Developing new plant varieties plays a crucial role in competitiveness in the agricultural and food industries and enhancing food security. Daehong (DH) is a new variety of Crataegus pinnatifida Bunge (CP); however, its physiological functions and potential as a nutraceutical ingredient remain unknown. Here, the efficacy of DH on inflammatory bowel disease (IBD) was investigated using dextran sulfate sodium (DSS)-induced colitis mice, and its relative pharmacological effects were analyzed against CP. DH improved colitis-induced weight loss, colon shortening, and inflammatory responses and reduced intestinal permeability. The reactive oxygen species (ROS)-mediated necroptotic signal that triggers enterocyte cell death in DSS-induced colitis was effectively controlled by DH, attributed to epicatechin. DSS-induced gut dysbiosis was recovered into a healthy gut microbiome environment by DH, increasing beneficial bacteria, like Akkermansia muciniphila, and changing harmful bacteria, including Bacteroides vulgatus and Peptostreptococcaceae. DH shows potential as a dietary or pharmaceutical ingredient to promote gut health and to prevent and treat IBD.

Schizophrenia genome-wide association studies (GWAS) have reported many genomic risk loci, but it is unclear how they affect schizophrenia susceptibility through interactions of multiple SNPs. We propose a stepwise deep learning technique with multi-precision data (SLEM) to explore the SNP combination effects on schizophrenia through intermediate molecular and cellular functions. The SLEM technique utilizes two levels of precision data for learning. It constructs initial backbone networks with more precise but small amount of multilevel assay data. Then, it learns strengths of intermediate interactions with the less precise but massive amount of GWAS data. The learned networks facilitate identifying effective SNP interactions from the intractably large space of all possible SNP combinations. We have shown that the extracted SNP combinations show higher accuracy than any single SNPs and preserve the accuracy in an independent dataset. The learned networks also provide interpretations of molecular and cellular interactions of SNP combinations toward schizophrenia etiology.

Pain is a ubiquitous nonmotor symptom in Parkinson’s disease (PD), substantially impairing quality of life. Although pharmacological and surgical interventions provide partial relief, effective treatment for PD‐associated pain remains limited. Pharmacopuncture, an injection of herbal extracts into acupoints, has demonstrated potential in pain management. This study evaluated the analgesic and neuroprotective effects of SU‐Eohyeol pharmacopuncture (SUEHP) in a 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP)–induced PD mouse model. C57BL/6N male mice received repeated intraperitoneal injections of MPTP to induce PD‐related pain. SUEHP was bilaterally administered at the GB34 acupoint or a control site. Pain sensitivity and motor function were evaluated, followed by postsacrifice histological assessments. Administration of SUEHP at GB34 significantly attenuated MPTP‐induced mechanical hypersensitivity and spinal c‐Fos expression, enhanced tyrosine hydroxylase and brain‐derived neurotrophic factor expression in the substantia nigra, and partially restored motor function. However, cotreatment with a CB1 or PPARγ antagonist eliminated these analgesic and neuroprotective effects, suggesting that SUEHP mediates its effects through specific pathways. Transcriptomic profiling of the midbrain and spinal cord revealed that SUEHP modulated inflammation, dopaminergic neurogenesis, and synaptic signaling pathways, which were typically reversed using cotreatment with CB1 or PPARγ antagonist. Collectively, SUEHP alleviates PD‐associated pain and neurodegeneration through CB1 and PPARγ pathways, suggesting its potential as a safe, noninvasive complementary therapy for PD symptom management.