Shiou Yih Lee

Aging is a multifactorial biological process characterized by progressive alterations in cellular homeostasis, metabolic regulation, immune function, and neurological integrity, contributing to chronic disease, functional decline, and reduced healthspan. Natural bioactive compounds are increasingly investigated as potential geroprotective agents because of their ability to modulate multiple pathways associated with biological aging. Polyphenols, alkaloids, terpenoids, peptides, and related phytochemicals have demonstrated antioxidant, anti-inflammatory, neuroprotective, metabolic, and immunomodulatory effects. However, modulation of aging-related pathways should be distinguished from direct evidence of lifespan extension. Medicinal plants, traditional medicine, and locally consumed functional foods represent important yet comparatively underexplored sources of bioactive compounds with potential relevance to healthy aging. This review synthesizes molecular, cellular, preclinical, and clinical evidence on medicinal plants and their bioactive constituents, with emphasis on neuroprotection, metabolic homeostasis, and immune regulation. Key mechanisms include modulation of oxidative stress, mitochondrial function, nutrient-sensing pathways, autophagy, cellular senescence, neuroinflammation, and chronic low-grade inflammation. Advances in analytical chemistry, molecular docking, network pharmacology, and multi-omics approaches are also considered for their role in strengthening mechanistic characterization and identifying potential responder profiles. Overall, current evidence supports further investigation of medicinal plants as candidate modulators of biological aging and healthspan-related processes, while emphasizing the need for standardized preparations, robust clinical studies, and mechanistically informed translational research.

Artocarpus nobilis Thwaites 1861, an endemic species to the wet tropical regions of southwestern Sri Lanka, is commonly known as Ceylon breadfruit or wal dhel (wal-del) by the locals (Madushani et ...

Oleamide, a naturally occurring compound that stimulates acetylcholine synthesis via the CB1 receptor, is vital for human physiology. This research aims to investigate the cannabinoid-like activity of oleamide-containing plants, focusing on their mechanism of action via the endocannabinoid-like receptor system. We quantified oleamide levels and evaluated the bioactivity, cytotoxicity, and genotoxicity of six plant extracts: the leaves of four Dillenia species (D. obovata, D. ovata, D. indica, and D. pentagyna), and the seeds of Cucurbita moschata and Cannabis sativa spp. sativa. Oleamide was detected in all extracts (0.06 to 0.11 mg/g). While no cytotoxicity was observed, the four Dillenia species extracts induced significant DNA damage in PBMCs and HepG2 cells (p< 0.01). The D. indica extract also damaged DNA in THLE-3 cells. Furthermore, all six extracts stimulated the expression of CB1 and ChAT genes in THLE-3 cells at various concentrations. Specifically, D. obovata increased CB1 gene expression by 318.2%–557.8% (at 1.7 and 0.017 mg/mL), while Cucurbita moschata increased ChAT gene expression by 236.3% at 0.263 mg/mL. These results indicate that the oleamide content in these extracts effectively promotes acetylcholine synthesis by inducing both the CB1 receptor and the ChAT enzyme in THLE-3 cells, suggesting potential applications in human health.

Diabetes mellitus is a chronic metabolic disorder that affects millions of people globally. Among three types of diabetes, Type 2 diabetes mellitus (T2DM) is a rapidly growing global health challenge. Despite available modern antidiabetic drugs, patients still struggle with side effects and treatment failure, as an alternative to this, there is a crucial requirement to develop a potential and traditional plant-based medicine which could be a safer sources and multi-target therapies to treat chronic disease like diabetes. Solanum lasiocarpum ( S. lasiocarpum ) is a sour fruit-vegetable being widely used in Southeast Asia as both food and traditional medicine, including for the management of diabetes. However, its active components and antidiabetic mechanisms have not been systematically explored. In this study, we combined metabolomics, proteomics, and transcriptomics to investigate the bioactive pathways and potential molecular targets of S. lasiocarpum . Untargeted UHPLC–QTOF–MS profiling identified 45 candidate bioactive compounds with good predicted gastrointestinal absorption, and the network pharmacology analysis linked these compounds to 43 diabetes-related human targets. Protein–protein interaction analysis highlighted several core nodes, including TNF , PPARG , IL6 , AKT1 , and STAT3 , and functional enrichment suggested roles in hormone regulation, inflammation, glucose and lipid metabolism, and vascular function. De novo transcriptome assembly and data-independent acquisition-based proteomics of mature S. lasiocarpum fruit showed that central carbon metabolism is highly active and that the shikimate, phenylpropanoid, and flavonoid pathways are strongly expressed at both gene and protein levels. Key enzymes such as EPSPS , PAL , C4H , 4CL , CHS , CHI , F3H , and FLS formed a coherent biosynthetic network supporting sustained production of phenolic and flavonoid metabolites. Integrating these omics layers with target prediction suggests that S. lasiocarpum may exert antidiabetic effects by modulating a TNF–PPARG axis, reducing pro-inflammatory signaling while supporting insulin-sensitizing pathways. Overall, these results support the traditional use of S. lasiocarpum and provide a multi-omics resource to prioritise candidate metabolites, enzymes and targets for follow-up studies. As the pathway links were inferred computationally, the proposed TNF–PPARG -centred mechanism should be regarded as hypothesis-generating and will require validation in experimental models and, ultimately, well-designed human intervention trials.

Solanum lasiocarpum Dunal. is a medicinal plant with medicinal properties for minor human diseases. To generate additional genomic resources for this species, we sequenced and characterised plastomes from seven S. lasiocarpum accessions collected in Malaysia, Indonesia, and Thailand. The seven plastomes range from 155,616 to 156,854 bp and each contains 128 genes. We identified 43–46 simple sequence repeats and 32–37 long repeats per plastome, with a strong bias towards A/T-rich motifs. Two indels and three highly variable regions ( pet A, pet A– psb J, rpl 32– trn L-UAG) were detected. The intraspecific pairwise distance between the previously published Hainan accession, SLHN (GenBank accession no.: PP234975), and the seven new accessions was 0.001. Phylogenetic analyses based on both complete plastomes and protein-coding sequences (CDS) recovered SLHN as the earliest-diverging lineage, followed by a split into two major clades. In the plastome-tree, the Mantin (SLMT), Serian (SLSR), and Phukhieo (SLTH) accessions formed one clade, whereas the Lachau (SLLC), Pontianak (SLPT), Sibu (SLSB), and Sibu wild (SLSW) accessions grouped together. In the CDS-tree, SLMT and SLTH clustered together, separate from the SLLC + SLPT + SLSR + SLSB + SLSW clade. Most internal branches received low statistical support in both trees. These results provide new insights into intraspecific plastome variation in S. lasiocarpum and establish a comparative framework to support marker development, molecular breeding, and future phylogenetic and evolutionary studies in Solanum .

Physalis minima L. is an herbaceous plant with ethnobotanic importance across many Asian cultures. In this study, we sequenced and assembled the plastid genome (plastome) of a P. minima sample from Malaysia, and conducted intraspecific pairwise and phylogenetic analyses with available data of its relatives. Our sample had a plastome of 156,973 bp in size with a GC content of 37.5%. The genome was circular, consisting of a large single-copy of 87,196 bp, a small single-copy of 18,447 bp, and a pair of inverted repeats of 25,665 bp each. A total of 129 genes were annotated, including 84 CDSs, 37 tRNAs, and eight rRNAs. Between the China and Malaysia accession, 458 variable sites were identified, and the pairwise distance was 0.003. Phylogenetic analysis was conducted using the complete plastome sequence based on the maximum likelihood and Bayesian inference methods. The findings revealed that our sample was significantly differentiated from the accession from China, and that both P. minima accessions clustered away from P. angulata, the synonym suggested by certain taxonomic authorities. This study facilitates precise taxonomic identification of P. minima within ethnomedicinal frameworks, enabling its distinction from closely related or putatively synonymous species that may exhibit divergent phytochemical compositions. These results provide important insights into the genetic diversity and taxonomic status of P. minima, and support its informed use in future research, conservation and medicinal applications.

Gastric diseases represent a significant challenge to global health. A comprehensive understanding of their complex molecular mechanisms, particularly the pathways of molecular progression in precancerous lesions, is essential for enhancing diagnosis and treatment. StomachDB, the first comprehensive multi-omics database dedicated to gastric diseases, has been developed to address these research needs. This database integrates 6 types of biological data: genomics, transcriptomics, emerging single-cell and spatial transcriptomics, proteomics, metabolomics, and therapeutic-related information. It encompasses 44 gastric-related pathologies, including various forms of gastric cancer, gastric ulcers, and gastritis, primarily involving humans and mice as model organisms. The database compiles approximately 2.5 million curated and standardized profiles, along with 268,394 disease-gene associations. The user-friendly analytics platform provides tools for browsing, querying, visualizing, and downloading data, facilitating systematic exploration of multi-omics features. This integrative approach addresses the limitations of single-omics analyses, such as data heterogeneity and insufficient analytical dimensions. Researchers can investigate the clinical significance of target genes (e.g., CDH1) across different omics levels and explore potential regulatory mechanisms. Furthermore, StomachDB emphasizes the discovery of therapeutic targets by cataloging interactions among chemical drugs, traditional herbal medicines, and probiotics. As an open-access resource, it serves as a powerful tool for studying complex biological interactions and regulatory mechanisms.

This study quantitatively examined the implementation and effectiveness of the Blended Teaching Mode (BTM) in primary and secondary schools in Ganzhou, Jiangxi Province, China, within the context of national educational digitalization initiatives. Guided by the Community of Inquiry (CoI) framework and the Technology Acceptance Model (TAM), a cross-sectional survey design was employed. Using stratified random sampling, 235 valid responses were collected from administrators (n=25), teachers (n=60), and students (n=150) across public and private schools in urban, suburban, and rural settings. Data were gathered through validated questionnaires and analyzed using descriptive statistics, correlation analysis, ANOVA, and structural equation modeling (SEM). Results indicated that stakeholder perceptions of BTM effectiveness were generally neutral (mean ≈3.0/5), reflecting a transitional stage of adoption. Student participation (β=0.746, p<.001) and teacher development (β=0.268, p=.005) emerged as significant predictors of effectiveness, whereas management and assessment mechanisms showed no direct effects. Contextual differences were evident, with private school students demonstrating higher participation, public school students reporting stronger perceptions of technology utility, suburban students showing lower engagement than urban and rural peers, and teachers rating BTM effectiveness more positively than administrators or students. Theoretically, the study extends the application of CoI and TAM to basic education. Practically, it highlights the importance of enhancing teacher digital competence, fostering student engagement, tailoring blended models to local contexts, and employing data-driven evaluation to support sustainable educational digitalization.

This study aims to investigate the application of music therapy and its impact on the mental health of students in colleges and universities in Zhumadian City. As a large population province in China, Henan Province, its college and university students are facing great learning pressure and challenges of further education, and students' mental health problems are becoming more and more prominent. Based on affective education theory and social learning theory, this study analyzes the effects of three factors, instrument choice, treatment intensity and cognitive regulation, on mental health. Ultimately, it helps colleges and universities create an environment with a high degree of support for mental health development. Music therapy, as a non-pharmacological intervention, has the potential to address students' psychological stress. This paper adopts a quantitative research method, using spss for analysis, combined with an online questionnaire to collect feedback from 404 students from three colleges and universities in Zhumadian City, Henan Province, focusing on analyzing the impact of factors such as musical instrument choices, music therapy intensity, and cognitive regulation on students' mental health. The questionnaire survey of the students found that appropriate musical instrument selection and therapy intensity significantly reduced anxiety levels. Reduced academic stress and increased their mental toughness. This finding provides empirical evidence for integrating music therapy in student mental health support strategies in colleges and universities in Zhumadian City, which has important practical significance and guiding value.

In the evolving landscape of arts education, teachers encounter a distinctive combination of emotional labour, creative demands, and institutional uncertainty. This study examined the influence of motivation and incentive mechanisms on job performance and job satisfaction among arts educators in China, with dance teachers serving as the focal case group. Guided by Self-Determination Theory and Herzberg’s Two-Factor Theory, a conceptual framework was developed to integrate intrinsic psychological needs with extrinsic organisational rewards. A quantitative, cross-sectional design was employed using a structured questionnaire distributed to teachers in private arts institutions. Correlation and regression analyses were conducted to assess the relationships between intrinsic motivation, extrinsic incentives, job performance, and job satisfaction. The results highlight the significant roles of both intrinsic and extrinsic factors in shaping professional engagement and well-being. These findings provide practical insights for the development of sustainable human resource practices and motivation-sensitive policies in the growing arts education sector.