Thermal imaging developments for respiratory airflow measurement to diagnose apnoea

Sleep-disordered breathing is a sleep disorder that manifests itself as intermittent pauses (apnoeas) in breathing during sleep. The condition disturbs the sleep and can results in a variety of health problems. Its diagnosis is complex and involves multiple sensors attached to the person to measure electroencephalogram (EEG), electrocardiogram (ECG), blood oxygen saturation (pulse oximetry, S

Mobile devices for the remote acquisition of physiological and behavioral biomarkers in psychiatric clinical research

Psychiatric disorders are linked to a variety of biological, psychological, and contextual causes and consequences. Laboratory studies have elucidated the importance of several key physiological and behavioral biomarkers in the study of psychiatric disorders, but much less is known about the role of these biomarkers in naturalistic settings. These gaps are largely driven by methodological barriers to assessing biomarker data rapidly, reliably, and frequently outside the clinic or laboratory. Mobile health (mHealth) tools offer new opportunities to study relevant biomarkers in concert with other types of data (e.g., self-reports, global positioning system data). This review provides an overview on the state of this emerging field and describes examples from the literature where mHealth tools have been used to measure a wide array of biomarkers in the context of psychiatric functioning (e.g., psychological stress, anxiety, autism, substance use). We also outline advantages and special considerations for incorporating mHealth tools for remote biomarker measurement into studies of psychiatric illness and treatment and identify several specific opportunities for expanding this promising methodology. Integrating mHealth tools into this area may dramatically improve psychiatric science and facilitate highly personalized clinical care of psychiatric disorders

Behavior Coding Strategies: Population Coupling and the Functional Role of Excitatory/Inhibitory Balance in Primary Motor Cortex

The complexities of an organism’s experience of- and interaction with the world are emergent phenomena produced by large populations of neurons within the cerebral cortex and other brain regions. The network dynamics of these populations have been shown to be sometimes synchronous, with many neurons firing together, and sometimes asynchronous, with neurons firing more independently, leading to a decades-old debate within the neuroscience community. This discrepancy comes from viewing the system at two different scales; at the single cell level, the spiking activity of two neurons within cortex tend to be rather independent, but when the average activity of a global population is measured (e.g. during EEG, LFP measurements), large scale oscillations are typically observed. Both modes confer certain benefits and drawbacks in regard to information processing. Synchronous networks display more robust signal propagation at the expense of lower information capacity and higher signal-to-noise while more asynchronous networks exhibit higher information capacity but lack strong signal throughput. Do either of these scenarios prevail within motor cortex or do the two regimes work simultaneously to produce behavior? Here we measure neuron-to-population and neuron-to-body coupling of neurons within primary motor cortex of awake, freely behaving rats. We found that neurons with high and low population coupling coexist within cortex and population coupling was tunable via modulation of inhibitory signaling. Thus, our results show that both high and low synchrony neurons coexist. We also found that neurons with high and low population coupling serve different functional roles; neurons with low values of population coupling were more strongly coupled to the activity of the body, while neurons which were more engaged with the population tended to be less responsible in commanding body movement. These findings suggest a possible optimization strategy- the neurons that are most responsible for body movements are balanced between synchronous and asynchronous network activity, making a compromise between the various benefits and disadvantages of either extreme synchrony or extreme asynchrony

Thyroid Hormone as a Method of Reducing Damage to Donor Hearts after Circulatory Arrest

There is a chronic lack of donor hearts to meet the need for heart transplant both in the US and worldwide. Further, the use of available hearts is limited by the short period between collection and implantation during which the heart can be safely preserved ex vivo. Using mid-thermic Langendorff machine perfusion, we have been able to preserve the metabolic function of a healthy heart for up to 8 hours, twice the limit for current static cold storage. We have also been able to preserve the metabolic function of a damaged DCD Heart collected 30 minutes after cardiac arrest for a period of 8 hours. We further investigated whether it was possible to improve the preservation of DCD heart using treatment with 10 μM Triiodothyronine to stimulate the tissue metabolism and we did find a reduction in damage markers in the treated DCD hearts as compared to the untreated group

New perspectives for viability studies with high-content analysis Raman spectroscopy (HCA-RS)

Raman spectroscopy has been widely used in clinical and molecular biological studies, providing high chemical specificity without the necessity of labels and with little-to-no sample preparation. However, currently performed Raman-based studies of eukaryotic cells are still very laborious and time-consuming, resulting in a low number of sampled cells and questionable statistical validations. Furthermore, the approach requires a trained specialist to perform and analyze the experiments, rendering the method less attractive for most laboratories. In this work, we present a new high-content analysis Raman spectroscopy (HCA-RS) platform that overcomes the current challenges of conventional Raman spectroscopy implementations. HCA-RS allows sampling of a large number of cells under different physiological conditions without any user interaction. The performance of the approach is successfully demonstrated by the development of a Raman-based cell viability assay, i.e., the effect of doxorubicin concentration on monocytic THP-1 cells. A statistical model, principal component analysis combined with support vector machine (PCA-SVM), was found to successfully predict the percentage of viable cells in a mixed population and is in good agreement to results obtained by a standard cell viability assay. This study demonstrates the potential of Raman spectroscopy as a standard high-throughput tool for clinical and biological applications