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In recent years, there has been a significant increase in the prevalence of electronic wearables, among which flexible magnetoelectronic skin has emerged as a key component. This technology is part of the rapidly progressing field of flexible wearable electronics, which has facilitated a new human perceptual development known as the magnetic sense. However, the magnetoelectronic skin is limited due to its low sensitivity and substantial field limitations as a wearable electronic device for sensing minor magnetic fields. Additionally, achieving efficient and non-destructive delamination in flexible magnetic sensors remains a significant challenge, hindering their development. In this study, we demonstrate a novel magnetoelectronic touchless interactive device that utilizes a flexible giant magnetoresistive sensor array. The flexible magnetic sensor array was developed through an electrochemical delamination process, and the resultant ultra-thin flexible electronic system possessed both ultra-thin and non-destructive characteristics. The flexible magnetic sensor is capable of achieving a bending angle of up to 90 degrees, maintaining its performance integrity even after multiple repetitive bending cycles. Our study also provides demonstrations of non-contact interaction and pressure sensing. This research is anticipated to significantly contribute to the advancement of high-performance flexible magnetic sensors and catalyze the development of more sophisticated magnetic electronic skins.
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The high mortality rate of esophageal squamous cell carcinoma (ESCC) is exacerbated by the absence of early diagnostic markers. The pronounced heterogeneity of mutations in ESCC renders copy number alterations (CNAs) more prevalent among patients. The identification of CNA genes within esophageal squamous dysplasia (ESD), a precancerous stage of ESCC, is crucial for advancing early detection efforts. Utilization of liquid biopsies via droplet-based digital PCR (ddPCR) offers a novel strategy for detecting incipient tumor traces. This study undertook a thorough investigation of CNA profiles across ESCC development stages, integrating data from existing databases and prior investigations to pinpoint and confirm CNA markers conducive to early detection of ESCC. Targeted sequencing was employed to select potential early detection genes, followed by the establishment of prediction models for ESCC early detection using ddPCR. Our analysis reveals widespread CNAs during the ESD stage, mirroring the CNA landscape observed in ESCC. A total of 40 CNA genes were identified as highly frequent in both ESCC and ESD lesions, through a comprehensive gene-level CNA analysis encompassing ESD and ESCC tissues, ESCC cell lines, and pan-cancer datasets. Subsequent validation of five candidate markers via ddPCR underscored the efficacy of combined predictive models-encompassing PIK3CA, SOX2, EGFR, MYC, and CCND1-in early ESCC screening, as evidenced by the area under the curve (AUC) values exceeding 0.92 (p<0.0001) across various detection contexts. The findings highlight the significant utility of CNA genes in the early screening of ESCC, presenting robust models that could facilitate early detection, broad-scale population screening, and adjunctive diagnosis.
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ß-Lactoglobulin (ßLG) is a major allergen in bovine milk protein. This study was designed to investigate changes in ßLG structure, digestibility, and allergenicity induced by covalent binding modification with different contents of (-)-epigallocatechin 3-gallate (EGCG). The reaction of EGCG conjugation with ßLG reached saturation at a molar ratio of 1:60 ßLG:EGCG. Conjugation with EGCG altered the ßLG structure, decreased IgE-binding capacity, and increased digestibility in a dose-dependent manner. In vivo studies showed that covalent conjugation with EGCG can reduce ßLG-induced allergic symptoms with reducing levels of IgE, histamine, and mast cell protease-1 (mMCP-1) and the percentage of sensitized mast cells. Allergenicity was reduced more effectively in saturated ßLG-EGCG conjugates compared to semisaturated conjugates. Observed changes in IFN-γ, IL-4, IL-5, IL-10, and TGF-ß levels suggested that ßLG-EGCG conjugates were able to promote Th1/Th2 immune balance. These findings further our understanding of the relationship between the degree of polyphenol conjugation and the allergenicity of food allergens.
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Alérgenos , Catequina , Inmunoglobulina E , Lactoglobulinas , Lactoglobulinas/química , Lactoglobulinas/inmunología , Catequina/análogos & derivados , Catequina/química , Catequina/inmunología , Animales , Alérgenos/inmunología , Alérgenos/química , Bovinos , Inmunoglobulina E/inmunología , Humanos , Ratones , Hipersensibilidad a la Leche/inmunología , Hipersensibilidad a la Leche/prevención & control , Ratones Endogámicos BALB C , Femenino , Interferón gamma/inmunología , Interferón gamma/metabolismo , Quimasas/química , Quimasas/inmunología , Quimasas/metabolismo , Células Th2/inmunología , Células Th2/efectos de los fármacos , Interleucina-5/inmunología , Interleucina-10/inmunología , Interleucina-10/metabolismo , Interleucina-4/inmunología , Interleucina-4/metabolismo , Mastocitos/inmunología , Mastocitos/efectos de los fármacosRESUMEN
Tomatoes, widely cherished for their high nutritional value, necessitate precise ripeness identification and selective harvesting of mature fruits to significantly enhance the efficiency and economic benefits of tomato harvesting management. Previous studies on intelligent harvesting often focused solely on identifying tomatoes as the target, lacking fine-grained detection of tomato ripeness. This deficiency leads to the inadvertent harvesting of immature and rotten fruits, resulting in economic losses. Moreover, in natural settings, uneven illumination, occlusion by leaves, and fruit overlap hinder the precise assessment of tomato ripeness by robotic systems. Simultaneously, the demand for high accuracy and rapid response in tomato ripeness detection is compounded by the need for making the model lightweight to mitigate hardware costs. This study proposes a lightweight model named PDSI-RTDETR to address these challenges. Initially, the PConv_Block module, integrating partial convolution with residual blocks, replaces the Basic_Block structure in the legacy backbone to alleviate computing load and enhance feature extraction efficiency. Subsequently, a deformable attention module is amalgamated with intra-scale feature interaction structure, bolstering the capability to extract detailed features for fine-grained classification. Additionally, the proposed slimneck-SSFF feature fusion structure, merging the Scale Sequence Feature Fusion framework with a slim-neck design utilizing GSConv and VoVGSCSP modules, aims to reduce volume of computation and inference latency. Lastly, by amalgamating Inner-IoU with EIoU to formulate Inner-EIoU, replacing the original GIoU to expedite convergence while utilizing auxiliary frames enhances small object detection capabilities. Comprehensive assessments validate that the PDSI-RTDETR model achieves an average precision mAP50 of 86.8%, marking a 3.9% enhancement over the original RT-DETR model, and a 38.7% increase in FPS. Furthermore, the GFLOPs of PDSI-RTDETR have been diminished by 17.6%. Surpassing the baseline RT-DETR and other prevalent methods regarding precision and speed, it unveils its considerable potential for detecting tomato ripeness. When applied to intelligent harvesting robots in the future, this approach can improve the quality of tomato harvesting by reducing the collection of immature and spoiled fruits.
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Silkworm (Bombyx mori) pupae are popular edible insects with high nutritional and therapeutic value. Currently, there is growing interest in the comprehensive application of silkworm pupae. In this study, peptides that exhibited anti-photoaging activity were obtained from silkworm pupae protein, aiming to investigate the protective effects and potential mechanisms of silkworm pupae peptides (SPPs) on skin photoaging. The results showed that SPPs were composed of 900 short peptides and could effectively alleviate skin photoaging progression. They significantly eliminated excessive production of ROS and MDA; meanwhile, they also renovated the antioxidant enzyme activities. The biomarkers related to collagen synthesis and degradation, including hydroxyproline, interstitial collagenase, and gelatinase, demonstrated that SPPs could suppress collagen degradation. Histopathological results showed that SPPs could reduce the inflammatory infiltrate and the thickness of the dermis and epidermis, as well as increase the collagen bundles and muscle fibers. The histopathological and biochemical results confirmed that SPPs could alleviate photoaging by inhibiting abnormal skin changes, reducing oxidative stress, and immune suppression. Overall, these data prove the protective effects of SPPs against the photoaging process, suggesting their potential as an active ingredient in skin photoaging prevention and therapy.
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Multi-modal attention mechanisms have been successfully used in multi-modal graph learning for various tasks. However, existing attention-based multi-modal graph learning (AMGL) architectures heavily rely on manual design, requiring huge effort and expert experience. Meanwhile, graph neural architecture search (GNAS) has made great progress toward automatically designing graph-based learning architectures. However, it is challenging to directly adopt existing GNAS methods to search for better AMGL architectures because of the search spaces that only focus on designing graph neural network architectures and the search objective that ignores multi-modal interactive information between modalities and long-term content dependencies within different modalities. To address these issues, we propose an automated attention-based multi-modal graph learning architecture search (AutoAMS) framework, which can automatically design the optimal AMGL architectures for different multi-modal tasks. Specifically, we design an effective attention-based multi-modal (AM) search space consisting of four sub-spaces, which can jointly support the automatic search of multi-modal attention representation and other components of multi-modal graph learning architecture. In addition, a novel search objective based on an unsupervised multi-modal reconstruction loss and task-specific loss is introduced to search and train AMGL architectures. The search objective can extract the global features and capture multi-modal interactions from multiple modalities. The experimental results on multi-modal tasks show strong evidence that AutoAMS is capable of designing high-performance AMGL architectures.
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Objective: To explore the active substances and targets of Danbie Capsules in Endometriosis therapy. Methods: This study was conducted through TCMSP and published literature screened and obtained 183 active substances of Danbie Capsules, combined and intersected with Endometriosis target genes collected and screened in the GEO database, obtained 24 target genes for Endometriosis treatment, and mapped the target network map of Danbie Capsules active substances against Endometriosis. The network was analyzed with the aid of Cytoscape version 3.9.1. With the aid of the platform of the STRING data analysis, PPI network analysis was conducted on 24 anti-Endometriosis targets of the Danbie Capsules. Results: The research results obtained three critical active substances, namely, Quercetin, ß-sitosterol, and Luteolin. Seven critical targets were identified, and two representative genes (TP53 and AKT1) have been verified in Macromolecular docking and immunohistochemical verification. Conclusion: The active substances of Danbie Capsules in the treatment of Endometriosis are Quercetin, ß-sitosterol and Luteolin, and the main targets are TP53 and AKT1.
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[This corrects the article DOI: 10.1038/s41378-022-00478-9.].
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OBJECTIVES: This study was designed to explore and validate the value of different machine learning models based on ultrasound image-omics features in the preoperative diagnosis of lymph node metastasis in pancreatic cancer (PC). METHODS: This research involved 189 individuals diagnosed with PC confirmed by surgical pathology (training cohort: n = 151; test cohort: n = 38), including 50 cases of lymph node metastasis. Image-omics features were extracted from ultrasound images. After dimensionality reduction and screening, eight machine learning algorithms, including logistic regression (LR), support vector machine (SVM), K-nearest neighbors (KNN), random forest (RF), extra trees (ET), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and multilayer perceptron (MLP), were used to establish image-omics models to predict lymph node metastasis in PC. The best omics prediction model was selected through ROC curve analysis. Machine learning models were used to analyze clinical features and determine variables to establish a clinical model. A combined model was constructed by combining ultrasound image-omics and clinical features. Decision curve analysis (DCA) and a nomogram were used to evaluate the clinical application value of the model. RESULTS: A total of 1561 image-omics features were extracted from ultrasound images. 15 valuable image-omics features were determined by regularization, dimension reduction, and algorithm selection. In the image-omics model, the LR model showed higher prediction efficiency and robustness, with an area under the ROC curve (AUC) of 0.773 in the training set and an AUC of 0.850 in the test set. The clinical model constructed by the boundary of lesions in ultrasound images and the clinical feature CA199 (AUC = 0.875). The combined model had the best prediction performance, with an AUC of 0.872 in the training set and 0.918 in the test set. The combined model showed better clinical benefit according to DCA, and the nomogram score provided clinical prediction solutions. CONCLUSION: The combined model established with clinical features has good diagnostic ability and can be used to predict lymph node metastasis in patients with PC. It is expected to provide an effective noninvasive method for clinical decision-making, thereby improving the diagnosis and treatment of PC.
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Metástasis Linfática , Aprendizaje Automático , Neoplasias Pancreáticas , Ultrasonografía , Humanos , Neoplasias Pancreáticas/diagnóstico por imagen , Neoplasias Pancreáticas/patología , Metástasis Linfática/diagnóstico por imagen , Masculino , Persona de Mediana Edad , Femenino , Anciano , Procesamiento de Imagen Asistido por Computador/métodos , AdultoRESUMEN
Ferromagnetic pipes are widely used in the oil and gas industry. They are subject to cracks due to corrosion, pressure, and fatigue. It is significant to detect cracks for the safety of pipes. A residual magnetic field testing (RMFT) system is developed for crack detection in ferromagnetic pipes. Based on this background, a detection probe based on an array of tunneling magneto-resistive (TMR) sensors and permanent magnets is exploited. The probe is able to partially magnetize the pipe wall and collect magnetic signals simultaneously. First, a theoretical analysis of RMFT is presented. The physics principle of RMFT is introduced, and a finite element model is built. In the finite element simulations, the effects of the crack length and depth on the RMFT signal are analyzed, and the signal characteristics are selected to represent the crack size. Next, the validated experiments are conducted to demonstrate the feasibility of the proposed RMFT method in this paper.
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Due to their compact size and exceptional sensitivity at room temperature, magnetoresistance (MR) sensors have garnered considerable interest in numerous fields, particularly in the detection of weak magnetic signals in biological systems. The "magnetrodes", integrating MR sensors with needle-shaped Si-based substrates, are designed to be inserted into the brain for local magnetic field detection. Although recent research has predominantly focused on giant magnetoresistance (GMR) sensors, tunnel magnetoresistance (TMR) sensors exhibit a significantly higher sensitivity. In this study, we introduce TMR-based magnetrodes featuring TMR sensors at both the tip and midsection of the probe, enabling detection of local magnetic fields at varied spatial positions. To enhance detectivity, we designed and fabricated magnetrodes with varied aspect ratios of the free layer, incorporating diverse junction shapes, quantities, and serial arrangements. Utilizing a custom-built magnetotransport and noise measurement system for characterization, our TMR-based magnetrode demonstrates a limit of detection (LOD) of 300pT/Hz at 1 kHz. This implies that neuronal spikes can be distinguished with minimal averaging, thereby facilitating the elucidation of their magnetic properties.
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TAT, a widely used treatment for HCC, can exacerbate the progression of residual HCC. The present study investigated the mechanism of action of PLK1 following ITA of HCC. The PLK1 levels in HCC were determined using qRT-PCR from clinical patient samples, IHC from tissue microarray, and data from globally high-throughput data and microarrays. The PLK1 levels and their effect on the biological phenotype of heat-stress HCC cells were evaluated through in vitro experiments. We detected PLK1 abnormal expression in HCC models of nude mice subjected to ITA. We detected the effects of different PLK1 expression levels on EMT pathway proteins. PLK1 exhibited an overexpression in HCC tissues with an SMD of 1.19 (3414 HCC and 3036 non-HCC tissues were included), distinguishing HCC from non-HCC effectively (AUC = 0.9). The qRT-PCR data from clinical HCC patient samples and IHC from HCC tissue microarray results also indicated an overexpressed level. In the incomplete ablation models, an increased PLK1 expression was found in both heat-stress cells and subcutaneous tumors. The upregulation of PLK1 following ITA was found to enhance the malignancy of HCC and exacerbate the proliferation, migration, and invasion of residual HCC cells, whereas PLK1 knockdown suppressed the biological malignancy of HCC cells. Meanwhile, PLK1 has different regulatory effects on various EMT pathway proteins. PLK1 promotes the progression of residual HCC by activating EMT pathway after ITA, which might provide a novel idea for the treatment and prognosis of residual HCC.
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BACKGROUND: Multimorbidity, individuals suffering from two or more chronic diseases, has become a major health challenge worldwide, especially in populous and prosperous cities, where studies of this phenomenon in China are limited. We examined the prevalence, trends, patterns, and associated factors of multimorbidity from 2009 to 2018 among community-dwelling adults in Guangzhou, China. METHODS: We conducted serial cross-sectional surveys for chronic diseases in Guangzhou, China, in 2009, 2013, and 2018. General and stratified prevalence were standardized using demographic data. Multivariable logistic regression and hierarchical cluster analysis were applied to identify associated factors and to assess the correlations and patterns of multimorbidity, respectively. RESULTS: This study included 23,284 adults aged 18 and over in 2009, 18,551 in 2013, and 15,727 in 2018. The standardized prevalence of multimorbidity increased substantially, with 12.69% (95% CI: 10.45-15.33) in 2009, 25.44% (95% CI: 23.47-27.52) in 2013, and 35.13% (95% CI:32.64-37.70) in 2018 (P for trend <0.001). The highest bi- and triple-conditions of multimorbidity were dyslipidemia (DP) and overweight or obesity (OO) (12.54%, 95% CI: 11.68-13.46), and DP, OO, and Hypertension (HT) (3.99%, 95% CI: 3.47-4.58) in 2018. From 2009 to 2018, (1) The majority of multimorbidity patterns showed a high prevalence; (2) The percentage of participants with only one chronic condition was found lower, while the percentage with multiple conditions was higher. CONCLUSIONS: The prevalence of chronic disease multimorbidity in Guangzhou China, has increased substantially among adults. Effective policies targeting multimorbidity are urgently needed, especially for the health management of primary medical institutions.
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Multimorbilidad , Humanos , China/epidemiología , Estudios Transversales , Multimorbilidad/tendencias , Masculino , Femenino , Persona de Mediana Edad , Prevalencia , Adulto , Enfermedad Crónica/epidemiología , Anciano , Adulto Joven , AdolescenteRESUMEN
Glutathione (GSH) is an important antioxidant that maintains cellular redox homeostasis and significantly contributes to resistance against various chemotherapeutic agents. To address the challenge of GSH-mediated drug resistance in etoposide (ETS), we developed a facile synthetic method to prepare a biocompatible acid-responsive polycarbonate (PEG-PCA) containing cinnamaldehyde (CA), a potent GSH-depleting agent, as a side chain using nontoxic raw materials. This polymer self-assembled in aqueous solutions to form nanoparticles (ETS@PCA) that encapsulated ETS, enhancing its water solubility and enabling tumor-targeted delivery. In vitro studies demonstrated that ETS@PCA could respond to the acidic tumor microenvironment, releasing CA to rapidly deplete GSH levels. Consequently, ETS@PCA exhibited superior cytotoxicity compared to free ETS. Furthermore, in vivo experiments corroborated the enhanced tumor inhibitory effects of ETS@PCA.
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BACKGROUND: This study aimed to examine the prevalence and associated factors of malnutrition in older community-dwellers and explore the interaction between associated factors. METHODS: A total of 474,467 older community-dwellers aged 65 or above were selected in Guangzhou, China. We used a two-step methodology to detect the associated factors of malnutrition and constructed logistic regression models to explore the influencing factors and interactive effects on three patterns of malnutrition. RESULTS: The prevalence of malnutrition was 22.28%. Older adults with both hypertension and diabetes (RERI = 0.13), both meat or fish diet and hypertension (RERI = 0.79), and both meat or fish diet and diabetes (RERI = 0.81) had positive additive interaction effects on the risk of obesity, whereas those on a vegetarian diet with hypertension (RERI = -0.25) or diabetes (RERI = -0.19) had negative additive interaction effects. Moreover, the interactions of physical activity with a meat or fish diet (RERI = -0.84) or dyslipidemia (RERI = -0.09) could lower the risk of obesity. CONCLUSIONS: Malnutrition was influenced by different health factors, and there were interactions between these influencing factors. Pertinent dietary instruction should be given according to different nutritional status indexes and the prevalence of metabolic diseases to avoid the occurrences of malnutrition among older adults.
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Minería de Datos , Hipertensión , Desnutrición , Humanos , Anciano , China/epidemiología , Masculino , Femenino , Desnutrición/epidemiología , Prevalencia , Hipertensión/epidemiología , Factores de Riesgo , Anciano de 80 o más Años , Vida Independiente , Estado Nutricional , Diabetes Mellitus/epidemiología , Obesidad/epidemiología , Dieta , Ejercicio Físico , Modelos Logísticos , Dislipidemias/epidemiologíaRESUMEN
Characterization studies of the plant metabolome are crucial for revealing plant physiology, developing functional foods, and controlling quality. Mass spectrometry-based metabolite profiling allows unprecedented qualitative coverage of complex biological extract composition. However, the electrospray ionization used in metabolite profiling generates multiple artifactual signals for a single analyte, which makes it challenging to filter out redundant signals and organize the signals corresponding to abundant constituents. This study proposed a strategy integrating in-source fragments elimination, diagnostic ions recognition, and feature-based molecular networking (ISFE-DIR-FBMN) to simultaneously characterize cycloartane triterpenoids (CTs) from three medicinal Cimicifuga species. The results showed that 63.1 % of the measured ions were redundant. A total of 184 CTs were annotated, with 27.1 % being reported for the first time. It presents a promising approach to assess the composition of natural extracts, thus facilitating new ingredient registrations or natural-extracts-based drug discovery campaigns. Besides, chemometrics analysis of the three Cimicifuga species identified 32 species-specific markers, highlighting significant differences among them. The valuable information can enhance the sustainable utilization and further development of Cimicifuga resources. The codes involved in ISFE-DIR-FBMN are freely available on GitHub (https://github.com/LHJ-Group/ISFE-DIR-FBMN.git).
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Cimicifuga , Extractos Vegetales , Triterpenos , Triterpenos/análisis , Triterpenos/química , Cimicifuga/química , Extractos Vegetales/química , Extractos Vegetales/análisis , Especificidad de la Especie , Biomarcadores/análisis , Espectrometría de Masa por Ionización de Electrospray/métodos , Metaboloma , Cromatografía Líquida de Alta Presión/métodosRESUMEN
Although chlorambucil (CHL) is a long-established anticancer drug, the drug failure of CHL, mediated by the intracellular defense system consisting of glutathione (GSH) and GSH S-transferase pi (GST-pi), has significantly limited the application of CHL. To overcome this issue, we first designed a GSH-responsive small-molecule prodrug (EA-SS-CHL) by combining CHL and ethacrynic acid (EA). Subsequently, drug-loaded nanoparticles (ECPP) were formed by the self-assembly between EA-SS-CHL and amphiphilic PEG-PDLLA to improve the water solubility of the prodrug and its ability to target tumor sites. Upon exposure to high intracellular GSH concentration, EA-SS-CHL gradually degrades, leading to the release of EA and CHL. The presence of EA facilitates the depletion of GSH and inhibition of GST-pi, ultimately attenuating the detoxification of the intracellular defense system to CHL. Cytotoxicity studies and apoptosis assays demonstrate that ECPP exhibits higher therapeutic efficiency than CHL. Additionally,in vivotumor suppression effects and biocompatibility provide further evidence for the superiority of ECPP. This work presents a promising strategy to enhance the efficacy of CHL in cancer therapy.
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Clorambucilo , Ácido Etacrínico , Glutatión , Micelas , Profármacos , Clorambucilo/farmacología , Clorambucilo/química , Profármacos/farmacología , Profármacos/química , Glutatión/metabolismo , Humanos , Animales , Ácido Etacrínico/farmacología , Ácido Etacrínico/química , Nanopartículas/química , Ratones , Gutatión-S-Transferasa pi/metabolismo , Gutatión-S-Transferasa pi/antagonistas & inhibidores , Apoptosis/efectos de los fármacos , Línea Celular Tumoral , Antineoplásicos/farmacología , Antineoplásicos/química , Polietilenglicoles/química , Glutatión Transferasa/metabolismo , Portadores de Fármacos/química , Liberación de FármacosRESUMEN
OBJECTIVE: Incomplete thermal ablation (ITA) fosters the malignancy of residual cells in Hepatocellular carcinoma (HCC) with unclear mechanisms now. This study aims to investigate the expression changes of NDST2 following ITA of HCC and its impact on residual cancer cells. METHODS: An in vitro model of heat stress-induced liver cancer was constructed to measure the expression of NDST2 using Quantitative Real-Time PCR and Western blotting experiments. The sequencing data from nude mice were used for validation. The clinical significance of NDST2 in HCC was evaluated by integrating datasets. Gene ontology and pathway analysis were conducted to explore the potential signaling pathways regulated by NDST2. Additionally, NDST2 was knocked down in heat stress-induced HCC cells, and the effects of NDST2 on these cells were verified using Cell Counting Kit-8 assays, scratch assays, and Transwell assays. RESULTS: NDST2 expression levels are elevated in HCC, leading to a decrease in overall survival rates of HCC patients. Upregulation of immune checkpoint levels in high NDST2-expressing HCC may contribute to immune evasion by liver cancer cells. Additionally, the low mutation rate of NDST2 in HCC suggests a relatively stable expression of NDST2 in this disease. Importantly, animal and cell models treated with ITA demonstrate upregulated expression of NDST2. Knockdown of NDST2 in heat stress-induced liver cancer cells results in growth inhibition associated with gene downregulation. CONCLUSION: The upregulation of NDST2 can accelerate the progression of residual HCC after ITA, suggesting a potential role for NDST2 in the therapeutic efficacy and prognosis of residual HCC.
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Amidohidrolasas , Carcinoma Hepatocelular , Hipertermia Inducida , Neoplasias Hepáticas , Animales , Humanos , Ratones , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/metabolismo , Carcinoma Hepatocelular/terapia , Línea Celular Tumoral , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/metabolismo , Neoplasias Hepáticas/terapia , Ratones Desnudos , Amidohidrolasas/genética , Amidohidrolasas/metabolismo , Sulfotransferasas/genética , Sulfotransferasas/metabolismoRESUMEN
Background: Cardiometabolic multimorbidity (CMM) has emerged as a prominent public health concern. Hypertensive patients are prone to develop comorbidities. Moreover, the accumulation of visceral adipose tissue is the main cause for the development of cardiometabolic diseases. The cardiometabolic index (CMI), lipid accumulation product (LAP), visceral adiposity index (VAI), and Chinese visceral adiposity index (CVAI) not only assess adipose tissue mass but also reflect adipose tissue dysfunction. So far, no study has been reported to evaluate the association of CMI, LAP, VAI, and CVAI with CMM risk in hypertensive patients. Therefore, this study aimed to assess the association between these adiposity indicators and the risk of CMM among Chinese hypertensive patients. Methods: In this cross-sectional study, a total of 229,287 hypertensive patients aged 35 years and older were included from the National Basic Public Health Service Project. All participants underwent a face-to-face questionnaire survey, physical examination, and the collection of fasting venous blood samples. Multivariable logistic regression models were performed to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Receiver operating characteristic curve was utilized to evaluate the identification ability for CMM. Results: After adjusting for confounders, each 1-standard deviation increase in CMI, LAP, VAI, and CVAI was associated with a 14%, 8%, 12%, and 54% increased risk of CMM, respectively. When comparing the highest quartile of these indicators with the lowest quartile, individuals in the highest quartile of CMM, LAP, VAI, and CVAI had a 1.39-fold (95% CI 1.30, 1.48), 1.28-fold (95% CI 1.19, 1.37), 1.37-fold (95% CI 1.29, 1.46), and 2.56-fold (95% CI 2.34, 2.79) increased risk of CMM after adjusting for potential confounders. Notably, a nonlinear association was observed for CMI, LAP, and VAI with the risk of CMM (all P nonlinearity < 0.001). CVAI exhibited the highest area under the receiver operating characteristic curve (AUC) among all the included adiposity indices in this analysis. Conclusion: This study indicated the significant positive association of CMI, LAP, VAI, and CVAI with the risk of CMM in hypertensive patients. Among these indicators, CVAI demonstrated the most robust performance in predicting CMM risk and may serve as a valuable tool for identifying CMM risk in Chinese hypertensive patients.
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Adiposidad , Hipertensión , Humanos , Estudios Transversales , Multimorbilidad , Índice de Masa Corporal , Obesidad , Hipertensión/epidemiología , Obesidad AbdominalRESUMEN
Electro-optic modulation devices are essential components in the field of integrated optical chips. High-speed, low-loss electro-optic modulation devices represent a key focus for future developments in integrated optical chip technology, and they have seen significant advancements in both commercial and laboratory settings in recent years. Current electro-optic modulation devices typically employ architectures based on thin-film lithium niobate (TFLN), traveling-wave electrodes, and impedance-matching layers, which still suffer from transmission losses and overall design limitations. In this paper, we demonstrate a lithium niobate electro-optic modulation device based on bound states in the continuum, featuring a non-overlay structure. This device exhibits a transmission loss of approximately 1.3 dB/cm, a modulation bandwidth of up to 9.2 GHz, and a minimum half-wave voltage of only 3.3 V.