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Background/Objectives: Tumor heterogeneity is reflected in cell composition, molecular states, spatial distribution, and microenvironment interactions. Spatial transcriptomics can map in situ expression and cell states but cannot fully explain upstream regulation, while spatial epigenomics provides complementary evidence such as chromatin accessibility, histone modifications, and deoxyribonucleic acid (DNA) methylation. This review summarizes the applications of spatial multi-omics and deep learning in prioritizing candidate drug targets in tumors. Methods: We reviewed spatial transcriptomics, spatial epigenomics, and combined sequencing technologies, with a focus on how deep learning supports the analysis and integration of spatial multi-omics data for candidate-target prioritization. Results: Deep learning facilitates the detection of abnormal regions, deciphering of cell origins, integration across samples, inference of cell–cell communication, and combination of imaging with omics data. Spatial multi-omics studies provide therapeutic insights into malignant cells, immunosuppression, stromal and vascular remodeling, and invasion and metastasis niches. Based on these applications, candidate targets can be evaluated in a layered manner according to spatial specificity, cell origin, regulatory consistency, reproducibility across patients, functional dependency, disease relevance, and druggability. Conclusions: Spatial multi-omics and deep learning can enhance the systematic and interpretable selection of candidate targets. However, computational associations cannot replace functional validation. Candidate targets still require verification through gene perturbation, drug sensitivity assays, organoids, animal models, and clinical cohorts to confirm their therapeutic potential. Full article

Peripheral blood mononuclear cells (PBMCs) are the most immunologically active and readily accessible fraction of whole blood, and they initiate host immune responses following infection and vaccination. Since PBMC transcriptomes capture diverse host–pathogen interactions, they offer a promising tool to uncover the genetic drivers of viral resistance and tolerance. As a detailed case study of this principle, we examine porcine reproductive and respiratory syndrome (PRRS), which remains one of the most economically important viral diseases of swine worldwide. Following PRRS virus (PRRSV) exposure, pigs rely on two complementary defense strategies: resistance, the capacity to limit viral replication, and tolerance, the capacity to sustain performance despite infection. Since resistance and tolerance phenotypes are difficult to measure directly through experimental challenge, indirect immune-trait measurements collected after vaccination offer a practical alternative. Most transcriptomic studies of the host response to PRRSV have focused on respiratory tissues, reflecting the virus’s tropism for pulmonary macrophages. However, intramuscularly delivered modified-live PRRSV vaccine reaches the bloodstream, bypassing the lung, so PBMCs, as the frontline defense system, mount the earliest measurable innate response. This review synthesizes the current literature on PBMC transcriptome models for deciphering innate resistance and tolerance to viral disease, using PRRS as our principal worked example; presents our own approach to profiling PBMCs after PRRSV vaccination; and outlines how the field has advanced since the original candidate-gene and QTL studies of the 2010s, including the recent FDA approval of the first CD163 gene-edited PRRSV-resistant pig line, and the emergence of single-cell and multi-tissue PBMC atlases, before considering how the same PBMC-based approach could extend to other host–virus interactions. Full article

To identify microRNAs (miRNAs) responsive to powdery mildew (PM) infection and elucidate their regulatory roles in melon PM resistance, thereby laying a foundation for deciphering the underlying molecular mechanisms, we combined high-throughput sequencing with bioinformatics analysis to screen PM-responsive miRNAs and their target genes using PM-resistant and PM-susceptible melon genotypes. In total, 113 non-redundant miRNAs were identified in both genotypes, including 70 known and 43 novel miRNAs. Subsequent differential expression analysis revealed distinct miRNA responses to PM infection between resistant and susceptible genotypes. Upon PM inoculation, 13 miRNAs showed significant differential expression in both susceptible and resistant genotypes. In addition, four miRNAs, including miR164c, miR396a, miR398a and miRn39, displayed differential expression specifically in the susceptible genotype. Conversely, five miRNAs (miR167c, miR398b, miR399g, miR530a and miRn8) showed differential expression exclusively in the resistant genotype upon PM infection. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses demonstrated that these miRNAs mediate melon’s susceptibility or resistance to PM by modulating plant immune homeostasis, antioxidant metabolism, and pathogen-triggered cell death. Quantitative real-time PCR (qRT-PCR) validation confirmed a negative regulatory relationship between the expression of PM-responsive miRNAs and their predicted target genes. Collectively, our findings provide novel insights and candidate targets for further investigations into miRNA functions and regulatory mechanisms underlying melon PM resistance. Full article

Background: Flavonoid secondary metabolites accumulate in xylem during heartwood formation and critically influence wood color and economic value. However, the distribution patterns of individual flavonoids across sapwood, transition zone, and heartwood remain poorly characterized in Castanopsis hystrix, limiting mechanistic understanding of heartwood formation and rational resource utilization. Methods: Sapwood, transition zone, and heartwood samples were collected and analyzed using ultra-performance liquid chromatography coupled with Q-Exactive Orbitrap mass spectrometry (UPLC-QE-MS) for qualitative and quantitative flavonoid determination. Multivariate statistical approaches, including hierarchical clustering, principal component analysis (PCA), and orthogonal partial least-squares discriminant analysis (OPLS-DA), were applied to compare regional metabolic profiles and to identify characteristic differential markers. Results: A total of 26 flavonoids were identified, covering flavones, flavonols, flavanones, dihydroflavonols, and flavanols. Quantitative and cluster analyses revealed distinct region-preferential accumulation: dihydrorobinetin, dihydromyricetin, morin, and kaempferol were highly enriched in heartwood; fustin, taxifolin, and cyanidin predominated in the transition zone, whereas afzelin and astilbin were more abundant in sapwood. PCA and OPLS-DA further selected four characteristic markers, namely dihydromyricetin, dihydrorobinetin, kaempferol and (−)-epicatechin, that effectively discriminated the three regions. Conclusions: This study establishes a clear radial gradient of flavonoid accumulation in C. hystrix xylem, demonstrating selective enrichment of specific metabolites from sapwood to heartwood. These findings provide essential data for deciphering the biochemical mechanisms of heartwood formation and offer a metabolic basis for quality assessment and high-value utilization of this timber species. Full article

The co-occurrence of liver cirrhosis (LC) and heart failure (HF) poses considerable clinical challenges, yet the cellular and molecular determinants of this comorbidity remain poorly characterized. To address this, we developed an integrative multi-omics pipeline encompassing GWAS meta-analysis, gsMap-based spatial transcriptomic projection, GeneEnrich functional annotation, single-cell atlas construction, seismicGWAS and ECLIPSER cell-type scoring, eCAVIAR and fastenloc colocalization, hdWGCNA network inference, scTenifoldKnk in silico gene perturbation, and GCTA-COJO fine-mapping. Quality-controlled meta-analysis yielded 12,347,758 and 9,256,862 variant-level associations for LC and HF, respectively. Spatial projection confirmed preferential enrichment of disease signals within embryonic hepatic and cardiac compartments. Pathway analyses disclosed that LC-linked loci were concentrated in lipid metabolic programs, whereas HF-linked loci implicated mitochondrial bioenergetics and lysosomal degradation. At the cellular level, endothelial cells emerged as the dominant HF-associated population. Convergent evidence from five orthogonal algorithms pinpointed CRIM1 as the sole robustly supported shared gene, selectively enriched in HF endothelial cells; virtual perturbation further identified LCP1 and PTPRC as downstream regulatory nodes. Fine-mapping of the chromosome 2 locus harboring rs12476437 revealed multiple statistically independent signals in the vicinity of CRIM1. Collectively, these findings computationally prioritize the endothelial–CRIM1 axis as a previously unappreciated candidate mechanistic bridge between LC and HF requiring experimental validation. Full article

Background: Despite the increasing use of vibration therapy (VT) in neurorehabilitation, its efficacy on post-stroke gait recovery remains controversial due to substantial heterogeneity in study protocols and outcome assessments. Previous systematic reviews have often aggregated disparate gait metrics and stroke stages, potentially obscuring domain-specific therapeutic effects and limiting clinical applicability. Furthermore, the specific influence of vibration parameters, such as frequency and amplitude, on gait outcomes has not been sufficiently quantified. Objective: This protocol outlines a systematic review and meta-regression analysis designed to rigorously evaluate the clinical efficacy of VT on the multidimensional recovery of gait function in stroke survivors. Unlike prior reviews, this study aims to decipher the heterogeneity of treatment effects by analyzing outcome variations based on specific gait domains and exploring associations between individual vibration parameters and treatment effect estimates. Methods: In adherence to PRISMA-P guidelines, a comprehensive search will be conducted across PubMed, Embase, Cochrane Library, Web of Science, and Scopus for randomized and non-randomized controlled trials involving adult stroke survivors. Interventions will include whole-body vibration (WBV) and focal muscle vibration (FMV) compared to sham or standard care. To address the multidimensional nature of gait, outcomes will be strictly categorized into four domains: (1) gait speed, (2) gait endurance, (3) functional mobility, and (4) spatiotemporal parameters. Methodological quality will be assessed using the Cochrane Risk of Bias 2 (RoB 2) and Risk of Bias In Non-randomized Studies of Interventions (ROBINS-I) tools. Data synthesis will utilize random-effects models, and prespecified meta-regression analyses will be employed to investigate the influence of key moderators, including vibration frequency, amplitude, and session duration. Discussion: This review aims to move beyond simple efficacy verification by exploring potential moderators of treatment effects and generating hypotheses regarding vibration parameters that may be associated with more favorable gait outcomes. By providing granular evidence across distinct gait domains and analyzing parameter-specific effects, this study is expected to resolve existing conflicting evidence and offer precise guidance for the clinical application of VT in post-stroke gait rehabilitation. Full article

To quantitatively characterize the pharmacokinetic and pharmacodynamic interactions between Hydroxysafflor Yellow A (HSYA) and Calycosin (CA) in cerebral ischemia–reperfusion injury (CIRI), a factorial experimental design was combined with a hierarchical coupled PK-PD modeling framework. The coupled PK model adequately described the concentration-time profiles of HSYA and CA under co-administration, with R² values of 0.83 and 0.86, respectively, while the PK-PD model showed good fitting performance for Caspase-3 and HIF-1α, with all R² values exceeding 0.97. Structural identifiability analysis showed that the newly introduced PK and PD coupling parameters were globally identifiable, and their Bootstrap 95% confidence intervals excluded zero. After Holm-Bonferroni correction, AUC_0-t, AUC_0-∞ and CL differed significantly between single and combined administration, whereas MRT did not. The model-derived relative contribution weights of HSYA and CA were quantified for both Caspase-3 and HIF-1α, with uncertainty assessed using Bootstrap 95% confidence intervals. Overall, the proposed coupled PK-PD framework provides a quantitative approach for characterizing component interactions and relative pharmacodynamic contributions in multi-component systems. Full article

Coral aggregate seawater concrete (CASC) capitalizes on locally sourced aggregates in marine and reef engineering, enabling in situ material utilization and conferring marked benefits in curbing conventional resource consumption and construction expenditures—a combination that underpins its considerable promise for reef infrastructure development. To date, research efforts have largely been confined to macroscopic mechanical characterization and qualitative microstructural inspections, and quantitative assessments of mesoscopic damage evolution across the full loading-to-failure process remain relatively scarce. In response, to quantitatively characterize the mesoscopic damage evolution mechanism of CASC with different natural aggregates, the present study draws upon statistical damage theory and incorporates uniaxial compressive stress–strain responses from CASC mixtures formulated with four replacement ratios (0%, 33%, 67%, and 100%) of natural coarse and fine aggregates, thereby establishing a statistical damage constitutive model. The model is intentionally structured to decipher the intricate interplay that translates progressive mesoscopic deterioration into the eventual macroscopic mechanical signature, rather than merely describing phenomenological curves. The outcomes reveal favorable concordance between model-generated predictions and experimental measurements. Introducing natural aggregates appreciably modulates the cumulative damage trajectory at the mesoscale; with rising replacement ratios, the macroscopic mechanical performance of CASC is systematically fortified, concomitant with orderly shifts in characteristic damage indices (ε_a, ε_b, ε_h and H). Specifically, when the replacement ratio of natural fine aggregate is fixed at 0%, as the replacement ratio of natural coarse aggregate increases from 0% to 100%, the values of ε_a, ε_b, ε_h, and H increase by 35.8%, 36.9%, 32.2%, and 66.5%, respectively. Additionally, both the fracture damage variable D_R and the integrated transverse strain area derived from digital image correlation (DIC) exhibit monotonic ascending trends as loading advances. Collectively, these contributions offer a theoretical foundation for performance optimization and a deeper mechanistic understanding of damage behavior in CASC. Full article

Panax ginseng (Panax ginseng C.A. Mey.) produces pharmacologically valuable ginsenosides. WD40-repeat (WDR) proteins act as versatile regulators of plant specialized metabolism, yet their biological roles under methyl jasmonate (MeJA) elicitation remain largely uncharacterized in ginseng. In this study, we identified 29 PgWDR family members at the whole-genome level, and systematically analyzed their phylogeny, gene structure, cis-acting promoter elements, as well as organ- and development-dependent expression patterns. Six candidate genes potentially associated with ginsenoside biosynthesis were screened through integrating gene–metabolite correlation analysis and gene co-expression analysis. Under MeJA treatment, three of these candidates showed statistically significant expression responses, while the other three exhibited variable expression fluctuations with no statistical significance. PgWDR24 displayed a positive correlation with key ginsenoside biosynthetic enzyme genes, and a negative correlation with protopanaxadiol-type ginsenoside accumulation. Combined with its predicted nuclear localization, we hypothesize that PgWDR24 participates in the negative modulation of protopanaxadiol-type ginsenoside accumulation, although further genetic functional validation is still required. This work provides valuable candidate genes for deciphering ginsenoside regulatory networks and offers support for molecular-assisted breeding of high-quality ginseng. Full article

Alcohol dehydrogenase (ADH) catalyzes the reduction of aldehydes to alcohols, key precursor substrates for volatile ester biosynthesis, which determines the characteristic aroma of apple fruit. However, a comprehensive genome-wide investigation of the ADH gene family in apple has been lacking. In this study, we systematically identified ADH genes in the apple genome using integrated bioinformatics approaches, including phylogenetic analysis, synteny evaluation, promoter cis-element prediction, codon usage bias assessment, and protein interaction network modeling. Expression patterns were examined through transcriptomic data and validated by RT-qPCR analysis across different organs and among ‘Red Delicious’ and its four bud mutant lines. We identified 44 ADH genes, with 12 forming a prominent cluster on chromosome 1. RT-qPCR analysis revealed that MdADH20 was dramatically upregulated in the ‘Red Chief’ mutant (relative expression of 59.38), suggesting its pivotal role. Phylogenetic analysis revealed a close evolutionary relationship with wild strawberry. The encoded proteins were generally stable and predominantly localized to the cytoplasm. Promoter analysis showed enrichment of growth/development-related and ARE elements, while codon usage analysis identified AGA, GCU, GUU, and CUU as preferred codons. Protein interaction prediction suggested MdADH19 and MdADH20 as hub proteins. Expression profiling and RT-qPCR further identified MdADH20 as a core candidate gene, characterized by its stable and high expression, particularly in the ‘Red Delicious’ mutant. Its central position in the predicted protein–protein interaction network suggests a potential regulatory role in the aroma biosynthesis pathway of apple fruit. This study provides the first systematic genome-wide characterization of the apple ADH gene family, establishing a theoretical groundwork for deciphering aroma biosynthesis mechanisms and offering potential target genes for flavor improvement through bud mutation breeding strategies. Full article

The mycelium of Phallus rubrovolvatus contains abundant metabolites with broad application prospects in functional foods and pharmaceuticals. However, how carbon and nitrogen substrate availability regulate the accumulation dynamics of mycelial metabolites remains under-explored. In this study, the supply levels of carbon (glucose) and nitrogen (peptone) were optimized to select high-biomass mycelia. Integrating nutritional activity assays with metabolomics and redundancy analysis, the regulatory mechanisms governing carbon–nitrogen metabolic flux were deciphered. The results demonstrated that mycelial nutritional content and antioxidant capacity exhibited a progressive upward trend under three distinct modes: carbon-driven, nitrogen-driven, and carbon–nitrogen synergistic-driven regimes. In the optimal carbon–nitrogen synergistic-driven group, the contents of total soluble sugars, reducing sugars, flavonoids, total phenolics, and soluble proteins increased by 72.06%, 160.80%, 52.47%, 113.69%, and 8.21%, respectively, compared with the control group. Meanwhile, the scavenging rates of superoxide anion, hydroxyl, ABTS, and DPPH free radicals increased by 14.12%, 24.09%, 14.77%, and 66.47%, respectively, compared with the control group. Differentially accumulated metabolites were significantly enriched in amino acid metabolism, energy metabolism, and secondary metabolite biosynthesis pathways. Carbon and nitrogen substrates reshaped intracellular metabolic flux, cooperatively regulating nutrient synthesis and intracellular redox equilibrium. This work reveals a cascade-linking relationship in which nutrient supply triggers metabolic remodeling, regulates oxidative balance, and drives pathway response. It provides theoretical support for the precision fermentation and industrial upgrade of P. rubrovolvatus, while offering a valuable reference paradigm for the high-value exploitation of other rare edible and medicinal fungi. Full article

Understanding the hydrochemical characteristics of groundwater in coal mining subsidence areas is of critical scientific significance for water environment protection and ecological restoration in mining regions. A systematic hydrochemical campaign was undertaken in the Luwa collapse zone (Jining city, Shandong Province) to decipher the composition, evolutionary behavior, and governing factors of groundwater within a high-water-table subsidence context. The analytical protocol comprised three complementary components: conventional hydrochemical profiling, ion-ratio-based source identification, and multivariate statistical modeling. The findings revealed that the groundwater in the study area was weakly alkaline (pH = 7.33 ± 0.217), with total dissolved solids (TDS) ranging from 1180 to 2280 mg/L, and all sampled sites exceeded the Class III groundwater quality standard of China. Na⁺, SO₄²⁻, and Cl⁻ were identified as the predominant pollutants, with exceedance rates of 91.3%, 95.7%, and 91.3%, respectively, which were primarily attributed to coal mine drainage and domestic sewage input. The groundwater chemical composition was governed by the combined effects of rock weathering, evaporation–concentration processes, and anthropogenic activities. Specifically, Na⁺ and Cl⁻ originated mainly from the dissolution of silicate minerals and halite, as well as domestic sewage input; SO₄²⁻ was primarily controlled by evaporite dissolution and industrial wastewater discharge; carbonate and silicate mineral weathering was identified as the primary source of Ca²⁺ and Mg²⁺; and NO₃⁻ was predominantly influenced by agricultural activities. Principal component analysis (PCA) extracted three major controlling factors shaping the groundwater hydrochemistry in this area, namely: (1) evaporite dissolution and sewage input, (2) carbonate dissolution and pH buffering processes, and (3) agricultural input. This study reveals a dual-driven evolutionary model of groundwater in high-water-table coal mining subsidence areas, characterized by “natural enrichment superimposed by anthropogenic input,” whose work contributes to the knowledge base for sustainable groundwater stewardship and contamination risk reduction in mining-affected areas with analogous conditions. Full article

Monitoring vegetation dynamics in drylands and disentangling their driving mechanisms are essential for deciphering vegetation–climate feedbacks and supporting targeted ecological restoration. Taking the Circum-Tarim Basin as the study region, this study adopted the modified soil-adjusted vegetation index (MSAVI) as a vegetation proxy and integrated multiple statistical approaches to quantify spatiotemporal vegetation variations across four land-use types from 2000 to 2021. The relative importance of time-lag and cumulative climatic effects on vegetation growth were evaluated for specific land-use types. The main results show that: (1) Widespread vegetation greening occurred across the study area, and croplands dominated this positive trend. (2) Vegetation generally exhibited more immediate responses to climate change in cropland and woodland, whereas grassland and unused land showed more heterogeneous, lagged responses. (3) Despite the inherently low absolute R² values typical of hyper-arid pixel-scale modeling, climate models incorporating cumulative and lagged effects showed substantial relative improvements in explanatory power (ΔR²) compared to contemporaneous models, particularly in cropland and woodland. These improvements were consistently retained under out-of-sample validation (positiveΔCV-R²). These findings highlight the importance of considering land-use-specific lagged and cumulative climate effects when assessing dryland vegetation–climate interactions, which provides useful implications for ecological restoration and climate adaptation in arid basins. Full article

Lentinula edodes is renowned for its unique aroma, which is characterized by various volatile sulfur-containing flavor metabolites (SCFMs). Cysteine and methionine could enhance the SCFMs biosynthesis in L. edodes; however, the underlying metabolic pathways remain unclear. To bridge this gap, integrated proteomic and metabolomic analysis were performed to decipher pathways through which cysteine and methionine regulate SCFM biosynthesis. Results showed that exogenous cysteine and methionine supplementation significantly increased the content of lenthionine, the key aroma compound of shiitake mushrooms. Both treatments induced substantial changes in the proteomic and metabolomic profiles. Proteomic analysis revealed that differentially expressed proteins were predominantly enriched in cysteine and methionine metabolism and sulfur metabolism following cysteine treatment, whereas methionine treatment mainly affected proteins associated with tryptophan metabolism and sulfur metabolism. Metabolomic analysis showed that differentially accumulated metabolites were significantly enriched in D-amino acid metabolism and cysteine and methionine metabolism, with glutathione metabolism specifically enriched under cysteine treatment. Integrated omics analysis further uncovered distinct sulfur metabolite–protein regulatory networks under different sulfur nutrition and identified treatment-specific hub proteins. These findings establish a molecular regulatory framework linking SCFM biosynthesis with broader primary metabolic pathways involved in sulfur intermediate generation and regulation, providing new insights into the potential regulatory networks underlying SCFM formation in L. edodes. Full article

The ubiquitin-proteasome system (UPS) constitutes a highly conserved regulatory hub governing protein turnover and signal transduction in eukaryotes, which precisely determines the fate of substrate proteins via dynamic and reversible ubiquitination. During long-term coevolution between plants and viruses, the UPS has evolved into a critical battlefield for host–virus arms races. Plants exploit the substrate recognition specificity and proteolytic activity of the UPS to selectively eliminate essential viral proteins required for infection, thereby establishing multilayered antiviral immune barriers. In contrast, viruses have evolved diverse effector proteins to antagonize or hijack this pathway to facilitate their replication and spread. Competitive exploitation of this shared regulatory machinery underlies the fundamental logic of bidirectional regulation in plant–virus interactions. This review systematically summarizes the molecular basis of UPS-mediated plant antiviral immunity, as well as convergent pathogenic strategies adopted by diverse viruses to perturb ubiquitin signaling, suppress host immune responses, and reprogram the intracellular environment. The work aims to provide theoretical insights for deciphering viral pathogenesis and breeding crops with durable virus resistance. Full article