RESUMEN
Objective: To assess the changes in QRS duration (â³QRSd) before and after primary percutaneous coronary intervention(PPCI) regarding the relation of left ventricular ejection fraction (LVEF) in patients after a first acute ST segment elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (PPCI). Methods: A total of 244 patients with STEMI were enrolled, and clinical, biochemical, and angiographic parameters were compared between two groups based on LVEF at 6 months post-discharge. QRS duration (QRSd) was analyzed in relation to LVEF, and feature selection using least absolute shrinkage and selection operator(LASSO) regression was performed. Logistic regression analysis and receiver operating characteristic (ROC) curve evaluation were conducted to identify predictors and assess model efficacy. Results: Significant differences were observed between the two groups in terms of various parameters, including age, time from symptom onset to balloon dilation (STB), N-terminal pro B-type natriuretic peptide (NT-proBNP) levels, Left ventricular end-diastolic volume(LVEDV) at baseline, left ventricular end-systolic volume(LVESV)at baseline, left ventricular end-diastolic diameter (LVDD)at baseline and six months, hospital length of stay(days), ST-segment resolution (STR), the left anterior descending artery as the infarction-related artery (IRA-LAD), frequency of TIMI 3 flow post PPCI, thrombus aspiration and/or intracoronary thrombolysis, the use of tirofiban, and the number of implanted stents(stents).In addition, postoperative QRSd and â³QRSd were significantly higher in patients with left ventricular systolic dysfunction(LVSD). LASSO regression selected six variables as predictors of postoperative LVEF. Logistic regression analysis identified age, STB, NT-proBNP, LVESV at baseline,â³QRSd, and stents, as independent factors associated with LVSD within six months for patients with a first occurrence of STEMI. The models achieved AUC values of 0.906 (using ΔQRSd),0.922(using 6 variables excluding ΔQRSd) and 0.962 (using 6 variables). Conclusion: This study identified ΔQRSd as a potential predictor of LVSD in patients with STEMI. The developed models showed good efficacy in predicting postoperative LVEF changes. These findings may contribute to risk stratification and individualized management strategies for STEMI patients.
RESUMEN
Low-dose computed tomography (LDCT) image reconstruction techniques can reduce patient radiation exposure while maintaining acceptable imaging quality. Deep learning (DL) is widely used in this problem, but the performance of testing data (also known as target domain) is often degraded in clinical scenarios due to the variations that were not encountered in training data (also known as source domain). Unsupervised domain adaptation (UDA) of LDCT reconstruction has been proposed to solve this problem through distribution alignment. However, existing UDA methods fail to explore the usage of uncertainty quantification, which is crucial for reliable intelligent medical systems in clinical scenarios with unexpected variations. Moreover, existing direct alignment for different patients would lead to content mismatch issues. To address these issues, we propose to leverage a probabilistic reconstruction framework to conduct a joint discrepancy minimization between source and target domains in both the latent and image spaces. In the latent space, we devise a Bayesian uncertainty alignment to reduce the epistemic gap between the two domains. This approach reduces the uncertainty level of target domain data, making it more likely to render well-reconstructed results on target domains. In the image space, we propose a sharpness-aware distribution alignment (SDA) to achieve a match of second-order information, which can ensure that the reconstructed images from the target domain have similar sharpness to normal-dose CT (NDCT) images from the source domain. Experimental results on two simulated datasets and one clinical low-dose imaging dataset show that our proposed method outperforms other methods in quantitative and visualized performance.
RESUMEN
The advancement of artificial intelligence (AI) for organ segmentation and tumor detection is propelled by the growing availability of computed tomography (CT) datasets with detailed, per-voxel annotations. However, these AI models often struggle with flexibility for partially annotated datasets and extensibility for new classes due to limitations in the one-hot encoding, architectural design, and learning scheme. To overcome these limitations, we propose a universal, extensible framework enabling a single model, termed Universal Model, to deal with multiple public datasets and adapt to new classes (e.g., organs/tumors). Firstly, we introduce a novel language-driven parameter generator that leverages language embeddings from large language models, enriching semantic encoding compared with one-hot encoding. Secondly, the conventional output layers are replaced with lightweight, class-specific heads, allowing Universal Model to simultaneously segment 25 organs and six types of tumors and ease the addition of new classes. We train our Universal Model on 3410 CT volumes assembled from 14 publicly available datasets and then test it on 6173 CT volumes from four external datasets. Universal Model achieves first place on six CT tasks in the Medical Segmentation Decathlon (MSD) public leaderboard and leading performance on the Beyond The Cranial Vault (BTCV) dataset. In summary, Universal Model exhibits remarkable computational efficiency (6× faster than other dataset-specific models), demonstrates strong generalization across different hospitals, transfers well to numerous downstream tasks, and more importantly, facilitates the extensibility to new classes while alleviating the catastrophic forgetting of previously learned classes. Codes, models, and datasets are available at https://github.com/ljwztc/CLIP-Driven-Universal-Model.
RESUMEN
BACKGROUND: Perillyl alcohol (POH) is a aroma monoterpene commonly obtained from various plants' essential oil. Recently, increasing researches have demonstrated that POH may be useful, not only as flavor compound, but also as bioactive molecule because of a variety of biological activities. PURPOSE: The aim of this review is to summarize the production, pharmacological activities and molecular mechanism, active derivatives, toxicity and parmacokinetics, and industrial application of POH. METHODS: A systematic search of published articles up to January 2024 in Web of Science, China Knowledge Network, and PubMed databases is conducted using the following keywords: POH, POH derivatives, biological or pharmacological, production or synthesis, pharmacokinetics, toxicity and application. RESULTS: Biotechnological production is considered to be a potential alternative approach to generate POH. POH provides diverse pharmacological benefits, including anticancer, antimicrobial, insecticidal, antioxidant, anti-inflammatory, hypotensive, vasorelaxant, antinociceptive, antiasthmatic, hepatoprotective effects, etc. The underlying mechanisms of action include modulation of NF-κB, JNK/c-Jun, Notch, Akt/mTOR, PI3K/Akt/eNOS, STAT3, Nrf2 and ERS response pathways, mitigation of mitochondrial dysfunction and membrane integrity damage, and inhibition of ROS accumulation, pro-inflammatory cytokines release and NLRP3 activation. What's more, the proteins or genes influenced by POH against diseases refer to Bax, Bcl-2, cyclin D1, CDK, p21, p53, HIF-1α, AP-1, caspase-3, M6P/IGF2R, PARP, VEGF, etc. Some clinical studies report that intranasal delivery of POH is a safe and effective treatment for cancer, but further clinical investigations are needed to confirm other health benefits of POH in human healthy. Depending on these health-promoting properties together with desirable flavor and safety, POH can be employed as dietary supplement, preservative and flavor additive in food and cosmetic fields, as building block in synthesis fields, as anticancer drug in medicinal fields, and as pesticides and herbicides in agricultural fields. CONCLUSION: This review systematically summarizes the recent advances in POH and highlights its therapeutic effects and potential mechanisms as well as the clinical settings, which is helpful to develop POH into functional food and new candidate drug for prevention and management of diseases. Future studies are needed to conduct more biological activity studies of POH and its derivatives, and check their clinical efficacy and potential side effects.
Asunto(s)
Monoterpenos , Monoterpenos/farmacología , Monoterpenos/química , Humanos , Animales , Aceites Volátiles/farmacología , Aceites Volátiles/químicaRESUMEN
Learning invariant representations via contrastive learning has seen state-of-the-art performance in domain generalization (DG). Despite such success, in this paper, we find that its core learning strategy - feature alignment - could heavily hinder model generalization. Drawing insights in neuron interpretability, we characterize this problem from a neuron activation view. Specifically, by treating feature elements as neuron activation states, we show that conventional alignment methods tend to deteriorate the diversity of learned invariant features, as they indiscriminately minimize all neuron activation differences. This instead ignores rich relations among neurons - many of them often identify the same visual concepts despite differing activation patterns. With this finding, we present a simple yet effective approach, Concept Contrast (CoCo), which relaxes element-wise feature alignments by contrasting high-level concepts encoded in neurons. Our CoCo performs in a plug-and-play fashion, thus it can be integrated into any contrastive method in DG. We evaluate CoCo over four canonical contrastive methods, showing that CoCo promotes the diversity of feature representations and consistently improves model generalization capability. By decoupling this success through neuron coverage analysis, we further find that CoCo potentially invokes more meaningful neurons during training, thereby improving model learning.
RESUMEN
Generalizable medical image segmentation enables models to generalize to unseen target domains under domain shift issues. Recent progress demonstrates that the shape of the segmentation objective, with its high consistency and robustness across domains, can serve as a reliable regularization to aid the model for better cross-domain performance, where existing methods typically seek a shared framework to render segmentation maps and shape prior concurrently. However, due to the inherent texture and style preference of modern deep neural networks, the edge or silhouette of the extracted shape will inevitably be undermined by those domain-specific texture and style interferences of medical images under domain shifts. To address this limitation, we devise a novel framework with a separation between the shape regularization and the segmentation map. Specifically, we first customize a novel whitening transform-based probabilistic shape regularization extractor namely WT-PSE to suppress undesirable domain-specific texture and style interferences, leading to more robust and high-quality shape representations. Second, we deliver a Wasserstein distance-guided knowledge distillation scheme to help the WT-PSE to achieve more flexible shape extraction during the inference phase. Finally, by incorporating domain knowledge of medical images, we propose a novel instance-domain whitening transform method to facilitate a more stable training process with improved performance. Experiments demonstrate the performance of our proposed method on both multi-domain and single-domain generalization.
RESUMEN
Domain generalization (DG) refers to the problem of generalizing machine learning systems to out-of-distribution (OOD) data with knowledge learned from several provided source domains. Most prior works confine themselves to stationary and discrete environments to tackle such generalization issue arising from OOD data. However, in practice, many tasks in non-stationary environments (e.g., autonomous-driving car system, sensor measurement) involve more complex and continuously evolving domain drift, emerging new challenges for model deployment. In this paper, we first formulate this setting as the problem of evolving domain generalization. To deal with the continuously changing domains, we propose MMD-LSAE, a novel framework that learns to capture the evolving patterns among domains for better generalization. Specifically, MMD-LSAE characterizes OOD data in non-stationary environments with two types of distribution shifts: covariate shift and concept shift, and employs deep autoencoder modules to infer their dynamics in latent space separately. In these modules, the inferred posterior distributions of latent codes are optimized to align with their corresponding prior distributions via minimizing maximum mean discrepancy (MMD). We theoretically verify that MMD-LSAE has the inherent capability to implicitly facilitate mutual information maximization, which can promote superior representation learning and improved generalization of the model. Furthermore, the experimental results on both synthetic and real-world datasets show that our proposed approach can consistently achieve favorable performance based on the evolving domain generalization setting.
RESUMEN
Learning the generalizable feature representation is critical to few-shot image classification. While recent works exploited task-specific feature embedding using meta-tasks for few-shot learning, they are limited in many challenging tasks as being distracted by the excursive features such as the background, domain, and style of the image samples. In this work, we propose a novel disentangled feature representation (DFR) framework, dubbed DFR, for few-shot learning applications. DFR can adaptively decouple the discriminative features that are modeled by the classification branch, from the class-irrelevant component of the variation branch. In general, most of the popular deep few-shot learning methods can be plugged in as the classification branch, thus DFR can boost their performance on various few-shot tasks. Furthermore, we propose a novel FS-DomainNet dataset based on DomainNet, for benchmarking the few-shot domain generalization (DG) tasks. We conducted extensive experiments to evaluate the proposed DFR on general, fine-grained, and cross-domain few-shot classification, as well as few-shot DG, using the corresponding four benchmarks, i.e., mini-ImageNet, tiered-ImageNet, Caltech-UCSD Birds 200-2011 (CUB), and the proposed FS-DomainNet. Thanks to the effective feature disentangling, the DFR-based few-shot classifiers achieved state-of-the-art results on all datasets.
RESUMEN
Polybrominated dibenzofurans (PBDFs) are characteristic dioxin-like products of polybrominated diphenyl ether (PBDE) photolysis. In this study, competition mechanisms of radical-based cyclization and hydrogen abstraction reactions are proposed in PBDF formation. Commonly, the ortho C-Br bond dissociation during photolysis generates aryl radicals, which undergo intramolecular cyclization to form PBDFs or hydrogen abstraction with hydrogen donors (such as organic solvents and water) to form lower brominated PBDEs. By using 2,4,4'-tribromodiphenyl ether (BDE-28) as the model reactant, the experimental PBDF formation ratios in various solutions are explained quantitatively by the calculated rate constants of cyclization and hydrogen abstraction reactions using the density functional theory (DFT) method. The solvent effect of pure and mixed solvents on PBDF formation is illustrated successfully. The structure-related hydrogen donation ability for hydrogen abstraction controls the bias of competition reactions and influences PBDF formation. Water resulted to be the most significant generation of PBDFs. Fulvic and humic acid display higher hydrogen donation ability than small-molecule organics due to the partitioning effect in aqueous solution. Quantitative structure-activity relationship (QSAR) models of the calculated rate constants for 512 cyclization and 319 hydrogen abstraction reactions using 189 PBDEs as the initial reactants in water are established, revealing the high risk of PBDF formation in aqueous solution.
Asunto(s)
Éteres Difenilos Halogenados , Agua , Éteres Difenilos Halogenados/química , Fotólisis , Ciclización , Solventes , Agua/químicaRESUMEN
Percutaneous coronary intervention and acute coronary syndrome are both closely tied to the frequently occurring complication of coronary microembolization (CME). Resveratrol (RES) has been shown to have a substantial cardioprotective influence in a variety of cardiac diseases, though its function and potential mechanistic involvement in CME are still unclear. The forty Sprague-Dawley rats were divided into four groups randomly: CME, CME + RES (25 mg/kg), CME + RES (50 mg/kg), and sham (10 rats per group). The CME model was developed. Echocardiography, levels of myocardial injury markers in the serum, and histopathology of the myocardium were used to assess the function of the cardiac muscle. For the detection of the signaling of TLR4/MyD88/NF-κB along with the expression of pyroptosis-related molecules, ELISA, qRT-PCR, immunofluorescence, and Western blotting were used, among other techniques. The findings revealed that myocardial injury and pyroptosis occurred in the myocardium following CME, with a decreased function of cardiac, increased levels of serum myocardial injury markers, increased area of microinfarct, as well as a rise in the expression levels of pyroptosis-related molecules. In addition to this, pretreatment with resveratrol reduced the severity of myocardial injury after CME by improving cardiac dysfunction, decreasing serum myocardial injury markers, decreasing microinfarct area, and decreasing cardiomyocyte pyroptosis, primarily by blocking the signaling of TLR4/MyD88/NF-κB and also reducing the NLRP3 inflammasome activation. Resveratrol may be able to alleviate CME-induced myocardial pyroptosis and cardiac dysfunction by impeding the activation of NLRP3 inflammasome and the signaling pathway of TLR4/MyD88/NF-κB.
RESUMEN
Background: Osteoarthritis (OA) is a chronic disease that may cause articular cartilage degeneration, and synovial inflammation, resulting in considerable pain, poor quality of life, and functional limitations. Previous research has shown that ECM degradation and inflammation are involved in the progression of OA. Stevioside (STE), a naturally diterpenoid glycoside, is isolated from the Stevia rebaudiana (Bertoni), which has been exerted a variety of pharmacological activities, involving anti-inflammatory, anti-oxidative, and neuroprotective effects. However, STE's effects on OA and its mechanism still need further research. Methods: In the present study, we examined the anti-inflammatory effects of STE (STE) in both mouse chondrocytes and OA model induced by destabilization of the medial meniscus (DMM). In vitro, the mouse chondrocytes were treated with STE (0, 10, 20, 40 âM, 24 âh) after stimulated with IL-1ß (10 âng/mL, 24 âh). The expression of ant-inflammation-relative mediators iNOS and Cox-2 were detected by Western blot and RT-PCR. The catabolic factors (MMP-13, ADAMTS-4) and cartilage matrix constituent (Aggrecan, Collagen II) were measured by Western blot and Immunofluorescence staining. The Nrf2/HO-1/NF-κB signaling molecules were detected by Western blot. In vivo, histological analysis was used to evaluate the severity of mouse OA models. Results: STE remarkably inhibited the IL-1ß-induced expression of iNOS and Cox-2, generation of MMP-13, ADAMTS-4 and degradation of Aggrecan and Collagen II. Furthermore, we found that the chondroprotective effect of STE via Nrf2/HO-1/NF-κB signaling pathway. In vivo, the cartilage treated with STE displayed attenuated degeneration, low OARIS scores compared with DMM group. In conclusion, we considered that STE might be a promising therapeutic agent for the treatment of OA in future. Conclusions: Our findings indicated that STE can ameliorate the development of OA via inhibiting the inflammation. The underlying mechanism may be related to the Nrf2/HO-1/NF-κB signaling pathway. Moreover, the treatment of STE significantly relieves the progression in the mouse DMM model. All of the results demonstrated the therapeutic of STE in OA treatment. The translational potential of this article: This study demonstrates a more efficient and safe application of STE in treating osteoarthritis, provide a new concept for the cartilage targeted application of natural compounds.
RESUMEN
This paper focuses on the domain generalization task where domain knowledge is unavailable, and even worse, only samples from a single domain can be utilized during training. Our motivation originates from the recent progresses in deep neural network (DNN) testing, which has shown that maximizing neuron coverage of DNN can help to explore possible defects of DNN (i.e., misclassification). More specifically, by treating the DNN as a program and each neuron as a functional point of the code, during the network training we aim to improve the generalization capability by maximizing the neuron coverage of DNN with the gradient similarity regularization between the original and augmented samples. As such, the decision behavior of the DNN is optimized, avoiding the arbitrary neurons that are deleterious for the unseen samples, and leading to the trained DNN that can be better generalized to out-of-distribution samples. Extensive studies on various domain generalization tasks based on both single and multiple domain(s) setting demonstrate the effectiveness of our proposed approach compared with state-of-the-art baseline methods. We also analyze our method by conducting visualization based on network dissection. The results further provide useful evidence on the rationality and effectiveness of our approach.
RESUMEN
Reflection removal has been discussed for more than decades. This paper aims to provide the analysis for different reflection properties and factors that influence image formation, an up-to-date taxonomy for existing methods, a benchmark dataset, and the unified benchmarking evaluations for state-of-the-art (especially learning-based) methods. Specifically, this paper presents a SIngle-image Reflection Removal Plus dataset "SIR 2+ " with the new consideration for in-the-wild scenarios and glass with diverse color and unplanar shapes. We further perform quantitative and visual quality comparisons for state-of-the-art single-image reflection removal algorithms. Open problems for improving reflection removal algorithms are discussed at the end. Our dataset and follow-up update can be found at https://reflectionremoval.github.io/sir2data/.
RESUMEN
Objectives: Coronary microembolization (CME) represents a serious periprocedural complication after percutaneous coronary intervention. Ferroptosis has been identified in multiple cardiovascular diseases. In this study, we aimed to investigate the effects of atorvastatin (ATV) on ferroptosis and inflammation following CME and elucidate the underlying mechanism. Methods: We established a rat model of CME by injecting microspheres into the left ventricle. Deferoxamine (DFO), a selective ferroptosis inhibitor, or ATV was pretreated before modeling. Cardiac function and cardiac troponin T (cTnT) levels were detected. Levels of ferroptosis-associated genes, malondialdehyde (MDA), glutathione (GSH), and ferrous iron (Fe2+) were measured to validate ferroptosis. Levels of tumor necrosis factor alpha (TNF-α) and interleukin 1 beta (IL-1ß) were assayed to determine the inflammation. Chromatin immunoprecipitation was performed to determine the binding of hypoxia-inducible factor 1 subunit alpha (Hif1a) to the promoter of prostaglandin-endoperoxide synthase-2 (Ptgs2). Results: Ferroptosis and inflammation were induced following CME with increased levels of MDA (â¼2.5 fold, p < 0.01), Fe2+ (â¼1.5 fold, p < 0.01), TNF-α, and IL-1ß and decreased GSH levels (â¼42%, p < 0.01). Meanwhile, the level of Ptgs2 was significantly increased, while those of glutathione peroxidase 4 (Gpx4) and solute carrier family 7 member 11 (Slc7a11) were decreased. The level of cTnT was increased by 7-fold (p < 0.01). Left ventricular ejection fraction (LVEF) was significantly reduced (â¼85% in the sham group versus â¼45% in the CME group, p < 0.01). DFO or Ptgs2 silencing inhibited the increase of MDA, Ptgs2, TNF-α, and IL-1ß, and induced the levels of GSH and Gpx4, followed by reduction in cTnT levels by approximately 50% (p < 0.01). LVEF was improved by approximately 2 fold (p < 0.01). Mechanistically, the transcription factor Hif1a bound to the promoter of Ptgs2 and upregulated its expression. In addition, ATV inhibited the activation of the Hif1a/Ptgs2 axis and attenuated cardiac ferroptosis and inflammation, thus ameliorating CME-induced myocardial injury (LVEF, â¼34% elevation; cTnT, â¼1.8 fold decrease, p < 0.01). Conclusion: Atorvastatin ameliorates ferroptosis-mediated myocardial injury and inflammation following CME via the Hif1a/Ptgs2 pathway.
RESUMEN
BACKGROUND: Coronary microembolization (CME) is a common and intractable complication of coronary revascularization, which leads to perioperative myocardial injury, cardiac dysfunction, and poor prognosis. Nicorandil is widely used for the management of ischemic heart diseases, but the cardioprotective effects of nicorandil beyond anti-angina in CME-induced myocardial injury are worthy of further exploration. Therefore, the present study investigated the effect of nicorandil on CME-induced cardiomyocyte pyroptosis and explored the underlying mechanism. METHODS: A rat model of CME was established via the injection of microspheres into the left ventricle. A cell model of H9c2 cardiomyocytes stimulated by lipopolysaccharide (LPS) and hypoxia mimicked the microenvironment induced by CME. Nicorandil or the adenosine monophosphate-activated protein kinase (AMPK)-specific inhibitor compound C (CC) was administered before CME induction and cell modeling. Cardiac function, histological alterations in the myocardium, myocardial injury biomarkers in serum and cell culture supernatant, cell viability, adenosine triphosphate (ATP) level, superoxide dismutase (SOD) activity, malondialdehyde (MDA) content, reactive oxygen species (ROS) activity, mitochondrial membrane potential, and pyroptosis-associated index were assessed after the animal and cell modeling of CME. RESULTS: Nicorandil pretreatment attenuated cardiac dysfunction and myocardial injury following CME. Nicorandil also alleviated oxidative stress and mitochondrial damage. Moreover, nicorandil promoted AMPK activation, reduced the expression of thioredoxin-interacting protein (TXNIP), inhibited the activation of the NOD-like receptor pyrin containing 3 (NLRP3) inflammasome, and mitigated cardiomyocyte pyroptosis. However, co-treatment with CC reversed the cardioprotective effects of nicorandil. CONCLUSION: Nicorandil pretreatment inhibits cardiomyocyte pyroptosis and alleviates CME-induced myocardial injury via the AMPK/TXNIP/NLRP3 signaling pathway.
Asunto(s)
Lesiones Cardíacas , Isquemia Miocárdica , Ratas , Animales , Miocitos Cardíacos , Nicorandil/farmacología , Nicorandil/uso terapéutico , Piroptosis , Proteínas Quinasas Activadas por AMP , Proteína con Dominio Pirina 3 de la Familia NLR , Miocardio , Transducción de Señal , Proteínas de Ciclo CelularRESUMEN
Objective: The objective is to observe the changes in aberrations before and after surgery in patients with common horizontal strabismus and to analyze the possible reasons for the changes. Methods: Forty eyes of 40 cases with concomitant exotropia who underwent strabismus correction at the Ophthalmology Department of Nantong University Hospital from October 2020 to July 2021 were included in this study, all of whom underwent unilateral lateral rectus recession combined with a medial rectus resection in the same eye. Aberration parameters were measured 1 day before surgery and 1 week, 1 month, 3 months, and 6 months after surgery. Differences in the indicators at each time period were compared by analysis of variance (ANOVA) of repeated measures data for a single factor, and data were analyzed using SPSS 25.0 statistical application software. Results: 5 mm pupil diameter: the preoperative and postoperative RMS of total aberration showed statistically significant difference (P < 0.01). Postoperation test (Bonferroni method) and preoperative comparison at each period after surgery showed statistically significant differences between 6 months after surgery (P=0.002) and preoperative comparison. The preoperative and postoperative comparison of RMS in LOAs was statistically significant (P < 0.01); postoperative test (Bonferroni method) and preoperative comparison showed that there were statistically significant differences between 1 week (P=0.033) and 6 months (P=0.002) after operation. The difference of RMS of defocus before and after operation was statistically significant (P < 0.01); postoperation test (Bonferroni method) and preoperative comparison showed that there was statistically significant difference between 6 months after operation (P=0.007) and preoperative comparison. There was statistically significant difference in preoperative and postoperative RMS of HOAs (P=0.013). Postoperative test (Bonferroni method) and preoperative comparison showed that there was statistically significant difference 6 months after surgery (P=0.03). The RMS of secondary astigmatism showed a statistically significant difference before and after operation (P=0.001), and the postoperation test (Bonferroni method) showed a statistically significant difference 6 months after operation (P=0.002). In 5 mm pupil diameter, the preoperative and postoperative RMS of total aberration showed statistically significant difference (P < 0.01), postoperative test (Bonferroni method) was used to compare each period after surgery with that before surgery, and there were statistically significant differences between 1 week after surgery (P=0.034), 3 months after surgery (P=0.033), and 6 months after surgery (P=0.003). The preoperative and postoperative comparison of RMS in LOAs was statistically significant (P < 0.01), postoperative test (Bonferroni method) was used to compare each period after surgery with that before surgery, and there were statistically significant differences between 1 week after surgery (P=0.04), 3 months after surgery (P=0.034), and 6 months after surgery (P=0.004). The difference of RMS of defocus before and after surgery was statistically significant (P=0.002), and the comparison between postoperation test (Bonferroni method) and preoperation showed that the difference was statistically significant 6 months after surgery (P=0.027). The RMS of astigmatism showed statistically significant difference before and after operation (P=0.002), and the postoperation test (Bonferroni method) showed statistically significant difference between 6 months after operation (P=0.009) and before operation. Conclusion: We found that horizontal rectus surgery had a transient effect on LOAs and almost no effect on HOAs. Long-term follow-up is recommended after strabismus surgery to observe eye position and binocular visual function. Because of the high prevalence of strabismus in adolescents, long-term observation of the eye axis and aberration is recommended.
Asunto(s)
Astigmatismo , Exotropía , Adolescente , Astigmatismo/etiología , Astigmatismo/cirugía , Exotropía/complicaciones , Exotropía/cirugía , Humanos , Músculos Oculomotores/cirugía , Estudios Retrospectivos , Visión BinocularRESUMEN
Pyroptosis is an inflammatory form of programmed cell death that is linked with invading intracellular pathogens. Cardiac pyroptosis has a significant role in coronary microembolization (CME), thus causing myocardial injury. Tanshinone IIA (Tan IIA) has powerful cardioprotective effects. Hence, this study aimed to identify the effect of Tan IIA on CME and its underlying mechanism. Forty Sprague-Dawley (SD) rats were randomly grouped into sham, CME, CME + low-dose Tan IIA, and CME + high-dose Tan IIA groups. Except for the sham group, polyethylene microspheres (42 µm) were injected to establish the CME model. The Tan-L and Tan-H groups received intraperitoneal Tan IIA for 7 days before CME. After CME, cardiac function, myocardial histopathology, and serum myocardial injury markers were assessed. The expression of pyroptosis-associated molecules and TLR4/MyD88/NF-κB/NLRP3 cascade was evaluated by qRT-PCR, Western blotting, ELISA, and IHC. Relative to the sham group, CME group's cardiac functions were significantly reduced, with a high level of serum myocardial injury markers, and microinfarct area. Also, the levels of caspase-1 p20, GSDMD-N, IL-18, IL-1ß, TLR4, MyD88, p-NF-κB p65, NLRP3, and ASC expression were increased. Relative to the CME group, the Tan-H and Tan-L groups had considerably improved cardiac functions, with a considerably low level of serum myocardial injury markers and microinfarct area. Tan IIA can reduce the levels of pyroptosis-associated mRNA and protein, which may be caused by inhibiting TLR4/MyD88/NF-κB/NLRP3 cascade. In conclusion, Tanshinone IIA can suppress cardiomyocyte pyroptosis probably through modulating the TLR4/MyD88/NF-κB/NLRP3 cascade, lowering cardiac dysfunction, and myocardial damage.
RESUMEN
Random-pattern skin flap is widely used in plastic and reconstructive surgery. However, its clinical effect is limited by ischemia necrosis occurs at the distal part of flap. Previous studies have proved that the protective effect of formononetin was associated with its antioxidant, anti-inflammatory ability. However, further research is still needed on the effect of formononetin on flap viability. The purpose of our study was to investigate the effect of formononetin on flap survival and the underlying mechanisms. Two doses (25 mg/kg, 50 mg/kg)of formononetin were administered for seven consecutive days on flap model. Flap tissues were collected on postoperative day 7. Our results revealed that formononetin promoted skin flap viability in a dose-dependent manner. Using immunohistochemical staining and western blot, we found that formononetin significantly reduced oxidative stress and inflammation. Hematoxylin and eosin (H and E) staining, laser Doppler images and immunofluorescence staining showed the enhancement of angiogenesis after formononetin treatment. Mechanistically, we demonstrated that the antioxidation of formononetin was mediated by activation and nuclear translocation of nuclear factor-E2-related factor 2 (Nrf2), while down-regulating cytoplasmic Kelch-like ECH-associated protein 1 (Keap1) expression. Co-treatment with formononetin and LY294002 (15 mg/kg), a potent Phosphatidylinositol-3-kinase (PI3K) inhibitor, which aborted nuclear Nrf2 expression and phosphorylated Akt, indicating that formononetin-mediated Nrf2 activation was related to PI3K/Akt pathway. Overall, our findings revealed that formononetin increased angiogenesis, reduced oxidative stress and inflammation, thus promoting flap survival. We highlighted the antioxidant effects of formononetin since the Nrf2 system was activated. Therefore, formononetin might be a promising candidate drug that can enhance survival of skin flaps.
RESUMEN
Organophosphate esters (OPEs) are a new class of flame retardants present in diverse waters. The study focused on the removal of aqueous OPEs using functionalized MIL-101(Fe), which was a representative of the metal-organic frameworks (MOFs). Adsorption kinetics of tris(2-chloroethyl) phosphate (TCEP), tributyl phosphate (TnBP), and triphenyl phosphate (TPhP) were investigated. Additionally, TCEP was selected as the model contaminant to study the adsorption isotherms, thermodynamics, and effect of solution matrix properties. Adsorption mechanisms obtained from the experiments were confirmed using density functional theory (DFT) calculations. Adsorption kinetics indicated that functionalized MOFs provided a significant enhancement to the removal of TCEP. The maximum adsorption capacities qm of MIL-101(Fe), MIL-101(Fe)-NH2, MIL-101(Fe)-OH, and MIL-101(Fe)-CH3 at 298 K for TCEP were 76.040, 282.940, 119.680, and 181.274 µmol/g, respectively. By comparing the adsorption behavior of functionalized MOFs, MIL-101(Fe)-NH2 was proved to be most efficient for TCEP removal. Based on the adsorption experiments and DFT calculations, TCEP removal was dominated by physical adsorption. The van der Waals (vdW) interactions and hydrogen bonding were assumed to be involved in the adsorption. This work proves that appropriate ligand functionalization is promising for the removal of aqueous OPEs, which also provides a new insight for the control of OPEs pollution.
Asunto(s)
Estructuras Metalorgánicas , Adsorción , Teoría Funcional de la Densidad , Ésteres , Ligandos , Organofosfatos , AguaRESUMEN
The deep learning based approaches which have been repeatedly proven to bring benefits to visual recognition tasks usually make a strong assumption that the training and test data are drawn from similar feature spaces and distributions. However, such an assumption may not always hold in various practical application scenarios on visual recognition tasks. Inspired by the hierarchical organization of deep feature representation that progressively leads to more abstract features at higher layers of representations, we propose to tackle this problem with a novel feature learning framework, which is called GMFAD, with better generalization capability in a multilayer perceptron manner. We first learn feature representations at the shallow layer where shareable underlying factors among domains (e.g., a subset of which could be relevant for each particular domain) can be explored. In particular, we propose to align the domain divergence between domain pair(s) by considering both inter-dimension and inter-sample correlations, which have been largely ignored by many cross-domain visual recognition methods. Subsequently, to learn more abstract information which could further benefit transferability, we propose to conduct feature disentanglement at the deep feature layer. Extensive experiments based on different visual recognition tasks demonstrate that our proposed framework can learn better transferable feature representation compared with state-of-the-art baselines.