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Abstract DNA walkers have attracted considerable attention in biosensing and bioimaging. Compared with the conventional single leg-based DNA walker, the bipedal DNA walker has remarkable advantages, with improved sensitivity and fast kinetics, and can work efficiently in a crowded cellular environment. However, most reported bipedal DNA walkers are powered by exogenous supplementation, and elaborate DNA sequence designs, auxiliary additives or extra carriers are often needed. A highly integrated bipedal DNA walker that can address robustness, sensitivity and consistency issues in a single system is highly desirable but remains a great challenge. We herein report a novel bipedal DNA nanowalker system through simple assembly of a DNA substrate, hairpin functionalized-AuNPs (AuNPs-H2), and a blocked Mn2+-dependent DNAzyme hairpin (H1) on degradable MnO2 nanosheets, which holds great potential for living cell operation. Highly integrated features enable the simultaneous delivery of core components of the bipedal DNA walker, including a walking track (AuNPs-H2), a walking strand (H1 cleaved by APE1), and a driving force (Mn2+-dependent DNAzyme cleavage) as a whole, thereby enhancing the control of the spatiotemporal distribution of these components at the intracellular target sites. The redox reaction between the MnO2 nanosheets and GSH inside the cells not only consumed the intracellular GSH to improve the biostability of the walking track but also generated abundant Mn2+ as a cofactor of the DNAzyme. As a proof of concept, the developed nanowalker was demonstrated to work efficiently for monitoring base excision repair (BER)-related human apurinic/apyrimidinic endonuclease 1 (APE1) in living cells, highlighting the great potential of the bipedal DNA nanowalker in biological systems. Graphical abstract

In recent years, many new modulation and multiplexing technologies and dynamic network concepts have been proposed to adapt to the ever-increasing network bandwidth and quality requirements. Network control platform has a systematic and intelli-gent development trend, which requires network managers to constantly monitor the parameters of the network and optimize the network state. However, it is not feasible to arrange additional monitoring equipment in a large range to obtain parameter informa-tion from the perspective of cost control. It is better to use known data and special algorithms to monitor and optimize network per-formance. Machine learning methods are increasingly adopted by the academic community because they are accurate and efficient enough to accomplish these tasks. This paper first reviews the different application scenarios of machine learning algorithms in op-tical network monitoring and optimization tasks. Then it reviews the research achievements in this field, and puts forward the ex-isting problems of machine learning-based optical network monitoring and optimization methods as well as the possible direction of future research. The optical performance monitoring based on machine learning includes failure identification, quality of transmis-sion estimation and channel power prediction. The network configuration optimization method based on machine learning includes reinforcement learning to optimize channel power. For future research direction, we believe that it is possible for researchers to use real data from network operators, newly collected data to dynamically train the model, and transfer learning and data enhancement techniques to ensure the robustness and generalization ability of the algorithm.

Background: Studies reported an association between rheumatoid arthritis and Diabetes mellitus. We sought to assess the causal association between rheumatoid arthritis and Diabetes mellitus risk using a two-way two-sample Mendelian randomization (MR) analysis. Methods: Data on Diabetes mellitus and rheumatoid arthritis were obtained from the GWAS genome-wide database, and the MR method was used to explore the bidirectional causal association, the inverse variance weighted (IVW) method was used as the primary analysis method, and sensitivity analysis was performed. Results: IVW results and MR-Egger method indicate that there is a significant correlation between Diabetes mellitus and rheumatoid arthritis (IVW: P = 0.002, OR = 1.057, 95%CI: 1.02–1.096, MR-Egger: P = 0.037, OR = 1.096, 95%CI: 1.006–1.194), MR-Egger intercept analysis shows that the P-value is 0.362 (>0.05), IVW results showed a significant association between rheumatoid arthritis and Diabetes mellitus (IVW: P = 2.65 × 10–9, OR = 1.797, 95%CI: 1.481–2.180), MR-Egger intercept analysis shows that the P-value is 0.221 (>0.05). Conclusion: The results confirm that Diabetes mellitus and rheumatoid arthritis have a two-way causal chain, and it is necessary to strengthen bidirectional surveillance.

Introduction Prolonged hyperglycemia in diabetes mellitus can result in the development of diabetic nephropathy (DN) and increase the susceptibility to kidney failure. Low-intensity pulsed ultrasound (LIPUS) is a non-invasive modality that has demonstrated effective tissue repair capabilities. The objective of this study was to showcase the reparative potential of LIPUS on renal injury at both animal and cellular levels, while also determining the optimal pulse length (PL).Research design and methods We established a rat model of DN, and subsequently subjected the rats’ kidneys to ultrasound irradiation (PL=0.2 ms, 10 ms, 20 ms). Subsequently, we assessed the structural and functional changes in the kidneys. Additionally, we induced podocyte apoptosis and evaluated its occurrence following ultrasound irradiation.Results Following irradiation, DN rats exhibited improved mesangial expansion and basement membrane thickening. Uric acid expression increased while urinary microalbumin, podocalyxin in urine, blood urea nitrogen, and serum creatinine levels decreased (p

Background Lung cancer is the most common cancer in the world and has become one of the malignancies with the highest incidence and mortality; more than half of patients die within one year of being diagnosed with lung cancer. In recent years, the concept of “patient-centered” service has gained popularity, and patients’ subjective feelings have gradually been used in clinical decision-making. Therefore, this study determined the application of visual patient report outcomes in the field of lung cancer, in order to provide reference for specific clinical practice. Methods Using the Web of Science core collection as the main analysis content, Citespace and VOSviewer were used to conduct this scientometric study. Results A total of 499 literatures that met the inclusion criteria were retrieved. The most prolific institution was The University of Texas MD Anderson Cancer Center, and the United States dominates this field. Conclusion The measurement of patient-reported outcomes is considered the gold standard for effectively evaluating patients' perceptions of clinical interventions or diseases. It is recommended that patient-reported outcomes be integrated into routine care for cancer patients in order to enhance communication between patients and healthcare providers. Patient or public contribution Not applicable. All data in this paper are obtained from the web of science database.

Abstract COVID‐19 can lead to adverse outcomes in patients with pre‐existing diseases. Azvudine has been approved for treating COVID‐19 in China, but the real‐world data is limited. It is aimed to investigate the efficacy of Azvudine in patients with COVID‐19 and pre‐existing cardiovascular diseases. Patients with confirmed COVID‐19 and pre‐existing cardiovascular diseases are retrospectively enrolled. The primary outcome is all‐cause death during hospitalization. Overall, 351 patients are included, with a median age of 74 years, and 44% are female. 212 (60.6%) patients are severe cases. Azvudine is used in 106 (30.2%) patients and not in 245 (69.8%). 72 patients died during hospitalization. After multivariate adjustment, patients who received Azvudine a lower risk of all‐cause death (hazard ratio: 0.431; 95% confidence interval: 0.252–0.738; p = 0.002) than controls. Azvudine therapy is also associated with lower risks of shock and acute kidney injury. For sensitivity analysis in the propensity score‐matched cohort (n = 90 for each group), there is also a significant difference in all‐cause death between the two groups (hazard ratio: 0.189; 95% confidence interval: 0.071–0.498; p

The biotoxicity of perfluoroalkyl and polyfluoroalkyl substances (PFASs) to aquatic organisms has been widely concerned. However, studies on toxic effects of PFASs are usually evaluated directly by using laboratory exposure rather than laboratory validation based on data obtained in the field. In this study, wild catfish (Silurus meridinalis) was explored on the relationship between PFASs bioaccumulation and lipid disorders. Nine and thirteen lipid metabolites were significantly associated with perfluorooctane sulfonate (PFOS) and 6:2/8:2Cl-PFESA (trade name F-53B) exposures, respectively; and the correlated lipid metabolites were the fatty acid (FA) and conjugates, FA esters, steroids, and glycerophosphate subclasses. The effects of PFASs on lipid metabolism of fish and its mechanism were further analyzed through exposure experiments. Zebrafish (Danio rerio) of different sexes underwent PFOS and F-53B exposures for 21 days at 100 ng/L and 100 μg/L. By determining gene expression levels, hepatic lipid contents, and histopathological change, the adverse effects order on lipid metabolism in male or female was 100 μg/L F-53B > 100 μg/L PFOS > 100 ng/L F-53B > 100 ng/L PFOS; the stress response in male was more intensive than that in female. PFOS and F-53B activated the peroxisome proliferator-activated receptor pathway, promoting the processes of FA and total cholesterol (T-CHO) transport, FA β-oxidation, FA synthesis, and finally induced FA and T-CHO transportation from blood into liver, then accelerated FA to FA ester transformation, and CHO into steroids. Laboratory experiments confirmed the field analysis. This study innovatively explored the adverse effects of PFOS and F-53B on lipid metabolism and their mechanisms at field and laboratory levels, highlighting concerns regarding PFASs health risks.

Based on the perspective of industrial agglomeration, this paper employs a dynamic panel model and mediating effects model to investigate the impact of digital economy’s development on air pollution in 274 Chinese cities from 2011 to 2019. The main findings include: (1) The development of the digital economy reduces air pollution emissions in Chinese cities, and the elasticity of pollution reduction is greater in central and western China than in eastern China. (2) The nexus between industrial agglomeration and air pollution is inverted-N-shaped. (3) Mechanism tests show that the digital economy can effectively promote the degree of industrial agglomeration in each area, and it plays a positive role in abating pollution in eastern and central China through the positive externalities of industrial agglomeration, but the mediating effect of industrial agglomeration on pollution reduction is not significant in western China. (4) Diversified agglomeration is an active mediator of the digital economy’s pollution reduction effect in eastern and central China. Accordingly, some policy implications are put forward for simultaneously promoting the development of the digital economy and reducing air pollution, impelling industrial agglomeration, and accelerating the green transformation in China.

Urban development is facing increasingly complex disturbances. Assessing large cities’ urban resilience is important for improving their ability to withstand disturbances and promoting sustainable development. Therefore, this paper establishes an improved assessment model for urban resilience based on the driving force–pressure–state–impact–response (DPSIR) and data envelopment analysis (DEA) model. The Malmquist index, Dagum Gini coefficient, and Markov chain were sequentially used for spatiotemporal evolution and differential resilience analysis. Then, 105 large Chinese cities were selected as case studies. The results indicate their overall resilience is relatively high; each year’s average resilience efficiency can achieve DEA effectiveness. The distribution pattern of resilience level presents a healthy olive-shaped structure. However, there is also a significant difference between the two poles. During the research period, the combined effect of technological efficiency improvement and technological progress resulted in the overall resilience slowly improving, and this process was more driven by technological innovation. At the same time, the overall regional difference in resilience also shows a narrowing trend, and the current spatial differences mainly come from the difference within subregions and super-density. In future transfer predictions, the resilience of large cities will show good stability with a higher probability of maintaining stability; if the resilience undergoes a transition, the probability of an increase will be higher than a decrease. Based on the life cycle process of resilience, this study selects indicators that can characterize the level of resilience according to the DPSIR model, which comprehensively reflects the characteristics of urban resilience. This study’s results can provide particular reference values for urban disaster response emergency planning and sustainable development construction, and it also provides new ideas for the assessment research of urban resilience.

Abstract Traffic classification is widely used in network security and network management. Early studies have mainly focused on mapping network traffic to different unencrypted applications, but little research has been done on network traffic classification of encrypted applications, especially the underlying traffic of encrypted applications. To address the above issues, this paper proposes a network encryption traffic classification model that combines attention mechanisms and spatiotemporal features. The model firstly uses the long short-term memory (LSTM) method to analyze continuous network flows and find the temporal correlation features between these network flows. Secondly, the convolutional neural network (CNN) method is used to extract the high-order spatial features of the network flow, and then, the squeeze and excitation (SE) module is used to weight and redistribute the high-order spatial features to obtain the key spatial features of the network flow. Finally, through the above three stages of training and learning, fast classification of network flows is achieved. The main advantages of this model are as follows: (1) the mapping relationship between network flow and label is automatically constructed by the model without manual intervention and decision by network features, (2) it has strong generalization ability and can quickly adapt to different network traffic datasets, and (3) it can handle encrypted applications and their underlying traffic with high accuracy. The experimental results show that the model can be applied to classify network traffic of encrypted and unencrypted applications at the same time, especially the classification accuracy of the underlying traffic of encrypted applications is improved. In most cases, the accuracy generally exceeds 90%.

BackgroundThe exposure to diesel particulate matter (DPM) and its polycyclic aromatic hydrocarbons (PAH) is closely related to the morbidity and mortality of ischemic heart disease (IHD). However, it is unclear what key components and targets of DPM exposure involve in myocardial ischemia-hypoxia injury and associated mechanisms.ObjectiveTo identify key PAH components of DPM that act on myocardial hypoxic injury, andclarify the role of oxygen sensors-regulated anaerobic metabolism in DPM and key components-induced hypoxic injury and the targets of the key PAH components.MethodsHuman cardiomyocyte cell line AC16 cells were exposed to 0, 1, 5, and 10 μg·mL−1 DPM in a high glucose DMEM medium with 10% fetal bovine serum (FBS) (HGM) or low FBS (0.5%) in high glucose DMEM medium (LFM), for 12 h under 2% O2, and expression of hypoxia-inducible factor-1α (HIF-1α), Bax, and Cleaved-caspase3 was determined by Western blotting. Under normal condition, the cell viability was detected after PAH exposure for 12 h. Under the condition of ischemia-hypoxia model, cells were exposed to 0, 0.005, 0.5, and 5 µg·mL−1 PAH for 12 h, and the protein expression of HIF-1α, Bax, and Cleaved-caspase3 was determined. After exposure to DPM or PAH for 12 h, the contents of pyruvate and lactate in cells were detected. Pretreatment with glycolysis inhibitor GSK2837808A was used to explore the role of glycolysis in DPM and benzo[a]pyrene (BaP)-induced hypoxia injury. A molecular docking technique was used to analyze the binding affinity between PAH and oxygen sensors (prolyl hydroxylase domain-containing protein 2, PHD2, and factor-inhibiting hypoxia-inducible factor 1, FIH1), and the protein levels of PHD2, FIH1, and hydroxyl-HIF-1-alpha (OH-HIF-1α) after the DPM or BaP treatment were further determined.ResultsUnder hypoxia, DPM exposure in the LFM induced the expression of HIF-1α, Bax, and Cleaved-caspase3 (P0.05), other PAH decreased cell viability when the concentration was above 1 μg·mL−1 (P

This study aimed to understand the community successions driven by different starters and their effects on the flavor development of Chinese fermented sausages. The results showed that the bacterial genus (67.6%) and pH (32.4%) were the key factors influencing the volatile profile. Inoculated the starters composed of Pediococcus and staphylococci maintained the stable community succession patterns dominated by staphylococci (samples T and S). Although the highly acidic environment (pH 5.4) resulted in a stable succession pattern of the microbial community, and it was not conducive to the accumulation of aldehydes, alcohols and esters.

Abstract Background Kojic acid (KA) is a widely used compound in the cosmetic, medical, and food industries, and is typically produced by Aspergillus oryzae. To meet increasing market demand, it is important to optimize KA production through seeking alternatives that are more economic than current A. oryzae-based methods. Results In this study, we achieved the first successful heterologous production of KA in Aspergillus niger, an industrially important fungus that does not naturally produce KA, through the expression of the kojA gene from A. oryzae. Using the resulting KA-producing A. niger strain as a platform, we identified four genes (nrkA, nrkB, nrkC, and nrkD) that negatively regulate KA production. Knocking down nrkA or deleting any of the other three genes resulted in a significant increase in KA production in shaking flask cultivation. The highest KA titer (25.71 g/L) was achieved in a pH controlled batch bioreactor using the kojA overexpression strain with a deletion of nrkC, which showed a 26.7% improvement compared to the KA titer (20.29 g/L) that was achieved in shaking flask cultivation. Conclusion Our study demonstrates the potential of using A. niger as a platform for studying KA biosynthesis and regulation, and for the cost-effective production of KA in industrial strain development.

TurboID, a proximity labelling method based on mutant biotin ligase, is an efficient new technique for recognizing protein-protein interactions and has been successfully applied to living cells. Sialic acid is typically the terminal monosaccharide attached to many glycoproteins and plays many important roles in many biological processes. However, the lack of enrichment methods for terminal sialic acid glycosylation in vivo hinders the identification and analysis of this glycosylation. Here, we introduce TurboID to identify terminal sialic acid glycosylation in living cells. SpCBM, the carbohydrate-binding domain of sialidase from Streptococcus pneumoniae, is fused with TurboID and overexpressed in HeLa cells. After streptavidin-based purification and detection by mass spectrometry, 31 terminal sialic acid N-glycosylated sites and 1359 putative terminal sialic acid glycosylated proteins are identified, many of which are located in the cytoplasm and nucleus.

IntroductionTumor-related depression is a series of symptoms or states triggered by a tumor as the basic disease. It does not belong to psychiatric depression but dramatically affects individuals’ quality of life. Acupuncture is extensively used to treat tumor-related depression, but the effect of body acupuncture on tumor-related depression is still unsubstantiated. This work, therefore, set out to assess the effect of acupuncture on tumor-related depression.MethodsEight databases were searched from inception to October 2022 for randomized controlled trials (RCTs). Two researchers separately implemented the database search, study selection, data extraction, and quality assessment. All analyses were performed by using Review Manager 5.3.ResultsA total of 10 studies, including 725 participants, were included. A majority of studies recruited patients diagnosed with various tumor types and statuses. Meta-analysis revealed that acupuncture had a beneficial effect compared with usual care on the Hamilton depression scale (HAMD) (mean difference (MD) = −2.23, 95% CI [−4.43, −0.03], p = 0.05), self-rating depression scale (SDS) (MD= −6.22, 95% CI [−10.67, −1.78], p = 0.006), effective rate (RR = 1.23, 95% CI [1.06, 1.43], p = 0.006), and quality-of-life questionnaire (QLQ-C30) (MD = 6.08, 95% CI [3.72, 8.43], p

With the development trend of an aging society, Alzheimer’s disease (AD) has become an urgent problem in the field of medicine worldwide. Cognitive impairment in AD patients leads to a decline in the ability to perform daily living and abnormalities in behavior and personality, causing abnormal psychiatric symptoms, which seriously affect the daily life of patients. Currently, mainly drug therapy is used for AD patients in the clinic, but a large proportion of patients will experience drug efficacy not working, and even some drugs bring severe sleep disorders. Acupuncture, with its unique concept and treatment method, has been validated through a large number of experiments and proved its reliability of acupuncture in the treatment of AD. Many advances have been made in the study of the neurobiological mechanisms of acupuncture in the treatment of AD, further demonstrating the good efficacy and unique advantages of acupuncture in the treatment of AD. This review first summarizes the pathogenesis of AD and then illustrates the research progress of acupuncture in the treatment of AD, which includes the effect of acupuncture on the changes of biochemical indicators in AD in vivo and the specific mechanism of action to exert the therapeutic effect. Changes in relevant indicators of AD similarly further validate the effectiveness of acupuncture treatment. The clinical and mechanistic studies of acupuncture in the treatment of AD are intensified to fit the need for social development. It is believed that acupuncture will achieve new achievements in the treatment of AD as research progresses.

After rapid development in recent decades, China has laid a strong economic foundation and established material conditions. Despite this, the country still confronts a range of challenges that impede higher-quality economic and social development. To measure high-quality regional development, eco-wellbeing performance (EWP) has become an important tool that seeks to strike a balance between economic development, human wellbeing, and environmental protection. This paper proposes a three-stage network efficiency evaluation model to decompose EWP into three stages, namely ecological economic efficiency (EEE), economic innovation efficiency (EIE), and innovation wellbeing efficiency (IWE). A directional distance function (DDF) model was utilized to assess the overall EWP efficiency and phase-in efficiency for 248 cities over the period from 2016 to 2020. The study results indicate that EWP in China is generally low. In terms of the three sub-stages of EWP, the first stage performs optimally, the third stage performs the second best, and the second stage is the worst. The research suggests that the principal reason for the generally low EWP may be linked to the efficiency of the transformation of economic investments into innovative outcomes in the second stage. From a regional viewpoint, EWP generally shows a gradually decreasing trend from the east, central, and west to the northeast, but the stage performance varies among regions. The eastern region has lower EEE, but both EIE and IWE perform better than the national average; the central region is well-balanced between the three stages; the western region leads the country in EEE, but lags in both EIE and IWE; and the northeast region has inferior performance in all stages. This study’s findings provide vital reference values for policy-makers to determine key points for enhancing EWP in different regions of China.

Aspergillus niger is a major cell factory for citric acid production, and the process of citrate export from mitochondria to cytoplasm is predicted to be one of rate-limiting steps in citric acid accumulation. Currently, the mitochondrial citrate transporters (Ctps) in A. niger are not fully characterized. Here, six putative Ctp encoding genes (ctpA to ctpF) were identified based on their homology with a mitochondrial citrate transporter ScCtp1 from Saccharomyces cerevisiae. Disruption of individual ctpA to ctpF caused varying degrees of decline in citric acid accumulation at different fermentation stages, whereas a mutant strain S1696 with disruption of all six ctps showed complete loss of citiric acid production. S1696 also exhibited delayed growth, reduced conidia formation, and decreased pigmentogenesis. Exogenous addition of citrate partially restored the conidia formation and pigmentogenesis in S1696 mutant. Reintroduction of individual ctps (ctpA to ctpF) into S1696 at the amyA locus showed that ctpA, ctpB, and ctpD restored the citric acid titers to 88.5, 93.8, and 94.6% of the parent strain, respectively. Additionally, the formation of conidia and pigment production was partially restored after reintroduction of ctpA, ctpB, or ctpD. Overexpression of respective ctpA, ctpB, and ctpD in the parent strain resulted in increases in citric acid accumulation by 32.8, 19.3, and 24.2%, respectively. These results demonstrate that CtpA, CtpB, and CtpD play important roles in citric acid transport across the mitochondrial membrane and function in a redundant manner. Enhancement of citric acid transport process can serve as a target for boosting citric acid accumulation in A. niger.

BACKGROUND The main types of copper deposits are porphyry and skarn types. Dacite porphyry is a rock type commonly developed in the porphyry Cu-Mo-Au system. The rock can be used as a marker clue for ore prospecting and ore-forming rock when there is well-developed hydrothermal alteration. The Dabaoshan deposit is currently the largest copper polymetallic deposit in the South China Block. Previous studies have shown that the dacite porphyry of the mining area is not only the ore-forming parent rock, but also a favorable ore-bearing wall rock. However, there are some debates about the relationship between dacite porphyry and mineralization in this mining area. With the breakthrough of prospecting for medium and large dacite porphyry ore bodies in recent years, the relationship between dacite porphyry and mineralization has once again become a concern. OBJECTIVES To understand the relationship between dacite porphyry alteration and mineralization of the Dabaoshan deposit. METHODS Based on field work and indoor analysis, X-ray fluorescence spectroscopy (XRF) and inductively coupled plasma-mass spectrometry (ICP-MS) were used to determine copper, tungsten, silicon, aluminum and calcium in Dabaoshan dacite porphyry samples. The isotope composition, metal element contents and alteration characteristics of the dacite porphyry in the mining area were used to discuss the relationship between alteration and prospecting direction. RESULTS The copper content ranged from 107 to 6909μg/g, which was consistent with the copper ore grade of 0.3%-0.5% in the mining area. The LOI and other geochemical indicators that can represent the degree of alteration were positively correlated with copper. Hydrothermal alteration was widely developed in dacite porphyry, including potassium, prophyliticition and quartz-sericitization from early to late stage. Among different stages of alterations, the copper content of quartz-sericitization was 2 to 5 times higher than other alteration types, indicating that quartz-sericitization was closely related to copper mineralization and was an important prospecting marker clue. CONCLUSIONS The deep alteration intensity of the dacite porphyry (below the 270m elevation) has not been weakened, suggesting a great prospecting potential. In addition, the contact zone between dacite porphyry and the Jurassic strata, and the xenoliths in the dacite porphyry are also important prospecting directions, which may host skarn-type copper-rich deposits.

Plasmonic Fano resonance (FR) that contributes to multitudinous potential applications in subwavelength nanostructures can facilitate the realization of tunable wavelength selectivity for controlling light–matter interactions in metasurfaces. However, the plasmonic FR can be generated in metasurfaces with simple or complex geometries, and few of them can support flexible amplitude modulation and multiwavelength information transfer and processing. Here, we study the near-infrared plasmonic FR in a hybrid metasurface composed of concentrically hybridized parabolic-hole and circular-ring-aperture unit cells, which can induce polarization-dependent dual-wavelength passive plasmonic switching (PPS) and digital metasurface (DM). It is shown that the designable plasmonic FR can be realized by changing the geometric configurations of the unit cells. In particular, owing to the polarization-dependent characteristic of FR, it is possible to fulfill a compact dual-wavelength PPS with high ON/OFF ratios in the related optical communication bands. Moreover, such PPS that manipulates the amplitude response of the transmitted spectrum is an efficient way to reveal a 1-bit DM, which can also be rationally extended to a 2-bit DM or more. Our results suggest a pathway for studying polarization-dependent PPS and programmable metasurface devices, yielding possibilities for subwavelength nanostructures in optical communication and information processing.

Objective. This systematic review and meta-analysis was conducted to assess the efficacy of acupuncture treatment for postprandial distress syndrome (PDS). Methods. Search the Web of Science, the Cochrane Library, PubMed, and Embase databases with acupuncture randomized controlled trials for the treatment of patients with PDS. Strictly according to inclusion and exclusion quality assessment standards, the qualified ones are used to study the optimum extraction and data by two independent reviewers. Stata 15.0 software was used for meta-analysis. Result. We initially identified 63 studies, of which five (1253 participants) were eventually included in our analysis. There were 643 cases in the experimental group and 610 cases in the control group. Acupuncture had a significant effect on the total therapeutic effect (OTE) at week 4 (OR 4.74, 95% CI 02.88-7.83, Z=6.10, P=0

Objectives. We assessed the potential of glial cell line-derived neurotrophic factor (GDNF) as a useful biomarker to predict cirrhosis in chronic hepatitis B (CHB) patients. Methods. A total of 735 patients from two medical centers (385 CHB patients and 350 healthy controls) were included to determine the association of serum and tissue GDNF levels with biopsy-proven cirrhosis. The diagnostic accuracy of serum GDNF (sGDNF) was estimated and compared with other indices of cirrhosis. Results. We showed significantly higher levels of sGDNF in CHB patients with fibrosis (28.4 pg/ml vs. 11.6 pg/ml in patients without) and patients with cirrhosis (33.8 pg/ml vs. 23.5 pg/ml in patients without). The areas under receiver operating curve (AUROCs) of sGDNF were 0.83 (95% confidence interval (CI): 0.80–0.87) for predicting liver fibrosis and 0.84 (95% CI: 0.79–0.89) for cirrhosis. Findings from the serum protein level and hepatic mRNA expression were consistent. Using the best cutoff to predict cirrhosis, we categorized the patients into sGDNF-high and sGDNF-low groups. The sGDNF-high group had significantly larger Masson’s trichrome and reticulin staining-positive area, higher Scheuer score, and METAVIR fibrosis stage (all p

Rapid road construction and expansion in China resulted in massive GHG emissions. The carbon emission factors of raw materials, particularly cement, have a significant influence on the calculation of GHG emissions from road construction. This study estimates GHG emissions from road construction by taking into account regional differences in cement carbon emission factors. The results indicate that (1) total GHG emissions from road construction have a “U” shape from 2009 to 2019, with the highest level being 437 million t CO2e 2009 and the lowest level being 184 million t CO2e in 2017; (2) Class-Ⅳ roads account for roughly 80% of total GHG emissions from road construction; and (3) GHG emissions from road construction are shifting from east to west regions. This is the first paper to calculate GHG emissions from road construction by taking into account both road type and cement carbon emission factors. The findings of this study could provide references for transportation agencies to better understand the impacts of road construction to climate change and improve policymaking, especially for the development of road construction technologies and raw material production technologies.

The SiC reinforced Ni60A alloy laser cladding coating on the 45 steel substrate was fabricated with the LDM2500-60 semiconductor laser equipment. The effect of SiC content on microstructure, dilution rate, wear resistance, friction coefficient and microhardness was investigated systematically.The results show that with the increase of SiC content, the microstructure of upper coating is refined obviously, the dilution rate, wear resistance, friction coefficient and microhardness increase firstly and then decrease;when the mass fraction of SiC is 20%, the wear resistance of the cladding coating is the best one, in which the wear loss of coating is only 0.0012g and is 1/36.3 of the matrix;the minimum friction coefficient is 0.464, the friction process is the most stable;the highest microhardness of the cladding coating is 1039.9HV0.2, which is 3.5 times of the substrate;but when the mass fraction of SiC is 25%, the microhardness and wear resistance of coating decrease.