Network-Derived Radioresistant Breast Cancer Target with Candidate Inhibitors from Brown Algae: A Sequential Assessment from Target Selection to Quantum Chemical Calculation.

Despite significant progress in early detection and treatment, a few aggressive breast cancers still exhibit resistance to therapy. This study aimed to identify a therapeutic target for radioresistant breast cancer (RRbc) through a protein network from breast cancer genes and to evaluate potent phytochemicals against the identified target. Our approach includes the integration of differential expression genes from expression datasets to create a protein network and to use survival analysis to identify the crucial RRbc protein in order to discover a therapeutic target. Next, the phytochemicals sourced from brown algae were screened through molecular docking, ADME (absorption, distribution, metabolism, and excretion), molecular dynamics (MD) simulation, MM-GBSA, and quantum mechanics against the identified target. As a result of our protein network investigation, the proto-oncogene c-KIT (KIT) protein was identified as a potent radioresistant breast cancer target. Further, phytochemical screening establishes that nahocol-A1 from brown algae has high binding characteristics (-8.56 kcal/mol) against the KIT protein. Then, quantum chemical analysis of nahocol-A1 provided insights into its electronic properties favorable for protein binding. Also, MD simulation comprehends the conformational stability of the KIT-nahocol-A1 complex. Overall, our findings suggest nahocol-A1 could serve as a promising therapeutic candidate for radioresistant breast cancer.

Multi-Target Effect of Aloeresin-A against Bacterial and Host Inflammatory Targets Benefits Contact Lens-Related Keratitis: A Multi-Omics and Quantum Chemical Investigation.

Contact lens-mediated microbial keratitis caused by Pseudomonas aeruginosa and Streptococcus pneumoniae provokes corneal damage and vision loss. Recently, natural phytochemicals have become complementary medicines for corneal destruction. Herein, we aimed to identify multi-targeting Aloe vera-derived phytochemicals capable of inhibiting bacterial and host targets of keratitis through ADME (absorption, distribution, metabolism, and excretion), docking, molecular dynamics (MD) simulation, MMGBSA (molecular mechanics generalized Born surface area) and density functional theory (DFT) investigations. An extensive literature search revealed ExoU, ExoS, ExoT, ExoY, and PLY as virulent bacterial targets. Simultaneously, differential gene expression (DGE) and pathway enrichment analysis-specified host transcription factor (SPI1) influences keratitis pathogenesis. Molecular docking analysis uncovered aloeresin-A as a promising inhibitor against bacterial and host targets, demonstrating strong binding energies ranging from -7.59 to -6.20 kcal/mol. Further, MMGBSA and MD simulation analysis reflect higher binding free energies and stable interactions of aloeresin-A with the targets. In addition, DFT studies reveal the chemical reactiveness of aloeresin-A through quantum chemical calculations. Hence, our findings show aloeresin-A to be a promising candidate for effectively inhibiting keratitis. However, additional research is imperative for potential integration into lens care solutions.

Structural Characteristics of PON1 with Leu55Met and Gln192Arg Variants Influencing Oxidative-Stress-Related Diseases: An Integrated Molecular Modeling and Dynamics Study.

Background and Objectives: PON1 is a multi-functional antioxidant protein that hydrolyzes a variety of endogenous and exogenous substrates in the human system. Growing evidence suggests that the Leu55Met and Gln192Arg substitutions alter PON1 activity and are linked with a variety of oxidative-stress-related diseases. Materials and Methods: We implemented structural modeling and molecular dynamics (MD) simulation along with essential dynamics of PON1 and molecular docking with their endogenous (n = 4) and exogenous (n = 6) substrates to gain insights into conformational changes and binding affinity in order to characterize the specific functional ramifications of PON1 variants. Results: The Leu55Met variation had a higher root mean square deviation (0.249 nm) than the wild type (0.216 nm) and Gln192Arg (0.202 nm), implying increased protein flexibility. Furthermore, the essential dynamics analysis confirms the structural change in PON1 with Leu55Met vs. Gln192Arg and wild type. Additionally, PON1 with Leu55Met causes local conformational alterations at the substrate binding site, leading to changes in binding affinity with their substrates. Conclusions: Our findings highlight the structural consequences of the variants, which would increase understanding of the role of PON1 in the pathogenesis of oxidative-stress-related diseases, as well as the management of endogenous and exogenous chemicals in the treatment of diseases.

Temporal changes of NF-κB signaling pathway genes in bacterial stimulated whole blood- a host mechanism associated with sepsis.

Bacterial sepsis affects both neonates and adults worldwide. There is no specific anti-sepsis treatment. Disease management mainly depends on early diagnosis. The gold standard blood culturing method is routinely practiced; it requires 24-48 h for confirmation. Understanding the disease mechanism may help in the early detection of sepsis. We studied the temporal change in NF-kB pathway genes in adult whole blood upon bacterial stimulations across time intervals (2-6 h). Four experimental conditions were investigated (1: Gram-positive, 2: Gram-negative, 3: Gram-positive + Gram-negative stimulated and compared with 4: un-stimulated group) to show host selection of canonical or non-canonical pathway against invading pathogens. Gene expression analysis showed significant variations (p < 0.5) in TLR2, TLR4, TRAF6, NIK, RelA, and RelB upon bacterial stimulants. Further, the correlation analysis showed the coherent behaviour of genes in selecting the canonical or non-canonical pathway. TLR2 sensed by gram-positive bacteria that immediately activates the canonical pathway through RelA, whereas other bacterial stimulants activate the non-canonical pathway via TLR4, NIK, and RelB. In addition, the inflammatory markers showed a significant increase in response to bacterial stimulants, suggesting the immediate activation of innate immunity. Overall, our results show the bacterial specific and time-dependent activation of the NF-kB pathway, which through a light towards the early detection of bacterial sepsis.

Molecular Regulator Driving Endometriosis Towards Endometrial Cancer: A Multi-Scale Computational Investigation to Repurpose Anti-Cancer drugs.

Endometriosis is a gynecological disorder among reproductive-aged women. Recent epidemiological investigations suggest endometriosis increases the risk of endometrial cancer. However, the molecular entity leading to endometriosis-to-endometrial cancer is largely unknown. This study aimed to combine a variety of computational approaches to identify the key therapeutic target promoting endometriosis-to-endometrial cancer and screen potential inhibitors against target to prevent cancer development. Our systematic investigations, includes transcriptomic profiling, protein network, pharmacophore modeling, docking, binding free energy calculation, dynamics simulation, and quantum mechanics. The gene expression analysis on endometriosis and endometrial cancer was performed and showed 108 shared upregulated genes in both conditions. Further construction of interaction network with 108 genes showed intercellular adhesion molecule 1 (ICAM1) to be a crucial molecule with a high degree of connectivity that influences vital mechanisms related to cancer pathways. We then generated ligand-based pharmacophore models using established ICAM1 inhibitors. Among the models, the ADRRR_8 pharmacophore exhibited a robust area under curve (AUC = 0.83), was employed to screen 1739 anti-cancer drugs. On screening, 421 anti-cancer drugs displayed ICAM1-inhibiting pharmacophore features. Further, the docking of 421 drugs with ICAM1 showed lanreotide (-7.80 kcal/mol) with better affinity than the reference ICAM1 inhibitor (-3.59 kcal/mol). Further validation though binding free energy and dynamics simulation of the lanreotide-ICAM1 complex showed a high binding affinity of -55.90 kcal/mol and contributed stable confirmation. According to quantum chemical calculations, lanreotide's electronic properties favour ICAM1 binding with highest occupied molecular orbital was -6.91 eV and lowest unoccupied molecular orbital was -3.93 eV. Our study supports using lanreotide to treat endometriosis, which could delay or prevent endometrial cancer. These predictions need to be confirmed and examined to determine the use of lanreotide in endometriosis treatment.

Dynamics of TUBB protein with five majorly occurring natural variants: a risk of cortical dysplasia.

Beta-tubulin (TUBB) protein is one of the components of the microtubule cytoskeleton that plays a critical role in the central nervous system. Genetic variants of TUBB cause cortical dysplasia, a developmental brain defect implicated in axonal guidance and the neuron migration. In this study, we assess pathogenic variants (Q15K, Y222F, M299V, V353I, and E401K) of TUBB protein and compared with non-pathogenic variant G235S to determine their impact on protein dynamic to cause cortical dysplasia. Among the analyzed variants, Q15K, Y222F, M299V, and E401K were noticed to have deleterious effect. Then, variant structures were modeled and their affinity with their known cofactor Guanosine-5'-triphosphate (GTP) was assessed which showed diverse binding energies ranged between (-7.436 to -6.950 kcal/mol) for the variants compared to wild-type (-7.428 kcal/mol). Finally, the molecular dynamics simulation of each variant was investigated which showed difference in trajectory between the pathogenic and non-pathogenic variant. Our analysis suggests change in amino acid residue of TUBB structure has notably affects the protein flexibility and their interactions with known cofactor. Overall, our findings provide insight on the relationship between TUBB variants and their structural dynamics that may cause diverse effects leading to cortical dysplasia.

Rheumatoid arthritis treatment with zoledronic acid, a potentialinhibitorofGWAS-derived pharmacogenetics STAT3 and IL2 targets.

Rheumatoid arthritis (RA) is an inflammatory condition that primarily affects the joints and progress to affect other vital organs. Variety of drugs are being recommended to control the disease progression that benefits patients to perform day-to-day activities. Few of these RA drugs have noticeable side effects; therefore, it's crucial to choose the appropriate drug for treating RA with an understanding of the disease's pathophysiology. Herein, we investigated the RA genes from GWAS data to construct protein-protein interaction (PPI) network and to define appropriate drug targets for RA. The predicted drug targets were screened with the known RA drugs based on molecular docking. Further, the molecular dynamics simulations were performed to comprehend the conformational changes and stability of the targets upon binding of the selected top ranked RA drug. As a result, our constructed protein network from GWAS data revealed, STAT3 and IL2 could be potential pharmacogenetics targets that interlink most of the RA genes encoding proteins. These interlinked proteins of both the targets showed involvement in cell signaling, immune response, and TNF signaling pathway. Among the 192 RA drugs investigated, zoledronic acid had the lowest binding energy that inhibit both STAT3 (-6.307 kcal/mol) and IL2 (-6.231 kcal/mol). Additionally, STAT3 and IL2 trajectories on zoledronic acid binding exhibit notable differences in MD simulations as compared to a drug-free environment. Also, the in vitro assessment with the zoledronic acid confirms the outcome of our computational study. Overall, our study identify zoledronic acid could be potential inhibitor against these targets, that will benefits patients with RA. Comparative efficiency assessments between the RA drugs through clinical trials are needed to validate our findings in the treatment of RA.

New Ways to Protect the Host from SARS-CoV-2? Lung Microbiome Metabolites Inhibit STAT3 and Modulate the Immunological Network.

COVID-19 caused by the SARS-CoV-2 infection is a systemic disease that affects multiple organs, biological pathways, and cell types. A systems biology approach would benefit the study of COVID-19 in the pandemic as well as the endemic state. Notably, patients with COVID-19 have dysbiosis of lung microbiota whose functional relevance to the host is largely unknown. We carried out a systems biology investigation of the impact of lung microbiome-derived metabolites on host immune system during COVID-19. RNAseq was performed to identify the host-specific pro- and anti-inflammatory differentially expressed genes (DEGs) in bronchial epithelium and alveolar cells during SARS-CoV-2 infection. The overlapping DEGs were harnessed to construct an immune network while their key transcriptional regulator was deciphered. We identified 68 overlapping genes from both cell types to construct the immune network, and Signal Transducer and Activator of Transcription 3 (STAT3) was found to regulate the majority of the network proteins. Furthermore, thymidine diphosphate produced from the lung microbiome had the highest affinity with STAT3 (-6.349 kcal/mol) than the known STAT3 inhibitors (n = 410), with an affinity ranging from -5.39 to 1.31 kcal/mol. In addition, the molecular dynamic studies showed distinguishable changes in the behavior of the STAT3 complex when compared with free STAT3. Overall, our results provide new observations on the importance of lung microbiome metabolites that regulate the host immune system in patients with COVID-19, and may open up new avenues for preventive medicine and therapeutics innovation.

Asn215Ser, Ala143Thr, and Arg112Cys variants in α-galactosidase A protein confer stability loss in Fabry's disease.

Alpha galactosidase A (α-GalA) gene contains nine exons localized at the q-arm of the X chromosome. Generally, an α-GalA enzyme is involved in the removal of galactosyl moieties from the glycoproteins and glycolipids. Dysregulation results in the accumulation of glycoproteins as well as glycolipids in various organs leading to Fabry disease (FD). In this study, we examine the impact of Asn215Ser, Ala143Thr and Arg112Cys variants on the α-GalA protein structure contributing to functional dynamic changes in FD. The seven computational pathogenicity prediction methods were used to predict the effects of these variants on the α-GalA protein. The three-dimensional structure of α-GalA variants was modeled with the Swiss Model and Robetta server and validated using a variety of tools. Then, molecular dynamics (MD) simulation was performed to understand the stability and dynamic behavior of the wild-type and variants structures. Most of our analyzed pathogenicity prediction tools showed that Asn215Ser, Ala143Thr and Arg112Cys variants cause a deleterious effect on the α-GalA protein. Further, MD trajectory analysis showed the destabilizing effect of variants on α-GalA structure based on the root mean square deviation, root mean square fluctuation, solvent accessible surface area, the radius of gyration, hydrogen bond, cluster analysis and PCA analysis. This concludes that the presence of these variants could potentially affect the protein functional process of galactosyl moieties removal which might lead to Fabry disease.Communicated by Ramaswamy H. Sarma.

Comparative Efficacy of Metformin and Glimepiride in Modulating Pharmacological Network to Increase BDNF Levels and Benefit Type 2 Diabetes-Related Cognitive Impairment.

Cognitive impairment is anotable complication of type 2 diabetes (T2DM), accompanied by reduced brain-derived neurotrophic factor (BDNF) in the brain and blood. Anti-diabetic drugs reduce hyperglycemia, yet their effect on cognitive improvement is unknown. We aimed to investigate the effect of anti-diabetic drugs regulating BDNF in T2DM through computational and case-control study design. We obtained T2DMproteins viatext-mining to construct a T2DMprotein network. From the T2DMnetwork, the metformin and glimepiride interactomes and their crucial shortest-path-stimulating BDNF were identified. Using qRTPCR, the genes encoding the shortest-path proteins were assessed in four groups (untreated-T2DM, metformin-treated, glimepiride-treated, and healthy controls). Finally, ELISA was used to assess serum BDNF levels to validate drug efficacy. As a result of this investigation, aT2DMnetwork was constructed with 3683 text-mined proteins. Then, the T2DMnetwork was explored to generate a metformin and glimepiride interactome that establishes the critical shortest-path for BDNF stimulation. Metformin stimulates BDNF via APP binding to the PRKAB1 receptor. Whereas, glimepiride increases BDNF by binding to KCNJ11 via AP2M1 and ESR1 proteins. Both drug shortest-path encoding genes differed significantly between the groups. Unlike metformin, BDNF gene and protein expression rise significantly with glimepiride. Overall, glimepiride can effectively increase BDNF, which could benefit T2DM patients with cognitive deterioration.

Elucidating the Histone Deacetylase Gene Expression Signatures in Peripheral Blood Mononuclear Cells That Correlate Essential Cardiac Function and Aid in Classifying Coronary Artery Disease through a Logistic Regression Model.

A proinflammatory role of HDACs has been implicated in the pathogenesis of atherosclerosis as an emerging novel epigenetic diagnostic biomarker. However, its association with the clinical and cardiovascular function in coronary artery disease is largely unknown. The study aimed to profile the gene expression of HDAC1-11 in human peripheral blood mononuclear cells and to evaluate their influence on hematological, biochemical, and two-dimensional echocardiographic indices in CAD. The HDAC gene expression profiles were assessed in 62 angioproven CAD patients and compared with 62 healthy controls. Among the HDACs, upregulated HDACs 1,2, 4, 6, 8, 9, and 11 were upregulated, and HDAC3 was downregulated, which was significantly (p ≤ 0.05) linked with the hematological (basophils, lymphocytes, monocytes, and neutrophils), biochemical (LDL, HDL, and TGL), and echocardiographic parameters (cardiac function: biplane LVEF, GLS, MV E/A, IVRT, and PV S/D) in CAD. Furthermore, our constructed diagnostic model with the crucial HDACs establishes the most crucial HDACs in the classification of CAD from control with an excellent accuracy of 88.6%. Conclusively, our study has provided a novel perspective on the HDAC gene expression underlying cardiac function that is useful in developing molecular methods for CAD diagnosis.

Screening of Crucial Cytosolicproteins Interconnecting the Endoplasmic Reticulum and Mitochondria in Parkinson's Disease and the Impact of Anti-Parkinson Drugs in the Preservation of Organelle Connectivity.

Mitochondrial dysfunction is well-established in Parkinson's disease (PD); however, its dysfunctions associating with cell organelle connectivity remain unknown. We aimed to establish the crucial cytosolic protein involved in organelle connectivity between mitochondria and the endopalmic reticulum (ER) through a computational approach by constructing an organelle protein network to extract functional clusters presenting the crucial PD protein connecting organelles. Then, we assessed the influence of anti-parkinsonism drugs (n = 35) on the crucial protein through molecular docking and molecular dynamic simulation and further validated its gene expression in PD participants under, istradefylline (n = 25) and amantadine (n = 25) treatment. Based on our investigation, D-aspartate oxidase (DDO )protein was found to be the critical that connects both mitochondria and the ER. Further, molecular docking showed that istradefylline has a high affinity (-9.073 kcal/mol) against DDO protein, which may disrupt mitochondrial-ER connectivity. While amantadine (-4.53 kcal/mol) shows negligible effects against DDO that contribute to conformational changes in drug binding, Successively, DDO gene expression was downregulated in istradefylline-treated PD participants, which elucidated the likelihood of an istradefylline off-target mechanism. Overall, our findings illuminate the off-target effects of anti-parkinsonism medications on DDO protein, enabling the recommendation of off-target-free PD treatments.

Pharmacoscreening, molecular dynamics, and quantum mechanics of inermin from Panax ginseng: a crucial molecule inhibiting exosomal protein target associated with coronary artery disease progression.

Background: Exosomes, microvesicles, carry and release several vital molecules across cells, tissues, and organs. Epicardial adipose tissue exosomes are critical in the development and progression of coronary artery disease (CAD). It is hypothesized that exosomes may transport causative molecules from inflamed tissue and deliver to the target tissue and progress CAD. Thus, identifying and inhibiting the CAD-associated proteins that are being transported to other cells via exosomes will help slow the progression of CAD. Methods: This study uses a systems biological approach that integrates differential gene expression in the CAD, exosomal cargo assessment, protein network construction, and functional enrichment to identify the crucial exosomal cargo protein target. Meanwhile, absorption, distribution, metabolism, and excretion (ADME) screening of Panax ginseng-derived compounds was conducted and then docked against the protein target to identify potential inhibitors and then subjected to molecular dynamics simulation (MDS) to understand the behavior of the protein-ligand complex till 100 nanoseconds. Finally, density functional theory (DFT) calculation was performed on the ligand with the highest affinity with the target. Results: Through the systems biological approach, Mothers against decapentaplegic homolog 2 protein (SMAD2) was determined as a potential target that linked with PI3K-Akt signaling, Ubiquitin mediated proteolysis, and the focal adhesion pathway. Further, screening of 190 Panax ginseng compounds, 27 showed drug-likeness properties. Inermin, a phytochemical showed good docking with -5.02 kcal/mol and achieved stability confirmation with SMAD2 based on MDS when compared to the known CAD drugs. Additionally, DFT analysis of inermin showed high chemical activity that significantly contributes to effective target binding. Overall, our computational study suggests that inermin could act against SMAD2 and may aid in the management of CAD.

Comparative assessment of anti-cancer drugs against NUDT15 variants to prevent leucopenia side effect in leukemia patients.

BACKGROUND: Human nucleotide triphosphate diphosphatase (NUDT15) is one of the essential proteins involved in the hydrolysis of anti-cancer drugs against leukemia. Polymorphisms in NUDT15 significantly affect the hydrolysis activity that leads to side effects, including leucopenia. Drugs having a better affinity with NUDT15 protein and contributing stable conformation may benefit patients from leucopenia. Most frequent NUDT15 polymorphisms causing structure variability and their association with leukemia were screened. The selected protein variants and anti-cancer drug structures were collected. Further, molecular docking was performed between drugs and NUDT15 variants along with the wild-type. Finally, molecular dynamics were executed for 100 ns to understand the stability of the protein with the anti-cancer drug based on molecular trajectories. RESULTS: Three-dimensional structures of NUDT15 wild, the most frequent variants (Val18Ile, Arg139Cys, and Arg139), and the anti-cancer drugs (azathioprine, mercaptopurine, and thioguanine) were selected and retrieved from structure databases. On molecular docking the binding energies of anti-cancer drugs against NUDT15 structures ranged from - 5.0 to - 5.9 kcal/mol. Among them, azathioprine showed the highest affinities (- 7.3 kcal/mol) for the wild and variant structures. Additionally, the molecular dynamics suggest all analyzed NUDT15 were stable with azathioprine based on the dynamic trajectories. CONCLUSION: Our results suggest azathioprine could be the preferable anti-cancer drug for the population with NUDT15 variants that could effectively be hydrolyzed as evidenced by molecular docking and dynamic simulation.

Virtual screening, molecular dynamics and density functional theory on pain inhibitors against TRPV1 associating inflammatory conditions.

Transient receptor potential vanilloid 1 protein (TRPV1) is expressed widely in skin and sensory neurons that contribute to pain/heat sensation in the human system. TRPV1 gene polymorphisms are susceptible to multiple diseases and it is considered a therapeutic target for various inflammatory conditions. Among the TRPV1 variants, rs8065080 (1911 A > G) plays a vital role in painful osteoarthritis and migraine. The presence of rs8065080 polymorphism may render drug efficacy. This study aimed to identify better antagonists against wild-type and variant TRPV1 that may help in the relief of pain/inflammation. We constructed suitable TRPV1 protein structures for wild-type and rs8065080 variant through a homology modelling approach. A total of 3363 anti-inflammatory compounds with high chemical diversity and good drug-like properties were collected and screened against the generated structures. Molecular docking showed that nobilamide B had the highest binding affinity (-5.83 kcal/mol) towards the wild-type. Whereas, isoquinoline analogue displayed highest binding potency with the variant TRPV1 (-11.65 kcal/mol). Besides those, C18H15F3N4O showed affinity towards both wild-type (-5.53 kcal/mol) and variant TRPV1 (-9.75 kcal/mol). Then, molecular dynamic simulation revealed stable conformation in wild-type and variant TRPV1 upon binding of nobilmaide B, isoquinoline analogue and C18H15F3N4O. Additionally, density functional theory (DFT) using B3LYP hybrid function showed high chemical reactiveness of nobilamie B, isoquinoline analogue and C18H15F3N4O. Overall, our systematic investigations provide, C18H15F3N4O could be a potential analgesic inhibiting both wild-type and variant TRPV1 against inflammatory conditions.

Eleven Crucial Pesticides Appear to Regulate Key Genes That Link MPTP Mechanism to Cause Parkinson's Disease through the Selective Degeneration of Dopamine Neurons.

Pesticides kill neurons, but the mechanism leading to selective dopaminergic loss in Parkinson's disease (PD) is unknown. Understanding the pesticide's effect on dopaminergic neurons (DA) can help to screen and treat PD. The critical uptake of pesticides by the membrane receptors at DA is hypothesized to activate a signaling cascade and accelerate degeneration. Using MPTP as a reference, we demonstrate the mechanisms of eleven crucial pesticides through molecular docking, protein networks, regulatory pathways, and prioritization of key pesticide-regulating proteins. Participants were recruited and grouped into control and PD based on clinical characteristics as well as pesticide traces in their blood plasma. Then, qPCR was used to measure pesticide-associated gene expression in peripheral blood mononuclear cells between groups. As a result of molecular docking, all eleven pesticides and the MPTP showed high binding efficiency against 274 membrane receptor proteins of DA. Further, the protein interaction networks showed activation of multiple signaling cascades through these receptors. Subsequent analysis revealed 31 biological pathways shared by all 11pesticides and MPTP that were overrepresented by 46 crucial proteins. Among these, CTNNB1, NDUFS6, and CAV1 were prioritized to show a significant change in gene expression in pesticide-exposed PD which guides toward therapy.

Identification of Cumin (Cuminum cyminum) MicroRNAs through Deep Sequencing and Their Impact on Plant Secondary Metabolism.

The pharmacological properties of plants lie in the content of secondary metabolites that are classified into different categories based on their biosynthesis, structures, and functions. MicroRNAs (miRNAs) are small non-coding RNA molecules that play crucial post-transcriptional regulatory roles in plants, including development and stress-response signaling; however, information about their involvement in secondary metabolism is still limited. Cumin is one of the most popular seeds from the plant Cuminum cyminum, with extensive applications in herbal medicine and cooking; nevertheless, no previous studies focus on the miRNA profile of cumin. In this study, the miRNA profile of C. cyminum and its association with the biosynthesis of secondary metabolites were determined using NGS technology. The sequencing data yielded 10,956,054 distinct reads with lengths ranging from 16 to 40 nt, of which 349 miRNAs were found to be conserved and 39 to be novel miRNAs. Moreover, this work identified 1959 potential target genes for C. cyminum miRNAs. It is interesting to note that several conserved and novel miRNAs have been found to specifically target important terpenoid backbone, flavonoid biosynthesis, and lipid/fatty acid pathways enzymes. We believe this investigation will aid in elucidating the implications of miRNAs in plant secondary metabolism.

Green remediation potential of immobilized oxidoreductases to treat halo-organic pollutants persist in wastewater and soil matrices - A way forward.

The alarming presence of hazardous halo-organic pollutants in wastewater and soils generated by industrial growth, pharmaceutical and agricultural activities is a major environmental concern that has drawn the attention of scientists. Unfortunately, the application of conventional technologies within hazardous materials remediation processes has radically failed due to their high cost and ineffectiveness. Consequently, the design of innovative and sustainable techniques to remove halo-organic contaminants from wastewater and soils is crucial. Altogether, these aspects have led to the search for safe and efficient alternatives for the treatment of contaminated matrices. In fact, over the last decades, the efficacy of immobilized oxidoreductases has been explored to achieve the removal of halo-organic pollutants from diverse tainted media. Several reports have indicated that these enzymatic constructs possess unique properties, such as high removal rates, improved stability, and excellent reusability, making them promising candidates for green remediation processes. Hence, in this current review, we present an insight of green remediation approaches based on the use of immobilized constructs of phenoloxidases (e.g., laccase and tyrosinase) and peroxidases (e.g., horseradish peroxidase, chloroperoxidase, and manganese peroxidase) for sustainable decontamination of wastewater and soil matrices from halo-organic pollutants, including 2,4-dichlorophenol, 4-chlorophenol, diclofenac, 2-chlorophenol, 2,4,6-trichlorophenol, among others.

Artificial Intelligence in the Diagnosis of Oral Diseases: Applications and Pitfalls.

Background: Machine learning (ML) is a key component of artificial intelligence (AI). The terms machine learning, artificial intelligence, and deep learning are erroneously used interchangeably as they appear as monolithic nebulous entities. This technology offers immense possibilities and opportunities to advance diagnostics in the field of medicine and dentistry. This necessitates a deep understanding of AI and its essential components, such as machine learning (ML), artificial neural networks (ANN), and deep learning (DP). Aim: This review aims to enlighten clinicians regarding AI and its applications in the diagnosis of oral diseases, along with the prospects and challenges involved. Review results: AI has been used in the diagnosis of various oral diseases, such as dental caries, maxillary sinus diseases, periodontal diseases, salivary gland diseases, TMJ disorders, and oral cancer through clinical data and diagnostic images. Larger data sets would enable AI to predict the occurrence of precancerous conditions. They can aid in population-wide surveillance and decide on referrals to specialists. AI can efficiently detect microfeatures beyond the human eye and augment its predictive power in critical diagnosis. Conclusion: Although studies have recognized the benefit of AI, the use of artificial intelligence and machine learning has not been integrated into routine dentistry. AI is still in the research phase. The coming decade will see immense changes in diagnosis and healthcare built on the back of this research. Clinical significance: This paper reviews the various applications of AI in dentistry and illuminates the shortcomings faced while dealing with AI research and suggests ways to tackle them. Overcoming these pitfalls will aid in integrating AI seamlessly into dentistry.

Identification of selected genes associated with the SARS-CoV-2: a therapeutic approach and disease severity.

BACKGROUND: The ongoing pandemic of COVID-19 viruses takes its sole origin from the Wuhan Huanan seafood market, China. The first case was recorded as viral pneumonia and later became a worldwide pandemic (officially declared by WHO on March 11, 2020). MAIN BODY: SARS-CoV-2 is an extremely infectious and transferrable virus that develops severe conditions like respiratory syndrome, high blood pressure and weakens the immune system. Coronavirus falls under the Coronaviridae family and Beta coronavirus genus. Affected individuals will encounter problems starting with fever followed by severe complications like SARS, ARDS, and many others. These SARS-CoV and MERS-CoV enter the host cells by the endosomal pathway, and about 16 non-structural proteins are involved in assembling the viral RNA synthesis complex. They possess a positive-sense single-stranded RNA, and about four major genes are mainly associated with the development of ASRD, SARS, and other respiratory problems. CONCLUSION: Susceptibility of these four major genes such as ACE2, IL-2, 7 and 10, TNF, and VEGF is associated with COVID-19. This highlights the identification of the above-mentioned genes that can be used as potential biomarkers for early diagnosis and targeted drug delivery for treating the SARS-CoV-2 neurological symptoms and reducing inflammation in the brain.