Insight into environmental adaptability of antibiotic resistome from surface water to deep sediments in anthropogenic lakes by metagenomics.

The escalating antibiotic resistance threatens the long-term global health. Lake sediment is a vital hotpot in transmitting antibiotic resistance genes (ARGs); however, their vertical distribution pattern and driving mechanisms in sediment cores remain unclear. This study first utilized metagenomics to reveal how resistome is distributed from surface water to 45 cm sediments in four representative lakes, central China. Significant vertical variations in ARG profiles were observed (R2 = 0.421, p < 0.001), with significant reductions in numbers, abundance, and Shannon index from the surface water to deep sediment (all p-values < 0.05). ARGs also has interconnections within the vertical profile of the lakes: twelve ARGs persistently exist all sites and depths, and shared ARGs (e.g., vanS and mexF) were assembled by diverse hosts at varying depths. The 0-18 cm sediment had the highest mobility and health risk of ARGs, followed by the 18-45 cm sediment and water. The drivers of ARGs transformed along the profile of lakes: microbial communities and mobile genetic elements (MGEs) dominated in water, whereas environmental variables gradually become the primary through regulating microbial communities and MGEs with increasing sediment depth. Interestingly, the stochastic process governed ARG assembly, while the stochasticity diminished under the mediation of Chloroflexi, Candidatus Bathyarcaeota and oxidation-reduction potential with increasing depth. Overall, we formulated a conceptual framework to elucidate the vertical environmental adaptability of resistome in anthropogenic lakes. This study shed on the resistance risks and their environmental adaptability from sediment cores, which could reinforce the governance of public health issues.

Association of MBL2 gene polymorphisms and MBL levels with dilated cardiomyopathy in a Chinese Han population.

BACKGROUND: It has been reported that Mannose-binding lectin 2 (MBL2) gene polymorphisms and expression levels are related to dilated cardiomyopathy (DCM). This study aimed to investigate the potential association between MBL2 gene polymorphisms and the pathogenesis of DCM. METHODS: Five single nucleotide polymorphisms (SNPs) of the MBL2 gene were genotyped in 440 DCM patients and 532 controls in Southwest China. A luciferase reporter assay was used to detect the transcriptional activity the different genotypes. MBL serum levels, left ventricle ejection fraction (LVEF) and lower left ventricular end-diastolic diameter (LVEDD) were measured. RESULTS: The rs11003125 C allele increased the transcriptional activity of the MBL2 promoter compared with the rs11003125 G allele. The rs11003125 CC carriers had higher MBL serum levels, LVEF and LVEDD than the rs11003125 CG and GG carriers. CONCLUSIONS: Our study first revealed that MBL2 polymorphisms and serum MBL levels were associated with DCM. Allele C in rs11003125 of MBL2 may upregulate the expression levels of MBL. High serum MBL levels may be a protective factor in DCM pathogenesis.

Ginseng-derived nanoparticles reprogram macrophages to regulate arginase-1 release for ameliorating T cell exhaustion in tumor microenvironment.

BACKGROUND: Lines of evidence indicated that, immune checkpoints (ICs) inhibitors enhanced T cell immune response to exert anti-tumor effects. However, T cell exhaustion has been so far a major obstacle to antitumor immunotherapy in colorectal cancer patients. Our previous studies showed that ginseng-derived nanoparticles (GDNPs) inhibited the growth of various tumors by reprograming tumor-associated macrophages (TAMs) and downregulated the ICs expression on T cells in tumor microenvironment (TME), but the underlying effector mechanisms remained unclear. METHODS: The correlation between arginase-1 (ARG1) and T cells was computed based on the colorectal cancer patients in TCGA database. In vitro, we observed that GDNPs reprogrammed TAMs inhibited ARG1 release and ultimately ameliorated T cell exhaustion according to several techniques including WB, PCR, ELISA and flow cytometry. We also used an in vivo MC38 tumor-bearing model and administered GDNPs to assess their anti-tumor effects through multiple indices. The mechanism that GDNPs improved T cell exhaustion was further clarified using the bioinformatics tools and flow cytometry. RESULTS: GDNPs reprogramed TAMs via reducing ARG1 production. Moreover, normalized arginine metabolism ameliorated T cell exhaustion through mTOR-T-bet axis, resulting in reduced ICs expression and enhanced CD8+ T cells expansion. CONCLUSIONS: By regulating the mTOR-T-bet axis, GDNPs reprogramed macrophages to regulate ARG1 release, which further ameliorated T cell exhaustion in TME. These findings provided new insights into comprehending the mechanisms underlying the mitigation of T cell exhaustion, which may facilitate the development of innovative therapeutic strategies in the field of cancer treatment.

NCRD: A non-redundant comprehensive database for detecting antibiotic resistance genes.

Antibiotic resistance genes (ARGs) are emerging pollutants present in various environments. Identifying ARGs has become a growing concern in recent years. Several databases, including the Antibiotic Resistance Genes Database (ARDB), Comprehensive Antibiotic Resistance Database (CARD), and Structured Antibiotic Resistance Genes (SARG), have been applied to detect ARGs. However, these databases have limitations, which hinder the comprehensive profiling of ARGs in environmental samples. To address these issues, we constructed a non-redundant antibiotic resistance genes database (NRD) by consolidating sequences from ARDB, CARD, and SARG. We identified the homologous proteins of NRD from Non-redundant Protein Database (NR) and the Protein DataBank Database (PDB) and clustered them to establish a non-redundant comprehensive antibiotic resistance genes database (NCRD) with similarities of 100% (NCRD100) and 95% (NCRD95). To demonstrate the advantages of NCRD, we compared it with other databases by using metagenome datasets. Results revealed its strong ability in detecting potential ARGs.

Lanthanum and magnesium activated palygorskite for adsorption of phosphate in piggery wastewater.

Removing phosphate from wastewater can help alleviate eutrophication. Therefore, in this study, lanthanum and magnesium were loaded onto the thermally modified palygorskite (PAL) using a coprecipitation method, and a composite material was prepared for phosphate recovery. In the pH range of 2-7, the material can effectively adsorb the phosphate. In the kinetic experiment, the material was able to rapidly adsorb phosphate within 4 h of the beginning of the reaction. The adsorption isotherm result of the material was in accordance with Freundlich isotherm model. When pH was 7, the theoretical maximum adsorption capacity was 20.4 mg P/g. When phosphate coexisted with CO32- and HCO3-, the adsorption was significantly inhibited. In the adsorption-desorption experiment, the material can be reused at least five times after elution with 1 mol/L of sodium hydroxide solution. The equilibrium adsorption capacity of the material for total phosphorus in piggery wastewater was 7.25 mg P/g, achieving a total phosphorus removal rate of 95.3%. The characterization of XRD, FT-IR and XPS suggested that phosphate was mainly exchanged with La-OH in the material, forming an amorphous LaPO4 complex.

Inhomogeneous antibiotic distribution in sediment profiles in anthropogenically impacted lakes: Source apportionment, fate drivers, and risk assessment.

Antibiotic residues in lake ecosystems have been widely reported; however, the vertical distribution of antibiotics in lake sediment profiles have rarely been examined. This study systematically revealed the vertical distribution pattern, sources, and risks of antibiotics in sediments of four typical agricultural lakes in central China. Nine of 33 target antibiotics were detected with a total concentration range of 39.3-18,250.6 ng/g (dry weight), and the order of average concentration was erythromycin (1447.4 ng/g) > sulfamethoxazole (443.7 ng/g) > oxytetracycline (62.6 ng/g) > enrofloxacin (40.7 ng/g) > others (0.1-2.1 ng/g). The middle-layer sediments (9-27 cm) had significantly higher antibiotic detected number and concentration than those in the top layer (0-9 cm) and bottom layer (27-45 cm) (p < 0.05). Correlation analysis showed that significant relationships existed between antibiotic concentrations and the octanol-water partition coefficients (Kow) of antibiotics (p < 0.05). Redundancy analysis indicated that Pb, Co, Ni, water content, and organic matter (p < 0.05) jointly affected the distribution of antibiotics in sediment profiles. Risk assessment showed that the highest potential ecological and resistance selection risks of antibiotics occurred in the middle-layer sediments, and oxytetracycline, tetracycline, and enrofloxacin had the most extensive potential risks in the sediment profiles. Additionally, the positive matrix factorization model revealed that human medical wastewater (54.5%) contributed more antibiotic pollution than animal excreta (45.5%) in sediment. This work highlights the inhomogeneous distribution of antibiotics in sediment profiles and provides valuable information for the prevention and control of antibiotic contamination in lakes.

Edible and cation-free kiwi fruit derived vesicles mediated EGFR-targeted siRNA delivery to inhibit multidrug resistant lung cancer.

Clinically, activated EGFR mutation associated chemo-drugs resistance has severely threaten NSCLC patients. Nanoparticle based small interfering RNA (siRNA) therapy representing another promising alternative by silencing specific gene while still suffered from charge associated toxicity, strong immunogenicity and poor targetability. Herein, we reported a novel EGFR-mutant NSCLC therapy relying on edible and cation-free kiwi-derived extracellular vesicles (KEVs), which showed sevenfold enhancement of safe dosage compared with widely used cationic liposomes and could be further loaded with Signal Transducer and Activator of Transcription 3 interfering RNA (siSTAT3). siSTAT3 loaded KEVs (STAT3/KEVs) could be easily endowed with EGFR targeting ability (STAT3/EKEVs) and fluorescence by surface modification with tailor-making aptamer through hydrophobic interaction. STAT3/EKEVs with a controlled size of 186 nm displayed excellent stability, high specificity and good cytotoxicity towards EGFR over-expressing and mutant PC9-GR4-AZD1 cells. Intriguingly, the systemic administration of STAT3/EKEVs significantly suppressed subcutaneous PC9-GR4-AZD1 tumor xenografts in nude mice by STAT3 mediated apoptosis. This safe and robust KEVs has emerged as the next generation of gene delivery platform for NSCLC therapy after multiple drug-resistance.

Lignin recovery from cocoa bean shell using microwave-assisted extraction and deep eutectic solvents.

Lignin is the second most abundant natural polymer after cellulose, and valorisation of lignin-rich streams has attracted increasing attention recently. This paper presents a novel and sustainable method to recover lignin from Cocoa Bean Shells (CBS) using Deep Eutectic Solvents (DES) and microwaves. A DES containing p-toluenesulfonic acid, choline chloride and glycerol (2:1:1 M ratio) was selected based on its dielectric properties. Under 200 W microwave power, the optimum yield of 95.5 % lignin was achieved at 130 °C and 30 min. DES-extracted lignin exhibited unique structural characteristics including larger particle sizes (242.5 µm D50 size), structural diversity (410.4 µm D90-D10 size) and H/G sub-unit ratio (71.9 %) compared with commercial Kraft lignin (77.2 µm, 157.9 µm and 0.1 % respectively), indicating the potential of DES in the modification and upgrading of lignin for novel value-added products.

[Research progress of Angelicae Sinensis Radix and predictive analysis on its quality markers].

Angelicae Sinensis Radix, as a medicinal and edible Chinese medicinal herb, is widely used in clinical practice. It is mainly cultivated in Minxian, Tanchang, Zhangxian and Weiyuan counties of Gansu province. In recent years, with the comprehensive and in-depth study of Angelicae Sinensis Radix in China and abroad, its chemical composition, pharmacological effects and application and development have attracted much attention. In this study, the chemical composition, traditional efficacy, and modern pharmacological effects of Angelicae Sinensis Radix were summarized. On this basis, combined with the core concept of quality markers(Q-markers), the Q-markers of Angelicae Sinensis Radix were discussed from the aspects of mass transfer and traceability and chemical composition specificity, availability, and measurability, which provided scientific basis for the quality evaluation of Angelicae Sinensis Radix.

How has airport service quality changed in the context of COVID-19: A data-driven crowdsourcing approach based on sentiment analysis.

Airport service quality (ASQ) is a competitive advantage for airport management in today's airport market. Since the COVID-19 health crisis has unprecedentedly influenced airport regulations and operations, effective measurement of ASQ has become crucial for airport administrations. Surveying travelers' attitudes is useful for ASQ assessment but collecting responses could be time-consuming and costly. Therefore, this paper adopts a data-driven crowdsourcing approach to study ASQ during the COVID-19 pandemic by investigating Google Maps reviews from the 98 busiest U.S. airports. To do so, this study develops a topical ontology of keywords regarding ASQ attributes and uses a sentiment tool to derive passengers' attitudes. Through sentiment analysis, Google Maps reviews show more positive sentiment toward environment and personnel but remain constant about facilities during COVID-19. The lexical salience-valence analysis (LSVA) is then applied to explain such changes by tracking the sentiment of frequent words in reviews. Through correlation and regression analysis, this study demonstrates that rating is significantly related to check-in, environment, and personnel in pre-and post-COVID periods. Additionally, the effect of access, wayfinding, facilities, and environment on rating significantly differs between the two periods. The findings illustrate the effectiveness of leveraging online reviews and offer practical implications for what matters to air travelers, especially in the COVID-19 context.

The Potential of Gut Microbiota Metabolic Capability to Detect Drug Response in Rheumatoid Arthritis Patients.

Gut microbiota plays an essential role in the development of rheumatoid arthritis (RA) and affects drug responses. However, the underlying mechanism remains elusive and urgent to elucidate to explore the pathology and clinical treatment of RA. Therefore, we selected methotrexate (MTX) as an example of RA drugs to explore the interactions between the gut microbiota and drug responses and obtain an in-depth understanding of their correlation from the perspective of the metabolic capability of gut microbiota on drug metabolism. We identified 2,654 proteins and the corresponding genes involved in MTX metabolism and then profiled their abundances in the gut microbiome datasets of four cohorts. We found that the gut microbiota harbored various genes involved in MTX metabolism in healthy individuals and RA patients. Interestingly, the number of genes involved in MTX metabolism was not significantly different between response (R) and non-response (NR) groups to MTX, but the gene composition in the microbial communities significantly differed between these two groups. Particularly, several models were built based on clinical information, as well as data on the gene, taxonomical, and functional biomarkers by using the random forest algorithm and then validated. Our findings provide bases for clinical management not only of RA but also other gut microbiome-related diseases. First, it suggests that the potential metabolic capability of gut microbiota on drug metabolism is important because they affect drug efficiency; as such, clinical treatment strategies should incorporate the gene compositions of gut microbial communities, in particular genes involved in drug metabolism. Second, a suitable model can be developed to determine hosts' responses to drugs before clinical treatment.

Ginseng-derived nanoparticles potentiate immune checkpoint antibody efficacy by reprogramming the cold tumor microenvironment.

Cold tumor microenvironment (TME) marked with low effector T cell infiltration leads to weak response to immune checkpoint inhibitor (ICI) treatment. Thus, switching cold to hot TME is critical to improve potent ICI therapy. Previously, we reported extracellular vesicle (EV)-like ginseng-derived nanoparticles (GDNPs) that were isolated from Panax ginseng C.A. Mey and can alter M2 polarization to delay the hot tumor B16F10 progression. However, the cold tumor is more common and challenging in the real world. Here, we explored a combinatorial strategy with both GDNPs and PD-1 (programmed cell death protein-1) monoclonal antibody (mAb), which exhibited the ability to alter cold TME and subsequently induce a durable systemic anti-tumor immunity in multiple murine tumor models. GDNPs enhanced PD-1 mAb anti-tumor efficacy in activating tumor-infiltrated T lymphocytes. Our results demonstrated that GDNPs could reprogram tumor-associated macrophages (TAMs) to increase CCL5 and CXCL9 secretion for recruiting CD8+ T cells into the tumor bed, which have the synergism to PD-1 mAb therapy with no detected systemic toxicity. In situ activation of TAMs by GDNPs may broadly serve as a facile platform to modulate the suppressive cold TME and optimize the PD-1 mAb immunotherapy in future clinical application.

Antibiotic resistome in a large urban-lake drinking water source in middle China: Dissemination mechanisms and risk assessment.

The increasing pollution of urban drinking water sources by antibiotic resistance genes (ARGs) threatens human health worldwide. However, the distribution and influencing factors of ARGs, especially how to reveal the risks of ARGs in this environment remains unclear. Hence, Chaohu Lake was selected as an example to investigate the characteristics of ARGs and explore the interactions among physicochemical factors, microorganisms, and ARGs by metagenomic approach. In this work, 75 ARG subtypes with an average of 30.4 × /Gb (ranging from 15.2 ×/Gb to 57.9 ×/Gb) were identified, and multidrug and bacA were most frequent in Chaohu Lake. Non-random co-occurrence patterns and potential host bacteria of ARGs were revealed through co-occurrence networks. Microbial community and mobile genetic elements (MGEs) were the major direct factors in ARG profiles. The dissemination of ARGs was mainly driven by plasmids. Considering the interactions among MGEs, human bacterial pathogens, and ARGs, antibiotic resistome risk index (ARRI) was proposed to manifest the risks of ARGs. Overall, our work systemically investigated the composition and associated factors of ARGs and built ARRI to estimate the potential risks of ARGs in a typical urban drinking water source, providing an intuitive indicator for managing similar lakes.

Comprehensive analysis of 84 Faecalibacterium prausnitzii strains uncovers their genetic diversity, functional characteristics, and potential risks.

Faecalibacterium prausnitzii is a beneficial human gut microbe and a candidate for next-generation probiotics. With probiotics now being used in clinical treatments, concerns about their safety and side effects need to be considered. Therefore, it is essential to obtain a comprehensive understanding of the genetic diversity, functional characteristics, and potential risks of different F. prausnitzii strains. In this study, we collected the genetic information of 84 F . prausnitzii strains to conduct a pan-genome analysis with multiple perspectives. Based on single-copy genes and the sequences of 16S rRNA and the compositions of the pan-genome, different phylogenetic analyses of F. prausnitzii strains were performed, which showed the genetic diversity among them. Among the proteins of the pan-genome, we found that the accessory clusters made a greater contribution to the primary genetic functions of F. prausnitzii strains than the core and specific clusters. The functional annotations of F. prausnitzii showed that only a very small number of proteins were related to human diseases and there were no secondary metabolic gene clusters encoding harmful products. At the same time, complete fatty acid metabolism was detected in F. prausnitzii. In addition, we detected harmful elements, including antibiotic resistance genes, virulence factors, and pathogenic genes, and proposed the probiotic potential risk index (PPRI) and probiotic potential risk score (PPRS) to classify these 84 strains into low-, medium-, and high-risk groups. Finally, 15 strains were identified as low-risk strains and prioritized for clinical application. Undoubtedly, our results provide a comprehensive understanding and insight into F. prausnitzii, and PPRI and PPRS can be applied to evaluate the potential risks of probiotics in general and to guide the application of probiotics in clinical application.

Diagnostic Classification of Patients with Dilated Cardiomyopathy Using Ventricular Strain Analysis Algorithm.

Dilated cardiomyopathy (DCM) is a cardiomyopathy with left ventricle or double ventricle enlargement and systolic dysfunction. It is an important cause of sudden cardiac death and heart failure and is the leading indication for cardiac transplantation. Major heart diseases like heart muscle damage and valvular problems are diagnosed using cardiac MRI. However, it takes time for cardiologists to measure DCM-related parameters to decide whether patients have this disease. We have presented a method for automatic ventricular segmentation, parameter extraction, and diagnosing DCM. In this paper, left ventricle and right ventricle are segmented by parasternal short-axis cardiac MR image sequence; then, related parameters are extracted in the end-diastole and end-systole of the heart. Machine learning classifiers use extracted parameters as input to predict normal people and patients with DCM, among which Random forest classifier gives the highest accuracy. The results show that the proposed system can be effectively utilized to detect and diagnose DCM automatically. The experimental results suggest the capabilities and advantages of the proposed method to diagnose DCM. A small amount of sample input can generate results comparable to more complex methods.

Mapping Drug-Induced Neuropathy through In-Situ Motor Protein Tracking and Machine Learning.

Chemotherapy can induce toxicity in the central and peripheral nervous systems and result in chronic adverse reactions that impede continuous treatment and reduce patient quality of life. There is a current lack of research to predict, identify, and offset drug-induced neurotoxicity. Rapid and accurate assessment of potential neuropathy is crucial for cost-effective diagnosis and treatment. Here we report dynamic near-infrared upconversion imaging that allows intraneuronal transport to be traced in real time with millisecond resolution, but without photobleaching or blinking. Drug-induced neurotoxicity can be screened prior to phenotyping, on the basis of subtle abnormalities of kinetic characteristics in intraneuronal transport. Moreover, we demonstrate that combining the upconverting nanoplatform with machine learning offers a powerful tool for mapping chemotherapy-induced peripheral neuropathy and assessing drug-induced neurotoxicity.

The Optimal Tetralogy of Fallot Repair Using Generative Adversarial Networks.

BACKGROUND: Tetralogy of Fallot (TOF) is a type of congenital cardiac disease with pulmonary artery (PA) stenosis being the most common defect. Repair surgery needs an appropriate patch to enlarge the narrowed artery from the right ventricular (RV) to the PA. METHODS: In this work, we proposed a generative adversarial networks (GANs) based method to optimize the patch size, shape, and location. Firstly, we built the 3D PA of patients by segmentation from cardiac computed tomography angiography. After that, normal and stenotic areas of each PA were detected and labeled into two sub-images groups. Then a GAN was trained based on these sub-images. Finally, an optimal prediction model was utilized to repair the PA with patch augmentation in the new patient. RESULTS: The fivefold cross-validation (CV) was performed for optimal patch prediction based on GANs in the repair of TOF and the CV accuracy was 93.33%, followed by the clinical outcome. This showed that the GAN model has a significant advantage in finding the best balance point of patch optimization. CONCLUSION: This approach has the potential to reduce the intraoperative misjudgment rate, thereby providing a detailed surgical plan in patients with TOF.

Digital Divide in Online Education During the COVID-19 Pandemic: A Cosmetic Course From the View of the Regional Socioeconomic Distribution.

Objectives: During the pandemic, quarantine has led to the lockdown of many physical educational institutions. Thus, massive open online courses (MOOCs) have become a more common choice for participants. MOOCs are often flagged as supplemental methods to educational disparities caused by regional socioeconomic distribution. However, dissenters argue that MOOCs can exacerbate the digital divide. This study aimed to compare the participants' performance before and after the outbreak of COVID-19, analyze the impact of the epidemic on online education of cosmetic dermatology from the view of the regional socioeconomic distribution, and investigate whether MOOCs exacerbate the digital divide in the COVID-19 epidemic. Methods: The study was conducted in participants of the MOOC course Appreciation and Analysis of Cosmetics from January 2018 to December 2020. Based on the platform data and official socioeconomic statistics, correlation of multivariate analysis was used to determine the factors related to the number of total participants. A panel regression model and stepwise least squares regression analysis (STEPLS) were employed to further analyze the relationship between GDP, population, number of college students and number of total participants in different years in the eastern, central and western regions of China. Results: The number of total participants in 2020 surged 82.02% compared with that in 2019. Completion rates were generally stable in 2018 and 2019 before the COVID-19 pandemic and significantly decreased in 2020 after the outbreak of the pandemic. GDP was the most important socioeconomic factor that determined the total number of participants and it was positively related to the total number of participants before and after the outbreak of the pandemic. The number of college students was unrelated to the total number of participants before the epidemic, and after the outbreak of COVID-19 in 2020, the number became positively related in all regions of China. Conclusions: This study shows that the epidemic pushes more people to choose MOOCs to study cosmetic dermatology, and online education could exacerbate rather than reduce disparities that are related to regional and socioeconomic status in the cosmetic field in the COVID-19 pandemic.

Increased expression of T helper 17 cells and interleukin-17 in atopic dermatitis: a systematic review and meta-analysis.

BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disease with genetic susceptibility and recurrent attacks. Research examining the etiology of this disease has mainly focused on environmental factors and immunity, with immune disorders believed to be the main factor in the occurrence and development of AD. While some studies have demonstrated that increased proportion of T helper 17 (Th17) cells in the lesions of specific dermatitis mouse models, the expression of Th17 cells and interleukin (IL)-17 in patients with AD remains controversial. METHODS: Related literatures were retrieved from English databases including PubMed, Embase, and Ovid-Medline. Literatures published from the establishment of the database to April 2021 were identified using the following keywords: AD, T helper cell 17 (Th17 cell), and interleukin 17 (IL-17). Review Manager5.3 software was adopted for meta-analysis. RESULTS: A total of 8 studies, involving 1,147 subjects, related to the pathogenesis of AD were included in this meta-analysis. The analysis revealed that the expression of Th17 cells in patients with AD was higher than that in healthy patients (P<0.00001), and the serum expression of IL-17 was also elevated in patients with AD compared to healthy participants (P=0.0001). DISCUSSION: A total of 8 publications related to the pathogenesis of AD were analyzed. The meta-analysis found that patients with AD had higher expressions of Th17 cells and IL-17 compared to healthy subjects, suggesting that AD may be related to Th17 cells and IL-17.

Diphenylcyclopropenone plays an effective therapeutic role by up-regulating the TSLP/OX40L/IL-13 pathway in severe alopecia areata.

Topical immunotherapy with diphenylcyclopropenone (DPCP) is considered to be the most effective treatment of severe AA. However, the mechanism is unclear and an early predictor for the efficacy needs to be explored. The TSLP/OX40L/IL-13 pathway is an important pathway to initiate and maintain Th2 immune responses. Our previous work suggests this pathway may play a role in severe AA treated with DPCP. Thus, to further investigate the mechanism of TSLP/OX40L/IL-13 pathway in severe AA treated with DPCP and explore the predictor for the efficacy of DPCP therapy, we conducted a prospective study to compare expression levels of TSLP, OX40L, Th2 cytokines IL-4, IL-5 and IL13, and Th1 cytokine IFN-γ in severe AA patients before and after the treatment. Results showed that 21 AA patients were responsive (responders) to the DPCP therapy and 12 were not responsive (non-responders). Responders had lower levels of TSLP, OX40L and IL-13 than non-responders before the treatment. After the DPCP treatment, TSLP, IL-5 and IL-13 increased and IFN-γ decreased in responders while there were no changes of TSLP, IL-4, IL-13 and IFN-γ in non-responders. Our data suggest that the TSLP/OX40L/IL-13 pathway is down-regulated in some severe AA patients and DPCP might play a therapeutic role by up-regulating the pathway in these severe AA patients. The TSLP/OX40L/IL-13 pathway could be a predictor of response to the DPCP therapy for severe AA patients.