Study on crystal and amorphous transformation of ultrasonic vibration assisted laser cladded Fe-based amorphous coatings.

In order to investigate the influence of ultrasonic vibration (UV) on microstructural evaluation of amorphous coating, the Fe-based amorphous (Fe41.5Co12.2Cr7.4Mo37.3C0.3B0.5Y0.4Al0.4) coatings with and without UV were fabricated by laser cladding technology. The microstructure and corrosion resistance of the coatings were studied in detail to understand the mechanism of the UV on amorphous coatings. It can be found that the cavitation effect generated by UV refines and breaks the columnar crystals at the interface. Compared to the coatings without UV, the average length of columnar crystals of coatings with UV decreases by 57.52 %, reducing from 25.26 ± 5.89 µm to 10.73 ± 3.91 µm. In addition, the sound pressure gradient drives the accelerated flow of the molten pool, resulting in a flow velocity of up to 0.134 m/s. The acoustic streaming effect of UV promotes the uniform distribution of elements and inhibits the segregation of the intermetallic compounds, which increases the amorphous content from 68.5 % to 75.3 %. The acoustic streaming and cavitation effects refine the microstructure and increase the amorphous content by using of UV, which contributes to improve the corrosion resistance.

Feasibility and Effectiveness of Venoarterial Extracorporeal Membrane Oxygenation Plus Intra-Aortic Balloon Pump Assisted High-Risk Percutaneous Coronary Intervention in Complex Coronary Disease.

Background: Mechanical circulatory support may facilitate high-risk percutaneous coronary intervention (PCI). This study aimed to assess the feasibility, safety and effectiveness of high-risk PCI under the support of venoarterial extracorporeal membrane oxygenation (VA-ECMO) combined with intra-aortic balloon pump (IABP). Methods: We enrolled patients who received VA-ECMO plus IABP-assisted PCI procedures at our center from April 2012 to June 2018. Major adverse cardiac events (MACEs) included all-cause death, myocardial infarction, and target vessel revascularization. Results: A total of 10 patients were included, with a mean age of 71 years, EuroSCORE II of 19.9%, and SYNTAX score of 39.8. Procedural success was achieved in nine (90%) patients. The mean duration of ECMO support was 1.5 hours, and 2.6 stents were implanted per patient. Major complications included contrast-induced nephropathy needing hemodialysis in one (10%) patient, significant hemoglobin drop requiring blood transfusion in two (20%) patients, pulmonary infection in one (10%) patient, and local surgical incision infection in one (10%) patient. The accumulative mortality rates for the nine patients with procedural success were 0, 22.2%, and 44.4% at 1, 3, and 5 years follow-up, respectively. However, cardiac death occurred in only one (11.1%) patient. In addition, two patients received repeat PCI or coronary artery bypass grafting within two years following the index procedure. The overall incidence rates of MACEs were 11.1%, 44.4%, and 66.7% at 1, 3, and 5 years follow-up, respectively. Conclusions: VA-ECMO plus IABP-assisted high-risk PCI was feasible in patients with complex coronary disease, with a high procedural success rate and acceptable mid-term clinical outcomes.

Universal All-In-One Lateral Flow Immunoassay with Triple Signal Amplification for Ultrasensitive and Simple Self-Testing of Treponema pallidum Antibodies.

Lateral flow immunoassay (LFIA) is valued for its simplicity and rapidity for on-site screening, however, it experienced false negatives in real sample analysis due to low sensitivity. Although many signal amplification techniques can improve the sensitivity, they usually require additional complicated steps. To address these issues, taking Treponema pallidum (T. pallidum) antibodies as a model detecting target, herein, we report an all-in-one LFIA (AIO-LFIA) with triple-step signal amplification to significantly improve sensitivity while maintaining simplicity. This LFIA utilizes a biotin-streptavidin system for initial signal amplification, followed by introducing a release controller with a specific imprinted structure for timed multicomponent release, which avoids the extra steps when adding components in traditional LFIA. Particularly, a 3D-printed programmed metal in situ growth (MISG) device is integrated to localize signal enhancement at specific sites, overcoming limitations of traditional MISG and substantially reducing reagent usage and assay time, and the nitrocellulose membrane surface was much cleaner than the conventional approach, which facilitates signal readout. After optimization, the proposed AIO-LFIA is capable of visual detection down to 1 pg/mLT. pallidum antibodies in 15 min, 1000-fold lower than the gold nanoparticle-based LFIA. In clinical testing of 152 samples, the AIO-LFIA can distinguish all positive samples, outperforming commercial LFIA which missed those positive samples with relatively low antibody levels. Thus, this study presents a universal ultrasensitive and reliable AIO-LFIA strategy for infectious diseases self-testing, providing an effective promising prospect to address the challenge over emerging infectious diseases in the future.

A rare complication of prophylactical clip closure after colonic endoscopic submucosal dissection.

Prophylactic defect closure has been considered to prevent delayed bleeding after polypectomy. However, recent evidence has demonstrated its beneficial effect is limited to those ≥20 mm proximal nonpedunculated lesions. Despite this, prophylactic defect closure is widely performed in clinical practice after colonic endoscopic submucosal dissection (ESD). We present a rare complication of prophylactical clip closure after colonic ESD.

Genome-wide analysis of the trihelix gene family reveals that MaGT21 modulates fruit ripening by regulating the expression of MaACO1 in Musa acuminata.

The trihelix transcription factor (GT) gene family members play vital roles in plant growth and development, responses to abiotic or biotic stress, and fruit ripening. However, its role in banana fruit ripening remains unclear. Here, 59 MaGT gene members were identified in banana and clustered into five subfamilies, namely GT1, GT2, GTγ, SIP1, and SH4. This classification is completely supported by their gene structures and conserved motif analysis. Transcriptome data analysis indicated that MaGT14, MaGT21, and MaGT27 demonstrated significant differential expression during fruit ripening. Quantitative real-time PCR analysis revealed that these three genes were highly induced by ethylene treatment, responded to cold and heat stress, and had a high expression abundance in ripe fruit. Subcellular localization demonstrated that MaGT21 and MaGT27 functioned as nuclear proteins, while MaGT14 functioned as a nuclear and cell membrane protein. Further investigation indicated MaGT21 could positively stimulate the transcription of the key ethylene biosynthesis gene MaACO1 by directly targeting the GT motif in the promoter. MaGT21 transient overexpression in banana fruit upregulated MaACO1 and accelerated fruit ripening. Our findings provide comprehensive and valuable information for further functional studies of MaGT genes in banana, help to understand the roles of MaGTs during banana fruit ripening.

CAR expression in invasive breast carcinoma and its effect on adenovirus transduction efficiency.

BACKGROUND: Breast cancer is the second leading cause of death in women, with invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) as the two most common forms of invasive breast cancer. While estrogen receptor positive (ER+) IDC and ILC are treated similarly, the multifocality of ILC presents challenges in detection and treatment, worsening long-term clinical outcomes in patients. With increasing documentation of chemoresistance in ILC, additional treatment options are needed. Oncolytic adenoviral therapy may be a promising option, but cancer cells must express the coxsackievirus & adenovirus receptor (CAR) for adenoviral therapy to be effective. The present study aims to evaluate the extent to which CAR expression is observed in ILC in comparison to IDC, and how the levels of CAR expression correlate with adenovirus transduction efficiency. The effect of liposome encapsulation on transduction efficiency is also assessed. METHODS: To characterize CAR expression in invasive breast carcinoma, 36 formalin-fixed paraffin-embedded (FFPE) human breast tumor samples were assayed by CAR immunohistochemistry (IHC). Localization of CAR in comparison to other junctional proteins was performed using a multiplex immunofluorescence panel consisting of CAR, p120-catenin, and E-cadherin. ILC and IDC primary tumors and cell lines were transduced with E1- and E3-deleted adenovirus type 5 inserted with a GFP transgene (Ad-GFP) and DOTAP liposome encapsulated Ad-GFP (DfAd-GFP) at various multiplicities of infection (MOIs). Transduction efficiency was measured using a fluorescence plate reader. CAR expression in the human primary breast carcinomas and cell lines was also evaluated by IHC. RESULTS: We observed membranous CAR, p120-catenin and E-cadherin expression in IDC. In ILC, we observed cytoplasmic expression of CAR and p120-catenin, with absent E-cadherin. Adenovirus effectively transduced high-CAR IDC cell lines, at MOIs as low as 12.5. Ad-GFP showed similar transduction as DfAd-GFP in high-CAR IDC cell lines. Conversely, Ad-GFP transduction of ILC cell lines was observed only at MOIs of 50 and 100. Furthermore, Ad-GFP did not transduce CAR-negative IDC cell lines even at MOIs greater than 100. Liposome encapsulation (DfAd-GFP) improved transduction efficiency 4-fold in ILC and 17-fold in CAR-negative IDC cell lines. CONCLUSION: The present study demonstrates that oncolytic adenoviral therapy is less effective in ILC than IDC due to differences in spatial CAR expression. Liposome-enhanced delivery may be beneficial for patients with ILC and tumors with low or negative CAR expression to improve adenoviral therapeutic effectiveness.

Identification of a specific APOE transcript and functional elements associated with Alzheimer's disease.

BACKGROUND: The APOE gene is the strongest genetic risk factor for late-onset Alzheimer's Disease (LOAD). However, the gene regulatory mechanisms at this locus remain incompletely characterized. METHODS: To identify novel AD-linked functional elements within the APOE locus, we integrated SNP variants with multi-omics data from human postmortem brains including 2,179 RNA-seq samples from 3 brain regions and two ancestries (European and African), 667 DNA methylation samples, and ChIP-seq samples. Additionally, we plotted the expression trajectory of APOE transcripts in human brains during development. RESULTS: We identified an AD-linked APOE transcript (jxn1.2.2) particularly observed in the dorsolateral prefrontal cortex (DLPFC). The APOE jxn1.2.2 transcript is associated with brain neuropathological features, cognitive impairment, and the presence of the APOE4 allele in DLPFC. We prioritized two independent functional SNPs (rs157580 and rs439401) significantly associated with jxn1.2.2 transcript abundance and DNA methylation levels. These SNPs are located within active chromatin regions and affect brain-related transcription factor-binding affinities. The two SNPs shared effects on the jxn1.2.2 transcript between European and African ethnic groups. CONCLUSION: The novel APOE functional elements provide potential therapeutic targets with mechanistic insight into the disease etiology.

Giant nonlinear optical wave mixing in a van der Waals correlated insulator.

Optical nonlinearities are one of the most fascinating properties of two-dimensional (2D) materials. While tremendous efforts have been made to find and optimize the second-order optical nonlinearity in enormous 2D materials, opportunities to explore higher-order ones are elusive because of the much lower efficiency. Here, we report the giant high odd-order optical nonlinearities in centrosymmetric correlated van der Waals insulator manganese phosphorus triselenide. When illuminated by two near-infrared femtosecond lasers, the sample generates a series of profound four- and six-wave mixing outputs. The near-infrared third-order nonlinear susceptibility reaches near the highest record values of 2D materials. Comparative measurements to other prototypical nonlinear optical materials [lithium niobate, gallium(II) selenide, and tungsten disulfide] reveal its extraordinary wave mixing efficiency. The wave mixing processes are further used for nonlinear optical waveguide with multicolor emission. Our work highlights the promising prospect for future research of the nonlinear light-matter interactions in the correlated 2D system and for potential nonlinear photonic applications.

Global Stability of Phase-Change Neural Networks With Mixed Time Delays.

Phase-change memory (PCM) is a novel type of nonvolatile memory and is suitable for artificial neural synapses. This article investigates the Lagrange global exponential stability (LGES) of a class of PCNNs with mixed time delays. First, based on the conductivity characteristics of PCM, a piecewise equation is established to describe the electrical conductivity of PCM. By using the proposed piecewise equation to simulate the neural synapses, a novel PCNN with discrete and distributed time delays is proposed. Then, using comparative theory and fundamental inequalities, the LGES conditions based on the M -matrix are proposed in the sense of Filippov, and the exponential attractive set (EAS) is obtained based on M -matrix and external input. Moreover, the Lyapunov global exponential stability (GES) conditions of PCNNs without external input are obtained by using the inequality technique and eigenvalue theory, which is a form of M -matrix. Finally, two simulation examples are given to verify the validity of the obtained results.

Asynchronous iterative Q-learning based tracking control for nonlinear discrete-time multi-agent systems.

This paper addresses the tracking control problem of nonlinear discrete-time multi-agent systems (MASs). First, a local neighborhood error system (LNES) is constructed. Then, a novel tracking algorithm based on asynchronous iterative Q-learning (AIQL) is developed, which can transform the tracking problem into the optimal regulation of LNES. The AIQL-based algorithm has two Q values QiA and QiB for each agent i, where QiA is used for improving the control policy and QiB is used for evaluating the value of the control policy. Moreover, the convergence of LNES is given. It is shown that the LNES converges to 0 and the tracking problem is solved. A neural network-based actor-critic framework is used to implement AIQL. The critic network of AIQL is composed of two neural networks, which are used for approximating QiA and QiB respectively. Finally, simulation results are given to verify the performance of the developed algorithm. It is shown that the AIQL-based tracking algorithm has a lower cost value and faster convergence speed than the IQL-based tracking algorithm.

Efficacy and Safety of Azvudine in Patients With COVID-19 in China: A Meta-Analysis of Observational Studies.

BACKGROUND: Azvudine (FNC) is a novel small molecule antiviral drug for treating COVID-19 that is available only on the Chinese market. Despite being recommended for treating COVID-19 by the Chinese guidelines, its efficacy and safety are still unclear. This study aimed to evaluate the protective effect of FNC on COVID-19 outcomes and its safety. METHODS: We followed the PRISMA 2020 guidelines and searched the PubMed, Embase, Web of Science, Scopus, and China National Knowledge Infrastructure (CNKI) databases to evaluate studies on the effectiveness of FNC in treating COVID-19 in China, focusing on mortality and overall outcomes. Additionally, its impact on the length of hospital stay (LOHS), time to first nucleic acid negative conversion (T-FNANC), and adverse events was evaluated. The inclusion criterion was that the studies were published from July 2021 to April 10, 2024. This study uses the ROBINS-I tool to assess bias risk and employs the GRADE approach to evaluate the certainty of the evidence. RESULTS: The meta-analysis included 24 retrospective studies involving a total of 11 830 patients. Low-certainty evidence revealed no significant difference in mortality (OR = 0.91, 95% CI: 0.76-1.08) or LOHS (WMD = -0.24, 95% CI: -0.83 to 0.35) between FNC and Paxlovid in COVID-19 patients. Low-certainty evidence shows that the T-FNANC was longer (WMD = 1.95, 95% CI: 0.36-3.53). Compared with the Paxlovid group, low-certainty evidence shows the FNC group exhibited a worse composite outcome (OR = 0.77, 95% CI: 0.63-0.95) and fewer adverse events (OR = 0.63, 95% CI: 0.46-0.85). Compared with supportive treatment, low certainty shows FNC significantly reduced the mortality rate in COVID-19 patients (OR = 0.61, 95% CI: 0.51-0.74) and decreased the composite outcome (OR = 0.67, 95% CI: 0.50-0.91), and very low certainty evidence shows significantly decreased the T-FNANC (WMD = -4.62, 95% CI: -8.08 to -1.15). However, in very low certainty, there was no significant difference in LOHS (WMD = -0.70, 95% CI: -3.32 to 1.91) or adverse events (OR = 1.97, 95% CI: 0.48-8.17). CONCLUSIONS: FNC appears to be a safe and potentially effective treatment for COVID-19 in China, but further research with larger, high-quality studies is necessary to confirm these findings. Due to the certainty of the evidence and the specific context of the studies conducted in China, caution should be exercised when considering whether the results are applicable worldwide. TRIAL REGISTRATION: PROSPERO number: CRD42024520565.

Synthesis and application of well-defined [Ph4P]+[Cu(CF2CF3)2]- complex as a versatile pentafluoroethylating reagent.

We herein describe the preparation and application of a new bispentafluoroethylated organocuprate [Ph4P]+[Cu(CF2CF3)2]-. This complex has demonstrated a remarkable range of reactivities towards carboxylic acids, diazonium salts, organic halides, boronic esters, terminal alkynes and (hetero)arenes as a versatile pentafluoroethylating reagent. The construction of C(sp3)-/C(sp2)-/C(sp)-CF2CF3 bonds can therefore be achieved using a single reagent.

Construction of hollow sphere MnOX with abundant oxygen vacancy for accelerating VOCs degradation: Investigation through operando spectroscopycombined with on-line mass spectrometry.

To clarify the key role of oxygen vacancy defects on enhancing the oxidative activity of the catalysts, metal-organic frameworks (MOFs) derived MnOX catalysts with different morphologies and oxygen vacancy defects were successfully prepared using a facile in-situ self-assembly strategy with different alkali moderators. The obtained morphologies included three-dimensional (3D) triangular cone stacked MnOX hollow sphere (MnOX-H) and 3D nanoparticle stacked MnOX nanosphere (MnOX-N). Compared to MnOX-N, MnOX-H exhibited higher activity for the oxidation of toluene (T90 = 226 °C). This was mainly due to the large number of oxygen vacancy defects and Mn4+ species in the MnOX-H catalyst. In addition, the hollow structure of MnOX-H not only facilitated toluene adsorption and activation of toluene and also provided more active sites for toluene oxidation. Reaction mechanism studies showed that the conversion of toluene to benzoate could be realized over MnOX-H catalyst during toluene adsorption at room temperature. In addition, abundant oxygen vacancy defects can accelerate the activated oxidation of toluene and the formation of oxidation products during toluene oxidation.

Sensitive Dual-Signal ELISA Based on Specific Phage-Displayed Double Peptide Probes with Internal Filtering Effect to Assay Monkeypox Virus Antigen.

The global spread of monkeypox has become a worldwide public healthcare issue. Therefore, there is an urgent need for accurate and sensitive detection methods to effectively control its spreading. Herein, we screened by phage display two peptides M4 (sequence: DPCGERICSIAL) and M6 (sequence: SCSSFLCSLKVG) with good affinity and specificity to monkeypox virus (MPXV) B21R protein. To simulate the state of the peptide in the phage and to avoid spatial obstacles of the peptide, GGGSK was added at the C terminus of M4 and named as M4a. Molecular docking shows that peptide M4a and peptide M6 are bound to different epitopes of B21R by hydrogen bonds and salt-bridge interactions, respectively. Then, peptide M4a was selected as the capture probe, phage M6 as the detection probe, and carbonized polymer dots (CPDs) as the fluorescent probe, and a colorimetric and fluorescent double-signal capture peptide/antigen/signal peptide-displayed phage sandwich ELISA triggered by horseradish peroxidase (HRP) through a simple internal filtration effect (IFE) was constructed. HRP catalyzes H2O2 to oxidize 3,3',5,5'-tetramethylbenzidine (TMB) to generate blue oxidized TMB, which can further quench the fluorescence of CPDs through IFE, enabling to detect MPXV B21R in colorimetric and fluorescent modes. The proposed simple immunoassay platform shows good sensitivity and reliability in MPXV B21R detection. The limit of detection for colorimetric and fluorescent modes was 27.8 and 9.14 pg/mL MPXV B21R, respectively. Thus, the established double-peptide sandwich-based dual-signal immunoassay provides guidance for the development of reliable and sensitive antigen detection capable of mutual confirmation, which also has great potential for exploring various analytical strategies for other respiratory virus surveillance.

Nutrient Recovery from Algae Using Mild Oxidative Treatment and Ion Exchange.

Valorization of algal biomass to fuels and chemicals frequently requires pretreatment to lyse cells and extract lipids, leaving behind an extracted solid residue as an underutilized intermediate. Mild oxidative treatment (MOT) is a promising route to simultaneously convert nitrogen contained in these residues to easily recyclable ammonium and to convert carbon in the same fraction to biofuel precursor carboxylates. We show that for a Nannochloropsis algae under certain oxidation conditions, nearly all the nitrogen in the residues can be converted to ammonium and recovered by cation exchange, while up to ∼20% of the carbon can be converted to short chain carboxylates. At the same time, we also show that soluble phosphorus in the form of phosphate can be selectively recovered by anion exchange, leaving a clean aqueous carbon stream for further upgrading.

Dynamic Monitoring of Biomolecular Hydrodynamic Dimensions by Magnetization Motion on Quartz Crystal Microbalance.

Hydrodynamic dimension (HD) is the primary indicator of the size of bioconjugated particles and biomolecules. It is an important parameter in the study of solid-liquid two-phase dynamics. HD dynamic monitoring is crucial for precise and customized medical research as it enables the investigation of the continuous changes in the physicochemical characteristics of biomolecules in response to external stimuli. However, current HD measurements based on Brownian motion, such as dynamic light scattering (DLS), are inadequate for meeting the polydisperse sample demands of dynamic monitoring. In this paper, we propose MMQCM method samples of various types and HD dynamic monitoring. An alternating magnetic field of frequency ωm excites biomolecule-magnetic bead particles (bioMBs) to generate magnetization motion, and the quartz crystal microbalance (QCM) senses this motion to provide HD dynamic monitoring. Specifically, the magnetization motion is modulated onto the thickness-shear oscillation of the QCM at the frequency ωq. By analysis of the frequency spectrum of the QCM output signal, the ratio of the magnitudes of the real and imaginary parts of the components at frequency ωq ± 2ωm is extracted to characterize the particle size. Using the MMQCM approach, we successfully evaluated the size of bioMBs with different biomolecule concentrations. The 30 min HD dynamic monitoring was implemented. An increase of ∼10 nm in size was observed upon biomolecular structural stretching. Subsequently, the size of bioMBs gradually reduced due to the continuous dissociation of biomolecules, with a total reduction of 20∼40 nm. This HD dynamic monitoring demonstrates that the release of biomolecules can be regulated by controlling the duration of magnetic stimulation, providing valuable insights and guidance for controlled drug release in personalized precision medicine.

De-risking Pretreatment of Microalgae To Produce Fuels and Chemical Co-products.

Conversion of microalgae to renewable fuels and chemical co-products by pretreating and fractionation holds promise as an algal biorefinery concept, but a better understanding of the pretreatment performance as a function of algae strain and composition is necessary to de-risk algae conversion operations. Similarly, there are few examples of algae pretreatment at scales larger than the bench scale. This work aims to de-risk algal biorefinery operations by evaluating the pretreatment performance across nine different microalgae samples and five different pretreatment methods at small (5 mL) scale and further de-risk the operation by scaling pretreatment for one species to the 80 L scale. The pretreatment performance was evaluated by solubilization of feedstock carbon and nitrogen [as total organic carbon (TOC) and total nitrogen (TN)] into the aqueous hydrolysate and extractability of lipids [as fatty acid methyl esters (FAMEs)] from the pretreated solids. A range of responses was noted among the algae samples across pretreatments, with the current dilute Brønsted acid pretreatment using H2SO4 being the most consistent and robust. This pretreatment produced TOC yields to the hydrolysate ranging from 27.7 to 51.1%, TN yields ranging from 12.3 to 76.2%, and FAME yields ranging from 57.9 to 89.9%. In contrast, the other explored pretreatments (other dilute acid pretreatments, dilute alkali pretreatment with NaOH, enzymatic pretreatment, and flash hydrolysis) produced lower or more variable yields across the three metrics. In light of the greater consistency across samples for dilute acid pretreatment, this method was scaled to 80 L to demonstrate scalability with microalgae feedstocks.

Role of Bß1 overexpression in the pathogenesis of SCA12.

BACKGROUND: Spinocerebellar ataxia type 12 (SCA12) is a neurodegenerative disease caused by a CAG/CTG repeat expansion at the PPP2R2B locus. OBJECTIVE: We investigated how the CAG repeat expansion within the PPP2R2B 7B7D transcript influences the expression of Bß1 and a potential protein containing a long polyserine tract. METHODS: Transcript and protein expression were measured using quantitative PCR (qPCR) Role of Bß1 overexpression in the pathogenesis of SCA12 and Western blot, respectively, in an SK-N-MC cell model that overexpresses the full-length PPP2R2B 7B7D transcript. The apoptotic effect of a protein containing a long polyserine tract on SK-N-MC cells was evaluated using caspase 3/7 activity. RESULTS: The CAG repeat expansion increases the expression of the PPP2R2B 7B7D transcript, as well as Bß1 protein, in an SK-N-MC cell model in which the full-length PPP2R2B 7B7D transcript is overexpressed. The CAG repeat expansion within the 7B7D transcript is translated into a long polyserine tract that triggers apoptosis in SK-N-MC cells. CONCLUSIONS: The SCA12 mutation leads to overexpression of PPP2R2B Bß1 and to expression of a protein containing a long polyserine tract; both these effects potentially contribute to SCA12 pathogenesis. © 2024 International Parkinson and Movement Disorder Society.

Crash severity analysis: A data-enhanced double layer stacking model using semantic understanding.

The crash severity analysis is of significant importance in traffic crash prevention and emergency resource allocation. A range of innovations offers potential traffic crash severity prediction models to improve road safety. However, the semantic information inherent in traffic crash data, which is crucial in enabling a deeper understanding of its underlying factors and impacts, has yet to be fully utilized. Moreover, traffic crash data are commonly characterized by a small sample size, which leads to sample imbalance problem resulting in prediction performance decline. To tackle these problems, we propose a semantic understanding-based data-enhanced double-layer stacking model, named EnLKtreeGBDT, for crash severity prediction. Specifically, to fully leverage the inherent semantic information within traffic crash data and analyze the factors influencing crashes, we design a semantic enhancement module for multi-dimensional feature extraction. This module aims to enhance the understanding of crash semantics and improve prediction accuracy. Then we introduce a data enhancement module that utilizes data denoising and migration techniques to address the challenge of data imbalance, reducing the prediction model's dependence on large sample crash data. Furthermore, we construct a two-layer stacking model that combines multiple linear and nonlinear classifiers. This model is designed to augment the capability of learning linear and nonlinear mixed relationships, thereby improving the accuracy of predicting the severity of crashes on complex urban roads. Experiments on historical datasets of UK road safety crashes validate the effectiveness of the proposed model, and superior performance of prediction precision is achieved compared with the state-of-the-arts. The ablation experiments on both semantic and data enhancement modules further confirm the indispensability of each module in the proposed model.