Polygonati Rhizoma demonstrates significant potential for addressing both chronic and hidden hunger. The supply of high-quality seedlings is a primary factor influencing the development of the Polygonati Rhizoma industry. Warm water soaking is often used in agriculture to promote the rapid germination of seeds, while its application and molecular mechanism in Polygonati Rhizoma have not been reported. To rapidly obtain high-quality seedlings, this study treated Polygonatum kingianum var. grandifolium seeds with sand storage at low temperatures, warm water soaking, and cultivation temperature gradients. The results showed that the culture at 25 ℃ or sand storage at 4 ℃ for 2 months rapidly broke the seed dormancy of P. kingianum var. grandifolium, while the culture at 20 ℃ or sand storage at 4 ℃ for 1 month failed to break the seed dormancy. Soaking seeds in 60 ℃ warm water further increased the germination rate, germination potential, and germination index. Specifically, the seeds soaked at 60 ℃ and cultured at 25 ℃ without sand storage treatment(Aa25) achieved a germination rate of 78. 67%±1. 53% on day 42 and 83. 40%±4. 63% on day 77. The seeds pretreated with sand storage at 4 ℃ for 2 months, soaked in 60 ℃ water, and then cultured at 25 ℃ achieved a germination rate comparable to that of Aa25 on day 77. Transcriptomic analysis indicated that warm water soaking might promote germination by triggering reactive oxygen species( ROS), inducing the expression of heat shock factors( HSFs) and heat shock proteins( HSPs), which accelerated DNA replication, transcript maturation, translation, and processing, thereby facilitating the accumulation and turnover of genetic materials. According to the results of indoor controlled experiments and field practices, maintaining a germination and seedling cultivation environment at approximately 25 ℃ was crucial for the one-year seedling cultivation of P. kingianum var. grandifolium.
Germination ; Seedlings/genetics* ; Water/metabolism* ; Seeds/metabolism* ; Polygonatum/genetics* ; Temperature ; Plant Proteins/genetics* ; Plant Dormancy

The patient, assigned female at birth and aged 1 year and 7 months, presented with clinical manifestations of 46,XY disorders of sex development. The external genitalia exhibited a severely undermasculinized phenotype. Laboratory tests and gonadal biopsy indicated poor Leydig cell function and good Sertoli cell function. Genetic testing revealed compound heterozygous mutations of c.867-2A>C and c.547G>A (p.G183R) in the LHCGR gene. The patient was ultimately diagnosed with type II Leydig cell hypoplasia. Type II Leydig cell hypoplasia presents a broad spectrum of clinical phenotypes, characterized by a lack of parallel function between Leydig cells and Sertoli cells, and significant individual variability in spermatogenesis and gender assignment. This condition should be considered when there is poor Leydig cell function but good development of Wolffian duct derivatives.
Female ; Humans ; Infant ; Disorder of Sex Development, 46,XY/genetics* ; Leydig Cells/pathology* ; Mutation ; Receptors, LH/genetics* ; Testis/abnormalities*

OBJECTIVE: To investigate the clinical application value of artificial intelligence (AI)-based bone marrow cell recognition and analysis system in the diagnosis of hematological diseases. METHODS: The bone marrow smears of hematological patients who were admitted to The Second Hospital of Shanxi Medical University from 2018 to 2020 were retrospectively analyzed. A total of 115 bone marrow smears with clear diagnosis and typical cell morphology characteristics were selected, including 20 cases of immune thrombocytopenia(ITP), 11 cases of iron deficiency anemia (IDA), 17 cases of megaloblastic anemia (MA), 20 cases of chronic myeloid leukemia (CML), 17 cases of acute lymphoblastic leukemia (ALL), 23 cases of acute promyelocytic leukemia (APL), and 7 cases of acute myeloid leukemia unclassified (AML-M2). The samples were analyzed by manual microscopic examination, AI automatic recognition, and manual correction after AI recognition. RESULTS: The images captured by the AI device were clear, and the cell morphological structures were distinct. The average experimental diagnostic efficiency parameters of the bone marrow nucleated cells classified in this system were calculated. The sensitivity was 74.90%, specificity was 99.03%, and accuracy was 98.29%. In the comparison between the AI recognition group and the manual examination group, the data of IDA, ITP, MA, and CML diseases were all greater than 0.85 in ICC correlation coefficient, with excellent consistency; the data of APL, AML-M2, and ALL three diseases were between 0.6 and 0.85 in ICC correlation coefficient, with moderate consistency. However, after manual review and correction, the ICC correlation coefficient between the data of the AI correction group and the data from the manual examination group was greatly improved. CONCLUSION The AI bone marrow cell recognition and analysis system has the characteristics of high accuracy, high specificity, good sensitivity and fast detection. When used in combination with manual review, it can improve the detection efficiency of bone marrow cells morphological analysis and meet the needs of clinical work.
Humans ; Artificial Intelligence ; Hematologic Diseases/diagnosis* ; Bone Marrow Cells/pathology* ; Retrospective Studies

OBJECTIVE: To assess the efficacy of Qingda Granule (QDG) in ameliorating hypertension-induced cardiac damage and investigate the underlying mechanisms involved. METHODS: Twenty spontaneously hypertensive rats (SHRs) were used to develope a hypertension-induced cardiac damage model. Another 10 Wistar Kyoto (WKY) rats were used as normotension group. Rats were administrated intragastrically QDG [0.9 g/(kg•d)] or an equivalent volume of pure water for 8 weeks. Blood pressure, histopathological changes, cardiac function, levels of oxidative stress and inflammatory response markers were measured. Furthermore, to gain insights into the potential mechanisms underlying the protective effects of QDG against hypertension-induced cardiac injury, a network pharmacology study was conducted. Predicted results were validated by Western blot, radioimmunoassay immunohistochemistry and quantitative polymerase chain reaction, respectively. RESULTS: The administration of QDG resulted in a significant decrease in blood pressure levels in SHRs (P<0.01). Histological examinations, including hematoxylin-eosin staining and Masson trichrome staining revealed that QDG effectively attenuated hypertension-induced cardiac damage. Furthermore, echocardiography demonstrated that QDG improved hypertension-associated cardiac dysfunction. Enzyme-linked immunosorbent assay and colorimetric method indicated that QDG significantly reduced oxidative stress and inflammatory response levels in both myocardial tissue and serum (P<0.01). CONCLUSIONS Both network pharmacology and experimental investigations confirmed that QDG exerted its beneficial effects in decreasing hypertension-induced cardiac damage by regulating the angiotensin converting enzyme (ACE)/angiotensin II (Ang II)/Ang II receptor type 1 axis and ACE/Ang II/Ang II receptor type 2 axis.
Animals ; Drugs, Chinese Herbal/therapeutic use* ; Hypertension/pathology* ; Renin-Angiotensin System/drug effects* ; Rats, Inbred SHR ; Oxidative Stress/drug effects* ; Male ; Rats, Inbred WKY ; Blood Pressure/drug effects* ; Myocardium/pathology* ; Rats ; Inflammation/pathology*

OBJECTIVE: To explore the therapeutic effects and underlying mechanisms of Dendrobium officinale (Tiepi Shihu) extract (DOE) on insomnia. METHODS: Forty-two male Sprague-Dawley rats were randomly divided into 6 groups (n=7 per group): normal control, model control, melatonin (MT, 40 mg/kg), and 3-dose DOE (0.25, 0.50, and 1.00 g/kg) groups. Rats were raised in a strong-light (10,000 LUX) and -noise (>80 db) environment (12 h/d) for 16 weeks to induce insomnia, and from week 10 to week 16, MT and DOE were correspondingly administered to rats. The behavior tests including sodium pentobarbital-induced sleep experiment, sucrose preference test, and autonomous activity test were used to evaluate changes in sleep and emotions of rats. The metabolic-related indicators such as blood pressure, blood viscosity, blood glucose, and uric acid in rats were measured. The pathological changes in the cornu ammonis 1 (CA1) region of rat brain were evaluated using hematoxylin and eosin staining and Nissl staining. Additionally, the sleep-related factors gamma-aminobutyric acid (GABA), glutamate (GA), 5-hydroxytryptamine (5-HT), and interleukin-6 (IL-6) were measured using enzyme linked immunosorbent assay. Finally, we screened potential sleep-improving receptors of DOE using polymerase chain reaction (PCR) array and validated the results with quantitative PCR and immunohistochemistry. RESULTS: DOE significantly improved rats' sleep and mood, increased the sodium pentobarbital-induced sleep time and sucrose preference index, and reduced autonomic activity times (P<0.05 or P<0.01). DOE also had a good effect on metabolic abnormalities, significantly reducing triglyceride, blood glucose, blood pressure, and blood viscosity indicators (P<0.05 or P<0.01). DOE significantly increased the GABA content in hippocampus and reduced the GA/GABA ratio and IL-6 level (P<0.05 or P<0.01). In addition, DOE improved the pathological changes such as the disorder of cell arrangement in the hippocampus and the decrease of Nissel bodies. Seven differential genes were screened by PCR array, and the GABA_A receptors (Gabra5, Gabra6, Gabrq) were selected for verification. The results showed that DOE could up-regulate their expressions (P<0.05 or P<0.01). CONCLUSION DOE demonstrated remarkable potential for improving insomnia, which may be through regulating GABA_A receptors expressions and GA/GABA ratio.
Animals ; Dendrobium/chemistry* ; Rats, Sprague-Dawley ; Male ; Sleep Initiation and Maintenance Disorders/blood* ; Plant Extracts/therapeutic use* ; Receptors, GABA-A/metabolism* ; Noise/adverse effects* ; Light/adverse effects* ; gamma-Aminobutyric Acid/metabolism* ; Sleep/drug effects* ; Rats ; Receptors, GABA/metabolism*

Eleven compounds were isolated and purified from the ethyl acetate part of 80% ethanol extract of Ferula feruloides root by a combination of normal-phase silica gel column chromatography, Sephadex LH-20 dextran gel column chromatography and semi-preparative liquid chromatography and then modern wave spectrometry methods (NMR, MS, UV, IR) were used to identify the structures of the compounds, which were identified as baigene D (1), baigene E (2), baigene F (3), β-kirialovin (4), α-kirialovin (5), falcarindiol (6), ammoresinol (7), dshamirone (8), 2,3-dihydro-7-hydroxy-2S*,3R*-dimethyl-3-[4-methyl-5-(4-methy1-2-furyl)-3(E)-pentenyl]-furo[3,2-c]coumarin (9), 2,3-dihydro-7-hydroxy-2S*,3R*-dimethyl-2-[4,8-dimethyl-3(E),7-nonadi-enyl]-furo[3,2-c]coumarin (10), and baigene C (11). Compounds 1-3 are new coumarin analogues, and compounds 4-6 are firstly isolated from F. feruloides. The anti-proliferative activity of compounds 5, 7-11 against human gastric cancer (MKN-45) cells was evaluated using MTT assay, which showed that compounds 7-11 exhibited strong inhibitory activity, and compound 5 exhibited weak inhibitory activity.

italic>Anoectochilus roxburghii liquid (spray, a hospital preparation of Wu Mengchao Hepatobiliary Hospital of Fujian Medical University) has shown a good clinical treatment effect during the COVID-19 pandemic, but its material basis and mechanism of action are still unclear. In this study, network pharmacology and molecular docking methods were used to predict the molecular mechanism of A. roxburghii liquid against COVID-19, and pharmacodynamic experiments in vitro were conducted to study the interaction between the current targets with clear preventive and therapeutic effects and the key components of A. roxburghii liquid. UPLC-MS and database were used to compare and analyze the active ingredients in the liquid, and 17 potential active ingredients with good drug-like properties were screened by in vivo pharmacokinetics process in SwissADME database. SwissTargetPrediction and GeneCards were searched to find 93 common targets. Cytoscape 3.8.2 software was used to construct the "component-target" network map, and the Metascape platform was used for gene function annotation and pathway enrichment analysis. It was found that the extract could regulate the positive response to external stimuli, inflammatory response, cytokine production and other biological processes by binding the active ingredients such as isorhamnetin, kaempferol, luteolin, quercetin and apigenin to the common targets (NOS3, MPO, MMP3, etc.), and play an anti-COVID-19 role. In the angiotensin-converting enzyme 2 (ACE2) activity inhibition assay, it was found that the stock solution of A. roxburghii liquid (for spray), and the supernatant after removing polysaccharides (mainly containing flavonoids) could to some extent inhibit the activity of ACE2. Crucially, in the experiment of 2019-nCOV-S pseudovirus infecting HEK-293T-ACE2 cells, we found that A. roxburghii liquid may exert anti-COVID-19 effects by blocking the binding of SARS-CoV-S protein to ACE2.

Lower-cost genotyping technology has promoted the generation of large genetic datasets with the evolving next-generation sequencing technology. The emergence of genome-wide association studies (GWAS) has facilitated researchers’ understanding of common complex diseases. GWAS refers to finding the sequence variations present in the human genome and screening out disease-related single nucleotide polymorphisms (SNPs). These SNPs are considered as the basis for assessing the stability of complex diseases. However, a single variation is not sufficient to assess an individual’s risk of disease. Polygenic risk score (PRS) is an emerging genetic data analysis method for quantitatively estimating an individual’s genetic risk for complex diseases by comprehensively considering multiple genetic variation sites. A single-value estimate of an individual’s genetic risk for a certain phenotype can be calculated as the cumulative impact of multiple genetic variants by building a PRS model. The finally expected risk score is weighted by the strength and direction of association of each SNP with the phenotype based on the number of alleles carried by each SNP. With the continuous development of various PRS calculation methods and the constant accumulation of genomic data, PRS has received widespread attention in the field of genetics. So far, quite a few studies at home and abroad have shown that PRS is valuable in risk prediction of different types of human traits or complex diseases, and its effectiveness has been further verified in clinical applications. At present, many studies have established PRS models based on GWAS summary statistics to quantify the genetic risk of susceptibility loci and clinical characteristics on diseases such as lung cancer, breast cancer, coronary heart disease, diabetes and Alzheimer’s disease. The disease-susceptible populations can be recognized through comparing the relative risk and absolute risk of the disease in different risk groups according to the population risk stratification results. Additionally, individual-level genotype data and omics data can also be used as data sources for PRS analysis research, especially the latter can dynamically reflect the short-term or long-term effects of environmental factors on human gene expression, and has potential application value in building early warning models to assess health risks. Since the calculation of PRS involves a large amount of genomic data analysis, there are big differences in the methods for data selection, model building and validation. Different PRS construction methods and software have different performances in disease risk prediction, and even the performance of same algorithm varies across diseases. It is worth noting that the PRS model often needs to be re-evaluated and verified for different groups of people, because PRS is affected by race and region. This review combines currently published PRS-related research and algorithms to describe the basic principles of PRS, compares their construction and verification methods, and discusses their applications and prospects. As a powerful genetic risk assessment tool, PRS has great potential in analyzing the genetic code of complex diseases and achieving precise diagnosis and personalized treatment.