Decoding the bitter taste of Idesia polycarpa var. vestita Diels fruit: Bitterness contribution and mechanisms.

To comprehensively explore the contribution and mechanisms of identified low-threshold bitter substances in Idesia polycarpa var. vestita Diels (I. vestita) fruit, we performed quantification and elucidated their interactions with main bitter taste receptors through molecular docking. The established method for quantifying bitter compounds in I. vestita fruit was validated, yielding satisfactory parameters for linearity, stability, and accuracy. Idescarpin (17.71-101.05 mg/g) and idesin (7.88-77.14 mg/g) were the predominant bitter compounds in terms of content. Taste activity values (TAVs) exceeded 10 for the bitter substances, affirming their pivotal role as major contributors to overall bitterness of I. vestita fruit. Notably, idescarpin with the highest TAV, played a crucial role in generating the bitterness of I. vestita fruit. Hydrogen bonds and hydrophobic interactions were the main driving forces. This study holds potential implications for industrial development of I. vestita fruit by providing novel insights into the mechanism underlying its bitterness formation.

Synergistic Crystallization Modulation and Defects Passivation in Kesterite via Anion-Coordinate Precursor Engineering for Efficient Solar Cells.

It has been validated that enhancing crystallinity and passivating the deep-level defect are critical for improving the device performance of kesterite Cu2ZnSn(S,Se)4 (CZTSSe) solar cells. Coordination chemistry interactions within the Cu-Zn-Sn-S precursor solution play a crucial role in the management of structural defects and the crystallization kinetics of CZTSSe thin films. Therefore, regulating the coordination environment of anion and cation in the precursor solution to control the formation process of precursor films is a major challenge at present. Herein, a synergetic crystallization modulation and defect passivation method is developed using P2S5 as an additive in the CZTS precursor solution to optimize the coordination structure and improve the crystallization process. The alignment of theoretical assessments with experimental observations confirms the ability of the P2S5 molecule to coordinate with the metal cation sites of CZTS precursor films, especially more liable to the Zn2+, effectively passivating the Zn-related defects, thereby significantly reducing the defect density in CZTSSe absorbers. As a result, the device with a power conversion efficiency of 14.36% has been achieved. This work provides an unprecedented strategy for fabricating high-quality thin films by anion-coordinate regulation and a novel route for realizing efficient CZTSSe solar cells.

A Review of Fluoride Removal from Phosphorous Gypsum: A Quantitative Analysis via a Machine Learning Approach.

This review comprehensively explores fluoride removal from phosphogypsum, focusing on its composition, fluorine-containing compounds, characterization methods, and defluorination techniques. It initially outlines the elemental composition of phosphogypsum prevalent in major production regions and infers the presence of fluorine compounds based on these constituents. The study highlights X-ray photoelectron spectroscopy (XPS) as a pivotal method for characterizing fluorine compounds, emphasizing its capability to determine precise binding energies essential for identifying various fluorine species. Additionally, the first-principle density functional theory (DFT) is employed to estimate binding energies of different fluorine-containing compounds. Significant correlations are observed between the total atomic energy of binary fluorides (e.g., of alkali metals, earth metals, and boron group metals) and XPS binding energies. However, for complex compounds like calcium fluorophosphate, correlations with the calculated average atomic total energy are less direct. The review categorizes defluorination methods applied to phosphogypsum as physical, chemical, thermal, and thermal-combined processes, respectively. It introduces neural network machine learning (ML) technology to quantitatively analyze and optimize reported defluorination strategies. Simulation results indicate potential optimizations based on quantitative analyses of process conditions reported in the literature. This review provides a systematic approach to understanding the phosphogypsum composition, fluorine speciation, analytical methodologies, and effective defluorination strategies. The attempts of adopting DFT simulation and quantitative analysis using ML in optimization underscore its potential and feasibility in advancing the industrial phosphogypsum defluorination process.

Anti-fungal effects of lactic acid bacteria from pickles on the growth and sterigmatocystin production of Aspergillus versicolor.

Sterigmatocystin (STC) is an emerging mycotoxin that poses a significant threat to the food security of cereal crops. To mitigate STC contamination in maize, this study employed selected lactic acid bacteria as biocontrol agents against Aspergillus versicolor, evaluating their biocontrol potential and analyzing the underlying mechanisms. Lactiplantibacillus plantarum HJ10, isolated from pickle, exhibited substantial in vitro antifungal activity and passed safety assessments, including antibiotic resistance and hemolysis tests. In vivo experiments demonstrated that L. plantarum HJ10 significantly reduced the contents of A. versicolor and STC in maize (both >84 %). The impact of heat, enzymes, alkali, and other treatments on the antifungal activity of cell-free supernatant (CFS) was investigated. Integrated ultra-high-performance liquid chromatography (UPLC) and gas chromatography-mass spectrometry (GC-MS) analysis revealed that lactic acid, acetic acid, and formic acid are the key substances responsible for the in vitro antifungal activity of L. plantarum HJ10. These metabolites induced mold apoptosis by disrupting cell wall structure, increasing cell membrane fluidity, reducing enzyme activities, and disrupting energy metabolism. However, in vivo antagonism by L. plantarum HJ10 primarily occurs through organic acid production and competition for growth space and nutrients. This study highlights the potential of L. plantarum HJ10 in reducing A. versicolor and STC contamination in maize.

Eco-friendly hydrogel based on locust bean gum for water retaining in sandy soil.

Sandy soils are suffering from water loss and desertification, which severely restrict the development of local agriculture. In this work, an eco-friendly hydrogel composed of borax and locust bean gum was synthesized to enhance the water retention capacity of sandy soil and support agricultural development in arid regions. Locust bean gum/borax hydrogel with a 3D network structure exhibited great water-absorbing capacity (130.29 g/g) within 30 min. After mixing 0.9 wt% hydrogel with sandy soil, the maximum soil water content, water retention time, soil porosity and soil organic matter were increased by 32.03 %, 14 days, 38.9 % and 8.64 g/kg respectively. Little effect on soil microorganisms revealed barely toxicity. Furthermore, the hydrogel was confirmed to be biodegradable at 43.47 % after 4 weeks. According to the study, locust bean gum/borax hydrogel possesses good water absorbing capacity, soil water retention ability, soil optimization ability and low adverse environmental impact. Together, it is inferred that the hydrogel can improve the water retention capacity of sandy soil in arid areas, promoting plant growth in arid areas.

Associations between the keratinized mucosa width and the underlying alveolar bone dimensions at partial edentulous molar sites: a retrospective cross-sectional study.

BACKGROUND: The assessment of hard and soft tissue at edentulous sites is important for subsequent implant treatment design. The aim of the present study was to explore the associations between the keratinized mucosa width (KMW) and the underlying alveolar bone dimensions at partial edentulous molar sites. METHODS: In this retrospective study, a total of 110 patients with at least one missing molar were selected. The buccal KMW of the edentulous molar sites was evaluated. Cone-beam computed tomography scans were collected, and the height discrepancy between the alveolar crest and the buccal bone plate (HC-B) as well as the alveolar bone height (ABH) were measured. The KMW was compared among the HC-B and ABH groups at both maxillary and mandibular sites. Linear regression and generalized estimation equations (GEEs) were used to explore the associations between the KMW and alveolar bone dimensions at α = 0.05. RESULTS: Among the 110 patients, 158 edentulous molar sites were analyzed. The average HC-B and ABH were significantly lower at the maxillary sites (1.26 ± 1.62 mm, 11.62 ± 3.94 mm) than at the mandibular sites (3.67 ± 2.85 mm, 14.91 ± 3.01 mm, p < 0.001). The KMW was significantly lower at sites with HC-B > 2 mm than at sites with HC-B ≤ 2 mm both in the maxilla and mandible (p < 0.001). No significant differences were found between the KMW at sites with ABH < 10 mm and sites with ABH ≥ 10 mm (p > 0.05). Linear regression and GEEs analyses revealed that the HC-B was significantly associated with the KMW (B = -0.339, p < 0.001), while the association between the KMW and the ABH was not statistically significant (B = -0.046, p = 0.352). CONCLUSIONS: The buccal KMW at edentulous molar sites was significantly associated with the HC-B. Alveolar ridges presenting with a sloped configuration were more prone to possess a narrower band of keratinized mucosa. Both hard and soft tissue augmentation should be considered for implant treatment at these sites. The correlations of dynamic changes between the KMW and alveolar bone dimensions after tooth extraction should be further investigated.

Methyl-Sensitive Amplification Polymorphism (MSAP) Analysis Provides Insights into the DNA Methylation Changes Underlying Adaptation to Low Temperature of Brassica rapa L.

BACKGROUND: DNA methylation can change rapidly to regulate the expression of stress-responsive genes. Previous studies have shown that there are significant differences in the cold resistance of winter rapeseed (Brassica rapa L.) after being domesticated in different selection environments; however, little is known about the epigenetic regulatory mechanisms of its cold resistance formation. METHODS: Four winter rapeseed materials ('CT-2360', 'MXW-1', '2018-FJT', and 'DT-7') domesticated in different environments were selected to analyze the DNA methylation level and pattern changes under low temperature using methylation-sensitive amplified polymorphism technology with 60 primer pairs. RESULTS: A total of 18 pairs of primers with good polymorphism were screened, and 1426 clear bands were amplified, with 594 methylation sites, accounting for 41.65% of the total amplified bands. The total methylation ratios of the four materials were reduced after low-temperature treatment, in which the DNA methylation level of 'CT-2360' was higher than that of the other three materials; the analysis of methylation patterns revealed that the degree of demethylation was higher than that of methylation in 'MXW-1', '2018-FJT', and 'DT-7', which were 22.99%, 19.77%, and 24.35%, respectively, and that the methylation events in 'CT-2360' were predominantly dominant at 22.95%. Fifty-three polymorphic methylated DNA fragments were randomly selected and further analyzed, and twenty-nine of the cloned fragments were homologous to genes with known functions. The candidate genes VQ22 and LOC103871127 verified the existence of different expressive patterns before and after low-temperature treatment. CONCLUSIONS: Our work implies the critical role of DNA methylation in the formation of cold resistance in winter rapeseed. These results provide a comprehensive insight into the adaptation epigenetic regulatory mechanism of Brassica rapa L. to low temperature, and the identified differentially methylated genes can also be used as important genetic resources for the multilateral breeding of winter-resistant varieties.

A Novel Adversarial Deep Learning Method for Substation Defect Image Generation.

The presence of defects in substation equipment is a major factor affecting the safety of power transmission. Therefore, timely and accurate detection of these defects is crucial. As intelligent inspection robots advance, using mainstream object detection models to diagnose surface defects in substation equipment has become a focal point of current research. However, the lack of defect image data is one of the main factors affecting the accuracy of supervised deep learning-based defect detection models. To address the issue of insufficient training data for defect images with complex backgrounds, such as rust and surface oil leakage in substation equipment, which leads to the poor performance of detection models, this paper proposes a novel adversarial deep learning model for substation defect image generation: the Abnormal Defect Detection Generative Adversarial Network (ADD-GAN). Unlike existing generative adversarial networks, this model generates defect images based on effectively segmented local areas of substation equipment images, avoiding image distortion caused by global style changes. Additionally, the model uses a joint discriminator for both overall images and defect images to address the issue of low attention to local defect areas, thereby reducing the loss of image features. This approach enhances the overall quality of generated images as well as locally generated defect images, ultimately improving image realism. Experimental results demonstrate that the YOLOV7 object detection model trained on the dataset generated using the ADD-GAN method achieves a mean average precision (mAP) of 81.5% on the test dataset, and outperforms other image data augmentation and generation methods. This confirms that the ADD-GAN method can generate a high-fidelity image dataset of substation equipment defects.

Is it high time to leave the chronic disease care of rural older people to village doctors in China: Insights from a population-based atrial fibrillation screening study.

OBJECTIVE: No study has systematically investigated the quality of long-term care delivered to the rural older people with chronic diseases, such as atrial fibrillation (AF) in China. This study aims to provide contemporary data on the prevalence and awareness of AF among the older population in rural China and to evaluate healthcare knowledge and delivery by village doctors. DESIGN: A cross-sectional study. SETTING: Rural villages in Daqiao and Xiaoji towns of Jiangsu Province, China. PARTICIPANTS: Rural population aged ≥65 years. OUTCOME MEASURES: AF was identified using 12-lead electrocardiography in the first-step (government-led health examination) and single-lead electrocardiography in the second-step (in-house AF screening). Questionnaire surveys were designed for the AF patients and their village doctors. RESULTS: Among 31,342 permanent residents, 12,630 (40.3 %) declined, 7,956 (25.3 %) participated in the first-step and 10,756 (34.3 %) in the second-step. The overall AF detection rate was 4.3 % (810/18,712). Of the 810 AF patients (mean age 76.1±5.9 years; 51.4 % female), 51.5 % were illiterate, only 2.6 % could use smartphone applications, and 8.1 % lived with their children. Common risk factors were older age, men, hypertension, diabetes, prior stroke, vascular disease, and congestive heart failure. Among the 402 patients with known AF, 367 were at high risk of stroke and 10.9 % (40/367) were anticoagulated. Only 17.6 % patients with known hypertension had blood pressure level <140/90 mmHg, and 6.0 % with known diabetes had a fasting blood glucose level ≤6.1 mmol/L. Only 7.3 % (9/122) village doctors reported having the knowledge of integrated care AF management. CONCLUSIONS: This study identified AF in 4.3 %, but AF management was suboptimal in rural China. The current village doctor-dominant rural healthcare system is far from delivering standardized AF management for older patients in rural China. There is an urgent need to empower the village doctors in optimising the care of AF patients.

Hydroxylamine-induced activation of permanganate for enhanced oxidation of sulfamethoxazole: Mechanism and products.

Recently, many reagents have been introduced to accelerate the formation of highly reactive intermediate Mn species from permanganate (KMnO4), thereby improving the oxidation activity of KMnO4 towards pollutants. However, most studies have mainly focused on sulfur-containing reducing agents (e.g., bisulfite and sodium sulfite), with little attention paid to nitrogen-containing reducing agents. This study found that hydroxylamine (HA) and hydroxylamine derivatives (HAs) can facilitate KMnO4 in pollutant removal. Taking sulfamethoxazole (SMX) as a target contaminant, the effect of pH, SMX concentration, KMnO4 and HA dosages, and the molar ratio of HA and KMnO4 on the degradation of SMX in the KMnO4/HA process was systematically investigated. Quenching experiments and probe analysis revealed MnO2-catalyzed KMnO4 oxidation, Mn(III) and reactive nitrogen species as the primary active species responsible for SMX oxidation in the KMnO4/HA system. Proposed transformation pathways of SMX in the KMnO4/HA system mainly involve hydroxylation and cleavage reactions. The KMnO4/HA system was more conducive to selective oxidation of SMX, 2,4-dichlorophenol, and several other pollutants, but reluctant to bisphenol S (BPS). Overall, this study proposed an effective system for eliminating pollutants, while providing mechanistic insight into HA-driven KMnO4 activation for environmental remediation.

Synergistically improve the strength and porosity of carbon paper by using a novel phenol formaldehyde resin modified with cellulose nanofiber for proton exchange membrane fuel cells.

To optimize the imbalance between the interfacial bonding and porosity properties of carbon paper (CP) caused by phenol formaldehyde resin (PF) impregnation, and therefore improve the performance of proton exchange membrane fuel cells (PEMFCs), a new approach through cellulose nanofibers grafted with methyl methacrylate (CNFM) as a modified reinforcement and pore-forming agent for PF is investigated. Through suppressing the methylene backbone fracture of CNFM-modified PF during its thermal depolymerization, the interfacial bonding between PF matrix carbon and carbon fibers is enhanced. Compared with unmodified CP, the in-plane resistivity of CNFM-modified CP is reduced by 35.78 %, while the connected porosity increases to 82.26 %, and more homogeneous pore size distribution (PSD) in the range of 20-40 µm is obtained for CNFM-modified CP. Besides, the tensile strength, flexural strength, and air permeability of CNFM-modified CP increase by 72.78 %, 298.4 %, and 103.97 %, respectively. In addition, CNFM-modified CP achieves the peak power density of PEMFCs to 701.81 mW·cm-2, exhibiting 10.98 % improvement compared with commercial CP (632.39 mW·cm-2), evidently achieving an integral promotion of CP and comprehensive performance.

Combined Periodontal-Orthodontic Treatment with Periodontal Corticotomy Regenerative Surgery in an Adult Patient Suffering from Periodontitis and Skeletal Class II Malocclusion: A Case Report with 5-Year Longitudinal Observation.

A thick periodontal phenotype with thick gingiva and alveolar bone volume is required for safe orthodontic tooth movement and long-term stability. A high incidence of dehiscence and fenestration in the labial aspect of mandibular anterior teeth may limit the correction of deformity and orthodontic treatment, especially when the lower anterior teeth are needed to have a large range of movement. This study reports a combination of periodontal therapy and orthodontic therapy with periodontal corticotomy regenerative surgery (PCRS) in a 25-year-old patient suffering from skeletal Class II malocclusion and periodontitis. The patient received periodontal therapy 5 years ago and commenced orthodontic treatment 4.5 years ago. During the 4 years of follow-up for PCRS, the clinical and radiographic evaluations revealed significant improvements in the periodontal phenotype of the mandibular anterior region. The periodontal phenotypes in the mandibular incisors region were all modified from thin to thick. Supplementing orthodontic treatment with labial PCRS could be a promising treatment strategy to maintain long-term periodontal health in adult patients with alveolar deficiency and thin gingiva tissue.

Carboxymethylated Lycium barbarum seed dreg dietary fiber alleviates high fat diet-induced hyperlipidemia in mice via intestinal regulation.

In this study, we investigated the ameliorative gut modulatory effect of carboxymethylated Lycium barbarum seed dreg insoluble dietary fiber (LBSDIDF) on hyperlipidemic mice. After seven weeks of insoluble dietary fiber (IDF) intervention, the results demonstrated that IDFs effectively inhibited body weight gain, with slimming and hypolipidemic effects, and improved liver histopathology by decreasing ALT, AST, TNF-α and IL-6, and increasing short-chain fatty acid (SCFA) levels in hyperlipidemic mice. With the increasing diversity and abundance of intestinal bacteria and decreasing ratio of Firmicutes to Bacteroidetes, intestinal flora facilitated cholesterol lowering effects in hyperlipidemic mice. Our research offers a novel concept for the use of LBSDIDF as a prebiotic to improve intestinal dysbiosis or as a preventive measure against obesity and dyslipidemia.

Asiaticoside Inhibits Growth and Metastasis in Non-Small Cell Lung Cancer by Disrupting EMT via Wnt/ß-Catenin Pathway.

Non-small cell lung cancer (NSCLC) is the primary inducer of cancer-related death worldwide. Asiaticoside (ATS) is a triterpenoid saponin that has been indicated to possess an antitumor activity in several malignancies. Nonetheless, its detailed functions in NSCLC remain unclarified. In this study, NSCLC cells were exposed to various doses of ATS. Functional experiments were employed to estimate the ATS effect on NSCLC cell behaviors. Western blotting was implemented for protein expression evaluation. A xenograft mouse model was established to assess the ATS effect on NSCLC in vivo. The results showed that ATS restrained NSCLC cell proliferation, cell cycle progression, migration, and invasiveness. ATS reversed TGF-ß-induced promotion in epithelial-mesenchymal transition (EMT). Mechanistically, ATS inhibited Wnt/ß-catenin signaling in NSCLC. Upregulating ß-catenin restored ATS-mediated suppression of NSCLC cell aggressiveness. Moreover, ATS administration repressed tumorigenesis in tumor-bearing mice. In conclusion, ATS represses growth and metastasis in NSCLC by blocking EMT via the inhibition of Wnt/ß-catenin signaling.

Automated detection and classification of coronary atherosclerotic plaques on coronary CT angiography using deep learning algorithm.

Background: Coronary artery disease (CAD) is the leading cause of mortality worldwide. Recent advances in deep learning technology promise better diagnosis of CAD and improve assessment of CAD plaque buildup. The purpose of this study is to assess the performance of a deep learning algorithm in detecting and classifying coronary atherosclerotic plaques in coronary computed tomographic angiography (CCTA) images. Methods: Between January 2019 and September 2020, CCTA images of 669 consecutive patients with suspected CAD from Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine were included in this study. There were 106 patients included in the retrospective plaque detection analysis, which was evaluated by a deep learning algorithm and four independent physicians with varying clinical experience. Additionally, 563 patients were included in the analysis for plaque classification using the deep learning algorithm, and their results were compared with those of expert radiologists. Plaques were categorized as absent, calcified, non-calcified, or mixed. Results: The deep learning algorithm exhibited higher sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy {92% [95% confidence interval (CI): 89.5-94.1%], 87% (95% CI: 84.2-88.5%), 79% (95% CI: 76.1-82.4%), 95% (95% CI: 93.4-96.3%), and 89% (95% CI: 86.9-90.0%)} compared to physicians with ≤5 years of clinical experience in CAD diagnosis for the detection of coronary plaques. The algorithm's overall sensitivity, specificity, PPV, NPV, accuracy, and Cohen's kappa for plaque classification were 94% (95% CI: 92.3-94.7%), 90% (95% CI: 88.8-90.3%), 70% (95% CI: 68.3-72.1%), 98% (95% CI: 97.8-98.5%), 90% (95% CI: 89.8-91.1%) and 0.74 (95% CI: 0.70-0.78), indicating strong performance. Conclusions: The deep learning algorithm has demonstrated reliable and accurate detection and classification of coronary atherosclerotic plaques in CCTA images. It holds the potential to enhance the diagnostic capabilities of junior radiologists and junior intervention cardiologists in the CAD diagnosis, as well as to streamline the triage of patients with acute coronary symptoms.

Sample compensation method for injection electroluminescent display panels.

Aiming at the problem of luminance uniformity for injection electroluminescent display panels, we present a new sample compensation method based on column-control according to successive scans theory. On the basis of our ideas, a small part of pixels of each column are selected as samples, and the column gating time calculated by sample average luminance value of corresponding column is written in hardware program. We adopt the 64 × 32 LEDs display panel as an example to expound the compensation method and obtain good result that the reduction in amplitude of luminance non-uniformity is 65.42% for the sample area, 58.67% for the non-sample area and 60.21% for the entire display panel.

Preparation of HMn2O4 lithium-ion sieves with low manganese dissolution loss for improved cycling stability.

Manganese-based lithium-ion sieves have become some of the promising adsorbents for extracting Li+ from brines. However, manganese dissolution loss (MDL) severely impairs the stability and cyclicity of ion sieves. A novel ozone eluent was first developed to extract Li+ from lithium manganese oxides, which decreased MDL decreased from 5.89% to 0.11%, and after ten regeneration cycles, the adsorption capacity retained 85.39% of the initial value, which was better than 55.15% when only hydrochloric acid (HCl) was used as the eluent. Based on these phenomena, the mechanism for the O3 lowering of MDL was investigated. First, the catalytic decomposition reaction of O3 competed with the disproportionation reaction, and the involvement of O3 inhibited the occurrence of the disproportionation reaction. Additionally, the presence of O3 and reactive oxygen species provided a preferential electron acceptor compared to Mn3+ during the migration of electrons from the bulk phase to the surface. In this study, MDL was greatly reduced with a very simple strategy, and the cycling stability of the adsorbent was improved.

Constructing Gradient Orbital Coupling to Induce Reactive Metal-Support Interaction in Pt-Carbide Electrocatalysts for Efficient Methanol Oxidation.

Reactive metal-support interaction (RMSI) is an emerging way to regulate the catalytic performance for supported metal catalysts. However, the induction of RMSI by the thermal reduction is often accompanied by the encapsulation effect on metals, which limits the mechanism research and applications of RMSI. In this work, a gradient orbital coupling construction strategy was successfully developed to induce RMSI in Pt-carbide system without a reductant, leading to the formation of L12-PtxM-MCy (M = Ti, Zr, Hf, V, Nb, Ta, Cr, Mo, and W) intermetallic electrocatalysts. Density functional theory (DFT) calculations suggest that the gradient coupling of the d(M)-2p(C)-5d(Pt) orbital would induce the electron transfer from M to C covalent bonds to Pt NPs, which facilitates the formation of C vacancy (Cv) and the subsequent M migration (occurrence of RMSI). Moreover, the good correlation between the formation energy of Cv and the onset temperature of RMSI in Pt-MCx systems proves the key role of nonmetallic atomic vacancy formation for inducing RMSI. The developed L12-Pt3Ti-TiC catalyst exhibits excellent acidic methanol oxidation reaction activity, with mass activity of 2.36 A mgPt-1 in half-cell and a peak power density of 187.9 mW mgPt-1 in a direct methanol fuel cell, which is one of the best catalysts ever reported. DFT calculations reveal that L12-Pt3Ti-TiC favorably weakens *CO absorption compared to Pt-TiC due to the change of the absorption site from Pt to Ti, which accounts for the enhanced MOR performance.