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Fabrication of waterproof decorative paintings has attracted a great deal of interest. In this work, in situ reaction using poly(glycidyl methacrylate) (PGMA) and polyhedral oligomeric silsesquioxane with amino group at end (amino-POSS) was utilized to fabricate coatings at surfaces of papery/cloth decorative paintings via spray, which endowed the decorative paintings with excellent hydrophobicity, transparency, and weather ability. Firstly, ring opening of epoxy groups in PGMA, cross-linking structure in coatings, and strong coating/painting interface adhesion were achieved. Then, surface morphology of coatings was observed, and high surface roughness was confirmed. Next, high transparency and thermal stability of coatings were confirmed. Finally, surface water-contact-angles (WCAs) of coatings with various substrates were tested as a function of POSS content. Weathering resistances of coating surface on cloth substrate were studied. Coatings exhibit excellent properties such as high light transmittance (over 80%), high glass-transition temperature (upper limit ~ 113 ℃), high hydrophobicity (maximum WCA ~ 149°), and strong weathering resistances (the aged WCAs over 140°). Work innovation lies in simultaneously gained high hydrophobicity, good transparency, and strong weather ability. This work might pave a road for fabricating excellent coatings for protecting decorative paintings. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) is an important cause of death in young adults and children. Till now, the treatment of TBI in the short- and long-term complications is still a challenge. Our previous evidence implied aquaporin 4 (AQP4) and hypoxia inducible factor-1α (HIF-1α) might be potential targets for TBI. In this study, we explored the roles of AQP4 and HIF-1α on brain edema formation, neuronal damage and neurological functional deficits after TBI using the controlled cortical injury (CCI) model. The adult male Sprague Dawley rats were randomly divided into sham and TBI group, the latter group was further divided into neutralized-AQP4 antibody group, 2-methoxyestradiol (2-ME2) group, and their corresponding control, IgG and isotonic saline groups, respectively. Brain edema was examined by water content. Hippocampal neuronal injury was assessed by neuron loss and neuronal skeleton related protein expressions. Spatial learning and memory deficits were evaluated by Morris water maze test and memory-related proteins were detected by western blot. Our data showed that increased AQP4 protein level was closely correlated with severity of brain edema after TBI. Compared with that in the control group, both blockage of AQP4 with neutralized-AQP4 antibody and inhibition of HIF-1α with 2-ME2 for one-time treatment within 30–60 min post TBI significantly ameliorated brain edema on the 1st day post-TBI, and markedly alleviated hippocampal neuron loss and spatial learning and memory deficits on the 21st day post-TBI. In summary, our preliminary study revealed the short-term and long-term benefits of targeting HIF-1α-AQP4 axis after TBI, which may provide new clues for the selection of potential therapeutic targets for TBI in clinical practice. [ABSTRACT FROM AUTHOR]

Although the use of bioactive ions and proteins are crucial for bone defect repair, delivering them in a stable and controlled manner remains challenging. To achieve controlled delivery of osteogenic active factor, we developed a novel double network (DN) hydrogel capable of co-delivering Mg2+ ions and BMP2 in a controlled localized manner. This DN hydrogel was composed of poly (acrylamide) and chitosan, in which the poly (acrylamide) was cross-linked via covalent bond and the chitosan was grafted using bisphosphonate (BP) to form metal coordination bonds with Mg2+ ions. Due to this dynamic dissociation and re-association of the "BP-Mg2+" coordination bond, it was possible to deliver Mg2+ ions in a stable and controlled manner. Additionally, the obtained DN hydrogel exhibited an effective tensile strength (0.62 MPa), perfect stretchability (973% fracture strain), and good creep and recovery properties due to the dynamic cross-linking effect of "BP-Mg2+". Additionally, the hydrogel could synergistically promote the proliferation and differentiation of mouse embryo osteoblast precursor cells (MC3T3-E1 cells) in vitro via the BMP2/Wnt pathway. In the skull defect rat model, this positive delivery government of Mg2+ ions and BMP2 synergistically accelerated bone regeneration. In conclusion, this dynamic cross-linked hydrogel containing Mg2+ ions established a new platform for the sustained release of osteogenesis factor and accelerated the bone regeneration process. • The hydrogel was cross-linked by covalent and ions dynamic coordination bond. • The dissociation and re-association of the coordination bond enables Mg2+ ions to be delivered in controlled manner. • The sulfhydryl group of BMP2 protein can bind with Mg2+ ions to form the "S-Mg2+-S" coordination bond. • The cross-linked hydrogel became degraded to adapt new bone regeneration as the Mg2+ ions released outside. [ABSTRACT FROM AUTHOR]

The remote and non-invasive optical thermometer exploiting fluorescence intensity ratio technology is of great importance in various intelligent optoelectronic sensors. Dual-emitting YNbO 4 :Bi3+, Eu3+ phosphor is synthesized and investigated for the development of temperature sensing materials. The phosphor excited at 318 nm shows a blue broad band emission and several red sharp peaks. The value of Bi3+→Eu3+ energy transfer can reach 98.2% when Eu3+ doping content is 0.14. Benefiting from diverse thermal response behaviors due to Bi3+ and Eu3+ ions completely different electronic configurations, a dual-emitting optical thermometer is designed. The maximum values of absolute and relative sensitivities are as high as 2.51% K−1 at 473 K and 1.43% K−1 at 423 K, respectively. The thermochromic phosphor possesses a great chromaticity shift (ΔE = 317×10−3) with temperature. Based on superior color discriminability, visual colorimetry temperature measurement relied on thermal characteristic is proposed. All the results demonstrate that YNbO 4 :0.01Bi3+, 0.005Eu3+ phosphor as a sensitive and reliable optical thermometer has great potentials in temperature measurement. [ABSTRACT FROM AUTHOR]

Introduction/Aims: Many small‐sized, single‐center preclinical studies have investigated the benefits of introducing stem cells into the interior of nerve conduit. The aims of this meta‐analysis are to review and contrast the effects of various types of stem cells in in vivo models used to reconstruct peripheral nerve injuries (PNIs) and to assess the reliability and stability of the available evidence. Methods: A systematic search was conducted using Cochrane Library, Embase, PubMed, and Web of Science to identify studies conducted from January 1, 2000, to September 21, 2022, and investigate stem cell therapy in peripheral nerve reconstruction animal models. Studies that met the relevant criteria were deemed eligible for this meta‐analysis. Results: Fifty‐five preclinical studies with a total of 1234 animals were incorporated. Stem cells demonstrated a positive impact on peripheral nerve regeneration at different follow‐up times in the forest plots of five outcome indicators: compound muscle action potential (CMAP) amplitude, latency, muscle mass ratio, nerve conduction velocity, and sciatic functional index (SFI). In most comparisons, stem cell groups showed substantial differences compared with the control groups. The superior performance of adipose‐derived stem cells (ADSCs) in terms of SFI, CMAP amplitude, and latency (p <.001) was identified. Discussion: The findings consistently demonstrated a favorable outcome in the reconstruction process when utilizing different groups of stem cells, as opposed to control groups where stem cells were not employed. [ABSTRACT FROM AUTHOR]

At present, some studies have combined federated learning with blockchain, so that participants can conduct federated learning tasks under decentralized conditions, sharing and aggregating model parameters. However, these schemes do not take into account the trusted supervision of federated learning and the case of malicious node attacks. This paper introduces the concept of a trusted computing sandbox to solve this problem. A federated learning multi-task scheduling mechanism based on a trusted computing sandbox is designed and a decentralized trusted computing sandbox composed of computing resources provided by each participant is constructed as a state channel. The training process of the model is carried out in the channel and the malicious behavior is supervised by the smart contract, ensuring the data privacy of the participant node and the reliability of the calculation during the training process. In addition, considering the resource heterogeneity of participant nodes, the deep reinforcement learning method was used in this paper to solve the resource scheduling optimization problem in the process of constructing the state channel. The proposed algorithm aims to minimize the completion time of the system and improve the efficiency of the system while meeting the requirements of tasks on service quality as much as possible. Experimental results show that the proposed algorithm has better performance than the traditional heuristic algorithm and meta-heuristic algorithm. [ABSTRACT FROM AUTHOR]

Background: Total hip arthroplasty (THA) is a successful treatment for many hip diseases. Length of stay (LOS) and hospital cost are crucial parameters to quantify the medical efficacy and quality of unilateral primary THA patients. Clinical variables associated with LOS and hospital costs haven't been investigated thoroughly. Methods: The present study retrospectively explored the contributors of LOS and hospital costs among a total of 452 unilateral primary THA patients from January 2019 to January 2020. All patients received conventional in-house rehabilitation services within our institute prior to discharge. Outcome parameters included LOS and hospital cost while clinical variables included patient characteristics and procedural variables. Multivariable linear regression analysis was performed to assess the association between outcome parameters and clinical variables by controlling confounding factors. Moreover, we analyzed patients in two groups according to their diagnosis with femur neck fracture (FNF) (confine THA) or non-FNF (elective THA) separately. Results: Among all 452 eligible participants (266 females and 186 males; age 57.05 ± 15.99 year-old), 145 (32.08%) patients diagnosed with FNF and 307 (67.92%) diagnosed with non-FNF were analyzed separately. Multivariable linear regression analysis revealed that clinical variables including surgery duration, transfusion, and comorbidity (stroke) among the elective THA patients while the approach and comorbidities (stoke, diabetes mellitus, coronary heart disease) among the confine THA patients were associated with a prolonged LOS (P < 0.05). Variables including the American Society of Anesthesiologists classification (ASA), duration, blood loss, and transfusion among the elective THA while the approach, duration, blood loss, transfusion, catheter, and comorbidities (stoke and coronary heart disease) among the confine THA were associated with higher hospital cost (P < 0.05). The results revealed that variables were associated with LOS and hospital cost at different degrees among both elective and confine THA. Conclusions: Specific clinical variables of the patient characteristics and procedural variables are associated the LOS and hospital cost, which may be different between the elective and confine THA patients. The findings may indicate that evaluation and identification of detailed perioperative factors are beneficial in managing perioperative preparation, adjusting patients' anticipation, decreasing LOS, and reducing hospital cost. [ABSTRACT FROM AUTHOR]

• Metabolic alteration of articular cartilage is associated with pathogenesis of Osteoarthritis (OA). This study aims to identify the metabolism-related genes, corresponding transcription factors, and relevant pathways. We established a comprehensive network integrated with transcription factors, metabolism-related genes, and hallmarks. Metabolic alteration of articular cartilage is associated with the pathogenesis of Osteoarthritis (OA). This study aims to identify the metabolism-related genes, corresponding transcription factors (TFs), and relevant pathways. Overall, RNA sequencing profiles of articular cartilage were collected from the GEO database. Metabolism-related genes and OA-related hallmarks were collected from the MSigDB v7.1. Differential expression analysis, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and Gene Set Variation Analysis (GSVA) were conducted to identify pathways or hallmarks that were related to the pathogenesis of OA. The Pearson correlation analysis was used to establish the regulatory network among transcription factors, metabolism-related genes, and hallmarks. To further confirm the regulation of the identified transcription factors, Chromatin Immunoprecipitation-sequencing (ChIP-seq) was conducted, and single-cell sequencing was used to locate the cell clusters. Connectivity Map (CM) analysis were also conducted to identify the potential specific bioactive small molecules targeting the metabolic alteration of osteoarthritis. scTPA database was used to detect activated signaling pathways. Collectively, a total of 74 and 38 differentially expressed metabolism-related genes and TFs were retrieved. Skeletal system development, extracellular matrix, and cell adhesion molecule binding were important pathways in GO analysis. Human papillomavirus infection, PI3K-Akt signaling pathway, and Human T-cell leukemia virus 1 infection were the top 3 pathways in KEGG. 7 and 12 hallmarks were down- and up-regulated in GSVA, respectively. Ten bioactive small molecules may be potential treatments of OA by regulating the metabolism of articular cartilage. ChIP-seq analysis showed high relativity between transcription factors and their target genes. Furthermore, single-cell sequencing confirms the high expression of identified transcription factors in chondrocytes. To conclude, we established a comprehensive network integrated with transcription factors, metabolism-related genes, and hallmarks. [ABSTRACT FROM AUTHOR]

The healing of critical-sized bone defects is a major challenge in the field of bone tissue engineering. Gelatin-related hydrogels have emerged as a potential solution due to their desirable properties. However, their limited osteogenic, mechanical, and reactive oxygen species (ROS)-scavenging capabilities have hindered their clinical application. To overcome this issue, we developed a biofunctional gelatin-Mxene nanocomposite hydrogel. Firstly, we prepared two-dimensional (2D) Ti 3 C 2 MXene nanosheets using a layer delamination method. Secondly, these nanosheets were incorporated into a transglutaminase (TG) enzyme-containing gallic acid-imbedded gelatin (GGA) pre-gel solution to create an injectable GGA-MXene (GM) nanocomposite hydrogel. The GM hydrogels exhibited superior compressive strength (44–75.6 kPa) and modulus (24–44.5 kPa) compared to the GGA hydrogels. Additionally, the GM hydrogel demonstrated the ability to scavenge reactive oxygen species (OH- and DPPH radicals), protecting MC3T3-E1 cells from oxidative stress. GM hydrogels were non-toxic to MC3T3-E1 cells, increased alkaline phosphatase secretion, calcium nodule formation, and upregulated osteogenic gene expressions (ALP, OCN, and RUNX2). The GM400 hydrogel was implanted in critical-sized calvarial defects in rats. Remarkably, it exhibited significant potential for promoting new bone formation. These findings indicated that GM hydrogel could be a viable candidate for future clinical applications in the treatment of critical-sized bone defects. • The successful incorporation of MXene nanosheets into a GGA hydrogel • The hydrogel was formed with a mild, simple, and controllable enzymatic method. • Improved compressive strength and modulus • The hydrogel presented in vitro osteogenic and ROS-scavenging properties • Ability to promote rat critical-sized calvarial defects repair. [ABSTRACT FROM AUTHOR]

The key issue in the field of smart contract security is efficient and rapid vulnerability detection in smart contracts. Most of the existing detection methods can only detect the presence of vulnerabilities in the contract and can hardly identify their type. Furthermore, they have poor scalability. To resolve these issues, in this study, we developed a smart contract vulnerability detection model based on multi-task learning. By setting auxiliary tasks to learn more directional vulnerability features, the detection capability of the model was improved to realize the detection and recognition of vulnerabilities. The model is based on a hard-sharing design, which consists of two parts. First, the bottom sharing layer is mainly used to learn the semantic information of the input contract. The text representation is first transformed into a new vector by word and positional embedding, and then the neural network, based on an attention mechanism, is used to learn and extract the feature vector of the contract. Second, the task-specific layer is mainly employed to realize the functions of each task. A classical convolutional neural network was used to construct a classification model for each task that learns and extracts features from the shared layer for training to achieve their respective task objectives. The experimental results show that the model can better identify the types of vulnerabilities after adding the auxiliary vulnerability detection task. This model realizes the detection of vulnerabilities and recognizes three types of vulnerabilities. The multi-task model was observed to perform better and is less expensive than a single-task model in terms of time, computation, and storage. [ABSTRACT FROM AUTHOR]

To meet the execution requirements of delay-sensitive services in vehicular edge computing (VEC) networks, vehicular services need to be offloaded to edge computing nodes. For complex, large-scale services, the services need to be migrated if the services are not completed before the vehicles leave the coverage of edge computing nodes. Trust and resource matching between areas thus become major problems. This paper studies the decision model of vehicular service offloading and migration. First, software-defined network (SDN) technology is introduced into the traditional network architecture, and a two-layer distributed SDN-controlled VEC network architecture is designed, which is divided into a domain control layer and an area control layer. In this framework, we use the consortium blockchain as a carrier to share network topology information between SDN controllers to prevent information leakage. We then established a service offloading and migration optimization problem model to minimize service execution delay, reduce energy consumption and maximize the throughput of the blockchain system. We describe the problem model as a Markov Decision Process (MDP), introduce a deep reinforcement learning (DRL) algorithm named asynchronous advantage actor-critic (A3C) and design a dynamic service offloading and migration algorithm (DSOMA) based on A3C to solve the problem. Simulation results show that DSOMA can increase the throughput of the blockchain system, and DSOMA is superior to the deep Q-learning (DQN) algorithm and greedy offloading algorithm in reducing service execution delay and system energy consumption. [ABSTRACT FROM AUTHOR]

Researches on tunable luminescence and temperature sensitivity of phosphors have become an increasingly popular trend. This paper reports a series of Ca 2 YZr 2 Al 3 O 12 (CYZA):Bi3+, Sm3+ phosphors prepared by solid-state reaction. The phase purity, energy transfer, luminescent properties and temperature sensing performance of the phosphors have been carefully studied. CYZA:Bi3+, Sm3+ phosphors excited by ultraviolet light show tunable color emission, and the color shifts from dark blue to pink due to Bi3+→Sm3+ energy transfer. The related luminescent mechanism of phosphors is also explained. In addition, according to the different thermal sensitivity of Bi3+ and Sm3+, the temperature sensitivity of the phosphors is studied by fluorescence intensity ratio model. The maximum values of absolute sensitivity and relative sensitivity reach up to 0.099% K−1 at 423 K and 0.356% K−1 at 473 K, respectively. These findings indicate that CYZA:Bi3+, Sm3+ phosphors are potential candidates for tunable luminescence and temperature sensing. • The color-tunable property can be obtained in CYZA:Bi3+, Sm3+ phosphors. • Energy transfer from Bi3+ to Sm3+ ions. • Different thermal attenuation behaviors of Bi3+ and Sm3+ ions. • Temperature sensing performance is investigated by FIR model. [ABSTRACT FROM AUTHOR]

Mobile edge computing is a new computing paradigm, which pushes cloud computing capabilities away from the centralized cloud to the network edge to satisfy the increasing amounts of low-latency tasks. However, challenges such as service interruption caused by user mobility occur. In order to address this problem, in this article, we first propose a multiple service placement algorithm, which initializes the placement of each service according to the user's initial location and their service requests. Furthermore, we build a network model and propose a based on Lyapunov optimization method with long-term cost constraints. Considering the importance of user mobility, we use the Kalman filter to correct the user's location to improve the success rate of communication between the device and the server. Compared with the traditional scheme, extensive simulation results show that the dynamic service migration strategy can effectively improve the service efficiency of mobile edge computing in the user's mobile scene, reduce the delay of requesting terminal nodes, and reduce the service interruption caused by frequent user movement. [ABSTRACT FROM AUTHOR]

Vulnerability detection is important for smart contracts because of their immutable and irreversible features. In this work, a new detection method based on adversarial multi-task learning is proposed to improve the accuracy of existing vulnerability detection methods, which is based on the multi-task learning framework, including a shared part and a task-specific part. We optimize the multi-task learning frameworks and propose the mixed parameter sharing method to make each task not only maintain its uniqueness, but also share features with other tasks, which helps solve the problem that the hard parameter sharing method cannot constrain the underlying shared layer and improve the quality of extracted features. In addition, we introduce adversarial transfer learning to reduce noise pollution caused by the private feature and interference between the general feature and the private feature. We experimented on datasets obtained from our previous work, and the experimental results prove that our proposed model can judge whether there are vulnerabilities in smart contracts and then identify their types. Additionally, the results also show that our model effectively improves detection accuracy and has an advantage in performance over representative methods. [ABSTRACT FROM AUTHOR]

Osteoporosis is a common disease in elderly individuals, and osteoporosis can easily lead to bone and hip fractures that seriously endanger the health of elderly individuals. At present, the treatment of osteoporosis is mainly anti-osteoporosis drugs, but there are side effects associated with anti-osteoporosis drugs. Therefore, it is very important to develop early diagnostic indicators and new therapeutic drugs for the prevention and treatment of osteoporosis. Long noncoding RNAs (lncRNAs), noncoding RNAs longer than 200 nucleotides, can be used as diagnostic markers for osteoporosis, and lncRNAs play an important role in the progression of osteoporosis. Many studies have shown that lncRNAs can be the target of osteoporosis. Therefore, herein, the role of lncRNAs in osteoporosis is summarized, aiming to provide some information for the prevention and treatment of osteoporosis. [ABSTRACT FROM AUTHOR]

Background: Disturbance of brain iron metabolism after intracerebral hemorrhage (ICH) results in oxidative brain injury and cognition impairment. Hepcidin plays an important role in regulating iron metabolism, and we have reported that serum hepcidin is positively correlated with poor outcomes in patients with ICH. However, the roles of hepcidin in brain iron metabolism after ICH remain largely unknown.Methods: Parabiosis and ICH models combined with in vivo and in vitro experiments were used to investigate the roles of hepcidin in brain iron metabolism after ICH.Results: Increased hepcidin-25 was found in serum and primarily in astrocytes after ICH. The brain iron efflux, oxidative brain injury, and cognition impairment were improved in Hepc-/- ICH mice but aggravated by the human hepcidin-25 peptide in C57BL/6 ICH mice. Data obtained in in vitro studies showed that increased hepcidin inhibited the intracellular iron efflux of brain microvascular endothelial cells but was rescued by a hepcidin antagonist, fursultiamine. Using parabiosis ICH models also shows that increased serum hepcidin prevents brain iron efflux. In addition, Toll-like receptor 4 (TLR4)/MyD88 signaling pathway increased hepcidin expression by promoting interleukin-6 expression and signal transducer and activator of transcription 3 phosphorylation. TLR4-/- and MyD88-/- mice exhibited improvement in brain iron efflux at 7, 14, and 28 days after ICH, and the TLR4 antagonist (6R)-6-[N-(2-chloro-4-fluorophenyl) sulfamoyl] cyclohex-1-ene-1-carboxylate significantly decreased brain iron levels at days 14 and 28 after ICH and improved cognition impairment at day 28.Conclusions: The results presented here show that increased hepcidin expression caused by inflammation prevents brain iron efflux via inhibition of the intracellular iron efflux of brain microvascular endothelial cells entering into circulation and aggravating oxidative brain injury and cognition impairment, which identifies a mechanistic target for muting inflammation to promote brain iron efflux and to attenuate oxidative brain injury after ICH. [ABSTRACT FROM AUTHOR]

Berberine (BBR) has recently been reported to be extensively used for musculoskeletal disorders such as osteoporosis through enhancing osteogenic differentiation, inhibiting osteoclastogenesis and bone resorption and repressing adipogenesis. Although canonical Wnt signaling plays a crucial role in suppressing bone marrow-derived mesenchymal stem cells (MSCs) commitment to the chondrogenic and adipogenic lineage and enhancing osteogenic differentiation, no previous reports have shown an association between BBR-induced osteogenesis and Wnt/β-catenin signaling pathway. In this study, we aimed to investigate the stimulatory effect and the mechanism of BBR on osteogenic differentiation of human bone marrow-derived MSCs. MSCs were isolated from bone marrow specimens and treated with different concentration of BBR. Cell viability was measured by the WST-8 assay. Effects of BBR on osteogenic differentiation of MSCs were assessed by von Kossa staining, ALP staining and ALP activity. Osteogenic specific genes, chondrogenic and adipogenic related marker genes were determined by quantitative real-time polymerase chain reaction analysis. Western blot and Immunofluorescence staining were performed to analyze OCN and OPN, and β-catenin expression in the presence or absence of BBR combined with DKK-1 or β-catenin siRNA transfection. Increasing concentration of BBR (3, 10 and 30 μM) promoted osteogenic differentiation and osteogenic genes expression after incubation for various days compared with DMSO group, whereas expression levels of chondrogenic and adipogenic related marker genes were dramatically suppressed. After treated with 10 μM BBR for 7 days, β-catenin, OPN and OCN expression were significantly induced, which could be effectively suppressed by the addition of DKK-1 or β-catenin siRNA β-catenin. Interestingly, the expression level of Runx2 gene was also decreased by inhibiting the transduction of Wnt/β-catenin signaling. These findings suggest that BBR can stimulate osteogenic differentiation of MSCs not only by enhancing Runx2 expression but also by activating canonical Wnt/β-catenin signaling pathway, and canonical Wnt/β-catenin signaling pathway is in part responsible for BBR-induced osteogenic differentiation of MSCs in vitro. BBR is a potential pharmaceutical medicine by enhancing osteogenic differentiation for bone disorders, such as osteoporosis. [ABSTRACT FROM AUTHOR]

• UV photodetectors based on GaN/PSS/PANI hybrid heterojunction were fabricated. • The photodetector is self-powered, which can work at 0 V bias voltage. • The device can produce a high photocurrent of 2.05 μA in 60 ms under 365 nm light. • The performance of the device can be optimized with the thicknesses of PANI and PSS. A series of highly sensitive and self-powered ultraviolet (UV) photodetectors were prepared. The photodetectors adopt a p-i-n heterojunction structure composed of a layer of molecular beam epitaxy (MBE) grown n-type GaN, a layer of spin coated high resistance poly (styrenesulfonate) (PSS) and a layer of dip-coating applied p-type polyaniline (PANI) synthesized by oxidation reaction. The effects of the thickness of PSS and PANI on device performance were investigated. With the increase of PANI and PSS thickness, the photocurrent increases and reaches the highest value, and then decreases gradually with the further increase of their thickness. The optimized device can rapidly produce a photocurrent of 2.05 μA when illuminated with a 6.7 mW/cm2 UV light at 365 nm without any external power supply. This type of UV photodetector has potential applications in optoelectronics. [ABSTRACT FROM AUTHOR]

Background: Coronavirus disease 2019 (COVID-19) has broken out and spread rapidly nationwide at the beginning of 2020, which has brought huge impacts to people and work. The current situation of prevention and control is severe and urges guidance for clinicians, especially for medical systems. In the hope of providing a reference and recommendation for the prevention and control of the COVID-19, we carried out research to improve the quality of patient care and prevention during this epidemic. Methods: All of the staff were trained rapidly to master personal protection in our department. We reviewed the patients' discharged records who underwent surgery in our department during January 1 to March 1, 2019, and January 1 to March 1, 2020. The management of the surgery patients and flow charts were described and analyzed. Post-operation outcomes of the patients include duration, complications, surgical site infection (SSI), system infection, re-operation, and mortality. Both chi-squared test and Student's t test were performed to determine the relationship between the two periods in terms of post-operation outcomes. Results: Descriptive statistics analysis revealed that demographic of the patients between the two periods is similar. We had benefited from the strict flowcharts, smart robot, and protection equipment during the perioperative managements for orthopedic patients. With the help of the strict flow charts and smart equipment, post-operation outcomes of the patients revealed that the rates of the complications and re-operation had been reduced significantly (p < 0.05), while duration of operation, SSI, and system infection had no significant difference between two periods (p > 0.05). No patient and staff caught COVID-19 infection or mortality during the epidemic. Conclusions: Our study indicated that medical quality and efficiency were affected little with the help of strategies described above during the epidemic, which could be a reference tool for medical staff in routine clinical practice for admission of patients around the world. What is more, the provided strategies, which may evolve over time, could be used as empirical guidance and reference for orthopedic peers to get through the pandemic and ensure the normal operation of the hospital. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of this study is to identify the factors that influence the length of stay (LOS) in total knee arthroplasty (TKA) patients with an enhanced recovery after surgery (ERAS) program. Methods: Information from 167 patients (31 males and 136 females, range from 43 years to 88 years old) who underwent the unilateral elective primary TKA from January 2017 to January 2019 were reviewed retrospectively. Factors were analyzed by single-factor variance and multi-factor linear regression. Results: By single-factor variance analysis, American Society of Anesthesiologists (ASA) physical status classification system, pre-operation albumin, pre-operation erythrocyte sedimentation rate (ESR), primary and merge diseases, hidden blood loss, and length of operation were correlated with LOS (P < 0.05). Multi-factor linear regression results suggested that gender, ASA class, pre-operation Alb, and pre-operation ESR were associated with LOS (P < 0.05). Moreover, ASA class 3 (B value 4.84), pre-operation Alb < 30 g/L (B value 18.33), and pre-operation ESR > 15 mmol/h (B value 2.21) could increase the LOS, while males (B value − 3.56) had a shortened LOS. Conclusions: Overall, our research found that female, ASA class 3, pre-operation Alb < 30 g/L, and pre-operation ESR > 15 mmol/h could extend LOS in TKA patients with ERAS. [ABSTRACT FROM AUTHOR]