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Colonoscopy is a reliable diagnostic method to detect colorectal polyps early on and prevent colorectal cancer. The current examination techniques face a significant challenge of high missed rates, resulting in numerous undetected polyps and irregularities. Automated and real-time segmentation methods can help endoscopists to segment the shape and location of polyps from colonoscopy images in order to facilitate clinician's timely diagnosis and interventions. Different parameters like shapes, small sizes of polyps, and their close resemblance to surrounding tissues make this task challenging. Furthermore, high-definition image quality and reliance on the operator make real-time and accurate endoscopic image segmentation more challenging. Deep learning models utilized for segmenting polyps, designed to capture diverse patterns, are becoming progressively complex. This complexity poses challenges for real-time medical operations. In clinical settings, utilizing automated methods requires the development of accurate, lightweight models with minimal latency, ensuring seamless integration with endoscopic hardware devices. To address these challenges, in this study a novel lightweight and more generalized Enhanced Nanonet model, an improved version of Nanonet using NanonetB for real-time and precise colonoscopy image segmentation, is proposed. The proposed model enhances the performance of Nanonet using Nanonet B on the overall prediction scheme by applying data augmentation, Conditional Random Field (CRF), and Test-Time Augmentation (TTA). Six publicly available datasets are utilized to perform thorough evaluations, assess generalizability, and validate the improvements: Kvasir-SEG, Endotect Challenge 2020, Kvasir-instrument, CVC-ClinicDB, CVC-ColonDB, and CVC-300. Through extensive experimentation, using the Kvasir-SEG dataset, our model achieves a mIoU score of 0.8188 and a Dice coefficient of 0.8060 with only 132,049 parameters and employing minimal computational resources. A thorough cross-dataset evaluation was performed to assess the generalization capability of the proposed Enhanced Nanonet model across various publicly available polyp datasets for potential real-world applications. The result of this study shows that using CRF (Conditional Random Fields) and TTA (Test-Time Augmentation) enhances performance within the same dataset and also across diverse datasets with a model size of just 132,049 parameters. Also, the proposed method indicates improved results in detecting smaller and sessile polyps (flats) that are significant contributors to the high miss rates.
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Hepatitis C virus is a single-stranded RNA based virus which can cause chronic HCV and hepatocellular carcinoma. HCV genotype 3a has relatively higher rate of fibrosis progression, prevalence of steatosis and incidence of HCC. Despite HCVs variation in genomic sequence, the 5' untranslated region containing internal ribosome entry site (IRES) is highly conserved among all genotypes. It is responsible for translation and initiation of the viral protein. In present study, IRES was targeted by designing variants of reported antigen binding fragment (Fab) through affinity maturation approach. Affinity maturation strategy allowed the rational antibody designing with better biophysical properties and antibody-antigen binding interactions. Complementarity determining regions of reported Fab (wild type) were assessed and docked with IRES. Best generated model of Fab was selected and subjected to alanine scanning Three sets of insilico mutations for variants (V) designing were selected; single (1-71), double (a-j) and triple (I-X). Redocking of IRES-Fab variants consequently enabled the discovery of three variants exhibiting better docking score as compared to the wild type Fab. V1, V39 and V4 exhibited docking scores of -446.51, -446.52 and-446.29 kcal/mol respectively which is better as compared to the wild type Fab that exhibited the docking score of -351.23 kcal/mol. Variants exhibiting better docking score were screened for aggregation propensity by assessing the aggregation prone regions in Fab structure. Total A3D scores of wild type Fab, V1, V4 and V39 were predicted as -315.325, -312.727, -316.967 and -317.545 respectively. It is manifested that solubility of V4 and V39 is comparable to wild type Fab. In future, development and invitro assessment of these promising Fab HCV3 variants is aimed.
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Carcinoma Hepatocelular , Hepatitis C , Neoplasias Hepáticas , Humanos , Hepacivirus/genética , Sitios Internos de Entrada al Ribosoma , Anticuerpos , Regiones no Traducidas 5'RESUMEN
Plants require copper for normal growth and development and have evolved an efficient system for copper management based on transport proteins such as P1B-ATPases, also known as heavy metal ATPases (HMAs). Here, we report HMAs in eleven different Poaceae species, including wheat. Furthermore, the possible role of wheat HMAs in copper stress was investigated. BlastP searches identified 27 HMAs in wheat, and phylogenetic analysis based on the Maximum Likelihood method demonstrated a separation into four distinct clades. Conserved motif analysis, domain identification, gene structure, and transmembrane helices number were also identified for wheat HMAs using computational tools. Wheat seedlings grown hydroponically were subjected to elevated copper and demonstrated toxicity symptoms with effects on fresh weight and changes in expression of selected HMAs TaHMA7, TaHMA8, and TaHMA9 were upregulated in response to elevated copper, suggesting a role in wheat copper homeostasis. Further investigations on these heavy metal pumps can provide insight into strategies for enhancing crop heavy metal tolerance in the face of heavy metal pollution.
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Cobre , Metales Pesados , Cobre/toxicidad , Triticum/genética , Poaceae , Filogenia , Metales Pesados/toxicidad , Adenosina TrifosfatasasRESUMEN
Tripartite motifs (TRIM) is a large family of E3 ubiquitin ligases that play an important role in ubiquitylation. TRIM proteins regulate a wide range of biological processes from cellular response to viral infection and are implicated in various pathologies, from Mendelian disease to cancer. Although the TRIM family has been identified and characterized in tetrapods, but the knowledge about common carp and other teleost species is limited. The genes and proteins in the TRIM family of common carp were analyzed for evolutionary relationships, characterization, and functional annotation. Phylogenetic analysis was used to elucidate the evolutionary relationship of TRIM protein among teleost and higher vertebrate species. The results show that the TRIM orthologs of highly distant vertebrates have conserved sequences and domain architectures. The pairwise distance was calculated among teleost species of TRIMs, and the result exhibits very few mismatches at aligned position thus, indicating that the members are not distant from each other. Furthermore, TRIM family of common carp clustered into six groups on the basis of phylogenetic analysis. Additionally, the analysis revealed conserved motifs and functional domains in the subfamily members. The difference in functional domains and motifs is attributed to the evolution of these groups from different ancestors, thus validating the accuracy of clusters in the phylogenetic tree. However, the intron-exon organization is not precisely similar, which suggests duplication of genes and complex alternative splicing. The percentage of secondary structural elements is comparable for members of the same group, but the tertiary conformation is varied and dominated by coiled-coil segments required for catalytic activity. Gene ontology analysis revealed that these proteins are mainly associated with the catalytic activity of ubiquitination, immune system, zinc ion binding, positive regulation of transcription, ligase activity, and cell cycle regulation. Moreover, the biological pathway analyses identified four KEGG and 22 Reactome pathways. The predicted pathways correspond to functional domains, and gene ontology which proposes that proteins with similar structures might perform the same functions.
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Carpas , Animales , Carpas/genética , Filogenia , Ubiquitina-Proteína Ligasas/metabolismo , Ubiquitinación/genética , Proteínas/genética , Genómica , Proteínas de Motivos Tripartitos/genéticaRESUMEN
Salinity severely affects crop yield by hindering nitrogen uptake and reducing plant growth. Plant growth-promoting bacteria (PGPB) are capable of providing cross-protection against biotic/abiotic stresses and facilitating plant growth. Genome-level knowledge of PGPB is necessary to translate the knowledge into a product as efficient biofertilizers and biocontrol agents. The current study aimed to isolate and characterize indigenous plant growth-promoting strains with the potential to promote plant growth under various stress conditions. In this regard, 72 bacterial strains were isolated from various saline-sodic soil/lakes; 19 exhibited multiple in vitro plant growth-promoting traits, including indole 3 acetic acid production, phosphate solubilization, siderophore synthesis, lytic enzymes production, biofilm formation, and antibacterial activities. To get an in-depth insight into genome composition and diversity, whole-genome sequence and genome mining of one promising Bacillus paralicheniformis strain ES-1 were performed. The strain ES-1 genome carries 12 biosynthetic gene clusters, at least six genomic islands, and four prophage regions. Genome mining identified plant growth-promoting conferring genes such as phosphate solubilization, nitrogen fixation, tryptophan production, siderophore, acetoin, butanediol, chitinase, hydrogen sulfate synthesis, chemotaxis, and motility. Comparative genome analysis indicates the region of genome plasticity which shapes the structure and function of B. paralicheniformis and plays a crucial role in habitat adaptation. The strain ES-1 has a relatively large accessory genome of 649 genes (~ 19%) and 180 unique genes. Overall, these results provide valuable insight into the bioactivity and genomic insight into B. paralicheniformis strain ES-1 with its potential use in sustainable agriculture.
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Bacillus , Sideróforos , Sideróforos/genética , Bacillus/genética , Bacterias/genética , Cloruro de Sodio , Antibacterianos , Fosfatos/farmacologíaRESUMEN
Background: Breast cancer is the second leading cause of cancer-related deaths globally, and its prevalence rates are increasing daily. In the past, studies predicting therapeutic drug targets for cancer therapy focused on the assumption that one gene is responsible for producing one protein. Therefore, there is always an immense need to find promising and novel anti-cancer drug targets. Furthermore, proteases have an integral role in cell proliferation and growth because the proteolysis mechanism is an irreversible process that aids in regulating cellular growth during tumorigenesis. Therefore, an inactive rhomboid protease known as iRhom2 encoded by the gene RHBDF2 can be considered an important target for cancer treatment. Speculatively, previous studies on gene expression analysis of RHBDF2 showed heterogenous behaviour during tumorigenesis. Consistent with this, several studies have reported the antagonistic role of iRhom2 in tumorigenesis, i.e., either they are involved in negative regulation of EGFR ligands via the ERAD pathway or positively regulate EGFR ligands via the EGFR signalling pathway. Additionally, different opinions suggest iRhom2 mediated cleavage of EGFR ligands takes place TACE dependently or TACE independently. However, reconciling these seemingly opposing roles is still unclear and might be attributed to more than one transcript isoform of iRhom2. Methods: To observe the differences at isoform resolution, the current strategy identified isoform switching in RHBDF2 via differential transcript usage using RNA-seq data during breast cancer initiation and progression. Furthermore, interacting partners were found via correlation and enriched to explain their antagonistic role. Results: Isoform switching was observed at DCIS, grade 2 and grade 3, from canonical to the cub isoform. Neither EGFR nor ERAD was found enriched. However, pathways leading to TACE-dependent EGFR signalling pathways were more observant, specifically MAPK signalling pathways, GPCR signalling pathways, and toll-like receptor pathways. Nevertheless, it was noteworthy that during CTCs, the cub isoform switches back to the canonical isoform, and the proteasomal degradation pathway and cytoplasmic ribosomal protein pathways were significantly enriched. Therefore, it could be inferred that cub isoform functions during cancer initiation in EGFR signalling. In contrast, during metastasis, where invasion is the primary task, the isoform switches back to the canonical isoform.
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Neoplasias de la Mama , Proteínas Portadoras , Humanos , Femenino , Proteínas Portadoras/genética , Neoplasias de la Mama/genética , Receptores ErbB/genética , Isoformas de Proteínas/genética , Carcinogénesis , Péptidos y Proteínas de Señalización Intracelular/metabolismoRESUMEN
Alzheimer's is a type of dementia that affects the affected person's thinking, memory, and behavior. It is a multifactorial disease, developed by the breakdown of the neurotransmitter acetylcholine via acetylcholinesterase (AChE). The present study was designed to evaluate potential inhibitors of acetylcholinesterase that could be used as a therapeutic agent against Alzheimer's disease (AD). For this course, synthetic compounds of the Schiff bases class of 2-mercaptobenzimidazole hydrazone derivatives (9-14) were determined to be potent acetylcholinesterase inhibitors with IC50 values varying between 37.64 ± 0.2 and 74.76 ± 0.3 µM. The kinetic studies showed that these are non-competitive inhibitors of AChE. Molecular docking studies revealed that all compounds accommodate well in the active site and are stabilized by hydrophobic interactions and hydrogen bonding. Molecular dynamics (MD) simulations of selected potent inhibitors confirm their stability in the active site of the enzyme. Moreover, all compounds showed antispasmodic and Ca2+ antagonistic activities. Among the selected compounds of 2-mercaptobenzimidazole hydrazone derivatives, compound 11 exhibited the highest activity on spontaneous and K+-induced contractions, followed by compound 13. Therefore, the Ca2+ antagonistic, AChE inhibition potential, and safety profile of these compounds in the human neutrophil viability assay make them potential drug candidates against AD in the future.
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Sphingomyelin (SM) belongs to a class of lipids termed sphingolipids. The disruption in the sphingomyelin signaling pathway is associated with various neurodegenerative disorders. TNF-α, a potent pro-inflammatory cytokine generated in response to various neurological disorders like Alzheimer's disease (AD), Parkinson's disease (PD), and Multiple Sclerosis (MS), is an eminent regulator of the sphingomyelin metabolic pathway. The immune-triggered regulation of the sphingomyelin metabolic pathway via TNF-α constitutes the sphingomyelin signaling pathway. In this pathway, sphingomyelin and its downstream sphingolipids activate various signaling cascades like PI3K/AKT and MAPK/ERK pathways, thus, controlling diverse processes coupled with neuronal viability, survival, and death. The holistic analysis of the immune-triggered sphingomyelin signaling pathway is imperative to make necessary predictions about its pivotal components and for the formulation of disease-related therapeutics. The current work offers a comprehensive in silico systems analysis of TNF-α mediated sphingomyelin and downstream signaling cascades via a model-based quantitative approach. We incorporated the intensity values of genes from the microarray data of control individuals from the AD study in the input entities of the pathway model. Computational modeling and simulation of the inflammatory pathway enabled the comprehensive study of the system dynamics. Network and sensitivity analysis of the model unveiled essential interaction parameters and entities during neuroinflammation. Scanning of the key entities and parameters allowed us to determine their ultimate impact on neuronal apoptosis and survival. Moreover, the efficacy and potency of the FDA-approved drugs, namely Etanercept, Nivocasan, and Scyphostatin allowed us to study the model's response towards inhibition of the respective proteins/enzymes. The network analysis revealed the pivotal model entities with high betweenness and closeness centrality values including recruit FADD, TNFR_TRADD, act CASP2, actCASP8, actCASP3 and 9, cytochrome C, and RIP_RAIDD which profoundly impacted the neuronal apoptosis. Whereas some of the entities with high betweenness and closeness centrality values like Gi-coupled receptor, actS1PR, Sphingosine, S1P, actAKT, and actERK produced a high influence on neuronal survival. However, the current study inferred the dual role of ceramide, both on neuronal survival and apoptosis. Moreover, the drug Nivocasan effectively reduces neuronal apoptosis via its inhibitory mechanism on the caspases.
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Enhancement of glycolysis and glutaminolysis are the two most common modalities associated with metabolic reprogramming in rheumatoid arthritis (RA). This enhancement is concomitant to the upregulation of hexokinase 2 (HK2) and glutaminase 1 (GLS1). Hence, the current study was undertaken to identify potential phytobiological inhibitors against HK2 and GLS1, from Dracaena (Sansevieria) trifasciata, an indigenous ethnomedicinal plant found in Pakistan, using computational analysis. Phytobiologics from Dracaena trifasciata were assessed for their ability to co-inhibit HK2 and GLS1 via molecular docking and molecular dynamics simulations. The results underscored seven phytobiologics with promising binding affinities for both HK2 and GLS1. Molecular dynamics simulations further elucidated that all seven identified phytobiologics inhibited HK2 by forming stable complexes but only five amongst the seven had the potential to form stable complexes with GLS1 in real time, thereby implying the potential of co-inhibition for these five compounds. Compound 28MS exhibited an equally strong binding profile for both HK2 (-8.19 kcal/mol) and GLS1 (-8.99 kcal/mol). Furthermore, it exhibited a similar trend in stability during simulation for both targets. Our results serve as a primer for a more lucid understanding towards co-inhibition of HK2 and GLS1 using multiple computational approaches. The identified phytobiologics should undergo in-vitro and in-vivo validation to corroborate their therapeutic potential in RA.
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Introduction: Several studies revealed that alcohol utilization impairs memory in adults; however, the underlying mechanism is still unclear. The production of inflammatory markers and reactive oxygen species (ROS) plays a major role in neurodegeneration, which leads to memory impairment. Therefore, targeting neuroinflammation and oxidative distress could be a useful strategy for abrogating the hallmarks of ethanol-induced neurodegeneration. Moreover, several studies have demonstrated multiple biological activities of thiazolidine derivatives including neuroprotection. Methods: In the current study, we synthesized ten (10) new thiazolidine-4-carboxylic acid derivatives (P1-P10), characterized their synthetic properties using proton nuclear magnetic resonance (1H-NMR) and carbon-13 NMR, and further investigated the neuroprotective potential of these compounds in an ethanol-induced neuroinflammation model. Results: Our results suggested altered levels of antioxidant enzymes associated with an elevated level of tumor necrosis factor-alpha (TNF-α), nuclear factor-κB (p-NF-κB), pyrin domain-containing protein 3 (NLRP3), and cyclooxygenase-2 (COX-2) in ethanol-treated animals. Ethanol treatment also led to memory impairment in rats, as assessed by behavioral tests. To further support our notion, we performed molecular docking studies, and all synthetic compounds exhibited a good binding affinity with a fair bond formation with selected targets (NF-κB, TLR4, NLRP3, and COX-2). Discussion: Overall, our results revealed that these derivatives may be beneficial in reducing neuroinflammation by acting on different stages of inflammation. Moreover, P8 and P9 treatment attenuated the neuroinflammation, oxidative stress, and memory impairment caused by ethanol.
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Chemotherapy resistance and peculiar tumor microenvironment, which diminish or mitigate the effects of therapies, make pancreatic cancer one of the deadliest malignancies to manage and treat. Advanced immunotherapies are under consideration intending to ameliorate the overall patient survival rate in pancreatic cancer. Oncolytic viruses therapy is a new type of immunotherapy in which a virus after infecting and lysis the cancer cell induces/activates patients' immune response by releasing tumor antigen in the blood. The current review covers the pathways and molecular ablation that take place in pancreatic cancer cells. It also unfolds the extensive preclinical and clinical trial studies of oncolytic viruses performed and/or undergoing to design an efficacious therapy against pancreatic cancer.
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The diverse pharmacological role of dihydropyrimidinone scaffold has made it to be an interesting drug target. Because of the high incidence and mortality rate of breast cancer, there is a dire need of discovering new pharmacotherapeutic agents in managing this disease. A series of twenty-two derivatives of 6-(chloromethyl)-4-(4-hydroxyphenyl)-2-oxo-1,2,3,4-tetrahydropyrimidine-5-carboxylate (3a-3k) and ethyl 6-(chloromethyl)-4-(2-hydroxyphenyl)-2-oxo-1,2,3,4-tetrahydropyrimidine-5-carboxylate (4a-4k) synthesized in a previous study were evaluated for their anticancer potential against breast cancer cell line. Molecular docking studies were performed to analyze the binding mode and interaction pattern of these compounds against nine breast cancer target proteins. The in vitro cell proliferation assay was performed against the breast cancer cell line MCF-7. The structure activity relationship of these compounds was further studied using QSARINS. Among nine proteins, the docking analysis revealed efficient binding of compounds 4f, 4e, 3e, 4g, and 4h against all target proteins. The in vitro cytotoxic assay revealed significant anticancer activity of compound 4f having IC50 of 2.15 µM. The compounds 4e, 3e, 4g, and 4h also showed anticancer activities with IC50 of 2.401, 2.41, 2.47 and 2.33 µM, respectively. The standard tamoxifen showed IC50 1.88 µM. The 2D qualitative structure-activity relationship (QSAR) analysis was also carried out to identify potential breast cancer targets through QSARINS. The final QSAR equation revealed good predictivity and statistical validation R 2 and Q 2 values for the model obtained from QSARINS was 0.98 and 0.97, respectively. The active compounds showed very good anticancer activities, and the binding analysis has revealed stable hydrogen bonding of these compounds with the target proteins. Moreover, the QSAR analysis has predicted useful information on the structural requirement of these compounds as anticancer agents with the importance of topological and autocorrelated descriptors in effecting the cancer activities.
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This study seeks to investigate the interaction profile of the L5 protein of oncolytic adenovirus with the overexpressed surface receptors of pancreatic cancer. This is an important area of research because pancreatic cancer is one of the most fatal malignancies with a very low patient survival rate. Multiple therapies to date to improve the survival rate are reported; however, they show a comparatively low success rate. Among them, oncolytic virus therapy is a type of immunotherapy that is currently under deliberation by researchers for multiple cancer types in various clinical trials. Talimogene laherparepvec (T-VEC) is the first oncolytic virus approved by the US Food and Drug Administration (FDA) for melanoma. The oncolytic virus not only kills cancer cells but also activates the anticancer immune response. Therefore, it is preferred over others to deal with aggressive pancreatic cancer. The efficacy of therapy primarily depends on how effectively the oncolytic virus enters and infects the cancer cell. Cell surface receptors and their interactions with virus coat proteins are a crucial step for oncolytic virus entry and a pivotal determinant. The L5 proteins of the virus coat are the first to interact with host cell surface receptors. Therefore, the objective of this study is to analyze the interaction profile of the L5 protein of oncolytic adenovirus with overexpressed surface receptors of pancreatic cancer. The L5 proteins of three adenovirus serotypes HAdV2, HAdV5, and HAdV3 were utilized in this study. Overexpressed pancreatic cancer receptors include SLC2A1, MET, IL1RAP, NPR3, GABRP, SLC6A6, and TMPRSS4. The protein structures of viral and cancer cell protein were docked using the High Ambiguity Driven protein-protein DOCKing (HADDOCK) server. The binding affinity and interaction profile of viral proteins against all the receptors were analyzed. Results suggest that the HAdV3 L5 protein shows better interaction as compared to HAdV2 and HAdV5 by elucidating high binding affinity with 4 receptors (NPR3, GABRP, SLC6A6, and TMPRSS4). The current study proposed that HAdV5 or HAdV2 virus pseudotyped with the L5 protein of HAdV3 can be able to effectively infect pancreatic cancer cells. Moreover, the current study surmises that the affinity maturation of HAdV3 L5 can enhance virus attachment with all the receptors of cancer cells.
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OBJECTIVES: The present study describes the draft genome sequence of a novel Bacillus sp. strain SD-4 isolated from animal feed. The study aims to get a deeper insight into antimicrobial resistance and secondary metabolite biosynthetic gene clusters (BGCs) and the association between them. METHODS: The strain SD-4 was preliminarily evaluated for antibacterial activities, motility, biofilm formation, and enterotoxin production using in vitro assays. The genome of strain SD-4 was sequenced using the Illumina HiSeq 2500 platform with paired-end reads. The reads were assembled and annotated using SPAdes and PGAP, respectively. The genome was further analysed using several bioinformatics tools, including TYGS, AntiSMASH, RAST, PlasmidFinder, VFDB, VirulenceFinder, CARD, PathogenFinder, MobileElement finder, IslandViewer, and CRISPRFinder. RESULTS: In vitro assays showed that the strain is motile, synthesises biofilm, and produces an enterotoxin and antibacterial metabolites. The genome analysis revealed that the strain SD-4 carries antimicrobial resistance genes (ARGs), virulence factors, and beneficial secondary metabolite BGCs. Further genome analysis showed interesting genome architectures containing several mobile genetic elements, including two plasmid replicons (repUS22 and rep20), five prophages, and at least four genomic islands (GIs), including one Listeria pathogenicity island LIPI-1. Moreover, the strain SD-4 is identified as a putative human pathogen. CONCLUSION: The genome of strain SD-4 harbours several BGCs coding for biologically active metabolites. It also contains antimicrobial resistance genes and is identified as a potential human pathogen. These results can be used to better comprehend antibiotic resistance in environmental bacteria that are not influenced by human intervention.
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Bacillus , Alimentación Animal , Animales , Antibacterianos/farmacología , Bacillus/genética , Bovinos , Enterotoxinas , Genoma BacterianoRESUMEN
A variety of diarylpyrazole derivatives III-VI were synthesized and structurally characterized using FTIR, 1H and 13C NMR spectroscopy, and in case of compound VIb by X-ray single crystal analysis. The in vitro biological studies revealed that seven of the diarylpyrazole derivatives IIIa, IIIb, IIId, IIIe, IVa, IVb and IVd are highly potent inhibitors of acetylcholinesterase enzyme with IC50 values of 0.48 ± 0.092 µg/mL, 0.45 ± 0.093 µg/mL, 0.30 ± 0.014 µg/mL, 0.59 ± 0.072 µg/mL, 0.29 ± 0.084 µg/mL, 0.56 ± 0.010 µg/mL and 0.28 ± 0.096 µg/mL, respectively. All these seven products were more potent than the standard drug, donepezil (IC50 = 0.73 ± 0.015 µg/mL), while compounds IIIc (0.67 ± 0.099 µg/ml) and VIa (0.66 ± 0.069 µg/ml) are almost equipotent to the donepezil. Particularly, compounds IVa and IVd are highly active acetylcholinesterase enzyme inhibitors, demonstrating more than two-fold inhibitory activity than the reference inhibitor. Molecular docking studies were carried out to identify the possible binding modes of the diarylpyrazoles within the active pocket of the enzymes. The docking interactions of the synthesized compounds with acetylcholinesterase also provided high docking scores. These results clearly indicate the potential of these compound as powerful lead molecules for further investigations.
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Acetilcolinesterasa , Inhibidores de la Colinesterasa , Acetilcolinesterasa/metabolismo , Inhibidores de la Colinesterasa/química , Donepezilo , Simulación del Acoplamiento Molecular , Estructura Molecular , Relación Estructura-ActividadRESUMEN
BACKGROUND: Cotton leaf curl disease (CLCuD) is a disease of cotton caused by begomoviruses, leading to a drastic loss in the annual yield of the crop. Pakistan has suffered two epidemics of this disease leading to the loss of billions in annual exports. The speculation that a third epidemic of CLCuD may result as consequence of the frequent occurrence of Tomato leaf curl New Delhi virus (ToLCNDV) and Cotton leaf curl Kokhran Virus-Burewala Strain (CLCuKoV-Bu) in CLCuD infected samples, demand that the interactions taking between the two viruses be properly evaluated. This study is designed to assess virus-virus interactions at the molecular level and determine the type of co-infection taking place. METHODS: Based on the amino acid sequences of the gene products of both CLCuKoV-Bu and ToLCNDV, protein structures were generated using different software, i.e., MODELLER, I-TASSER, QUARKS, LOMETS and RAPTORX. A consensus model for each protein was selected after model quality assessment using ERRAT, QMEANDisCo, PROCHECK Z-Score and Ramachandran plot analysis. The active and passive residues in the protein structures were identified using the CPORT server. Protein-Protein Docking was done using the HADDOCK webserver, and 169 Protein-Protein Interaction (PPIs) were performed between the proteins of the two viruses. The docked complexes were submitted to the PRODIGY server to identify the interacting residues between the complexes. The strongest interactions were determined based on the HADDOCK Score, Desolvation energy, Van der Waals Energy, Restraint Violation Energy, Electrostatic Energy, Buried Surface Area and Restraint Violation Energy, Binding Affinity and Dissociation constant (Kd). A total of 50 ns Molecular Dynamic simulations were performed on complexes that exhibited the strongest affinity in order to validate the stability of the complexes, and to remove any steric hindrances that may exist within the structures. RESULTS: Our results indicate significant interactions taking place between the proteins of the two viruses. Out of all the interactions, the strongest were observed between the Replication Initiation protein (Rep) of CLCuKoV-Bu with the Movement protein (MP), Nuclear Shuttle Protein (NSP) of ToLCNDV (DNA-B), while the weakest were seen between the Replication Enhancer protein (REn) of CLCuKoV-Bu with the REn protein of ToLCNDV. The residues identified to be taking a part in interaction belonged to domains having a pivotal role in the viral life cycle and pathogenicity. It maybe deduced that the two viruses exhibit antagonistic behavior towards each other, and the type of infection may be categorised as a type of Super Infection Exclusion (SIE) or homologous interference. However, further experimentation, in the form of transient expression analysis, is needed to confirm the nature of these interactions and increase our understanding of the direct interactions taking place between two viruses.
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Pancreatic cancer (PaCa) is the seventh most fatal malignancy, with more than 90% mortality rate within the first year of diagnosis. Its treatment can be improved the identification of specific therapeutic targets and their relevant pathways. Therefore, the objective of this study is to identify cancer specific biomarkers, therapeutic targets, and their associated pathways involved in the PaCa progression. RNA-seq and microarray datasets were obtained from public repositories such as the European Bioinformatics Institute (EBI) and Gene Expression Omnibus (GEO) databases. Differential gene expression (DE) analysis of data was performed to identify significant differentially expressed genes (DEGs) in PaCa cells in comparison to the normal cells. Gene co-expression network analysis was performed to identify the modules co-expressed genes, which are strongly associated with PaCa and as well as the identification of hub genes in the modules. The key underlaying pathways were obtained from the enrichment analysis of hub genes and studied in the context of PaCa progression. The significant pathways, hub genes, and their expression profile were validated against The Cancer Genome Atlas (TCGA) data, and key biomarkers and therapeutic targets with hub genes were determined. Important hub genes identified included ITGA1, ITGA2, ITGB1, ITGB3, MET, LAMB1, VEGFA, PTK2, and TGFß1. Enrichment analysis characterizes the involvement of hub genes in multiple pathways. Important ones that are determined are ECM-receptor interaction and focal adhesion pathways. The interaction of overexpressed surface proteins of these pathways with extracellular molecules initiates multiple signaling cascades including stress fiber and lamellipodia formation, PI3K-Akt, MAPK, JAK/STAT, and Wnt signaling pathways. Identified biomarkers may have a strong influence on the PaCa early stage development and progression. Further, analysis of these pathways and hub genes can help in the identification of putative therapeutic targets and development of effective therapies for PaCa.
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Psoriasis is the most common and chronic skin disease that affects individuals from every age group. The rate of psoriasis is increasing over the time in both developed and developing countries. Studies have revealed the possibility of association of psoriasis with skin cancers, particularly non-melanoma skin cancers (NMSC), which, include basal cell carcinoma and cutaneous squamous cell carcinoma (cSCC). There is a need to analyze the disease at molecular level to propose potential biomarkers and therapeutic targets in comparison to cSCC. Therefore, the second analyzed disease of this study is cSCC. It is the second most common prevalent skin cancer all over the world with the potential to metastasize and recur. There is an urge to validate the proposed biomarkers and discover new potential biomarkers as well. In order to achieve the goals and objectives of the study, microarray and RNA-sequencing data analyses were performed followed by network analysis. Afterwards, quantitative systems biology was implemented to analyze the results at a holistic level. The aim was to predict the molecular patterns that can lead psoriasis to cancer. The current study proposed potential biomarkers and therapeutic targets for psoriasis and cSCC. IL-17 signaling pathway is also identified as significant pathway in both diseases. Moreover, the current study proposed that autoimmune pathology, neutrophil recruitment, and immunity to extracellular pathogens are sensitive towards MAPKs (MAPK13 and MAPK14) and genes for AP-1 (FOSL1 and FOS). Therefore, these genes should be further studied in gene knock down based studies as they may play significant role in leading psoriasis towards cancer.
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Carcinoma de Células Escamosas/genética , Psoriasis/genética , Neoplasias Cutáneas/genética , Biología de Sistemas/métodos , Biomarcadores/análisis , Biomarcadores de Tumor/genética , Carcinoma de Células Escamosas/diagnóstico , Carcinoma de Células Escamosas/etiología , Regulación Neoplásica de la Expresión Génica , Humanos , Análisis por Micromatrices , Recurrencia Local de Neoplasia , Psoriasis/complicaciones , Psoriasis/diagnóstico , Neoplasias Cutáneas/diagnósticoRESUMEN
Breast cancer is among the lethal types of cancer with a high mortality rate, globally. Its high prevalence can be controlled through improved analysis and identification of disease-specific biomarkers. Recently, long non-coding RNAs (lncRNAs) have been reported as key contributors of carcinogenesis and regulate various cellular pathways through post-transcriptional regulatory mechanisms. The specific aim of this study was to identify the novel interactions of aberrantly expressed genetic components in breast cancer by applying integrative analysis of publicly available expression profiles of both lncRNAs and mRNAs. Differential expression patterns were identified by comparing the breast cancer expression profiles of samples with controls. Significant co-expression networks were identified through WGCNA analysis. WGCNA is a systems biology approach used to elucidate the pattern of correlation between genes across microarray samples. It is also used to identify the highly correlated modules. The results obtained from this study revealed significantly differentially expressed and co-expressed lncRNAs and their cis- and trans-regulating mRNA targets which include RP11-108F13.2 targeting TAF5L, RPL23AP2 targeting CYP4F3, CYP4F8 and AL022324.2 targeting LRP5L, AL022324.3, and Z99916.3, respectively. Moreover, pathway analysis revealed the involvement of identified mRNAs and lncRNAs in major cell signalling pathways, and target mRNAs expression is also validated through cohort data. Thus, the identified lncRNAs and their target mRNAs represent novel biomarkers that could serve as potential therapeutics for breast cancer and their roles could also be further validated through wet labs to employ them as potential therapeutic targets in future.
Asunto(s)
Neoplasias de la Mama , ARN Largo no Codificante , Biomarcadores , Neoplasias de la Mama/genética , Femenino , Perfilación de la Expresión Génica , Regulación de la Expresión Génica , Redes Reguladoras de Genes , Humanos , ARN Largo no Codificante/genética , ARN Mensajero/genéticaRESUMEN
The CRISPR-Cas9 system has recently evolved as a powerful mutagenic tool for targeted genome editing. The impeccable functioning of the system depends on the optimal design of single guide RNAs (sgRNAs) that mainly involves sgRNA specificity and on-target cleavage efficacy. Several research groups have designed algorithms and models, trained on mammalian genomes, for predicting sgRNAs cleavage efficacy. These models are also implemented in most plant sgRNA design tools due to the lack of on-target cleavage efficacy studies in plants. However, one of the major drawbacks is that almost all of these models are biased for considering only coding regions of the DNA while excluding ineffective regions, which are of immense importance in functional genomics studies especially for plants, thus making prediction less reliable. In the present study, we evaluate the on-target cleavage efficacy of experimentally validated sgRNAs designed against diverse ineffective regions of Arabidopsis thaliana genome using various statistical tests. We show that nucleotide preference in protospacer adjacent motif (PAM) proximal region, GC content in the PAM proximal seed region, intact RAR and 3rd stem loop structures, and free accessibility of nucleotides in seed and tracrRNA regions of sgRNAs are important determinants associated with their high on-target cleavage efficacy. Thus, our study describes the features important for plant sgRNAs high on-target cleavage efficacy against ineffective genomic regions previously shown to give rise to ineffective sgRNAs. Moreover, it suggests the need of developing an elaborative plant-specific sgRNA design model considering the entire genomic landscape including ineffective regions for enabling highly efficient genome editing without wasting time and experimental resources.