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This paper proposes a new damage index named degree of health (DoH) to efficiently tackle structural damage monitoring in real-time. As a key contribution, the proposed index relies on a pattern matching methodology that measures the time-of-flight mismatch of sequential ultrasonic guided-wave measurements using fuzzy logic fundamentals. The ultrasonic signals are generated using the transmission beamforming technique with a phased-array of piezoelectric transducers. The acquisition is carried out by two phased-arrays to compare the influence of pulse-echo and pitch-catch modes in the damage assessment. The proposed monitoring approach is illustrated in a fatigue test of an aluminum sheet with an initial notch. As an additional novelty, the proposed pattern matching methodology uses the data stemming from the transmission beamforming technique for structural health monitoring. The results demonstrate the efficiency and robustness of the proposed framework in providing a qualitative and quantitative assessment for fatigue crack damage.
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The17 Sustainable Development Goals (SDGs) established by the United Nations Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity worldwide. Artificial intelligence and other digital technologies that have emerged in the last years, are being currently applied in virtually every area of society, economy and the environment. Hence, it is unsurprising that their current role in the pursuance or hampering of the SDGs has become critical. This study aims at providing a snapshot and comprehensive view of the progress made and prospects in the relationship between artificial intelligence technologies and the SDGs. A comprehensive review of existing literature has been firstly conducted, after which a series SWOT (Strengths, Weaknesses, Opportunities and Threats) analyses have been undertaken to identify the strengths, weaknesses, opportunities and threats inherent to artificial intelligence-driven technologies as facilitators or barriers to each of the SDGs. Based on the results of these analyses, a subsequent broader analysis is provided, from a position vantage, to (i) identify the efforts made in applying AI technologies in SDGs, (ii) pinpoint opportunities for further progress along the current decade, and (iii) distill ongoing challenges and target areas for important advances. The analysis is organized into six categories or perspectives of human needs: life, economic and technological development, social development, equality, resources and natural environment. Finally, a closing discussion is provided about the prospects, key guidelines and lessons learnt that should be adopted for guaranteeing a positive shift of artificial intelligence developments and applications towards fully supporting the SDGs attainment by 2030.
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Gene therapy has long been proposed for cancer treatment. However, the use of therapeutic nucleic acids presents several limitations such as enzymatic degradation, rapid clearance, and poor cellular uptake and efficiency. In this work we propose the use of putrescine, a precursor for higher polyamine biosynthesis for the preparation of cationic nanosystems for cancer gene therapy. We have formulated and characterized putrescine-sphingomyelin nanosystems (PSN) and studied their endocytic pathway and intracellular trafficking in cancer cells. After loading a plasmid DNA (pDNA) encoding the apoptotic Fas Ligand (FasL), we proved their therapeutic activity by measuring the cell death rate after treatment of MDA-MB-231 cells. We have also used xenografted zebrafish embryos as a first in vivo approach to demonstrate the efficacy of the proposed PSN-pDNA formulation in a more complex model. Finally, intratumoral and intraperitoneal administration to mice-bearing MDA-MB-231 xenografts resulted in a significant decrease in tumour cell growth, highlighting the potential of the developed gene therapy nanoformulation for the treatment of triple negative breast cancer.
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Neoplasias da Mama , Neoplasias , Humanos , Camundongos , Animais , Feminino , Putrescina , Peixe-Zebra , Ciclo Celular , Morte Celular , Linhagem Celular TumoralRESUMO
Correction for 'Effectiveness of a novel gene nanotherapy based on putrescine for cancer treatment' by Saínza Lores et al., Biomater. Sci., 2023, https://doi.org/10.1039/d2bm01456d.
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The prognosis and quality of life of HER2 breast cancer patients have significantly improved due to the crucial clinical benefit of various anti-HER2 targeted therapies. However, HER2 tumors can possess or develop several resistance mechanisms to these treatments, thus leaving patients with a limited set of additional therapeutic options. Fortunately, to overcome this problem, in recent years, multiple different and complementary approaches have been developed (such as antibody-drug conjugates (ADCs)) that are in clinical or preclinical stages. In this review, we focus on emerging strategies other than on ADCs that are either aimed at directly target the HER2 receptor (i.e., novel tyrosine kinase inhibitors) or subsequent intracellular signaling (e.g., PI3K/AKT/mTOR, CDK4/6 inhibitors, etc.), as well as on innovative approaches designed to attack other potential tumor weaknesses (such as immunotherapy, autophagy blockade, or targeting of other genes within the HER2 amplicon). Moreover, relevant technical advances such as anti-HER2 nanotherapies and immunotoxins are also discussed. In brief, this review summarizes the impact of novel therapeutic approaches on current and future clinical management of aggressive HER2 breast tumors.
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Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related death worldwide. Alterations in proteins of the p53-family are a common event in CRC. ΔNp73, a p53-family member, shows oncogenic properties and its effectors are largely unknown. We performed an in-depth proteomics characterization of transcriptional control by ∆Np73 of the secretome of human colon cancer cells and validated its clinical potential. The secretome was analyzed using high-density antibody microarrays and stable isotopic metabolic labeling. Validation was performed by semiquantitative PCR, ELISA, dot-blot and western blot analysis. Evaluation of selected effectors was carried out using 60 plasma samples from CRC patients, individuals carrying premalignant colorectal lesions and colonoscopy-negative controls. In total, 51 dysregulated proteins were observed showing at least 1.5-foldchange in expression. We found an important association between the overexpression of ∆Np73 and effectors related to lymphangiogenesis, vasculogenesis and metastasis, such as brain-derived neurotrophic factor (BDNF) and the putative aminoacyl tRNA synthase complex-interacting multifunctional protein 1 (EMAP-II)-vascular endothelial growth factor C-vascular endothelial growth factor receptor 3 axis. We further demonstrated the usefulness of BDNF as a potential CRC biomarker able to discriminate between CRC patients and premalignant individuals from controls with high sensitivity and specificity.
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Neoplasias Colorretais , Linfangiogênese , Fator Neurotrófico Derivado do Encéfalo/metabolismo , Neoplasias Colorretais/genética , Humanos , Proteômica , Proteína Supressora de Tumor p53 , Fator A de Crescimento do Endotélio Vascular/metabolismo , Fator C de Crescimento do Endotélio Vascular/metabolismoRESUMO
BACKGROUND: Gasdermin B (GSDMB) over-expression promotes poor prognosis and aggressive behavior in HER2 breast cancer by increasing resistance to therapy. Decoding the molecular mechanism of GSDMB-mediated drug resistance is crucial to identify novel effective targeted treatments for HER2/GSDMB aggressive tumors. METHODS: Different in vitro approaches (immunoblot, qRT-PCR, flow cytometry, proteomic analysis, immunoprecipitation, and confocal/electron microscopy) were performed in HER2 breast and gastroesophageal carcinoma cell models. Results were then validated using in vivo preclinical animal models and analyzing human breast and gastric cancer samples. RESULTS: GSDMB up-regulation renders HER2 cancer cells more resistant to anti-HER2 agents by promoting protective autophagy. Accordingly, the combination of lapatinib with the autophagy inhibitor chloroquine increases the therapeutic response of GSDMB-positive cancers in vitro and in zebrafish and mice tumor xenograft in vivo models. Mechanistically, GSDMB N-terminal domain interacts with the key components of the autophagy machinery LC3B and Rab7, facilitating the Rab7 activation during pro-survival autophagy in response to anti-HER2 therapies. Finally, we validated these results in clinical samples where GSDMB/Rab7/LC3B co-expression associates significantly with relapse in HER2 breast and gastric cancers. CONCLUSION: Our findings uncover for the first time a functional link between GSDMB over-expression and protective autophagy in response to HER2-targeted therapies. GSDMB behaves like an autophagy adaptor and plays a pivotal role in modulating autophagosome maturation through Rab7 activation. Finally, our results provide a new and accessible therapeutic approach for HER2/GSDMB + cancers with adverse clinical outcome.
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Neoplasias da Mama , Receptor ErbB-2 , Animais , Autofagia , Neoplasias da Mama/tratamento farmacológico , Neoplasias da Mama/genética , Linhagem Celular Tumoral , Cloroquina/farmacologia , Resistencia a Medicamentos Antineoplásicos , Feminino , Humanos , Lapatinib/farmacologia , Camundongos , Recidiva Local de Neoplasia , Proteômica , Receptor ErbB-2/genética , Peixe-ZebraRESUMO
The prediction of water table height in unconfined layered porous media is a difficult modelling problem that typically requires numerical simulation. This paper proposes an analytical model to approximate the exact solution based on a steady-state Dupuit-Forchheimer analysis. The key contribution in relation to a similar model in the literature relies in the ability of the proposed model to consider more than two layers with different thicknesses and slopes, so that the existing model becomes a special case of the proposed model herein. In addition, a model assessment methodology based on the Bayesian inverse problem is proposed to efficiently identify the values of the physical parameters for which the proposed model is accurate when compared against a reference model given by MODFLOW-NWT, the open-source finite-difference code by the U.S. Geological Survey. Based on numerical results for a representative case study, the ratio of vertical recharge rate to hydraulic conductivity emerges as a key parameter in terms of model accuracy so that, when appropriately bounded, both the proposed model and MODFLOW-NWT provide almost identical results.
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PURPOSE: Gasdermin B (GSDMB) overexpression/amplification occurs in about 60% of HER2 breast cancers, where it promotes cell migration, resistance to anti-HER2 therapies, and poor clinical outcome. Thus, we tackle GSDMB cytoplasmic overexpression as a new therapeutic target in HER2 breast cancers. EXPERIMENTAL DESIGN: We have developed a new targeted nanomedicine based on hyaluronic acid-biocompatible nanocapsules, which allow the intracellular delivery of a specific anti-GSDMB antibody into HER2 breast cancer cells both in vitro and in vivo. RESULTS: Using different models of HER2 breast cancer cells, we show that anti-GSDMB antibody loaded to nanocapsules has significant and specific effects on GSDMB-overexpressing cancer cells' behavior in ways such as (i) lowering the in vitro cell migration induced by GSDMB; (ii) enhancing the sensitivity to trastuzumab; (iii) reducing tumor growth by increasing apoptotic rate in orthotopic breast cancer xenografts; and (iv) diminishing lung metastasis in MDA-MB-231-HER2 cells in vivo. Moreover, at a mechanistic level, we have shown that AbGB increases GSDMB binding to sulfatides and consequently decreases migratory cell behavior and may upregulate the potential intrinsic procell death activity of GSDMB. CONCLUSIONS: Our findings portray the first evidence of the effectiveness and specificity of an antibody-based nanomedicine that targets an intracellular oncoprotein. We have proved that intracellular-delivered anti-GSDMB reduces diverse protumor GSDMB functions (migration, metastasis, and resistance to therapy) in an efficient and specific way, thus providing a new targeted therapeutic strategy in aggressive HER2 cancers with poor prognosis.