Temperature Effect on the Electrochemical Current Response during Scanning Electrochemical Microscopy of Living Cells.

Scanning electrochemical microscopy (SECM) is being used increasingly to monitor electrochemical processes at the interface of living cells and electrodes. This allows the detection and quantification of biomarkers that further the understanding of various diseases. Rapid SECM experiments are often carried out without monitoring the analyte solution temperature or are performed at room temperature. The reported research demonstrates that temperature control is crucial during SECM imaging of living cells to obtain reliable data. In this study, a SECM-integrated thermostatic ring on the sample stage enabled imaging of living biological cells in a constant height mode at various temperatures. Two-dimensional line scans were conducted while scanning single Adenocarcinoma Cervical cancer (HeLa) cells. Numerical modeling was carried out to evaluate the effect of the temperature on the electrochemical current response of living cells to compare the apparent heterogeneous rate constant (k0), representing cellular reaction kinetics. This study reveals that even slight temperature variations of approximately 2 °C affect the reaction kinetics of single living cells, altering the measured current during SECM.

Reliability of gaze-contingent perimetry.

Standard automated perimetry, a psychophysical task performed routinely in eyecare clinics, requires observers to maintain fixation for several minutes at a time in order to measure visual field sensitivity. Detection of visual field damage is confounded by eye movements, making the technique unreliable in poorly attentive individuals and those with pathologically unstable fixation, such as nystagmus. Microperimetry, which utilizes 'partial gaze-contingency' (PGC), aims to counteract eye movements but only corrects for gaze position errors prior to each stimulus onset. Here, we present a novel method of visual field examination in which stimulus position is updated during presentation, which we refer to as 'continuous gaze-contingency' (CGC). In the first part of this study, we present three case examples that demonstrate the ability of CGC to measure the edges of the physiological blind spot in infantile nystagmus with greater accuracy than PGC and standard 'no gaze-contingency' (NoGC), as initial proof-of-concept for the utility of the paradigm in measurements of absolute scotomas in these individuals. The second part of this study focused on healthy observers, in which we demonstrate that CGC has the lowest stimulus positional error (gaze-contingent precision: CGC = ± 0.29°, PGC = ± 0.54°, NoGC = ± 0.81°). CGC test-retest variability was shown to be at least as good as both PGC and NoGC. Overall, CGC is supported as a reliable method of visual field examination in healthy observers. Preliminary findings demonstrate the spatially accurate estimation of visual field thresholds related to retinal structure using CGC in individuals with infantile nystagmus.

Accelerated MRI using intelligent protocolling and subject-specific denoising applied to Alzheimer's disease imaging.

Magnetic Resonance Imaging (MR Imaging) is routinely employed in diagnosing Alzheimer's Disease (AD), which accounts for up to 60-80% of dementia cases. However, it is time-consuming, and protocol optimization to accelerate MR Imaging requires local expertise since each pulse sequence involves multiple configurable parameters that need optimization for contrast, acquisition time, and signal-to-noise ratio (SNR). The lack of this expertise contributes to the highly inefficient utilization of MRI services diminishing their clinical value. In this work, we extend our previous effort and demonstrate accelerated MRI via intelligent protocolling of the modified brain screen protocol, referred to as the Gold Standard (GS) protocol. We leverage deep learning-based contrast-specific image-denoising to improve the image quality of data acquired using the accelerated protocol. Since the SNR of MR acquisitions depends on the volume of the object being imaged, we demonstrate subject-specific (SS) image-denoising. The accelerated protocol resulted in a 1.94 × gain in imaging throughput. This translated to a 72.51% increase in MR Value-defined in this work as the ratio of the sum of median object-masked local SNR values across all contrasts to the protocol's acquisition duration. We also computed PSNR, local SNR, MS-SSIM, and variance of the Laplacian values for image quality evaluation on 25 retrospective datasets. The minimum/maximum PSNR gains (measured in dB) were 1.18/11.68 and 1.04/13.15, from the baseline and SS image-denoising models, respectively. MS-SSIM gains were: 0.003/0.065 and 0.01/0.066; variance of the Laplacian (lower is better): 0.104/-0.135 and 0.13/-0.143. The GS protocol constitutes 44.44% of the comprehensive AD imaging protocol defined by the European Prevention of Alzheimer's Disease project. Therefore, we also demonstrate the potential for AD-imaging via automated volumetry of relevant brain anatomies. We performed statistical analysis on these volumetric measurements of the hippocampus and amygdala from the GS and accelerated protocols, and found that 27 locations were in excellent agreement. In conclusion, accelerated brain imaging with the potential for AD imaging was demonstrated, and image quality was recovered post-acquisition using DL-based image denoising models.

Single-cell scanning photoelectrochemical microscopy using micro-optical-ring electrodes.

Microelectrodes as analytical sensing tools have gained immense popularity in a wide range of applications, ranging from probe design advancement to single live cell imaging. Micro-optical-ring electrodes (MOREs) are micro-scale ring-electrodes with an optical fiber core, that enables the MORE to conduct an optical signal while performing electrochemistry. Herein, we present a user-friendly and cost-effective method to fabricate MOREs for scanning photoelectrochemical microscopy (SPECM) applications. MOREs were characterized by electrochemistry, numerical modelling, and scanning electron microscopy (SEM), ensuring reproducibility in terms of a well-defined geometry and functionality. In this study, the integration of MOREs into scanning probe microscopy enabled the spectro-electrochemical detection of N, N, N, N'- Tetramethyl-p-phenyl-enediamine (TMPD) and its oxidized radical cation counterpart. UV-VIS spectroscopy capabilities of MOREs were optimized through tip-to-substrate distance variations. To demonstrate the applicability of MOREs to electrochemical single live cell imaging, oxygen production was detected in living algae (Eremosphaera viridis) by local illumination and concurrent electrochemical measurements.

A Machine Learning Approach for Continuous Mining of Nonidentifiable Smartphone Data to Create a Novel Digital Biomarker Detecting Generalized Anxiety Disorder: Prospective Cohort Study.

BACKGROUND: Anxiety is one of the leading causes of mental health disability around the world. Currently, a majority of the population who experience anxiety go undiagnosed or untreated. New and innovative ways of diagnosing and monitoring anxiety have emerged using smartphone sensor-based monitoring as a metric for the management of anxiety. This is a novel study as it adds to the field of research through the use of nonidentifiable smartphone usage to help detect and monitor anxiety remotely and in a continuous and passive manner. OBJECTIVE: This study aims to evaluate the accuracy of a novel mental behavioral profiling metric derived from smartphone usage for the identification and tracking of generalized anxiety disorder (GAD). METHODS: Smartphone data and self-reported 7-item GAD anxiety assessments were collected from 229 participants using an Android operating system smartphone in an observational study over an average of 14 days (SD 29.8). A total of 34 features were mined to be constructed as a potential digital phenotyping marker from continuous smartphone usage data. We further analyzed the correlation of these digital behavioral markers against each item of the 7-item Generalized Anxiety Disorder Scale (GAD-7) and its influence on the predictions of machine learning algorithms. RESULTS: A total of 229 participants were recruited in this study who had completed the GAD-7 assessment and had at least one set of passive digital data collected within a 24-hour period. The mean GAD-7 score was 11.8 (SD 5.7). Regression modeling was tested against classification modeling and the highest prediction accuracy was achieved from a binary XGBoost classification model (precision of 73%-81%; recall of 68%-87%; F1-score of 71%-79%; accuracy of 76%; area under the curve of 80%). Nonparametric permutation testing with Pearson correlation results indicated that the proposed metric (Mental Health Similarity Score [MHSS]) had a colinear relationship between GAD-7 Items 1, 3 and 7. CONCLUSIONS: The proposed MHSS metric demonstrates the feasibility of using passively collected nonintrusive smartphone data and machine learning-based data mining techniques to track an individuals' daily anxiety levels with a 76% accuracy that directly relates to the GAD-7 scale.

Voluntary Flutter Presenting During Ophthalmoscopy: A Case Report.

Voluntary flutter (sometimes known as "voluntary nystagmus") is a conjugate saccadic oscillation of the eyes that occurs in some healthy individuals. It has no relation to pathological nystagmus, which can manifest in infancy or become acquired later in life. This report presents an unusual case of voluntary flutter that presented in a 20-year-old male with autism spectrum disorder during ocular examination via direct ophthalmoscopy. Refraction and ocular motor balance were normal, and visual acuity was good in each eye (-0.10 logMAR). During direct ophthalmoscopy, a fine intermittent tremor was initiated. The patient was referred for further assessment, and eye movements were recorded at 1,000 Hz with an EyeLink 1000 eye tracker. Upon request, the patient could manifest voluntary flutter again and sustain the eye movements with effort during convergence. The voluntary flutter consisted of back-to-back saccadic oscillations in a predominantly horizontal direction, with an average frequency of 13 Hz and an amplitude of ∼8°, both reducing over time. We speculate that the discomfort induced by the proximity of the clinician during direct ophthalmoscopy examination may have triggered the eye oscillations. Although the oscillations typically manifest during convergence, atypical forms of voluntary flutter can also occur during divergence. Voluntary flutter can be a useful differential diagnosis in patients with a recently onset apparent "nystagmus," and no other neurological signs and symptoms.

A Machine Learning Approach for Detecting Digital Behavioral Patterns of Depression Using Nonintrusive Smartphone Data (Complementary Path to Patient Health Questionnaire-9 Assessment): Prospective Observational Study.

BACKGROUND: Depression is a major global cause of morbidity, an economic burden, and the greatest health challenge leading to chronic disability. Mobile monitoring of mental conditions has long been a sought-after metric to overcome the problems associated with the screening, diagnosis, and monitoring of depression and its heterogeneous presentation. The widespread availability of smartphones has made it possible to use their data to generate digital behavioral models that can be used for both clinical and remote screening and monitoring purposes. This study is novel as it adds to the field by conducting a trial using private and nonintrusive sensors that can help detect and monitor depression in a continuous, passive manner. OBJECTIVE: This study demonstrates a novel mental behavioral profiling metric (the Mental Health Similarity Score), derived from analyzing passively monitored, private, and nonintrusive smartphone use data, to identify and track depressive behavior and its progression. METHODS: Smartphone data sets and self-reported Patient Health Questionnaire-9 (PHQ-9) depression assessments were collected from 558 smartphone users on the Android operating system in an observational study over an average of 10.7 (SD 23.7) days. We quantified 37 digital behavioral markers from the passive smartphone data set and explored the relationship between the digital behavioral markers and depression using correlation coefficients and random forest models. We leveraged 4 supervised machine learning classification algorithms to predict depression and its severity using PHQ-9 scores as the ground truth. We also quantified an additional 3 digital markers from gyroscope sensors and explored their feasibility in improving the model's accuracy in detecting depression. RESULTS: The PHQ-9 2-class model (none vs severe) achieved the following metrics: precision of 85% to 89%, recall of 85% to 89%, F1 of 87%, and accuracy of 87%. The PHQ-9 3-class model (none vs mild vs severe) achieved the following metrics: precision of 74% to 86%, recall of 76% to 83%, F1 of 75% to 84%, and accuracy of 78%. A significant positive Pearson correlation was found between PHQ-9 questions 2, 6, and 9 within the severely depressed users and the mental behavioral profiling metric (r=0.73). The PHQ-9 question-specific model achieved the following metrics: precision of 76% to 80%, recall of 75% to 81%, F1 of 78% to 89%, and accuracy of 78%. When a gyroscope sensor was added as a feature, the Pearson correlation among questions 2, 6, and 9 decreased from 0.73 to 0.46. The PHQ-9 2-class model+gyro features achieved the following metrics: precision of 74% to 78%, recall of 67% to 83%, F1 of 72% to 78%, and accuracy of 76%. CONCLUSIONS: Our results demonstrate that the Mental Health Similarity Score can be used to identify and track depressive behavior and its progression with high accuracy.

Time-series analysis of daily ambient temperature and emergency department visits in five US cities with a comparison of exposure metrics derived from 1-km meteorology products.

BACKGROUND: Ambient temperature observations from single monitoring stations (usually located at the major international airport serving a city) are routinely used to estimate heat exposures in epidemiologic studies. This method of exposure assessment does not account for potential spatial variability in ambient temperature. In environmental health research, there is increasing interest in utilizing spatially-resolved exposure estimates to minimize exposure measurement error. METHODS: We conducted time-series analyses to investigate short-term associations between daily temperature metrics and emergency department (ED) visits for well-established heat-related morbidities in five US cities that represent different climatic regions: Atlanta, Los Angeles, Phoenix, Salt Lake City, and San Francisco. In addition to airport monitoring stations, we derived several exposure estimates for each city using a national meteorology data product (Daymet) available at 1 km spatial resolution. RESULTS: Across cities, we found positive associations between same-day temperature (maximum or minimum) and ED visits for heat-sensitive outcomes, including acute renal injury and fluid and electrolyte imbalance. We also found that exposure assessment methods accounting for spatial variability in temperature and at-risk population size often resulted in stronger relative risk estimates compared to the use of observations at airports. This pattern was most apparent when examining daily minimum temperature and in cities where the major airport is located further away from the urban center. CONCLUSION: Epidemiologic studies based on single monitoring stations may underestimate the effect of temperature on morbidity when the station is less representative of the exposure of the at-risk population.

Alemtuzumab for the treatment of multiple sclerosis.

INTRODUCTION: Alemtuzumab is a monoclonal antibody that targets for the destruction CD52+ cells, particularly B and T cells. Alemtuzumab is approved in more than 50 countries around the world for the treatment of adult patients with relapsing remitting multiple sclerosis (MS). Areas covered: In this review, the authors summarize biological, clinical and safety data related to the use of alemtuzumab in patients with MS. The authors then provide their expert opinion on alemtuzumab and the field as of whole before providing their perspectives for the future. Expert opinion: Alemtuzumab is highly efficacious; more so than first line treatments but comparable to natalizumab. Treatment schedule makes alemtuzumab administration easy and attractive to patients. However, its safety profile makes it a choice for a very limited number of patients, in a specific disease window. As of now, a cure for MS remains elusive and there is an unmet need for a safe and highly potent agent at the level of and beyond the blood brain barrier.

Photoluminescence intensity ratio of Eu-conjugated lactates-A simple optical imaging technique for biomarker analysis for critical diseases.

Instant measurement of elevated biomarkers such as lactic acid offers the most promising approaches for early treatment and prevention of many critical diseases including cardiac arrest, stroke, septic shock, trauma, liver dysfunction, as well as for monitoring lactic acid level during intense exercise. In the present study, a unique dependence of visible photoluminescence of Eu3+ ions resulting from 5 D0 to 7 FJ(J = 0,1,2,3,4) transitions, which can be exploited for rapid detection of biomarkers, both in vitro and ex vivo, has been reported. It is observed that the integrated intensity ratio of photoluminescence signals dominating at 591 and 616 nm originating from 5 D0 to 7 F2 and 5 D0 to 7 F1 transitions in Eu3+ ions can be used as a biosensing and bioimaging tool for detection of biomarkers released at disease states. The Eu3+ integrated photoluminescence intensity ratio approach reported herein for optical detection of lactates in blood serum, plasma and confocal imaging of brain tissues has very high potential for exploitation of this technique in both in vitro monitoring and in vivo bioimaging applications for the detection of biomarkers in various diseases states.

Ultrafast endocytosis at Caenorhabditis elegans neuromuscular junctions.

Synaptic vesicles can be released at extremely high rates, which places an extraordinary demand on the recycling machinery. Previous ultrastructural studies of vesicle recycling were conducted in dissected preparations using an intense stimulation to maximize the probability of release. Here, a single light stimulus was applied to motor neurons in intact Caenorhabditis elegans nematodes expressing channelrhodopsin, and the animals rapidly frozen. We found that docked vesicles fuse along a broad active zone in response to a single stimulus, and are replenished with a time constant of about 2 s. Endocytosis occurs within 50 ms adjacent to the dense projection and after 1 s adjacent to adherens junctions. These studies suggest that synaptic vesicle endocytosis may occur on a millisecond time scale following a single physiological stimulus in the intact nervous system and is unlikely to conform to current models of endocytosis. DOI:http://dx.doi.org/10.7554/eLife.00723.001.