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Background and Objective Cardiac arrhythmia, which is an abnormal heart rhythm, is a common clinical problem in cardiology. Arrhythmias can be divided into many Categories, and accurate detection of arrhythmias can effectively prevent heart disease and reduce mortality. However, existing screening methods require long time monitoring and are low cost and low yield. Our goal is to develop a mixed depth model for processing time series to predict multi-classification electrocardiograph (ECG). Methods In this study, we developed a new, more robust network model named Hybrid Convolutional Recurrent Neural Network (HCRNet) for the time-series signal of ECG. This model utilized a nine-class ECG dataset containing tens of thousands of data to automatically detect cardiac arrhythmias. At the same time, a large imbalance arose because some of the cases in our selected MIT-BIH atrial fibrillation database had less than 100 records, but some had more than 10,000 records. Therefore, during data preprocessing, we adopted a scientific and efficient method to solve the ECG data imbalance problem. In the experimental studies, 10-fold cross validation technique is employed to evaluate performance of the model. Results In order to fully validate our proposed model, we conducted a comprehensive experiment to investigate the performance of the proposed method. Our proposed HCRNet achieved the average accuracy of 99.01% performance and the average sensitivity of 99.58% performance on this dataset. Results suggest that the proposed model outperformed some state-of-the-art studies in ECG classification with a high overall performance value. Conclusion The HCRNet model can effectively classify arrhythmia signals in nine categories and obtain high efficiency, accuracy and F1 values. These improvements in efficiency and accuracy explain the rationality and science of setting up the modules in the HCRNet. By using this model, it can help cardiologists to correctly identify heartbeat types and perform arrhythmia diagnosis quickly.

Sha Yang,* Yun Yang,* Sixin Cui, Ziqi Feng, Yuzhi Du, Zhen Song, Yanan Tong, Liuyang Yang, Zelin Wang, Hao Zeng, Quanming Zou, Hongwu Sun National Engineering Research Center of Immunological Products & Department of Microbiology and Biochemical Pharmacy, College of Pharmacy, Third Military Medical University of Chinese PLA, Chongqing, 400038, People’s Republic of China *These authors contributed equally to this work Introduction: Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most predominant and fatal pathogens at wound infection sites. MRSA is difficult to treat because of its antibiotic resistance and ability to form biofilms at the wound site. Methods: In this study, a novel nanoscale liquid film-forming system (LFFS) loaded with benzalkonium bromide was produced based on polyvinyl alcohol and chitosan. Results: This LFFS showed a faster and more potent effect against MRSA252 than benzalkonium bromide aqueous solution both in vitro and invivo. Additionally, the LFFS had a stronger ability to destroy biofilms (5 mg/mL) and inhibit their formation (1.33 µg/mL). The LFFS inflicted obvious damage to the structure and integrity of MRSA cell membranes and caused increases in the release of alkaline phosphate and lactate dehydrogenase in the relative electrical conductivity and in K+ and Mg2+ concentrations due to changes in the MRSA cell membrane permeability. Conclusion: The novel LFFS is promising as an effective system for disinfectant delivery and for application in the treatment of MRSA wound infections. Keywords: liquid film-forming system, methicillin-resistant Staphylococcus aureus, wound healing, antibiofilm, antibacterial

With more and more drug-resistant Staphylococcus aureus strains emerging in hospitals, there is an urgent need to develop an effective vaccine to combat S. aureus infection. In this study, we constructed a novel bivalent fusion vaccine, SpA-DKKAA-FnBPA37-507 (SF), based on the D domain of staphylococcal protein A (SpA) and the A domain of fibronectin-binding protein A (FnBPA). Immunisation with SF induced a more ideal protective effect compared with the single components alone in a sepsis model. It also showed broad immunoprotection against seven FnBPA isotypes. Vaccination with SF induced strong antibodies responses and Th1/Th17 polarized cellular responses. Further we demonstrated the protective effect of antibodies by the opsonophagocytic assay (OPA) and passive immunisation. Moreover, vaccination with SF showed protective efficacy in a murine pneumonia model and skin abscess model. These results suggest that SF can be regarded as a promising vaccine candidate for the prevention of S. aureus infections.

No licensed Staphylococcus aureus (S. aureus) vaccine is currently available. To develop an effective S. aureus vaccine, we selected the recombinant proteins staphylococcal enterotoxin B (rSEB) and manganese transport protein C (rMntC) as vaccine candidates and formulated a 2C-Staph vaccine. Based on the optimised formation of nanoemulsion (NE) technology, we constructed a novel NE adjuvant vaccine, 2C-Staph/NE. The 2C-Staph/NE particles showed a suitable diameter (24.9 ± 0.14 nm), a good protein structure of integrity and specificity, and high thermodynamic stability. 2C-Staph formulated with an NE adjuvant induced higher survival rates than a 2C-Staph/MF59 vaccine in sepsis and pneumonia models. Moreover, intramuscular vaccination with 2C-Staph/NE yielded protection efficacy in a sepsis model, and the intranasal vaccination route induced a potent protective effect in a pneumonia model. Intranasal vaccination with 2C-Staph/NE induced a strong mucosal response with high levels of IgA and IL-17A in bronchoalveolar lavage fluid (BALF), and the IgG levels in the BALF were comparable to those induced by the intramuscular vaccination route. Furthermore, the serum and BALF induced by intranasal administration showed potent opsonophagocytic activity against S. aureus. And, the IL-17A played a protective role in the pneumonia model demonstrated by a cytokine neutralization test. Taken together, our results showed that intranasal administration of 2C-Staph formulated with an NE adjuvant yielded ideal protection in a murine S. aureus pneumonia model.

As an ingredient of vaccines, adjuvants are indispensable for enhancing and directly inducing robust and extensive adaptive immune responses associated with vaccine antigens. In this study, we initially determined that a new molecular immunopotentiator, ophiopogonin D (OP-D), enhanced the antibody response to antigen. Because OP-D has certain disadvantages, including poor solubility, we next encapsulated OP-D in a nanoemulsion adjuvant (nanoemulsion-encapsulated OP-D, NOD) using low-energy emulsification methods. The NOD thus produced was small, with an average size of 76.45 nm, and exhibited good distribution (PdI value 0.16), significantly increasing the solubility of OP-D. Furthermore, NOD exhibited reduced cellular toxicity and acute toxicity. Our results showed that a fusion antigen of MRSA (HlaH35LIsdB348-465) formulated with NOD significantly improved humoral and cellular immune responses compared to those observed in the antigen/OP-D and antigen/AlPO4 groups. Compared with antigen/OP-D, the antigen formulated with NOD more effectively promoted antigen uptake by dendritic cells (DCs) and the activation of antigen-presenting cells (APCs). Moreover, the NOD-formulated antigen had ideal protective efficacy in a MRSA sepsis model by inducing more potent antibody responses and a Th1/Th17-biased CD4+ T cell immune response. Therefore, these results suggest that NOD is a promising and robust adjuvant platform for a MRSA vaccine. Statement of Significance We first identified a new powerful immunopotentiator, Ophiopogonin D, among dozens of natural products and then used nanotechnology to construct a highly efficient and low toxic adjuvant system (NOD). Our approach intersects natural medicinal chemistry, nanomaterials and immunology, revealing that a strong adjuvant activity of this adjuvant system was verified in vitro and in vivo, and the application of MRSA subunit vaccine model for survival experiments achieved a 100% protection rate. This research illustrate that NOD is a promising and robust adjuvant platform for subunit vaccines.

Pseudomonas aeruginosa is a formidable pathogen that is responsible for a diverse spectrum of human infectious diseases, resulting in considerable annual mortality rates. Because of biofilm formation and its ability of rapidly acquires of resistance to many antibiotics, P. aeruginosa related infections are difficult to treat, and therefore, developing an effective vaccine is the most promising method for combating infection. In the present study, we designed a novel trivalent vaccine, PcrV28-294-OprI25-83-Hcp11-162 (POH), and evaluated its protective efficacy in murine pneumonia and burn models. POH existed as a dimer in solution, it induced better protection efficacy in P. aeruginosa lethal pneumonia and murine burn models than single components alone when formulated with Al(OH)3 adjuvant, and it showed broad immune protection against several clinical isolates of P. aeruginosa. Immunization with POH induced strong immune responses and resulted in reduced bacterial loads, decreased pathology, inflammatory cytokine expression and inflammatory cell infiltration. Furthermore, in vitro opsonophagocytic killing assay and passive immunization studies indicated that the protective efficacy mediated by POH vaccination was largely attributed to POH-specific antibodies. Taken together, these data provided evidence that POH is a potentially promising vaccine candidate for combating P. aeruginosa infection in pneumonia and burn infections.

Background The use of speech based data in the classification of Parkinson disease (PD) has been shown to provide an effect, non-invasive mode of classification in recent years. Thus, there has been an increased interest in speech pattern analysis methods applicable to Parkinsonism for building predictive tele-diagnosis and tele-monitoring models. One of the obstacles in optimizing classifications is to reduce noise within the collected speech samples, thus ensuring better classification accuracy and stability. While the currently used methods are effect, the ability to invoke instance selection has been seldomly examined. Methods In this study, a PD classification algorithm was proposed and examined that combines a multi-edit-nearest-neighbor (MENN) algorithm and an ensemble learning algorithm. First, the MENN algorithm is applied for selecting optimal training speech samples iteratively, thereby obtaining samples with high separability. Next, an ensemble learning algorithm, random forest (RF) or decorrelated neural network ensembles (DNNE), is used to generate trained samples from the collected training samples. Lastly, the trained ensemble learning algorithms are applied to the test samples for PD classification. This proposed method was examined using a more recently deposited public datasets and compared against other currently used algorithms for validation. Results Experimental results showed that the proposed algorithm obtained the highest degree of improved classification accuracy (29.44%) compared with the other algorithm that was examined. Furthermore, the MENN algorithm alone was found to improve classification accuracy by as much as 45.72%. Moreover, the proposed algorithm was found to exhibit a higher stability, particularly when combining the MENN and RF algorithms. Conclusions This study showed that the proposed method could improve PD classification when using speech data and can be applied to future studies seeking to improve PD classification methods.

Methicillin-resistant Staphylococcus aureus (MRSA) sepsis is a life-threatening medical condition that involves systemic inflammation throughout the body. Glucocorticoids are widely used in combination with antibiotics in the treatment of MRSA sepsis to fight the overwhelming inflammation. Here, we describe the improved anti-inflammatory properties of a nitric oxide (NO)-releasing derivative of dexamethasone, ND8008. ND8008 affected MRSA biofilm formation, caused biofilm cell death and reduced the effects of virulence factors, such as α-toxin, by inhibiting the activity of the Staphylococcus aureus accessory gene regulator (agr) system. Dosing of mice with ND8008 (127.4 nmol/kg, i.p.) alone greatly reduced the inflammatory response caused by MRSA blood stream infection and considerably increased the survival rate of septic mice. These findings suggest that this novel NO-releasing derivative of dexamethasone ND8008 could be helpful in the treatment of MRSA sepsis.

Vaccination strategies for Staphylococcus aureus, particularly methicillin-resistant S. aureus (MRSA) infections have attracted much research attention. Recent efforts have been made to select manganese transport protein C, or manganese binding surface lipoprotein C (MntC), which is a metal ion associated with pathogen nutrition uptake, as potential candidates for an S. aureus vaccine. Although protective humoral immune responses to MntC are well-characterised, much less is known about detailed MntC-specific B cell epitope mapping and particularly epitope vaccines, which are less-time consuming and more convenient. In this study, we generated a recombinant protein rMntC which induced strong antibody response when used for immunisation with CFA/IFA adjuvant. On the basis of the results, linear B cell epitopes within MntC were finely mapped using a series of overlapping synthetic peptides. Further studies indicate that MntC113-136, MntC209-232, and MntC263-286 might be the original linear B-cell immune dominant epitope of MntC, furthermore, three-dimensional (3-d) crystal structure results indicate that the three immunodominant epitopes were displayed on the surface of the MntC antigen. On the basis of immunodominant MntC113-136, MntC209-232, and MntC263-286 peptides, the epitope vaccine for S. aureus induces a high antibody level which is biased to TH2 and provides effective immune protection and strong opsonophagocytic killing activity in vitro against MRSA infection. In summary, the study provides strong proof of the optimisation of MRSA B cell epitope vaccine designs and their use, which was based on the MntC antigen in the development of an MRSA vaccine.

Staphylococcus aureus causes serious sepsis and necrotic pneumonia worldwide. Due to the spread of multidrug-resistant strains, developing an effective vaccine is the most promising method for combating S. aureus infection. In this study, based on the immune-dominant areas of the iron surface determinant B (IsdB) and clumping factor A (ClfA), we designed the novel chimeric vaccine IsdB151-277ClfA33-213 (IC). IC formulated with the AlPO4 adjuvant induced higher protection in an S. aureus sepsis model compared with the single components alone and showed broad immune protection against several clinical S. aureus isolates. Immunisation with IC induced strong antibody responses. The protective effect of antibodies was demonstrated through the opsonophagocytic assay (OPA) and passive immunisation experiment. Moreover, this new chimeric vaccine induced Th1/Th17-skewed cellular immune responses based on cytokine profiles and CD4+ T cell stimulation tests. Neutralisation of IL-17A alone (but not IFN-γ) resulted in a significant decrease in vaccine immune protection. Finally, we found that IC showed protective efficacy in a pneumonia model. Taken together, these data provide evidence that IC is a potentially promising vaccine candidate for combating S. aureus sepsis and pneumonia.