The expression and significance of PD-L1 in condyloma acuminatum.

BACKGROUND: It has been reported that programmed death-ligand 1 (PD-L1) is highly expressed in cells during viral infection, which helps the virus escape host immunity. However, the relationship between human papillomavirus (HPV) and PD-L1 in condyloma acuminatum and whether they participate in immunosuppression have not been reported. In this paper, we aimed to explore the expression and significance of PD-L1 in condyloma acuminatum. METHODS: The expression of PD-L1 in the wart of condyloma acuminatum patients and the foreskin of healthy individuals was evaluated. Lentivirus transfection was used to introduce the HPV11-E7 gene into HaCaT cells to investigate whether HPV infection could affect the expression of PD-L1. The successfully constructed HPV11-E7 HaCaT cells were cocultured with Jurkat cells, and Jurkat cell apoptosis and proliferation as well as the Jurkat cell cycle were evaluated by flow cytometry and cell counting kit-8 (CCK-8) assays. RESULTS: PD-L1 was highly expressed in keratinocytes of genital warts. Through the construction of a cell model, we found that HPV11-E7 could upregulate the expression of PD-L1 in HaCaT cells. Furthermore, HPV11-E7 HaCaT cells can promote the apoptosis of Jurkat cells, inhibit the proliferation of Jurkat cells and mediate the cell cycle arrest of Jurkat cells through the PD-1/PD-L1 signalling pathway. CONCLUSIONS: HPV infection may upregulate PD-L1 expression in the keratinocytes of genital warts and participate in the inhibition of local T-cell function.

Convolutional neural network based on T-SPOT.TB assay promoting the discrimination between active tuberculosis and latent tuberculosis infection.

OBJECTIVES: The study aims to investigate the potential of convolutional neural network (CNN) based on spot image of T-SPOT assay for distinguishing active tuberculosis (ATB) from latent tuberculosis infection (LTBI). METHODS: CNN was applied to recognize and classify T-SPOT spot image. Logistic regression was used to establish prediction model based on CNN. RESULTS: Areas under the receiver operating characteristic curve (AUCs) of early secreted antigenic target 6 (ESAT-6) CNN, culture filtrate protein 10 (CFP-10) CNN, and phytohemagglutinin (PHA) CNN were more than 0.7 in differentiating ATB from LTBI, while the performance of these indicators was significantly better than that of spot number. Furthermore, prediction model based on the combination of CNNs yielded an AUC of 0.898. The model presented a sensitivity of 85.76% and a specificity of 90.23%. CONCLUSIONS: The current study identified CNN based on T-SPOT spot image with the potential to serve as a tool for TB diagnostics.

Prediction model of no-response before the first transarterial chemoembolization for hepatocellular carcinoma: TACF score.

Previous clinic models for patients with hepatocellular carcinoma (HCC) receiving transarterial chemoembolization (TACE) mainly focused on the overall survival, whereas a simple-to-use tool for predicting the response to the first TACE and the management of risk classification before TACE are lacking. Our aim was to develop a scoring system calculated manually for these patients. A total of 437 patients with hepatocellular carcinoma (HCC) who underwent TACE treatment were carefully selected for analysis. They were then randomly divided into two groups: a training group comprising 350 patients and a validation group comprising 77 patients. Furthermore, 45 HCC patients who had recently undergone TACE treatment been included in the study to validate the model's efficacy and applicability. The factors selected for the predictive model were comprehensively based on the results of the LASSO, univariate and multivariate logistic regression analyses. The discrimination, calibration ability and clinic utility of models were evaluated in both the training and validation groups. A prediction model incorporated 3 objective imaging characteristics and 2 indicators of liver function. The model showed good discrimination, with AUROCs of 0.735, 0.706 and 0.884 and in the training group and validation groups, and good calibration. The model classified the patients into three groups based on the calculated score, including low risk, median risk and high-risk groups, with rates of no response to TACE of 26.3%, 40.2% and 76.8%, respectively. We derived and validated a model for predicting the response of patients with HCC before receiving the first TACE that had adequate performance and utility. This model may be a useful and layered management tool for patients with HCC undergoing TACE.

Enhanced Glycogen Metabolism Supports the Survival and Proliferation of HPV-Infected Keratinocytes in Condylomata Acuminata.

Condylomata acuminata (CA) is caused by human papillomavirus (HPV) infections of keratinocytes and is a common sexually transmitted disease. The main clinical feature and risk of CA is the high recurrence of genital warts formed by infected keratinocytes. Metabolic reprogramming of most types of mammalian cells including keratinocytes can provide energy and intermediates essential for their survival. Here, we report that HPV infection develops a hypoxic microenvironment in CA warts by inducing the accumulation of glycogen and increased glycogen metabolism in the infected keratinocytes in a hypoxia-inducible factor 1α (HIF-1α) -dependent pathway. Our in vitro studies show that the increased glycogen metabolism is essential for the survival and proliferation of keratinocytes. Regarding its mechanism of action, glycogenolysis generates glucose-1-phosphate that fluxes into the pentose phosphate pathway and, then, generates abundant nicotinamide adenine dinucleotide phosphate, thereby ensuring high levels of glutathione in keratinocytes under hypoxia. The abrogation of glycogen synthesis and glycogenolysis decreases the ratio of glutathione and glutathione disulfide and increases the level of ROS, further resulting in the impairment of keratinocyte survival. Collectively, our work offers an insight into the metabolic reprogramming in the development of CA and implies that the intervention of glycogen metabolism would be a promising therapeutic target for CA.

Diagnostic Accuracy of T-SPOT.TB Assay for Tuberculous Meningitis: An Updated Meta-Analysis.

Background: The role of T-SPOT.TB (T-SPOT) assay for tuberculous meningitis (TBM) diagnosis has not been fully assessed. Here, we conducted an updated meta-analysis to evaluate the diagnostic accuracy of peripheral blood (PB) T-SPOT and cerebrospinal fluid (CSF) T-SPOT for diagnosing TBM. Methods: Relevant studies in the PubMed database, EmBase database, Cochrane database, Scopus database, Google Scholar, China National Knowledge Internet, and Wan-Fang database were retrieved from August 1, 2005, to June 22, 2020. Statistical analysis was performed using Stata, Revman, and Meta-Disc software. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), summary receiver operating characteristic curves, and the area under the curve were determined and analyzed. Results: A total of 27 studies were eligible for inclusion within the meta-analysis. The pooled sensitivity and specificity of PB T-SPOT for TBM diagnosis were 0.78 (95% CI, 0.76-0.81) and 0.68 (95% CI, 0.66-0.71), respectively, whereas the pooled PLR, NLR, and DOR were 2.80 (95% CI, 2.29-3.42), 0.32 (95% CI, 0.27-0.38), and 10.08 (95% CI, 7.21-14.08), respectively. On the other hand, the pooled sensitivity and specificity of CSF T-SPOT on diagnosing TBM were 0.76 (95% CI, 0.72-0.80) and 0.88 (95% CI, 0.85-0.90), respectively, whereas the pooled PLR, NLR, and DOR were 5.92 (95% CI, 4.25-8.25), 0.28 (95% CI, 0.21-0.39), and 29.05 (95% CI, 16.40-51.45), respectively. The area under the summary receiver operating characteristic curve values of PB T-SPOT and CSF T-SPOT for TBM diagnosis were 0.83 (95% CI, 0.80-0.86) and 0.92 (95% CI, 0.89-0.94), respectively. Conclusions: CSF T-SPOT showed a higher specificity compared with PB T-SPOT for diagnosing TBM. Both two T-SPOT assays have considerable potential in improving the diagnosis of TBM. Furthermore, the standardization of the operating procedure is further needed when performing CSF T-SPOT.

Diagnostic value of pleural fluid T-SPOT for tuberculous pleurisy: An updated meta-analysis.

BACKGROUND: Diagnosing tuberculous pleurisy (TP) remains a clinical challenge and the best method to diagnose it is controversial. Although several studies have investigated the performance of pleural fluid (PF) T-SPOT for pleural tuberculosis (plTB) diagnosis, the heterogeneity of its accuracy exists. Therefore, we performed an updated meta-analysis of the existing evidence on the utility of PF T-SPOT to diagnose TP. METHODS: PubMed and EmBase were searched for relevant English articles up to July 29, 2019. Statistical analysis was performed using Stata, Revman, and Meta-Disc. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were determined. Summary receiver operating characteristic (SROC) curves and the area under the curve (AUC) were used to summarize the overall diagnostic performance. RESULTS: A total of 13 studies (997 patients with TP and 656 patients without TP) were identified and enrolled to meta-analysis, giving the following pooled values for diagnostic accuracy of PF T-SPOT: sensitivity, 0.91 (95% CI, 0.89-0.92, I2 = 80.9%); specificity, 0.88 (95% CI, 0.86-0.91, I2 = 87.3%); PLR, 6.28 (95% CI, 2.88-13.69, I2 = 93.3%); NLR, 0.12 (95% CI, 0.07-0.21, I2 = 84.9%); DOR, 59.74 (95% CI, 24.13-147.93, I2 = 78.3%); and the area under the SROC curve, 0.95 (95% CI, 0.93-0.97). CONCLUSIONS: Our meta-analysis suggests that PF T-SPOT has important diagnostic value for plTB. However, the standardization of the operating procedure needs to be further promoted, which would make the results more credible.