Malignant epithelioid angiomyolipoma of the submandibular gland: A case report.

An epithelioid angiomyolipoma (a perivascular epithelioid cell tumor) is a rare mesenchymal neoplasm with distinctive cellular morphology and nonspecific imaging appearances. Mostly reported perivascular epithelioid cell tumors (PEComas) are benign; however, rarely, PEComas can be malignant with pulmonary, hepatic, nodal, and osseous metastases. We present a case of a 40-year-old man with malignant right submandibular salivary gland PEComa, metastasized to the bones, lungs, and liver. We are going to discuss the diagnosis and management options of the rare disease of metastatic PEComa of the submandibular salivary gland.

CRISPR-Cas9 guided RNA-based model for the silencing of spinal bulbar muscular atrophy: A functional genetic disorder.

This study explores a novel therapeutic approach for spinal bulbar muscular atrophy (SBMA), a neurodegenerative disorder caused by a mutation in the Androgen Receptor (AR) gene. The aim is to investigate the potential of CRISPR-Cas9 technology in targeting the mutant AR gene to inhibit its production. The objectives include assessing the accuracy and efficacy of CRISPR-Cas9 guided RNAs in silencing the mutant gene and evaluating the feasibility of this approach as a treatment for SBMA. Computational and in-silico approaches are used to evaluate the feasibility of using CRISPR-Cas9 technology for treating SBMA. Computational analysis is used to design CRISPR-Cas9 guided RNAs targeting the mutant AR gene, assessing their on-target and off-target scores, GC content, and structural accuracy. In-silico simulations predict the potential therapeutic outcomes of the CRISPR-Cas9 approach in an artificial environment. Three guided RNA (gRNA) sequences were designed using the CHOPCHOP tool, targeting specific regions of the AR gene with high efficiency and 100% match. These gRNAs demonstrated effective targeting with minimal off-target scores and optimal GC content. Additionally, lentiCRISPR v2 plasmids were designed for the delivery of CRISPR materials, enabling high-efficiency multiplex genome editing of the AR gene. Thermodynamic ensemble predictions indicated favorable secondary structure stability of the designed gRNAs, further supporting their suitability for gene editing. The evaluation of designed gRNAs confirmed their strong binding ability to the target sequences, validating their potential as effective tools for genome editing. The study highlights the potential of CRISPR-Cas9 technology for targeting the Androgen Receptor gene associated with spinal bulbar muscular atrophy (SBMA). The findings support the feasibility of this approach for gene editing and suggest further exploration in preclinical and clinical settings. Recommendations include continued research to optimize CRISPR-Cas9 delivery methods and enhance specificity for therapeutic applications in SBMA.

Effects of SZV-2649, a new multiple ion channel inhibitor mexiletine analogue.

The antiarrhythmic and cardiac electrophysiological effects of SZV-2649 that contains a 2,6-diiodophenoxy moiety but lacks the benzofuran ring system present in amiodarone, were studied in mammalian cell line, rat and dog cardiac preparations. SZV-2649 exerted antiarrhythmic effects against coronary artery occlusion/reperfusion induced ventricular arrhythmias in rats and in acetylcholine- and burst stimulation induced atrial fibrillation in dogs. SZV-2649 inhibited hERG and GIRK currents in HEK cells (IC50: 342 and 529 nM, respectively). In canine ventricular myocytes, SZV-2649 (10 µM) decreased the densities of IKr, and Ito outward and INaL and ICaL inward currents. The compound (2.5-10 µM) elicited Class IB type Vmax reducing and Class III type action potential duration prolonging effects in dog right ventricular muscle preparations. In canine atrial muscle, SZV-2629 (2.5-10 µM) moderately prolonged action potential duration and this effect was greatly augmented in preparations pretreated with 1 µM carbachol. In conclusion, SZV-2649, has antiarrhythmic effects based on its multiple ion channel blocking properties. Since its chemical structure substantially differs from that of amiodarone, it is expected that SZV-2649 would exhibit fewer adverse effects than the currently used most effective multichannel inhibitor drug amiodarone and may be a promising molecule for further development.

The Prominence of the Broad-Spectrum Protease inhibitor gene A2ML1 as a potential biomarker in cervical cancer diagnostics using Immunotherapeutic and Multi-Omics approaches.

One of the venereal tumors that threaten human life is cervical cancer. A2ML1 is detected in advanced-stage cancer patients and is found to be strongly associated with cervical cancer. A2ML1 was shown to be substantially expressed in cervical cancer in this study, which used data from the TCGA database. Those with high A2ML1 expression had a lower chance of survival than patients with low A2ML1 expression. Both univariate and multivariate Cox regression analyses were utilized to investigate the relationship between clinical variables and overall survival rates. An investigation into the link between A2ML1 and immune infiltration was subsequently conducted. Utilizing the immune cell database, research was conducted to investigate the dispersion of 24 immune cells and their correlation to A2ML1 expression. In addition to this, the favorable correlation between immune cells and A2ML1 was validated using all three immune cell methodologies. The Genomics of Drug Sensitivity in Cancer database was used to confirm the idea that there is a link between A2ML1 expression and the efficacy of chemotherapy or immunotherapy. The findings demonstrated that A2ML1 is a potential biomarker for cervical cancer diagnostics. This biomarker may be used to chaperone immunotherapy, as well as to explain the elucidates of cervical cancer caused by the immunological microenvironment.

A federated learning architecture for secure and private neuroimaging analysis.

The amount of biomedical data continues to grow rapidly. However, collecting data from multiple sites for joint analysis remains challenging due to security, privacy, and regulatory concerns. To overcome this challenge, we use federated learning, which enables distributed training of neural network models over multiple data sources without sharing data. Each site trains the neural network over its private data for some time and then shares the neural network parameters (i.e., weights and/or gradients) with a federation controller, which in turn aggregates the local models and sends the resulting community model back to each site, and the process repeats. Our federated learning architecture, MetisFL, provides strong security and privacy. First, sample data never leave a site. Second, neural network parameters are encrypted before transmission and the global neural model is computed under fully homomorphic encryption. Finally, we use information-theoretic methods to limit information leakage from the neural model to prevent a "curious" site from performing model inversion or membership attacks. We present a thorough evaluation of the performance of secure, private federated learning in neuroimaging tasks, including for predicting Alzheimer's disease and for brain age gap estimation (BrainAGE) from magnetic resonance imaging (MRI) studies in challenging, heterogeneous federated environments where sites have different amounts of data and statistical distributions.

Earing Prediction of AA5754-H111 (Al-Alloy) with Linear Transformation-Based Anisotropic Drucker Yield Function under Non-Associated Flow Rule (Non-AFR).

The yield behavior of aluminum alloy 5754-H111 under different stress conditions for three kinds of plastic work is studied using an anisotropic Drucker model. It is found that when the plastic work is 30 MPa, the anisotropic Drucker model has the most accurate prediction. Comparing the Hill48 and Yld91 models with the Drucker model, the results show that both the anisotropic Drucker and Yld91 models can accurately predict the yield behavior of the alloy. Cylinder drawing finite element analysis is performed under the AFR, but it is not possible to accurately predict the position and height of earing appearance. The anisotropic Drucker model is used to predict the earing behavior under the non-AFR, which can accurately predict the earing phenomenon. Numerical simulation is conducted using three different combinations of yield functions: the anisotropic yield function and the anisotropic plastic potential function (AYAPP), the anisotropic yield function and the isotropic plastic potential function (AYIPP), and the isotropic yield function and the anisotropic plastic potential function (IYAPP). It is concluded that the influence of the plastic potential function on predicting earing behavior is more critical than that of the yield function.

Enhancing chromium resistance and bulb quality in onion (Allium cepa L.) through copper nanoparticles and possible health risk.

Chromium (Cr) is a toxic metal in soil-plant system, hence causing possible health risks prominently in the areas with forgoing industrial activities. Copper nanoparticles (Cu NPs) have been reported as an excellent adsorbent for pollutants. Therefore, this study investigates how copper nanoparticles enhance onion growth while decreasing chromium uptake in onion plants. Additionally, it examines the potential health risks of consuming onion plants with elevated chromium levels. The results demonstrated that the addition of CuNPs at 15 mg kg-1 significantly improved the plant height (48%), leaf length (37%), fresh weight of root (61%), root dry weight (70%), fresh weight of bulb (52%), bulb dry weight (59%), leaves fresh weight (52%) and dry weight of leaves (59%), leaf area (72%), number of onion leaves per plant (60%), Chl. a (42%), chl. b (36%), carotenoids (40%), total chlorophyll (40%), chlorophyll contents SPAD value (56%), relative water contents (35%), membrane stability index (16%), total sugars (25%), crude protein (21%), ascorbic acid (19%) and ash contents (64%) at 10 mg kg-1 Cr. Whereas, maximum decline of Cr by 46% in roots, 68% in leaves and 92% in bulb was found with application of 15 mg kg-1 of Cu NPs in onion plants under 10 mg kg-1 Cr toxicity. The health risk assessment parameters of onion plants showed minimum values 0.0028 for average daily intake (ADI), 0.001911 for Non-cancer risk (NCR), and 0.001433 for cancer risk (CR) in plants treated with Cu NPs at 15 mg kg-1 concentration grown in soil spiked with 10 mg kg-1 chromium. It is concluded that Cu NPs at 15 mg kg-1 concentration improved growth of plants in control as well as Cr contaminated soil. Therefore, use of Cu NPs at 15 mg kg-1 concentration is recommended for improving growth of plants under normal and metal contaminated soils.

Mix-match synthesis of nanosynbiotics from probiotics and prebiotics to counter gut dysbiosis via AI integrated formulation profiling.

Antibiotics, improper food, and stress have created a dysbiotic state in the gut and almost 81% of the world's population has been affected due to the pandemic of COVID-19 and the prevalence of dengue virus in the past few years. The main intent of this study is to synthesize nanosynbiotics as nu traceuticals by combining probiotics, and prebiotics with nanoformulation. The effectiveness of the nanosynbiotics was evaluated using a variety of Nutra-pharmacogenetic assays leading to an AI-integrated formulation profiling was assessed by using machine learning methods. Consequently, Acetobacter oryzoeni as a probiotic and inulin as a prebiotic has been chosen and iron-mediated nanoformulation of symbiotic is achieved. Nanosynbiotics possessed 89.4, 96.7, 93.57, 83.53, 88.53% potential powers of Nutra-pharmacogenetic assays. Artificial intelligent solid dispersion formulation of nanosynbiotics has high dissolution, absorption, distribution, and synergism, in addition, they are non-tox, non-allergen and have a docking score of - 10.83 kcal/mol, implying the best interaction with Pregnane X receptor involved in dysbiosis. The potential of nanosynbiotics to revolutionize treatment strategies through precise targeting and modulation of the gut microbiome for improved health outcomes and disease management is promising. Their transformational influence is projected to be powered by integration with modern technology and customized formulas. Further in-vivo studies are required for the validation of nanosynbiotics as nutraceuticals.

Astrocyte involvement in metabolic regulation and disease.

Astrocytes, the predominant glial cell type in the mammalian brain, influence a wide variety of brain parameters including neuronal energy metabolism. Exciting recent studies have shown that obesity and diabetes can impact on astrocyte function. We review evidence that dysregulation of astrocytic lipid metabolism and glucose sensing contributes to dysregulation of whole-body energy balance, thermoregulation, and insulin sensitivity. In addition, we consider the overlooked topic of the sex-specific roles of astrocytes and their response to hormonal fluctuations that provide insights into sex differences in metabolic regulation. Finally, we provide an update on potential ways to manipulate astrocyte function, including genetic targeting, optogenetic and chemogenetic techniques, transplantation, and tailored exosome-based therapies, which may lead to improved treatments for metabolic disease.

Unlocking the potential of biofilm-forming plant growth-promoting rhizobacteria for growth and yield enhancement in wheat (Triticum aestivum L.).

Plant growth-promoting rhizobacteria (PGPR) boost crop yields and reduce environmental pressures through biofilm formation in natural climates. Recently, biofilm-based root colonization by these microorganisms has emerged as a promising strategy for agricultural enhancement. The current work aims to characterize biofilm-forming rhizobacteria for wheat growth and yield enhancement. For this, native rhizobacteria were isolated from the wheat rhizosphere and ten isolates were characterized for plant growth promoting traits and biofilm production under axenic conditions. Among these ten isolates, five were identified as potential biofilm-producing PGPR based on in vitro assays for plant growth-promoting traits. These were further evaluated under controlled and field conditions for their impact on wheat growth and yield attributes. Surface-enhanced Raman spectroscopy analysis further indicated that the biochemical composition of the biofilm produced by the selected bacterial strains includes proteins, carbohydrates, lipids, amino acids, and nucleic acids (DNA/RNA). Inoculated plants in growth chamber resulted in larger roots, shoots, and increase in fresh biomass than controls. Similarly, significant increases in plant height (13.3, 16.7%), grain yield (29.6, 17.5%), number of tillers (18.7, 34.8%), nitrogen content (58.8, 48.1%), and phosphorus content (63.0, 51.0%) in grains were observed in both pot and field trials, respectively. The two most promising biofilm-producing isolates were identified through 16 s rRNA partial gene sequencing as Brucella sp. (BF10), Lysinibacillus macroides (BF15). Moreover, leaf pigmentation and relative water contents were significantly increased in all treated plants. Taken together, our results revealed that biofilm forming PGPR can boost crop productivity by enhancing growth and physiological responses and thus aid in sustainable agriculture.

Follicular, luteal dynamics and effect of synchronization methods on reproductive responses in Cholistani cows.

The Cholistani cow is considered one of the milch breeds of Zebu cattle. Despite being heat and tick-resistant, it has not yet gained much popularity among Pakistan dairy farmers due to its long calving interval. This study aimed to understand the basic reproductive physiology of Cholistani cows using sonography and reproductive biotechnologies such as estrus synchronization and timed artificial insemination to improve reproductive efficiency. In experiment 1, six Cholistani cows with mixed parity 3.20 ± 1.30 and weighing 400 kg were selected to monitor ovarian dynamics on alternate days by the same sonographer from the onset of heat through ovulation until the next ovulation. Experiment 2 measured the effect of estrus synchronization methods, controlled internal drug release-gonadotropin-releasing hormone (CIDR-GnRH, n = 31) and Ovsynch (OVS, n = 32) on various reproductive parameters. The mean estrous cycle length was 19.81 ± 0.56 days with two follicular waves. The mean inter-ovulatory interval was 20.80 ± 0.52 days, with a preovulatory follicular size of 13.83 ± 2.37 mm. Estrus response was higher (p > 0.05) in controlled internal drug release (CIDR)-GnRH (93.54%) than in OVS (84.37%) cows. Similarly, ovulation and conception rates were higher in CIDR-GnRH (91.66% vs. 68.42%) than in OVS cows (41.37% vs. 33.33%), respectively. In conclusion, CIDR-GnRH results in a better estrus response, higher ovulation rate, and subsequently greater conception rate than OVS in Bos indicus dairy cows.

Revolutionizing the probiotic functionality, biochemical activity, antibiotic resistance and specialty genes of Pediococcus acidilactici BCB1H via in-vitro and in-silico approaches.

This study presents a comprehensive genomic exploration, biochemical characterization, and the identification of antibiotic resistance and specialty genes of Pediococcus acidilactici BCB1H strain. The functional characterization, genetic makeup, biological activities, and other considerable parameters have been investigated in this study with a prime focus on antibiotic resistance and specialty gene profiles. The results of this study revealed the unique susceptibility patterns for antibiotic resistance and specialty genes. BCB1H had good in vitro probiotic properties, which survived well in simulated artificial gastrointestinal fluid, and exhibited acid and bile salt resistance. BCB1H didn't produce hemolysis and had certain antibiotic sensitivity, making it a relatively safe LAB strain. Simultaneously, it had good self-coagulation characteristics and antioxidant activity. The EPS produced by BCB1H also had certain antioxidant activity and hypoglycemic function. Moreover, the genome with a 42.4 % GC content and a size of roughly 1.92 million base pairs was analyzed in the genomic investigations. The genome annotation identified 192 subsystems and 1,895 genes, offering light on the metabolic pathways and functional categories found in BCB1H. The identification of specialty genes linked to the metabolism of carbohydrates, stress response, pathogenicity, and amino acids highlighted the strain's versatility and possible uses. This study establishes the groundwork for future investigations by highlighting the significance of using multiple strains to investigate genetic diversity and experimental validation of predicted genes. The results provide a roadmap for utilizing P. acidilactici BCB1H's genetic traits for industrial and medical applications, opening the door to real-world uses in industries including food technology and medicine.

Redefining a new frontier in alkaptonuria therapy with AI-driven drug candidate design via in- silico innovation.

A rare metabolic condition called alkaptonuria (AKU) is caused by a decrease in homogentisate 1,2 dioxygenase (HGO) activity due to a mutation in homogentisate dioxygenase (HGD) gene. Homogentisic acid is a byproduct of the catabolism of tyrosine and phenylalanine that darkens the urine and accumulates in connective tissues which causes an agonizing arthritis. Employing the use of deep learning artificial intelligence (AI) drug design, this study aims to alleviate the current toxicity of the AKU drugs currently in use, particularly nitisinone, by utilizing the natural flavanol kaempferol molecule as a 4-hydroxyphenylpyruvate dioxygenase inhibitor. Kaempferol was employed to generate three effective de novo drug candidates targeting the enzyme 4-hydroxyphenylpyruvate dioxygenase using an AI drug design tool. We present novel AIK formulations in the present study. The AIK's (Artificial Intelligence Kaempferol) examination of drug-likeliness among the three led to its choice as a possible target. The toxicity assessment research of AIK demonstrates that it is not only safer to use than other treatments, but also more efficient. The docking of the AIGT with 4-hydroxyphenylpyruvate dioxygenase, which revealed a binding affinity of around -9.099 kcal/mol, highlights the AIK's potential as a therapeutic candidate. An innovative approach to deal with challenging circumstances is thus presented in this study by new formulations kaempferol that have been meticulously designed by AI. The results of the in vitro tests must be confirmed in vivo, even though AI-designed AIK is effective and sufficiently safe as computed.

Designing an mRNA Vaccine against P. jirovecii Involved in Fatal Pneumonia Infections via Comparative Proteomics and Reverse Vaccinology Approaches.

BACKGROUND: Pneumocystis jirovecii is the most emerging life-threating health problem that causes acute and fatal pneumonia infection. It is rare and more contagious for patients with leukemia and immune-deficiency disorders. Until now there is no treatment available for this infection therefore, it is needed to develop any treatment against this pathogen. METHODS: In this work, we used comparative proteomics, robust immune-informatics, and reverse vaccinology to create an mRNA vaccine against Pneumocystis jirovecii by targeting outer and transmembrane proteins. Using a comparative subtractive proteomic analysis of two Pneumocystis jirovecii proteomes, a distinct non-redundant Pneumocystis jirovecii (strain SE8) proteome was chosen. Seven Pneumocystis jirovecii transmembrane proteins were chosen from this proteome based on hydrophilicity, essentiality, virulence, antigenicity, pathway interaction, protein-protein network analysis, and allergenicity. OBJECTIVE: The reverse vaccinology approach was used to predict the immunogenic and antigenic epitopes of major histocompatibility complex (MHC) I, II and B-cells from the selected proteins on the basis of their antigenicity, toxicity and allergenicity. These immunogenic epitopes were linked together to construct the mRNA-based vaccine. To enhance the immunogenicity, suitable adjuvant, linkers (GPGPG, KK, and CYY), and PRDRE sequences were used. RESULTS: Through predictive modeling and confirmation via the Ramachandran plot, we assessed secondary and 3D structures. The adjuvant RpfE was incorporated to enhance the vaccine construct's immunogenicity (GRAVY index: -0.271, instability index: 39.53, antigenicity: 1.0428). The physiochemical profiling of vaccine construct was predicted it an antigenic, efficient, and potential vaccine. Notably, strong interactions were observed between the vaccine construct and TLR-3/TLR-4 (-1301.7 kcal/mol-1 and -1374.7 kcal/mol-1). CONCLUSIONS: The results predicted that mRNA-based vaccines trigger a cellular and humoral immune response, making the vaccine potential candidate against Pneumocystis jirovecii and it is more suitable for in-vitro analysis and validation to prove its effectiveness.

Urinary polycyclic aromatic hydrocarbons and adult obesity among the US population: NHANES 2003-2016.

Polycyclic aromatic hydrocarbons (PAHs) are naturally occurring environmental pollutants that may contribute to obesity in the adult population. To investigate the relationship between the urinary concentrations of PAH metabolites and adult obesity among the US population, the National Health and Nutritional Examination Survey (NHANES, 2003-2016) was used as a data source for this study. As many as 4464 participants in the NHANES 2003-2016 were included in the final analyses. We used logistic regression to look at the link between urinary PAH metabolites and obesity, using odds ratios (ORs) and 95% confidence intervals (CIs). The study sample comprised 4464 individuals aged ≥18 years, 2199 were male and 2265 were female. The study characteristics for four different quartiles were analyzed, and the average ages of the four urinary PAH quartiles were 49.61 ± 20.01, 46.63 ± 20.33, 44.28 ± 19.19, and 43.27 ± 17.68 years, respectively. In the quartile analysis of all participants, the third quartile was significantly associated with an increased prevalence of obesity (OR = 1.33, 95% CI = 1.12-1.59) with p-values <.05. In addition, females, but not males, had a strong link between the second, third, and fourth quartiles of urinary PAH and a higher risk of obesity (OR = 1.27, 95% CI = 1.00-1.61; OR = 1.52, 95% CI = 1.19-1.94; and OR = 1.39, 95% CI = 1.09-1.78). In conclusion, the study observed that urinary PAH metabolites were associated with the prevalence of obesity among the US population.

Optimizing the resveratrol fragments for novel in silico hepatocellular carcinoma de novo drug design.

Hepatocellular carcinoma (HCC) incidence varies widely around the world and is impacted by factors such as the prevalence of chronic hepatitis B and C infections, alcohol intake, and access to healthcare. The proteins (BRAF_human, VGFR3_human, EGFR_human and UFO_human) play a vital role in hepatocellular carcinoma prognosis, which involves cell proliferation, cell growth, transmission of extracellular signals to the cell nucleus and consequently regulating many other cellular processes. Fostamatinib has been studied for its possible use in the treatment of hepatocellular cancer because it is a more convenient therapy choice for patients and has minor side effects on the human body. However, resveratrol phytochemical has been investigated for its potential use in the prevention and treatment of a wide range of disorders, including cancer, cardiovascular disease, diabetes, and neurological problems due to its frequently antioxidant, anti-inflammatory, and immune-modulating characteristics, which can aid in the prevention of chronic illnesses. This study developed de novo-based fragment-optimized resveratrol (FOR), enhancing therapeutic potential and lowering toxicity. The docking study was performed with four target proteins, and the findings reveal that the vascular endothelial growth factor receptor 3 protein possessed the highest binding energy values of -7.6 kcal/mol with FOR. Additionally, it completely fulfills the criteria of drug-likeliness rules. Thus, FOR proves to be an efficient drug candidate for future in-vivo studies against hepatocellular carcinoma.

Green extraction and application of yellow natural curcumin colorant from Curcuma aromatica rhizomes for silk dyeing.

Green products such as plant tints are becoming more and more well-known worldwide due to their superior biological and ayurvedic properties. In this work, colorant from Amba Haldi (Curcuma aromatica) was isolated using microwave (MW), and bio-mordants were added to produce colorfast shades. Response surface methodology was used to develop a central composite design (CCD), which maximizes coloring variables statistically. The findings from 32 series of experiments show that excellent color depth (K/S = 12.595) was established onto MW-treated silk fabric (RS = 4 min) by employing 65 mL of radiated aqueous extract (RE = 4 min) of 5 pH cutting-edge the existence of 1.5 g/100 mL used sodium chloride at 75 °C for 45 min. It was discovered that acacia (keekar) extract (1%), pomegranate extract (2%), and pistachio extract (1.5%) were present before coloring by the use of bio-mordants. On the other hand, upon dyeing, acacia extract (1.5%), pomegranate extract (1.5%), and pistachio extract (2%) have all shown extremely strong colorfast colors. Comparatively, before dyeing, salts of Al3+ (1.5%), Fe2+ (2%), and TA (1.5%) gave good results; after dyeing, salts of Al3+ (1%) and Fe2+ (1.5%) and TA (2%) gave good results. When applied to silk fabric, MW radiation has increased the production of dyes recovered from rhizomes. Additionally, the right amount of chemical and biological mordants have been added, resulting in color fastness ratings ranging from outstanding to good. Therefore, the natural color extracted from Amba Haldi can be a sustainable option for the dyeing of silk fabric in the textile dyeing and finishing industries.

Evaluating the MDCK cell permeability of greenly synthesize bimetallic Ag/Zn Nanoparticles using leaf extract of Vallaris solanacea as a potential antipesticide-resistant agent.

Bimetallic nanoparticles, particularly Ag/Zn bimetallic nanoparticles, have gained increasing attention due to their unique properties, making them suitable for a variety of applications such as catalysis, water treatment, and environmental remediation. This study aimed to elucidate the use of bimetallic nanoparticles of Ag/Zn as an alternative to resistant pesticides for pest control. Furthermore, this research demonstrates that BNPs can target specific pollutants and degrade them through various mechanisms. BNP docking with the Nilaparvata lugens cytochrome P450 (CYP6ER1) protein exhibited the lowest binding energy of -7.5 kcal/mol. The cell permeability analysis of BNP in plant cells reveals that the BNP has 0 % permeability towards any cell at -10 kcal/mol energy, which is the lowest free energy translocation pathway. The harmful leftover residues of the pesticides have a higher chance of degradability in case of interaction with BNP validated by chemical-chemical interaction analysis. Additionally, MDCK permeability coefficient of small molecules based on the regression model was calculated for BNP which authenticated the efficiency of BNP. Moreover, Swiss ADMET simulated absorption using a boiled egg model with no blood-brain barrier and gastrointestinal crossing for the expected BNP molecule has been observed. Significantly, the findings indicate that employing bimetallic nanoparticles like Ag/Zn is a crucial strategy for bioremediation because they proficiently decompose pesticides while posing no risk to humans. Our results will facilitate the design of novel BNPs materials for environmental remediation and pest control ensuring human health safety that are predicated on bimetallic nanoparticles.