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Purpose: Studying perivascular spaces (PVSs) is important for understanding the pathogenesis and pathological changes of neurological disorders. Although some methods for automated segmentation of PVSs have been proposed, most of them were based on 7T MR images that were majorly acquired in healthy young people. Notably, 7T MR imaging is rarely used in clinical practice. Herein, we propose a deep-learning-based method that enables automatic segmentation of PVSs on T2-weighted 3T MR images. Method: Twenty patients with Parkinson's disease (age range, 42-79 years) participated in this study. Specifically, we introduced a multi-scale supervised dense nested attention network designed to segment the PVSs. This model fosters progressive interactions between high-level and low-level features. Simultaneously, it utilizes multi-scale foreground content for deep supervision, aiding in refining segmentation results at various levels. Result: Our method achieved the best segmentation results compared with the four other deep-learning-based methods, achieving a dice similarity coefficient (DSC) of 0.702. The results of the visual count of the PVSs in our model correlated extremely well with the expert scoring results on the T2-weighted images (basal ganglia: rs = 0.845, P < 0.001; rs = 0.868, P < 0.001; centrum semiovale: rs = 0.845, P < 0.001; rs = 0.823, P < 0.001 for raters 1 and 2, respectively). Experimental results show that the proposed method performs well in the segmentation of PVSs. Conclusion: The proposed method can accurately segment PVSs; it will facilitate practical clinical applications and is expected to replace the method of visual counting directly on T1-weighted images or T2-weighted images.

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Segmentation in medical images is inherently ambiguous. It is crucial to capture the uncertainty in lesion segmentations to assist cancer diagnosis and further interventions. Recent works have made great progress in generating multiple plausible segmentation results as diversified references to account for the uncertainty in lesion segmentations. However, the efficiency of existing models is limited, and the uncertainty information lying in multi-annotated datasets remains to be fully utilized. In this study, we propose a series of methods to corporately deal with the above limitation and leverage the abundant information in multi-annotated datasets: (1) Customized T-time Inner Sampling Network to promote the modeling flexibility and efficiently generate samples matching the ground-truth distribution of a number of annotators; (2) Uncertainty Degree defined for quantitatively measuring the uncertainty of each sample and the imbalance of the whole multi-annotated dataset from a brand new perspective; (3) Uncertainty-aware Data Augmentation Strategy to help probabilistic models adaptively fit samples with different ranges of uncertainty. We have evaluated each of them on both the publicly available lung nodule dataset and our in-house Liver Tumor dataset. Results show that our proposed methods achieves the overall best performance on both accuracy and efficiency, demonstrating its great potential in lesion segmentations and more downstream tasks in real clinical scenarios.

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Synergistic reduction of air pollutants and carbon dioxide (CO2) emissions is currently a key environmental policy in China, yet provincial-level studies remain scarce. To fill the gap, this study developed a coupled emission inventory from 2013 to 2020 in Shanxi, a coal-dependent province critical to China's energy security. This facilitated the investigation of emission trends, primary sources, synergistic effects, and spatial distribution. The results show that, while air pollutant emissions decreased significantly during the study period, CO2 emissions increased slightly. The main emitters of SO2, NOx, and CO2 were identified as power, heating, industrial boilers, and residential coal combustion. The iron and steel industry contributed significantly to PM2.5 emissions, coke production to VOCs, and vehicles to NOx and VOCs. NH3 emissions were mainly attributed to fertilizer use and livestock. Synergistic reductions were evident in coal-related sources, especially industrial boilers and residential coal combustion, underlining the importance of optimizing the energy structure. Anthropogenic emissions were concentrated in basins with poor dispersion conditions. Taiyuan, Yuncheng, and Linfen emerged as key areas for synergistic reduction efforts. This study provides important insights for environmental policy development in Shanxi and other coal-dependent regions.

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PURPOSE: This study aimed to automatically segment knee computed tomography (CT) images of tibial plateau fractures using a three-dimensional (3D) U-net-based method, accurately construct 3D maps of tibial plateau fractures, and examine their usefulness for Schatzker classification in clinical practice. METHODS: We retrospectively enrolled 234 cases with tibial plateau fractures from our hospital in this study. The four constituent bones of the knee were manually annotated using ITK-SNAP software. Finally, image features were extracted using deep learning. The usefulness of the results for Schatzker classification was examined by an orthopaedic and a radiology resident. RESULTS: On average, our model required < 40 s to process a 3D CT scan of the knee. The average Dice coefficient for all four knee bones was higher than 0.950, and highly accurate 3D maps of the tibia were produced. With the aid of the results of our model, the accuracy, sensitivity, and specificity of the Schatzker classification of both residents improved. CONCLUSIONS: The proposed method can rapidly and accurately segment knee CT images of tibial plateau fractures and assist residents with Schatzker classification, which can help improve diagnostic efficiency and reduce the workload of junior doctors in clinical practice.

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Glutathione S-transferases (GSTs) are multifunctional enzymes, and insect GSTs play a pivotal role in the metabolism of insecticides. Grapholita molesta is a worldwide pest that causes substantial economic losses to the fruit industry. However, it remains unclear how imidacloprid, a commonly used insecticide in orchards, is metabolized by G. molesta. In the present study, the synergist diethyl maleate (DEM), which inhibits the GST activity, exhibited a 22-fold synergistic ratio against imidacloprid. Two new GST genes, GmGSTD2 (OR096251) and GmGSTD3 (OR096252), were identified and successfully cloned, showing the highest expression in the Malpighian tubes. Knockdown of GmGSTD2 and GmGSTD3 by RNA interference, increased the mortality of G. molesta from 28% to 47% following imidacloprid treatment. Both recombinant GmGSTD2 and GmGSTD3 proteins exhibited 1-chloro-2,4-dinitrobenzene (CDNB) activity and could be inhibited by imidacloprid in vitro, with maximum inhibition was 60% for GmGSTD2 and 80% for GmGSTD3. These results suggested that GSTs participate in the metabolism of imidacloprid with GmGSTD2 and GmGSTD3 playing key roles in this process.

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Intensive agricultural activities could cause lead (Pb) bioaccumulation, threatening human health. Although the enzyme-induced carbonate precipitation (EICP) technology has been applied to tackle the aforesaid problem, the urease may denature or even lose its activity when subjected to a significant Pb2+ toxicity effect. To this end, the nano-hydroxyapatite (nHAP)-assisted EICP was proposed to reduce the mobility of Pb2+. Results indicated that a below 30% immobilization efficiency at 60 mM Pb2+ was attained under EICP. nHAP adsorbed the majority of Pb2+, preventing Pb2+ attachment to urease. Further, hydroxylphosphohedyphane or hydroxylpyromorphite was formed at 60 mM Pb2+, followed by the formation of cerussite, allowing hydroxylphosphohedyphane or hydroxylpyromorphite to be wrapped by cerussite. By contrast, carbonate-bearing hydroxylpyromorphite of higher stability (Pb10(PO4)6CO3) was developed at 20 mM Pb2+ as CO3 2- substituted the hydroxyl group in hydroxylpyromorphite. Moreover, nHAP helped EICP to form nucleated minerals. As a result, the EICP-nHAP technology raised the immobilization efficiency at 60 mM Pb2+ up to 70%. The findings highlight the potential of applying the EICP-nHAP technology to Pb-containing water bodies remediation.

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BACKGROUND: To investigate the association between white matter changes and ventricular expansion in idiopathic normal pressure hydrocephalus (iNPH) based on diffusion spectrum imaging (DSI). METHODS: We included 32 patients with iNPH who underwent DSI using a 3T MRI scanner. The lateral ventricles were manually segmented, and ventricular volumes were measured. Two methods were utilised in the study: manual region-of-interest (ROI) delineation and tract diffusion profile analysis. General fractional anisotropy (GFA) and fractional anisotropy (FA) were extracted in different white matter regions, including the bilateral internal capsule (anterior and posterior limbs) and corpus callosum (body, genu, and splenium) with manual ROI delineation. The 18 main tracts in the brain of each patient were extracted; the diffusion metrics of 100 equidistant nodes on each fibre were calculated, and Spearman's correlation coefficient was used to determine the correlation between diffusion measures and ventricular volume of iNPH patients. RESULTS: The GFA and FA of all ROI showed no significant correlation with lateral ventricular volume. However, in the tract diffusion profile analysis, lateral ventricular volume was positively correlated with part of the cingulum bundle, left corticospinal tract, and bilateral thalamic radiation posterior, whereas it was negatively correlated with the bilateral cingulum parahippocampal (all p < 0.05). CONCLUSIONS: The effect of ventricular enlargement in iNPH on some white matter fibre tracts around the ventricles was limited and polarizing, and most white matter fibre tract integrity changes were not associated with ventricular enlargement; this reflects that multiple pathological mechanisms may have been combined to cause white matter alterations in iNPH.

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Natural enemies of arthropods contribute considerably to agriculture by suppressing pests, particularly when combined with chemical control. Studies show that insect recovery after insecticide application is rare. Here, we discovered the recovery of the predatory bug Arma chinensis from knockdown following the application of ß-cypermethrin but not five other insecticides. A. chinensis individuals were more tolerant to ß-cypermethrin than lepidopteran and coleopteran larvae, which did not recover from knockdown. We assessed A. chinensis recovery by monitoring their respiration and tracking locomotion through the entire process. We identified and verified the trans-regulation of detoxifying genes, including those encoding cytochrome P450s and α/ß-hydrolase, which confer recovery from ß-cypermethrin exposure in A. chinensis, by mitogen-activated protein kinase (MAPK) and cAMP response element binding protein (CREB). Furthermore, we discovered a novel mechanism, the neurotransmitter clearance, in vivo during the recovery process, by which the insect initiated the removal of excessive dopamine with a degrading enzyme ebony. Overall, these results provide mechanistic insights into the detoxification and neurotransmitter clearance that jointly drive insect recovery from insecticide exposure.

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Heat-activated second harmonic generation (SHG) switching materials are gaining interest for their ability to switch between SHG on and off states, offering potential in optoelectronic applications. The novel nonlinear optical (NLO) switch, (C5H6NO)+(CH3SO3)- (4-hydroxypyridinium methylsulfonate, 4HPMS), is a near-room-temperature thermal driven material with a strong SHG response (3.3 × KDP), making it one of the most potent heat-stimulated NLO switches. It offers excellent contrast of 13 and a high laser-induced damage threshold (2.5 × KDP), with reversibility > 5 cycles. At 73 °C, 4HPMS transitions from the noncentrosymmetric Pna21 room temperature phase (RTP) to the centrosymmetric P21/c phase, caused by the rotation of the (C5H6NO)+ and (CH3SO3)- due to partially thermal breaking of intermolecular hydrogen bonds. The reverse phase change exhibits a large 50 °C thermal hysteresis. Density functional theory (DFT) calculations show that (C5H6NO)+ primarily dictates both the SHG coefficient (dij) and birefringence (▵n(Zeiss) = 0.216 vs ▵n(cal.) = 0.202 at 546 nm; Δn(Immersion) = 0.210 vs ▵n(cal.) = 0.198 at 589.3 nm), while the band gap (Eg) is influenced synergistically by (C5H6NO)+ and (CH3SO3)-. Additionally, 4HPMS-RTP also exhibits mechanochromism upon grinding as well as an aggregation-enhanced emission in a mixture of acetone and water.

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Chronic wounds, resulting from persistent inflammation, can trigger a cascade of detrimental effects including exacerbating inflammatory cytokines, compromised blood circulation at the wound site, elevation of white blood cell count, increased reactive oxygen species, and the potential risk of bacterial infection. The interleukin-17 (IL-17) signaling pathway, which plays a crucial role in regulating immune responses, has been identified as a promising target for treating inflammatory skin diseases. This review aims to delve deeper into the potential pathological role and molecular mechanisms of the IL-17 family and its pathways in wound repair. The intricate interactions between IL-17 and other cytokines will be discussed in detail, along with the activation of various signaling pathways, to provide a comprehensive understanding of IL-17's involvement in chronic wound inflammation and repair.

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BACKGROUND: PM2.5 is a harmful mixture of various chemical components that pose a challenge in determining their individual and combined health effects due to multicollinearity issues with traditional linear regression models. This study aimed to develop an analytical methodology combining traditional and novel machine learning models to evaluate PM2.5's combined effects on blood pressure (BP) and identify the most toxic components. METHODS: We measured late-pregnancy BP of 1138 women from the Heshan cohort while simultaneously analyzing 31 PM2.5 components. We utilized multiple linear regression modeling to establish the relationship between PM2.5 components and late-pregnancy BP and applied Random Forest (RF) and generalized Weighted Quantile Sum (gWQS) regression to identify the most toxic components contributing to elevated BP and to quantitatively evaluate the cumulative effect of the PM2.5 component mixtures. RESULTS: The results revealed that 16 PM2.5 components, such as EC, OC, Ti, Fe, Mn, Cu, Cd, Mg, K, Pb, Se, Na+, K+, Cl-, NO3-, and F-, contributed to elevated systolic blood pressure (SBP), while 26 components, including two carbon components (EC, OC), fourteen metallics (Ti, Fe, Mn, Cr, Mo, Co, Cu, Zn, Cd, Na, Mg, Al, K, Pb), one metalloid (Se), and nine water-soluble ions (Na+, K+, Mg2+, Ca2+, NH4+, Cl-, NO3-, SO42-, F-), contributed to elevated diastolic blood pressure (DBP). Mn and Cr were the most toxic components for elevated SBP and DBP, respectively, as analyzed by RF and gWQS models and verified against each other. Exposure to PM2.5 component mixtures increased SBP by 1.04 mmHg (95% CI: 0.33-1.76) and DBP by 1.13 mmHg (95% CI: 0.47-1.78). CONCLUSIONS: Our study highlights the effectiveness of combining traditional and novel models as an analytical strategy to quantify the health effects of PM2.5 constituent mixtures.

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BACKGROUND: Myoglobin (Mb) in duck meat is commonly over-oxidized when heated at high temperatures, which may worsen the color of the meat. Enhancing the oxidative stability of Mb is essential for improving the color of duck meat. Capsaicin and dihydrocapsaicin (CA-DI) in chili exhibit antioxidant properties. This study investigated the effects of CA-DI on the structure and oxidative damage of Mb by fluorescence spectroscopy, differential scanning calorimetry analysis and particle size in duck meat during heat treatment. RESULTS: When the ratio of CA-DI to Mb was 10:1 g kg-1 and heat-treated for 36 min, oxymyoglobin significantly increased, and metmyoglobin significantly decreased compared with the control group (P < 0.05). In parallel, the carbonyl content of Mb in the CA-DI group decreased by 43.40 ± 0.10%, the sulfhydryl content increased by 188 ± 0.21%, and the free radical scavenging activity of Mb was significantly enhanced (P < 0.05). Moreover, the addition of CA-DI resulted in a significant decrease in the particle size of the Mb surface (P < 0.05). When the ratio of CA-DI to Mb was 10:1 g kg-1, CA-DI enhanced the thermal stability and significantly increased the thermal denaturation temperature of Mb. The molecular docking results indicated that hydrophobic interactions and hydrogen bonds were involved in the binding of CA-DI to Mb. CONCLUSION: CA-DI could combine with Mb and improve the oxidation stability of Mb in duck meat. This suggested that CA-DI could be a potential natural antioxidant that improves the color of meat products. © 2024 Society of Chemical Industry.

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BACKGROUND: There is a dearth of feasibility assessments regarding using large language models (LLMs) for responding to inquiries from autistic patients within a Chinese-language context. Despite Chinese being one of the most widely spoken languages globally, the predominant research focus on applying these models in the medical field has been on English-speaking populations. OBJECTIVE: This study aims to assess the effectiveness of LLM chatbots, specifically ChatGPT-4 (OpenAI) and ERNIE Bot (version 2.2.3; Baidu, Inc), one of the most advanced LLMs in China, in addressing inquiries from autistic individuals in a Chinese setting. METHODS: For this study, we gathered data from DXY-a widely acknowledged, web-based, medical consultation platform in China with a user base of over 100 million individuals. A total of 100 patient consultation samples were rigorously selected from January 2018 to August 2023, amounting to 239 questions extracted from publicly available autism-related documents on the platform. To maintain objectivity, both the original questions and responses were anonymized and randomized. An evaluation team of 3 chief physicians assessed the responses across 4 dimensions: relevance, accuracy, usefulness, and empathy. The team completed 717 evaluations. The team initially identified the best response and then used a Likert scale with 5 response categories to gauge the responses, each representing a distinct level of quality. Finally, we compared the responses collected from different sources. RESULTS: Among the 717 evaluations conducted, 46.86% (95% CI 43.21%-50.51%) of assessors displayed varying preferences for responses from physicians, with 34.87% (95% CI 31.38%-38.36%) of assessors favoring ChatGPT and 18.27% (95% CI 15.44%-21.10%) of assessors favoring ERNIE Bot. The average relevance scores for physicians, ChatGPT, and ERNIE Bot were 3.75 (95% CI 3.69-3.82), 3.69 (95% CI 3.63-3.74), and 3.41 (95% CI 3.35-3.46), respectively. Physicians (3.66, 95% CI 3.60-3.73) and ChatGPT (3.73, 95% CI 3.69-3.77) demonstrated higher accuracy ratings compared to ERNIE Bot (3.52, 95% CI 3.47-3.57). In terms of usefulness scores, physicians (3.54, 95% CI 3.47-3.62) received higher ratings than ChatGPT (3.40, 95% CI 3.34-3.47) and ERNIE Bot (3.05, 95% CI 2.99-3.12). Finally, concerning the empathy dimension, ChatGPT (3.64, 95% CI 3.57-3.71) outperformed physicians (3.13, 95% CI 3.04-3.21) and ERNIE Bot (3.11, 95% CI 3.04-3.18). CONCLUSIONS: In this cross-sectional study, physicians' responses exhibited superiority in the present Chinese-language context. Nonetheless, LLMs can provide valuable medical guidance to autistic patients and may even surpass physicians in demonstrating empathy. However, it is crucial to acknowledge that further optimization and research are imperative prerequisites before the effective integration of LLMs in clinical settings across diverse linguistic environments can be realized. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2300074655; https://www.chictr.org.cn/bin/project/edit?pid=199432.

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As a typical form of optical fringes with a quadratic phase, Newton's ring patterns play an important role in spherical measurements and optical interferometry. A variety of methods have been used to analyze Newton's ring patterns. However, it is still rather challenging to fulfill the analysis. We present a deep-learning-based method to estimate the parameters of Newton's ring patterns and fulfill the analysis accordingly. The experimental results indicate the excellent accuracy, noise robustness, and demodulation efficiency of our method. It provides another applicable approach to analyzing Newton's ring patterns and brings insights into fringe analysis and interferometry-based measurements.

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The low ionic conductivity of LiCoO2 limits the rate performance of the overall electrode. Here, a polymeric composite binder composed of poly(vinylidene fluoride) (PVDF) and poly(ethylene oxide) (PEO) is reported to efficiently improve the ion transport in the LiCoO2 electrode. This is where the lithium-ion transport channel constructed by oxygen atoms of PEO can afford the electrode a lithium-ion transport number (tLi+) as high as 0.70 with the optimized composite binder in a mass ratio of 1:1 (O5F5), significantly higher than that of traditional PVDF (0.44). As a result, the O5F5 binder endows the LiCoO2 electrode with an impressive capacity of 90 mAh g-1 even at 15 C, which is twice as high as the PVDF electrode. In addition, the initial Coulombic efficiency of the LiCoO2 electrode with the O5F5 binder is close to 100% and the capacity retention is 91% after 100 cycles at 1 C. This study overcomes the problem of slow ion conductivity of the LiCoO2 electrode, providing an easy method for developing high-rate cathode binders.

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Diabetic wound healing (DWH) represents a major complication of diabetes where inflammation is a key impediment to proper healing. The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway has emerged as a central mediator of inflammatory responses to cell stress and damage. However, the contribution of cGAS-STING activation to impaired healing in DWH remains understudied. In this review, we examine the evidence that cGAS-STING-driven inflammation is a critical factor underlying defective DWH. We summarize studies revealing upregulation of the cGAS-STING pathway in diabetic wounds and discuss how this exacerbates inflammation and senescence and disrupts cellular metabolism to block healing. Partial pharmaceutical inhibition of cGAS-STING has shown promise in damping inflammation and improving DWH in preclinical models. We highlight key knowledge gaps regarding cGAS-STING in DWH, including its relationships with endoplasmic reticulum stress and metal-ion signaling. Elucidating these mechanisms may unveil new therapeutic targets within the cGAS-STING pathway to improve healing outcomes in DWH. This review synthesizes current understanding of how cGAS-STING activation contributes to DWH pathology and proposes future research directions to exploit modulation of this pathway for therapeutic benefit.

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Diabetic wounds represent a formidable challenge in the clinical management of diabetes mellitus, markedly diminishing the patient's quality of life. These wounds arise from a multifaceted etiology, with the pathophysiological underpinnings remaining elusive and complex. Diabetes precipitates neuropathies and vasculopathies in the lower extremities, culminating in infections, ulcerations, and extensive tissue damage. The hallmarks of non-healing diabetic wounds include senescence, persistent inflammation, heightened apoptosis, and attenuated cellular proliferation. The TP53 gene, a pivotal tumor suppressor frequently silenced in human malignancies, orchestrates cellular proliferation, senescence, DNA repair, and apoptosis. While p53 is integral in cell cycle regulation, its role in initial tissue repair appears to be deleterious. In typical cutaneous wounds, p53 levels transiently dip, swiftly reverting to baseline. Yet in diabetic wounds, protracted p53 activation impedes healing via two distinct pathways: i) activating the p53-p21-Retinoblastoma (RB) axis, which halts the cell cycle, and ii) upregulating the cGAS-STING and nuclear factor-kappaB (NF-κB) cascades, instigating ferroptosis and pyroptosis. Furthermore, p53 intersects with various metabolic pathways, including glycolysis, gluconeogenesis, oxidative phosphorylation, and autophagy. In diabetic wounds, p53 may drive metabolic reprogramming, thus potentially derailing macrophage polarization. This review synthesizes case studies investigating the therapeutic modulation of p53 in diabetic wounds care. In summation, p53 modulates chronic inflammation and cellular aging within diabetic cutaneous wounds and is implicated in a novel cell death modality, encompassing ferroptosis and pyroptosis, which hinders the reparative process.

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Tobacco mosaic virus (TMV) is the most widely spread and harmful virus in the world, causing serious economic losses annually. However, the low anti-erosion ability of the pesticides for TMV management make it easy to be washed by the rain, which makes the effective duration of the pesticides shorter. In this paper, a new bio-based nanogel with superior antiviral activity was reported, and its slow-release behavior, rain erosion resistance and the antiviral mechanism was systematically studied. The results determined that the nanogels (Zn2+@ALGNP and Zn2+@ALGNP@PL) exhibited sustained releasing of Zn2+ with a 7 days duration, and the ε-PL coating could enhance the releasing rate of Zn2+. Moreover, Zn2+@ALGNP@PL displayed a lower contact angle, indicating greater adhesion to the leaf surface, and in consequence imposed better resistance to simulate rain erosion than pure Zn2+. Strikingly, Zn2+@ALGNP@PL could inhibit plant virus infection by aggregating the virions and reducing its coat protein stability, as well as inducing the efficient expression of reactive oxygen species, antioxidant enzymes and resistance genes to enhance plant resistance and promote plant growth. Overall, this study had successfully developed a high rain-erosion resistant bio-based nanogel capable of continue to induce resistant plants and promote plant growth.

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Dalbergia odorifera T. Chen is traditionally referred to as "Dalbergiae Odoriferae Lignum" in traditional Chinese medicine. Its quality is typically assessed subjectively based on colour and texture observations and lacks a universal grading system. Our objective was to establish a relationship between heartwood colour and the content of key constituents, including total flavonoids, six specific flavonoids, alcohol-soluble extracts, and volatile oils, to assess their impact on heartwood quality. Substantial correlations were observed between the colour depth (L*), red-green direction (a*), and yellow-blue direction (b*), as well as the content of the extract, volatile oil, total flavonoids, naringenin, formononetin, pinocembrin, and isoliquiritigenin. Specifically, a* was correlated with the extract, total flavonoids, and isoliquiritigenin, whereas b* was correlated with the extract, volatile oil, total flavonoids, naringenin, formononetin, pinocembrin, and isoliquiritigenin. The results suggested that L*, b*, and chemical composition indices, such as extract, volatile oil, total flavonoids, and naringenin, could serve as primary criteria for classifying the quality of medicinal materials. This is consistent with market classification based on colour and texture, which facilitates material identification and guides the cultivation, harvesting, and processing of D. odorifera. This study provides a scientific foundation for its future development and use.

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Spice and its extracts have gained widespread utilization as natural and eco-friendly additives, imparting enhancements in flavor, color, and antioxidative attributes to meat-based products. This work aims to study the effect mechanism of capsaicin (CA) and dihydrocapsaicin (DI) in capsicum (chili pepper) on the structure and function of myofibrillar proteins (MPs) in duck meat during thermal treatment. The results showed that at a CA-DI to MP ratio of 1:500 (g/g) following a 12 min heat treatment, the carbonyl content of MPs in duck meat decreased by 48.30%, and the sulfhydryl content increased by 53.42%. When the concentration was 1:500 (CA-DI, g/g) after 24 min of heat treatment, the •OH and DPPH radical scavenging rates were highest at 59.5% and 94.0%, respectively. And the initial denaturation temperature of MPs was the highest at 96.62 °C, and the thermal absorption was lowest at 200.24 J g-1. At the parameter, the smallest particle size and size distribution range of MP were 190 nm (9.51%). Furthermore, the interplay between CA-DI and MPs contributed to a reduction in the protein particle size and intrinsic fluorescence. In summary, the combination of CA-DI and MPs played a crucial role in inducing protein unfolding and disintegration.