DWP16001, 0.5 mg/kg DWP16001 and 1 mg/kg DWP16001, respectively. The food for maintenance was provided to dogs as 2 RER (Resting energy requirement) in kcal and DWP16001-supplemented food was administered once a day for 8 weeks. RESULTS: Body condition score, body weight, and fat thickness were significantly reduced (P < 0.05) in the DWP0.2 group compared with the OC group, respectively without affecting the food consumption. At the 10th week the food consumption rate was 101.35 ± 2.56, 166.59 ± 4.72, 98.47 ± 1.44 and 123.15 ± 2.45% compared with initial food consumption rate. Body fat percentage, chest and waist circumference, blood glucose, and insulin were reduced compared to OC group but not significantly different from those of the OC group during experimental period. Serum alanine aminotransferase, alkaline phosphatase, creatine phosphokinase, and creatinine were significantly reduced in DWP0.2 group on 8 weeks. Serum cholesterol and triglycerides were reduced but not significantly. No specific adverse effects were observed throughout the experiment, and hematological parameters were unchanged. The results indicate that DWP16001 was not harmful to the dogs in our study and might have anti-obesity effects in naturally obese dogs. CONCLUSIONS: The above results and discussion suggest that DWP16001 is safe and might have anti-obesity effects in naturally obese dogs.

Cuffless Blood Pressure Measurement Using Linear and Nonlinear Optimized Feature Selection.

The cuffless blood pressure (BP) measurement allows for frequent measurement without discomfort to the patient compared to the cuff inflation measurement. With the availability of a large dataset containing physiological waveforms, now it is possible to use them through different learning algorithms to produce a relationship with changes in BP. In this paper, a novel cuffless noninvasive blood pressure measurement technique has been proposed using optimized features from electrocardiogram and photoplethysmography based on multivariate symmetric uncertainty (MSU). The technique is an improvement over other contemporary methods due to the inclusion of feature optimization depending on both linear and nonlinear relationships with the change of blood pressure. MSU has been used as a selection criterion with algorithms such as the fast correlation and ReliefF algorithms followed by the penalty-based regression technique to make sure the features have maximum relevance as well as minimum redundancy. The result from the technique was compared with the performance of similar techniques using the MIMIC-II dataset. After training and testing, the root mean square error (RMSE) comes as 5.28 mmHg for systolic BP and 5.98 mmHg for diastolic BP. In addition, in terms of mean absolute error, the result improved to 4.27 mmHg for SBP and 5.01 for DBP compared to recent cuffless BP measurement techniques which have used substantially large datasets and feature optimization. According to the British Hypertension Society Standard (BHS), our proposed technique achieved at least grade B in all cumulative criteria for cuffless BP measurement.

Asymptomatic RT-PCR positive COVID-19 patients in orthopaedic pre-operative evaluation during the peak of the second wave.

Introduction: Asymptomatic COVID-19 patients are the most challenging and feared obstacles in resuming these surgical procedures. The purpose of this study was to evaluate the proportion of asymptomatic carriers detected by RT-PCR in pre-operative orthopaedic evaluation during the peak of the second wave. Methods: 514 asymptomtomatic COVID-19 patients, negative for TOCC (Travel, Profession, Cluster, Contact) risk factors were observed retrospectively. A nasopharyFngeal RT-PCR test was obtained 48 to 72 h before the surgery in all cases. Possible risk factors for a positive test was identified. Results: The detected asymptomatic COVID-19 infection rate during the peak of the second wave among the pre-operative orthopaedic patients was 12.3%. Younger age, female gender, longer duration of admission to RT-PCR test interval were found to be significant (p= < 0.05) risk factors for asymptomatic RT-PCR to be positive. The hazard ratio (HR) for being asymptomatic RT-PCR positive was 4.3 (p = 0. 025), while the RT-PCR was performed at 14 days, but the HR increased to 9.2 (p = 0.049) when the test was performed after 45 days. Conclusion: According to our findings, pre-operative testing to rule out COVID-19 should be regarded as a critical step in preventing the disease clusters in hospitals.

Advancement in the Cuffless and Noninvasive Measurement of Blood Pressure: A Review of the Literature and Open Challenges.

Hypertension is a chronic condition that is one of the prominent reasons behind cardiovascular disease, brain stroke, and organ failure. Left unnoticed and untreated, the deterioration in a health condition could even result in mortality. If it can be detected early, with proper treatment, undesirable outcomes can be avoided. Until now, the gold standard is the invasive way of measuring blood pressure (BP) using a catheter. Additionally, the cuff-based and noninvasive methods are too cumbersome or inconvenient for frequent measurement of BP. With the advancement of sensor technology, signal processing techniques, and machine learning algorithms, researchers are trying to find the perfect relationships between biomedical signals and changes in BP. This paper is a literature review of the studies conducted on the cuffless noninvasive measurement of BP using biomedical signals. Relevant articles were selected using specific criteria, then traditional techniques for BP measurement were discussed along with a motivation for cuffless measurement use of biomedical signals and machine learning algorithms. The review focused on the progression of different noninvasive cuffless techniques rather than comparing performance among different studies. The literature survey concluded that the use of deep learning proved to be the most accurate among all the cuffless measurement techniques. On the other side, this accuracy has several disadvantages, such as lack of interpretability, computationally extensive, standard validation protocol, and lack of collaboration with health professionals. Additionally, the continuing work by researchers is progressing with a potential solution for these challenges. Finally, future research directions have been provided to encounter the challenges.

Cuff-less blood pressure measurement based on hybrid feature selection algorithm and multi-penalty regularized regression technique.

One of the prominent reasons behind the deterioration of cardiovascular conditions is hypertension. Due to lack of specific symptoms, sometimes existing hypertension goes unnoticed until significant damage happens to the heart or any other body organ. Monitoring of BP at a higher frequency is necessary so that we can take early preventive measures to control and keep it within the normal range. The cuff-based method of measuring BP is inconvenient for frequent daily measurements. The cuffless BP measurement method proposed in this paper uses features extracted from the electrocardiogram (ECG) and photoplethysmography (PPG). ECG and PPG both have distinct characteristics, which change with the change of blood pressure levels. Feature extraction and hybrid feature selection algorithms are followed by a generalized penalty-based regression technique led to a new BP measurement process that uses the minimum number of features. The performance of the proposed technique to measure blood pressure was compared to an approach using an ordinary linear regression method with no feature selection and to other contemporary techniques. MIMIC-II database was used to train and test our proposed method. The root mean square error (RMSE) for systolic blood pressure (SBP) improved from 11.2 mmHg to 5.6 mmHg when the proposed technique was implemented and for diastolic blood pressure (DBP) improved from 12.7 mmHg to 6.69 mmHg. The mean absolute error (MAE) was found to be 4.91 mmHg for SBP and 5.77 mmHg for DBP, which have shown improvement over other existing cuffless techniques where the substantial number of patients, as well as feature selection algorithm, were implemented. In addition, according to the British Hypertension Society standard (BHS) standard for cuff-based BP measurement, the criteria for acceptable measurement are to achieve at least grade B; our proposed method also satisfies this criterion.

Determination of in vitro antioxidant activity and in vivo antineoplastic effects against Ehrlich ascites carcinoma of methanolic extract of Sphagneticola calendulacea (L.) Pruski.

BACKGROUND AND AIM: Sphagneticola calendulacea (L.) Pruski (S. calendulacea) is a well-known medicinal plant that is widely used in traditional medicine. This study was conducted to evaluate the antioxidant and antineoplastic properties of S. calendulacea leaf. EXPERIMENTAL PROCEDURE: Methanol was used as a solvent to prepare leaf extract from the dried leaf of S. calendulacea (MESL). We have evaluated the total phenolic and flavonoid contents of MESL, and using five different assays; we have also evaluated the antioxidant property of MESL. In vivo antineoplastic activity of MESL against Ehrlich ascites carcinoma (EAC) cells in experimental mice was also explored. RESULTS: The phytochemical analysis of MESL exhibited the total phenolic, and total flavonoid contents in the dry extracts were 32.86 mg/gm of gallic acid equivalent and 127.26 mg/gm of catechin equivalent, respectively. Moreover, MESL also showed promising scavenging activity in all assays (IC50 value ≥70.5 µg/mL). In the in vivo antineoplastic assay, MESL showed increased EAC cell death at the doses of 50 mg/kg and 100 mg/kg body weight. MESL administration also induced apoptosis of EAC cells, significantly inhibited EAC cell growth, and increased the life span of EAC cell-bearing mice compared to EAC cell-bearing control mice. CONCLUSIONS: All findings of this study suggest potential antioxidant and antineoplastic properties of MESL.