Background: The aim of the present review is to discuss how the promising field of biobanking can support health care research strategies. As the concept has evolved over time, biobanks have grown from simple biological sample repositories to complex and dynamic units belonging to large infrastructure networks, such as the Pan-European Biobanking and Biomolecular Resources Research Infrastructure (BBMRI). Biobanks were established to support scientific knowledge. Different professional figures with varied expertise collaborate to obtain and collect biological and clinical data from human subjects. At same time biobanks preserve the human and legal rights of each person that offers biomaterial for research.Methods: A literature review was conducted in April 2019 from the online database PubMed, accessed through the Bibliosan platform. Four primary topics related to biobanking will be discussed: (i) evolution, (ii) bioethical issues, (iii) organization, and (iv) imaging.Results: Most biobanks were founded as local units to support specific research projects, so they evolved in a decentralized manner. The consequence is an urgent needing for procedure harmonization regarding sample collection, processing, and storage. Considering the involvement of biomaterials obtained from human beings, different ethical issues such as the informed consent model, sample ownership, veto rights, and biobank sustainability are debated. In the face of these methodological and ethical challenges, international organizations such as BBMRI play a key role in supporting biobanking activities. Finally, a unique development is the creation of imaging biobanks that support the translation of imaging biomarkers (identified using a radiomic approach) into clinical practice by ensuring standardization of data acquisition and analysis, accredited technical validation, and transparent sharing of biological and clinical data.Conclusion: Modern biobanks permit large-scale analysis for individuation of specific diseases biomarkers starting from biological or digital material (i.e., bioimages) with well-annotated clinical and biological data. These features are essential for improving personalized medical approaches, where effective biomarker identification is a critical step for disease diagnosis and prognosis.

Cell lines are in vitro model systems that are widely used in different fields of medical research, especially basic cancer research and drug discovery. Their usefulness is primarily linked to their ability to provide an indefinite source of biological material for experimental purposes. Under the right conditions and with appropriate controls, authenticated cancer cell lines retain most of the genetic properties of the cancer of origin. During the last few years, comparing genomic data of most cancer cell lines has corroborated this statement and those that were observed studying the tumoral tissue equivalents included in the The Cancer Genome Atlas (TCGA) database. We are at the disposal of comprehensive open access cell line datasets describing their molecular and cellular alterations at an unprecedented level of accuracy. This aspect, in association with the possibility of setting up accurate culture conditions that mimic the in vivo microenvironment (e.g., three-dimensional (3D) coculture), has strengthened the importance of cancer cell lines for continuing to sustain medical research fields. However, it is important to consider that the appropriate use of cell lines needs to follow established guidelines for guaranteed data reproducibility and quality, and to prevent the occurrence of detrimental events (i.e., those that are linked to cross-contamination and mycoplasma contamination).

Background: Metagenomic data support an association between certain bacterial strains and Alzheimer’s disease (AD), but their functional dynamics remain elusive. Objective: To investigate the association between amyloid pathology, bacterial products such as lipopolysaccharide (LPS) and short chain fatty acids (SCFAs: acetate, valerate, butyrate), inflammatory mediators, and markers of endothelial dysfunction in AD. Methods: Eighty-nine older persons with cognitive performance from normal to dementia underwent florbetapir amyloid PET and blood collection. Brain amyloidosis was measured with standardized uptake value ratio versus cerebellum. Blood levels of LPS were measured by ELISA, SCFAs by mass spectrometry, cytokines by using real-time PCR, and biomarkers of endothelial dysfunction by flow cytometry. We investigated the association between the variables listed above with Spearman’s rank test. Results: Amyloid SUVR uptake was positively associated with blood LPS (rho≥0.32, p≤0.006), acetate and valerate (rho≥0.45, p < 0.001), pro-inflammatory cytokines (rho≥0.25, p≤0.012), and biomarkers of endothelial dysfunction (rho≥0.25, p≤0.042). In contrast, it was negatively correlated with butyrate (rho≤–0.42, p≤0.020) and the anti-inflammatory cytokine IL10 (rho≤–0.26, p≤0.009). Endothelial dysfunction was positively associated with pro-inflammatory cytokines, acetate and valerate (rho≥0.25, p≤0.045) and negatively with butyrate and IL10 levels (rho≤–0.25, p≤0.038). Conclusion: We report a novel association between gut microbiota-related products and systemic inflammation with brain amyloidosis via endothelial dysfunction, suggesting that SCFAs and LPS represent candidate pathophysiologic links between the gut microbiota and AD pathology.

In the last few years, biomedical research has been boosted by the technological development of analytical instrumentation generating a large volume of data. Such information has increased in complexity from basic (i.e., blood samples) to extensive sets encompassing many aspects of a subject phenotype, and now rapidly extending into genetic and, more recently, radiomic information. Radiogenomics integrates both aspects, investigating the relationship between imaging features and gene expression. From a methodological point of view, radiogenomics takes advantage of non-conventional data analysis techniques that reveal meaningful information for decision-support in cancer diagnosis and treatment. This survey is aimed to review the state-of-the-art techniques employed in radiomics and genomics with special focus on analysis methods based on molecular and multimodal probes. The impact of single and combined techniques will be discussed in light of their suitability in correlation and predictive studies of specific oncologic diseases.

Anhidrotic Ectodermal Dysplasia with ImmunoDeficiency (EDA-ID, OMIM 300291) and Incontinentia Pigmenti (IP, OMIM 308300) are two rare diseases, caused by mutations of the IKBKG/NEMO gene. The protein NEMO/IKKγ is essential for the NF-κB activation pathway, involved in a variety of physiological and cellular processes, such as immunity, inflammation, cell proliferation, and survival. A wide spectrum of IKBKG/NEMO mutations have been identified so far, and, on the basis of their effect on NF-κB activation, they are considered hypomorphic or amorphic (loss of function) mutations. IKBKG/NEMO hypomorphic mutations, reducing but not abolishing NF-κB activation, have been identified in EDA-ID and IP patients. Instead, the amorphic mutations, abolishing NF-κB activation by complete IKBKG/NEMO gene silencing, cause only IP. Here, we present an overview of IKBKG/NEMO mutations in EDA-ID and IP patients and describe similarities and differences between the clinical/immunophenotypic and genetic aspects, highlighting any T and B lymphocyte defect, and paying particular attention to the cellular and molecular defects that underlie the pathogenesis of both diseases.

After leaving the endoplasmic reticulum, secretory proteins traverse several membranous transport compartments before reaching their destinations. How they move through the Golgi complex, a major secretory station composed of stacks of membranous cisternae, is a central yet unsettled issue in membrane biology. Two classes of mechanisms have been proposed. One is based on cargo-laden carriers hopping across stable cisternae and the other on “maturing” cisternae that carry cargo forward while progressing through the stack. A key difference between the two concerns the behavior of Golgi-resident proteins. Under stable cisternae models, Golgi residents remain in the same cisterna, whereas, according to cisternal maturation, Golgi residents recycle from distal to proximal cisternae via retrograde carriers in synchrony with cisternal progression. Here, we have engineered Golgi-resident constructs that can be polymerized at will to prevent their recycling via Golgi carriers. Maturation models predict the progress of such polymerized residents through the stack along with cargo, but stable cisternae models do not. The results support the cisternal maturation mechanism.