Soft robotic artificial left ventricle simulator capable of reproducing myocardial biomechanics.

The heart's intricate myocardial architecture has been called the Gordian knot of anatomy, an impossible tangle of intricate muscle fibers. This complexity dictates equally complex cardiac motions that are difficult to mimic in physical systems. If these motions could be generated by a robotic system, then cardiac device testing, cardiovascular disease studies, and surgical procedure training could reduce their reliance on animal models, saving time, costs, and lives. This work introduces a bioinspired soft robotic left ventricle simulator capable of reproducing the minutiae of cardiac motion while providing physiological pressures. This device uses thin-filament artificial muscles to mimic the multilayered myocardial architecture. To demonstrate the device's ability to follow the cardiac motions observed in the literature, we used canine myocardial strain data as input signals that were subsequently applied to each artificial myocardial layer. The device's ability to reproduce physiological volume and pressure under healthy and heart failure conditions, as well as effective simulation of a cardiac support device, were experimentally demonstrated in a left-sided mock circulation loop. This work also has the potential to deliver faithful simulated cardiac motion for preclinical device and surgical procedure testing, with the potential to simulate patient-specific myocardial architecture and motion.

Needle-Shaped Biosensors for Precision Diagnoses: From Benchtop Development to In Vitro and In Vivo Applications.

To achieve the accurate recognition of biomarkers or pathological characteristics within tissues or cells, in situ detection using biosensor technology offers crucial insights into the nature, stage, and progression of diseases, paving the way for enhanced precision in diagnostic approaches and treatment strategies. The implementation of needle-shaped biosensors (N-biosensors) presents a highly promising method for conducting in situ measurements of clinical biomarkers in various organs, such as in the brain or spinal cord. Previous studies have highlighted the excellent performance of different N-biosensor designs in detecting biomarkers from clinical samples in vitro. Recent preclinical in vivo studies have also shown significant progress in the clinical translation of N-biosensor technology for in situ biomarker detection, enabling highly accurate diagnoses for cancer, diabetes, and infectious diseases. This article begins with an overview of current state-of-the-art benchtop N-biosensor designs, discusses their preclinical applications for sensitive diagnoses, and concludes by exploring the challenges and potential avenues for next-generation N-biosensor technology.

Soft Fibrous Syringe Architecture for Electricity-Free and Motorless Control of Flexible Robotic Systems.

Flexible robotic systems (FRSs) and wearable user interfaces (WUIs) have been widely used in medical fields, offering lower infection risk and shorter recovery, and supporting amiable human-machine interactions (HMIs). Recently, soft electric, thermal, magnetic, and fluidic actuators with enhanced safety and compliance have innovatively boosted the use of FRSs and WUIs across many sectors. Among them, soft hydraulic actuators offer great speed, low noise, and high force density. However, they currently require bulky electric motors/pumps, pistons, valves, rigid accessories, and complex controllers, which inherently result in high cost, low adaptation, and complex setups. This paper introduces a novel soft fibrous syringe architecture (SFSA) consisting of two or more hydraulically connected soft artificial muscles that enable electricity-free actuation, motorless control, and built-in sensing ability for use in FRSs and WUIs. Its capabilities are experimentally demonstrated with various robotic applications including teleoperated flexible catheters, cable-driven continuum robotic arms, and WUIs. In addition, its sensing abilities to detect passive and active touch, surface texture, and object stiffness are also proven. These excellent results demonstrate a high feasibility of using a current-free and motor-less control approach for the FRSs and WUIs, enabling new methods of sensing and actuation across the robotic field.

Gene Electrotransfer via Conductivity-Clamped Electric Field Focusing Pivots Sensori-Motor DNA Therapeutics: "A Spoonful of Sugar Helps the Medicine Go Down".

Viral vectors and lipofection-based gene therapies have dispersion-dependent transduction/transfection profiles that thwart precise targeting. The study describes the development of focused close-field gene electrotransfer (GET) technology, refining spatial control of gene expression. Integration of fluidics for precise delivery of "naked" plasmid deoxyribonucleic acid (DNA) in sucrose carrier within the focused electric field enables negative biasing of near-field conductivity ("conductivity-clamping"-CC), increasing the efficiency of plasma membrane molecular translocation. This enables titratable gene delivery with unprecedently low charge transfer. The clinic-ready bionics-derived CC-GET device achieved neurotrophin-encoding miniplasmid DNA delivery to the cochlea to promote auditory nerve regeneration; validated in deafened guinea pig and cat models, leading to improved central auditory tuning with bionics-based hearing. The performance of CC-GET is evaluated in the brain, an organ problematic for pulsed electric field-based plasmid DNA delivery, due to high required currents causing Joule-heating and damaging electroporation. Here CC-GET enables safe precision targeting of gene expression. In the guinea pig, reporter expression is enabled in physiologically critical brainstem regions, and in the striatum (globus pallidus region) delivery of a red-shifted channelrhodopsin and a genetically-encoded Ca2+ sensor, achieved photoactivated neuromodulation relevant to the treatment of Parkinson's Disease and other focal brain disorders.

Energy-Efficient Sleep Apnea Detection Using a Hyperdimensional Computing Framework Based on Wearable Bracelet Photoplethysmography.

OBJECTIVE: Sleep apnea syndrome (SAS) is a common sleep disorder, which has been shown to be an important contributor to major neurocognitive and cardiovascular sequelae. Considering current diagnostic strategies are limited with bulky medical devices and high examination expenses, a large number of cases go undiagnosed. To enable large-scale screening for SAS, wearable photoplethysmography (PPG) technologies have been used as an early detection tool. However, existing algorithms are energy-intensive and require large amounts of memory resources, which are believed to be the major drawbacks for further promotion of wearable devices for SAS detection. METHODS: In this paper, an energy-efficient method of SAS detection based on hyperdimensional computing (HDC) is proposed. Inspired by the phenomenon of chunking in cognitive psychology as a memory mechanism for improving working memory efficiency, we proposed a one-dimensional block local binary pattern (1D-BlockLBP) encoding scheme combined with HDC to preserve dominant dynamical and temporal characteristics of pulse rate signals from wearable PPG devices. RESULTS: Our method achieved 70.17 % accuracy in sleep apnea segment detection, which is comparable with traditional machine learning methods. Additionally, our method achieves up to 67× lower memory footprint, 68× latency reduction, and 93× energy saving on the ARM Cortex-M4 processor. CONCLUSION: The simplicity of hypervector operations in HDC and the novel 1D-BlockLBP encoding effectively preserve pulse rate signal characteristics with high computational efficiency. SIGNIFICANCE: This work provides a scalable solution for long-term home-based monitoring of sleep apnea, enhancing the feasibility of consistent patient care.

Deep learning in spatially resolved transcriptfomics: a comprehensive technical view

Spatially resolved transcriptomics (SRT) is a pioneering method for simultaneously studying morphological contexts and gene expression at single-cell precision. Data emerging from SRT are multifaceted, presenting researchers with intricate gene expression matrices, precise spatial details and comprehensive histology visuals. Such rich and intricate datasets, unfortunately, render many conventional methods like traditional machine learning and statistical models ineffective. The unique challenges posed by the specialized nature of SRT data have led the scientific community to explore more sophisticated analytical avenues. Recent trends indicate an increasing reliance on deep learning algorithms, especially in areas such as spatial clustering, identification of spatially variable genes and data alignment tasks. In this manuscript, we provide a rigorous critique of these advanced deep learning methodologies, probing into their merits, limitations and avenues for further refinement. Our in-depth analysis underscores that while the recent innovations in deep learning tailored for SRT have been promising, there remains a substantial potential for enhancement. A crucial area that demands attention is the development of models that can incorporate intricate biological nuances, such as phylogeny-aware processing or in-depth analysis of minuscule histology image segments. Furthermore, addressing challenges like the elimination of batch effects, perfecting data normalization techniques and countering the overdispersion and zero inflation patterns seen in gene expression is pivotal. To support the broader scientific community in their SRT endeavors, we have meticulously assembled a comprehensive directory of readily accessible SRT databases, hoping to serve as a foundation for future research initiatives.

FD-Net: Feature Distillation Network for Oral Squamous Cell Carcinoma Lymph Node Segmentation in Hyperspectral Imagery.

Oral squamous cell carcinoma (OSCC) has the characteristics of early regional lymph node metastasis. OSCC patients often have poor prognoses and low survival rates due to cervical lymph metastases. Therefore, it is necessary to rely on a reasonable screening method to quickly judge the cervical lymph metastastic condition of OSCC patients and develop appropriate treatment plans. In this study, the widely used pathological sections with hematoxylin-eosin (H&E) staining are taken as the target, and combined with the advantages of hyperspectral imaging technology, a novel diagnostic method for identifying OSCC lymph node metastases is proposed. The method consists of a learning stage and a decision-making stage, focusing on cancer and non-cancer nuclei, gradually completing the lesions' segmentation from coarse to fine, and achieving high accuracy. In the learning stage, the proposed feature distillation-Net (FD-Net) network is developed to segment the cancerous and non-cancerous nuclei. In the decision-making stage, the segmentation results are post-processed, and the lesions are effectively distinguished based on the prior. Experimental results demonstrate that the proposed FD-Net is very competitive in the OSCC hyperspectral medical image segmentation task. The proposed FD-Net method performs best on the seven segmentation evaluation indicators: MIoU, OA, AA, SE, CSI, GDR, and DICE. Among these seven evaluation indicators, the proposed FD-Net method is 1.75%, 1.27%, 0.35%, 1.9%, 0.88%, 4.45%, and 1.98% higher than the DeepLab V3 method, which ranks second in performance, respectively. In addition, the proposed diagnosis method of OSCC lymph node metastasis can effectively assist pathologists in disease screening and reduce the workload of pathologists.

Non-invasive parameters of autonomic function using beat-to-beat cardiovascular variations and arterial stiffness in hypertensive individuals: a systematic review.

PURPOSE: Non-invasive, beat-to-beat variations in physiological indices provide an opportunity for more accessible assessment of autonomic dysfunction. The potential association between the changes in these parameters and arterial stiffness in hypertension remains poorly understood. This systematic review aims to investigate the association between non-invasive indicators of autonomic function based on beat-to-beat cardiovascular signals with arterial stiffness in individuals with hypertension. METHODS: Four electronic databases were searched from inception to June 2022. Studies that investigated non-invasive parameters of arterial stiffness and autonomic function using beat-to-beat cardiovascular signals over a period of > 5min were included. Study quality was assessed using the STROBE criteria. Two authors screened the titles, abstracts, and full texts independently. RESULTS: Nineteen studies met the inclusion criteria. A comprehensive overview of experimental design for assessing autonomic function in terms of baroreflex sensitivity and beat-to-beat cardiovascular variabilities, as well as arterial stiffness, was presented. Alterations in non-invasive indicators of autonomic function, which included baroreflex sensitivity, beat-to-beat cardiovascular variabilities and hemodynamic changes in response to autonomic challenges, as well as arterial stiffness, were identified in individuals with hypertension. A mixed result was found in terms of the association between non-invasive quantitative autonomic indices and arterial stiffness in hypertensive individuals. Nine out of 12 studies which quantified baroreflex sensitivity revealed a significant association with arterial stiffness parameters. Three studies estimated beat-to-beat heart rate variability and only one study reported a significant relationship with arterial stiffness indices. Three out of five studies which studied beat-to-beat blood pressure variability showed a significant association with arterial structural changes. One study revealed that hemodynamic changes in response to autonomic challenges were significantly correlated with arterial stiffness parameters. CONCLUSIONS: The current review demonstrated alteration in autonomic function, which encompasses both the sympathetic and parasympathetic modulation of sinus node function and vasomotor tone (derived from beat-to-beat cardiovascular signals) in hypertension, and a significant association between some of these parameters with arterial stiffness. By employing non-invasive measurements to monitor changes in autonomic function and arterial remodeling in individuals with hypertension, we would be able to enhance our ability to identify individuals at high risk of cardiovascular disease. Understanding the intricate relationships among these cardiovascular variability measures and arterial stiffness could contribute toward better individualized treatment for hypertension in the future. SYSTEMATIC REVIEW REGISTRATION: PROSPERO ID: CRD42022336703. Date of registration: 12/06/2022.

A Digitally Enabled, Pharmacist service to detecT medicine harms in residential aged care (nursing home) (ADEPT): protocol for a feasibility study.

INTRODUCTION: This feasibility study aims to develop and test a new model of practice in Australia using digital technologies to enable pharmacists to monitor early signs and symptoms of medicine-induced harms in residential aged care. METHODS AND ANALYSIS: Thirty residents will be recruited from an aged care facility in South Australia. The study will be conducted in two phases. In phase I, the study team will work with aged care software providers and developers of digital technologies (a wearable activity tracker and a sleep tracking sensor) to gather physical activity and sleep data, as well as medication and clinical data from the electronic medication management system and aged care clinical software. Data will be centralised into a cloud-based monitoring platform (TeleClinical Care (TCC)). The TCC will be used to create dashboards that will include longitudinal visualisations of changes in residents' health, function and medicine use over time. In phase II, the on-site pharmacist will use the centralised TCC platform to monitor each resident's medicine, clinical, physical activity and sleep data to identify signs of medicine-induced harms over a 12-week period.A mixed methods process evaluation applying the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) evaluation framework will be used to assess the feasibility of the service. Outcome measures include service reach, changes in resident symptom scores (measured using the Edmonton Symptom Assessment System), number of medication adverse events detected, changes in physical activity and sleep, number of pharmacist recommendations provided, cost analysis and proportion of all pharmacists' recommendations implemented at 4-week, 8-week and 12-week postbaseline period. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the University of South Australia's Human Research Ethics Committee (205098). Findings will be disseminated through published manuscripts, conference presentations and reporting to the study funder. TRIAL REGISTRATION NUMBER: ACTRN12623000506695.

Grand Challenges at the Interface of Engineering and Medicine.

Over the past two decades Biomedical Engineering has emerged as a major discipline that bridges societal needs of human health care with the development of novel technologies. Every medical institution is now equipped at varying degrees of sophistication with the ability to monitor human health in both non-invasive and invasive modes. The multiple scales at which human physiology can be interrogated provide a profound perspective on health and disease. We are at the nexus of creating "avatars" (herein defined as an extension of "digital twins") of human patho/physiology to serve as paradigms for interrogation and potential intervention. Motivated by the emergence of these new capabilities, the IEEE Engineering in Medicine and Biology Society, the Departments of Biomedical Engineering at Johns Hopkins University and Bioengineering at University of California at San Diego sponsored an interdisciplinary workshop to define the grand challenges that face biomedical engineering and the mechanisms to address these challenges. The Workshop identified five grand challenges with cross-cutting themes and provided a roadmap for new technologies, identified new training needs, and defined the types of interdisciplinary teams needed for addressing these challenges. The themes presented in this paper include: 1) accumedicine through creation of avatars of cells, tissues, organs and whole human; 2) development of smart and responsive devices for human function augmentation; 3) exocortical technologies to understand brain function and treat neuropathologies; 4) the development of approaches to harness the human immune system for health and wellness; and 5) new strategies to engineer genomes and cells.

Neural activity of retinal ganglion cells under continuous, dynamically-modulated high frequency electrical stimulation.

Objective.Current retinal prosthetics are limited in their ability to precisely control firing patterns of functionally distinct retinal ganglion cell (RGC) types. The aim of this study was to characterise RGC responses to continuous, kilohertz-frequency-varying stimulation to assess its utility in controlling RGC activity.Approach.We usedin vitropatch-clamp experiments to assess electrically-evoked ON and OFF RGC responses to frequency-varying pulse train sequences. In each sequence, the stimulation amplitude was kept constant while the stimulation frequency (0.5-10 kHz) was changed every 40 ms, in either a linearly increasing, linearly decreasing or randomised manner. The stimulation amplitude across sequences was increased from 10 to 300µA.Main results.We found that continuous stimulation without rest periods caused complex and irreproducible stimulus-response relationships, primarily due to strong stimulus-induced response adaptation and influence of the preceding stimulus frequency on the response to a subsequent stimulus. In addition, ON and OFF populations showed different sensitivities to continuous, frequency-varying pulse trains, with OFF cells generally exhibiting more dependency on frequency changes within a sequence. Finally, the ability to maintain spiking behaviour to continuous stimulation in RGCs significantly reduced over longer stimulation durations irrespective of the frequency order.Significance.This study represents an important step in advancing and understanding the utility of continuous frequency modulation in controlling functionally distinct RGCs. Our results indicate that continuous, kHz-frequency-varying stimulation sequences provide very limited control of RGC firing patterns due to inter-dependency between adjacent frequencies and generally, different RGC types do not display different frequency preferences under such stimulation conditions. For future stimulation strategies using kHz frequencies, careful consideration must be given to design appropriate pauses in stimulation, stimulation frequency order and the length of continuous stimulation duration.

Modulating functionally-distinct vagus nerve fibers using microelectrodes and kilohertz frequency electrical stimulation.

Modulation of functionally distinct nerve fibers with bioelectronic devices provides a therapeutic opportunity for various diseases. In this study, we began by developing a computational model including four major subtypes of myelinated fibers and one unmyelinated fiber. Second, we used an intrafascicular electrode to perform kHz-frequency electric stimulation to preferentially modulate a population of fibers. Our model suggests that fiber physical properties and electrode-to-fascicle distance severely impacts stimulus-response relationships. Large diameter fibers (Aα- and Aß-) were only minimally influenced by the fascicle size and electrode location, while smaller diameter fibers (Aδ-, B- and C-) indicated a stronger dependency.Clinical Relevance- Our findings support the possibility of selectively modulating functionally-distinct nerve fibers using electrical stimulation in a small, localized region. Our model provides an effective tool to design next-generation implantable devices and therapeutic stimulation strategies toward minimizing off-target effects.

Assessing the Generalizability of a Deep Learning-based Automated Atrial Fibrillation Algorithm.

Automated detection of atrial fibrillation (AF) from electrocardiogram (ECG) traces remains a challenging task and is crucial for telemonitoring of patients after stroke. This study aimed to quantify the generalizability of a deep learning (DL)-based automated ECG classification algorithm. We first developed a novel hybrid DL (HDL) model using the PhysioNet/CinC Challenge 2017 (CinC2017) dataset (publicly available) that can classify the ECG recordings as one of four classes: normal sinus rhythm (NSR), AF, other rhythms (OR), and too noisy (TN) recordings. The (pre)trained HDL was then used to classify 636 ECG samples collected by our research team using a handheld ECG device, CONTEC PM10 Portable ECG Monitor, from 102 (age: 68 ± 15 years, 74 male) outpatients of the Eastern Heart Clinic and inpatients in the Cardiology ward of Prince of Wales Hospital, Sydney, Australia. The proposed HDL model achieved average test F1-score of 0.892 for NSR, AF, and OR, relative to the reference values, on the CinC2017 dataset. The HDL model also achieved an average F1-score of 0.722 (AF: 0.905, NSR: 0.791, OR: 0.471 and TN: 0.342) on the dataset created by our research team. After retraining the HDL model on this dataset using a 5-fold cross validation method, the average F1-score increased to 0.961. We finally conclude that the generalizability of the HDL-based algorithm developed for AF detection from short-term single-lead ECG traces is acceptable. However, the accuracy of the pre-trained DL model was significantly improved by retraining the model parameters on the new dataset of ECG traces.

Evaluating Indices for Non-invasive Myocardial Recovery Assessment in LVAD-Supported Heart Failure Patients.

Accurate assessment of myocardial recovery (MR) under left ventricular assist device (LVAD) support is essential for clinicians to manage heart failure patients. However, current techniques for assessing MR are time-consuming, invasive, and infrequent. Measuring MR using indices derived from LVAD operating data instead provides a potential real-time alternative. Several of these indices for assessing the MR of LVAD-supported heart failure patients were collated from the literature and subject to a comprehensive comparative analysis. The objective of this analysis was to determine the most accurate index for assessing systolic cardiac function under LVAD-support, characterized by maximal end-systolic elastance (Emax), while remaining insensitive to preload & afterload. The indices were compared in computational simulation, utilizing an LVAD + cardiovascular system model to sweep through a large array of Emax and resistance conditions. Results demonstrated the index that correlated best with Emax, showing the highest accuracy, was the ratio between maximum flow acceleration and flow pulsatility (average R2 =0.9790). The same index also exhibited the lowest % variation (sensitivity) to preload & afterload (1.32% & 13.53% respectively). However, opportunities for improvement remain among current recovery assessment indices, with this study providing a baseline of performance for potential future indices to improve upon.Clinical relevance- This study presents a potential real-time measure of native cardiac function in LVAD-supported heart failure patients to support patient management and further recovery.

Immediate Effects of Lower Limb Sensory Simulation Using Smart Socks to Stabilize Gait in People with Parkinson's Disease.

People with Parkinson's disease (PD) experience gait impairment that can lead to falls and poor quality of life. Here we investigate the feasibility of using smart socks to stimulate the lower limbs of people with PD to reduce excessive step time variability during walking. We hypothesised that rythmic excitation of lower limb afferents, matched to a participant's comfortable pace, would entrain deficient neuro-muscular signals resulting in improved gait. Five people with mild to moderate PD symptoms (70 ± 9 years) were tested on medication before and after a 30-minute familierization session. Paired t-tests and Cohen's d were used to assess gait changes and report effect sizes. Participant experiences were recorded through structured interviews. Lower limb stimulation resulted in an acute 15% increase in gait speed (p=0.006, d=0.62), an 11% increase in step length (p=0.04, d=0.35), a 44% reduction in step time variability (p=0.03, d=0.91), a 22% increase in perceived gait quality (p=0.04, d=1.17), a 24% reduction in mental effort to walk (p=0.02, d=0.79) and no statistical difference for cadence (p=0.16). Participants commented positively on the benefit of stimulation during training but found that stimulation could be distracting when not walking and the socks hard to put on. While the large effects for step time variability and percieved gait quality (Cohen's d > 0.8) are promising, limitations regarding sample size, potential placebo effects and translation to the home environment should be addressed by future studies.Clinical Relevance- This study demonstrates the feasibility of using smart stimulating socks to reduce excessive step time variability in people with PD. As step time variability is a risk factor for falls, the use of smart textiles to augment future rehabilitation programs warrants further investigation.

Probing the Contribution of Vertical Processing Layers of the Retina to White-Noise Electrical Stimulation Responses.

Optimal stimulus parameters for epiretinal prostheses have been investigated by analyzing retinal ganglion cell (RGC) spiking responses to white-noise electrical stimulation, through a spike-triggered average (STA) analysis technique. However, it is currently unknown as to activation of which retinal cells contribute to features of the STA. We conducted whole-cell patch clamping recordings in ON and OFF RGCs in response to white-noise epiretinal electrical stimulation by using different inhibitors of synaptic transmission in a healthy retina. An mGluR6 agonist, L-AP4, was firstly used to selectively block the output of photoreceptors (PRs) to ON bipolar cells (BCs). We subsequently fully blocked all synaptic inputs to RGCs using a combination of pharmacological agents. Our data shows that PRs dominate the ability of ON RGCs to integrate electrical pulses and form a unique STA shape, while BCs do not contribute in any way. In addition, our results demonstrate that the ability of OFF RGCs to integrate pulses is consistently impaired after blocking the PR to ON BC pathway. We hypothesise that the mechanisms underlying this co-effect are related to the narrow field AII amacrine cells connecting ON and OFF pathways.Clinical Relevance-Recent retinal studies recorded mirror-inverted STAs in ON and OFF retinal pathways, thus raising the possibility of designing a stimulation approach that can differentially activate ON and OFF pathways with electrical stimulation. However, the detailed contribution of three major retinal cell layers in forming characteristic STAs is still unclear. It is of great clinical relevance to investigate the isolated contribution of PRs to the electrically driven STA since PRs progressively degenerate in the course of retinal disease.

Development of a rabbit model of Adenosine triphosphate-induced monocular retinal degeneration for optimization of retinal prostheses.

Optimization of retinal prostheses requires preclinical animal models that mimic features of human retinal disease, have appropriate eye sizes to accommodate implantable arrays, and provide options for unilateral degeneration so as to enable a contralateral, within-animal control eye. In absence of a suitable non-human primate model and shortcomings of our previous feline model generated through intravitreal injections of Adenosine Triphosphate (ATP), we aimed in the present study to develop an ATP induced degeneration model in the rabbit. Six normally sighted Dutch rabbits were monocularly blinded with this technique. Subsequent retinal degeneration was assessed with optical coherence tomography, electroretinography, and histological assays. Overall, there was a 42% and 26% reduction in a-wave and oscillatory potential amplitudes in the electroretinograms respectively, along with a global decrease in retinal thickness, with increased variability. Qualitative inspection also revealed that there were variable levels of retinal degeneration and remodeling both within and between treated eyes, mimicking the disease heterogeneity observed in retinitis pigmentosa. These findings confirm that ATP can be utilized to unilaterally induce blinding in rabbits and, potentially present an ideal model for future cortical recording experiments aimed at optimizing vision restoration strategies.Clinical Relevance- A rapid, unilaterally induced model of retinal degeneration in an animal with low binocular overlap and large eyes will allow for clinically valid recordings of downstream cortical activity following retinal stimulation. Such a model would be highly beneficial for the optimization of clinically appropriate vision restoration approaches.

The direct influence of retinal degeneration on electrical stimulation efficacy: Significant implications for retinal prostheses.

Photoreceptor loss and inner retinal network remodeling severely impacts the ability of retinal prosthetic devices to create artificial vision. We developed a computational model of a degenerating retina based on rodent data and tested its response to retinal electrical stimulation. This model includes detailed network connectivity and diverse neural intrinsic properties, capable of exploring how the degenerated retina influences the performance of electrical stimulation during the degeneration process. Our model suggests the possibility of quantitatively modulating retinal ON and OFF pathways between phase II and III of retinal degeneration without requiring any differences between ON and OFF RGC intrinsic cellular properties. The model also provided insights about how remodeling events influence stage-dependent differential electrical responses of ON and OFF pathways.Clinical Relevance-This data-driven model can guide future development of retinal prostheses and stimulation strategies that may benefit patients at different stages of retinal disease progression, particularly in the early and mid-stages, thus increasing their global acceptance.

Towards a single-use, low-cost endoscope for gastroenterological diagnostics.

Early diagnosis and treatment of diseases in the gastrointestinal (GI) tract including colorectal cancers (CRC) via natural orifices have led to a significant increase in patient survival rates. Most screening procedures utilize image-guided techniques via a conventional endoscope. The cost of conventional endoscopes is substantial, ranging in the tens of thousands of USD or more. This presents significant burden for developing countries, which are disproportionally affected by gastroenterological diseases. Conventional endoscopes also require sterilization between use. This increases the chance of cross-infection between patients. To address these problems, this paper introduces a soft endoscope with a disposable insertion tube that can be articulated. This prototype device is hydraulically actuated, capable of a 10 mm bend radius and 180-degree bend angle. The camera system provides 110 degrees field-of-view. The component parts of this disposable endoscope costs less than 200 USD.Clinical relevance-Our low-cost, single-use endoscope eliminates the sterilization step required by conventional systems, thereby reducing the risks of infection and lowering the operating costs. There is also significant scope for our device to be used beyond the human GI track, such as screening for lung or bladder cancers. Given the compact footprint, the minimal cost of the disposable parts, the proposed platform can widen cancer screening programs with quantifiable economic benefit for many patients, particularly those in developing countries.

Differences in Cardiovascular Regulation to Head-up Tilt between Healthy and Hypertensive Subjects.

To date there have only been limited studies exploring abnormal hemodynamic responses to head-up tilt tests (HUTs) in elderly, treated patients with hypertension. Cardiovascular regulation in response to HUT as well as upright hemodynamics may be altered when older hypertensive patients with antihypertensive treatments are studied. Hypertensive patients with and without receiving antihypertensive medication and above the age of 45 were recruited in this study. This study compared the cardiovascular responses to HUT and at rest between healthy and hypertensives using non-invasive hemodynamic measurements. Parameters such as systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), stroke index (SI) and total peripheral resistance index (TPRI) were measured in 40 subjects (20 healthy and 20 hypertensives) for 10-min supine baseline, 10-min HUT at 70◦ and 6-min supine recovery. At rest and during HUT, SBP and TPRI were significantly higher in hypertensives together with a significantly smaller baseline SI. In response to HUT, both groups showed changes in hemodynamic parameters at differing degrees. During recovery, all parameters returned to the baseline range. Our findings indicated that hypertensive patients of older age being treated by antihypertensive drugs may have different cardiovascular changes in response to orthostatic stress.Clinical Relevance- This pilot study describes how cardiovascular regulation in response to postural change may behave differently in hypertensive elder patients taking antihypertensive drugs.