Oxidized ATP Suppresses B Lymphocyte Activity to Attenuate Antibody-mediated Rejection of Kidney Allografts in Mice.

BACKGROUND: Antibody-mediated rejection (AMR) is a major cause of renal allograft dysfunction and loss. Targeting B cells and/or donor-specific antibody removal using plasma exchange and anti-CD20 antibodies are increasingly used in clinical practice, but the efficacy remains limited. Recent studies suggest that targeting purinergic P2X7 receptor/ATP axis can have profound immune regulatory effects in transplant models, but the mechanisms involved remain incompletely defined. METHODS: Purified B cells were isolated from the spleen of Balb/C mice and cultured with oxidized ATP at different concentrations. Proliferation and differentiation of B cells were examined. Effects of oxidized ATP were examined in a presensitized animal model where kidney allograft rejection mimics aspects of clinical AMR. Histopathology was assessed at the time of rejection or on day 5 after kidney transplantation. Infiltrating immune cells in renal allografts were detected by flow cytometry. RESULTS: Oxidized ATP inhibited B-cell activation and proliferation in vitro, significantly attenuated histological signs of graft injury and prolonged kidney allograft survival. Mechanistically, oxidized ATP inhibited antibody secretion by activated B cells in response to lipopolysaccharide stimulation and markedly suppressed the production of donor-specific antibody in kidney allograft recipients. Oxidized ATP also reduced graft infiltration by other inflammatory cells. CONCLUSIONS: These findings provide evidence for the involvement of the purinergic P2X7 receptor pathway in AMR and suggest that targeting this pathways may have important clinical implications.

A dual RNA-seq analyses revealed dynamic arms race during the invasion of walnut by Colletotrichum gloeosporioides.

BACKGROUND: Walnut anthracnose caused by Colletotrichum gloeosporioides seriously endangers the yield and quality of walnut, and has now become a catastrophic disease in the walnut industry. Therefore, understanding both pathogen invasion mechanisms and host response processes is crucial to defense against C. gloeosporioides infection. RESULTS: Here, we investigated the mechanisms of interaction between walnut fruits (anthracnose-resistant F26 fruit bracts and anthracnose-susceptible F423 fruit bracts) and C. gloeosporioides at three infection time points (24hpi, 48hpi, and 72hpi) using a high-resolution time series dual transcriptomic analysis, characterizing the arms race between walnut and C. gloeosporioides. A total of 20,780 and 6670 differentially expressed genes (DEGs) were identified in walnut and C. gloeosporioides against 24hpi, respectively. Generous DEGs in walnut exhibited opposite expression patterns between F26 and F423, which indicated that different resistant materials exhibited different transcriptional responses to C. gloeosporioides during the infection process. KEGG functional enrichment analysis indicated that F26 displayed a broader response to C. gloeosporioides than F423. Meanwhile, the functional analysis of the C. gloeosporioides transcriptome was conducted and found that PHI, SignalP, CAZy, TCDB genes, the Fungal Zn (2)-Cys (6) binuclear cluster domain (PF00172.19) and the Cytochrome P450 (PF00067.23) were largely prominent in F26 fruit. These results suggested that C. gloeosporioides secreted some type of effector proteins in walnut fruit and appeared a different behavior based on the developmental stage of the walnut. CONCLUSIONS: Our present results shed light on the arms race process by which C. gloeosporioides attacked host and walnut against pathogen infection, laying the foundation for the green prevention of walnut anthracnose.

JrPHL8-JrWRKY4-JrSTH2L module regulates resistance to Colletotrichum gloeosporioides in walnut.

Walnut anthracnose (Colletotrichum gloeosporioides) reduces walnut yield and quality and seriously threatens the healthy development of the walnut industry. WRKY transcription factors (TFs) are crucial regulatory factors involved in plant-pathogen interactions. Our previous transcriptome analysis results indicate that JrWRKY4 responds to infection by C. gloeosporioides, but its specific regulatory network and disease resistance mechanism are still unclear. Herein, the characteristics of JrWRKY4 as a transcription activator located in the nucleus were first identified. Gain-of-function and loss-of-function analyses showed that JrWRKY4 could enhance walnut resistance against C. gloeosporioides. A series of molecular experiments showed that JrWRKY4 directly interacted with the promoter region of JrSTH2L and positively regulated its expression. In addition, JrWRKY4 interacted with JrVQ4 to form the protein complex, which inhibited JrWRKY4 for the activation of JrSTH2L. Notably, a MYB TF JrPHL8 interacting with the JrWRKY4 promoter has also been identified, which directly bound to the MBS element in the promoter of JrWRKY4 and induced its activity. Our study elucidated a novel mechanism of the JrPHL8-JrWRKY4-JrSTH2L in regulating walnut resistance to anthracnose. This mechanism improves our understanding of the molecular mechanism of WRKY TF mediated resistance to anthracnose in walnut, which provides new insights for molecular breeding of disease-resistant walnuts in the future.

Pharmacokinetics of nirmatrelvir/ritonavir and the drug-drug interaction with calcineurin inhibitor in renal transplant recipients.

OBJECTIVES: To describe the pharmacokinetic (PK) characteristics of nirmatrelvir/ritonavir in renal transplant recipients and explore the potential factors that related to the PK variance of nirmatrelvir/ritonavir and its interaction with calcineurin inhibitor (CNI). METHODS: Renal transplant recipients treated with CNI and nirmatrelvir/ritonavir were prospectively enrolled. Steady-state plasma concentrations of nirmatrelvir/ritonavir were determined by high-performance liquid chromatography-tandem mass spectrometry, and the PK parameters were calculated using non-compartmental analysis. Spearman correlation analysis was used for exploring influencing factors. RESULTS: A total of eight recipients were enrolled; for nirmatrelvir and ritonavir, AUC/dose was 0.24179 ± 0.14495 and 0.06196 ± 0.03767 µg·h·mL-1·mg-1. Red blood cell (RBC), hematocrit (Ht), hemoglobins (Hb), and creatinine clearance (Ccr) were negatively correlated with AUC/dose of nirmatrelvir, while Ccr, CYP3A5 genotype, and CYP3A4 genotype were related to the AUC/dose of ritonavir. Ccr was negatively correlated with the C0/dose of tacrolimus (TAC) after termination of nirmatrelvir/ritonavir (rs = -0.943, p = 0.008). CONCLUSIONS: The PK characteristics of nirmatrelvir/ritonavir vary greatly among renal transplant recipients. Factors including Ccr and CYP3A5 genotype were related to the in vivo exposure of nirmatrelvir/ritonavir. During the whole process before and after nirmatrelvir/ritonavir therapy, it is recommended to adjust the CNI basing on renal function to avoid CNI toxicity exposure.

The association between systemic inflammatory response index and contrast-associated acute kidney injury in patients undergoing elective percutaneous coronary intervention.

BACKGROUND: The systemic inflammatory response index (SIRI), served as a novel inflammatory biomarker, is the synthesis of neutrophils, monocytes and lymphocytes. AIMS: We hypothesized that SIRI has predictive value for contrast-associated acute kidney injury (CA-AKI) and long-term mortality in patients undergoing elective percutaneous coronary intervention (PCI). METHODS: We retrospectively observed 5685 patients undergoing elective PCI from January 2012 to December 2018. Venous blood samples were collected to obtain the experimental data on the day of admission or the morning of the next day. SIRI = neutrophil count × monocyte count/lymphocyte count. CA-AKI was defined as an increase of 50% or 0.3 mg/dl in SCr from baseline within 48 h after contrast exposure. RESULTS: The incidence of CA-AKI was 6.1% (n = 352). The best cutoff value of SIRI for predicting CA-AKI was 1.39, with a sensitivity of 52.3% and a specificity of 67.3%. [AUC: 0.620, 95% confidence interval (CI): 0.590-0.651, p < 0.001]. After adjusting for potential confounders, multivariate analysis showed that the high SIRI group (SIRI > 1.39) was a strong independent predictor of CA-AKI in patients undergoing elective PCI compared with the low SIRI group (SIRI ≤ 1.39) (odds ratio = 1.642, 95% CI: 1.274-2.116, p < 0.001). Additionally, COX regression analysis showed that SIRI > 1.39 was significantly associated with long-term mortality at a median follow-up of 2.8 years. [Hazard ratio (HR)=1.448, 95%CI: 1.188-1.765; p < 0.001]. Besides, Kaplan-Meier survival curve also indicated that the cumulative rate of mortality was considerably higher in the high SIRI group. CONCLUSIONS: High levels of SIRI are independent predictors of CA-AKI and long-term mortality in patients undergoing elective PCI.

Quantitative analysis and stochastic modeling of osteophyte formation and growth process on human vertebrae based on radiographs: a follow-up study.

Osteophytes are frequently observed in elderly people and most commonly appear at the anterior edge of the cervical and lumbar vertebrae body. The anterior osteophytes keep developing and will lead to neck/back pain over time. In clinical practice, the accurate measurement of the anterior osteophyte length and the understanding of the temporal progression of anterior osteophyte growth are of vital importance to clinicians for effective treatment planning. This study proposes a new measuring method using the osteophyte ratio index to quantify anterior osteophyte length based on lateral radiographs. Moreover, we develop a continuous stochastic degradation model with time-related functions to characterize the anterior osteophyte formation and growth process on cervical and lumbar vertebrae over time. Follow-up data of anterior osteophytes up to 9 years are obtained for measurement and model validation. The agreement test indicates excellent reproducibility for our measuring method. The proposed model accurately fits the osteophyte growth paths. The model predicts the mean time to onset of pain and obtained survival function of the degenerative vertebrae. This research opens the door to future quantification and mathematical modeling of the anterior osteophyte growth on human cervical and lumbar vertebrae. The measured follow-up data is shared for future studies.

The effect of retirement on physical and mental health in China: a nonparametric fuzzy regression discontinuity study.

BACKGROUND: With the rapid aging of the domestic population, China has a strong incentive to increase the statutory retirement age. How retirement affects the health of the elderly is crucial to this policymaking. The health consequences of retirement have been debated greatly. This study aims to investigate the effects of retirement on physical and mental health among Chinese elderly people. METHODS: The data we use in this study comes from four waves (2011, 2013, 2015, and 2018) of the Harmonized China Health and Retirement Longitudinal Study (Harmonized CHARLS), a prospective cohort. We use the nonparametric fuzzy regression discontinuity design to estimate the effects of retirement on physical and mental health. We test the robustness of our results with respect to different bandwidths, kernel functions, and polynomial orders. We also explore the heterogeneity across gender and education. RESULTS: Results show that retirement has an insignificant effect on a series of physical and mental health outcomes, with and without adjusting several sociodemographic variables. Heterogeneity exists regarding gender and education. Although stratified analyses indicate that the transition from working to retirement leaves minimal effects on males and females, the effects go in the opposite direction. This finding holds for low-educated and high-educated groups for health outcomes including depression and cognitive function. Most of the results are stable with respect to different bandwidths, kernel functions, and polynomial orders. CONCLUSIONS: Our results suggest that it is possible to delay the statutory retirement age in China as retirement has insignificant effects on physical and mental health. However, further research is needed to assess the long-term effect of retirement on health.

Healthcare facilities management: A novel data-driven model for predictive maintenance of computed tomography equipment.

BACKGROUND: The breakdown of healthcare facilities is a huge challenge for hospitals. Medical images obtained by Computed Tomography (CT) provide information about the patients' physical conditions and play a critical role in diagnosis of disease. To deliver high-quality medical images on time, it is essential to minimize the occurrence frequencies of anomalies and failures of the equipment. METHODS: We extracted the real-time CT equipment status time series data such as oil temperature, of three equipment, between May 19, 2020, and May 19, 2021. Tube arcing is treated as the classification label. We propose a dictionary-based data-driven model SAX-HCBOP, where the two methods, Histogram-based Information Gain Binning (HIGB) and Coefficient improved Bag of Pattern (CoBOP), are implemented to transform the data into the bag-of-words paradigm. We compare our model to the existing predictive maintenance models based on statistical and time series classification algorithms. RESULTS: The results show that the Accuracy, Recall, Precision and F1-score of the proposed model achieve 0.904, 0.747, 0.417, 0.535, respectively. The oil temperature is identified as the most important feature. The proposed model is superior to other models in predicting CT equipment anomalies. In addition, experiments on the public dataset also demonstrate the effectiveness of the proposed model. CONCLUSIONS: The two proposed methods can improve the performance of the dictionary-based time series classification methods in predictive maintenance. In addition, based on the proposed real-time anomaly prediction system, the model assists hospitals in making accurate healthcare facilities maintenance decisions.

Value of original and modified pathological scoring systems for prognostic prediction in paraffin-embedded donor kidney core biopsy.

BACKGROUND: No study has validated, compared and adapted scoring systems for prognosis prediction based on donor kidney core biopsy (CB), with less glomeruli than wedge biopsy. METHODS: A total of 185 donor kidney CB specimens were reviewed using seven scoring systems. The association between the total score, item scores, score-based grading, and allograft prognosis was investigated. In specimens with less than ten glomeruli (88/185, 47.6%), scoring systems were modified by adjusting weights of the item scores. RESULTS: The Maryland aggregate pathology index (MAPI) score-based grading and periglomerular fibrosis (PGF) associated with delayed graft function (DGF) (Grade: OR = 1.59, p < 0.001; PGF: OR = 1.06, p = 0.006). Total score, score-based grading and chronic lesion score in scoring systems associated with one-year and 3-year eGFR after transplantation. Total-score-based models had similar predictive capacities for eGFR in all scoring systems, except MAPI and Ugarte. Score of glomerulosclerosis (GS), interstitial fibrosis (IF), tubular atrophy (TA), and arteriolar hyalinosis (AH) had good eGFR predictive capacities. In specimens with less than ten glomeruli, modified scoring systems had better eGFR predictive capacities than original scoring systems. CONCLUSIONS: Scoring systems could predict allograft prognosis in paraffin-embedded CB with ten more glomeruli. A simple and pragmatic scoring system should include GS, IF, TA and AH, with weights assigned based on predictive capacity for prognosis. Replacing GS scores with tubulointerstitial scores could significantly improve the predictive capacity of eGFR. The conclusion should be further validated in frozen section.

The Association Between the Albumin-Bilirubin Score and Contrast-Associated Acute Kidney Injury in Patients Undergoing Elective Percutaneous Coronary Intervention.

The albumin-bilirubin (ALBI) score is considered an effective and convenient scoring system for assessing liver function. We hypothesized that the ALBI score was predictive of contrast-associated acute kidney injury (CA-AKI) and long-term mortality in patients undergoing elective percutaneous coronary intervention (PCI). We retrospectively observed 5629 patients undergoing elective PCI. Contrast-associated acute kidney injury is defined as a 50% or 0.3 mg/dl increase in baseline serum creatinine levels within 48 h of contrast exposure. The incidence of CA-AKI was 6.2% (n = 350). After adjusting for potential confounding factors, multivariate analysis showed that the ALBI score was an independent predictor of CA-AKI (P = .002). A restricted cubic spline analysis confirmed approximately linear relationships between the ALBI score and risks of CA-AKI. Furthermore, at a median follow-up of 2.8 years, multivariate Cox regression analysis indicated that the ALBI score was an independent risk factor for long-term mortality (P < .001). The ALBI score was closely related to the occurrence of CA-AKI and long-term mortality in patients who underwent elective PCI. This score might be useful for risk stratification in high-risk patient groups to predict CA-AKI.

A Machine Learning-Driven Virtual Biopsy System For Kidney Transplant Patients.

In kidney transplantation, day-zero biopsies are used to assess organ quality and discriminate between donor-inherited lesions and those acquired post-transplantation. However, many centers do not perform such biopsies since they are invasive, costly and may delay the transplant procedure. We aim to generate a non-invasive virtual biopsy system using routinely collected donor parameters. Using 14,032 day-zero kidney biopsies from 17 international centers, we develop a virtual biopsy system. 11 basic donor parameters are used to predict four Banff kidney lesions: arteriosclerosis, arteriolar hyalinosis, interstitial fibrosis and tubular atrophy, and the percentage of renal sclerotic glomeruli. Six machine learning models are aggregated into an ensemble model. The virtual biopsy system shows good performance in the internal and external validation sets. We confirm the generalizability of the system in various scenarios. This system could assist physicians in assessing organ quality, optimizing allograft allocation together with discriminating between donor derived and acquired lesions post-transplantation.

Prognostic Biomarkers in Kidney Transplantation: A Systematic Review and Critical Appraisal.

SIGNIFICANCE STATEMENT: Why are there so few biomarkers accepted by health authorities and implemented in clinical practice, despite the high and growing number of biomaker studies in medical research ? In this meta-epidemiological study, including 804 studies that were critically appraised by expert reviewers, the authors have identified all prognostic kidney transplant biomarkers and showed overall suboptimal study designs, methods, results, interpretation, reproducible research standards, and transparency. The authors also demonstrated for the first time that the limited number of studies challenged the added value of their candidate biomarkers against standard-of-care routine patient monitoring parameters. Most biomarker studies tended to be single-center, retrospective studies with a small number of patients and clinical events. Less than 5% of the studies performed an external validation. The authors also showed the poor transparency reporting and identified a data beautification phenomenon. These findings suggest that there is much wasted research effort in transplant biomarker medical research and highlight the need to produce more rigorous studies so that more biomarkers may be validated and successfully implemented in clinical practice. BACKGROUND: Despite the increasing number of biomarker studies published in the transplant literature over the past 20 years, demonstrations of their clinical benefit and their implementation in routine clinical practice are lacking. We hypothesized that suboptimal design, data, methodology, and reporting might contribute to this phenomenon. METHODS: We formed a consortium of experts in systematic reviews, nephrologists, methodologists, and epidemiologists. A systematic literature search was performed in PubMed, Embase, Scopus, Web of Science, and Cochrane Library between January 1, 2005, and November 12, 2022 (PROSPERO ID: CRD42020154747). All English language, original studies investigating the association between a biomarker and kidney allograft outcome were included. The final set of publications was assessed by expert reviewers. After data collection, two independent reviewers randomly evaluated the inconsistencies for 30% of the references for each reviewer. If more than 5% of inconsistencies were observed for one given reviewer, a re-evaluation was conducted for all the references of the reviewer. The biomarkers were categorized according to their type and the biological milieu from which they were measured. The study characteristics related to the design, methods, results, and their interpretation were assessed, as well as reproducible research practices and transparency indicators. RESULTS: A total of 7372 publications were screened and 804 studies met the inclusion criteria. A total of 1143 biomarkers were assessed among the included studies from blood ( n =821, 71.8%), intragraft ( n =169, 14.8%), or urine ( n =81, 7.1%) compartments. The number of studies significantly increased, with a median, yearly number of 31.5 studies (interquartile range [IQR], 23.8-35.5) between 2005 and 2012 and 57.5 (IQR, 53.3-59.8) between 2013 and 2022 ( P < 0.001). A total of 655 studies (81.5%) were retrospective, while 595 (74.0%) used data from a single center. The median number of patients included was 232 (IQR, 96-629) with a median follow-up post-transplant of 4.8 years (IQR, 3.0-6.2). Only 4.7% of studies were externally validated. A total of 346 studies (43.0%) did not adjust their biomarker for key prognostic factors, while only 3.1% of studies adjusted the biomarker for standard-of-care patient monitoring factors. Data sharing, code sharing, and registration occurred in 8.8%, 1.1%, and 4.6% of studies, respectively. A total of 158 studies (20.0%) emphasized the clinical relevance of the biomarker, despite the reported nonsignificant association of the biomarker with the outcome measure. A total of 288 studies assessed rejection as an outcome. We showed that these rejection studies shared the same characteristics as other studies. CONCLUSIONS: Biomarker studies in kidney transplantation lack validation, rigorous design and methodology, accurate interpretation, and transparency. Higher standards are needed in biomarker research to prove the clinical utility and support clinical use.

Dual-Targeting Nanovesicles Carrying CSF1/CD47 Identified from Single-Cell Transcriptomics of Innate Immune Cells in Heart Transplant for Alleviating Acute Rejection.

Although immunosuppressive drugs for targeting T cells are the standard of care in acute transplantation rejection, the role of innate immune cells should not be ignored. Here, single-cell RNA sequencing (scRNA-seq) and flow cytometry are performed to reveal the dynamic changes of innate immune cells within the acute rejection time and find a significantly-increased presence of Ly6G- Ly6C+ inflammatory macrophages and decreased presence of neutrophils among all types of immune cells. Next, to further explore potential targets regulating Ly6G- Ly6C+ inflammatory macrophages, scRNA-seq is used to analyze the reciprocal signaling of both neutrophils and macrophages, along with the surface genes of macrophages. It is found that activating colony-stimulating factor 1/ colony-stimulating factor 1 receptor (CSF1/CSF1R) andcluster of differentiation 47/signal regulatory protein α (CD47/SIRPα) signaling may serve as a strategy to relieve Ly6G- Ly6C+ inflammatory macrophage-mediated early graft rejection. To investigate this hypothesis, CSF1/CD47 dual-targeting nanovesicles (NVs) derived from IFN-γ-stimulated induced pluripotent stem cell-derived mesenchymal stem cells ( iPSC-MSCs )are designed and constructed. It is confirmed that CSF1/CD47 NVs synergistically induce the differentiation of Ly6G- Ly6C- M2 inhibitory macrophages by the CSF1/CSF1R pathway, and inhibit the phagocytosis of inflammatory macrophages and inflammatory response by the CD47/SIRPα pathway, ultimately relieving immune rejection. This study highlights the power of dual-targeting CSF1/CD47 NVs as an immunosuppressant against early innate immune responses with the potential for broad clinical applications.

LncRNA109897-JrCCR4-JrTLP1b forms a positive feedback loop to regulate walnut resistance against anthracnose caused by Colletotrichum gloeosporioides.

Walnut anthracnose induced by Colletotrichum gloeosporioides is a disastrous disease that severely restricts the development of the walnut industry in China. Long non-coding RNAs (lncRNAs) are involved in adaptive responses to disease, but their roles in the regulation of walnut anthracnose resistance response are not well defined. In this study, transcriptome analysis demonstrated that a C. gloeosporioides-induced lncRNA, lncRNA109897, located upstream from the target gene JrCCR4, upregulated the expression of JrCCR4. JrCCR4 interacted with JrTLP1b and promoted its transcriptional activity. In turn, JrTLP1b induced the transcription of lncRNA109897 to promote its expression. Meanwhile, transient expression in walnut leaves and stable transformation of Arabidopsis thaliana further proved that lncRNA, JrCCR4, and JrTLP1b improve the resistance of C. gloeosporioides. Collectively, these findings provide insights into the mechanism by which the lncRNA109897-JrCCR4-JrTLP1b transcriptional cascade regulates the resistance of walnut to anthracnose.

Anomaly prediction of CT equipment based on IoMT data.

BACKGROUND: Large-scale medical equipment, which is extensively implemented in medical services, is of vital importance for diagnosis but vulnerable to various anomalies and failures. Most hospitals that conduct regular maintenance have been suffering from medical equipment-related incidents for years. Currently, the Internet of Medical Things (IoMT) has emerged as a crucial tool in monitoring the real-time status of the medical equipment. In this paper, we develop an IoMT system of Computed Tomography (CT) equipment in the West China Hospital, Sichuan University and collected the system status time-series data. Novel multivariate time-series classification models and frameworks are proposed to predict the anomalies of CT equipment. The important features that are closely related to the equipment anomalies are identified with the model. METHODS: We extracted the real-time CT equipment status time-series data of 11 equipment between May 19, 2020 and May 19, 2021 from the IoMT, which includes the equipment oil temperature, anode voltage, etc. The arcs are identified as labels of anomalies due to their relationship with decreased imaging quality and CT equipment failures. To improve prediction accuracy, the statistics and transformations of the raw historical time-series data segment in the sliding time window are used to construct new features. Due to the particularity of time-series data, two frameworks are proposed for splitting the training and test sets. Then the Decision Tree, Support Vector Machine, Logistic Regression, Naive Bayesian, and K-Nearest Neighbor classification models are used to classify the system status. We also compare our model to state-of-the-art models. RESULTS: The results show that the anomaly prediction accuracy and recall of our method are 79% and 77%, respectively. The oil temperature and anode voltage are identified as the decisive features that may lead to anomalies. The proposed model outperforms the others when predicting the anomalies of the CT equipment based on our dataset. CONCLUSIONS: The proposed method could predict the state of CT equipment and be used as a reference for practical maintenance, where unexpected anomalies of medical equipment could be reduced. It also brings new insights into how to handle non-uniform and imbalanced time series data in practical cases.

RENAL nephrometry scoring system in bilateral Wilms tumor: predictive application.

AIM: This study aims to explore the application of RENAL nephrometry scoring system in bilateral Wilms tumor (BWT). METHODS: A retrospective review of patients with BWT from January 2010 to June 2022 was performed. Each kidney unit of the BWT was evaluated independently and scored according to RENAL nephrometry scoring system by 2 blinded reviewers, and reviewers were blinded to what surgery the patients ultimately had. Discrepancies were evaluated by a third reviewer to reach a consensus. Tumor anatomical characteristics were summarized and compared. RESULTS: 29 patients with 53 kidney units were included in the study. 53 kidney units included 12 (22.6%) low-complexity, 9 (17.0%) intermediate-complexity, and 32 (60.4%) high-complexity. 2 kidney units (3.8%) had tumor thrombus, and 14 (26.4%) had multiple lesions. A total of 42 kidney units (79.2%) underwent initial nephron-sparing surgery (NSS) and 11 (20.8%) underwent radical nephrectomy. Less complexity tumors were observed in the NSS group. Of the 42 kidney units undergoing initial NSS, 26 were performed in vivo and 16 ex vivo via autotransplantation. The latter group featured a higher complexity. During follow-up, 22 patients survived and 7 died, no statistically significant tumor complexity was observed between the two groups. CONCLUSIONS: The anatomical characteristics of BWT are complex. Despite this study did not indicate that the complexity correlates with prognosis, low-complexity tumors were candidates for NSS, and kidney autotransplantation provided a feasible procedure for high-complexity tumors. A refined system is required due to multiple lesions and tumor thrombus.

Predictive Value of Systemic Inflammation Score for Contrast-Associated Acute Kidney Injury and Adverse Outcomes Among Patients Undergoing Elective Percutaneous Coronary Intervention.

Purpose: Prior research has demonstrated a key role of systemic inflammatory state in the pathogenesis and progression of contrast-associated acute kidney injury (CA-AKI). Recently, the systemic inflammation score (SIS) has been introduced to evaluate the inflammatory status, utilizing the lymphocyte-to-monocyte ratio (LMR) and albumin. The primary objective of this study was to determine whether the SIS can predict CA-AKI and long-term prognosis in patients undergoing elective percutaneous coronary intervention (PCI). Patients and Methods: A total of 5726 patients who underwent elective PCI were included from January 2012 to December 2018. The primary outcome was CA-AKI, defined as an increase in serum creatinine (SCr) ≥0.3 mg/dl or ≥50% than baseline SCr within 48 h after the PCI procedure. The secondary outcome was long-term mortality. All patients were classified into low- and high-SIS groups. Results: During hospitalization, 349 (6.1%) patients developed CA-AKI. Multivariate logistic regression analysis showed that patients in the high SIS group had a 1.47-fold higher risk of developing CA-AKI than those in the low SIS group [odds ratio (OR): 1.50, 95% confidence interval (CI): 1.12-2.01, P =0.006]. Furthermore, the SIS showed the greatest prediction performance for CA-AKI compared with other inflammatory hematological ratios. In the multivariate Cox regression analysis, the high SIS group was found to be closely associated with long-term mortality [hazard ratio (HR): 1.58, 95% CI: 1.26-1.97, P <0.001, vs low SIS group]. The Kaplan-Meier curve analysis also demonstrated a difference in long-term mortality between the two groups (Log rank test, P <0.001). Conclusion: The SIS was closely associated with CA-AKI and long-term mortality in patients after elective PCI. Thus, more attention should be paid to exploring the potential benefits of anti-inflammatory strategies in preventing CA-AKI and improving the prognosis of patients undergoing PCI.

Interferon-gamma FlowSpot assay for the measurement of the T-cell response to cytomegalovirus.

Objectives: We describe a new method, FlowSpot, to assess CMV-specific T-cell response by quantification of interferon-gamma (IFN-γ). CMV-specific, T-cell-released IFN-γ was captured by flow beads and measured via flow cytometry. In the present study, we used FlowSpot to assess CMV-specific T-cell response in healthy individuals. The FlowSpot results were compared with those of serological analysis and enzyme-linked immunospot (ELISpot) assay. Methods: Experimental results and parameter analysis were investigated by using serological, ELISpot, and FlowSpot assays. Results: The levels of IFN-γ, which is released from CMV-specific T-cells, were measured, and the results and parameter analysis showed a good correlation between FlowSpot and ELISpot. However, FlowSpot was more sensitive and better reflected the strength of IFN-γ secretion than did ELISpot. Conclusions: Compared to ELISpot, FlowSpot has a high sensitivity and is cost and time effective. Thus, this method can be used in wider clinical and scientific applications.

Shear wave elastography using high-frequency linear probe for kidney transplant monitoring: A methodological study.

OBJECTIVES: To investigate the influencing factors of the image quality of shear wave elastography (SWE) performed using a high-frequency probe and its reproducibility for renal allografts. METHODS: A total of 211 patients with transplanted kidneys who underwent SWE examination performed using high-frequency or low-frequency probes were recruited for the study. The reproducibility of inter- and intraobserver agreements were analysed by using the intraclass correlation coefficient (ICC). According to the colour filling of the area of interest and imaging noise when conducting SWE, the image quality was classified as three grades: "good", "common", and "poor". A logistic regression was used to analyse the independent factors for SWE quality. RESULTS: In the comparative analysis, high frequency, transection measurement and middle pole were selected as the appropriate measurement methods. Regarding reproducibility, the ICCs) of the intra- and interobserver agreements were 0.85 and 0.77, respectively. Multivariate analysis indicated that only the skin allograft distance and kidney width were independent variables for SWE quality. In the subgroup analysis of the skin-allograft distance, the "good" and "common" rates of images decreased as the distance increased, but the CV (coefficients of variation) showed the opposite trend. The SWE quality of kidney width <5.4 cm was significantly better than that of kidney width ≥5.4 cm. CONCLUSIONS: High-frequency SWE can be used in the evaluation of transplanted kidneys due to its good repeatability and high successful measurement rate, but we should pay attention to the influence of the skin-allograft distance and kidney width on SWE quality.