Medicinal herbs have been utilized in the treatment of various pathologic conditions, including neoplasms, organ fibrosis, and diabetes mellitus. However, the precise pharmacological actions of plant miRNAs in animals remain to be fully elucidated, particularly in terms of their therapeutic efficacy and mechanism of action. In this review, some important miRNAs from foods and medicinal herbs are presented. Plant miRNAs exhibit a range of pharmacological properties, such as anti-cancer, anti-fibrosis, anti-viral, anti-inflammatory effects, and neuromodulation, among others. These results have not only demonstrated a cross-species regulatory effect, but also suggested that the miRNAs from medicinal herbs are their bioactive components. This shows a promising prospect for plant miRNAs to be used as drugs. Here, the pharmacological properties of plant miRNAs and their underlying mechanisms have been highlighted, which can provide new insights for clarifying the therapeutic mechanisms of medicinal herbs and suggest a new way for developing therapeutic drugs.

The tire rubber antioxidant N-(1,3-dimethylbutyl)-N\'-phenyl-p-phenylenediamine (6PPD) and its quinone product (6PPDQ) are prevalent emerging contaminants, yet their biotransformation profiles remain poorly understood, hampering the assessment of environmental and health risks. This study investigated the phase-I metabolism of 6PPD and 6PPDQ across aquatic and mammalian species through in vitro liver microsome (LM) incubations and in silico simulations. A total of 40 metabolites from seven pathways were identified using the highly sensitive nano-electrospray ionization mass spectrometry. Notably, 6PPDQ was consistently detected as a 6PPD metabolite with an approximate 2% yield, highlighting biotransformation as a neglected indirect exposure pathway for 6PPDQ in organisms. 6PPDQ was calculated to form through a facile two-step phenyl hydroxylation of 6PPD, catalyzed by cytochrome P450 enzymes. Distinct species-specific metabolic kinetics were observed, with fish LM demonstrating retarded biotransformation rates for 6PPD and 6PPDQ compared to mammalian LM, suggesting the vulnerability of aquatic vertebrates to these contaminants. Intriguingly, two novel coupled metabolites were identified for 6PPD, which were predicted to exhibit elevated toxicity compared to 6PPDQ and result from C-N oxidative coupling by P450s. These unveiled metabolic profiles offer valuable insights for the risk assessment of 6PPD and 6PPDQ, which may inform future studies and regulatory actions.

BACKGROUND: There is still a lack of effective treatment for sepsis-induced myocardial dysfunction (SIMD), while the pathogenesis of SIMD still remains largely unexplained.
METHODS: RNA sequencing results (GSE267388 and GSE79962) were used for cross-species integrative analysis. Bioinformatic analyses were used to delve into function, tissue- and cell- specificity, and interactions of genes. External datasets and qRT-PCR experiments were used for validation. L1000 FWD was used to predict targeted drugs, and 3D structure files were used for molecular docking.
RESULTS: Based on bioinformatic analyses, ten differentially expressed genes were selected as genes of interest, seven of which were verified to be significantly differential expression. Bucladesine was considered as a potential targeted drug for SIMD, which banded to seven target proteins primarily by forming hydrogen bonds.
CONCLUSIONS: It was considered that Cebpd, Timp1, Pnp, Osmr, Tgm2, Cp, and Asb2 were novel disease genes, while bucladesine was a potential therapeutic drug, of SIMD.

UNASSIGNED: Inherited retinal diseases (IRDs) affect ∼4.5 million people worldwide. Elusive pathogenic variants in over 280 genes are associated with one or more clinical forms of IRDs. It is necessary to understand the complex interaction among retinal cell types and pathogenic genes by constructing a regulatory network. In this study, we attempt to establish a panoramic expression view of the cooperative work in retinal cells to understand the clinical manifestations and pathogenic bases underlying IRDs.
UNASSIGNED: Single-cell RNA sequencing (scRNA-seq) data on the retinas from 35 retina samples of 3 species (human, mouse, and zebrafish) including 259,087 cells were adopted to perform a comparative analysis across species. Bioinformatic tools were used to conduct weighted gene co-expression network analysis (WGCNA), single-cell regulatory network analysis, cell-cell communication analysis, and trajectory inference analysis.
UNASSIGNED: The cross-species comparison revealed shared or species-specific gene expression patterns at single-cell resolution, such as the stathmin family genes, which were highly expressed specifically in zebrafish Müller glias (MGs). Thirteen gene modules were identified, of which nine were associated with retinal cell types, and Gene Ontology (GO) enrichment of module genes was consistent with cell-specific highly expressed genes. Many IRD genes were identified as hub genes and cell-specific regulons. Most IRDs, especially the retinitis pigmentosa (RP) genes, were enriched in rod-specific regulons. Integrated expression and transcription regulatory network genes, such as congenital stationary night blindness (CSNB) genes GRK1, PDE6B, and TRPM1, showed cell-specific expression and transcription characteristics in either rods or bipolar cells (BCs). IRD genes showed evolutionary conservation (GNAT2, PDE6G, and SAG) and divergence (GNAT2, MT-ND4, and PDE6A) along the trajectory of photoreceptors (PRs) among species. In particular, the Leber congenital amaurosis (LCA) gene OTX2 showed high expression at the beginning of the trajectory of both PRs and BCs.
UNASSIGNED: We identified molecular pathways and cell types closely connected with IRDs, bridging the gap between gene expression, genetics, and pathogenesis. The IRD genes enriched in cell-specific modules and regulons suggest that these diseases share common etiological bases. Overall, mining of interspecies transcriptome data reveals conserved transcriptomic features of retinas across species and promising applications in both normal retina anatomy and retina pathology.

UNASSIGNED: Gout is the most common inflammatory arthritis in adults. Gout is an arthritic disease caused by the deposition of monosodium urate crystal (MSU) in the joints, which can lead to acute inflammation and damage adjacent tissue. Hyperuricemia is the main risk factor for MSU crystal deposition and gout. With the increasing burden of gout disease, the identification of potential biomarkers and novel targets for diagnosis is urgently needed.
UNASSIGNED: For the analysis of this subject paper, we downloaded the human gout data set GSE160170 and the gout mouse model data set GSE190138 from the GEO database. To obtain the differentially expressed genes (DEGs), we intersected the two data sets. Using the cytohubba algorithm, we identified the key genes and enriched them through GO and KEGG. The gene expression trends of three subgroups (normal control group, intermittent gout group and acute gout attack group) were analyzed by Series Test of Cluster (STC) analysis, and the key genes were screened out, and the diagnostic effect was verified by ROC curve. The expression of key genes in dorsal root nerve and spinal cord of gout mice was analyzed. Finally, the clinical samples of normal control group, hyperuricemia group, intermittent gout group and acute gout attack group were collected, and the expression of key genes at protein level was verified by ELISA.
UNASSIGNED: We obtained 59 co-upregulated and 28 co-downregulated genes by comparing the DEGs between gout mouse model data set and human gout data set. 7 hub DEGs(IL1B, IL10, NLRP3, SOCS3, PTGS2) were screened out via Cytohubba algorithm. The results of both GO and KEGG enrichment analyses indicate that 7 hub genes play a significant role in regulating the inflammatory response, cytokine production in immune response, and the TNF signaling pathway. The most representative hub genes SOCS3 and PTGS2 were screened out by Series Test of Cluster, and ROC analysis results showed the AUC values were both up to 1.000. In addition, we found that PTGS2 expression was significantly elevated in the dorsal root ganglia and spinal cord in monosodium urate(MSU)-induced gout mouse model. The ELISA results revealed that the expression of SOCS3 and PTGS2 was notably higher in the acute gout attack and intermittent gout groups compared to the normal control group. This difference was statistically significant, indicating a clear distinction between the groups.
UNASSIGNED: Through cross-species comprehensive analysis and experimental verification, SOCS3 and PTGS2 were proved to be new biomarkers for diagnosing gout and predicting disease progression.

For canine parvovirus -2 (CPV-2), a zoonotic virus capable of cross-species transmission in animals, the amino acid changes of capsid protein VP2 are key factors when binding to other species\' transferrin receptors (TfR). CPV-2 variants can spread from felines and canines, for example, to Carnivora, Artiodactyla, and Pholidota species, and CPV-2c variants are essential to spread from Carnivora to Artiodactyla and Pholidota species in particular. In our study, a CPV-2a variant maintained a relatively stable trend, and the proportion of CPV-2c gradually rose from 1980 to 2021. The VP2 amino acid sequence analysis showed that five amino acid mutations at 426E/D, 305H/D, and 297S may be necessary for the virus to bind to different host receptors. Meanwhile, receptor-binding loop regions and amino acid sites 87 L, 93 N, 232I, and 305Y were associated with CPV-2 cross-species transmission. The homology of TfRs in different hosts infected with CPV-2 ranged from 77.2 % to 99.0 %, and from pig to feline, canine, and humans was 80.7 %, 80.4 %, and 77.2 %, respectively. The amino acid residues of TfRs involved in the viral binding in those hosts are highly conserved, which suggests that CPV-2 may be capable of pig-to-human transmission. Our analysis of the origin, evolutionary trend, cross-species transmission dynamics, and genetic characteristics of CPV-2 when binding to host receptors provides a theoretical basis for further research on CPV-2\'s mechanism of cross-species transmission and for establishing an early warning and monitoring mechanism for the possible threat of CPV-2 to animal-human public security.

Identifying polyphenotype genes that simultaneously regulate important agronomic traits (e.g., plant height, yield, and disease resistance) is critical for developing novel high-quality crop varieties. Predicting the associations between genes and traits requires the organization and analysis of multi-dimensional scientific data. The existing methods for establishing the relationships between genomic data and phenotypic data can only elucidate the associations between genes and individual traits. However, there are relatively few methods for detecting elite polyphenotype genes. In this study, a knowledge graph for traits regulating-genes was constructed by collecting data from the PubMed database and eight other databases related to the staple food crops rice, maize, and wheat as well as the model plant Arabidopsis thaliana. On the basis of the knowledge graph, a model for predicting traits regulating-genes was constructed by combining the data attributes of the gene nodes and the topological relationship attributes of the gene nodes. Additionally, a scoring method for predicting the genes regulating specific traits was developed to screen for elite polyphenotype genes. A total of 125,591 nodes and 547,224 semantic relationships were included in the knowledge graph. The accuracy of the knowledge graph-based model for predicting traits regulating-genes was 0.89, the precision rate was 0.91, the recall rate was 0.96, and the F1 value was 0.94. Moreover, 4,447 polyphenotype genes for 31 trait combinations were identified, among which the rice polyphenotype gene IPA1 and the A. thaliana polyphenotype gene CUC2 were verified via a literature search. Furthermore, the wheat gene TraesCS5A02G275900 was revealed as a potential polyphenotype gene that will need to be further characterized. Meanwhile, the result of venn diagram analysis between the polyphenotype gene datasets (consists of genes that are predicted by our model) and the transcriptome gene datasets (consists of genes that were differential expression in response to disease, drought or salt) showed approximately 70% and 54% polyphenotype genes were identified in the transcriptome datasets of Arabidopsis and rice, respectively. The application of the model driven by knowledge graph for predicting traits regulating-genes represents a novel method for detecting elite polyphenotype genes.

Over the last three years, the pandemic of COVID-19 has had a significant impact on people\'s lives and the global economy. The incessant emergence of variant strains has compounded the challenges associated with the management of COVID-19. As the predominant variant from late 2021 to the present, Omicron and its sublineages, through continuous evolution, have demonstrated iterative viral fitness. The comprehensive elucidation of the biological implications that catalyzed this evolution remains incomplete. In accordance with extant research evidence, we provide a comprehensive review of subvariants of Omicron, delineating alterations in immune evasion, cellular infectivity, and the cross-species transmission potential. This review seeks to clarify the underpinnings of biology within the evolution of SARS-CoV-2, thereby providing a foundation for strategic considerations in the post-pandemic era of COVID-19.

High-throughput in vitro assays combined with in vitro-in vivo extrapolation (IVIVE) leverage in vitro responses to predict the corresponding in vivo exposures and thresholds of concern. The integrated approach is also expected to offer the potential for efficient tools to provide estimates of chemical toxicity to various wildlife species instead of animal testing. However, developing fish physiologically based toxicokinetic (PBTK) models for IVIVE in ecological applications is challenging, especially for plausible estimation of an internal effective dose, such as fish equivalent concentration (FEC). Here, a fish PBTK model linked with the IVIVE approach was established, with parameter optimization of chemical unbound fraction, pH-dependent ionization and hepatic clearance, and integration of temperature effect and growth dilution. The fish PBTK-IVIVE approach provides not only a more precise estimation of tissue-specific concentrations but also a reasonable approximation of FEC targeting the estrogenic potency of endocrine-disrupting chemicals. Both predictions were compared with in vivo data and were accurate for most indissociable/dissociable chemicals. Furthermore, the model can help determine cross-species variability and sensitivity among the five fish species. Using the available IVIVE-derived FEC with target pathways is helpful to develop predicted no-effect concentration for chemicals with similar mode of action and support screening-level ecological risk assessment.

Despite recent advances in single-cell genomics, the lack of maps for single-cell candidate cis-regulatory elements (cCREs) in non-mammal species has limited our exploration of conserved regulatory programs across vertebrates and invertebrates. Here, we developed a combinatorial-hybridization-based method for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) named CH-ATAC-seq, enabling the construction of single-cell accessible chromatin landscapes for zebrafish, Drosophila, and earthworms (Eisenia andrei). By integrating scATAC censuses of humans, monkeys, and mice, we systematically identified 152 distinct main cell types and around 0.8 million cell-type-specific cCREs. Our analysis provided insights into the conservation of neural, muscle, and immune lineages across species, while epithelial cells exhibited a higher organ-origin heterogeneity. Additionally, a large-scale gene regulatory network (GRN) was constructed in four vertebrates by integrating scRNA-seq censuses. Overall, our study provides a valuable resource for comparative epigenomics, identifying the evolutionary conservation and divergence of gene regulation across different species.