Factor Xa inhibitors vs. warfarin in patients with Hughes syndrome: a systematic review and meta-analysis of randomized controlled trials.

Background: The optimal treatment regimen for patients with Hughes syndrome remains unclear. Therefore, the authors sought to compare the outcomes of warfarin vs. factor Xa inhibitors in patients with Hughes syndrome. Methods: MEDLINE, Embase, and Cochrane Central databases were searched for randomized controlled trials (RCTs) comparing 8 efficacy and safety of warfarin and factor Xa inhibitors in patients with Hughes syndrome. Recurrent thrombosis, all-cause mortality, stroke, adverse reactions, and bleeding were among 10 outcomes of interest. Mantel-Haenszel weighted random-effects model was used to calculate 11 relative risks (RRs) with 95% CIs. Results: The analysis included 625 patients from four RCTs and one post-hoc analysis. Meta-analysis showed a statistically non-significant difference between factor Xa inhibitors and warfarin in the recurrent thrombosis risk (arterial or venous) [RR 2.77 (95%, CI 0.79, 9.65); P=0.11, I2=50%]. Consistent results were revealed among patients with a previous history of arterial thrombosis [RR 2.76 (95% CI 0.93, 8.16); P=0.75, I2=0%], venous thrombosis [RR 1.71 (95% CI 0.60, 4.84); P=0.31, I2=15%] and patients who were triple antiphospholipid antibodies (aPL) positive [RR 4.12 (95% CI 0.46, 37.10); 21 P=0.21, I2=58%]. Factor Xa inhibitors were significantly associated with an increased risk of stroke [RR 8.51 (95% CI 2.35, 13.82); P=0.47, I2=0%]. Conclusion: Factor Xa inhibitors exhibited an increased risk of stroke among patients with Hughes syndrome. In addition, although not significant, the higher RRs among patients on factor Xa inhibitors may indicate a higher risk of thrombotic events associated with factor Xa inhibitors.

In Silico Prediction of New Inhibitors for Kirsten Rat Sarcoma G12D Cancer Drug Target Using Machine Learning-Based Virtual Screening, Molecular Docking, and Molecular Dynamic Simulation Approaches.

Single-point mutations in the Kirsten rat sarcoma (KRAS) viral proto-oncogene are the most common cause of human cancer. In humans, oncogenic KRAS mutations are responsible for about 30% of lung, pancreatic, and colon cancers. One of the predominant mutant KRAS G12D variants is responsible for pancreatic cancer and is an attractive drug target. At the time of writing, no Food and Drug Administration (FDA) approved drugs are available for the KRAS G12D mutant. So, there is a need to develop an effective drug for KRAS G12D. The process of finding new drugs is expensive and time-consuming. On the other hand, in silico drug designing methodologies are cost-effective and less time-consuming. Herein, we employed machine learning algorithms such as K-nearest neighbor (KNN), support vector machine (SVM), and random forest (RF) for the identification of new inhibitors against the KRAS G12D mutant. A total of 82 hits were predicted as active against the KRAS G12D mutant. The active hits were docked into the active site of the KRAS G12D mutant. Furthermore, to evaluate the stability of the compounds with a good docking score, the top two complexes and the standard complex (MRTX-1133) were subjected to 200 ns MD simulation. The top two hits revealed high stability as compared to the standard compound. The binding energy of the top two hits was good as compared to the standard compound. Our identified hits have the potential to inhibit the KRAS G12D mutation and can help combat cancer. To the best of our knowledge, this is the first study in which machine-learning-based virtual screening, molecular docking, and molecular dynamics simulation were carried out for the identification of new promising inhibitors for the KRAS G12D mutant.

Perioperative sildenafil therapy in pulmonary hypertension associated with congenital cardiac disease: An updated meta-analysis.

To provide an updated meta-analysis to evaluate the efficacy and safety of sildenafil on pediatric patients with pulmonary hypertension (PH) associated with congenital heart disease (CHD). To assess the efficacy and safety of sildenafil, five outcomes, time duration of post-operative need for mechanical ventilation, time duration of post-operative ICU stay, length of hospitalization (LOH), the incidence of mortalities and pulmonary arterial pressure to aortic pressure ratio (PAP/AoP) were regarded as primary efficacy outcomes. Standardized mean difference (SMD) was calculated for continuous data. In comparison to the control group (CG), there was a significant decrease in the time duration of ICU stay in the sildenafil group (SG) (SMD = -0.61 [95% CI -1.17, 0.04]; P < 0.01, I2 = 85%). Length of hospitalization was assessed in the sildenafil and control groups (SMD = -0.18 [95% CI -0.67, 0.31] P = 0.05, I2 = 62%). However, there was no significant difference seen in mortality rates between the SG and CG (SMD = 0.53 [ 95% CI 0.13, 2.17] p = 0.61, I2 = 0%), in the time duration of postoperative mechanical ventilation between the SG and CG (SMD = -0.23 [95% CI -0.49, 0.03] p = 0.29, I2 = 19%), or PAP/AoP ratio between the SG and CG (SMD = -0.42 [95% CI -1.35, 0.51] P < 0.01, I2 = 90%). Based on our analysis, sildenafil has little to no effect in reducing postoperative morbidity and mortality due to PH in infants and children with CHD.

Insights into Covid-19 mortality: A comprehensive study of cardiovascular sensitivity, gender, race, and geography trends in the United States (2020-2023).

This investigation meticulously explores the evolving landscape of Covid-19-related mortality in the United States from 2020 to 2023. Leveraging the comprehensive CDC WONDER database, the study conducts a detailed analysis of age-adjusted mortality rates (AAMRs), considering various demographic and regional parameters. The identified pattern illustrates an initial surge in AAMRs from 2020 to 2021, followed by a subsequent decline until 2023. Notably, there is a discernible reduction in AAMRs for both the elderly (85 years and older) and infants (below one year). Within specific demographic segments, heightened AAMRs are observed among NH American Indian or Alaska Native individuals, men, and residents in particular states and regions. Emphasizing the significant impact of Covid-19 on cardiovascular health, the study underscores increased mortality rates associated with the cardiovascular and respiratory systems. AAMR rates were standardized per 100,000 population, providing a comparative metric. Noteworthy states with elevated AAMRs include Mississippi, Oklahoma, Kentucky, New Mexico, and Alabama, with the Southern region exhibiting the highest AAMR. The research sheds light on demographic and regional disparities in Covid-19-related mortality, calling for intensified efforts in prevention and treatment strategies. These findings, offering nuanced insights, serve as a guide for strategic public health initiatives to mitigate the multifaceted repercussions of the pandemic, especially among vulnerable populations.

Effects of Co-Fermentation of Lactiplantibacillus plantarum and Saccharomyces cerevisiae on Digestive and Quality Properties of Steamed Bread.

The leavening of wheat-based steamed bread is carried out either with a pure yeast culture or with traditional starter cultures containing both lactic acid bacteria and yeast/mold. The use of variable starter cultures significantly affects steamed bread's quality attributes, including nutritional profile. In this paper, differences in physicochemical properties, the type of digested starch, the production of free amino acids, and the specific volume of steamed bread under three fermentation methods (blank, yeast, and LP-GM4-yeast) were compared. The digestion characteristics (protein and starch hydrolysis) of steamed bread produced by using either yeast alone or a combination of Lactiplantibacillus plantrum and yeast (LP-GM4-yeast) were analyzed by an in vitro simulated digestion technique. It was found that the specific volume of steamed bread fermented by LP-GM4-yeast co-culture was increased by about 32%, the proportion of resistant starch was significantly increased (more than double), and soluble protein with molecular weight of 30-40 kDa was significantly increased. The results of this study showed that steamed bread produced by LP-GM4-yeast co-culture is more beneficial to human health than that by single culture.

Identification of Drug Targets and Their Inhibitors in Yersinia pestis Strain 91001 through Subtractive Genomics, Machine Learning, and MD Simulation Approaches.

Yersinia pestis, the causative agent of plague, is a Gram-negative bacterium. If the plague is not properly treated it can cause rapid death of the host. Bubonic, pneumonic, and septicemic are the three types of plague described. Bubonic plague can progress to septicemic plague, if not diagnosed and treated on time. The mortality rate of pneumonic and septicemic plague is quite high. The symptom-defining disease is the bubo, which is a painful lymph node swelling. Almost 50% of bubonic plague leads to sepsis and death if not treated immediately with antibiotics. The host immune response is slow as compared to other bacterial infections. Clinical isolates of Yersinia pestis revealed resistance to many antibiotics such as tetracycline, spectinomycin, kanamycin, streptomycin, minocycline, chloramphenicol, and sulfonamides. Drug discovery is a time-consuming process. It always takes ten to fifteen years to bring a single drug to the market. In this regard, in silico subtractive proteomics is an accurate, rapid, and cost-effective approach for the discovery of drug targets. An ideal drug target must be essential to the pathogen's survival and must be absent in the host. Machine learning approaches are more accurate as compared to traditional virtual screening. In this study, k-nearest neighbor (kNN) and support vector machine (SVM) were used to predict the active hits against the beta-ketoacyl-ACP synthase III drug target predicted by the subtractive genomics approach. Among the 1012 compounds of the South African Natural Products database, 11 hits were predicted as active. Further, the active hits were docked against the active site of beta-ketoacyl-ACP synthase III. Out of the total 11 active hits, the 3 lowest docking score hits that showed strong interaction with the drug target were shortlisted along with the standard drug and were simulated for 100 ns. The MD simulation revealed that all the shortlisted compounds display stable behavior and the compounds formed stable complexes with the drug target. These compounds may have the potential to inhibit the beta-ketoacyl-ACP synthase III drug target and can help to combat Yersinia pestis-related infections. The dataset and the source codes are freely available on GitHub.

Evolution of NLR genes in genus Arachis reveals asymmetric expansion of NLRome in wild and domesticated tetraploid species.

Arachis hypogaea is an allotetraploid crop widely grown in the world. Wild relatives of genus Arachis are the rich source of genetic diversity and high levels of resistance to combat pathogens and climate change. The accurate identification and characterization of plant resistance gene, nucleotide binding site leucine rich repeat receptor (NLRs) substantially contribute to the repertoire of resistances and improve production. In the current study, we have studied the evolution of NLR genes in genus Arachis and performed their comparative genomics among four diploids (A. duranensis, A. ipaensis, A. cardenasii, A. stenosperma) and two tetraploid (wild: A. monticola and domesticated: A. hypogaea) species. In total 521, 354, 284, 794, 654, 290 NLR genes were identified from A. cardenasii, A. stenosperma and A. duranensis, A. hypogaea, A. monticola and A. ipaensis respectively. Phylogenetic analysis and classification of NLRs revealed that they belong to 7 subgroups and specific subgroups have expanded in each genome leading towards divergent evolution. Gene gain and loss, duplication assay reveals that wild and domesticated tetraploids species have shown asymmetric expansion of NLRome in both sub-genome (AA and BB). A-subgenome of A. monticola exhibited significant contraction of NLRome while B-subgenome shows expansion and vice versa in case of A. hypogaea probably due to distinct natural and artificial selection pressure. In addition, diploid species A. cardenasii revealed the largest repertoire of NLR genes due to higher frequency of gene duplication and selection pressure. A. cardenasii and A. monticola can be regarded as putative resistance resources for peanut breeding program for introgression of novel resistance genes. Findings of this study also emphasize the application neo-diploids and polyploids due to higher quantitative expression of NLR genes. To the best of our knowledge, this is the first study that studied the effect of domestication and polyploidy on the evolution of NLR genes in genus Arachis to identify genomic resources for improving resistance of polyploid crop with global importance on economy and food security.

Machine learning-based drug design for identification of thymidylate kinase inhibitors as a potential anti-Mycobacterium tuberculosis.

The rise of antibiotic-resistant Mycobacterium tuberculosis (Mtb) has reduced the availability of medications for tuberculosis therapy, resulting in increased morbidity and mortality globally. Tuberculosis spreads from the lungs to other parts of the body, including the brain and spine. Developing a single drug can take several decades, making drug discovery costly and time-consuming. Machine learning algorithms like support vector machines (SVM), k-nearest neighbor (k-NN), random forest (RF) and Gaussian naive base (GNB) are fast and effective and are commonly used in drug discovery. These algorithms are ideal for the virtual screening of large compound libraries to classify molecules as active or inactive. For the training of the models, a dataset of 307 was downloaded from BindingDB. Among 307 compounds, 85 compounds were labeled as active, having an IC50 below 58 mM, while 222 compounds were labeled inactive against thymidylate kinase, with 87.2% accuracy. The developed models were subjected to an external ZINC dataset of 136,564 compounds. Furthermore, we performed the 100-ns dynamic simulation and post trajectories analysis of compounds having good interaction and score in molecular docking. As compared to the standard reference compound, the top three hits revealed greater stability and compactness. In conclusion, our predicted hits can inhibit thymidylate kinase overexpression to combat Mycobacterium tuberculosis.Communicated by Ramaswamy H. Sarma.

Investigation of NLR Genes Reveals Divergent Evolution on NLRome in Diploid and Polyploid Species in Genus Trifolium.

Crop wild relatives contain a greater variety of phenotypic and genotypic diversity compared to their domesticated counterparts. Trifolium crop species have limited genetic diversity to cope with biotic and abiotic stresses due to artificial selection for consumer preferences. Here, we investigated the distribution and evolution of nucleotide-binding site leucine-rich repeat receptor (NLR) genes in the genus of Trifolium with the objective to identify reference NLR genes. We identified 412, 350, 306, 389 and 241 NLR genes were identified from Trifolium. subterraneum, T. pratense, T. occidentale, subgenome-A of T. repens and subgenome-B of T. repens, respectively. Phylogenetic and clustering analysis reveals seven sub-groups in genus Trifolium. Specific subgroups such as G4-CNL, CCG10-CNL and TIR-CNL show distinct duplication patterns in specific species, which suggests subgroup duplications that are the hallmarks of their divergent evolution. Furthermore, our results strongly suggest the overall expansion of NLR repertoire in T. subterraneum is due to gene duplication events and birth of gene families after speciation. Moreover, the NLRome of the allopolyploid species T. repens has evolved asymmetrically, with the subgenome -A showing expansion, while the subgenome-B underwent contraction. These findings provide crucial background data for comprehending NLR evolution in the Fabaceae family and offer a more comprehensive analysis of NLR genes as disease resistance genes.

In Silico Identification of Lead Compounds for Pseudomonas Aeruginosa PqsA Enzyme: Computational Study to Block Biofilm Formation.

Pseudomonas aeruginosa is an opportunistic Gram-negative bacterium implicated in acute and chronic nosocomial infections and a leading cause of patient mortality. Pseudomonas aeruginosa infections are frequently associated with the development of biofilms, which give the bacteria additional drug resistance and increase their virulence. The goal of this study was to find strong compounds that block the Anthranilate-CoA ligase enzyme made by the pqsA gene. This would stop the P. aeruginosa quorum signaling system. This enzyme plays a crucial role in the pathogenicity of P. aeruginosa by producing autoinducers for cell-to-cell communication that lead to the production of biofilms. Pharmacophore-based virtual screening was carried out utilizing a library of commercially accessible enzyme inhibitors. The most promising hits obtained during virtual screening were put through molecular docking with the help of MOE. The virtual screening yielded 7/160 and 10/249 hits (ZINC and Chembridge). Finally, 2/7 ZINC hits and 2/10 ChemBridge hits were selected as potent lead compounds employing diverse scaffolds due to their high pqsA enzyme binding affinity. The results of the pharmacophore-based virtual screening were subsequently verified using a molecular dynamic simulation-based study (MDS). Using MDS and post-MDS, the stability of the complexes was evaluated. The most promising lead compounds exhibited a high binding affinity towards protein-binding pocket and interacted with the catalytic dyad. At least one of the scaffolds selected will possibly prove useful for future research. However, further scientific confirmation in the form of preclinical and clinical research is required before implementation.

Dynamic Evolution of NLR Genes in Dalbergioids.

Dalbergioid is a large group within the family Fabaceae that consists of diverse plant species distributed in distinct biogeographic realms. Here, we have performed a comprehensive study to understand the evolution of the nucleotide-binding leucine-rich repeats (NLRs) gene family in Dalbergioids. The evolution of gene families in this group is affected by a common whole genome duplication that occurred approximately 58 million years ago, followed by diploidization that often leads to contraction. Our study suggests that since diploidization, the NLRome of all groups of Dalbergioids is expanding in a clade-specific manner with fewer exceptions. Phylogenetic analysis and classification of NLRs revealed that they belong to seven subgroups. Specific subgroups have expanded in a species-specific manner, leading to divergent evolution. Among the Dalbergia clade, the expansion of NLRome in six species of the genus Dalbergia was observed, with the exception of Dalbergia odorifera, where a recent contraction of NLRome occurred. Similarly, members of the Pterocarpus clade genus Arachis revealed a large-scale expansion in the diploid species. In addition, the asymmetric expansion of NLRome was observed in wild and domesticated tetraploids after recent duplications in the genus Arachis. Our analysis strongly suggests that whole genome duplication followed by tandem duplication after divergence from a common ancestor of Dalbergioids is the major cause of NLRome expansion. To the best of our knowledge, this is the first ever study to provide insight toward the evolution of NLR genes in this important tribe. In addition, accurate identification and characterization of NLR genes is a substantial contribution to the repertoire of resistances among members of the Dalbergioids species.

Transcriptional Regulatory Mechanism of Differential Metabolite Formation in Root and Stem of Ephedra sinica.

Ephedra sinica, a well-known Chinese medicinal plant, is characterized as having the opposite medicinal effect among its root and stem. However, there is a lack of understanding to differentiate the active components present in the root and stem of E. sinica, as well as the molecular mechanisms underlying the formation of the differential compounds, which has significantly hampered the further development and utilization of E. sinica resource. In this study, forty-five differential metabolic markers are affiliated to alkaloids, flavonoids, terpenoids, and organic acids between root and stem of E. sinica, and sixty genes of key enzymes are involved in their biosynthesis distributed in metabolic pathway branches such as phenylalanine metabolism, flavonoid biosynthesis and phenylpropane biosynthesis, based on combination non-targeted metabolome with transcriptome technologies. The finding revealed that the expression activity changes of these enzyme genes had a direct impact on the distinction of differential metabolic markers in the root and stem of E. sinica. This study will help to understand the molecular mechanism of the differentiation and biosynthesis of the primary active metabolites in the root and stem of E. sinica, providing a theoretical foundation for its quality control and promotion in cultivation.

FOXD3 Regulates Pluripotent Stem Cell Potential by Simultaneously Initiating and Repressing Enhancer Activity.

Early development is governed by the ability of pluripotent cells to retain the full range of developmental potential and respond accurately to developmental cues. This property is achieved in large part by the temporal and contextual regulation of gene expression by enhancers. Here, we evaluated regulation of enhancer activity during differentiation of embryonic stem to epiblast cells and uncovered the forkhead transcription factor FOXD3 as a major regulator of the developmental potential of both pluripotent states. FOXD3 bound to distinct sites in the two cell types priming enhancers through a dual-functional mechanism. It recruited the SWI/SNF chromatin remodeling complex ATPase BRG1 to promote nucleosome removal while concurrently inhibiting maximal activation of the same enhancers by recruiting histone deacetylases1/2. Thus, FOXD3 prepares cognate genes for future maximal expression by establishing and simultaneously repressing enhancer activity. Through switching of target sites, FOXD3 modulates the developmental potential of pluripotent cells as they differentiate.

Let-7 and miR-125 cooperate to prime progenitors for astrogliogenesis.

The molecular basis of astrocyte differentiation and maturation is poorly understood. As microRNAs have important roles in cell fate transitions, we set out to study their function during the glial progenitor cell (GPC) to astrocyte transition. Inducible deletion of all canonical microRNAs in GPCs in vitro led to a block in the differentiation to astrocytes. In an unbiased screen, the reintroduction of let-7 and miR-125 families of microRNAs rescued differentiation. Let-7 and miR-125 shared many targets and functioned in parallel to JAK-STAT signaling, a known regulator of astrogliogenesis. While individual knockdown of shared targets did not rescue the differentiation phenotype in microRNA-deficient GPCs, overexpression of these targets in wild-type GPCs blocked differentiation. This finding supports the idea that microRNAs simultaneously suppress multiple mRNAs that inhibit differentiation. MicroRNA-regulated transcripts exhibited concordant changes during in vivo differentiation and were enriched for a gene set upregulated in glioblastomas, consistent with validity of using the in vitro model to study in vivo events. These findings provide insight into the microRNAs and the genes they regulate in this important cell fate transition.