In view of the few studies on the influence of Armillaria spp. infection on the content of the chemical components in different parts of Polyporus umbellatus sclerotia, this study determined the biomass of P. umbellatus sclerotia and the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in the separated cavity wall of the sclerotia and the uninfected part of the sclerotia in different harvesting years under the conditions of A. gallica and A. mellea infection respectively. According to the difference of content and dynamic changes of the polysaccharide and the steroid substances, the superior Armillaria sp. was screened to obtain the best harvest years of P. umbellatus. Using HPLC and UV-VIS spectrophotometry methods, the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in P. umbellatus sclerotia infected by the two Armillaria spp. in different years were determined. In addition, the differentially expressed genes related to P. umbellatus polysaccharide synthesis were screened according to the transcriptomic data of different parts of P. umbellatus after A. mellea infection. With the increase of years, the biomass of sclerotia infected by different Armillaria spp. had significant differences, and there were significant differences in the four components of sclerotia. The four components of the separated cavity wall of the sclerotia were significantly higher than those of the uninfected part. The best harvest time was the third year after cultivation. Transcriptomic analysis showed that the infection of Armillaria spp. could significantly promote polysaccharide synthesis, which provided a basis for polysaccharide content determination at the molecular level. The study clarified the influence of different Armillaria spp. infection on the accumulation of chemical components of P. umbellatus sclerotia, laying a foundation for exploring the symbiosis mechanism and provided a scientific clue for screening superior Armillaria sp. and guiding the artificial cultivation of P. umbellatus sclerotia.

ObjectiveNon-invasive magnetic stimulation technology has been widely used in the treatment of Alzheimer’s disease (AD), but there is a lack of convenient and timely methods for evaluating and providing feedback on the effectiveness of the stimulation, which can be used to guide the adjustment of the stimulation protocol. This study aims to explore the possibility of heart rate variability (HRV) in diagnosing AD and guiding AD magnetic stimulation intervention techniques. MethodsIn this study, we used a 40 Hz, 10 mT pulsed magnetic field to expose AD mouse models to whole-body exposure for 18 d, and detected the behavioral and electroencephalographic signals before and after exposure, as well as the instant electrocardiographic signals after exposure every day. ResultsUsing one-way ANOVA and Pearson correlation coefficient analysis, we found that some HRV indicators could identify AD mouse models as accurately as behavioral and electroencephalogram(EEG) changes (P<0.05) and significantly distinguish the severity of the disease (P<0.05), including rMSSD, pNN6, LF/HF, SD1/SD2, and entropy arrangement. These HRV indicators showed good correlation and statistical significance with behavioral and EEG changes (r>0.3, P<0.05); HRV indicators were significantly modulated by the magnetic field exposure before and after the exposure, both of which were observed in the continuous changes of electrocardiogram (ECG) (P<0.05), and the trend of the stimulation effect was more accurately observed in the continuous changes of ECG. ConclusionHRV can accurately reflect the pathophysiological changes and disease degree, quickly evaluate the effect of magnetic stimulation, and has the potential to guide the pattern of magnetic exposure, providing a new idea for the study of personalized electromagnetic neuroregulation technology for brain diseases.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Nuclear factor-kappa B （NF-κB） is an important intracellular transcription factor widely involved in the processes such as immune response， inflammatory response， cell proliferation， and apoptosis. The abnormal activation of the NF-κB signaling pathway plays a pivotal role in various liver diseases including chronic hepatitis， liver fibrosis， liver cirrhosis， and hepatocellular carcinoma. Extensive studies have shown that inhibiting NF-κB activity may effectively reduce inflammation and fibrosis and improve metabolic disorders. Several natural compounds， such as matrine and salvianolic acid B， have shown the potential in suppressing NF-κB activity， thereby exerting anti-inflammatory， anti-fibrotic， and anti-tumor effects. This article systematically reviews the critical role of the NF-κB signaling pathway in liver diseases and its potential as a therapeutic target， in order to highlight its potential as a therapeutic target for liver diseases and provide new directions for the treatment of liver diseases.

Objective To establish and validate a method for simultaneous determination of 9 sedative-hypnotics in human plasma,and to explore the preliminary clinical application.Methods Plasma samples were precipitated with acetonitrile and determined by high performance liquid chromatography tandem mass spectrometry.The column was Agilent Poroshell 120 EC-C18(2.1 mm × 50.0 mm,2.7μm)and eluted with acetonitrile water containing 0.1％formic acid in an equal degree program at a flow rate of 0.3 mL·min-1.The column temperature was 20 ℃ and injection volume was 5 μL.The deprotonated ions of analytes were ionized by positive ion,electron spray ionization and multiple reaction monitoring mode.The specificity,standard curve and lower limit of quantification,precision and recovery,matrix effect,stability and dilution effect of the method were investigated.Results Excellent linear relationship with correlation coefficient of r2 ≥ 0.997 7 was obtained.The linear of esazolam,alprazolam,oxazepam,clonazepam,lorazepam,triazolam,midazolam,diazepam and zolpidem were 18-1 800,4.5-450,25-2 500,3.5-350,25-2 500,1.5-150,5.5-550,35-3 500,4-400 ng·mL-1,respectively.The lower limit of quantification were 18,4.5,25,3.5,25,1.5,5.5,35,4 ng·mL-1.The method was accurate and precise with acceptable intra-day and inter-day precisions(relative standard deviations were less than 20％for a lower limit of quantification and less than 15％for other quality control samples)and an accuracy of 86.21％-112.38％.The extraction recovery rate were 93.07％-110.50％.The matrix factors normalized by internal standard were 86.61％-108.41％,relative standard deviations were less than 15％.Plasma samples remained stable under various storage conditions.The precision and accuracy of plasma samples were acceptable after dilution.Conclusion The method is simple,rapid,sensitive and specific,and it can be used for simultaneous detection of the 9 sedative-hypnotics in human plasma.

OBJECTIVE: To determine the role of Tripterygium wilfordii multiglycoside (TGW) in the treatment of psoriatic dermatitis from a cellular immunological perspective. METHODS: Mouse models of psoriatic dermatitis were established by imiquimod (IMQ). Twelve male BALB/c mice were assigned to IMQ or IMQ₊TGW groups according to a random number table. Histopathological changes in vivo were assessed by hematoxylin and eosin staining. Ratios of immune cells and cytokines in mice, as well as PAM212 cell proliferation in vitro were assessed by flow cytometry. Pro-inflammatory cytokine expression was determined using reverse transcription quantitative polymerase chain reaction. RESULTS: TGW significantly ameliorated the severity of IMQ-induced psoriasis-like mouse skin lesions and restrained the activation of CD45⁺ cells, neutrophils and T lymphocytes (all P<0.01). Moreover, TGW significantly attenuated keratinocytes (KCs) proliferation and downregulated the mRNA levels of inflammatory cytokines including interleukin (IL)-17A, IL-23, tumor necrosis factor α, and chemokine (C-X-C motif) ligand 1 (P<0.01 or P<0.05). Furthermore, it reduced the number of γ δ T17 cells in skin lesion of mice and draining lymph nodes (P<0.01). CONCLUSIONS TGW improved psoriasis-like inflammation by inhibiting KCs proliferation, as well as the associated immune cells and cytokine expression. It inhibited IL-17 secretion from γ δ T cells, which improved the immune-inflammatory microenvironment of psoriasis.
Male ; Animals ; Mice ; Tripterygium ; Psoriasis/drug therapy* ; Keratinocytes ; Skin Diseases/metabolism* ; Cytokines/metabolism* ; Imiquimod/metabolism* ; Dermatitis/pathology* ; Disease Models, Animal ; Mice, Inbred BALB C ; Skin/metabolism*

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.

The purpose of this study was to enrich the genomic information and provide a basis for further development and utilization of Polygonatum kingianum. The fresh rhizome of P. kingianum was used as the experimental material, and the full-length transcriptome was sequenced by PacBio Sequel platform. The final measured polymerase reads were 1 120 485, with a total of 77.73 GB of data. In NR database, 41 864 homologous sequence alignments were aligned to 5 species; 40 506 were annotated in the KOG database and classified into 26 categories based on their functionality; 69 060 GO annotated 32 functional groups divided into 3 categories: cellular components, molecular functions, and biological processes; 45 779 annotations were added to 145 metabolic pathways in the KEGG database. Among them, there are 127 identified transcripts related to polysaccharide synthesis in the glycolysis/gluconeogenesis metabolic pathway, 144 in the starch and sucrose metabolic pathway, 85 in the amino acid sugar and nucleotide sugar metabolic pathway, and 69 in the fructose and mannose metabolic pathway. In addition, 1 781 transcription factors were detected, distributed in 37 transcription factor families; 180 293 SSR loci were detected, among which single base repeats accounted for the most, accounting for 30.48% of all base repeats, and at least five base repeats, accounting for only 0.14% of single base repeats. The results of this study provide important data supporting for enriching the genomic information of P. kingianum and exploring its effective biosynthetic pathway.