Fast detection of sodium dithionite in sugar using a xanthylium-based fluorescent probe.

Dithionite remained in the foodstuff may pose a great threat to the health of consumers. Three xanthylium-based probes were synthesized and their responses to dithionite were explored. Probe SH-1 could respond to dithionite selectively in PBS buffer (15% DMSO, 10 mM, pH = 7.4). Upon the addition of dithionite, the fluorescent emission of SH-1 at 684 nm dropped quickly (within 10 s) and the fluorescence decline was proportional to the concentration of dithionite (0-7.0 µM). The limit of detection was determined to be 0.139 µM. Then, the sensing mechanism was tentatively presented and the structure of resulted adduct (SH-1-SO3-) which was the reaction product of SH-1 and dithionite via a Micheal addition reaction followed by an oxidation reaction was verified. Moreover, white granulated sugar was subjected to the standard spike experiments and the results demonstrated a great potential of SH-1 for the quantitative monitoring of dithionite in foodstuffs.

Sludge dewaterability improvement with microbial fuel cell powered electro-Fenton system (MFCⓠEFs): Performance and mechanisms.

Throughout the entire process of sludge treatment and disposal, it is crucial to explore stable and efficient techniques to improve sludge dewaterability, which can facilitate subsequent resource utilization and space and cost savings. Traditional Fenton oxidation has been widely researched to enhance the performance of sludge dewaterability, which was limited by the additional energy input and the instabilities of Fe2+ and H2O2. To reduce the consumption of energy and chemicals and further break the rate-limiting step of the iron cycle, a novel and feasible method that constructed microbial fuel cell powered electro-Fenton systems (MFCⓅEFs) with ferrite and biochar electrode (MgFe2O4@BC/CF) was successfully demonstrated. The MFCⓅEFs with MgFe2O4@BC/CF electrode achieved specific resistance filtration and sludge cake water content of 2.52 × 1012 m/kg and 66.54 %. Cellular structure and extracellular polymeric substances (EPS) were disrupted, releasing partially bound water and destroying hydrophilic structures to facilitate sludge flocs aggregation, which was attributed to the oxidation of hydroxyl radicals. The consistent electron supply supplied by MFCⓅEFs and catalytically active sites on the surface of the multifunctional functional group electrode was responsible for producing more hydroxyl radicals and possessing a better oxidizing ability. The study provided an innovative process for sludge dewaterability improvement with high efficiency and low energy consumption, which presented new insights into the green treatment of sludge.

Identification and Regulation of Hypoxia-Tolerant and Germination-Related Genes in Rice.

In direct seeding, hypoxia is a major stress faced by rice plants. Therefore, dissecting the response mechanism of rice to hypoxia stress and the molecular regulatory network is critical to the development of hypoxia-tolerant rice varieties and direct seeding of rice. This review summarizes the morphological, physiological, and ecological changes in rice under hypoxia stress, the discovery of hypoxia-tolerant and germination-related genes/QTLs, and the latest research on candidate genes, and explores the linkage of hypoxia tolerance genes and their distribution in indica and japonica rice through population variance analysis and haplotype network analysis. Among the candidate genes, OsMAP1 is a typical gene located on the MAPK cascade reaction for indica-japonica divergence; MHZ6 is involved in both the MAPK signaling and phytohormone transduction pathway. MHZ6 has three major haplotypes and one rare haplotype, with Hap3 being dominated by indica rice varieties, and promotes internode elongation in deep-water rice by activating the SD1 gene. OsAmy3D and Adh1 have similar indica-japonica varietal differentiation, and are mainly present in indica varieties. There are three high-frequency haplotypes of OsTPP7, namely Hap1 (n = 1109), Hap2 (n = 1349), and Hap3 (n = 217); Hap2 is more frequent in japonica, and the genetic background of OsTPP7 was derived from the japonica rice subpopulation. Further artificial selection, natural domestication, and other means to identify more resistance mechanisms of this gene may facilitate future research to breed superior rice cultivars. Finally, this study discusses the application of rice hypoxia-tolerant germplasm in future breeding research.

On the Robustness of Average Losses for Partial-Label Learning.

Partial-label learning (PLL) utilizes instances with PLs, where a PL includes several candidate labels but only one is the true label (TL). In PLL, identification-based strategy (IBS) purifies each PL on the fly to select the (most likely) TL for training; average-based strategy (ABS) treats all candidate labels equally for training and let trained models be able to predict TL. Although PLL research has focused on IBS for better performance, ABS is also worthy of study since modern IBS behaves like ABS in the beginning of training to prepare for PL purification and TL selection. In this paper, we analyze why ABS was unsatisfactory and propose how to improve it. Theoretically, we propose two problem settings of PLL and prove that average PL losses (APLLs) with bounded multi-class losses are always robust, while APLLs with unbounded losses may be non-robust, which is the first robustness analysis for PLL. Experimentally, we have two promising findings: ABS using bounded losses can match/exceed state-of-the-art performance of IBS using unbounded losses; after using robust APLLs to warm start, IBS can further improve upon itself. Our work draws attention to ABS research, which can in turn boost IBS and push forward the whole PLL.

Recent Advances in Fluorescent Nanoprobes for Food Safety Detection.

Fluorescent nanoprobes show similar fluorescence properties to traditional organic dyes, but the addition of nanotechnology accurately controls the size, shape, chemical composition, and surface chemistry of the nanoprobes with unique characteristics and properties, such as bright luminescence, high photostability, and strong biocompatibility. For example, modifying aptamers or antibodies on a fluorescent nanoprobe provides high selectivity and specificity for different objects to be tested. Fluorescence intensity, life, and other parameters of targets can be changed by different sensing mechanisms based on the unique structural and optical characteristics of fluorescent nanoprobes. What's more, the detection of fluorescent nanoprobes is cost-saving, simple, and offers great advantages in rapid food detection. Sensing mechanisms of fluorescent nanoprobes were introduced in this paper, focusing on the application progress in pesticide residues, veterinary drug residues, heavy metals, microbes, mycotoxins, and other substances in food safety detection in recent years. A brief outlook for future development was provided as well.

Constructing Oxygen Vacancies via Engineering Heterostructured Fe3 C/Fe3 O4 Catalysts for Electrochemical Ammonia Synthesis.

Electrocatalytic nitrogen reduction reaction (NRR) under ambient conditions provides an intriguing pathway to convert N2 into NH3 . However, significant kinetic barriers of the NRR at low temperatures in desirable aqueous electrolytes remain a grand challenge due to the inert N≡N bond of the N2 molecule. Herein, we propose a unique strategy for in situ oxygen vacancy construction to address the significant trade-off between N2 adsorption and NH3 desorption by building a hollow shell structured Fe3 C/Fe3 O4 heterojunction coated with carbon frameworks (Fe3 C/Fe3 O4 @C). In the heterostructure, the Fe3 C triggers the oxygen vacancies of the Fe3 O4 component, which are likely active sites for the NRR. The design could optimize the adsorption strength of the N2 and Nx Hy intermediates, thus boosting the catalytic activity for the NRR. This work highlights the significance of the interaction between defect and interface engineering for regulating electrocatalytic properties of heterostructured catalysts for the challenging NRR. It could motivate an in-depth exploration to advance N2 reduction to ammonia.

Designed Tetranuclear Iron-oxo Clusters with Redox Activity for High-Performance Lithium Storage.

Polyoxometalates (POMs) are considered as promising catalysts with unique redox activity at the molecular level for energy storage. However, eco-friendly iron-oxo clusters with special metal coordination structures have rarely been reported for Li-ion storage. Herein, three novel redox-active tetranuclear iron-oxo clusters have been synthesized using the solvothermal method with different ratios of Fe3+ and SO4 2- . Further, they can serve as anode materials for Li-ion batteries. Among them, cluster H6 [Fe4 O2 (H2 O)2 (SO4 )7 ]⋅H2 O, the stable structure extended by SO4 2- with a unique 1D pore, displays a specific discharge capacity of 1784 mAh g-1 at 0.2 C and good cycle performance (at 0.2 C and 4 C). This is the first instance of inorganic iron-oxo clusters being used for Li-ion storage. Our findings present a new molecular model system with a well-defined structure and offer new design concepts for the practical application of studying the multi-electron redox activity of iron-oxo clusters.

Insights into the multirole CoAl layered double hydroxide on boosting photoelectrochemical activity of hematite: Application to hydrogen peroxide sensing.

As an important compound in many industrial and biological processes, hydrogen peroxide (H2O2) would cause harmfulness to human health at high concentration level. It thus is urgent to develop highly sensitive and selective sensors for practical H2O2 detection in the fields of water monitoring, food quality control, and so on. In this work, CoAl layered double hydroxide ultrathin nanosheets decorated hematite (CoAl-LDH/α-Fe2O3) photoelectrode was successfully fabricated by a facile hydrothermal process. CoAl-LDH/α-Fe2O3 displays the relatively wide linear range from 1 to 2000 µM with a high sensitivity of 132.0 µA mM-1 cm-2 and a low detection limit of 0.04 µM (S/N ≥ 3) for PEC detection of H2O2, which is superior to other similar α-Fe2O3-based sensors in literatures. The (photo)electrochemical characterizations, such as electrochemical impedance spectroscopy, Mott-Schottky plot, cyclic voltammetry, open circuit potential and intensity modulated photocurrent spectroscopy, were used to investigate the roles of CoAl-LDH on the improved PEC response of α-Fe2O3 toward H2O2. It revealed that, CoAl-LDH could not only passivate the surface states and enlarge the band bending of α-Fe2O3, but also could act as trapping centers for holes and followed by as active sites for H2O2 oxidation, thus facilitated the charge separation and transfer. The strategy for boosting PEC response would be help for the further development of semiconductor-based PEC sensors.

Importance of amylose chain-length distribution in determining starch gelatinization and retrogradation property of wheat flour in the presence of different salts.

Although starch gelatinization and retrogradation properties of wheat flour have been studied with respect to their relations to starch structures, it remains less understood how starch structure and salt (a common food additive) together determine these properties. Gelatinization and retrogradation properties of seven wheat flours with distinct starch structures were thus investigated after adding different salts. NaCl most efficiently increased starch gelatinization temperatures, while KCl showed highest efficiency in retarding the retrogradation degree. Both gelatinization and retrogradation parameters were significantly affected by amylose structural parameters and types of salts. E.g., wheat flours with longer amylose long chains had more heterogeneous amylopectin double helices during gelatinization, while this relationship disappeared after adding NaCl. More amylose short chains increased the heterogeneity of retrograded short-range starch double helices, while the relationship was opposite after adding NaCl. These results help a better understanding of the complex relationship between starch structure and physicochemical property.

N, F Codoped FeOOH Nanosheets with Intercalated Carbonate Anions Rich in Oxygen Defects for Enhanced Alkaline Electrocatalytic Water Splitting.

Alkaline water splitting is a highly efficient and clean technology for hydrogen energy generation. However, in alkaline solutions, most catalysts suffer from extreme instability. Herein, a cross-nanostructured N, F, and CO32- codoped iron oxyhydroxide composite (N,F-FeO(OH)-CO3-NF) rich in oxygen defects is designed for water splitting in the alkaline solution. X-ray photoelectron spectroscopy (XPS) and density functional theory (DFT) calculations show that the introduction of F and CO32- can induce electron redistribution around the active center Fe, accelerate the four-electron transfer process, and optimize the d-band center, thereby improving the efficiency and stability of HER and OER. In a 1 M KOH solution, N,F-FeO(OH)-CO3-NF only needs the overpotential of 248 mV for OER and the overpotential of 199 mV for HER to reach the current density of 10 mA·cm-2. Meanwhile, it can reach 100 mA·cm-2 current density at 1.55 V vs RHE and maintains a current density of 10 mA·cm-2 for 120 h in a two-electrode electrolytic water device. Compared with bulk hydroxides, the heteroatom and anion codoped composite hydroxides are more stable and have dual functions in the electrolyte solution. This is of great significance for designing a new stable water-splitting electrocatalyst.

Learning With Proper Partial Labels.

Partial-label learning is a kind of weakly supervised learning with inexact labels, where for each training example, we are given a set of candidate labels instead of only one true label. Recently, various approaches on partial-label learning have been proposed under different generation models of candidate label sets. However, these methods require relatively strong distributional assumptions on the generation models. When the assumptions do not hold, the performance of the methods is not guaranteed theoretically. In this letter, we propose the notion of properness on partial labels. We show that this proper partial-label learning framework requires a weaker distributional assumption and includes many previous partial-label learning settings as special cases. We then derive a unified unbiased estimator of the classification risk. We prove that our estimator is risk consistent, and we also establish an estimation error bound. Finally, we validate the effectiveness of our algorithm through experiments.

Identification of key pathways and genes in the progression of silicosis based on WGCNA.

Silicosis, induced by inhaling silica particles in workplaces, is one of the most common occupational diseases. The prognosis of silicosis and its consequent fibrosis is extremely poor due to limited treatment modalities and lack of understanding of the disease mechanisms. In this study, a Wistar rat model for silicosis fibrosis was established by intratracheal instillation of silica (0, 50, 100 and 200 mg/mL, 1 mL) with the evidence of Hematoxylin and Eosin (HE) and Masson staining and the expressions of inflammatory and fibrotic proteins of rats' lung tissues. RNA of lung tissues of rats exposed to 200 mg/mL silica particles and normal saline for 14 d and 28 d was extracted and sequenced to detect differentially expressed genes (DEGs) and to identify silicosis fibrosis-associated modules and hub genes by Weighted gene co-expression network analysis (WGCNA). Predictions of gene functions and signaling pathways were conducted using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. In this study, it has been demonstrated the promising role of the Hippo signaling pathway in silicosis fibrosis, which will be conducive to elucidating the specific mechanism of pulmonary fibrosis induced by silica and to determining molecular initiating event (MIE) and adverse outcome pathway (AOP) of silicosis fibrosis.

The Task Pre-Configuration Is Associated With Cognitive Performance Evidence From the Brain Synchrony.

Although many resting state and task state characteristics have been studied, it is still unclear how the brain network switches from the resting state during tasks. The current theory shows that the brain is a complex dynamic system and synchrony is defined to measure brain activity. The study compared the changes of synchrony between the resting state and different task states in healthy young participants (N = 954). It also examined the ability to switch from the resting state to the task-general architecture of synchrony. We found that the synchrony increased significantly during the tasks. And the results showed that the brain has a task-general architecture of synchrony during different tasks. The main feature of task-based reasoning is that the increase in synchrony of high-order cognitive networks is significant, while the increase in synchrony of sensorimotor networks is relatively low. In addition, the high synchrony of high-order cognitive networks in the resting state can promote task switching effectively and the pre-configured participants have better cognitive performance, which shows that spontaneous brain activity and cognitive ability are closely related. These results revealed changes in the brain network configuration for switching between the resting state and task state, highlighting the consistent changes in the brain network between different tasks. Also, there was an important relationship between the switching ability and the cognitive performance.

Biomarkers of exposure and effect in the serum and urine of rats or workers exposed to 1-bromopropane.

Extensively used in several industries in China as a cleaning agent, 1-bromopropane (1-BP) has significant adverse effects on the central nervous system. However, neither its mechanism of action nor sensitive biomarkers related to it have been determined thus far. In this study, animal experiments and occupational surveys were performed to explore the typical exposure and effect biomarkers of neurotoxicity induced by 1-BP. Male Wistar rats were exposed to 0, 500, or 1000 ppm of 1-BP followed by pathological and biomarker analyses. An epidemiological survey was conducted on 71 workers each from 1-BP exposed and control groups. Serum and urine samples were collected for biomarker testing. cNSE represents neuron-specific enolase (NSE) in the cerebral cortex, where as sNSE represents NSE in the serum; similar terminology applies to S-100ß, and cyclooxygenase-2 (COX-2). In rats exposed to 1000 ppm 1-BP, pathological changes were observed in Purkinje cells, lumbar gray matter, and tibiofibular nerve, while levels of cNSE, cS-100ß, cCOX-2, sS-100ß, and sCOX-2 were significantly elevated at different time checkpoints. In the 500 ppm group, cCOX-2, sNSE, and sCOX-2 levels were significantly elevated at different time checkpoints. 1-BP and N-acetyl-S-(n-propyl)-L-cysteine (AcPrCys) were detected in rat urine, and there was a correlation between the level of sNSE or sCOX-2 and AcPrCys in the 500 ppm group. In the occupational epidemiological study, a significant correlation between AcPrCys and exposure concentration was also detected. The findings of this study indicated that AcPrCys was a sensitive exposure biomarker of 1-BP in rats as well as occupational populations.

Study on a Strain of Lysinibacillus sp. with the Potential to Improve the Quality of Oil Sands.

A strain of Lysinibacillus sp., named as Y316, can degrade heavy fractions such as resins and asphaltenes in oil sand. We used Y316 to degrade oil sand samples for 35 days. After bacterial degradation, the oil sand degradation efficiency was 5.88%, while the degradation efficiency of the control group was only 0.29% under the same conditions. Compared with the control group, the saturated content of oil sand in the degradation group increased from 9.56 to 14.39%. After degradation, the resin and asphaltene fractions decreased by 5.34 and 4.77%, respectively. The results of the vaporizable fraction analysis also confirmed the degradation of heavy fractions and the formation of light fractions. After 35 days of degradation, the vaporizable fractions of saturates increased by 3.76 times. The results indicate that Y316 has great significance for improving the quality of oil sands and assisting in oil sand exploitation.

Molecular Iron Oxide Clusters Boost the Oxygen Reduction Reaction of Platinum Electrocatalysts at Near-Neutral pH.

The oxygen reduction reaction (ORR) is a key energy conversion process, which is critical for the efficient operation of fuel cells and metal-air batteries. Here, we report the significant enhancement of the ORR-performance of commercial platinum-on-carbon electrocatalysts when operated in aqueous electrolyte solutions (pH 5.6), containing the polyoxoanion [Fe28 (µ3 -O)8 (L-(-)-tart)16 (CH3 COO)24 ]20- . Mechanistic studies provide initial insights into the performance-improving role of the iron oxide cluster during ORR. Technological deployment of the system is demonstrated by incorporation into a direct formate microfluidic fuel cell (DFMFC), where major performance increases are observed when compared with reference electrolytes. The study provides the first examples of iron oxide clusters in electrochemical energy conversion and storage.

A Promising transwell co-culture cell model for silicosis.

Silicosis, one of the most ancient occupational diseases, has not been elucidated and addressed until now. Although some medicines were partly effective in the clinical treatment and certain plausible mechanisms were partially ascertained, it is still urgent and necessary to explore its real and specific pathogenesis. With the development of the cell co-culture technique, the transwell co-culture system has been applied in several scientific fields, which is able to simulate the pathogenic process in vivo to the largest extent. In this sense, a transwell co-culture cell model for silicosis including RFL-6 (lung fibroblasts of rats), RLE-6TN (type II alveolar epithelial cells of rats) and NR8383 (alveolar macrophages of rats) cells was successfully established and the developmental process of silicosis in this model could be roughly divided into three stages: inflammatory stage, progressive stage and fibrotic stage, as evidenced by the morphological features and the inflammatory cytokines and fibrotic proteins of supernatants and the cells in this system. Results of this project will pave the way for clarifying the mechanism of silicosis and building a practical platform for the further exploration of molecular initiating event (MIE) and adverse outcome pathway (AOP) of silicosis.

Multilabel Ranking With Inconsistent Rankers.

While most existing multilabel ranking methods assume the availability of a single objective label ranking for each instance in the training set, this paper deals with a more common case where only subjective inconsistent rankings from multiple rankers are associated with each instance. Two ranking methods are proposed from the perspective of instances and rankers, respectively. The first method, Instance-oriented Preference Distribution Learning (IPDL), is to learn a latent preference distribution for each instance. IPDL generates a common preference distribution that is most compatible to all the personal rankings, and then learns a mapping from the instances to the preference distributions. The second method, Ranker-oriented Preference Distribution Learning (RPDL), is proposed by leveraging interpersonal inconsistency among rankers, to learn a unified model from personal preference distribution models of all rankers. These two methods are applied to natural scene images dataset and 3D facial expression dataset BU_3DFE. Experimental results show that IPDL and RPDL can effectively incorporate the information given by the inconsistent rankers, and perform remarkably better than the compared state-of-the-art multilabel ranking algorithms.

Photoelectrochemical sensing and mechanism investigation of hydrogen peroxide using a pristine hematite nanoarrays.

In this paper, a facile hydrothermal combined with subsequent two-step post-calcination method was used to fabricate hematite (α-Fe2O3) nanoarrays on fluorine-doped SnO2 glass (FTO). The morphology, crystalline phase, optical property and surface chemical states of the fabricated α-Fe2O3 photoelectrode were characterized by scanning electron microscopy, X-ray diffraction, ultraviolet visible spectroscopy and X-ray photoelectron spectroscopy correspondingly. The α-Fe2O3 photoelectrode exhibits excellent photoelectrochemical (PEC) response toward hydrogen peroxide (H2O2) in aqueous solutions, with a low detection limit of 20 µM (S/N = 3) and wide linear range (0.01-0.09, 0.3-4, and 6-16 mM). Additionally, the α-Fe2O3 photoelectrode shows satisfying reproducibility, stability, selectivity and good feasibility for real samples. Mechanism analysis indicates, comparing with H2O, H2O2 possesses much more fast reaction kinetics over α-Fe2O3 surface, thus the recombination of photogenerated charges are reduced, followed by much more photogenerated electrons are migrated to the counter electrode via external circuit. The insight on the enhanced photocurrent, which is corelative to the concentration of H2O2 in aqueous solution, will stimulate us to further optimize the surface structure of α-Fe2O3 to gain highly efficient α-Fe2O3 based sensors.