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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.

Background The impact of coronavirus diseases 2019 (COVID-19) related non-pharmaceutical interventions (NPIs) on influenza activity in the presence of other known seasonal driving factors is unclear, especially at the municipal scale. This study aimed to assess the impact of NPIs on outpatient influenza-like illness (ILI) consultations in Beijing and the Hong Kong Special Administrative Region (SAR) of China. Methods We descriptively analyzed the temporal characteristics of the weekly ILI counts, nine NPI indicators, mean temperature, relative humidity, and absolute humidity from 2011 to 2021. Generalized additive models (GAM) using data in 2011–2019 were established to predict the weekly ILI counts under a counterfactual scenario of no COVID-19 interventions in Beijing and the Hong Kong SAR in 2020–2021, respectively. GAM models were further built to evaluate the potential impact of each individual or combined NPIs on weekly ILI counts in the presence of other seasonal driving factors in the above settings in 2020–2021. Results The weekly ILI counts in Beijing and the Hong Kong SAR fluctuated across years and months in 2011–2019, with an obvious winter-spring seasonality in Beijing. During the 2020–2021 season, the observed weekly ILI counts in both Beijing and the Hong Kong SAR were much lower than those of the past 9 flu seasons, with a 47.5% [95% confidence interval (CI): 42.3%, 52.2%) and 60.0% (95% CI: 58.6%, 61.1%) reduction, respectively. The observed numbers for these two cities also accounted for only 40.2% (95% CI: 35.4%, 45.3%) and 58.0% (95% CI: 54.1%, 61.5%) of the GAM model estimates in the absence of COVID-19 NPIs, respectively. Our study revealed that, “Cancelling public events” and “Restrictions on internal travel” measures played an important role in the reduction of ILI in Beijing, while the “restrictions on international travel” was statistically most associated with ILI reductions in the Hong Kong SAR. Conclusions Our study suggests that COVID-19 NPIs had been reducing outpatient ILI consultations in the presence of other seasonal driving factors in Beijing and the Hong Kong SAR from 2020 to 2021. In cities with varying local circumstances, some NPIs with appropriate stringency may be tailored to reduce the burden of ILI caused by severe influenza strains or other respiratory infections in future. Graphical Abstract

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.

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

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.

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

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

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.

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.