An artificial neural network integrated pipeline for biomarker discovery using Alzheimer's disease as a case study

The field of machine learning has allowed researchers to generate and analyse vast amounts of data using a wide variety of methodologies. Artificial Neural Networks (ANN) are some of the most commonly used statistical models and have been successful in biomarker discovery studies in multiple disease types. This review seeks to explore and evaluate an integrated ANN pipeline for biomarker discovery and validation in Alzheimer's disease, the most common form of dementia worldwide with no proven cause and no available cure. The proposed pipeline consists of analysing public data with a categorical and continuous stepwise algorithm and further examination through network inference to predict gene interactions. This methodology can reliably generate novel markers and further examine known ones and can be used to guide future research in Alzheimer's disease

Discovery and application of immune biomarkers for hematological malignancies

Introduction: Haematological malignancies originate and progress in primary and secondary lymphoid organs, where they establish a uniquely immune-suppressive tumour microenvironment. Although high-throughput transcriptomic and proteomic approaches are being employed to interrogate immune surveillance and escape mechanisms in patients with solid tumours, and to identify actionable targets for immunotherapy, our knowledge of the immunological landscape of haematological malignancies, as well as our understanding of the molecular circuits that underpin the establishment of immune tolerance, is not comprehensive. Areas covered: This article will discuss how multiplexed immunohistochemistry, flow cytometry/mass cytometry, proteomic and genomic techniques can be used to dynamically capture the complexity of tumour-immune interactions. Moreover, the analysis of multi-dimensional, clinically annotated data sets obtained from public repositories such as Array Express, TCGA and GEO is crucial to identify immune biomarkers, to inform the rational design of immune therapies and to predict clinical benefit in individual patients. We will also highlight how artificial neural network models and alternative methodologies integrating other algorithms can support the identification of key molecular drivers of immune dysfunction. Expert comment: High-dimensional technologies have the potential to enhance our understanding of immune-cancer interactions and will support clinical decision making and the prediction of therapeutic benefit from immune-based interventions

Physical Activity Characteristics across GOLD Quadrants Depend on the Questionnaire Used

BACKGROUND:The GOLD multidimensional classification of COPD severity combines the exacerbation risk with the symptom experience, for which 3 different questionnaires are permitted. This study investigated differences in physical activity (PA) in the different GOLD quadrants and patient's distribution in relation to the questionnaire used. METHODS:136 COPD patients (58±21% FEV1 predicted, 34F/102M) completed COPD assessment test (CAT), clinical COPD questionnaire (CCQ) and modified Medical Research Council (mMRC) questionnaire. Exacerbation history, spirometry and 6MWD were collected. PA was objectively measured for 2 periods of 1 week, 6 months apart, in 5 European centres; to minimise seasonal and clinical variation the average of these two periods was used for analysis. RESULTS:GOLD quadrants C+D had reduced PA compared with A+B (3824 [2976] vs. 5508 [4671] steps.d-1, p<0.0001). The choice of questionnaire yielded different patient distributions (agreement mMRC-CAT κ = 0.57; CCQ-mMRC κ = 0.71; CCQ-CAT κ = 0.72) with different clinical characteristics. PA was notably lower in patients with an mMRC score ≥2 (3430 [2537] vs. 5443 [3776] steps.d-1, p <0.001) in both the low and high risk quadrants. CONCLUSIONS:Using different questionnaires changes the patient distribution and results in different clinical characteristics. Therefore, standardization of the questionnaire used for classification is critical to allow comparison of different studies using this as an entry criterion. CLINICAL TRIAL REGISTRATION:ClinicalTrials.gov NCT01388218

PYK2 promotes HER2-positive breast cancer invasion

Background: Metformin, a biguanide, is one of the most commonly prescribed treatments for type 2 diabetes and has recently been recommended as a potential drug candidate for advanced cancer therapy. Although Metformin has antiproliferative and proapoptotic effects on breast cancer, the heterogenous nature of this disease affects the response to metformin leading to the activation of pro-invasive signalling pathways that are mediated by the focal adhesion kinase PYK2 in pure HER2 phenotype breast cancer. Methods: The effect of metformin on different breast cancer cell lines, representing the molecular heterogenicity of the disease was investigated using in vitro proliferation and apoptosis assays. The activation of PYK2 by metformin in pure HER2 phenotype (HER2+/ER−/PR-) cell lines was investigated by microarrays, quantitative real time PCR and immunoblotting. Cell migration and invasion PYK2-mediated and in response to metformin were determined by wound healing and invasion assays using HER2+/ER−/PR- PYK2 knockdown cell lines. Proteomic analyses were used to determine the role of PYK2 in HER2+/ER−/PR- proliferative, migratory and invasive cellular pathways and in response to metformin. The association between PYK2 expression and HER2+/ER−/PR- patients’ cancer-specific survival was investigated using bioinformatic analysis of PYK2 expression from patient gene expression profiles generated by the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) study. The effect of PYK2 and metformin on tumour initiation and invasion of HER2+/ER−/PR- breast cancer stem-like cells was performed using the in vitro stem cell proliferation and invasion assays. Results: Our study showed for the first time that pure HER2 breast cancer cells are more resistant to metformin treatment when compared with the other breast cancer phenotypes. This drug resistance was associated with the activation of PTK2B/PYK2, a well-known mediator of signalling pathways involved in cell proliferation, migration and invasion. The role of PYK2 in promoting invasion of metformin resistant HER2 breast cancer cells was confirmed through investigating the effect of PYK2 knockdown and metformin on cell invasion and by proteomic analysis of associated cellular pathways. We also reveal a correlation between high level of expression of PYK2 and reduced survival in pure HER2 breast cancer patients. Moreover, we also report a role of PYK2 in tumour initiation and invasion-mediated by pure HER2 breast cancer stem-like cells. This was further confirmed by demonstrating a correlation between reduced survival in pure HER2 breast cancer patients and expression of PYK2 and the stem cell marker CD44. Conclusions: We provide evidence of a PYK2-driven pro-invasive potential of metformin in pure HER2 cancer therapy and propose that metformin-based therapy should consider the molecular heterogeneity of breast cancer to prevent complications associated with cancer chemoresistance, invasion and recurrence in treated patients

Greater exercise tolerance in COPD during acute interval, compared to equivalent constant‐load, cycle exercise: physiological mechanisms

The relative importance of ventilatory, circulatory and peripheral muscle factors in determining tolerance to exercise in patients with COPD is not known. In twelve COPD patients (FEV1 :58 ± 17%pred.) we measured ventilation, cardiac output, dynamic hyperinflation, local muscle oxygenation, blood lactate and time to exhaustion during a) interval exercise (IE) consisting of 30 s at 100% peak work-rate alternated with 30 s at 50% and b) constant load exercise (CLE) at 75% WRpeak, designed to produce the same average work rate. Exercise time was substantially longer during IE than CLE (19.5 ± 4.8 versus 11.4 ± 2.1 min, p = 0.0001). Total work output was therefore greater during IE than CLE (81.3 ± 27.7 versus 48.9 ± 23.8 kJ, p = 0.0001). Dynamic hyperinflation (assessed by changes from baseline in inspiratory capacity-ΔIC) was less during IE than CLE at CLE exhaustion time (isotime, p = 0.009), but was similar at exhaustion (ΔICCLE : -0.38 ± 0.10 versus ΔICIE : -0.33 ± 0.12 l, p = 0.102). In contrast, at isotime, minute ventilation, cardiac output and systemic oxygen delivery did not differ between protocols (p>0.05). At exhaustion in both protocols, vastus lateralis and intercostal muscle oxygen saturation were higher in IE than CLE (p = 0.014 and p = 0.0002, respectively) and blood lactate concentrations were lower (4.9 ± 2.4 mmol/l versus 6.4 ± 2.2 mmol/l, p = 0.039). These results suggest that 1) exercise tolerance in COPD is limited by dynamic hyperinflation; and 2) cyclically lower (50%) effort intervals in IE help preserve muscle oxygenation and reduce metabolic acidosis compared to CLE at the same average work rate, but these factors do not appear to determine time to exhaustion

Elucidating new molecular drivers and pathways involved in Alzheimer's disease using systems biology approaches

Alzheimer's Disease is the most common form of dementia worldwide with 40 million patients in the USA alone. This neurodegenerative disease is commonly characterised by the presence of amyloid plaques and neurofibrillary tangles in the brain, which result from the deposition of extracellular β-amyloid protein fragments and abnormal tau protein respectively. Over the years, research and medical efforts to control the disease by targeting these proteins have been largely unsuccessful, originally due to the difficulty in detection and targeting, but even with advanced technology, the effects of approaches targeting these proteins have been minimal. Further research is required to fully understand the causes of the disease, how it progresses, which systems are affected and how it can be treated efficiently and effectively. With the advent of high throughput sequencing technologies such as transcription microarrays, methylation arrays and RNA sequencing, a wealth of high quality data is being generated allowing for the tracking of changes at the genetic level over the course of the disease. This information was analysed using machine learning methods including the in-house Stepwise Artificial Neural Network algorithm as well as the Network Inference algorithm developed by Graham Ball and his research group to elucidate new molecular markers and drivers of the disease and also to evaluate existing ones. The results were analysed using a non-parametric systems biology approach to determine the impact of these markers on the systems involved in the disease and new techniques including the driver analysis were developed to reduce bias and increase clarity. In order to achieve the most comprehensive set of results and reduce the risk of error and false discovery, the E-GEOD-48350 dataset was selected for its comprehensive and high-quality data and was used to test both old and new methods and obtain a preliminary set of results. These results were validated using other transcription datasets as well as an RNA sequencing dataset, leading to the identification of dysregulated genes related to microtubule stabilisation and immune system regulation in Alzheimer's disease, providing a foundation for further expansion and research

Improvement in respiratory muscle O2 delivery is associated with less dyspnoea during exercise in COPD

An expansion upon work presented in 'Blood flow does not redistribute from respiratory to leg muscles during exercise breathing heliox or oxygen in COPD' (http://jap.physiology.org/content/jap/117/3/267.full.pdf

Additive manufacturing of hydroxyapatite–chitosan–genipin composite scaffolds for bone tissue engineering applications

Additive manufacturing holds promise for the fabrication of three-dimensional scaffolds with precise geometry, to serve as substrates for the guided regeneration of natural tissue. In this work, a bioinspired approach is adopted for the synthesis of hybrid hydroxyapatite hydrogels, which were subsequently printed to form 3D scaffolds for bone tissue engineering applications. These hydrogels consist of hydroxyapatite nanocrystals, biomimetically synthesized in the presence of both chitosan and L-arginine. To improve their mechanical properties, chemical crosslinking was performed using a natural crosslinking agent (genipin), and their rheology was modified by employing an acetic acid/gelatin solution. Regarding the 3D printing process, several parameters (flow, infill and perimeter speed) were studied in order to accurately produce scaffolds with predesigned geometry and micro-architecture, while also applying low printing temperature (15 °C). Following the printing procedure, the 3D scaffolds were freeze dried in order to remove the entrapped solvents and therefore, obtain a porous interconnected network. Evaluation of porosity was performed using micro-computed tomography and nanomechanical properties were assessed through nanoindentation. Results of both characterization techniques, showed that the scaffolds&apos; porosity as well as their modulus values, fall within the corresponding range of the respective values of cancellous bone. The biocompatibility of the 3D printed scaffolds was assessed using MG63 human osteosarcoma cells for 7 days of culturing. Cell viability was evaluated by MTT assay as well as double staining and visualized under fluorescence microscopy, while cell morphology was analyzed through scanning electron microscopy. Biocompatibility tests, revealed that the scaffolds constitute a cell-friendly environment, allowed them to adhere on the scaffolds&apos; surface, increase their population and maintain high levels of viability. © 2020 Elsevier B.V

Impact of COVID-19 Pandemic on Fragility Fractures of the Hip: An Interrupted Time-Series Analysis of the Lockdown Periods in Western Greece and Review of the Literature

Since December 2019, the COVID-19 pandemic has had a significant impact on healthcare systems worldwide, prompting policymakers to implement measures of isolation and eventually adopt strict national lockdowns, which affected mobility, healthcare-seeking behavior, and services, in an unprecedented manner. This study aimed to analyze the effects of these lockdowns on hip-fracture epidemiology and care services, compared to nonpandemic periods in previous years. We retrospectively collected data from electronic patient records of two major hospitals in Western Greece and included patients who suffered a fragility hip fracture and were admitted during the two 5-week lockdown periods in 2020, compared to time-matched patients from 2017–2019. The results showed a drop in hip-fracture incidence, which varied among hospitals and lockdown periods, and conflicting impacts on time to surgery, time to discharge after surgery, and total hospitalization time. The study also found that differences between the two differently organized units were exaggerated during the COVID-19 lockdown periods, highlighting the impact of compliance with social-distancing measures and the reallocation of resources on the quality of healthcare services. Further research is needed to fully understand the specific variations and patterns of geriatric hip-fracture care during emergency health crises characterized by limited resources and behavioral changes

Highlights from the 2018 European Respiratory Society International Congress: sleep and clinical physiology

The 2018 European Respiratory Society (ERS) International Congress held in Paris, France, served as a platform to discover the latest research on respiratory diseases, the improvement in their treatments and patient care. Specifically, the scientific sessions organised by ERS Assembly 4 provided novel insights into sleep disordered breathing and fresh knowledge in respiratory physiology, stressing its importance to understanding and treating respiratory diseases. This article, divided by session, will summarise the most relevant studies presented at the ERS International Congress. Each session has been written by early career members specialised in the different fields of this interdisciplinary assembly.Peer reviewe