In December 2019, a new type viral pneumonia cases occurred in Wuhan, Hubei Province; and then named "2019 novel coronavirus (2019-nCoV)" by the World Health Organization (WHO) on 12 January 2020. For it is a never been experienced respiratory disease before and with infection ability widely and quickly, it attracted the world's attention but without treatment and control manual. For the request from frontline clinicians and public health professionals of 2019-nCoV infected pneumonia management, an evidence-based guideline urgently needs to be developed. Therefore, we drafted this guideline according to the rapid advice guidelines methodology and general rules of WHO guideline development; we also added the first-hand management data of Zhongnan Hospital of Wuhan University. This guideline includes the guideline methodology, epidemiological characteristics, disease screening and population prevention, diagnosis, treatment and control (including traditional Chinese Medicine), nosocomial infection prevention and control, and disease nursing of the 2019-nCoV. Moreover, we also provide a whole process of a successful treatment case of the severe 2019-nCoV infected pneumonia and experience and lessons of hospital rescue for 2019-nCoV infections. This rapid advice guideline is suitable for the first frontline doctors and nurses, managers of hospitals and healthcare sections, community residents, public health persons, relevant researchers, and all person who are interested in the 2019-nCoV.

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Background6-mercaptopurine (6-MP) contributes substantially to remarkable improvement in the survival of childhood acute lymphoblastic leukemia (ALL) patients. However, 6-MP also has dose-limiting toxicities, particularly life-threatening myelosuppression, due to genetic polymorphisms in enzymes that metabolize 6-MP. Promising biomarkers for predicting 6-MP-induced leukopenia is still unclear in Chinese population. Here, we evaluated the associations of NUDT15, TPMT and ITPA genotypes with 6-MP intolerance in our cohort of childhood ALL patients.MethodsA total of 105 Chinese pediatric patients with a confirmed diagnosis of ALL were enrolled. We identified the NUDT15 coding variant rs116855232 (c.415C > T), a newly discovered 6-MP toxicity-related locus in Asians, and polymorphisms in TPMT rs1142345 and ITPA rs11273540. Associations between genotypes and 6-MP dose sensitivity, leukopenia, hepatotoxicity, and therapy interruption were evaluated.ResultsThe minor allele frequencies (MAFs) of NUDT15 rs116855232, TPMT rs1142345 and ITPA rs11273540 were 15.7, 2.9, and 18.1%, respectively. NUDT15 and TPMT genetic variants were strongly associated with 6-MP dose intensity. Patients with NUDT15 homogenous genotype (TT) were highly sensitive to 6-MP (dose intensity of 60.27%) compared to these with heterozygous genotype (TC) or wild type (CC), who tolerated an average dose intensity of 83.83 and 94.24%, respectively. The NUDT15 variant was a predictor for leukopenia (OR: 3.62, 95% CI 1.377–9.501, P = 0.009) and early-onset leukopenia (OR: 9.63, 95% CI 2.764–33.514, P = 3.75 × 10− 4). No differences were found between 6-MP dose intensity and ITPA polymorphisms.ConclusionNUDT15 variant is an optimal predictor for 6-MP intolerance in Chinese pediatric ALL patients and may have greatly clinical implications for individualized therapy.

Follicular regulatory T (Tfr) cell can effectively regulate humoral immunity, but its function and mechanism in antibody-mediated rejection (AMR) after organ transplantation remains unclear. Here we detected follicular helper T (Tfh) cell subsets in 88 renal transplant patients with chronic renal allograft dysfunction (40 with AMR and 48 without AMR). The ratio of Tfr cells in renal graft tissues and peripheral blood of AMR patients significantly decreased, while the ratio of IL-21-producing Tfh cells (Tfh2 and Tfh17) significantly increased, compared to non-AMR patients. When tested in functional assays, Tfr cells from both AMR and non-AMR patients exerted equivalent inhibitory function. Tfr cell transplantation or CTLA-4 virus transfection could significantly inhibit IL-21 secretion from Tfh cells of these patients, further suppress the proliferation and differentiation of B cells. CTLA-4 blocking, IL-10 and TGF-β neutralization could partially weaken such inhibitory effect of Tfr cells. Besides, our study found that sirolimus reduced the ratio of Tfr cells, while cyclosporine and tacrolimus had no significant effect on Tfr cells. In a word, renal transplant patients with AMR have low proportion of Tfr cells but these cell exerted normal function.

Aim: The aim of this study was to evaluate tacrolimus population pharmacokinetics and investigate factors that explain tacrolimus variability in adult heart transplant patients. Methods: A total of 707 tacrolimus concentrations from 107 adult heart transplant patients were included in model development. The effects of demographic, clinical factors and CYP3A5 genotype on tacrolimus clearance were evaluated using a nonlinear mixed-effects modeling. 24 patients with 106 tacrolimus concentrations were used for external validation. Results: The pharmacokinetic data were adequately described by a one-compartment model with first-order absorption and elimination. The estimated apparent clearance and volume of distribution of tacrolimus were 13.7 l/h and 791 l, respectively. Tacrolimus apparent clearance was significantly reduced in CYP3A5 nonexpressers (CYP3A5*3/*3), concomitant with azole antifungal drugs and Wuzhi capsule (WZ). A predictive performance was further confirmed in an external validation by Bayesian estimation. Recommended dose regimens were obtained by simulations based on the established model. Conclusion: This is the first population pharmacokinetic study conducted in Chinese heart transplant recipients. These findings are of great importance with regards to tacrolimus dose optimization in heart transplantation patients.

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Background The supervised deep learning approach provides state-of-the-art performance in a variety of fundus image classification tasks, but it is not applicable for screening tasks with numerous or unknown disease types. The unsupervised anomaly detection (AD) approach, which needs only normal samples to develop a model, may be a workable and cost-saving method of screening for ocular diseases. Objective This study aimed to develop and evaluate an AD model for detecting ocular diseases on the basis of color fundus images. Methods A generative adversarial network–based AD method for detecting possible ocular diseases was developed and evaluated using 90,499 retinal fundus images derived from 4 large-scale real-world data sets. Four other independent external test sets were used for external testing and further analysis of the model’s performance in detecting 6 common ocular diseases (diabetic retinopathy [DR], glaucoma, cataract, age-related macular degeneration, hypertensive retinopathy [HR], and myopia), DR of different severity levels, and 36 categories of abnormal fundus images. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the model’s performance were calculated and presented. Results Our model achieved an AUC of 0.896 with 82.69% sensitivity and 82.63% specificity in detecting abnormal fundus images in the internal test set, and it achieved an AUC of 0.900 with 83.25% sensitivity and 85.19% specificity in 1 external proprietary data set. In the detection of 6 common ocular diseases, the AUCs for DR, glaucoma, cataract, AMD, HR, and myopia were 0.891, 0.916, 0.912, 0.867, 0.895, and 0.961, respectively. Moreover, the AD model had an AUC of 0.868 for detecting any DR, 0.908 for detecting referable DR, and 0.926 for detecting vision-threatening DR. Conclusions The AD approach achieved high sensitivity and specificity in detecting ocular diseases on the basis of fundus images, which implies that this model might be an efficient and economical tool for optimizing current clinical pathways for ophthalmologists. Future studies are required to evaluate the practical applicability of the AD approach in ocular disease screening.