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In China, population growth and aging have partially negated the public health benefits of air pollution control measures, underscoring the ongoing need for precise PM2.5 monitoring and mapping. Despite its prevalence, the satellite-derived Aerosol Optical Depth (AOD) method for estimating PM2.5 concentrations often encounters significant spatial data gaps. Additionally, current research still needs better representation of PM2.5 spatiotemporal heterogeneity. Addressing these challenges, we developed a two-stage model employing the Extreme Gradient Boosting (XGBoost) algorithm. By incorporating improved spatiotemporal factors, we achieved high-precision and full-coverage daily 1-km PM2.5 mappings across China for the year 2020 without utilizing AOD products. Specifically, Model 1 develops improved temporal encodings and a terrain classification factor (DC), while Model 2 constructs an enhanced spatial autocorrelation term (Ps) by integrating observed and estimated values. Notably, Model 2 excelled in 10-fold sample-based cross-validation, achieving a coefficient of determination of 0.948, a mean absolute error of 3.792 µg/m³, a root mean square error of 7.144 µg/m³, and a mean relative error of 14.171%. Feature importance and Shapley Additive exPlanations (SHAP) analyses determined the relative importance of predictors in model training and outcome prediction, while correlation analysis identified strong links between improved temporal encodings, PM2.5 concentrations, and significant meteorological factors. Two-way Partial Dependence Plots (PDPs) further explored the interactions among these factors and their impact on PM2.5 levels. Compared to traditional methods, improved temporal encodings align more closely with seasonal variations and synergize more effectively with meteorological factors. Besides, the structured nature of DC aids in model training, while the improved Ps more effectively captures PM2.5's spatial autocorrelation, outperforming traditional Ps. Overall, this study effectively represents spatiotemporal information, thereby boosting model accuracy and enabling seamless large-scale PM2.5 estimations. It provides deep insights into variables and models, providing significant implications for future air pollution research.
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In recent years, the interaction of intracellular organelles such as mitochondria and lysosomal functions has attracted increasing attention. Recent evidence suggests that mitochondrion-lysosomal contact plays a key role in regulating lysosomal biogenesis and maintaining cellular homeostasis. Myocardial ischemia and reperfusion will lead to corresponding changes in the autophagy flux in cardiomyocytes, and lysosomes are a key link in the process of autophagy, and the fusion of lysosomes and autophagosomes is an essential link in the occurrence of autophagy. Therefore, the function and homeostasis of lysosomes also undergo different changes during myocardial ischemia and reperfusion. Lysosomal-related biological factors and membrane proteins also play different roles. This article will review the mechanism of lysosomes in myocardial ischemia-reperfusion injury and the research progress of lysosomal-related proteins.
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In this study, a difluorocarbene-promoted O-O bond activation of peroxy acids is developed through the insertion of difluorocarbene into O-H bond. This activation strategy in synergy with O-B coordination with boronic acids/ester greatly polarizes the O-O bond for in-situ generation of carboxylium species that reacts with the nucleophilic part of boronic acids in a concerted way to produce esters. Good efficiency and functional group tolerance are demonstrated. Application of this method to the functionalization of a boronic acid drug used as HSL enzyme inhibitor produces smoothly the ester derivative. This difluorocarbene-mediated O-O bond activation strategy is conceptually different from traditional radical type methods, and is also complementary to conventional esterification methods with a distinct retro-synthetic disconnection.
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Implantable sensors, especially ion sensors, facilitate the progress of scientific research and personalized healthcare. However, the permanent retention of implants induces health risks after sensors fulfill their mission of chronic sensing. Biodegradation is highly anticipated; while; biodegradable chemical sensors are rare due to concerns about the leakage of harmful active molecules after degradation, such as ionophores. Here, a novel biodegradable fiber calcium ion sensor is introduced, wherein ionophores are covalently bonded with bioinert nanoparticles to replace the classical ion-selective membrane. The fiber sensor demonstrates comparable sensing performance to classical ion sensors and good flexibility. It can monitor the fluctuations of Ca2+ in a 4-day lifespan in vivo and biodegrade in 4 weeks. Benefiting from the stable bonding between ionophores and nanoparticles, the biodegradable sensor exhibits a good biocompatibility after degradation. Moreover, this approach of bonding active molecules on bioinert nanoparticles can serve as an effective methodology for minimizing health concerns about biodegradable chemical sensors.
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A protocol has been developed for the synthesis of α-aryl-oxindoles from isatin and Grignard reagents in the presence of diphenyl phosphite for the first time. This reaction was conveniently carried out under mild conditions in a one-pot fashion with moderate to excellent yields.
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Megalencephaly-polymicrogyria-polydactyly-hydrocephalus syndrome (MPPH), a type of overgrowth syndrome, is characterized by progressive megalencephaly, cortical brain malformations, and distal limb anomalies. Previous studies have revealed that the overactivity of the phosphatidylinositol 3-kinase-Protein kinase B pathway and the increased cyclin D2 (CCND2) expression were the main factors contributing to this disease. Here, we present the case of a patient who exhibited megalencephaly, polymicrogyria, abnormal neuronal migration, and developmental delay. Serum tandem mass spectrometry and chromosome examination did not detect any metabolic abnormalities or copy number variants. However, whole-exome sequencing and Sanger sequencing revealed a de novo nonsense mutation (NM_001759.3: c.829C>T; p.Gln277X) in the CCND2 gene of the patient. Bioinformatics analysis predicted that this mutation may disrupt the structure and surface charge of the CCND2 protein. This disruption could potentially prevent polyubiquitination of CCND2, leading to its resistance against degradation. Consequently, this could drive cell division and growth by altering the activity of key cell cycle regulatory nodes, ultimately contributing to the development of MPPH. This study not only presents a new case of MPPH and expands the mutation spectrum of CCND2 but also enhances our understanding of the mechanisms connecting CCND2 with overgrowth syndromes.
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Ciclina D2 , Megalencefalia , Polidactilia , Polimicrogiria , Feminino , Humanos , Masculino , Códon sem Sentido/genética , Ciclina D2/genética , Sequenciamento do Exoma , Hidrocefalia , Malformações do Desenvolvimento Cortical , Megalencefalia/genética , Megalencefalia/diagnóstico , Polidactilia/genética , Polidactilia/diagnóstico , Polimicrogiria/genética , Polimicrogiria/diagnóstico , Pré-EscolarRESUMO
Flexible fiber electrodes offer new opportunities for bioelectronics and are reliable in vivo applications, high flexibility, high electrical conductivity, and satisfactory biocompatibility are typically required. Herein, we present an all-metal flexible and biocompatible fiber electrode based on a metal nanowire hybrid strategy, i.e., silver nanowires were assembled on a freestanding framework, and further to render them inert, they were plated with a gold nanoshell. Our fiber electrodes exhibited a low modulus of â¼75 MPa and electrical conductivity up to â¼4.8 × 106 S m-1. They can resist chemical erosion with negligible leakage of biotoxic silver ions in the physiological environment, thus ensuring satisfactory biocompatibility. Finally, we demonstrated the hybrid fiber as a neural electrode that stimulated the sciatic nerve of a mouse, proving its potential for applications in bioelectronics.
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Eletrodos , Ouro , Nanofios , Prata , Prata/química , Nanofios/química , Ouro/química , Animais , Camundongos , Condutividade Elétrica , Materiais Biocompatíveis/química , Nervo Isquiático , Tamanho da PartículaRESUMO
This study reports selective dual amino acylation and C-H bromination of aniline compounds enabled by Cu/O2 catalyst systems. This method involves crucial oxidation-induced C-CN bond cleavage of α-methylene nitriles to generate an acylcyanide intermediate that is facilely intercepted by anilines. After amino acylation, the Cu(II) precatalyst in combination with NBS generates Cu(III)-Br in situ that engages in selective electrophilic para- or ortho-C-H bromination. The substrate scope, mechanistic aspects, and late-stage functionalization of biologically active anilines are studied. This study shows the synthetic potential of oxidative C-CN bond activation of nitriles for the development of valuable reactions.
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Alpine grassland is the main vegetation on the Qinghai-Tibetan Plateau (QTP) and exhibits high sensitivity to extreme weather events. With global warming, extreme weather events are projected to become more frequent on the QTP. However, the impact of these extreme weather events on the carbon cycle of alpine grassland remains unclear. The long-term in-situ carbon fluxes data was collected from 2013 to 2022 at an alpine grassland site to examine the impact of extreme low air temperature (ELT) and reduced moisture (including air and soil) on carbon fluxes during the growing season. Our findings indicated that a significant increase in net ecosystem production (NEP) after 2019, with the average NEP increasing from 278.91 ± 43.27 g C m-2 year-1 during 2013-2018 to 415.45 ± 45.29 g C m-2 year-1 during 2019-2022. The ecosystem carbon use efficiency (CUE) increased from 0.38 ± 0.06 during 2013-2018 to 0.62 ± 0.11 during 2019-2022. By combining concurrently measured environmental factors and remote sensing data, we identified the factors responsible for the abrupt change in the NEP after 2019. This phenomenon was caused by an abrupt decrease in ecosystem respiration (Reco) after 2019, which resulted from the inhibition imposed by ELT and reduced moisture. In contrast, gross primary production (GPP) remained stable from 2013 to 2022, which was confirmed by the remotely sensed vegetation index. This study highlights that combined extreme weather events associated with climate change can significantly impact the NEP of alpine grassland, potentially affecting different carbon fluxes at different rates. These findings provide new insights into the mechanisms governing the carbon cycle of alpine grassland.
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Ciclo do Carbono , Monitoramento Ambiental , Pradaria , Tibet , Mudança Climática , Temperatura Baixa , EcossistemaRESUMO
Metal-organic frameworks (MOFs) have been regarded as a potential candidate with great application prospects in the field of gas sensing. Although plenty of previous efforts have been made to improve the sensitivity of MOF-based nanocomposites, it is still a great challenge to realize ultrafast and high selectivity to typical flammable gases in a wide range. Herein, porous xPd-NPs@ZnO were prepared by optimized heat treatment, which maintained the controllable morphology and high specific surface area of 471.08 m2g-1. The coupling effects of photoexcitation and thermal excitation on the gas-sensing properties of nanocomposites were systematically studied. An ultrafast high response of 88.37 % towards 200 ppm H2 was realized within 1.2 s by 5.0Pd-NPs@ZnO under UV photoexcitation. All xPd-NPs@ZnO exhibited favorable linearity over an extremely wide range (0.2-4000 ppm H2) of experimental tests, indicating the great potential in quantitative detection. The photoexcited carriers enabled the nanocomposites a considerable response at lower operating temperatures, which made diverse applications of the sensors. The mechanisms of high sensing performances and the photoexcitation enhancement were systematically explained by DFT calculations. This work provides a solid experimental foundation and theoretical basis for the design of controllable porous materials and novel photoexcited gas detection.
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OBJECTIVE: Deep learning has been shown to be useful in detecting breast cancer metastases by analyzing whole slide images (WSI) of sentinel lymph nodes; however, it requires extensive analysis of all the lymph node slides. Our deep learning study attempts to provide a rapid screen for metastasis by analyzing only a small set of image patches to detect changes in tumor environment. METHODS: We designed a convolutional neural network to build a diagnostic model for metastasis detection. We obtained WSIs of Hematoxylin and Eosin-stained slides from 34 cases with equal distribution in positive/negative categories. Two WSIs were selected from each case for a total of 69 WSIs. From each WSI, 40 image patches (100x100 pixels) were obtained to yield 2720 image patches, from which 2160 (79%) were used for training, 240 (9%) for validation, and 320 (12%) for testing. Interobserver variation was also examined among 3 users. RESULTS: The test results showed excellent diagnostic results: accuracy (91.15%), sensitivity (77.92%), and specificity (92.09%). No significant variation in results was observed among the 3 observers. CONCLUSION: This preliminary study provided a proof of concept for conducting a rapid screen for metastasis rather than an exhaustive search for tumors in all fields of all sentinel lymph nodes.
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Neoplasias da Mama , Aprendizado Profundo , Melanoma , Linfonodo Sentinela , Neoplasias Cutâneas , Humanos , Feminino , Neoplasias da Mama/diagnósticoRESUMO
A NO2 sensor with a detection limit down to the ppb level based on pristine SnO2 has been developed through a facile poly(acrylic acid)-mediated hydrothermal method. SnO2 particles of solid microsphere, hollow microsphere, and nanosphere morphologies were synthesized, with respective constitutional crystallite of size â¼2 µm in length and 10-20 nm and â¼7 nm in diameter. All sensors show great selectivity to NO2. The hollow microsphere sensor exhibits the best performance, with medium specific surface area (SSA), followed by the nanosphere sensor with the largest SSA. This is attributed to the superposition of two opposite effects on sensor response with increased SSA: more adsorption sites and fewer electrons to be taken out with overly small crystallite that may reach complete depletion. O2 is found to speed up the response and recovery times but reduce the response because O adsorbates facilitate the adsorption/desorption of NO2 thermodynamically, and the two oxidizing gases compete in harvesting electrons from SnO2. The adverse effect of humidity can be minimized by operating the sensor at 110 °C. The response of the hollow microsphere sensor to 50 ppb of NO2 is 8.8 (Rg/Ra) at room temperature, and it increases to 15.1 at 110 °C. These findings are useful for developing other oxidizing gas semiconductor sensors.
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Nanosferas , Oxigênio , Dióxido de Nitrogênio , Microesferas , GasesRESUMO
Rosmarinic acid (RA) and salvianolic acid B (SAB) are main phenolic acids in Salvia miltiorrhiza Bunge have been widely used in the treatment of cardiovascular and cerebrovascular diseases due to their excellent pharmacological activity. RA is a precursor of SAB, and tyrosine transaminase (TAT, EC 2.6.1.5) is a crucial rate-limiting enzyme in their metabolism pathway. This study identified a novel TAT gene, SmTAT3-2, and found that it is a new transcript derived from unconventional splicing of SmTAT3. We used different substrates for enzymatic reaction with SmTAT1, SmTAT3 and SmTAT3-2. Subcellular localization of SmTAT1 and SmTAT3-2 was completed based on submicroscopic techniques. In addition, they were overexpressed and CRISPR/Cas9 gene edited in hairy roots of S. miltiorrhiza. Revealed SmTAT3-2 and SmTAT1 showed a stronger affinity for L-tyrosine than SmTAT3, localized in the cytoplasm, and promoted the synthesis of phenolic acid. In overexpressed SmTAT3-2 hairy roots, the content of RA and SAB was significantly increased by 2.53 and 3.38 fold, respectively, which was significantly higher than that of overexpressed SmTAT1 strain compared with EV strain. These findings provide a valuable key enzyme gene for the phenolic acids metabolism pathway and offer a theoretical basis for the clinical application.
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Salvia miltiorrhiza , Tirosina Transaminase , Tirosina Transaminase/genética , Salvia miltiorrhiza/genética , Salvia miltiorrhiza/química , Genes tat , Hidroxibenzoatos/metabolismo , Ácido Rosmarínico , Raízes de Plantas/química , Regulação da Expressão Gênica de PlantasRESUMO
OBJECTIVES: To investigate if delta-radiomics features have the potential to predict the major pathological response (MPR) to neoadjuvant chemoimmunotherapy in non-small cell lung cancer (NSCLC) patients. METHODS: Two hundred six stage IIA-IIIB NSCLC patients from three institutions (Database1 = 164; Database2 = 21; Database3 = 21) who received neoadjuvant chemoimmunotherapy and surgery were included. Patients in Database1 were randomly assigned to the training dataset and test dataset, with a ratio of 0.7:0.3. Patients in Database2 and Database3 were used as two independent external validation datasets. Contrast-enhanced CT scans were obtained at baseline and before surgery. The delta-radiomics features were defined as the relative net change of radiomics features between baseline and preoperative. The delta-radiomics model and pre-treatment radiomics model were established. The performance of Immune-Related Response Evaluation Criteria in Solid Tumors (iRECIST) for predicting MPR was also evaluated. RESULTS: Half of the patients (106/206, 51.5%) showed MPR after neoadjuvant chemoimmunotherapy. For predicting MPR, the delta-radiomics model achieved a satisfying area under the curves (AUCs) values of 0.768, 0.732, 0.833, and 0.716 in the training, test, and two external validation databases, respectively, which showed a superior predictive performance than the pre-treatment radiomics model (0.644, 0.616, 0.475, and 0.608). Compared with iRECIST criteria (0.624, 0.572, 0.650, and 0.466), a mixed model that combines delta-radiomics features and iRECIST had higher AUC values for MPR prediction of 0.777, 0.761, 0.850, and 0.670 in four sets. CONCLUSION: The delta-radiomics model demonstrated superior diagnostic performance compared to pre-treatment radiomics model and iRECIST criteria in predicting MPR preoperatively in neoadjuvant chemoimmunotherapy for stage II-III NSCLC. CLINICAL RELEVANCE STATEMENT: Delta-radiomics features based on the relative net change of radiomics features between baseline and preoperative CT scans serve a vital support tool in accurately identifying responses to neoadjuvant chemoimmunotherapy, which can help physicians make more appropriate treatment decisions. KEY POINTS: ⢠The performances of pre-treatment radiomics model and iRECIST model in predicting major pathological response of neoadjuvant chemoimmunotherapy were unsatisfactory. ⢠The delta-radiomics features based on relative net change of radiomics features between baseline and preoperative CT scans may be used as a noninvasive biomarker for predicting major pathological response of neoadjuvant chemoimmunotherapy. ⢠Combining delta-radiomics features and iRECIST can further improve the predictive performance of responses to neoadjuvant chemoimmunotherapy.
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Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Humanos , Área Sob a Curva , Carcinoma Pulmonar de Células não Pequenas/diagnóstico por imagem , Carcinoma Pulmonar de Células não Pequenas/terapia , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/terapia , Terapia Neoadjuvante , Radiômica , Estudos RetrospectivosRESUMO
This study reports sequential dehydrogenation and transfer oxygenation of 1,2-diarylepoxides by high-valent phenCu(III)(CF3)3 and DMSO to produce 1,2-diketones. The Cu(III)-CF3 compound serves as a CF3 radical source to abstract the hydrogen atom of the epoxide ring. The resulting ether α-carbon radical undergoes ring-opening rearrangement to give a ketone α-carbon radical intermediate, which is oxygenated by DMSO with the release of Me2S. The combination of a Cu(III)-CF3 compound and DMSO may be exploited to develop other novel oxidation reactions.
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Cr(III) is a common oxidation state of chromium, and its presence in the environment can occur naturally or as a result of human activities, such as industrial processes, mining, and waste disposal. This article explores the application of machine learning algorithms for the intelligent decision recognition and quantification of Cr(III) in chromium speciation. Three different machine learning models, namely, the Decision Tree (DT) model, the PCA-SVM (Principal Component Analysis-Support Vector Machine) model, and the LDA (Linear Discriminant Analysis) model, were employed and evaluated for accurate and efficient classification of chromium concentrations based on their fluorescence responses. Furthermore, stepwise multiple linear regression analysis was utilized to achieve a more precise quantification of trivalent chromium concentrations through fluorescence visualization. The results demonstrate the potential of machine learning algorithms in accurately detecting and quantifying Cr(III) in chromium speciation with implications for environmental and industrial applications in chromium detection and quantification. The findings from this research pave the way for further exploration and implementation of these models in real-world scenarios, offering valuable insights into various environmental and industrial contexts.
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The spatial unit of urban agglomerations is extremely important for reducing negative externalities in large cities. Although there is a large body of literature on reducing negative externalities within a single city, few studies have focused on the important role of urban agglomerations. To offer a new method for reducing negative externalities in large cities and fill in this gap in the literature, our paper examines the effect of spatial functional division in urban agglomerations on negative externalities in large cities by applying the concept of spatial functional division to data on 19 urban agglomerations and data on negative externalities from 35 large cities in China. We first show that spatial functional division in urban agglomerations can significantly reduce negative externalities. The robustness of the results was confirmed using the instrumental variable approach, alternative indicators, and other robustness checks. Furthermore, we identified the productivity improvement mechanisms in large cities that generate the observed mitigatory effects of spatial functional division in urban agglomerations on negative externalities in large cities. The heterogeneous analyzes indicate that spatial functional division in urban agglomerations has a stronger mitigatory effect on negative externalities in large cities in the context of higher inter-city connectivity, greater polycentricity, and official approval regarding urban agglomerations' regional planning. Our findings emphasize the importance of urban agglomerations for reducing negative externalities in large cities, particularly in China, where urban agglomerations have been rapidly developing and spatial functional division in urban agglomerations has been continuously improving.
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Myocardial fibrosis is an underlying cause of many cardiovascular diseases. Novel insights into the epigenetic control of myocardial fibrosis are now emerging. The current work is focused on investigating the biological role of DNA methyltransferase 1 (DNMT1) in myocardial fibrosis as well as the underlying mechanism. Our findings revealed that DNMT1 expression levels were upregulated, whereas miR-133b expression levels were decreased in a rat model of myocardial fibrosis following myocardial infarction. In vitro, the expression levels of DNMT1 increased and those of miR-133b decreased after Ang-II treatment in cardiac fibroblasts. DNMT1 knockdown inhibited Ang-II-induced cardiac myofibroblast activation, and DNMT1 overexpression increased the proliferation and collagen generation of cardiac myofibroblasts. Furthermore, DNMT1 expression levels decreased, while miR-133b expression levels increased after treatment with 5-Aza (5-Azacytidine, a known inhibitor of DNA methylation) in Ang-II-induced cardiac fibroblasts. BSP (Bisulfite sequencing PCR) results showed a marked decrease in methylation levels in the miR-133b promoter region upon overexpression of DNMT1, whereas knockdown of DNMT1 blocked increased methylation levels in the miR-133b promoter region in Ang-II-induced cardiac fibroblasts. Finally, 5-Aza treatment reduced the progression of myocardial fibrosis after myocardial infarction in rats in vivo. Collectively, our results suggest that DNMT1 mediates CTGF expression in cardiac fibroblast activation by regulating the methylation of miR-133b. The present work reveals the unique role of the DNMT1/miR-133b/CTGF axis in myocardial fibrosis, thus suggesting its great therapeutic potential in the treatment of cardiac diseases.
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MicroRNAs , Infarto do Miocárdio , Animais , Ratos , Azacitidina/farmacologia , Metilação de DNA , Fibrose , Coração , MicroRNAs/genética , Infarto do Miocárdio/genéticaRESUMO
Seedless grapes are increasingly popular throughout the world, and the development of seedless varieties is a major breeding goal. In this study, we demonstrate an essential role for the grapevine MADS-box gene VvMADS28 in morphogenesis of the ovule. We found that VvMADS28 mRNA accumulated in the ovules of a seeded cultivar, 'Red Globe', throughout the course of ovule and seed development, especially within the integument/seed coat. In contrast, in the seedless cultivar 'Thompson Seedless', VvMADS28 was expressed only weakly in ovules, and this was associated with increased levels of histone H3 lysine 27 trimethylation (H3K27me3) within the VvMADS28 promoter region. RNAi-mediated transient suppression of VvMADS28 expression in 'Red Globe' led to reduced seed size associated with inhibition of episperm and endosperm cell development. Heterologous overexpression of VvMADS28 in transgenic tomatoes interfered with sepal development and resulted in smaller fruit but did not obviously affect seed size. Assays in yeast cells showed that VvMADS28 is subject to regulation by the transcription factor VvERF98, and that VvMADS28 could interact with the Type I/ Mß MADS-domain protein VvMADS5. Moreover, through DNA-affinity purification-sequencing (DAP-seq), we found that VvMADS28 protein specifically binds to the promoter of the grapevine WUSCHEL (VvWUS) gene, suggesting that maintenance of the VvMADS28-VvMADS5 dimer and VvWUS expression homeostasis influences seed development. Taken together, our results provide insight into regulatory mechanisms of ovule and seed development associated with VvMADS28.
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Tetracycline pollution in soil irreversibly damages the biosafety of plants by inhibiting the mitochondrial function. Some traditional Chinese medicine (TCM) plants, such as Salvia miltiorrhiza Bunge, have a strong tolerance to mitochondrial damage. We comprehensively compared the doxycycline (DOX) tolerances of two ecotypes of S. miltiorrhiza in the Sichuan and Shandong provinces and found that the Sichuan ecotype had a lower yield reduction, more stable accumulation of medicinal ingredients, higher mitochondrial integrity, and a more robust antioxidant system. The synergetic response networks under DOX pollution of both ecotypes were constructed using RNA sequencing and ultrahigh-performance liquid chromatography-tandem mass spectrometry. The differentiation of the downstream pathways of aromatic amino acids (AAAs) produced variations in the DOX tolerance of S. miltiorrhiza in different regions. The Sichuan ecotype maintained redox homeostasis and xylem development by activating salvianolic acid and indole biosynthesis, while the Shandong ecotype balanced chemical and mechanical defenses by regulating the flavonoid biosynthesis. Rosmarinic acid, a downstream AAA molecule, maintains the mitochondrial homeostasis of plant seedlings under DOX pollution by targeting the ABCG28 transporter. We also highlight the significance of downstream AAA small molecules in guiding the development of bio-based environmental pollution remediation agents.