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Tinnitus is a hearing disorder that is characterized by the perception of sounds in the absence of an external source. Currently, there is no pharmaceutical cure for tinnitus, however, multiple therapies and interventions have been developed that improve or control associated distress and anxiety. We propose a new Artificial Intelligence (AI) algorithm as a digital prognostic health system that models electroencephalographic (EEG) data in order to predict patients’ responses to tinnitus therapies. The EEG data was collected from patients prior to treatment and 3-months following a sound-based therapy. Feature selection techniques were utilised to identify predictive EEG variables with the best accuracy. The patients’ EEG features from both the frequency and functional connectivity domains were entered as inputs that carry knowledge extracted from EEG into AI algorithms for training and predicting therapy outcomes. The AI models differentiated the patients’ outcomes into either therapy responder or non-responder, as defined by their Tinnitus Functional Index (TFI) scores, with accuracies ranging from 98%–100%. Our findings demonstrate the potential use of AI, including deep learning, for predicting therapy outcomes in tinnitus. The research suggests an optimal configuration of the EEG sensors that are involved in measuring brain functional changes in response to tinnitus treatments. It identified which EEG electrodes are the most informative sensors and how the EEG frequency and functional connectivity can better classify patients into the responder and non-responder groups. This has potential for real-time monitoring of patient therapy outcomes at home.

Study region: Northeast China Study focus: Northeast China is one of the largest agricultural regions in the world and a strategically important granary for China. Information on hydrological extremes is crucially important for water management. Yet, comprehensive studies on hydrological extremes, both extreme flood and drought events, based on hydrological gauge comprehensive and large coverage observations are still lacking in Northeast China. This study investigated observed hydrological extremes with 124 hydrological gauges in the region ranging from the 1950s to present for the first time. New hydrological insights for the region: We find that flood extremes, mean discharge and standardized discharge are decreasing in over 80% of the gauges, and no gauges show significantly increasing flood extremes. The findings suggest that sustainable water management strategies should be employed to meet increasing water demand for long-term development. In addition, we find that flood peak discharge and flood volume are significantly correlated in all the gauges, motivating flood risk studies considering multiple flood variables together. Further, we quantify probability changes of severe and extreme hydrological droughts, and find that the probability of drought events is decreasing in most of the gauges, suggesting that the number of drought events is reducing. Data availability: Discharge data are from the hydrology bureau, and can be found by contacting Songliao River Water Resources Commission, Ministry of Water Resources, the People’s Republic of China (http://www.mwr.gov.cn/english/).

Study region: Northeast China Study focus: Northeast China is an important region for industry and agriculture in China. In this region, investigations are lacking on the spatial distribution of snow melt contributions to the spring maximum runoff/discharge, and no studies have compared the spring and summer potential flood risks. Here, for the first time in Northeast China, we investigated the spatial distribution of snow melt contributions to spring maximum runoff/discharge and compared the spring and summer potential flood risks in terms of their spatial distributions, crop production and economic exposures. New hydrological insights for the region: We find that snow contributes approximately three-fourths of spring maximum floods from 1982 to 2011. On average, potential economic exposures to the summer and spring floods represent 3.9% and 0.4% of total GDP, respectively. Potentially exposed production of maize, rice and soybean to summer floods accounts for approximately 2.8% of the total, and potentially exposed wheat production to the spring floods accounts for 0.3% of the total. GDP growth amplifies increasing trends of potential economic exposure, while changes in potential crop production exposure are dominated by flood variations. This study is unique in that snow melt contributions to the spring maximum floods are quantified and that potential GDP and crop production exposure risks to spring and summer floods are quantified and compared for the first time in Northeast China.

Long non-coding RNAs (lncRNAs) and their N6-methyladenosine (m6A) modifications play an essential role in tumorigenesis and cancer progression. This study was designed to explore the value of m6A-related lncRNAs in prognosis and therapeutic applications of immune infiltration of colon adenocarcinoma (COAD). We downloaded the COAD gene expression and clinical data from The Cancer Genome Atlas project. By co-expression analysis, Lasso Cox regression analysis, and univariate and multivariate Cox regression, we constructed an independent prognostic signature of seven m6A-related lncRNAs. The prognostic lncRNAs were divided into two clusters by consistent clustering analysis, as well as into two groups of low–high risk based on the signature. Then we identified the relationship between the different groups with clinical features and immune cell infiltration. Cluster 2 had a higher risk score with a lower survival rate. The risk score was higher in groups with advanced clinical features, such as stage III–IV, N1-3, and M1. The expression of AC156455.1 was increased in tumor tissues and cluster 2, and the lncRNA ZEB1−AS1 was notably higher in the high-risk group. Five types of immune cells showed differences in two clusters, and most were upregulated in type 2. The expression of memory B cells was positively correlated with the risk score. The prognostic model was verified by the Gene Expression Omnibus (GEO) dataset. Besides, we found that the expression of these seven lncRNAs in tumor tissues was significantly higher than that in normal tissues, which verified the feasibility of the model. Thus, the signature of seven m6A-related lncRNAs can independently predict the prognosis of COAD. This signature is also closely associated with immune cell infiltration, and new therapeutic targets can be explored from this field.

KCNQ5 is suggestively associated with myopia, but its specific role in the myopic process has not been studied further. The aim of this study was to investigate the expression of potassium channel gene KCNQ5 and the changes of K+ microenvironment within the retina of form deprivation myopia (FDM) guinea pigs. A total of 60 guinea pigs were randomly divided into the normal control (NC) group, the self-control (SC) group, and the form-deprivation (FD) group for different treatments. Molecular assays and immunohistochemistry (IHC) were conducted to measure the expression and distribution of KCNQ5-related gene and protein in the retina. We determined the K+ concentration in the retina. In addition, the possible effects of form deprivation on potassium ionic currents and the pharmacological sensitivity of KCNQ5 activator Retigabine and inhibitor XE991 to the M-current in RPE cells were investigated using the patch-clamp technique. As a result, FD eyes exhibited more myopic refraction and longer AL. The mRNA and protein levels of KCNQ5 significantly decreased in the FD eyes, but the K+ concentration increased. In addition, the M-type K+ current [IK(M)] density decreased in FD RPE cells, and were activated or inhibited in a concentration-dependent manner due to the addition of Retigabine or XE991. Overall, KCNQ5 was significantly downregulated in the retina of FD guinea pigs, which may be associated with the increasing K+ concentration, decreasing IK(M) density, and elongating ocular axis. It suggested that KCNQ5 may play a role in the process of myopia, and the intervention of potassium channels may contribute to the prevention and control of myopia.

The insufficient of lignocellulose degradation enzymes, such as cellulase and hemicellulase, is the major obstacle that hinders the bioconversion of lignocellulosic biomass to monosaccharides, especially during the woody biomass hydrolysis process. The addition of additives has received significant attention due to their enhancement of the enzymatic degradation efficiency of lignocellulose. In the present study, a combination of organic alcohols and a biosurfactant could synergistically enhance the saccharification of the cellulose substrate of Avicel, as well as that of pretreated poplar. Results showed that compound additives can greatly improve the conversion rate of enzymatic hydrolysis. The combination of 0.1% (v/v) n-decanol and 1% (v/v) sophorolipid dramatically increased the poplar enzymatic conversion rate from 17.9% to 85%, improving it by 67.1%. Enzyme-rich Hypocrea sp. W63 was fermented to obtain beta-glucosidase (BGL) and xylanase (XYL), which were used as auxiliary enzymes during enzymatic hydrolysis. It was found that the effects of such a combination of additives improved the filter paper activity, stability, and longevity, helping in the recovery of the cellulase cocktail. The compound additives associated with the commercial cellulase and Hypocrea sp. W63 enzyme solution formed an excellent formula for improving the stability of BGL and XYL. The results provide insight into compound additives and the use of a cellulase and auxiliary enzyme cocktail to improve enzymatic hydrolysis for lignocellulose conversion into biofuels.

Thanks to the advantages of low disturbance, good concealment and high mobility, bionic fishes have been developed by many countries as equipment for underwater observation and data collection. However, differentiating between true and bionic fishes has become a challenging task. Commonly used acoustic and optical technologies have difficulty in differentiating bionic fishes from real ones due to their high similarity in shape, size, and camouflage ability. To solve this problem, this paper proposes a novel idea for bionic fish recognition based on blue-green light reflection, which is a powerful observation technique for underwater object detection. Blue-green light has good penetration under water and thus can be used as a signal carrier to recognize bionic fishes of different surface materials. Three types of surface materials representing bionic fishes, namely titanium alloy, carbon fiber, and nylon, are investigated in this paper. We collected 1620 groups of blue-green light reflection data of these three kinds of materials and for two real fishes. Following this, three machine learning algorithms were utilized for recognition among them. The recognition accuracy can reach up to about 92.22%, which demonstrates the satisfactory performance of our method. To the best of our knowledge, this is the first work to investigate bionic fish recognition from the perspective of surface material difference using blue-green light reflection.

The Phaeocystis globosa widely exists in the seawater, which becomes a great threat for the health of humans and animals in the ecological ecosystem. In this work, we reported a promising control strategy with quercetin(QT) enhanced cellulose nanocrystals (CNC). The quercetin enhanced cellulose nanocrystals (QT/CNC) was characterized through Atomic Force Microscopy (AFM), Fourier Transform Infrared Spectrometer (FTIR) and X-ray diffractometer (XRD). The effects of concentrations of CNC and QT on controlled Phaeocystis globosa were investigated. The results showed that the removal rate of Phaeocystis globosa exhibited an optimal value (92.1 %) at 0.05 g L-1 CNC and 0.1 g L-1 QT. Furthermore, the chlorophyll-a content in the Phaeocystis globosa exhibited a remarkable decrease from 3.72 mg L-1 to 0.21 mg L-1 when QT/CNC was interacted. On the basis of these results, we concluded that Phaeocystis globosa could be removed by QT/CNC effectively. During the removal of Phaeocystis globosa, the pH of algal solution decreased from 9.45 to 7.36, indicating that QT/CNC could maintain the normal pH of water. In addition, the testing result of the QT/CNC zeta potentials was negative, which revealed that Phaeocystis globosa was removed through inhibition and flocculation. Accordingly, a possible removal mechanism of Phaeocystis globose by QT/CNC was presumed. This study suggested that QT/CNC might be a potential treatment materials on the removal of Phaeocystis globosa.

Calcium silicate hydrate-polycarboxylate (C-S-H-PCE) nanocomposites can greatly increase the hydration speed of cement paste. To obtain the optimal synthesis condition for smaller particle size, C-S-H-PCE was prepared by adding Ca(NO3)2(4H2O and Na2SiO3(5H2O solution into PCE dispersion solution under high speed stirring, and the effects of reaction temperature, drip flow rate, aging time, C-S-H content and molecular weight of PCE on the particle size distribution of C-S-H were studied. Dynamic light scattering (DLS) and transmission electron microscopy (TEM) were employed to conduct the analysis of particle size and morphology of the prepared C-S-H-PCE. The application performance of the nano composite was characterized by testing the compressive strength of cement paste added with C-S-H-PCE. The experimental results showed that at 25 ?, C-S-H-PCE synthesized with lower PCE molecular weight, slower drip flow rate, and smaller C-S-H content had better performance. The compressive strength of cement paste with C-S-H-PCE cured under low temperature condition was tested. It turned out that the prepared nanocomposites can remarkably enhance the early strength of cement paste for up to 63.8 % and 24.2 % after 1 d and 3 d.

The results of a commissioning experiment on the SILEX-Ⅱ laser facility (formerly known as CAEP-PW) are reported. SILEX-Ⅱ is a complete optical parametric chirped-pulse amplification laser facility. The peak power reached about 1 PW in a 30 fs pulse duration during the experiment. The laser contrast was better than 1010 at 20 ps ahead of the main pulse. In the basic laser foil target interaction, a set of experimental data were collected, including spatially resolved x-ray emission, the image of the coherent transition radiation, the harmonic spectra in the direction of reflection, the energy spectra and beam profile of accelerated protons, hot-electron spectra, and transmitted laser energy fraction and spatial distribution. The experimental results show that the laser intensity reached 5 × 1020 W/cm2 within a 5.8 µm focus (FWHM). Significant laser transmission did not occur when the thickness of the CH foil was equal to or greater than 50 nm. The maximum energy of the accelerated protons in the target normal direction was roughly unchanged when the target thickness varied between 50 nm and 15 µm. The maximum proton energy via the target normal sheath field acceleration mechanism was about 21 MeV. We expect the on-target laser intensity to reach 1022 W/cm2 in the near future, after optimization of the laser focus and upgrade of the laser power to 3 PW.

Background and Aims: The N-terminal pro-B-type natriuretic peptide (NT-proBNP) may predict adverse cardiovascular outcomes in patients with diabetes. However, its prognostic value in patients with multivessel disease (MVD) undergoing coronary revascularization remains unclear. This study aimed to evaluate the prognostic significance of preprocedural NT-proBNP levels in diabetic patients with MVD undergoing coronary revascularization.Methods: A total of 886 consecutive diabetic patients with MVD who underwent coronary revascularization were enrolled in this study. Patients were divided into quartiles according to their pre-procedural NT-proBNP levels. Kaplan-Meier curves and Cox regression analyses were performed to evaluate the risk of cardiovascular events, including all-cause death, cardiovascular death, myocardial infarction (MI), stroke, and major adverse cardiovascular events (MACE), according to the NT-proBNP quartiles.Results: During a median follow-up period of 4.2 years, 111 patients died (with 82 being caused by cardiovascular disease), 133 had MI, 55 suffered from stroke, and 250 experienced MACE. Kaplan-Meier curves demonstrated that NT-proBNP levels were significantly associated with higher incidences of all-cause death, cardiovascular death, MI, and MACE (log-rank test, P < 0.001, respectively). Multivariate Cox regression analysis revealed that NT-proBNP level was an independent predictor of adverse outcomes, including all-cause death (HR, 1.968; 95% CI, 1.377–2.812; P < 0.001), cardiovascular death (HR, 1.940; 95% CI, 1.278–2.945; P = 0.002), MI (HR, 1.722; 95% CI, 1.247–2.380; P = 0.001), and MACE (HR, 1.356; 95% CI, 1.066–1.725; P = 0.013). The role of NT-proBNP in predicting adverse outcomes was similar in patients with stable angina pectoris and acute coronary syndrome. Moreover, preprocedural NT-proBNP alone discriminated against the SYNTAX II score for predicting all-cause death [area under the curve (AUC), 0.662 vs. 0.626, P = 0.269], cardiovascular death (AUC, 0.680 vs. 0.622, P = 0.130), MI (AUC, 0.641 vs. 0.579, P = 0.050), and MACE (AUC, 0.593 vs. 0.559, P = 0.171). The addition of NT-proBNP to the SYNTAX II score showed a significant net reclassification improvement, integrated discrimination improvement, and improved C-statistic (all P < 0.05).Conclusion: NT-proBNP levels were an independent prognostic marker for adverse outcomes in diabetic patients with MVD undergoing coronary revascularization, suggesting that preprocedural NT-proBNP measurement might help in the risk stratification of high-risk patients.

It’s of paramount importance to develop renewable nanocarbon materials to replace conventional precious metal catalysts in alkane dehydrogenation reactions. Graphene-based materials with high surface area have great potential for light alkane dehydrogenation. However, the powder-like state of the graphene-based materials seriously limits their potential industrial applications. In the present work, a new synthetic route is designed to fabricate nitrogen-doped graphene-based monolith catalysts for oxidative dehydrogenation of propane. The synthetic strategy combines the hydrothermal-aerogel and the post thermo-treatment procedures with urea and graphene as precursors. The structural characterization and kinetic analysis show that the monolithic catalyst well maintains the structural advantages of graphene with relatively high surface area and excellent thermal stability. The homogeneous distributed nitrogen species can effectively improve the yield of propylene (5.3% vs. 1.9%) and lower the activation energy (62.6 kJ mol−1 vs. 80.1 kJ mol−1) in oxidative dehydrogenation of propane reaction comparing with un-doped graphene monolith. An optimized doping amount at 1:1 weight content of the graphene to urea precursors could exhibit the best catalytic performance. The present work paves the way for developing novel and efficient nitrogen-doped graphene monolithic catalysts for oxidative dehydrogenation reactions of propane.

The petiole–lamina relationship is central to the functional tradeoff between photosynthetic efficiency and the support/protection cost. Understanding environmental gradients in the relationship and its underlying mechanisms remains a critical challenge for ecologists. We investigated the possible scaling of the petiole–lamina relationships in three dimensions, i.e., petiole length (PL) vs. lamina length (LL), petiole cross sectional area (PCA) vs. lamina area (LA), and petiole mass (PM) vs. lamina mass (LM), for 325 Qinghai–Tibetan woody species, and examined their relation to leaf form, altitude, climate, and vegetation types. Both crossspecies analysis and meta-analysis showed significantly isometric, negatively allometric, and positively allometric scaling of the petiole–lamina relationships in the length, area, and mass dimensions, respectively, reflecting an equal, slower, and faster variation in the petiole than in the lamina in these trait dimensions. Along altitudinal gradients, the effect size of the petiole–lamina relationship decreased in the length and mass dimensions but increased in the area dimension, suggesting the importance of enhancing leaf light-interception and nutrient transport efficiency in the warm zones in petiole development, but enhancing leaf support/protection in the cold zones. The significant additional influences of LA, LM, and LA were observed on the PL–LL, PCA–LA, and PM–LM relationships, respectively, implying that the single-dimension petiole trait is affected simultaneously by multidimensional lamina traits. Relative to simple-leaved species, the presence of petiolule in compound-leaved species can increase both leaf light interception and static gravity loads or dynamic drag forces on the petiole, leading to lower dependence of PL variation on LL variation, but higher biomass allocation to the petiole. Our study highlights the need for multidimension analyses of the petiole–lamina relationships and illustrates the importance of plant functional tradeoffs and the change in the tradeoffs along environmental gradients in determining the relationships.

Exploring how human settlement expansion affects landscape fragmentation is particularly critical to understanding the complex interactions between human activities and landscape functions, patterns, and processes. Here, we use recently developed built-up data and land use data to characterize this effect and its spatial–temporal heterogeneity between 1975 and 2014 in China based on the grids at the national level. Findings suggest that the mean built-up ratio has enlarged three-fold in the past 40 years. The landscape pattern has become increasingly fragmented. Due to anthropogenic encroachment, human settlement expansion has become directly associated with natural habitat loss. Meanwhile, the swift growth of settlements leads to landscape fragmentation with a snowballing number of patches and reducing mean patch size. However, landscape isolation is negatively correlated with settlement expansion. Contrary to traditional perception, the influence of settlement growth on landscape fragmentation in large cities is not as pronounced as that of small and medium cities. Furthermore, there are significant regional differences and gradient effects in the impact of settlement expansion on landscape fragmentation. Specifically, this impact is most intense in western China, followed by central China, and the weakest in eastern China. Several innovative policy implications of these findings are discussed.

People living with dementia, especially those who live in nursing homes, are susceptible to social isolation and activity disengagement. Pet robots are technology-based substitutes to animal-assisted therapy that have demonstrated positive impacts on people with dementia in long term care settings, such as reducing agitation, improving mood and increasing social engagement. Nevertheless, knowledge about the issues influencing their implementation is lacking, as there is a scarcity of research that have explicitly investigated the barriers and facilitators influencing their implementation in real-world practice. The objective of this study is to understand the multi-level barriers and facilitators to the implementation of pet robots for people with living dementia in nursing homes, from the perspectives of key stakeholders. A qualitative study employing a descriptive qualitative approach will be used. The Consolidated Framework of Implementation Research (CFIR) will be used to guide the research process. Multi-level stakeholders, including people living with dementia, healthcare professionals and organisational decision makers in nursing homes, will be recruited for one-to-one interviews. Data will be analysed through framework analysis, using a combination of both deductive (based on the constructs and domains in the CFIR) and inductive approaches. To the best of our knowledge, this will be the first study to explore multi-level determinants to the implementation of pet robots in nursing homes for people living with dementia. Findings will be used to inform the identification of strategies that may be used to guide the implementation of pet robots for people living with dementia in nursing homes.

In order to solve various security risks faced by image privacy protection, we propose a 3D cuboid image encryption scheme based on message-encoded controlled alternate quantum walks. Firstly, we calculated the initial parameters of the quantum system and performed a one-dimensional quantum walk to generate a probability distribution sequence. Secondly, we encoded the sequence into a quaternary message using multiple sets of encoded messages to control the alternate quantum walk model, generating a 3D probability amplitude matrix and 3D probability distribution matrix to obtain the 3D quantum hash sequence through the 3D probability distribution matrix. Then, the image was divided into blocks and integrated into a cuboid. The image cuboid was scrambled between layers using the probability value sequence, and the 3D probability distribution matrix was used to complete the scrambling of the cross-section between layers. Finally, we converted each pixel value of the scrambled cuboid into a binary cube and controlled it to perform the rotation operation through the 3D probability magnitude matrix, then used the 3D quantum hash sequence to XOR the obtained cuboid image and tilted it to obtain the final encrypted image. The simulation results show that the image encryption scheme can resist various typical attacks and has good security performance.

Improving the well-being of the employees is the inevitable choice to improve corporate performance and competitive advantage and the social responsibility that enterprises must undertake. Based on the job demands-resources model, this study introduces perceived organizational support and work stress as the mediator and trade union practice as the moderator to explore the double-edged sword effect of a high-performance work system (HPWS) on the well-being of the employee. Taking 243 employees from Jiangsu, Zhejiang, and Anhui as samples, we found that HPWS positively affects the well-being of the employee through perceived organizational support and negatively affects the well-being of the employee through work stress. Union practices can significantly reduce the positive effect of HPWS on work stress and further weaken the negative effect of HPWS on the well-being of the employee through work stress. The results of this study provide a new way to explain the impact of the HPWS on the well-being of the employees and find that union practice can weaken the negative effects of HPWS. This study provides a new thinking direction for improving the well-being of employees in enterprises.

Weed invasion is the main reason affecting grassland productivity, which also serves as a key difficulty encountered during technical grassland restoration. Modern agriculture relies heavily on chemical herbicides to control weeds; however, this is not applicable to the restoration of degraded grasslands. In this study, artificial establishment methods employing interspecific competition were used to suppress weed invasion while greatly increasing grassland productivity.The establishment of different combinations and densities were then evaluated. Compared to the blank control block, the high-density planting of four pastures was found to reduce the types of invasive weeds by 69.4% and the number of invasive weeds by 79.4%. In addition, the individual biomass of weeds fell by 96.3%. Moreover, 7.56 t hm−2 dry weight of forage was provided in the first year, and 6.52 t hm−2 dry weight of forage was continuously provided in the second year, which had the best input-output ratio in this experiment. This study also demonstrated that the low-density mixed sowing scheme of the three forages can effectively inhibit the invasion of weeds, reducing the types of invasive weeds by 58.3%, the number of invasive weeds by 73.9%, and the individual biomass of weeds by 89.1%, which was the least economical investment among weed control programs. At the same time, unsupervised learning, which was included in the machine learning framework Scikit-learn, was used to verify the relationship between the establishment density of pasture and the number of weed invasive species. The results indicated that the contribution rate of Avena sativa and Elymus nutans to the number of invasive weed species was 89.79%. The present study demonstrated that artificial planting methods can effectively control weeds and increase pasture yields. Accordingly, they have great potential and research value in terms of ecological and economic recovery of degraded grasslands.

Background and Aims: Studies have highlighted the role of the triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio on subsequent cardiovascular events. However, the association of the TG/HDL-C ratio with survival outcomes in diabetic patients with coronary artery disease (CAD) treated with statins remains unknown. This study aimed to assess the predictive value of the TG/HDL-C ratio for all-cause mortality and cardiovascular death in diabetic patients with CAD treated with statins.Methods: The data of patients with type 2 diabetes and angiographically-confirmed CAD who were undergoing statin therapy and visited Tianjin Chest Hospital between January 2016 and September 2016 were retrospectively collected. The patients were categorized based on the baseline TG/HDL-C ratio tertile. Kaplan-Meier analysis and multivariate Cox proportional hazard regression were applied to assess the role of the TG/HDL-C ratio in predicting all-cause mortality and cardiovascular death.Results: A total of 2,080 patients were included. During the 4-year follow-up, 209 patients died, 136 of whom from cardiovascular death. The Kaplan-Meier analyses showed that an increased TG/HDL-C ratio was associated with an increased risk of all-cause mortality (P < 0.001) and cardiovascular death (P < 0.001). The multivariate cox hazard regression analysis revealed a similar effect of the TG/HDL-C ratio on the risk of all-cause mortality (P = 0.046) and cardiovascular death (P = 0.009). The role of the TG/HDL-C ratio in predicting all-cause mortality and cardiovascular death was similar among all subgroups (P > 0.050). For all-cause mortality, the TG/HDL-C ratio significantly improved the C-statistic from 0.799 to 0.812 (P = 0.018), and the net reclassification index (NRI) and integrated discrimination index (IDI) were 0.252 (95% CI: 0.112–0.392; P < 0.001) and 0.012 (95% CI: 0.003–0.022; P = 0.012), respectively. Similarly, for cardiovascular death, the TG/HDL-C ratio significantly improved the C-statistic from 0.771 to 0.804 (P < 0.001), and the NRI and IDI were 0.508 (95% CI: 0.335–0.680; P < 0.001) and 0.033 (95% CI: 0.015–0.050; P < 0.001).Conclusion: TG/HDL-C ratio might be useful for predicting all-cause mortality and cardiovascular death in diabetic patients with CAD treated with statins.

Plant ecologists have long been interested in quantifying how leaf traits vary with climate factors, but there is a paucity of knowledge on these relationships given a large number of the relevant leaf traits and climate factors to be considered. We examined the responses of 11 leaf traits (including leaf morphology, stomatal structure and chemical properties) to eight common climate factors for 340 eastern Qinghai-Tibetan woody species. We showed temperature as the strongest predictor of leaf size and shape, stomatal size and form, and leaf nitrogen and phosphorus concentrations, implying the important role of local heat quantity in determining the variation in the cell- or organ-level leaf morphology and leaf biochemical properties. The effects of moisture-related climate factors (including precipitation and humidity) on leaf growth were mainly through variability in leaf traits (e.g., specific leaf area and stomatal density) related to plant water-use physiological processes. In contrast, sunshine hours affected mainly cell- and organ-level leaf size and shape, with plants developing small/narrow leaves and stomata to decrease leaf damage and water loss under prolonged solar radiation. Moreover, two sets of significant leaf trait-climate relationships, i.e., the leaf/stomata size traits co-varying with temperature, and the water use-related leaf traits co-varying with precipitation, were obtained when analyzing multi-trait relationships, suggesting these traits as good indicators of climate gradients. Our findings contributed evidence to enhance understanding of the regional patterns in leaf trait variation and its environmental determinants.

Abstract We present a facile and effective method for fabrication of the localized surface plasmon resonance (LSPR) optical fiber sensor assisted by two polydopamine (PDA) layers with enhanced plasmonic sensing performance. The first PDA layer was self-polymerized onto the bare optical fiber to provide the catechol groups for the reduction from Ag+ to Ago through chelating and redox activity. As the reduction of Ag+ proceeds, Ag nanoparticles (NPs) were grown in-situ on the PDA layer with uniform distribution. The second PDA layer was applied to prevent Ag NPs from oxidating and achieve an improvement of LSPR signal. The PDA/Ag/PDA-based optical fiber sensor has an enhanced LSPR sensitivity of 961 nm/RIU and excellent oxidation resistance. The stable PDA/Ag/PDA-based LSPR sensor with high optical performance is very promising for future application in optical sensing field.

Accumulated HMG-CoA reductase (HMGCR) limits the cholesterol-lowering effect of statins via a feedback loop. Here the authors developed a compound that degrades HMGCR, thus decreasing cholesterol levels and reducing atherosclerotic plaques.

Nanoplastics (NPs) are becoming an emerging pollutant of global concern. A potential risk of NPs is that they can serve as carriers and synergistically function with other contaminants to cause diseases. A variety of diseases such as Alzheimer’s disease are related to the generation of amyloid fibrils, and insulin is typically used as a model to study the fibrillation process. In this study, we examined the fibrillation of insulin promoted by polystyrene nanoplastics (PSNPs) alone and synergistically with organic contaminants (denoted as X, X = pyrene, bisphenol A, 2,2′,4,4′-tetrabromodiphenyl ether, 4,4′-dihydroxydiphenylmethane, or 4-nonylphenol) having different polarities using thioflavin T fluorescence assays, dynamic light scattering, and circular dichroism spectroscopy. The presence of PSNPs and small organic contaminants decreased the lag phase time (tlag) for insulin fibrillation from 54.6 h to 35-51 h and their combination (PS-X) enhanced this process (tlag = 21-30 h). Notably, the lag phase time for insulin fibrillation with PS-nonpolar contaminants, PS-weakly polar contaminants, and PS-polar contaminants is around 20.8, 26.7, and 30.1 h, respectively, indicating the synergistic effect of PS-nonpolar contaminants or PS-weakly polar contaminants was more obvious than that of PS-polar contaminants. Moreover, molecular dynamic simulation reveal the interactions between insulin and PSs or small organic contaminants are primarily driven by van der Waals forces and hydrophobic interactions. Overall, the findings of this study underscore the potentially significant environmental impact of small organic contaminants assisting NPs in promoting insulin fibrillation.

Carbon surface oxides have been demonstrated to be crucial for high performing carbon materials in various applications. Diffuse reflectance infrared Fourier transform spectroscopy represents a powerful time-resolved method to study the surfaces of functional materials under process conditions. Due to the severe overlap of the contributions of individual surface groups in combination with compared to organic molecules shifted absorption maxima meaningful analysis remains challenging. Especially due to the unknown maxima, deconvolution of the superimposed bands is strongly hindered. In this study, we developed a procedure based on hydrolysis, thermal annealing or a combination thereof, which allows to disentangle carbonyl absorption maxima of carboxylic acids, anhydrides and lactones on carbon surfaces. In order to verify the proposed transformations, thorough characterization by temperature programmed desorption, X-ray photoelectron spectroscopy, potentiometric titration and Boehm titration was carried out. Applying this procedure for a polymer derived reference material, the carbonyl absorption maximum could be deduced, which are positioned for lactones at 1771 cm−1, for carboxylic acids between 1753 cm−1 and 1760 cm−1, and for carboxylic anhydrides at 1792 cm-1 and 1852 cm-1. This allowed deconvolution of the carbonyl band, paving the way for in situ time-resolved analyses.

Plant biomass (size) inequality among and within species is central to maintenance of species diversity. Understanding its role in community dynamic and variation with environments in stressful alpine systems where plant communities are structured by a number of different interactions remains a critical challenge for ecologists. Using data from 531 Qinghai-Tibetan grassland communities, we analyzed community-scale plant biomass inequality both in individual- (i.e. inter-specific difference in mean individual biomass) and species- (i.e. mean difference in species’ overall biomass) dimension, and used regression, two-level general linear models (GLM), and structural equation models (SEMs) to evaluate their association with communities’ species richness, productivity, abundance and environmental factors. We found that individual-dimension biomass inequality increased with increasing air temperature but decreasing soil water content (SWC), while species-dimension inequality increased with increasing SWC, resulting in a higher individual-dimension biomass inequality than species-dimension one toward warm and arid environments but lower toward cold and (or) wet conditions. The effects of community factors on plant biomass inequality operated in different dimensions, in which individual-dimension inequality decreased with abundance but species-dimension inequality increased with species richness and especial above-ground biomass. The SEMs showed that individual-dimension biomass inequality decreased mainly with abundance indirectly via decreasing temperature but increasing precipitation as well as with SWC directly; while species-dimension biomass inequality increased mainly with productivity indirectly via increasing SWC and secondarily with species diversity indirectly via increasing precipitation. Overall, our results imply that both ‘environment constraint’ and ‘resource competition’ mechanism operate simultaneously driving plant biomass difference in the Qinghai-Tibetan grassland systems. We also evidence the importance of community biomass and abundance in regulating species’ and individual biomass variation, respectively. Furthermore, our results demonstrate that a reduction in interspecific individual biomass difference acts as a common mechanism in maintaining species coexistence for grassland community under stressful environments.

Isolated central nervous system involvement in multiple myeloma (CNS-MM) is rare and carries extremely poor prognosis. Chimeric antigen receptor T cell therapy (CART) targeting B-cell maturation antigen (BCMA) is demonstrated as a promising strategy in MM treatment, but the clinical safety and efficacy of BCMA-CART against isolated CNS-MM remain elusive. Here we report on a 56-year-old male with refractory isolated CNS-MM who received autologous BCMA-CART therapy and developed grade 4 neurological complications. Cerebrospinal fluid (CSF) analyses showed significant expansion of CART cells and a substantially elevated interleukin-6 (IL-6) level. Intravenous methylprednisolone was administered and the symptoms resolved gradually. Unexpectedly, the level of IL-6 in the CSF was maintained for another 3 days even after the relief of the neurological symptoms. A partial response was achieved and sustained for 5.5 months. This is the first report describing a patient with isolated CNS-MM treated using BCMA-CART therapy. The results demonstrated that BCMA-CART cells administered intravenously trafficked into the CSF, eradicated tumor cells, and induced severe but reversible neurological adverse events. This single-patient report suggests that BCMA-CART therapy can be considered as an alternative option for isolated CNS-MM.Clinical Trial RegistrationClinicalTrials.gov, identifier NCT03196414.

Tourist values determine the behavior of tourists. To pinpoint the behaviors and preferences of tourists, it is necessary to explore their value orientation and intergenerational differences. The exploration is of great significance to the activation of tourism in traditional villages. After analyzing the value of tourists to two traditional villages (Hongcun and Xidi), this paper investigated the value preferences and intergenerational differences of tourists of four generations to traditional villages, using means-end chain (MEC) theory and hard laddering. Through a questionnaire survey on tourists born in the 1960s, 1970s, 1980s, and 1990s, the authors established 36 MEC value chains of 18 classes. The results show that the post-60s traditional village tourists are a generation of wisdom-loving learners, who prefer the values of wisdom and self-improvement; the post-70s and 80s tourists are a generation of beauty lovers with a strong sense of belonging, who prefer the values of beautiful world, inner harmony, and sense of belonging; the post-90s tourists are a generation of inclusive advocators of diversity, with no special value preference. These results provide theoretical support and practical enlightenment for the market segmentation of traditional village tourism and the protection and activation of traditional villages.

We aimed to evaluate the effect of activated platelet-rich plasma (PRP) on proliferation and chondrogenic differentiation of bone marrow-derived mesenchymal stem cells (BMSCs). Six mature male rabbits were included in this study. PRP was obtained by two-step centrifugation from whole blood, and it was activated using CaCl2 solution. BMSCs were isolated and proliferated from bone marrow of rabbits and characterized by flow cytometry. Passage 3 BMSCs were cultured in high-glucose Dulbecco’s modified Eagle’s medium (HG-DMEM) with the four different compositions for consecutive 7 days, including 10% fetal bovine serum, 5% PRP, 10% PRP, and 15% PRP. Cell counting assays were performed to evaluate the cell proliferation of BMSCs. BMSCs (5×105 cells/well in 6-well plates) were induced in four conditions for 21 days to chondrogenic differentiation evaluation, including commercial chondrogenic medium (control), 5% PRP (HG-DMEM+5% PRP), 10% PRP (HG-DMEM+10% PRP), and 15% PRP (HG-DMEM+15% PRP). The gene expression levels of ACAN, COL2A1, and SOX9 in pellets were detected. Morphological and pathological assessments were performed by the blind observer. After purifying, the percentages of cells with CD105(+)/CD34(−) and CD44(+)/CD45(−) were 96.5% and 92.9%, respectively. The proliferation of BMSCs was enhanced in all groups, and 10% PRP revealed more significant outcome than the others from day 5. The levels of ACAN, COL2A1, and SOX9 were lower in the three PRP groups than control group, but the levels of ACAN and SOX9 were higher in 10% PRP group than 5% and 15% PRP groups. Histological examinations showed that 10% PRP-treated pellets had more regular appearance, larger size, and abundant extracellular matrix than 5% or 10% PRP groups, but still inferior to commercial chondrogenic medium. In conclusion, our results show that PRP may enhance the proliferation of rabbit BMSCs. However, PRP have limited effect on chondrogenic differentiation in comparison with commercial chondrogenic medium in pellets culture.

The regulation of endogenous hormones in seed germination and dormancy has been discussed widely in Arabidopsis and crops species, but wild species are rarely examined. In this study, seeds of Anemone rivularis var. flore-minore, a common species in the alpine meadows, were used to test the relationships between endogenous hormone levels and seed germination. The contents of abscisic acid (ABA), gibberellic acid (GA), trans-zeatin (ZT) and indole-3-acetic acid (IAA) in dry, imbibed, and germinated seeds that incubated in either light (12 h/12 h light/dark) or dark (24 h dark) periods were detected by reversed phase high-performance liquid chromatography (RP-HPLC) with ultraviolet detection. When seeds cultivated in the light were compared to those in the dark, A. rivularis seeds germinated more efficiently and had significantly higher values of ZT content and ZT/ABA ratio in light. Meanwhile, the values of ZT/GA, ZT/IAA, and GA/ABA showed increasing trends while ABA content decreased. The effects of light on hormone contents were great in the early stages of seed imbibition and were significantly weakened during late imbibition. The half imbibition time point (the ninth day) revealed to be a turning point of variation within endogenous hormone contents of A. rivularis, especially with ABA content. The half imbibition time point also resulted in the lowest value ZT/ABA, GA/ABA and IAA/ABA. After that point, ZT remained high, IAA levels remained low, and GA and ABA decreased from their respective peaks. As the imbibition process moved forward, IAA content decreased and the common trend of GA and ABA increasing then decreasing was also observed. Transitioning to later imbibition time points of seed gemination (the 17th d), whether light was considered or not, the values of GA, IAA, and ABA contents remained at a lower hormone level, except for ZT. At the same time, ZT/ABA, GA/IAA and ZT/IAA showed the highest values during germination. When assessing pair-wise hormone correlations, the imbibition time strengthened the GA-IAA positive correlation but weakened the GA-ABA positive correlation found when imbibition time was not controlled. Furthermore, by controlling for the light conditions, the ZT-IAA and ZT-ABA correlations were strengthened. These results suggest that both light condition and seed imbibition time play roles during seed germination of A. rivularis by regulating hormone levels and their interactions to some extent.

When an unmanned aerial vehicle (UAV) performs tasks such as power patrol inspection, water quality detection, field scientific observation, etc., due to the limitations of the computing capacity and battery power, it cannot complete the tasks efficiently. Therefore, an effective method is to deploy edge servers near the UAV. The UAV can offload some of the computationally intensive and real-time tasks to edge servers. In this paper, a mobile edge computing offloading strategy based on reinforcement learning is proposed. Firstly, the Stackelberg game model is introduced to model the UAV and edge nodes in the network, and the utility function is used to calculate the maximization of offloading revenue. Secondly, as the problem is a mixed-integer non-linear programming (MINLP) problem, we introduce the multi-agent deep deterministic policy gradient (MADDPG) to solve it. Finally, the effects of the number of UAVs and the summation of computing resources on the total revenue of the UAVs were simulated through simulation experiments. The experimental results show that compared with other algorithms, the algorithm proposed in this paper can more effectively improve the total benefit of UAVs.

Histone deacetylase 6 (HDAC6) acts as a regulator of the nuclear factor kappa-B (NF-κB) signaling pathway by deacetylating the non-histone protein myeloid differentiation primary response 88 (MyD88) at lysine residues, which is an adapter protein for the Toll-like receptor (TLR) and interleukin (IL)-1β receptor. Over-activated immune responses, induced by infiltrated immune cells, excessively trigger the NF-κB signaling pathway in other effector cells and contribute to the development of rheumatoid arthritis (RA). It has also been reported that HDAC6 can promote the activation of the NF-κB signaling pathway. In the present study, we showed that HDAC6 protein level was increased in the synovium tissues of adjuvant-induced arthritis rats. In addition, hydrogen sulfide (H2S) donor S-propargyl-cysteine (SPRC) can inhibit HDAC6 expression and alleviate inflammatory response in vivo. In vitro study revealed that HDAC6 overexpression activated the NF-κB signaling pathway by deacetylating MyD88. Meanwhile, sodium hydrosulfide (NaHS) or HDAC6 inhibitor tubastatin A (tubA) suppressed the pro-inflammatory function of HDAC6. Furthermore, the reduced expression of HDAC6 appeared to result from transcriptional inhibition by S-sulfhydrating specificity protein 1 (Sp1), which is a transcription factor of HDAC6. Our results demonstrate that Sp1 can regulate HDAC6 expression, and S-sulfhydration of Sp1 by antioxidant molecular H2S ameliorates RA progression via the HDAC6/MyD88/NF-κB signaling pathway.

Au nanocluster (AuNCs)-based luminescent functional materials have attracted the interest of researchers owing to their small size, tractable surface modification, phosphorescence lifetime and biocompatibility. However, the poor luminescence quantum yield (QY) of AuNCs limits their practical applications. Herein, we synthesized a type of AuNCs modified by 4,6-diamino-2-mercaptopyrimidine hydrate (DPT-AuNCs). Furthermore, organic acids, i.e., citric acid (CA) and tartaric acid (TA), were chosen for co-assembly with DPT-AuNCs to produce AuNCs-based luminescent materials with enhanced emission. Firstly, it was found that CA could significantly enhance the emission of DPT−AuNCs with the formation of red emission nanofibers (QY = 17.31%), which showed a potential for usage in I− detection. The n···π/π···π interaction between the CA and the DPT ligand was proposed as crucial for the emission. Moreover, chiral TA could not only improve the emission of DPT-AuNCs, but could also transfer its chirality to DPT-AuNCs and induce the formation of circularly polarized luminescence (CPL)-active nanofibers. It was demonstrated that the CPL signal could increase 4.6-fold in a ternary CA/TA/DPT-AuNCs co-assembly system. This work provides a convenient way to build AuNCs-based luminescent materials as probes, and opens a new avenue for building CPL-active materials by achiral NCs through a co-assembly strategy.

Background: Diverse sequence types (ST) and various carbapenemase-producing carbapenem-resistant Enterobacterales (CP-CRE) infections, which complicate treatment strategies, have emerged in Singapore. We aim to describe these CP-CRE infections and clinical outcomes according to their carbapenemase types and determine the hierarchy of predictors for mortality that are translatable to clinical practice.Methods: Clinically significant CP-CRE infections were identified in Singapore General Hospital between 2013 and 2016. Retrospectively, all clinically relevant data were retrieved from electronic medical records from the hospital. Univariate analysis was performed. To further explore the relationship between the variables and mortality in different subsets of patients with CP-CRE, we conducted recursive partitioning analysis on all study variables using the “rpart” package in R.Results: One hundred and fifty five patients were included in the study. Among them, 169 unique CP-CRE were isolated. Thirty-day all-cause in-hospital mortality was 35.5% (n = 55). There was no difference in the severity of illness, or any clinical outcomes exhibited by patients between the various carbapenemases. Root node began with patients with Acute Physical and Chronic Health Evaluation (APACHEII) score ≥ 15 (n = 98; mortality risk = 52.0%) and

Detection of copper ions is important for environmental protection and human healthy. In this study, a ratiometric fluorescent probe was developed by using silica nanoparticles capped carbon dots (CDs) as the core and red quantum dots (CdTe) as the shell linking onto the surface of silica. Cu(II) was found to quench the fluorescence of red-emitting CdTe on the shell, while not changing the fluorescence of the core blue-emitting CDs embedding silica nanoparticles. Based on multiple spectroscopic studies, we propose that selective binding of Cu(II) to CdTe of CDs@SiO2-CdTe via a photoinduced electron transfer (PET) process. The as-proposed sensor allows selective determination of Cu(II) in the range from 0.82 µM to 25 µM, with a detection limit of 0.053 µM.