Publications by authors named "Marco Salvatore"

427 Publications

Novel Antimicrobial Strategies to Prevent Biofilm Infections in Catheters after Radical Cystectomy: A Pilot Study.

Life (Basel) 2022 May 27;12(6). Epub 2022 May 27.

Andrological and Urogynecological Clinic, Santa Maria Terni Hospital, University of Perugia, 05100 Terni, Italy.

Catheter-associated infections in bladder cancer patients, following radical cystectomy or ureterocutaneostomy, are very frequent, and the development of antibiotic resistance poses great challenges for treating biofilm-based infections. Here, we characterized bacterial communities from catheters of patients who had undergone radical cystectomy for muscle-invasive bladder cancer. We evaluated the efficacy of conventional antibiotics, alone or combined with the human ApoB-derived antimicrobial peptide r(P)ApoB, to treat ureteral catheter-colonizing bacterial communities on clinically isolated bacteria. Microbial communities adhering to indwelling catheters were collected during the patients' regular catheter change schedules (28 days) and extracted within 48 h. Living bacteria were characterized using selective media and biochemical assays. Biofilm growth and novel antimicrobial strategies were analyzed using confocal laser scanning microscopy. Statistical analyses confirmed the relevance of the biofilm reduction induced by conventional antibiotics (fosfomycin, ceftriaxone, ciprofloxacin, gentamicin, and tetracycline) and a well-characterized human antimicrobial peptide r(P)ApoB (1:20 ratio, respectively). Catheters showed polymicrobial communities, with Enterobactericiae and Proteus isolates predominating. In all samples, we recorded a meaningful reduction in biofilms, in both biomass and thickness, upon treatment with the antimicrobial peptide r(P)ApoB in combination with low concentrations of conventional antibiotics. The results suggest that combinations of conventional antibiotics and human antimicrobial peptides might synergistically counteract biofilm growth on ureteral catheters, suggesting novel avenues for preventing catheter-associated infections in patients who have undergone radical cystectomy and ureterocutaneostomy.
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http://dx.doi.org/10.3390/life12060802DOI Listing
May 2022

Prognostic Value of Hybrid PET/MR Imaging in Patients with Differentiated Thyroid Cancer.

Cancers (Basel) 2022 Jun 15;14(12). Epub 2022 Jun 15.

Department of Advanced Biomedical Sciences, University Federico II, 80131 Naples, Italy.

Background: Hybrid positron emission tomography (PET)/magnetic resonance (MR) is an emerging imaging modality with great potential to provide complementary data acquired at the same time, under the same physiological conditions. The aim of this study was to evaluate the prognostic value of hybrid F-fluorodeoxyglucose (FDG) PET/MR in patients with differentiated thyroid cancer (DTC) who underwent total thyroidectomy and radioactive iodine therapy for suspicion of disease relapse.

Methods: Between November 2015 and February 2017, 55 patients underwent hybrid F-FDG PET/MR. Assessment of positive MR was made considering all sequences in terms of malignancy based on the morphological T2-weighted features and the presence of restricted diffusivity on diffusion-weighted imaging images and both needed to be positive on the same lesion. Both foci with abnormal F-FDG uptake, which corresponded to tissue abnormalities on the MR, and tracer accumulation, which did not correspond to normal morphological structures, were considered positive.

Results: During follow-up (mean 42 ± 27 months), 29 patients (53%) had disease recurrence. In the Cox univariate regression analysis age, serum Tg level ≥ 2 ng/mL, positive short tau inversion recovery (STIR), and positive PET were significant predictors of DTC recurrence. Kaplan-Meier survival analyses showed that patients with Tg ≥ 2 ng/mL had poorer outcomes compared to those with serum Tg level < 2 ng/mL ( 0.05). Similarly, patients with positive STIR and positive PET had a worst outcome compared to those with negative STIR ( 0.05) and negative PET ( 0.005). Survival analysis performed in the subgroup of 36 subjects with Tg level ≥ 2 ng/mL revealed that patients with positive PET had a worst outcome compared to those with negative PET ( 0.05).

Conclusions: Age, serum Tg level ≥ 2 ng/mL, positive STIR, and positive F-FDG PET were significant predictors of DTC recurrence. However, the serum Tg level was the only independent predictor of DTC. Hybrid PET/MR imaging may have the potential to improve the information content of one modality with the other and would offer new opportunities in patients with DTC. Thus, further studies in a larger patient population are needed to understand the additional value of F-FDG PET/MR in patients with DTC.
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http://dx.doi.org/10.3390/cancers14122958DOI Listing
June 2022

Discovering Common miRNA Signatures Underlying Female-Specific Cancers via a Machine Learning Approach Driven by the Cancer Hallmark ERBB.

Biomedicines 2022 Jun 2;10(6). Epub 2022 Jun 2.

IRCCS Synlab SDN, 80143 Naples, Italy.

Big data processing, using omics data integration and machine learning (ML) methods, drive efforts to discover diagnostic and prognostic biomarkers for clinical decision making. Previously, we used the TCGA database for gene expression profiling of breast, ovary, and endometrial cancers, and identified a top-scoring network centered on the gene, which plays a crucial role in carcinogenesis in the three estrogen-dependent tumors. Here, we focused on microRNA expression signature similarity, asking whether they could target the family. We applied an ML approach on integrated TCGA miRNA profiling of breast, endometrium, and ovarian cancer to identify common miRNA signatures differentiating tumor and normal conditions. Using the ML-based algorithm and the miRTarBase database, we found 205 features and 158 miRNAs targeting isoforms, respectively. By merging the results of both databases and ranking each feature according to the weighted Support Vector Machine model, we prioritized 42 features, with accuracy (0.98), AUC (0.93-95% CI 0.917-0.94), sensitivity (0.85), and specificity (0.99), indicating their diagnostic capability to discriminate between the two conditions. In vitro validations by qRT-PCR experiments, using model and parental cell lines for each tumor type showed that five miRNAs (hsa-mir-323a-3p, hsa-mir-323b-3p, hsa-mir-331-3p, hsa-mir-381-3p, and hsa-mir-1301-3p) had expressed trend concordance between breast, ovarian, and endometrium cancer cell lines compared with normal lines, confirming our in silico predictions. This shows that an integrated computational approach combined with biological knowledge, could identify expression signatures as potential diagnostic biomarkers common to multiple tumors.
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http://dx.doi.org/10.3390/biomedicines10061306DOI Listing
June 2022

Identifying interactions in omics data for clinical biomarker discovery using symbolic regression.

Bioinformatics 2022 Jun 22. Epub 2022 Jun 22.

Abzu ApS, Orient Plads, Copenhagen, 2150, Denmark.

Motivation: The identification of predictive biomarker signatures from omics and multi-omics data for clinical applications is an active area of research. Recent developments in assay technologies and machine learning (ML) methods have led to significant improvements in predictive performance. However, most high-performing ML methods suffer from complex architectures and lack interpretability.

Results: We present the application of a novel symbolic-regression-based algorithm, the QLattice, on a selection of clinical omics datasets. This approach generates parsimonious high-performing models that can both predict disease outcomes and reveal putative disease mechanisms, demonstrating the importance of selecting maximally relevant and minimally redundant features in omics-based machine-learning applications. The simplicity and high predictive power of these biomarker signatures make them attractive tools for high-stakes applications in areas such as primary care, clinical decision making and patient stratification.

Availability: The QLattice is available as part of a python package (feyn), which is available at the Python Package Index (https://pypi.org/project/feyn/) and can be installed via pip. The documentation provides guides, tutorials, and the API reference (https://docs.abzu.ai/). All code and data used to generate the models and plots discussed in this work can be found in (https://github.com/abzu-ai/QLattice-clinical-omics).

Supplementary Information: Supplementary material is available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btac405DOI Listing
June 2022

A Systematic Review of the Current Status and Quality of Radiomics for Glioma Differential Diagnosis.

Cancers (Basel) 2022 May 31;14(11). Epub 2022 May 31.

IRCCS Synlab SDN, 80143 Naples, Italy.

Radiomics is a promising tool that may increase the value of imaging in differential diagnosis (DDx) of glioma. However, implementation in clinical practice is still distant and concerns have been raised regarding the methodological quality of radiomic studies. Therefore, we aimed to systematically review the current status of radiomic studies concerning glioma DDx, also using the radiomics quality score (RQS) to assess the quality of the methodology used in each study. A systematic literature search was performed to identify original articles focused on the use of radiomics for glioma DDx from 2015. Methodological quality was assessed using the RQS tool. Spearman's correlation (ρ) analysis was performed to explore whether RQS was correlated with journal metrics and the characteristics of the studies. Finally, 42 articles were selected for the systematic qualitative analysis. Selected articles were grouped and summarized in terms of those on DDx between glioma and primary central nervous system lymphoma, those aiming at differentiating glioma from brain metastases, and those based on DDx of glioma and other brain diseases. Median RQS was 8.71 out 36, with a mean RQS of all studies of 24.21%. Our study revealed that, despite promising and encouraging results, current studies on radiomics for glioma DDx still lack the quality required to allow its introduction into clinical practice. This work could provide new insights and help to reach a consensus on the use of the radiomic approach for glioma DDx.
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http://dx.doi.org/10.3390/cancers14112731DOI Listing
May 2022

Reduction of De Novo Lipogenesis Mediates Beneficial Effects of Isoenergetic Diets on Fatty Liver: Mechanistic Insights from the MEDEA Randomized Clinical Trial.

Nutrients 2022 May 23;14(10). Epub 2022 May 23.

Department of Clinical Medicine and Surgery, Federico II University, Via Sergio Pansini 5, 80131 Naples, Italy.

Background: Non-alcoholic liver steatosis (NAS) results from an imbalance between hepatic lipid storage, disposal, and partitioning. A multifactorial diet high in fiber, monounsaturated fatty acids (MUFAs), n-6 and n-3 polyunsaturated fatty acids (PUFAs), polyphenols, and vitamins D, E, and C reduces NAS in people with type 2 diabetes (T2D) by 40% compared to a MUFA-rich diet. We evaluated whether dietary effects on NAS are mediated by changes in hepatic de novo lipogenesis (DNL), stearoyl-CoA desaturase (SCD1) activity, and/or β-oxidation.

Methods: According to a randomized parallel group study design, 37 individuals with T2D completed an 8-week isocaloric intervention with a MUFA diet ( = 20) or multifactorial diet ( = 17). Before and after the intervention, liver fat content was evaluated by proton magnetic resonance spectroscopy, serum triglyceride fatty acid concentrations measured by gas chromatography, plasma β-hydroxybutyrate by enzymatic method, and DNL and SCD-1 activity assessed by calculating the palmitic acid/linoleic acid (C16:0/C18:2 n6) and palmitoleic acid/palmitic acid (C16:1/C16:0) ratios, respectively.

Results: Compared to baseline, mean ± SD DNL significantly decreased after the multifactorial diet (2.2 ± 0.8 vs. 1.5 ± 0.5, = 0.0001) but did not change after the MUFA diet (1.9 ± 1.1 vs. 1.9 ± 0.9, = 0.949), with a significant difference between the two interventions ( = 0.004). The mean SCD-1 activity also decreased after the multifactorial diet (0.13 ± 0.05 vs. 0.10 ± 0.03; = 0.001), but with no significant difference between interventions ( = 0.205). Fasting plasma β-hydroxybutyrate concentrations did not change significantly after the MUFA or multifactorial diet. Changes in the DNL index significantly and positively correlated with changes in liver fat (r = 0.426; = 0.009).

Conclusions: A diet rich in multiple beneficial dietary components (fiber, polyphenols, MUFAs, PUFAs, and other antioxidants) compared to a diet rich only in MUFAs further reduces liver fat accumulation through the inhibition of DNL. Registered under ClinicalTrials.gov no. NCT03380416.
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http://dx.doi.org/10.3390/nu14102178DOI Listing
May 2022

MRI-Based Radiomic Features Help Identify Lesions and Predict Histopathological Grade of Hepatocellular Carcinoma.

Diagnostics (Basel) 2022 Apr 26;12(5). Epub 2022 Apr 26.

IRCCS Synlab SDN, 80143 Naples, Italy.

Hepatocellular carcinoma (HCC) is the most common form of liver cancer. Radiomics is a promising tool that may increase the value of magnetic resonance imaging (MRI) in the management of HCC. The purpose of our study is to develop an MRI-based radiomics approach to preoperatively detect HCC and predict its histological grade. Thirty-eight HCC patients at staging who underwent axial T2-weighted and dynamic contrast-enhanced MRI (DCE-MRI) were considered. Three-dimensional volumes of interest (VOIs) were manually placed on HCC lesions and normal hepatic tissue (HT) on arterial phase post-contrast images. Radiomic features from T2 images and arterial, portal and tardive post-contrast images from DCE-MRI were extracted by using Pyradiomics. Feature selection was performed using correlation filter, Wilcoxon-rank sum test and mutual information. Predictive models were constructed for HCC differentiation with respect to HT and HCC histopathologic grading used at each step an imbalance-adjusted bootstrap resampling (IABR) on 1000 samples. Promising results were obtained from radiomic prediction models, with best AUCs ranging from 71% to 96%. Radiomics MRI based on T2 and DCE-MRI revealed promising results concerning both HCC detection and grading. It may be a suitable tool for personalized treatment of HCC patients and could also be used to develop new prognostic biomarkers useful for HCC assessment without the need for invasive procedures.
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http://dx.doi.org/10.3390/diagnostics12051085DOI Listing
April 2022

Role of gut microbiota in neuropathy and neuropathic pain states: A systematic preclinical review.

Neurobiol Dis 2022 Aug 25;170:105773. Epub 2022 May 25.

IRCCS Synlab SDN, Via Emanuele Gianturco 113, 80143 Naples, Italy.

Gut microbiota has implications in Central Nervous System (CNS) disorders. Our study systematically identified preclinical studies aimed to investigate the possible gut microbiota contribution in neuropathy and neuropathic pain. The systematic review is reported in accordance with PRISMA checklist and guidelines outlined updated to 2020. We included research articles reporting neuropathy-related behavioral evaluations and/or neurological scores coupled to gut microbiota analysis performed by high-throughput technologies in the last ten years. Two investigators performed a search through 3 electronic bibliographic databases for full-text articles (PubMed, Scopus, and EMBASE) and three registries (Prospero, SyRF, and bioRxiv), cross-references, and linear searches. We assessed the methodological quality via the CAMARADES checklist and appraised the heterogeneous body of evidence by narrative synthesis. In total, there were 19 eligible studies. The most of these reports showed significant changes in gut microbiota setting in neuropathy conditions. The major gut microbiome remodeling was through fecal microbiome transplantation. Mechanistic proof of the gut-CNS communication was achieved by measuring inflammatory mediators, metabolic products, or neurotransmitters. As a limitation, we found considerable heterogeneity across eligible studies. We conclude that the current understanding of preclinical findings suggested an association between neuropathy and/or neuropathic pain and gut microbiota modifications. Our analysis provides the basis for further studies targeting microbiota for managing symptoms of neuropathy or other neuroinflammation-based CNS disorders. The systematic review protocol was registered on the international database Prospero under the registration number (257628).
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http://dx.doi.org/10.1016/j.nbd.2022.105773DOI Listing
August 2022

Brain Networks Involved in Depression in Patients with Frontotemporal Dementia and Parkinson's Disease: An Exploratory Resting-State Functional Connectivity MRI Study.

Diagnostics (Basel) 2022 Apr 12;12(4). Epub 2022 Apr 12.

Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Synlab SDN, Via Emanuele Gianturco, 113, 80143 Naples, Italy.

Depression is characterized by feelings of sadness, loss, or anger that may interfere with everyday activities. Such a neuropsychiatric condition is commonly reported in multiple neurodegenerative disorders, which are quite different from each other. This study aimed at investigating the brain networks involved in depression in patients with frontotemporal dementia (FTD) and Parkinson's disease (PD) as compared to healthy controls (HC). Fifty participants were included in the study: 17 depressed FTD/PD patients; 17 non-depressed FTD/PD patients; and 16 non-depressed HCs matched for age and gender. We used the Beck depression inventory (BDI-II) to measure depression in all groups. On the same day, 3T brain magnetic resonance with structural and resting-state functional sequences were acquired. Differences in resting-state functional connectivity (FC) between depressed and non-depressed patients in all the experimental groups were assessed by using seed-to-seed and network-to-network approaches. We found a significant seed-to-seed hyperconnectivity patterns between the left thalamus and the left posterior temporal fusiform cortex, which differentiated FTD/PD depressed patients from the HCs. Network-to-network analysis revealed a significant hyperconnectivity among the default-mode network (left lateral-parietal region), the medial prefrontal cortex and the left lateral prefrontal cortex (i.e., part of the central executive network). We investigated whether such FC patterns could be related to the underlying neurodegenerative disorder by replicating the analyses with two independent samples (i.e., non-depressed PD and non-depressed FTD patients) and adding clinical parameters as covariates. We found no FC differences in these groups, thus suggesting how the FC pattern we found may signal a common depression-related neural pathway implicated in both the neurocognitive disorders.
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http://dx.doi.org/10.3390/diagnostics12040959DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9029925PMC
April 2022

Evaluation of AI-Based Segmentation Tools for COVID-19 Lung Lesions on Conventional and Ultra-low Dose CT Scans.

Dose Response 2022 Jan-Mar;20(1):15593258221082896. Epub 2022 Apr 6.

IRCCS SDN, Naples, Italy.

A reliable diagnosis and accurate monitoring are pivotal steps for treatment and prevention of COVID-19. Chest computed tomography (CT) has been considered a crucial diagnostic imaging technique for the injury assessment of the viral pneumonia. Furthermore, the automatization of the segmentation methods for lung alterations helps to speed up the diagnosis and lighten radiologists' workload. Considering the assiduous pathology monitoring, ultra-low dose (ULD) chest CT protocols have been implemented to drastically reduce the radiation burden. Unfortunately, the available AI technologies have not been trained on ULD-CT data and validated and their applicability deserves careful evaluation. Therefore, this work aims to compare the results of available AI tools (BCUnet, CORADS AI, NVIDIA CLARA Train SDK and CT Pneumonia Analysis) on a dataset of 73 CT examinations acquired both with conventional dose (CD) and ULD protocols. COVID-19 volume percentage, resulting from each tool, was statistically compared. This study demonstrated high comparability of the results on CD-CT and ULD-CT data among the four AI tools, with high correlation between the results obtained on both protocols (R > .68, P < .001, for all AI tools).
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http://dx.doi.org/10.1177/15593258221082896DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002358PMC
April 2022

KCTD15 Is Overexpressed in her2+ Positive Breast Cancer Patients and Its Silencing Attenuates Proliferation in SKBR3 CELL LINE.

Diagnostics (Basel) 2022 Feb 25;12(3). Epub 2022 Feb 25.

IRCCS SYNLAB SDN S.p.a., Napoli, Via E. Gianturco 113, 80143 Napoli, Italy.

Studies carried out in the last decade have demonstrated that the members of the KCTD protein family play active roles in carcinogenesis. Very recently, it has been reported that KCTD15, a protein typically associated with other physio-pathological processes, is involved in medulloblastoma and leukemia. Starting with some preliminary indications that emerged from the analysis of online databases that suggested a possible overexpression of KCTD15 in breast cancer, in this study, we evaluated the expression levels of the protein in breast cancer cell lines and in patients and the effects of its silencing in the HER2+ cell model. The analysis of the KCTD15 levels indicates a significant overexpression of the protein in Luminal A and Luminal B breast cancer patients as well as in the related cell lines. The greatest level of over-expression of the protein was found in HER2+ patients and in the related SKBR3 cell line model system. The effects of KCTD15 silencing in terms of cell proliferation, cell cycle, and sensitivity to doxorubicin were evaluated in the SKBR3 cell line. Notably, the KCTD15 silencing in SKBR3 cells by CRISPR/CAS9 technology significantly attenuates their proliferation and cell cycle progression. Finally, we demonstrated that KCT15 silencing also sensitized SKBR3 cells to the cytotoxic agent doxorubicin, suggesting a possible role of the protein in anti HER2+ therapeutic strategies. Our results highlight a new possible player in HER2 breast cancer carcinogenesis, paving the way for its use in breast cancer diagnosis and therapy.
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http://dx.doi.org/10.3390/diagnostics12030591DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947324PMC
February 2022

The visual encoding of graspable unfamiliar objects.

Psychol Res 2022 Mar 23. Epub 2022 Mar 23.

IRCCS Synlab SDN, Naples, Italy.

We explored by eye-tracking the visual encoding modalities of participants (N = 20) involved in a free-observation task in which three repetitions of ten unfamiliar graspable objects were administered. Then, we analysed the temporal allocation (t = 1500 ms) of visual-spatial attention to objects' manipulation (i.e., the part aimed at grasping the object) and functional (i.e., the part aimed at recognizing the function and identity of the object) areas. Within the first 750 ms, participants tended to shift their gaze on the functional areas while decreasing their attention on the manipulation areas. Then, participants reversed this trend, decreasing their visual-spatial attention to the functional areas while fixing the manipulation areas relatively more. Crucially, the global amount of visual-spatial attention for objects' functional areas significantly decreased as an effect of stimuli repetition while remaining stable for the manipulation areas, thus indicating stimulus familiarity effects. These findings support the action reappraisal theoretical approach, which considers object/tool processing as abilities emerging from semantic, technical/mechanical, and sensorimotor knowledge integration.
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http://dx.doi.org/10.1007/s00426-022-01673-zDOI Listing
March 2022

Diagnostic and prognostic significance of extracellular vesicles in prostate cancer drug resistance: A systematic review of the literature.

Prostate Cancer Prostatic Dis 2022 Mar 9. Epub 2022 Mar 9.

IRCCS SYNLAB SDN S.p.A., 80131, Napoli, Italy.

Background: The clinical behavior of prostate cancer is highly heterogeneous, with most patients diagnosed with localized disease that successfully responds to surgery or radiotherapy. However, a fraction of men relapse after initial treatment because they develop drug resistance. The failure of anticancer drugs leaves resistant cancer cells to survive and proliferate, negatively affecting patient survival. Thus, drug resistance remains a significant obstacle to the effective treatment of prostate cancer patients. In this scenario, the involvement of extracellular vesicles (EVs) in intrinsic and acquired resistance have been reported in several tumors, and accumulating data suggests that their differential content can be used as diagnostic or prognostic factors. Thus, we propose a systematic study of literature to provide a snapshot of the current scenario regarding EVs as diagnostic and prognostic biomarkers resource in resistant prostate cancer.

Methods: We performed the current systematic review according to PRISMA guidelines and comprehensively explored PubMed, EMBASE and Google Scholar databases to achieve the article search.

Results: Thirty-three studies were included and investigated. Among all systematically reviewed EV biomarkers, we found mainly molecules with prognostic significance (61%), molecules with diagnostic relevance (18%), and molecules that serve both purposes (21%). Moreover, among all analyzed molecules isolated from EVs, proteins, mRNAs, and miRNAs emerged to be the most investigated and proposed as potential tools to diagnose or predict resistance/sensitivity to advanced PCa treatments.

Discussion: Our analysis provides a snapshot of the current scenario regarding EVs as potential clinical biomarkers in resistant PCa. Nevertheless, despite many efforts, the use of EV biomarkers in PCa is currently at an early stage: none of the selected EV biomarkers goes beyond preclinical studies, and their translatability is yet far from clinical settings.
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http://dx.doi.org/10.1038/s41391-022-00521-wDOI Listing
March 2022

RIPK4 regulates cell-cell adhesion in epidermal development and homeostasis.

Hum Mol Genet 2022 Feb 26. Epub 2022 Feb 26.

Department of Life, Health and Environmental Sciences, University of L'Aquila, 67100 L'Aquila, Italy.

Epidermal development and maintenance are finely regulated events requiring a strict balance between proliferation and differentiation. Alterations in these processes give rise to human disorders such as cancer or syndromes with skin and annexes defects, known as ectodermal dysplasias (EDs). Here, we studied the functional effects of two novel receptor-interacting protein kinase 4 (RIPK4) missense mutations identified in siblings with an autosomal recessive ED with cutaneous syndactyly, palmoplantar hyperkeratosis and orofacial synechiae. Clinical overlap with distinct EDs caused by mutations in transcription factors (i.e. p63 and interferon regulatory factor 6, IRF6) or nectin adhesion molecules was noticed. Impaired activity of the RIPK4 kinase resulted both in altered epithelial differentiation and defective cell adhesion. We showed that mutant RIPK4 resulted in loss of PVRL4/nectin-4 expression in patient epidermis and primary keratinocytes, and demonstrated that PVRL4 is transcriptionally regulated by IRF6, a RIPK4 phosphorylation target. In addition, defective RIPK4 altered desmosome morphology through modulation of plakophilin-1 and desmoplakin. In conclusion, this work implicates RIPK4 kinase function in the p63-IRF6 regulatory loop that controls the proliferation/differentiation switch and cell adhesion, with implications in ectodermal development and cancer.
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http://dx.doi.org/10.1093/hmg/ddac046DOI Listing
February 2022

Acceptance of COVID-19 and Influenza Vaccine Co-Administration: Insights from a Representative Italian Survey.

J Pers Med 2022 Jan 20;12(2). Epub 2022 Jan 20.

Hygiene Unit, San Martino Policlinico Hospital-IRCCS for Oncology and Neurosciences, 16132 Genoa, Italy.

Co-administration of coronavirus disease 2019 (COVID-19) and seasonal influenza vaccines has several advantages, has been advocated by various public health authorities and should be seen as an opportunity to increase the uptake of both vaccines. The objective of this survey was to quantify the acceptance of concomitant COVID-19/influenza vaccination and to identify its correlates in a representative sample of Italian adults. Of 2463 participants, a total of 22.9% were favorable to vaccine co-administration, while 16.6% declared their firm unwillingness to receive both vaccines simultaneously. The remaining 60.5% of subjects could be dubbed hesitant to some degree. Compliance with the primary COVID-19 vaccination schedule (adjusted proportional odds ratio (aOR) = 7.78), previous influenza vaccination (aOR = 1.89) and trust in public health institutions (aOR = 1.22) were the main determinants of positive attitudes toward vaccine co-administration. Other significant correlates included age, sex, perceived disease severity and vaccination risk-benefit, being offered a more personalized influenza vaccine and recent seeking for influenza-related information. In Italy, hesitancy toward COVID-19/influenza vaccine co-administration is common and appears to be higher than hesitancy toward either vaccine administered alone. This pattern is multifaceted and requires specific and tailored strategies, with public health institutions playing the central role.
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http://dx.doi.org/10.3390/jpm12020139DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8878648PMC
January 2022

Evaluation of a Whole-Liver Dixon-Based MRI Approach for Quantification of Liver Fat in Patients with Type 2 Diabetes Treated with Two Isocaloric Different Diets.

Diagnostics (Basel) 2022 Feb 16;12(2). Epub 2022 Feb 16.

Institute of Biostructures and Bioimaging, National Research Council, 80145 Naples, Italy.

Dixon-based methods for the detection of fatty liver have the advantage of being non-invasive, easy to perform and analyze, and to provide a whole-liver coverage during the acquisition. The aim of the study was to assess the feasibility of a whole-liver Dixon-based approach for liver fat quantification in type 2 diabetes (T2D) patients who underwent two different isocaloric dietary treatments: a diet rich in monosaturated fatty acids (MUFA) and a multifactorial diet. Thirty-nine T2D patients were randomly assigned to MUFA diet ( = 21) and multifactorial diet ( = 18). The mean values of the proton density fat fraction (PDFF) over the whole liver and over the ROI corresponding to that chosen for MRS were compared to MRS-PDFF using Spearman's correlation (ρ). Before-after changes in percentage of liver volume corresponding to MRI-PDFF above thresholds associated with hepatic steatosis (LV%, with TH = 5.56%, 7.97% and 8.8%) were considered to assess the proposed approach and compared between diets using Wilcoxon rank-sum test. Statistical significance set at < 0.05. A strong linear relationship was found between MRS-PDFF and MRI-PDFFs (ρ = 0.85, < 0.0001). Changes in LV% were significantly higher ( < 0.05) in the multifactorial diet than in MUFA diet (25% vs. 9%, 35% vs. 12%, and 38% vs. 13% decrease, respectively, for TH = 5.56%, 7.97%, and 8.8%) and this was reproducible compared to results obtained using the standard liver fat analysis. A volumetric approach based on Dixon method could be an effective, non-invasive technique that could be used for the quantitative analysis of hepatic steatosis in T2D patients.
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http://dx.doi.org/10.3390/diagnostics12020514DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871286PMC
February 2022

A Complex Radiomic Signature in Luminal Breast Cancer from a Weighted Statistical Framework: A Pilot Study.

Diagnostics (Basel) 2022 Feb 15;12(2). Epub 2022 Feb 15.

IRCCS Synlab SDN, Via E. Gianturco, 113, 80143 Naples, Italy.

Radiomics is rapidly advancing in precision diagnostics and cancer treatment. However, there are several challenges that need to be addressed before translation to clinical use. This study presents an ad-hoc weighted statistical framework to explore radiomic biomarkers for a better characterization of the radiogenomic phenotypes in breast cancer. Thirty-six female patients with breast cancer were enrolled in this study. Radiomic features were extracted from MRI and PET imaging techniques for malignant and healthy lesions in each patient. To reduce within-subject bias, the ratio of radiomic features extracted from both lesions was calculated for each patient. Radiomic features were further normalized, comparing the z-score, quantile, and whitening normalization methods to reduce between-subjects bias. After feature reduction by Spearman's correlation, a methodological approach based on a principal component analysis (PCA) was applied. The results were compared and validated on twenty-seven patients to investigate the tumor grade, Ki-67 index, and molecular cancer subtypes using classification methods (LogitBoost, random forest, and linear discriminant analysis). The classification techniques achieved high area-under-the-curve values with one PC that was calculated by normalizing the radiomic features via the quantile method. This pilot study helped us to establish a robust framework of analysis to generate a combined radiomic signature, which may lead to more precise breast cancer prognosis.
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http://dx.doi.org/10.3390/diagnostics12020499DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871349PMC
February 2022

Self-Reported Sleep Quality Across Age Modulates Resting-State Functional Connectivity in Limbic and Fronto-Temporo-Parietal Networks: An Exploratory Cross-Sectional fMRI Study.

Front Aging Neurosci 2022 7;14:806374. Epub 2022 Feb 7.

Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Synlab SDN, Naples, Italy.

Sleep problems are increasingly present in the general population at any age, and they are frequently concurrent with-or predictive of-memory disturbances, anxiety, and depression. In this exploratory cross-sectional study, 54 healthy participants recruited in Naples (Italy; 23 females; mean age = 37.1 years, range = 20-68) completed the Pittsburgh Sleep Quality Index (PSQI) and a neurocognitive assessment concerning both verbal and visuospatial working memory as well as subjective measures of anxiety and depression. Then, 3T fMRI images with structural and resting-state functional sequences were acquired. A whole-brain seed-to-seed functional connectivity (FC) analysis was conducted by contrasting good (PSQI score <5) vs. bad (PSQI score ≥5) sleepers. Results highlighted FC differences in limbic and fronto-temporo-parietal brain areas. Also, bad sleepers showed an anxious/depressive behavioural phenotype and performed worse than good sleepers at visuospatial working-memory tasks. These findings may help to reveal the effects of sleep quality on daily-life cognitive functioning and further elucidate pathophysiological mechanisms of sleep disorders.
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http://dx.doi.org/10.3389/fnagi.2022.806374DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8859450PMC
February 2022

In silico recognition of a prognostic signature in basal-like breast cancer patients.

PLoS One 2022 15;17(2):e0264024. Epub 2022 Feb 15.

IRCCS Synlab SDN S.p.A., Naples, Italy.

Background: Triple-negative breast cancers (TNBCs) display poor prognosis, have a high risk of tumour recurrence, and exhibit high resistance to drug treatments. Based on their gene expression profiles, the majority of TNBCs are classified as basal-like breast cancers. Currently, there are not available widely-accepted prognostic markers to predict outcomes in basal-like subtype, so the selection of new prognostic indicators for this BC phenotype represents an unmet clinical challenge.

Results: Here, we attempted to address this challenging issue by exploiting a bioinformatics pipeline able to integrate transcriptomic, genomic, epigenomic, and clinical data freely accessible from public repositories. This pipeline starts from the application of the well-established network-based SWIM methodology on the transcriptomic data to unveil important (switch) genes in relation with a complex disease of interest. Then, survival and linear regression analyses are performed to associate the gene expression profiles of the switch genes with both the patients' clinical outcome and the disease aggressiveness. This allows us to identify a prognostic gene signature that in turn is fed to the last step of the pipeline consisting of an analysis at DNA level, to investigate whether variations in the expression of identified prognostic switch genes could be related to genetic (copy number variations) or epigenetic (DNA methylation differences) alterations in their gene loci, or to the activities of transcription factors binding to their promoter regions. Finally, changes in the protein expression levels corresponding to the so far identified prognostic switch genes are evaluated by immunohistochemical staining results taking advantage of the Human Protein Atlas.

Conclusion: The application of the proposed pipeline on the dataset of The Cancer Genome Atlas (TCGA)-Breast Invasive Carcinoma (BRCA) patients affected by basal-like subtype led to an in silico recognition of a basal-like specific gene signature composed of 11 potential prognostic biomarkers to be further investigated.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0264024PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8846521PMC
February 2022

Endogenous retroviruses co-opted as divergently transcribed regulatory elements shape the regulatory landscape of embryonic stem cells.

Nucleic Acids Res 2022 02;50(4):2111-2127

The Bioinformatics Centre, Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark.

Transposable elements are an abundant source of transcription factor binding sites, and favorable genomic integration may lead to their recruitment by the host genome for gene regulatory functions. However, it is unclear how frequent co-option of transposable elements as regulatory elements is, to which regulatory programs they contribute and how they compare to regulatory elements devoid of transposable elements. Here, we report a transcription initiation-centric, in-depth characterization of the transposon-derived regulatory landscape of mouse embryonic stem cells. We demonstrate that a substantial number of transposable element insertions, in particular endogenous retroviral elements, are associated with open chromatin regions that are divergently transcribed into unstable RNAs in a cell-type specific manner, and that these elements contribute to a sizable proportion of active enhancers and gene promoters. We further show that transposon subfamilies contribute differently and distinctly to the pluripotency regulatory program through their repertoires of transcription factor binding site sequences, shedding light on the formation of regulatory programs and the origins of regulatory elements.
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http://dx.doi.org/10.1093/nar/gkac088DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8887488PMC
February 2022

Geographic distribution and phenotype of European people with cystic fibrosis carrying A1006E mutation.

Respir Med 2022 02 6;192:106736. Epub 2022 Jan 6.

Pediatric Pulmonology and Cystic Fibrosis Unit, Hospital Clinico Universitario Virgen de la Arrixaca, Murcia, Spain; Department of Surgery, Paediatrics, Obstetrics and Genecology, Universidad de Murcia, Spain. Biomedical Research Institute of Murcia (IMIB), Murcia, Spain.

Background: A1006E is a Cystic Fibrosis (CF) mutation that is still not widely known. We report phenotypic features and geographic distribution of the largest cohort of people with CF (pwCF) carrying A1006E to date.

Methods: Study of European pwCF carrying A1006E mutation, included in the European CF Society Patient Registry (ECFSPR). Genotype, ancestries and all variables recorded were compared to a cohort of F508del/F508del patients. Rate of decline in percentage-of-predicted FEV (ppFEV) was also analyzed using the 2010-2017 ECFSPR.

Results: 44 pwCF carrying A1006E were reported (59% males), median age 33 years old (3-58), 54.5% Spanish and 40.9% Italian, most with ancestry in Murcia (Spain) and Lazio (Italy) regions. Compared to F508del homozygous, A1006E-pwCF were significantly older (75% vs. 52.5% ≥ 18 years old) and diagnosed at later median age (6.98 vs. 0.29 years); showed lower rates of meconium ileus (2.33% vs. 17.7%), pancreatic insufficiency (27.91% vs. 99.26%), diabetes (2.33% vs. 21.98%), liver disease (6.98% vs. 36.72%) and Pseudomonas aeruginosa chronic colonization (30.95% vs. 42.51%); and presented better nutrition (BMI z-score 0.44 vs. -0.43) and ppFEV (90.8% vs. 78.6%), with 18.9% (most >40 years old) having a ppFEV<70%. Additional ppFEV decline (0.96% per year) was attributed to F508del/F508del genotype (p = 0.0007). None died or needed organ transplantation during the study period.

Conclusions: A1006E-pwCF are mainly of Western Mediterranean Spanish and Italian descent. When compared with F508del/F508del-pwCF, they usually have a milder form of the disease, associated with pancreatic sufficiency and slower FEV decline. However, some will develop progressive respiratory impairment during adulthood.
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http://dx.doi.org/10.1016/j.rmed.2022.106736DOI Listing
February 2022

Machine Learning and Bioinformatics Framework Integration to Potential Familial DCM-Related Markers Discovery.

Genes (Basel) 2021 12 2;12(12). Epub 2021 Dec 2.

Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania "Luigi Vanvitelli", 80138 Naples, Italy.

Objectives: Dilated cardiomyopathy (DCM) is characterized by a specific transcriptome. Since the DCM molecular network is largely unknown, the aim was to identify specific disease-related molecular targets combining an original machine learning (ML) approach with protein-protein interaction network.

Methods: The transcriptomic profiles of human myocardial tissues were investigated integrating an original computational approach, based on the Custom Decision Tree algorithm, in a differential expression bioinformatic framework. Validation was performed by quantitative real-time PCR.

Results: Our preliminary study, using samples from transplanted tissues, allowed the discovery of specific DCM-related genes, including MYH6, NPPA, MT-RNR1 and NEAT1, already known to be involved in cardiomyopathies Interestingly, a combination of these expression profiles with clinical characteristics showed a significant association between NEAT1 and left ventricular end-diastolic diameter (LVEDD) (Rho = 0.73, = 0.05), according to severity classification (NYHA-class III).

Conclusions: The use of the ML approach was useful to discover preliminary specific genes that could lead to a rapid selection of molecular targets correlated with DCM clinical parameters. For the first time, NEAT1 under-expression was significantly associated with LVEDD in the human heart.
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http://dx.doi.org/10.3390/genes12121946DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8701745PMC
December 2021

Radiogenomics and Artificial Intelligence Approaches Applied to Cardiac Computed Tomography Angiography and Cardiac Magnetic Resonance for Precision Medicine in Coronary Heart Disease: A Systematic Review.

Circ Cardiovasc Imaging 2021 12 17;14(12):1133-1146. Epub 2021 Dec 17.

Department of Advanced Medical and Surgical Sciences (DAMSS), University of Campania "Luigi Vanvitelli", Naples, Italy (T.I., C.N.).

The risk of coronary heart disease (CHD) clinical manifestations and patient management is estimated according to risk scores accounting multifactorial risk factors, thus failing to cover the individual cardiovascular risk. Technological improvements in the field of medical imaging, in particular, in cardiac computed tomography angiography and cardiac magnetic resonance protocols, laid the development of radiogenomics. Radiogenomics aims to integrate a huge number of imaging features and molecular profiles to identify optimal radiomic/biomarker signatures. In addition, supervised and unsupervised artificial intelligence algorithms have the potential to combine different layers of data (imaging parameters and features, clinical variables and biomarkers) and elaborate complex and specific CHD risk models allowing more accurate diagnosis and reliable prognosis prediction. Literature from the past 5 years was systematically collected from PubMed and Scopus databases, and 60 studies were selected. We speculated the applicability of radiogenomics and artificial intelligence through the application of machine learning algorithms to identify CHD and characterize atherosclerotic lesions and myocardial abnormalities. Radiomic features extracted by cardiac computed tomography angiography and cardiac magnetic resonance showed good diagnostic accuracy for the identification of coronary plaques and myocardium structure; on the other hand, few studies exploited radiogenomics integration, thus suggesting further research efforts in this field. Cardiac computed tomography angiography resulted the most used noninvasive imaging modality for artificial intelligence applications. Several studies provided high performance for CHD diagnosis, classification, and prognostic assessment even though several efforts are still needed to validate and standardize algorithms for CHD patient routine according to good medical practice.
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http://dx.doi.org/10.1161/CIRCIMAGING.121.013025DOI Listing
December 2021

Rhinoplasty Pre-Surgery Models by Using Low-Dose Computed Tomography, Magnetic Resonance Imaging, and 3D Printing.

Dose Response 2021 Oct-Dec;19(4):15593258211060950. Epub 2021 Nov 29.

IRCCS SDN, Naples, Italy.

Rhinoplasty and surgical reconstruction of cartilaginous structures still remain a great challenge today. This study aims to identify an imaging strategy in order to merge the information from CT scans and magnetic resonance imaging (MRI) acquisitions and build a 3D printed model true to the patient's anatomy, for better surgical planning. Using MRI, information can be obtained about the cartilage structures of which the nose is composed. Ten rhinoplasty candidate patients underwent both a low-dose protocol CT scan and a specific MRI for characterization of nasal structures. Bone and soft tissue segmentations were performed in CT, while cartilage segmentations were extrapolated from MRI and validated by both an expert radiologist and surgeon. Subsequently, a 3D model was produced in materials and colors reproducing the density of the three main structures (bone, soft tissue, and cartilage), useful for pre-surgical evaluation. This study has highlighted that the optimization of a CT and MR dedicated protocol has allowed to reduce the CT radiation dose up to 60% compared to standard acquisitions with the same machine, and MR acquisition time of about 20%. Patient-tailored 3D models and pre-surgical planning have reduced the mean operative time by 20 minutes.
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http://dx.doi.org/10.1177/15593258211060950DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8647253PMC
November 2021

A Systematic Review on the Role of the Perfusion Computed Tomography in Abdominal Cancer.

Dose Response 2021 Oct-Dec;19(4):15593258211056199. Epub 2021 Nov 24.

IRCCS SDN, Naples, Italy.

Background And Purpose: Perfusion Computed Tomography (CTp) is an imaging technique which allows quantitative and qualitative evaluation of tissue perfusion through dynamic CT acquisitions. Since CTp is still considered a research tool in the field of abdominal imaging, the aim of this work is to provide a systematic summary of the current literature on CTp in the abdominal region to clarify the role of this technique for abdominal cancer applications.

Materials And Methods: A systematic literature search of PubMed, Web of Science, and Scopus was performed to identify original articles involving the use of CTp for clinical applications in abdominal cancer since 2011. Studies were included if they reported original data on CTp and investigated the clinical applications of CTp in abdominal cancer.

Results: Fifty-seven studies were finally included in the study. Most of the included articles (33/57) dealt with CTp at the level of the liver, while a low number of studies investigated CTp for oncologic diseases involving UGI tract (8/57), pancreas (8/57), kidneys (3/57), and colon-rectum (5/57).

Conclusions: Our study revealed that CTp could be a valuable functional imaging tool in the field of abdominal oncology, particularly as a biomarker for monitoring the response to anti-tumoral treatment.
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http://dx.doi.org/10.1177/15593258211056199DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8647276PMC
November 2021

How does DICOM support big data management? Investigating its use in medical imaging community.

Insights Imaging 2021 Nov 8;12(1):164. Epub 2021 Nov 8.

IRCCS SDN, Via Emanuele Gianturco 113, 80143, Naples, Italy.

The diagnostic imaging field is experiencing considerable growth, followed by increasing production of massive amounts of data. The lack of standardization and privacy concerns are considered the main barriers to big data capitalization. This work aims to verify whether the advanced features of the DICOM standard, beyond imaging data storage, are effectively used in research practice. This issue will be analyzed by investigating the publicly shared medical imaging databases and assessing how much the most common medical imaging software tools support DICOM in all its potential. Therefore, 100 public databases and ten medical imaging software tools were selected and examined using a systematic approach. In particular, the DICOM fields related to privacy, segmentation and reporting have been assessed in the selected database; software tools have been evaluated for reading and writing the same DICOM fields. From our analysis, less than a third of the databases examined use the DICOM format to record meaningful information to manage the images. Regarding software, the vast majority does not allow the management, reading and writing of some or all the DICOM fields. Surprisingly, if we observe chest computed tomography data sharing to address the COVID-19 emergency, there are only two datasets out of 12 released in DICOM format. Our work shows how the DICOM can potentially fully support big data management; however, further efforts are still needed from the scientific and technological community to promote the use of the existing standard, encouraging data sharing and interoperability for a concrete development of big data analytics.
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http://dx.doi.org/10.1186/s13244-021-01081-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8574146PMC
November 2021

Diffusion tensor imaging for the study of early renal dysfunction in patients affected by bardet-biedl syndrome.

Sci Rep 2021 10 21;11(1):20855. Epub 2021 Oct 21.

IRCCS SDN, Via Emanuele Gianturco 113, 80131, Naples, Italy.

Kidney structural abnormalities are common features of Bardet-Biedl syndrome (BBS) patients that lead to a progressive decline in renal function. Magnetic resonance diffusion tensor imaging (DTI) provides useful information on renal microstructures but it has not been applied to these patients. This study investigated using DTI to detect renal abnormalities in BBS patients with no overt renal dysfunction. Ten BBS subjects with estimated glomerular filtration rates over 60 ml/min/1.73m and 14 individuals matched for age, gender, body mass index and renal function were subjected to high-field DTI. Fractional anisotropy (FA), and mean, radial and axial diffusivity were evaluated from renal cortex and medulla. Moreover, the corticomedullary differentiation of each DTI parameter was compared between groups. Only cortical FA statistically differed between BBS patients and controls (p = 0.033), but all the medullary DTI parameters discriminated between the two groups with lower FA (p < 0.001) and axial diffusivity (p = 0.021) and higher mean diffusivity (p = 0.043) and radial diffusivity (p < 0.001) in BBS patients compared with controls. Corticomedullary differentiation values were significantly reduced in BBS patients. Thus, DTI is a valuable tool for investigating microstructural alterations in renal disorders when kidney functionality is preserved.
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http://dx.doi.org/10.1038/s41598-021-00394-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531379PMC
October 2021

Impact of radiogenomics in esophageal cancer on clinical outcomes: A pilot study.

World J Gastroenterol 2021 Sep;27(36):6110-6127

IRCCS SDN, Naples 80143, Italy.

Background: Esophageal cancer (ESCA) is the sixth most common malignancy in the world, and its incidence is rapidly increasing. Recently, several microRNAs (miRNAs) and messenger RNA (mRNA) targets were evaluated as potential biomarkers and regulators of epigenetic mechanisms involved in early diagnosis. In addition, computed tomography (CT) radiomic studies on ESCA improved the early stage identification and the prediction of response to treatment. Radiogenomics provides clinically useful prognostic predictions by linking molecular characteristics such as gene mutations and gene expression patterns of malignant tumors with medical images and could provide more opportunities in the management of patients with ESCA.

Aim: To explore the combination of CT radiomic features and molecular targets associated with clinical outcomes for characterization of ESCA patients.

Methods: Of 15 patients with diagnosed ESCA were included in this study and their CT imaging and transcriptomic data were extracted from The Cancer Imaging Archive and gene expression data from The Cancer Genome Atlas, respectively. Cancer stage, history of significant alcohol consumption and body mass index (BMI) were considered as clinical outcomes. Radiomic analysis was performed on CT images acquired after injection of contrast medium. In total, 1302 radiomics features were extracted from three-dimensional regions of interest by using PyRadiomics. Feature selection was performed using a correlation filter based on Spearman's correlation (ρ) and Wilcoxon-rank sum test respect to clinical outcomes. Radiogenomic analysis involved ρ analysis between radiomic features associated with clinical outcomes and transcriptomic signatures consisting of eight N6-methyladenosine RNA methylation regulators and five up-regulated miRNA. The significance level was set at < 0.05.

Results: Of 25, five and 29 radiomic features survived after feature selection, considering stage, alcohol history and BMI as clinical outcomes, respectively. Radiogenomic analysis with stage as clinical outcome revealed that six of the eight mRNA regulators and two of the five up-regulated miRNA were significantly correlated with ten and three of the 25 selected radiomic features, respectively (-0.61 < ρ < -0.60 and 0.53 < ρ < 0.69, < 0.05). Assuming alcohol history as clinical outcome, no correlation was found between the five selected radiomic features and mRNA regulators, while a significant correlation was found between one radiomic feature and three up-regulated miRNAs (ρ = -0.56, ρ = -0.64 and ρ = 0.61, < 0.05). Radiogenomic analysis with BMI as clinical outcome revealed that four mRNA regulators and one up-regulated miRNA were significantly correlated with 10 and two radiomic features, respectively (-0.67 < ρ < -0.54 and 0.53 < ρ < 0.71, < 0.05).

Conclusion: Our study revealed interesting relationships between the expression of eight N6-methyladenosine RNA regulators, as well as five up-regulated miRNAs, and CT radiomic features associated with clinical outcomes of ESCA patients.
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http://dx.doi.org/10.3748/wjg.v27.i36.6110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8476334PMC
September 2021

Impact of Breast Tumor Onset on Blood Count, Carcinoembryonic Antigen, Cancer Antigen 15-3 and Lymphoid Subpopulations Supported by Automatic Classification Approach: A Pilot Study.

Cancer Control 2021 Jan-Dec;28:10732748211048612

591458IRCCS SDN, Naples, Italy.

Background: Recent observations showed that systemic immune changes are detectable in case of breast cancer (BC). In this preliminary study, we investigated routinely measured peripheral blood (PB) parameters for malignant BC cases in comparison to benign breast conditions. Complete blood count, circulating lymphoid subpopulation, and serological carcinoembryonic antigen (CEA) and cancer antigen 15-3 (CA15-3) levels were considered.

Methods: A total of 127 female patients affected by malignant (n = 77, mean age = 63 years, min = 36, max = 90) BC at diagnosis (naïve patients) or benign breast conditions (n = 50, mean age = 33 years, min = 18, max = 60) were included in this study. For each patient, complete blood count and lymphoid subpopulations (T-helper, T-cytotoxic, B-, NK-, and NKT-cells) analysis on PB samples were performed. Hormonal receptor status, Ki-67 expression, and serological CEA and CA15-3 levels were assessed in the case of patients with malignant BC via statistical analysis.

Results: Women with malignant BC disclosed increased circulating T-helper lymphocytes and CD4/CD8 ratio in PB when compared to those affected by benign breast conditions (2.345 vs 1.894, < .05 Wilcoxon rank-sum test). In the case of malignant BC patients, additive logistic regression method was able to identify malignant BC cases with increased CA15-3 levels (CA15-3 >25 UI/mL) via the hematocrit and neutrophils/lymphocytes ratio values. Moreover, in the case of women with aggressive malignant BC featured by high levels of Ki-67 proliferation marker, an increasing number of correlations were found among blood count parameters and lymphocytes subpopulations by performing a Spearman's correlation analysis.

Conclusions: This preliminary study confirms the ability of malignant BC to determine systemic modifications. The stratification of malignant BC cases according to the Ki-67 proliferation marker highlighted increasing detectable alterations in the periphery of women with aggressive BC. The advent of novel and more sensitive biomarkers, as well as deep immunophenotyping technologies, will provide additional insights for describing the relationship between tumor onset and peripheral alterations.
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http://dx.doi.org/10.1177/10732748211048612DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8504274PMC
January 2022

Structural Brain Network Reproducibility: Influence of Different Diffusion Acquisition and Tractography Reconstruction Schemes on Graph Metrics.

Brain Connect 2021 Dec 6. Epub 2021 Dec 6.

IRCCS SDN, Napoli, Italy.

Graph metrics of structural brain networks demonstrate to be a powerful tool for investigating brain topology at a large scale. However, the variability of the results related to applying different magnetic resonance acquisition schemes and tractography reconstruction techniques is not fully characterized. The present work aims to evaluate the influence of different combinations of diffusion acquisition schemes (single and multishell), diffusion models (tensor and spherical deconvolution), and tractography reconstruction approaches (deterministic and probabilistic) on the reproducibility of graph metrics derived from structural connectome on test/retest (TRT) data released by the Human Connectome Project. From each implemented experimental setup, both global and local graph metrics were evaluated and their reproducibility was estimated by the intraclass correlation coefficient (ICC). Moreover, the percentage relative standard deviation (pRSD) from the ICC values of local graph metrics was calculated to quantify how much the reproducibility varied across nodes within each experimental setup. The presented results show that different combinations of diffusion acquisition schemes, diffusion models, and tractography algorithms can strongly affect the reproducibility of global and local graph metrics. The combination of constrained spherical deconvolution (CSD) and deterministic tractography gave generally high reproducibility (ICCs >0.75) and lowest pRSD for the considered graph metrics, meanwhile probabilistic CSD with a high -value returned the highest reproducibility. Notably, the introduction of streamline selection filters on CSD can substantially affect the reproducibility. This work demonstrates that the TRT reproducibility of graph metrics is generally high but can vary substantially with different combinations of acquisition and reconstruction schemes. Impact statement This work demonstrates the influence of different diffusion acquisition schemes, diffusion models, and tractography reconstruction approaches on the reproducibility of graph metrics derived from structural connectome. The presented findings impact on the choice of both acquisition protocol and processing pipeline for topological analyses to produce reproducible measurements for brain network studies.
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http://dx.doi.org/10.1089/brain.2021.0123DOI Listing
December 2021
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