High-Energy Ball Milling Promoted Sulfur Immobilization for Constructing High-Performance Na-Storage Carbon Anodes.

Sulfur (S) doping is an effective method for constructing high-performance carbon anodes for sodium-ion batteries. However, traditional designs of S-doped carbon often exhibit low initial Coulombic efficiency (ICE), poor rate capability, and impoverished cycle performance, limiting their practical applications. This study proposes an innovative design strategy to fabricate S-doped carbon using sulfonated sugar molecules as precursors via high-energy ball milling. The results show that the high-energy ball milling can immobilize S for sulfonated sugar molecules by modulating the chemical state of S atoms, thereby creating a S-rich carbon framework with a doping level of 15.5 wt %. In addition, the S atoms are present mainly in the form of C-S bonds, facilitating a stable electrochemical reaction; meanwhile, S atoms expand the spacing between carbon layers and contribute sufficient capacitance-type Na-storage sites. Consequently, the S-doped carbon exhibits a large capacity (>600 mAh g-1), a high ICE (>90%), superior cycling stability (490 mAh g-1 after 1100 cycles at 5 A g-1), and outstanding rate performance (420 mAh g-1 at a high current density of 50 A g-1). Such excellent Na-storage properties of S-doped carbon have rarely been reported in the literatures before.

Edge Graphitized Oxygen-Rich Carbon Based on Stainless Steel-Assisted High-energy Ball Milling for High-Capacity and Ultrafast Sodium Storage.

Oxygen doping is an effective strategy for constructing high-performance carbon anodes in Na ion batteries; however, current oxygen-doped carbons always exhibit low doping levels and high-defect surfaces, resulting in limited capacity improvement and low initial Coulombic efficiency (ICE). Herein, a stainless steel-assisted high-energy ball milling is exploited to achieve high-level oxygen doping (19.33%) in the carbon framework. The doped oxygen atoms exist dominantly in the form of carbon-oxygen double bonds, supplying sufficient Na storage sites through an addition reaction. More importantly, it is unexpected that the random carbon layers on the surface are reconstructed into a quasi-ordered arrangement by robust mechanical force, which is low-defect and favorable for suppressing the formation of thick solid electrolyte interfaces. As such, the obtained carbon presents a large reversible capacity of 363 mAh g-1 with a high ICE up to 83.1%. In addition, owing to the surface-dominated capacity contribution, an ultrafast Na storage is achieved that the capacity remains 139 mAh g-1 under a large current density of 100 A g-1 . Such good Na storage performance, especially outstanding rate capability, has rarely been achieved before.

Maximal Margin Support Vector Machine for Feature Representation and Classification.

High-dimensional small sample size data, which may lead to singularity in computation, are becoming increasingly common in the field of pattern recognition. Moreover, it is still an open problem how to extract the most suitable low-dimensional features for the support vector machine (SVM) and simultaneously avoid singularity so as to enhance the SVM's performance. To address these problems, this article designs a novel framework that integrates the discriminative feature extraction and sparse feature selection into the support vector framework to make full use of the classifiers' characteristics to find the optimal/maximal classification margin. As such, the extracted low-dimensional features from high-dimensional data are more suitable for SVM to obtain good performance. Thus, a novel algorithm, called the maximal margin SVM (MSVM), is proposed to achieve this goal. An alternatively iterative learning strategy is adopted in MSVM to learn the optimal discriminative sparse subspace and the corresponding support vectors. The mechanism and the essence of the designed MSVM are revealed. The computational complexity and convergence are also analyzed and validated. Experimental results on some well-known databases (including breastmnist, pneumoniamnist, colon-cancer, etc.) show the great potential of MSVM against classical discriminant analysis methods and SVM-related methods, and the codes can be available on https://www.scholat.com/laizhihui.

Myoelectric Pattern Recognition Using Gramian Angular Field and Convolutional Neural Networks for Muscle-Computer Interface.

In the field of the muscle-computer interface, the most challenging task is extracting patterns from complex surface electromyography (sEMG) signals to improve the performance of myoelectric pattern recognition. To address this problem, a two-stage architecture, consisting of Gramian angular field (GAF)-based 2D representation and convolutional neural network (CNN)-based classification (GAF-CNN), is proposed. To explore discriminant channel features from sEMG signals, sEMG-GAF transformation is proposed for time sequence signal representation and feature modeling, in which the instantaneous values of multichannel sEMG signals are encoded in image form. A deep CNN model is introduced to extract high-level semantic features lying in image-form-based time sequence signals concerning instantaneous values for image classification. An insight analysis explains the rationale behind the advantages of the proposed method. Extensive experiments are conducted on benchmark publicly available sEMG datasets, i.e., NinaPro and CagpMyo, whose experimental results validate that the proposed GAF-CNN method is comparable to the state-of-the-art methods, as reported by previous work incorporating CNN models.

Enhanced robust spatial feature selection and correlation filter learning for UAV tracking.

Spatial boundary effect can significantly reduce the performance of a learned discriminative correlation filter (DCF) model. A commonly used method to relieve this effect is to extract appearance features from a wider region of a target. However, this way would introduce unexpected features from background pixels and noises, which will lead to a decrease of the filter's discrimination power. To address this shortcoming, this paper proposes an innovative method called enhanced robust spatial feature selection and correlation filter Learning (EFSCF), which performs jointly sparse feature learning to handle boundary effects effectively while suppressing the influence of background pixels and noises. Unlike the ℓ2-norm-based tracking approaches that are prone to non-Gaussian noises, the proposed method imposes the ℓ2,1-norm on the loss term to enhance the robustness against the training outliers. To enhance the discrimination further, a jointly sparse feature selection scheme based on the ℓ2,1 -norm is designed to regularize the filter in rows and columns simultaneously. To the best of the authors' knowledge, this has been the first work exploring the structural sparsity in rows and columns of a learned filter simultaneously. The proposed model can be efficiently solved by an alternating direction multiplier method. The proposed EFSCF is verified by experiments on four challenging unmanned aerial vehicle datasets under severe noise and appearance changes, and the results show that the proposed method can achieve better tracking performance than the state-of-the-art trackers.

[Characteristics and Sources of DOM in Lake Sediments Under Different Inundation Environments].

The characteristics and sources of DOM in sediments are significantly affected by fluctuations in lake water levels. However, the impact of spatial differences on water levels remain unclear. Here, 36 sediment samples were collected from the flood passage and coastal beach of East Dongting Lake. The differences in the composition and source of DOM in sediments under perennial inundation and seasonal inundation were studied using UV-visible absorbance (UV-Vis) and fluorescent excitation-emission matrix (EEM)-parallel factor analysis (PARAFAC). Three fluorescent components of DOM in the sediment were identified. The relative abundance of protein-like components was as high as (72.95±8.94)%, including tryptophan (C2) and tyrosine (C3). However, the humic-like component (C1) abundance was (27.05±8.94)%. Compared with that in perennial inundation, DOM in seasonal inundation had a higher and lower relative abundance of protein-like components and humic-like components, respectively. Further, the aromatic and hydrophobic components were higher in perennial inundation, showing a spatial pattern of the middle>entrance>outlet of the lake, which was more conducive to the migration of pollutants. The high FI (1.93) and BIX (0.91) and low HIX (1.57) indicated that the DOM in sediments had the mixed characteristics of being mainly endogenic and relatively weakly terrigenous. This was mainly influenced by human input and sediment characteristics. The direct effect of sewage discharge was intensified by sediment exposure in the seasonal inundation zone. Additionally, the contents of clay and total nitrogen (TN) were significantly positively correlated with FI, indicating that high nutrients and clay in sediments enhanced the endogenous input of DOM (FI>1.9). The perennial inundation zone was influenced by external runoff input. At the same time, the pH and C/N were significantly positively correlated with HIX and C1, indicating that DOM in the sediments had higher terrigenic characteristics (HIX=1.38±0.57) than those in the seasonal inundation zone owing to the alkaline environment (pH>7.5) and runoff input. The results above revealed the relevant theories of the response of DOM in sediment to water quality and pollution in the process of hydrology and human activities and provide a scientific basis for the prevention and control of sediment pollution in lakes.

How do drying-wetting cycles influence availability of heavy metals in sediment? A perspective from DOM molecular composition.

Investigating the influence mechanism of drying-wetting cycles on the availability and mobility of heavy metals in sediment from the perspective of the molecular composition of dissolved organic matter (DOM) may gain a new understanding, but little current information exists. Here, we used spectral technologies, high-resolution mass spectrometry, and elemental stoichiometry method to trace the change rules of the molecular composition of DOM in the riparian sediment of the river. Results showed that the drying-wetting cycles could benefit the degradation of labile fractions (e.g., proteins, aliphatics, and lipids) of DOM and retain the fractions with high aromaticity and molecular size (e.g., lignin). The decrease in the availability of Cd after drying-wetting alternation processes was highly related to these changes in DOM composition. However, the availability of Zn and Cu remained almost unchanged, which probably resulted from the release and depletion of N and S in sediment-derived DOM under drying-wetting alternation conditions. As for Cr, its exchangeable fraction was unchanged during the drying-wetting alternation process, likely due to its high stability in the sediment. These results have implications on the environmental geochemical cycling of heavy metals in the riparian sediment with frequent drying-wetting alternation.

Effects of pyrolysis temperature on proton and cadmium binding properties onto biochar-derived dissolved organic matter: Roles of fluorophore and chromophore.

Understanding the environmental behavior of biochar-derived dissolved organic matter (BDOM) is crucial for promoting the extensive utilization of biochar and meeting the carbon neutrality targets. However, limited studies focused on the binding mechanism of protons and Cd with DOM released from biochar produced at different pyrolysis temperatures. By combining excitation-emission matrix spectroscopy and parallel factor analysis, we found that the humic-like fluorophores in BDOM had higher aromaticity, molecular weight, and contents of carboxylic and phenolic groups relative to the protein-like fluorophores. Conversely, the protein-like fluorophores exhibited a stronger binding affinity for Cd than humic-like fluorophores. With the pyrolysis temperature increased from 300 °C to 500 °C, the quenching effects of Cd on the protein-like components were enhanced significantly. Their fluorescence intensities could be quenched up to 51.64%. The results of ultraviolet-visible absorbance spectroscopy and differential absorbance spectroscopy showed that the carboxylic-like and phenolic-like chromophores were involved in the protons and Cd binding process of BDOM. The binding ability of phenolic-like chromophores with Cd was reduced as a function of increasing pyrolysis temperature. These findings implied that these carboxylic and phenolic groups were mainly contained in the non-fluorescent components. Besides, protons and Cd could also induce inter-chromophore interactions in BDOM, and the interaction was proportional to the pyrolysis temperature. These results clearly demonstrated the pyrolysis temperature-dependent changes in the protons and Cd binding properties of BDOM. More importantly, the possible risk of Cd mobility caused by the protein-like components in BDOM cannot be ignored when the biochar was applied in contaminated soils. This research extends our knowledge of the application potentiality of biochar in heavy metal polluted soil.

Fe oxides and fulvic acids together promoted the migration of Cd(II) to the root surface of Phragmites australis.

Dissolved organic matter (DOM) or iron/manganese (hydro)oxides were important factors in the migration of Cd in sediments of wetlands. DOM and Fe oxides simultaneously affect the longitudinal and transverse migration of Cd in wetlands sediments of plants was still unclear. In this study, a 14-day rhizobox experiment was conducted and the result showed that the rhizosphere effect of Cd migration was only limited to the upper layer of sediments (- 2 to - 4 cm). Fe with fulvic acid (FA) simultaneously existed can precipitate Cd(II) from supernatant to sediments downward. Fe oxides at sediment concentration could effectively prevent Cd(II) from migrating to root surface (0.21 vs 0.02 at%). While Fe oxides with FA together at sediment concentration could effectively promoted the migration of Cd(II) to root surface (0.07 vs 0.08 at%). The formation of organo-metallic complexes of Fe in the presence of FA profoundly proved this finding (increased by ~33.0%). And the polysaccharides and aromatics in organic matter were the chief functional groups participating in the incorporation of Cd and Fe oxides. The findings reveal the migration rules of Cd(II) in sediments by FA and Fe oxides and give an insight into the mechanisms of Cd(II) migration to the root surface around wetland plants.

Dipeptidyl peptidase-4 inhibitor cardiovascular safety in patients with type 2 diabetes, with cardiovascular and renal disease: a retrospective cohort study.

Clinical trials investigating cardiovascular safety of dipeptidyl peptidase-IV inhibitors (DPP-4i) among patients with cardiovascular and renal disease rarely recruit patients with renal impairment, despite associations with increased risk for major adverse cardiovascular events (MACE). We investigated the risk of MACE associated with the use of DPP-4i among these high-risk patients. Using a new-user, retrospective, cohort design, we analyzed 2010-2015 IBM MarketScan Commercial Claims and Encounters for patients with diabetes, comorbid with cardiovascular disease and/or renal impairment. We compared time to first MACE for DPP-4i versus sulfonylurea and versus metformin. Of 113,296 individuals, 9146 (8.07%) were new DPP-4i users, 17,481 (15.43%) were new sulfonylurea users, and 88,596 (78.20%) were new metformin users. Exposure groups were not mutually exclusive. DPP-4i was associated with lower risk for MACE than sulfonylurea (aHR 0.84; 95% CI 0.74, 0.93) and similar risk for MACE to metformin (aHR 1.07; 95% CI [1.04, 1.16]). DPP-4i use was associated with lower risk for MACE compared to sulfonylureas and similar risk for MACE compared to metformin. This association was most evident in the first year of therapy, suggesting that DPP-4i is a safer choice than sulfonylurea for diabetes treatment initiation in high-risk patients.

[Promotion and Mechanisms of DOM on Copper Adsorption by Suspended Sediment Particles].

The adsorption of heavy metals by suspended sediment particles is a key process in the migration of heavy metals in lakes and is affected by various environmental conditions. To reveal the effects and mechanisms of dissolved organic matter (DOM) on the adsorption of copper ions by suspended sediment particles, a Cu(Ⅱ) adsorption test was conducted through a laboratory simulation test. The results showed that DOM promoted the adsorption of Cu(Ⅱ) onto the suspended particles. Under the respective influences of fulvic acid and DOM extracted from the sediment of the Xiangjiang River, the adsorption percentage of Cu(Ⅱ) increased from 71.51% to 75.31% and 85.69%. Scanning electron microscope-energy spectroscopy results showed that under the influence of DOM, Cu(Ⅱ) existed inside the sediment particles after being adsorbed. The results of UV-visible (UV-Vis) spectroscopy showed that Cu(Ⅱ) and DOM were first complexed and then dissociated during the adsorption reaction. The results of fluorescent excitation-emission matrix spectroscopy combined with parallel factor analysis and synchronous fluorescence spectroscopy combined with two-dimensional correlation analysis indicate that protein-like components promoted the adsorption of Cu(Ⅱ) onto the sediment suspended particles. In particular, tyrosine-like components played a critical role in promoting adsorption. However, humic-like components hardly promote this adsorption. This study has improved the theory of heavy metal migration in lakes and can be used as a basis for the prevention and control of heavy metal pollution in sediments.

Laboratory and simulation study on the Cd(â ¡) adsorption by lake sediment: Mechanism and influencing factors.

Sediments are the major sinks for Cd(Ⅱ) in the aquatic environment. Here, the detailed binding mechanisms and effects of environmental factors on Cd(Ⅱ) adsorption onto lake sediment were tested by a batch of adsorption and characteristic experiments. Sediment samples and sediment-Cd complexes were characterized using Scanning electron microscopy, Energy dispersive spectroscopy, X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, and X-ray diffraction spectral analyses. The interactive and main effect of parameters such as pH, flow velocity, Cd(II) concentration, sediment particle size, humic acid, fulvic acid and adsorption time involved in the adsorption process were determined using two models based on response surface methodology (RSM) and a back-propagation neural network with genetic algorithm (GABP). Results showed that Cd(II) adsorption onto sediment was mainly achieved through surface complexation with O-containing groups and precipitation with carbonate and sulfide. RSM was favorable for modeling Cd(II) adsorption in lake systems because it intuitively reflected the influence of the factors and had a good fitting precision (R2 = 0.8838, RSME = 2.5496) close to that of the GABP model (R2 = 0.8959, RSME = 2.5410). pH, sediment particle size, and humic acid exerted strong influences on Cd(II) immobilized by the sediment. Overall, our findings facilitate a better understanding of Cd(II) mobility in lakes and provide a reference for controlling heavy metals derived from both aqueous and sediment sources.

Comparative effectiveness of biologics and targeted therapies for psoriatic arthritis.

OBJECTIVE: To quantify comparative effectiveness of interleukin (IL)-12/23 antagonist (ustekinumab), IL-17A antagonists (secukinumab and ixekizumab), PDE4 inhibitor (apremilast) and tumour necrosis factor-alpha (TNF-α) inhibitors (infliximab, etanercept, adalimumab, certolizumab pegol and golimumab) for psoriatic arthritis (PsA). METHODS: We adapted a deidentified claims-based algorithm validated for inflammatory arthritis treatments to compare treatments among a retrospective cohort of commercially insured and Medicare Advantage beneficiaries with PsA from October 2013 to April 2019 in the OptumLabs Data Warehouse. Main outcomes include (1) treatment effectiveness, based on: adherence, adding or switching biologic or PDE4, addition of new non-biologic disease-modifying antirheumatic drug, increase in biologic or PDE4 dose or frequency and glucocorticoid use and (2) percentage of each group fulfilling the effectiveness algorithm. We used Poisson regression with robust variance stratified by prior PsA biologic exposure and adjusted for potential confounders. RESULTS: Of 2730 individuals with PsA, 327 received IL-12/23, 138 IL-17A's, 624 PDE4 and 1641 TNF-α's. Effectiveness criteria were fulfilled among 63 (19.3%) IL-12/23 recipients, 40 (29.0%) IL-17A recipients, 160 (25.6%) PDE4 recipients and 530 (32.3%) TNF-α recipients. Among biologic-naïve individuals, IL-12/23 was less effective than TNF-α's with fully adjusted relative risk (aRR) compared with TNF-α's of 0.63 (95% CI 0.45 to 0.89). Among biologic-experienced individuals, PDE4 recipients were less effective than TNF-α's (aRR 0.67, 95% CI 0.46 to 0.96). CONCLUSIONS: TNF-α's appeared more effective than IL-12/23's for biologic-naïve individuals, and PDE4's for biologic-experienced individuals. These results may help inform treatment choice for individuals with PsA.

Development of a Copper-Based Metal Organic Electrode for Nitrite Sensing.

BACKGROUND: Nitrite is naturally present in vegetables and added to processed meats to enhance their color and prolong their shelf life. It is of concern because it reacts to form nitrosamines, which have been linked to cancer. OBJECTIVE: To develop a quick, reliable, and inexpensive method for quantifying nitrite in foods. METHOD: A copper-based metal organic framework (Cu-MOF)/gold-platinum alloy nanoparticle(Au@Pt)-modified glassy carbon electrode (GCE) was developed via a simple wet chemical synthesis followed by electrochemical deposition of gold-platinum alloy nanoparticles onto the surface of a GCE. Morphological characterization and component analysis of the prepared nanomaterials were carried out by Fourier transform infrared spectroscopy and scanning electron microscopy. Cyclic voltammetry and electrochemical impedance spectroscopy were used to study the electrochemical behavior of the fabricated electrodes. RESULTS: The quantitative and specific detection of nitrite was obtained by the amperometric i-t method. At a pH of 7, temperature of 25°C, and ionic strength of 0.4 M, the electrode exhibited a linear range of 0.001-12.2 mM nitrite with a low detection limit of 72 nM (S/N = 3). CONCLUSIONS: The Cu-MOF/Au@Pt/GCE exhibited good repeatability, reproducibility, stability, and selectivity to provide a capable analysis method for food samples. HIGHLIGHTS: A Cu-MOF with a large surface area and high porosity was developed to provide an electrode with many active sites. The Au@Pt alloy nanoparticle improved the electrocatalytic activity toward nitrite. The synergistic action between the Cu-MOF and Au@Pt alloy nanoparticle enhanced the electrochemical performance of the sensor.

Effect of redundant clinical trials from mainland China evaluating statins in patients with coronary artery disease: cross sectional study.

OBJECTIVE: To identify redundant clinical trials evaluating statin treatment in patients with coronary artery disease from mainland China, and to estimate the number of extra major adverse cardiac events (MACEs) experienced by participants not treated with statins in those trials. DESIGN: Cross sectional study. SETTING: 2577 randomized clinical trials comparing statin treatment with placebo or no treatment in patients with coronary artery disease from mainland China, searched from bibliographic databases to December 2019. PARTICIPANTS: 250 810 patients with any type of coronary artery disease who were enrolled in the 2577 randomized clinical trials. MAIN OUTCOME MEASURES: Redundant clinical trials were defined as randomized clinical trials that initiated or continued recruiting after 2008 (ie, one year after statin treatment was strongly recommended by clinical practice guidelines). The primary outcome is the number of extra MACEs that were attributable to the deprivation of statins among patients in the control groups of redundant clinical trials-that is, the number of extra MACEs that could have been prevented if patients were given statins. Cumulative meta-analyses were also conducted to establish the time points when statins were shown to have a statistically significant effect on coronary artery disease. RESULTS: 2045 redundant clinical trials were identified published between 2008 and 2019, comprising 101 486 patients in the control groups not treated with statins for 24 638 person years. 3470 (95% confidence interval 3230 to 3619) extra MACEs were reported, including 559 (95% confidence interval 506 to 612) deaths, 973 (95% confidence interval 897 to 1052) patients with new or recurrent myocardial infarction, 161 (132 to 190) patients with stroke, 83 (58 to 105) patients requiring revascularization, 398 (352 to 448) patients with heart failure, 1197 (1110 to 1282) patients with recurrent or deteriorated angina pectoris, and 99 (95% confidence interval 69 to 129) unspecified MACEs. CONCLUSIONS: Of more than 2000 redundant clinical trials on statins in patients with coronary artery disease identified from mainland China, an extra 3000 MACEs, including nearly 600 deaths, were experienced by participants not treated with statins in these trials. The scale of redundancy necessitates urgent reform to protect patients.

Phosphate hinders the complexation of dissolved organic matter with copper in lake waters.

The properties of phosphate in lakes and their ability to cause eutrophication have been well studied; however, the effects of phosphate on the environmental behavior of other substances in lakes have been ignored. Dissolved organic matter (DOM) and heavy metals may coexist with phosphate in lakes. Herein, the mechanisms underlying the influence of phosphate on heavy metals complexation with DOM were investigated using multi-spectroscopic tools. Overall, the amount of DOM-bound Cu(Ⅱ) decreased with the increasing phosphate content. Furthermore, the fluorescence excitation and emission matrix results combined with parallel factor analysis showed that when the Cu(Ⅱ) concentration increased from 0 to 5 mg/L and 50 µM phosphate to the reaction of DOM and copper, the fluorescence intensity of tyrosine (component 1), humic-like (component 2) and tryptophan (component 3) decreased by 36.46%, 57.34%, and 74.70% compared with the treatment with no phosphate addition, respectively. This finding indicates that the binding of different fluorescent components to Cu(Ⅱ) was restricted by phosphate. Furthermore, different functional groups responded differently to Cu(Ⅱ) under different phosphate concentrations. The binding sequence of different functional groups under high concentration of phosphate (phenolic hydroxyl group＞amide (Ⅰ) ＞carbohydrates) was completely opposite to that with no phosphate. These results demonstrated that phosphate could restrict the binding affinity of heavy metals with different fluorescent substances or organic ligands of DOM, suggesting that the comigration of DOM-bound heavy metals in lakes is hindered by phosphate and the risk of heavy metal poisoning in aquatic organisms is therefore diminished.

Restriction of dissolved organic matter on the stabilization of Cu(II) by phosphate.

The precipitation of Cu(II) by phosphate and the influence of dissolved organic matter (DOM) on the precipitation are essential for the fate of Cu(II) in aquatic environments. In this study, the influence of DOM on the reaction of phosphate with Cu(II) was investigated. Here, 51.61%, 29.75%, and 24.32% of the added Cu(II) (50 µM) precipitated without DOM and with the addition of fulvic acid (FA) and humic acid (HA), respectively, owing to the reaction with phosphate (50 µM). Excitation-emission matrix spectroscopy-parallel factor (PARAFAC) and two-dimensional ultraviolet-visible correlation spectroscopy analyses were conducted to characterize the influence of DOM on the precipitation of Cu(II) with phosphate. One humic-like and two protein-like fluorescent components were identified by the PARAFAC model for FA, whereas two humic-like fluorescent components and one protein-like fluorescent component were validated for HA. The humic-like components had primary roles, whereas the protein-like components had secondary roles in limiting the precipitation of Cu(II) with phosphate. Cu(II) binding to DOM chromophores initially occurred at shorter wavelengths, and then at longer wavelengths. Phenolic and carboxylic constituents had important roles, and HA exhibited more binding sites than FA. Therefore, humic-like fluorescent components and chromophores containing phenolic and carboxylic groups and functional groups with peaks at short wavelengths (200-220 nm) were primarily responsible for restricting the precipitation of Cu(II) with phosphate.

Recent advances in nanomaterial-based biosensors for the detection of exosomes.

Exosomes are a type of extracellular vesicle actively secreted by almost all eukaryotic cells. They are ideal candidates for reliable next-generation biomarkers in the early diagnosis and therapeutic response evaluation of cancer. Thus, the quantification of exosomes is crucial in facilitating clinical research and application. Compared with traditional materials, nanomaterials have better optical, magnetic, electrical, and catalytic properties due to their small size, high specific surface area, and variable structure. The incorporation of nanomaterials into sensing systems is an attractive approach towards improving sensitivity and can provide improved sensor selectivity and stability. In this paper, we summarize the progress in nanomaterial-based exosome detection methods, including electrochemical biosensors, photoelectrochemical biosensors, colorimetric biosensors, fluorescence biosensors, chemiluminescence biosensors, electrochemiluminescence biosensors, surface plasmon resonance biosensors, and surface-enhanced Raman spectroscopy biosensors. Moreover, future research directions and challenges in exosome detection methods are discussed. We hope that this article will offer an overview of nanomaterial-based exosome detection techniques and open new avenues in disease research.Graphical abstract.

Molecular insights into the effects of pyrolysis temperature on composition and copper binding properties of biochar-derived dissolved organic matter.

Biochar-derived dissolved organic matter (BDOM), which has a substantial impact on the environmental behavior of heavy metals, is critical for understanding the environmental efficacy of biochar. Here, we used a suite of advanced spectroscopic and mass spectroscopic methods to investigate the relationship among the pyrolysis temperature of biochar, composition of BDOM, and interactions of BDOM with Cu. The binding affinity of BDOM and Cu showed incredibly increase, with the increasing pyrolysis temperature (300-500 °C) which promoted the release of condensed aromatic compounds and oxygen-containing functional groups from biochar into dissolved phase. A notable difference in the sequences binding with Cu was occurred during the changing pyrolysis temperature. The amide only involved in the binding process between Cu and BDOM at low-temperature (300 and 400 °C), whereas phenolic only associated with the such binding process at high-temperature (500 °C). Apart from this, the carboxyl and polysaccharides took part in the binding process of Cu with BDOM, no matter how higher the temperature is. A further analysis by X-ray absorption spectroscopy revealed that bidentate carboxylic-Cu complexes appear to be the predominant binding pattern for Cu to BDOM. Our results might contribute to provide novel information for the environment applications of biochar.

Association between switching of primary outcomes and reported trial findings among randomized drug trials from China.

BACKGROUND AND OBJECTIVE: To evaluate the association between the nature of findings and the switching of registered primary outcomes among randomized controlled trials (RCTs) from mainland China. METHODS: This is a retrospective cohort study. We retrieved RCTs from trial registries and identified the corresponding journal articles from bibliographic databases until August 2019. Trial registries and journal articles were compared to evaluate whether registered primary outcomes with negative findings were more likely to be switched to secondary outcomes in the subsequent journal articles than those with positive findings. RESULTS: Switching of registered primary outcomes occurred in 131 (45%) of 294 RCTs. A total of 450 registered primary outcomes were matched to 522 (37%) primary outcomes and 871 (63%) secondary outcomes in the journal articles. Among RCTs registered before they started, the odds of switching primary outcomes with negative findings were 2.64 (95% CI: 1.16-6.02) times the odds of switching those with positive findings. Among RCTs registered when they were ongoing, the odds of switching primary outcomes with negative findings were 8.84 (95% CI: 3.62-25.93) times the odds of switching those with positive findings. CONCLUSION: The nature of findings may play a role in how likely a prespecified primary outcome is switched subsequently.