Clinician and Family Caregiver Perspectives on Deprescribing Chronic Disease Medications in Older Nursing Home Residents Near the End of Life.

INTRODUCTION: Nursing home (NH) residents with limited life expectancy (LLE) who are intensely treated for hyperlipidemia, hypertension, or diabetes may benefit from deprescribing. OBJECTIVE: This study sought to describe NH clinician and family caregiver perspectives on key influences on deprescribing decisions for chronic disease medications in NH residents near the end of life. METHODS: We recruited family caregivers of veterans who recently died in a Veterans Affairs (VA) NH, known as community living centers (CLCs), and CLC healthcare clinicians (physicians, nurse practitioners, physician assistants, pharmacists, registered nurses). Respondents completed semi-structured interviews about their experiences with deprescribing statin, antihypertensive, and antidiabetic medications for residents near end of life. We conducted thematic analysis of interview transcripts to identify key themes regarding influences on deprescribing decisions. RESULTS: Thirteen family caregivers and 13 clinicians completed interviews. Key themes included (1) clinicians and caregivers both prefer to minimize drug burden; (2) clinical factors strongly influence deprescribing of chronic disease medications, with differences in how clinicians and caregivers weigh specific factors; (3) caregivers trust and rely on clinicians to make deprescribing decisions; (4) clinicians perceive caregiver involvement and buy-in as essential to deprescribing decisions, which requires time and effort to obtain; and (5) clinicians perceive conflicting care from other clinicians as a barrier to deprescribing. CONCLUSIONS: Findings suggest a need for efforts to encourage communication with and education for family caregivers of residents with LLE about deprescribing, and to foster better collaboration among clinicians in CLC and non-CLC settings.

DeepDOF-SE: affordable deep-learning microscopy platform for slide-free histology.

Histopathology plays a critical role in the diagnosis and surgical management of cancer. However, access to histopathology services, especially frozen section pathology during surgery, is limited in resource-constrained settings because preparing slides from resected tissue is time-consuming, labor-intensive, and requires expensive infrastructure. Here, we report a deep-learning-enabled microscope, named DeepDOF-SE, to rapidly scan intact tissue at cellular resolution without the need for physical sectioning. Three key features jointly make DeepDOF-SE practical. First, tissue specimens are stained directly with inexpensive vital fluorescent dyes and optically sectioned with ultra-violet excitation that localizes fluorescent emission to a thin surface layer. Second, a deep-learning algorithm extends the depth-of-field, allowing rapid acquisition of in-focus images from large areas of tissue even when the tissue surface is highly irregular. Finally, a semi-supervised generative adversarial network virtually stains DeepDOF-SE fluorescence images with hematoxylin-and-eosin appearance, facilitating image interpretation by pathologists without significant additional training. We developed the DeepDOF-SE platform using a data-driven approach and validated its performance by imaging surgical resections of suspected oral tumors. Our results show that DeepDOF-SE provides histological information of diagnostic importance, offering a rapid and affordable slide-free histology platform for intraoperative tumor margin assessment and in low-resource settings.

Miniature battery-free epidural cortical stimulators.

Miniaturized neuromodulation systems could improve the safety and reduce the invasiveness of bioelectronic neuromodulation. However, as implantable bioelectronic devices are made smaller, it becomes difficult to store enough power for long-term operation in batteries. Here, we present a battery-free epidural cortical stimulator that is only 9 millimeters in width yet can safely receive enough wireless power using magnetoelectric antennas to deliver 14.5-volt stimulation bursts, which enables it to stimulate cortical activity on-demand through the dura. The device has digitally programmable stimulation output and centimeter-scale alignment tolerances when powered by an external transmitter. We demonstrate that this device has enough power and reliability for real-world operation by showing acute motor cortex activation in human patients and reliable chronic motor cortex activation for 30 days in a porcine model. This platform opens the possibility of simple surgical procedures for precise neuromodulation.

Mesoscopic calcium imaging in a head-unrestrained male non-human primate using a lensless microscope.

Mesoscopic calcium imaging enables studies of cell-type specific neural activity over large areas. A growing body of literature suggests that neural activity can be different when animals are free to move compared to when they are restrained. Unfortunately, existing systems for imaging calcium dynamics over large areas in non-human primates (NHPs) are table-top devices that require restraint of the animal's head. Here, we demonstrate an imaging device capable of imaging mesoscale calcium activity in a head-unrestrained male non-human primate. We successfully miniaturize our system by replacing lenses with an optical mask and computational algorithms. The resulting lensless microscope can fit comfortably on an NHP, allowing its head to move freely while imaging. We are able to measure orientation columns maps over a 20 mm2 field-of-view in a head-unrestrained macaque. Our work establishes mesoscopic imaging using a lensless microscope as a powerful approach for studying neural activity under more naturalistic conditions.

Clinical outcomes of peripheral nerve interfaces for rehabilitation in paralysis and amputation: a literature review.

Peripheral nerve interfaces (PNIs) are electrical systems designed to integrate with peripheral nerves in patients, such as following central nervous system (CNS) injuries to augment or replace CNS control and restore function. We review the literature for clinical trials and studies containing clinical outcome measures to explore the utility of human applications of PNIs. We discuss the various types of electrodes currently used for PNI systems and their functionalities and limitations. We discuss important design characteristics of PNI systems, including biocompatibility, resolution and specificity, efficacy, and longevity, to highlight their importance in the current and future development of PNIs. The clinical outcomes of PNI systems are also discussed. Finally, we review relevant PNI clinical trials that were conducted, up to the present date, to restore the sensory and motor function of upper or lower limbs in amputees, spinal cord injury patients, or intact individuals and describe their significant findings. This review highlights the current progress in the field of PNIs and serves as a foundation for future development and application of PNI systems.

Imine-Linked 2D Conjugated Porous Organic Polymer Films for Tunable Acid Vapor Sensing.

Two-dimensional (2D) films of conjugated porous organic polymers (C-POPs) can translate the rich in-plane functionalities of conjugated frameworks into diverse optical and electronic applications while addressing the processability issues of their crystalline analogs for adaptable device architectures. However, the lack of facile single-step synthetic routes to obtain large-area high-quality films of 2D-C-POPs has limited their application possibilities so far. Here, we report the synthesis of four mechanically robust imine-linked 2D-C-POP free-standing films using a single-step fast condensation route that is scalable and tunable. The rigid covalently bonded 2D structures of the C-POP films offer high stability for volatile gas sensing in harsh environments while simultaneously enhancing site accessibility for gas molecules due to mesoporosity by structural design. Structurally, all films were composed of exfoliable layers of 2D polymeric nanosheets (NSs) that displayed anisotropy from disordered stacking, evinced by out-of-plane birefringent properties. The tunable in-plane conjugation, different nitrogen centers, and porous structures allow the films to act as ultraresponsive colorimetric sensors for acid sensing via reversible imine bond protonation. All the films could detect hydrogen chloride (HCl) gas down to 0.05 ppm, far exceeding the Occupational Safety and Health Administration's permissible exposure limit of 5 ppm with fast response time and good recyclability. Computational insights elucidated the effect of conjugation and tertiary nitrogen in the structures on the sensitivity and response time of the films. Furthermore, we exploited the exfoliated large 2D NSs and anisotropic optoelectronic properties of the films to adapt them into micro-optical and triboelectric devices to demonstrate their real-time sensing capabilities.

Self-rectifying magnetoelectric metamaterials for remote neural stimulation and motor function restoration.

Magnetoelectric materials convert magnetic fields into electric fields. These materials are often used in wireless electronic and biomedical applications. For example, magnetoelectrics could enable the remote stimulation of neural tissue, but the optimal resonance frequencies are typically too high to stimulate neural activity. Here we describe a self-rectifying magnetoelectric metamaterial for a precisely timed neural stimulation. This metamaterial relies on nonlinear charge transport across semiconductor layers that allow the material to generate a steady bias voltage in the presence of an alternating magnetic field. We generate arbitrary pulse sequences with time-averaged voltage biases in excess of 2 V. As a result, we can use magnetoelectric nonlinear metamaterials to wirelessly stimulate peripheral nerves to restore a sensory reflex in an anaesthetized rat model and restore signal propagation in a severed nerve with latencies of less than 5 ms. Overall, these results showing the rational design of magnetoelectric metamaterials support applications in advanced biotechnology and electronics.

Miniature battery-free bioelectronics.

Miniature wireless bioelectronic implants that can operate for extended periods of time can transform how we treat disorders by acting rapidly on precise nerves and organs in a way that drugs cannot. To reach this goal, materials and methods are needed to wirelessly transfer energy through the body or harvest energy from the body itself. We review some of the capabilities of emerging energy transfer methods to identify the performance envelope for existing technology and discover where opportunities lie to improve how much-and how efficiently-we can deliver energy to the tiny bioelectronic implants that can support emerging medical technologies.

Real-time, deep-learning aided lensless microscope.

Traditional miniaturized fluorescence microscopes are critical tools for modern biology. Invariably, they struggle to simultaneously image with a high spatial resolution and a large field of view (FOV). Lensless microscopes offer a solution to this limitation. However, real-time visualization of samples is not possible with lensless imaging, as image reconstruction can take minutes to complete. This poses a challenge for usability, as real-time visualization is a crucial feature that assists users in identifying and locating the imaging target. The issue is particularly pronounced in lensless microscopes that operate at close imaging distances. Imaging at close distances requires shift-varying deconvolution to account for the variation of the point spread function (PSF) across the FOV. Here, we present a lensless microscope that achieves real-time image reconstruction by eliminating the use of an iterative reconstruction algorithm. The neural network-based reconstruction method we show here, achieves more than 10000 times increase in reconstruction speed compared to iterative reconstruction. The increased reconstruction speed allows us to visualize the results of our lensless microscope at more than 25 frames per second (fps), while achieving better than 7 µm resolution over a FOV of 10 mm2. This ability to reconstruct and visualize samples in real-time empowers a more user-friendly interaction with lensless microscopes. The users are able to use these microscopes much like they currently do with conventional microscopes.

Magnetoelectrics Enables Large Power Delivery to mm-Sized Wireless Bioelectronics.

To maximize the capabilities of minimally invasive implantable bioelectronic devices, we must deliver large amounts of power to small implants; however, as devices are made smaller, it becomes more difficult to transfer large amounts of power without a wired connection. Indeed, recent work has explored creative wireless power transfer (WPT) approaches to maximize power density (the amount of power transferred divided by receiver footprint area (length × width)). Here, we analyzed a model for WPT using magnetoelectric (ME) materials that convert an alternating magnetic field into an alternating voltage. With this model, we identify the parameters that impact WPT efficiency and optimize the power density. We find that improvements in adhesion between the laminated ME layers, clamping, and selection of material thicknesses lead to a power density of 3.1 mW/mm 2 , which is over 4 times larger than previously reported for mm-sized wireless bioelectronic implants at a depth of 1 cm or more in tissue. This improved power density allows us to deliver 31 mW and 56 mW to 10-mm 2 and 27-mm 2 ME receivers, respectively. This total power delivery is over 5 times larger than similarly sized bioelectronic devices powered by radiofrequency electromagnetic waves, inductive coupling, ultrasound, light, capacitive coupling, or previously reported magnetoelectrics. This increased power density opens the door to more power-intensive bioelectronic applications that have previously been inaccessible using mm-sized battery-free devices.

Magnetoelectrics enables large power delivery to mm-sized wireless bioelectronics.

To maximize the capabilities of minimally invasive implantable bioelectronic devices, we must deliver large amounts of power to small implants; however, as devices are made smaller, it becomes more difficult to transfer large amounts of power without a wired connection. Indeed, recent work has explored creative wireless power transfer (WPT) approaches to maximize power density [the amount of power transferred divided by receiver footprint area (length × width)]. Here, we analyzed a model for WPT using magnetoelectric (ME) materials that convert an alternating magnetic field into an alternating voltage. With this model, we identify the parameters that impact WPT efficiency and optimize the power density. We find that improvements in adhesion between the laminated ME layers, clamping, and selection of material thicknesses lead to a power density of 3.1 mW/mm2, which is over four times larger than previously reported for mm-sized wireless bioelectronic implants at a depth of 1 cm or more in tissue. This improved power density allows us to deliver 31 and 56 mW to 10 and 27-mm2 ME receivers, respectively. This total power delivery is over five times larger than similarly sized bioelectronic devices powered by radiofrequency electromagnetic waves, inductive coupling, ultrasound, light, capacitive coupling, or previously reported magnetoelectrics. This increased power density opens the door to more power-intensive bioelectronic applications that have previously been inaccessible using mm-sized battery-free devices.

Molecular machines stimulate intercellular calcium waves and cause muscle contraction.

Intercellular calcium waves (ICW) are complex signalling phenomena that control many essential biological activities, including smooth muscle contraction, vesicle secretion, gene expression and changes in neuronal excitability. Accordingly, the remote stimulation of ICW could result in versatile biomodulation and therapeutic strategies. Here we demonstrate that light-activated molecular machines (MM)-molecules that perform mechanical work on the molecular scale-can remotely stimulate ICW. MM consist of a polycyclic rotor and stator that rotate around a central alkene when activated with visible light. Live-cell calcium-tracking and pharmacological experiments reveal that MM-induced ICW are driven by the activation of inositol-triphosphate-mediated signalling pathways by unidirectional, fast-rotating MM. Our data suggest that MM-induced ICW can control muscle contraction in vitro in cardiomyocytes and animal behaviour in vivo in Hydra vulgaris. This work demonstrates a strategy for directly controlling cell signalling and downstream biological function using molecular-scale devices.

High-Speed Time-Domain Diffuse Optical Tomography with a Sensitivity Equation-based Neural Network.

Steady progress in time-domain diffuse optical tomography (TD-DOT) technology is allowing for the first time the design of low-cost, compact, and high-performance systems, thus promising more widespread clinical TD-DOT use, such as for recording brain tissue hemodynamics. TD-DOT is known to provide more accurate values of optical properties and physiological parameters compared to its frequency-domain or steady-state counterparts. However, achieving high temporal resolution is still difficult, as solving the inverse problem is computationally demanding, leading to relatively long reconstruction times. The runtime is further compromised by processes that involve 'nontrivial' empirical tuning of reconstruction parameters, which increases complexity and inefficiency. To address these challenges, we present a new reconstruction algorithm that combines a deep-learning approach with our previously introduced sensitivity-equation-based, non-iterative sparse optical reconstruction (SENSOR) code. The new algorithm (called SENSOR-NET) unfolds the iterations of SENSOR into a deep neural network. In this way, we achieve high-resolution sparse reconstruction using only learned parameters, thus eliminating the need to tune parameters prior to reconstruction empirically. Furthermore, once trained, the reconstruction time is not dependent on the number of sources or wavelengths used. We validate our method with numerical and experimental data and show that accurate reconstructions with 1 mm spatial resolution can be obtained in under 20 milliseconds regardless of the number of sources used in the setup. This opens the door for real-time brain monitoring and other high-speed DOT applications.

Unrolled-DOT: an interpretable deep network for diffuse optical tomography.

Significance: Imaging through scattering media is critical in many biomedical imaging applications, such as breast tumor detection and functional neuroimaging. Time-of-flight diffuse optical tomography (ToF-DOT) is one of the most promising methods for high-resolution imaging through scattering media. ToF-DOT and many traditional DOT methods require an image reconstruction algorithm. Unfortunately, this algorithm often requires long computational runtimes and may produce lower quality reconstructions in the presence of model mismatch or improper hyperparameter tuning. Aim: We used a data-driven unrolled network as our ToF-DOT inverse solver. The unrolled network is faster than traditional inverse solvers and achieves higher reconstruction quality by accounting for model mismatch. Approach: Our model "Unrolled-DOT" uses the learned iterative shrinkage thresholding algorithm. In addition, we incorporate a refinement U-Net and Visual Geometry Group (VGG) perceptual loss to further increase the reconstruction quality. We trained and tested our model on simulated and real-world data and benchmarked against physics-based and learning-based inverse solvers. Results: In experiments on real-world data, Unrolled-DOT outperformed learning-based algorithms and achieved over 10× reduction in runtime and mean-squared error, compared to traditional physics-based solvers. Conclusion: We demonstrated a learning-based ToF-DOT inverse solver that achieves state-of-the-art performance in speed and reconstruction quality, which can aid in future applications for noninvasive biomedical imaging.

Subdural CMOS optical probe (SCOPe) for bidirectional neural interfacing.

Optical neurotechnologies use light to interface with neurons and can monitor and manipulate neural activity with high spatial-temporal precision over large cortical extents. While there has been significant progress in miniaturizing microscope for head-mounted configurations, these existing devices are still very bulky and could never be fully implanted. Any viable translation of these technologies to human use will require a much more noninvasive, fully implantable form factor. Here, we leverage advances in microelectronics and heterogeneous optoelectronic packaging to develop a transformative, ultrathin, miniaturized device for bidirectional optical stimulation and recording: the subdural CMOS Optical Probe (SCOPe). By being thin enough to lie entirely within the subdural space of the primate brain, SCOPe defines a path for the eventual human translation of a new generation of brain-machine interfaces based on light.

Recent Advances in Lensless Imaging.

Lensless imaging provides opportunities to design imaging systems free from the constraints imposed by traditional camera architectures. Thanks to advances in imaging hardware, fabrication techniques, and new algorithms, researchers have recently developed lensless imaging systems that are extremely compact, lightweight or able to image higher-dimensional quantities. Here we review these recent advances and describe the design principles and their effects that one should consider when developing and using lensless imaging systems.

Magnetoelectric Bio-Implants Powered and Programmed by a Single Transmitter for Coordinated Multisite Stimulation.

This paper presents a hardware platform including stimulating implants wirelessly powered and controlled by a shared transmitter for coordinated leadless multisite stimulation. The adopted novel single-transmitter, multiple-implant structure can flexibly deploy stimuli, improve system efficiency, easily scale stimulating channel quantity and relieve efforts in device synchronization. In the proposed system, a wireless link leveraging magnetoelectric effects is co-designed with a robust and efficient system-on-chip to enable reliable operation and individual programming of every implant. Each implant integrates a 0.8-mm2 chip, a 6-mm2 magnetoelectric film, and an energy storage capacitor within a 6.2-mm3 size. Magnetoelectric power transfer is capable of safely transmitting milliwatt power to devices placed several centimeters away from the transmitter coil, maintaining good efficiency with size constraints and tolerating 60-degree, 1.5-cm misalignment in angular and lateral movement. The SoC robustly operates with 2-V source amplitude variations that spans a 40-mm transmitter-implant distance change, realizes individual addressability through physical unclonable function IDs, and achieves 90% efficiency for 1.5-to-3.5-V stimulation with fully programmable stimulation parameters.

Health care costs and utilization prior to diagnosis of antineutrophil cytoplasmic antibody vasculitis in Medicare beneficiaries.

BACKGROUND: Antineutrophil cytoplasmic antibody (ANCA) vasculitis (AV) is a complex group of autoimmune disorders affecting blood vessels in multiple organ systems. Delays in diagnosis are common because AV symptoms can be nonspecific and present heterogeneously. This may result in increased health care utilization in the months preceding diagnosis. OBJECTIVE: To examine whether Medicare beneficiaries with AV experienced increased health care utilization and costs in the year before the first diagnosis recorded in claims, relative to beneficiaries without AV. METHODS: This retrospective cohort study used 2015-2016 Medicare Part A/B claims and Part D prescription drug data. Beneficiaries with newly diagnosed AV were identified by having 1 or more inpatient claims or 2 or more noninpatient claims 7 or more days apart in 2016 with an International Classification of Diseases, Tenth Revision, Clinical Modification code for AV, with no AV claims in the year prior. Beneficiaries with AV were matched 1:1 on age and sex to beneficiaries without any diagnoses for any type of systemic vasculitis in 2016. Beneficiaries with Part A/B coverage (AB, n = 1,460) and Part A/B/D coverage (ABD, n = 3,252) were analyzed separately. We estimated generalized linear mixed models with a negative binomial distribution to compare health care costs and utilization by AV status. RESULTS: Beneficiaries with AV had approximately 3 times higher Medicare Part A/B payments (incidence rate ratio [95% CI]: AB: 2.94 [2.44-3.53]; ABD: 2.95 [2.64-3.29]) and 2.5 times higher beneficiary Part A/B payments (AB: 2.47 [2.14-2.84]; ABD: 2.62 [2.40-2.87]) vs beneficiaries without AV. Beneficiaries with AV experienced significantly higher utilization across all categories, with the largest differences observed in hospital outpatient visits (AB: 2.69 [2.22-3.27]; ABD: 3.08 [2.73-3.47]). CONCLUSIONS: In the year prior to AV diagnosis, Medicare beneficiaries have significantly higher health care costs and utilization than beneficiaries without AV. DISCLOSURES: Dr Huang was supported by the University of North Carolina and GlaxoSmithKline Health Outcomes Fellowship during the time of the study and reports current employment at Horizon Therapeutics, Deerfield, IL. Dr Nguyen received predoctoral funding through a fellowship appointment sponsored by Bristol Myers Squibb during the time of the study and reports current employment at GlaxoSmithKline, Collegeville, PA. Dr Derebail receives personal fees from Travere Therapeutics, Bayer, and UpToDate, outside of the submitted work. The views expressed are those of the authors and do not represent the views of the Department of Veteran Affairs. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Central sleep apnea in otherwise healthy term infants.

STUDY OBJECTIVES: To describe the outcomes of central sleep apnea requiring home supplemental oxygen therapy in otherwise healthy term infants. METHODS: All children < 1 year of age undergoing polysomnography between 2015 and 2020 at the Queensland Children's Hospital were retrospectively studied. Children with gestational age < 37 weeks, underlying syndrome, cleft palate, those with obstructive apnea-hypopnea index > 50% of total apnea-hypopnea index, or with underlying cardiac or pulmonary parenchymal pathology were excluded. Polysomnography parameters were extracted for periods both on and off supplemental oxygenation. RESULTS: Fifty-two (mean [standard deviation] age at polysomnography 32.6 [34.7] days; 21 females) term infants were included. There was a statistically significant improvement in apnea-hypopnea index on supplemental oxygen (mean [standard deviation] in room air 50.2 [36.3] vs 11.6 [9], P < .001 on supplemental oxygen), in both rapid eye movement and nonrapid eye movement sleep, as well as in mean oxygen saturations (96.6% in room air to 98.9% on oxygen; P < .001). There was no statistically significant change in transcutaneous carbon dioxide levels or sleep duration. Oxygenation was prescribed for a median (interquartile range) age of 197 (127) days. CONCLUSIONS: Central sleep apnea in term infants who are otherwise healthy generally has a good prognosis, with oxygen therapy prescribed for around 6 months. Oxygen therapy was associated with improved saturations and decrease in apnea-hypopnea index when assessed with polysomnography. CITATION: Hayashi A, Suresh S, Kevat A, Robinson J, Kapur N. Central sleep apnea in otherwise healthy term infants. J Clin Sleep Med. 2022; 18(12):2813-2817.