Profile hidden Markov models (pHMMs) are able to achieve high sensitivity in remote homology search, making them popular choices for detecting novel or highly diverged viruses in metagenomic data. However, many existing pHMM databases have different design focuses, making it difficult for users to decide the proper one to use. In this review, we provide a thorough evaluation and comparison for multiple commonly used profile HMM databases for viral sequence discovery in metagenomic data. We characterized the databases by comparing their sizes, their taxonomic coverage, and the properties of their models using quantitative metrics. Subsequently, we assessed their performance in virus identification across multiple application scenarios, utilizing both simulated and real metagenomic data. We aim to offer researchers a thorough and critical assessment of the strengths and limitations of different databases. Furthermore, based on the experimental results obtained from the simulated and real metagenomic data, we provided practical suggestions for users to optimize their use of pHMM databases, thus enhancing the quality and reliability of their findings in the field of viral metagenomics.

In the era of high throughput sequencing, special software is required for the clinical evaluation of genetic variants. We developed REEV (Review, Evaluate and Explain Variants), a user-friendly platform for clinicians and researchers in the field of rare disease genetics. Supporting data was aggregated from public data sources. We compared REEV with seven other tools for clinical variant evaluation. REEV (semi-)automatically fills individual ACMG criteria facilitating variant interpretation. REEV can store disease and phenotype data related to a case to use these for phenotype similarity measures. Users can create public permanent links for individual variants that can be saved as browser bookmarks and shared. REEV may help in the fast diagnostic assessment of genetic variants in a clinical as well as in a research context. REEV (https://reev.bihealth.org/) is free and open to all users and there is no login requirement.

Large-scale association analyses using whole-genome sequence data have become feasible, but understanding the functional impacts of these associations remains challenging. Although many tools are available to predict the functional impacts of genetic variants, it is unclear which tool should be used in practice. This work provides a practical guide to assist in selecting appropriate tools for variant annotation. We conducted a MEDLINE search up to November 10, 2023, and included tools that are applicable to a broad range of phenotypes, can be used locally, and have been recently updated. Tools were categorized based on the types of variants they accept and the functional impacts they predict. Sequence Ontology terms were used for standardization. We identified 118 databases and software packages, encompassing 36 variant types and 161 functional impacts. Combining only three tools, namely SnpEff, FAVOR, and SparkINFERNO, allows predicting 99 (61%) distinct functional impacts. Thirty-seven tools predict 89 functional impacts that are not supported by any other tool, while 75 tools predict pathogenicity and can be used within the ACMG/AMP guidelines in a clinical context. We launched a website allowing researchers to select tools based on desired variants and impacts. In summary, more than 100 tools are already available to predict approximately 160 functional impacts. About 60% of the functional impacts can be predicted by the combination of three tools. Unexpectedly, recent tools do not predict more impacts than older ones. Future research should allow predicting the functionality of so far unsupported variant types, such as gene fusions.URL: https://cardio-care.shinyapps.io/VEP_Finder/ .Registration: OSF Registries on November 10, 2023, https://osf.io/s2gct .

Kuntai capsules are effective in controlling primary ovarian insufficiency (POI). However, the precise mechanisms underlying the pharmacological effects of Kuntai capsules remain unclear. This study aimed to screen the active components and underlying mechanisms of Kuntai capsules for POI treatment using network pharmacology protocols and molecular docking technology. Potential active constituents in the chemical composition of Kuntai capsules were obtained from the Traditional Chinese Medicine System Pharmacology Database. Targets for POI were obtained from the Online Mendelian Inheritance in Man and Gene Cards database. All target data were integrated to identify the active ingredients of POI treatment. Enrichment analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery database. The STRING database and Cytoscape software were used for protein-protein interaction network construction and core target identification. Finally, a molecular docking analysis of the active components and core targets was performed. A total of 157 ingredients related to POI were identified. Enrichment analysis showed that these components might participate in the mitogen-activated protein kinase, tumor necrosis factor, phosphoinositide-3-kinase/AKT serine/threonine kinase 1, and forkhead box O signaling pathways. Further protein-protein interaction network analysis revealed that the core targets were Jun proto-oncogene, AKT serine/threonine kinase 1, tumor protein P53, interleukin 6, and the epidermal growth factor receptor. Molecular docking analysis showed that baicalein was the most active ingredient with the highest affinity for the core targets. This study identified baicalein as the core functional component and elucidated the potential pharmacological effects of Kuntai capsule in the treatment of POI.

Peach kernel and safflower herb-pair (PKSH) are widely used in traditional Chinese medicine for the treatment of liver fibrosis. Therefore, network pharmacology was performed to explore potential therapeutic targets and pharmacological mechanisms of PKSH. The active components of PKSH from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database and potential targets of liver fibrosis from the Online Mendelian Inheritance in Man, Pharmacogenetics and Pharmacogenomics Knowledge Base, GeneCards, and DrugBank Database were identified. The protein-protein interaction network was constructed using Cytoscape (v3.8.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed for the treatment of liver fibrosis, and molecular docking was carried out to verify the results of network pharmacology analysis. After screening disease-related genes, 179 intersection genes overlapped between 196 target proteins of the active compound and 9189 potential disease targets. Furthermore, we obtained 15 hub nodes and 146 edges to establish a related network diagram using CytoNCA. 2559 Gene Ontology biological processes underlying PKSH have been explored for the treatment of liver fibrosis, in which the response to oxidative stress plays a vital role. Furthermore, Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that PKSH might play a role in inhibiting liver fibrosis, mainly through the PI3K-Akt signaling pathway. PKSH can regulate the response to oxidative stress through the PI3K-Akt signaling pathway for the treatment of liver fibrosis. The main bioactive components in PKSH, including quercetin and luteolin, can activate the PI3K-Akt signaling pathway by binding with the hub targets of the disease, which may provide insights into drug development for liver fibrosis.

To explore the potential active ingredients and related mechanisms of Jiaotai Pill in the treatment of Type 2 diabetes mellitus (T2DM) based on network pharmacology and molecular docking. The main active components of Jiaotai Pills were obtained by TCMSP and BATMAN-TCM database combined with literature mining, and the targets of the active components of Jiaotai Pills were predicted by reverse pharmacophore matching (PharmMapper) method. Verifying and normalizing the obtained action targets by using a Uniprot database. Obtaining T2DM related targets through GeneCards, the online mendelian inheritance in man, DrugBank, PharmGKB and therapeutic target databases, constructing a Venn diagram by using a Venny 2.1 online drawing platform to obtain the intersection action targets of Jiaotai pills and T2DM, and the protein-protein interaction network was constructed by String platform. Bioconductor platform and R language were used to analyze the function of gene ontology and the pathway enrichment of Kyoto Encyclopedia of Genes and Genomes. A total of 21 active components and 262 potential targets of Jiaotai Pill were screened by database analysis and literature mining, including 89 targets related to T2DM. Through gene ontology functional enrichment analysis, 1690 biological process entries, 106 molecular function entries and 78 cellular component entries were obtained. Seven pathways related to T2DM were identified by Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Jiaotai Pill can achieve the purpose of treating T2DM through multiple active ingredients, multiple disease targets, multiple biological pathways and multiple pathways, which provides a theoretical basis for the clinical treatment of T2DM by Jiaotai Pill.

Allergic rhinitis is prone to recurrence, and clinical treatments focus on control symptoms; however there is no radical cure. Our aim was to use network pharmacology and molecular docking to reveal the hub genes, biological functions, and signaling pathways of Tongqiao Huoxue decoction against allergic rhinitis. First, the chemical components and target genes of Tongqiao Huoxue decoction were obtained from the Traditional Chinese Medicine Systems Pharmacology database. Similarly, allergic rhinitis targets were screened using online Mendelian Inheritance In Man and GeneCards database. Then, all potential targets of Tongqiao Huoxue decoction in the treatment of allergic rhinitis were identified, the Venn diagram was portrayed using R software, and protein-protein interaction network was built using String. The hub genes were analyzed using enrichment analyses. Finally, molecular docking was used to verify the reliability of the key gene prediction. The core targets for Tongqiao Huoxue decoction to improve allergic rhinitis were AKT1, TP53, IL6, and so on. The enrichment analysis results showed that Tongqiao Huoxue decoction treatment in allergic rhinitis might be involved in the AGE-RAGE signaling pathway and fluid shear stress and atherosclerosis pathway. The molecular docking verification indicated that its ingredients bound well to the core targets of allergic rhinitis, and stigmasterol\'s docking ability with TNF (-12.73 kcal/mol) is particularly prominent. Based on these findings, it may be deduced that stigmasterol treated allergic rhinitis by acting on TNF targets. But, this conclusion needs to be confirmed by further in vitro and in vivo trials.

Hypotonia is considered a determinant factor in multiple developmental disorders and is associated with various characteristics and morbidities. It is necessary to perform a systematic review to know which characteristics are described as associated with hypotonia in children and which methods are used for its diagnosis.
Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were used to develop the systematic review protocol. A search of databases (Pubmed, Cochrane, Web of Knowledge, among others) was performed in May 2021 to identify relevant studies. Those describing characteristics or tests of hypotonia assessment were included, excluding those that exclusively addressed peripheral hypotonia. Two reviewers evaluated the articles and collected the data in a table, noting the authors, date of publication, type of study, and characteristics or tests described in relation to hypotonia. The quality of the studies was also assessed, and data were extracted.
A total of 8778 studies were identified and analyzed, of which 45 met the inclusion criteria. Fifty-three characteristics associated with hypotonia and tests used for its evaluation were located, with pull to sit and vertical suspension being the most frequently referenced.
The characteristics associated with hypotonia, more highly debated by authors are muscle strength, hypermobility, or the maintenance of antigravity postures. The most used test in the diagnosis of hypotonia is observation, followed by the pull-to-sit test, and adoption of frog posture. A unanimous understanding of the term hypotonia would favor further research.

MicroRNAs (miRNAs) are gene regulators involved in the pathogenesis of complex diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic targets. The prerequisite for designing effective miRNA therapies is accurate discovery of miRNA-disease associations (MDAs), which has attracted substantial research interests during the last 15 years, as reflected by more than 55 000 related entries available on PubMed. Abundant experimental data gathered from the wealth of literature could effectively support the development of computational models for predicting novel associations. In 2017, Chen et al. published the first-ever comprehensive review on MDA prediction, presenting various relevant databases, 20 representative computational models, and suggestions for building more powerful ones. In the current review, as the continuation of the previous study, we revisit miRNA biogenesis, detection techniques and functions; summarize recent experimental findings related to common miRNA-associated diseases; introduce recent updates of miRNA-relevant databases and novel database releases since 2017, present mainstream webservers and new webserver releases since 2017 and finally elaborate on how fusion of diverse data sources has contributed to accurate MDA prediction.

Extraneural metastases of glioblastoma (GBM), although rare, are becoming an increasingly recognized occurrence. Currently, the biological mechanism underlying this rare occurrence is not understood. To explore the potential genomic drivers of extraneural metastasis in GBM, we present the molecular features of 4 extraneural metastatic GBMs, along with a comprehensive review and analysis of previously reported cases that had available molecular characterization. In addition to our 4 cases, 42 patients from 35 publications are reviewed. To compare the molecular profiles between GBM cases with extraneural metastasis and the general GBM population, genomic data from GBM samples in The Cancer Genome Atlas (TCGA) database were also analyzed. We found that 64.5% (20/31) of the cases with extraneural metastasis that were tested for TP53 changes had at least 1 TP53 pathogenic variant detected in either 1 or both primary and metastatic tumors. In contrast, TP53 mutation was significantly less frequent in the unselected GBM from TCGA (22.6%, 56/248) (P=0.000). In addition, O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation was more common in unselected TCGA GBM cases (48.6%, 170/350) than in cases with extraneural metastasis (31.8%, 7/22), although not statistically significant. Although isocitrate dehydrogenase (IDH) mutation is a rare occurrence in high-grade astrocytomas, IDH-mutant grade 4 astrocytomas are at least as likely to metastasize as IDH wild-type GBMs; 3 metastatic cases definitively harbored an IDH1 (p.R132H) mutation in our analysis. Our findings not only provide potential biomarkers for earlier screening of extraneural metastasis, but could also suggest clues to understanding biological mechanisms underlying GBM metastasis, and for the development of therapeutic modalities.