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Background: This study aims to investigate the efficacy of multifactorial MRI in diagnosing breast cancer, specifically in the context of predicting lymphovascular invasion (LVI).Materials & methods: The patients were stratified into two groups: the primary group (100 patients) and the validation group (100 patients), based on essential characteristics. Multifactorial MRI, encompassing tumor size evaluation, diffusion coefficient assessment and dynamic contrast enhancement, was employed for patient examination.Results: Statistically significant differences were observed in tumor size, diffusion coefficient and dynamic contrast enhancement between groups with LVI (LVI+) and those without (LVI-). Key parameters were identified for predicting the degree of invasion.Conclusion: The results affirm the effectiveness of multifactorial MRI in forecasting LVI.

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As one of the most widely used pesticides in the global fungicide market, tebuconazole has become heavily embedded in soil along with antibiotic resistance genes (ARGs). However, it remains unclear whether the selective pressure produced by tebuconazole affects ARGs and their horizontal transfer. In this experiment, we simulated a tebuconazole-contaminated soil ecosystem and observed changes in the abundance of ARGs and mobile genetic element (MGEs) due to tebuconazole exposure. We also established a plasmid RP4-mediated conjugative transfer system to investigate in depth the impact of tebuconazole on the horizontal transfer of ARGs and its mechanism of action. The results showed that under tebuconazole treatment at concentrations ranging from 0 to 10 mg/L, there was a gradual increase in the frequency of plasmid conjugative transfer, peaking at 10 mg/L which was 7.93 times higher than that of the control group, significantly promoting horizontal transfer of ARGs. Further analysis revealed that the conjugative transfer system under tebuconazole stress exhibited strong ability to form biofilm, and the conjugative transfer frequency ratio of biofilm to planktonic bacteria varied with the growth cycle of biofilm. Additionally, scanning electron microscopy and flow cytometry demonstrated increased cell membrane permeability in both donor and recipient bacteria under tebuconazole stress, accompanied by upregulation of ompA gene expression controlling cell membrane permeability. Furthermore, enzyme activity assays indicated significant increases in CAT, SOD activity, and GSH content in recipient bacteria under tebuconazole stress. Moreover, expression levels of transmembrane transporter gene trfAp as well as genes involved in oxidative stress and SOS response were found to be correlated with the frequency of plasmid conjugative transfer.

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Background: Autophagy plays important roles in cancer progression and therapeutic resistance, and the autophagy underlying the tumor pathogenesis and further mechanisms of chemoresistance emergence remains unknown. Methods: In this study, via the single-sample gene set enrichment analysis (ssGSEA) method, an autophagy 45-gene list was identified to evaluate samples' autophagy activity, verified through six GEO datasets with a confirmed autophagy phenotype. It was further utilized to distinguish tumors into autophagy score-high and score-low subtypes, and analyze their transcriptome landscapes, including survival analysis, correlation analysis of autophagy- and resistance-related genes, biological functional enrichment, and immune- and hypoxia-related and genomic heterogeneity comparison, in TCGA pan-cancer datasets. Furthermore, we performed an analysis of autophagy status in breast cancer chemoresistance combined with multiple GEO datasets and in vitro experiments to validate the mechanisms of potential anticancer drugs for reversing chemoresistance, including CCK-8 cell viability assays, RT-qPCR, and immunofluorescence. Results: The 45-gene list was used to identify autophagy score-high and score-low subtypes and further analyze their multi-dimensional features. We demonstrated that cancer autophagy status correlated with significantly different prognoses, molecular alterations, biological process activations, immunocyte infiltrations, hypoxia statuses, and specific mutational processes. The autophagy score-low subtype displayed a more favorable prognosis compared with the score-high subtype, associated with their immune-activated features, manifested as high immunocyte infiltration, including high CD8+T, Tfh, Treg, NK cells, and tumor-associated macrophages M1/M2. The autophagy score-low subtype also showed a high hypoxia score, and hypoxic tumors showed a significantly differential prognosis in different autophagy statuses. Therefore, "double-edged" cell fates triggered by autophagy might be closely correlated with the immune microenvironment and hypoxia induction. Results demonstrated that dysregulated autophagy was involved in many cancers and their therapeutic resistance and that the autophagy was induced by the resistance-reversing drug response, in five breast cancer GEO datasets and validated by in vitro experiments. In vitro, dihydroartemisinin and artesunate could reverse breast cancer doxorubicin resistance, through inducing autophagy via upregulating LC3B and ATG7. Conclusion: Our study provided a comprehensive landscape of the autophagy-related molecular and tumor microenvironment patterns for cancer progression and resistance, and highlighted the promising potential of drug-induced autophagy in the activation of drug sensitivity and reversal of resistance.

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[This corrects the article DOI: 10.1016/j.apsb.2019.12.012.].

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This study explored the potential of ultrasonic-assisted three-phase partitioning (UTPP) to simultaneously extract lipids, proteins, and polysaccharides from Idesia polycarpa Maxim (IPM) cake meal, a significant byproduct of oil extraction. The impact of variables such as inorganic salt type, solid-liquid ratio, salt concentration, pH, ultrasonic time, temperature, and volume of dimethyl carbonate was examined. Based on the single-factor tests and response surface methodology (RSM), optimal conditions were identified as 30 % ammonium citrate, a 1:26 solid-liquid ratio, pH 3, 31 min of ultrasonic time, 30 °C temperature, and 15 mL of dimethyl carbonate. These conditions achieved extraction rates of 8.10 % for lipids, 5.03 % for proteins, and 10.03 % for polysaccharides, with recovery rates of 91.62 %, 83.08 %, and 93.95 % respectively. Chemical analysis showed the lipid fraction rich in linoleic acid, and the protein fraction high in glutamic acid, aspartate, and serine. The polysaccharide fraction, mainly RG-I pectin with a molecular weight of 226.58 kDa, exhibited strong thermal stability and inhibitory effects on α-glucosidase and glycation, suggesting potential for functional food and dietary supplement applications. This highlights UTPP as a sustainable method for effectively utilizing valuable compounds from IPM cake meal, outperforming traditional extraction techniques.

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Yellow fever (YF), caused by the yellow fever virus (YFV), continually spreads and causes epidemics worldwide, posing a great threat to human health. The live-attenuated YF 17D vaccine (YF-17D) has been licensed for preventing YFV infection and administrated via the intramuscular (i.m.) route. In this study, we sought to determine the immunogenicity and protective efficacy of aerosolized YF-17D via the intratracheal (i.t.) route in mice. YF-17D stocks in liquids were successfully aerosolized into particles of 6 µm. Further in vitro phenotype results showed the aerosolization process did not abolish the infectivity of YF-17D. Meanwhile, a single i.t. immunization with aerosolized YF-17D induced robust humoral and cellular immune responses in A129 mice, which is comparable to that received i.p. immunization. Notably, the aerosolized YF-17D also triggered specific secretory IgA (SIgA) production in bronchoalveolar lavage. Additionally, all immunized animals survived a lethal dose of YFV challenge in mice. In conclusion, our results support further development of aerosolized YF-17D in the future.

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Whenever the elastic energy of a solid depends on magnetic field, there is a magnetostrictive response. Field-linear magnetostriction implies piezomagnetism and vice versa. Here, we show that Mn3Sn, a non-collinear antiferromanget with Weyl nodes, hosts a large and almost perfectly linear magnetostriction even at room temperature. The longitudinal and transverse magnetostriction, with opposite signs and similar amplitude are restricted to the kagome planes and the out-of-plane response is negligibly small. By studying four different samples with different Mn:Sn ratios, we find a clear correlation between the linear magnetostriction, the spontaneous magnetization and the concentration of Sn vacancies. The recently reported piezomagnetic data fits in our picture. We show that linear magnetostriction and piezomagnetism are both driven by the field-induced in-plane twist of spins. A quantitative account of the experimental data requires the distortion of the spin texture by Sn vacancies. We find that the field-induced domain nucleation within the hysteresis loop corresponds to a phase transition. Within the hysteresis loop, a concomitant mesoscopic modulation of local strain and spin twist angles, leading to twisto-magnetic stripes, arises as a result of the competition between elastic and magnetic energies.

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Interferon Gamma Inducible Protein 30 (IFI30), also known as Gamma-Interferon-Inducible Lysosomal Thiol Reductase (GILT), is predominantly found in lysosomes and the cytoplasm. As the sole enzyme identified to catalyze disulfide bond reduction in the endocytic pathway, IFI30 contributes to both major histocompatibility complex (MHC) class I-restricted antigen cross-presentation and MHC class II-restricted antigen processing by decreasing the disulfide bonds of endocytosed proteins. Remarkably, emerging research has revealed that IFI30 is involved in tumorigenesis, tumor development, and the tumor immune response. Targeting IFI30 may provide new strategies for cancer therapy and improve the prognosis of patients. This review provided a comprehensive overview of the research progress on IFI30 in tumor progression, cellular redox status, autophagy, tumor immune response, and drug sensitivity, with a view to providing the theoretical basis for pharmacological intervention of IFI30 in tumor therapy, particularly in immunotherapy.

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OBJECTIVES: Pulmonary neuroendocrine neoplasms (NENs) are the most frequent cause of ectopic adrenocorticotropic hormone syndrome (EAS); lung infection is common in EAS. An imaging finding of infection in EAS patients can mimic NENs. This retrospective study investigated EAS-associated pulmonary imaging indicators. METHODS: Forty-five pulmonary NENs and 27 tumor-like infections from 59 EAS patients (45 NEN and 14 infection patients) were included. Clinical manifestations, CT features, 18F-FDG, or 68Ga-DOTATATE-PET/CT images and pathological results were collected. RESULTS: High-sensitivity C-reactive protein (p < 0.001) and expectoration occurrence (p = 0.04) were higher, and finger oxygen saturation (p = 0.01) was lower in the infection group than the NENs group. Higher-grade NENs were underrepresented in our cohort. Pulmonary NENs were solitary primary tumors, 80% of which were peripheral tumors. Overlying vessel sign and airway involvement were more frequent in the NENs group (p < 0.001). Multifocal (p = 0.001) and peripheral (p = 0.02) lesions, cavity (p < 0.001), spiculation (p = 0.01), pleural retraction (p < 0.001), connection to pulmonary veins (p = 0.02), and distal atelectasis or inflammatory exudation (p = 0.001) were more frequent in the infection group. The median CT value increment between the non-contrast and arterial phases was significantly higher in NENs lesions (p < 0.001). Receiver operating characteristic curve analysis indicated a moderate predictive ability at 48.3 HU of delta CT value (sensitivity, 95.0%; specificity, 54.1%). CONCLUSION: Chest CT scans are valuable for localizing and characterizing pulmonary lesions in rare EAS, thereby enabling prompt differential diagnosis and treatment. CRITICAL RELEVANCE STATEMENT: Thin-slice CT images are valuable for the localization and identification of pulmonary ectopic adrenocorticotropic hormone syndrome lesions, leading to prompt differential diagnosis and effective treatment. KEY POINTS: Lung tumor-like infections can mimic neuroendocrine neoplasms (NENs) in ectopic adrenocorticotropic hormone syndrome (EAS) patients. NENs are solitary lesions, whereas infections are multiple peripheral pseudotumors each with identifying imaging findings. Typical CT signs aid in localization and creating an appropriate differential diagnosis.

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In recent years, significant improvement has been made in the management of non-small cell lung cancer (NSCLC), primarily driven by advances in targeted therapy and immunotherapy. Research on neoadjuvant targeted therapy has also experienced considerable development, primarily directed towards NSCLC harboring epidermal growth factor receptor or anaplastic lymphoma kinase mutations. Nevertheless, there remains a dearth of studies investigating neoadjuvant targeted therapy in the context of BRAF (V-Raf murine sarcoma viral oncogene homolog B) V600E mutant NSCLC. Herein, we describe the clinical trajectory of a stage IIIA NSCLC patient who underwent a two-month course of neoadjuvant targeted therapy comprising BRAF and MEK (mitogen-activated extracellular signal-regulated kinase) inhibitors prior to surgical intervention, and subsequent postoperative evaluation unveiled a pathological complete response. The case reported here indicates the efficacy and safety of combining BRAF and MEK inhibitors as neoadjuvant targeted therapy in BRAF V600E-mutant NSCLC and suggests the potential viability of such a therapeutic modality in improving treatment outcomes in this subset of NSCLC.

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PURPOSE: To examine whether there is a significant difference in image quality between the deep learning reconstruction (DLR [AiCE, Advanced Intelligent Clear-IQ Engine]) and hybrid iterative reconstruction (HIR [AIDR 3D, adaptive iterative dose reduction three dimensional]) algorithms on the conventional enhanced and CE-boost (contrast-enhancement-boost) images of indirect computed tomography venography (CTV) of lower extremities. MATERIALS AND METHODS: In this retrospective study, seventy patients who underwent CTV from June 2021 to October 2022 to assess deep vein thrombosis and varicose veins were included. Unenhanced and enhanced images were reconstructed for AIDR 3D and AiCE, AIDR 3D-boost and AiCE-boost images were obtained using subtraction software. Objective and subjective image qualities were assessed, and radiation doses were recorded. RESULTS: The CT values of the inferior vena cava (IVC), femoral vein ( FV), and popliteal vein (PV) in the CE-boost images were approximately 1.3 (1.31-1.36) times higher than in those of the enhanced images. There were no significant differences in mean CT values of IVC, FV, and PV between AIDR 3D and AiCE, AIDR 3D-boost and AiCE-boost images. Noise in AiCE, AiCE-boost images was significantly lower than in AIDR 3D and AIDR 3D-boost images ( P < 0.05). The SNR (signal-to-noise ratio), CNR (contrast-to-noise ratio), and subjective scores of AiCE-boost images were the highest among 4 groups, surpassing AiCE, AIDR 3D, and AIDR 3D-boost images (all P < 0.05). CONCLUSION: In indirect CTV of the lower extremities images, DLR with the CE-boost technique could decrease the image noise and improve the CT values, SNR, CNR, and subjective image scores. AiCE-boost images received the highest subjective image quality score and were more readily accepted by radiologists.

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OBJECTIVE: This study leverages the rich diversity of the All of Us Research Program (All of Us)'s dataset to devise a predictive model for cardiovascular disease (CVD) in breast cancer (BC) survivors. Central to this endeavor is the creation of a robust data integration pipeline that synthesizes electronic health records (EHRs), patient surveys, and genomic data, while upholding fairness across demographic variables. MATERIALS AND METHODS: We have developed a universal data wrangling pipeline to process and merge heterogeneous data sources of the All of Us dataset, address missingness and variance in data, and align disparate data modalities into a coherent framework for analysis. Utilizing a composite feature set including EHR, lifestyle, and social determinants of health (SDoH) data, we then employed Adaptive Lasso and Random Forest regression models to predict 6 CVD outcomes. The models were evaluated using the c-index and time-dependent Area Under the Receiver Operating Characteristic Curve over a 10-year period. RESULTS: The Adaptive Lasso model showed consistent performance across most CVD outcomes, while the Random Forest model excelled particularly in predicting outcomes like transient ischemic attack when incorporating the full multi-model feature set. Feature importance analysis revealed age and previous coronary events as dominant predictors across CVD outcomes, with SDoH clustering labels highlighting the nuanced impact of social factors. DISCUSSION: The development of both Cox-based predictive model and Random Forest Regression model represents the extensive application of the All of Us, in integrating EHR and patient surveys to enhance precision medicine. And the inclusion of SDoH clustering labels revealed the significant impact of sociobehavioral factors on patient outcomes, emphasizing the importance of comprehensive health determinants in predictive models. Despite these advancements, limitations include the exclusion of genetic data, broad categorization of CVD conditions, and the need for fairness analyses to ensure equitable model performance across diverse populations. Future work should refine clinical and social variable measurements, incorporate advanced imputation techniques, and explore additional predictive algorithms to enhance model precision and fairness. CONCLUSION: This study demonstrates the liability of the All of Us's diverse dataset in developing a multi-modality predictive model for CVD in BC survivors risk stratification in oncological survivorship. The data integration pipeline and subsequent predictive models establish a methodological foundation for future research into personalized healthcare.

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BACKGROUND: The significant impact of digital health emerged prominently during the COVID-19 pandemic. Despite this, there is a paucity of bibliometric analyses focusing on technologies within the field of digital health patents. Patents offer a wealth of insights into technologies, commercial prospects, and competitive landscapes, often undisclosed in other publications. Given the rapid evolution of the digital health industry, safeguarding algorithms, software, and advanced surgical devices through patent systems is imperative. The patent system simultaneously acts as a valuable repository of technological knowledge, accessible to researchers. This accessibility facilitates the enhancement of existing technologies and the advancement of medical equipment, ultimately contributing to public health improvement and meeting public demands. OBJECTIVE: The primary objective of this study is to gain a more profound understanding of technology hotspots and development trends within the field of digital health. METHODS: Using a bibliometric analysis methodology, we assessed the global technological output reflected in patents on digital health published between 2017 and 2021. Using Citespace5.1R8 and Excel 2016, we conducted bibliometric visualization and comparative analyses of key metrics, including national contributions, institutional affiliations, inventor profiles, and technology topics. RESULTS: A total of 15,763 digital health patents were identified as published between 2017 and 2021. The China National Intellectual Property Administration secured the top position with 7253 published patents, whereas Koninklijke Philips emerged as the leading institution with 329 patents. Notably, Assaf Govari emerged as the most prolific inventor. Technology hot spots encompassed categories such as "Medical Equipment and Information Systems," "Image Analysis," and "Electrical Diagnosis," classified by Derwent Manual Code. A patent related to the technique of receiving and transmitting data through microchips garnered the highest citation, attributed to the patentee Covidien LP. CONCLUSIONS: The trajectory of digital health patents has been growing since 2017, primarily propelled by China, the United States, and Japan. Applications in health interventions and enhancements in surgical devices represent the predominant scenarios for digital health technology. Algorithms emerged as the pivotal technologies protected by patents, whereas techniques related to data transfer, storage, and exchange in the digital health domain are anticipated to be focal points in forthcoming basic research.

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Tumor metastasis occurs in hepatocellular carcinoma (HCC), leading to tumor progression and therapeutic failure. Anoikis is a matrix detachment-induced apoptosis, also known as detachment-induced cell death, and mechanistically prevents tumor cells from escaping their native extracellular matrix to metastasize to new organs. Deciphering the regulators and mechanisms of anoikis in cancer metastasis is urgently needed to treat HCC. Several natural and synthetic products induce anoikis in HCC cells and in vivo models. Here, we first briefly summarize the current understanding of the molecular mechanisms of anoikis regulation and relevant regulators involved in HCC metastasis. Then we discuss the therapeutic potential of pharmacological induction of anoikis as a potential treatment against HCC. Finally, we discuss the key limitations of this therapeutic paradigm and propose possible strategies to overcome them. Cumulatively this review suggests that the pharmacological induction of anoikis can be used a promising therapeutic modality against HCC.

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The electrical outputs of single-layer antiferromagnetic memory devices relying on the anisotropic magnetoresistance effect are typically rather small at room temperature. Here we report a new type of antiferromagnetic memory based on the spin phase change in a Mn-Ir binary intermetallic thin film at a composition within the phase boundary between its collinear and noncollinear phases. Via a small piezoelectric strain, the spin structure of this composition-boundary metal is reversibly interconverted, leading to a large nonvolatile room-temperature resistance modulation that is two orders of magnitude greater than the anisotropic magnetoresistance effect for a metal, mimicking the well-established phase change memory from a quantum spin degree of freedom. In addition, this antiferromagnetic spin phase change memory exhibits remarkable time and temperature stabilities, and is robust in a magnetic field high up to 60 T.

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Drug resistance presents a significant obstacle in treating human ovarian cancer. The development of effective methods for detecting drug-resistant cancer cells is pivotal for tailoring personalized therapies and prognostic assessments. In this investigation, we introduce a dual-mode detection technique employing a fluorogenic aptamer probe for the qualification of P-glycoprotein (P-gp) in drug-resistant ovarian cancer cells. The probe, initially in an "off" state due to the proximity of a quencher to the fluorophore, exhibits increased fluorescence intensity upon binding with the target. The fluorescence enhancement shows a linear correlation with both the concentration of P-gp and the presence of P-gp in drug-resistant ovarian cancer cells. This correlation is quantifiable, with detection limits of 1.56 nM and 110 cells per mL. In an alternate mode, the optimized fluorophores, attached to the aptamer, form larger complexes upon binding to the target protein, which diminishes the rotation speed, thereby augmenting fluorescence polarization. The alteration in fluorescence polarization enables the quantitative analysis of P-gp in the cells, ranging from 100 to 1500 cells per milliliter, with a detection limit of 40 cells per mL. Gene expression analyses, protein expression studies, and immunofluorescence imaging further validated the reliability of our aptamer-based probe for its specificity towards P-gp in drug-resistant cancer cells. Our findings underscore that the dual-mode detection approach promises to enhance the diagnosis and treatment of multidrug-resistant ovarian cancer.

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