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Spinal cord injury (SCI) is a serious and disabling disease with a high mortality rate. It often leads to complete or partial sensory and motor dysfunction and is accompanied by a series of secondary outcomes, such as pressure sores, pulmonary infections, deep vein thrombosis in the lower extremities, urinary tract infections, and autonomic dysfunction. Currently, the main treatments for SCI include surgical decompression, drug therapy, and postoperative rehabilitation. Studies have shown that cell therapy plays a beneficial role in the treatment of SCI. Nonetheless, there is controversy regarding the therapeutic effect of cell transplantation in SCI models. Meanwhile exosomes, as a new therapeutic medium for regenerative medicine, possess the advantages of small size, low immunogenicity, and the ability to cross the blood-spinal cord barrier. Certain studies have shown that stem cell-derived exosomes have anti-inflammatory effects and can play an irreplaceable role in the treatment of SCI. In this case, it is difficult for a single treatment method to play an effective role in the repair of neural tissue after SCI. The combination of biomaterial scaffolds and exosomes can better transfer and fix exosomes to the injury site and improve their survival rate. This paper first reviews the current research status of stem cell-derived exosomes and biomaterial scaffolds in the treatment of SCI respectively, and then describes the application of exosomes combined with biomaterial scaffolds in the treatment of SCI, as well as the challenges and prospects.

Herein, we report a Rh(iii)-catalyzed C–H functionalization of indoles at the C4 position with alkylidenecyclopropanes (ACPs).

The DSCG, GelMA, and MenSCs were cross-linked by photoinitiators under UV irradiation to make composite scaffolds. The MenSC-encapsulated composite scaffolds were then transplanted into a rat model with complete spinal cord transection.

An indazolone-directed chemoselective synthesis of 8H-indazolo [1,2-a]cinnolines has been realized via a cascade Cp*Ir(iii)- and Cp*Rh(iii)-catalyzed C–H activation/cyclization reaction of 1-arylindazolones with sulfoxonium ylides.

Optical macroscopic imaging techniques have shown great significance in the investigations of biomedical issues by revealing structural or functional information of living bodies through the detection of visible or near-infrared light derived from different mechanisms. However, optical macroscopic imaging techniques suffer from poor spatial resolution due to photon diffusion in biological tissues. This dramatically restricts the application of optical imaging techniques in numerous situations. In this paper, an image restoration method based on deep learning is proposed to eliminate the blur caused by photon diffusion in optical macroscopic imaging. Two blurry images captured at orthogonal angles are used as the additional information to ensure the uniqueness of the solution and restore the small targets at deep locations. Then a fully convolutional neural network is proposed to accomplish the image restoration, which consists of three sectors: V-shaped network for central view, V-shaped network for side views, and synthetical path. The two V-shaped networks are concatenated to the synthetical path with skip connections to generate the output image. Simulations as well as phantom and mouse experiments are implemented. Results indicate the effectiveness of the proposed method.

Coal gangue is the main solid waste in coal mining areas, and its annual emissions account for about 10% of coal production. The composition information of coal gangue is the basis of reasonable utilization of coal gangue, and according to the composition information of coal gangue, one can choose the appropriate application scene. The reasonable utilization of coal gangue can not only effectively alleviate the environmental problems in mining areas but also produce significant economic and social benefits. Chemical analysis techniques are the principal ones used in traditional coal gangue analysis; however, they are slow and expensive. Many researchers have used machine learning techniques to analyze the spectral data of coal gangue, primarily random forests (RFs), extreme learning machines (ELMs), and two-hidden-layer extreme learning machines (TELMs). However, these techniques are heavily reliant on the preprocessing of the spectral data. This research suggests a quick analysis approach for coal gangue based on thermal infrared spectroscopy and deep learning in light of the drawbacks of the aforementioned methodologies. The proposed deep learning model is named SR-TELM, which extracts spectral features using a convolutional neural network (CNN) consisting of a spatial attention mechanism and residual connections and implements content prediction with TELM as a regressor, which can effectively overcome the dependence on preprocessing. The usefulness and speed of SR-TELM in coal gangue analysis were demonstrated by comparing several models in order to verify the proposed coal gangue analysis model. The experimental findings show that, for the prediction tasks of moisture, ash, volatile matter, and fixed carbon content, respectively, the SR-TELM model attained an R2 of 0.947, 0.972, 0.967, and 0.981 and an RMSE of 0.274, 4.040, 1.567, and 2.557 with a test time of just 0.03 s. It offers a method for the analysis of coal gangue that is low cost, highly effective, and highly reliable.

The pace of nanomaterial discovery for high-performance electrocatalysts could be accelerated by the development of efficient screening methods. However, conventional electrochemical characterization via drop-casting is inherently inaccurate and time-consuming, as such ensemble measurements are serially performed through nanocatalyst synthesis, morphological characterization, and performance testing. Herein, we propose a rapid electrochemical screening method for bimetallic electrocatalysts that combines nanoparticle (NP) preparation and performance testing at the single NP level, thus avoiding any inhomogeneous averaging contribution. We employed single NP collision electrochemistry to realize in situ electrodeposition of a precisely tunable Pt shell onto individual parent NPs, followed by instantaneous electrocatalytic measurement of the newborn bimetallic core-shell NPs. We demonstrated the utility of this approach by screening bimetallic Au-Pt NPs and Ag-Pt NPs, thereby exhibiting promising electrocatalytic activity at optimal atomic ratios for methanol oxidation and oxygen reduction reactions, respectively. This work provides a new insight for the rapid screening of other bimetallic electrocatalysts.

Spinal cord injury (SCI), as a serious disabling disease, is still haunted by lacking of effective treatments. We previously found that transplantation of menstrual blood-derived mesenchymal stem cells (MenSCs) promoted axon regeneration in rats with SCI, while the abominable microenvironment after the SCI inhibited the survival of stem cells after transplantation. Biomaterials can support the activity of stem cells and accelerate the functional reconstruction of the injured spinal cord. In this study, we constructed a novel composite scaffold consisting of the decellularized spinal cord extracellular matrix-gel (DSCG) and the GelMA hydrogel, which harbored high water retention, wettability, degradability and soft mechanical property.

Spinal cord injury (SCI) leads to severe loss of motor and sensory functions, and the rehabilitation of SCI is a worldwide problem. Tissue-engineered scaffolds offer new hope for SCI patients, while the newly developed materials encountered a challenge in modeling the microenvironment around the lesion site. We constructed a new composite scaffold by mixing decellularized spinal cord extracellular matrix (dECM) with gelatin methacryloyl (GelMA). The dECM, as a natural biological material, retained a large number of proteins and growth factors related to neurogenesis. GelMA was a photopolymerizable material, harbored a polymer network structure, soft texture, certain shape and plenty of water. The viability, proliferation, and differentiation of neural stem cells (NSCs) on the composite scaffold were evaluated by cell count kit-8 (CCK8), Live/Dead assay, phalloidin staining, 5-Ethynyl-2'-deoxyurdine (EdU), immunofluorescence staining and western blot. The Live/Dead assay, phalloidin staining, EdU, and CCK8 assay showed that the composite scaffold had good biocompatibility and provided better support for proliferation of NSCs. Results of immunocytochemistry and western blot showed that the composite scaffolds promoted the specific differentiation of NSCs into neuron cells. Together, this dECM/GelMA composite scaffold can be used as a cell culture coating, the isolated NSCs seeded on the surface of composite scaffold expressed neuronal markers and assumed neuronal morphology. Our work provided a new method that would be widely used in tissue engineering of SCI.

Transcriptional regulatory protein (TRP)-based whole-cell biosensors are widely used nowadays. Here, they were demonstrated to have great potential application in screening cell efflux and influx pumps for small molecules. First, a vanillin whole-cell biosensor was developed by altering the specificity of a TRP, VanR, and strains with improved vanillin productions that were selected from a random genome mutagenesis library by using this biosensor as a high-throughput screening tool. A high intracellular vanillin concentration was found to accumulate due to the inactivation of the AcrA protein, indicating the involvement of this protein in vanillin efflux. Then, the application of this biosensor was extended to explore efflux and influx pumps, combined with directed genome evolution. Elevated intracellular vanillin levels resulting from efflux pump inactivation or influx pump overexpression could be rapidly detected by the whole-cell biosensor, markedly facilitating the identification of genome targets related to small-molecule transmembrane transport, which is of great importance in metabolic engineering.

The rapid mutation and spread of SARS-CoV-2 variants recently, especially through the emerging variants Omicron BA5, BF7, XBB and BQ1, necessitate the development of universal vaccines to provide broad spectrum protection against variants. For the SARS-CoV-2 universal recombinant protein vaccines, an effective approach is necessary to design broad-spectrum antigens and combine them with novel adjuvants that can induce high immunogenicity. In this study, we designed a novel targeted retinoic acid-inducible gene-I (RIG-I) receptor 5′triphosphate double strain RNA (5′PPP dsRNA)-based vaccine adjuvant (named AT149) and combined it with the SARS-CoV-2 Delta and Omicron chimeric RBD-dimer recombinant protein (D-O RBD) to immunize mice. The results showed that AT149 activated the P65 NF-κB signaling pathway, which subsequently activated the interferon signal pathway by targeting the RIG-I receptor. The D-O RBD + AT149 and D-O RBD + aluminum hydroxide adjuvant (Al) + AT149 groups showed elevated levels of neutralizing antibodies against the authentic Delta variant, and Omicron subvariants, BA1, BA5, and BF7, pseudovirus BQ1.1, and XBB compared with D-O RBD + Al and D-O RBD + Al + CpG7909/Poly (I:C) groups at 14 d after the second immunization, respectively. In addition, D-O RBD + AT149 and D-O RBD + Al + AT149 groups presented higher levels of the T-cell-secreted IFN-γ immune response. Overall, we designed a novel targeted RIG-I receptor 5′PPP dsRNA-based vaccine adjuvant to significantly improve the immunogenicity and broad spectrum of the SARS-CoV-2 recombinant protein vaccine.

The complete removal of tetracycline residuals under visible light still is a challenging task because of their robust ring structure. To tackle this issue, we explore a novel Bi2O3-sensitized TiO2 visible-light photocatalyst by combining p-n heterojunction with hollow structure. The hollow TiO2/Bi2O3 photocatalyst manifests excellent photocatalytic performance and recyclability toward the complete degradation (100%) of antibiotics under visible light (λ > 420 nm) because of the synergistic effect of p-n heterojunction and hollow structure, successfully overcoming the challenge of the incomplete removal of antibiotics over almost all of the reported visible-light photocatalysts. Additionally, the effects of inorganic ions, pH value, water matrix, and outdoor light on the degradation of tetracyclines were investigated with many details. Notably, the degradation pathways and mechanism of tetracycline were revealed according to trapping experiments, HPLC-MS, and photoelectrochemical characterizations. Therefore, this work provides a new insight into developing visible-light photocatalysts with excellent photocatalytic performances for the complete removal of other refractory contaminants.

Ensemble-averaging measurements mask the link between the electrochemical performances and the intrinsic properties of an individual because of its inhomogeneity and heterogeneity. Single entity collision electrochemistry has been used to investigate the electrochemical behaviors of free-diffused individual entities during their collisions at ultramicroelectrodes. However, the dynamic behavior of an individual is closely related to the electrochemical reaction process. Therefore, the studies on the electrochemical behavior of individual entities can real-time obtain the dynamic electrochemical reaction information of individual entities at the electrode interface, in order to understand the dynamic transfer process of charges or electrons at the electrode interface. In this review, we summarize dynamic electrochemical behaviors of individual entities. We first introduce dynamic electrochemical reaction process based on the transient current response generated by collision event from a single nanoparticle at the electrode surface, and then extend to the dynamic electrochemical behavior of other entities. Furthermore, optical visualization has been combined with the stochastic collision electrochemical measurement as a high spatial- and temporal-resolved method to generate a full picture of single entity dynamic electrochemical reaction mechanism/dynamics with sufficient information. Finally, the main scientific challenging and future research concerning in this field are proposed.

Bioluminescence tomography (BLT) is a promising pre-clinical imaging technique for a wide variety of biomedical applications, which can non-invasively reveal functional activities inside living animal bodies through the detection of visible or near-infrared light produced by bioluminescent reactions. Recently, reconstruction approaches based on deep learning have shown great potential in optical tomography modalities. However, these reports only generate data with stationary patterns of constant target number, shape, and size. The neural networks trained by these data sets are difficult to reconstruct the patterns outside the data sets. This will tremendously restrict the applications of deep learning in optical tomography reconstruction. To address this problem, a self-training strategy is proposed for BLT reconstruction in this paper. The proposed strategy can fast generate large-scale BLT data sets with random target numbers, shapes, and sizes through an algorithm named random seed growth algorithm and the neural network is automatically self-trained. In addition, the proposed strategy uses the neural network to build a map between photon densities on surface and inside the imaged object rather than an end-to-end neural network that directly infers the distribution of sources from the photon density on surface. The map of photon density is further converted into the distribution of sources through the multiplication with stiffness matrix. Simulation, phantom, and mouse studies are carried out. Results show the availability of the proposed self-training strategy.

The biosynthetic efficiency of curcumin, a highly bioactive compound from the plant Curcuma longa, needs to be improved. In this study, we performed host cell and biosynthetic pathway engineering to improve curcumin biosynthesis. Using in vivo-directed evolution, the expression level of curcuminoid synthase (CUS), the rate-limiting enzyme in the curcumin biosynthetic pathway, was significantly improved. Furthermore, as curcumin is a highly hydrophobic compound, two cell membrane engineering strategies were applied to optimize the biosynthetic efficiency. Curcumin storage was increased by overexpression of monoglucosyldiacylglycerol synthase from Acholeplasma laidlawii, which optimized the cell membrane morphology. Furthermore, unsaturated fatty acid supplementation was used to enhance membrane fluidity, which greatly ameliorated the damaging effect of curcumin on the cell membrane. These two strategies enhanced curcumin biosynthesis and demonstrated an additive effect.

Mitochondrial dynamics plays a crucial role in tubular injury in diabetic kidney disease (DKD). Asiatic acid (AA) has demonstrated renal protective effects in DKD; however, its therapeutic effect on tubular injury in DKD remains unclear.This study aimed to verify the effects of AA on tubular injury in DKD and underlying mechanisms.In the present study, the effects of AA on tubular injury were assessed in rats with streptozotocin-induced diabetes and advanced glycation end products (AGEs)-stimulated HK-2 cells models.After oral administration with or without AA for ten weeks, body weight and levels of fast blood glucose, serum creatinine (sCr), blood urea nitrogen (BUN), urinary albumin, and kidney injury molecule-1 (KIM-1) were detected. Histological analysis was performed to evaluate the renal function of rats. Moreover, the expression of proteins associated with the Nrf-2 pathway and mitochondrial dynamics was analyzed. AGEs-stimulated HK-2 cells were examined to evaluate the tubular protection and the mechanism of AA in vitro.AA remarkably decreased albumin levels, KIM-1 levels in urine, and serum Cr, and BUN levels. In addition, AA prevented tubular injury and mitochondrial injury by regulating the Nrf-2 pathway and mitochondrial dynamics. Furthermore, the effects of AA on mitochondrial dynamics and tubular protection were eliminated after treatment with ML385 (Nrf2 inhibitor).These findings suggested that AA might be developed as a potential candidate for the treatment of tubular injury in DKD, and its effects are potentially mediated via the regulation of the Nrf-2 pathway and mitochondrial dynamics.

Objective Ying Yang1 (YY1) has already been discussed in oral squamous cell carcinoma (OSCC), but the knowledge about its mediation on long non-coding RNA KCNQ1 overlapping transcript 1/microRNA-506-3p/synaptophysin like 1 (Kcnq1ot/miR-506-3p/SYPL1) axis in OSCC is still in its infancy. Hence, this article aims to explain the mechanism of YY1/Kcnq1ot1/miR-506-3p/SYPL1 axis in OSCC development. Methods YY1, Kcnq1ot1, miR-506-3p and SYPL1 expression levels were determined in OSCC tissues. The potential relation among YY1, Kcnq1ot1, miR-506-3p and SYPL1 was explored. Cell progression was observed to figure out the actions of depleted YY1, Kcnq1ot1 and SYPL1 and restored miR-506-3p in OSCC. OSCC tumorigenic ability in mice was examined. Results Elevated YY1, Kcnq1ot1 and SYPL1 and reduced miR-506-3p were manifested in OSCC. YY1 promoted Kcnq1ot1 transcription and up-regulated Kcnq1ot1 expression, thereby promoting OSCC cell procession. Silencing Kcnq1ot1 or elevating miR-506-3p delayed OSCC cell progression and silencing Kcnq1ot1 impeded tumorigenic ability of OSCC cells in mice. YY1-mediated Kcnq1ot1 sponged miR-506-3p to target SYPL1. Conclusion YY1 promotes OSCC cell progression via up-regulating Kcnq1ot1 to sponge miR-506-3p to elevate SYPL1, guiding a novel way to treat OSCC.

The persistence of latent human immunodeficiency virus type 1 (HIV-1) reservoirs remains a major hurdle for HIV-1 eradication. The "shock and kill" strategy relies on the drug-mediated reversion of HIV-1 latency and the subsequent death of HIV-producing cells. Unfortunately, none of the agents currently in use possess a sufficient potency to reactivate latent virus or eliminate the latent HIV-1 reservoir in vivo. Here, we demonstrated that a promising specific bromodomain and extraterminal domain inhibitor, CPI-203, could potently reactivate latent HIV-1 in different latently infected cell lines with minimal cytotoxicity by activating the positive transcription elongation factor b signaling pathway. Notably, CPI-203 exhibited synergism in latent HIV-1 reactivation and alleviated the HIV-1-induced "cytokine storm" when used in combination with the protein kinase C (PKC) agonist prostratin. These findings highlight that CPI-203 shows promise as a novel, safe candidate for the design of targeted strategies to "shock and kill" HIV-1 and thus represents a potential functional cure.

This article proposes two new concepts, adsorption and rejection accumulation and the membrane fouling efficiency per unit accumulation to quantitatively characterize the membrane fouling capacity of different single substances. The membrane fouling caused by bovine serum albumin (BSA), sucrose, glycerol triacetate, l-glutathione and maltodextrin on a polyethersulfone (PES) microfiltration membrane was studied. The real-time variations in filtrate concentration and transmembrane pressure were measured with an ultraviolet (UV) detector and pressure sensor during constant-flux filtration. The results showed that the PES membrane had rejection effects for the five substances. However, adsorption phenomena on the PES membrane were observed only for BSA and l-glutathione filtration. The membrane fouling capacity depended on the accumulation and fouling coefficient of the fouling component. The adsorption and rejection accumulation over 40 min followed the order of BSA (1441.39 µg·cm−2) > sucrose (908.53 µg·cm−2) > glycerol triacetate (290.29 µg·cm−2) > l-glutathione (145.18 µg·cm−2), while the membrane fouling efficiency per unit accumulation followed the order of l-glutathione (6.06 × 108 m−1·µg−1·cm2)>BSA (2.44 × 108 m−1·µg−1·cm2) > glycerol triacetate (2.08 × 108 m−1·µg−1·cm2) > sucrose (8.41 × 107m−1·µg−1·cm2). Based on these two factors, the membrane fouling was the most severe with BSA, followed by sucrose, l-glutathione and glycerol triacetate. The membrane fouling caused by maltodextrin was severe in the early stage and weakened in the later period due to the periodic formation and collapse of the maltodextrin cake layer on the membrane surface.

Polar codes were first proposed by E. Arıkan in 2009 and have received significant attention in recent years. Successive-cancellation (SC) and belief-propagation (BP) decoding algorithms have been applied by some researchers to polar codes. However, unlike SC-based decoders, the performance optimization of BP-based decoders has not been fully explored yet, especially in regard to the impact of the number of iterations on the decoding complexity. In this paper, a novel early stopping criterion based on partial frozen bits for belief-propagation polar code decoders is designed. The proposed criterion is based on the fact that some of the frozen bits that are known to the decoders have a higher average error probability than the information bits and can be used to terminate the decoding. Furthermore, the hardware architecture of the BP-based polar code decoder with the proposed stopping criterion is presented. The simulation results show that the proposed early stopping criterion greatly reduces the number of iterations of BP-based polar code decoders without any performance loss and reduces the hardware complexity from O (NlogN) to O (N) compared with state-of-the-art design.

Small targets have low resolution and small size. Using the YOLOv3 model may not detect the target object. In view of this situation, this paper improves the YOLOv3 model and proposes a network structure with refined features. The channel feature refinement mechanism is introduced, and four detection scales are designed to prevent small objects from being submerged; and the spatial pyramid structure-Spp module is added to detect five defects of glass. The experimental results show that compared with the YOLOv3 model, the mAP value of the optimized model is 97.22%, and the mAP value of the original version is 92.31%, an increase of 4.91%. In the self-built data set, the accuracy of automotive glass defect recognition reached 97.66%, and the optimized model’s recognition effect on small targets was significantly improved. Compared with the traditional glass defect detection method, the method improves the detection accuracy and the recognition accuracy.

Cyclocarya paliurus (Batal.) Iljinskaja. (C. paliurus) is a distinctive traditional Chinese herb, with remarkable hypoglycemic capacity. Emerging evidence suggested that glomerular endothelial injury is a crucial pathological process of diabetic kidney disease (DKD). Our previous research found that C. paliurus triterpenoids fraction (CPT) has ameliorative effects on DKD. However, whether C. paliurus could counteract the glomerular endothelial injury of DKD is still undefined.We aimed to investigate the effects of CPT on glomerular endothelial function and explore its underlying mechanisms with in vivo and in vitro experiments.The effects and possible mechanisms of CPT on glomerular endothelial injury in streptozotocin (STZ)-induced diabetic rats and HIn vivo, we found that CPT treatment obviously decreased the levels of blood glucose, microalbumin, BUN and mesangial expansion. Additionally, CPT could ameliorate renal endothelium function by reducing the content of VCAM-1 and ICAM-1, and blocking the loss of glycocalyx. In vitro, CPT could also alleviate HThese findings suggested that CPT could be sufficient to protect against glomerular endothelial injury in DKD through regulating ROCK pathway.

Wearable inertial sensors may be used to objectively quantify exposure to some physical risk factors associated with musculoskeletal disorders. However, concerns regarding their potential negative effects on user safety and satisfaction remain. This study characterized the self-reported daily discomfort, distraction, and burden associated with wearing inertial sensors on the upper arms, trunk, and dominant wrist of 31 manufacturing workers collected over 15 full work shifts. Results indicated that the workers considered the devices as generally comfortable to wear, not distracting, and not burdensome to use. Exposure to non-neutral postures (discomfort, right arm, beta = 0.02; trunk, beta = -0.01), non-cyclic tasks (distraction, beta = -0.26), and higher body mass indices (discomfort, beta = 0.05; distraction, beta = 0.02) contributed to statistically significant (p 0.05), albeit practically small increases in undesirable ratings. For instance, for each additional percentage of time working with the right arm elevated ≥60°, self-reported discomfort ratings increased 0.02 cm on a standard 10 cm visual analog scale. Female workers reported less discomfort and distraction while wearing the sensors at work than males (discomfort, beta = -0.93; distraction, beta = -0.3). In general, the low ratings of discomfort, distraction, and burden associated with wearing the devices during work suggests that inertial sensors may be suitable for extended use among manufacturing workers.

Introduction There is relatively little research on the impact of government cash subsidies on health risk behaviors of the elderly in China. We thus analyzed the effect of pension subsidies on the smoking and drinking behaviors of rural elderly using a pension scheme introduced in rural China in 2009. Methods Based on panel data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2008 and 2011, a Difference-in-Differences (DID) method was applied to comprehensively analyze the impact of the new agricultural insurance on the health risk behaviors of the rural elderly. In order to solve possible sample selection biases, the Propensity Score Matching with Difference-in-Differences (PSM-DID) approach was used. Results We found that the implementation of the government cash subsidies clearly promoted smoking rather than drinking behavior among rural older adults. Specifically, the government cash subsidies facilitated smokers to smoke an additional 2.9 cigarettes/day, and the impact of government cash subsidies on the average cigarettes/day among smokers was more pronounced among the male elderly, lower age elderly, higher income elderly, and elderly with intact instrumental activities of daily living (IADL). Conclusions In order to reduce the negative externalities of old-age subsidies, the government should place some restrictions on the use of cash subsidies for tobacco purchase by the elderly.

Tropospheric delay is an important error affecting GNSS high-precision navigation and positioning, which will decrease the precision of navigation and positioning if it is not well corrected. Actually, tropospheric delay, especially in the zenith direction, is related to a series of meteorological parameters, such as temperature and pressure. To estimate the zenith tropospheric delay (ZTD) as accurately as possible, the paper proposes a new fused model using the least squares support vector machines (LSSVM) and the particle swarm optimization (PSO) to improve the precision and temporal resolution of meteorological parameters in global pressure and temperature 2 wet (GPT2w). The proposed model uses the time series of meteorological parameters from the GPT2w model as the initial value, and thus, the time series of the residuals can be obtained between the meteorological parameters from meteorological sensors (MS) and the GPT2w model. The long time series of meteorological parameters is the evident periodic signal. The GPT2w model describes its dominant frequency (harmonics), and the residuals thus can be seen as the short-period signal (nonharmonics). The combined PSO and LSSVM model (PSO-LSSVM) is used to predict the specific value of the short-period signal. The new GPT2w model, in which the meteorological parameter value is obtained by combining the estimated meteorological parameters residuals and the GPT2w-derived meteorological parameters, can be acquired. The GNSS network stations in Hong Kong throughout 2017-2018 are processed by the GNSS Processing and Analysis Software (GPAS), which is developed by the Chinese Academy of Surveying & Mapping, to estimate the zenith tropospheric delay and station coordinates using the new GPT2w model. Statistical results reveal that the accuracy of the new GPT2w model-derived ZTD was improved by 60% or more compared with that of the GPT2w-derived ZTD. In addition, the positioning accuracy of the GNSS station has been effectively improved up to 44.89%. Such results reveal that the new GPT2w model can greatly reduce the influence of nonharmonic components (short-period terms) of the meteorological parameter time series and achieve better accuracy than the GPT2w model.

This study aims to evaluate and analyze the implementation effect by central government of the housing rental market in different cities in the context of rent and purchase in parallel. Game theory and panel data empirical analysis were used to study the subsidy transmission mechanism of the development of the housing rental market under the perspective of financial decentralization. The central finance played an indirect role in the development of the local housing rental market, and the local government’s support for the local housing rental market was an intermediary variable. To promote the rapid and healthy development of the domestic housing rental market, the central government needs to make top-level design and give certain local policies and financial support. At the same time, local governments must actively implement relevant policies of the central government and support corresponding local support policies.

The complete removal of tetracycline residuals under visible light still is a challenging task because of their robust ring structure. To tackle this issue, we explore a novel Bi

The biosynthetic efficiency of curcumin, a highly bioactive compound from the plant

Accurate pulmonary nodule detection plays an important role in early screening of lung cancer. Although there are many presented CAD systems based on deep learning for pulmonary nodule detection, these methods still have some problems in clinical use. The improvement of false negatives rate of tiny nodules, the reduction of false alarms and the optimization of time consumption are some of them that need to be solved as soon as possible. In view of the above problems, in this paper, we first propose a novel full convolution segmentation framework for lung cavity extraction in preprocessing stage to solve the time consumption problem of the existing pulmonary nodule detection systems. Furthermore, a 2D-NestedUNet segmentation network and a 3D-RPN detection network is stacked to get the high recall and low false positive rate on nodule candidate extraction, especially the recall of tiny nodules. Finally, a false positive reduction method based on multi-model ensemble is proposed for the further classification of nodule candidates. Our methods are evaluated on several public datasets, LUNA16, LNDb and ChestCT2019, which demonstrated the superior performance of our CAD system.

The auxiliary diagnosis and debugging of filters play an increasingly important role in the design of microwave filters, where aggressive space mapping (ASM) is one of the most commonly used debugging methods. This paper introduces ASM and designs a sixth-order two-layer microstrip interdigital filter with a center frequency of 20.4 GHz and a bandwidth of 1.6 GHz using ASM. The filter reached design indexes after seven iterations, which greatly reduces the number of simulations in the fine model, thereby saving time. It was fabricated with Micro-Electro-Mechanical Systems technology and the size of the chip is 7 mm × 3 mm × 0.8 mm. The measurement result was in good agreement with the simulation result.

As one of the most popular nutrient supplements, creatine has been highly used to increase muscle mass and improve exercise performance. Here, we report an adverse effect of creatine using orthotopic mouse models, showing that creatine promotes colorectal and breast cancer metastasis and shortens mouse survival. We show that glycine amidinotransferase (GATM), the rate-limiting enzyme for creatine synthesis, is upregulated in liver metastases. Dietary uptake, or GATM-mediated de novo synthesis of creatine, enhances cancer metastasis and shortens mouse survival by upregulation of Snail and Slug expression via monopolar spindle 1 (MPS1)-activated Smad2 and Smad3 phosphorylation. GATM knockdown or MPS1 inhibition suppresses cancer metastasis and benefits mouse survival by downregulating Snail and Slug. Our findings call for using caution when considering dietary creatine to improve muscle mass or treat diseases and suggest that targeting GATM or MPS1 prevents cancer metastasis, especially metastasis of transforming growth factor beta receptor mutant colorectal cancers.