J Med Virol. 2024 Feb;96(2):e29469. doi: 10.1002/jmv.29469.

ABSTRACT

The mpox outbreak has subdued with fewer reported cases at the present in high-income countries. It is known that mpox virus (MPXV) infection has been epidemic for more than 50 years in African countries. The ancestral MPXV strain has changed into multiple clades, indicating the ongoing evolution of MPXV, which reflects the historical neglect of mpox in Africa, especially after smallpox eradication, and bestows the danger of more severe mpox epidemics in the future. It is thus imperative to continue the development of mpox diagnostics and treatments so we can be prepared in the event of a new mpox epidemic. In this study, we have developed an MPXV detection tool that leverages the recombinase-aid amplification assay by integrating lateral flow strips (RAA-LF) and one-step sample DNA preparation, with visible readout, no need of laboratory instrument, and ready for field deployment. The detection limit reaches 10 copies per reaction. The performance of our RAA-FL assay in diagnosing mpox clinical samples is on par with that of the quantitative polymerase chain reaction (PCR) assay. Taken together, we have developed a point-of-care RAA-LF method of high accuracy and sensitivity, readily deployable for field detection of MPXV. This diagnostic tool is expected to improve and accelerate field- and self-diagnosis, allow timely isolation and treatment, reduce the spread of MPXV, thus effectively mitigate MPXV outbreak in the future.

PMID:38376919 | DOI:10.1002/jmv.29469

J Cell Biol. 2024 Apr 1;223(4):e202307026. doi: 10.1083/jcb.202307026. Epub 2024 Feb 20.

ABSTRACT

DNA methylation (DNAme) is a key epigenetic mark that regulates critical biological processes maintaining overall genome stability. Given its pleiotropic function, studies of DNAme dynamics are crucial, but currently available tools to interfere with DNAme have limitations and major cytotoxic side effects. Here, we present cell models that allow inducible and reversible DNAme modulation through DNMT1 depletion. By dynamically assessing whole genome and locus-specific effects of induced passive demethylation through cell divisions, we reveal a cooperative activity between DNMT1 and DNMT3B, but not of DNMT3A, to maintain and control DNAme. We show that gradual loss of DNAme is accompanied by progressive and reversible changes in heterochromatin, compartmentalization, and peripheral localization. DNA methylation loss coincides with a gradual reduction of cell fitness due to G1 arrest, with minor levels of mitotic failure. Altogether, this system allows DNMTs and DNA methylation studies with fine temporal resolution, which may help to reveal the etiologic link between DNAme dysfunction and human disease.

PMID:38376465 | DOI:10.1083/jcb.202307026

J Chem Inf Model. 2024 Feb 20. doi: 10.1021/acs.jcim.3c02031. Online ahead of print.

ABSTRACT

This letter gives results on improving protein-ligand binding affinity predictions based on molecular dynamics simulations using machine learning potentials with a hybrid neural network potential and molecular mechanics methodology (NNP/MM). We compute relative binding free energies with the Alchemical Transfer Method and validate its performance against established benchmarks and find significant enhancements compared with conventional MM force fields like GAFF2.

PMID:38376463 | DOI:10.1021/acs.jcim.3c02031

Elife. 2024 Feb 20;12:RP87895. doi: 10.7554/eLife.87895.

ABSTRACT

The adaptive dynamics of evolving microbial populations takes place on a complex fitness landscape generated by epistatic interactions. The population generically consists of multiple competing strains, a phenomenon known as clonal interference. Microscopic epistasis and clonal interference are central aspects of evolution in microbes, but their combined effects on the functional form of the population's mean fitness are poorly understood. Here, we develop a computational method that resolves the full microscopic complexity of a simulated evolving population subject to a standard serial dilution protocol. Through extensive numerical experimentation, we find that stronger microscopic epistasis gives rise to fitness trajectories with slower growth independent of the number of competing strains, which we quantify with power-law fits and understand mechanistically via a random walk model that neglects dynamical correlations between genes. We show that increasing the level of clonal interference leads to fitness trajectories with faster growth (in functional form) without microscopic epistasis, but leaves the rate of growth invariant when epistasis is sufficiently strong, indicating that the role of clonal interference depends intimately on the underlying fitness landscape. The simulation package for this work may be found at https://github.com/nmboffi/spin_glass_evodyn.

PMID:38376390 | DOI:10.7554/eLife.87895

Elife. 2024 Feb 20;12:RP89262. doi: 10.7554/eLife.89262.

ABSTRACT

Angiogenesis is a morphogenic process resulting in the formation of new blood vessels from pre-existing ones, usually in hypoxic micro-environments. The initial steps of angiogenesis depend on robust differentiation of oligopotent endothelial cells into the Tip and Stalk phenotypic cell fates, controlled by NOTCH-dependent cell-cell communication. The dynamics of spatial patterning of this cell fate specification are only partially understood. Here, by combining a controlled experimental angiogenesis model with mathematical and computational analyses, we find that the regular spatial Tip-Stalk cell patterning can undergo an order-disorder transition at a relatively high input level of a pro-angiogenic factor VEGF. The resulting differentiation is robust but temporally unstable for most cells, with only a subset of presumptive Tip cells leading sprout extensions. We further find that sprouts form in a manner maximizing their mutual distance, consistent with a Turing-like model that may depend on local enrichment and depletion of fibronectin. Together, our data suggest that NOTCH signaling mediates a robust way of cell differentiation enabling but not instructing subsequent steps in angiogenic morphogenesis, which may require additional cues and self-organization mechanisms. This analysis can assist in further understanding of cell plasticity underlying angiogenesis and other complex morphogenic processes.

PMID:38376371 | DOI:10.7554/eLife.89262

Pest Manag Sci. 2024 Feb 20. doi: 10.1002/ps.7994. Online ahead of print.

ABSTRACT

BACKGROUND: Adaptation of specialist insects to their host plants and defense responses of plants to phytophagous insects have been extensively recognized while the dynamic interaction between these two events has been largely underestimated. Here, we provide evidence for characterization of an unrevealed dynamic interaction mode of digestive enzymes of specialist insect silkworm and inhibitor of its host plant mulberry tree.

RESULTS: MnKTI-1, a mulberry Kunitz-type protease inhibitor, whose messenger RNA (mRNA) transcription and protein expression in mulberry leaf were severely triggered and up-regulated by tens of times in a matter of hours in response to silkworm, Bombyx mori, and other mulberry pest insects, suggesting a quick response and broad spectrum to insect herbivory. MnKTI-1 proteins were detected in gut content and frass of specialist B. mori, and exhibited significant post-ingestive stability. Recombinant refolded MnKTI-1 (rMnKTI-1) displayed binding affinity to digestive enzymes and a dual inhibitory activity to α-amylase BmAmy and serine protease BmSP2956 in digestive juice of silkworm. Moreover, data from in vitro assays proved that the inhibition of recombinant rMnKTI-1 to BmAmy can be reverted by pre-incubation with BmSP15920, an inactivated silkworm digestive protease that lack of complete catalytic triad.

CONCLUSION: These findings demonstrate that mulberry MnKTI-1 has the potential to inhibit the digestive enzyme activities of its specialist insect herbivore silkworm, whereas this insect may employ inactivated proteases to block protease inhibitors to accomplish food digestion. The current work provides an insight to better understand the interacting mode between host plant Kunitz protease inhibitors and herbivorous insect digestive enzymes. © 2024 Society of Chemical Industry.

PMID:38375972 | DOI:10.1002/ps.7994

Nucleic Acids Res. 2024 Feb 20:gkae103. doi: 10.1093/nar/gkae103. Online ahead of print.

ABSTRACT

High-level folding of chromatin is a key determinant of the shape and functional state of chromosomes. During cell division, structural maintenance of chromosome (SMC) complexes such as condensin and cohesin ensure large-scale folding of chromatin into visible chromosomes. In contrast, the SMC5/6 complex plays more local and context-specific roles in the structural organization of interphase chromosomes with important implications for health and disease. Recent advances in single-molecule biophysics and cryo-electron microscopy revealed key insights into the architecture of the SMC5/6 complex and how interactions connecting the complex to chromatin components give rise to its unique repertoire of interphase functions. In this review, we provide an integrative view of the features that differentiates the SMC5/6 complex from other SMC enzymes and how these enable dramatic reorganization of DNA folding in space during DNA repair reactions and other genome transactions. Finally, we explore the mechanistic basis for the dynamic targeting of the SMC5/6 complex to damaged chromatin and its crucial role in human health.

PMID:38375830 | DOI:10.1093/nar/gkae103

Nat Comput Sci. 2024 Feb 19. doi: 10.1038/s43588-024-00593-9. Online ahead of print.

ABSTRACT

To automate the discovery of new scientific and engineering principles, artificial intelligence must distill explicit rules from experimental data. This has proven difficult because existing methods typically search through the enormous space of possible functions. Here we introduce deep distilling, a machine learning method that does not perform searches but instead learns from data using symbolic essence neural networks and then losslessly condenses the network parameters into a concise algorithm written in computer code. This distilled code, which can contain loops and nested logic, is equivalent to the neural network but is human-comprehensible and orders-of-magnitude more compact. On arithmetic, vision and optimization tasks, the distilled code is capable of out-of-distribution systematic generalization to solve cases orders-of-magnitude larger and more complex than the training data. The distilled algorithms can sometimes outperform human-designed algorithms, demonstrating that deep distilling is able to discover generalizable principles complementary to human expertise.

PMID:38374361 | DOI:10.1038/s43588-024-00593-9

Nat Med. 2024 Feb 19. doi: 10.1038/s41591-023-02793-8. Online ahead of print.

ABSTRACT

Despite intensive preventive cardiovascular disease (CVD) efforts, substantial residual CVD risk remains even for individuals receiving all guideline-recommended interventions. Niacin is an essential micronutrient fortified in food staples, but its role in CVD is not well understood. In this study, untargeted metabolomics analysis of fasting plasma from stable cardiac patients in a prospective discovery cohort (n = 1,162 total, n = 422 females) suggested that niacin metabolism was associated with incident major adverse cardiovascular events (MACE). Serum levels of the terminal metabolites of excess niacin, N1-methyl-2-pyridone-5-carboxamide (2PY) and N1-methyl-4-pyridone-3-carboxamide (4PY), were associated with increased 3-year MACE risk in two validation cohorts (US n = 2,331 total, n = 774 females; European n = 832 total, n = 249 females) (adjusted hazard ratio (HR) (95% confidence interval) for 2PY: 1.64 (1.10-2.42) and 2.02 (1.29-3.18), respectively; for 4PY: 1.89 (1.26-2.84) and 1.99 (1.26-3.14), respectively). Phenome-wide association analysis of the genetic variant rs10496731, which was significantly associated with both 2PY and 4PY levels, revealed an association of this variant with levels of soluble vascular adhesion molecule 1 (sVCAM-1). Further meta-analysis confirmed association of rs10496731 with sVCAM-1 (n = 106,000 total, n = 53,075 females, P = 3.6 × 10-18). Moreover, sVCAM-1 levels were significantly correlated with both 2PY and 4PY in a validation cohort (n = 974 total, n = 333 females) (2PY: rho = 0.13, P = 7.7 × 10-5; 4PY: rho = 0.18, P = 1.1 × 10-8). Lastly, treatment with physiological levels of 4PY, but not its structural isomer 2PY, induced expression of VCAM-1 and leukocyte adherence to vascular endothelium in mice. Collectively, these results indicate that the terminal breakdown products of excess niacin, 2PY and 4PY, are both associated with residual CVD risk. They also suggest an inflammation-dependent mechanism underlying the clinical association between 4PY and MACE.

PMID:38374343 | DOI:10.1038/s41591-023-02793-8

Nat Methods. 2024 Feb 19. doi: 10.1038/s41592-024-02175-z. Online ahead of print.

ABSTRACT

Modern multiomic technologies can generate deep multiscale profiles. However, differences in data modalities, multicollinearity of the data, and large numbers of irrelevant features make analyses and integration of high-dimensional omic datasets challenging. Here we present Significant Latent Factor Interaction Discovery and Exploration (SLIDE), a first-in-class interpretable machine learning technique for identifying significant interacting latent factors underlying outcomes of interest from high-dimensional omic datasets. SLIDE makes no assumptions regarding data-generating mechanisms, comes with theoretical guarantees regarding identifiability of the latent factors/corresponding inference, and has rigorous false discovery rate control. Using SLIDE on single-cell and spatial omic datasets, we uncovered significant interacting latent factors underlying a range of molecular, cellular and organismal phenotypes. SLIDE outperforms/performs at least as well as a wide range of state-of-the-art approaches, including other latent factor approaches. More importantly, it provides biological inference beyond prediction that other methods do not afford. Thus, SLIDE is a versatile engine for biological discovery from modern multiomic datasets.

PMID:38374265 | DOI:10.1038/s41592-024-02175-z

Cell Commun Signal. 2024 Feb 19;22(1):137. doi: 10.1186/s12964-023-01436-2.

ABSTRACT

BACKGROUND: Protein phosphorylation is one of the most prevalent posttranslational modifications involved in molecular control of cellular processes, and is mediated by over 520 protein kinases in humans and other mammals. Identification of the protein kinases responsible for phosphorylation events is key to understanding signaling pathways. Unbiased phosphoproteomics experiments have generated a wealth of data that can be used to identify protein kinase targets and their preferred substrate sequences.

METHODS: This study utilized prior data from mass spectrometry-based studies identifying sites of protein phosphorylation after in vitro incubation of protein mixtures with recombinant protein kinases. PTM-Logo software was used with these data to generate position-dependent Shannon information matrices and sequence motif 'logos'. Webpages were constructed for facile access to logos for each kinase and a new stand-alone application was written in Python that uses the position-dependent Shannon information matrices to identify kinases most likely to phosphorylate a particular phosphorylation site.

RESULTS: A database of kinase substrate target preference logos allows browsing, searching, or downloading target motif data for each protein kinase ( https://esbl.nhlbi.nih.gov/Databases/Kinase_Logos/ ). These logos were combined with phylogenetic analysis of protein kinase catalytic sequences to reveal substrate preference patterns specific to particular groups of kinases ( https://esbl.nhlbi.nih.gov/Databases/Kinase_Logos/KinaseTree.html ). A stand-alone program, KinasePredictor, is provided ( https://esbl.nhlbi.nih.gov/Databases/Kinase_Logos/KinasePredictor.html ). It takes as input, amino-acid sequences surrounding a given phosphorylation site and generates a ranked list of protein kinases most likely to phosphorylate that site.

CONCLUSIONS: This study provides three new resources for protein kinase characterization. It provides a tool for prediction of kinase-substrate interactions, which in combination with other types of data (co-localization, etc.), can predict which kinases are likely responsible for a given phosphorylation event in a given tissue. Video Abstract.

PMID:38374071 | DOI:10.1186/s12964-023-01436-2

Microb Pathog. 2024 Feb 17:106587. doi: 10.1016/j.micpath.2024.106587. Online ahead of print.

ABSTRACT

BACKGROUND: The condition of COVID-19-related myocarditis has emerged as a prominent contributor to COVID-19 mortality. As the epidemic persists, its incidence continues to rise. Despite ongoing efforts, the elucidation of COVID-19-related myocarditis underlying molecular mechanisms still requires further investigation.

METHODS: Hub genes for COVID-19-related myocarditis were screened by integrating gene expression profile analysis via differential expression in COVID-19 (GSE196822) and myocarditis (GSE148153 and GSE147517). After verification with independent datasets (GSE211979, GSE167028, GSE178491 and GSE215865), the hub genes were studied using a range of systems-biology approaches, such as ceRNA, TF-mRNA networks and PPI networks, as well as gene ontology, pathway enrichment, immune infiltration analysis and drug target identification.

RESULTS: TBKBP1 and ERGIC1 were identified as COVID-19-related myocarditis hub genes via integrated bioinformatics analysis. In addition, receiver operating characteristic curves constructed based on the expression levels of TBKBP1 and ERGIC1 could effectively distinguish healthy control individuals from patients with COVID-19. Functional enrichment analysis suggested several enriched biological pathways related to inflammation and immune response. Immune cell changes correlated with TBKBP1 and ERGIC1 levels in patients with COVID-19 or patients with COVID-19 and myocarditis. Tamibarotene, methotrexate and theophylline were identified as a potential drug targeting TBKBP1 and ERGIC1.

CONCLUSION: TBKBP1 and ERGIC1 were identified as crucial genes in the development of COVID-19-related myocarditis and have demonstrated a strong association with innate antiviral immunity. The present work may be helpful for further investigation of the molecular mechanisms and new therapeutic drug targets correlated with myocarditis in COVID-19.

PMID:38373644 | DOI:10.1016/j.micpath.2024.106587

J Phys Chem B. 2024 Feb 19. doi: 10.1021/acs.jpcb.3c07025. Online ahead of print.

ABSTRACT

Electrophysiology studies of secondary active transporters have revealed quantitative mechanistic insights over many decades of research. However, the emergence of new experimental and analytical approaches calls for investigation of the capabilities and limitations of the newer methods. We examine the ability of solid-supported membrane electrophysiology (SSME) to characterize discrete-state kinetic models with >10 rate constants. We use a Bayesian framework applied to synthetic data for three tasks: to quantify and check (i) the precision of parameter estimates under different assumptions, (ii) the ability of computation to guide the selection of experimental conditions, and (iii) the ability of our approach to distinguish among mechanisms based on SSME data. When the general mechanism, i.e., event order, is known in advance, we show that a subset of kinetic parameters can be "practically identified" within ∼1 order of magnitude, based on SSME current traces that visually appear to exhibit simple exponential behavior. This remains true even when accounting for systematic measurement bias and realistic uncertainties in experimental inputs (concentrations) are incorporated into the analysis. When experimental conditions are optimized or different experiments are combined, the number of practically identifiable parameters can be increased substantially. Some parameters remain intrinsically difficult to estimate through SSME data alone, suggesting that additional experiments are required to fully characterize parameters. We also demonstrate the ability to perform model selection and determine the order of events when that is not known in advance, comparing Bayesian and maximum-likelihood approaches. Finally, our studies elucidate good practices for the increasingly popular but subtly challenging Bayesian calculations for structural and systems biology.

PMID:38373358 | DOI:10.1021/acs.jpcb.3c07025

J Med Virol. 2024 Feb;96(2):e29443. doi: 10.1002/jmv.29443.

ABSTRACT

Cross-neutralizing activity of human antibody response against Dengue virus complex (DENV) changes importantly over time. Domain III (DIII) of the envelope protein of DENV elicits a potently neutralizing and mostly type-specific IgG response. We used sera from 24 individuals from early- or late convalescence of DENV1 infection to investigate the evolution of anti-DIII human IgG with the time lapse since the infection. We evaluated the correlation between the serotype-specific reactivity against recombinant DIII proteins and the neutralization capacity against the four serotypes, and examined its behavior with the time of convalescence. Also, we use a library of 71 alanine mutants of surface-exposed amino acid residues to investigate the dominant epitopes. In early convalescence anti-DIII titers and potency of virus neutralization were positively associated with correlation coefficients from 0.82 to 1.0 for the four serotypes. For late convalescence, a positive correlation (r = 0.69) was found only for DENV1. The dominant epitope of the type-specific response is centered in the FG-loop (G383, E384, and K385) and includes most of the lateral ridge. The dominant epitope of the anti-DIII cross-reactive IgG in secondary infections shifts from the A-strand during early convalescence to a site centered in residues E314-H317 of the AB-loop and I352-E368 of the DI/DIII interface, in late convalescence. An immunoassay based on the detection of IgG anti-DIII response can be implemented for detection of infecting serotype in diagnosis of DENV infection, either primary or secondary. Human dominant epitopes of the cross-reactive circulating antibodies change with time of convalescence.

PMID:38373154 | DOI:10.1002/jmv.29443

J Proteome Res. 2024 Feb 19. doi: 10.1021/acs.jproteome.3c00485. Online ahead of print.

ABSTRACT

Huanglongbing (HLB) is a fatal citrus disease that is currently threatening citrus varieties worldwide. One putative causative agent, Candidatus Liberibacter asiaticus (CLas), is vectored by Diaphorina citri, known as the Asian citrus psyllid (ACP). Understanding the details of CLas infection in HLB disease has been hindered by its Candidatus nature and the inability to confidently detect it in diseased trees during the asymptomatic stage. To identify early changes in citrus metabolism in response to inoculation of CLas using its natural psyllid vector, leaves from Madam Vinous sweet orange (Citrus sinensis (L.) Osbeck) trees were exposed to CLas-positive ACP or CLas-negative ACP and longitudinally analyzed using transcriptomics (RNA sequencing), proteomics (liquid chromatography-tandem mass spectrometry; data available in Dryad: 10.25338/B83H1Z), and metabolomics (proton nuclear magnetic resonance). At 4 weeks postexposure (wpe) to psyllids, the initial HLB plant response was primarily to the ACP and, to a lesser extent, the presence or absence of CLas. Additionally, analysis of 4, 8, 12, and 16 wpe identified 17 genes and one protein as consistently differentially expressed between leaves exposed to CLas-positive ACP versus CLas-negative ACP. This study informs identification of early detection molecular targets and contributes to a broader understanding of vector-transmitted plant pathogen interactions.

PMID:38373055 | DOI:10.1021/acs.jproteome.3c00485

Adv Mater. 2024 Feb 19:e2307679. doi: 10.1002/adma.202307679. Online ahead of print.

ABSTRACT

Triggering lysosome-regulated immunogenic cell death (ICD, e.g., pyroptosis and necroptosis) with nanomedicines is an emerging approach for turning an "immune-cold" tumor "hot"- a key challenge faced by cancer immunotherapies. Proton sponge such as high-molecular-weight branched polyethylenimine (PEI) is excellent at rupturing lysosomes, but its therapeutic application is hindered by uncontrollable toxicity due to fixed charge density and poor understanding of resulted cell death mechanism. Here, a series of proton sponge nano-assemblies (PSNAs) with self-assembly controllable surface charge density and cell cytotoxicity were created. Such PSNAs were constructed via low-molecular-weight branched PEI covalently bound to self-assembling peptides carrying tetraphenylethene pyridinium (PyTPE, an aggregation-induced emission based luminogen). Assembly of PEI assisted by the self-assembling peptide-PyTPE led to enhanced surface positive charges and cell cytotoxicity of PSNA. The self-assembly tendency of PSNAs was further optimized by tuning hydrophilic and hydrophobic components within the peptide, thus resulting in the PSNA with the highest fluorescence, positive surface charge density, cell uptake, and cancer cell cytotoxicity. Systematic cell death mechanistic studies revealed that the lysosome rupturing-regulated pyroptosis and necroptosis are at least two causes of the cell death. Tumor cells undergoing PSNA-triggered ICD activated immune cells, suggesting the great potential of PSNAs to trigger anticancer immunity. This article is protected by copyright. All rights reserved.

PMID:38372431 | DOI:10.1002/adma.202307679

Phytother Res. 2024 Feb 19. doi: 10.1002/ptr.8160. Online ahead of print.

ABSTRACT

Oxidative stress is implicated in the initiation, pathogenesis, and progression of various gastric inflammatory diseases (GID). The prevalence of these diseases remains a concern along with the increasing risks of adverse effects in current clinical interventions. Hence, new gastroprotective agents capable of inhibiting oxidative stress by modulating cellular defense systems such as the nuclear factor erythroid 2-related factor 2 (Nrf2)/antioxidant response element (ARE) signaling pathway are critically needed to address these issues. A candidate to solve the present issue is xanthone, a natural compound that reportedly exerts gastroprotective effects via antioxidant, anti-inflammatory, and cytoprotective mechanisms. Moreover, xanthone derivatives were shown to modulate the Nrf2/ARE signaling pathway to counter oxidative stress in both in vitro and in vivo models. Thirteen natural xanthones have demonstrated the ability to modulate the Nrf2/ARE signaling pathway and have high potential as lead compounds for GID as indicated by their in vivo gastroprotective action-particularly mangiferin (2), α-mangostin (3), and γ-mangostin (4). Further studies on these compounds are recommended to validate the Nrf2 modulatory ability in relation to their gastroprotective action.

PMID:38372084 | DOI:10.1002/ptr.8160

Biochem Biophys Rep. 2023 Dec 14;37:101606. doi: 10.1016/j.bbrep.2023.101606. eCollection 2024 Mar.

ABSTRACT

Papillary thyroid cancer (PTC) is a prevalent kind of thyroid cancer (TC), with the risk of metastasis increasing faster than any other malignancy. So, understanding the role of PTC in pathogenesis requires studying the various gene expressions to find out which particular molecular biomarkers will be helpful. The authors conducted a comprehensive search on the PubMed microarray database and a meta-analysis approach on the remaining ones to determine the differentially expressed genes between PTC and normal tissues, along with the analyses of overall survival (OS) and recurrence-free survival (RFS) rates in patients with PTC. We considered the associated genes with MAPK, Wnt, and Notch signaling pathways. Two GEO datasets have been included in this research, considering inclusion and exclusion criteria. Nineteen genes were found to have higher differences through the meta-analysis procedure. Among them, ten genes were upregulated, and nine genes were downregulated. The expression of 19 genes was examined using the GEPIA2 database, and the Kaplan-Meier plot statistics were used to analyze RFS and the OS rates. We discovered seven significant genes with the validation: PRICKLE1, KIT, RPS6KA5, GADD45B, FGFR2, FGF7, and DTX4. To further explain these findings, it was discovered that the mRNA expression levels of these seven genes and the remaining 12 genes were shown to be substantially linked with the results of the experimental literature investigations on the PTC. Our research found nineteen panels of genes that could be involved in the PTC progression and metastasis and the immune system infiltration of these cancers.

PMID:38371530 | PMC:PMC10873880 | DOI:10.1016/j.bbrep.2023.101606

iScience. 2023 Sep 28;27(2):108077. doi: 10.1016/j.isci.2023.108077. eCollection 2024 Feb 16.

ABSTRACT

This communication presents a mathematical mechanism-based model of the regenerating liver after drug-induced pericentral lobule damage resolving tissue microarchitecture. The consequence of alternative hypotheses about the interplay of different cell types on regeneration was simulated. Regeneration dynamics has been quantified by the size of the damage-induced dead cell area, the hepatocyte density and the spatial-temporal profile of the different cell types. We use deviations of observed trajectories from the simulated system to identify branching points, at which the systems behavior cannot be explained by the underlying set of hypotheses anymore. Our procedure reflects a successful strategy for generating a fully digital liver twin that, among others, permits to test perturbations from the molecular up to the tissue scale. The model simulations are complementing current knowledge on liver regeneration by identifying gaps in mechanistic relationships and guiding the system toward the most informative (lacking) parameters that can be experimentally addressed.

PMID:38371522 | PMC:PMC10869925 | DOI:10.1016/j.isci.2023.108077

bioRxiv. 2024 Jan 30:2024.01.26.577518. doi: 10.1101/2024.01.26.577518. Preprint.

ABSTRACT

Quantitative trait loci (QTL) denote regions of DNA whose variation is associated with variations in quantitative traits. QTL discovery is a powerful approach to understand how changes in molecular and clinical phenotypes may be related to DNA sequence changes. However, QTL discovery analysis encompasses multiple analytical steps and the processing of multiple input files, which can be laborious, error prone, and hard to reproduce if performed manually. In order to facilitate and automate large-scale QTL analysis, we developed the yQTL Pipeline, where the 'y' indicates the dependent quantitative variable being modeled. Prior to genome-wide association test, the pipeline supports the calculation or the direct input of pre-defined genome-wide principal components and genetic relationship matrix when applicable. User-specified covariates can also be provided. Depending on whether familial relatedness exists among the subjects, genome-wide association tests will be performed using either a linear mixed-effect model or a linear model. Using the workflow management tool Nextflow, the pipeline parallelizes the analysis steps to optimize run-time and ensure results reproducibility. In addition, a user-friendly R Shiny App is developed to facilitate result visualization. Upon uploading the result file, it can generate Manhattan plots of user-selected phenotype traits and trait-QTL connection networks based on user-specified p-value thresholds. We applied the yQTL Pipeline to analyze metabolomics profiles of blood serum from the New England Centenarians Study (NECS) participants. A total of 9.1M SNPs and 1,052 metabolites across 194 participants were analyzed. Using a p-value cutoff 5e-8, we found 14,983 mQTLs cumulatively associated with 312 metabolites. The built-in parallelization of our pipeline reduced the run time from ~90 min to ~26 min. Visualization using the R Shiny App revealed multiple mQTLs shared across multiple metabolites. The yQTL Pipeline is available with documentation on GitHub at https://github.com/montilab/yQTL-Pipeline.

PMID:38370654 | PMC:PMC10874520 | DOI:10.1101/2024.01.26.577518