Selective Activation of Cells by Piezoelectric Molybdenum Disulfide Nanosheets with Focused Ultrasound.

An accurate method for neural stimulation within the brain could be very useful for treating brain circuit dysfunctions and neurological disorders. With the aim of developing such a method, this study investigated the use of piezoelectric molybdenum disulfide nanosheets (MoS2 NS) to remotely convert ultrasound energy into localized electrical stimulation in vitro and in vivo. The application of ultrasound to cells surrounding MoS2 NS required only a single pulse of 2 MHz ultrasound (400 kPa, 1,000,000 cycles, and 500 ms pulse duration) to elicit significant responses in 37.9 ± 7.4% of cells in terms of fluxes of calcium ions without detectable cellular damage. The proportion of responsive cells was mainly influenced by the acoustic pressure, number of ultrasound cycles, and concentration of MoS2 NS. Tests using appropriate blockers revealed that voltage-gated membrane channels were activated. In vivo data suggested that, with ultrasound stimulation, neurons closest to the MoS2 NS were 3-fold more likely to present c-Fos expression than cells far from the NS. The successful activation of neurons surrounding MoS2 NS suggests that this represents a method with high spatial precision for selectively modulating one or several targeted brain circuits.

Classification of Patient Recovery from COVID-19 Symptoms using Consumer Wearables and Machine Learning.

Current remote monitoring of COVID-19 patients relies on manual symptom reporting, which is highly dependent on patient compliance. In this research, we present a machine learning (ML)-based remote monitoring method to estimate patient recovery from COVID-19 symptoms using automatically collected wearable device data, instead of relying on manually collected symptom data. We deploy our remote monitoring system, namely eCOVID, in two COVID-19 telemedicine clinics. Our system utilizes a Garmin wearable and symptom tracker mobile app for data collection. The data consists of vitals, lifestyle, and symptom information which is fused into an online report for clinicians to review. Symptom data collected via our mobile app is used to label the recovery status of each patient daily. We propose a ML-based binary patient recovery classifier which uses wearable data to estimate whether a patient has recovered from COVID-19 symptoms. We evaluate our method using leave-one-subject-out (LOSO) cross-validation, and find that Random Forest (RF) is the top performing model. Our method achieves an F1-score of 0.88 when applying our RF-based model personalization technique using weighted bootstrap aggregation. Our results demonstrate that ML-assisted remote monitoring using automatically collected wearable data can supplement or be used in place of manual daily symptom tracking which relies on patient compliance.

Wireless neuromodulation in vitro and in vivo by intrinsic TRPC-mediated magnetomechanical stimulation.

Various magnetic deep brain stimulation (DBS) methods have been developing rapidly in the last decade for minimizing the invasiveness of DBS. However, current magnetic DBS methods, such as magnetothermal and magnetomechanical stimulation, require overexpressing exogeneous ion channels in the central nervous system (CNS). It is unclear whether magnetomechanical stimulation can modulate non-transgenic CNS neurons or not. Here, we reveal that the torque of magnetic nanodiscs with weak and slow alternative magnetic field (50 mT at 10 Hz) could activate neurons through the intrinsic transient receptor potential canonical channels (TRPC), which are mechanosensitive ion channels widely expressed in the brain. The immunostaining with c-fos shows the increasement of neuronal activity by wireless DBS with magnetomechanical approach in vivo. Overall, this research demonstrates a magnetic nanodiscs-based magnetomechanical approach that can be used for wireless neuronal stimulation in vitro and untethered DBS in vivo without implants or genetic manipulation.

Personalized Blood Pressure Estimation Using Photoplethysmography: A Transfer Learning Approach.

In this paper, we present a personalized deep learning approach to estimate blood pressure (BP) using the photoplethysmogram (PPG) signal. We propose a hybrid neural network architecture consisting of convolutional, recurrent, and fully connected layers that operates directly on the raw PPG time series and provides BP estimation every 5 seconds. To address the problem of limited personal PPG and BP data for individuals, we propose a transfer learning technique that personalizes specific layers of a network pre-trained with abundant data from other patients. We use the MIMIC III database which contains PPG and continuous BP data measured invasively via an arterial catheter to develop and analyze our approach. Our transfer learning technique, namely BP-CRNN-Transfer, achieves a mean absolute error (MAE) of 3.52 and 2.20 mmHg for SBP and DBP estimation, respectively, outperforming existing methods. Our approach satisfies both the BHS and AAMI blood pressure measurement standards for SBP and DBP. Moreover, our results demonstrate that as little as 50 data samples per person are required to train accurate personalized models. We carry out Bland-Altman and correlation analysis to compare our method to the invasive arterial catheter, which is the gold-standard BP measurement method.

Using Wearables and Machine Learning to Enable Personalized Lifestyle Recommendations to Improve Blood Pressure.

Background: Blood pressure (BP) is an essential indicator for human health and is known to be greatly influenced by lifestyle factors, like activity and sleep factors. However, the degree of impact of each lifestyle factor on BP is unknown and may vary between individuals. Our goal is to investigate the relationships between BP and lifestyle factors and provide personalized and precise recommendations to improve BP, as opposed to the current practice of general lifestyle recommendations. Method: Our proposed system consists of automated data collection using home BP monitors and wearable activity trackers and feature engineering techniques to address time-series data and enhance interpretability. We propose Random Forest with Shapley-Value-based Feature Selection to offer personalized BP modeling and top lifestyle factor identification, and subsequent generation of precise recommendations based on the top factors. Result: In collaboration with UC San Diego Health and Altman Clinical and Translational Research Institute, we performed a clinical study, applying our system to 25 patients with elevated BP or stage I hypertension for three consecutive months. Our study results validate our system's ability to provide accurate personalized BP models and identify the top features which can vary greatly between individuals. We also validate the effectiveness of personalized recommendations in a randomized controlled experiment. After receiving recommendations, the subjects in the experimental group decreased their BPs by 3.8 and 2.3 for systolic and diastolic BP, compared to the decrease of 0.3 and 0.9 for the subjects without recommendations. Conclusion: The study demonstrates the potential of using wearables and machine learning to develop personalized models and precise lifestyle recommendations to improve BP.

Magnetothermal nanoparticle technology alleviates parkinsonian-like symptoms in mice.

Deep brain stimulation (DBS) has long been used to alleviate symptoms in patients suffering from psychiatric and neurological disorders through stereotactically implanted electrodes that deliver current to subcortical structures via wired pacemakers. The application of DBS to modulate neural circuits is, however, hampered by its mechanical invasiveness and the use of chronically implanted leads, which poses a risk for hardware failure, hemorrhage, and infection. Here, we demonstrate that a wireless magnetothermal approach to DBS (mDBS) can provide similar therapeutic benefits in two mouse models of Parkinson's disease, the bilateral 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and in the unilateral 6-hydroxydopamine (6-OHDA) model. We show magnetothermal neuromodulation in untethered moving mice through the activation of the heat-sensitive capsaicin receptor (transient receptor potential cation channel subfamily V member 1, TRPV1) by synthetic magnetic nanoparticles. When exposed to an alternating magnetic field, the nanoparticles dissipate heat, which triggers reversible firing of TRPV1-expressing neurons. We found that mDBS in the subthalamic nucleus (STN) enables remote modulation of motor behavior in healthy mice. Moreover, mDBS of the STN reversed the motor deficits in a mild and severe parkinsonian model. Consequently, this approach is able to activate deep-brain circuits without the need for permanently implanted hardware and connectors.

In Vivo Photopharmacology Enabled by Multifunctional Fibers.

Photoswitchable ligands can add an optical switch to a target receptor or signaling cascade and enable reversible control of neural circuits. The application of this approach, termed photopharmacology, to behavioral experiments has been impeded by a lack of integrated hardware capable of delivering both light and compounds to deep brain regions in moving subjects. Here, we devise a hybrid photochemical genetic approach to target neurons using a photoswitchable agonist of the capsaicin receptor TRPV1, red-AzCA-4. Using multifunctional fibers with optical and microfluidic capabilities, we delivered a transgene coding for TRPV1 into the ventral tegmental area (VTA). This sensitized excitatory VTA neurons to red-AzCA-4, allowing us to optically control conditioned place preference in mice, thus extending applications of photopharmacology to behavioral experiments. Applied to endogenous receptors, our approach may accelerate future studies of molecular mechanisms underlying animal behavior.

Remotely Controlled Proton Generation for Neuromodulation.

Understanding and modulating proton-mediated biochemical processes in living organisms have been impeded by the lack of tools to control local pH. Here, we design nanotransducers capable of converting noninvasive alternating magnetic fields (AMFs) into protons in physiological environments by combining magnetic nanoparticles (MNPs) with polymeric scaffolds. When exposed to AMFs, the heat dissipated by MNPs triggered a hydrolytic degradation of surrounding polyanhydride or polyester, releasing protons into the extracellular space. pH changes induced by these nanotransducers can be tuned by changing the polymer chemistry or AMF stimulation parameters. Remote magnetic control of local protons was shown to trigger acid-sensing ion channels and to evoke intracellular calcium influx in neurons. By offering a wireless modulation of local pH, our approach can accelerate the mechanistic investigation of the role of protons in biochemical signaling in the nervous system.

In situ electrochemical generation of nitric oxide for neuronal modulation.

Understanding the function of nitric oxide, a lipophilic messenger in physiological processes across nervous, cardiovascular and immune systems, is currently impeded by the dearth of tools to deliver this gaseous molecule in situ to specific cells. To address this need, we have developed iron sulfide nanoclusters that catalyse nitric oxide generation from benign sodium nitrite in the presence of modest electric fields. Locally generated nitric oxide activates the nitric oxide-sensitive cation channel, transient receptor potential vanilloid family member 1 (TRPV1), and the latency of TRPV1-mediated Ca2+ responses can be controlled by varying the applied voltage. Integrating these electrocatalytic nanoclusters with multimaterial fibres allows nitric oxide-mediated neuronal interrogation in vivo. The in situ generation of nitric oxide in the ventral tegmental area with the electrocatalytic fibres evoked neuronal excitation in the targeted brain region and its excitatory projections. This nitric oxide generation platform may advance mechanistic studies of the role of nitric oxide in the nervous system and other organs.

Magnetic Vortex Nanodiscs Enable Remote Magnetomechanical Neural Stimulation.

Magnetic nanomaterials in magnetic fields can serve as versatile transducers for remote interrogation of cell functions. In this study, we leveraged the transition from vortex to in-plane magnetization in iron oxide nanodiscs to modulate the activity of mechanosensory cells. When a vortex configuration of spins is present in magnetic nanomaterials, it enables rapid control over their magnetization direction and magnitude. The vortex configuration manifests in near zero net magnetic moment in the absence of a magnetic field, affording greater colloidal stability of magnetic nanomaterials in suspensions. Together, these properties invite the application of magnetic vortex particles as transducers of externally applied minimally invasive magnetic stimuli in biological systems. Using magnetic modeling and electron holography, we predict and experimentally demonstrate magnetic vortex states in an array of colloidally synthesized magnetite nanodiscs 98-226 nm in diameter. The magnetic nanodiscs applied as transducers of torque for remote control of mechanosensory neurons demonstrated the ability to trigger Ca2+ influx in weak (≤28 mT), slowly varying (≤5 Hz) magnetic fields. The extent of cellular response was determined by the magnetic nanodisc volume and magnetic field conditions. Magnetomechanical activation of a mechanosensitive cation channel TRPV4 (transient receptor potential vanilloid family member 4) exogenously expressed in the nonmechanosensitive HEK293 cells corroborated that the stimulation is mediated by mechanosensitive ion channels. With their large magnetic torques and colloidal stability, magnetic vortex particles may facilitate basic studies of mechanoreception and its applications to control electroactive cells with remote magnetic stimuli.

Transgene-free remote magnetothermal regulation of adrenal hormones.

The field of bioelectronic medicines seeks to modulate electrical signaling within peripheral organs, providing temporally precise control of physiological functions. This is usually accomplished with implantable devices, which are often unsuitable for interfacing with soft and highly vascularized organs. Here, we demonstrate an alternative strategy for modulating peripheral organ function, which relies on the endogenous expression of a heat-sensitive cation channel, transient receptor potential vanilloid family member 1 (TRPV1), and heat dissipation by magnetic nanoparticles (MNPs) in remotely applied alternating magnetic fields. We use this approach to wirelessly control adrenal hormone secretion in genetically intact rats. TRPV1-dependent calcium influx into the cells of adrenal cortex and medulla is sufficient to drive rapid release of corticosterone and (nor)epinephrine. As altered levels of these hormones have been correlated with mental conditions such as posttraumatic stress disorder and major depression, our approach may facilitate the investigation of physiological and psychological impacts of stress.

Magnetothermal Multiplexing for Selective Remote Control of Cell Signaling.

Magnetic nanoparticles have garnered sustained research interest for their promise in biomedical applications including diagnostic imaging, triggered drug release, cancer hyperthermia, and neural stimulation. Many of these applications make use of heat dissipation by ferrite nanoparticles under alternating magnetic fields, with these fields acting as an externally administered stimulus that is either present or absent, toggling heat dissipation on and off. Here, we motivate and demonstrate an extension of this concept, magnetothermal multiplexing, in which exposure to alternating magnetic fields of differing amplitude and frequency can result in selective and independent heating of magnetic nanoparticle ensembles. The differing magnetic coercivity of these particles, empirically characterized by a custom high amplitude alternating current magnetometer, informs the systematic selection of a multiplexed material system. This work culminates in a demonstration of magnetothermal multiplexing for selective remote control of cellular signaling in vitro.

Remotely controlled chemomagnetic modulation of targeted neural circuits.

Connecting neural circuit output to behaviour can be facilitated by the precise chemical manipulation of specific cell populations1,2. Engineered receptors exclusively activated by designer small molecules enable manipulation of specific neural pathways3,4. However, their application to studies of behaviour has thus far been hampered by a trade-off between the low temporal resolution of systemic injection versus the invasiveness of implanted cannulae or infusion pumps2. Here, we developed a remotely controlled chemomagnetic modulation-a nanomaterials-based technique that permits the pharmacological interrogation of targeted neural populations in freely moving subjects. The heat dissipated by magnetic nanoparticles (MNPs) in the presence of alternating magnetic fields (AMFs) triggers small-molecule release from thermally sensitive lipid vesicles with a 20 s latency. Coupled with the chemogenetic activation of engineered receptors, this technique permits the control of specific neurons with temporal and spatial precision. The delivery of chemomagnetic particles to the ventral tegmental area (VTA) allows the remote modulation of motivated behaviour in mice. Furthermore, this chemomagnetic approach activates endogenous circuits by enabling the regulated release of receptor ligands. Applied to an endogenous dopamine receptor D1 (DRD1) agonist in the nucleus accumbens (NAc), a brain area involved in mediating social interactions, chemomagnetic modulation increases sociability in mice. By offering a temporally precise control of specified ligand-receptor interactions in neurons, this approach may facilitate molecular neuroscience studies in behaving organisms.

Scalable Fabrication of Porous Microchannel Nerve Guidance Scaffolds with Complex Geometries.

Microchannel scaffolds accelerate nerve repair by guiding growing neuronal processes across injury sites. Although geometry, materials chemistry, stiffness, and porosity have been shown to influence nerve growth within nerve guidance scaffolds, independent tuning of these properties in a high-throughput manner remains a challenge. Here, fiber drawing is combined with salt leaching to produce microchannels with tunable cross sections and porosity. This technique is applicable to an array of biochemically inert polymers, and it delivers hundreds of meters of porous microchannel fibers. Employing these fibers as filaments during 3D printing enables the production of microchannel scaffolds with geometries matching those of biological nerves, including branched topographies. Applied to sensory neurons, fiber-based porous microchannels enhance growth as compared to non-porous channels with matching materials and geometries. The combinatorial scaffold fabrication approach may advance the studies of neural regeneration and accelerate the development of nerve repair devices.

ASIC-dependent LTP at multiple glutamatergic synapses in amygdala network is required for fear memory.

Genetic variants in the human ortholog of acid-sensing ion channel-1a subunit (ASIC1a) gene are associated with panic disorder and amygdala dysfunction. Both fear learning and activity-induced long-term potentiation (LTP) of cortico-basolateral amygdala (BLA) synapses are impaired in ASIC1a-null mice, suggesting a critical role of ASICs in fear memory formation. In this study, we found that ASICs were differentially expressed within the amygdala neuronal population, and the extent of LTP at various glutamatergic synapses correlated with the level of ASIC expression in postsynaptic neurons. Importantly, selective deletion of ASIC1a in GABAergic cells, including amygdala output neurons, eliminated LTP in these cells and reduced fear learning to the same extent as that found when ASIC1a was selectively abolished in BLA glutamatergic neurons. Thus, fear learning requires ASIC-dependent LTP at multiple amygdala synapses, including both cortico-BLA input synapses and intra-amygdala synapses on output neurons.

GABA is depolarizing in hippocampal dentate granule cells of the adolescent and adult rats.

GABAergic signaling in hippocampal pyramidal neurons undergoes a switch from depolarizing to hyperpolarizing during early neuronal development. Whether such a transformation of GABAergic action occurs in dentate granule cells (DGCs), located at the first stage of the hippocampal trisynaptic circuit, is unclear. Here, we use noninvasive extracellular recording to monitor the effect of synaptically released GABA on the DGC population. We find that GABAergic responses in adolescent and adult rat DGCs are still depolarizing from rest. Using a morphologically realistic DGC model, we show that GABAergic action, depending on its precise timing and location, can have either an excitatory or inhibitory role in signal processing in the dentate gyrus.