A human-derived protein SBP (HBsAg-binding protein) can bind to hepatitis B virus surface antigen (HBsAg) and enhance the immune response to hepatitis B virus (HBV) vaccine

A high titer of antibody to HBsAg (Hepatitis B virus surface antigen) (anti-HBs) is a requisite for the prevention of HB (Hepatitis B), and adjuvants generally play a great role in eliciting special anti-HBs to HB vaccine. However, adjuvants still need to be improved because of their shortages such as unremarkable efficacy, undesirable side effect or poor security. In this study, we used HBsAg separated from HB patient sera to screen a human liver cDNA expression library, and found a novel HBsAg-binding protein (SBP), which is located at the human chromosome 14q32.33 and is similar to human IgG heavy chain in structure. Western blot demonstrated that SBP existed in both healthy human sera and HB patient sera. Furthermore, SBP could bind to HBsAg by its N-terminal domain. Notably, we confirmed that SBP could promote dendritic cells (DC) to phagocytize HBsAg more effectively and enhance the immunogenicity of HB vaccine, when SBP was mixed proportionally with HBsAg and the resulting mixture was infused into mice. These results suggest that SBP could be developed into a safe and promising adjuvant of HB vaccine.     

Ablation of the microglial protein DOCK2 reduces amyloid burden in a mouse model of Alzheimer's disease

Alzheimer's disease (AD) neuropathology is characterized by innate immune activation primarily through prostaglandin E2 (PGE₂) signaling. Dedicator of cytokinesis 2 (DOCK2) is a guanyl nucleotide exchange factor expressed exclusively in microglia in the brain and is regulated by PGE₂ receptor EP2. DOCK2 modulates microglia cytokine secretion, phagocytosis, and paracrine neurotoxicity. EP2 ablation in experimental AD results in reduced oxidative damage and amyloid beta (Aβ) burden. This discovery led us to hypothesize that genetic ablation of DOCK2 would replicate the anti-Aβ effects of loss of EP2 in experimental AD. To test this hypothesis, we crossed mice that lacked DOCK2 (DOCK2 −/−), were hemizygous for DOCK2 (DOCK2 +/−), or that expressed two DOCK2 genes (DOCK2 +/+) with APPswe-PS1Δe9 mice (a model of AD). While we found no DOCK2-dependent differences in cortex or in hippocampal microglia density or morphology in APPswe-PS1Δe9 mice, cerebral cortical and hippocampal Aβ plaque area and size were significantly reduced in 10-month-old APPswe-PS1Δe9/DOCK2 −/− mice compared with APPswe-PS1Δe9/DOCK2 +/+ controls. DOCK2 hemizygous APPswe-PS1Δe9 mice had intermediate Aβ plaque levels. Interestingly, soluble Aβ₄₂ was not significantly different among the three genotypes, suggesting the effects were mediated specifically in fibrillar Aβ. In combination with earlier cell culture results, our in vivo results presented here suggest DOCK2 contributes to Aβ plaque burden via regulation of microglial innate immune function and may represent a novel therapeutic target for AD.     

SEMG-based hand motion recognition using cumulative residual entropy and extreme learning machine

This paper proposes a scheme consisting of two novel components to recognize multiple hand motions from surface electromyography (SEMG). First, we use the cumulative residual entropy (CREn), a measure of uncertainty in a random variable, as the feature. Second, we employ the extreme learning machine (ELM), a fast and effective classifier using single-hidden layer feedforward neural network with additive neurons, to distinguish different motions. To evaluate performance of the proposed system, we compare CREn with fuzzy entropy, sample entropy, and approximate entropy, and a state-of-the-art time-domain feature; and ELM with linear discriminant analysis and support vector machine. They are tested on four channel SEMG signals acquired from ten normal subjects. Experimental results indicate that the classification accuracies of CREn are not only better than those of other entropies with all the classifiers, but also comparable to the time-domain feature for all the segment lengths of 200, 250 and 1,000 ms with all classifiers that are evaluated. Furthermore, the computational complexity of CREn is lower than those of other features, and ELM performs significantly faster than other classifiers without sacrificing any performance. It suggests that the proposed CREn-ELM scheme has the potential to be applied to real-time control of SEMG-based multifunctional prosthesis.     

Nanoparticles-based multi-adjuvant whole cell tumor vaccine for cancer immunotherapy

Whole cell tumor vaccine (WCTV), as a potential treatment modality, elicits limited immune responses because of the poor immunogenicity. To address this issue, researchers have attempted to transduce a cytokine adjuvant into tumor cells, but these single-adjuvant WCTVs curtail the high expectations. In present study, we constructed a multi-adjuvant WCTV based on the nanoparticles modified with cell penetrating peptide, which could facilitate the transportation of granulocyte macrophage colony-stimulating factor (GM-CSF) and interleukin 2 (IL-2) into tumor cells. After inactivation, as-designed multi-adjuvant WCTV exhibited programmed promotions on DC recruitment, antigen presentation, and T-cell activation. In vivo evaluations demonstrated the satisfactory effects on tumor growth suppression, metastasis inhibition, and recurrence prevention. Therefore, the nanoparticles-based multi-adjuvant WCTV may serve as a high-performance treatment for anti-tumor immunotherapy.     

Combination of IL-1 Receptor Antagonist, IL-20 and CD40 Ligand for the Prediction of Acute Cellular Renal Allograft Rejection

Purpose

The outcome of renal transplantation is difficult to predict, even with an allograft biopsy. The aim of this study was to develop a sensitive, specific and noninvasive method for prediction of acute cellular rejection (ACR).

Methods

Luminex analysis was used to determine the levels of 95 cytokines/chemokines and their soluble receptors in sera from recipients with: ACR (in the first month post-transplantation, before and during rejection, and after rejection reversal); stable allograft function; delayed graft function (DGF); pulmonary infection. Evaluation of significant differential protein expression in ACR patients compared with stable allograft controls revealed a three-analyte combination as a marker of renal transplantation outcome. The predictive value of this combination was further validated in DGF and infection groups and in a blind binary code study of 24 additional serum samples.

Results

Significant differential expression was detected in 26 proteins expressed in patients during the period preceding an ACR episode compared with stable controls. A blood test for discrimination of such patients was developed based on the simultaneous quantification of three analytes (IL-1 receptor antagonist, IL-20 and sCD40 ligand). This test exhibited 90.9 % sensitivity, 96 % specificity, a positive predictive value (PPV) of 95.2 % and a negative predictive value (NPV) of 92.3 %. Moreover, this combination allowed discrimination between patients with ACR and DGF and pulmonary infection.

Conclusions

With further development and validation, this blood test can be used to predict ACR and direct the treatment of transplant patients in the clinic.     

Young Adults with Autism Spectrum Disorder and the Criminal Justice System

Journal of Autism and Developmental Disorders - This study describes charges, outcomes, and recidivism in both the juvenile and adult criminal justice systems (CJS) for young adults aged 17 to...     

Establishment and Evaluation of a Simplified Evaluation System of Acute Respiratory Distress Syndrome

Purpose

In recent years, a variety of acute respiratory distress syndrome (ARDS) evaluation systems have been developed worldwide; however, they are not so convenient for the doctors clinically, we decided to establish and evaluate a simplified evaluation system of ARDS (SESARDS).

Materials and Methods

Data from 140 ARDS patients (derivation data set) were collected to screen for prognostic factors affecting outcomes in ARDS patients. By logistic regression analysis, scores were allocated to corresponding intervals of the variables, respectively, by means of analysis of the frequency distribution to establish a preliminary scoring system. Based on this primary scoring system, a definitive evaluation scheme was created through consultation with a panel of experts. The scores for the validation data set (92 cases) were assigned and calculated by their predictive mortality with the SESARDS and acute physiology and chronic health evaluation II (APACHE II). The performance of SESARDS was compared with that of APACHE II by means of statistical analysis.

Results

The factors of age, pH, Glasgow coma scale (GCS), oxygenation index (OI), and the lobes of lung were associated with prognosis of ARDS respectively. The sensitivity and specificity of SESARDS for the validation data set were 96.43% and 58.33%, respectively. On the AUC, no significant difference between APACHE II and SESARDS was detected. There were no significant differences between the prediction and the actuality obtained by SESARDS for the validation data set the SESARDS scores were positively correlated with the actual mortality.

Conclusion

SESARDS was shown to be simple, accurate and effective in predicting ARDS progression.