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Abstract Electrical conductivity is a pivotal biophysical factor for neural interfaces, though optimal values remain controversial due to challenges isolating this cue. To address this issue, conductive substrates made of carbon nanotubes and graphene oxide nanoribbons, exhibiting a spectrum of conductivities from 0.02 to 3.2 S m−1, while controlling other surface properties is designed. The focus is to ascertain whether varying conductivity in isolation has any discernable impact on neural lineage specification. Remarkably, neural‐tissue‐like low conductivity (0.02–0.1 S m−1) prompted neural stem/progenitor cells to exhibit a greater propensity toward neuronal lineage specification (neurons and oligodendrocytes, not astrocytes) compared to high supraphysiological conductivity (3.2 S m−1). High conductivity instigated the apoptotic process, characterized by increased apoptotic fraction and decreased neurogenic morphological features, primarily due to calcium overload. Conversely, cells exposed to physiological conductivity displayed epigenetic changes, specifically increased chromatin openness with H3acetylation (H3ac) and neurogenic‐transcription‐factor activation, along with a more balanced intracellular calcium response. The pharmacological inhibition of H3ac further supported the idea that such epigenetic changes might play a key role in driving neuronal specification in response to neural‐tissue‐like, not supraphysiological, conductive cues. These findings underscore the necessity of optimal conductivity when designing neural interfaces and scaffolds to stimulate neuronal differentiation and facilitate the repair process.

In mammals, photic information delivered to the suprachiasmatic nucleus (SCN) via the retinohypothalamic tract (RHT) plays a crucial role in synchronizing the master circadian clock located in the SCN to the solar cycle. It is well known that glutamate released from the RHT terminals initiates the synchronizing process by activating ionotropic glutamate receptors (iGluRs) on retinorecipient SCN neurons. The potential role of metabotropic glutamate receptors (mGluRs) in modulating this signaling pathway has received less attention. In this study, using extracellular single-unit recordings in mouse SCN slices, we investigated the possible roles of the Gq/11 protein-coupled mGluRs, mGluR1 and mGluR5, in photic resetting. We found that mGluR1 activation in the early night produced phase advances in neural activity rhythms in the SCN, while activation in the late night produced phase delays. In contrast, mGluR5 activation had no significant effect on the phase of these rhythms. Interestingly, mGluR1 activation antagonized phase shifts induced by glutamate through a mechanism that was dependent upon CaV1.3 L-type voltage-gated Ca2+ channels (VGCCs). While both mGluR1-evoked phase delays and advances were inhibited by knockout (KO) of CaV1.3 L-type VGCCs, different signaling pathways appeared to be involved in mediating these effects, with mGluR1 working via protein kinase G in the early night and via protein kinase A signaling in the late night. We conclude that, in the mouse SCN, mGluR1s function to negatively modulate glutamate-evoked phase shifts.

Background : : Parkinson’s disease (PD) lacks disease-modifying drugs or sustainable interventions, creating an unmet treatment need. Investigating complementary and alternative medicines aims to improve PD patients’ quality of life by alleviating symptoms and delaying the course of the disease.Objectives: In this single-center, prospective, observational, single-arm study, we aimed to assess the effectiveness and safety of acupuncture combined with exercise therapy and the Meridian Activation Remedy System (MARS).Methods : : From March to October 2021, 13 PD patients with Hoehn and Yahr stages 1 to 3 were recruited. For 8 weeks, MARS intervention was carried out twice a week. T-statistics were used to evaluate functional near-infrared spectroscopy (fNIRS) and GAITRite outcomes. All of the remaining outcome variables were evaluated using the Wilcoxon signed-rank test.Results : : The MARS intervention significantly reduced PD patients’ Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale (MDSUPDRS) Part III score (from 20.0 ± 11.8 to 8.8 ± 5.5, p = 0.003), 10-meter walk test speed (from 9.5 ± 1.8 to 8.7 ± 1.3 seconds, p = 0.040), and timed up and go time (from 9.8 ± 1.8 to 8.9 ± 1.4 seconds, p = 0.040). Moreover, the MDS-UPDRS Part II, fNIRS hemodynamics, 360-degree turn test, fall efficacy scale, and Parkinson’s Disease Questionnaire 39 scores improved but not significantly. All participants completed the 8-week intervention without any adverse reactions.Conclusion : : An 8-week MARS intervention improved motor symptoms in PD patients. In particular, improvements in UPDRS Part III scores exhibited large clinically important differences. The findings are encouraging, and a randomized controlled trial will be conducted to determine the efficacy and cost-effectiveness of MARS intervention.

This study examined the transition process of clinical laboratory technologists’ national examination and job definition in Korea and compared the differences in the national examination between Korea and neighboring countries, such as Japan and Taiwan. In Korea, the number of questions made for it was 200 (1965), 200 (1977), 300 (1982), 250 (1992), 330 (2006), and 280 (2015). The practice of clinical physiology is important for real-time monitoring, given the characteristics of physiological testing. On the other hand, there are conflicts between other occupations in the working area. Clinical molecular biology needs to be established as a new major subject considering the diagnostic importance of molecular biological tests and the speed of science and technology development. Clinical laboratory operations provide policy and guidance recommendations to technologist staff. The proposed clinical laboratory technologists’ national examination comprises major subjects: clinical biochemistry, clinical hematology, clinical transfusionology, clinical immunology, clinical microbiology, clinical molecular biology, clinical histology, clinical cytology, clinical physiology, and clinical laboratory operations. In addition, this study proposes the job definition of clinical laboratory technologists, revising various chemical or physiological testing to biomedical or physiological testing required for medical practice.

AimsAbundant evidence indicates that oestrogen (E2) plays a protective role against hypertension. Yet, the mechanism underlying the antihypertensive effect of E2 is poorly understood. In this study, we sought to determine the mechanism through which E2 inhibits salt-dependent hypertension.Methods and resultsTo this end, we performed a series of in vivo and in vitro experiments employing a rat model of hypertension that is produced by deoxycorticosterone acetate (DOCA)-salt treatment after uninephrectomy. We found that E2 prevented DOCA-salt treatment from inducing hypertension, raising plasma arginine-vasopressin (AVP) level, enhancing the depressor effect of the V1a receptor antagonist (Phenylac1,D-Tyr(Et)2,Lys6,Arg8,des-Gly9)-vasopressin, and converting GABAergic inhibition to excitation in hypothalamic magnocellular AVP neurons. Moreover, we obtained results indicating that the E2 modulation of the activity and/or expression of NKCC1 (Cl- importer) and KCC2 (Cl- extruder) underpins the effect of E2 on the transition of GABAergic transmission in AVP neurons. Lastly, we discovered that, in DOCA-salt-treated hypertensive ovariectomized rats, CLP290 (prodrug of the KCC2 activator CLP257, intraperitoneal injections) lowered blood pressure, and plasma AVP level and hyperpolarized GABA equilibrium potential to prevent GABAergic excitation from emerging in the AVP neurons of these animals.ConclusionBased on these results, we conclude that E2 inhibits salt-dependent hypertension by suppressing GABAergic excitation to decrease the hormonal output of AVP neurons.

Air compressors are widely used in industrial fields. Compressed air systems aggregate air flows and then supply them to places of demand. These huge systems consume a significant amount of energy and generate heat internally. Machine components in compressed air systems are vulnerable to heat, and, in particular, a radiator to cool the heat of the overall air compressor is the core component. Dirty radiators increase energy consumption due to anomalous cooling. To reduce the energy consumption of air compressors, this mechanism emphasizes a machine learning-based radiator fault detection, using features such as RPM, motor power, outlet pressure, air flow, water pump power, and outlet temperature with slight true fault labels. Moreover, the proposed system adds an LSTM-based motor power prediction model to point out the initial judgment of radiator fault possibility. Via the rigorous analysis and the comparison among machine learning models, this meticulous approach improves the performance of radiator fault prediction up to 93.0%, and decreases the mean power consumption of the air compressor around 2.24%.

Nighttime light pollution is linked to metabolic and cognitive dysfunction. Many patients with autism spectrum disorders (ASD) show disturbances in their sleep/wake cycle, and may be particularly vulnerable to the impact of circadian disruptors. In this study, we examined the impact of exposure to dim light at night (DLaN, 5 lx) in a model of ASD: the contactin associated protein-like 2 knock out (Cntnap2 KO) mice. DLaN was sufficient to disrupt locomotor activity rhythms, exacerbate the excessive grooming and diminish the social preference in Cntnap2 mutant mice. On a molecular level, DLaN altered the phase and amplitude of PER2:LUC rhythms in a tissue-specific manner in vitro. Daily treatment with melatonin reduced the excessive grooming of the mutant mice to wild-type levels and improved activity rhythms. Our findings suggest that common circadian disruptors such as light at night should be considered in the management of ASD.

Nighttime light pollution is linked to metabolic and cognitive dysfunction. Many patients with autism spectrum disorders (ASD) show disturbances in their sleep/wake cycle, and may be particularly vulnerable to the impact of circadian disruptors. In this study, we examined the impact of exposure to dim light at night (DLaN, 5 lx) in a model of ASD: the contactin associated protein-like 2 knock out (Cntnap2 KO) mice. DLaN was sufficient to disrupt locomotor activity rhythms, exacerbate the excessive grooming and diminish the social preference in Cntnap2 mutant mice. On a molecular level, DLaN altered the phase and amplitude of PER2:LUC rhythms in a tissue-specific manner in vitro. Daily treatment with melatonin reduced the excessive grooming of the mutant mice to wild-type levels and improved activity rhythms. Our findings suggest that common circadian disruptors such as light at night should be considered in the management of ASD.

One of the main challenges in recommendation system is the item cold-start problem, where absence of historical interactions or ratings in new items makes recommendation difficult. In order to solve the cold-start problem, hybrid neural network models using meta data of the item as a feature is widely used. However, existing cold-start models tend to focus too much on utilizing the side information of items, which may not be flexible enough to capture the interaction information of users. In this study, we propose a flexible framework for better capturing the interaction information of users. Specifically, we incorporate the multiple choice learning scheme into the two-tower neural network which is a popular recommendation model that consists of two towers - one for users and one for items. In our proposed framework, we construct two encoders. One of the two encoders, the tightly-coupled encoder, focuses on the side information of items with which the user has interacted, the other one, loosely-coupled encoder, focuses the user’s interaction information. We utilize Gumbel-Softmax to stochastically select the encoder, enhancing the flexibility that considers not only item feature but also user interaction information. We evaluate our proposed framework on two datasets - the MLIMDb dataset which is a combination of widely used the MovieLens and IMDb datasets based on common movies, and the CiteULike dataset. The experimental results show that our proposed framework achieves state-of-the-art results on cold-start recommendation. In the Recall@150 experiments on the CiteULike dataset, we achieved improvement of approximately 2.7% compared to the base model. In the Recall@150 experiments on the MLIMDb dataset, we achieved improvement of approximately 5.2% compared to the base model. We further show our proposed model improves the performance in the warm-start settings. In the Recall@100 experiments on the Citeulike dataset, we observed an improvement of approximately 1.3% compared to the base model. In the Recall@100 experiments on the MLIMDb dataset, we observed an improvement of approximately 3.9% compared to the base model. Our proposed framework provides a flexible approach for capturing the diverse aspects of users in recommendation systems, even for cold-start items. As demonstrated through extensive experiments, our proposed model outperforms several State-Of-The-Art (SOTA) models on both datasets.

Fake news can be easily propagated through social media and cause negative societal effects. Since fake news is disinformation with malicious intent, manual fact-checking requires great effort. In order to cope with these challenges, many automatic fake news detection models have been introduced. Recent studies have shown that social network information along with news content can be used effectively for detecting fake news. In this paper, we propose a Topological and Sequential Neural Network model (TSNN) for detecting fake news by capturing the diffusion patterns between source news and users in social networks. We employ the supernode approach instead of simple graph pooling methods to extract representative features in graph topological structure. To better learn the representations in the supernode, we design two-staged graph neural networks reflecting the heterogeneity between news and Twitter users. Our model additionally captures sequential information on news diffusion path by using a transformer. We evaluate our model with two fake news benchmark datasets annotated by fact-checking websites: PolitiFact and GossipCop. TSNN achieves 92.15% accuracy and 92.11% F1-score on PolitiFact, and 97.91% accuracy and 97.88% F1-score on GossipCop. These results demonstrate that our model significantly outperforms other baselines, establishing it as a state-of-the-art solution for fake news detection. To verify the effectiveness following model configuration, we perform ablation studies to demonstrate how each component among our two-stage graph neural networks, and sequential information modules contribute to the performance improvements.

Emotion recognition in conversation is the task of recognizing the emotion in each utterance of a conversation, and it is an active field of study with various applications. Many studies have been conducted in well-designed settings in which all of the emotion labels in the training set are available. However, a rich dataset with emotion labels for all utterances is rare. In this study, we address this problem by resorting to few-shot learning. Specifically, we propose Directed Acyclic Graph (DAG)-based prototypical networks, namely ProtoDAG, to better capture contextual information in conversations, which in turn leads to accurate emotion predictions. In our model, the DAG layers are tailored into prototypical networks, which is learned end-to-end. Our experiments with popular benchmark datasets demonstrate that our model achieves state-of-the-art results outperforming the existing few-shot learning model by a significant margin and is even competitive with fully supervised baseline models for emotion recognition in conversation.

Abstract Background Digital infrared thermal imaging (DITI), which detects infrared rays emitted from body surface to create a body heat map, has been utilized at various musculocutaneous conditions. Notably, DITI can demonstrate autonomic vasomotor activity in the nerve-innervated area, and thus may be of use in carpal tunnel syndrome (CTS). In this study, we compared DITI findings before and after carpal tunnel release (CTR) surgery in patients with unilateral CTS to investigate the corresponding neurophysiological changes. Methods In this retrospective cohort study, DITI parameters such as the temperature differences between the median and ulnar nerve territories and median nerve-innervated digital anisometry were measured. Subjective symptom duration, pain scale, and ultrasonographic findings were also compared before and after CTR. Patients were evaluated before and 6 weeks after CTR, respectively. Results A total of 27 patients aged 59.0 ± 11.2 years were finally included. After CTR, median nerve-innervated thermal anisometry was improved (2.55 ± 0.96 °C to 1.64 ± 1.34 °C; p = 0.003). The temperature differences between the median and ulnar nerve territories were not significantly changed. Subjective pain, the Simovic Weinberg Clinical Scale, and palmar bowing of the flexor retinaculum were also significantly improved (p

Abstract Soil corrosion is always a critical concern to corrosion engineering because of the economic influence of soil infrastructures as has been and has recently been the focus of spent nuclear fuel canisters. Besides corrosion protection, the corrosion prediction of the canister is also important. Advanced knowledge of the corrosion rate of spent nuclear fuel canister material in a particular environment can be extremely helpful in choosing the best protection method. Applying machine learning (ML) to corrosion rate prediction solves all the challenges because of the number of variables affecting soil corrosion. In this study, several algorithms of ML, including series individual, boosting, bagging artificial neural network (ANN), series individual, boosting, bagging Chi-squared automatic interaction detection (CHAID) tree decision, linear regression (LR) and an ensemble learning (EL) merge the best option that collects from 3 algorithm methods above. From the performance of each model to find the model with the highest accuracy is the ensemble stacking method. Mean absolute error performance matrices are shown in Fig. 15. Besides applying ML, the significance of the input variables was also determined through sensitivity analysis using the feature importance criterion, and the carbon steel corrosion rate is the most sensitive to temperature and chloride.

Abstract Background The application of telemedicine and electronic health (eHealth) technology has grown in importance during the COVID-19 pandemic, and a new approach in personal data management and processing MyData, has emerged. Data portability and informational self-determination are fundamental concepts of MyData. This study analysed the factors that influence acceptance of the MyData platform, which, reflects the right to self-determine personal data. Methods The study involved participants having experience using the MyData platform, and the key factors of the unified theory of acceptance and use of technology were used in the research model (performance expectancy, effort expectancy, social influence, facilitation condition and behavioural intention to use). The questionnaire comprided 27 items, and system usage log data were used to confirm that behavioural intention to use affected actual use behaviour through structural equation modeling. Results In total, 1153 participants completed the survey. The goodness of fit in the structural equation model indices indicates that the data fit the research model well. Performance expectancy, social influence, and facilitating conditions had direct effects on behavioural intention to use. We used system usage log data to confirm that behavioural intention to use positively affected actual use behaviour. The impact of the main factors in the unified theory of acceptance and use of technology was not moderated by age or gender, except for performance expectancy. Conclusions This study is the first to examine the factors influencing the use of the MyData platform based on the personal health record data sharing system in Korea. In addition, the study confirmed the use behaviour of the MyData platform utilising the system’s actual usage log for each function and analysing the effect of the intention of use on actual use. Our study serves as a significant foundation for the acceptance of data portability and sharing concepts. It also lays the foundation for expanding the data economy and ecosystem in the pandemic era.

In mammals, photic information delivered to the suprachiasmatic nucleus (SCN) via the retinohypothalamic tract (RHT) plays a crucial role in synchronizing the master circadian clock located in the SCN to the solar cycle. It is well known that glutamate released from the RHT terminals initiates the synchronizing process by activating ionotropic glutamate receptors (iGluRs) on retinorecipient SCN neurons. The potential role of metabotropic glutamate receptors (mGluRs) in modulating this signaling pathway has received less attention. In this study, using extracellular single-unit recordings in mouse SCN slices, we investigated the possible roles of the Gq/11 protein-coupled mGluRs, mGluR1 and mGluR5, in photic resetting. We found that mGluR1 activation in the early night produced phase advances in neural activity rhythms in the SCN, while activation in the late night produced phase delays. In contrast, mGluR5 activation had no significant effect on the phase of these rhythms. Interestingly, mGluR1 activation antagonized phase shifts induced by glutamate through a mechanism that was dependent upon CaV1.3 L-type voltage-gated Ca2+ channels (VGCCs). While both mGluR1-evoked phase delays and advances were inhibited by knockout (KO) of CaV1.3 L-type VGCCs, different signaling pathways appeared to be involved in mediating these effects, with mGluR1 working via protein kinase G in the early night and via protein kinase A signaling in the late night. We conclude that, in the mouse SCN, mGluR1s function to negatively modulate glutamate-evoked phase shifts.

This study attempted to provide the basic data for developing a system to identify the role of medical technologists and ensure an efficient response for quick and accurate diagnostic tests in the COVID-19 era. The research method involved using focus group interviews for a survey and analysis of 15 medical institutions. Eleven sample collection institutions, 10.4 medical technologists, 2.1 minutes of collection time, 5.4 hours of test time, 9,670 tests, 6.2 member test workforce size, and 7 screening center operating institutions were surveyed. The results of the focus group interview analysis revealed that there were no standardized guidelines covering working hours, area, and environment to protect sample collectors and testers in relation to the COVID-19 tests. Also, legal protection measures were insufficient in the event of accidental infections and there were no personnel regulations related to COVID-19. In addition, the professional training of sample collectors and molecular diagnostic testers was required for reliable COVID-19 testing. In conclusion, it is necessary to provide professional education through special test short-term training institutions to cope with emergency infectious diseases such as COVID-19. Legal systems should be put in place to protect the workforce and ensure stability.

Although a diversity of religions exists in South Korea, with Buddhism and Christianity (Protestantism and Catholicism) being the two main faiths, Korean beliefs are deeply rooted in Confucianism. Despite the notion that the Confucian norm of filial piety discourages body donation to medical science, there has been a mindset shift in favor of body donation, driven by a heightened awareness of the body bequest programs and the care and dignity accorded to the altruistic body donors, together with the institution of commemorative services to honor them. As spirituality and religion are known to be factors that influence body donation, how religious‐ and non‐religious‐based memorial services are held to honor the donors as exemplified by two Korean medical schools—from a public university with no religious affiliation and from a Protestant‐based university—are described here. The key concept of expressing gratitude and respect for the donors and their family members has positively impacted body bequest programs in this multi‐religious society. Commemorative services held to pay tribute to the altruistic body donors may play an important role in inspiring a humanistic spirit in students, regardless of religious or non‐religious beliefs, as exemplified by the two Korean medical schools. The takeaway here is that the elevation of spirituality in memorial services effectively resonates with society, thereby demonstrating the impact of spiritual principles independent of religious influence. [ABSTRACT FROM AUTHOR]