Antonella  Sciarra Sciarra

Dr. Antonella Sciarra Sciarra


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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31 August 2020 in Nutrients
Verified
Journal Article
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FCFelice Crocetto
Felice Crocetto
Mariarosaria BoccellinoMariarosaria Boccellino
Mariarosaria Boccellino
Biagio BaroneBiagio Barone
Biagio Barone
Erika Di ZazzoErika Di Zazzo
Erika Di Zazzo
ASAntonella Sciarra Sciarra
Antonella Sciarra Sciarra
MDMarina Di Domenico
Marina Di Domenico
The human microbiota shows pivotal roles in urologic health and disease. Emerging studies indicate that gut and urinary microbiomes can impact several urological diseases, both benignant and malignant, acting particularly on prostate inflammation and prostate cancer. Indeed, the microbiota exerts its influence on prostate cancer initiation and/or progression mechanisms through the regulation of chronic inflammation, apoptotic processes, cytokines, and hormonal production in response to different pathogenic noxae. Additionally, therapies’ and drugs’ responses are influenced in their efficacy and tolerability by microbiota composition. Due to this complex potential interconnection between prostate cancer and microbiota, exploration and understanding of the involved relationships is pivotal to evaluate a potential therapeutic application in clinical practice. Several natural compounds, moreover, seem to have relevant effects, directly or mediated by microbiota, on urologic health, posing the human microbiota at the crossroad between prostatic inflammation and prostate cancer development. Here, we aim to analyze the most recent evidence regarding the possible crosstalk between prostate, microbiome, and inflammation.

9 July 2022 in Cancers
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Journal Article
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Mariarosaria BoccellinoMariarosaria Boccellino
Mariarosaria Boccellino
PAPASQUALINA AMBROSIO
PASQUALINA AMBROSIO
ABAndrea Ballini
Andrea Ballini
DANILA DE VITODANILA DE VITO
DANILA DE VITO
Salvatore ScaccoSalvatore Scacco
Salvatore Scacco
MDMarina Di Domenico
Marina Di Domenico
A major challenge in the clinical management of prostate cancer (PC) is to inhibit tumor growth and prevent metastatic spreading. In recent years, considerable efforts have been made to discover new compounds useful for PC therapy, and promising advances in this field were reached. Drugs currently used in PC therapy frequently induce resistance and PC progresses toward metastatic castration-resistant forms (mCRPC), making it virtually incurable. Curcumin, a commercially available nutritional supplement, represents an attractive therapeutic agent for mCRPC patients. In the present study, we compared the effects of chemotherapeutic drugs such as docetaxel, paclitaxel, and cisplatin, to curcumin, on two PC cell lines displaying a different metastatic potential: DU145 (moderate metastatic potential) and PC-3 (high metastatic potential). Our results revealed a dose-dependent reduction of DU145 and PC-3 cell viability upon treatment with curcumin similar to chemotherapeutic agents (paclitaxel, cisplatin, and docetaxel). Furthermore, we explored the EGFR-mediated signaling effects on ERK activation in DU145 and PC-3 cells. Our results showed that DU145 and PC-3 cells overexpress EGFR, and the treatment with chemotherapeutic agents or curcumin reduced EGFR expression levels and ERK activation. Finally, chemotherapeutic agents and curcumin reduced the size of DU145 and PC-3 spheroids and have the potential to induce apoptosis and also in Matrigel. In conclusion, despite different studies being carried out to identify the potential synergistic curcumin combinations with chemopreventive/therapeutic efficacy for inhibiting PC growth, the results show the ability of curcumin used alone, or in combinatorial approaches, to impair the size and the viability of PC-derived spheroids.

18 February 2024 in Applied Sciences
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Journal Article
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ESEnrica Serretiello
Enrica Serretiello
ASAnnafrancesca Smimmo
Annafrancesca Smimmo
ABAndrea Ballini
Andrea Ballini
Domenico ParmeggianiDomenico Parmeggiani
Domenico Parmeggiani
MAMassimo Agresti
Massimo Agresti
MDMarina Di Domenico
Marina Di Domenico
Breast cancer (BC) caused 685,000 deaths globally in 2020, earning the title of the most common type of tumor among females. With a multifactorial genesis, BC is influenced by several factors such as age, genetic and epigenetic predisposition, and an individual’s exposome, and its classification is based on morphological/histological, invasiveness, and molecular futures. Extracellular vesicles (EVs) are cell-derived lipid-bilayer-delimited nanoparticles, which are distinguishable by size, genesis, and the markers expressed in exosomes (40 to 150 nm), microvesicles (40 to 10,000 nm), and apoptotic bodies (100–5000 nm). Produced in physiological and pathological cellular contexts, EVs are shuttles of biological material and are implicated in cell-to-cell communications, thus attracting significant interest in diagnostic and drug delivery research. We report and discuss the latest evidence regarding the important role of EVs in BC, deepening their implication in tumorigenesis and metastatic mechanisms. On the other hand, the use of BC-derived EVs as prognostic biomarkers and therapeutic approaches is undergoing investigation. Hence, EVs have become new weapons in precision medicine; however, only with the support of advanced algorithms such as artificial intelligence (AI) can we develop a wide range of information. Looking ahead, it is possible to see the application of AI in the prognosis and diagnosis of different pathologies.

Verified
Journal Article
Open access
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FCFelice Crocetto
Felice Crocetto
AFAlfonso Falcone
Alfonso Falcone
BMBenito Fabio Mirto
Benito Fabio Mirto
Enrico SicignanoEnrico Sicignano
Enrico Sicignano
GPGiovanni Pagano
Giovanni Pagano
Biagio BaroneBiagio Barone
Biagio Barone
Renal cell carcinoma (RCC) remains a formidable diagnostic challenge, especially in the context of small renal masses. The quest for non-invasive screening tools and biomarkers has steered research towards liquid biopsy, focusing on microRNAs (miRNAs), exosomes, and circulating tumor cells (CTCs). MiRNAs, small non-coding RNAs, exhibit notable dysregulation in RCC, offering promising avenues for diagnosis and prognosis. Studies underscore their potential across various biofluids, including plasma, serum, and urine, for RCC detection and subtype characterization. Encouraging miRNA signatures show correlations with overall survival, indicative of their future relevance in RCC management. Exosomes, with their diverse molecular cargo, including miRNAs, emerge as enticing biomarkers, while CTCs, emanating from primary tumors into the bloodstream, provide valuable insights into cancer progression. Despite these advancements, clinical translation necessitates further validation and standardization, encompassing larger-scale studies and robust evidence generation. Currently lacking approved diagnostic assays for renal cancer, the potential future applications of liquid biopsy in follow-up care, treatment selection, and outcome prediction in RCC patients are profound. This review aims to discuss and highlight recent advancements in liquid biopsy for RCC, exploring their strengths and weaknesses in the comprehensive management of this disease.

17 October 2023 in Diagnostics
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Journal Article
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NFNoemi Fico
Noemi Fico
Graziella Di GreziaGraziella Di Grezia
Graziella Di Grezia
Vincenzo CuccurulloVincenzo Cuccurullo
Vincenzo Cuccurullo
ASAntonio Alessandro Salvia
Antonio Alessandro Salvia
AIAniello Iacomino
Aniello Iacomino
GGGianluca Gatta
Gianluca Gatta
Breast cancer is the most frequently diagnosed neoplasm in women in Italy. There are several risk factors, but thanks to screening and increased awareness, most breast cancers are diagnosed at an early stage when surgical treatment can most often be conservative and the adopted therapy is more effective. Regular screening is essential but advanced technology is needed to achieve quality diagnoses. Mammography is the gold standard for early detection of breast cancer. It is a specialized technique for detecting breast cancer and, thus, distinguishing normal tissue from cancerous breast tissue. Mammography techniques are based on physical principles: through the proper use of X-rays, the structures of different tissues can be observed. This first part of the paper attempts to explain the physical principles used in mammography. In particular, we will see how a mammogram is composed and what physical principles are used to obtain diagnostic images.

Verified
Journal Article
Open access
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ACAlessio Cece
Alessio Cece
MAMassimo Agresti
Massimo Agresti
NFNadia De Falco
Nadia De Falco
PSPasquale Sperlongano
Pasquale Sperlongano
GMGiancarlo Moccia
Giancarlo Moccia
Domenico ParmeggianiDomenico Parmeggiani
Domenico Parmeggiani
The progress of artificial intelligence (AI), particularly its core algorithms—machine learning (ML) and deep learning (DL)—has been significant in the medical field, impacting both scientific research and clinical practice. These algorithms are now capable of analyzing ultrasound images, processing them, and providing outcomes, such as determining the benignity or malignancy of thyroid nodules. This integration into ultrasound machines is referred to as computer-aided diagnosis (CAD). The use of such software extends beyond ultrasound to include cytopathological and molecular assessments, enhancing the estimation of malignancy risk. AI’s considerable potential in cancer diagnosis and prevention is evident. This article provides an overview of AI models based on ML and DL algorithms used in thyroid diagnostics. Recent studies demonstrate their effectiveness and diagnostic role in ultrasound, pathology, and molecular fields. Notable advancements include content-based image retrieval (CBIR), enhanced saliency CBIR (SE-CBIR), Restore-Generative Adversarial Networks (GANs), and Vision Transformers (ViTs). These new algorithms show remarkable results, indicating their potential as diagnostic and prognostic tools for thyroid pathology. The future trend points to these AI systems becoming the preferred choice for thyroid diagnostics.