Using Inspiratory Muscle Training to Improve Respiratory Strength, Functional Capacity, Fatigue, and Stress in Breast Cancer Patients Undergoing Surgery.

Purpose: The main aim of the trial was to assess the effectiveness of inspiratory muscle training on respiratory muscle strength, functional capacity, fatigue, and stress in post-surgical breast cancer survivors. Methods: Forty-seven females who had undergone unilateral post-mastectomy were randomly assigned to an intervention group (IG; n = 24) and a control group (CG; n = 23). Both groups received aerobic exercise training. In addition, the intervention group received inspiratory muscle training 3 days a week for 8 weeks. Maximum inspiratory and expiratory pressure (Pimax) (Pemex), 6-minute walk test, Handgrip strength by hand-held dynamometer, Fatigue Assessment Scale (FAS), and Perceived Stress Scale pss 10 values were measured before the training and then at the eighth week for both groups. Results: No differences were detected between the groups in terms of sample and clinical characteristics 8 weeks post-intervention. In favor of the intervention group, a significant difference with medium to high effect size was found in terms of Pimax, Pemax, FAS, PS, and 6MWT (p < 0.05). However, there was no difference in terms of handgrip strength (p-value: 0.072), with a medium effect size (0.070). Regarding within-group comparisons, IG exhibited substantial differences in all outcome measures (p < 0.05) compared to CG, with the exception of PImax and 6MWT. Conclusion: In post-operative breast cancer survivors, respiratory muscle training combined with aerobic training increases respiratory muscle strength and functional ability while lowering stress and tiredness.

Impact of adding Mediterranean diet to aerobic and strengthening exercise program on pain, inflammation, and muscle performance in females with rheumatoid arthritis: a randomized controlled trial.

BACKGROUND: People with rheumatoid arthritis (RA) frequently use dietary interventions such as Mediterranean diet (MedDiet) and exercises to complement pharmacotherapy. OBJECTIVE: To investigate the effect of adding MedDiet to a designed exercise program on quadriceps and hamstrings muscles performance, pain, C-reactive protein (CRP), handgrip strength, bodyweight, and function in females with RA. METHODS: Sixty females were allocated randomly to the MedDiet plus exercise program (n = 30) or exercise program only (n = 30). The interventions continued for 6 months followed by 6 months of follow-up with no intervention. The primary outcome was the quadriceps and hamstrings muscles performance (agonist-antagonist ratio). The secondary outcomes were visual analog scale (VAS) for pain, CRP blood marker for inflammation, handheld dynamometer for handgrip strength, Health AssessmentQuestionnaire disability index (HAQ-DI) for function, and body weight. All outcomes were measured at baseline, 6-month post-intervention, and 12 months from baseline as a follow-up. RESULTS: The MedDiet group showed statistically significant improvements in all the measured outcomes than the control group (p < .05) after 6 and 12 months. After 6 months of intervention, the mean±SD for agonist-antagonist ratio, pain, and HAQ-DI were 84.59 ± 5.33 and 69.92 ± 5.56 (p < .001, ƞ2 = 0.65), 42.33 ± 8.98 and 54.33 ± 10.06 (p < .001, ƞ2 = 0.3), 1.13 ± 0.48 and 1.9 ± 0.59 (p < .001, ƞ2 = 0.34) in the MedDiet and control groups, respectively. CONCLUSION: Adding MedDiet to aerobic and strengthening exercise program improved quadriceps and hamstrings muscles performance, pain, functional ability, CRP, handgrip strength, and body weight. Consequently, Mediterranean diet should be considered as adjunctive therapy in treating females with RA.

Candidate genes associated with reproductive traits in rabbits.

In the era of scientific advances and genetic progress, opportunities in the livestock sector are constantly growing. The application of molecular-based methods and approaches in farm animal breeding would accelerate and improve the expected results. The current work aims to comprehensively review the most important causative mutations in candidate genes that affect prolificacy traits in rabbits. Rabbits are a source of excellent-tasting meat that is high in protein and low in fat. Their early maturity and intensive growth are highly valued all over the world. However, improving reproductive traits and prolificacy in rabbits could be very tricky with traditional selection. Therefore, traditional breeding programs need new methods based on contemporary discoveries in molecular biology and genetics because of the complexity of the selection process. The study and implementation of genetic markers related to production in rabbits will help to create populations with specific productive traits that will produce the desired results in an extremely short time. Many studies worldwide showed an association between different genes and productive traits in rabbits. The study of these polymorphisms and their effects could be useful for molecular-oriented breeding, particularly marker-assisted selection programs in rabbit breeding.

Influence of polymorphisms in candidate genes on carcass and meat quality traits in rabbits.

Candidate gene is a powerful approach to study gene-trait association and offers valuable information for genetic improvement using marker-assisted selection. The current work aimed to study the polymorphisms of four single nucleotide polymorphism (SNPs) at located growth hormone (GH), insulin-like growth factor-II (IGF-II), fat mass and obesity-associated (FTO), and insulin receptor substrate-1 (IRS-1) genes, and their association with the carcass, and meat quality traits in rabbits. The SNPs were genotyped using RFLP-PCR in New Zealand White and local Baladi rabbits. The results revealed that the heterozygous genotype was the most frequent in all cases, except for the FTO SNP in LB rabbits. There was a significant effect for GH genotypes on meat lightness after slaughter and hind-part weight. While, IGF-II mutation significantly affected slaughter, hot carcass, commercial carcass, and hind-part weights. The FTO SNP was associated with cooking loss and intramuscular fat weight, and the IRS-1 SNP was significantly associated with drip loss and intramuscular fat. Specific-breed effects were obtained for IGF-II SNP on cooking loss, and for the intramuscular fat. Although the results suggested that these mutations are useful candidate genes for selection, more research for detecting more variants associated with carcass and meat quality traits in rabbits are recommended.

Genome-wide in silico characterization, validation, and cross-species transferability of microsatellite markers in Mallard and Muscovy ducks.

BACKGROUND: Microsatellites are important markers for livestock including ducks. The development of microsatellites is expensive and labor-intensive. Meanwhile, the in silico approach for mining for microsatellites became a practicable alternative. Therefore, the current study aimed at comparing whole-genome and chromosome-wise microsatellite mining approaches in Muscovy and Mallard ducks and testing the transferability of markers between them. The GMATA software was used for the in silico study, and validation was performed using 26 primers. RESULTS: The total number of the detected microsatellites using chromosome-wise was 250,053 and 226,417 loci compared to 260,059 and 238,462 loci using whole genome in Mallards and Muscovies. The frequencies of different motifs had similar patterns using the two approaches. Dinucleotide motifs were predominant (> 50%) in both Mallards and Muscovies. The amplification of the genomes revealed an average number of alleles of 5.08 and 4.96 in Mallards and Muscovies. One locus was monographic in Mallards, and two were monomorphic in Muscovies. The average expected heterozygosity was higher in Muscovy than in Mallards (0.45 vs. 0.43) with no significant difference between the two primer sets, which indicated the usefulness of cross-species amplification of different primers. CONCLUSION: The current study developed a whole-genome SSR panel for ducks for the first time, and the results could prove that using chromosome-wise mining did not generate different results compared to the whole-genome approach.

Optimal energy management applying load elasticity integrating renewable resources.

Urban growth aimed at developing smart cities confronts several obstacles, such as difficulties and costs in constructing stations and meeting consumer demands. These are possible to overcome by integrating Renewable Energy Resources (RESs) with the help of demand side management (DSM) for managing generation and loading profiles to minimize electricity bills while accounting for reduction in carbon emissions and the peak to average ratio (PAR) of the load. This study aims to achieve a multi-objective goal of optimizing energy management in smart cities which is accomplished by optimally allocating RESs combined with DSM for creating a flexible load profile under RESs and load uncertainty. A comprehensive study is applied to IEEE 69-bus with different scenarios using Sea-Horse Optimization (SHO) for optimal citing and sizing of the RESs while serving the objectives of minimizing total power losses and reducing PAR. SHO performance is evaluated and compared to other techniques such as Genetic Algorithm (GA), Grey Wolf Optimization (GWO), Whale Optimization (WO), and Zebra Optimization (ZO) algorithms. The results show that combining elastic load shifting with optimal sizing and allocation using SHO achieves a global optimum solution for the highest power loss reduction while using a significantly smaller sized RESs than the counterpart.

Role of penile rehabilitation through daily intake of 5 mg tadalafil on erectile dysfunction after different presentations of penile fracture: a prospective case-control study.

PURPOSE: We aimed in the current study to identify the predictive factors of ED occurrence in healthy individuals following penile fracture surgical repair as well as the effect of penile rehabilitation in the form of daily tadalafil 5 mg intake for 1 month for patients who suffered from ED after penile fracture incident. METHOD: The current study was a prospective case-control study. Twenty-five patients were enrolled into the study starting from January (2022) to February (2023). Furthermore, time of presentation was determined, and length of tear intra-operative was measured, and then, a follow-up 1 week postoperatively in the outpatient clinic was conducted. All patients were instructed to start intercourse at least 2 weeks after the first visit provided that the wound epithelialized. Potent patients returned back home. A rehabilitation course of daily tadalafil 5 mg for 1 month was prescribed for patients who started complaining of ED that was confirmed by evaluation with the Arabic validated version of the international index of erectile function (ArIIEF-5). The rehabilitation therapy was terminated by resumption of normal erectile function. Thus, re-evaluation with the ArIIEF-5 was determined according to their response to therapy. Also, the patients were evaluated by hospital anxiety and depression scale (HADS) before and after penile fracture repair. RESULTS: The current study had demonstrated that a 1% increase in age determines an increase in odds ratio for post-penile fracture ED with 73.6% and 1 cm increase in the length of tear determines an increase in odds ratio for post-penile fracture ED with 20.04 times. CONCLUSION: The current study enhances the proper counseling of these patients prior to repairing the defect about the probability of ED occurrence as well as initiating early penile rehabilitation to help these patients resuming their normal sexual activity as soon as possible.

Self-Supervised Contrastive Representation Learning for Semi-Supervised Time-Series Classification.

Learning time-series representations when only unlabeled data or few labeled samples are available can be a challenging task. Recently, contrastive self-supervised learning has shown great improvement in extracting useful representations from unlabeled data via contrasting different augmented views of data. In this work, we propose a novel Time-Series representation learning framework via Temporal and Contextual Contrasting (TS-TCC) that learns representations from unlabeled data with contrastive learning. Specifically, we propose time-series-specific weak and strong augmentations and use their views to learn robust temporal relations in the proposed temporal contrasting module, besides learning discriminative representations by our proposed contextual contrasting module. Additionally, we conduct a systematic study of time-series data augmentation selection, which is a key part of contrastive learning. We also extend TS-TCC to the semi-supervised learning settings and propose a Class-Aware TS-TCC (CA-TCC) that benefits from the available few labeled data to further improve representations learned by TS-TCC. Specifically, we leverage the robust pseudo labels produced by TS-TCC to realize a class-aware contrastive loss. Extensive experiments show that the linear evaluation of the features learned by our proposed framework performs comparably with the fully supervised training. Additionally, our framework shows high efficiency in few labeled data and transfer learning scenarios.

Assessment of variations in productive performance of two different plumage color varieties of Japanese quail and their reciprocal crosses.

This study aimed to detect the phenotypic differences between the brown (BB) and white (WW) feathered quails and their reciprocal crosses (BW and WB) over two successive generations. The WW and cross quails, especially the BW, had the heaviest body weights, throughout the studied period, with significant variations between the two studied generations (P<0.05). Moreover, the WW and BW possessed the largest egg production during the F1, while in the F2, the BB had superiority among the studied quails with a prominent superiority of the F2 over the F1 (P<0.05). However, the F1 had higher egg weights than F2 with superiority of WW quails compared to the others (P<0.05). Also, the WW quails had the lowest lipid contents of the eggs. These phenotypic variations among the studied quails might be preliminarily explained by the results of the analyzed microsatellite markers despite the few markers used. The high variability among the BW and WB quails might be due to the larger number of alleles (NA and Ne) and the lower values of FIS with low heterozygosity levels (HO and He). Moreover, the BW and BB were the closest, while WB and WW were the farthest because of the high and low genetic identities and the high and low genetic distance between them, respectively. So the obtained results might introduce an initial scientific basis for evaluating and employing the genetic properties of BB, WW, BW, and WB quails in further genetic improvement program, and more microsatellite markers are recommended.

Endometriosis Causing Large Bowel Obstruction: A Case Report.

Endometriosis is defined as the presence of endometrial glands and stroma in ectopic locations, with extrapelvic sites being less commonly affected. Only a few cases of colonic endometriosis causing acute bowel obstruction have been reported in the literature, in which resection and primary anastomosis were the treatments performed. We present the case of a 40-year-old female who presented with signs and symptoms of acute large bowel obstruction thought to be due to malignancy; however, further evaluation confirmed the diagnosis of rectosigmoid endometriosis. The management plan was an immediate laparotomy with rectosigmoid resection and primary anastomosis.

The comparison of two different plumage-color lines of Japanese quail (Coturnix japonica) disclosed a significant effect in increasing abdominal fat contents with increasing age.

This study aimed to investigate the characteristic differences between the white and brown-feathered Japanese quails, by evaluating the carcass traits and egg fat content, blood parameters, and intestinal histopathological features. A total of 1200 1-day-old Japanese quail chicks of two varieties (brown and white-feathered) were used in this study. Live body weight and feed intake were reordered every week. At the 4th week of age, 80 birds from each variety were slaughtered and carcass quality measurements and histopathological changes were recorded. After 6 weeks of age, eggs were collected, and egg quality was assessed. The results revealed that white-feathered quails had significantly heavier body weights and higher growth rates. At 4 weeks of age, females of the white-feather quail had significantly heavier slaughter, after de-feathering, and carcass weights. Remarkable variations between the studied quail varieties, with significant dominance of females in both varieties, at the level of water holding capacity, pH, and meat tenderness ascertained an obvious superiority of white-feathered quails compared to brown ones and indicated the higher tendency of the white quails for meat production. These results were linked with significant changes in biochemical profiles including lipids biomarkers, total protein, and Ca and phosphorus levels along with variations in the intestinal morphometry. It can be concluded that white-feathered quails had, in general, higher values of productivity compared with the brown-feathered ones during growing and laying periods.

Self-supervised Learning for Label-Efficient Sleep Stage Classification: A Comprehensive Evaluation.

The past few years have witnessed a remarkable advance in deep learning for EEG-based sleep stage classification (SSC). However, the success of these models is attributed to possessing a massive amount of labeled data for training, limiting their applicability in real-world scenarios. In such scenarios, sleep labs can generate a massive amount of data, but labeling can be expensive and time-consuming. Recently, the self-supervised learning (SSL) paradigm has emerged as one of the most successful techniques to overcome labels' scarcity. In this paper, we evaluate the efficacy of SSL to boost the performance of existing SSC models in the few-labels regime. We conduct a thorough study on three SSC datasets, and we find that fine-tuning the pretrained SSC models with only 5% of labeled data can achieve competitive performance to the supervised training with full labels. Moreover, self-supervised pretraining helps SSC models to be more robust to data imbalance and domain shift problems.

Association between IRS-1, PPAR-γ and LEP genes polymorphisms and growth traits in rabbits.

Single nucleotide polymorphisms are commonly associated with changes in quantitative traits, and have been considered useful markers for improving different traits in livestock. The current study aimed to explore the effect of three SNPs located in Insulin receptor substrate (IRS-1), Peroxisome proliferator-activated receptor γ (PPAR-γ), and Leptin (LEP) genes on the growth traits of rabbits. Individuals from three rabbit breeds were genotyped using RFLP-PCR. The IRS-1 variant (c.189T > G) was associated with post-weaning body weight, and body weight gains, However, the effect on growth rates was insignificant in Baladi Red and V-line rabbits. The PPAR-γ variant (c.207A > C) was significantly associated with 8-wk body weights in V-line rabbits, 10-wk body weights, and growth rates from 8 to 10 weeks of age in New Zealand rabbits. However, the differences between genotypes were insignificant for body weight gains and average daily gain. The LEP gene mutation (g.16079636C > G) had significant effects on body weights at 6 and 8 weeks of age in New Zealand White rabbits and 8 weeks of age in Baladi Red rabbits were associated with the presence of the C allele. Concludingly, the results stressed the importance of the IRS-1 gene in post-weaning growth and suggested the existence of breed-specific effects for PPAR-γ and LEP.

Genotype by heat conditions interaction effects on growth and litter traits in rabbits.

Heat stress has severe impacts on rabbit performance because they have difficulty getting rid of excess heat. The interaction between genetic and environmental factors plays a vital role in the adaptation process. The current study aimed to evaluate the effects of interaction between the genotype and heat conditions (G×H) on litter size and growth traits. Two rabbit lines were used in the current study, Egyptian maternal line (APRI) and New Zealand White (NZW). The rabbits were raised under normal (22°C) or heat stress (35°C) conditions. The does were raised in individual cages, and their kits were reared under the same conditions. Negative effects of heat conditions were noted for litter traits, as heat stress had significantly reduced the number of born alive, total born, and marketed number rabbits by about 16, 11, and 25%, respectively. Moreover, growth traits were reduced under heat stress conditions compared to normal temperature conditions. Significant differences between genotypes were observed, APRI rabbits were higher than NWZ rabbits in the total born, number of born alive, number weaned, and the number of marketed rabbits by 10, 8, 11, and 10%, respectively. Genotype by heat conditions interaction effects were observed, APRI litters under normal conditions showed significantly higher litter traits than NWZ litters, whereas relevant reductions in litter traits of APRI line than NZW litters when reared in heat conditions. For growth traits, the differences between the two lines under normal conditions were reduced when animals of the two lines were raised under heat stress, for BW28, BW42, BW63, ADG28-42, and DF28-42 while these differences were increased for ADG42-63, DF28-42 and feed conversion during the whole fattening period. Based on the observed G × H interactions, it is important to select the animals under the same production conditions to raise rabbits that can cope with the expected global warming conditions.

Self-Supervised Autoregressive Domain Adaptation for Time Series Data.

Unsupervised domain adaptation (UDA) has successfully addressed the domain shift problem for visual applications. Yet, these approaches may have limited performance for time series data due to the following reasons. First, they mainly rely on the large-scale dataset (i.e., ImageNet) for source pretraining, which is not applicable for time series data. Second, they ignore the temporal dimension on the feature space of the source and target domains during the domain alignment step. Finally, most of the prior UDA methods can only align the global features without considering the fine-grained class distribution of the target domain. To address these limitations, we propose a SeLf-supervised AutoRegressive Domain Adaptation (SLARDA) framework. In particular, we first design a self-supervised (SL) learning module that uses forecasting as an auxiliary task to improve the transferability of source features. Second, we propose a novel autoregressive domain adaptation technique that incorporates temporal dependence of both source and target features during domain alignment. Finally, we develop an ensemble teacher model to align class-wise distribution in the target domain via a confident pseudo labeling approach. Extensive experiments have been conducted on three real-world time series applications with 30 cross-domain scenarios. The results demonstrate that our proposed SLARDA method significantly outperforms the state-of-the-art approaches for time series domain adaptation. Our source code is available at: https://github.com/mohamedr002/SLARDA.

Genotype by feeding regimen interactions for slaughter traits in rabbit and expected responses under restricted and full feeding.

The interaction between the genotype and feeding regimen (G×FR) for slaughter traits was estimated from data corresponding to 2557 animals under full (FF) and 2424 with restricted feeding (RF). Expected responses to selection under different scenario regarding feeding regimen were also calculated. Body weight at slaughter (SW), carcass weight (CW) and dressing out percentage (DoP) were analysed by using linear animal models in which records obtained under different feeding regimes were treated as different traits. Animals belonged to Caldes line, selected for average daily gain (G) under ad libitum feeding. The selection process information was included in the analyses. Marginal posterior mean of heritabilities were 0.102 for G, and 0.364, 0.257 and 0.167 for SW, CW and DoP under FF feeding. The corresponding values for animals fed on RF were 0.243, 0.203 and 0.379 for SW, CW and DoP, respectively. Genetic correlations between G and CW were positive and moderate, and those between G and DoP were low. The estimated genetic correlation between SW, CW and DoP under different feeding regimens were: 0.73, 0.69 and 0.87, respectively. These correlations cannot be said to be far enough from one to generate relevant G×FR interaction variance, which were estimated to be only 11.1%, 8.6% and 5.3% of the mean of the phenotypic variance for SW, CW and DoP, respectively. This lack of G×FR interaction variance, jointly with the higher heritability of DoP under RF, explains that the genetic improvement of DoP can be done more efficiently recording traits on animals under RF, even if the interest is on the performances under FF, i.e. by indirect selection.

New Alpha-Amylase Inhibitory Metabolites from Pericarps of Garcinia mangostana.

Two new benzophenones: garcimangophenones A (6) and B (7) and five formerly reported metabolites were purified from the pericarps EtOAc fraction of Garcinia mangostana ((GM) Clusiaceae). Their structures were characterized by various spectral techniques and by comparing with the literature. The α-amylase inhibitory (AAI) potential of the isolated metabolites was assessed. Compounds 7 and 6 had significant AAI activity (IC50 9.3 and 12.2 µM, respectively) compared with acarbose (IC50 6.4 µM, reference α-amylase inhibitor). On the other hand, 5 had a moderate activity. Additionally, their activity towards the α-amylase was assessed utilizing docking studies and molecular dynamics (MD) simulations. The docking and predictive binding energy estimations were accomplished using reported crystal structure of the α-amylase (PDB ID: 5TD4). Compounds 7 and 6 possessed highly negative docking scores of -11.3 and -8.2 kcal/mol, when complexed with 5TD4, respectively while acarbose had a docking score of -16.1 kcal/mol, when complexed with 5TD4. By using molecular dynamics simulations, the compounds stability in the complexes with the α-amylase was analyzed, and it was found to be stable over the course of 50 ns. The results suggested that the benzophenone derivative 7 may be potential α-amylase inhibitors. However, further investigations to support these findings are required.

Estrogen Receptor Gene Polymorphism as a Possible Genetic Risk Factor for Treatment Response in ER-Positive Breast Cancer Patients.

Estrogen receptor-α (ESR1) single nucleotide polymorphisms (SNPs) have been related to breast cancer (BC) susceptibility. In this retrospective study we investigated ESR1 SNPs in association with survival and treatment response in BC patients. Seven ESR1 SNPs were genotyped using TaqMan probe assay in 100 formalin-fixed paraffin embedded blocks of Egyptian ER+BC patients. Log-binomial regression was used to assess the association of 5 ESR1 SNPs with relative risk of non-response to adjuvant-hormonal treatment. We compared the performance of five machine learning classification models for prediction of treatment response. Predictive models were developed using rs1801132, rs2228480, and rs9322354 that were significantly associated with increased risk for non-response along with the relevant clinical features. Survival analysis was performed to detect prognostic significance of ESR1 SNPs in ESR+BC patients. rs1801132 (C), rs2228480 (A), and rs9322354 (G) minor alleles significantly increased the risk of non-response to tamoxifen by more than 81, 84, and 117%, respectively, in ER+BC patients on anthracycline/anthracycline-taxanes-based chemotherapy. Multivariate Cox regression survival analysis revealed that rs1801132 (C) and large tumor size were independent predictors for poor survival outcome in ER+BC. The best response predictive model was a combination random forest, K-nearest neighbor, and decision tree having an area under the curve of 0.94 and an accuracy of 90.8%. Our proposed predictive model based on ESR1 rs1801132, rs2228480, and rs9322354 SNPs represents a promising genetic risk stratification for selection patients who could benefit from tamoxifen therapy in such a way that might facilitate personalized medicine required to improve ER+BC patients' outcome.

Candidate genes for marker-assisted selection for growth, carcass and meat quality traits in rabbits.

Growth and meat production are the most relevant targets for animal breeders, there are strong relationships between animal growth regulation, body composition and meat quality. Therefore, it is essential to identify the genetic factors that are controlling growth, carcass, and meat quality traits and to explore the correlations between identified genes of those traits. Identification of candidate genes may shift rabbit breeding from classical to modern approaches, which offer great potential to accelerate genetic improvement plans, especially in developing countries. The current work reviews several genes and mutations affecting growth, carcass and meat quality traits. These candidate genes and mutations can be incorporated into MAS programs to improve rabbit breeds especially local breeds, provided that a reasonable proportion of trait additive genetic variance is explained by the significant marker. Furthermore, we highlighted the indispensable need for more researches investigating candidate genes for different traits.

Fusaroxazin, a novel cytotoxic and antimicrobial xanthone derivative from Fusarium oxysporum.

Oxazines and their derivatives are an uncommon natural heterocyclic compounds, which contain oxygen and nitrogen atoms and possess various bioactivities. A novel 1,4-oxazine-xanthone derivative, fusarioxazin (4) and three known sterols (1-3) were separated from Fusarium oxysporum EtOAc extract associated with Vicia faba L. (broad bean, Fabaceae) roots. Their structural assignment was accomplished using various spectroscopic tools and comparing with literature data. The cytotoxic and antimicrobial potentials of the novel metabolite (4) were evaluated. It possessed a significant antibacterial activity towards S. aureus (IZD 14.8 mm and MIC 5.3 µg/mL) and B. cereus (IZD 18.9 mm and MIC 3.7 µg/mL), in comparison to ciprofloxacin (IZDs 16.9 and 20.5 mm; MICs 3.9 and 2.3 µg/mL, respectively). Furthermore, it displayed a promising cytotoxic effect toward HCT-116 (IC50 2.1 µM), MCF-7 (IC50 1.8 µM), and A549 (IC50 3.2 µM) comparable to doxorubicin (IC50s 0.68, 0.54, and 0.39 µM, respectively).