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Background Since the first report of carbapenem-resistant Klebsiella pneumoniae isolates in China in 2007, the prevalence of CRKP and CRE has increased significantly. However, the molecular characteristics of IMP-producing Klebsiella pneumoniae (IMPKp) are rarely reported. Methods A total of 29 IMPKp isolates were collected from a Chinese tertiary hospital from 2011 to 2017. Clinical IMPKp were identified by VITEK®MS, and further analyzed by whole-genome DNA sequencing with HiSeq and PacBio RSII sequencer. Sequencing data were analyzed using CSI Phylogeny 1.4, Resfinder, PlasmidFinder and the MLST tool provided by the Centre for Genomic Epidemiology. The analysis results were visualized using iTOL editor v1_1. The open reading frames and pseudogenes were predicted using RAST 2.0 combined with BLASTP/BLASTN searches against the RefSeq database. The databases CARD, ResFinder, ISfinder, and INTEGRALL were performed for annotation of the resistance genes, mobile elements, and other features. The types of blaIMP in clinical isolates were determined by BIGSdb-Pasteur. Integrons were drawn by Snapgene, and the gene organization diagrams were drawn by Inkscape 0.48.1. Results Four novel ST type, including ST5422, ST5423, ST5426 and ST5427 were identified. The IMP-4 and IMP-1 were the dominant IMP type. The majority of blaIMP-carrying plasmids belonged to IncN and IncHI5. Two novel blaIMP-carrying integrons (In2146 and In2147) were uncovered. A novel variant blaIMP-90 presented in novel integron In2147 has been identified. Conclusions IMPKp showed low prevalence in China. Novel molecular characteristics of IMPKp have been identified. Continuous monitoring of IMPKp shall also be carried out in the future.

We present a 64-channel fiber-optic ultrasound detector array with high sensitivity. The sensor can exhibit an NEP of 0.64 kPa and a wide bandwidth about 47 MHz, which gives a favorable resolution of photoacoustic imaging.

To achieve dexterous motion controlling of robot, the sensors that function like human neurons for motion perception are essential. In this work, a silica microfiber probe-based optical neuron (MPON) for robot finger motion detection is proposed. The silica microfiber probe was fabricated by snapping a biconical silica optical microfiber that drawn from the standard optical fibre. Then it was embedded into thin polydimethylsiloxane (PDMS) to detect and recognize motions of robotic finger. Specifically, a PDMS-Teflon-Microfiber-Teflon-PDMS composite structure was prepared to protect the waveguide structure of silica microfiber probe and avoid the environmental pollution. With the help of this composite structure, the proposed MPON achieved the accurate measurement of bending angle with large range and fast response. The repeatability and stability of MPON were also investigated. Additionally, different finger motions were successfully distinguished through observing the output power variation of MPON. The proposed MPON could serve as the perceptron of robot hand, which could be applied in dexterous gesture control even human machine interaction.

Background: It is very important to establish more accurate influenza prediction models in megacities. The purpose of this study was to compare the different time series prediction models for influenza from 2010 to 2019 in Beijing, China. Methods: We took the influenza-like illness rate (ILI%), the influenza positive rate and the product of ILI% and influenza positive rate as dependent variables respectively. Subsequently, and model performances of summer point, peak bottom point and peak rising point were analyzed. After selecting the best prediction point, we compared the model performances of different parameters at that point using the SARIMA model. Then, the best model selected by SARIMA was compared with the hybrid LSTM model. Results: Between the 26th week of 2010 and the 25th week of 2019, there were 6,753,116(1.24%) ILI patients, 15,883(16.75%) of which were positive for influenza.The trends and the peak times of ILI%, the influenza positive rate and the product of ILI% and influenza positive rate were roughly the same. The SARIMA model of the peak rising point was better than those of the summer point and peak bottom point. The hybrid LSTM model performed better than the selected best SARIMA model in terms of ILI%, influenza positive rate and the product of ILI% and influenza positive rate. Also, the hybrid LSTM model could maintain a good prediction effect from the 1st to the 26th week.. On the contrary, the prediction effect of the SARIMA model decreased significantly with the extension of the prediction period. Conclusions: Our results suggested that the prediction effect of the hybrid LSTM model was better than the SARIMA model, in terms of ILI%, influenza positive rate and the product of ILI% and influenza positive rate. SARIMA was more suitable for short-term prediction, while the hybrid LSTM model showed obvious advantages in long-term prediction. Our research could help to improve the prediction and early warning of influenza and other respiratory infectious diseases.

Continuous monitoring of blood pressure has significant clinical value for the cardiovascular disease prevention and diagnosis in daily life. However, conventional blood pressure measurement is unsuitable for long-term monitoring due to its discomfort and poor portability. Wearable device is an ideal solution to overcome this problem, which has attracted increasing interests of many researchers. While, high-performance wearable blood pressure sensor still remains a challenge. Here, we present a wearable blood pressure wristband system based on optical fiber. The end face of optical fiber was coated with a Polydimethylsiloxane (PDMS) + Ag composite diaphragm. The continuous and accurate measurement of the pulse waveform was achieved through the phase variation of the light reflected from the diaphragm. Then, the blood pressure can be estimated from the pulse transit time (PTT) which is extracted from the high-fidelity pulse waveform. The estimation model was established using data from 45 subjects. The clinical experiment was also carried out on 17 subjects to test the performance of the proposed wearable blood pressure wristband. The results show that the errors of systolic pressure (SBP) and diastolic pressure (DBP) are 0.24 ± 2.39 mmHg and 0.12 ± 2.62 mmHg compared with commercial sphygmomanometer, respectively. The measurement errors were within the required range of the Association for the Advancement of Medical Instrumentation (AAMI) and the British Hypertension Society (BHS) Grade A, which indicates that the blood pressure wristband has a good accuracy and practicability. This wearable and user-friendly optical fiber blood pressure monitor is a competitive alternative to current commercial products.

Ursolic acid (UA) has been proved to have antioxidant and anti-inflammatory effects. However, it is not clear whether it has a protective impact on kidney damage induced by crystals of calcium oxalate monohydrate (COM). This work aimed to make clear the potential mechanism of UA protecting COM-induced kidney damage. The results manifested that high- and low-dose UA reduced COM crystals in COM rats’ kidney, down-regulated urea, creatinine, and neutrophil gelatinase-associated lipocalin (NGAL) levels in rat plasma, declined kidney tissue and HK-2 cell apoptosis, inhibited Bax expression but elevated Bcl-2 expression. Additionally, UA alleviated renal fibrosis in COM rats, repressed α-SMA and collagen I protein expressions in the kidney and COM rats’ HK-2 cells, depressed COM-induced oxidative damage in vivo and in vitro via up-regulating Nrf2/HO-1 pathway, up-regulated SOD levels and reduced MDA levels, down-regulated TNF-α, IL-1β, and IL-6 levels in vivo and in vitro via suppressing activation of TLR4/NF-κB pathway. In summary, the results of this study suggest that COM-induced renal injury can be effectively improved via UA, providing powerful data support for the development of effective clinical drugs for renal injury in the future., Graphical abstract

Background In megacities, there is an urgent need to establish more sensitive forecasting and early warning methods for acute respiratory infectious diseases. Existing prediction and early warning models for influenza and other acute respiratory infectious diseases have limitations and therefore there is room for improvement. Objective The aim of this study was to explore a new and better-performing deep-learning model to predict influenza trends from multisource heterogeneous data in a megacity. Methods We collected multisource heterogeneous data from the 26th week of 2012 to the 25th week of 2019, including influenza-like illness (ILI) cases and virological surveillance, data of climate and demography, and search engines data. To avoid collinearity, we selected the best predictor according to the weight and correlation of each factor. We established a new multiattention-long short-term memory (LSTM) deep-learning model (MAL model), which was used to predict the percentage of ILI (ILI%) cases and the product of ILI% and the influenza-positive rate (ILI%×positive%), respectively. We also combined the data in different forms and added several machine-learning and deep-learning models commonly used in the past to predict influenza trends for comparison. The R2 value, explained variance scores, mean absolute error, and mean square error were used to evaluate the quality of the models. Results The highest correlation coefficients were found for the Baidu search data for ILI% and for air quality for ILI%×positive%. We first used the MAL model to calculate the ILI%, and then combined ILI% with climate, demographic, and Baidu data in different forms. The ILI%+climate+demography+Baidu model had the best prediction effect, with the explained variance score reaching 0.78, R2 reaching 0.76, mean absolute error of 0.08, and mean squared error of 0.01. Similarly, we used the MAL model to calculate the ILI%×positive% and combined this prediction with different data forms. The ILI%×positive%+climate+demography+Baidu model had the best prediction effect, with an explained variance score reaching 0.74, R2 reaching 0.70, mean absolute error of 0.02, and mean squared error of 0.02. Comparisons with random forest, extreme gradient boosting, LSTM, and gated current unit models showed that the MAL model had the best prediction effect. Conclusions The newly established MAL model outperformed existing models. Natural factors and search engine query data were more helpful in forecasting ILI patterns in megacities. With more timely and effective prediction of influenza and other respiratory infectious diseases and the epidemic intensity, early and better preparedness can be achieved to reduce the health damage to the population.

Mercury (Hg) significantly inhibits maize (Zea mays L.) production, which could be aggravated by water deficit (WD) due to climate change. However, there is no report on the maize in response to combined their stresses. This work was conducted for assessing the response and adaptive mechanism of maize to combined Hg and WD stress using two maize cultivars, Xianyu (XY) 335 and Yudan (YD) 132. The analysis was based on plant growth, physiological function, and transcriptomic data. Compared with the single Hg stress, Hg accumulation in whole plant and translocation factor (TF) under Hg+WD were increased by 64.51 % (1.44 mg kg

A dye-doped polymer based optical fiber transducer is demonstrated for PA-US dual-modality imaging, which an ultrasound generation efficiency of 0.064MPa mJ-1cm2 with a bandwidth of 33.5MHz as well as an optical transmittance of 83.1%.

A 32-channel high sensitivity optic ultrasound detector array is demonstrated for rapid photoacoustic imaging. The probe exhibits a NEP of 0.61kPa and the scanning time could be four times faster than a mechanical scan theoretically.

A compact fiber optic ultrasound transducer with integrated ultrasound emission and detection is developed. The transducer an emission pressure of 0.45MPa and a noise equivalent pressure of 72.8Pa.

A miniaturized ultrasound sensor based on optical fiber is designed and realized for multichannel parallel ultrasound detection and photoacoustic imaging. The fiber optic sensor is composed of a polymer coating, a reflective mirror and a single-mode optical fiber, with only 125 µm in diameter. By integrating the coherent demodulation technology and multiplexing technology, which using a relatively cheap fixed wavelength laser, hundreds of sensors could work simultaneously. Meanwhile, highly sensitive ultrasound detection has been demonstrated with the noise equivalent pressure as low as 0.46 kPa and the sensor exhibits a nearly omnidirectional directivity. Furthermore, a photoacoustic imaging system based on three sensors working in parallel is demonstrated. High lateral resolutions of 165-217 µm and axial resolutions of 112-131 µm over a depth range of larger than 5 mm are obtained. A three-dimensional phantom imaging experiment is also demonstrated. Benefited from parallel detection, the imaging speed is three times faster than that of a single sensor. The miniaturized fiber optic ultrasound sensor probe provides a competitive alternative for mechanically scanning-free endoscopic imaging, which is beneficial from small size, omnidirectional directivity and parallel detection capability.

Heavy metals (HMs) in mixed hazardous waste can be volatilized in the kiln for preparing sintered bricks, which greatly increases the environmental risk. In this study, the volatilization, transformation, and leaching of HMs from bricks were evaluated. Field tests and laboratory leaching experiments were carried out. HM-contaminated soil was used to prepare sintered bricks at high-temperature in a tunnel kiln. Release of HMs from brick under rainfall conditions was investigated in laboratory simulation experiments. The field tests showed that the total amount of Pb, Zn, Cd distributed to the gas phase were all less than 2%, but the amount of Hg entering the gas phase 40.1%-60.5% in the particulate forms. The As leaching rate increased after sintering of bricks in the kiln, which was attributed to the increased formation of soluble arsenate and the reduced availability of sorption sites. The tank leaching test indicated that the release mechanism of trance elements (Cr, As, Zn, Cd, Pb and Ni) was mainly controlled by diffusion. This study provides useful knowledge for decreasing the volatilization and leaching of HMs from sintered bricks prepared using hazardous waste.

In seawater pipeline, the welding joint is a non-uniform structure composed of welding seam, base metal and heat affected zone. It has inhomogeneity in chemical composition, organizational structure, residual stress, etc. As local defects and high turbulence accelerate corrosion, the welding joint is often the weakest link in pipeline corrosion. Herein, the electrochemical corrosion behavior of B10 alloy welded joint in flowing seawater is studied from macroscopic and submicroscopic viewpoints using AC impedance, linear polarization, array electrode and morphological characterization. The results reveal that the corrosion rate of weld metal (WM), base metal (BM) and heat-affected zone (HAZ) decreased with the increase of time. Combined with SEM and EDS analysis, it can be seen that the increase in time led to the decomposition and accumulation of corrosion products, which gradually enhanced the corrosion resistance of welded joints. At the submicroscopic scale, WM acts as a cathode to mitigate corrosion during the later stages of high flow rate.

Coherence algorithm is widely used to describe geological discontinuity and subtle features of seismic data. Traditional coherence algorithms often use the linear correlation measurement to measure the relationship between two seismic traces. It does not work well because seismic data do not obey the normal distribution. To describe the coherence measurement of seismic data, we propose an improved coherence algorithm by combining the mutual information (MI) and third-generation coherence (C3) algorithm. The MI is a measurement of the general dependence and used to describe nonlinear relationships between two variables. Note that, the MI does not require that variables obey specific distribution (e.g., the normal distribution). Note that, we calculate precise MI values using the copula function. In addition, we introduce the information divergence to save calculation time by replacing the eigenvalue decomposition of the C3 algorithm. To demonstrate the effectiveness of the proposed algorithm, we apply it to field data. Field data experiments demonstrate the effectiveness of the proposed algorithm to describe geological discontinuity and heterogeneity, such as channels with different thicknesses.

A multi-channel parallel ultrasound detection system based on a photothermal tunable fiber optic sensor array is proposed. The resonant wavelength of the ultrasound sensor has a quadratic relationship with the power of a 980-nm heating laser. The maximum tuning range is larger than 15 nm. Through photothermal tuning, the inconsistent operating wavelengths of the Fabry–Perot (FP) sensor array can be solved, and then a multiplexing capacity of up to 53 can be theoretically realized, which could greatly reduce the time required for data acquisition. Then, a fixed wavelength laser with ultra-narrow linewidth is used to interrogate the sensor array. The interrogation system demonstrates a noise equivalent pressure (NEP) as low as 0.12 kPa, which is 5.5-times lower than the commercial hydrophone. Furthermore, a prototype of a four-channel ultrasound detection system is built to demonstrate the parallel detection capability. Compared with the independent detection, the SNR of parallel detection does not deteriorate, proving that the parallel detection system and the sensor array own very low cross talk characteristics. The parallel detection technique paves a way for real-time photoacoustic/ultrasound imaging.

Persistent organic pollutants in soil are not readily degraded in the short term. The utilization of co-processing solid waste in cement kilns has received increasing attention in recent years. Co-processing may be a good way of disposing of dichlorodiphenyltrichloroethane-contaminated soil (CS). The feasibility of co-processing CS pretreated to desorb dichlorodiphenyltrichloroethane, was assessed by performing an industrial-scale trial, focusing on the risks posed by emissions to the environment. Samples of the input and output in cement kiln were collected for determining clinker quality, production operation, pollutant emissions, cement kiln system destruction efficiency, and distribution profiles of persistent organic pollutants unintentionally produced from kiln. The destruction efficiency and destruction removal efficiency both were > 99.99% in cement kiln system at the appropriate CS feeding rate. Emissions of stack gases produced by cement kilns co-processing CS were within the reasonable range set in China. Dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), and polychlorinated biphenyls (PCBs) concentrations and distribution profiles in flue gases and particulate samples from two tests showed PCBs mainly formed at the same sites as PCDD/Fs, indicating they are may formed in a similar way in cement kiln. A comparison with the processing parameters in the clinker, cement kiln dust, and flue gas under baseline and co-processing conditions, manifested that co-processing had no effect on the operation or cement quality of the cement kiln. Thus co-processing CS at a rate of 20 t/h with pretreatment process, is an environmentally sound and highly efficient treatment for CS.

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.

We demonstrated a hybrid coating based fiber probe for simultaneous ultrasound generation and detection. The probe exhibits a generated pressure of 864kPa and a bandwidth about 25MHz, as well as a high sensitivity of 3.41V/MPa.

A highly sensitive and compact fiber optic ultrasound sensor based on a composite sensing film is demonstrated. Assisted with the coherent demodulation, a NEP of 0.46kPa and the bandwidth of 20MHz are successfully achieved.

Global climate change is gradually changing the distribution and diversity pattern of species. In order to study the change of distribution area and distribution barycenter of Bufo gargarizans under climate change, we adopted the maximum-entropy modeling (Maxent) model and barycenter migration analysis. And four General circulation models (GCMs) under four representative concentration pathways (RCPs), 29 environment variables (including bioclimate, topography, habitat and human impact) were used to predict the current and future (2050 and 2070) distribution of B. gargarizans. The results show that the Mean temperature of Driest quarter (Bio9), Precipitation of driest month (Bio14) and population (POP) have greater influence on the distribution of B. gargarizans, it indicates that climate and anthropogenic factors have greater influence on the distribution of B. gargarizans than other environmental factors such as topography and landform. And in the next 30 to 50 years, from the perspective of the large spatial scale of the whole China, the distribution area of B. gargarizans is in the eastern part of China, the southeastern part is reduced, and the Midwest and northwest part is expanded. On the whole, the suitable habitat of B. gargarizans will be reduced in the future and will migrate to the high latitude and altitude area. In this study, B. gargarizans was used as a sentinel species to study the response of amphibians to climate change, this paper aims to reveal the mechanism of amphibian response to climate change from the current and future dispersal patterns of B. gargarizans.

Oil-based drilling cuttings (OBDC) produced from shale gas development is a hazardous waste that have high calorific values and should be disposed of properly. Burning bricks with OBDC is a promising co-disposal method; however, organic pollutants emitted during this process have not received sufficient attention. In this study, the composition and combustion characteristics of OBDC were determined, and the emissions of typical organic pollutants when burning bricks with the addition of OBDC were investigated; these included benzene series compounds (BTEXs), non-methane total hydrocarbons (NMHC), polycyclic aromatic hydrocarbons (PAHs), and polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs). The results showed that OBDC comprised large amounts of alkanes and aromatic hydrocarbons, and combusted mainly in the temperature range of 145-450 °C with an ignition temperature of 145 °C. The co-processing 10% OBDC increased the concentrations of toluene, NMHC, and PAHs in the flue gases by ∼1000%, ∼500%, and 200%, respectively, compared to the control experiment; however, their emission concentrations were within the limits set by the Integrated emission standards of air pollutants of Chongqing. It is worth noting that 26.443 ng/Nm

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.

We present a wearable blood pressure wristband based on optical fiber probe with composite diaphragm. Clinical results show errors of systolic pressure and diastolic pressure are 0.24 ± 2.32 mmHg and 0.18 ± 2.48 mmHg.

An ultra-sensitive optical microfiber ultrasonic sensor is proposed and demonstrated. The noise equivalent pressure length product of this sensor is 1.71kPa mm, which gives a 53 times improvement compared with standard single-mode fiber.

We report a single end microfiber probe with compact size, which is simply fabricated by snapping a biconical microfiber. Its application in DNA hybridization detection is also presented.

The determination of hemoglobin (Hb) level is indispensable in the pathological study of many blood diseases. Graphene oxide (GO), with its excellent optical properties and great biocompatibility, has attracted significant attention and been widely utilized in biochemical detection. Here, we report an ultrasensitive Hb sensor based on a graphene oxide (GO)-coated microfiber. The GO was utilized as a linking layer deposited on the microfiber surface, which can provide an enhanced local evanescent light field and abundant bonding sites for Hb molecules. The optical microfiber with a compact structure and a strong evanescent light field served as the platform for biosensing. The surface morphology characterized by optical microscope, scanning electron microscope, and Raman spectroscopy offers detailed evidence for the success of GO deposition. The dynamic bonding between GO and target Hb molecules was monitored in real-time through an optical spectrum analyzer. An ultrahigh sensitivity of 6.02 nm/(mg/mL) with a detection limit of 0.17 &mu, g/mL was achieved by tracking the resonant wavelength shift of spectra. It is important to highlight that the detection limit of GO-coated microfiber is 1&ndash, 2 orders of magnitude lower than other reported fiber optic Hb sensors. Benefiting from high sensitivity, low cost, small size, and fast response, the proposed sensing microfiber coated with GO could be a competitive alternative in the diagnosis of blood diseases and a subject of further research in the medical field.

Background Helicobacter pylori (H. pylori) infection remains a global public health issue, especially in Asia. Due to the emergence of antibiotic-resistant strains and the complexity of H. pylori infection, conventional vaccination is the best way to control the disease. Our previous study found that the N-acetyl-neuroaminyllactose-binding hemagglutinin protein (HpaA) is an effective protective antigen for vaccination against H. pylori infection, and intranasal immunization with the immunodominant HpaA epitope peptide (HpaA 154-171, P22, MEGVLIPAGFIKVTILEP) in conjunction with a CpG adjuvant decreased bacterial colonization in H. pylori-infected mice. However, to confer more robust and effective protection against H. pylori infection, an optimized delivery system is needed to enhance the P22-specific memory T cell response. Results In this study, an intranasal nanoemulsion (NE) delivery system offering high vaccine efficacy without obvious cytotoxicity was designed and produced. We found that this highly stable system significantly prolonged the nasal residence time and enhanced the cellular uptake of the epitope peptide, which powerfully boosted the specific Th1 responses of the NE-P22 vaccine, thus reducing bacterial colonization without CpG. Furthermore, the protection efficacy was further enhanced by combining the NE-P22 vaccine with CpG. Conclusion This epitope-loaded nanoemulsion delivery system was shown to extend antigen release and elicit potent Th1 response, it is an applicable delivery system for intranasal vaccine against H. pylori. Electronic supplementary material The online version of this article (10.1186/s12951-019-0441-y) contains supplementary material, which is available to authorized users.

This study aims to model the temporal and spatial characteristics of end-of-life (EOL) power batteries from electric vehicles (EVs) in China. A Stanford estimation model is used, assuming that the lifetime of power batteries obeys a Weibull distribution. We collected the sales data for two types of power batteries used in four types of EVs from 2009 to 2018 in mainland China and predicted the sales data from 2019 to 2030 according to the Chinese government's plan. The results present a complete picture of EOL batteries in China: (1) the generation of retired power batteries in China is predicted from 2020 to 2036, including 112 k tonnes in 2020 and 708 k tonnes in 2030; (2) the potential economic value of retired batteries for echelon and recovery utilization is analyzed; and (3) the generation of retired power batteries in 20 provinces was estimated and compared with their collection station numbers. Considering the weight of different batteries and the service life increase caused by technology upgrades, our predictions for the quantity of retired batteries are lower and more accurate than others' predictions. Large-scale battery retirement will come later than previously anticipated. We should plan the number of recycling sites in main provinces based on the accurate retired amount.

Parkinson’s disease(PD)diagnosis based on speech data has been proved to be an effective way in recent years.There are still some problems on preprocessing samples,ensemble learning,and so on.The problems can further cause misleading of classifiers,unsatisfactory classification accuracy and stability.This paper proposed a new diagnosis algorithm of PD by combining multi-edit sample selection method and random forest.At the end of it,this paper presents a group of experiments carried out with the newest public datasets.Experimental results showed that this proposed algorithm realized the classification of the samples and the subjects of PD.Furthermore,it achieved average classification accuracy of 100% and obtained improvement of up to 29.44% compared to those provided by the subjects.This paper proposes a new speech diagnosis algorithm for PD based on instance selection;and the method algorithm has a higher and more stable classification accuracy,compared with the other algorithms.

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.

A label-free biosensor based on a reflective microfiber probe for in-situ real-time DNA hybridization detection is proposed and experimentally demonstrated. The microfiber probe is simply fabricated by snapping a non-adiabatic biconical microfiber through closing the oxyhydrogen flame during fiber stretching. Assisted with the Fresnel reflection at the end of microfiber, a reflective microfiber modal interferometer is realized. The in-situ DNA hybridization relies on the surface functionalization of a monolayer of Poly-L-lysine (PLL) and synthetic DNA sequences that bind to a given target with high specificity. The detection processes of DNA hybridization in various concentration of target DNA solutions are monitored in real-time and the experimental results present a minimum detectable concentration of 10pM with good repeatability. Additionally, the detection specificity is also investigated by immersing the microfiber probe into the non-complementary ssDNA solutions and observing the spectral variation. The proposed biosensor has advantages of high sensitivity, compact size, ease of use and simple fabrication, which makes it has great potential to be applied in a lot of fields such as disease diagnosis, medicine, and environmental science.

Porous WO 3 /TiO 2 hollow microspheres were prepared by a spray drying method for photodegradation of methylene blue and phenol. The catalysts were characterized by X-ray diffraction, Field Emission Scanning Electron Microscope, High Resolution Transmission Electron Microscope, N 2 adsorption–desorption measurements, Raman spectrometer, UV–Vis Diffuse Reflectance Spectroscopy and Zeta-Meter measurements. The results showed that the tungsten oxides mainly existed in highly dispersed amorphous form on anatase when the loading amount of tungsten oxide was below 3 mol%. The improved photocatalytic activity under UV light irradiation of the WO 3 /TiO 2 catalyst mainly arises from the enhanced charge separation efficiency rather than the improved light absorbance by highly dispersed amorphous tungsten oxides. Highly dispersed amorphous WO x can form a shallowly trapped site due to its similar band structure with TiO 2 . The strongly electron-withdrawing of tungsten oxide in highly dispersed state facilitates the electron transition between titanium and WO x , and consequently improves the charge separation. The enhanced acidity of catalyst by WO x in reactant environment also improved the charge separation efficiency due to the timely transition of holes and electrons accumulated on TiO 2 and WO x , respectively. However, the improved photocatalytic activity under visible light irradiation of the WO 3 /TiO 2 catalyst mainly arises from light harvest. TiO 2 containing 3 mol% WO 3 displayed the highest photocatalytic activity under UV light irradiation while that containing 4 mol% WO 3 present highest activity under visible light irradiation.