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Engineering slope stability issues typically exhibit the impact of deteriorating durability on the susceptibility of slopes to failure. A thorough investigation was essential to explore theoretical and experimental aspects of slope durability degradation and its implications on long-term stability. Hence, a durability model was developed to accommodate slope stabilization using reinforced concrete (RC) support structures. This model was grounded in classical durability principles for RC structures. Subsequently, a model test was conducted to compare the responses of a standard slope model with a weakened counterpart subjected to environmental impacts. According to the proposed methodology for slope durability and stability, a case study involving future durability and stability predictions was performed. It was found that the theoretical solutions for the carbonation or neutralization (CN) velocity, depth, and penetration time agreed well with model test results. The slope surface displacements of the weakened slope with deteriorating coefficients between 0.6 and 0.9 were 4 to 8 times those of the standard slope, demonstrating significant degradation in stability. The case study indicated a steady reduction in the safety factor, at a rate of 2.3 to 2.4 per year throughout the slope's service life. Finite-element-based predictions also suggested the potential for corrosion of slope anchor bolts within 20 years and breakage within 30 years, at an average rate of 7.5 per year in the ultimate bearing capacity. These findings highlight the need for timely maintenance and reinforcement interventions to ensure the long-term durability of operational slopes.
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At present, researches on brain fatigue recognition are still in the stage of single task and simple brain region network features, while researches on high-order brain functional network features and brain region state mechanisms during fatigue in multi-task scenarios are still insufficient, making it difficult to meet the needs of fatigue recognition under complex conditions. Therefore, this study utilized functional near-infrared spectroscopy (fNIRS) technology to explore the correlation and differences in the low-order and high-order brain functional network attributes of three task induced mental fatigue, and to explore the brain regions that have a major impact on mental fatigue. Self-training algorithms were used to identify the three levels of brain fatigue. The results showed that during the fatigue development, the overall connection strength of the endothelial cell metabolic activity and neural activity frequency bands of the low-order brain functional network first decreased and then increased, while the myogenic activity and heart rate activity frequency bands showed the opposite pattern. Network topology analysis indicated that from no fatigue to mild fatigue, the clustering coefficient of endothelial cell metabolic activity and myogenic activity frequency bands significantly decreased, while the characteristic path length of myogenic activity significantly increased; when experiencing severe fatigue, the small-world attribute of the neural frequency band significantly weakened. However, each frequency band maintained its small-world attribute, reflecting the self-optimization and adaptability of the network during the fatigue process. During mild fatigue, neuronal activity bands' node degree, cluster coefficient, and efficiency rose in high-order brain networks, while low-order networks showed no significant changes. As fatigue progressed, the myogenic activity bands of high-order network properties dominated, but neural bands gained prominence in mild fatigue, approaching the level of myogenic bands in severe fatigue, indicating that brain fatigue orchestrated a shift from myogenic to neural dominance in frequency bands. In addition, during the process of fatigue, the four network attributes of the high-order network cluster composed of low-order nodes related to the prefrontal cortex region, left anterior motor region, motor assist region, and left frontal lobe eye movement region significantly increased, indicating that these brain regions had a significant impact on brain fatigue status. The accuracy of using both high-order and low-order features to identify fatigue levels reached 88.095%, indicating that the combined network features of both high-order and low-order fNIRS signals could effectively detect multi-level mental fatigue, providing innovative ideas for fatigue warning.
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Encéfalo , Espectroscopia de Luz Próxima ao Infravermelho , Humanos , Espectroscopia de Luz Próxima ao Infravermelho/métodos , Encéfalo/fisiologia , Masculino , Fadiga Mental/fisiopatologia , Adulto , Rede Nervosa/fisiologia , Adulto Jovem , Feminino , Algoritmos , Mapeamento Encefálico/métodos , Fadiga/fisiopatologiaRESUMO
Milk boasts an array of potent bioactive compounds, such as lactoferrin (Lf), immunoglobulins, and functional proteins, all delivering substantial therapeutic benefits. In this study, Immune Powder (a functional dairy formulation) and its primary component called Fractionated Milk Protein (FMP) containing Lf, zinc, and immunoglobulins and formulated by Ausnutria Pty Ltd. were evaluated for their potential broad-spectrum pharmacological activity. In particular, this study investigated the antibacterial (against pathogenic Escherichia coli), prebiotic (promoting Lactobacillus delbrueckii growth), anti-inflammatory (inhibition of NO production in RAW264.7 macrophages), and antiviral (against human coronavirus 229E) effects of the samples. In addition, the impact of simulated gastric digestion on the efficacy of the samples was explored. LCMS-based proteomics was implemented to unveil cellular and molecular mechanisms underlying antiviral activity. The Immune Powder demonstrated antibacterial activity against E. coli (up to 99.74 ± 11.47% inhibition), coupled with prebiotic action (10.84 ± 2.2 viability fold-change), albeit these activities diminished post-digestion (p < 0.01). The Immune Powder effectively mitigated NO production in lipopolysaccharide-stimulated RAW264.7 macrophages, with declining efficacy post-digestion (p < 0.0001). The Immune Powder showed similar antiviral activity before and after digestion (p > 0.05) with up to 3-fold improvement. Likewise, FMP exhibited antibacterial potency pre-digestion at high concentrations (95.56 ± 1.23% inhibition at 125 mg/mL) and post-digestion at lower doses (61.82 ± 5.58% inhibition at 3906.25 µg/mL). FMP also showed enhanced prebiotic activity post-digestion (p < 0.0001), NO inhibition pre-digestion, and significant antiviral activity. The proteomics study suggested that the formulation and its primary component shared similar antiviral mechanisms by inhibiting scavenger receptor binding and extracellular matrix interaction.
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Pós , Probióticos , Animais , Camundongos , Probióticos/farmacologia , Células RAW 264.7 , Humanos , Microbioma Gastrointestinal/efeitos dos fármacos , Antivirais/farmacologia , Escherichia coli/efeitos dos fármacos , Escherichia coli/crescimento & desenvolvimento , Antibacterianos/farmacologia , Proteínas do Leite/farmacologia , Macrófagos/metabolismo , Macrófagos/efeitos dos fármacos , Óxido Nítrico/metabolismo , Prebióticos , Laticínios/microbiologia , Coronavirus/efeitos dos fármacosRESUMO
A novel metal-organic framework (MOF) material, MIL-100(Fe)-DMA, was synthesized using the solvothermal method. The structure of the MOF was characterized using scanning electron microscopy-energy dispersive X-ray spectroscopy, N2 adsorption-desorption isotherms, X-ray diffraction analysis, Fourier-transform infrared spectroscopy, X-ray photoelectron spectroscopy, and Mössbauer spectroscopy. Batch adsorption experiments were performed to investigate the effects of initial Sr2+ and Cs+ concentrations, adsorption time, pH, and coexisting cations on the adsorption performance of the material. The adsorption mechanism was further elucidated using adsorption kinetics and isotherm models. The results indicated that the adsorption of Sr2+ and Cs+ does not significantly affect the MOF material structure. As reaction time and initial ion concentration increased, the adsorption capacity of MIL-100(Fe)-DMA for Sr2+ and Cs+ increased rapidly and then gradually reached equilibrium. Optimal adsorption occurred under alkaline conditions, with maximum adsorption capacity observed at pH = 8. The adsorption process for Sr2+ and Cs+ was well described by the pseudo-second-order kinetic model, the Weber-Morris model, and the Langmuir adsorption isothermal model. The adsorption process was mainly identified as monolayer chemical adsorption, influenced by multiple factors. Characterization combined with density functional theory calculations revealed that the unsaturated carboxylic acid groups on the surface of the MOFs play a crucial role in the interaction with Sr2+ and Cs+.
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Pedestrian detection plays a critical role in computer vision as it contributes to ensuring traffic safety. Existing methods that rely solely on RGB images suffer from performance degradation under low-light conditions due to the lack of useful information. To address this issue, recent multispectral detection approaches have combined thermal images to provide complementary information and have obtained enhanced performances. Nevertheless, few approaches focus on the negative effects of false positives (FPs) caused by noisy fused feature maps. Different from them, we comprehensively analyze the impacts of FPs on detection performance and find that enhancing feature contrast can significantly reduce these FPs. In this article, we propose a novel target-aware fusion strategy for multispectral pedestrian detection, named TFDet. The target-aware fusion strategy employs a fusion-refinement paradigm. In the fusion phase, we reveal the parallel-and cross-channel similarities in RGB and thermal features and learn an adaptive receptive field to collect useful information from both features. In the refinement phase, we use a segmentation branch to discriminate the pedestrian features from the background features. We propose a correlation-maximum loss function to enhance the contrast between the pedestrian features and background features. As a result, our fusion strategy highlights pedestrian-related features and suppresses unrelated ones, generating more discriminative fused features. TFDet achieves state-of-the-art performance on two multispectral pedestrian benchmarks, KAIST and LLVIP, with absolute gains of 0.65% and 4.1% over the previous best approaches, respectively. TFDet can easily extend to multiclass object detection scenarios. It outperforms the previous best approaches on two multispectral object detection benchmarks, FLIR and M3FD, with absolute gains of 2.2% and 1.9%, respectively. Importantly, TFDet has comparable inference efficiency to the previous approaches and has remarkably good detection performance even under low-light conditions, which is a significant advancement for ensuring road safety. The code will be made publicly available at https://github.com/XueZ-phd/TFDet.git.
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Since the discovery in 2000, conversion-type materials have emerged as a promising negative-electrode candidate for next-generation batteries with high capacity and tunable voltage, limited by low reversibility and severe voltage hysteresis. Heterogeneous construction stands out as a cost-effective and efficient approach to reducing reaction barriers and enhancing energy density. However, the second term introduced by conventional heterostructure inevitably complicates the electrochemical analysis and poses great challenges to harvesting systematic insights and theoretical guidance. A model cell is designed and established herein for the conversion reactions between Na and TMSA-SnO2, where TMSA-SnO2 represents single atom modification of eight different 3d transition elements (V, Cr, Mn, Fe, Co, Ni, Cu or Zn). Such a model unit fundamentally eliminates the interference from the second phase and thus enables independent exploration of activation manifestations of the heterogeneous architecture. For the first time, a thermodynamically dependent catalytic effect is proposed and verified through statistical data analysis. The mechanism behind the unveiled catalytic effect is further elucidated by which the active d orbitals of transition metals weaken the surface covalent bonds and lower the reaction barriers. This research provides both theoretical insights and practical demonstrations of the advanced heterogeneous electrodes.
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BACKGROUND: Detection of cancer and identification of tumor origin at an early stage improve the survival and prognosis of patients. Herein, we proposed a plasma cfDNA-based approach called TOTEM to detect and trace the cancer signal origin (CSO) through methylation markers. METHODS: We performed enzymatic conversion-based targeted methylation sequencing on plasma cfDNA samples collected from a clinical cohort of 500 healthy controls and 733 cancer patients with seven types of cancer (breast, colorectum, esophagus, stomach, liver, lung, and pancreas) and randomly divided these samples into a training cohort and a testing cohort. An independent validation cohort of 143 healthy controls, 79 liver cancer patients and 100 stomach cancer patients were recruited to validate the generalizability of our approach. RESULTS: A total of 57 multi-cancer diagnostic markers and 873 CSO markers were selected for model development. The binary diagnostic model achieved an area under the curve (AUC) of 0.907, 0.908 and 0.868 in the training, testing and independent validation cohorts, respectively. With a training specificity of 98%, the specificities in the testing and independent validation cohorts were 100% and 98.6%, respectively. Overall sensitivity across all cancer stages was 65.5%, 67.3% and 55.9% in the training, testing and independent validation cohorts, respectively. Early-stage (I and II) sensitivity was 50.3% and 45.7% in the training and testing cohorts, respectively. For cancer patients correctly identified by the binary classifier, the top 1 and top 2 CSO accuracies were 77.7% and 86.5% in the testing cohort (n = 148) and 76.0% and 84.0% in the independent validation cohort (n = 100). Notably, performance was maintained with only 21 diagnostic and 214 CSO markers, achieving a training AUC of 0.865, a testing AUC of 0.866, and an integrated top 2 accuracy of 83.1% in the testing cohort. CONCLUSIONS: TOTEM demonstrates promising potential for accurate multi-cancer detection and localization by profiling plasma methylation markers. The real-world clinical performance of our approach needs to be investigated in a much larger prospective cohort.
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Biomarcadores Tumorais , DNA Tumoral Circulante , Metilação de DNA , Neoplasias , Humanos , Biomarcadores Tumorais/sangue , Biomarcadores Tumorais/genética , Neoplasias/genética , Neoplasias/sangue , Neoplasias/diagnóstico , Feminino , Masculino , DNA Tumoral Circulante/sangue , DNA Tumoral Circulante/genética , Pessoa de Meia-Idade , Idoso , Detecção Precoce de Câncer/métodos , Estudos de Casos e Controles , Sensibilidade e Especificidade , Adulto , PrognósticoRESUMO
Cytokine storm (CS) is the main driver of SARS-CoV-2-induced acute respiratory distress syndrome (ARDS) in severe coronavirus disease-19 (COVID-19). The pathological mechanisms of CS are quite complex and involve multiple critical molecular targets that turn self-limited and mild COVID-19 into a severe and life-threatening concern. At present, vaccines are strongly recommended as safe and effective treatments for preventing serious illness or death from COVID-19. However, effective treatment options are still lacking for people who are at the most risk or hospitalized with severe disease. Chinese herbal medicines have been shown to improve the clinical outcomes of mild to severe COVID-19 as an adjunct therapy, particular preventing the development of mild to severe ARDS. This review illustrates in detail the pathogenesis of CS-involved ARDS and its associated key molecular targets, cytokines and signalling pathways. The therapeutic targets were identified particularly in relation to the turning points of the development of COVID-19, from mild symptoms to severe ARDS. Preclinical and clinical studies were reviewed for the effects of Chinese herbal medicines together with conventional therapies in reducing ARDS symptoms and addressing critical therapeutic targets associated with CS. Multiple herbal formulations, herbal extracts and single bioactive phytochemicals with or without conventional therapies demonstrated strong anti-CS effects through multiple mechanisms. However, evidence from larger, well-designed clinical trials is lacking and their detailed mechanisms of action are yet to be well elucidated. More research is warranted to further evaluate the therapeutic value of Chinese herbal medicine for CS in COVID-19-induced ARDS.
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The correlation between hematopoietic cell-specific lyn substrate 1 (HCLS1) expression levels and heart failure (HF) remains unclear. HF datasets GSE192886 and GSE196656 profiles were generated from GPL24676 and GPL20301 platforms in gene expression omnibus (GEO) database and differentially expressed genes (DEGs) were obtained, which was followed by weighted gene co-expression network analysis, protein-protein interaction (PPI) networks, functional enrichment analysis and comparative toxicogenomics database (CTD) analysis. Heatmaps of gene expression levels were plotted. TargetScan was used to screen miRNAs regulating central DEGs. A total of 500 DEGs were found and mainly concentrated in leukocyte activation, protein phosphorylation, and protein complexes involved in cell adhesion, PI3K Akt signaling pathway, Notch signaling pathway, and right ventricular cardiomyopathy. PPI network identified 15 core genes (HCLS1, FERMT3, CD53, CD34, ITGAL, EP300, LYN, VAV1, ITGAX, LEP, ITGB1, IGF1, MMP9, SMAD2, RAC2). Heatmap shows that 4 genes (EP300, CD53, HCLS1, LYN) are highly expressed in HF tissue samples. We found that 4 genes (EP300, CD53, HCLS1, LYN) were associated with heart diseases, cardiovascular diseases, edema, rheumatoid arthritis, necrosis, and inflammation. HCLS1 is highly expressed in HF and maybe its target.
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Biomarcadores , Insuficiência Cardíaca , Humanos , Insuficiência Cardíaca/genética , Insuficiência Cardíaca/metabolismo , Biomarcadores/metabolismo , Mapas de Interação de Proteínas/genética , MicroRNAs/metabolismo , MicroRNAs/genética , Perfilação da Expressão GênicaRESUMO
Background: Esophageal cancer remains a significant burden of lethal cancers worldwide, particularly in China. This is an annual report of Shanghai Chest Hospital (SCH) on surgical treatment for esophageal cancer patients in 2017. Methods: All patients who received surgical treatment for esophageal cancer at SCH in 2017 were given a detailed summary of clinical information based on the database of SCH. Kaplan-Meier method was used to present their survival, subgroup analyses, and multivariate Cox regression analysis were used to estimate the potential risk factors for prognosis. Results: In 2017, a total of 663 patients received surgical treatment (628 esophagectomies and 35 endoscopic resections) for esophageal cancer at SCH. Of the patients who underwent esophagectomy, 292 patients received perioperative treatment, majority of which was postoperative treatment (47.9%). Only 69 (10.4%) patients received preoperative treatment. Minimally invasive techniques were used in 444 (70.7%) patients and robotic-assisted esophagectomies were used in 130 (20.7%) patients. Complete resection (R0) was achieved in 90.3% of esophagectomy patients. The 5-year overall survival (OS) rate after esophagectomy was 52.5%. Conclusions: The 5-year OS of patients with esophageal cancer can reach 52.5% after surgical treatment in 2017 at SCH. The exact beneficiaries of neoadjuvant therapy are still unclear in the 2017 cohort.
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Granite, as the natural barrier for the disposal of high-level radioactive waste, plays an important role in ensuring environmental and public safety. The safety assessment of the repository depends on the reliable migration parameters of radionuclides in granite. In this study, we developed a kinetic adsorption-advection-dispersion model based on first-order adsorption kinetics. It introduces a first-order adsorption rate coefficient to describe the kinetics of adsorption process and accounts for other crucial mechanisms affecting the migration of radionuclide ions, namely, the electromigration, electroosmosis, and dispersion. This model is then applied to interpret the experimental results of electromigration of tracer ions in intact granite. The results show that for the weakly adsorbed radionuclides studied, iodide and selenite, the effective diffusion coefficients and formation factors calculated by this model are in constant with those derived from the classical advection-dispersion model based on linear adsorption equilibrium. By contrast, for the moderately or strongly adsorbed tracer ions studied, including cobalt, cesium, and strontium, the migration parameters calculated by this model exhibit significantly less uncertainty than those obtained from the advection-dispersion model simulations. The advection-dispersion model based on the first order adsorption kinetics introduces the first order adsorption rate coefficient, and considers the influence of electromigration, electroosmosis and dispersion mechanism, which helps to explain the migration mechanism of nuclide ions in intact granite more accurately.
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New dynamic, wireless and cost-effective analytical devices are developing rapidly in biochemical analysis. Here, we report on a remotely-controlled rotating electrochemiluminescence (ECL) sensing system for enzymatic detection of a model analyte, glucose, on both polarized sides of an iron wire acting as a bipolar electrode. The iron wire is controlled by double contactless mode, involving remote electric field polarization, and magnetic field-induced rotational motion. The former triggers the interfacial polarization of both extremities of the wire by bipolar electrochemistry, which generates ECL emission of the luminol derivative (L-012) with the enzymatically produced hydrogen peroxide in presence of glucose, at both anodic and cathodic poles, simultaneously. The latter generates a convective flow, leading to an increase in mass transfer and amplifying the corresponding ECL signals. Quantitative glucose detection in human serum samples is achieved. The ECL signals were found to be a linear function of the glucose concentration within the range of 10-1000 µM and with a limit of detection of 10 µM. The dynamic bipolar ECL system simultaneously generates light emissions at both anodic and cathodic poles for glucose detection, which can be further applied to biosensing and imaging in autonomous devices.
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Técnicas Eletroquímicas , Medições Luminescentes , Medições Luminescentes/métodos , Humanos , Técnicas Eletroquímicas/métodos , Técnicas Eletroquímicas/instrumentação , Eletrodos , Técnicas Biossensoriais/métodos , Técnicas Biossensoriais/instrumentação , Limite de Detecção , Glicemia/análise , Tecnologia sem Fio , Peróxido de Hidrogênio/química , Peróxido de Hidrogênio/análise , Glucose Oxidase/química , Glucose Oxidase/metabolismo , Luminol/químicaRESUMO
A three-dimensional (3D) self-assembled AuNPs/Ti3C2 MXene hydrogel (AuNPs/Ti3C2 MXH) nanocomposite was prepared for the fabrication of a novel microRNA-122 electrochemical biosensor. The 3D hydrogel structure was gelated from two-dimensional MXene nanosheets with the assistance of graphite oxide and ethylenediamine. MXene hydrogels supported the in situ formation of Au nanoparticles (AuNPs) that predominantly exploring the (111) facet, and these AuNPs are utilized as carriers for hairpin DNA (hpDNA) probes, facilitating DNA hybridization. MXene acted as both a reductant and stabilizer, significantly improving the electrochemical signal. In addition, the conjugation of PAMAM dendrimer-encapsulated AuNPs and H-DNA worked as an ideal bridge to connect targets and efficient electrochemical tags, providing a high amplification efficiency for the sensing of microRNA-122. A linear relationship between the peak currents and the logarithm of the concentrations of microRNA-122 from 1.0 × 10-2 to 1.0 × 102 fM (I = 1.642 + 0.312 lgc, R2 = 0.9891), is obtained. The detection limit is 0.8 × 10-2 fM (S/N = 3). The average recovery for human serum detection ranged from 97.32 to 101.4% (RSD < 5%).
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Nanopartículas Metálicas , MicroRNAs , Nitritos , Elementos de Transição , Humanos , Ouro/química , Nanopartículas Metálicas/química , Hidrogéis , Titânio/química , DNA/químicaRESUMO
It is necessary to explore new targets for the treatment of colon adenocarcinoma (COAD) according to the tumor microenvironment. The expression levels of JAML and CXADR were analyzed by bioinformatics analysis and validation of clinical samples. JAML over-expression CD8+ T cell line was constructed, and the proliferation activity was detected by MTT. The production of inflammatory factors was detected by ELISA. The expression of immune checkpoint PD-1 and TIM-3 was detected by Western blot. The apoptosis level was detected by flow cytometry and apoptosis markers. The AOM/DSS mouse model of colorectal cancer was constructed. The expression levels of JAML, CXADR and PD-1 were detected by PCR and Western blot, and the proportion of CD8+ T cells and exhausted T cells were detected by flow cytometry. The expression levels of JAML and CXADR were significantly decreased in colon cancer tissues. Overexpression of JAML can promote the proliferation of T cells, secrete a variety of inflammatory factors. Overexpression of CXADR can reduce the proliferation of colorectal cancer cells, promote apoptosis, and down-regulate the migration and invasion ability of tumor cells. Both JAML agonists and PD-L1 inhibitors can effectively treat colorectal cancer, and the combined use of JAML agonists and PD-L1 inhibitors can enhance the effect. JAML can promote the proliferation and toxicity of CD8+ T cells and down-regulate the expression of immune checkpoints in colon cancer. CXADR can inhibit the proliferation of cancer cells and promote the apoptosis. JAML agonist can effectively treat colorectal cancer by regulating CD8+ T cells.
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Carcinogênese , Neoplasias Colorretais , Microambiente Tumoral , Animais , Humanos , Masculino , Camundongos , Apoptose/efeitos dos fármacos , Antígeno B7-H1/metabolismo , Antígeno B7-H1/genética , Carcinogênese/efeitos dos fármacos , Carcinogênese/imunologia , Carcinogênese/genética , Linfócitos T CD8-Positivos/imunologia , Linfócitos T CD8-Positivos/efeitos dos fármacos , Moléculas de Adesão Celular/metabolismo , Moléculas de Adesão Celular/genética , Linhagem Celular Tumoral , Movimento Celular/efeitos dos fármacos , Proliferação de Células/efeitos dos fármacos , Neoplasias Colorretais/patologia , Neoplasias Colorretais/imunologia , Neoplasias Colorretais/genética , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Microambiente Tumoral/efeitos dos fármacos , Microambiente Tumoral/imunologiaRESUMO
Understanding the structure-performance relationships of a frustrated Lewis pair (FLP) at the atomic level is key to yielding high efficiency in activating chemically "inert" molecules into value-added products. A sound strategy was developed herein through incorporating oxygen defects into a Zr-based metal-organic layer (Zr-MOL-D) and employing Lewis basic proximal surface hydroxyls for the in situ formation of solid heterogeneous FLP (Zr4-δ-VO-Zr-OH). Zr-MOL-D exhibits a superior CO2 to CO conversion rate of 49.4 µmol g-1 h-1 in water vapor without any sacrificing agent or photosensitizer, which is about 12 times higher than that of pure MOL (Zr-MOL-P), with extreme stability even after being placed for half a year. Theoretical and experimental results reveal that the introduction of FLP converts the process of the crucial intermediate COOH* from an endothermic reaction to an exothermic spontaneous reaction. This work is expected to provide new prospects for developing efficient MOL-based photocatalysts in FLP chemistry through a sound defect-engineering strategy.
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OBJECTIVES: Severe pulmonary complications such as postoperative respiratory failure can occur after minimally invasive oesophagectomy. However, the risk factors have not been well identified. The goal of this study was to develop a predictive model for the occurrence of postoperative respiratory failure with a large sample. METHODS: We collected data from patients with oesophageal cancer who had a minimally invasive oesophagectomy at Shanghai Chest Hospital from 2019 to 2022. Univariable and backward stepwise logistic regression analysis of 19 pre- and intra-operative factors was used before model fitting, and its performance was evaluated with the receiver operating characteristic curve. Internal validation was assessed with a calibration plot, decision curve analysis and area under the curve with 95% confidence intervals, obtained from 1000 resamples set by the bootstrap method. RESULTS: This study enrolled 2,386 patients, 57 (2.4%) of whom developed postoperative respiratory failure. Backward stepwise logistic regression analysis revealed that age, body mass index, cardiovascular disease, diabetes, diffusion capacity of the lungs for carbon monoxide, tumour location and duration of chest surgery ≥101.5 min were predictive factors. A predictive model was constructed and showed acceptable performance (area under the curve: 0.755). The internal validation with the bootstrap method proves the good agreement for prediction and reality. CONCLUSIONS: Obesity, severe diffusion dysfunction and upper segment oesophageal cancer were strong predictive factors. The established predictive model has acceptable predictive validity for postoperative respiratory failure after minimally invasive oesophagectomy, which may improve the identification of high-risk patients and enable health-care professionals to perform risk assessment for postoperative respiratory failure at the initial consultation.
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Neoplasias Esofágicas , Insuficiência Respiratória , Humanos , Esofagectomia/efeitos adversos , Esofagectomia/métodos , Complicações Pós-Operatórias/epidemiologia , Complicações Pós-Operatórias/etiologia , Complicações Pós-Operatórias/cirurgia , China/epidemiologia , Neoplasias Esofágicas/complicações , Fatores de Risco , Insuficiência Respiratória/epidemiologia , Insuficiência Respiratória/etiologia , Estudos Retrospectivos , Procedimentos Cirúrgicos Minimamente Invasivos/métodosRESUMO
A growing body of literature underlines the fundamental role of gut microbiota in the occurrence, treatment, and prognosis of cancer. In particular, the activity of gut microbial metabolites (also known as postbiotics) against different cancer types has been recently reported in several studies. However, their in-depth molecular mechanisms of action and potential interactions with standard chemotherapeutic drugs remain to be fully understood. This research investigates the antiproliferative activities of postbiotics- short-chain fatty acid (SCFA) salts, specifically magnesium acetate (MgA), sodium propionate (NaP), and sodium butyrate (NaB), against the AGS gastric adenocarcinoma cells. Furthermore, the potential synergistic interactions between the most active SCFA salt-NaB and the standard drug dexamethasone (Dex) were explored using the combination index model. The molecular mechanisms of the synergy were investigated using reactive oxygen species (ROS), flow cytometry and biochemometric and liquid chromatography-mass spectrometry (LC-MS)-driven proteomics analyses. NaB exhibited the most significant inhibitory effect (p < 0.05) among the tested SCFA salts against the AGS gastric cancer cells. Additionally, Dex and NaB exhibited strong synergy at a 2:8 ratio (40 µg/mL Dex + 2,400 µg/mL NaB) with significantly greater inhibitory activity (p < 0.05) compared to the mono treatments against the AGS gastric cancer cells. MgA and NaP reduced ROS production, while NaB exhibited pro-oxidative properties. Dex displayed antioxidative effects, and the combination of Dex and NaB (2,8) demonstrated a unique pattern, potentially counteracting the pro-oxidative effects of NaB, highlighting an interaction. Dex and NaB individually and in combination (Dex:NaB 40:2400 µg/mL) induced significant changes in cell populations, suggesting a shift toward apoptosis (p < 0.0001). Analysis of dysregulated proteins in the AGS cells treated with the synergistic combination revealed notable downregulation of the oncogene TNS4, suggesting a potential mechanism for the observed antiproliferative effects. These findings propose the potential implementation of NaB as an adjuvant therapy with Dex. Further investigations into additional combination therapies, in-depth studies of the molecular mechanisms, and in vivo research will provide deeper insights into the use of these postbiotics in cancer, particularly in gastric malignancies.
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CircLRIG1, a newly discovered circRNA, has yet to have its potential function and biological processes reported. This study explored the role of circLRIG1 in the development and progression of bladder carcinoma and its potential molecular mechanisms. Techniques such as qRT-PCR, Western blot, various cellular assays, and in vivo models were used to investigate mRNA and protein levels, cell behavior, molecular interactions, and tumor growth. The results showed that both circLRIG1 and LRIG1 were significantly reduced in bladder carcinoma tissues and cell lines. Low circLRIG1 expression was associated with poor patient prognosis. Overexpressing circLRIG1 inhibited bladder carcinoma cell growth, migration, and invasion, promoted apoptosis, and decreased tumor growth and metastasis in vivo. Importantly, circLRIG1 was found to sponge miR-214-3p, enhancing LRIG1 expression, and its overexpression also modulated protein levels of E-cadherin, N-cadherin, Vimentin, and LRIG1. Similar effects were observed with LRIG1 overexpression. Notably, a positive correlation was found between circLRIG1 and LRIG1 expression in bladder carcinoma tissues. Additionally, the tumor-suppressing effect of circLRIG1 was reversed by overexpressing miR-214-3p or silencing LRIG1. The study concludes that circLRIG1 suppresses bladder carcinoma progression by enhancing LRIG1 expression via sponging miR-214-3p, providing a potential strategy for early diagnosis and treatment of bladder carcinoma.
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Carcinoma , MicroRNAs , Neoplasias da Bexiga Urinária , Humanos , MicroRNAs/genética , MicroRNAs/metabolismo , Bexiga Urinária/metabolismo , Bexiga Urinária/patologia , Linhagem Celular Tumoral , Proliferação de Células/genética , Neoplasias da Bexiga Urinária/genética , Neoplasias da Bexiga Urinária/metabolismo , Neoplasias da Bexiga Urinária/patologia , Carcinoma/genética , Movimento Celular , Regulação Neoplásica da Expressão Gênica , Glicoproteínas de Membrana/metabolismoRESUMO
Neural architecture search (NAS) has shown great promise in automatically designing neural network models. Recently, block-wise NAS has been proposed to alleviate deep coupling problem between architectures and weights existed in the well-known weight-sharing NAS, by training the huge weight-sharing supernet block-wisely. However, the existing block-wise NAS methods, which resort to either supervised distillation or self-supervised contrastive learning scheme to enable block-wise optimization, take massive computational cost. To be specific, the former introduces an external high-capacity teacher model, while the latter involves supernet-scale momentum model and requires a long training schedule. Considering this, in this work, we propose a resource-friendly deeply supervised block-wise NAS (DBNAS) method. In the proposed DBNAS, we construct a lightweight deeply-supervised module after each block to enable a simple supervised learning scheme and leverage ground-truth labels to indirectly supervise optimization of each block progressively. Besides, the deeply-supervised module is specifically designed as structural and functional condensation of the supernet, which establishes global awareness for progressive block-wise optimization and helps search for promising architectures. Experimental results show that the DBNAS method only takes less than 1 GPU day to search out promising architectures on the ImageNet dataset with less GPU memory footprint than the other block-wise NAS works. The best-performing model among the searched DBNAS family achieves 75.6% Top-1 accuracy on ImageNet, which is competitive with the state-of-the-art NAS models. Moreover, our DBNAS family models also achieve good transfer performance on CIFAR-10/100, as well as two downstream tasks: object detection and semantic segmentation.
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Lung adenocarcinoma (LUAD) is the most commonly diagnosed subtype of lung cancer worldwide. Inhibitor of growth 3 (ING3) serves as a tumor suppressor in many cancers. This study aimed to elucidate the role of ING3 in the progression of LUAD and investigate the underlying mechanism related to integrin ß4 (ITGB4) and Src/focal adhesion kinase (FAK) signaling. ING3 expression in LUAD tissues and the correlation between ING3 expression and prognosis were analyzed by bioinformatics databases. After evaluating ING3 expression in LUAD cells, ING3 was overexpressed to assess the proliferation, cell cycle arrest, migration and invasion of LUAD cells. Then, ITGB4 was upregulated to observe the changes of malignant activities in ING3-overexpressed LUAD cells. The transplantation tumor model of NCI-H1975 cells in nude mice was established to analyze the antineoplastic effect of ING3 upregulation in vivo. Downregulated ING3 expression was observed in LUAD tissues and cells and lower ING3 expression predicated the poor prognosis. ING3 upregulation restrained the proliferation, migration, invasion and induced the cell cycle arrest of NCI-H1975 cells. Additionally, ITGB4 expression was negatively correlated with ING3 expression in LUAD tissue. ING3 led to reduced expression of ITGB4, Src and p-FAK. Moreover, ITGB4 overexpression alleviated the effects of ING3 upregulation on the malignant biological properties of LUAD cells. It could be also found that ING3 upregulation limited the tumor volume, decreased the expression of ITGB4, Src and p-FAK, which was restored by ITGB4 overexpression. Collectively, ING3 inhibited the malignant progression of LUAD by negatively regulating ITGB4 expression to inactivate Src/FAK signaling.