Phytoconstituents of Artemisia Annua as potential inhibitors of SARS CoV2 main protease: an in silico study.

BACKGROUND: In November 2019, the world faced a pandemic called SARS-CoV-2, which became a major threat to humans and continues to be. To overcome this, many plants were explored to find a cure. METHODS: Therefore, this research was planned to screen out the active constituents from Artemisia annua that can work against the viral main protease Mpro as this non-structural protein is responsible for the cleavage of replicating enzymes of the virus. Twenty-five biocompounds belonging to different classes namely alpha-pinene, beta-pinene, carvone, myrtenol, quinic acid, caffeic acid, quercetin, rutin, apigenin, chrysoplenetin, arteannunin b, artemisinin, scopoletin, scoparone, artemisinic acid, deoxyartemisnin, artemetin, casticin, sitogluside, beta-sitosterol, dihydroartemisinin, scopolin, artemether, artemotil, artesunate were selected. Virtual screening of these ligands was carried out against drug target Mpro by CB dock. RESULTS: Quercetin, rutin, casticin, chrysoplenetin, apigenin, artemetin, artesunate, sopolin and sito-gluside were found as hit compounds. Further, ADMET screening was conducted which represented Chrysoplenetin as a lead compound. Azithromycin was used as a standard drug. The interactions were studied by PyMol and visualized in LigPlot. Furthermore, the RMSD graph shows fluctuations at various points at the start of simulation in Top1 (Azithromycin) complex system due to structural changes in the helix-coil-helix and beta-turn-beta changes at specific points resulting in increased RMSD with a time frame of 50 ns. But this change remains stable after the extension of simulation time intervals till 100 ns. On other side, the Top2 complex system remains highly stable throughout the time scale. No such structural dynamics were observed bu the ligand attached to the active site residues binds strongly. CONCLUSION: This study facilitates researchers to develop and discover more effective and specific therapeutic agents against SARS-CoV-2 and other viral infections. Finally, chrysoplenetin was identified as a more potent drug candidate to act against the viral main protease, which in the future can be helpful.

Optimal-Band Analysis for Chlorophyll Quantification in Rice Leaves Using a Custom Hyperspectral Imaging System.

Hyperspectral imaging (HSI) is a promising tool in chlorophyll quantification, providing a non-invasive method to collect important information for effective crop management. HSI contributes to food security solutions by optimising crop yields. In this study, we presented a custom HSI system specifically designed to provide a quantitative analysis of leaf chlorophyll content (LCC). To ensure precise estimation, significant wavelengths were identified using optimal-band analysis. Our research was centred on two sets of 120 leaf samples sourced from Thailand's unique Chaew Khing rice variant. The samples were subjected to (i) an analytical LCC assessment and (ii) HSI imaging for spectral reflectance data capture. A linear regression comparison of these datasets revealed that the green (575 ± 2 nm) and near-infrared (788 ± 2 nm) bands were the most outstanding performers. Notably, the green normalised difference vegetation index (GNDVI) was the most reliable during cross-validation (R2=0.78 and RMSE = 2.4 µg∙cm-2), outperforming other examined vegetable indices (VIs), such as the simple ratio (RED/GREEN) and the chlorophyll index. The potential development of a streamlined sensor dependent only on these two wavelengths is a significant outcome of identifying these two optimal bands. This innovation can be seamlessly integrated into farming landscapes or attached to UAVs, allowing real-time monitoring and rapid, targeted N management interventions.

Immunoinformatics and Evaluation of Peptide Vaccines Derived from Global Hepatitis B Viral HBx and HBc Proteins Critical for Covalently Closed Circular DNA Integrity.

The Hepatitis B virus (HBV) HBx and HBc proteins play a crucial role in associating with covalently closed circular DNA (cccDNA), the primary factor contributing to intrahepatic viral persistence and a major obstacle in achieving a cure for HBV. The cccDNA serves as a reservoir for viral persistence. Targeting the viral HBc and HBx proteins' interaction with cccDNA could potentially limit HBV replication. In this study, we present epitopes identified from global consensus sequences of HBx and HBc proteins that have the potential to serve as targets for the development of effective vaccine candidates. Furthermore, conserved residues identified through this analysis can be utilized in designing novel, site-specific anti-HBV agents capable of targeting all major genotypes of HBV. Our approach involved designing global consensus sequences for HBx and HBc proteins, enabling the analysis of variable regions and highly conserved motifs. These identified motifs and regions offer potent sites for the development of peptide vaccines, the design of site-specific RNA interference, and the creation of anti-HBV inhibitors. The epitopes derived from global consensus sequences of HBx and HBc proteins emerge as promising targets for the development of effective vaccine candidates. Additionally, the conserved residues identified provide valuable insights for the development of innovative, site-specific anti-HBV agents capable of targeting all major genotypes of HBV from A to J.

Optimizing Nitrogen Fertilization to Enhance Productivity and Profitability of Upland Rice Using CSM-CERES-Rice.

Nitrogen (N) deficiency can limit rice productivity, whereas the over- and underapplication of N results in agronomic and economic losses. Process-based crop models are useful tools and could assist in optimizing N management, enhancing the production efficiency and profitability of upland rice production systems. The study evaluated the ability of CSM-CERES-Rice to determine optimal N fertilization rate for different sowing dates of upland rice. Field experimental data from two growing seasons (2018-2019 and 2019-2020) were used to simulate rice responses to four N fertilization rates (N30, N60, N90 and a control-N0) applied under three different sowing windows (SD1, SD2 and SD3). Cultivar coefficients were calibrated with data from N90 under all sowing windows in both seasons and the remaining treatments were used for model validation. Following model validation, simulations were extended up to N240 to identify the sowing date's specific economic optimum N fertilization rate (EONFR). Results indicated that CSM-CERES-Rice performed well both in calibration and validation, in simulating rice performance under different N fertilization rates. The d-index and nRMSE values for grain yield (0.90 and 16%), aboveground dry matter (0.93 and 13%), harvest index (0.86 and 7%), grain N contents (0.95 and 18%), total crop N uptake (0.97 and 15%) and N use efficiencies (0.94-0.97 and 11-15%) during model validation indicated good agreement between simulated and observed data. Extended simulations indicated that upland rice yield was responsive to N fertilization up to 180 kg N ha-1 (N180), where the yield plateau was observed. Fertilization rates of 140, 170 and 130 kg N ha-1 were identified as the EONFR for SD1, SD2 and SD3, respectively, based on the computed profitability, marginal net returns and N utilization. The model results suggested that N fertilization rate should be adjusted for different sowing windows rather than recommending a uniform N rate across sowing windows. In summary, CSM-CERES-Rice can be used as a decision support tool for determining EONFR for seasonal sowing windows to maximize the productivity and profitability of upland rice production.

Unveiling the ESR1 Conformational Stability and Screening Potent Inhibitors for Breast Cancer Treatment

BACKGROUND: The current study recognizes the significance of estrogen receptor alpha (ERα) as a member of the nuclear receptor protein family, which holds a central role in the pathophysiology of breast cancer. ERα serves as a valuable prognostic marker, with its established relevance in predicting disease outcomes and treatment responses. METHOD: In this study, computational methods are utilized to search for suitable drug-like compounds that demonstrate analogous ligand binding kinetics to ERα. RESULTS: Docking-based simulation screened out the top 5 compounds - ZINC13377936, NCI35753, ZINC35465238, ZINC14726791, and NCI663569 against the targeted protein. Further, their dynamics studies reveal that the compounds ZINC13377936 and NCI35753 exhibit the highest binding stability and affinity. CONCLUSION: Anticipating the competitive inhibition of ERα protein expression in breast cancer, we envision that both ZINC13377936 and NCI35753 compounds hold substantial promise as potential therapeutic agents. These candidates warrant thorough consideration for rigorous In vitro and In vivo evaluations within the context of clinical trials. The findings from this current investigation carry significant implications for the advancement of future diagnostic and therapeutic approaches for breast cancer.

[1, 8]-Naphthyridine derivatives as dual inhibitor of alkaline phosphatase and carbonic anhydrase.

[1,8]-Naphthyridine derivatives have been reported to possess important biological activities and may serve as attractive pharmacophores in the drug discovery process. [1,8]-Naphthyridine derivatives (1a-1l) were evaluated for inhibitory potential for isozymes of carbonic anhydrase (CA) and alkaline phosphatase (ALP). CAs have been reported to carry out reversible hydration of CO2 into HCO3-, secretion of electrolytes, acid-base regulation, bone resorption, calcification, and biosynthetic reactions. Whereas ALPs hydrolyze monophosphate esters with the release of inorganic phosphate and play an important role in bone mineralization. Both enzymes have been found to be over-expressed and raised functional activities in patients suffering from rheumatoid arthritis. The discovery of dual inhibitors of these enzymes may provide a synergistic effect to cure bone disorders such as rheumatoid arthritis and ankylosing spondylitis. Among the test compounds, the most potent inhibitors for CA-II, CA-IX, and CA-XII were 1e, 1g, and 1a with IC50 values of 0.44 ± 0.19, 0.11 ± 0.03 and 0.32 ± 0.07 µM, respectively. [1,8]-Naphthyridine derivatives (1a-1l) were approximately 4 folds more potent than standard CA inhibitor acetazolamide. While in the case of ALPs, the most potent compounds for b-TNAP and c-IAP were 1b and 1e with IC50 values of 0.122 ± 0.06 and 0.107 ± 0.02 µM, respectively. Thus, synthesized derivatives proved to be 100 to 800 times more potent as compared to standard inhibitors of b-TNAP and c-IAP (Levamisole and L-phenyl alanine, respectively). In addition, selectivity and dual inhibition of [1,8]-Naphthyridine derivatives confer precedence over known inhibitors. Molecular docking and molecular simulation studies were also conducted in the present studies to define the type of interactions between potential inhibitors and enzyme active sites.

Elucidation of genetic determinants of dyslipidaemia using a global screening array for the early detection of coronary artery disease.

Dyslipidemia is a major risk factor for the development of coronary artery disease (CAD). Understanding the genetic determinants of dyslipidemia can provide valuable information on the pathogenesis of CAD and aid in the development of early detection strategies. In this study, we used a Global Screening Array (GSA) to elucidate the genetic factors associated with dyslipidemia and their potential role in the prediction of CAD. We conducted a GSA-based association study in 265 subjects to identify the genetic loci associated with dyslipidemia traits using Multiple Linear Regression (MLR) and Logistic Regression (LR), Classification and Regression Tree (CART), and Manhattan plots. We identified an association between dyslipidemia and variants identified in genes such as JCAD, GLIS3, CD38, FN1, CELSR2, MTNR1B, GIPR, DYM, APOB, APOE, ADCY5. The MLR models explained 62%, 71%, and 81% of the variability in HDL, LDL, and triglycerides, respectively. The Area Under the Curve (AUC) values in the LR models of HDL, LDL, and triglycerides were 1.00, 0.94, and 0.95, respectively. CART models identified novel gene-gene interactions influencing the risk for dyslipidemia. To conclude, we have identified the association of 12 SNVs with dyslipidemia and demonstrated their clinical utility in four different models such as MLR, LR, CART, and Manhattan plots. The identified genetic variants and associated pathways shed light on the underlying biology of dyslipidemia and offer potential avenues for precision medicine strategies in the management of CAD.

The role of TLR7 agonists in modulating COVID-19 severity in subjects with loss-of-function TLR7 variants.

We investigate the mechanism associated with the severity of COVID-19 in men with TLR7 mutation. Men with loss-of-function (LOF) mutations in TLR7 had severe COVID-19. LOF mutations in TLR7 increased the risk of critical COVID by 16.00-fold (95% confidence interval 2.40-106.73). The deleterious mutations affect the binding of SARS-CoV2 RNA (- 328.66 ± 26.03 vs. - 354.08 ± 27.70, p = 0.03) and MYD88 (ß: 40.279, p = 0.003) to TLR7 resulting in the disruption of TLR7-MyD88-TIRAP complex. In certain hypofunctional variants and all neutral/benign variants, there is no disruption of TLR7-MyD88-TIRAP complex and four TLR7 agonists showed binding affinity comparable to that of wild protein. N-acetylcysteine (NAC) also showed a higher binding affinity for the LOF variants (p = 0.03). To conclude, TLR7 LOF mutations increase the risk of critical COVID-19 due to loss of viral RNA sensing ability and disrupted MyD88 signaling. Majority of hypofunctional and neutral variants of TLR7 are capable of carrying MyD88 signaling by binding to different TLR7 agonists and NAC.

Global and local evolutionary dynamics of Dengue virus serotypes 1, 3, and 4.

Evolutionary studies on Dengue virus (DENV) in endemic regions are necessary since naturally occurring mutations may lead to genotypic variations or shifts in serotypes, which may lead to future outbreaks. Our study comprehends the evolutionary dynamics of DENV, using phylogenetic, molecular clock, skyline plots, network, selection pressure, and entropy analyses based on partial CprM gene sequences. We have collected 250 samples, 161 in 2017 and 89 in 2018. Details for the 2017 samples were published in our previous article and that of 2018 are presented in this study. Further evolutionary analysis was carried out using 800 sequences, which incorporate the study and global sequences from GenBank: DENV-1 (n = 240), DENV-3 (n = 374), and DENV-4 (n = 186), identified during 1944-2020, 1956-2020, and 1956-2021, respectively. Genotypes V, III, and I were identified as the predominant genotypes of the DENV-1, DENV-3, and DENV-4 serotypes, respectively. The rate of nucleotide substitution was found highest in DENV-3 (7.90 × 10-4 s/s/y), followed by DENV-4 (6.23 × 10-4 s/s/y) and DENV-1 (5.99 × 10-4 s/s/y). The Bayesian skyline plots of the Indian strains revealed dissimilar patterns amongst the population size of the three serotypes. Network analyses showed the presence of different clusters within the prevalent genotypes. The data presented in this study will assist in supplementing the measures for vaccine development against DENV.

Synthesis, characterization and biological evaluation of pyrazole-based benzene sulfonamides as inhibitors of human carbonic anhydrase II, IX and XII.

The aberrant level of the carbonic anhydrase isozymes is linked with various disorders which include glaucoma, epilepsy, altitude sickness and obesity. In the present study, a series of the pyrazole-based benzene sulfonamides derivatives (4a-4l) were designed, synthesized and evaluated as the inhibitors of the three isoforms of human carbonic anhydrases (hCAII, hCAIX and hCAXII). A number of the derivatives were found more active inhibitors than acetazolamide used as a standard against the human hCAII, hCAIX and hCAXII. Among the series, the compound 4k inhibited the hCAII to a submicromolar level presenting the IC50 ± SEM concentration of 0.24 ± 0.18 µM, the inhibitor 4j reduced the activity of the hCAIX to the IC50 ± SEM equals 0.15 ± 0.07 µM, whereas, the molecule 4g blocked the catalytic potential of the isozyme hCAXII with as low as IC50 concentration of 0.12 ± 0.07 µM. In addition, compounds 4e and 4k were screened as the preferential inhibitors of the isoform hCAXII as compared to the hCAIX and hCAXII with half of the maximal concentrations of 0.75 ± 0.13 µM, and 0.24 ± 0.18 µM, respectively. Moreover, the compounds 4k, 4j and 4g were docked inside the active pocket of the crystallographic structure of the isoforms hCAXII, hCAIX and hCAXII, respectively. The docked inhibitors showed the binding interactions with the important amino acid residues such as Leu1198, Thr1199, His1094, and Phe1131 in hCAXII isozyme; residues Val121, Thr200, Pro203, and Gln71 in hCAIX; the amino acids Val119, Leu197, Gln89, and Asn64 in the case of hCAXII. In addition, structural geometries, reactivity descriptors, optimization energy and electronic parameters were calculated to predict the activity of the synthesized compounds.

Indian Psychiatric Society multicentre study: Diagnostic patterns, comorbidity and prescription practices for patients with Dementia.

Background: There are more than 5 million people with dementia in India. Multicentre studies looking at details of treatment for people with dementia In India are lacking. Clinical audit is a quality improvement process which aims to systematically assess, evaluate, and improve patient care. Evaluating current practice is the key to a clinical audit cycle. Aim: This study aimed to assess the diagnostic patterns and prescribing practices of psychiatrists for patients with dementia in India. Method: A retrospective case file study was conducted across several centers in India. Results: Information from the case records of 586 patients with dementia was obtained. Mean age of the patients was 71.14 years (standard deviation = 9.42). Three hundred twenty one (54.8%) were men. Alzheimer's disease (349; 59.6%) was the most frequent diagnosis followed by vascular dementia (117; 20%). Three hundred fifty five (60.6%) patients had medical disorders and 47.4% patients were taking medications for their medical conditions. Eighty one (69.2%) patients with vascular dementia had cardiovascular problems. Majority of the patients (524; 89.4%) were on medications for dementia. Most frequently prescribed treatment was Donepezil (230; 39.2%) followed by Donepezil-Memantine combination (225; 38.4%). Overall, 380 (64.8%) patients were on antipsychotics. Quetiapine (213, 36.3%) was the most frequently used antipsychotic. Overall, 113 (19.3%) patients were on antidepressants, 80 (13.7%) patients were on sedatives/hypnotics, and 16 (2.7%) patients were on mood stabilizers. Three hundred nineteen (55.4%) patients and caregivers of 374 (65%) patients were receiving psychosocial interventions. Conclusions: Diagnostic and prescription patterns in dementia which emerged from this study are comparable to other studies both nationally and internationally. Comparing current practices at individual and national levels against accepted guidelines, obtaining feedback, identifying gaps and instituting remedial measures help to improve the standard of care provided.

Genetic Diversity and Evolutionary Kinetics of Influenza A Virus H3N2 Subtypes Circulating in Riyadh, Saudi Arabia.

Presence of a large foreign workforce and the annual gathering of people for pilgrimage from around the globe have significantly contributed to the emergence and diversity of respiratory viruses in Saudi Arabia. Here, we report the sequence and phylogenetic analysis of the H3N2 subtype of influenza A virus (IAV) in clinical samples collected from Riyadh, Saudi Arabia. Based on RT-PCR, IAV was found in 88 (28.3%) of the 311 samples screened. Of the 88-IAV positive samples, 43 (48.8%) were H1N1 subtype while the remaining 45 (51.2%) were found to be of the H3N2 subtype. Complete sequencing of HA and NA genes of H3N2 revealed, twelve and nine amino acid (AA) substitutions respectively, and importantly, these variations are absent in the current vaccine strains. Based on the phylogenetic analysis, the majority of H3N2 strains were grouped in the same clades as the vaccine strains. Importantly, the N-glycosylation sites at AA 135(NSS) were found to be unique to 6 strains in the investigated HA1 protein and were absent in the current vaccine strains. These data may have significant clinical implications in designing novel and population-based vaccines for IAV and underscore the need for regular monitoring of efficacy of vaccines due to emerging variants.

Structure-Based Virtual Screening, Molecular Docking, Molecular Dynamics Simulation of EGFR for the Clinical Treatment of Glioblastoma.

Glioblastoma (GBM) is a WHO Grade IV tumor with poor visibility, a high risk of comorbidity, and exhibit limited treatment options. Resurfacing from second-rate glioma was originally classified as either mandatory or optional. Recent interest in personalized medicine has motivated research toward biomarker stratification-based individualized illness therapy. GBM biomarkers have been investigated for their potential utility in prognostic stratification, driving the development of targeted therapy and customizing therapeutic treatment. Due to the availability of a specific EGFRvIII mutational variation with a clear function in glioma-genesis, recent research suggests that EGFR has the potential to be a prognostic factor in GBM, while others have shown no clinical link between EGFR and survival. The pre-existing pharmaceutical lapatinib (PubChem ID: 208,908) with a higher affinity score is used for virtual screening. As a result, the current study revealed a newly screened chemical (PubChem CID: 59,671,768) with a higher affinity than the previously known molecule. When the two compounds are compared, the former has the lowest re-rank score. The time-resolved features of a virtually screened chemical and an established compound were investigated using molecular dynamics simulation. Both compounds are equivalent, according to the ADMET study. This report implies that the virtual screened chemical could be a promising Glioblastoma therapy.

ON-1 and BA-IX Are the Dominant Sub-Genotypes of Human Orthopneumovirus A&B in Riyadh, Saudi Arabia.

Human orthopneumovirus (HOPV) is the major viral pathogen responsible for lower respiratory tract infections (LRTIs) in infants and young children in Riyadh, Saudi Arabia. Yet, predominant HOPV subtypes circulating in this region and their molecular and epidemiological characteristics are not fully ascertained. A total of 300 clinical samples involving nasopharyngeal aspirates (NPAs), throat swabs, and sputum were collected during winter seasons of 2019/2020 and 2021/2022 for HOPV subtyping and genotyping. Of the 300 samples, HOPV was identified in 55 samples (18.3%) with a distinct predominance of type A viruses (81.8%) compared to type B viruses (18.2%). Importantly, the ON1 strain of HOPV-A and BA-IX strain of HOPV-B groups were found to be responsible for all the infections. Sequence analysis revealed a duplication region within 2nd HVR of G protein gene of ON1 and BA-IX strains. This nucleotide duplication exerted a profound effect on protein length and affinity towards cell receptors. Further, these modifications may aid the HOPV in immune evasion and recurrent infections. Data from this study showed that ON-1 genotype of HOPV-A and BA-IX genotype of HOPV-B were dominant in Riyadh, Saudi Arabia. Further, a duplication of sequence within 2nd HVR of G protein gene was found.

Vaccinomics-Aided Development of a Next-Generation Chimeric Vaccine against an Emerging Threat: Mycoplasma genitalium.

Mycoplasma genitalium, besides urethritis, causes a number of other sexually transmitted diseases, posing a significant health threat to both men and women, particularly in developing countries. In light of the rapid appearance of multidrug-resistant strains, M. genitalium is regarded as an emerging threat and has been placed on the CDC's "watch list". Hence, a protective vaccine is essential for combating this pathogen. In this study, we utilized reverse vaccinology to develop a chimeric vaccine against M. genitalium by identifying vaccine targets from the reference proteome (Strain G-37) of this pathogen. A multiepitope vaccine was developed using proteins that are non-toxic, non-allergic, and non-homologous to human proteins. Several bioinformatic tools identified linear and non-linear B-cell epitopes, as well as MHC epitopes belonging to classes I and II, from the putative vaccine target proteins. The epitopes that showed promiscuity among the various servers were shortlisted and subsequently selected for further investigation based on an immunoinformatic analysis. Using GPGPG, AAY, and KK linkers, the shortlisted epitope sequences were assembled to create a chimeric construct. A GPI anchor protein immunomodulating adjuvant was adjoined to the vaccine construct's N-terminus through the EAAK linker so as to improve the overall immunogenicity. For further investigations of the designed construct, various bioinformatic tools were employed to study the physicochemical properties, immune profile, solubility, and allergenicity profile. A tertiary chimeric design was computationally modeled using I-TASSER and Robetta and was subsequently refined through GalaxyRefine. ProSA-Web was exploited to corroborate the quality of the construct by detecting errors and the Ramachandran plot was used to identify possible quality issues. Simulation studies of the molecular dynamics demonstrated the robustness and flexibility of the designed construct. Following the successful docking of the designed model to the immune receptors, the construct was computationally cloned into Escherichia coli plasmids to affirm the efficient expression of the designed construct in a biological system.

Recent advancement in OMICS approaches to enhance abiotic stress tolerance in legumes.

The world is facing rapid climate change and a fast-growing global population. It is believed that the world population will be 9.7 billion in 2050. However, recent agriculture production is not enough to feed the current population of 7.9 billion people, which is causing a huge hunger problem. Therefore, feeding the 9.7 billion population in 2050 will be a huge target. Climate change is becoming a huge threat to global agricultural production, and it is expected to become the worst threat to it in the upcoming years. Keeping this in view, it is very important to breed climate-resilient plants. Legumes are considered an important pillar of the agriculture production system and a great source of high-quality protein, minerals, and vitamins. During the last two decades, advancements in OMICs technology revolutionized plant breeding and emerged as a crop-saving tool in wake of the climate change. Various OMICs approaches like Next-Generation sequencing (NGS), Transcriptomics, Proteomics, and Metabolomics have been used in legumes under abiotic stresses. The scientific community successfully utilized these platforms and investigated the Quantitative Trait Loci (QTL), linked markers through genome-wide association studies, and developed KASP markers that can be helpful for the marker-assisted breeding of legumes. Gene-editing techniques have been successfully proven for soybean, cowpea, chickpea, and model legumes such as Medicago truncatula and Lotus japonicus. A number of efforts have been made to perform gene editing in legumes. Moreover, the scientific community did a great job of identifying various genes involved in the metabolic pathways and utilizing the resulted information in the development of climate-resilient legume cultivars at a rapid pace. Keeping in view, this review highlights the contribution of OMICs approaches to abiotic stresses in legumes. We envisage that the presented information will be helpful for the scientific community to develop climate-resilient legume cultivars.

Development of pharmacogenomic algorithm to optimize nateglinide dose for the treatment of type 2 diabetes mellitus.

BACKGROUND: Nateglinide is a meglitinide used for the treatment of type 2 diabetes mellitus. Individual studies demonstrated the association of CYP2C9, SLCO1B1, and MTNR1B variants with the safety and efficacy of nateglinide. The current study aimed to develop a pharmacogenomic algorithm to optimize nateglinide therapy. METHODS: Multiple linear regression (MLR) and classification and regression tree (CART) were used to develop a pharmacogenomic algorithm for nateglinide dosing based on the published nateglinide pharmacokinetic data on the area under the curve data (AUC) and Cmax (n = 143). CYP2C9 metabolizer phenotype, SLCO1B1, MTNR1B genotypes, and CYP2C9 inhibitor usage were used as the input variables. The results and associations were further confirmed by meta-analysis and in silico studies. RESULTS: The MLR models of AUC and Cmax explain 87.4% and 59% variability in nateglinide pharmacokinetics. The Bland and Altman analysis of the nateglinide dose predicted by these two MLR models showed a bias of ± 26.28 mg/meal. The CART algorithm was proposed based on these findings. This model is further justified by the meta-analysis showing increased AUCs in CYP2C9 intermediate metabolizers and SLCOB1 TC and CC genotypes compared to the wild genotypes. The increased AUC in SLCO1B1 mutants is due to decreased binding affinity of nateglinide to the mutant affecting the influx of nateglinide into hepatocytes. MTNR1B rs10830963 G-allele-mediated poor response to nateglinide is attributed to increased transcriptional factor binding causing decreased insulin secretion. CONCLUSION: CYP2C9, SLCO1B1, and MTNR1B genotyping help in optimizing nateglinide therapy based on this algorithm and ensuring safety and efficacy.

Identification of the Key miRNAs and Genes Associated with the Regulation of Non-Small Cell Lung Cancer: A Network-Based Approach.

Lung cancer is the major cause of cancer-associated deaths across the world in both men and women. Lung cancer consists of two major clinicopathological categories, i.e., small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). Lack of diagnosis of NSCLC at an early stage in addition to poor prognosis results in ineffective treatment, thus, biomarkers for appropriate diagnosis and exact prognosis of NSCLC need urgent attention. The proposed study aimed to reveal essential microRNAs (miRNAs) involved in the carcinogenesis of NSCLC that probably could act as potential biomarkers. The NSCLC-associated expression datasets revealed 12 differentially expressed miRNAs (DEMs). MiRNA-mRNA network identified key miRNAs and their associated genes, for which functional enrichment analysis was applied. Further, survival and validation analysis for key genes was performed and consequently transcription factors (TFs) were predicted. We obtained twelve miRNAs as common DEMs after assessment of all datasets. Further, four key miRNAs and nine key genes were extracted from significant modules based on the centrality approach. The key genes and miRNAs reported in our study might provide some information for potential biomarkers profitable to increased prognosis and diagnosis of lung cancer.

Synchronizing Nitrogen Fertilization and Planting Date to Improve Resource Use Efficiency, Productivity, and Profitability of Upland Rice.

Synchronizing nitrogen (N) fertilization with planting date (PD) could enhance resource use efficiency and profitability of upland rice (Oryza sativa L.) production in Thailand. The objective of the study was to assess upland rice responses to four N fertilization rates (NFRs) and three planting dates. Field experiments were conducted during two growing seasons under four NFRs, no N applied (N0), 30 (N30), 60 (N60), and 90 kg N ha-1 (N90), and NFR were applied at the initiation of tillering and panicle emergence stages. The planting dates selected were early (PD1), intermedium (PD2), and late planting (PD3) between September and December of each season. The NFRs and planting dates had a significant influence on N uptake, N use efficiency (NUE), crop water productivity, yield and yield attributes, and profitability of upland rice production. A linear relationship among NFRs, agronomic traits of upland rice, N uptake, and crop water productivity was observed, and a significant seasonal effect was indicated. Fertilization at N90 under PD2 enhanced yields, yield attributes, and grain yields, as well as crop water productivity by 56 and 105% during the second and first seasons, respectively. Grain N, total N, and straw N were increased by 159, 159, and 160%, and by 90, 114, and 153%, during the first and second seasons, respectively. Enhanced N efficiencies, including agronomic efficiency, recovery efficiency, partial factor productivity, and N harvest index, at varying NFRs were observed under PD2 during both seasons. Highly significant (p < 0.001) and positive associations were observed among agronomic attributes, N uptake, NUE, and crop water productivity of upland rice in correlation assessment. Profitability from grain yields was observed with N fertilization and N90 resulted in maximum profit under all the PDs. However, the highest marginal benefit-cost ratio was observed at N60 under PD2 during both seasons. The results suggest that the NFR of 90 kg N ha-1 and planting at the end of September or start of October would enhance resource use efficiency and productivity, and maximize profitability. Furthermore, long-term field investigations with a range of NFRs and adopting forecasting measures to adjust the planting date for upland rice are recommended.

Structure-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation of VEGF inhibitors for the clinical treatment of Ovarian Cancer.

Vascular endothelial growth factor (VEGF) and its receptor play an important role both in physiologic and pathologic angiogenesis, which is identified in ovarian cancer progression and metastasis development. The aim of the present investigation is to identify a potential vascular endothelial growth factor inhibitor which is playing a crucial role in stimulating the immunosuppressive microenvironment in tumor cells of the ovary and to examine the effectiveness of the identified inhibitor for the treatment of ovarian cancer using various in silico approaches. Twelve established VEGF inhibitors were collected from various literatures. The compound AEE788 displays great affinity towards the target protein as a result of docking study. AEE788 was further used for structure-based virtual screening in order to obtain a more structurally similar compound with high affinity. Among the 80 virtual screened compounds, CID 88265020 explicates much better affinity than the established compound AEE788. Based on molecular dynamics simulation, pharmacophore and comparative toxicity analysis of both the best established compound and the best virtual screened compound displayed a trivial variation in associated properties. The virtual screened compound CID 88265020 has a high affinity with the lowest re-rank score and holds a huge potential to inhibit the VGFR and can be implemented for prospective future investigations in ovarian cancer.