Search

Introduction. Coronavirus disease 2019 (COVID-19) is a global public health crisis. However, whether it can cause respiratory dysfunction or physical and psychological disorders in patients remains unknown. Thus, this study was conducted to investigate the respiratory function, activities of daily living, quality of life, and mental status of patients with COVID-19. Participants and outcomes. Data was collected from the follow-up of eligible patients who attended the fever clinic of three hospitals in Jiangxi Province, from March to May 2020. The outcomes included respiratory muscle function, degree of dyspnea, aerobic capacity, activities of daily living, quality of life, and mental status. Results. A total of 139 patients (72 men and 67 women) were included in this study. The proportions of mild, moderate, severe, and critical cases of COVID-19 were 7.1% (10 cases), 68.3% (95 cases), 20.1% (28 cases), and 4.2% (6 cases), respectively. The rates of abnormal maximal inspiratory pressure were 10.0%, 25.2%, 25.0%, and 16.7%, respectively. There were 50%, 65.3%, 50%, and 66.7% of the patients with abnormal dyspnea in the four clinical classifications, respectively. Patients generally show a decline in quality of life, anxiety, and depression symptoms. Conclusions. Respiratory dysfunction, decreased quality of life, and psychological disorders were present in each clinical classification of COVID-19. Therefore, it is necessary to carry out respiratory rehabilitation and psychological intervention for COVID-19 patients.

To study statistical characteristics of the random spray autoignition, aviation kerosene was injected transiently into non-vitiated air crossflow in a flow reactor with optical accesses. The operating conditions were relevant to gas turbine combustor: the air crossflow pressure and temperature were in the range of 1.4–1.7 MPa and 830–947 K, respectively, and the jet-to-crossflow momentum flux ratios were 20, 50 and 80. Statistical distributions of random ignition delay times with adequate convergence were estimated based on histograms. The dependences of the distributions on reactor pressure, temperature, and jet-to-crossflow momentum flux ratio were studied. The results show that the resulting distributions appear more concentrated with the increase of air temperature or jet-to-crossflow momentum flux ratio. And then the correlations for the mean and standard deviation of the ignition delay time sample data were developed based on the present results. Compared with the correlations of ignition delay time of homogeneous premixed gas-phase kerosene/air mixture reported in the literature, the results show a greater significance pressure dependence and lower temperature sensitivity of the ignition delay time of non-premixed kerosene spray.

As a novel two-dimensional material, Ti3C2 MXenes has attracted lots of attention in biomedical filed for its large surface area and excellent near-infrared (NIR) responsiveness. In this paper, an in-situ growth and self-assembly approach was employed to combine gold nanorods (GNRs) with Ti3C2 nanosheets to prepare intelligent sandwich-like Ti3C2@GNRs/PDA/Ti3C2 nanohybrids. Compared with Ti3C2 nanosheets, in-situ growth Ti3C2@GNRs possessed excellent photothermal conversion efficiency (45.89%), caused by the distinguished photothermal synergy between GNRs and Ti3C2 nanosheets. Moreover, the high specific surface area of Ti3C2 MXene and outstanding adhesion performance of PDA endowed Ti3C2@GNRs/PDA/Ti3C2 nanohybrids with superior drug loading ability for doxorubicin hydrochloride (DOX) (95.88%). Besides, Ti3C2@GNRs/PDA/Ti3C2 nanohybrids displayed distinct pH/NIR responsive drug release properties upon NIR irradiation owing to the strong π-π stacking interaction between Ti3C2@GNRs/PDA/Ti3C2 and DOX, along with the excellent NIR-responsiveness of Ti3C2@GNRs/PDA/Ti3C2. This paper offers a practicable method to prepare Ti3C2 MXene-based nanoplatform with synergistically enhanced NIR drug release behavior, brilliant biocompatibility and high drug loading efficiency, which is expected to be applied in remote cancer therapy.

Multi-responsive hybrid microgels have attracted lots of attention in biomedical filed owing to the tunable degree of flexibility, high particle stability, and remarkable sensitivity to external stimuli. In this paper, a novel remote drug delivery platform based on gold nanorods (AuNRs)-P(NIPAM-co-AAc) (PNA) hybrid microgel was prepared by electrostatic self-assembly approach. The electrostatic self-assembly of mercapto-modified polyethylene glycol (mPEG) and polyallylamine hydrochloride (PAH) was utilized to safeguard AuNRs, which could greatly enhance the stability of AuNRs and endow AuNRs-PNA hybrid microgels with excellent physiological dispersibility and stability. More importantly, due to the change of electrostatic force between microgels and DOX at different pH values, as well as the thermal sensitivity of PNA and NIR response of AuNRs, AuNR-PNA hybrid microgels displayed prominently pH/temperature/NIR synergistic responsive drug release performance. This paper furnishes a green and feasible method to prepare intelligently remotely controllable hybrid microgels with great physiological stability, which has great perspectives in photothermal therapy and remotely controllable drug delivery area. pH/temperature/NIR synergistic responsive AuNRs-P(NIPAM-co-AAc) hybrid microgel for smart drug delivery was prepared by in situ self-assembly.

Remotely multi-responsive chitosan (CS) hydrogels holds great promise in the design of anticancer drug carriers. In this paper, near-infrared (NIR)-/pH-dual responsive CS/β-GP/Ti

Long non-coding RNA small nuclear RNA host gene 14 (SNHG14) is a novel contributor of dopaminergic neuronal injury in Parkinson's disease. We further explored its role in 1-methyl-4-phenylpyridinium (MPP

The frosting of the evaporator of the ship’s low-temperature cold storage will affect the heat exchange performance of the evaporator operation, the stability of the low-temperature cold storage of the ship’s food security and the effect of food refrigeration. Therefore, the evaporator coil of the low-temperature cold storage needs to be defrosted regularly. The low-temperature refrigeration system of a ship adopts the defrosting mode of electric heating. The lower the temperature of the low-temperature warehouse, the more important the thermal effect of defrosting is. This paper puts forward a technical innovation scheme for the design of the ship’s cold storage and the defrosting control mode, which can provide a reference for the design of the ship’s low-temperature refrigeration system and the defrosting of the low-temperature cold storage.

Background: Among discharged COVID-19 patients, the health-related quality of life is poor, and patients suffer from significant physical and psychological impairment. This study was designed to investigate the effects of Liuzijue exercise on the rehabilitation of COVID-19 patients. Methods: Thirty three eligible patients with COVID-19 were enrolled in the study after discharge. All the participants practiced Liuzijue exercise once per day for 20 minutes over 4 weeks. Data were collected at baseline and the end of the intervention. Primary outcomes involved functional capacity and secondary outcomes involved quality of life. Results: The maximal inspiratory pressure (MIP), peak inspiratory flow (PIF), and diaphragm movement in deep breathing (DM-DB) of patients increased significantly after 4 weeks of intervention. The dyspnea was also alleviated and exercise capacity was significantly improved. In terms of quality of life, physical functioning and role-physical scores were significantly increased. Moreover, Liuzijue could significantly alleviate the depression and anxiety status of the patients. Conclusion: Liuzijue exercise is a viable alternative home exercise program that produced better functional capacity and quality of life in discharged patients with COVID-19. These findings also showed the necessity of rehabilitation intervention for cured COVID-19 patients.

Risk management (RM) is an effective means of safety assessment and reliability management of nuclear power plant (NPP). During the operation of NPP, the main contents of RM work are as follows: 1. Real-time reliability assessment of NPP system, and evaluate NPP risk, so as to ensure that the NPP system can complete the specified functions to deal with the consequences of system failure. 2. Complete the diagnosis and mitigation of abnormal faults, so as to ensure that the NPP system can return to a safe state as soon as possible in the case of abnormal operation of NPP. With the continuous improvement of the requirements of online RM, LPSA (Living PSA) technology, as an effective tool of RM, has been developed and provides more powerful support for the safe operation of NPP. In order to evaluate the reliability of NPP system in real time, LPSA model needs to be updated to match the state of the system. Most of the existing LPSA model updating techniques are based on the premise that the system information is completely knowable and the information is accurate. However, in the process of NPP operation, the accessibility of system information and the accuracy of information are difficult to meet the requirements of updating the existing LPSA model. How to update the LPSA model in the case of incomplete and inaccurate information is one of the difficulties in the application of online LPSA technology. Especially when the NPP is in abnormal conditions, it is more urgent for operators to obtain correct system information in real time to recognize the available state of the plant system. In fact, the required system information needs to be obtained by the operator through his or her cognitive behavior process, such as the fault diagnosis process. At the same time, this information can be used to help operators complete the diagnosis of system status and the evaluation of system reliability. In this study, an information reasoning method is proposed to evaluate the probability of various failure modes under the information known to the operator through the modeling and analysis of the cognitive behavior process of the operator. The method can assist the operator to make the correct fault judgment to complete the fault diagnosis and fault mitigation. In addition, the information obtained by the operator in the process of cognitive behavior, and the results of information reasoning can be used to update the LPSA model in real time, so as to obtain the real-time reliability evaluation results of the NPP system.

Fault detection and diagnosis (FDD) provides safety alarms and diagnostic functions for a nuclear power plant (NPP), which comprises large and complex systems. NPP has a large number of parameters which make it difficult achieve FDD. Now many diagnosis methods have lack of better explanation for faults and quantitative analysis. Therefore, to overcome the “black box” of FDD based on data-driven methods, this paper adopts signed directed graph (SDG) in knowledge graph for FDD. It can express the cause and effect of accidents through knowledge maps. At same time, this paper uses correlation analysis to conduct a quantitative analysis between parameters and faults. It this paper, SDG is used to explain the reason of faults. In order to quickly achieve FDD, this paper introduces a quantitative analysis method. It combines expert system and correlation analysis method to analyze the weight of each parameter. On this basis, matrix reasoning is used to achieve the FDD, and the reason is shown in SDG model inference. This paper takes loss of coolant accident as the case study, the case shows that the proposed method is superior to the conventional SDG method and can diagnose the faults timely.

The simultaneous elimination of organic pollutant and heavy metals using efficient catalysts has attracted much attentions, but facing obstacles of low redox ability and high recombination rate of photogenerated carriers. Herein, we have successfully synthesized Bi2SeO5/rGO/MIL-88A composition for the synergistic photocatalytic removal of chloramphenicol (CAP) and Cr6+. The optimal sample can concurrently remove 85.68% of CAP and 91.85% of Cr6+ in 120 min. The enhanced performance is attributed to that Z-scheme heterojunction formed between metal compounds, which accelerates the separation of electrons and holes. Notably, the hybrid of rGO is proved to facilitate the flow of electrons and significantly inspire the nitrogen reduction (59.34% of N is reduced into ammonia). Furthermore, the mineralization and denitrification pathway of CAP are proposed based on calculation and experiment. Our study integrates reduction, degradation and denitrification innovatively, providing a new insight for simultaneous removal of heavy metal and nitrogenous organic pollutant.

Antibacterial nanomaterials produced by sustainable or ‘green’ synthesis methods are very important. Moreover, combination of photocatalytic antibacterial materials and antiseptic inorganic nanopar...

This paper aims at the electrical failure of the ship anchor machine, the potential causes of the failure are summarized and summarized by analyzing the electrical principle of the anchor machine. After the on-site failure investigation, the cause of the failure is accurately located, so as to put forward a feasible plan for the use and daily maintenance of the ship anchor machine. Because of its simple structure, stable operation and easy maintenance, the anchor machine is used for anchoring and maintenance of ships. Port docking is very important for ship safety and is widely used on ships.

With the development of aquaculture, there is an urgent demand for an alternative antibacterial agent to reduce the drug resistance and environmental pollution caused by the abuse of antibiotics. Recently, silver nanoparticles (AgNPs) have been viewed as a novel type of antimicrobial agents due to their unique advantages. In this study, AgNPs were biosynthesized with the ginger rhizomes extract. The biosynthesized AgNPs were characterised by UV–visible spectroscopy, transmission electron microscopy, X-ray diffraction and fourier transform infrared spectroscopy. Furthermore, the antimicrobial activities of the AgNPs were fully analyzed against six typical aquatic pathogens. The results indicated that the components in ginger extract could function as the chemical reductant to synthesize AgNPs. Moreover, compared with the AgNPs synthesized by chemical methods, the biosynthesized AgNPs were smaller, and had higher stability and antibacterial activity. Therefore, the biosynthesized AgNPs using ginger extract may have prospective applications in aquaculture.

Additional file 2. Search strategy for PubMed.

Additional file 3 Table A1. Characteristics of studies excluded from further analysis.

Xiaoyukang Jiaonang (XYK) is a Chinese patent medicine approved by the National Medical Product Administration which is used to treat intracranial hematoma in China. In this study, we observed the molecular mechanism of XYK in hypoxia-inducible factor 1α (HIF-1α), inflammation and angiogenesis of chronic subdural hematoma (CSDH). The CSDH model was made by using internal iliac vein blood of Wister rats, and rats were divided into sham group, CSDH group and XYK group. The rats in the XYK group were gavaged with Xiaoyukang Jiaonang (185 mg/kg) for 7 days, and rats in the CSDH group and sham group were gavaged with the same amount of physiological saline for 7 days. In the CSHD rat model, active inflammation and angiogenesis were observed around the hematoma. XYK promoted the ubiquitination and degradation of HIF-1α, and reduced the concentration of VEGF and the ratio of angiopoietin-1/angiopoietin-2. XYK reduced proinflammatory cytokines and increased anti-inflammatory cytokine. In tissue section, XYK reduced the size of the hematoma and membrane, and reduced vWF positive cells in membrane. Furthermore, the endothelial progenitor cells in blood decreased as well. Overall, XYK shows anti-inflammatory and antiangiogenesis effects which may relate to the degradation of HIF-1α.

New materials with good antibacterial activity synthesized by simple, environmentally friendly method have attracted numerous research interests. Taking advantage of Ag and graphene oxide (GO), the GO/Ag nanocomposites were prepared by a facile, green “one-pot” reaction to achieve superior antibacterial properties. AgNO3 is as a precursor of Ag nanoparticles (Ag NPs), and the grape seeds extract as an environmentally friendly reducing and stabilizing agent. The as-prepared GO/Ag nanocomposites were characterized by various technologies. The results indicated that the silver ion was reduced by the grade seeds extract and Ag NPs were decorated on the surface of GO nanosheets successfully. The average size of the Ag NPs anchored on the GO surface was 40–50 nm. In this study, we prepared GO/Ag nanocomposites with different Ag NPs to GO ratios and carefully investigated their antibacterial activities. We found that the GO/Ag nanocomposites show better antibacterial activity when the concentration of AgNO3 is 2 mM. GO/Ag nanocomposites have a minimum inhibitory concentration 23.8 μg/mL, lower than bare Ag NPs 25.5 μg/mL. We try to explain the antibacterial mechanism based on optical microscopy observation.

With the development of aquaculture, there is an urgent demand for an alternative antibacterial agent to reduce the drug resistance and environmental pollution caused by the abuse of antibiotics. Recently, as promising antimicrobial agents, silver nanoparticles (AgNPs) synthesized via organisms has received much attention. Cordyceps militaris , a valuable edible and medicinal fungus, is rich in a variety of biologically active substances. So, it is of interest to biosynthesis a new antimicrobial agent of AgNPs with the aid of C. militaris . In this study, AgNPs were synthesized using the cell filtrate of C. militaris mycelium as reducing agents. The formation of AgNPs was first confirmed by the surface plasmon resonance illustrated in UV–visible spectrophotometer. X-ray diffraction analysis further confirmed that the AgNPs were composed of highly crystalline Ag. Transmission electron microscopy analysis revealed that most the AgNPs were in spherical shape with mean diameter about 15 nm. Moreover, the synthesized AgNPs exhibited superior antibacterial activities against the all the aquatic as well as clinical pathogenic bacteria. Besides, the prepared AgNPs were proven to be highly stable, even after long-term storage. To the best of our knowledge, this is the first report that the C. militaris extract could facilitate the synthesis of AgNPs.

Here, we construct a three-dimensional artificial nanoforest consisting of p-type narrow-band-gap CuO nanowires as tree trunks and polar facet regulatory n-type wide-band-gap ZnO nanodisks (NDs) as tree leaves through a two-step hydrothermal process on Cu mesh. Such heterostructure device performs a synergistic-effect enhanced photocatalytic activity with stable recyclability for the reduction of hexavalent chromium Cr(VI). The improved photocatalytic activity and durability were attributed to the well-steered transfer of photogenerated carriers accelerated by built-in electric field, the extension of solar absorption realized by bandgaps integrated heterostructure and proliferative active sites induced by ZnO NDs with high ratio of polar surface. This work provides a new approach to design versatile devices for solar energy conversion.

Myasthenia gravis (MG) is an autoimmune disease. A proportion of MG patients did not get satisfactory results after treatment with pyridostigmine and prednisone. Jia Wei Bu Zhong Yi Qi (Jia Wei BZYQ) decoction, a water extract from multiple herbs, has been demonstrated to be effective in the treatment of multiple “Qi deficiency type” diseases including MG in China. In this text, we investigated protein alterations in the plasma from healthy volunteers (C), MG patients without any treatment (T1), MG patients with routine western medical treatment (T2), and MG patients with combined treatments of Jia Wei BZYQ decoction and routine western medicines (T3) and identified some potential proteins involved in the pathogenesis and treatment of MG. iTRAQ (isobaric tags for relative and absolute quantitation) and 2D-LC-MS/MS (two-dimensional liquid chromatography-tandem mass spectrometry technologies) were employed to screen differentially expressed proteins. The identification, quantification, functional annotation, and interaction of proteins were analyzed by matching software and databases. In our project, 618 proteins were identified, among which 447 proteins had quantitative data. The number of differentially expressed proteins was 110, 117, 143, 115, 86, and 158 in T1 vs. C, T2 vs. C, T2 vs. T1, T3 vs. C, T3 vs. T1, and T3 vs. T2 groups, respectively. Functional annotation results showed that many differentially expressed proteins were closely associated with immune responses. For instance, some key proteins such as C-reactive protein, apolipoprotein C-III, apolipoprotein A-II, alpha-actinin-1, and thrombospondin-1 have been found to be abnormally expressed in T3 group compared to T1 group or T2 group. Interaction network analyses also provided some potential biomarkers or targets for MG management.

The most promising strategies to overcome bacterial drug resistance are the use of nanoparticles (NPs). In this paper, the extract of Gynostemma pentaphyllum Makino was prepared and used as reducing as well as stabilising agent to obtain silver NPs (AgNPs). The active phytochemicals present in the herb were responsible for the quick reduction in silver ion (Ag+) to metallic AgNPs (Ag0). The method is green and rapid, and the whole synthesis process can be finished within 15 min at 60°C. An intense surface plasmon resonance band in 420–450 nm range clearly revealed the formation of AgNPs. The obtained AgNPs were further characterised using X-ray diffraction, transmission electron microscopy (TEM), Fourier transform infrared (FTIR) spectroscopy and zeta potential. Moreover, the as prepared AgNPs have a superior antibacterial activity against four kinds of aquatic pathogenic bacteria, which shows great potential in aquaculture field.

The development of new type of antimicrobials without drug-resistence has increased exponentially. “One pot” green synthesis method was developed to synthesize the graphitic-phase C 3 N 4 (g-C 3 N 4 ) loaded with metal Ag nanoparticles (Ag NPs) using grape seed extract as reducing agent and stabilizing agent, which is rapid, economic and environmentally friendly. Ag NPs and g-C 3 N 4 sheets have strong interaction between Ag atoms and –C–N–, –C=N– bonds in g-C 3 N 4 sheets, resulting in successful deposition of AgNPs on g-C 3 N 4 sheets. The as-prepared g-C 3 N 4 /Ag nanocomposite shows better antibacterial activity than the green synthesized bare Ag NPs, showing great promise in application for new antibacterial material.

Making good use of food wastes is a challenging task. If the food waste can be reused, we can turn the waste into treasure. Grape seed is one kind of food waste and the extract was obtained by using water as extracting reagent in this paper. Using this kind of extract as reducing reagent and stabilizing reagent, silver nanoparticles (AgNPs) with high stability were biosynthesized within 10 min. The as prepared AgNPs were further confirmed by X-ray diffraction (XRD), transmission electron microscopy (TEM), Ultraviolet–visible (UV–vis) spectroscopy, Fourier transform infrared (FTIR) spectroscopy and Atomic force microscopy (AFM). The zeta potential of the obtained AgNPs was found to be −28.4 mV, indicating the dispersion and stability. Their antimicrobial activity against 8 kinds of pathogenic bacteria was also studied in detail. What interests us is that the as prepared AgNPs from grape wastes exhibit very good antibacterial activity against 4 kinds of ocean pathogenic bacteria, Vibrio alginolyticus, Vibrio anguillarum, Vibrio Parahaemolyticus and Aeromonas punctata, which shows that the NPs synthesized from grape seed extract may have great potential application in aquaculture. At last, the possible antibacterial mechanism was presented.

In terms of the uncertainties and incompleteness of alarm information in power grid fault diagnosis, this paper proposes a fault diagnosis method based on rough set combined with Bayesian network. Using the ability of rough set to reduce knowledge and process indeterminate information and mine fault information hierarchically, using the attribute reducing method based on cognizable matrix and information entropy, the optimal attribute reduction combination is extracted. Finally, by means of the reduction decision table formed by optimal attribute reduction combination, the Bayesian network model is built for parallel reasoning of each region, and the nodal probability is trained to achieve fault diagnosis. The experiment proves that this method can diagnose the fault rapidly and accurately, and has strong fault tolerance and adaptability.