De novo generation of dual-target ligands using adversarial training and reinforcement learning.

Artificial intelligence, such as deep generative methods, represents a promising solution to de novo design of molecules with the desired properties. However, generating new molecules with biological activities toward two specific targets remains an extremely difficult challenge. In this work, we conceive a novel computational framework, herein called dual-target ligand generative network (DLGN), for the de novo generation of bioactive molecules toward two given objectives. Via adversarial training and reinforcement learning, DLGN treats a sequence-based simplified molecular input line entry system (SMILES) generator as a stochastic policy for exploring chemical spaces. Two discriminators are then used to encourage the generation of molecules that belong to the intersection of two bioactive-compound distributions. In a case study, we employ our methods to design a library of dual-target ligands targeting dopamine receptor D2 and 5-hydroxytryptamine receptor 1A as new antipsychotics. Experimental results demonstrate that the proposed model can generate novel compounds with high similarity to both bioactive datasets in several structure-based metrics. Our model exhibits a performance comparable to that of various state-of-the-art multi-objective molecule generation models. We envision that this framework will become a generally applicable approach for designing dual-target drugs in silico.

Method development for analyzing ultratrace polyhalogenated carbazoles in soil and sediment.

In the past few years, polyhalogenated carbazoles (PHCZs) have been of increasing concern because their structure is similar to that of legacy POPs. In the present study, an analytical method, including intensive cleanup and fractionation procedures in combination with instrumental parameters, was developed to determine ultratrace polyhalogenated carbazoles (PHCZs) in soil and sediment. The eluting sorbents, volume and packing of the column were optimized. Our results showed that 5 g of florisil and 4 g of silica gel under 150 mL of hexane/DCM = 3:1 presented good performance in terms of recovery and repeatability. GC-HRMS, GC-MS/MS (EI-MRM) and GC-MS (EI-SIM) were applied to compare the performance of PHCZ analysis. For sensitivity, EI-MRM presents method detection limits comparable to those of GC-HRMS and much lower than those of EI-SIM. Regarding selectivity, GC-HRMS performed better than the other two techniques since GC-HRMS can reduce interference from perfluorokerosene (PFK) and DDX (DDT, DDE, and DDD) due to its high resolution. GC-HRMS was then further optimized by shortening the run time and modifying the SIM ion. The final method was successfully applied to determine PHCZs in soil and sediment, and the target compounds had almost 100% detection frequency in the samples. The ubiquitous presence of PHCZ in soil and sediment calls for a further investigation of its source, distribution and degradation in the environment.

Determination of trace polychlorinated biphenyls and organochlorine pesticides in water samples through large-volume stir bar sorptive extraction method with thermal desorption gas chromatography.

A fast and sensitive analytical method based on stir bar sorptive extraction technology with gas chromatography and mass spectrometry was developed to simultaneously analyze 18 kinds of polychlorinated biphenyls and 20 kinds of organochlorine pesticides in aqueous samples. A long adsorption time and small sample volume, which are problems encountered in conventional methods of stir bar sorptive extraction, were effectively solved by simultaneously using multiple stir bars for enrichment with sequential cryofocusing and merged injection. Optimized results showed good linear coefficients in the range of 10-500 ng/L and the method detection limits of 0.12-2.07 ng/L for polychlorinated biphenyls and organochlorine pesticides. The recovery ratios of the spiked samples at different concentrations were between 64.7 and 111.0%, and their relative standard deviations ranged from 0.9 to 17.6%. Four types of the studied compounds were determined in Qiantang River water samples, and their contents were between 0.82 and 5.00 ng/L.

Annual risk of tuberculosis infection in rural China: a population-based prospective study.

Prospective population data on the incidence of tuberculosis (TB) infection has been sparsely reported in the global literature.A population-based prospective study was conducted in rural China to investigate the annual risk of TB infection, and its persistence using serial tuberculin skin tests (TSTs) and an interferon-γ release assay. In total, 13 580 eligible participants from four rural sites, identified as TST negative (<10 mm) or QuantiFERON-TB Gold In-Tube (QFT) (an interferon-γ release assay) negative from a baseline survey, were included in the first year's follow-up examination.The annual conversion rate of QFT among the study sites ranged between 2.1% and 4.9% (average 3.1%), and the incidence of TST conversion ranged between 6.0% and 31.1% (average 14.5%). During the second year's follow-up, infection persistence was investigated using 390 subjects with QFT conversions. Among them, 49.7% (164 out of 330) were found to be consistently QFT positive. Both the conversion and the persistence of QFT positivity were found to be significantly increased with increasing age.In conclusion, the annual TB infection rate was suggested to be ∼1.5% based on persistent positive results after QFT conversion in rural China. Therefore, infection control among those high-risk populations, including the elderly, should be prioritised for TB control in China.

Human papillomavirus infection and laryngeal cancer risk: a systematic review and meta-analysis.

BACKGROUND: A number of molecular epidemiological studies have been conducted to explore the association of human papillomavirus (HPV) infection with laryngeal cancer. However, the findings are heterogeneous. METHODS: We systematically reviewed studies on HPV infection and laryngeal cancer published up to 15 May 2012 and quantitatively summarized the prevalence of HPV infection and its association with the risk of laryngeal cancer by means of meta-analysis. RESULTS: In total, 55 eligible studies were included. The overall HPV prevalence in laryngeal cancer tissues was 28.0% (95% confidence interval [CI], 23.5%-32.9%). A total of 26.6% laryngeal cancer patients were infected with high-risk HPV types only, and HPV-16 was most frequently observed type, with a prevalence of 19.8% (95% CI, 15.7%-24.6%). The meta-analysis based on 12 eligible case-control studies suggests a strong association between HPV infection and laryngeal squamous cell carcinoma, with a summary odds ratio (OR) of 5.39 (95% CI, 3.25-8.94). Different magnitudes of association were observed for HPV-16 (OR, 6.07; 95% CI, 3.44-10.70) and HPV-18 (OR = 4.16; 95% CI, .87-20.04; P < .01). Stratified analyses were performed with respect to HPV genotypes and characteristics of the study population. CONCLUSIONS: HPV infection, especially infection due to the high-risk type HPV-16, was found to be significantly associated with the risk of laryngeal squamous cell carcinoma.

Osteoinductive biomaterials: Machine learning for prediction and interpretation.

Biomaterials with osteoinductivity are widely used for bone defect repair due to their unique structures and functions. Machine learning (ML) is pivotal in analyzing osteoinductivity and accelerating new material design. However, challenges include creating a comprehensive database of osteoinductive materials and dealing with low-quality, disparate data. As a standard for evaluating the osteoinductivity of biomaterials, ectopic ossification has been used. This paper compiles research findings from the past thirty years, resulting in a robust database validated by experts. To tackle issues of limited data samples, missing data, and high-dimensional sparsity, a data enhancement strategy is developed. This approach achieved an area under the curve (AUC) of 0.921, a precision of 0.839, and a recall of 0.833. Model interpretation identified key factors such as porosity, bone morphogenetic protein-2 (BMP-2), and hydroxyapatite (HA) proportion as crucial determinants of outcomes. Optimizing pore structure and material composition through partial dependence plot (PDP) analysis led to a new bone area ratio of 14.7 ± 7 % in animal experiments, surpassing the database average of 10.97 %. This highlights the significant potential of ML in the development and design of osteoinductive materials. STATEMENT OF SIGNIFICANCE: This study leverages machine learning to analyze osteoinductive biomaterials, addressing challenges in database creation and data quality. Our data enhancement strategy significantly improved model performance. By optimizing pore structure and material composition, we increased new bone formation rates, showcasing the vast potential of machine learning in biomaterial design.

Health literacy and associated factors in China: findings from the Wa ethnic group.

Background: The health literacy of ethnic groups in remote areas of China is far from satisfactory. However, the health literacy of ethnic groups in China remains unclear. This study aimed to explore the health literacy of the "advancing directly" ethnic group and its influencing factors. Methods: A cross-sectional study was conducted using a staged sampling method among the Wa ethnic group, who have rapidly transitioned directly from the traditional lifestyle of slash-and-burn cultivation to modern societies. We used the Health Literacy Questionnaire (HLQ) to assess health literacy. We defined low health literacy as less than 60% of the total score and adequate health literacy as more than 80% of the total score. Results: A total of 668 individuals met the inclusion criteria and the mean age was 42.19 (SD 10.56) years. The mean HLQ total score was 29.9 (SD 10.56). The prevalence of adequate health literacy was 0.89%. There were significant differences between the low and the non-low health literacy groups in terms of gender, age, education, marital status, occupation, residing place, current smoking status, and waist circumference (all p < 0.05). Multiple linear regression analysis showed that women (t = 9·418, p < 0.001), older age (B = -0.0091, t = -2.644, p = 0.008), low educational level (B = 0.766, t = 6.018, p < 0.001), current smoking (B = -2.66, t = -3.038, p = 0.008), and residence far from township (B = -5.761, t = -4.1, p < 0.001) were associated with low HLQ total score. Conclusion: Our findings suggest that the health literacy of the Wa ethnic group is far from favorable. It indicates the need for increased efforts in improving the health literacy of "advancing directly" ethnic groups.

Potential association of pulmonary tuberculosis with genetic polymorphisms of toll-like receptor 9 and interferon-gamma in a Chinese population.

BACKGROUND: Association studies have been employed to investigate the relationships between host single nucleotide polymorphisms (SNPs) and susceptibility to pulmonary Tuberculosis (PTB). However, such candidate genetic markers have not been widely studied in Chinese population, especially with respect to the disease development from latent M. tuberculosis infection (LTBI). METHODS: In this case-control study, 44 candidate SNPs were examined in a total of 600 participants (PTB patients, LTBI controls and healthy controls without M. tuberculosis infection) from Zhengzhou, China. The two groups of controls were frequency matched on gender and age with PTB patients. Genotyping was carried out by the Illumina Golden Gate assay. RESULTS: When comparing PTB patients with LTBI controls but not healthy controls without M. tuberculosis infection, significant associations with disease development were observed for TLR9 1174 A/G, TLR9 1635 A/G and IFNG 2109G/A. The two loci in TLR9 were in LD in our study population (r(2)=0.96, D'=1.00). A combined effect of the genotypes associated with increased risk of PTB (i.e. TLR9 1174G/G and IFNG 2109 A/A) was found when comparing PTB patients with LTBI controls (p=0.004) but not with healthy controls without infection (p=0.433). CONCLUSIONS: Potential associations between TLR9 and IFN-γ genetic polymorphisms and PTB were observed in a Chinese population which supports further study of the roles played by TLR9/IFN-γ pathway during the development of PTB.

Combination of switchable hydrophilic solvent liquid-liquid microextraction with QuEChERS for trace determination of triazole fungicide pesticides by GC-MS.

This work first proposed a novel green and efficient method based on Quick, Easy, Cheap, Efficient, Rugged, and Safe pretreatment (QuEChERS) combined with switchable hydrophilic solvent homogeneous liquid-liquid microextraction (SHS-HLLME) for trace determination of triazole fungicides (TFs) in agricultural products such as vegetables and fruits by gas chromatography-mass spectrometry (GC-MS). N,N-Dimethyl benzylamine was used for the synthesis of SHS. Box-Behnken design was applied for the optimization of extraction conditions and a mathematical model was obtained. Ultimately, 0.50 mL SHS, 1.0 mL 10 mol L-1 sodium hydroxide, and 45 s ultrasonic time were determined as optimal conditions for the SHS-HLLME method. The limit of detection and limit of quantification determined using the optimal method (SHS-HLLME/GC-MS) were 0.13-0.27 ng mL-1 and 0.43-0.90 ng mL-1, respectively. In addition, the SHS-HLLME method under optimal conditions was combined with the traditional QuEChERS method to realize the advancement of the SHS-HLLME method from simple to complex matrix analysis, and the QuEChERS-SHS-HLLME method was successfully applied to the analysis of TFs in cucumbers, tomatoes, watermelon and grapes in agricultural products. Matrix-matched calibration standards were used to improve the accuracy of TFs in spiked cucumber samples to obtain recovery results close to 100%. It was shown that the new method is green and rapid, enabling fast and inexpensive sample pretreatment with up to 100-fold enrichment factor and low detection limit compared with the original QuEChERS method.

Benchmarking Accuracy and Generalizability of Four Graph Neural Networks Using Large In Vitro ADME Datasets from Different Chemical Spaces.

In this work, we benchmark a variety of single- and multi-task graph neural network (GNN) models against lower-bar and higher-bar traditional machine learning approaches employing human engineered molecular features. We consider four GNN variants - Graph Convolutional Network (GCN), Graph Attention Network (GAT), Message Passing Neural Network (MPNN), and Attentive Fingerprint (AttentiveFP). So far deep learning models have been primarily benchmarked using lower-bar traditional models solely based on fingerprints, while more realistic benchmarks employing fingerprints, whole-molecule descriptors and predictions from other related endpoints (e. g., LogD7.4) appear to be scarce for industrial ADME datasets. In addition to time-split test sets based on Genentech data, this study benefits from the availability of measurements from an external chemical space (Roche data). We identify GAT as a promising approach to implementing deep learning models. While all the deep learning models significantly outperform lower-bar benchmark traditional models solely based on fingerprints, only GATs seem to offer a small but consistent improvement over higher-bar benchmark traditional models. Finally, the accuracy of in vitro assays from different laboratories predicting the same experimental endpoints appears to be comparable with the accuracy of GAT single-task models, suggesting that most of the observed error from the models is a function of the experimental error propagation.

A knowledge graph of clinical trials ([Formula: see text]).

Effective and successful clinical trials are essential in developing new drugs and advancing new treatments. However, clinical trials are very expensive and easy to fail. The high cost and low success rate of clinical trials motivate research on inferring knowledge from existing clinical trials in innovative ways for designing future clinical trials. In this manuscript, we present our efforts on constructing the first publicly available Clinical Trials Knowledge Graph, denoted as [Formula: see text]. [Formula: see text] includes nodes representing medical entities in clinical trials (e.g., studies, drugs and conditions), and edges representing the relations among these entities (e.g., drugs used in studies). Our embedding analysis demonstrates the potential utilities of [Formula: see text] in various applications such as drug repurposing and similarity search, among others.

A Novel Green Diluent for the Preparation of Poly(4-methyl-1-pentene) Membranes via a Thermally-Induced Phase Separation Method.

The use of green solvents satisfies safer chemical engineering practices and environmental security. Herein, myristic acid (MA)-a green diluent-was selected to prepare poly- (4-methyl-1-pentene) (PMP) membranes with bicontinuous porous structure via a thermally induced phase separation (TIPS) process to maintain a high gas permeability. Firstly, based on the Hansen solubility parameter 'distance', Ra, the effect of four natural fatty acids on the PMP membrane structure was compared and studied to determine the optimal green diluent, MA. The thermodynamic phase diagram of the PMP-MA system was calculated and presented to show that a liquid-liquid phase separation region could be found during the TIPS process and the monotectic point was around 34.89 wt%. Then, the effect of the PMP concentration on the morphologies and crystallization behavior was systematically investigated to determine a proper PMP concentration for the membrane preparation. Finally, PMP hollow fiber (HF) membranes were fabricated with a PMP concentration of 30 wt% for the membrane performance characterization. The resultant PMP HF membranes possessed good performances that the porosity was 70%, the tensile strength was 96 cN, and the nitrogen flux was 8.20 ± 0.10 mL·(bar·cm2·min)-1. We believe that this work can be a beneficial reference for people interested in the preparation of PMP membranes for medical applications.

DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science.

Graph neural networks (GNNs) constitute a class of deep learning methods for graph data. They have wide applications in chemistry and biology, such as molecular property prediction, reaction prediction, and drug-target interaction prediction. Despite the interest, GNN-based modeling is challenging as it requires graph data preprocessing and modeling in addition to programming and deep learning. Here, we present Deep Graph Library (DGL)-LifeSci, an open-source package for deep learning on graphs in life science. Deep Graph Library (DGL)-LifeSci is a python toolkit based on RDKit, PyTorch, and Deep Graph Library (DGL). DGL-LifeSci allows GNN-based modeling on custom datasets for molecular property prediction, reaction prediction, and molecule generation. With its command-line interfaces, users can perform modeling without any background in programming and deep learning. We test the command-line interfaces using standard benchmarks MoleculeNet, USPTO, and ZINC. Compared with previous implementations, DGL-LifeSci achieves a speed up by up to 6×. For modeling flexibility, DGL-LifeSci provides well-optimized modules for various stages of the modeling pipeline. In addition, DGL-LifeSci provides pretrained models for reproducing the test experiment results and applying models without training. The code is distributed under an Apache-2.0 License and is freely accessible at https://github.com/awslabs/dgl-lifesci.

Multiple classes of chemical contaminants in soil from an e-waste disposal site in China: Occurrence and spatial distribution.

E-waste recycling is well known for releasing halogenated organic compounds (HOCs) and heavy metals. This study investigated the occurrence and distribution of traditional and novel classes of contaminants, including chlorinated, brominated, and mixed halogenated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs, PBDD/Fs, PXDD/Fs), polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs) and polyhalogenated carbazoles (PHCZs), in soil from an e-waste disposal site in Hangzhou. PBDEs were the most abundant, at 343-69306 ng kg-1, followed by PHCZs (896-41,362 ng kg-1), PCDD/Fs (349-19,396 ng kg-1), PCBs (51.3-1834 ng kg-1), PBDD/Fs (2.99-524 ng kg-1) and PXDD/Fs (0.104-21.2 ng kg-1). The detected target compound concentrations were generally lower than those reported in the literature for informal e-waste sites. Nevertheless, they can serve as a basis of information for evaluation and subsequent control. The toxic equivalent (TEQ) contributions from these contaminants (except PBDEs) decreased as follows: PCDD/Fs > PXDD/Fs > PHCZs > PCBs > PBDD/Fs. ΣDioxins (PCDD/Fs + PBDD/Fs + PXDD/Fs) accounted for 47.7%-97.2% of the total TEQs in the soil. OCDD, 1,2,3,4,6,7,8-HpBDF and OBDF were the dominant congeners, mainly derived from combustion and transport because of their low saturated vapor pressure. PXDFs were more abundant than PXDDs, and homologue profiles suggested a similar formation mechanism for PXDFs and PBDFs involving successive Br-to-Cl exchange. PHCZs were reported in soil from an e-waste disposal area for the first time, and their concentrations were several orders of magnitude higher than those of the other contaminants. Although the risk of human exposure in this study was estimated to be lower than the values recommended by the WHO (1-4 pg TEQ/kg bw/day), health implications still exist, and further investigations are necessary.

Evaluation of atmospheric sources of PCDD/Fs, PCBs and PBDEs around an MSWI plant using active and passive air samplers.

This study evaluated the spatial distributions and concentrations of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) in ambient air around a municipal solid waste incineration (MSWI) plant located in eastern China in two sampling campaigns within one year. Twenty high-volume samples and 27 passive air samples were collected from May 2012 to May 2013. The mean sampling rate of the passive sampler was estimated to be 3.8 ± 1.8 m3 d-1 in summer and autumn, while the mean sampling rate was 2.8 ± 1.0 m3 d-1 in winter and spring. Hence, the annual mean sampling rate was approximately 3.2 ± 1.4 m3 d-1. The mean levels of PCDD/Fs, PCBs, PBDEs (excluding BDE-209) and BDE-209 in the passive air samples varied in the ranges of 0.086 ± 0.058-0.76 ± 0.51 pg TEQ m-3, 39 ± 26-170 ± 120 pg m-3, 3.3 ± 2.2-36 ± 24 pg m-3 and 58 ± 39-300 ± 150 pg m-3, respectively. The levels, congener profiles and spatial distributions of PCDD/Fs, PCBs and PBDEs were investigated. The results showed that the concentrations of PCDD/Fs and PCBs decreased with increasing distance from the emission source and that different sampling sites had slightly different effects. However, this trend was opposite to that observed for PBDEs. Moreover, principal component analysis (PCA) demonstrated that the MSWI emission source was the primary factor for PCDD/Fs in ambient air. Further monitoring should be conducted to evaluate the noticeable impact on the environment and human health due to exposure.

Serum level of IL-8 is associated with reversion of QuantiFERON-TB gold in-tube tests.

BACKGROUND: Frequent reversion has been commonly observed in serial QuantiFERON-TB Gold In-Tube (QFT) tests, which limited its accuracy in defining the status of Mycobacterium tuberculosis (MTB) infection. Serum cytokine profiles might provide additional information to clarify the infection status. METHOD: Based on a population-based cohort study aiming to track MTB infection acquisition and disease development, serum profiles of 12 cytokines were determined by bead-based multiplex assays in parallel with QFT and tuberculin skin tests (TST) to explore potential relation between serum cytokines and MTB infection status. RESULTS: Totally, 309 subjects got QFT conversion in one year (2013-2014) and 46.92% (145/309) of them got reversion in 2015. The study subjects were classified into three groups according to their QFT and TST results in 2015 (QFT persistence positive, QFT-/TST + and QFT-/TST-). The serum levels of MCP-1 and IL-8 were significantly different among the three groups. Furthermore, level of IL-8 was dramatically lower in QFT-/TST- group as compared to the other two groups, and no significant difference was observed for QFT-/TST + group as comparing with persistent positive group. CONCLUSION: Our results suggested that the decreased serum level of IL-8 might be potential biomarker to identify QFT reversion caused by infection clearance.

Human Papillomavirus awareness and vaccine acceptability among men who have sex with men from mainland China.

Reductions in persistent HPV infection and related diseases occurrence have been proved among vaccinated males. However, little was known on awareness of HPV and the vaccine in males, especially in high-risk subgroups such as men who have sex with men (MSM), in China. A multicenter cross-sectional study was conducted in MSM from 10 selected cities in mainland China. HPV awareness and vaccination acceptability were investigated through interviews and questionnaires. In total, 3057 eligible participants aged 18 years older from 10 cities were investigated. Only 20.6% (629/3057) of them had ever heard of HPV and 4.8% (146/3057) had heard of HPV vaccine. Factors that potentially influence willingness for HPV vaccination were found to be safety of the vaccine (54.2%, 1656/3057) and severity of HPV infection (52.3%, 1599/3057). After education, 97.8% (2882/2946) of participants would like to pay for HPV vaccination, and only a minority of them (2.5%, 75/2946) would like to afford more than 2000 RMB. Our results showed that the awareness on HPV and the vaccine were quite poor among MSM in mainland China. To promote the application of HPV vaccination in male populations, appropriate information delivery and education on HPV infection and health should be enhanced as well as in females.

Study on the pollution characteristics and emission factors of PCDD/Fs from disperse dye production in China.

According to an analysis of the input and output of polychlorinated dibenzo-p-dioxin and dibenzofurans (PCDD/Fs) of two disperse dye manufacturers, the average PCDD/F emission factor was 56.3 µg I-TEQ/T product, and dioxin was mainly emitted with products and solid waste. The PCDD/F concentrations of different series of disperse dyes varied from 2.87 to 323 pg I-TEQ/g, and the dominant congener was OCDD or 2,3,7,8-TCDF with the highest ratio of 83.4% or 79.3%, respectively. The distributions of PCDD/F congeners in raw materials and the products were different, indicating that the structure of PCDD/Fs greatly changed in the synthesis process. PCDD/Fs in the wastewater and sludge of the companies are mainly from the production process of a product with dominant emission factors. Our results confirm that disperse dyes may be a source of PCDD/Fs, resulting in human exposure and environmental contamination.

Serial testing of Mycobacterium tuberculosis infection in Chinese village doctors by QuantiFERON-TB Gold Plus, QuantiFERON-TB Gold in-Tube and T-SPOT.TB.

OBJECTIVES: To evaluate the performance of QuantiFERON-TB Gold Plus (QFT-Plus) on Mycobacterium tuberculosis (MTB) infection test among registered village doctors from China. METHODS: MTB infection of the registered village doctors in Zhongmu County were tested using QFT-Plus and two other interferon-gamma release assays (IGRAs) in parallel: QuantiFERON-TB Gold In-Tube (QFT) and T-SPOT.TB (T-SPOT). Retests were carried out for baseline positives at 3 and 6 months later, respectively. RESULTS: A total of 616 village doctors were included in the baseline examination. The positivity of QFT, QFT-Plus and T-SPOT was 27.91% (168/602), 31.22% (187/599) and 27.70% (169/610), respectively. The concordance between QFT and QFT-Plus was 94.81% (Kappa coefficient: 0.87) and between T-SPOT and QFT-Plus was 88.93% (Kappa coefficient: 0.73). Reversions were frequently observed for all three assays. With respect to QFT-Plus, the quantitative results of reversions in the serial testing were mostly distributed in an "uncertain range" zone (0.2-0.7 IU/mL). Similar patterns of distribution were observed for QFT and T-SPOT as well. CONCLUSION: Village doctors should gain more attention as an at-risk group for TB infection control in rural China. Our results support, by means of serial testing, a good agreement between QFT-Plus and QFT in Chinese population.

Reversion of QuantiFERON-TB Gold In-Tube test in individuals with and without prophylactic treatment for latent tuberculosis infection: A systematic review and meta-analysis.

OBJECTIVES: Reversion of tuberculosis (TB) infection testing has been suggested to be associated with prophylactic treatment efficacy. However, evidences based on randomized controlled study were sparse. METHODS: Studies on serial QuantiFERON-TB Gold In-Tube (QFT) test, among individuals with and without prophylactic treatment were identified in the databases of PubMed, MEDLINE and EMBASE up to 28 February 2018. The reversion rates were quantitatively summarized by means of meta-analysis using the random-effect model. RESULTS: A total of 52 eligible studies were included in the meta-analysis on QFT test reversion rate among participants with (20 studies) and without (32 studies) prophylactic treatment. Summarized reversion rate was found to be 24.9% (95% confidence interval [CI]: 18.4-32.9%) and 25.3% (95% CI: 19.6-32.0%) for those completed or without treatment, respectively. When the analysis was restricted to the participants completed treatment, higher summarized rate of QFT reversion was found among those with longer course therapy (9INH vs. the other regimens), studies from Asia (vs. Europe and America), and individuals with immunosuppression disorders (vs. general populations). CONCLUSIONS: Our results suggested that QFT reversion was frequently observed regardless of with or without prophylactic treatment. Serial QFT testing might be inappropriate for evaluating preventive treatment efficacy.