Ankylosing spondylitis (AS) is an immune-mediated inflammatory arthritis and enthesitis involving the spine and peripheral joints. In recent years, specific antagonist of tumor necrosis factor (anti-TNFα, etanercept) 50 mg weekly therapy has rapidly gained popularity for the treatment of AS. However, the dose of etanercept has not been determined in Asian, particularly Chinese populations. The purpose of the study was to evaluate the efficacy and safety of dose reduction of etanercept (50 mg/week in 4 weeks followed by 25 mg/week in 8 weeks) in the treatment of AS with synovitis of the hip, as against the conventional dose (50 mg/week in 12 weeks) in a Chinese population. Forty-three Chinese AS patients with synovitis of the hip were involved in this study. Seventeen of them were randomized to receive conventional dose of etanercept treatment and 26 were given a dose reduction regimen for 12 weeks. The primary efficacy endpoint was disease activity of response for AS at week 12, including Bath AS Disease Activity Index (BASDAI), the serum erythrocyte sediment rate (ESR), C-reactive protein (CRP), and assessment of synovitis of the hip by ultrasonography. At 12 weeks, all of the patients had responses to some extent and the efficacy variables improved significantly over time, but not between treatment groups. Nine patients experienced at least one adverse event (generally, infections and injection site reactions), most of them mild or moderate. In sum, the dose reduction of etanercept regimen in the 12-week AS treatment was confirmed as a safe and effective therapy as the conventional dose was given.
We explored the mechanism of Markovnikov-selective hydrosilylation of phenylacetylene catalyzed by N–N–N Pincer–cobalt complex with density functional theory (DFT) calculations. In contrast to the previously proposed Co(I) mechanism, computational results suggest a Co(0) pathway, which is further supported by experimental studies. At the same time, our study reveals unexpected complexity in terms of the origin of regioselectivity. First, different orientations between the phenyl group in the substrate and the ligand plane lead to two possible transition states responsible for the branched product. However, the favored one varies according to ligand substitution pattern. Second, both entropy and solvation effects (rather than the conventional approach that considers electronic energies) have to be considered to explain regioselectivity, where the dominant factor also varies from case to case. Despite this complexity, computations predict a general overall ligand structure–regioselectivity relationship. In addition to increasing steric hindrance, introduction of an electron-withdrawing group to the ligands will also increase regioselectivity, which unveils a new dimension of ligand design.
Purpose. To investigate whether icariin (ICA), a well-known medicine extracted from the stem and leaf of Epimedium brevicornum Maxim, had analgesic effect on lower back pain (LBP) in rats. Methods. In a puncture-induced LBP rat model, the severity of LBP was quantified using the paw/foot withdrawal threshold method after intragastric administration of ICA at a dosage of 50 mg/kg/d or 100 mg/kg/d. The pain-related peptides of substance P (SP) and calcitonin gene-related peptide (CGRP) were also measured in intervertebral disc (IVD) tissue using RT-PCR after ICA treatment. In addition, the expression of cytokine-induced neutrophil chemoattractant-1 (CINC-1) in IVD was quantified using RT-PCR and ELISA examination. Results. ICA treatment resulted in a significant amelioration of mechanical allodynia in a dose-response manner, and the analgesic effect could last for two weeks even during the washout period. More importantly, the mechanism of analgesic pharmacological effect in ICA was to suppress the upregulated CINC-1, the homolog of IL-8 in rats, which is a crucial proalgesic factor contributing to LBP, in IVDs. Conclusion. ICA is a novel herbal extract to relieve LBP, and it may be a promising alternative pain killer in the future.
Background: Osteosarcoma (OS) is the most common highly malignant primary solid bone-tumor. Despite its relatively low incidence rate among overall cancers, it remains one of the most harmful primary malignant tumors in childhood and adolescence. It is now evident that serum autoantibodies against tumor-associated antigens (TAAs) could be used as serological cancer biomarkers in types of cancers. Methods: Serological proteome analysis (SERPA) approach was applied to profile anti-TAA autoantibody responses in sera from patients with OS, and Normal Human, and explore differences of these responses. This approach can detect autoantibodies to TAAs that could serve as clinical biomarkers and immunotherapeutic agents. Sera from OS, Osteochondroma (OC) and Normal Human Sera (NHS) were probed by immunoblotting against cellular proteins extracted from U2-OS and Saos-2 cell lines, with OS sera showing stronger immunoreactivity. MALDI-TOF/TOF Mass Spectrometry (MS) analysis of immunoreactive protein spots revealed that several OS sera contained autoantibodies to a number of proteins, particularly to alpha-enolase (ENO1). Results: Analysis of 172 serum samples from patients with OS, OC and NHS by ELISA showed higher frequency of anti-ENO1 autoantibodies in OS sera compared to others. Interestingly, descant of ENO1 immunoreactivity was observed in most patients after treatments, which may imply a potential association between anti-ENO1 autoantibody titers and disease progression. Nine of twelve sera reacted strongly against purified ENO1, but 3 weakly against purified ENO1, which indicates 75.0% sera with positive optimal density values from ELISA were consistently positive in Western blotting. The expression of ENO1 in Osteosarcoma tissues was evaluated by immunohistochemistry in tumor microarray. Conclusion: Our intriguing findings firstly demonstrate that ENO1 is one of autoantigens that elicit autoimmune responses in OS and can be used as biomarkers in immunodiagnosis and progression of OS. Key words: Osteosarcoma (OS), Tumor-associated antigen (TAA), Serological proteome analysis (SERPA), ENO1, Immunodiagnosis. Citation Format: Jitian Li, Manyu Huang, Liping Dai, Zongchang Han, Xiaofei Qin, Wen Xie, Wei Qian, Wuyin Li, Jianying Zhang. Immunoseroproteomic profiling in autoantibodies to ENO1 as potential biomarkers in immunodiagnosis of osteosarcoma by serological proteome analysis (SERPA) approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2585.
Osteosarcoma (OS) is the most common malignant primary solid bone-tumor. Despite its relatively low incidence rate among overall cancers, it remains one of the most harmful primary malignant tumors in childhood and adolescence. Thus, a critical need in the diagnosis and management of OS is to determine an optimal combination of clinical biomarkers that could detect tumors early with high specificity/sensitivity and with limited invasiveness. The objective of this study is to identify and characterize the targeted tumor-associated antigens (TAAs) as biomarkers in OS by serological proteome analysis (SERPA) approach, and further to analyze the frequency and specificity of anti-TAA antibodies in OS patients. In this initial study, autoantibodies to 29 TAAs were detected by ELISA and Western blotting in 90 sera from patients with OS, Osteochondroma (OC), and age matched normal individuals. Only 8 protein antigens including DSF70, HMGB1, HCC1, RalA, c-myc, AnnexinA1, IMP1, PBP, can induce significantly higher antibody responses in OS patients compared to normal individuals, achieving the highest sensitivity and specificity, 66% and 95%, respectively. The cumulative positive rate of autoantibodies against these eight selected TAAs in OS reached 70.7% with an observed AUC of 0.972 (95% CI: 0.867-0.988), significantly higher than that in normal control sera. Positive results were also confirmed by Western blotting. These preliminary data extensively evidence that not all proteins identified in cancer can be used as TAA biomarkers in OS, and only some of these proteins can induce immune responses, which could be potential TAAs in OS immunodiagnosis or prognosis, and further studies of novel targeted proteins in OS are currently in progress by SERPA approach. In addition, it supports the hypothesis that a customized TAA array can be used for enhancing anti-TAA antibodies detection, and it may constitute a promising and powerful tool for immunodiagnosis of OS. Citation Format: Jitian Li, Manyu Huang, Manli Luo, Liping Dai, Wen Xie, Xiaofei Qin, Zongchang Han, Wuyin Li, Jianying Zhang. Detection of autoantibodies against tumor-associated antigens (TAAs) improving immunodiagnosis in human osteosarcoma by serological proteome analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4659. doi:10.1158/1538-7445.AM2017-4659
Osteosarcoma (OS) is the most common highly malignant primary solid bone-tumor. Despite its relatively low incidence rate among overall cancers, it remains one of the most harmful primary malignant tumors in childhood and adolescence. Although some tumor markers like mutant p53 can be potentially used as biomarker to detect OS, the sensitivity and specificity are not optimal, especially for early diagnosis. The establishment of a methodology to identify patient with early stage of OS remains to be investigated. There has been a growing interest in using serum autoantibodies against tumor-associated antigens (TAAs) as serological cancer biomarkers, which stems from the notion that anti-TAA antibodies are “sensors” or “reporters” of molecular events associated with tumorigenesis. The objective of this study is to identify and characterize the targeted TAAs as biomarkers in OS, and further to analyze the frequency and specificity of autoantibodies in OS patients. In this initial study, we have tested 35 sera from OS patients, 12 sera from Osteochondroma (OC) patients and 32 age-matched normal human sera (NHS), for the presence of autoantibodies to the TAAs from extracted protein antigens from U2-OS culture cells in 1-D Western blot and by indirect immunofluorescence (IIF). Autoantibodies were detected in 34 of 35 (97.1%) sera from patients with OS, which were significantly higher than that in NHS (12.5%, 4/32). In contrast, there is no significate association between OC and NHS group, which implies that the OS sera may encompass more specific autoantibodies than OC sera. Interestingly, 35% (7/20), 25% (5/20), 20% (4/20) and 35% (7/20) OS sera were identified by 1D Western blotting analysis containing antibodies against unknown cellular protein antigens around 35 kD, 45 kD, 55 kD and 60 kD respectively. Additionally, no reactivity with the 45 kD and 55 kD protein was detected in 32 NHS. In the further study, these cellular proteins targeted by serum antibodies in OS will be identified by using serological proteome analysis (SERPA) approach. This preliminary data supports that autoimmune responses to certain cellular proteins maybe a by-product in the transformation to OS, and further studies of novel targeted proteins in OS may provide insights into how these proteins might be involved in malignancy. Key Words: Osteosarcoma (OS), Tumor-associated antigens (TAAs), Serological proteome analysis (SERPA), Cancer early detection, Immunodiagnosis Citation Format: Jitian Li, Manyu Huang, Manli Luo, Pei Li, Wen Xie, Zongchang Han, Wuyin Li, Jianying Zhang. Identification and characterization of tumor-associated antigens (TAAs) and anti-TAAs autoantibodies as biomarkers in immunodiagnosis of human osteosarcoma by serological proteome analysis. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 454.
Autoencoders have been widely used for dimensional reduction and feature extraction. Various types of autoencoders have been proposed by introducing regularization terms. Most of these regularizations improve representation learning by constraining the weights in the encoder part, which maps input into hidden nodes and affects the generation of features. In this study, we show that a constraint to the decoder can also significantly improve its performance because the decoder determines how the latent variables contribute to the reconstruction of input. Inspired by the structural modal analysis method in mechanical engineering, a new modal autoencoder (MAE) is proposed by othogonalising the columns of the readout weight matrix. The new regularization helps to disentangle explanatory factors of variation and forces the MAE to extract fundamental modes in data. The learned representations are functionally independent in the reconstruction of input and perform better in consecutive classification tasks. The results were validated on the MNIST variations and USPS classification benchmark suite. Comparative experiments clearly show that the new algorithm has a surprising advantage. The new MAE introduces a very simple training principle for autoencoders and could be promising for the pre-training of deep neural networks.Preprint. Under review.
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