Research on prediction of PPV in open-pit mine used RUN-XGBoost model.

The drill-blasting method is a commonly used mining technique in open-pit mines, and the peak particle velocity (PPV) caused by blasting vibrations is an important indicator for evaluating the rationality of blasting mining design parameters. To develop an effective PPV prediction model, a parameter self-optimizing RUN-XGBoost prediction model is implemented using the Runge-Kutta optimization algorithm (RUN) combined with extreme gradient boosting (XGBoost). The factors affecting the prediction of PPV, including maximum explosive (ME), total explosive (TE), blast center distance (BCD), blast hole depth (BHD), and height difference between the measurement location and the blast location (DH), are selected as the influencing indicators. 188 pieces of blasting operation data were measured at the RK open pit copper-cobalt mine. Then, the RUN-XGBoost prediction model for PPV is studied and compared with the Sadovsky empirical formula, traditional XGBoost model, PSO-XGBoost model, and some traditional machine learning models (Ridge, LASSO, SVM, and SVR) using R2, RMSE, VAF, MAE, and MBE as evaluation indicators for model prediction results. Finally, the Shapley Additive Explanations (SHAP) method is used to evaluate the contribution of different influencing indicators to the PPV prediction results. The results show that the RUN-XGBoost prediction model is significantly better than other machine learning models and the Sadovsky empirical formula in the prediction of PPV, further demonstrating that the RUN-XGBoost prediction model can handle the nonlinear features of multiple factors and provide a reliable, simple, and effective PPV prediction model, forming a rapid prediction and evaluation method for blasting vibrations in open-pit mining.

Arabinosylation of cell wall extensin is required for the directional response to salinity in roots.

Soil salinity is a major contributor to crop yield losses. To improve our understanding of root responses to salinity, we developed and exploited a real-time salt-induced tilting assay. This assay follows root growth upon both gravitropic and salt challenges, revealing that root bending upon tilting is modulated by Na+ ions, but not by osmotic stress. Next, we measured this salt-specific response in 345 natural Arabidopsis (Arabidopsis thaliana) accessions and discovered a genetic locus, encoding the cell wall-modifying enzyme EXTENSIN ARABINOSE DEFICIENT TRANSFERASE (ExAD) that is associated with root bending in the presence of NaCl (hereafter salt). Extensins are a class of structural cell wall glycoproteins known as hydroxyproline (Hyp)-rich glycoproteins, which are posttranslationally modified by O-glycosylation, mostly involving Hyp-arabinosylation. We show that salt-induced ExAD-dependent Hyp-arabinosylation influences root bending responses and cell wall thickness. Roots of exad1 mutant seedlings, which lack Hyp-arabinosylation of extensin, displayed increased thickness of root epidermal cell walls and greater cell wall porosity. They also showed altered gravitropic root bending in salt conditions and a reduced salt-avoidance response. Our results suggest that extensin modification via Hyp-arabinosylation is a unique salt-specific cellular process required for the directional response of roots exposed to salinity.

Polyvinyl Chloride-Based Luminescent Downshifting Film with High Flame Retardancy and Excellent UV Resistance for Silicon Solar Cells.

Solar power generation, as a clean energy source, has significant potential for development. This work reports the recent efforts to address the challenge of low power conversion efficiency in photovoltaic devices by proposing the fabrication of a luminescence downshifting layer using polyvinyl chloride (PVC) with added fluorescent dots to enhance light utilization. A photoluminescent microsphere (HCPAM) is synthesized by cross-linking hexachlorocyclotriphosphazene, 2-iminobenzimidazoline, and polyethyleneimine. Low addition of HCPAM can improve the fire safety of PVC films, raising the limiting oxygen index of PVC to 32.4% and reducing the total heat release and smoke production rate values by 14.5% and 42.9%, respectively. Additionally, modified PVC film remains a transparency of 88% and shows down-conversion light properties. When the PVC+1%HCPAM film is applied to the solar cell, the short-circuit current density increases from 42.3 to 43.8 mA cm-2, resulting in a 7.0% enhancement in power conversion efficiency. HCPAM also effectively delays the photooxidative aging of PVC, particularly at a 3% content, maintaining the surface morphology and optical properties of PVC samples during ultraviolet aging. This study offers an innovative strategy to enhance the fire and UV-resistant performance of PVC films and expand their applications in protecting and efficiently utilizing photovoltaic devices.

Melt memory in random ethylene-1-alkene copolymers.

Chain flexibility or stiffness based polymer conformation plays a crucial role in affecting the dynamics and kinetics of polymers, which is related to the hierarchical architecture of chains. A series of random copolymers of ethylene and 1-alkenes including 1-hexene, 1-octene, and 1-dodecene were synthesized with metallocene catalysts. The crystallization behavior and memory effect in random ethylene-1-alkene copolymers with different side groups were investigated via differential scanning calorimetry (DSC) and wide-angle X-ray scattering (WAXS). Rheological tests were performed for understanding their dynamical behavior. The results show that the melting peak and the viscosity decrease but the orthorhombic crystal dimensions increase with co-unit contents increasing in the copolymers. It was found that the scaling relationship between the zero shear viscosity (η0) and molecular weight (Mn) of the copolymers containing ethylene-1-hexene and ethylene-1-octene is 3.6, which is higher than the classical scaling value of 3.4. The memory of crystals in the melt is enhanced with the increase of 1-alkene contents but is independent of the types of 1-alkenes. The enhanced melt memory effect in the copolymers was proposed due to the effect of the 1-alkene based side groups on the dynamics of polymer chains. The present work would be helpful to understand the chain stiffness based polymer dynamics and processing of polyolefins and copolymers prepared with the metallocene catalyst.

Ingesting yeast extract causes excitation of neurogenic and myogenic colonic motor patterns in the rat.

Fermented foods play a significant role in the human diet for their natural, highly nutritious and healthy attributes. Our aim was to study the effect of yeast extract, a fermented substance extracted from natural yeast, on colonic motility to better understand its potential therapeutic role. A yeast extract was given to rats by gavage for 3 days, and myogenic and neurogenic components of colonic motility were studied using spatiotemporal maps made from video recordings of the whole colon ex vivo. A control group received saline gavages. The yeast extract caused excitation of the musculature by increasing the propagation length and duration of long-distance contractions, the major propulsive activity of the rat colon. The yeast extract also evoked rhythmic propulsive motor complexes (RPMCs) which were antegrade in the proximal and mid-colon and retrograde in the distal colon. RPMC activity was evoked by distention-induced neural activity, but it was myogenic in nature since we showed it to be generated by bethanechol in the presence of tetrodotoxin. In conclusion, ingestion of yeast extract stimulates rat colon motility by exciting neurogenic and myogenic control mechanisms.

CsRAXs negatively regulate leaf size and fruiting ability through auxin glycosylation in cucumber.

Leaves are the main photosynthesis organ that directly determines crop yield and biomass. Dissecting the regulatory mechanism of leaf development is crucial for food security and ecosystem turn-over. Here, we identified the novel function of R2R3-MYB transcription factors CsRAXs in regulating cucumber leaf size and fruiting ability. Csrax5 single mutant exhibited enlarged leaf size and stem diameter, and Csrax1/2/5 triple mutant displayed further enlargement phenotype. Overexpression of CsRAX1 or CsRAX5 gave rise to smaller leaf and thinner stem. The fruiting ability of Csrax1/2/5 plants was significantly enhanced, while that of CsRAX5 overexpression lines was greatly weakened. Similarly, cell number and free auxin level were elevated in mutant plants while decreased in overexpression lines. Biochemical data indicated that CsRAX1/5 directly promoted the expression of auxin glucosyltransferase gene CsUGT74E2. Therefore, our data suggested that CsRAXs function as repressors for leaf size development by promoting auxin glycosylation to decrease free auxin level and cell division in cucumber. Our findings provide new gene targets for cucumber breeding with increased leaf size and crop yield.

Prediction of protein N-terminal acetylation modification sites based on CNN-BiLSTM-attention model.

N-terminal acetylation is one of the most common and important post-translational modifications (PTM) of eukaryotic proteins. PTM plays a crucial role in various cellular processes and disease pathogenesis. Thus, the accurate identification of N-terminal acetylation modifications is important to gain insight into cellular processes and other possible functional mechanisms. Although some algorithmic models have been proposed, most have been developed based on traditional machine learning algorithms and small training datasets. Their practical applications are limited. Nevertheless, deep learning algorithmic models are better at handling high-throughput and complex data. In this study, DeepCBA, a model based on the hybrid framework of convolutional neural network (CNN), bidirectional long short-term memory network (BiLSTM), and attention mechanism deep learning, was constructed to detect the N-terminal acetylation sites. The DeepCBA was built as follows: First, a benchmark dataset was generated by selecting low-redundant protein sequences from the Uniport database and further reducing the redundancy of the protein sequences using the CD-HIT tool. Subsequently, based on the skip-gram model in the word2vec algorithm, tripeptide word vector features were generated on the benchmark dataset. Finally, the CNN, BiLSTM, and attention mechanism were combined, and the tripeptide word vector features were fed into the stacked model for multiple rounds of training. The model performed excellently on independent dataset test, with accuracy and area under the curve of 80.51% and 87.36%, respectively. Altogether, DeepCBA achieved superior performance compared with the baseline model, and significantly outperformed most existing predictors. Additionally, our model can be used to identify disease loci and drug targets.

Thermal conductivity of irregularly shaped nanoparticles from equilibrium molecular dynamics.

The computation of thermal conductivity for finite nanoparticulate systems, particularly those of irregular shapes, poses significant challenges. Much of the previous work on the thermal conductivity of nanoparticles has been carried out by applying traditional nonequilibrium molecular dynamics (NEMD) methods. One of our recent works [Physical Review B 103, 035417 (2021)] proposed that equilibrium molecular dynamics (EMD) methods can be used for the simulation of thermal conductivity of finite-scale systems and demonstrated their equivalence to NEMD methods. In this work, we explored the application of the EMD approach to calculating the thermal conductivity of zero-dimensional nanoparticles. In our initial step, we merged both methodologies to substantiate the equivalence in thermal conductivity calculation for cube and cylinder nanoparticles. Post data filtration, the usefulness of EMD for thermal conductivity evaluation of zero-dimensional materials was confirmed. The NEMD method struggles with accuracy in nanoparticle systems characterized by a cross-sectional area change in the direction of transport, whereas in the case where the volume can be determined, EMD methods can be used to calculate the thermal conductivity. In a subsequent study, we used the latest machine learning potential (NEP) to calculate the thermal conductivity of spherical nanoparticles and evaluated the results against the classical Tersoff potential.Ultimately, predictions were made for the thermal conductivity of nanoparticles with various unique shapes in all directions. Collectively, our findings underscore the simplicity and effectiveness of using EMD methods for thermal conductivity calculations in the context of nanoparticles. This paves the way for novel strategies in studying the thermal transport properties of finite nanoparticle systems as well as nanopowders.

Curcumin alleviates zearalenone-induced liver injury in mice by scavenging reactive oxygen species and inhibiting mitochondrial apoptosis pathway.

Curcumin (CUR) is a compound extracted from turmeric that has a variety of functions including antioxidant and anti-inflammatory. As an estrogen-like mycotoxin, zearalenone (ZEN) not only attacks the reproductive system, but also has toxic effects on the liver. However, whether CUR can alleviate ZEN-induced liver injury remains unclear. This paper aims to investigate the protective effect of CUR against ZEN-induced liver injury in mice and explore the molecular mechanism involved. BALB/c mice were randomly divided into control (CON) group, CUR group (200 mg/kg b. w. CUR), ZEN group (40 mg/kg b. w. ZEN) and CUR+ZEN group (200 mg/kg b. w. CUR+40 mg/kg b. w. ZEN). 28 d after ZEN exposure and CUR treatment, blood and liver samples were collected for subsequent testing. The results showed that CUR reversed ZEN-induced hepatocyte swelling and necrosis in mice. It significantly reduced the serum alkaline phosphatase (ALP), alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels in mice (p < 0.05). In addition, CUR significantly reduced hepatic ROS, malondialdehyde, hydrogen peroxide and apoptosis levels in mice (p < 0.05). Quantitative RT-PCR and Western blot results showed that CUR significantly reduced the expression of Bax and Caspase3, and reversed the increase of Nrf2, HO-1 and NQO1 expression in the liver of mice induced by ZEN (p < 0.05). In conclusion, CUR alleviated ZEN-induced liver injury in mice by scavenging ROS and inhibiting the mitochondrial apoptotic pathway.

A Temperature Self-Adaptive Electrolyte for Wide-Temperature Aqueous Zinc-Ion Batteries.

The advancement of aqueous zinc-ion batteries (AZIBs) is often hampered by the dendritic zinc growth and the parasitic side reactions between the zinc anode and the aqueous electrolyte, especially under extreme temperature conditions. This study unveils the performance decay mechanism of zinc anodes in harsh environments, characterized by "dead zinc" at low temperatures and aggravated hydrogen evolution and adverse by-products at elevated temperatures. To address these issues, a temperature self-adaptive electrolyte (TSAE), founded on the competitive coordination principle of co-solvent and anions, is introduced. This electrolyte exhibits a dynamic solvation capability, engendering an inorganic-rich solid electrolyte interface (SEI) at low temperatures while an organic alkyl ether- and alkyl carbonate-containing SEI at elevated temperatures. The self-adaptability of the electrolyte significantly enhances the performance of the zinc anode across a broad temperature range. A Zn//Zn symmetrical cell, based on the TSAE, showcases reversible plating/stripping exceeding 16 800 h (>700 d) at room temperature under 1 mA cm-2 and 1 mAh cm-2, setting a record of lifespan. Furthermore, the TSAE enables stable operation of the zinc full batteries across an ultrawide temperature range of -35 to 75 °C. This work illuminates a pathway for optimizing AZIBs under extreme temperatures by fine-tuning the interfacial chemistry.

Limitations and modifications in the clinical application of calcium sulfate.

Calcium sulfate and calcium sulfate-based biomaterials have been widely used in non-load-bearing bone defects for hundreds of years due to their superior biocompatibility, biodegradability, and non-toxicity. However, lower compressive strength and rapid degradation rate are the main limitations in clinical applications. Excessive absorption causes a sharp increase in sulfate ion and calcium ion concentrations around the bone defect site, resulting in delayed wound healing and hypercalcemia. In addition, the space between calcium sulfate and the host bone, resulting from excessively rapid absorption, has adverse effects on bone healing or fusion techniques. This issue has been recognized and addressed. The lack of sufficient mechanical strength makes it challenging to use calcium sulfate and calcium sulfate-based biomaterials in load-bearing areas. To overcome these defects, the introduction of various inorganic additives, such as calcium carbonate, calcium phosphate, and calcium silicate, into calcium sulfate is an effective measure. Inorganic materials with different physical and chemical properties can greatly improve the properties of calcium sulfate composites. For example, the hydrolysis products of calcium carbonate are alkaline substances that can buffer the acidic environment caused by the degradation of calcium sulfate; calcium phosphate has poor degradation, which can effectively avoid the excessive absorption of calcium sulfate; and calcium silicate can promote the compressive strength and stimulate new bone formation. The purpose of this review is to review the poor properties of calcium sulfate and its complications in clinical application and to explore the effect of various inorganic additives on the physicochemical properties and biological properties of calcium sulfate.

Multi-Omics Analysis of Gut Microbiota and Host Transcriptomics Reveal Dysregulated Immune Response and Metabolism in Young Adults with Irritable Bowel Syndrome.

The integrated dysbiosis of gut microbiota and altered host transcriptomics in irritable bowel syndrome (IBS) is yet to be known. This study investigated the associations among gut microbiota and host transcriptomics in young adults with IBS. Stool and peripheral blood samples from 20 IBS subjects and 21 healthy controls (HCs) collected at the baseline visit of an RCT were sequenced to depict the gut microbiota and transcriptomic profiles, respectively. The diversities, composition, and predicted metabolic pathways of gut microbiota significantly differed between IBS subjects and HCs. Nine genera were significantly abundant in IBS stool samples, including Akkermansia, Blautia, Coprococcus, Granulicatella, Holdemania, Oribacterium, Oscillospira, Parabacteroides, and Sutterella. There were 2264 DEGs found between IBS subjects and HCs; 768 were upregulated, and 1496 were downregulated in IBS participants compared with HCs. The enriched gene ontology included the immune system process and immune response. The pathway of antigen processing and presentation (hsa04612) in gut microbiota was also significantly different in the RNA-seq data. Akkermansia, Blautia, Holdemania, and Sutterella were significantly correlated with ANXA2P2 (upregulated, positive correlations), PCSK1N (downregulated, negative correlations), and GLTPD2 (downregulated, negative correlations). This study identified the dysregulated immune response and metabolism in IBS participants revealed by the altered gut microbiota and transcriptomic profiles.

Safety of early antiplatelet therapy for non-cardioembolic mild stroke patients with thrombocytopenia. / åˆå¹¶è¡€å°æ¿å‡å°‘ç—‡çš„éžå¿ƒæºæ€§è½»åž‹è„‘å’ä¸­æ‚£è€ æ—©æœŸæŠ—è¡€å°æ¿æ²»ç–—çš„å®‰å ¨æ€§ç ”ç©¶.

OBJECTIVES: To investigate the safety of early antiplatelet therapy for non-cardioembolic mild stroke patients with thrombocytopenia. METHODS: Data of acute ischemic stroke patients with baseline National Institutes of Health Stroke Scale (NIHSS) score ≤3 and a platelet count <100×109/L were obtained from a multicenter register. Those who required anticoagulation or had other contraindications to antiplatelet therapy were excluded. Short-term safety outcomes were in-hospital bleeding events, while the long-term safety outcome was a 1-year all-cause death. The short-term neurological outcomes were evaluated by modified Rankin scale (mRS) score at discharge. RESULTS: A total of 1868 non-cardioembolic mild stroke patients with thrombocytopenia were enrolled. Multivariate regression analyses showed that mono-antiplatelet therapy significantly increased the proportion of mRS score of 0-1 at discharge (OR=1.657, 95%CI: 1.253-2.192, P<0.01) and did not increase the risk of intracranial hemorrhage (OR=2.359, 95%CI: 0.301-18.503, P>0.05), compared with those without antiplatelet therapy. However, dual-antiplatelet therapy did not bring more neurological benefits (OR=0.923, 95%CI: 0.690-1.234, P>0.05), but increased the risk of gastrointestinal bleeding (OR=2.837, 95%CI: 1.311-6.136, P<0.01) compared with those with mono-antiplatelet therapy. For patients with platelet counts ≤75×109/L and >90×109/L, antiplatelet therapy significantly improved neurological functional outcomes (both P<0.05). For those with platelet counts (>75-90)×109/L, antiplatelet therapy resulted in a significant improvement of 1-year survival (P<0.05). For patients even with concurrent coagulation abnormalities, mono-antiplatelet therapy did not increase the risk of various types of bleeding (all P>0.05) but improved neurological functional outcomes (all P<0.01). There was no significant difference in the occurrence of bleeding events, 1-year all-cause mortality risk, and neurological functional outcomes between aspirin and clopidogrel (all P>0.05). CONCLUSIONS: For non-cardioembolic mild stroke patients with thrombocytopenia, antiplatelet therapy remains a reasonable choice. Mono-antiplatelet therapy has the same efficiency as dual-antiplatelet therapy in neurological outcome improvement with lower risk of gastrointestinal bleeding.

In situ community transcriptomics illuminates CO2-fixation potentials and supporting roles of phagotrophy and proton pump in plankton in a subtropical marginal sea.

Lineage-wise physiological activities of plankton communities in the ocean are important but challenging to characterize. Here, we conducted whole-assemblage metatranscriptomic profiling at continental shelf and slope sites in the South China Sea to investigate carbon fixation potential in different lineages. RuBisCO expression, the proxy of Calvin carbon fixation (CCF) potential, was mainly contributed by Bacillariophyta, Chlorophyta, Cyanobacteria, and Haptophyta, which was differentially affected by environmental factors among lineages. CCF potential exhibited positive or negative correlations with phagotrophy gene expression, suggesting phagotrophy possibly enhances or complements CCF. Our data also reveal significant non-Calvin carbon fixation (NCF) potential, as indicated by the active expression of genes in all five currently recognized NCF pathways, mainly contributed by Flavobacteriales, Alteromonadales, and Oceanospirillales. Furthermore, in Flavobacteriales, Alteromonadales, Pelagibacterales, and Rhodobacterales, NCF potential was positively correlated with proton-pump rhodopsin (PPR) expression, suggesting that NCF might be energetically supported by PPR. The novel insights into the lineage-differential potential of carbon fixation, widespread mixotrophy, and PPR as an energy source for NCF lay a methodological and informational foundation for further research to understand carbon fixation and the trophic landscape in the ocean.IMPORTANCEMarine plankton plays an important role in global carbon cycling and climate regulation. Phytoplankton and cyanobacteria fix CO2 to produce organic compounds using solar energy and mainly by the Calvin cycle, whereas autotrophic bacteria and archaea may fix CO2 by non-Calvin cycle carbon fixation pathways. How active individual lineages are in carbon fixation and mixotrophy, and what energy source bacteria may employ in non-Calvin carbon fixation, in a natural plankton assemblage are poorly understood and underexplored. Using metatranscriptomics, we studied carbon fixation in marine plankton with lineage resolution in tropical marginal shelf and slope areas. Based on the sequencing results, we characterized the carbon fixation potential of different lineages and assessed Calvin- and non-Calvin- carbon fixation activities and energy sources. Data revealed a high number of unigenes (4.4 million), lineage-dependent differential potentials of Calvin carbon fixation and responses to environmental conditions, major contributors of non-Calvin carbon fixation, and their potential energy source.

Competition-Induced Macroscopic Superlubricity of Ionic Liquid Analogues by Hydroxyl Ligands Revealed by in Situ Raman.

High load-bearing capacity is one of the crucial indicators for liquid superlubricants to move toward practicality. However, some of the current emerging systems not only have low contact pressures but also are highly susceptible to further degradation due to water adsorption and even superlubricity failure. Herein, a novel choline chloride-based ionic liquid analogues (ILAs) of a superlubricant with triethanolamine (TEOA) as the H-bond donor is reported for the first time; it obtains an ultralow coefficient of friction (0.005) and high load-bearing capacity (360 MPa, more than 2 times that of similar systems) due to adsorption of a small amount of water (<5 wt %) from the air. In situ Raman combined with 1H NMR and FTIR techniques reveals that adsorbed water competes with the hydroxyl group of TEOA for coordination with Cl-, leading to the conversion of some strong H-bonds to weak H-bonds in ILAs; the localized strong H-bonds and weak H-bonds endow the ILAs with high load-bearing capacity and the formation of ultralow shear-resistance sliding interfaces, respectively, under the shear motion. This study proposes a strategy to modulate the interactions between liquid species using adsorbed water from air as a competing ligand, which provides new insights into the design of ILA-based macroscopic liquid superlubricants with a high load-bearing capacity.

Long-term all-cause death prediction by coronary, aortic, and valvular calcification in patients with acute ST-segment elevation myocardial infarction.

BACKGROUND: To determine the prognostic value of cumulative calcification score of coronary artery calcification (CAC), thoracic aortic calcification (TAC) and aortic valve calcification (AVC) in acute ST segment elevation myocardial infarction (STEMI) patients. METHODS: This was a retrospective, single-center cohort study. A total of 332 STEMI patients who received primary percutaneous coronary intervention (PPCI) were enrolled in this study between January 2010 to October 2018. We assessed the calcification in the left anterior descending branch (LAD), left circumflex branch (LCX), right coronary artery (RCA), thoracic aorta, and aortic valve. Calcification of each part was counted as 1 point, and the cumulative calcification score was calculated as the sum of all points. The primary endpoint was all-cause mortality. Multivariate Cox proportional hazards models were used to determine association of cumulative calcification score with end points. The performance of the score was evaluated by receiver operating characteristic (ROC) curve analysis and absolute net reclassification improvement (NRI), compared with the Global Registry of Acute Coronary Events (GRACE) risk score. RESULTS: The overall population's calcification score was 2.0 ± 1.6. During a mean follow-up time of 69.8 ± 29.3 months, the all-cause mortality rate was 12.1%. Kaplan-Meier curve showed that the score was significantly associated with mortality (log-rank p < 0.001). The multivariable Cox proportional hazard analyses showed that a calcification score of 4-5 was independently associated with all-cause death in STEMI patients [hazard ratio (HR) = 2.32, 95% confidence interval (CI): 1.01-5.31, p = 0.046]. The area under the ROC curve (AUC) of the calcification score was 0.67 (95% CI: 0.61-0.72), and the AUC of the GRACE score was 0.80 (95% CI: 0.75-0.84). There was no statistical difference in the predictive value between both scores for 3-year mortality in STEMI patients after PPCI (p = 0.06). Based on the NRI analysis, the calcification score showed better risk classification compared with the GRACE score (absolute NRI = 6.63%, P = 0.027). CONCLUSION: The cumulative calcification score is independently associated with the long-term prognosis of STEMI patients after PPCI.

Surface modification of zinc oxide and its application in polypropylene with excellent fire performance and ultra-violet resistance.

Despite the advantages of easy moulding and excellent mechanical properties, there are still some shortcomings with polypropylene (PP) such as high flammability and poor ultra-violet (UV) resistance. In this work, modified zinc oxide (mZnO) was prepared by reacting zinc oxide nanoparticles (ZnO) with polysiloxanes, and the effect of mZnO on the effectiveness of intumescent flame-retardant and on the UV aging resistance of polypropylene were investigated. By introducing 16 wt% (intumescent flame-retardant /mZnO) and 0.3 wt% maleic anhydride-grafted PP (MAH-g-PP), the limiting oxygen index increased to 32.7 %, and passed UL-94V-0 rating. In comparison to the controls, the peak heat release rate and the peak smoke release rate were 88.5 % and 80 % lower, respectively. In addition, PP samples showed improved mechanical properties, with a 5 % increase in tensile properties compared to the pure PP sample. After 100 h of UV irradiation, the surface of the samples was relatively flat and smooth, and the carbonyl index decreased from 81.1 of neat PP to 26.7. PP composites with 100 h aging treatment still had excellent flame retardancy and mechanical properties. The results showed that mZnO was effective in improving the flame retardancy, mechanical properties and light aging tolerance of PP. This study provides a novel approach to fabricate long-life flame-retardant PP composites with low additive content.

Fine Tuning Water States in Hydrogels for High Voltage Aqueous Batteries.

Hydrogels are widely used as quasi-solid-state electrolytes in aqueous batteries. However, they are not applicable in high-voltage batteries because the hydrogen evolution reaction cannot be effectively suppressed even when water is incorporated into the polymer network. Herein, by profoundly investigating the states of water molecules in hydrogels, we designed supramolecular hydrogel electrolytes featuring much more nonfreezable bound water and much less free water than that found in conventional hydrogels. Specifically, two strategies are developed to achieve this goal. One strategy is adopting monomers with a variety of hydrophilic groups to enhance the hydrophilicity of polymer chains. The other strategy is incorporating zwitterionic polymers or polymers with counterions as superhydrophilic units. In particular, the nonfreezable bound water content increased from 0.129 in the conventional hydrogel to >0.4 mg mg-1 in the fabricated hydrogels, while the free water content decreased from 1.232 to ∼0.15 mg mg-1. As a result, a wide electrochemical stability window of up to 3.25 V was obtained with the fabricated hydrogels with low concentrations of incorporated salts and enhanced hydrophilic groups or superhydrophilic groups. The ionic conductivities achieved with our developed hydrogel electrolytes were much higher than those in the conventional highly concentrated salt electrolytes, and their cost is also much lower. The designed supramolecular hydrogel electrolytes endowed an aqueous K-ion battery (AKIB) system with a high voltage plateau of 1.9 V and contributed to steady cycling of the AKIB for over 3000 cycles. The developed supramolecular hydrogel electrolytes are also applicable to other batteries, such as aqueous lithium-ion batteries, hybrid sodium-ion batteries, and multivalent-ion aqueous batteries, and can achieve high voltage output.

Potassium dehydroandrographolide succinate regulates the MyD88/CDH13 signaling pathway to enhance vascular injury-induced pathological vascular remodeling.

Pathological vascular remodeling is a hallmark of various vascular diseases. Previous research has established the significance of andrographolide in maintaining gastric vascular homeostasis and its pivotal role in modulating endothelial barrier dysfunction, which leads to pathological vascular remodeling. Potassium dehydroandrographolide succinate (PDA), a derivative of andrographolide, has been clinically utilized in the treatment of inflammatory diseases precipitated by viral infections. This study investigates the potential of PDA in regulating pathological vascular remodeling. The effect of PDA on vascular remodeling was assessed through the complete ligation of the carotid artery in C57BL/6 mice. Experimental approaches, including rat aortic primary smooth muscle cell culture, flow cytometry, bromodeoxyuridine (BrdU) incorporation assay, Boyden chamber cell migration assay, spheroid sprouting assay, and Matrigel-based tube formation assay, were employed to evaluate the influence of PDA on the proliferation and motility of smooth muscle cells (SMCs). Molecular docking simulations and co-immunoprecipitation assays were conducted to examine protein interactions. The results revealed that PDA exacerbates vascular injury-induced pathological remodeling, as evidenced by enhanced neointima formation. PDA treatment significantly increased the proliferation and migration of SMCs. Further mechanistic studies disclosed that PDA upregulated myeloid differentiation factor 88 (MyD88) expression in SMCs and interacted with T-cadherin (CDH13). This interaction augmented proliferation, migration, and extracellular matrix deposition, culminating in pathological vascular remodeling. Our findings underscore the critical role of PDA in the regulation of pathological vascular remodeling, mediated through the MyD88/CDH13 signaling pathway.

DBPboost:A method of classification of DNA-binding proteins based on improved differential evolution algorithm and feature extraction.

DNA-binding proteins are a class of proteins that can interact with DNA molecules through physical and chemical interactions. Their main functions include regulating gene expression, maintaining chromosome structure and stability, and more. DNA-binding proteins play a crucial role in cellular and molecular biology, as they are essential for maintaining normal cellular physiological functions and adapting to environmental changes. The prediction of DNA-binding proteins has been a hot topic in the field of bioinformatics. The key to accurately classifying DNA-binding proteins is to find suitable feature sources and explore the information they contain. Although there are already many models for predicting DNA-binding proteins, there is still room for improvement in mining feature source information and calculation methods. In this study, we created a model called DBPboost to better identify DNA-binding proteins. The innovation of this study lies in the use of eight feature extraction methods, the improvement of the feature selection step, which involves selecting some features first and then performing feature selection again after feature fusion, and the optimization of the differential evolution algorithm in feature fusion, which improves the performance of feature fusion. The experimental results show that the prediction accuracy of the model on the UniSwiss dataset is 89.32%, and the sensitivity is 89.01%, which is better than most existing models.