The LIKE SEX FOUR 1-malate dehydrogenase complex functions as a scaffold to recruit ß-amylase to promote starch degradation.

In plant leaves, starch is composed of glucan polymers that accumulate in chloroplasts as the products of photosynthesis during the day; starch is mobilized at night to continuously provide sugars to sustain plant growth and development. Efficient starch degradation requires the involvement of several enzymes, including ß-amylase and glucan phosphatase. However, how these enzymes cooperate remains largely unclear. Here, we show that the glucan phosphatase LIKE SEX FOUR 1 (LSF1) interacts with plastid NAD-dependent malate dehydrogenase (MDH) to recruit ß-amylase (BAM1), thus reconstituting the BAM1-LSF1-MDH complex. The starch hydrolysis activity of BAM1 drastically increased in the presence of LSF1-MDH in vitro. We determined the structure of the BAM1-LSF1-MDH complex by a combination of cryo-electron microscopy, crosslinking mass spectrometry, and molecular docking. The starch-binding domain of the dual-specificity phosphatase and carbohydrate-binding module of LSF1 was docked in proximity to BAM1, thus facilitating BAM1 access to and hydrolysis of the polyglucans of starch, thus revealing the molecular mechanism by which the LSF1-MDH complex improves the starch degradation activity of BAM1. Moreover, LSF1 is phosphatase inactive, and the enzymatic activity of MDH was dispensable for starch degradation, suggesting nonenzymatic scaffold functions for LSF1-MDH in starch degradation. These findings provide important insights into the precise regulation of starch degradation.

CHSY3 promotes proliferation and migration in gastric cancer and is associated with immune infiltration.

BACKGROUND: The glycosyltransferase CHSY3 is a CHSY family member, yet its importance in the context of gastric cancer development remains incompletely understood. The present study was thus developed to explore the mechanistic importance of CHSY3 as a regulator of gastric cancer. METHODS: Expression of CHSY3 was verified by TCGA, GEO and HPA databases. Kaplan-Meier curve, ROC, univariate cox, multivariate cox, and nomogram models were used to verify the prognostic impact and predictive value of CHSY3. KEGG and GO methods were used to identify signaling pathways associated with CHSY3. TIDE and IPS scores were used to assess the immunotherapeutic value of CHSY3. WGCNA, Cytoscape constructs PPI networks and random forest models to identify key Hub genes. Finally, qRT-PCR and immunohistochemical staining were performed to verify CHSY3 expression in clinical specimens. The ability of CHSY3 to regulate tumor was further assessed by CCK-8 assay and cloning assay, EDU assay, migration assay, invasion assay, and xenograft tumor model analysis. RESULTS: The expression of CHSY3 was discovered to be abnormally upregulated in GC tissues through TCGA, GEO, and HPA databases, and the expression of CHSY3 was associated with poor prognosis in GC patients. Correlation analysis and Cox regression analysis revealed higher CHSY3 expression in higher T staging, an independent prognostic factor for GC. Moreover, elevated expression of CHSY3 was found to reduce the benefit of immunotherapy as assessed by the TIDE score and IPS score. Then, utilizing WGCNA, the PPI network constructed by Cytoscape, and random forest model, the Hub genes of COL5A2, POSTN, COL1A1, and FN1 associated with immunity were screened. Finally, the expression of CHSY3 in GC tissues was verified by qRT-PCR and immunohistochemical staining. Moreover, the expression of CHSY3 was further demonstrated by in vivo and in vitro experiments to promote the proliferation, migration, and invasive ability of GC. CONCLUSIONS: The results of this study suggest that CHSY3 is an important regulator of gastric cancer progression, highlighting its promise as a therapeutic target for gastric cancer.

Experimental research and comparison of LDPC and RS channel coding in ultraviolet communication systems.

We have implemented a modified Low-Density Parity-Check (LDPC) codec algorithm in ultraviolet (UV) communication system. Simulations are conducted with measured parameters to evaluate the LDPC-based UV system performance. Moreover, LDPC (960, 480) and RS (18, 10) are implemented and experimented via a non-line-of-sight (NLOS) UV test bed. The experimental results are in agreement with the simulation and suggest that based on the given power and 10(-3)bit error rate (BER), in comparison with an uncoded system, average communication distance increases 32% with RS code, while 78% with LDPC code.

Scientometric analysis on the review research evolution of tailings dam failure disasters.

As the most severe damage form of tailings ponds, dam failure causes a serious threat and damage to the surrounding lives and environment. Therefore, based on the systematic collection and consultation of relevant data at home and abroad, the literature source analysis on tailings dam failure disasters is conducted using the CiteSpace scientometric tool. The research on tailings dam failure disasters can be classified into two stages: the preliminary germination stage and rapid development stage. Based on the scientometric knowledge map, the research hotspots of tailings dam failure disasters are analyzed and summarized as three main research directions: environmental impact, risk assessment, and mechanical behavior. With the maturity of the research on ecological problems caused by tailings leakage, ecological restoration has also gradually become a hot research topic. Through the analysis of keyword bursts and co-cited bursts, the research frontier of tailings dam break disaster is explored. "Risk management," "real-time monitoring," and "tailings characteristic" represent the current research frontier. Among them, risk management is burst for the longest time and is expected to be a very important research direction in the future. Finally, a tailings pond risk management and control suggestion is proposed with risk management as the core, emphasizing risk monitor, and combined with dynamic risk control, which provides a foundation for the construction of tailings dam safety management and dynamic monitoring systems.

Leaching toxicity and deformation failure characteristics of phosphogypsum-based cemented paste backfill under chemical solution erosion.

In order to explore the potential environmental and safety risks of phosphogypsum-based cemented paste backfill (PCPB) in mines, aiming at the actual problems of different acidity and alkalinity of the groundwater environment where PCPB is located, the chemical solution erosion test, element concentration determination test, uniaxial compressive strength (UCS) test, and microscopic analysis test of PCPB were carried out. The effects of three different chemical solutions, HCl solution, NaOH solution, and pure water on the leaching toxicity and deformation failure characteristics of PCPB were analyzed. The kinetic equations of pH value of PCPB in the HCl and NaOH solutions, the leaching models of total P and fluoride, and the UCS erosion model of PCPB were established. The research shows that the pH value of PCPB is weak alkaline or alkalinity, when it reaches dynamic equilibrium in different chemical solutions. The leaching concentration of total P is higher than the Class III standard of surface water; the leaching concentration of fluoride is higher than the Class III standard of surface water, the Class III standard of groundwater, and the Class I standard of sewage. In the early stage of chemical solution erosion, scanning electron microscope (SEM) images show that the hydration product C-S-H gel and Aft are intertwined and firmly combined. The research results have important engineering practice and application value in mine environmental governance and safety management.

Mechanical properties and damage constitutive model of phosphogypsum-based cemented backfill under hydrochemical action.

In order to analyze the early mechanical properties and damage characteristics of phosphogypsum-based cemented backfill (PCB) under hydrochemical action, hydrochemical erosion and uniaxial compression strength (UCS) tests were carried out with HCl solution, NaOH solution, and water respectively. The damage degree is defined by taking the effective bearing area of the soluble cements of PCB under hydrochemistry action as the chemical damage variable, and the modified damage parameter α, which reflects the damage development characteristics, is introduced to construct the damage constitutive model of PCB considering chemical damage and load damage, and the theoretical model is verified with the experimental results. The results show that the damage constitutive model curves of PCB under different hydrochemical action are in good agreement with the experimental results, which verifies the correctness of the theoretical model. When the modified damage parameter α decreases from 1.0 to 0.8, the residual load-bearing capacity of PCB gradually increases, with the damage values of PCB samples in HCl solution and water gradually increasing before the peak and decreasing after the peak, while the damage values of PCB samples in NaOH solution show an overall increasing trend before and after the peak. The slope of the post peak curve of PCB decreases with increasing model parameter n. The results of the study can provide theoretical support and practical guidance for the strength design, long-term erosion deformation, and prediction of PCB in hydrochemical environment.

Uncertainty prediction of mining safety production situation.

In order to explore the occurrence and development law of mining safety production accidents, analyze its future change trends, and aim at the ambiguity, non-stationarity, and randomness of mining safety production accidents, an uncertainty prediction model for mining safety production situation is proposed. Firstly, the time series effect evaluation function is introduced to determine the optimal time granularity, which is used as the window width of fuzzy information granulation (FIG), and the time series of mining safety production situation is mapped to Low, R, and Up three granular parameter sequences, according to the triangular fuzzy number; then, the mean value of the intrinsic mode function (IMF) is maintained in the normal dynamic filtering range. After the ensemble empirical mode decomposition (EEMD), the three non-stationary granulation parameter sequences of Low, R, and Up are decomposed into the intrinsic mode function components representing the detail information and the trend components representing the overall change, and then the sub-sequences are reconstructed according to the sample entropy to highlight the correlation among the sub-sequences; finally, the cloud model language rules of mining safety production situation prediction are created. Through time series discretization, cloud transformation, concept jump, time series set division, association rule mining, and uncertain reasoning, the reconstructed component sequence is modeled and predicted by uncertainty information extraction. The accuracy of the uncertainty prediction model was verified by 21 sets of test samples. The average relative errors of Low, R, and Up sequences were 9.472 %, 16.671 %, and 3.625 %, respectively. The research shows that the uncertainty prediction model of mining safety production situation overcomes the fuzziness, non-stationarity, and uncertainty of safety production accidents, and provides theoretical reference and practical guidance for mining safety management and decision-making.

Multi-hazard risk characterization and collaborative control oriented to space in non-coal underground mines.

In order to realize accurate risk assessment and collaborative control of multi-hazard risk in non-coal underground mines, a space-oriented risk characterization and collaborative control model of multi-hazard risk in non-coal underground mines is proposed. Statistical analysis of non-coal underground mine accidents from 2000 to 2022, revealing the characteristics of non-coal underground mine accidents and 5 risk types were identified, including cage fall accident, powered haulage accident, fire accident, mine water inrush accident, and roof fall and rib spalling accident. A multi-hazard risk analysis and assessment framework for non-coal underground mines based on the inherent risk of the system, the vulnerability of the disaster-bearing body and the adaptability of the disaster-bearing area is proposed. The multi-hazard inherent risks in non-coal underground mines are comprehensively identified and evaluated in five aspects, including hazardous equipment and facilities, hazardous materials, hazardous processes, hazardous operations and hazardous places, and the characterization and unified measurement of multi-hazard risk is realized by combining the vulnerability index of disaster-bearing body and the adaptability index of disaster-bearing area. Regional multi-hazard risk aggregation is achieved through the Nemerow pollution index and space-oriented multi-hazard risk is obtained. Constructed a multi-hazard safety risk collaborative control system of source identification, classification and control, process control, continuous improvement, and full participation. Finally, the validity and rationality of the risk characterization model and the risk collaborative control system are verified. The research can both support the formulation of macro policies for non-coal underground mines and provide guidance for the specific spatial layout.

Ensemble stacking rockburst prediction model based on Yeo-Johnson, K-means SMOTE, and optimal rockburst feature dimension determination.

Rockburst forecasting plays a crucial role in prevention and control of rockburst disaster. To improve the accuracy of rockburst prediction at the data structure and algorithm levels, the Yeo-Johnson transform, K-means SMOTE oversampling, and optimal rockburst feature dimension determination are used to optimize the data structure. At the algorithm optimization level, ensemble stacking rockburst prediction is performed based on the data structure optimization. First, to solve the problem of many outliers and data imbalance in the distribution of rockburst data, the Yeo-Johnson transform and k-means SMOTE algorithm are respectively used to solve the problems. Then, based on six original rockburst features, 21 new features are generated using the PolynomialFeatures function in Sklearn. Principal component analysis (PCA) dimensionality reduction is applied to eliminate the correlations between the 27 features. Thirteen types of machine learning algorithms are used to predict datasets that retain different numbers of features after dimensionality reduction to determine the optimal rockburst feature dimension. Finally, the 14-feature rockburst dataset is used as the input for integrated stacking. The results show that the ensemble stacking model based on Yeo-Johnson, K-means SMOTE, and optimal rockburst feature dimension determination can improve the accuracy of rockburst prediction by 0.1602-0.3636. Compared with the 13 single machine learning models without data preprocessing, this data structure optimization and algorithm optimization method effectively improves the accuracy of rockburst prediction.

New chording text entry methods combining physical and virtual buttons on a mobile phone.

Traditional mobile phones depend on MultiTap, virtual or physical QWERTY keyboard for text entry, and they had some respective drawbacks include low input performance, occupying too large an area, high error rates, lack of feedbacks, etc. Therefore, some researches utilized the characteristics of the chording keyboard to improve input performance. Yet, as the learning efficiency of the chording keyboard is too low, users are not highly willing to learn. In view of that, this study combines the physical and virtual keys, and develops two chording input methods, MagArea and MemoryTap. After three days of learning, the fourteen experiment participants show effectively reduce error rates on MagArea, and they enhance their input speed on MemoryTap. In addition, excellent learning efficiency is found in the two methods, will be more motivated and willing to employ.

[Size distributions of organic carbon and elemental carbon in Nanjing aerosol particles].

The concentrations and size distributions of organic carbon (OC) and elemental carbon (EC) in particles collected in Nanjing Normal University representing urban area and in Nanjing College of Chemical Technology standing for industrial area were analyzed using Model 2001A Thermal Optical Carbon Analyzer. The mass concentrations were the highest with the size below 0.43 microm in urban and industrial area. OC accounted for 20.9%, 21.9%, 29.6%, 27.9% respectively and those were 24.0%, 23.5%, 31.4%, 22.6% respectively for EC in the four seasons in urban area. In the industrial area, OC accounted for 18.6%, 45.8%, 26.6%, 25.9% respectively and the proportions of EC were 16.7%, 60.9%, 26.3%, 24.3% respectively. Overall, OC and EC were enriched in fine particles below 2.1 microm and they accounted for the highest proportion in summer in urban area while it did not show significant seasonal variation for industrial area. SOC in fine particles achieved high values in summer while the unobvious seasonal variation in coarse particles might be attributed to the contribution of different pollution sources and meteorological factors. Correlations and OC/EC ratio method implied that OC and EC mainly came from vehicles exhaust and coal combustion in fine particles while they were also related to biomass combustion and cooking in coarse particles.

[Stable carbon isotopic composition in PM 2.1 in Nanjing Region].

Stable carbon isotopes (delta13C) in aerosol fine particles (PM2.1) collected in Nanjing Normal University representing urban area, and in Nanjing College of Chemical Technology standing for suburban industrial area, were analyzed using EA-IRMS. Besides, sources of carbonaceous contents were studied and the pollution characteristics of total carbon (TC) were evaluated. The annual average concentrations of TC in urban area and suburban industrial area were 15.94 microg.m-3 and 17.17 microg.m-3, respectively. The proportions for TC in PM2.1 were 17.18% and 16. 40% , indicating that carbonaceous pollution was more serious and the pollutants were more complex in suburban industrial area. The average delta13C for winter, spring, summer and autumn were -24. 42 per thousand +/- 1. 12 per thousand, -25. 19 per thousand +/- 1. 92% per thousand, - 25.79 per thousand +/- 0.45 per thousand and - 25.58 per thousand + 0. 65 per thousand, respectively in urban area and - 25.34 per thousand +/- 1. 18 per thousand, -25. 55 per thousand +/- 1. 50 per thousand, -25. 31 per thousand +/- 0. 55%o and -25. 38 per thousand +/- 0. 82 per thousand, respectively in suburban area. Correlation analysis and isotopic signatures of potential sources suggested that carbonaceous contents mainly came from gasoline vehicles exhaust in urban area, and might be attributed to the vehicle exhaust emissions and industrial emissions in suburban area. In addition, coal combustion,biomass burning and geological sources might have important contribution to aerosols in winter and spring. Back trajectory analysis implied that the long-range transport had considerable contribution to the carbonaceous aerosol in winter and spring. However, the major sources might be attributed to local emissions in the other two seasons.