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Journal of Addiction Medicine Jun 2024To prospectively assess rates of QT prolongation, arrhythmia, syncope, and sudden cardiac death (SCD) in a cohort of people with heroin dependence.
OBJECTIVES
To prospectively assess rates of QT prolongation, arrhythmia, syncope, and sudden cardiac death (SCD) in a cohort of people with heroin dependence.
METHODS
To estimate rates of QT prolongation, arrhythmia, and syncope, a subcohort (n = 130) from the Australian Treatment Outcomes Study, a prospective longitudinal cohort study of 615 people with heroin dependence, underwent medical history, venepuncture, and ECG at the 18- to 20-year follow-up.To estimate rates of SCD, probabilistic matching for the entire cohort was undertaken with the Australian Institute of Health and Welfare National Death Index. Deaths were classified into suicide, accidental overdose, trauma, unknown, and disease, which were then further subclassified by probability of SCD. SCD rate was the number of possible or probable SCDs divided by total patient years from the cohort.
RESULTS
From the subcohort, 4 participants (3%) met the criteria for QT prolongation; 3 were prescribed methadone. Seven participants (5%) reported history of arrhythmia, including 2 transferred from methadone to buprenorphine. Thirty participants (23%) reported a previous syncopal event-14 diagnosed as nonarrhythmic syncope and 13 not investigated. In the previous 12 months, 66 participants (51%) reported heroin use; 55 participants (42%) were prescribed methadone. No participant had QTc greater than 500 milliseconds.There were 3 possible SCDs, translating to an estimated SCD rate of 0.29 (CI: 0.05, 0.8) events per 1000 patient years. More cohort members died of overdose (n = 50), suicide (n = 11), and hepatitis C (n = 4).
CONCLUSIONS
Low rates of QT prolongation, arrhythmia, syncope, and SCD in the cohort despite high rates of heroin use and methadone treatment.
PubMed: 38941157
DOI: 10.1097/ADM.0000000000001317 -
Sensors (Basel, Switzerland) Jun 2024Smart wearable devices are extensively utilized across diverse domains due to their inherent advantages of flexibility, portability, and real-time monitoring. Among...
Smart wearable devices are extensively utilized across diverse domains due to their inherent advantages of flexibility, portability, and real-time monitoring. Among these, flexible sensors demonstrate exceptional pliability and malleability, making them a prominent focus in wearable electronics research. However, the implementation of flexible wearable sensors often entails intricate and time-consuming processes, leading to high costs, which hinder the advancement of the entire field. Here, we report a pressure and proximity sensor based on oxidized laser-induced graphene (oxidized LIG) as a dielectric layer sandwiched by patterned LIG electrodes, which is characterized by high speed and cost-effectiveness. It is found that in the low-frequency range of fewer than 0.1 kHz, the relative dielectric constant of the oxidized LIG layer reaches an order of magnitude of 104. The pressure mode of this bimodal capacitive sensor is capable of detecting pressures within the range of 1.34 Pa to 800 Pa, with a response time of several hundred milliseconds. The proximity mode involves the application of stimulation using an acrylic probe, which demonstrates a detection range from 0.05 mm to 37.8 mm. Additionally, it has a rapid response time of approximately 100 ms, ensuring consistent signal variations throughout both the approach and withdrawal phases. The sensor fabrication method proposed in this project effectively minimizes expenses and accelerates the preparation cycle through precise control of laser processing parameters to shape the electrode-dielectric layer-electrode within a single substrate material. Based on their exceptional combined performance, our pressure and proximity sensors exhibit significant potential in practical applications such as motion monitoring and distance detection.
PubMed: 38931691
DOI: 10.3390/s24123907 -
Sensors (Basel, Switzerland) Jun 2024The investigation of gait and its neuronal correlates under more ecologically valid conditions as well as real-time feedback visualization is becoming increasingly...
The investigation of gait and its neuronal correlates under more ecologically valid conditions as well as real-time feedback visualization is becoming increasingly important in neuro-motor rehabilitation research. The Gait Real-time Analysis Interactive Lab (GRAIL) offers advanced opportunities for gait and gait-related research by creating more naturalistic yet controlled environments through immersive virtual reality. Investigating the neuronal aspects of gait requires parallel recording of brain activity, such as through mobile electroencephalography (EEG) and/or mobile functional near-infrared spectroscopy (fNIRS), which must be synchronized with the kinetic and /or kinematic data recorded while walking. This proof-of-concept study outlines the required setup by use of the lab streaming layer (LSL) ecosystem for real-time, simultaneous data collection of two independently operating multi-channel EEG and fNIRS measurement devices and gait kinetics. In this context, a customized approach using a photodiode to synchronize the systems is described. This study demonstrates the achievable temporal accuracy of synchronous data acquisition of neurophysiological and kinematic and kinetic data collection in the GRAIL. By using event-related cerebral hemodynamic activity and visually evoked potentials during a start-to-go task and a checkerboard test, we were able to confirm that our measurement system can replicate known physiological phenomena with latencies in the millisecond range and relate neurophysiological and kinetic data to each other with sufficient accuracy.
Topics: Humans; Biomechanical Phenomena; Electroencephalography; Spectroscopy, Near-Infrared; Gait; Male; Gait Analysis; Adult; Female; Virtual Reality; Walking; Brain; Proof of Concept Study; Young Adult
PubMed: 38931563
DOI: 10.3390/s24123779 -
Advances in Experimental Medicine and... 2024Speech can be defined as the human ability to communicate through a sequence of vocal sounds. Consequently, speech requires an emitter (the speaker) capable of... (Review)
Review
Speech can be defined as the human ability to communicate through a sequence of vocal sounds. Consequently, speech requires an emitter (the speaker) capable of generating the acoustic signal and a receiver (the listener) able to successfully decode the sounds produced by the emitter (i.e., the acoustic signal). Time plays a central role at both ends of this interaction. On the one hand, speech production requires precise and rapid coordination, typically within the order of milliseconds, of the upper vocal tract articulators (i.e., tongue, jaw, lips, and velum), their composite movements, and the activation of the vocal folds. On the other hand, the generated acoustic signal unfolds in time, carrying information at different timescales. This information must be parsed and integrated by the receiver for the correct transmission of meaning. This chapter describes the temporal patterns that characterize the speech signal and reviews research that explores the neural mechanisms underlying the generation of these patterns and the role they play in speech comprehension.
Topics: Humans; Speech; Speech Perception; Speech Acoustics; Periodicity
PubMed: 38918356
DOI: 10.1007/978-3-031-60183-5_14 -
Advances in Experimental Medicine and... 2024Temporal information processing in the range of a few hundred milliseconds to seconds involves the cerebellum and basal ganglia. In this chapter, we present recent... (Review)
Review
Temporal information processing in the range of a few hundred milliseconds to seconds involves the cerebellum and basal ganglia. In this chapter, we present recent studies on nonhuman primates. In the studies presented in the first half of the chapter, monkeys were trained to make eye movements when a certain amount of time had elapsed since the onset of the visual cue (time production task). The animals had to report time lapses ranging from several hundred milliseconds to a few seconds based on the color of the fixation point. In this task, the saccade latency varied with the time length to be measured and showed stochastic variability from one trial to the other. Trial-to-trial variability under the same conditions correlated well with pupil diameter and the preparatory activity in the deep cerebellar nuclei and the motor thalamus. Inactivation of these brain regions delayed saccades when asked to report subsecond intervals. These results suggest that the internal state, which changes with each trial, may cause fluctuations in cerebellar neuronal activity, thereby producing variations in self-timing. When measuring different time intervals, the preparatory activity in the cerebellum always begins approximately 500 ms before movements, regardless of the length of the time interval being measured. However, the preparatory activity in the striatum persists throughout the mandatory delay period, which can be up to 2 s, with different rate of increasing activity. Furthermore, in the striatum, the visual response and low-frequency oscillatory activity immediately before time measurement were altered by the length of the intended time interval. These results indicate that the state of the network, including the striatum, changes with the intended timing, which lead to different time courses of preparatory activity. Thus, the basal ganglia appear to be responsible for measuring time in the range of several hundred milliseconds to seconds, whereas the cerebellum is responsible for regulating self-timing variability in the subsecond range. The second half of this chapter presents studies related to periodic timing. During eye movements synchronized with alternating targets at regular intervals, different neurons in the cerebellar nuclei exhibit activity related to movement timing, predicted stimulus timing, and the temporal error of synchronization. Among these, the activity associated with target appearance is particularly enhanced during synchronized movements and may represent an internal model of the temporal structure of stimulus sequence. We also considered neural mechanism underlying the perception of periodic timing in the absence of movement. During perception of rhythm, we predict the timing of the next stimulus and focus our attention on that moment. In the missing oddball paradigm, the subjects had to detect the omission of a regularly repeated stimulus. When employed in humans, the results show that the fastest temporal limit for predicting each stimulus timing is about 0.25 s (4 Hz). In monkeys performing this task, neurons in the cerebellar nuclei, striatum, and motor thalamus exhibit periodic activity, with different time courses depending on the brain region. Since electrical stimulation or inactivation of recording sites changes the reaction time to stimulus omission, these neuronal activities must be involved in periodic temporal processing. Future research is needed to elucidate the mechanism of rhythm perception, which appears to be processed by both cortico-cerebellar and cortico-basal ganglia pathways.
Topics: Animals; Cerebellum; Basal Ganglia; Time Perception; Saccades; Time Factors; Humans
PubMed: 38918348
DOI: 10.1007/978-3-031-60183-5_6 -
Advances in Experimental Medicine and... 2024Time is a critical variable that organisms must be able to measure in order to survive in a constantly changing environment. Initially, this paper describes the myriad... (Review)
Review
Time is a critical variable that organisms must be able to measure in order to survive in a constantly changing environment. Initially, this paper describes the myriad of contexts where time is estimated or predicted and suggests that timing is not a single process and probably depends on a set of different neural mechanisms. Consistent with this hypothesis, the explosion of neurophysiological and imaging studies in the last 10 years suggests that different brain circuits and neural mechanisms are involved in the ability to tell and use time to control behavior across contexts. Then, we develop a conceptual framework that defines time as a family of different phenomena and propose a taxonomy with sensory, perceptual, motor, and sensorimotor timing as the pillars of temporal processing in the range of hundreds of milliseconds.
Topics: Humans; Time Perception; Animals; Brain; Neurobiology
PubMed: 38918343
DOI: 10.1007/978-3-031-60183-5_1 -
Journal of Biomolecular NMR Jun 2024Solution NMR spectroscopy is a particularly powerful technique for characterizing the functional dynamics of biomolecules, which is typically achieved through the...
Solution NMR spectroscopy is a particularly powerful technique for characterizing the functional dynamics of biomolecules, which is typically achieved through the quantitative characterization of chemical exchange processes via the measurement of spin relaxation rates. In addition to the conventional nuclei such as N and C, which are abundant in biomolecules, fluorine-19 (F) has recently garnered attention and is being widely used as a site-specific spin probe. While F offers the advantages of high sensitivity and low background, it can be susceptible to artifacts in quantitative relaxation analyses due to a multitude of dipolar and scalar coupling interactions with nearby H spins. In this study, we focused on the ribose 2'-F spin probe in nucleic acids and investigated the effects of H-F spin interactions on the quantitative characterization of slow exchange processes on the millisecond time scale. We demonstrated that the H-F dipolar coupling can significantly affect the interpretation of F chemical exchange saturation transfer (CEST) experiments when H decoupling is applied, while the H-F interactions have a lesser impact on Carr-Purcell-Meiboom-Gill relaxation dispersion applications. We also proposed a modified CEST scheme to alleviate these artifacts along with experimental verifications on self-complementary RNA systems. The theoretical framework presented in this study can be widely applied to various F spin systems where H-F interactions are operative, further expanding the utility of F relaxation-based NMR experiments.
PubMed: 38918317
DOI: 10.1007/s10858-024-00446-7 -
Neuron Jun 2024The hippocampus receives sequences of sensory inputs from the cortex during exploration and encodes the sequences with millisecond precision. We developed a predictive...
The hippocampus receives sequences of sensory inputs from the cortex during exploration and encodes the sequences with millisecond precision. We developed a predictive autoencoder model of the hippocampus including the trisynaptic and monosynaptic circuits from the entorhinal cortex (EC). CA3 was trained as a self-supervised recurrent neural network to predict its next input. We confirmed that CA3 is predicting ahead by analyzing the spike coupling between simultaneously recorded neurons in the dentate gyrus, CA3, and CA1 of the mouse hippocampus. In the model, CA1 neurons signal prediction errors by comparing CA3 predictions to the next direct EC input. The model exhibits the rapid appearance and slow fading of CA1 place cells and displays replay and phase precession from CA3. The model could be learned in a biologically plausible way with error-encoding neurons. Similarities between the hippocampal and thalamocortical circuits suggest that such computation motif could also underlie self-supervised sequence learning in the cortex.
PubMed: 38917804
DOI: 10.1016/j.neuron.2024.05.024 -
Proceedings of the National Academy of... Jul 2024Dynamic protein structures are crucial for deciphering their diverse biological functions. Two-dimensional infrared (2DIR) spectroscopy stands as an ideal tool for...
Dynamic protein structures are crucial for deciphering their diverse biological functions. Two-dimensional infrared (2DIR) spectroscopy stands as an ideal tool for tracing rapid conformational evolutions in proteins. However, linking spectral characteristics to dynamic structures poses a formidable challenge. Here, we present a pretrained machine learning model based on 2DIR spectra analysis. This model has learned signal features from approximately 204,300 spectra to establish a "spectrum-structure" correlation, thereby tracing the dynamic conformations of proteins. It excels in accurately predicting the dynamic content changes of various secondary structures and demonstrates universal transferability on real folding trajectories spanning timescales from microseconds to milliseconds. Beyond exceptional predictive performance, the model offers attention-based spectral explanations of dynamic conformational changes. Our 2DIR-based pretrained model is anticipated to provide unique insights into the dynamic structural information of proteins in their native environments.
Topics: Machine Learning; Proteins; Spectrophotometry, Infrared; Protein Conformation; Protein Folding; Protein Structure, Secondary
PubMed: 38917009
DOI: 10.1073/pnas.2409257121 -
The Journal of Head Trauma... Jun 2024We investigated the acoustic startle reflex in recently concussed adolescent athletes compared to healthy controls and those with concussion history (>1 year prior) but...
OBJECTIVES
We investigated the acoustic startle reflex in recently concussed adolescent athletes compared to healthy controls and those with concussion history (>1 year prior) but no current symptoms. We hypothesized that individuals with recent concussion would have a suppressed startle response compared to healthy controls.
METHODS
We conducted a cross-sectional study on 49 adolescent athletes with a recent concussion (n = 20; age: 14.6 ± 1.6 years; 60% female), a concussion history > 1 year prior (n = 16; age: 14.8 ± 2.0 years; 44% female), and healthy controls (n = 13; age: 13.3 ± 2.8 years; 54% female). We measured the eyeblink of the general startle reflex via electromyography activity of the orbicularis oculi muscle using electrodes placed under the right eye. Measurement sessions included twelve 103 decibel acoustic startle probes ~50 milliseconds in duration delivered ~15-25 seconds apart. The primary dependent variable was mean startle magnitude (µV), and group was the primary independent variable. We used a one-way analysis of variance followed by a Tukey post hoc test to compare mean startle magnitude between groups.
RESULTS
Mean startle magnitude significantly differed (F = 5.49, P = .007) among the groups. Mean startle magnitude was significantly suppressed for the concussion (P = .01) and concussion history groups (P = .02) compared to healthy controls. There was no significant difference between the recent concussion and concussion history groups (P = 1.00).
CONCLUSION
Our results provide novel evidence for startle suppression in adolescent athletes following concussion. The concussion history group had an attenuated startle response beyond resolution of their recovery, suggesting there may be lingering physiological dysfunction.
PubMed: 38916433
DOI: 10.1097/HTR.0000000000000979