A superconducting nanowire single-photon camera with 400,000 pixels.

For the past 50 years, superconducting detectors have offered exceptional sensitivity and speed for detecting faint electromagnetic signals in a wide range of applications. These detectors operate at very low temperatures and generate a minimum of excess noise, making them ideal for testing the non-local nature of reality1,2, investigating dark matter3,4, mapping the early universe5-7 and performing quantum computation8-10 and communication11-14. Despite their appealing properties, however, there are at present no large-scale superconducting cameras-even the largest demonstrations have never exceeded 20,000 pixels15. This is especially true for superconducting nanowire single-photon detectors (SNSPDs)16-18. These detectors have been demonstrated with system detection efficiencies of 98.0% (ref. 19), sub-3-ps timing jitter20, sensitivity from the ultraviolet21 to the mid-infrared22 and microhertz dark-count rates3, but have never achieved an array size larger than a kilopixel23,24. Here we report on the development of a 400,000-pixel SNSPD camera, a factor of 400 improvement over the state of the art. The array spanned an area of 4 × 2.5 mm with 5 × 5-µm resolution, reached unity quantum efficiency at wavelengths of 370 nm and 635 nm, counted at a rate of 1.1 × 105 counts per second (cps) and had a dark-count rate of 1.0 × 10-4 cps per detector (corresponding to 0.13 cps over the whole array). The imaging area contains no ancillary circuitry and the architecture is scalable well beyond the present demonstration, paving the way for large-format superconducting cameras with near-unity detection efficiencies across a wide range of the electromagnetic spectrum.

Quantum circuits with many photons on a programmable nanophotonic chip.

Growing interest in quantum computing for practical applications has led to a surge in the availability of programmable machines for executing quantum algorithms1,2. Present-day photonic quantum computers3-7 have been limited either to non-deterministic operation, low photon numbers and rates, or fixed random gate sequences. Here we introduce a full-stack hardware-software system for executing many-photon quantum circuit operations using integrated nanophotonics: a programmable chip, operating at room temperature and interfaced with a fully automated control system. The system enables remote users to execute quantum algorithms that require up to eight modes of strongly squeezed vacuum initialized as two-mode squeezed states in single temporal modes, a fully general and programmable four-mode interferometer, and photon number-resolving readout on all outputs. Detection of multi-photon events with photon numbers and rates exceeding any previous programmable quantum optical demonstration is made possible by strong squeezing and high sampling rates. We verify the non-classicality of the device output, and use the platform to carry out proof-of-principle demonstrations of three quantum algorithms: Gaussian boson sampling, molecular vibronic spectra and graph similarity8. These demonstrations validate the platform as a launchpad for scaling photonic technologies for quantum information processing.

Pasa: leveraging population pangenome graph to scaffold prokaryote genome assemblies.

Whole genome sequencing has increasingly become the essential method for studying the genetic mechanisms of antimicrobial resistance and for surveillance of drug-resistant bacterial pathogens. The majority of bacterial genomes sequenced to date have been sequenced with Illumina sequencing technology, owing to its high-throughput, excellent sequence accuracy, and low cost. However, because of the short-read nature of the technology, these assemblies are fragmented into large numbers of contigs, hindering the obtaining of full information of the genome. We develop Pasa, a graph-based algorithm that utilizes the pangenome graph and the assembly graph information to improve scaffolding quality. By leveraging the population information of the bacteria species, Pasa is able to utilize the linkage information of the gene families of the species to resolve the contig graph of the assembly. We show that our method outperforms the current state of the arts in terms of accuracy, and at the same time, is computationally efficient to be applied to a large number of existing draft assemblies.

AMRViz enables seamless genomics analysis and visualization of antimicrobial resistance.

We have developed AMRViz, a toolkit for analyzing, visualizing, and managing bacterial genomics samples. The toolkit is bundled with the current best practice analysis pipeline allowing researchers to perform comprehensive analysis of a collection of samples directly from raw sequencing data with a single command line. The analysis results in a report showing the genome structure, genome annotations, antibiotic resistance and virulence profile for each sample. The pan-genome of all samples of the collection is analyzed to identify core- and accessory-genes. Phylogenies of the whole genome as well as all gene clusters are also generated. The toolkit provides a web-based visualization dashboard allowing researchers to interactively examine various aspects of the analysis results. Availability: AMRViz is implemented in Python and NodeJS, and is publicly available under open source MIT license at https://github.com/amromics/amrviz .

AMRomics: a scalable workflow to analyze large microbial genome collections.

Whole genome analysis for microbial genomics is critical to studying and monitoring antimicrobial resistance strains. The exponential growth of microbial sequencing data necessitates a fast and scalable computational pipeline to generate the desired outputs in a timely and cost-effective manner. Recent methods have been implemented to integrate individual genomes into large collections of specific bacterial populations and are widely employed for systematic genomic surveillance. However, they do not scale well when the population expands and turnaround time remains the main issue for this type of analysis. Here, we introduce AMRomics, an optimized microbial genomics pipeline that can work efficiently with big datasets. We use different bacterial data collections to compare AMRomics against competitive tools and show that our pipeline can generate similar results of interest but with better performance. The software is open source and is publicly available at https://github.com/amromics/amromics under an MIT license.

A study of genetic variants associated with skin traits in the Vietnamese population.

BACKGROUND: Most skin-related traits have been studied in Caucasian genetic backgrounds. A comprehensive study on skin-associated genetic effects on underrepresented populations such as Vietnam is needed to fill the gaps in the field. OBJECTIVES: We aimed to develop a computational pipeline to predict the effect of genetic factors on skin traits using public data (GWAS catalogs and whole-genome sequencing (WGS) data from the 1000 Genomes Project-1KGP) and in-house Vietnamese data (WGS and genotyping by SNP array). Also, we compared the genetic predispositions of 25 skin-related traits of Vietnamese population to others to acquire population-specific insights regarding skin health. METHODS: Vietnamese cohorts of whole-genome sequencing (WGS) of 1008 healthy individuals for the reference and 96 genotyping samples (which do not have any skin cutaneous issues) by Infinium Asian Screening Array-24 v1.0 BeadChip were employed to predict skin-associated genetic variants of 25 skin-related and micronutrient requirement traits in population analysis and correlation analysis. Simultaneously, we compared the landscape of cutaneous issues of Vietnamese people with other populations by assessing their genetic profiles. RESULTS: The skin-related genetic profile of Vietnamese cohorts was similar at most to East Asian cohorts (JPT: Fst = 0.036, CHB: Fst = 0.031, CHS: Fst = 0.027, CDX: Fst = 0.025) in the population study. In addition, we identified pairs of skin traits at high risk of frequent co-occurrence (such as skin aging and wrinkles (r = 0.45, p = 1.50e-5) or collagen degradation and moisturizing (r = 0.35, p = 1.1e-3)). CONCLUSION: This is the first investigation in Vietnam to explore genetic variants of facial skin. These findings could improve inadequate skin-related genetic diversity in the currently published database.

LmTag: functional-enrichment and imputation-aware tag SNP selection for population-specific genotyping arrays.

Despite the rapid development of sequencing technology, single-nucleotide polymorphism (SNP) arrays are still the most cost-effective genotyping solutions for large-scale genomic research and applications. Recent years have witnessed the rapid development of numerous genotyping platforms of different sizes and designs, but population-specific platforms are still lacking, especially for those in developing countries. SNP arrays designed for these countries should be cost-effective (small size), yet incorporate key information needed to associate genotypes with traits. A key design principle for most current platforms is to improve genome-wide imputation so that more SNPs not included in the array (imputed SNPs) can be predicted. However, current tag SNP selection methods mostly focus on imputation accuracy and coverage, but not the functional content of the array. It is those functional SNPs that are most likely associated with traits. Here, we propose LmTag, a novel method for tag SNP selection that not only improves imputation performance but also prioritizes highly functional SNP markers. We apply LmTag on a wide range of populations using both public and in-house whole-genome sequencing databases. Our results show that LmTag improved both functional marker prioritization and genome-wide imputation accuracy compared to existing methods. This novel approach could contribute to the next generation genotyping arrays that provide excellent imputation capability as well as facilitate array-based functional genetic studies. Such arrays are particularly suitable for under-represented populations in developing countries or non-model species, where little genomics data are available while investment in genome sequencing or high-density SNP arrays is limited. $\textrm{LmTag}$ is available at: https://github.com/datngu/LmTag.

Assessing polygenic risk score models for applications in populations with under-represented genomics data: an example of Vietnam.

Most polygenic risk score (PRS)models have been based on data from populations of European origins (accounting for the majority of the large genomics datasets, e.g. >78% in the UK Biobank and >85% in the GTEx project). Although several large-scale Asian biobanks were initiated (e.g. Japanese, Korean, Han Chinese biobanks), most other Asian countries have little or near-zero genomics data. To implement PRS models for under-represented populations, we explored transfer learning approaches, assuming that information from existing large datasets can compensate for the small sample size that can be feasibly obtained in developing countries, like Vietnam. Here, we benchmark 13 common PRS methods in meta-population strategy (combining individual genotype data from multiple populations) and multi-population strategy (combining summary statistics from multiple populations). Our results highlight the complementarity of different populations and the choice of methods should depend on the target population. Based on these results, we discussed a set of guidelines to help users select the best method for their datasets. We developed a robust and comprehensive software to allow for benchmarking comparisons between methods and proposed a computational framework for improving PRS performance in a dataset with a small sample size. This work is expected to inform the development of genomics applications in under-represented populations. PRSUP framework is available at: https://github.com/BiomedicalMachineLearning/VGP.

EVALUATION OF THE ANTI-CARIES EFFECT OF LESPEDEZA CUNEATA EXTRACT AGAINST STREPTOCOCCUS MUTANS.

The purpose of this study was to identify the antimicrobial activity of Lespedeza cuneata extract, a natural medicine, against a main causative bacterium of dental caries, Streptococcus mutans (S. mutans). Lespedeza cuneata purchased from Hwalim Natural Drug Co., Ltd. (Busan, South Korea) was immersed in 70% ethanol for 12 h, and concentrated Lespedeza cuneata extract was applied to S. mutans diluted to 6×105 CFU/mL at the concentrations of 0, 1.25, 2.5, 5, 10, 20, and 40 mg/ml. Then the colony-forming units (CFUs) were checked at 6 and 24 h to evaluate the antimicrobial activity of the extract. The CFUs and survival rate of S. mutans according to the concentration showed a higher mortality rate as the concentration of Lespedeza cuneata extract increased. In the time-dependent changes, the minimal inhibitory concentration (MIC), and minimum bactericidal concentration (MBC) were 1.25 and 40 mg/mL or more, respectively, at 6 h, but they were 1.25 and 5 mg/mL, respectively, at 24 h. Therefore, Lespedeza cuneata extract is considered an excellent natural antibiotic for the prevention and treatment of dental caries, a typical oral disease, because it has excellent dental caries development suppression and bacteria extermination effects.

Genomic Analysis of Vascular Invasion in HCC Reveals Molecular Drivers and Predictive Biomarkers.

BACKGROUND AND AIMS: Vascular invasion (VI) is a critical risk factor for HCC recurrence and poor survival. The molecular drivers of vascular invasion in HCC are open for investigation. Deciphering the molecular landscape of invasive HCC will help identify therapeutic targets and noninvasive biomarkers. APPROACH AND RESULTS: To this end, we undertook this study to evaluate the genomic, transcriptomic, and proteomic profile of tumors with VI using the multiplatform cancer genome atlas (The Cancer Genome Atlas; TCGA) data (n = 373). In the TCGA Liver Hepatocellular Carcinoma cohort, macrovascular invasion was present in 5% (n = 17) of tumors and microvascular invasion in 25% (n = 94) of tumors. Functional pathway analysis revealed that the MYC oncogene was a common upstream regulator of the mRNA, miRNA, and proteomic changes in VI. We performed comparative proteomic analyses of invasive human HCC and MYC-driven murine HCC and identified fibronectin to be a proteomic biomarker of invasive HCC (mouse fibronectin 1 [Fn1], P = 1.7 × 10-11 ; human FN1, P = 1.5 × 10-4 ) conserved across the two species. Mechanistically, we show that FN1 promotes the migratory and invasive phenotype of HCC cancer cells. We demonstrate tissue overexpression of fibronectin in human HCC using a large independent cohort of human HCC tissue microarray (n = 153; P < 0.001). Lastly, we showed that plasma fibronectin levels were significantly elevated in patients with HCC (n = 35; mean = 307.7 µg/mL; SEM = 35.9) when compared to cirrhosis (n = 10; mean = 41.8 µg/mL; SEM = 13.3; P < 0.0001). CONCLUSIONS: Our study evaluates the molecular landscape of tumors with VI, identifying distinct transcriptional, epigenetic, and proteomic changes driven by the MYC oncogene. We show that MYC up-regulates fibronectin expression, which promotes HCC invasiveness. In addition, we identify fibronectin to be a promising noninvasive proteomic biomarker of VI in HCC.

Investigation of target sequencing of SARS-CoV-2 and immunogenic GWAS profiling in host cells of COVID-19 in Vietnam.

BACKGROUND: A global pandemic has been declared for coronavirus disease 2019 (COVID-19), which has serious impacts on human health and healthcare systems in the affected areas, including Vietnam. None of the previous studies have a framework to provide summary statistics of the virus variants and assess the severity associated with virus proteins and host cells in COVID-19 patients in Vietnam. METHOD: In this paper, we comprehensively investigated SARS-CoV-2 variants and immune responses in COVID-19 patients. We provided summary statistics of target sequences of SARS-CoV-2 in Vietnam and other countries for data scientists to use in downstream analysis for therapeutic targets. For host cells, we proposed a predictive model of the severity of COVID-19 based on public datasets of hospitalization status in Vietnam, incorporating a polygenic risk score. This score uses immunogenic SNP biomarkers as indicators of COVID-19 severity. RESULT: We identified that the Delta variant of SARS-CoV-2 is most prevalent in southern areas of Vietnam and it is different from other areas in the world using various data sources. Our predictive models of COVID-19 severity had high accuracy (Random Forest AUC = 0.81, Elastic Net AUC = 0.7, and SVM AUC = 0.69) and showed that the use of polygenic risk scores increased the models' predictive capabilities. CONCLUSION: We provided a comprehensive analysis for COVID-19 severity in Vietnam. This investigation is not only helpful for COVID-19 treatment in therapeutic target studies, but also could influence further research on the disease progression and personalized clinical outcomes.

State Readout of a Trapped Ion Qubit Using a Trap-Integrated Superconducting Photon Detector.

We report high-fidelity state readout of a trapped ion qubit using a trap-integrated photon detector. We determine the hyperfine qubit state of a single ^{9}Be^{+} ion held in a surface-electrode rf ion trap by counting state-dependent ion fluorescence photons with a superconducting nanowire single-photon detector fabricated into the trap structure. The average readout fidelity is 0.9991(1), with a mean readout duration of 46 µs, and is limited by the polarization impurity of the readout laser beam and by off-resonant optical pumping. Because there are no intervening optical elements between the ion and the detector, we can use the ion fluorescence as a self-calibrated photon source to determine the detector quantum efficiency and its dependence on photon incidence angle and polarization.

Cryogenic spectrometer for measuring the far-IR to millimeter-wave absorptivity of cosmic analog dusts.

We report on the design, construction, and performance of a custom apparatus built to measure the frequency- and temperature-dependent absorptivity of millimeter-wave light by cosmic analog dusts. We highlight the unique challenges faced as well as a few key innovations that are part of the instrument. Among those is an ultra-compact Fourier transform spectrometer. We have measured its effective frequency range and FWHM resolution to be 150-2100 GHz and ∼45GHz, respectively. Another innovation is a cold sample positioner whose temperature can be controlled within the range of 3.7-50 K. The use of a pulse-tube cryocooler results in a pulse-synchronous signal that dominates the detector (bolometer) signal. Methods used to address that challenge are also presented.

Prenylflavonoids isolated from Macaranga tanarius stimulate odontoblast differentiation of human dental pulp stem cells and tooth root formation via the mitogen-activated protein kinase and protein kinase B pathways.

AIM: To identify odontogenesis-promoting compounds and examine the molecular mechanism underlying enhanced odontoblast differentiation and tooth formation. METHODOLOGY: Five different nymphaeols, nymphaeol B (NB), isonymphaeol B (INB), nymphaeol A (NA), 3'-geranyl-naringenin (GN) and nymphaeol C (NC) were isolated from the fruit of Macaranga tanarius. The cytotoxic effect of nymphaeols on human DPSCs was observed using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The effect of nymphaeols on odontoblast differentiation was analysed with Alizarin Red S staining and odontoblast marker expression was assessed using real-time polymerase chain reaction and Western blot analysis. The molecular mechanism was investigated with Western blot analysis. In order to examine the effect of INB on dentine formation in the developing tooth germ, INB-soaked beads were placed under the tooth bud explants in the collagen gel; thereafter, the tooth bud explant-bead complexes were implanted into the sub-renal capsules for 3 weeks. Tooth root formation was analysed using micro-computed tomography and histological analysis. Data are presented as mean ± standard error (SEM) values of three independent experiments, and results are compared using a two-tailed Student's t-test. The data were considered to have statistical significance when the P-value was less than 0.05. RESULTS: Three of the compounds, NB, INB, and GN, did not exert a cytotoxic effect on human DPSCs. However, INB was most effective in promoting the deposition of calcium minerals in vitro (P < 0.001) and induced the expression of odontogenic marker genes (P < 0.05). Moreover, this compound strongly induced the phosphorylation of mitogen-activated protein (MAP) kinases and protein kinase B (AKT) (P < 0.05). The inhibition of p38 MAP, c-Jun N-terminal kinase (JNK), and AKT substantially suppressed the INB-induced odontoblast differentiation (P < 0.001). In addition, isonymphaeol B significantly induced the formation of dentine and elongation of the tooth root in vivo (P < 0.05). CONCLUSIONS: Prenylflavonoids, including INB, exerted stimulatory effects on odontoblast differentiation and tooth root and dentine formation via the MAP kinase and AKT signalling pathways. These results suggest that nymphaeols could stimulate the repair processes for dentine defects or injuries.

Influence of complications following total mastectomy and immediate reconstruction on breast cancer recurrence.

BACKGROUND: Immediate breast reconstruction is safe from an oncological perspective, but the relatively high rate of postoperative complications raises oncological concerns. The present study aimed to evaluate the potential influence of postoperative complications after immediate breast reconstruction on breast cancer recurrence and survival. METHODS: Patients with breast cancer who had total mastectomy and immediate reconstruction between 2008 and 2013 were followed for at least 5 years. The impact of postoperative complications on oncological outcomes was assessed using multivariable Cox regression analyses. RESULTS: In total, 438 patients with a median follow-up of 82 months were analysed. Five-year local recurrence-free, disease-free and overall survival rates were 95·4, 93·1 and 98·4 per cent respectively. Postoperative complications developed in the operated breast in 120 patients (27·4 per cent) and at other sites (flap donor) in 30 patients (6·8 per cent). Development of breast complications was associated with significantly increased rate of recurrence compared with no complications (16·7 versus 5·9 per cent; P = 0·002). In multivariable analysis, patients with breast complications had significantly worse disease-free survival than those with no complications (hazard ratio (HR) 2·25; P = 0·015). This remained significant in patients who received adjuvant therapy without delay (8 weeks or less after surgery) (HR 2·45; P = 0·034). CONCLUSION: Development of postoperative complications in the breast can have a negative impact on survival and recurrence after immediate reconstruction.

ANTECEDENTES: La reconstrucción mamaria inmediata es una técnica segura desde el punto de vista oncológico, pero con una tasa relativamente alta de complicaciones postoperatorias, lo que preocupa por si puede afectar a los resultados. Este estudio tuvo como objetivo evaluar la influencia potencial de las complicaciones postoperatorias tras la reconstrucción mamaria inmediata en la recidiva y la supervivencia del cáncer de mama. MÉTODOS: Se hizo un seguimiento de al menos 5 años de las pacientes a las que se realizó una mastectomía total por cáncer de mama y una reconstrucción mamaria inmediata entre 2008 y 2013. Se evaluó el impacto de las complicaciones postoperatorias en los resultados oncológicos mediante un análisis multivariables de regresión de Cox. RESULTADOS: Se analizaron 438 pacientes con una mediana de seguimiento de 82 meses. La supervivencia libre de recidiva local a 5 años, la supervivencia libre de enfermedad y la supervivencia global fueron del 95,4%, 93,1% y 98,4%, respectivamente. Hubo complicaciones postoperatorias en la mama en 120 (31,8%) pacientes y en otros lugares (zona donante de colgajo) en 30 (6,8%). La presentación de complicaciones mamarias se asoció con una tasa de recidiva significativamente mayor en comparación con el grupo de pacientes sin complicaciones (16,7% versus 5,9%, P < 0,01). En el análisis multivariable, las pacientes con complicaciones mamarias mostraron una supervivencia libre de enfermedad significativamente menor que aquellas que no padecieron complicaciones (cociente de riesgos instantáneos, hazard ratio, HR 2,25; P = 0,02). También fue significativo el porcentaje de pacientes que recibieron tratamiento adyuvantes sin demora (≤ 8 semanas después de la operación) (HR 2,45; P = 0,03). CONCLUSIÓN: El desarrollo de complicaciones postoperatorias en la mama puede impactar negativamente en la supervivencia y en la recidiva después de la reconstrucción inmediata.

Detector-Agnostic Phase-Space Distributions.

The representation of quantum states via phase-space functions constitutes an intuitive technique to characterize light. However, the reconstruction of such distributions is challenging as it demands specific types of detectors and detailed models thereof to account for their particular properties and imperfections. To overcome these obstacles, we derive and implement a measurement scheme that enables a reconstruction of phase-space distributions for arbitrary states whose functionality does not depend on the knowledge of the detectors, thus defining the notion of detector-agnostic phase-space distributions. Our theory presents a generalization of well-known phase-space quasiprobability distributions, such as the Wigner function. We implement our measurement protocol, using state-of-the-art transition-edge sensors without performing a detector characterization. Based on our approach, we reveal the characteristic features of heralded single- and two-photon states in phase space and certify their nonclassicality with high statistical significance.

Leveraging known genomic variants to improve detection of variants, especially close-by Indels.

Motivation: The detection of genomic variants has great significance in genomics, bioinformatics, biomedical research and its applications. However, despite a lot of effort, Indels and structural variants are still under-characterized compared to SNPs. Current approaches based on next-generation sequencing data usually require large numbers of reads (high coverage) to be able to detect such types of variants accurately. However Indels, especially those close to each other, are still hard to detect accurately. Results: We introduce a novel approach that leverages known variant information, e.g. provided by dbSNP, dbVar, ExAC or the 1000 Genomes Project, to improve sensitivity of detecting variants, especially close-by Indels. In our approach, the standard reference genome and the known variants are combined to build a meta-reference, which is expected to be probabilistically closer to the subject genomes than the standard reference. An alignment algorithm, which can take into account known variant information, is developed to accurately align reads to the meta-reference. This strategy resulted in accurate alignment and variant calling even with low coverage data. We showed that compared to popular methods such as GATK and SAMtools, our method significantly improves the sensitivity of detecting variants, especially Indels that are close to each other. In particular, our method was able to call these close-by Indels at a 15-20% higher sensitivity than other methods at low coverage, and still get 1-5% higher sensitivity at high coverage, at competitive precision. These results were validated using simulated data with variant profiles extracted from the 1000 Genomes Project data, and real data from the Illumina Platinum Genomes Project and ExAC database. Our finding suggests that by incorporating known variant information in an appropriate manner, sensitive variant calling is possible at a low cost. Availability and implementation: Implementation can be found in our public code repository https://github.com/namsyvo/IVC. Supplementary information: Supplementary data are available at Bioinformatics online.

Src-type tyrosine kinase p56lck is critical for thymic stromal lymphopoietin-induced allergic rhinitis.

BACKGROUND: Thymic stromal lymphopoietin (TSLP) is a regulator of mast cell-mediated allergic inflammatory reactions, but the manner in which TSLP contributes to allergic rhinitis (AR) remains unclear. OBJECTIVE: Here, we sought to determine that TSLP plays a crucial role in AR by interacting with Src-type tyrosine kinase p56lck and STAT6 and promoting mast cells degranulation. METHODS: The effects of TSLP on mast cell degranulation and AR were analysed in human mast cell line (HMC-1 cells), ovalbumin (OVA)-induced AR animal model, and human subjects. Small interfering RNA experiments were performed in HMC-1 cells and OVA-induced AR model. Immune responses were analysed by enzyme-linked immunosorbent assay, Western blotting, immunoprecipitation, and histological studies. RESULTS: Thymic stromal lymphopoietin levels and mast cell-derived p56lck activation were elevated in human subjects with AR, and in AR mice, exogenous TSLP accelerated TH2-allergic inflammatory reactions by up-regulating p56lck and STAT6. On the other hand, depletion of TSLP, p56lck, and STAT6 ameliorated clinical symptoms in AR mice. The selective inhibitor of p56lck, damnacanthal, inhibits AR reactions. CONCLUSION: Collectively, these observations suggest a role for TSLP/p56lck/STAT6 in AR and offer insight into potential therapeutic strategies.

Early development of de novo hepatocellular carcinoma after direct-acting agent therapy: Comparison with pegylated interferon-based therapy in chronic hepatitis C patients.

Patients with chronic hepatitis C who achieve a sustained viral response after pegylated interferon therapy have a reduced risk of hepatocellular carcinoma, but the risk after treatment with direct-acting antivirals is unclear. We compared the rates of early development of hepatocellular carcinoma after direct-acting antivirals and after pegylated interferon therapy. We retrospectively analysed 785 patients with chronic hepatitis C who had no history of hepatocellular carcinoma (211 treated with pegylated interferon, 574 with direct-acting antivirals) and were followed up for at least 24 weeks after antiviral treatment. De novo hepatocellular carcinoma developed in 6 of 574 patients receiving direct-acting antivirals and in 1 of 211 patients receiving pegylated interferon. The cumulative incidence of early hepatocellular carcinoma development did not differ between the treatment groups either for the whole cohort (1.05% vs 0.47%, P = .298) or for those patients with Child-Pugh Class A cirrhosis (3.73% vs 2.94%, P = .827). Multivariate analysis indicated that alpha-fetoprotein level >9.5 ng/mL at the time of end-of-treatment response was the only independent risk factor for early development of hepatocellular carcinoma in all patients (P < .0001, hazard ratio 176.174, 95% confidence interval 10.768-2882.473) and in patients treated with direct-acting agents (P < .0001, hazard ratio 128.402, 95% confidence interval 8.417-1958.680). In conclusion, the rate of early development of hepatocellular carcinoma did not differ between patients treated with pegylated interferon and those treated with direct-acting antivirals and was associated with the serum alpha-fetoprotein level at the time of end-of-treatment response.