This study aimed to investigate the impact of the coronavirus disease 2019 (COVID-19) pandemic on erectile function in Chinese patients with chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). A retrospective study was conducted on 657 CP/CPPS patients who visited The Third Xiangya Hospital of Central South University (Changsha, China) from November 2018 to November 2022. Patients were divided into two groups based on the timeline before and after the COVID-19 outbreak in China. The severity of CP/CPPS, penile erection status, anxiety, and depression was evaluated using the National Institutes of Health-Chronic Prostatitis Symptom Index (NIH-CPSI), International Index of Erectile Function-5 (IIEF-5), Generalized Anxiety Disorder-7 (GAD-7), and Patient Health Questionnaire-9 (PHQ-9) scales, respectively. Compared with patients before the COVID-19 outbreak, more CP/CPPS patients developed severe erectile dysfunction (ED) due to depression and anxiety caused by the pandemic. After developing moderate-to-severe ED, mild and moderate-to-severe CP/CPPS patients exhibited more apparent symptoms of anxiety and depression ( P < 0.001 and P = 0.001, respectively), forming a vicious cycle. The COVID-19 pandemic has adversely affected the psychological status of CP/CPPS patients, exacerbating their clinical symptoms and complicating ED. The exacerbation of clinical symptoms further worsens the anxiety and depression status of patients, forming a vicious cycle. During the COVID-19 pandemic, paying more attention to the mental health of CP/CPPS patients, strengthening psychological interventions, and achieving better treatment outcomes are necessary.
Male ; Humans ; Erectile Dysfunction/etiology* ; Pandemics ; Penile Erection ; Prostatitis/complications* ; Retrospective Studies ; East Asian People ; COVID-19/complications* ; Chronic Disease ; Pelvic Pain/complications*

Saposhnikovia divaricata is a commonly used bulk medicinal plant. To explore the key enzyme genes and their expression in the biosynthesis of chromone and coumarin, the key active components, we carried out transcriptome sequencing(Illumina HiSeq) and bioinformatics analysis for the 1-year-old(S1) and 2-year-old(S2) plants of S. divaricata. A total of 40.8 Gb data was obtained. After the sequence assembly via Trinity, 110 732 transcripts and 86 233 unigenes were obtained, which were aligned and annotated with NR, Swiss-Prot, GO, KEGG, and PFAM. Daucus carota and S. divaricata had the highest sequence homology. KEGG pathway enrichment showed that the differentially expressed genes were mainly enriched in plant hormone signal transduction, phenylpropanoid biosynthesis, and flavonoid biosynthesis pathways. A total of 27 differentially expressed unigenes, including 13 enzyme genes, were identified in the pathways related to the synthesis of active ingredients in S. divaricata. Compared with S1 plant, S2 plant showed up-regulated expression of PAL, BGL, C4H, 4CL, CYP98A, CSE, REF, and CCoAOMT and down-regulated expression of CHS, CAD, and COMT. HCT and POD had both up-regulated and down-regulated unigenes. Among them, PAL, C4H, 4CL, BGL, and CHS can be used as candidate genes for the synthesis of the active ingredients in S. divaricata. The four key enzyme genes were verified by RT-qPCR, which showed the results consistent with transcriptome sequencing. This study enriches the genetic information of S. divaricata and provides support for the identification of candidate genes in the biosynthesis of secondary metabolites.
Apiaceae/genetics* ; Chromones ; Coumarins ; Flavonoids ; Gene Expression Profiling ; Gene Expression Regulation, Plant ; High-Throughput Nucleotide Sequencing/methods* ; Plant Growth Regulators ; Transcriptome

Near-infrared spectroscopy(NIRS) combined with band screening method and modeling algorithm can be used to achieve the rapid and non-destructive detection of the traditional Chinese medicine(TCM) production process. This paper focused on the ginkgo leaf macroporous resin purification process, which is the key technology of Yinshen Tongluo Capsules, in order to achieve the rapid determination of quercetin, kaempferol and isorhamnetin in effluent. The abnormal spectrum was eliminated by Mahalanobis distance algorithm, and the data set was divided by the sample set partitioning method based on joint X-Y distances(SPXY). The key information bands were selected by synergy interval partial least squares(siPLS); based on that, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA) and Monte Carlo uninformative variable(MC-UVE) were used to select wavelengths to obtain less but more critical variable data. With selected key variables as input, the quantitative analysis model was established by genetic algorithm joint extreme learning machine(GA-ELM) algorithm. The performance of the model was compared with that of partial least squares regression(PLSR). The results showed that the combination with siPLS-CARS-GA-ELM could achieve the optimal model performance with the minimum number of variables. The calibration set correlation coefficient R_c and the validation set correlation coefficient R_p of quercetin, kaempferol and isorhamnetin were all above 0.98. The root mean square error of calibration(RMSEC), the root mean square error of prediction(RMSEP) and the relative standard errors of prediction(RSEP) were 0.030 0, 0.029 2 and 8.88%, 0.041 4, 0.034 8 and 8.46%, 0.029 3, 0.027 1 and 10.10%, respectively. Compared with the PLSR me-thod, the performance of the GA-ELM model was greatly improved, which proved that NIRS combined with GA-ELM method has a great potential for rapid determination of effective components of TCM.
Algorithms ; Ginkgo biloba ; Least-Squares Analysis ; Plant Leaves ; Spectroscopy, Near-Infrared

Tumors are new organisms formed by uncontrollable cell proliferation of local tissues driven by various oncogenic factors. The cause of tumors is unknown with life-threating outcome. Tumors can be classified into benign tumors， borderline tumors， and malignant tumors according to their pathological properties. Among them， malignant tumor is commonly known as cancer， with no specific medicines or reliable cure means， so this is a hot spot and difficult point in current medical research. In ancient literatures， there are many records about the efficacy of Chinese herbal medicine in treating tumor， and modern pharmacological researches have shown that more and more active ingredients of traditional Chinese medicine（TCM） have gradually highlighted their inhibitory effect on various types of tumor. Caulis sinomenii has been used for treatment of rheumatic diseases in TCM for a long history. Sinomenine is a major bioactive alkaloid presented in C. sinomenii， which has demonstrated a wide range of pharmacological activities such as anti-inflammation， immunosuppression， analgesia and sedation， and due to its slightly soluble in water， it is commonly used in clinic in the form of hydrochloride， with its commercial name of Zhengqing Fengtongning. Recent studies show that sinomenine alone or combined with chemoradiotherapy can inhibit growth of several tumors significantly or in a synergistic way， so it is termed as an inhibitor of tumors. Anti-tumor effect of sinomenine involve inhibition of tumor cell proliferation， induction of tumor cell apoptosis， blockade of tumor cell cycle， suppression of tumor invasion and metastasis， induction of autophagy of tumor cells， and reversal of multidrug resistance of tumor cells. Upon combination with nanomaterials， it can enhance efficiency and reduce toxicity. Here we summarized and reviewed recent advances on basic anti-tumor research of sinomenine， and then made a classification and description according to its in vivo and in vitro pharmacological action and mechanism of action， so as to elucidate the great potential of sinomenine as a promising anti-tumor drug， and provide reference for further research on its anti-tumor mechanism.

ObjectiveTo analyze the timeliness of health science popularization during the outbreak of coronavirus disease 2019 （COVID-19） and its correlation with the epidemic situation and policies. MethodsThe original reports of health science popularization by 26 major media in Shanghai during the COVID19 outbreak between January 19 and March 25 of 2020 were retrieved， and the timeliness of the number of reports， media sources and categories， and contents were analyzed. ResultsDuring the epidemic of COVID-19， public media reported timely. Online media accounted for 63.35%， and text-based reports accounted for 85.90%. There was a correlation between the trend of the number of reports and the development of COVID-19 and the prevention and control policy issued by the government. After the change in the epidemic or the release of policy， the number of reports increased. The top four topics were personal protection， disease treatment， healthy lifestyle and psychological health， accounting for 18.62%， 18.54%， 12.96% and 11.74%， respectively. Reports focused on different aspects at different stages of COVID-19 epidemic， and the number of reports tended to increase one week after the occurrence of major events. ConclusionDuring the COVID-19 epidemic， the coverage of health science on media is timely and targeted. For future similar public health emergencies， it is suggested to respond quickly to major events according to the trend， to carry out publicity timely， to innovate the report forms， and thus make it easy for the public to accept and implement.

Age-associated changes in immune cells have been linked to an increased risk for infection. However, a global and detailed characterization of the changes that human circulating immune cells undergo with age is lacking. Here, we combined scRNA-seq, mass cytometry and scATAC-seq to compare immune cell types in peripheral blood collected from young and old subjects and patients with COVID-19. We found that the immune cell landscape was reprogrammed with age and was characterized by T cell polarization from naive and memory cells to effector, cytotoxic, exhausted and regulatory cells, along with increased late natural killer cells, age-associated B cells, inflammatory monocytes and age-associated dendritic cells. In addition, the expression of genes, which were implicated in coronavirus susceptibility, was upregulated in a cell subtype-specific manner with age. Notably, COVID-19 promoted age-induced immune cell polarization and gene expression related to inflammation and cellular senescence. Therefore, these findings suggest that a dysregulated immune system and increased gene expression associated with SARS-CoV-2 susceptibility may at least partially account for COVID-19 vulnerability in the elderly.
Adult ; Aged ; Aged, 80 and over ; Aging ; genetics ; immunology ; Betacoronavirus ; CD4-Positive T-Lymphocytes ; metabolism ; Cell Lineage ; Chromatin Assembly and Disassembly ; Coronavirus Infections ; immunology ; Cytokine Release Syndrome ; etiology ; immunology ; Cytokines ; biosynthesis ; genetics ; Disease Susceptibility ; Flow Cytometry ; methods ; Gene Expression Profiling ; Gene Expression Regulation, Developmental ; Gene Rearrangement ; Humans ; Immune System ; cytology ; growth & development ; immunology ; Immunocompetence ; genetics ; Inflammation ; genetics ; immunology ; Mass Spectrometry ; methods ; Middle Aged ; Pandemics ; Pneumonia, Viral ; immunology ; Sequence Analysis, RNA ; Single-Cell Analysis ; Transcriptome ; Young Adult

OBJECTIVE: To study the risk factors and infection characteristics of nosocomial infection in children with acute lymphoblastic leukemia (ALL) and analyze the relationship between different nutritional status and nosocomial infection, early treatment response. METHOD: The clinical data of 133 children with ALL treated with CCCG-ALL-2015 from June 2016 to June 2019 (chemotherapy stage, risk level, MRD), infection during hospitalization (course of infection, laboratory indicators, sites of infection, outcome) and nutritional status (sex, age, height/ length, weight) were enrolled. The Chi 2 test and Logistic regression analysis were used for statistical analysis. RESULTS: The rate of nosocomial infection was 19.9% in 133 children with ALL, in which 3 were infection-related death. Sex, immunophenotype and risk showed no significantly affect on the occurrence of nosocomial infection (P＞0.05), but neutrophil count, hemoglobin level, platelet count, chemotherapy stage, length of stay in hospital and nutritional status showed affect on the occurrence of nosocomial infection (P＜0.05). Logistic multivariate regression analysis showed that chemotherapy stage, length of hospital stay, neutrophils and nutritional status were the independent risk factors, in which the respiratory tract infection was the most common. Gram-positive bacteria, Gram-negative bacteria and fungi accounted for 44.1%, 52.9% and 2.9% respectively. The negative rate of MRD in day 19 and day 46 between different nutritional status groups showed statistically significant (P＜0.05). CONCLUSION Neutrophil count, chemotherapy stage, length of stay in hospital and nutritional status are independent risk factors for nosocomial infection. Among of them, nutritional status negatively correlated with nosocomial infection, and the poorer nutritional status, the higher risk of nosocomial infection. Malnutrition, overweight and obesity can affect the early treatment response of ALL children. The level of nutrition at first diagnosis can be used as a bad factor to evaluate the early treatment response of ALL children.
Child ; Cross Infection ; Gram-Negative Bacteria ; Humans ; Nutritional Status ; Precursor Cell Lymphoblastic Leukemia-Lymphoma ; Retrospective Studies

As traditional data management model cannot effectively manage the massive data in traditional Chinese medicine(TCM) due to the uncertainty of data object attributes as well as the diversity and abstraction of data representation, a management strategy for TCM data based on big data technology is proposed. Based on true characteristics of TCM data, this strategy could solve the problems of the uncertainty of data object attributes in TCM information and the non-uniformity of the data representation by using modeless properties of stored objects in big data technology. Hybrid indexing mode was also used to solve the conflicts brought by different storage modes in indexing process, with powerful capabilities in query processing of massive data through efficient parallel MapReduce process. The theoretical analysis provided the management framework and its key technology, while its performance was tested on Hadoop by using several common traditional Chinese medicines and prescriptions from practical TCM data source. Result showed that this strategy can effectively solve the storage problem of TCM information, with good performance in query efficiency, completeness and robustness.
Big Data ; Information Storage and Retrieval ; methods ; Medicine, Chinese Traditional

Due to abstract and intricate theories of TCM theories, its essential characteristics are difficult to master, so the mechanism can be better explored through study on quantification of prescription properties. At present, quantification research by many scholars mainly adopts isolated research model limited to one or several kinds of TCM properties, which is difficult to reveal treatment mechanism of prescriptions. The development of big data and cloud computing technology provides a new way for the deep analysis of massive and complex TCM information. Based on syndrome differentiation, it is trending in prescription quantification to employ a comprehensive analysis by using "four properties - five flavors - channel tropism - ascending and descending, floating and sinking - toxicity -efficacy" overall on macroscopic level to analyze and quantify the characteristics of TCM prescriptions and their relationships among each other. This article reviewed recent research progress in the quantification of prescription properties and provided references for the modernization and specification of quantification of prescription properties.

Objective To investigate the effect of different serum sodium levels on heart function and prognosis in very elderly patients with heart failure. Methods Totally 152 elderly patients(aged ≥ 85 years)with hyponatremia were enrolled.Based on the serum sodium level ,they were divided into mild(125 mmol/L &le; Na+ < 135 mmol/L) ,moderate(125 mmol/L &le; Na+ < 135 mmol/L) ,and severe hyponatremia(Na+ < 115 mmol/L)groups ,and 76 patients with normal blood sodium level(Na+ ≥ 135 mmol/L)were selected as control group. The general data ,levels of serum creatinine and N-terminal pro-brain natriuretic peptide (NTproBNP)and prognosis were compared among the above groups. Results Compared with the control group ,patients with severe hyponatremia were much older ,with more diuretics administration ,higher level of serum creatinine , lowerlevelofeGFRandleftventricularejectionfractions[(38.1±3.9)％ vs.(45.2±9.7)％ ].There were higher incidences of coronary atherosclerotic heart disease [72.4％ (n=21)vs. 56.6％ (n=43)] ,diabetes[41.4％ (n=12)vs. 23.7％ (n=18)] ,chronic renal insufficiency [22.6％ (n=8)vs. 11.8％ (n=9)] ,stroke[20.6％ (n=6)vs. 9.2％ (n=7)]in patients with severe hyponatremia compared with other groups. The severe hyponatremia group showed significantly higher levels of NTproBNP [(4823. 9 ± 588. 1 )ng/L v s. (1124. 4 ± 349. 1 )ng/L ,(1836. 2 ± 369. 3 )ng/L ,(2894. 1 ± 687. 3 )ng/L ]and higher rates of mortality [27.6％ (n=8) vs.5.3％ (n=4) ,7.6％ (n=6) ,13.6％ (n=6)]as compared to the control group ,mild and moderate hyponatremia groups. Furthermore ,length of stay in hospital were markedly longer in patients with severe hyponatremia than those with mild and moderate hyponatremia[(11.1 ± 7.1)d vs. (19.6 ± 5.7)d ,(16.1 ± 4.2)d] . Conclusions Hyponatremia is a common type of electrolyte disorder in very elderly patients with heart failure ,and severe hyponatremia may predictand increased risk of death.