From Wearable Sensors to Smart Implants – Towards Pervasive and Personalised Healthcare

<p>Objective: This article discusses the evolution of pervasive healthcare from its inception for activity recognition using wearable sensors to the future of sensing implant deployment and data processing. Methods: We provide an overview of some of the past milestones and recent developments, categorised into different generations of pervasive sensing applications for health monitoring. This is followed by a review on recent technological advances that have allowed unobtrusive continuous sensing combined with diverse technologies to reshape the clinical workflow for both acute and chronic disease management. We discuss the opportunities of pervasive health monitoring through data linkages with other health informatics systems including the mining of health records, clinical trial databases, multi-omics data integration and social media. Conclusion: Technical advances have supported the evolution of the pervasive health paradigm towards preventative, predictive, personalised and participatory medicine. Significance: The sensing technologies discussed in this paper and their future evolution will play a key role in realising the goal of sustainable healthcare systems.</p> <p> </p

Effect of acylation on the interaction of the N-Terminal segment of pulmonary surfactant protein SP-C with phospholipid membranes.

AbstractSP-C, the smallest pulmonary surfactant protein, is required for the formation and stability of surface-active films at the air–liquid interface in the lung. The protein consists of a hydrophobic transmembrane α-helix and a cationic N-terminal segment containing palmitoylated cysteines. Recent evidence suggests that the N-terminal segment is of critical importance for SP-C function. In the present work, the role of palmitoylation in modulating the lipid–protein interactions of the N-terminal segment of SP-C has been studied by analyzing the effect of palmitoylated and non-palmitoylated synthetic peptides designed to mimic the N-terminal segment on the dynamic properties of phospholipid bilayers, recorded by spin-label electron spin resonance (ESR) spectroscopy. Both palmitoylated and non-palmitoylated peptides decrease the mobility of phosphatidylcholine (5-PCSL) and phosphatidylglycerol (5-PGSL) spin probes in dipalmitoylphosphatidylcholine (DPPC) or dipalmitoylphosphatidylglycerol (DPPG) bilayers. In zwitterionic DPPC membranes, both peptides have a greater effect at temperatures below than above the main gel-to-liquid-crystalline phase transition, the palmitoylated peptide inducing greater immobilisation of the lipid than does the non-palmitoylated form. In anionic DPPG membranes, both palmitoylated and non-palmitoylated peptides have similar immobilizing effects, probably dominated by electrostatic interactions. Both palmitoylated and non-palmitoylated peptides have effects comparable to whole native SP-C, as regards improving the gel phase solubility of phospholipid spin probes and increasing the polarity of the bilayer surface monitored by pK shifts of fatty acid spin probes. This indicates that a significant part of the perturbing properties of SP-C in phospholipid bilayers is mediated by interactions of the N-terminal segment. The effect of SP-C N-terminal peptides on the chain flexibility gradient of DPPC and DPPG bilayers is consistent with the existence of a peptide-promoted interdigitated phase at temperatures below the main gel-to-liquid-crystalline phase transition. The palmitoylated peptide, but not the non-palmitoylated version, is able to stably segregate interdigitated and non-interdigitated populations of phospholipids in DPPC bilayers. This feature suggests that the palmitoylated N-terminal segment stabilizes ordered domains such as those containing interdigitated lipids. We propose that palmitoylation may be important to promote and facilitate association of SP-C and SP-C-containing membranes with ordered lipid structures such as those potentially existing in highly compressed states of the interfacial surfactant film

Characterization of a raspberry Pi as the core for a low-cost multimodal EEG-fNIRS platform.

Poor understanding of brain recovery after injury, sparsity of evaluations and limited availability of healthcare services hinders the success of neurorehabilitation programs in rural communities. The availability of neuroimaging ca-pacities in remote communities can alleviate this scenario supporting neurorehabilitation programs in remote settings. This research aims at building a multimodal EEG-fNIRS neuroimaging platform deployable to rural communities to support neurorehabilitation efforts. A Raspberry Pi 4 is chosen as the CPU for the platform responsible for presenting the neurorehabilitation stimuli, acquiring, processing and storing concurrent neuroimaging records as well as the proper synchronization between the neuroimaging streams. We present here two experiments to assess the feasibility and characterization of the Raspberry Pi as the core for a multimodal EEG-fNIRS neuroimaging platform; one over controlled conditions using a combination of synthetic and real data, and another from a full test during resting state. CPU usage, RAM usage and operation temperature were measured during the tests with mean operational records below 40% for CPU cores, 13.6% for memory and 58.85 ° C for temperatures. Package loss was inexistent on synthetic data and negligible on experimental data. Current consumption can be satisfied with a 1000 mAh 5V battery. The Raspberry Pi 4 was able to cope with the required workload in conditions of operation similar to those needed to support a neurorehabilitation evaluation

Design of a fuzzy PID controller for a MEMS tunable capacitor for noise reduction in a voltage reference source

This study presents a conventional Ziegler-Nichols (ZN) Proportional Integral Derivative (PID) controller, having reviewed the mathematical modeling of the Micro Electro Mechanical Systems (MEMS) Tunable Capacitors (TCs), and also proposes a fuzzy PID controller which demonstrates a better tracking performance in the presence of measurement noise, in comparison with conventional ZN-based PID controllers. Referring to importance and impact of this research, the proposed controller takes advantage of fuzzy control properties such as robustness against noise. TCs are responsible for regulating the reference voltage when integrated into Alternating Current (AC) Voltage Reference Sources (VRS). Capacitance regulation for tunable capacitors in VRS is carried out by modulating the distance of a movable plate. A successful modulation depends on maintaining the stability around the pull-in point. This distance regulation can be achieved by the proposed controller which guarantees the tracking performance of the movable plate in moving towards the pull-in point, and remaining in this critical position. The simulation results of the tracking performance and capacitance tuning are very promising, subjected to measurement noise. Article Highlights This article deals with MEMS tunable capacitor dynamics and modeling, considering measurement noise. It designs and applies fuzzy PID control system for regulating MEMS voltage reference output. This paper contributes to robustness increase in pull-in performance of the tunable capacitor

Methylthioadenosine (MTA) inhibits melanoma cell proliferation and in vivo tumor growth

BACKGROUND: Melanoma is the most deadly form of skin cancer without effective treatment. Methylthioadenosine (MTA) is a naturally occurring nucleoside with differential effects on normal and transformed cells. MTA has been widely demonstrated to promote anti-proliferative and pro-apoptotic responses in different cell types. In this study we have assessed the therapeutic potential of MTA in melanoma treatment. METHODS: To investigate the therapeutic potential of MTA we performed in vitro proliferation and viability assays using six different mouse and human melanoma cell lines wild type for RAS and BRAF or harboring different mutations in RAS pathway. We also have tested its therapeutic capabilities in vivo in a xenograft mouse melanoma model and using variety of molecular techniques and tissue culture we investigated its anti-proliferative and pro-apoptotic properties. RESULTS: In vitro experiments showed that MTA treatment inhibited melanoma cell proliferation and viability in a dose dependent manner, where BRAF mutant melanoma cell lines appear to be more sensitive. Importantly, MTA was effective inhibiting in vivo tumor growth. The molecular analysis of tumor samples and in vitro experiments indicated that MTA induces cytostatic rather than pro-apoptotic effects inhibiting the phosphorylation of Akt and S6 ribosomal protein and inducing the down-regulation of cyclin D1. CONCLUSIONS: MTA inhibits melanoma cell proliferation and in vivo tumor growth particularly in BRAF mutant melanoma cells. These data reveal a naturally occurring drug potentially useful for melanoma treatment

Effective Brain Connectivity for fNIRS with Fuzzy Cognitive Maps in Neuroergonomics

Effective connectivity (EC) amongst functional near-infrared spectroscopy (fNIRS) signals is a quantitative measure of the strength of influence between brain activity associated with different regions of the brain. Evidently, accurate deciphering of EC gives further insight into the understanding of the intricately complex nature of neuronal interactions in the human brain. This work presents a novel approach to estimate EC in the human brain signals using enhanced fuzzy cognitive maps (FCMs). The proposed method presents a regularized methodology of FCMs, called effective FCMs (E-FCMs), with improved accuracy for predicting EC between real, and synthetic fNIRS signals. Essentially, the revisions made in the FCM methodology include a more powerful prediction formula for FCM combined with independent tuning of the transformation function parameter. A comparison of EC in fNIRS signals obtained from E-FCM with that obtained from standard FCM, general linear model (GLM) parameters that power Dynamic Causal Modelling (DCM), and Granger Causality (GC) manifests the greater prowess of the proposed E-FCM over the aforementioned methods. For real fNIRS data, an empirical investigation is also made to gain an insight into the role of oxyhemoglobin and deoxyhemoglobin (oxy-Hb, deoxy-Hb) in representing the cognitive activity. We believe this work has profound implications for neuroergonomics research communities

BCR-ABL induces the expression of Skp2 through the PI3K pathway to promote p27Kip1 degradation and proliferation of chronic myelogenous leukemia cells

Chronic myelogenous leukemia (CML) is characterized by the expression of the BCR-ABL tyrosine kinase, which results in increased cell proliferation and inhibition of apoptosis. In this study, we show in both BCR-ABL cells (Mo7e-p210 and BaF/3-p210) and primary CML CD34+ cells that STI571 inhibition of BCR-ABL tyrosine kinase activity results in a G(1) cell cycle arrest mediated by the PI3K pathway. This arrest is associated with a nuclear accumulation of p27(Kip1) and down-regulation of cyclins D and E. As a result, there is a reduction of the cyclin E/Cdk2 kinase activity and of the retinoblastoma protein phosphorylation. By quantitative reverse transcription-PCR we show that BCR-ABL/PI3K regulates the expression of p27(Kip1) at the level of transcription. We further show that BCR-ABL also regulates p27(Kip1) protein levels by increasing its degradation by the proteasome. This degradation depends on the ubiquitinylation of p27(Kip1) by Skp2-containing SFC complexes: silencing the expression of Skp2 with a small interfering RNA results in the accumulation of p27(Kip1). We also demonstrate that BCR-ABL cells show transcriptional up-regulation of Skp2. Finally, expression of a p27(Kip1) mutant unable of being recognized by Skp2 results in inhibition of proliferation of BCR-ABL cells, indicating that the degradation of p27(Kip1) contributes to the pathogenesis of CML. In conclusion, these results suggest that BCR-ABL regulates cell cycle in CML cells at least in part by inducing proteasome-mediated degradation of the cell cycle inhibitor p27(Kip1) and provide a rationale for the use of inhibitors of the proteasome in patients with BCR-ABL leukemias

Comparison of ex vivo expansion culture conditions of mesenchymal stem cells for human cell therapy

Mesenchymal stem cells (MSCs) are multipotent stem cells. Based on their properties, several clinical trials have been designed to explore their potential therapeutic effect. Fetal calf serum (FCS, commonly used for in vitro expansion) is an undesirable source of xenogeneic antigens and bears the risk of transmitting contaminations. As an alternative for FCS, platelet lysate (PL) and both autologous and allogeneic human serum have been proposed. The aim of this study is to compare the culture of bone marrow (BM)- derived MSCs in the presence of different serum supplements to determine the effect on cell growth, differentiation potential, and immunologic function

Effect of oral anticoagulants on the outcome of faecal immunochemical test

Background: We aimed to evaluate whether oral anticoagulants (OACs) alter faecal immunochemical test (FIT) performance in average-risk colorectal cancer (CRC) screening. Methods: Individuals aged 50–69 years were invited to receive one FIT sample (cutoff 75¿ng¿ml–1) between November 2008 and June 2011. Results: Faecal immunochemical test was positive in 9.3% (21 out of 224) of users of OAC and 6.2% (365 out of 5821) of non-users (P-trend=0.07). The positive predictive value (PPV) for advanced neoplasia (AN) in non-users was 50.4% vs 47.6% in users (odds ratio, 0.70; 95% CI, 0.3–1.8; P=0.5). The PPV for AN in OAC more antiplatelets (aspirin or clopidogrel) was 75% (odds ratio, 2; 95% CI, 0.4–10.8; P=0.4). Conclusions: Oral anticoagulant did not significantly modify the PPV for AN in this population-based colorectal screening program. The detection rate of advanced adenoma was higher in the combination OAC more antiplatelets

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur