Search results for: Calogero Lo Destro

Authors: Calogero Lo Destro

Abstract:

Numerous nations around the world are facing exceptional challenges in employing measures to stop the spread of COVID-19. Following the recommendations of the World Health Organization, a series of preventive measures have been adopted. However, individuals must comply with these rules and recommendations in order to make these measures effective. While COVID-19 was climaxing, it seemed of crucial importance to analyze which psychosocial factors contribute to the acceptance of such preventive behavior, thus favoring the management of COVID-19 worldwide health crisis. In particular, the identification of aspects related to obstacles and facilitation of adherence to social distancing has been considered crucial in the containment of the virus spread. Since the virus was firstly detected in China, Asian people could be considered a relevant outgroup targeted for exclusion. We also hypothesized social distance could be influenced by characteristics of the target, such as smiling or coughing. 260 participants participated in this research on a voluntary basis. They filled a survey designed to explore a series of COVID-19 measures (such as exposure to virus and fear of infection). We also assessed participants state and trait anxiety. The dependent variable was social distance, based on a measure of seating distance designed ad hoc for the present work. Our hypothesis that participants could report greater distance in response to Asian people was not confirmed. On the other hand, significantly lower distance in response to smiling compared to coughing targets was reported. Adopting a regression analysis model, we found that participants' social distance, in response to both coughing and smiling targets, was predicted by fear of infection and by the perception COVID-19 could become a pandemic. Social distance in response to the coughing target was also significantly and positively predicted by age and state anxiety. In summary, the present work has sought to identify a set of psychological variables, which may still be predictive of social distancing.

Keywords: COVID-19, social distancing, health, preventive behaviors, risk of infection

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Authors: Raffaele A. Calogero

Abstract:

RNAseq represents an attractive methodology for the detection of functional genomic variants. RNAseq results obtained from polyA+ RNA selection protocol (POLYA) and from exonic regions capturing protocol (ACCESS) indicate that ACCESS detects 10% more coding SNV/INDELs with respect to POLYA. ACCESS requires less reads for coding SNV detection with respect to POLYA. However, if the analysis aims at identifying SNV/INDELs also in the 5’ and 3’ UTRs, POLYA is definitively the preferred method. No particular advantage comes from ACCESS or POLYA in the detection of fusion transcripts.

Keywords: fusion transcripts, INDEL, RNA-seq, WES, SNV

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Authors: Vinicius Buccelli Ribeiro, Maria Teresa Destro, Mariza Landgraf

Abstract:

Bacteriophages are one of the most abundant replicating entities on Earth and can be found everywhere in which their hosts live and there are reports regarding isolation from different niches such as soil and foods. Since studies are moving forward with regard to biotechnology area, different research projects are being performed focusing on the phage technology and its use by the food industry. This study aimed to evaluate a cocktail (LP501) of phages isolated in Brazil for its lytic potential against Listeria monocytogenes. Three bacteriophages (LP05, LP12 and LP20) were isolated from soil samples and all of them showed 100% lysis against a panel of 10 L. monocytogenes strains representing different serotypes of this pathogen. A mix of L. monocytogenes 1/2a and 4b were inoculated in soft cheeses (approximately 105 cfu/cm2) with the phage cocktail added thereafter (1 x 109 PFU/cm2). Samples were analyzed immediately and then stored at 10°C for ten days. At 30 min post-infection, the cocktail reduced L. monocytogenes counts approximately 1.5 logs, compared to controls without bacteriophage. The treatment produced a statistically significant decrease in the counts of viable cells (p < 0.05) and in all assays performed we observed a decrease of up to 4 logs of L. monocytogenes. This study will make available to the international community behavioral and molecular data regarding bacteriophages present in soil samples in Brazil. Furthermore, there is the possibility to apply this new cocktail of phages in different food products to combat L. monocytogenes.

Keywords: bacteriophages, biocontrol, listeria monocytogenes, soft cheese

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Authors: Maddalena Arigoni, Maria Luisa Ratto, Raffaele A. Calogero, Luca Alessandri

Abstract:

The presence of tumor heterogeneity, where distinct cancer cells exhibit diverse morphological and phenotypic profiles, including gene expression, metabolism, and proliferation, poses challenges for molecular prognostic markers and patient classification for targeted therapies. Understanding the causes and progression of cancer requires research efforts aimed at characterizing heterogeneity, which can be facilitated by evolving single-cell sequencing technologies. However, analyzing single-cell data necessitates computational methods that often lack objective validation. Therefore, the establishment of benchmarking datasets is necessary to provide a controlled environment for validating bioinformatics tools in the field of single-cell oncology. Benchmarking bioinformatics tools for single-cell experiments can be costly due to the high expense involved. Therefore, datasets used for benchmarking are typically sourced from publicly available experiments, which often lack a comprehensive cell annotation. This limitation can affect the accuracy and effectiveness of such experiments as benchmarking tools. To address this issue, we introduce omics benchmark experiments designed to evaluate bioinformatics tools to depict the heterogeneity in single-cell tumor experiments. We conducted single-cell RNA sequencing on six lung cancer tumor cell lines that display resistant clones upon treatment of EGFR mutated tumors and are characterized by driver genes, namely ROS1, ALK, HER2, MET, KRAS, and BRAF. These driver genes are associated with downstream networks controlled by EGFR mutations, such as JAK-STAT, PI3K-AKT-mTOR, and MEK-ERK. The experiment also featured an EGFR-mutated cell line. Using 10XGenomics platform with cellplex technology, we analyzed the seven cell lines together with a pseudo-immunological microenvironment consisting of PBMC cells labeled with the Biolegend TotalSeq™-B Human Universal Cocktail (CITEseq). This technology allowed for independent labeling of each cell line and single-cell analysis of the pooled seven cell lines and the pseudo-microenvironment. The data generated from the aforementioned experiments are available as part of an online tool, which allows users to define cell heterogeneity and generates count tables as an output. The tool provides the cell line derivation for each cell and cell annotations for the pseudo-microenvironment based on CITEseq data by an experienced immunologist. Additionally, we created a range of pseudo-tumor tissues using different ratios of the aforementioned cells embedded in matrigel. These tissues were analyzed using 10XGenomics (FFPE samples) and Curio Bioscience (fresh frozen samples) platforms for spatial transcriptomics, further expanding the scope of our benchmark experiments. The benchmark experiments we conducted provide a unique opportunity to evaluate the performance of bioinformatics tools for detecting and characterizing tumor heterogeneity at the single-cell level. Overall, our experiments provide a controlled and standardized environment for assessing the accuracy and robustness of bioinformatics tools for studying tumor heterogeneity at the single-cell level, which can ultimately lead to more precise and effective cancer diagnosis and treatment.

Keywords: single cell omics, benchmark, spatial transcriptomics, CITEseq

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