Molecular interactions of the chaperone CcmS and carboxysome shell protein CcmK1 that mediate ß-carboxysome assembly.

The carboxysome is a natural proteinaceous organelle for carbon fixation in cyanobacteria and chemoautotrophs. It comprises hundreds of protein homologs that self-assemble to form a polyhedral shell structure to sequester cargo enzymes, ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco) and carbonic anhydrases. How these protein components assemble to construct a functional carboxysome is a central question in not only understanding carboxysome structure and function but also synthetic engineering of carboxysomes for biotechnological applications. Here, we determined the structure of the chaperone protein CcmS, which has recently been identified to be involved in ß-carboxysome assembly, and its interactions with ß-carboxysome proteins. The crystal structure at 1.99 Å resolution reveals CcmS from Nostoc sp. PCC 7120 forms a homodimer, and each CcmS monomer consists of five α-helices and four ß-sheets. Biochemical assays indicate that CcmS specifically interacts with the C-terminal extension of the carboxysome shell protein CcmK1, but not the shell protein homolog CcmK2 or the carboxysome scaffolding protein CcmM. Moreover, we solved the structure of a stable complex of CcmS and the C-terminus of CcmK1 at 1.67 Å resolution and unveiled how the CcmS dimer interacts with the C-terminus of CcmK1. These findings allowed us to propose a model to illustrate CcmS-mediated ß-carboxysome assembly by interacting with CcmK1 at the outer shell surface. Collectively, our study provides detailed insights into the accessory factors that drive and regulate carboxysome assembly, thereby improving our knowledge of carboxysome structure, function, and bioengineering.

Hydrophobic Hydrogen-Bonded Polymer Network for Efficient and Stable Perovskite/Si Tandem Solar Cells.

The pursuit of highly efficient and stable wide-band gap (WBG) perovskite solar cells (PSCs), especially for monolithic perovskite/silicon tandem devices, is a key focus in achieving the commercialization of perovskite photovoltaics. In this study, we initially designed poly(ionic liquid)s (PILs) with varying alkyl chain lengths based on density functional theory calculations. Results pinpoint that PILs with longer alkyl chain lengths tend to exhibit more robust binding energy with the perovskite structure. Then we synthesized the PILs to craft a hydrophobic hydrogen-bonded polymer network (HHPN) that passivates the WBG perovskite/electron transport layer interface, inhibits ion migration and serves as a barrier layer against water and oxygen ingression. Accordingly, the HHPN effectively curbs nonradiative recombination losses while facilitating efficient carrier transport, resulting in substantially enhanced open-circuit voltage (Voc ) and fill factor. As a result, the optimized single-junction WBG PSC achieves an impressive efficiency of 23.18 %, with Voc as high as 1.25 V, which is the highest reported for WBG (over 1.67 eV) PSCs. These devices also demonstrate outstanding thermostability and humidity resistance. Notably, this versatile strategy can be extended to textured perovskite/silicon tandem cells, reaching a remarkable efficiency of 28.24 % while maintaining exceptional operational stability.

A Novel Wide-Band Directional MUSIC Algorithm Using the Strength Proportion.

The directional multiple signal classification (Dir-MUSIC) algorithm based on the antenna gain array manifold has been proposed to find the direction of the partial discharge (PD) source in substations. However, PD signals are wideband signals and the antenna gain pattern functions are always different at different frequencies; therefore, the accuracy can be improved using a wideband Dir-MUSIC algorithm. In this paper, wideband Dir-MUSIC algorithms are discussed and a novel wideband Dir-MUSIC algorithm using the strength proportion (DirSP) is proposed. This algorithm estimates a focusing PD signal at a certain frequency using the strength proportion among different directions, and then the Dir-MUSIC algorithm can process the focusing PD signal at this frequency. In simulations, when the antenna gain functions among different frequency bins are quite different, the Dir-MUSIC algorithm loses accuracy; meanwhile, DirDP performs very well. In the experiments, we deal with six sets of samples, and the mean error and standard deviation are both smaller than 4° better than other methods.

Dir-MUSIC Algorithm for DOA Estimation of Partial Discharge Based on Signal Strength Represented by Antenna Gain Array Manifold.

Inspection robots are widely used in the field of smart grid monitoring in substations, and partial discharge (PD) is an important sign of the insulation state of equipment. PD direction of arrival (DOA) algorithms using conventional beam forming and time difference of arrival (TDOA) require large-scale antenna arrays and high computational complexity, making them difficult to implement on inspection robots. To address this problem, a novel directional multiple signal classification (Dir-MUSIC) algorithm for PD direction finding based on signal strength is proposed, and a miniaturized directional spiral antenna circular array is designed in this paper. First, the Dir-MUSIC algorithm is derived based on the array manifold characteristics. This method uses strength intensity information rather than the TDOA information, which could reduce the computational difficulty and the requirement of array size. Second, the effects of signal-to-noise ratio (SNR) and array manifold error on the performance of the algorithm are discussed through simulations in detail. Then, according to the positioning requirements, the antenna array and its arrangement are developed and optimized. Simulation results suggested that the algorithm has reliable direction-finding performance in the form of six elements. Finally, the effectiveness of the algorithm is tested by using the designed spiral circular array in real scenarios. The experimental results show that the PD direction-finding error is 3.39°, which meets the need for partial discharge DOA estimation using inspection robots in substations.

Determining multi-pesticide residues in teas by dispersive solid-phase extraction combined with speed-regulated directly suspended droplet microextraction followed by gas chromatography-tandem mass spectrometry.

In this study, an effective speed-regulated directly suspended droplet microextraction method was developed to condense pesticide residues from teas through dispersive solid-phase extraction prior to analysis by gas chromatography with tandem mass spectrometry. The extractant was intentionally dispersed into the sample solution in the form of globules through high-speed agitation. This procedure increases the contact area between the binary phases and shortens the distribution equilibrium time. The fine globules reassembled by decelerating stirring speed, the extractant could be taken out for gas chromatography with tandem mass spectrometry. Recovery studies were performed under optimized extraction conditions by using matrix blanks fortified with pesticides at three concentrations (10, 50, and 100 µg/kg). Over 87% of the recoveries for the analytes in four tea matrices were acceptable given their recovery ranges of 70-120% and relative standard deviations of ≤20%. The limits of quantification of most pesticides were lower than 10 µg/kg and thus satisfied the requirements for maximum residue levels prescribed by the European Community. A total of 38 tea samples from local markets were analyzed by using the proposed method. Results showed that chlorpyrifos was the most frequently detected pesticide in teas. The method is a potential choice for the routine monitoring of pesticide residues in complex matrices.

Inefficient ATP synthesis by inhibiting mitochondrial respiration causes lipids to decrease in MSTN-lacking muscles of loach Misgurnus anguillicaudatus.

Myostatin (MSTN) lacking could lead to enhanced muscle growth and lipid metabolism disorder in animals. Plenty of researches have been performed to warrant a better understanding of the mechanisms underlying the enhanced muscle growth; however, mechanisms for lipid metabolic changes are poorly understood. In this study, MSTN-depletion loaches Misgurnus anguillicaudatus (MU for short) were firstly generated by CRISPR/Cas9 technique. Based on histological observation, we found that skeletal muscle fat accumulation in MU sharply reduced compared with wild-type loaches (WT for short). To further investigate the fat change, muscle lipidomic analysis was performed. There were no significant differences in three membrane phospholipid contents between WT and MU. The contents of six other major lipid species in MU muscles were all significantly lower than those in WT muscles, indicating that MSTN deficiency could obviously decrease muscle lipid production in the loach. Meanwhile, it was also supported by results of three lipogenesis-related genes' expressions. And then combined with muscle ATP determination and gene expression profiles of the five mitochondrial respiration chain complexes, we speculated that MSTN lacking may cause the weak of mitochondrial respiration functions in the loach muscles, leading to ATP synthesis decreasing and finally reducing the production of lipids.

Determination of multiple pesticide residues in teas by gas chromatography with accurate time-of-flight mass spectrometry.

In this work, gas chromatography tandem with electron ionization and full-scan high-resolution mass spectrometry with a time-of-flight mass analyzer was evaluated for analyzing pesticide residues in teas. The relevant aspects for mass spectrometry analysis, including the resolution and mass accuracy, acquisition rate, temperature of ion source, were investigated. Under acquisition condition in 2-GHz extended dynamic range mode, accurate mass spectral library including 184 gas chromatography detectable pesticides was established and retrieval parameters were optimized. The mass spectra were consistent over a wide concentration range (three orders) with good match values to those of NIST (EI-quadrupole). The methodology was verified by the validation of 184 pesticides in four tea matrices. A wide linear range (1-1000 µg/kg) was obtained for most compounds in four matrices. Limit of detection, limit of quantification, and limit of identification values acquired in this study could satisfy the requirements for maximum residue levels prescribed by the European Community. Recovery studies were performed at three concentrations (10, 50, and 100 µg/kg). Most of the analytes were recovered at an acceptable range of 70-120% with relative standard deviations ≤ 20% in four matrices. The potential extension of qualitative screening scope makes gas chromatography tandem with electron ionization and mass spectrometry with a time-of-flight mass analyzer a more powerful tool compared with gas chromatography with tandem mass spectrometry.

Data Field Modeling and Spectral-Spatial Feature Fusion for Hyperspectral Data Classification.

Classification is a significant subject in hyperspectral remote sensing image processing. This study proposes a spectral-spatial feature fusion algorithm for the classification of hyperspectral images (HSI). Unlike existing spectral-spatial classification methods, the influences and interactions of the surroundings on each measured pixel were taken into consideration in this paper. Data field theory was employed as the mathematical realization of the field theory concept in physics, and both the spectral and spatial domains of HSI were considered as data fields. Therefore, the inherent dependency of interacting pixels was modeled. Using data field modeling, spatial and spectral features were transformed into a unified radiation form and further fused into a new feature by using a linear model. In contrast to the current spectral-spatial classification methods, which usually simply stack spectral and spatial features together, the proposed method builds the inner connection between the spectral and spatial features, and explores the hidden information that contributed to classification. Therefore, new information is included for classification. The final classification result was obtained using a random forest (RF) classifier. The proposed method was tested with the University of Pavia and Indian Pines, two well-known standard hyperspectral datasets. The experimental results demonstrate that the proposed method has higher classification accuracies than those obtained by the traditional approaches.

Achieving enhanced multifunctional performance for structural composite supercapacitors by reinforcing interfaces with polymer coating.

Carbon fiber structural composite supercapacitors possess the multifunctionality of storing electrochemical energy and withstanding mechanical loads simultaneously, attracting increased attention in electric vehicles, drones, and aircraft sectors. A polymer-based coating was meticulously constructed at the electrode/electrolyte interface to enhance adhesion and stability between active materials and the carbon fiber fabric collector under diverse conditions, especially mechanical stress. Mechanical testing and corresponding physical characterization substantiated the superior performance of the polymer coating. With the protective polymer coating, the optimized structural composite Zn-ion supercapacitor (SZSC), consisting of carbon fiber@active carbon-P (CF@AC-P) cathode, ionogel electrolyte, and Zn anode, displayed a maximum energy density of 164.6 mWh kg-1, at power density of 563.3 mW kg-1. Moreover, the optimized SZSC demonstrated stable operation over more than 8000 cycles at 0.3 mA cm-2 without capacity degradation. The optimized SZSC exhibited a tensile strength of 399.7 MPa and Young's modulus of 11.5 GPa. Furthermore, employing vacuum infusion techniques, the fabricated three-dimensional (3D) wing skin model shell and tube shell curved-surface structural composite Zn-ion supercapacitor component composites showcased exceptional electrochemical performance. These achievements further validate the practicality of 3D multifunctional composites. Consequently, this research presented a practical and straightforward interface engineering approach to develop multifunctional structural devices with remarkable electrochemical and mechanical properties.

Dynamical Attention Hypergraph Convolutional Network for Group Activity Recognition.

Recently, group activity recognition (GAR) has drawn growing interests in video analysis and computer vision communities. The current models of GAR tasks are often impractical in that they suppose that all interactions between actors are pairwise, which only models and leverages part of the information in real entire interactions. Motivated by this, we design a distinct dynamical attention hypergraph convolutional network framework, referred to as DAHGCN, for precise GAR, modeling the entire interactions and capturing the high-order relationships among involved actors in a real-life scenario. Specifically, to learn complementary feature representations for fine-grained GAR, a multilevel feature descriptor (MLFD) module is proposed. Furthermore, for learning higher order interaction relationships, we construct a DAHGCN to accommodate complex group interactions, which can dynamically change the topology of the hypergraph and learn these key representations by virtue of the "similarity-based shared nearest-neighbor (SSNN) clustering" and "attention mechanisms" on hypergraph. Finally, a multiscale temporal convolution (MSTC) module is utilized to explore various long-range temporal dynamic correlations across different frames. In addition, comprehensive experiments on three commonly used GAR datasets clearly demonstrate that, when compared with the state-of-the-art methods, our proposed method can achieve the most optimal performance.

Characterization and exploration of dynamic variation of volatile compounds in vine tea during processing by GC-IMS and HS-SPME/GC-MS combined with machine learning algorithm.

It is imperative to unravel the dynamic variation of volatile components of vine tea during processing to provide guidance for tea quality evaluation. In this study, the dynamic changes of volatile compounds of vine tea during processing were characterized by GC-IMS and HS-SPME/GC-MS. As a result, 103 volatile compounds were characterized by the two technologies with three overlapped ones. The random forest approach was employed to develop the models and explore key volatile compounds. 23 key compounds were explored, among which 13 were derived from GC-IMS and ten were from HS-SPME/GC-MS. Moreover, the area under the receiver operating characteristics curve with 100 cross validations by the pair-wised models were all 1 for the established models. Furthermore, the primary aroma formation mechanism for the key volatile compounds were mainly involved in fatty acid and amino acid metabolism. Besides, this study provides a theoretical support for directed processing and quality control of vine tea.

Dynamic Compressive Stress Relaxation Model of Tomato Fruit Based on Long Short-Term Memory Model.

Tomatoes are prone to mechanical damage due to improper gripping forces during automated harvest and postharvest processes. To reduce this damage, a dynamic viscoelastic model based on long short-term memory (LSTM) is proposed to fit the dynamic compression stress relaxation characteristics of the individual fruit. Furthermore, the classical stress relaxation models involved, the triple-element Maxwell and Caputo fractional derivative models, are compared with the LSTM model to validate its performance. Meanwhile, the LSTM and classical stress relaxation models are used to predict the stress relaxation characteristics of tomato fruit with different fruit sizes and compression positions. The results for the whole test dataset show that the LSTM model achieves a RMSE of 2.829×10-5 Mpa and a MAPE of 0.228%. It significantly outperforms the Caputo fractional derivative model by demonstrating a substantial enhancement with a 37% decrease in RMSE and a 36% reduction in MAPE. Further analysis of individual tomato fruit reveals the LSTM model's performance, with the minimum RMSE recorded at the septum position being 3.438×10-5 Mpa, 31% higher than the maximum RMSE at the locule position. Similarly, the lowest MAPE at the septum stands at 0.375%, outperforming the highest MAPE at the locule position by a significant margin of 90%. Moreover, the LSTM model consistently reports the smallest discrepancies between the predicted and observed values compared to classical stress relaxation models. This accuracy suggests that the LSTM model could effectively supplant classical stress relaxation models for predicting stress relaxation changes in individual tomato fruit.

An integrated calibration strategy for the development and validation of an LC-MS/MS method for accurate quantification of egg allergens (Gal d 1-6) in foods.

Accurate determination of egg allergens in food is vital for allergen management and labeling. However, quantifying egg allergens with mass spectrometry poses challenges and lacks validation methods. Here, we developed and validated an LC-MS/MS method for quantifying egg allergens (Gal d 1-6) in foods. Sample extraction, enzymatic digestion, purification, proteins/peptides selection, and calibration curves were optimized. VMVLC[+57]NR (Gal d 1) and GTDVQAWIR (Gal d 5) exhibited outstanding sensitivity and stability, serving as quantitation markers for egg white and yolk. Using a matrix-matched calibration curve with allergen ingredients as calibrants and labeled peptides as standards, we achieved highly accurate quantitation. Validation involved spiking egg protein into egg-free foods, showing excellent sensitivity (LOQ: 1-5 mg/kg), accuracy (62.4 %-88.5 %), and reproducibility (intra-/inter-day precision: 3.5 %-14.2 %/8.2 %-14.6 %). Additionally, we successfully applied this method to commercial food analysis. These findings demonstrate optimal allergen selection, peptides, and calibration strategy are crucial parameters for food allergen quantification via MS-based methods.

A lipidomic and volatilomic approach to map the lipid profile and related volatile compounds in roasted quail meat using circulating non-fried roast technology.

Lipids play a significant role in aroma formation. However, lipid variations and their impact on aroma during the processing of quail meat remain unknown. Therefore, a comprehensive analysis of lipids and aroma compounds was conducted in circulating non-fried roasted quail meat. Nineteen odorants were identified as key aroma compounds in the roasted quail meat at 40 min with OAVs of >1. The concentrations of most key odorants significantly increased in circulating non-fried roasted (CNR) quail meat within the first 30 min of roasting, reaching maximum values at 40 min. Phospholipids, neutral lipids, and sphingolipids emerged as potential markers for distinguishing different samples. Neutral lipids had the highest peak areas and significantly contributed to the aroma retention. Phospholipids and neutral lipids with unsaturated fatty acids, particularly C18 acyl groups, played a crucial role in aroma formation. This study provides valuable insights into the role of lipids in determining aroma quality.

Formation and retention of aroma compounds in pigeons roasted by circulating non-fried roast technique by means of UHPLC-HRMS and GC-O-MS.

Lipids are key aroma contributors in meat products. However, the role of different lipids in the presence of aroma compounds in roasted pigeons has not been studied. The formation of aroma compounds and lipids during the circulating non-fried roasting of pigeons was investigated. The results presented that 18 aroma compounds, including 5-methy-2,3-diethylpyrazine, were identified as key aroma compounds. A total of 6324 lipids were classed into 47 categories, such as phosphatidylcholine (PC), phosphatidylethanolamine (PE), and triglyceride (TG). Nine lipids, containing PA(P-20:0/22:4(7Z,10Z,13Z,16Z)) and LPC 16:0-SN1, showed promise as potential biomarkers for discriminating differential pigeons using OPLS-DA. PC (13.76%), TG (13.58%), and their products were major lipids, among which TG 16:0 16:0 18:2, LPC 18:2-SN1, and PC 18:1_18:1 played a crucial role in the presence of aroma compounds. Interestingly, the linoleic acid, an important aroma contributor, was predominantly bonded to the sn-2 position of phospholipid and sn-3 position of neutral lipids.

Advancing High-Throughput MS-Based Protein Quantification: A Case Study on Quantifying 10 Major Food Allergens by LC-MS/MS Using a One-Sample Multipoint External Calibration Curve.

The LC-MS-based method has emerged as the preferred approach for quantifying food allergens. However, the preparation of a traditional calibration curve (MSCC) is labor-intensive and error-prone. Here, a sensitive and robust LC-MS/MS method for quantifying 10 major food allergens was developed and validated, where the one-sample multipoint external calibration curve (OSCC) was employed instead of MSCC. By employing the multiple isotopologue reaction monitoring (MIRM) technique with only one spiked level in the blank, OSCC can be effectively established. Results demonstrate that the proposed method exhibits excellent performance in selectivity, sensitivity, accuracy, and precision, comparable to that of the traditional MSCC. Additionally, this strategy allows for isotope sample dilution by monitoring the less abundant MIRM channel. Moreover, the developed method was successfully applied to investigate the contamination of 10 food allergens in commercial food products. With its high throughput and robustness, the MIRM-OSCC-LC-MS/MS methodology has many potential applications, especially in the MS-based protein quantification analysis.

[Calculation and simulation on infrared radiation of hot jet from engine].

Spectral distribution of infrared radiation from plume by the method to calculate infrared radiance of the gaze direction in small sight field was calculated. Based on numerical value and form of radiative transfer equation, infrared radiant intensity of the gaze direction was calculated using the Malkmus statistical narrow-band model and CG approach. Flow field and mole fraction distribution were simulated using a FLUENT computational fluid dynamic (CFD) software. Infrared imaging simulation model of hot jet was established. The hot jet's infrared images of liquid rocket engine were generated. The results demonstrate that the method can detect well-resolved fine structure of flow field. And the model is also applicable to calculation and simulation on infrared radiation of hot jet from engine.

Advances in mechanisms and engineering of electroactive biofilms.

Electroactive biofilms (EABs) are electroactive microorganisms (EAMs) encased in conductive polymers that are secreted by EAMs and formed by the accumulation and cross-linking of extracellular polysaccharides, proteins, nucleic acids, lipids, and other components. EABs are present in the form of multicellular aggregates and play a crucial role in bioelectrochemical systems (BESs) for diverse applications, including biosensors, microbial fuel cells for renewable bioelectricity production and remediation of wastewaters, and microbial electrosynthesis of valuable chemicals. However, naturally occurred EABs are severely limited owing to their low electrical conductivity that seriously restrict the electron transfer efficiency and practical applications. In the recent decade, synthetic biology strategies have been adopted to elucidate the regulatory mechanisms of EABs, and to enhance the formation and electrical conductivity of EABs. Based on the formation of EABs and extracellular electron transfer (EET) mechanisms, the synthetic biology-based engineering strategies of EABs are summarized and reviewed as follows: (i) Engineering the structural components of EABs, including strengthening the synthesis and secretion of structural elements such as polysaccharides, eDNA, and structural proteins, to improve the formation of biofilms; (ii) Enhancing the electron transfer efficiency of EAMs, including optimizing the distribution of c-type cytochromes and conducting nanowire assembly to promote contact-based EET, and enhancing electron shuttles' biosynthesis and secretion to promote shuttle-mediated EET; (iii) Incorporating intracellular signaling molecules in EAMs, including quorum sensing systems, secondary messenger systems, and global regulatory systems, to increase the electron transfer flux in EABs. This review lays a foundation for the design and construction of EABs for diverse BESs applications.

Dietary exposure risk assessment of pyrethroids in fruits and vegetables: a national scale investigation.

The pyrethroids (PYRs) were extensively used to increase agriculture outputs. However, the cumulative exposures of PYRs would bring about potential risks through food intake. It is an urgent requirement to explore the cumulative exposures on the fruits and vegetables. In this study, a total of 1720 samples incorporating eight primary fruits and vegetables collected around China were investigated to assess the health risk for adults and children from eight PYRs. The relative potency factor (RPF) method was employed to reveal both chronic and acute cumulative exposure. As a result, the hazard index (HI) were 0.004 ~ 0.200% and 11.85 ~ 99.19% for chronic and acute cumulative dietary exposure, respectively. The national wide investigation indicated the cumulative assessments were not hazardous. Besides, the acute intake of pear, grape, and lettuce should be paid on more attention, particularly. This study provides compelling evidence to develop relative policy and regulation to improve the food quality and safety.

Flavoromics Approach in Critical Aroma Compounds Exploration of Peach: Correlation to Origin Based on OAV Combined with Chemometrics.

It is essential to seek the critical aroma compounds to identify the origins of peach as well as provide a guidance for quality evaluation. In this study, the peach was characterized by HS-SPME/GC-MS. Subsequently, the odor activity value (OAV) was calculated to specify the primary aroma-active compounds. Afterwards, the chemometrics methods were employed to explore the potentially critical aroma on the basis of p value, fold change (FC), S-plot, jack-knifing confidence interval, variable importance for projection (VIP), and the Shared and Unique Structures (SUS) plots. As a result, five compounds (methyl acetate, (E)-hex-2-enal, benzaldehyde, [(Z)-hex-3-enyl] acetate, and 5-ethyloxolan-2-one) were considered as critical aromas. Moreover, the multi-classification model was developed with an outstanding performance (accuracy of 100%) using the five critical aroma. Moreover, the potential chemical basis of odors was sought through sensory evaluation. In addition, this study provides the theoretical and practical foundation for geographical origin traceability and quality evaluation.