Ichthyosis uteri complicated by endometrial adenocarcinoma with transitional cell differentiation: A case report.

RATIONALE: Ichthyosis uteri is a rare pathological condition characterized by the replacement of the endometrial lining by stratified squamous epithelium. Yet its occurrence with endometrial adenocarcinoma is very rare. PATIENT CONCERNS: A 68-year-old woman has been experiencing sporadic, minor vaginal hemorrhages for a few months. The gynecological evaluation revealed a uterine enlargement and imaging demonstrated an irregular mass within the uterus. DIAGNOSIS: Endometrial adenocarcinoma with transitional cell differentiation; ichthyosis uteri with dysplasia. INTERVENTIONS: Radical hysterectomy with pelvic lymphadenectomy was performed followed by postoperative radiotherapy. OUTCOMES: Postoperative follow-up at 8 months showed a favorable outcome without signs of recurrence and metastasis. LESSONS: Adequate pathological sampling is crucial to identifying the accompanying lesions of ichthyosis uteri. Finding molecular alterations in various pathological morphologies is important to understand the evolution of disease.

Quantitative assessment and driving factors analysis of surface urban heat island of urban agglomerations in China based on GEE.

The urban heat island (UHI) effect generated by the development of high-speed urbanization has become one of the major problems affecting the urban ecological environment. As the main body of urbanization in China, China's urban agglomerations are the core areas of urban heat island effect. The purpose of this study is to study the spatial-temporal characteristics and driving factors of surface urban heat island in 19 urban agglomerations in China, with a view to providing theoretical references for the prevention of urban thermal environmental risks. Based on Google Earth Engine (GEE), this paper estimated the surface urban heat island intensity (SUHII) of 19 urban agglomerations in China from 2003 to 2019 using MODIS land surface temperature (LST) data. Correlation analysis and regression analysis were used to explore the correlation between the change of SUHII and driving factors. Finally, the driving factors of SUHII were detected by the geo-detector model. Results showed that (1) the SUHII of 19 urban agglomerations in arid and semi-arid areas of northwestern China is higher than that in humid areas of eastern and southeastern China. (2) The SUHII of 19 urban agglomerations in China generally shows a decreasing trend, and the spatial variation of the change trend is significant. (3) There are positive correlations between SUHII and reference evapotranspiration (ET0), population density (POP), gross domestic product (GDP), nitrogen dioxide (NO2), ozone (O3), and ultraviolet aerosol index (UVAI); negative correlations with normalized difference vegetation index (NDVI), DEM, sulfur dioxide (SO2), carbon monoxide (CO), and formaldehyde (HCHO); the correlations all pass the significance test of P < 0.05 and are statistically significant. (4) The factor detection results showed that NDVI, land cover type (LC), and UVAI were the main driving factors of SUHII. The interaction detection results showed that the interaction between O3 and UVAI had the most significant impact on SUHII.

Effects of isolated scenting on the taste quality of broken green tea based on metabolomics.

Liquid chromatography-mass spectrometry (LC-MS) combined with multivariate analysis were used to characterize the nonvolatile compounds of broken green tea and explore the effect of isolated scenting on metabolic profile and taste quality of broken green tea in this research. A total of 236 nonvolatile compounds were identified and 13 compounds were believed to be the key characteristic taste compounds of scented broken green tea. Meanwhile, the optimal isolated scenting time of broken green tea was determined to be 10 h based on the sensory evaluation and PLS results. The contents and types of flavonoids, organic acids and catechins lead to the difference of taste quality at different scenting times. Overall, these findings provided a theoretical basis for scenting to improve the taste of broken green tea, and provide a new idea for improving the taste of broken green tea.

Using 1/2 Descending Time in CEUS to Identify Renal Allograft Rejection.

RATIONALE AND OBJECTIVES: This study investigates the potential of quantitative Contrast-Enhanced Ultrasound (CEUS) parameters to distinguish between graft dysfunction due to rejection and non-rejection in kidney transplant recipients. METHODS: In this retrospective study, 50 kidney transplant patients who presented elevated serum creatinine or proteinuria were analyzed. They were categorized as rejection or non-rejection based on biopsy outcomes. These classifications were applied in both derivation (n = 33) and validation cohorts (n = 17). Prior to the biopsy, all patients underwent a CEUS. Quantitative parameters derived from the CEUS were further analyzed for their consistency and reliability. Additionally, the relationship between the Banff scores, a standard for diagnosing transplant rejections, and these CEUS parameters was explored. RESULTS: Significant differences between rejection and non-rejection groups were observed in the CEUS parameters of derivation cohorts. Specifically, Peak Intensity (PI), 1/2 Descending Time (DT/2), Area Under Curve (AUC), and Mean Transit Time (MTT) stood out. Sensitivity and specificity for these parameters were 76.5% and 87.5% for PI, 76.5% and 81.2% for DT/2, 76.5% and 87.5% for AUC, and 68.8% and 94.1% for MTT, respectively. DT/2 and MTT showed superior interobserver agreement compared to PI and AUC. When extrapolating the cutoff values from the derivation cohort to the validation group, DT/2 and AUC exhibited optimal diagnostic precision with positive and negative predictive values being 91.7% vs. 100% and 100% vs. 85.7%, respectively. Additionally, DT/2 effectively differentiated between mild and moderate to severe microvascular inflammation, pivotal in diagnosing antibody-mediated renal transplant rejection. CONCLUSION: DT/2 from CEUS parameters presents as a reliable tool to differentiate rejection from non-rejection causes in renal transplant dysfunction. Yet, large-scale, multi-center studies are essential for further validation.

Effects of laminarin on growth performance and resistance against Pseudomonas plecoglossicida of large yellow croaker （Larimichthys crocea）.

Laminarin (LAM) is widely used as an immunopotentiator in aquaculture, but its protective mechanism is still unclear. In this study, the effects of LAM on the growth performance and resistance against Pseudomonas plecoglossicida of large yellow croaker were studied in vitro and in vivo. The 42 d-feeding trial in large yellow croaker showed that dietary LAM could obviously promote the fish growth by improving the weight gain rate (WGR), specific growth rate (SGR), and feed conversion rate (FCR). Dietary LAM could also improve the survival rate of large yellow croakers subjected to P. plecoglossicida infection, and 500 mg/kg LAM produced the highest relative percent survival (RPS) of 35.00 %. LAM improved fish antioxidant level by enhancing serum total antioxidant capacity (T-AOC) and superoxide dismutase (SOD) activity, and reducing malondialdehyde (MDA) content. In addition, LAM also improved fish innate immunity by increasing serum acid phosphatase (ACP) and alkaline phosphatase (AKP) activities and complement 3 (C3) content under P. plecoglossicida infection. What is more, on 9 d post P. plecoglossicida challenge, LAM could significantly decrease the bacteria load in head kidneys, spleens and livers of fish, and the lowest bacterial load was found in 500 mg/kg LAM group. In vitro, LAM exerted a protective role against inactivated P. plecoglossicida-triggered inflammatory injury in primary head kidney macrophages (PKM) of large yellow croaker by recovering cell viability, suppressing NO production, and reversing pro-inflammatory cytokine expression (IL-1ß, IL-6, and IL-8). All these findings therefore will provide insights into the protection mechanism of LAM in fish, facilitating its application in prevention and control of fish bacteriosis.

Characterization of key volatile compounds in jasmine tea infusion with different amount of flowers.

The quality of jasmine tea is related to the volatiles of its infusion. In this study, the volatiles of jasmine tea infusion were extracted under the optimal conditions with a 50/30 µm DVB/CAR/PDMS fiber, tea/water ratio of 1:25 and extraction time of 5 min. A total of 204 volatiles were analyzed by comprehensive two-dimensional gas chromatography-quadrupole time-of-flight mass spectrometry (GC × GC-Q-TOF-MS). Twenty-five compounds were identified as the key volatile compounds by fold change (FC), orthogonal partial least squares discriminant analysis (OPLS-DA), and two-way orthogonal partial least squares analysis (O2PLS). Then optimal amount of flowers (80%-120%) was obtained by the equation describing key volatiles and quality of jasmine tea infusion. And 80% amount of flowers was more appropriate considering the production cost and more pleasant taste. This study laid a foundation for the extraction and research of volatiles of tea infusion and guided the reasonable amount of flowers to produce jasmine tea.

Analysis of Non-Volatile Compounds in Jasmine Tea and Jasmine Based on Metabolomics and Sensory Evaluation.

Scenting tea with Jasminum sambac is beneficial to forming a unique taste of jasmine tea, which is regulated by numerous compounds. To investigate the relationship between metabolites in jasmine and jasmine tea, as well as the impact of metabolites on the characteristic taste of jasmine tea, the liquid chromatography-mass spectrometry, sensory evaluation, and multivariate analysis were applied in this study. A total of 585 and 589 compounds were identified in jasmine tea and jasmine, respectively. After scented, jasmine tea added 70 compounds, which were believed to come from jasmine flowers. Furthermore, seventy-four compounds were identified as key characteristic compounds of jasmine tea, and twenty-two key differential metabolite compounds were believed to be used to distinguish jasmine tea scented differently and contribute to the taste of jasmine tea. Additionally, the relationship between taste compounds and aroma quality was also explored, and it was found that five compounds were positively correlated with the aroma properties of jasmine tea and seven compounds were negatively correlated with the aroma properties of jasmine tea. Overall, these findings provided insights into the future study of the mechanism of taste formation in jasmine tea and provided the theoretical basis for the production of jasmine tea.

Deep Learning-Based Recognition of Cervical Squamous Interepithelial Lesions.

Cervical squamous intraepithelial lesions (SILs) are precursor lesions of cervical cancer, and their accurate diagnosis enables patients to be treated before malignancy manifests. However, the identification of SILs is usually laborious and has low diagnostic consistency due to the high similarity of pathological SIL images. Although artificial intelligence (AI), especially deep learning algorithms, has drawn a lot of attention for its good performance in cervical cytology tasks, the use of AI for cervical histology is still in its early stages. The feature extraction, representation capabilities, and use of p16 immunohistochemistry (IHC) among existing models are inadequate. Therefore, in this study, we first designed a squamous epithelium segmentation algorithm and assigned the corresponding labels. Second, p16-positive area of IHC slides were extracted with Whole Image Net (WI-Net), followed by mapping the p16-positive area back to the H&E slides and generating a p16-positive mask for training. Finally, the p16-positive areas were inputted into Swin-B and ResNet-50 to classify the SILs. The dataset comprised 6171 patches from 111 patients; patches from 80% of the 90 patients were used for the training set. The accuracy of the Swin-B method for high-grade squamous intraepithelial lesion (HSIL) that we propose was 0.914 [0.889-0.928]. The ResNet-50 model for HSIL achieved an area under the receiver operating characteristic curve (AUC) of 0.935 [0.921-0.946] at the patch level, and the accuracy, sensitivity, and specificity were 0.845, 0.922, and 0.829, respectively. Therefore, our model can accurately identify HSIL, assisting the pathologist in solving actual diagnostic issues and even directing the follow-up treatment of patients.

Comprehensive analysis of microbiota signature across 32 cancer types.

Microbial communities significantly inhabit the human body. Evidence shows the interaction between the human microbiome and host cells plays a central role in multiple physiological processes and organ microenvironments. However, the majority of related studies focus on gut microbiota or specific tissues/organs, and the component signature of intratumor microbiota across various cancer types remains unclear. Here, we systematically analyzed the correlation between intratumor microbial signature with survival outcomes, genomic features, and immune profiles across 32 cancer types based on the public databases of Bacteria in Cancer (BIC) and The Cancer Genome Atlas (TCGA). Results showed the relative abundance of microbial taxa in tumors compared to normal tissues was observed as particularly noticeable. Survival analysis found that specific candidate microbial taxa were correlated with prognosis across various cancers. Then, a microbial-based scoring system (MS), which was composed of 64 candidate prognostic microbes, was established. Further analyses showed significant differences in survival status, genomic function, and immune profiles among the distinct MS subgroups. Taken together, this study reveals the diversity and complexity of microbiomes in tumors. Classifying cancer into different subtypes based on intratumor microbial signatures might reasonably reflect genomic characteristics, immune features, and survival status.

A novel fatty-acid metabolism-based classification for triple negative breast cancer.

BACKGROUND: The high heterogeneity of triple negative breast cancer (TNBC) is the main clinical challenge for individualized therapy. Considering that fatty acid metabolism (FAM) plays an indispensable role in tumorigenesis and development of TNBC, we proposed a novel FAM-based classification to characterize the tumor microenvironment immune profiles and heterogeneous for TNBC. METHODS: Weighted gene correlation network analysis (WGCNA) was performed to identify FAM-related genes from 221 TNBC samples in Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset. Then, non-negative matrix factorization (NMF) clustering analysis was applied to determine FAM clusters based on the prognostic FAM-related genes, which chosen from the univariate/multivariate Cox regression model and the least absolute shrinkage and selection operator (LASSO) regression algorithm. Then, a FAM scoring scheme was constructed to further quantify FAM features of individual TNBC patient based on the prognostic differentially expressed genes (DEGs) between different FAM clusters. Systematically analyses were performed to evaluate the correlation between the FAM scoring system (FS) with survival outcomes, genomic characteristics, tumor microenvironment (TME) features and immunotherapeutic response for TNBC, which were further validated in the Cancer Genome Atlas (TCGA) and GSE58812 datasets. Moreover, the expression level and clinical significancy of the selected FS gene signatures were further validated in our cohort. RESULTS: 1860 FAM-genes were screened out using WGCNA. Three distinct FAM clusters were determined by NMF clustering analysis, which allowed to distinguish different groups of patients with distinct clinical outcomes and tumor microenvironment (TME) features. Then, prognostic gene signatures based on the DEGs between different FAM clusters were identified using univariate Cox regression analysis and Lasso regression algorithm. A FAM scoring scheme was constructed, which could divide TNBC patients into high and low-FS subgroups. Low FS subgroup, characterized by better prognosis and abundance with effective immune infiltration. While patients with higher FS were featured with poorer survival and lack of effective immune infiltration. In addition, two independent immunotherapy cohorts (Imvigor210 and GSE78220) confirmed that patients with lower FS demonstrated significant therapeutic advantages from anti-PD-1/PD-L1 immunotherapy and durable clinical benefits. Further analyses in our cohort found that the differential expression of CXCL13, FBP1 and PLCL2 were significantly associated with clinical outcomes of TNBC samples. CONCLUSIONS: This study revealed FAM plays an indispensable role in formation of TNBC heterogeneity and TME diversity. The novel FAM-based classification could provide a promising prognostic predictor and guide more effective immunotherapy strategies for TNBC.

Genomic Profiling and Response to Immune Checkpoint Inhibition plus Tyrosine Kinase Inhibition in FH-Deficient Renal Cell Carcinoma.

BACKGROUND: FH-deficient renal cell carcinoma (RCC) is a rare and exceptionally aggressive RCC subtype. There is currently limited understanding of the molecular alterations, pathogenesis, survival outcomes, and systemic therapy efficacy for this cancer. OBJECTIVE: To perform a retrospective multicenter analysis of molecular profiling and clinical outcomes for patients with FH-deficient RCC, with an emphasis on treatment response to first-line immune checkpoint inhibitor plus tyrosine kinase inhibitor (ICI/TKI) versus bevacizumab plus erlotinib (Bev/Erlo) combination therapy in patients with advanced disease. DESIGN, SETTING, AND PARTICIPANTS: The study included 77 cases of FH-deficient RCC from 15 centers across China. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Clinical characteristics, molecular correlates, 18F-fluorodeoxyglucose positron emission tomography/computed tomography imaging, and treatment outcomes were analyzed. RESULTS AND LIMITATIONS: A total of 77 patients were identified, including 70 cases with a germline FH alteration (hereditary leiomyomatosis RCC syndrome [HLRCC]-associated RCC) and seven patients with somatic FH loss. Recurrent pathogenic alterations were found in NF2 (six/57, 11%), CDH1 (six/57, 11%), PIK3CA (six/57, 11%), and TP53 (five/57, 8.8%). Sixty-seven patients were evaluable for response to first-line systemic therapy with Bev/Erlo (n = 12), TKI monotherapy (n = 29), or ICI/TKI (n = 26). ICI/TKI combination therapy was associated with more favorable overall survival on systemic treatment (hazard ratio [HR] 0.19, 95% confidence interval [CI] 0.04-0.90) and progression-free survival on first-line therapy (HR 0.22, 95% CI 0.07-0.71) compared to Bev/Erlo combination therapy. The main limitation is the retrospective study design. CONCLUSIONS: We described the genomic characteristics of FH-deficient RCC in an Asian population and observed a favorable response to ICI/TKI combinational therapy among patients with advanced disease. PATIENT SUMMARY: This real-world study provides evidence supporting the antitumour activity of combining molecular targeted therapy plus immunotherapy for kidney cancer deficient in fumarate hydratase. Further studies are needed to investigate the efficacy of this combination strategy in this rare cancer.

Influence of Calcineurin Inhibitors and Genetic Polymorphism of Transporters on Enterohepatic Circulation and Exposure of Mycophenolic Acid in Chinese Adult Renal Allograft Recipients.

There is significant enterohepatic circulation (EHC) during the disposition of mycophenolic acid (MPA). The aim of this study was to elucidate factors influencing the EHC of MPA in Chinese adult renal allograft recipients. After 2 weeks of therapy with mycophenolate mofetil or enteric-coated mycophenolate sodium, blood samples were collected from 125 patients at 0 to 12 hours post-administration and MPA concentrations were determined. The influence of calcineurin inhibitors (CNIs) and genetic polymorphisms on MPA exposure and EHC was studied. The Shapley additive explanations method was used to estimate the impact of various factors on the area under the plasma drug concentration-time curve (AUC0-12h ) for MPA. An extreme gradient boosting (XGboost) machine learning-based model was established to predict AUC0-12h . Results showed that the dose-normalized AUC6-12h (dn-AUC6-12h ) of MPA was significantly lower in patients co-administered with cyclosporine (CsA) than in patients co-administered with tacrolimus (TAC) (P < .05). For patients co-administered with TAC, patients with ABCC2 C-24T CC or SLCO1B1 T521C TT genotypes had significantly higher values of dn-AUC6-12h (P < .05). Patients with SLCO1B3 334T/699G alleles had significantly lower dn-AUC6-12h values than homozygotes (P < .05). By introducing body weight, age, and EHC-related factors, including co-administered CNIs and genetic polymorphism of drug transporters, as covariates in the XGboost machine learning model, the prediction performance of AUC0-12h for MPA in Chinese adult renal allograft recipients can be improved.

Estimation of Mycophenolic Acid Exposure in Chinese Renal Transplant Patients by a Joint Deep Learning Model.

BACKGROUND: To predict mycophenolic acid (MPA) exposure in renal transplant recipients using a deep learning model based on a convolutional neural network with bilateral long short-term memory and attention methods. METHODS: A total of 172 Chinese renal transplant patients were enrolled in this study. The patients were divided into a training group (n = 138, Ruijin Hospital) and a validation group (n = 34, Zhongshan Hospital). Fourteen days after renal transplantation, rich blood samples were collected 0-12 hours after MPA administration. The plasma concentration of total MPA was measured using an enzyme-multiplied immunoassay technique. A limited sampling strategy based on a convolutional neural network-long short-term memory with attention (CALS) model for the prediction of the area under the concentration curve (AUC) of MPA was established. The established model was verified using the data from the validation group. The model performance was compared with that obtained from multiple linear regression (MLR) and maximum a posteriori (MAP) methods. RESULTS: The MPA AUC 0-12 of the training and validation groups was 54.28 ± 18.42 and 41.25 ± 14.53 µg·ml -1 ·h, respectively. MPA plasma concentration after 2 (C 2 ), 6 (C 6 ), and 8 (C 8 ) hours of administration was the most significant factor for MPA AUC 0-12 . The predictive performance of AUC 0-12 estimated using the CALS model of the validation group was better than the MLR and MAP methods in previous studies (r 2 = 0.71, mean prediction error = 4.79, and mean absolute prediction error = 14.60). CONCLUSIONS: The CALS model established in this study was reliable for predicting MPA AUC 0-12 in Chinese renal transplant patients administered mycophenolate mofetil and enteric-coated mycophenolic acid sodium and may have good generalization ability for application in other data sets.

Surface urban heat island and its relationship with land cover change in five urban agglomerations in China based on GEE.

The development of urbanization has changed the original land cover and exacerbated the urban heat island effect, seriously affecting the sustainable development of the ecological environment. Research on urban heat island characteristics and land cover changes in five major urban agglomerations in China to provide a reference for preventing thermal environmental risks and urban agglomeration construction planning. This paper estimates the surface urban heat island intensity (SUHII) of the five major urban agglomerations in China from 2003 to 2019 based on Google Earth Engine (GEE) through the urban-rural dichotomy, analyzes their trends through the Sen + M-K trend analysis method, and combines the detrending rate matrix to analyze the impact of land cover type shift on urban heat island change. Research shows that (1) the land cover types of the five major urban agglomerations in China have changed considerably from 2003 to 2019, and all five major urban agglomerations in China experienced varying degrees of urban expansion. (2) The annual average value of SUHII decreases in Beijing-Tianjin-Hebei, Yangtze River Delta, and middle reaches of the urban agglomerations, while the annual average value of SUHII increases in Chengdu-Chongqing and Pearl River Delta urban agglomerations. (3) The spatial composition of land cover types in the five major urban agglomerations in China is highly spatially correlated with urban heat islands, with urban land and bare land urban heat islands being the most pronounced. (4) The land cover type shift has the most significant heat island impact on Beijing-Tianjin-Hebei, Yangtze River Delta, and Chengdu-Chongqing urban agglomerations. (5) The land cover change (LCC) with an increasing trend in SUHII is mainly bare land converted to arable land, and water bodies, grassland, forest land, and arable land converted to urban land.

The pharmacokinetics of tacrolimus in peripheral blood mononuclear cells and limited sampling strategy for estimation of exposure in renal transplant recipients.

PURPOSE: Intracellular exposure of tacrolimus (TAC) may be a better marker of therapeutic effect than whole blood exposure. We aimed to evaluate the influence of genetic polymorphism on the pharmacokinetics of TAC in peripheral blood mononuclear cells (PBMCs) and develop limited sampling strategy (LSS) models to estimate the area under the curve (AUC0-12h) in the PBMC of Chinese renal transplant patients. METHODS: Ten blood samples of each of the 23 renal transplant patients were collected 0-12h after 14 (10-18) days of TAC administration. PBMCs were separated and quantified. The TAC level in PBMCs was determined, and pharmacokinetic parameters were estimated by noncompartmental study. The AUC0-12h of TAC in whole blood was estimated by Bayesian approach based on a population pharmacokinetic model established in 65 renal transplant patients. The influence of CYP3A5 and ABCB1 genotypes on exposure was estimated. By applying multiple stepwise linear regression analysis, LSS equations for TAC AUC0-12h in the PMBC of renal transplant patients were established, and the bias and precision of various equations were identified and compared. RESULTS: We found a modest correlation between TAC exposure in whole blood and PBMC (r2 = 0.5260). Patients with the CYP3A5 6986GG genotype had a higher AUC0-12h in PBMCs than those with the 6986 AA or GA genotype (P = 0.026). Conversely, patients with the ABCB1 3435TT genotype had a higher AUC0-12h in PBMC than those with the 3435 CC and CT genotypes (P = 0.046). LSS models with 1-4 blood time points were established (r2 = 0.570-0.989). The best model for predicting TAC AUC0-12h was C2-C4-C6-C10 (r2 = 0.989). The model with C0.5-C6 (r2 = 0.849) can be used for outpatients who need monitoring to be performed in a short period. CONCLUSIONS: The CYP3A5 and ABCB1 genotypes impact TAC exposure in PBMCs, which may further alter the effects of TAC. The LSS model consisting of 2-4 time points is an effective approach for estimating full TAC AUC0-12h in Chinese renal transplant patients. This approach may provide convenience and the possibility for clinical monitoring of TAC intracellular exposure.

Study on the key volatile compounds and aroma quality of jasmine tea with different scenting technology.

The aroma quality of jasmine tea refers to the strength and freshness of jasmine fragrance and its coordination with tea aroma, which is regulated by various volatile compounds. In this study, seventy volatile compounds of jasmine tea scented by different scenting technology were analyzed qualitatively and quantitatively by gas chromatography-mass spectrometry (GC-MS). And seven compounds were identified as the key volatile compounds by weighted gene co-expression network analysis (WGCNA), orthogonal partial least squares discriminant analysis (OPLS-DA) and odor activity value (OAV). According to the equation describing seven key volatile compounds and quality of jasmine tea, the optimal scenting technology was obtained, that is, the amount of flowers (AF) was 65-78%, scenting time (ST) was 15-17 h, and scenting temperature (SW) was 35-40 °C. This study lays a foundation for the study of aroma characteristics of jasmine tea, and guides enterprises to improve jasmine tea processing technology.

Analysis of Volatile Components of Jasmine and Jasmine Tea during Scenting Process.

Jasmine tea is widely loved by the public because of its unique and pleasant aroma and taste. The new scenting process is different from the traditional scenting process, because the new scenting process has a thin pile height to reduce the high temperature and prolong the scenting time. We qualified and quantified volatiles in jasmine and jasmine tea during the scenting process by gas chromatography-mass spectrometry (GC-MS) with a headspace solid-phase microextraction (HS-SPME). There were 71 and 78 effective volatiles in jasmine and jasmine tea, respectively, including 24 terpenes, 9 alcohols, 24 esters, 6 hydrocarbons, 1 ketone, 3 aldehydes, 2 nitrogen compounds, and 2 oxygen-containing compounds in jasmine; 29 terpenes, 6 alcohols, 28 esters, 8 nitrogen compounds, 1 aldehyde, and 6 other compounds in jasmine tea. The amounts of terpenes, esters, alcohols, nitrogen compounds, and hydrocarbons in jasmine and tea rose and then fell. The amount of oxygenated compounds of tea in the new scenting process first rose and then fell, while it showed a continuous upward trend during the traditional process. The amount of volatiles in jasmine and tea produced by the new scenting process were higher than that of the traditional scenting process at the same time. This study indicated that jasmine tea produced by the new scenting process had better volatile quality, which can provide proof for the new scenting process.

Deep phenotyping of T cell populations under long-term treatment of tacrolimus and rapamycin in patients receiving renal transplantations by mass cytometry.

Tacrolimus (FK506) and rapamycin (RAPA) are widely used to maintain long-term immunosuppression after organ transplantation. However, the impact of accumulative drug administration on the recipients' immune systems remains unclear. We investigated the impact of 3-year FK506 or RAPA treatment after renal transplantation on the human immune systems. A discovery cohort of 30 patients was first recruited, and we discovered two distinctive T lineage suppressive regulatory patterns induced by chronic treatment of FK506 and RAPA. The increased percentage of senescent CD8+ CD57+ T lineages and less responsive T cell receptor (TCR) pathway in the FK506 group indicate better graft acceptance. Meanwhile, percentages of regulatory T cells (Tregs) and expression of CTLA-4 were both up to two-fold higher in the RAPA group, suggesting the inconsistent reactivation potential of the FK506 and RAPA groups when an anti-tumour or anti-infection immune response is concerned. Additionally, up-regulation of phosphorylated signaling proteins in T lineages after in vitro CD3/CD28 stimulation suggested more sensitive TCR-signaling pathways reserved in the RAPA group. An independent validation cohort of 100 renal transplantation patients was further investigated for the hypothesis that long-term RAPA administration mitigates the development of tumours and infections during long-term intake of immunosuppressants. Our results indicate that RAPA administration indeed results in less clinical oncogenesis and infection. The deep phenotyping of T-cell lineages, as educated by the long-term treatment of different immunosuppressants, provides new evidence for personalized precision medicine after renal transplantations.