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This study aims to develop an optimally performing convolutional neural network to classify Alzheimer's disease into mild cognitive impairment, normal controls, or Alzheimer's disease classes using a magnetic resonance imaging dataset. To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. Subsequently, a convolutional neural network model comprising four convolutional layers and two hidden layers was devised for classifying Alzheimer's disease into three (3) distinct categories, namely mild cognitive impairment, Alzheimer's disease, and normal controls. The model was trained and evaluated using a 10-fold cross-validation sampling approach with a learning rate of 0.001 and 200 training epochs at each instance. The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. The model further showed superior results on binary classification compared with existing methods. The model recorded 94.39%, 94.92%, and 95.62% accuracies for Alzheimer's disease versus normal controls, Alzheimer's disease versus mild cognitive impairment, and mild cognitive impairment versus normal controls classes, respectively.
Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Humans , Alzheimer Disease/diagnostic imaging , Magnetic Resonance Imaging/methods , Neural Networks, Computer , Algorithms , Image Enhancement , Cognitive Dysfunction/diagnostic imaging , Neuroimaging/methodsABSTRACT
PURPOSE: Adreno-muscarinic synergy, a supra-additional contractile response to simultaneous application of α-adrenoreceptor and muscarinic receptor agonists, is a feature of several lower urinary tract regions that have dual sympathetic and parasympathetic innervation. We tested the hypothesis that synergy is also a feature of prostate tissue obtained from men with benign prostatic enlargement. METHODS: Isolated tissue strips were dissected from prostate 'chips', collected after transurethral prostate resection procedures for in vitro experiments, to measure isometric tension at 36°C. RESULTS: Added separately to the superfusate, phenylephrine and carbachol generated contractions with mean pEC50 (-log10EC50) values of 5.36 and 5.58, respectively, although phenylephrine maximal responses were about six-fold greater. In the presence of carbachol, the mean phenylephrine pEC50 was significantly increased to 5.84 and maximal response increased by 28%; overall, a significant synergistic response was demonstrated. The synergistic response was reduced by muscarinic receptor antagonists, most potently by the M3-selective agent 4-DAMP (1,1-dimethyl-4-diphenylacetoxypiperidinium iodide), and less so by M2 and M1-selective inhibitors gallamine and pirenzepine, but with an overall profile indicating M3/M2 mediation of the synergistic response. The magnitude of the synergistic response was variable between prostate chips that provided isolated preparations suggesting regional heterogenicity, although their zonal origin could not be determined. CONCLUSION: These experiments show that adreno-muscarinic contractile synergy is a feature of human hyperplastic prostate tissue. This has implications for the use of a combination therapy of α-blockers and anti-muscarinic agent to relieve secondary symptoms associated with benign prostatic hyperplasia, at least in men who can tolerate antimuscarinics without a risk of retention.
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Introduction: Many people worldwide suffer from chronic pain. Improving our knowledge on chronic pain prevalence and management requires methods to collect pain self-reports in large populations. Smartphone-based tools could aid data collection by allowing people to use their own device, but the measurement properties of such tools are largely unknown. Objectives: To assess the reliability, validity, and responsiveness of a smartphone-based manikin to support pain self-reporting. Methods: We recruited people with fibromyalgia, rheumatoid arthritis, and/or osteoarthritis and access to a smartphone and the internet. Data collection included the Global Pain Scale at baseline and follow-up, and 30 daily pain drawings completed on a 2-dimensional, gender-neutral manikin. After deriving participants' pain extent from their manikin drawings, we evaluated convergent and discriminative validity, test-retest reliability, and responsiveness and assessed findings against internationally agreed criteria for good measurement properties. Results: We recruited 131 people; 104 were included in the full sample, submitting 2185 unique pain drawings. Manikin-derived pain extent had excellent test-retest reliability (intraclass correlation coefficient, 0.94), moderate convergent validity (ρ, 0.46), and an ability to distinguish fibromyalgia and osteoarthritis from rheumatoid arthritis (F statistics, 30.41 and 14.36, respectively; P < 0.001). Responsiveness was poor (ρ, 0.2; P, 0.06) and did not meet the respective criterion for good measurement properties. Conclusion: Our findings suggest that smartphone-based manikins can be a reliable and valid method for pain self-reporting, but that further research is warranted to explore, enhance, and confirm the ability of such manikins to detect a change in pain over time.
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While the use of electronic methods to collect patient-reported outcome data in clinical trials continues to increase, it remains the case that many patient-reported outcome measures (PROMs) have originally been developed and validated on paper. Careful consideration during the move from paper PROMs to electronic format is required to preserve the integrity of the measure and ensure a "faithful migration." Relevant literature has long called out the importance of following migration best practices during this process; nevertheless, such best practices are distributed across multiple documents. This article consolidates and builds upon existing electronic PROM implementation best practice recommendations to provide a comprehensive, up-to-date, single point of reference. It reflects the current consensus based on the significant advances in technology capabilities and knowledge gleaned from the growing evidence base on electronic migration and implementation, to balance the need for maintaining the integrity of the measure while optimizing respondent usability. It also specifies whether the practice is rooted in evidence or expert consensus, to enable those using these best practices to make informed and considered decisions when conducting migration.
Subject(s)
Patient Reported Outcome Measures , Humans , ConsensusABSTRACT
Background: As management of chronic pain continues to be suboptimal, there is a need for tools that support frequent, longitudinal pain self-reporting to improve our understanding of pain. This study aimed to assess the feasibility and acceptability of daily pain self-reporting using a smartphone-based pain manikin. Methods: For this prospective feasibility study, we recruited adults with lived experience of painful musculoskeletal condition. They were asked to complete daily pain self-reports via an app for 30 days. We assessed feasibility by calculating pain report completion levels, and investigated differences in completion levels between subgroups. We assessed acceptability via an end-of-study questionnaire, which we analysed descriptively. Results: Of the 104 participants, the majority were female (n = 87; 84%), aged 45-64 (n = 59; 57%), and of white ethnic background (n = 89; 86%). The mean completion levels was 21 (± 7.7) pain self-reports. People who were not working (odds ratio (OR) = 1.84; 95% confidence interval (CI), 1.52-2.23) were more likely, and people living in less deprived areas (OR = 0.77; 95% CI, 0.62-0.97) and of non-white ethnicity (OR = 0.45; 95% CI, 0.36-0.57) were less likely to complete pain self-reports than their employed, more deprived and white counterparts, respectively. Of the 96 participants completing the end-of-study questionnaire, almost all participants agreed that it was easy to complete a pain drawing (n = 89; 93%). Conclusion: It is feasible and acceptable to self-report pain using a smartphone-based manikin over a month. For its wider adoption for pain self-reporting, the feasibility and acceptability should be further explored among people with diverse socio-economic and ethnic backgrounds.
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BACKGROUND: Culture and ethnicity influence how people communicate about their pain. This makes it challenging to develop pain self-report tools that are acceptable across ethnic groups. OBJECTIVE: We aimed to inform the development of cross-culturally acceptable digital pain self-report tools by better understanding the similarities and differences between ethnic groups in pain experiences and self-reporting needs. METHODS: Three web-based workshops consisting of a focus group and a user requirement exercise with people who self-identified as being of Black African (n=6), South Asian (n=10), or White British (n=7) ethnicity were conducted. RESULTS: Across ethnic groups, participants shared similar lived experiences and challenges in communicating their pain to health care professionals. However, there were differences in beliefs about the causes of pain, attitudes toward pain medication, and experiences of how stigma and gender norms influenced pain-reporting behavior. Despite these differences, they agreed on important aspects for pain self-report, but participants from non-White backgrounds had additional language requirements such as culturally appropriate pain terminologies to reduce self-reporting barriers. CONCLUSIONS: To improve the cross-cultural acceptability and equity of digital pain self-report tools, future developments should address the differences among ethnic groups on pain perceptions and beliefs, factors influencing pain reporting behavior, and language requirements.
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Kidney transplant survival is shortened by chronic rejection and side effects of standard immunosuppressive drugs. Cell-based immunotherapy with tolerogenic dendritic cells has long been recognized as a promising approach to reduce general immunosuppression. Published trials report the safety and the absence of therapy-related adverse reactions in patients treated with tolerogenic dendritic cells suffering from several inflammatory diseases. Here, we present the first phase I clinical trial results using human autologous tolerogenic dendritic cells (ATDC) in kidney transplantation. Eight patients received ATDC the day before transplantation in conjunction with standard steroids, mycophenolate mofetil and tacrolimus immunosuppression with an option to taper mycophenolate mofetil. ATDC preparations were manufactured in a Good Manufacturing Practice-compliant facility and fulfilled cell count, viability, purity and identity criteria for release. A control group of nine patients received the same standard immunosuppression, except basiliximab induction replaced ATDC therapy and mycophenolate tapering was not allowed. During the three-year follow-up, no deaths occurred and there was 100% graft survival. No significant increase of adverse events was associated with ATDC infusion. Episodes of rejection were observed in two patients from the ATDC group and one patient from the control group. However, all rejections were successfully treated by glucocorticoids. Mycophenolate was successfully reduced/stopped in five patients from the ATDC group, allowing tacrolimus monotherapy for two of them. Regarding immune monitoring, reduced CD8 T cell activation markers and increased Foxp3 expression were observed in the ATDC group. Thus, our results demonstrate ATDC administration safety in kidney-transplant recipients.
Subject(s)
Kidney Transplantation , Tacrolimus , Humans , Tacrolimus/therapeutic use , Mycophenolic Acid/therapeutic use , Kidney Transplantation/adverse effects , Transplant Recipients , Immunosuppressive Agents/therapeutic use , Immunosuppression Therapy/methods , Dendritic Cells , Graft Rejection , Graft SurvivalABSTRACT
To track and control self-location, animals integrate their movements through space. Representations of self-location are observed in the mammalian hippocampal formation, but it is unknown if positional representations exist in more ancient brain regions, how they arise from integrated self-motion, and by what pathways they control locomotion. Here, in a head-fixed, fictive-swimming, virtual-reality preparation, we exposed larval zebrafish to a variety of involuntary displacements. They tracked these displacements and, many seconds later, moved toward their earlier location through corrective swimming ("positional homeostasis"). Whole-brain functional imaging revealed a network in the medulla that stores a memory of location and induces an error signal in the inferior olive to drive future corrective swimming. Optogenetically manipulating medullary integrator cells evoked displacement-memory behavior. Ablating them, or downstream olivary neurons, abolished displacement corrections. These results reveal a multiregional hindbrain circuit in vertebrates that integrates self-motion and stores self-location to control locomotor behavior.
Subject(s)
Neurons , Zebrafish , Animals , Zebrafish/physiology , Neurons/physiology , Rhombencephalon/physiology , Brain/physiology , Swimming/physiology , Homeostasis , MammalsABSTRACT
The statistics of vesicle release determine how synapses transfer information, but the classical Poisson model of independent release does not always hold at the first stages of vision and hearing. There, ribbon synapses also encode sensory signals as events comprising two or more vesicles released simultaneously. The implications of such coordinated multivesicular release (MVR) for spike generation are not known. Here we investigate how MVR alters the transmission of sensory information compared with Poisson synapses using a pure rate-code. We used leaky integrate-and-fire models incorporating the statistics of release measured experimentally from glutamatergic synapses of retinal bipolar cells in zebrafish (both sexes) and compared these with models assuming Poisson inputs constrained to operate at the same average rates. We find that MVR can increase the number of spikes generated per vesicle while reducing interspike intervals and latency to first spike. The combined effect was to increase the efficiency of information transfer (bits per vesicle) over a range of conditions mimicking target neurons of different size. MVR was most advantageous in neurons with short time constants and reliable synaptic inputs, when less convergence was required to trigger spikes. In the special case of a single input driving a neuron, as occurs in the auditory system of mammals, MVR increased information transfer whenever spike generation required more than one vesicle. This study demonstrates how presynaptic integration of vesicles by MVR can increase the efficiency with which sensory information is transmitted compared with a rate-code described by Poisson statistics.SIGNIFICANCE STATEMENT Neurons communicate by the stochastic release of vesicles at the synapse and the statistics of this process will determine how information is represented by spikes. The classical model is that vesicles are released independently by a Poisson process, but this does not hold at ribbon-type synapses specialized to transmit the first electrical signals in vision and hearing, where two or more vesicles can fuse in a single event by a process termed coordinated multivesicular release. This study shows that multivesicular release can increase the number of spikes generated per vesicle and the efficiency of information transfer (bits per vesicle) over a range of conditions found in the retina and peripheral auditory system.
Subject(s)
Synaptic Vesicles , Zebrafish , Male , Animals , Female , Synaptic Vesicles/physiology , Synapses/physiology , Retinal Bipolar Cells , Retina/physiology , Synaptic Transmission/physiology , MammalsABSTRACT
Computer vision is the science that enables computers and machines to see and perceive image content on a semantic level. It combines concepts, techniques, and ideas from various fields such as digital image processing, pattern matching, artificial intelligence, and computer graphics. A computer vision system is designed to model the human visual system on a functional basis as closely as possible. Deep learning and Convolutional Neural Networks (CNNs) in particular which are biologically inspired have significantly contributed to computer vision studies. This research develops a computer vision system that uses CNNs and handcrafted filters from Log-Gabor filters to identify medicinal plants based on their leaf textural features in an ensemble manner. The system was tested on a dataset developed from the Centre of Plant Medicine Research, Ghana (MyDataset) consisting of forty-nine (49) plant species. Using the concept of transfer learning, ten pretrained networks including Alexnet, GoogLeNet, DenseNet201, Inceptionv3, Mobilenetv2, Restnet18, Resnet50, Resnet101, vgg16, and vgg19 were used as feature extractors. The DenseNet201 architecture resulted with the best outcome of 87% accuracy and GoogLeNet with 79% preforming the worse averaged across six supervised learning algorithms. The proposed model (OTAMNet), created by fusing a Log-Gabor layer into the transition layers of the DenseNet201 architecture achieved 98% accuracy when tested on MyDataset. OTAMNet was tested on other benchmark datasets; Flavia, Swedish Leaf, MD2020, and the Folio dataset. The Flavia dataset achieved 99%, Swedish Leaf 100%, MD2020 99%, and the Folio dataset 97%. A false-positive rate of less than 0.1% was achieved in all cases.
Subject(s)
Deep Learning , Plants, Medicinal , Algorithms , Artificial Intelligence , Humans , Neural Networks, ComputerABSTRACT
BACKGROUND: People with rheumatic diseases experience troublesome fluctuations in fatigue. Debated causes include pain, mood and inflammation. To determine the relationships between these potential causes, serial assessments are required but are methodologically challenging. This mobile health (mHealth) study explored the viability of using a smartphone app to collect patient-reported symptoms with contemporaneous Dried Blood Spot Sampling (DBSS) for inflammation. METHODS: Over 30 days, thirty-eight participants (12 RA, 13 OA, and 13 FM) used uMotif, a smartphone app, to report fatigue, pain and mood, on 5-point ordinal scales, twice daily. Daily DBSS, from which C-reactive Protein (CRP) values were extracted, were completed on days 1-7, 14 and 30. Participant engagement was determined based on frequency of data entry and ability to calculate within- and between-day symptom changes. DBSS feasibility and engagement was determined based on the proportion of samples returned and usable for extraction, and the number of days between which between-day changes in CRP which could be calculated (days 1-7). RESULTS: Fatigue was reported at least once on 1085/1140 days (95.2%). Approximately 65% of within- and between-day fatigue changes could be calculated. Rates were similar for pain and mood. A total of 287/342 (83.9%) DBSS, were returned, and all samples were viable for CRP extraction. Fatigue, pain and mood varied considerably, but clinically meaningful (≥ 5 mg/L) CRP changes were uncommon. CONCLUSIONS: Embedding DBSS in mHealth studies will enable researchers to obtain serial symptom assessments with matched biological samples. This provides exciting opportunities to address hitherto unanswerable questions, such as elucidating the mechanisms of fatigue fluctuations.
Subject(s)
Patient Generated Health Data , Rheumatic Diseases , Biomarkers , Ecological Momentary Assessment , Fatigue/diagnosis , Fatigue/etiology , Feasibility Studies , Humans , Inflammation/complications , Pain/etiology , Rheumatic Diseases/complications , Rheumatic Diseases/diagnosisABSTRACT
Neuromodulators adapt sensory circuits to changes in the external world or the animal's internal state and synapses are key control sites for such plasticity. Less clear is how neuromodulation alters the amount of information transmitted through the circuit. We investigated this question in the context of the diurnal regulation of visual processing in the retina of zebrafish, focusing on ribbon synapses of bipolar cells. We demonstrate that contrast-sensitivity peaks in the afternoon accompanied by a four-fold increase in the average Shannon information transmitted from an active zone. This increase reflects higher synaptic gain, lower spontaneous "noise" and reduced variability of evoked responses. Simultaneously, an increase in the probability of multivesicular events with larger information content increases the efficiency of transmission (bits per vesicle) by factors of 1.5-2.7. This study demonstrates the multiplicity of mechanisms by which a neuromodulator can adjust the synaptic transfer of sensory information.
Subject(s)
Synaptic Transmission , Zebrafish , Animals , Neurotransmitter Agents , Retina/physiology , Synapses/physiology , Synaptic Transmission/physiologyABSTRACT
BACKGROUND: Sleep disturbances and poor health-related quality of life (HRQoL) are common in people with rheumatoid arthritis (RA). Sleep disturbances, such as less total sleep time, more waking periods after sleep onset, and higher levels of nonrestorative sleep, may be a driver of HRQoL. However, understanding whether these sleep disturbances reduce HRQoL has, to date, been challenging because of the need to collect complex time-varying data at high resolution. Such data collection is now made possible by the widespread availability and use of mobile health (mHealth) technologies. OBJECTIVE: This mHealth study aimed to test whether sleep disturbance (both absolute values and variability) causes poor HRQoL. METHODS: The quality of life, sleep, and RA study was a prospective mHealth study of adults with RA. Participants completed a baseline questionnaire, wore a triaxial accelerometer for 30 days to objectively assess sleep, and provided daily reports via a smartphone app that assessed sleep (Consensus Sleep Diary), pain, fatigue, mood, and other symptoms. Participants completed the World Health Organization Quality of Life-Brief (WHOQoL-BREF) questionnaire every 10 days. Multilevel modeling tested the relationship between sleep variables and the WHOQoL-BREF domains (physical, psychological, environmental, and social). RESULTS: Of the 268 recruited participants, 254 were included in the analysis. Across all WHOQoL-BREF domains, participants' scores were lower than the population average. Consensus Sleep Diary sleep parameters predicted the WHOQoL-BREF domain scores. For example, for each hour increase in the total time asleep physical domain scores increased by 1.11 points (ß=1.11, 95% CI 0.07-2.15) and social domain scores increased by 1.65 points. These associations were not explained by sociodemographic and lifestyle factors, disease activity, medication use, anxiety levels, sleep quality, or clinical sleep disorders. However, these changes were attenuated and no longer significant when pain, fatigue, and mood were included in the model. Increased variability in total time asleep was associated with poorer physical and psychological domain scores, independent of all covariates. There was no association between actigraphy-measured sleep and WHOQoL-BREF. CONCLUSIONS: Optimizing total sleep time, increasing sleep efficiency, decreasing sleep onset latency, and reducing variability in total sleep time could improve HRQoL in people with RA.
Subject(s)
Arthritis, Rheumatoid , Sleep Wake Disorders , Telemedicine , Adult , Arthritis, Rheumatoid/complications , Fatigue , Humans , Pain , Prospective Studies , Quality of Life/psychology , Sleep , Surveys and QuestionnairesABSTRACT
Painful conditions are prevalent and substantially contribute to disability worldwide. Digital manikins are body-shaped drawings to facilitate self-reporting of pain. Some of them have been validated, but without allowing for recording of location-specific pain intensity and for use on a smartphone. This paper describes the initial development of a digital pain manikin to support self-reporting of pain location and location-specific intensity using people's own mobile device. Subsequently, we conducted reliability and usability tests with eight researchers and seven patient representatives. Test-retest reliability depended on the manikin's level of detail, but was generally high with most intraclass correlation coefficients âLe0.70 and all similarity coefficients âLe0.50. Participants found the manikin easy to use, but suggested clearer orientation (front/back, certain body locations) and would value additional feedback and diary functions. We will address these issues in the next version of the manikin before conducting a validation study.
Subject(s)
Manikins , Humans , Pain , Pain Measurement , Reproducibility of Results , SmartphoneABSTRACT
BACKGROUND: Use of cell-based medicinal products (CBMPs) represents a state-of-the-art approach for reducing general immunosuppression in organ transplantation. We tested multiple regulatory CBMPs in kidney transplant trials to establish the safety of regulatory CBMPs when combined with reduced immunosuppressive treatment. METHODS: The ONE Study consisted of seven investigator-led, single-arm trials done internationally at eight hospitals in France, Germany, Italy, the UK, and the USA (60 week follow-up). Included patients were living-donor kidney transplant recipients aged 18 years and older. The reference group trial (RGT) was a standard-of-care group given basiliximab, tapered steroids, mycophenolate mofetil, and tacrolimus. Six non-randomised phase 1/2A cell therapy group (CTG) trials were pooled and analysed, in which patients received one of six CBMPs containing regulatory T cells, dendritic cells, or macrophages; patient selection and immunosuppression mirrored the RGT, except basiliximab induction was substituted with CBMPs and mycophenolate mofetil tapering was allowed. None of the trials were randomised and none of the individuals involved were masked. The primary endpoint was biopsy-confirmed acute rejection (BCAR) within 60 weeks after transplantation; adverse event coding was centralised. The RTG and CTG trials are registered with ClinicalTrials.gov, NCT01656135, NCT02252055, NCT02085629, NCT02244801, NCT02371434, NCT02129881, and NCT02091232. FINDINGS: The seven trials took place between Dec 11, 2012, and Nov 14, 2018. Of 782 patients assessed for eligibility, 130 (17%) patients were enrolled and 104 were treated and included in the analysis. The 66 patients who were treated in the RGT were 73% male and had a median age of 47 years. The 38 patients who were treated across six CTG trials were 71% male and had a median age of 45 years. Standard-of-care immunosuppression in the recipients in the RGT resulted in a 12% BCAR rate (expected range 3·2-18·0). The overall BCAR rate for the six parallel CTG trials was 16%. 15 (40%) patients given CBMPs were successfully weaned from mycophenolate mofetil and maintained on tacrolimus monotherapy. Combined adverse event data and BCAR episodes from all six CTG trials revealed no safety concerns when compared with the RGT. Fewer episodes of infections were registered in CTG trials versus the RGT. INTERPRETATION: Regulatory cell therapy is achievable and safe in living-donor kidney transplant recipients, and is associated with fewer infectious complications, but similar rejection rates in the first year. Therefore, immune cell therapy is a potentially useful therapeutic approach in recipients of kidney transplant to minimise the burden of general immunosuppression. FUNDING: The 7th EU Framework Programme.
Subject(s)
Cell- and Tissue-Based Therapy/methods , Graft Rejection/prevention & control , Immunosuppression Therapy/methods , Immunosuppressive Agents/therapeutic use , Kidney Transplantation , Cell- and Tissue-Based Therapy/adverse effects , Dendritic Cells/immunology , Graft Rejection/immunology , Humans , Immunosuppression Therapy/adverse effects , Macrophages/immunology , T-Lymphocytes, Regulatory/immunologyABSTRACT
Patients with chronic pain commonly believe their pain is related to the weather. Scientific evidence to support their beliefs is inconclusive, in part due to difficulties in getting a large dataset of patients frequently recording their pain symptoms during a variety of weather conditions. Smartphones allow the opportunity to collect data to overcome these difficulties. Our study Cloudy with a Chance of Pain analysed daily data from 2658 patients collected over a 15-month period. The analysis demonstrated significant yet modest relationships between pain and relative humidity, pressure and wind speed, with correlations remaining even when accounting for mood and physical activity. This research highlights how citizen-science experiments can collect large datasets on real-world populations to address long-standing health questions. These results will act as a starting point for a future system for patients to better manage their health through pain forecasts.
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BACKGROUND: The BRadykinesia Akinesia INcoordination (BRAIN) tap test is an online keyboard tapping task that has been previously validated to assess upper limb motor function in Parkinson's disease (PD). OBJECTIVES: To develop a new parameter that detects a sequence effect and to reliably distinguish between PD patients on and off medication. In addition, we sought to validate a mobile version of the test for use on smartphones and tablet devices. METHODS: The BRAIN test scores in 61 patients with PD and 93 healthy controls were compared. A range of established parameters captured number and accuracy of alternate taps. The new velocity score recorded the intertap speed. Decrement in the velocity score was used as a marker for the sequence effect. In the validation phase, 19 PD patients and 19 controls were tested using different hardware including mobile devices. RESULTS: Quantified slopes from the velocity score demonstrated bradykinesia (sequence effect) in PD patients (slope cut-off -0.002) with 58% sensitivity and 81% specificity (discovery phase of the study) and 65% sensitivity and 88% specificity (validation phase). All BRAIN test parameters differentiated between on and off medication states in PD. Differentiation between PD patients and controls was possible on all hardware versions of the test. CONCLUSION: The BRAIN tap test is a simple, user-friendly, and free-to-use tool for the assessment of upper limb motor dysfunction in PD, which now includes a measure of bradykinesia.
ABSTRACT
Most neurons transmit information digitally using spikes that trigger the release of synaptic vesicles with low probability. The first stages of vision and hearing are distinct in that they operate with analog signals, but it is unclear how these are recoded for synaptic transmission. By imaging the release of glutamate in live zebrafish, we demonstrate that ribbon synapses of retinal bipolar cells encode contrast through changes in both the frequency and amplitude of release events. Higher contrasts caused multiple vesicles to be released within an event, and such coding by amplitude often continued after the rate code had reached a maximum frequency. Glutamate packets equivalent to five vesicles transmitted four times as many bits of information per vesicle compared with those released individually. By discretizing analog signals into sequences of numbers up to about 11, ribbon synapses can increase the dynamic range, temporal precision and efficiency with which visual information is transmitted.
Subject(s)
Retinal Bipolar Cells/physiology , Synaptic Transmission/physiology , Synaptic Vesicles/physiology , Visual Pathways/physiology , Action Potentials , Animals , Genes, Reporter , Glutamic Acid/physiology , Membrane Fusion , Patch-Clamp Techniques , Signal Detection, Psychological , Zebrafish/physiologyABSTRACT
Understanding how neurons encode and compute information is fundamental to our study of the brain, but opportunities for hands-on experience with neurophysiological techniques on live neurons are scarce in science education. Here, we present Spikeling, an open source in silico implementation of a spiking neuron that costs £25 and mimics a wide range of neuronal behaviours for classroom education and public neuroscience outreach. Spikeling is based on an Arduino microcontroller running the computationally efficient Izhikevich model of a spiking neuron. The microcontroller is connected to input ports that simulate synaptic excitation or inhibition, to dials controlling current injection and noise levels, to a photodiode that makes Spikeling light sensitive, and to a light-emitting diode (LED) and speaker that allows spikes to be seen and heard. Output ports provide access to variables such as membrane potential for recording in experiments or digital signals that can be used to excite other connected Spikelings. These features allow for the intuitive exploration of the function of neurons and networks mimicking electrophysiological experiments. We also report our experience of using Spikeling as a teaching tool for undergraduate and graduate neuroscience education in Nigeria and the United Kingdom.
Subject(s)
Action Potentials/physiology , Models, Neurological , Neurons/physiology , Neurosciences/education , Neurosciences/instrumentation , Animals , Community-Institutional Relations , Computer Simulation , Equipment Design , Nerve Net/physiology , Neural Networks, Computer , Synapses/physiologyABSTRACT
INTRODUCTION: People with rheumatoid arthritis (RA) frequently report reduced health-related quality of life (HRQoL), the impact one's health has on physical, emotional and social well-being. There are likely numerous causes for poor HRQoL, but people with RA have identified sleep disturbances as a key contributor to their well-being. This study will identify sleep/wake rhythm-associated parameters that predict HRQoL in patients with RA. METHODS AND ANALYSIS: This prospective cohort study will recruit 350 people with RA, aged 18 years or older. Following completion of a paper-based baseline questionnaire, participants will record data on 10 symptoms including pain, fatigue and mood two times a day for 30 days using a study-specific mobile application (app). A triaxial accelerometer will continuously record daytime activity and estimate evening sleep parameters over the 30 days. Every 10 days following study initiation, participants will complete a questionnaire that measures disease specific (Arthritis Impact Measurement Scale 2-Short Form (AIMS2-SF)) and generic (WHOQOL-BREF) quality of life. A final questionnaire will be completed at 60 days after entering the study. The primary outcomes are the AIMS2-SF and WHOQOL-BREF. Structural equation modelling and latent trajectory models will be used to examine the relationship between sleep/wake rhythm-associated parameters and HRQoL, over time. ETHICS AND DISSEMINATION: Results from this study will be disseminated at regional and international conferences, in peer-reviewed journals and Patient and Public Engagement events, as appropriate.