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It is imperative to unravel the dynamic variation of volatile components of vine tea during processing to provide guidance for tea quality evaluation. In this study, the dynamic changes of volatile compounds of vine tea during processing were characterized by GC-IMS and HS-SPME/GC-MS. As a result, 103 volatile compounds were characterized by the two technologies with three overlapped ones. The random forest approach was employed to develop the models and explore key volatile compounds. 23 key compounds were explored, among which 13 were derived from GC-IMS and ten were from HS-SPME/GC-MS. Moreover, the area under the receiver operating characteristics curve with 100 cross validations by the pair-wised models were all 1 for the established models. Furthermore, the primary aroma formation mechanism for the key volatile compounds were mainly involved in fatty acid and amino acid metabolism. Besides, this study provides a theoretical support for directed processing and quality control of vine tea.
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Background: To assess the bioequivalence between Gan & Lee (GL) glargine U300 and Toujeo® regarding pharmacokinetics (PK), pharmacodynamics (PD), and safety in Chinese healthy male participants. Methods: A single-center, randomized, double-blind, single-dose, two-preparation, two-sequence, four-cycle repeated crossover design study was performed to compare GL glargine U300 and Toujeo® in 40 healthy participants. The primary PK endpoints were the area under the curve of glargine metabolites, M1 concentration from 0 to 24 hours (AUC0-24h), and the maximum glargine concentration within 24 hours post-dose (Cmax). The primary PD endpoints were the area under the glucose infusion rate (GIR) curve from 0 to 24 hours (AUCGIR.0-24h) and the maximum GIR within 24 hours post-dose (GIRmax). Results: GL Glargine U300 demonstrated comparable PK parameters (AUC0-24h, Cmax, AUC0-12h, and AUC12-24h of M1) and PD responses [AUCGIR.0-24h, GIRmax, AUCGIR.0-12h, and AUCGIR.12-24h] to those of Toujeo®, as indicated by 90% confidence intervals ranging from 80% to 125%. No significant disparities in safety profiles were observed between the two treatment groups, and there were no reported instances of serious adverse events. Conclusion: The PK, PD, and safety of GL glargine U300 were bioequivalent to that of Toujeo®. Clinical trial registration: https://www.chinadrugtrials.org.cn/, identifier CTR20212419.
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Estudos Cross-Over , Voluntários Saudáveis , Hipoglicemiantes , Insulina Glargina , Equivalência Terapêutica , Humanos , Masculino , Insulina Glargina/farmacocinética , Insulina Glargina/administração & dosagem , Adulto , Adulto Jovem , Hipoglicemiantes/farmacocinética , Hipoglicemiantes/administração & dosagem , Método Duplo-Cego , Glicemia/efeitos dos fármacos , Glicemia/análise , China , Área Sob a CurvaRESUMO
The epitranscriptomic mark N 6-methyladenosine (m6A) is the most common type of messenger RNA (mRNA) post-transcriptional modification in eukaryotes. With the discovery of the demethylase FTO (FAT MASS AND OBESITY-ASSOCIATED PROTEIN) in Homo Sapiens, this modification has been proven to be dynamically reversible. With technological advances, research on m6A modification in plants also rapidly developed. m6A modification is widely distributed in plants, which is usually enriched near the stop codons and 3'-UTRs, and has conserved modification sequences. The related proteins of m6A modification mainly consist of three components: methyltransferases (writers), demethylases (erasers), and reading proteins (readers). m6A modification mainly regulates the growth and development of plants by modulating the RNA metabolic processes and playing an important role in their responses to environmental signals. In this review, we briefly outline the development of m6A modification detection techniques; comparatively analyze the distribution characteristics of m6A in plants; summarize the methyltransferases, demethylases, and binding proteins related to m6A; elaborate on how m6A modification functions in plant growth, development, and response to environmental signals; and provide a summary and outlook on the research of m6A in plants.
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Potassium-ion batteries (PIBs) have been widely studied owing to the abundant reserves, widespread distribution, and easy extraction of potassium (K) resources. Molybdenum disulfide (MoS2) has received a great deal of attention as a key anode material for PIBs owing to its two-dimensional diffusion channels for K+ ions. However, due to its poor electronic conductivity and the huge influence of embedded K+ ions (with a large ionic radius of 3.6 Å) on MoS2 layer, MoS2 anodes exhibit a poor rate performance and easily collapsed structure. To address these issues, the common strategies are enlarging the interlayer spacing to reduce the mechanical strain and increasing the electronic conductivity by adding conductive agents. However, simultaneous implementation of the above strategies by simple methods is currently still a challenge. Herein, MoS2 anodes on reduced graphene oxide (MoS2/rGO) composite were prepared using one-step hydrothermal methods. Owing to the presence of rGO in the synthesis process, MoS2 possesses a unique scaled structure with large layer spacing, and the intrinsic conductivity of MoS2 is proved. As a result, MoS2/rGO composite anodes exhibit a larger rate performance and better cycle stability than that of anodes based on pure MoS2, and the direct mixtures of MoS2 and graphene oxide (MoS2-GO). This work suggests that the composite material of MoS2/rGO has infinite possibilities as a high-quality anode material for PIBs.
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BACKGROUND: Sepsis-induced coagulopathy (SIC) is a common cause of poor prognosis in critically ill patients in the intensive care unit (ICU). However, currently there are no tools specifically designed for predicting the occurrence of SIC in septic patients earlier. This study aimed to develop a predictive nomogram incorporating clinical markers and scoring systems to individually predict the probability of SIC in septic patients. METHODS: Patients consecutively recruited in the stage between January 2022 and April 2023 constituted the development cohort for retrospective analysis to internally test the nomogram, and patients in the stage between May 2023 to November 2023 constituted the validation cohort for prospective analysis to externally validate the nomogram. Univariate logistic regression analysis of the development cohort was performed firstly, and then multivariate logistic regression analysis was performed using backward stepwise method to determine the best-fitting model and obtain the nomogram from it. The nomogram was validated in an independent external validation cohort, involving discrimination and calibration. A decision curve analysis was also performed to evaluate the net benefit of the insertion decision with this nomogram. RESULTS: A total of 548 and 245 patients, 55.1 and 49.4% with SIC occurrence, were included in the development and validation cohorts, respectively. Predictors contained in the prediction nomogram included shock, platelets, and international normalized ratio (INR). Patients with shock (odds ratio [OR]: 4.499; 95% confidence interval [CI]: 2.730-7.414; p < 0.001), higher INR (OR: 349.384; 95% CI: 62.337-1958.221; p < 0.001), and lower platelet (OR: 0.985; 95% CI: 0.982-0.988; p < 0.001) had higher probabilities of SIC. The development model showed good discrimination, with an area under the receiver operating characteristic curve (AUROC) of 0.879 (95% CI: 0.850-0.908) and good calibration. Application of the nomogram in the validation cohort also gave good discrimination with an AUROC of 0.872 (95% CI: 0.826-0.917) and good calibration. The decision curve analysis of the nomogram provided better net benefit than the alternate options (intervention or no intervention). CONCLUSION: By incorporating shock, platelets, and INR in the model, this useful nomogram could be accessibly utilized to predict SIC occurrence in septic patients. However, external validation is still required for further generalizability improvement of this nomogram.
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BACKGROUND: Cardiotoxicity is a major cause of drug withdrawal. The hERG channel, regulating ion flow, is pivotal for heart and nervous system function. Its blockade is a concern in drug development. Predicting hERG blockade is essential for identifying cardiac safety issues. Various QSAR models exist, but their performance varies. Ongoing improvements show promise, necessitating continued efforts to enhance accuracy using emerging deep learning algorithms in predicting potential hERG blockade. STUDY DESIGN AND METHOD: Using a large training dataset, six individual QSAR models were developed. Additionally, three ensemble models were constructed. All models were evaluated using 10-fold cross-validations and two external datasets. RESULTS: The 10-fold cross-validations resulted in Mathews correlation coefficient (MCC) values from 0.682 to 0.730, surpassing the best-reported model on the same dataset (0.689). External validations yielded MCC values from 0.520 to 0.715 for the first dataset, exceeding those of previously reported models (0-0.599). For the second dataset, MCC values fell between 0.025 and 0.215, aligning with those of reported models (0.112-0.220). CONCLUSIONS: The developed models can assist the pharmaceutical industry and regulatory agencies in predicting hERG blockage activity, thereby enhancing safety assessments and reducing the risk of adverse cardiac events associated with new drug candidates.
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Aprendizado Profundo , Aprendizado de Máquina , Relação Quantitativa Estrutura-Atividade , Humanos , Desenvolvimento de Medicamentos/métodos , Cardiotoxicidade/etiologia , Canais de Potássio Éter-A-Go-Go/antagonistas & inibidores , Bloqueadores dos Canais de Potássio/farmacologia , Bloqueadores dos Canais de Potássio/química , Bloqueadores dos Canais de Potássio/efeitos adversos , AlgoritmosRESUMO
Three long alkyl chain-bearing dibenzotriazole ionic liquids (BTA-R-BTA, R = 8, 12, and 16) were synthesized with high yield (>98%) through a simple and eco-friendly process. Their anticorrosion performance for Q235 carbon steel in 6 M hydrochloride acid was comprehensively evaluated by weight loss tests, electrochemical methods (potentiodynamic polarization and electrochemical impedance spectroscopy), and surface analysis techniques. As the length of the alkyl chain increased, the maximum corrosion inhibition efficiency enhanced from 55.02% (for BTA-8-BTA at 1.2 mM) to 97.10% (for BTA-12-BTA at 0.3 mM) and 98.84% (for BTA-16-BTA at 0.3 mM). Density functional theory calculation indicated that the alkyl chain length had little influence on the inhibitors' electronic structures, while molecular dynamics simulations revealed that the thickness, surface coverage, and compactness of adsorption films formed at the metal-electrolyte interface increased with the elongated alkyl chain. Corrosion inhibition efficiency is strongly correlated with the structures of the adsorption film.
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Aqueous aluminum-ion batteries have many advantages such as their safety, environmental friendliness, low cost, high reserves and the high theoretical specific capacity of aluminum. So aqueous aluminum-ion batteries are potential substitute for lithium-ion batteries. In this paper, the current research status and development trends of cathode and anode materials and electrolytes for aqueous aluminum-ion batteries are described. Aiming at the problem of passivation, corrosion and hydrogen evolution reaction of aluminum anode and dissolution and irreversible change of cathode after cycling in aqueous aluminum-ion batteries. Solutions of different research routes such as ASEI (artificial solid electrolyte interphase), alloying, amorphization, elemental doping, electrolyte regulation, etc and different transformation mechanisms of anode and cathode materials during cycling have been summarized. Moreover, it looks forward to the possible research directions of aqueous aluminum-ion batteries in the future. We hope that this review can provide some insights and support for the design of more suitable electrode materials and electrolytes for aqueous aluminum-ion batteries.
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Aluminum (Al) possesses high combustion enthalpy and is thus extensively used as the fuel additive in explosives to form aluminized explosives with excellent energy performance. In the energy release process of aluminized explosives, the adsorption of Al surfaces plays an important role in catalyzing the explosive decomposition and triggering the oxidation of themselves. However, it still remains elusive owing to the multiplicity of adsorbed substances. Herein, the adsorption mechanism of decomposition species of CHON-containing explosives on Al surfaces is studied synoptically by combining reactive molecular dynamics simulations with density functional theory calculations. The results indicate that the Al surface structure and the activity of adsorbed molecules both have an impact on adsorption. The cluster surface generally outperforms the slab one in adsorptivity due to the lower coordination number of Al atoms. Meanwhile, the more active adsorbed molecules lead to chemisorption or even dissociative adsorption, beneficial to the subsequent Al oxidation. Besides, electrons will transfer from the Al surface to the adsorbed molecules as chemisorption occurs; while the density of states of the Al surface and molecules are altered, especially for carbon oxides with significant electronic delocalization. This work is expected to deepen insights into the energy release of aluminized explosives and help provide a proposal for enhancing energy release efficiency.
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BACKGROUND: Many guidelines have recommended renin-angiotensin system inhibitors (RASI) as the first-line treatment for patients with chronic kidney disease (CKD). We studied RASI prescription trends from 2010 to 2019, and analyzed the characteristics associated with RASI prescription in Chinese hospitalized CKD patients. AIM: To study the prescription of renin angiotensin system inhibitors in hospitalized patients with CKD in China. METHODS: It was retrospectively, cross-sectional reviewed RASI prescriptions in hospitalized CKD patients in China from 2010 to 2019. RASI prescribing trends were analyzed from 2010 to 2019, and bivariate and multivariate logistic regression analyses were conducted to identify characteristics associated with RASI prescription. RESULTS: A total of 35090 CKD patients were included, with 10043 (28.6%) RASI prescriptions. Among these patients, 18919 (53.9%) met the criteria for RASI treatments based on the 2012 kidney disease: Improving global outcomes guidelines. Of these, 7246 (38.3%) patients received RASI prescriptions. RASI prescriptions showed an initial rapid increase from 2011 to 2012, reached its peak around 2015 and 2016, and then exhibited a subsequent slight decreasing trend. Both bivariate and multivariate analyses showed that several characteristics, including the male gender, age less than 60-year-old, nephrology department admission, lower CKD stage, history of hypertension or diabetes, proteinuria, glomerulonephritis as the CKD etiology, and non-acute kidney injury were associated with RASI prescriptions. CONCLUSION: The frequency of RASI prescriptions showed an initial increase but a slight decreasing trend in more recent years. CKD patients with certain characteristics such as elderly age, advanced disease stage, surgery department admission, or acute kidney injury were less likely to receive RASI prescriptions. In the application of RASI in hospitalized CKD patients is insufficient. The actual clinical practice needs to be improved. The development of related research is helpful to guide the correct choice of clinical treatment strategy.
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Photon-counting computed tomography (PCCT) reconstructs multiple energy-channel images to describe the same object, where there exists a strong correlation among different channel images. In addition, reconstruction of each channel image suffers photon count starving problem. To make full use of the correlation among different channel images to suppress the data noise and enhance the texture details in reconstructing each channel image, this paper proposes a tensor neural network (TNN) architecture to learn a multi-channel texture prior for PCCT reconstruction. Specifically, we first learn a spatial texture prior in each individual channel image by modeling the relationship between the center pixels and its corresponding neighbor pixels using a neural network. Then, we merge the single channel spatial texture prior into multi-channel neural network to learn the spectral local correlation information among different channel images. Since our proposed TNN is trained on a series of unpaired small spatial-spectral cubes which are extracted from one single reference multi-channel image, the local correlation in the spatial-spectral cubes is considered by TNN. To boost the TNN performance, a low-rank representation is also employed to consider the global correlation among different channel images. Finally, we integrate the learned TNN and the low-rank representation as priors into Bayesian reconstruction framework. To evaluate the performance of the proposed method, four references are considered. One is simulated images from ultra-high-resolution CT. One is spectral images from dual-energy CT. The other two are animal tissue and preclinical mouse images from a custom-made PCCT systems. Our TNN prior Bayesian reconstruction demonstrated better performance than other state-of-the-art competing algorithms, in terms of not only preserving texture feature but also suppressing image noise in each channel image.
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The incidence of metabolic diseases has progressively increased, which has a negative impact on human health and life safety globally. Due to the good efficacy and limited side effects, there is growing interest in developing effective drugs to treat metabolic diseases from natural compounds. Kaempferol (KMP), an important flavonoid, exists in many vegetables, fruits, and traditional medicinal plants. Recently, KMP has received widespread attention worldwide due to its good potential in the treatment of metabolic diseases. To promote the basic research and clinical application of KMP, this review provides a timely and comprehensive summary of the pharmacological advances of KMP in the treatment of four metabolic diseases and its potential molecular mechanisms of action, including diabetes mellitus, obesity, non-alcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH), and atherosclerosis. According to the research, KMP shows remarkable therapeutic effects on metabolic diseases by regulating multiple signaling transduction pathways such as NF-κB, Nrf2, AMPK, PI3K/AKT, TLR4, and ER stress. In addition, the most recent literature on KMP's natural source, pharmacokinetics studies, as well as toxicity and safety are also discussed in this review, thus providing a foundation and evidence for further studies to develop novel and effective drugs from natural compounds. Collectively, our manuscript strongly suggested that KMP could be a promising candidate for the treatment of metabolic diseases.
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Aterosclerose , Diabetes Mellitus , Quempferóis , Hepatopatia Gordurosa não Alcoólica , Obesidade , Humanos , Quempferóis/farmacologia , Quempferóis/uso terapêutico , Hepatopatia Gordurosa não Alcoólica/tratamento farmacológico , Hepatopatia Gordurosa não Alcoólica/metabolismo , Animais , Obesidade/tratamento farmacológico , Obesidade/metabolismo , Aterosclerose/tratamento farmacológico , Aterosclerose/metabolismo , Diabetes Mellitus/tratamento farmacológico , Diabetes Mellitus/metabolismo , Doenças Metabólicas/tratamento farmacológico , Doenças Metabólicas/metabolismo , Transdução de Sinais/efeitos dos fármacosRESUMO
Bubble dynamics significantly impact mass transfer and energy conversion in electrochemical gas evolution reactions. Micro-/nanostructured surfaces with extreme wettability have been employed as gas-evolving electrodes to promote bubble departure and decrease the bubble-induced overpotential. However, effects of the electrodes' wickability on the electrochemical reaction performances remain elusive. In this work, hydrogen evolution reaction (HER) performances are experimentally investigated using micropillar array electrodes with varying interpillar spacings, and effects of the electrodes' wettability, wickability as well as bubble adhesion are discussed. A deep learning-based object detection model was used to obtain bubble counts and bubble departure size distributions. We show that microstructures on the electrode have little effect on the total bubble counts and bubble size distribution characteristics at low current densities. At high current densities, however, micropillar array electrodes have much higher total bubble counts and smaller bubble departure sizes compared with the flat electrode. We also demonstrate that surface wettability is a critical factor influencing HER performances under low current densities, where bubbles exist in an isolated regime. Under high current densities, where bubbles are in an interacting regime, the wickability of the micropillar array electrodes emerges as a determining factor. This work elucidates the roles of surface wettability and wickability on enhancing electrochemical performances, providing guidelines for the optimal design of micro-/nanostructured electrodes in various gas evolution reactions.
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Objective: To develop an algorithm using deep learning methods to calculate the volume of intraretinal and subretinal fluid in optical coherence tomography (OCT) images for assessing diabetic macular edema (DME) patients' condition changes. Design: Cross-sectional study. Participants: Treatment-naive patients diagnosed with DME recruited from April 2020 to November 2021. Methods: The deep learning network, which was built for autonomous segmentation utilizing an encoder-decoder network based on the U-Net architecture, was used to calculate the volume of intraretinal fluid (IRF) and subretinal fluid (SRF). The alterations of retinal vessel density and thickness, and the correlation between best-corrected visual acuity (BCVA) and OCT parameters were analyzed. Results: 2,955 OCT images of fourteen eyes from DME patients with IRF and SRF who received anti-vascular endothelial growth factor (VEGF) agents were obtained. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the algorithm was 0.993 for IRF and 0.998 for SRF. The volumes of IRF and SRF were significantly decreased from 1.93 ± 0.58 /1.14 ± 0.25 mm3 (baseline) to 0.26 ± 0.13 /0.26 ± 0.18 mm3 (post-injection), respectively (p = 0.0170 for IRF, and p = 0.0004 for SRF). The Spearman correlation demonstrated that the reduction of IRF volume was negatively correlated with age (coefficient = -0.698, p = 0.006). Conclusion: We developed a deep learning assisted fluid volume calculation algorithm with high sensitivity and specificity for assessing the volume of IRF and SRF in DME patients. Key words: deep learning; diabetic macular edema; optical coherence tomography.
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Objective: This study aims to compare gray matter volume changes in patients with chronic kidney disease (CKD) undergoing peritoneal dialysis (PD) and hemodialysis (HD) using voxel-based morphometry (VBM). Methods: A total of 27 PD patients, 25 HD patients, and 42 healthy controls were included. VBM analysis was performed, and cognitive function was assessed using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment Scale (MoCA). The correlation between cognitive function and changes in brain gray matter volume was analyzed. Results: Both peritoneal dialysis and hemodialysis patients had partial gray matter volume reduction compared to the controls, but the affected brain regions were not uniform. The hemodialysis patients had greater volume reduction in certain brain regions than the PD patients. The MMSE and MoCA scores were positively correlated with gray matter volume changes. Conclusion: Different dialysis modalities cause damage to specific areas of the brain, which can be detected using VBM. VBM, combined with cognitive function assessment, can help detect structural brain changes and cognitive impairment in patients with different dialysis modalities. The comprehensive application of VBM in the field of neurological function deserves further exploration.
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Background: Osteoarthritis (OA) is a chronic and degenerative condition that persists and progresses over time. Sipeimine (Sip), a steroidal alkaloid derived from Fritillariae Cirrhosae Bulbus, has attracted considerable attention due to its exceptional anti-inflammatory, analgesic, antioxidant, and anti-cancer characteristics. However, Sip's effects on OA and its mechanism still need further research. Methods: This study utilized network pharmacology to identify initial targets for Sip. Functional associations of Sip in OA were clarified through Gene Ontology (GO) enrichment analysis, bioinformatically analyzing a list of targets. Subsequently, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis assessed pathways linked to Sip's therapeutic efficacy in OA. Molecular docking techniques explored Sip's binding affinity with key targets. In vitro experiments assessed Sip's impact on lipopolysaccharide (LPS)-induced pro-inflammatory factors and its protective effects on collagen-II and aggrecan degradation within the extracellular matrix (ECM). Western blotting and fluorescence analyses were conducted to determine Sip-mediated signaling pathways. Moreover, in vivo experiments using a mouse OA model validated Sip's therapeutic efficacy. Results: The results from network pharmacology revealed a total of 57 candidate targets for Sip in OA treatment. GO enrichment analysis demonstrated a robust correlation between Sip and inflammatory response, response to LPS and NF-κB-inducing kinase activity in OA. KEGG enrichment analysis highlighted the significance of NF-κB and PI3K-AKT pathways in Sip's therapeutic potential for OA. Furthermore, molecular docking results demonstrated Sip's robust binding affinity with p65 and PI3K. In vitro experiments demonstrated Sip's effectively suppressed the expression of pro-inflammatory factors induced by LPS, such as COX-2, iNOS, IL-1ß, and IL-18. Besides, Sip counteracted the degradation of collagen-II and aggrecan within the ECM and the expression of MMP-13 and ADAMTS-5 mediated by LPS. The safeguarding effects of Sip were ascribed to its inhibition of PI3K/AKT/NF-κB pathway and NLRP3 inflammasome mediated pyroptosis. Additionally, in vivo experiments revealed that Sip could alleviate the subchondral remodeling, cartilage degeneration, synovitis as well as ECM degradation a mouse model of OA. Conclusion: Sip exhibited potential in attenuating OA progression by suppressing the PI3K/AKT/NF-κB pathway, consequently inhibiting the activation of NLRP3 inflammasome and pyroptosis. The translational potential statement: The translational potential of this articleThis study provides a biological rationale for the use of Sip as a potential candidate for OA treatment, provide a new concept for the cartilage targeted application of natural compounds.
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Extracellular vesicles (EVs) derived from Mesenchymal Stromal Cells (MSCs) have shown promising therapeutic potential for multiple diseases, including intervertebral disc degeneration (IDD). Nevertheless, the limited production and unstable quality of EVs hindered the clinical application of EVs in IDD. Selenomethionine (Se-Met), the major form of organic selenium present in the cereal diet, showed various beneficial effects, including antioxidant, immunomodulatory and anti-apoptotic effects. In the current study, Se-Met was employed to treat MSCs to investigate whether Se-Met can facilitate the secretion of EVs by MSCs and optimize their therapeutic effects on IDD. On the one hand, Se-Met promoted the production of EVs by enhancing the autophagy activity of MSCs. On the other hand, Se-Met pretreated MSC-derived EVs (Se-EVs) exhibited an enhanced protective effects on alleviating nucleus pulposus cells (NPCs) senescence and attenuating IDD compared with EVs isolated from control MSCs (C-EVs) in vitro and in vivo. Moreover, we performed a miRNA microarray sequencing analysis on EVs to explore the potential mechanism of the protective effects of EVs. The result indicated that miR-125a-5p is markedly enriched in Se-EVs compared to C-EVs. Further in vitro and in vivo experiments revealed that knockdown of miR-125a-5p in Se-EVs (miRKD-Se-EVs) impeded the protective effects of Se-EVs, while overexpression of miR-125a-5p (miROE-Se-EVs) boosted the protective effects. In conclusion, Se-Met facilitated the MSC-derived EVs production and increased miR-125a-5p delivery in Se-EVs, thereby improving the protective effects of MSC-derived EVs on alleviating NPCs senescence and attenuating IDD.
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Vesículas Extracelulares , Degeneração do Disco Intervertebral , Células-Tronco Mesenquimais , MicroRNAs , Selenometionina , Degeneração do Disco Intervertebral/terapia , Degeneração do Disco Intervertebral/metabolismo , Células-Tronco Mesenquimais/metabolismo , Vesículas Extracelulares/metabolismo , MicroRNAs/genética , MicroRNAs/metabolismo , Animais , Selenometionina/farmacologia , Humanos , Núcleo Pulposo/metabolismo , Células Cultivadas , Masculino , Senescência Celular , Transplante de Células-Tronco Mesenquimais , Autofagia , Ratos Sprague-Dawley , RatosRESUMO
BACKGROUND: Neovascular age-related macular degeneration (nAMD), accounts for up to 90% of AMD-associated vision loss, ultimately resulting in the formation of fibrotic scar in the macular region. The pathogenesis of subretinal fibrosis in nAMD involves the process of epithelial-mesenchymal transition (EMT) occurring in retinal pigment epithelium (RPE). Here, we aim to investigate the underlying mechanisms involved in the Wnt signaling during the EMT of RPE cells and in the pathological process of subretinal fibrosis secondary to nAMD. METHODS: In vivo, the induction of subretinal fibrosis was performed in male C57BL/6J mice through laser photocoagulation. Either FH535 (a ß-catenin inhibitor) or Box5 (a Wnt5a inhibitor) was intravitreally administered on the same day or 14 days following laser induction. The RPE-Bruch's membrane-choriocapillaris complex (RBCC) tissues were collected and subjected to Western blot analysis and immunofluorescence to examine fibrovascular and Wnt-related markers. In vitro, transforming growth factor beta 1 (TGFß1)-treated ARPE-19 cells were co-incubated with or without FH535, Foxy-5 (a Wnt5a-mimicking peptide), Box5, or Wnt5a shRNA, respectively. The changes in EMT- and Wnt-related signaling molecules, as well as cell functions were assessed using qRT-PCR, nuclear-cytoplasmic fractionation assay, Western blot, immunofluorescence, scratch assay or transwell migration assay. The cell viability of ARPE-19 cells was determined using Cell Counting Kit (CCK)-8. RESULTS: The in vivo analysis demonstrated Wnt5a/ROR1, but not Wnt3a, was upregulated in the RBCCs of the laser-induced CNV mice compared to the normal control group. Intravitreal injection of FH535 effectively reduced Wnt5a protein expression. Both FH535 and Box5 effectively attenuated subretinal fibrosis and EMT, as well as the activation of ß-catenin in laser-induced CNV mice, as evidenced by the significant reduction in areas positive for fibronectin, alpha-smooth muscle actin (α-SMA), collagen I, and active ß-catenin labeling. In vitro, Wnt5a/ROR1, active ß-catenin, and some other Wnt signaling molecules were upregulated in the TGFß1-induced EMT cell model using ARPE-19 cells. Co-treatment with FH535, Box5, or Wnt5a shRNA markedly suppressed the activation of Wnt5a, nuclear translocation of active ß-catenin, as well as the EMT in TGFß1-treated ARPE-19 cells. Conversely, treatment with Foxy-5 independently resulted in the activation of abovementioned molecules and subsequent induction of EMT in ARPE-19 cells. CONCLUSIONS: Our study reveals a reciprocal activation between Wnt5a and ß-catenin to mediate EMT as a pivotal driver of subretinal fibrosis in nAMD. This positive feedback loop provides valuable insights into potential therapeutic strategies to treat subretinal fibrosis in nAMD patients.
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Degeneração Macular , Sulfonamidas , beta Catenina , Humanos , Masculino , Animais , Camundongos , beta Catenina/metabolismo , Proteína Wnt-5a , Camundongos Endogâmicos C57BL , Epitélio Pigmentado da Retina/metabolismo , Transição Epitelial-Mesenquimal , Degeneração Macular/metabolismo , Fibrose , RNA Interferente Pequeno/metabolismoRESUMO
A whole-cell biosensor (WCB) is a convenient and cost-effective method for detecting contaminants. However, the practical application of the cadmium WCBs has been hampered by performance deficiencies, such as low sensitivity, specificity, and responsive strength. In this study, to improve the performance of cadmium WCBs, the cadmium transcription factor (CadC) and its DNA binding site (CadO), the key sensing module of the biosensor, were successively and separately subjected to a two-step directed evolution: 6-round random mutagenesis for CadC and 2-round saturation mutagenesis for CadO. For practical application, the GFP reporter gene was replaced with the lacZ gene and a facile and rapid smartphone detection platform for actual water samples was established by optimizing the reaction systems with detergents. The results showed that the evolved cadmium fluorescent biosensor CadO66 exhibited a higher specificity and a detection limit of 0.034 µg/L, representing a 19-fold reduction compared to the wild-type cadmium biosensor. The detergent sodium dodecylbenzenesulfonate effectively enhanced the visualization of WCB B0033-lacZ. Using the fluorescent WCB CadO66 and the visual WCB B0033-lacZ to analyze the cadmium contents of the actual water samples, the results were also consistent with a graphite furnace atomic absorption spectrometer. Taken together, this study indicates that the two-step directed evolution of CadC and CadO can efficiently improve the performance of cadmium WCBs, further promoting the utilization of WCB in actual sample detection and presenting a promising and feasible method for rapid sample detection.
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Técnicas Biossensoriais , Cádmio , Cádmio/análise , Cádmio/metabolismo , Águas Residuárias , Genes Reporter , Água , Técnicas Biossensoriais/métodosRESUMO
Myopia accounts for a significant proportion of visual lesions worldwide and has the potential to progress toward pathological myopia. This study aims to reveal the difference in protein content in aqueous humor between high myopic and nonhigh myopic patients, as well as better understand the dysregulation of proteins in myopic eyes. Aqueous humor was collected for liquid chromatograph mass spectrometer (LC/MS) analysis from 30 individual eyes that underwent phacoemulsification and intraocular lens (IOL) implantation. Results showed that a total of 190 differentially expressed proteins were identified, which revealed their involvement in cell metabolism, immune and inflammatory response, and system and anatomical structure. Further analysis focused on 15 intensively interacted hub proteins, encompassing functions related to complement cascades, lipoprotein metabolism, and fibrin biological function. Subsequent validations demonstrated elevated levels of APOE (apolipoprotein E), C3 (complement 3), and AHSG (α-2-HS-glycoprotein) in the high myopia group (31 eyes of cataracts and 45 eyes of high myopia with cataracts). AHSG had a significant positive correlation with axial length in high myopic patients, with good efficacy in distinguishing between myopic and nonmyopic groups. AHSG may be a potential indicator of the pathological severity and participator in the pathological progress of high myopia. This study depicted differential expression characteristics of aqueous humor in patients with high myopia and provided optional information for further experimental research on exploring the molecular mechanisms and potential therapeutic targets for high myopia. Data are available via ProteomeXchange with the identifier PXD047584.