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Background Venous thromboembolism (VTE) is a potentially fatal complication after arthroplasty. Numerous prophylactic strategies and studies to reduce VTEs have focused on the duration of the hospital stay and on few extramural hospitals. This study aimed to investigate extramural hospital management of VTE after total hip/knee arthroplasty (THA/TKA) in China with a novel survey tool. Methods A total of 180 patients undergoing arthroplasty, including 68 THA patients and 112 TKA patients, were enrolled in this study. All patients received anticoagulant treatment management. A survey querying VTE management and adherence, such as therapy information, understanding of anticoagulation, satisfaction with the ability of medical staff, and satisfaction with health care costs, was administered by a questionnaire (TKA/THA Patients’ Experience with Anticoagulation in the Post-discharge Period) for quality improvement. Results The average age of the patients was 65.27 ± 13.62 years. All patients knew their follow-up times. 85 % of them were suggested that re-examine at the next 14 days, and the others at the next 28 days. All patients continued to visit the orthopaedic clinic after discharge without choosing other types of outpatient services, such as an anticoagulant clinic or home visit with a nurse/pharmacist or remote evaluation by telephone. A total of 96.6 % of all patients used new oral anticoagulants, and the most common treatment duration was 2–4 weeks (93.3 %). 48 % informed their physicians that they were taking anticoagulation medications when they visited ophthalmology, dentistry, dermatology, and other departments. The overall rate of satisfaction with anticoagulation management was 81.67 %, and 6.67 % of patients were not unsatisfied with their medical expenses. Patient compliance decreased with increasing follow-up time. Continuous follow-ups after discharge significantly improved patient compliance. Conclusions These results elucidate how we can improve the quality of anticoagulation. Continuous follow-up appointments for 30 days after discharge, especially for individuals over 65 years old, significantly improved patient satisfaction and reduced the incidence of VTE and medical costs.

Background Allergen identification is the first step for allergen-specific immunotherapy (AIT) of allergic rhinitis (AR). Currently, the diagnosis of AR is based mainly on the positive results of the skin prick test (SPT) and/or serum specific immunoglobulin E (sIgE) measurement. However, the results of these two tests may not always directly correlate with AR. Objective To investigate the importance of nasal provocation testing (NPT) in the diagnosis of Dermatophagoides pteronyssinus (Der p)-induced AR. Methods Rhinitis patients willing to undergo AIT (n = 171) were enrolled. The correlations of Der p SPT, sIgE, NPT, and clinical symptom severity were assessed. Results NPT-positive responses were more common in patients with higher SPT and sIgE levels. The optimal cut-off value for a NPT-positive response for SPT was 5.5 mm and for sIgE was 2.77 kUA/L, based on the respective receiver operating characteristic (ROC) curves. The area under the curve (AUC) of the ROCs was 0.814 (SPT only) and 0.794 (sIgE only) and increased to 0.828 with the combination of SPT and sIgE. The Der p-NPT concentration was inversely correlated with SPT and sIgE levels ( r = −0.477, P Conclusion For patients who are willing to receive Der p AIT, NPT is a useful and safe test to confirm diagnosis prior to treatment initiation, especially in patients with lower levels of Der p SPT (

To improve the clutter suppression performance of airborne radar in heterogeneous environment, a robust refined training sample reweighting space–time adaptive processing (STAP) method called RRSRW is proposed here. First, some target‐free training samples around the cell under test (CUT) are selected and the corresponding clutter dictionary matrices are constructed using the radar system parameters. Then, the clutter patch amplitudes and array error for selected training samples are simultaneously estimated through the formulated constrained least squares problem. Subsequently, based on the covariance matching estimation criterion, the local weighting coefficients for selected training samples are estimated by the redesigned convex optimisation problem. Finally, the STAP weight vector is calculated to process the CUT data. The proposed method is robust to array error and can effectively protect the moving targets in CUT data, which is free of hyper‐parameters and has global convergence properties. Simulation results demonstrate that the proposed RRSRW method can effectively suppress the strong ground clutter and greatly improve the detection performance of moving targets in heterogeneous environment.

Background To date, there are no generally recognized biomarkers for allergen immunotherapy (AIT) and even the changes in immunological indicators during AIT are inconsistent in different publications. Objective This study was conducted to quantify the immunological changes that occur during AIT and identify the determinants of heterogeneity. Methods Randomized controlled trials of AIT published in the past 10 years were searched in Medline, Embase and Cochrane CENTRAL. Data on immunological indicators were extracted, and the characteristics of the included studies were collected. Meta-analysis and meta-regression were conducted for each indicator. The study was registered on the PROSPERO website (CRD42020176127). Results We reviewed 1898 studies. Forty-six studies met the inclusion criteria, and 31 studies were included in the quantitative analyses. Subset analyses by time demonstrated that serum allergen-specific IgE (sIgE) of AIT patients increased in the first 12 months, then decreased and became slightly lower than that of control patients. Allergen-specific IgG4 (sIgG4) was elevated in the AIT group during and after treatment. IgE-blocking factor (IgE-BF) was increased and IgE-facilitated allergen binding (IgE-FAB) was reduced in AIT patients. Both of them of the 2 factors were associated with clinical efficacy in the multivariate regression analysis. sIgE/sIgG4 decreased in AIT patients, while there was no change in total IgE. Conclusion The levels of serum sIgE and sIgG4 during AIT showed a time-dependent pattern. IgE-BF and IgE-FAB should be further investigated as biomarkers for predicting and monitoring AIT efficacy.

To evaluate the feasibility and safety of endovascular recanalization for symptomatic subacute and chronic internal carotid artery occlusion (ICAO); to propose a newly modified radiographic classification of ICAO that can rigorously identify suitable candidates for endovascular ICAO treatment.We included 42 consecutive patients who had ICAO with ischaemic symptoms refractory to medical therapy. We examined the symptomatology, complications, follow-up results and radiographic images of ICAO receiving attempted endovascular treatment. We attempted to stratify all radiographic images into categories based on morphological occlusion patterns, occlusion segments and distal ICA reconstitution on digital subtraction angiography (DSA).Four types (A-D) of radiographic ICAO were identified. We redefined type B as having a tapered stump but no distal lumen. The rate of successful recanalization was 83.33% (35/42 ICAOs; type A, 18/20; type B, 7/10; type C, 10/11; type D, 0/1). The perioperative complication rate was 11.90% (5/42), including 3 asymptomatic distal embolisms, 1 symptomatic cerebral infarction and 1 asymptomatic carotid artery dissection. None of these technique-related complications led to severe neurological damage or death. Modified Rankin Scale (mRS) scores after 1-20 months of follow-up were significantly decreased in successfully revascularized patients (P0.001). There was no significant change in mRS scores in the 7 patients in whom recanalization failed (P0.05).Endovascular recanalization seems to achieve technical success and clinical improvement for symptomatic subacute and chronic ICAO. Additionally, our newly modified radiographic classification of ICAO may be valuable in assessing the technical feasibility and safety of procedures in symptomatic ICAO patients.

The adaptability of traffic lights in the control of vehicle traffic heavily affects the trafficability of vehicles and the travel efficiency of traffic participants in busy urban areas. Existing studies mainly have focused on the presence of traffic lights, but rarely evaluate the impact of traffic lights by analyzing traffic data, thus there is no solution for practicably and precisely self-regulating traffic lights. To address these issues, we propose a low-cost and fast traffic signal detection and impact assessment framework, which detects traffic lights from GPS trajectories and intersection features in a supervised way, and analyzes the impact range and time of traffic lights from intersection track data segments. The experimental results show that our approach gains the best AUC value of 0.95 under the ROC standard classification and indicates that the impact pattern of traffic lights at intersections is high related to the travel rule of traffic participants.

With the development of distributed energy microgrid and the interaction of multi-microgrid in the power market, optimizing the interactive price of multi-microgrid has become an important means to adjust network supply and demand and improve social benefits. The traditional physical model methods are widely used to solve the microgrid pricing problem. However, the calculation is growing sharply with the increase in the equipment number, and there is a lack of consideration of uncertainty in the traditional model. In this paper, a deep learning-based interactive pricing optimization method for multi-microgrid is proposed. Based on the deep learning method, an interactive encapsulation model for multi-microgrid is established. Uncertain factors are taken into account while improving the model accuracy, and the interactive pricing optimization strategy is optimized based on the model. The deep learning interaction model is applied in the retail market pricing scenario to optimize the interactive price under the interaction of multi-microgrid. The results show that the proposed interactive pricing method of multi-microgrid can optimize the interactive price based on the deep learning interactive model of multi-microgrid, avoid the deviation between the electricity consumption curve and the day-ahead curve, improve the economic benefits of both multi-microgrid and retailer, and provide a reference for the optimization of interactive pricing strategy of multi-microgrid.

Background Chlorhexidine and clindamycin, especially the latter, rarely cause anaphylaxis. Objective To report a rare case of chlorhexidine- and clindamycin-induced anaphylaxis. Methods Case report. Results A 21-year-old female experienced anaphylaxis after receiving intravenous clindamycin after a left big toe fracture fixation operation; she also had a similar reaction after using a mouthwash. Therefore, we suspected the culprit might be chlorhexidine, and the skin prick and serum specific IgE test results confirmed our suspicion. Then the clindamycin provocation test verified that the patient also had hypersensitivity to clindamycin. However, the allergy tests for penicillin and cefuroxime were negative. Conclusions Only four cases of clindamycin-induced anaphylaxis have been reported, and this is the first report of clindamycin-induced anaphylaxis verified by provocation test. The patient was given clindamycin because she was incorrectly labeled as having penicillin and cephalosporin allergies during the routine allergy test. It is essential to address this problem in China.

Dexamethasone is widely used to treat preterm labor and related diseases. However, prenatal dexamethasone treatment (PDT) can cause multiorgan developmental toxicities in offspring. Our previous study found that the occurrence of fetal-originated diseases was associated with adrenal developmental programming alterations in offspring. Here, we investigated the effects of PDT on adrenal function in offspring and its intrauterine programming mechanism. A rat model of PDT was established to observe the alterations of adrenal steroidogenesis in offspring. Furthermore, we confirmed the sex differences of adrenal steroidogenesis and its molecular mechanism combined with in vivo and in vitro experiments. PDT caused a decrease in adrenal steroidogenic function in fetal rats, but it was decreased in males and increased in females after birth. Meanwhile, the adrenal H3K14ac level and expression of 11β-hydroxysteroid dehydrogenase 2 (11β-HSD2) in PDT offspring were decreased in males and increased in females, suggesting that 11β-HSD2 might mediate sex differences in adrenal function. We further confirmed that dexamethasone inhibited the H3K14ac level and expression of 11β-HSD2 through the GR/SP1/p300 pathway. After bilateral testectomy or ovariectomy of adult PDT offspring rats, adrenal 11β-HSD2 expression and steroidogenic function were both reduced. Using rat primary fetal adrenal cells, the differential expression of AR and ERβ was proven to be involved in regulating the sex difference in 11β-HSD2 expression. This study demonstrated the sex difference in adrenal steroidogenic function of PDT offspring after birth and elucidated a sex hormone receptor-dependent epigenetically regulating mechanism for adrenal 11β-HSD2 programming alteration.

Obesity is an issue of great concern to people all over the world. It is accompanied by serious complications, leading to reduced quality of life and higher morbidity and mortality. Over the past few years, there has been an explosion in knowledge about the roles of potential therapeutic agents in obesity management. Among them, amino acid (AA) derivatives, such as taurine, glutathione (GSH), betaine, α-ketoglutarate (AKG), β-aminoisobutyric acid (BAIBA), and β-hydroxy-β-methylbutyrate (HMB), have recently gained popularity due to their beneficial effects on the promotion of weight loss and improvement in the lipid profile. The mechanisms of action of these derivatives mainly include inhibiting adipogenesis, increasing lipolysis, promoting brown/beige adipose tissue (BAT) development, and improving glucose metabolism. Therefore, this review summarizes these AA derivatives and the possible mechanisms responsible for their anti-obesity effects. Based on the current findings, these AA derivatives could be potential therapeutic agents for obesity and its related metabolic diseases.

Multibolt composite joints are widely used in aircraft structures. The determination of the pin-load distribution among the bolts is a critical step in the failure prediction of bolted joints. In this paper, a two-dimensional model of the multibolt composite structure is established for the pin-load distribution analysis. Its accuracy is validated by experimental results and the results from a 3D finite element model. Based on the determined pin-load distribution, FE models for a laminated plate with three-row fastener joints are built for failure prediction. Hashin stress criteria and the degradation guidelines of the material stiffness with respect to the different failure modes proposed by Tserpes are applied for the failure evaluation and the material degradation, respectively. The failure location and ultimate load are well predicted, which further validates the effectiveness and applicability of the proposed model for the pin-load distribution analysis.

In this work, three dimensional self-supported Co3O4@Ni3S2 nanowire arrays on nickel foam substrates are prepared by a multi-step method. The as-synthesized product harvests the advantages of the high electrical conductivity of the Co3O4 nanowire arrays, large surface area provided by the Ni3S2 nanosheets, and the efficient ion diffusion pathway offered by the self-supported structure. The sample is subsequently used as the electrode material for supercapacitors, at a current density of 2 mA cm−2 a charge storage capability of 2.41C cm−2 (5.5 F cm−2) was achieved. When the sample is charged and discharged at 50 mA cm−2 for 10000 cycles, a stable capacity of 0.86C cm−2 (1.5 F cm−2) can still be maintained at the end of the test. Such a performance is better than those values reported in the literature obtained with similar systems even at a lower current density. We also assemble an asymmetric supercapacitor by pairing the Co3O4@Ni3S2 nanoarrays with activated carbon, and it shows good cyclability over 10000 cycles. The device yields energy densities of 65 and 32.3 Wh kg−1 at power densities of 361 and 9090 W kg−1, respectively. Furthermore, it is able to light up 12 red light-emitting diodes, showing promising potential for practical applications.

Private query allows a client, Alice, to retrieve an item of a database hold by the server, Bob, without revealing which item he or she retrieved, while limiting his ability to access other items. In this paper, an efficient quantum private query (QPQ) protocol is proposed, where two oracle operations Ok, Od are utilized to encode the encryption keys and the encrypted data items into their corresponding quantum superposition states $\left | {\phi ^{\prime }} \right \rangle $ , $\left | {\psi ^{\prime }} \right \rangle $ , and the Grover iteration is also introduced to extract the target state $\left | {{d_{i}}^{\prime }} \right \rangle $ (i.e., the state of the encrypted data item Alice retrieved) from the superposition state. In order to guarantee the client’s privacy, the server Bob transmits all the encrypted data items of the database to the client Alice with oblivious transfer strategy. Compared with the previous qRAM-based or QKD-based QPQ protocols, our communication complexity (i.e., the number of transmitted qubits) is reduced from O(NlogN) or O(N) to O(logN), and the exchanged classical message is reduced from O(N) bits to O(logN) bits too. The security analysis shows our protocol can not only guarantee the server’s privacy but also the client’s privacy.

Offering a flexible paradigm for intelligently discovering, aggregating and processing big distributed data is a crucial requirement in large content-centric Internet. However, the major hindrances to this paradigm are network's dynamic feature, traffic balance, wired forwarding and the absence of cooperation between communications and computations. In this paper, we present a scalable Semantic Concast service on Named Data Networking (NDN) being considered as a promising paradigm for the future Internet. The service enables cooperation between data discovering, aggregating and processing among intermediate nodes for a user's Interest that contained a hierarchical name and semantic constraints. Specifically, multiple types and strategies of data aggregation and processing for combining and processing the positive data and suppressing the negative, futile data, as well as a determination of response completeness are introduced for enhancing relevant results recall and sharing. The experimentation demonstrated the Semantic Concast service can effectively improve service quality, reduce network traffic and shorten response time.

BackgroundSecondary Acute Myeloid Leukemia (S-AML) patients generally have a poor prognosis, and the chromosomal karyotype of S-AML have been rarely reported in the published literature. We aimed to explore the chromosomal karyotype and its clinical significance in patients with S-AML.MethodsClinical characteristics and chromosome karyotypes of 26 patients with S-AML were retrospectively analyzed. The overall survival (OS) was measured from the time of the patients’ transition to AML (which means the time of S-AML diagnosis) .ResultsAmong the 26 S-AML patients, there were 13 males and 13 females, with a median age of 63 years old (range, 20-77 years old). All of them were secondary to a variety of hematologic malignancies or solid tumors, and most of them were secondary to myelodysplastic syndrome (MDS). About 62% of the S-AML patients showed chromosome abnormalities. The level of serum lactate dehydrogenase (LDH) in S-AML patients with abnormal chromosome karyotype was higher than those with normal chromosome karyotype. Apart from the differences in treatment regimens, S-AML patients with chromosomal karyotype abnormalities had shorter OS (P

Objectives: The role of neuroinflammation in the pathogenesis of Alzheimer's disease (AD) has attracted much attention recently. Regulatory T-cells (Tregs) play an important role in modulating inflammation. We aimed to explore the Treg-related immunosuppression status at different stages of AD.Methods: Thirty healthy control (HC) subjects, 26 patients with mild cognitive impairment (MCI), 30 patients with mild probable AD-related dementia, and 28 patients with moderate-to-severe probable AD-related dementia underwent detailed clinical history taking, structural MRI scanning, and neuropsychological assessment. Peripheral blood samples were taken to measure the percentage of CD4+CD25+CD127low/− Tregs by flow cytometry and the levels of interleukin (IL-10), interleukin (IL-35), and transforming growth factor β (TGF-β) by ELISA.Results: The percentage of Tregs in the blood of MCI patients was the highest (9.24%); there was a significant difference between patients with MCI and patients with probable AD-related dementia. The level of TGF-β in patients with MCI (47.02 ng/ml) was significantly increased compared with patients with AD-related dementia. There were positive correlations between Treg percentage, IL-35, and Mini-mental state evaluation scores in patients with MCI and probable AD-related dementia.Conclusions: Patients with MCI have stronger Treg-related immunosuppression status compared with patients with probable AD-related dementia.

Renewable energy(RE) and energy storage system(ESS) are important parts for future integrated energy system(IES). The optimal operation of IESs faces great challenges with high percentage of RE with uncertainty and energy storage(ES) integration. However, the impact of uncertainty of RE output and ES modes on optimal operation of IES has not been clearly investigated yet. In this paper, an optimal operation method which takes the uncertainty of RE output into account is proposed. And the impact of ES modes on economics of IES is analysed. Firstly, the uncertainty model of RE and loads are established based on the probabilistic scenario method. And the IES model including ESS is proposed. Then the differential evolution(DE) optimization method is utilized to solve the optimal equipment capacity with minimum overall cost. Based on this, the second-order cone optimization method is applied to solve the optimal operation strategy. Moreover, the interactions of ES equipment in different modes including single ES and hybrid ES are investigated thoroughly. And the economics of IES under different ES modes are discussed in detail. Finally, the effectiveness and advantages of the proposed method are verified by simulations. And the suggestions on ES configuration are made.

Demand response(DR) and energy storage(ES) systems play important roles in future integrated energy system(IES). DR and ES need to be considered during the optimal operation of IES. In this paper, a bi-level coordinated optimization method of IES considering DR and ES is proposed, which bases on the genetic algorithm(GA) and improved second-order cone optimization method. Firstly, the models of renewable energy(RE), DR, ES and other devices of IES are established. Then the GA is used as the optimization method of the first-level optimization, which obtains the optimal equipment capacity. Next the second-order cone optimization method is used as the second-level optimization method. The optimal operation strategy is determined in this level. Moreover, the effect of DR and ES on optimal operation and economics of IES is studied. Finally, the validity and effectiveness of the proposed method are verified by simulations on the IES modified from the IEEE 33 node system.

The interactive operation of Microgrid (MG) in energy market is facing more and more incomplete information decision-making requirements due to the enhanced privacy of users, which brings great challenges to the participation flexibility of MG in demand response program. To address this problem, this paper proposes a novel LSTM recurrent neural network (RNN) based method for MG interactive operation, the proposed method uses LSTM-RNN to map the relationship between tie-line power and the available resources data outside of MG, and improves the prediction accuracy through iteratively learning of the accumulated operating data. On this basis, the interactive behaviour learning and interactive operation of MGs under incomplete information is effectively realized. The example analysis and test are carried out on a typical MG system, the validity of the proposed method is verified by comparing with traditional model-based method.

Background and purpose Prenatal caffeine exposure (PCE) can cause developmental toxicity of long bones in offspring, but the long-term effects and the underlying mechanism have not been fully clarified. Here, we investigated the effects of PCE peak bone mass accumulation and osteoporosis susceptibility in offspring and its intrauterine programming mechanism. Experimental approach Pregnant Wistar rats were administrated intragastrically with saline or caffeine (120 mg·kg-1 ·day-1 ) on gestational days 9-20. The serum and bone samples were collected from the fetal and postnatal offspring for bone mass, genes expression and corticosterone analysis. Then, rat bone marrow mesenchymal stem cells (BMSCs) were treated with corticosterone in vitro to confirm the molecular mechanism. Key results PCE caused fetal bone dysplasia in male and female offspring. In adulthood, PCE reduced peak bone mass and increased osteoporosis susceptibility in male offspring but not in females. Meanwhile, PCE only decreased the H3K9ac and expression levels of 11β-hydroxysteroid dehydrogenase 2 (11β-HSD2) before and after birth in the male offspring but not in the females. Moreover, the high level of corticosterone induced by PCE down-regulated the H3K9ac and expression levels of 11β-HSD2 through promoting glucocorticoid receptor (GR; NR3C1) into the nucleus of bone marrow mesenchymal stem cells (BMSCs) and recruiting histone deacetylase 11 (HDAC11) binding to 11β-HSD2 promoter region, which further enhanced the effect of corticosterone on suppressing osteogenic function of BMSCs. Conclusion and implications PCE caused osteoporosis susceptibility in male adult offspring, which attributed to the low-functional programming of 11β-HSD2 induced by corticosterone via GR/HDAC11 signalling.

An Internet-of-Things (IoT) system is generally composed of endpoint clients, network devices, and cloud servers. As such, data transfers in the network are full of security concerns. Besides, coming booming IoT applications will accelerate the network infrastructure to provide timely and safe information exchange services. Existing network could have a shortcoming of static key authentication. To enable an automatic key-update mechanism for IoT devices to enhance security in Machine-toĮMachine (M2M) communications, we implemented a lightweight key-update mechanism based on the libcoap library. Experimental results show that just 1.03% latency overhead is added for a better security performance.

ObjectiveTo explore the prevalence of diabetes mellitus in rural areas of central Hunan province, and to analyze the risk factors related to diabetes mellitus (DM).MethodsA cross-sectional study was conducted by using questionnaires (gender, age, occupation, degree of education, exercise habits, smoke status, alcohol consumption, hypertension, cardiovascular disease, family history of diabetes), anthropometric measurements (height, weight, waist circumference, blood pressure) and biochemical indexes test (fasting blood-glucose, glycosylated hemoglobin, blood lipids). Villagers over 40 years old from a community in rural areas of central Hunan Province were investigated.ResultsA total of 410 clinical data were collected. The prevalence of diabetes mellitus in 410 (177 in male and 233 in female) villagers was 13.41%, including 13 males with a prevalence rate of 7.34% and 42 females with a prevalence rate of 15.16%. The prevalence of impaired fasting glucose (IFG) was 11.95%, 21 males (11.86% of males) and 28 females (10.11% of females). And the results of glycosylated hemoglobin test showed that 64% villagers with diabetes mellitus had hemoglobin A1c(HbA1c) above 6.5%. Univariate analysis suggested that gender, smoke status, alcohol consumption, family history of diabetes mellitus, hypercholesterolemia and hypertension were involved in diabetes mellitus (PConclusionThe prevalence of diabetes mellitus in rural areas of central Hunan Province is higher. Family history of diabetes, hypercholesterolemia and hypertension are major risk factors for diabetes mellitus. The knowledge of diabetes should be strengthened. Related interventions should be given based on the diabetes epidemic status of local.

Resistance to therapeutic drugs occurs in virtually all types of cancers, and the tolerance to one drug frequently becomes broad therapy resistance; however, the underlying mechanism remains elusive. Combining a whole whole‐genome‐wide RNA interference screening and an evolutionary drug pressure model with MDA‐MB‐231 cells, it is found that enhanced protein damage clearance and reduced mitochondrial respiratory activity are responsible for cisplatin resistance. Screening drug‐resistant cancer cells and human patient‐derived organoids for breast and colon cancers with many anticancer drugs indicates that activation of mitochondrion protein import surveillance system enhances proteasome activity and minimizes caspase activation, leading to broad drug resistance that can be overcome by co‐treatment with a proteasome inhibitor, bortezomib. It is further demonstrated that cisplatin and bortezomib encapsulated into nanoparticle further enhance their therapeutic efficacy and alleviate side effects induced by drug combination treatment. These data demonstrate a feasibility for eliminating broad drug resistance by targeting its common mechanism to achieve effective therapy for multiple cancers., Many anticancer drugs can induce protein damage, which is a common way to kill cancer cells. Meanwhile, the damaged proteins trigger mitochondrial protein import surveillance checkpoint which impairs mitochondrial respiration activity, leading to the activation of proteasome and clearance of damaged proteins. This feedback loop triggers broad drug resistance, which is overcome by proteasome inhibitors.

To investigate the efficacy and safety of bencycloquidium bromide nasal spray (BCQB) in patients with persistent allergic rhinitis (PAR). We enrolled 720 patients from 15 hospitals across China and randomly assigned them into BCQB group or placebo group (90 μg per nostril qid) to receive a 4-week treatment. Visual analog scale (VAS) for rhinorrhea, sneezing, nasal congestion, itching and overall symptoms were recorded by patients every day. Anterior rhinoscopy scoring was completed by doctors on every visit. Adverse events were recorded in detail. A total of 354 and 351 patients were included in BCQB group and in placebo group. Baseline information was comparable. At the end of the trial, the decrease of VAS for rhinorrhea from baseline was 4.83 ± 2.35 and 2.46 ± 2.34 in BCQB group and placebo group, respectively (P

Background and Objective: Virus identification in electron microscopy (EM) images is considered as one of the front-line method in pathogen diagnosis and re-emerging infectious agents. However, the existing methods either focused on the detection of a single virus or required large amounts of manual labeling work to segment virus. In this work, we focus on the task of virus classification and propose an effective and simple method to identify different viruses. Methods: We put forward a residual mixed attention network (RMAN) for virus classification. The proposed network uses channel attention, bottom-up and top-down attention, and incorporates a residual architecture in an end-to-end training manner, which is suitable for dealing with EM virus images and reducing the burden of manual annotation. Results: We validate the proposed network through extensive experiments on a transmission electron microscopy virus image dataset. The top-1 error rate of our RMAN on 12 virus classes is 4.285%, which surpasses that of state-of-the-art networks and even human experts. In addition, the ablation study and the visualization of class activation mapping (CAM) further demonstrate the effectiveness of our method. Conclusions: The proposed automated method contributes to the development of medical virology, which provides virologists with a high-accuracy approach to recognize viruses as well as assist in the diagnosis of viruses.

Background. Monocytic myeloid-derived suppressor cells (M-MDSCs) characterized with the phenotype of CD14+HLA-DRlow/- have attracted a lot of attention in the field of human tumor immunology. However, little is known about the roles of M-MDSCs in acute myeloid leukemia (AML) as opposed to their multiple roles in solid tumors. Methods. We examined the frequencies of M-MDSCs identified for CD14+HLA-DRlow/- by flow cytometry in the peripheral circulating blood of 109 newly diagnosed adult patients with AML and 30 healthy controls (HC). Then, we, respectively, validated the clinic significance of circulating M-MDSCs on the relevance of spectral features for diagnostic stratification, induction therapy response, treatment effect maintenance, and long-term survival in AML. Results. Circulating M-MDSC frequencies of AML were significantly higher than those of HC both in CD14+ monocytes ( 46.22 % ± 2.95 % vs. 1.07 % ± 0.17 % , p < 0.01 ) and peripheral blood mononuclear cells (PBMCs) ( 4.21 % ± 0.80 % vs. 0.17 % ± 0.03 % , p < 0.01 ). Elevated circulating M-MDSCs in patients with AML were significantly associated with low complete remission (CR) rate, high relapse/refractory rate, and poor long-term survival, but had no correlation with common clinic risks and cytogenetic molecular risk categories. Conclusions. It was demonstrated that circulating M-MDSCs are elevated and associated with poor prognosis in AML, suggesting M-MDSCs might be a prognostic indicator for AML.

Hydrogen production and clean heating from renewable power are promising methods to promote renewable energy consumption and reduce carbon emission. This paper is concentrated on the cooperative planning and operation problems of Wind-Hydrogen-Heat multi-agent energy system. A cooperative planning and operative model for the Wind-Hydrogen-Heating multi-agent energy system is proposed based on the Nash bargaining game theory. This cooperative model is transformed into two subproblems on the alliance planning and operation cost minimization problem and the payment bargaining problem. To protect the privacy of each participant, two distributed algorithms are proposed based on the Alternating Direction Method of Multipliers to solve the two subproblems. Finally, the effectiveness of the proposed cooperative model and distributed algorithms are demonstrated. Simulation results demonstrate that the proposed cooperative model can improve the benefits of both each participant and the cooperative alliance significantly. Furthermore, the wind power curtailment can be reduced through cooperation. And the decline of feed-in tariff of wind power will incentivize the cooperation of Wind-Hydrogen-Heat agents to improve their own benefits.

We report a case of a previously well 58-year-old man, who presented with delirium and low GCS, and was found to have extreme hypernatraemia (Na+ = 191 mmol/L) and hyperglycaemia (glucose = 31 mmol/L). This resulted in a corrected serum sodium of 202 mmol/L. He was treated with fluid and electrolyte replacement in the intensive care unit, and had returned to essentially normal function by hospital discharge. The aetiology was believed to be due to severe dehydration and a new diagnosis of diabetes mellitus. Extreme hypernatraemia (serum sodium level greater than 190 mmol/L) is rare and associated with a high mortality. The mainstay of treatment is careful fluid and electrolyte management. Most recommendations advise to reduce the serum sodium by 0.5 mmol/L/hour, due to concerns over cerebral oedema; however, there are reports that slower correction is associated with higher mortality. In this case, the initial corrected sodium of 202 mmol/L was steadily corrected to 160 mmol/L over 91 hours, at a rate of 0.46 mmol/L/hour. This demonstrates the safety of the recommended approach.

High penetration of renewable energy could causes system frequency fluctuation of power flow and this significantly affects the power system operation. Control strategy of Flywheel and lithium battery hybrid energy storage system (HESS) is designed in this paper. An improved energy allocation strategy of grid-connected PV power smoothing strategy is designed. Coordinated control strategy is added to avoid the power output direction inconsistent of two kinds of storage, and consider energy storage SOC level simultaneously. This strategy effectively reduces the number of charge and discharge cycles of energy storage system(ESS). The strategy is applied to a demonstration project. Results show that the proposed coordinated control strategy can improve the life expectancy of the battery and reduce the operating cost.

The optimal planning and design of an integrated energy system (IES) is of great significance to facilitate distributed renewable energy (DRE) technology and improve the overall energy efficiency of the energy system. With the increased penetration of distributed generation (DG), the power supply and load sides of an IES present more increased levels of uncertainties. Demand response (DR) and the energy storage system (ESS) serve as important means to shift energy supply and use across time to counter the indeterminate variations. However, the current IES planning methods are unable to effectively deal with the uncertainties of DREs and loads, and to optimize the operations of DG-DR-ESS due to the enormous possible combinations. In this paper, a new method for the optimal planning and design of an integrated energy system has been introduced and verified. The new method consists of three integrated elements. First, the method of the probability scenario has been used to model the uncertainties of the DREs and loads so as to better characterize the impact of uncertainty on the planning and design of the IES. Secondly, the optimal operation of the IES under different probability scenarios is ensured using the second-order cone optimization for quick solutions due to the simplicity of this sub-problem, serving as the bottom-level optimization. Thirdly, the optimal planning and design of IES through optimal sizing of the power generating components and ESS are performed using a special meta-model based global optimization method due to the complex, black-box, and computation intensive nature of this top-level optimization in a nested, bi-level global optimization problem. The combined approach takes full account of the interrelated operations of DG-DR-ESS under different design configurations to support a better optimal planning and design of the IES. The simulation has been carried out on an IES system modified from the IEEE 33-node distribution system. The simulation results show that the proposed method and model are effective.

Fast Fourier transform (FFT) plays an important role in digital signal processing systems. In this study, the authors explore the very large-scale integration (VLSI) design of high-precision fixed-point reconfigurable FFT processor. To achieve high accuracy under the limited wordlength, this study analyses the quantisation noise in FFT computation and proposes the mixed use of multiple scaling approaches to compensate the noise. In addition, a statistics-based optimisation scheme is proposed to configure the scaling operations of the cascaded arithmetic blocks at each stage for yielding the most optimised accuracy for a given FFT length. On the basis of this approach, they further present a VLSI implementation of area-efficient and high-precision FFT processor, which can perform power-of-two FFT from 32 to 8192 points. By using the SMIC 0.13 μ m process, the area of the proposed FFT processor is 27 m m 2 with a maximum operating frequency of 400 MHz. When the FFT processor is configured to perform 8192-point FFT at 40 MHz, the signal-to-quantisation-noise ratio is up to 53.28 dB and the power consumption measured by post-layout simulation is 35.7 mW.

Owing to its up-conversion photoluminescence, photo-induced electron transfer property, and excellent conductivity, carbon quantum dots (CQDs) have been established as effective sensitizers in combination with Fe2O3 nanowires for enhancing the catalytic activity of photoelectrochemical water oxidation. In comparison to pristine Fe2O3 nanowires, Fe2O3 nanowires decorated with CQDs demonstrate 27 orders of magnitude increase in photocurrent density at 0.23 V vs. Ag/AgCl. The mechanism of enhanced photoelectrochemical activity of CQDs/Fe2O3 composite was also investigated. Thereby, it is confirmed that the enhanced optical absorption, accelerated interfacial charge carrier transfer and effective separation of photogenerated electron-hole pairs induced by CQDs decoration account for the enhancement of CQDs/Fe2O3 nanowire arrays in photoelectrochemical application.

CuSbS2 is regarded as a promising photo-absorber for solar energy conversion due to its proper bandgap, high absorptivity and earth abundance. Herein, novel low-cost ZnO/CdS/CuSbS2 core-shell nanowire arrays were constructed as photoanode for hydrogen evolution through non-aqueous electrodeposition and cation exchange. The nanowire demonstrates even and compact multilayer structure. The optimal ZnO/CdS/CuSbS2 photoanode achieves a photocurrent of 6.48 mA/cm2 at 0 V versus Ag/AgCl and the remarkable IPCE value with approximately 52% at 480 nm in an electrolyte solution containing 0.35 mol/L Na2SO3 and 0.25 mol/L Na2S. It also exhibited a good stability, maintained 87.9% of the initial current after 1 h measurement. The high performance benefits from well-crystalline and compact multilayer structure, high absorptivity of CuSbS2 and CdS, p-n junction formed between CdS and CuSbS2 which promotes the electron-hole separation and ZnO nanowire array as three dimensional scaffolds for electron percolation pathway. This work suggests the potential applications of low-cost p-n junction core-shell nanowire arrays as a highly efficient photoanode for hydrogen evolution in oil-field waste water with reductive sulfide.

In this paper, a reconfigurable architecture of CLEFIA block cipher which supports multi-configuration is proposed. Moreover, different generalized Feistel networks are integrated into a novel folding structure, which not only increases the circuit flexibility but also reduces the hardware overhead. Besides, the processes of generating intermediate key and encryption share the same circuit by time-division multiplexing technology to reduce the hardware resource consumption further. The proposed CLEFIA design is implemented in Artix-7 XC7A35 T FPGA board. Measurement results show that it can realize all the three CLEFIA configurations of key size, which are 128/192/256-bit, with a few resources of 1725 look-up-tables and 663 registers. At a clock frequency of 147 MHz, it also reaches high throughputs of 990 Mbps, 818 Mbps, and 696 Mbps in the three configurations respectively.

We introduce the term effective Verdet constant to describe the effect of spun fiber fabrication parameters on the Faraday polarization rotation sensitivity in response to a longitudinal magnetic field along the fiber. We obtain the expression of the effective Verdet constant of a spun fiber showing that it is always less than that of an ideal fiber free of birefringence by a factor relating to the ratio of spin twist rate to unspun fiber retardation per unit length. The larger the ratio, the closer the effective Verdet constant to that of the ideal fiber is. By measuring the polarization rotation in spun fibers with a highly accurate polarization analysis system made with binary polarization rotators, we experimentally obtain the effective Verdet constants of three different high birefringence spun fibers from three different manufactures at 1310 nm, with values of 1.07 × 10−6 rad/A, 1.05 × 10−6 rad/A, and 1.04 × 10−6 rad/A, respectively, which are 98%, 96%, and 95% of that of the ideal fused silica fiber free of birefringence. Our work is important for understanding the Faraday Effect in the spun optical fibers, as well as for quantifying the Faraday sensitivity of different spun fibers for electrical current and magnetic field sensing applications.

Human detection is a keyproblem in computer vision. Recently, some research has been focusing on the detection ofpedestrianusing infrared images. The infrared images have outstanding merit. It depends only on object's temperature, but not on color or texture. In this paper, the pedestrian crowd detection approach is proposed. The approach is compose of ROI blocks extraction and crowd block recognition. ROI blocks can be extracted with circle gradient operator and weighted geometric filtering. Crowd blocks are recognized by support vector machine, which combines histogram of oriented gradient and circle gradient. The experimental results show thatthe approach works effectively in different scenes.

Facing the issues for ineffective visible light utilization, insufficient separation of photogenerated electron-hole pairs of WO 3 photoanode, herein, ultrasmall MoS 2 quantum dots (QDs) are exploited as surface sensitizers to boost the photoelectrochemical (PEC) properties of MoS 2 /WO 3 . The MoS 2 /WO 3 photoanode is prepared by decorating 2D WO 3 nanoplatelet arrays with ultra-small MoS 2 QDs via a facile and effective assembly method. The interspersing of MoS 2 QDs, not only broadens the photoabsorption region, but also provides more active sites for the surface reactions and enhances charge separation of the photogenerated electron-hole pairs, leading to a 2.13-fold enhancement in photocurrent density at 1.0 V vs. Ag/AgCl (1.23 V vs. RHE). MoS 2 /WO 3 photoanodes hold potentialities for the straightforward building of molecular level devices for PEC production.

This study proposes an alternative input–output based spatial structural decomposition analysis to elucidate the importance of domestic regional heterogeneity and inter-regional spillover effects in determining China's regional CO 2 emissions growth. Our empirical results, based on the 2007 and 2010 Chinese inter-regional input–output tables, show that changes in most regions' final demand scale, final expenditure structure, and export scale have positive spatial spillover effects on other regions' CO 2 emissions growth; changes in most regions' consumption and export preference help reduce other regions' CO 2 emissions; changes in production technology and investment preferences may exert positive or negative effects on other region's CO 2 emissions growth through domestic supply chains. For some regions, the aggregate spillover effect from other regions may be larger than the intra-regional effect in determining regional emissions growth. All these facts can significantly help provide a better, deeper understanding of the driving forces behind the growth of regional CO 2 emissions and can thus enrich the policy implications concerning a narrow definition of “carbon leakage” through domestic inter-regional “trade” as well as a relevant political consensus about responsibility sharing between developed and developing regions inside China.

Prenatal nicotine exposure (PNE) induces developmental toxicity in offspring. However, the long-term harmful effects on bone development and the intrauterine programming mechanism attributed to PNE remain unclear. In the present research, pregnant Wistar rats were injected subcutaneously with nicotine (2 mg/kg/d) to obtain and analyze bone samples from the fetal and adult offspring. Bone marrow mesenchymal stem cells (BMSCs) were treated with nicotine during osteogenic differentiation to clarify the related molecular mechanisms. The results indicated that PNE led to bone dysplasia in the fetuses and reduced bone mass in the adult offspring, which was mediated by the sustained activation of the local bone renin angiotensin system (RAS) and suppressed osteogenic differentiation before and after birth. In vitro, nicotine suppressed BMSCs' osteogenic function through promoting angiotensin-converting enzyme (ACE) expression and activating RAS. Furthermore, nicotine induced histone acetylase p300 into the nuclei of the BMSCs by acting on the α4β2-nicotinic acetylcholine receptor (α4β2-nAChR), leading to the increased histone 3 lysine 9 acetylation level of ACE and RAS activation. Taken together, the sustained activation of local bone RAS mediated prenatal nicotine-induced osteopenia in adult offspring via the α4β2-nAChR-p300-ACE pathway.-Xiao, H., Wen, Y., Pan, Z., Shangguan, Y., Magdalou, J., Wang, H., Chen, L. Nicotine exposure during pregnancy programs osteopenia in male offspring rats via α4β2-nAChR-p300-ACE pathway.

Multi-terminal flexible structure can interconnect multiple AC systems through DC network, which can fundamentally change the original structure of traditional power grid. However, with the increasing penetration of distributed generation (DG), the quality of DC voltage has been widely concerned. In this paper, the equivalent model of DC load group is analyzed, and the complete model of multi-terminal DC (MTDC) system is constructed, and as a result the discrete state equation is deduced. On this basis, considering the effect of voltage control and the capacity of voltage source converter (VSC), a centralized coordinated control method of variable droop gains based on model predictive control (MPC) is designed. The problem of voltage fluctuation is solved by minimizing the deviation between the predicted voltage and the rated voltage of each VSC. According to the different power margin of the converter station, the droop gains is adjusted in real time without changing the operation mode of the converter station, so that the converter station can participate in the power regulation flexibly according to its power distribution ability to achieve the optimal power distribution.

In order to fast and accurately extract the star centroid from high-resolution satellite imageries, this paper presents an algorithm-hardware design of real-time star centroid for deep space exploration missions. First, a block threshold segmentation method is proposed to eliminate the stray light effects in different regions. Then, an optimized one-scan centroid extraction algorithm with label combination is proposed for detecting complex star patterns and extracting its centroid. Moreover, we present an FPGA-based hardware architecture for the proposed algorithm. Experimental results show that the proposed algorithm-hardware design enables accurate and real-time star centroid extraction.

The task of re-identifying groups of people underdifferent camera views is an important yet less-studied problem.Group re-identification (Re-ID) is a very challenging task sinceit is not only adversely affected by common issues in traditionalsingle object Re-ID problems such as viewpoint and human posevariations, but it also suffers from changes in group layout andgroup membership. In this paper, we propose a novel conceptof group granularity by characterizing a group image by multi-grained objects: individual persons and sub-groups of two andthree people within a group. To achieve robust group Re-ID,we first introduce multi-grained representations which can beextracted via the development of two separate schemes, i.e. onewith hand-crafted descriptors and another with deep neuralnetworks. The proposed representation seeks to characterize bothappearance and spatial relations of multi-grained objects, and isfurther equipped with importance weights which capture varia-tions in intra-group dynamics. Optimal group-wise matching isfacilitated by a multi-order matching process which in turn,dynamically updates the importance weights in iterative fashion.We evaluated on three multi-camera group datasets containingcomplex scenarios and large dynamics, with experimental resultsdemonstrating the effectiveness of our approach. The published dataset can be found in \url{http://min.sjtu.edu.cn/lwydemo/GroupReID.html}, 14 pages, 10 figures, to appear in IEEE transaction on Cybernetics

Pericardial involvement of multiple myeloma is a rare and late-stage complication, with only a few cases reported in the literature. PET/CT has demonstrated a growing role in the diagnosis and follow-up of patients with multiple myeloma. We present a case of pericardial multiple myeloma in a patient with relapsed/refractory disease, showcasing previously unpublished FDG PET/CT findings.

As a classical artificial intelligence algorithm, the convolutional neural network (CNN) algorithm plays an important role in image recognition and classification and is gradually being applied in the Internet of Things (IoT) system. A compact CNN accelerator for the IoT endpoint System-on-Chip (SoC) is proposed in this paper to meet the needs of CNN computations. Based on analysis of the CNN structure, basic functional modules of CNN such as convolution circuit and pooling circuit with a low data bandwidth and a smaller area are designed, and an accelerator is constructed in the form of four acceleration chains. After the acceleration unit design is completed, the Cortex-M3 is used to construct a verification SoC and the designed verification platform is implemented on the FPGA to evaluate the resource consumption and performance analysis of the CNN accelerator. The CNN accelerator achieved a throughput of 6.54 GOPS (giga operations per second) by consuming 4901 LUTs without using any hardware multipliers. The comparison shows that the compact accelerator proposed in this paper makes the CNN computational power of the SoC based on the Cortex-M3 kernel two times higher than the quad-core Cortex-A7 SoC and 67% of the computational power of eight-core Cortex-A53 SoC.

With the development of information society, Recommendation System has been an import tool to help users filter information and create more economic value for enterprises. However, it is difficult for traditional recommendation systems to interpret recommendation results. In order to improve users’ trust in recommendation results, interpretable recommendation models have attracted more and more attention. In this paper, we present the Explanation Chains Model based on the Fine-grained Data (F-ECM) to enhance the effectiveness of recommendation while achieving the interpretability of recommendation. First, we generate parsing trees from user comments and extract three key sentence structure information (i.e., aspects, features and sentiment tendency) from those generated parsing tree. The fine-grained similarity is computed based on the aspects and features of the products to be recommended, and users’ product satisfaction is predicted by combining sentiment tendency. Then the recommendation chain will be constructed according to the satisfaction degree in the recommendation list. Finally, we calculate recommendation chain scores of all the items to be recommended to the target user, generate the recommendation results and personal explanation for the user by the recommendation chains. Experiments in the Amazon data set show that the Explanation Chains Model based on the Fine-grained Data achieve better interpretability and performance of product recommendation systems.