Executive Summary of 2023 International Conference of the Korean Dementia Association (IC-KDA 2023): A Report From the Academic Committee of the Korean Dementia Association.

The Korean Dementia Association (KDA) has been organizing biennial international academic conferences since 2019, with the International Conference of the KDA (IC-KDA) 2023 held in Busan under the theme 'Beyond Boundaries: Advancing Global Dementia Solutions.' The conference comprised 6 scientific sessions, 3 plenary lectures, and 4 luncheon symposiums, drawing 804 participants from 35 countries. Notably, a Korea-Taiwan Joint Symposium addressed insights into Alzheimer's disease (AD). Plenary lectures by renowned scholars explored topics such as microbiome-related AD pathogenesis, social cognition in neurodegenerative diseases, and genetic frontotemporal dementia (FTD). On the first day, specific presentations covered subjects like the gut-brain axis and neuroinflammation in dementia, blood-based biomarkers in AD, and updates in AD therapeutics. The second day's presentations addressed recent issues in clinical neuropsychology, FTD cohort studies, and the pathogenesis of non-AD dementia. The Academic Committee of the KDA compiles lecture summaries to provide comprehensive understanding of the advanced dementia knowledge presented at IC-KDA 2023.

A comprehensive research setup for monitoring Alzheimer's disease using EEG, fNIRS, and Gait analysis.

Alzheimer's disease (AD) has a detrimental impact on brain function, affecting various aspects such as cognition, memory, language, and motor skills. Previous research has dominantly used electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to individually measure brain signals or combine the two methods to target specific brain functions. However, comprehending Alzheimer's disease requires monitoring various brain functions rather than focusing on a single function. This paper presents a comprehensive research setup for a monitoring platform for AD. The platform incorporates a 32-channel dry electrode EEG, a custom-built four-channel fNIRS, and gait monitoring using a depth camera and pressure sensor. Various tasks are employed to target multiple brain functions. The paper introduced the detailed instrumentation of the fNIRS system, which measures the prefrontal cortex, outlines the experimental design targeting various brain functioning programmed in BCI2000 for visualizing EEG signals synchronized with experimental stimulation, and describes the gait monitoring hardware and software and protocol design. The ultimate goal of this platform is to develop an easy-to-perform brain and gait monitoring method for elderly individuals and patients with Alzheimer's disease. Supplementary Information: The online version contains supplementary material available at 10.1007/s13534-023-00306-7.

Advancements in Wearable EEG Technology for Improved Home-Based Sleep Monitoring and Assessment: A Review.

Sleep is a fundamental aspect of daily life, profoundly impacting mental and emotional well-being. Optimal sleep quality is vital for overall health and quality of life, yet many individuals struggle with sleep-related difficulties. In the past, polysomnography (PSG) has served as the gold standard for assessing sleep, but its bulky nature, cost, and the need for expertise has made it cumbersome for widespread use. By recognizing the need for a more accessible and user-friendly approach, wearable home monitoring systems have emerged. EEG technology plays a pivotal role in sleep monitoring, as it captures crucial brain activity data during sleep and serves as a primary indicator of sleep stages and disorders. This review provides an overview of the most recent advancements in wearable sleep monitoring leveraging EEG technology. We summarize the latest EEG devices and systems available in the scientific literature, highlighting their design, form factors, materials, and methods of sleep assessment. By exploring these developments, we aim to offer insights into cutting-edge technologies, shedding light on wearable EEG sensors for advanced at-home sleep monitoring and assessment. This comprehensive review contributes to a broader perspective on enhancing sleep quality and overall health using wearable EEG sensors.

Rapid identification of counterfeited beef using deep learning-aided spectroscopy: Detecting colourant and curing agent adulteration.

The adulteration of meat products using colourants and curing agents has heightened concerns over food safety, thereby necessitating the development of advanced detection methods. This study introduces a deep-learning-based spectroscopic method for swiftly identifying counterfeit beef altered to appear fresh. The experiment involved 60 beef samples, half of which were artificially adulterated using a colouring solution. Despite meticulous analysis of the beef's colour attributes, no significant differences were observed between the fresh and adulterated samples. However, our method, utilising a 344-1040 nm spectral range, achieved a classification accuracy of 98.84%. To enhance practicality, we employed gradient-weighted class activation mapping and identified the 580-600 nm range as particularly influential for classification. Remarkably, even when we narrowed the input to the model to this spectral range, a high level of classification accuracy was maintained. To further validate the model's robustness and generalisability, we allocated 70 beef samples to an external validation set. Comparative performance analysis revealed that our model outperformed traditional machine learning algorithms, such as SVM and logistic regression, by 9.3% and 28.4%, respectively. Overall, this study offers invaluable insights for detecting counterfeited beef, thereby contributing to the preservation of meat product quality and integrity within the food industry.

Quantification of identifying cognitive impairment using olfactory-stimulated functional near-infrared spectroscopy with machine learning: a post hoc analysis of a diagnostic trial and validation of an external additional trial.

BACKGROUND: We aimed to quantify the identification of mild cognitive impairment and/or Alzheimer's disease using olfactory-stimulated functional near-infrared spectroscopy using machine learning through a post hoc analysis of a previous diagnostic trial and an external additional trial. METHODS: We conducted two independent, patient-level, single-group, diagnostic interventional trials (original and additional trials) involving elderly volunteers (aged > 60 years) with suspected declining cognitive function. All volunteers were assessed by measuring the oxygenation difference in the orbitofrontal cortex using an open-label olfactory-stimulated functional near-infrared spectroscopy approach, medical interview, amyloid positron emission tomography, brain magnetic resonance imaging, Mini-Mental State Examination, and Seoul Neuropsychological Screening Battery. RESULTS: In total, 97 (original trial) and 36 (additional trial) elderly volunteers with suspected decline in cognitive function met the eligibility criteria. The statistical model reported classification accuracies of 87.3% in patients with mild cognitive impairment and Alzheimer's disease in internal validation (original trial) but 63.9% in external validation (additional trial). The machine learning algorithm achieved 92.5% accuracy with the internal validation data and 82.5% accuracy with the external validation data. For the diagnosis of mild cognitive impairment, machine learning performed better than statistical methods with internal (86.0% versus 85.2%) and external validation data (85.4% versus 68.8%). INTERPRETATION: In two independent trials, machine learning models using olfactory-stimulated oxygenation differences in the orbitofrontal cortex were superior in diagnosing mild cognitive impairment and Alzheimer's disease compared to classic statistical models. Our results suggest that the machine learning algorithm is stable across different patient groups and increases generalization and reproducibility. TRIAL REGISTRATION: Clinical Research Information Service (CRiS) of Republic of Korea; CRIS numbers, KCT0006197 and KCT0007589.

Tablet-Based Wearable Patch Sensor Design for Continuous Cardiovascular System Monitoring in Postoperative Settings.

Meticulous monitoring for cardiovascular systems is important for postoperative patients in postanesthesia or the intensive care unit. The continuous auscultation of heart and lung sounds can provide a valuable information for patient safety. Although numerous research projects have proposed the design of continuous cardiopulmonary monitoring devices, they primarily focused on the auscultation of heart and lung sounds and mostly served as screening tools. However, there is a lack of devices that could continuously display and monitor the derived cardiopulmonary parameters. This study presents a novel approach to address this need by proposing a bedside monitoring system that utilizes a lightweight and wearable patch sensor for continuous cardiovascular system monitoring. The heart and lung sounds were collected using a chest stethoscope and microphones, and a developed adaptive noise cancellation algorithm was implemented to remove the background noise corrupted with those sounds. Additionally, a short-distance ECG signal was acquired using electrodes and a high precision analog front end. A high-speed processing microcontroller was used to allow real-time data acquisition, processing, and display. A dedicated tablet-based software was developed to display the acquired signal waveforms and the processed cardiovascular parameters. A significant contribution of this work is the seamless integration of continuous auscultation and ECG signal acquisition, thereby enabling the real-time monitoring of cardiovascular parameters. The wearability and lightweight design of the system were achieved through the use of rigid-flex PCBs, which ensured patient comfort and ease of use. The system provides a high-quality signal acquisition and real-time monitoring of the cardiovascular parameters, thus proving its potential as a health monitoring tool.

Vision transformers for the prediction of mild cognitive impairment to Alzheimer's disease progression using mid-sagittal sMRI.

Background: Alzheimer's disease (AD) is one of the most common causes of neurodegenerative disease affecting over 50 million people worldwide. However, most AD diagnosis occurs in the moderate to late stage, which means that the optimal time for treatment has already passed. Mild cognitive impairment (MCI) is an intermediate state between cognitively normal people and AD patients. Therefore, the accurate prediction in the conversion process of MCI to AD may allow patients to start preventive intervention to slow the progression of the disease. Nowadays, neuroimaging techniques have been developed and are used to determine AD-related structural biomarkers. Deep learning approaches have rapidly become a key methodology applied to these techniques to find biomarkers. Methods: In this study, we aimed to investigate an MCI-to-AD prediction method using Vision Transformers (ViT) to structural magnetic resonance images (sMRI). The Alzheimer's Disease Neuroimaging Initiative (ADNI) database containing 598 MCI subjects was used to predict MCI subjects' progression to AD. There are three main objectives in our study: (i) to propose an MRI-based Vision Transformers approach for MCI to AD progression classification, (ii) to evaluate the performance of different ViT architectures to obtain the most advisable one, and (iii) to visualize the brain region mostly affect the prediction of deep learning approach to MCI progression. Results: Our method achieved state-of-the-art classification performance in terms of accuracy (83.27%), specificity (85.07%), and sensitivity (81.48%) compared with a set of conventional methods. Next, we visualized the brain regions that mostly contribute to the prediction of MCI progression for interpretability of the proposed model. The discriminative pathological locations include the thalamus, medial frontal, and occipital-corroborating the reliability of our model. Conclusion: In conclusion, our methods provide an effective and accurate technique for the prediction of MCI conversion to AD. The results obtained in this study outperform previous reports using the ADNI collection, and it suggests that sMRI-based ViT could be efficiently applied with a considerable potential benefit for AD patient management. The brain regions mostly contributing to prediction, in conjunction with the identified anatomical features, will support the building of a robust solution for other neurodegenerative diseases in future.

The Effects of Manual Acupuncture on Mitochondrial Fusion and Fission Gene Expression in Rat Spleen.

Background: A significant amount of research has been conducted to establish the validity of acupuncture, and it has been demonstrated through animal disease model studies that acupuncture influences mitochondrial changes. However, to more accurately examine the mechanisms of acupuncture treatment effectiveness in pathological models, it is crucial to investigate changes in disease-free animals. Among various hypotheses regarding the effects of acupuncture on the body, we focused on the result that acupuncture stimulation is related to mitochondria. Objectives: We examined the effects of acupuncture mitochondrial fission and fusionrelated mediators in disease-free Sprague Dawley (SD) rats' spleen meridian acupoints. Methods: SD rats were divided into control, SP1, SP2, SP3, SP5, and SP9 acupuncture groups. Acupuncture was performed at each point for 10 minutes daily for four days. Peroxisome proliferator-activated receptor-gamma coactivator 1-α (PGC-1α) and fission protein 1 (Fis1) levels were evaluated using quantitative real-time polymerase chain reaction (qRT-PCR), while dynamin-related protein 1 (DRP1), optic atrophy-1 (OPA1), mitofusin-1 (MFN1), and mitofusin-2 (MFN2) levels were assessed via western blotting. Mitochondria protein concentrations and NADH dehydrogenase activity in spleen tissues were measured using enzyme-linked immunosorbent assay (ELISA). Results: PGC-1α expression decreased in the SP1 (p < 0.01), SP5 (p < 0.05), and SP9 (p < 0.05) groups, while Fis1 expression increased in the SP1 (p < 0.01), SP5 (p < 0.01), and SP9 (p < 0.05) groups. DRP1, OPA1, MFN1, and MFN2 levels exhibited no significant changes. Mitochondrial protein concentrations decreased in the SP2 (p < 0.01), SP3 (p < 0.01), SP5 (p < 0.01), and SP9 (p < 0.01) groups, while NADH dehydrogenase activity decreased in the SP2 (p < 0.05) and SP9 (p < 0.05) groups. Conclusion: Acupuncture at the SP9 acupoint influenced the mitochondrial fission pathway by modulating PGC-1α and Fis1 mediators in the rat spleen under non-disease conditions.

Cutaneous Photorejuvenation of Light Emitting Diodes via the Melatonin Membrane Receptor Pathway.

BACKGROUND: Melatonin receptors are present in the human skin and retina. These receptors can be stimulated by light emitting diodes (LEDs) at specific wavelengths, thereby inducing cutaneous photorejuvenation. However, the underlying mechanism remains unclear. OBJECTIVE: To evaluate the influence of LEDs at specific wavelengths on melatonin membrane receptor (MT1) and cutaneous photorejuvenation via the MT1 pathway in vitro. METHODS: Normal human dermal fibroblasts (HDFs) were irradiated using LEDs at different wavelengths (410~940 nm) at a dose of 1 J/cm². MT1 activity was evaluated after melatonin stimulation and LED irradiation. Thereafter, the expressions of collagen (COL) and matrix metalloproteinases (MMPs), with and without luzindole (MT1/2 receptor antagonist), were investigated via semi-quantitative reverse transcription polymerase chain reaction (PCR), real-time PCR, western blotting, and enzyme-linked immunosorbent assay. RESULTS: In HDFs, the MT1 mRNA and protein levels increased significantly in response to melatonin (dose, 50 nM) (p<0.01) and LED irradiation at 595, 630, 850, and 940 nm (p<0.01). LED irradiation up-regulated COL type I and down-regulated MMP-1. Compared to LED irradiation without luzindole, LED irradiation with luzindole produced no significant increase in COL type I mRNA and protein levels (p<0.01). CONCLUSION: We found that LED irradiation induces collagen synthesis and MMP-1 inhibition in HDFs via MT1 activation. Additionally, multiple LED wavelengths (595, 630, 850, and 940 nm) stimulated MT1 in HDFs, unlike in the eyes, where only blue light induced plasma melatonin suppression. This suggests the possibility of the melatoninergic pathway in photorejuvenation.

Use of Hypoxic Respiratory Challenge for Differentiating Alzheimer's Disease and Wild-Type Mice Non-Invasively: A Diffuse Optical Spectroscopy Study.

Alzheimer's disease is one of the most critical brain diseases. The prevalence of the disease keeps rising due to increasing life spans. This study aims to examine the use of hemodynamic signals during hypoxic respiratory challenge for the differentiation of Alzheimer's disease (AD) and wild-type (WT) mice. Diffuse optical spectroscopy, an optical system that can non-invasively monitor transient changes in deoxygenated (ΔRHb) and oxygenated (ΔOHb) hemoglobin concentrations, was used to monitor hemodynamic reactivity during hypoxic respiratory challenges in an animal model. From the acquired signals, 13 hemodynamic features were extracted from each of ΔRHb and -ΔOHb (26 features total) for more in-depth analyses of the differences between AD and WT. The hemodynamic features were statistically analyzed and tested to explore the possibility of using machine learning (ML) to differentiate AD and WT. Among the twenty-six features, two features of ΔRHb and one feature of -ΔOHb showed statistically significant differences between AD and WT. Among ML techniques, a naive Bayes algorithm achieved the best accuracy of 84.3% when whole hemodynamic features were used for differentiation. While further works are required to improve the approach, the suggested approach has the potential to be an alternative method for the differentiation of AD and WT.

Changes in Mitochondria-Related Gene Expression upon Acupuncture at LR3 in the D-Galactosamine-Induced Liver Damage Rat Model.

Hepatic diseases, such as hepatonecrosis, hepatitis, and hepatocirrhosis, are associated with mitochondrial dysfunction and increased reactive oxygen species generation and inflammation, ultimately leading to liver failure. In this study, we examined if acupuncture at LR3 can affect mitochondria-related gene expression in a liver damage model of experimentally induced acute liver failure (ALF). ALF was induced by the intraperitoneal injection of D-galactosamine (D-GalN) in experimental rats, who then received either sham (ALF), manual acupuncture (MA), electroacupuncture (EA), or silymarin (PC, positive control) treatment. Liver tissues were extracted from experimental and untreated control rats for histopathological analysis and expression profiling of genes involved in mitochondrial function. Of the 168 mitochondria-related genes profiled, two genes belonging to the solute-carrier transporter family (Slc25a15 and Slc25a25) and Ndufb7 were upregulated. Gamma-glutamylcysteine synthetase was more downregulated in MA than ALF. Furthermore, MA reversed D-GalN-induced inflammatory cell infiltration, destruction of hepatic cell plates, and increase in the levels of the proinflammatory cytokine TNF-α. MA at LR3 can reduce the risk of D-GalN-induced ALF by inducing the expression of metabolic and inflammation-related genes and regulating proinflammatory factor production in hepatic mitochondria.

Deep Learning-Based Multilevel Classification of Alzheimer's Disease Using Non-invasive Functional Near-Infrared Spectroscopy.

The timely diagnosis of Alzheimer's disease (AD) and its prodromal stages is critically important for the patients, who manifest different neurodegenerative severity and progression risks, to take intervention and early symptomatic treatments before the brain damage is shaped. As one of the promising techniques, functional near-infrared spectroscopy (fNIRS) has been widely employed to support early-stage AD diagnosis. This study aims to validate the capability of fNIRS coupled with Deep Learning (DL) models for AD multi-class classification. First, a comprehensive experimental design, including the resting, cognitive, memory, and verbal tasks was conducted. Second, to precisely evaluate the AD progression, we thoroughly examined the change of hemodynamic responses measured in the prefrontal cortex among four subject groups and among genders. Then, we adopted a set of DL architectures on an extremely imbalanced fNIRS dataset. The results indicated that the statistical difference between subject groups did exist during memory and verbal tasks. This presented the correlation of the level of hemoglobin activation and the degree of AD severity. There was also a gender effect on the hemoglobin changes due to the functional stimulation in our study. Moreover, we demonstrated the potential of distinguished DL models, which boosted the multi-class classification performance. The highest accuracy was achieved by Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) using the original dataset of three hemoglobin types (0.909 ± 0.012 on average). Compared to conventional machine learning algorithms, DL models produced a better classification performance. These findings demonstrated the capability of DL frameworks on the imbalanced class distribution analysis and validated the great potential of fNIRS-based approaches to be further contributed to the development of AD diagnosis systems.

Changes in Cytochrome C Oxidase Redox State and Hemoglobin Concentration in Rat Brain During 810 nm Irradiation Measured by Broadband Near-Infrared Spectroscopy.

Objective: The effects of 810 nm light-emitting diode (LED) photobiomodulation (PBM) on cerebral metabolism and cerebral hemodynamic were investigated by using a broadband near-infrared spectroscopy (bb-NIRS) under anesthesia conditions with isoflurane. Background data: PBM was supposed to increase cerebral hemodynamic and cerebral metabolism. There has been no study about the effect of 810 nm LED stimulation on cerebral hemodynamic and cerebral metabolism in vivo by using bb-NIRS measurement. Methods: PBM was applied to seven Sprague-Dawley rats at 50 mW/cm2 power density. The changes in hemoglobin concentration (ΔHbO2 and ΔHHb) and oxidized cytochrome c oxidase (CCO) concentration (ΔoxCCO) were measured using a bb-NIRS. The total hemoglobin and the difference in hemoglobin concentration changes were calculated by summation and difference of ΔHbO2 and ΔHHb, respectively. Results: PBM evoked the gradual increases of ΔHbO2 (+7.7 µM vs. baseline, p = 0.008), ΔHbT (+9.5 µM vs. baseline, p = 0.0044), and ΔHbD (+5.9 µM vs. baseline, p > 0.05) during light stimulation. Meanwhile, ΔoxCCO (-3.5 µM vs. baseline, p = 0.0019) was significantly decreased right after the onset of stimulation. Conclusions: PBM with 810 nm LED (50 mW/cm2) increased cerebral oxygenation and blood volume as expected. However, oxidized CCO concentration was decreased, which was contrary to most previous studies. The two pathways of PBM effects on mitochondria and the inhibition of complex I by isoflurane were suggested to explain the decreased ΔoxCCO during PBM, but further study is required for the verification.

Novel diagnostic tools for identifying cognitive impairment using olfactory-stimulated functional near-infrared spectroscopy: patient-level, single-group, diagnostic trial.

INTRODUCTION: Basic studies suggest that olfactory dysfunction and functional near-infrared spectroscopy (fNIRS) can be used as tools for the diagnosis of mild cognitive impairment (MCI); however, real-world evidence is lacking. We investigated the potential diagnostic efficacy of olfactory-stimulated fNIRS for early detection of MCI and/or Alzheimer disease (AD). METHODS: We conducted a patient-level, single-group, diagnostic interventional trial involving elderly volunteers (age >60 years) suspected of declining cognitive function. Patients received open-label olfactory-stimulated fNIRS for measurement of oxygenation difference in the orbitofrontal cortex. All participants underwent amyloid PET, MRI, Mini-Mental State Examination (MMSE), and Seoul Neuropsychological Screening Battery (SNSB). RESULTS: Of 97 subjects, 28 (28.9%) were cognitively normal, 32 (33.0%) had preclinical AD, 21 (21.6%) had MCI, and 16 (16.5%) had AD. Olfactory-stimulated oxygenation differences in the orbitofrontal cortex were associated with cognitive impairment; the association was more pronounced with cognitive severity. Olfactory-stimulated oxygenation difference was associated with MMSE (adjusted ß [aß] 1.001; 95% CI 0.540-1.463), SNSB language and related function (aß, 1.218; 95% CI, 0.020-2.417), SNSB memory (aß, 1.963; 95% CI, 0.841-3.084), SNSB frontal/executive function (aß, 1.715; 95% CI, 0.401-3.029) scores, standard uptake value ratio from amyloid PET (aß, -10.083; 95% CI, -19.063 to -1.103), and hippocampal volume from MRI (aß, 0.002; 95% CI, 0.001-0.004). Olfactory-stimulated oxygenation difference in the orbitofrontal cortex was superior in diagnosing MCI and AD (AUC, 0.909; 95% CI, 0.848-0.971), compared to amyloid PET (AUC, 0.793; 95% CI, 0.694-0.893) or MRI (AUC, 0.758; 95% CI, 0.644-0.871). DISCUSSION: Our trial showed that olfactory-stimulated oxygenation differences in the orbitofrontal cortex detected by fNIRS were associated with cognitive impairment and cognitive-related objectives. This novel approach may be a potential diagnostic tool for patients with MCI and/or AD. TRIAL REGISTRATION: CRIS number, KCT0006197 .

Effects of transcranial ultrasound stimulation pulsed at 40 Hz on Aß plaques and brain rhythms in 5×FAD mice.

BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia, and is characterized by amyloid-ß (Aß) plaques and tauopathy. Reducing Aß has been considered a major AD treatment strategy in pharmacological and non-pharmacological approaches. Impairment of gamma oscillations, which play an important role in perception and cognitive function, has been shown in mouse AD models and human patients. Recently, the therapeutic effect of gamma entrainment in AD mouse models has been reported. Given that ultrasound is an emerging neuromodulation modality, we investigated the effect of ultrasound stimulation pulsed at gamma frequency (40 Hz) in an AD mouse model. METHODS: We implanted electroencephalogram (EEG) electrodes and a piezo-ceramic disc ultrasound transducer on the skull surface of 6-month-old 5×FAD and wild-type control mice (n = 12 and 6, respectively). Six 5×FAD mice were treated with two-hour ultrasound stimulation at 40 Hz daily for two weeks, and the other six mice received sham treatment. Soluble and insoluble Aß levels in the brain were measured by enzyme-linked immunosorbent assay. Spontaneous EEG gamma power was computed by wavelet analysis, and the brain connectivity was examined with phase-locking value and cross-frequency phase-amplitude coupling. RESULTS: We found that the total Aß42 levels, especially insoluble Aß42, in the treatment group decreased in pre- and infra-limbic cortex (PIL) compared to that of the sham treatment group. A reduction in the number of Aß plaques was also observed in the hippocampus. There was no increase in microbleeding in the transcranial ultrasound stimulation (tUS) group. In addition, the length and number of microglial processes decreased in PIL and hippocampus. Encelphalographic spontaneous gamma power was increased, and cross-frequency coupling was normalized, implying functional improvement after tUS stimulation. CONCLUSION: These results suggest that the transcranial ultrasound-based gamma-band entrainment technique can be an effective therapy for AD by reducing the Aß load and improving brain connectivity.

Development of an Integrated EEG/fNIRS Brain Function Monitoring System.

In this study, a fully integrated electroencephalogram/functional near-infrared spectroscopy (EEG/fNIRS) brain monitoring system was designed to fulfill the demand for a miniaturized, light-weight, low-power-consumption, and low-cost brain monitoring system as a potential tool with which to screen for brain diseases. The system is based on the ADS1298IPAG Analog Front-End (AFE) and can simultaneously acquire two-channel EEG signals with a sampling rate of 250 SPS and six-channel fNIRS signals with a sampling rate of 8 SPS. AFE is controlled by Teensy 3.2 and powered by a lithium polymer battery connected to two protection circuits and regulators. The acquired EEG and fNIRS signals are monitored and stored using a Graphical User Interface (GUI). The system was evaluated by implementing several tests to verify its ability to simultaneously acquire EEG and fNIRS signals. The implemented system can acquire EEG and fNIRS signals with a CMRR of -115 dB, power consumption of 0.75 mW/ch, system weight of 70.5 g, probe weight of 3.1 g, and a total cost of USD 130. The results proved that this system can be qualified as a low-cost, light-weight, low-power-consumption, and fully integrated EEG/fNIRS brain monitoring system.

Heart and Lung Sound Measurement Using an Esophageal Stethoscope with Adaptive Noise Cancellation.

In surgeries where general anesthesia is required, the auscultation of heart and lung sounds is essential to provide information on the patient's cardiorespiratory system. Heart and lung sounds can be recorded using an esophageal stethoscope; however, there is huge background noise when this device is used in an operating room. In this study, a digital esophageal stethoscope system was designed. A 3D-printed case filled with Polydimethylsiloxane material was designed to hold two electret-type microphones. One of the microphones was placed inside the printed case to collect the heart and lung sound signals coming out from the patient through the esophageal catheter, the other was mounted on the surface of the case to collect the operating room sounds. A developed adaptive noise canceling algorithm was implemented to remove the operating room noise corrupted with the main heart and lung sound signals and the output signal was displayed on software application developed especially for this study. Using the designed case, the noise level of the signal was reduced to some extent, and by adding the adaptive filter, further noise reduction was achieved. The designed system is lightweight and can provide noise-free heart and lung sound signals.

Changes of Apomorphine-Induced Vaginal Hemodynamics in an Ovariectomized Rat Model Using Near-Infrared Spectroscopic Probe.

INTRODUCTION: Female sexual arousal disorder (FSAD) can be caused by the change in vaginal structure due to the decline of estrogen and one of the main symptoms is vaginal dryness. FSAD is a prevalent problem afflicting women all over the world and thus the interest is growing on the matter, but related studies of monitoring FSAD using a non-invasive optical method barely have been carried out. AIM: This study aims to investigate the longitudinal changes in female sexual arousal response induced by apomorphine (APO) administration in the ovariectomized rat using near-infrared spectroscopy (NIRS) probe. METHODS: To elicit sexual arousal, APO was administered subcutaneously to animals (n = 6) before and after ovariectomy, and the changes in oxyhemoglobin (OHb), deoxyhemoglobin (RHb), total hemoglobin (THb) concentration, and temperature on the vaginal wall after APO administration were monitored bi-weekly for 8 weeks. Furthermore, estradiol hormone, vaginal secretion, and body weight have been measured for comparison with the results from vaginal hemodynamics. RESULTS: APO administration caused the increase of vaginal OHb and RHb concentration but a decrease in temperature. The amplitude of OHb, RHb, and THb increase induced by APO gradually decreased over 8 weeks after ovariectomy while the decrease in vaginal temperature became profound. The level of estradiol and vaginal secretions also decreased over 8 weeks after ovariectomy, but bodyweight showed an increasing trend. CONCLUSIONS: A comparison between the parameters measured from the NIRS probe and the others (estradiol level, amount of vaginal secretion, and body weight) proved that the NIRS has the potential as a monitoring tool to evaluate female sexual arousal response. Jeong H, Lee HS, Seong M, et al. Changes of Apomorphine-Induced Vaginal Hemodynamics in an Ovariectomized Rat Model Using Near-Infrared Spectroscopic Probe. J Sex Med 2021;18:1328-1336.

Rapid and non-destructive spectroscopic method for classifying beef freshness using a deep spectral network fused with myoglobin information.

A simple, novel, rapid, and non-destructive spectroscopic method that employs the deep spectral network for beef-freshness classification was developed. The deep-learning-based model classified beef freshness by learning myoglobin information and reflectance spectra over different freshness states. The reflectance spectra (480-920 nm) were measured from 78 beef samples for 17 days, and the datasets were sorted into three freshness classes based on their pH values. Myoglobin information showed statistically significant differences depending on the freshness; consequently, it was utilized as a crucial parameter for classification. The model exhibited improved performance when the reflectance spectra were combined with the myoglobin information. The accuracy of the proposed model improved to 91.9%, whereas that of the single-spectra model was 83.6%. Further, a high value for the area under the receiver operating characteristic curve (0.958) was recorded. This study provides a basis for future studies on the investigation of myoglobin information associated with meat freshness.

Wearable Transcranial Ultrasound System for Remote Stimulation of Freely Moving Animal.

OBJECTIVE: Transcranial focused ultrasound (tFUS) has drawn considerable attention in the neuroscience field as a noninvasive approach to modulate brain circuits. However, the conventional approach requires the use of anesthetized or immobilized animal models, which places considerable restrictions on behavior and affects treatment. Thus, this work presents a wireless, wearable system to achieve ultrasound brain stimulation in freely behaving animals. METHODS: The wearable tFUS system was developed based on a microcontroller and amplifier circuit. Brain activity induced by tFUS was monitored through cerebral hemodynamic changes using near-infrared spectroscopy. The system was also applied to stroke rehabilitation after temporal middle cerebral artery occlusion (tMCAO) in rats. Temperature calculations and histological results showed the safety of the application even with prolonged 40 min sonication. RESULTS: The output ultrasonic wave produced from a custom PZT transducer had a central frequency of 457 kHz and peak to peak pressure of 426 kPa. The device weight was 20 g, allowing a full range of motion. The stimulation was found to induce hemodynamic changes in the sonicated area, while open-field tests showed that ultrasound applied to the ipsilateral hemisphere for 5 consecutive days after the stroke facilitated recovery. CONCLUSION: The wearable tFUS system has been designed and implemented on moving rats. The results showed the ability of device to cause both short- and long lasting effects. SIGNIFICANCE: The proposed device provides a more natural environment to investigate the effects of tFUS for behavioral and long-term studies.