Natural killer(NK)cells are important members of innate immune system,playing an important role in anti-viral and anti-tumor responses.Development and differentiation of NK cells go through multiple stages and are regulated by a variety of factors.Conventional NK(cNK)cells,which are widely present in peripheral tissues of adult organisms,mainly develop from bone marrow hematopoietic stem cells(HSCs)through common lymphoid progenitors(CLPs)and NK cell precursors(NKPs).Transcrip-tion factors play a key role in regulating differentiation of hematopoietic precursors into NK cells.In recent years,with discovery and in-depth study of other members of innate lymphoid cells(ILCs)family,it has been revealed that NK cells have a developmental path-way independent of other ILC subsets,development and differentiation stages of NK cells have been more finely defined,and a series of transcription factors regulating development and differentiation of NK cells at various stages have been gradually discovered.This article focuses on definition of NK cell development stages and regulation of transcription factors,which will improve our understanding of development and differentiation of NK cells.

Objective To explore and analyze the prescription patterns of Professor Zhou Min in treating primary liver cancer at different stages according to the China Liver Cancer Staging (CNLC) system. Methods The clinical records of outpatients with primary liver cancer treated by Professor Zhou Min were collected and entered into the Traditional Chinese Medicine Inheritance Support System (Version 2.50) to establish a database. Data mining methods such as frequency analysis, drug association analysis, and cluster analysis were employed, the pathogenesis of primary liver cancer the prescription patterns at different stages was explored and medication rules were analyzed according to Professor Zhou Min's experience in treating liver cancer at various CNLC stages. Results A total of 202 prescriptions from 113 patients with primary liver cancer were collected, involving 230 traditional Chinese medicines. The high-frequency drugs and drug combinations at each stage were identified. The drugs with higher frequencies at each stage included Fuling, Chenpi, Yiyiren, fried Baishu, and Fabanxia. For stage Ⅰ, high-frequency drugs also included Zhongjiefeng, Xiangfu, Jiangcan, and Jianghuang. For stages Ⅱ and Ⅲ, high-frequency drugs further encompassed Zhongjiefeng, Xianhecao, Banzhilian, Baihua Sheshecao, Jiangcan, Zeqi, Xiangfu, and Maidong. For stage Ⅳ, high-frequency drugs also include Maydis stigma, Huoxiang, fried Maiya, Jineijin, and fried Guya. The majority of the drugs were cold in nature, with sweet and bitter tastes being the most common, and their meridian tropism were mostly distributed in the spleen and stomach meridians. The drug combinations with higher frequencies at each stage were mostly derived from Sijunzi Decoction and Erchen Decoction. The drug efficacies were mainly heat-clearing and dampness-resolving. Cluster analysis screened out new prescriptions with unique characteristics at each stage. Conclusion By performing data mining on the prescriptions used by Professor Zhou Min in treating primary liver cancer at various CNLC stages through the Traditional Chinese Medicine Inheritance Platform, combined with his understanding of the pathogenesis and clinical experience of the disease, the pathogenesis characteristics of primary liver cancer are summarized as dampness-heat, phlegm, and toxin accumulation, as well as qi and yin deficiency. The basic treatment methods established are heat-clearing and dampness-resolving, spleen-invigorating and yin-nourishing, with an emphasis on strengthening the body resistance to eliminate pathogenic factors and stage-based treatment. Flexible prescriptions and medications are used for different complications.

Objective: To create a model to predict nosocomial infections in emergency intensive care units (EICU), so as to provide insights into early identification and interventions among patients with nosocomial infections. Methods: All nosocomial infections were collected from patients hospitalized in the EICU of a large tertiary hospital from 2017 to 2020. The 2017-2019 data were selected as the training set to create a logistic regression model, and the fitting effectiveness of the predictive model was evaluated using Hosmer-Lemeshow test. The 2020 data were selected as the test set to evaluate the external validation of the predictive model. In addition, the value of the model for prediction of nosocomial infections was examined using the receiver operating characteristic (ROC) curve analysis. Results : Totally 1 546 inpatients in EICU were enrolled, and the prevalence of nosocomial infections was 7.18%. Multivariable logistic regression analysis identified hospital stay duration of >7 days (OR=21.845, 95%CI: 7.901-60.398), use of ventilators (OR=3.405, 95%CI: 1.335-8.682), and surgery (OR=1.854, 95%CI: 1.121-3.064) as risk factors of nosocomial infections. The predictive model was p=ey/(1+ey), y=-6.105+(3.084×duration of hospital stay)+(1.225×use of ventilators)+(0.617×surgery). The area under ROC curve was 0.806 (95%CI: 0.774-0.838) for the training set and 0.723 (95%CI: 0.623-0.823) for the test set, and if the 0.065 cut-off of the predictive model created by the training set was included in the test set, the predictive value yield a 0.739 sensitivity and 0.642 specificity for prediction of nosocomial infections among patients hospitalized in EICU. Conclusion The created predictive model for nosocomial infections among patients hospitalized in EICU presents a high accuracy, which shows a satisfactory predictive value for high-risk nosocomial infections.

Phenylalaninammo-nialyase (PAL) is a key enzyme in the synthesis of methyl benzoate - a plant aroma compound. In order to understand the function of this enzyme in the formation of fragrance in the scented Rhododendron species-Rhododendron fortunei, we cloned a gene encoding this enzyme and subsequently examined the gene expression patterns and the profile of enzyme activity during development in various tissues. The full length of RhPAL gene was cloned by reverse transcription-PCR (RT-PCR) and rapid amplification of cDNA ends (RACE) techniques. The expression levels of RhPAL gene were measured by real-time quantitative reverse transcription PCR (qRT-PCR) and the amount of phenylalanine and cinnamic acid were assayed with LC-MS. The results showed that the ORF sequence of RhPAL gene amplified from the cDNA templates of flower buds had 2 145 bp, encoding 715 amino acids, and shared 90% homology to the PAL amino acid sequences from other species. qRT-PCR analysis showed that the expression of RhPAL in petals during flowering kept in rising even until the flowers wilted. The expression of RhPAL in pistil was much higher than that in stamen, while the expression in the younger leaves was higher than in old leaves. However, the expression level was relatively lower in petal and stamen compared to that in leaves. We also measured the PAL activity by Enzyme-linked immuno sorbent assay in the petals of flowers at different flowering stages. The results showed that PAL activity reached the highest at the bud stage and then decreased gradually to the lowest when the flowers wilted, which followed a similar trend in the emission of the flower fragrance. The phenylalanine and cinnamic acid contents measured by LC-MS were highly correlated to the expression level of RhPAL in various tissues and at different flowering stages, implying that RhPAL plays an important role in the formation of the flower fragrance. This work may facilitate the breeding and improvement of new fragrant Rhododendron cultivars.
Amino Acid Sequence ; Cloning, Molecular ; DNA, Complementary ; Flowers/genetics* ; Rhododendron/genetics*

Terpene synthase (TPS) plays important roles in the synthesis of terpenoids which are the main fragrances in Rhododendron flowers. To understand the function of TPS genes in terpenoid metabolism in relation to flower aroma formation, we identified all TPS gene family members in Rhododendron by analyzing its genome database. We then used a transcriptomic approach to analyze the differential gene expression patterns of TPS gene family members in the scented flower Rhododendron fortunei compared to the non-scented flower Rhododendron 'Nova Zembla'. The contents of terpenoid compounds in petals of the above two Rhododendron species at different developmental stages were also measured by using qRT-PCR and head space-solid phase micro-extraction combined with gas chromatography-mass spectrometry. Our results showed that a total of 47 RsTPS members, with individual lengths ranged from 591 to 2 634 bp, were identified in the Rhododendron genome. The number of exons in RsTPS gene ranged from 3 to 12, while the length of each protein encoded ranged from 196 to 877 amino acids. Members of the RsTPS family are mainly distributed in the chloroplast and cytoplasm. Phylogenetic analysis showed that RsTPS genes can be clustered into 5 subgroups. Seven gene family members can be functionally annotated as TPS gene family since they were temporally and spatially expressed as shown in the transcriptome data. Notably, TPS1, TPS10, TPS12 and TPS13 in Rhododendron fortunei were expressed highly in flower buds reached the peak in the full blossoming. Correlation analysis between gene expression levels and terpenoid content indicates that the expression levels of TPS1, TPS4, TPS9, TPS10, TPS12 and TPS13 were positively correlated with the content of terpenoids in the petals of R. fortunei at all flower developmental stages, suggesting that these six genes might be involved in the aroma formation in R. fortunei.
Rhododendron/metabolism* ; Phylogeny ; Terpenes/metabolism* ; Family ; Gene Expression Regulation, Plant

Objective: To describe the distribution and drug resistance of pathogens at hematology department of Jiangsu Province from 2014 to 2015 to provide reference for empirical anti-infection treatment. Methods: Pathogens were from hematology department of 26 tertiary hospitals in Jiangsu Province from 2014 to 2015. Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or agar dilution method. Collection of drug susceptibility results and corresponding patient data were analyzed. Results: The separated pathogens amounted to 4 306. Gram-negative bacteria accounted for 64.26%, while the proportions of gram-positive bacteria and funguses were 26.99% and 8.75% respectively. Common gram-negative bacteria were Escherichia coli (20.48%) , Klebsiella pneumonia (15.40%) , Pseudomonas aeruginosa (8.50%) , Acinetobacter baumannii (5.04%) and Stenotropho-monas maltophilia (3.41%) respectively. CRE amounted to 123 (6.68%) . Common gram-positive bacteria were Staphylococcus aureus (4.92%) , Staphylococcus hominis (4.88%) and Staphylococcus epidermidis (4.71%) respectively. Candida albicans were the main fungus which accounted for 5.43%. The rates of Escherichia coli and Klebsiella pneumonia resistant to carbapenems were 3.5%-6.1% and 5.0%-6.3% respectively. The rates of Pseudomonas aeruginosa resistant to tobramycin and amikacin were 3.2% and 3.3% respectively. The resistant rates of Acinetobacter baumannii towards tobramycin and cefoperazone/sulbactam were both 19.2%. The rates of Stenotrophomonas maltophilia resistant to minocycline and sulfamethoxazole were 3.5% and 9.3% respectively. The rates of Staphylococcus aureus, Enterococcus faecium and Enterococcus faecalis resistant wards vancomycin were 0, 6.4% and 1.4% respectively; also, the rates of them resistant to linezolid were 1.2%, 0 and 1.6% respectively; in addition, the rates of them resistant to teicoplanin were 2.8%, 14.3% and 8.0% respectively. Furthermore, MRSA accounted for 39.15% (83/212) . Conclusions Pathogens were mainly gram-negative bacteria. CRE accounted for 6.68%. The rates of Escherichia coli and Klebsiella pneumonia resistant to carbapenems were lower compared with other antibacterial agents. The rates of gram-positive bacteria resistant to vancomycin, linezolid and teicoplanin were still low. MRSA accounted for 39.15%.