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.

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.

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.

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.

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.

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.

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.

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.

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.

A Smart, Textile-Driven, Soft Exosuit for Spinal Assistance.

Work-related musculoskeletal disorders (WMSDs) are often caused by repetitive lifting, making them a significant concern in occupational health. Although wearable assist devices have become the norm for mitigating the risk of back pain, most spinal assist devices still possess a partially rigid structure that impacts the user's comfort and flexibility. This paper addresses this issue by presenting a smart textile-actuated spine assistance robotic exosuit (SARE), which can conform to the back seamlessly without impeding the user's movement and is incredibly lightweight. To detect strain on the spine and to control the smart textile automatically, a soft knitting sensor that utilizes fluid pressure as a sensing element is used. Based on the soft knitting hydraulic sensor, the robotic exosuit can also feature the ability of monitoring and rectifying human posture. The SARE is validated experimentally with human subjects (N = 4). Through wearing the SARE in stoop lifting, the peak electromyography (EMG) signals of the lumbar erector spinae are reduced by 22.8% ± 12 for lifting 5 kg weights and 27.1% ± 14 in empty-handed conditions. Moreover, the integrated EMG decreased by 34.7% ± 11.8 for lifting 5 kg weights and 36% ± 13.3 in empty-handed conditions. In summary, the artificial muscle wearable device represents an anatomical solution to reduce the risk of muscle strain, metabolic energy cost and back pain associated with repetitive lifting tasks.

Emerging trends in the development of flexible optrode arrays for electrophysiology.

Optical-electrode (optrode) arrays use light to modulate excitable biological tissues and/or transduce bioelectrical signals into the optical domain. Light offers several advantages over electrical wiring, including the ability to encode multiple data channels within a single beam. This approach is at the forefront of innovation aimed at increasing spatial resolution and channel count in multichannel electrophysiology systems. This review presents an overview of devices and material systems that utilize light for electrophysiology recording and stimulation. The work focuses on the current and emerging methods and their applications, and provides a detailed discussion of the design and fabrication of flexible arrayed devices. Optrode arrays feature components non-existent in conventional multi-electrode arrays, such as waveguides, optical circuitry, light-emitting diodes, and optoelectronic and light-sensitive functional materials, packaged in planar, penetrating, or endoscopic forms. Often these are combined with dielectric and conductive structures and, less frequently, with multi-functional sensors. While creating flexible optrode arrays is feasible and necessary to minimize tissue-device mechanical mismatch, key factors must be considered for regulatory approval and clinical use. These include the biocompatibility of optical and photonic components. Additionally, material selection should match the operating wavelength of the specific electrophysiology application, minimizing light scattering and optical losses under physiologically induced stresses and strains. Flexible and soft variants of traditionally rigid photonic circuitry for passive optical multiplexing should be developed to advance the field. We evaluate fabrication techniques against these requirements. We foresee a future whereby established telecommunications techniques are engineered into flexible optrode arrays to enable unprecedented large-scale high-resolution electrophysiology systems.

Modulating individual axons and axonal populations in the peripheral nerve using transverse intrafascicular multichannel electrodes.

Objective.A transverse intrafascicular multichannel electrode (TIME) may offer advantages over more conventional cuff electrodes including higher spatial selectivity and reduced stimulation charge requirements. However, the performance of TIME, especially in the context of non-conventional stimulation waveforms, remains relatively unexplored. As part of our overarching goal of investigating stimulation efficacy of TIME, we developed a computational toolkit that automates the creation and usage ofin siliconerve models with TIME setup, which solves nerve responses using cable equations and computes extracellular potentials using finite element method.Approach.We began by implementing a flexible and scalable Python/MATLAB-based toolkit for automatically creating models of nerve stimulation in the hybrid NEURON/COMSOL ecosystems. We then developed a sciatic nerve model containing 14 fascicles with 1,170 myelinated (A-type, 30%) and unmyelinated (C-type, 70%) fibers to study fiber responses over a variety of TIME arrangements (monopolar and hexapolar) and stimulation waveforms (kilohertz stimulation and cathodic ramp modulation).Main results.Our toolkit obviates the conventional need to re-create the same nerve in two disparate modeling environments and automates bi-directional transfer of results. Our population-based simulations suggested that kilohertz stimuli provide selective activation of targeted C fibers near the stimulating electrodes but also tended to activate non-targeted A fibers further away. However, C fiber selectivity can be enhanced by hexapolar TIME arrangements that confined the spatial extent of electrical stimuli. Improved upon prior findings, we devised a high-frequency waveform that incorporates cathodic DC ramp to completely remove undesirable onset responses.Conclusion.Our toolkit allows agile, iterative design cycles involving the nerve and TIME, while minimizing the potential operator errors during complex simulation. The nerve model created by our toolkit allowed us to study and optimize the design of next-generation intrafascicular implants for improved spatial and fiber-type selectivity.

Technological Convergence: Highlighting the Power of CRISPR Single-Cell Perturbation Toolkit for Functional Interrogation of Enhancers.

Higher eukaryotic enhancers, as a major class of regulatory elements, play a crucial role in the regulation of gene expression. Over the last decade, the development of sequencing technologies has flooded researchers with transcriptome-phenotype data alongside emerging candidate regulatory elements. Since most methods can only provide hints about enhancer function, there have been attempts to develop experimental and computational approaches that can bridge the gap in the causal relationship between regulatory regions and phenotypes. The coupling of two state-of-the-art technologies, also referred to as crisprQTL, has emerged as a promising high-throughput toolkit for addressing this question. This review provides an overview of the importance of studying enhancers, the core molecular foundation of crisprQTL, and recent studies utilizing crisprQTL to interrogate enhancer-phenotype correlations. Additionally, we discuss computational methods currently employed for crisprQTL data analysis. We conclude by pointing out common challenges, making recommendations, and looking at future prospects, with the aim of providing researchers with an overview of crisprQTL as an important toolkit for studying enhancers.

Development and preliminary usability testing of an electronic conversation guide incorporating patient values and prognostic information in preparation for older people's decision-making near the end of life.

Initiating end-of-life conversations can be daunting for clinicians and overwhelming for patients and families. This leads to delays in communicating prognosis and preparing for the inevitable in old age, often generating potentially harmful overtreatment and poor-quality deaths. We aimed to develop an electronic resource, called Communicating Health Alternatives Tool (CHAT) that was compatible with hospital medical records software to facilitate preparation for shared decision-making across health settings with older adults deemed to be in the last year of life. The project used mixed methods including: literature review, user-directed specifications, web-based interface development with authentication and authorization; clinician and consumer co-design, iterative consultation for user testing; and ongoing developer integration of user feedback. An internet-based conversation guide to facilitate clinician-led advance care planning was co-developed covering screening for short-term risk of death, patient values and preferences, and treatment choices for chronic kidney disease and dementia. Printed summary of such discussion could be used to begin the process in hospital or community health services. Clinicians, patients, and caregivers agreed with its ease of use and were generally accepting of its contents and format. CHAT is available to health services for implementation in effectiveness trials to determine whether the interaction and documentation leads to formal decision-making, goal-concordant care, and subsequent reduction of unwanted treatments at the end of life.