A Soft-Voting Ensemble Classifier for Detecting Patients Affected by COVID-19

COVID-19 is an ongoing global pandemic of coronavirus disease 2019, which may cause severe acute respiratory syndrome. This disease highlighted the limitations of health systems worldwide regarding managing the pandemic. In particular, the lack of diagnostic tests that can quickly and reliably detect infected patients has contributed to the spread of the virus. Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) and antigen tests, which are the main diagnostic tests for COVID-19, showed their limitations during the pandemic. In fact, RT-PCR requires several hours to provide a diagnosis and is not properly accurate, thus generating a high number of false negatives. Unlike RT-PCR, antigen tests provide rapid diagnosis but are less accurate in detecting COVID-19 positive patients. Medical imaging is an alternative diagnostic test for COVID-19. In particular, chest computed tomography allows detecting lung infections related to the disease with high accuracy. However, visual analysis of a chest scan generated by computed tomography is a demanding activity for radiologists, making widespread use of this test unfeasible. Therefore, it is essential to lighten their work with automated tools able to provide accurate diagnosis in a short time. To deal with this challenge, in this work, an approach based on 3D Inception CNNs is proposed. Specifically, 3D Inception-V1 and Inception-V3 models have been built and compared. Then, soft-voting ensemble classifier models have been separately built on these models to boost the performance. As for the individual models, results showed that Inception-V1 outperformed Inception-V3 according to different measures. As for the ensemble classifier models, the outcome of experiments pointed out that the adopted voting strategy boosted the performance of individual models. The best results have been achieved enforcing soft voting on Inception-V1 models

A HPC and Grid enabling framework for genetic linkage analysis of SNPs

Understanding the structure, function and development of the human genome is a key factor to improve the quality of life. In order to achieve this goal developing and using a modern ICT infrastructure is essential, and can exploit next generation High Performance Computing (HPC) systems beyond the Petaflop scale in a collaborative and efficient way. The genetic linkage analysis of Single Nucleotide Polymorphism (SNP) markers has recently become a very popular approach for genetic epidemiology and population studies, aiming to discover the genetic correlation in complex diseases. The high computational cost and memory requirements of the major algorithms proposed in the literature make analyses of medium/large data sets very hard on a single CPU. A Grid based facility has hence been set up upon a high-performance infrastructure, the EGEE Grid, in order to create a tool for achieving whole-genome linkage analysis

A HPC and Grid enabling framework for genetic linkage analysis of SNPs

Understanding the structure, function and development of the human genome is a key factor to improve the quality of life. In order to achieve this goal developing and using a modern ICT infrastructure is essential, and can exploit next generation High Performance Computing (HPC) systems beyond the Petaflop scale in a collaborative and efficient way. The genetic linkage analysis of Single Nucleotide Polymorphism (SNP) markers has recently become a very popular approach for genetic epidemiology and population studies, aiming to discover the genetic correlation in complex diseases. The high computational cost and memory requirements of the major algorithms proposed in the literature make analyses of medium/large data sets very hard on a single CPU. A Grid based facility has hence been set up upon a high-performance infrastructure, the EGEE Grid, in order to create a tool for achieving whole-genome linkage analysis

History of mammography: analysis of breast imaging diagnostic achievements over the last century

Breast cancer is the most common forms of cancer and a leading cause of mortality in women. Early and correct diagnosis is, therefore, essential to save lives. The development of diagnostic imaging applied to the breast has been impressive in recent years and the most used diagnostic test in the world is mammography, a low-dose X-ray technique used for imaging the breast. In the first half of the 20th century, the diagnosis was in practice only clinical, with consequent diagnostic delay and an unfavorable prognosis in the short term. The rise of organized mammography screening has led to a remarkable reduction in mortality through the early detection of breast malignancies. This historical review aims to offer a complete panorama of the development of mammography and breast imaging during the last century. Through this study, we want to understand the foundations of the pillar of radiology applied to the breast through to the most modern applications such as contrast-enhanced mammography (CEM), artificial intelligence, and radiomics. Understanding the history of the development of diagnostic imaging applied to the breast can help us understand how to better direct our efforts toward an increasingly personalized and effective diagnostic approach. The ultimate goal of imaging applied to the detection of breast malignancies should be to reduce mortality from this type of disease as much as possible. With this paper, we want to provide detailed documentation of the main steps in the evolution of breast imaging for the diagnosis of breast neoplasms; we also want to open up new scenarios where the possible current and future applications of imaging are aimed at being more precise and personalized

ACYLATED AND UNACYLATED GHRELIN IMPAIR SKELETAL MUSCLE ATROPHY IN MICE.

Cachexia is a wasting syndrome associated with cancer, AIDS, and multiple sclerosis, and several other disease states. It is characterized by weight loss, fatigue, loss of appetite and skeletal muscle atrophy and is associated with poor patient prognosis, making it an important treatment target. Ghrelin is a peptide hormone that stimulates growth hormone (GH) release and positive energy balance through binding to the receptor GHSR-1a. Only acylated ghrelin (AG), but not the unacylated form (UnAG), can bind GHSR-1a; however, UnAG and AG share several GHSR-1aindependent biological activities. Here we investigated whether UnAG and AG could protect against skeletal muscle atrophy in a GHSR-1a-independent manner. We found that both AG and UnAG inhibited dexamethasone-induced skeletal muscle atrophy and atrogene expression through PI3K\u3b2-, mTORC2-, and p38-mediated pathways in myotubes. Up-regulation of circulating UnAG in mice impaired skeletal muscle atrophy induced by either fasting or denervation without stimulating muscle hypertrophy and GHSR-1a-mediated activation of the GH/IGF-1 axis. In Ghsrdeficient mice, both AG and UnAG induced phosphorylation of Akt in skeletal muscle and impaired fasting-induced atrophy. These results demonstrate that AG and UnAG act on a common, unidentified receptor to block skeletal muscle atrophy in a GH-independent manner

Further Characterisation of the Molecular Signature of Quiescent and Activated Mouse Muscle Satellite Cells

Satellite cells are the resident stem cells of adult skeletal muscle. To date though, there is a paucity of native markers that can be used to easily identify quiescent satellite cells, with Pax7 probably being the best that is currently available. Here we have further characterized a number of recently described satellite cell markers, and also describe novel ones. Caveolin-1, integrin α7 and the calcitonin receptor proved reliable markers for quiescent satellite cells, being expressed by all satellite cells identified with Pax7. These three markers remained expressed as satellite cells were activated and underwent proliferation. The nuclear envelope proteins lamin A/C and emerin, mutations in which underlie Emery-Dreifuss muscular dystrophy, were also expressed in both quiescent and proliferating satellite cells. Conversely, Jagged-1, a Notch ligand, was not expressed in quiescent satellite cells but was induced upon activation. These findings further contribute to defining the molecular signature of muscle satellite cells

Uncoordinated Transcription and Compromised Muscle Function in the Lmna-Null Mouse Model of Emery-Dreifuss Muscular Dystrophy

LMNA encodes both lamin A and C: major components of the nuclear lamina. Mutations in LMNA underlie a range of tissue-specific degenerative diseases, including those that affect skeletal muscle, such as autosomal-Emery-Dreifuss muscular dystrophy (A-EDMD) and limb girdle muscular dystrophy 1B. Here, we examine the morphology and transcriptional activity of myonuclei, the structure of the myotendinous junction and the muscle contraction dynamics in the lmna-null mouse model of A-EDMD. We found that there were fewer myonuclei in lmna-null mice, of which ∼50% had morphological abnormalities. Assaying transcriptional activity by examining acetylated histone H3 and PABPN1 levels indicated that there was a lack of coordinated transcription between myonuclei lacking lamin A/C. Myonuclei with abnormal morphology and transcriptional activity were distributed along the length of the myofibre, but accumulated at the myotendinous junction. Indeed, in addition to the presence of abnormal myonuclei, the structure of the myotendinous junction was perturbed, with disorganised sarcomeres and reduced interdigitation with the tendon, together with lipid and collagen deposition. Functionally, muscle contraction became severely affected within weeks of birth, with specific force generation dropping as low as ∼65% and ∼27% of control values in the extensor digitorum longus and soleus muscles respectively. These observations illustrate the importance of lamin A/C for correct myonuclear function, which likely acts synergistically with myotendinous junction disorganisation in the development of A-EDMD, and the consequential reduction in force generation and muscle wasting

A sex-informed approach to improve the personalised decision making process in myelodysplastic syndromes: a multicentre, observational cohort study

Background Sex is a major source of diversity among patients and a sex-informed approach is becoming a new paradigm in precision medicine. We aimed to describe sex diversity in myelodysplastic syndromes in terms of disease genotype, phenotype, and clinical outcome. Moreover, we sought to incorporate sex information into the clinical decision-making process as a fundamental component of patient individuality. Methods In this multicentre, observational cohort study, we retrospectively analysed 13 284 patients aged 18 years or older with a diagnosis of myelodysplastic syndrome according to 2016 WHO criteria included in the EuroMDS network (n=2025), International Working Group for Prognosis in MDS (IWG-PM; n=2387), the Spanish Group of Myelodysplastic Syndromes registry (GESMD; n=7687), or the Dusseldorf MDS registry (n=1185). Recruitment periods for these cohorts were between 1990 and 2016. The correlation between sex and genomic features was analysed in the EuroMDS cohort and validated in the IWG-PM cohort. The effect of sex on clinical outcome, with overall survival as the main endpoint, was analysed in the EuroMDS population and validated in the other three cohorts. Finally, novel prognostic models incorporating sex and genomic information were built and validated, and compared to the widely used revised International Prognostic Scoring System (IPSS-R). This study is registered with ClinicalTrials.gov, NCT04889729. Findings The study included 7792 (58middot7%) men and 5492 (41middot3%) women. 10 906 (82middot1%) patients were White, and race was not reported for 2378 (17middot9%) patients. Sex biases were observed at the single-gene level with mutations in seven genes enriched in men (ASXL1, SRSF2, and ZRSR2 p<0middot0001 in both cohorts; DDX41 not available in the EuroMDS cohort vs p=0middot0062 in the IWG-PM cohort; IDH2 p<0middot0001 in EuroMDS vs p=0middot042 in IWG-PM; TET2 p=0middot031 vs p=0middot035; U2AF1 p=0middot033 vs p<0middot0001) and mutations in two genes were enriched in women (DNMT3A p<0middot0001 in EuroMDS vs p=0middot011 in IWG-PM; TP53 p=0middot030 vs p=0middot037). Additionally, sex biases were observed in co-mutational pathways of founding genomic lesions (splicing-related genes, predominantly in men, p<0middot0001 in both the EuroMDS and IWG-PM cohorts), in DNA methylation (predominantly in men, p=0middot046 in EuroMDS vs p<0middot0001 in IWG-PM), and TP53 mutational pathways (predominantly in women, p=0middot0073 in EuroMDS vs p<0middot0001 in IWG-PM). In the retrospective EuroMDS cohort, men had worse median overall survival (81middot3 months, 95% CI 70middot4-95middot0 in men vs 123middot5 months, 104middot5-127middot5 in women; hazard ratio [HR] 1middot40, 95% CI 1middot26-1middot52; p<0middot0001). This result was confirmed in the prospective validation cohorts (median overall survival was 54middot7 months, 95% CI 52middot4-59middot1 in men vs 74middot4 months, 69middot3-81middot2 in women; HR 1middot30, 95% CI 1middot23-1middot35; p<0middot0001 in the GEMSD MDS registry; 40middot0 months, 95% CI 33middot4-43middot7 in men vs 54middot2 months, 38middot6-63middot8 in women; HR 1middot23, 95% CI 1middot08-1middot36; p<0middot0001 in the Dusseldorf MDS registry). We developed new personalised prognostic tools that included sex information (the sex-informed prognostic scoring system and the sex-informed genomic scoring system). Sex maintained independent prognostic power in all prognostic systems; the highest performance was observed in the model that included both sex and genomic information. A five-to-five mapping between the IPSS-R and new score categories resulted in the re-stratification of 871 (43middot0%) of 2025 patients from the EuroMDS cohort and 1003 (42middot0%) of 2387 patients from the IWG-PM cohort by using the sex-informed prognostic scoring system, and of 1134 (56middot0%) patients from the EuroMDS cohort and 1265 (53middot0%) patients from the IWG-PM cohort by using the sex-informed genomic scoring system. We created a web portal that enables outcome predictions based on a sex-informed personalised approach. Interpretation Our results suggest that a sex-informed approach can improve the personalised decision making process in patients with myelodysplastic syndromes and should be considered in the design of clinical trials including low-risk patients. Copyright (c) 2022 Published by Elsevier Ltd. All rights reserved

Absence of CD34 on Murine Skeletal Muscle Satellite Cells Marks a Reversible State of Activation during Acute Injury

Background: Skeletal muscle satellite cells are myogenic progenitors that reside on myofiber surface beneath the basal lamina. In recent years satellite cells have been identified and isolated based on their expression of CD34, a sialomucin surface receptor traditionally used as a marker of hematopoietic stem cells. Interestingly, a minority of satellite cells lacking CD34 has been described. Methodology/Principal Findings: In order to elucidate the relationship between CD34+ and CD34- satellite cells we utilized fluorescence-activated cell sorting (FACS) to isolate each population for molecular analysis, culture and transplantation studies. Here we show that unless used in combination with a7 integrin, CD34 alone is inadequate for purifying satellite cells. Furthermore, the absence of CD34 marks a reversible state of activation dependent on muscle injury. Conclusions/Significance: Following acute injury CD34- cells become the major myogenic population whereas the percentage of CD34+ cells remains constant. In turn activated CD34- cells can reverse their activation to maintain the pool of CD34+ reserve cells. Such activation switching and maintenance of reserve pool suggests the satellite cell compartment is tightly regulated during muscle regeneration

Preclinical evaluation of KIT/PDGFRA and mTOR inhibitors in gastrointestinal stromal tumors using small animal FDG PET

<p>Abstract</p> <p>Background</p> <p>Primary and secondary drug resistance to imatinib and sunitinib in patients with gastrointestinal stromal tumors (GISTs) has led to a pressing need for new therapeutic strategies such as drug combinations. Most GISTs are caused by mutations in the KIT receptor, leading to upregulated KIT tyrosine kinase activity. Imatinib and nilotinib directly inhibit the kinase activity of KIT, while RAD001 (everolimus) inhibits mTOR. We report a preclinical study on drug combinations in a xenograft model of GIST in which effects on tumor dimensions and metabolic activity were assessed by small animal PET imaging.</p> <p>Methods</p> <p>Rag2-/-; γcommon -/- male mice were injected s.c. into the right leg with GIST 882. The animals were randomized into 6 groups of 6 animals each for different treatment regimens: No therapy (control), imatinib (150 mg/kg b.i.d.) by oral gavage for 6 days, then once/day for another 7 days, everolimus (10 mg/kg/d.) by oral gavage, everolimus (10 mg/kg/d.) + imatinib (150 mg/kg b.i.d.) by oral gavage for 6 days, then once/day for another 7 days, nilotinib (75 mg/kg/d.) by oral gavage, nilotinib (75 mg/kg/d.) + imatinib (150 mg/kg b.i.d) by oral gavage for 6 days, then once/day for another 7 days. Tumor growth control was evaluated by measuring tumor volume (cm³). Small animal PET (GE Explore tomography) was used to evaluate tumor metabolism and performed in one animal per group at base-line then after 4 and 13 days of treatment.</p> <p>Results</p> <p>After a median latency time of 31 days, tumors grew in all animals (volume 0,06-0,15 cm³) and the treatments began at day 38 after cell injection. Tumor volume control (cm3) after 13 days of treatment was > 0.5 for imatinib alone and nilotinib alone, and < 0.5 for the 2 combinations of drugs and for everolimus alone. The baseline FDG uptake was positive in all animals. FDG/SUV/TBR was strongly reduced over time by everolimus both as a single agent and in combination with imatinib respectively: 3.1 vs. 2.3 vs. 1.9 and 2.5 vs 2.3 vs 0.</p> <p>Conclusions</p> <p>As single agents, all drugs showed an anti-tumor effect in GIST xenografts but everolimus was superior. The everolimus plus imatinib combination appeared to be the most active regimen both in terms of inhibiting tumor growth and tumor metabolism. The integration of everolimus in GIST treatment merits further investigation.</p