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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.

Hematopoietic stem cells (HSCs) reside in specific microenvironments that facilitate their regulation through both internal mechanisms and external cues. Bone marrow endothelial cells (BMECs), which are found in one of these microenvironments, play a vital role in controlling the self-renewal and differentiation of HSCs during hematological stress. We previously showed that 27-hydroxycholesterol (27HC) administration of exogenous 27HC negatively affected the population of HSCs and progenitor cells by increasing the reactive oxygen species levels in the bone marrow. However, the effect of 27HC on BMECs is unclear. To determine the function of 27HC in BMECs, we employed magnetic-activated cell sorting to isolate CD31+ BMECs and CD31− cells. We demonstrated the effect of 27HC on CD31+ BMECs and HSCs. Treatment with exogenous 27HC led to a decrease in the number of BMECs and reduced the expression of adhesion molecules that are crucial for maintaining HSCs. Our results demonstrate that BMECs are sensitively affected by 27HC and are crucial for HSC survival. [ABSTRACT FROM AUTHOR]

Atherosclerosis is characterized by the deposition and accumulation of extracellular cholesterol and inflammatory cells in the arterial blood vessel walls, and 27-hydroxycholesterol (27OHChol) is the most abundant cholesterol metabolite. 27OHChol is an oxysterol that induces immune responses, including immune cell activation and chemokine secretion, although the underlying mechanisms are not fully understood. In this study, we investigated the roles of the mechanistic target of rapamycin (mTOR) in 27HChol-induced inflammation using rapamycin. Treating monocytic cells with rapamycin effectively reduced the expression of CCL2 and CD14, which was involved with the increased immune response by 27OHChol. Rapamycin also suppressed the phosphorylation of S6 and 4EBP1, which are downstream of mTORC1. Additionally, it also alleviates the increase in differentiation markers into macrophage. These results suggest that 27OHChol induces inflammation by activating the mTORC1 signaling pathway, and rapamycin may be useful for the treatment of atherosclerosis-related inflammation involving 27OHchol. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Extremely large volumes of documents are available from online news platforms and social media. While the quantity of these documents have grown exponentially, the majority lack their quality, which can cause digital fatigue or promote misinformation. To this end, we propose a novel framework that can evaluate the quality of documents in terms of consistency. We model low-quality document detection as a binary classification task, which is able to measure how the documents have consistent contents. Specifically, we relax the problem by considering each sentence or paragraph as node. A given document is then considered as a network of nodes. We show how we define the supernode in a network and show how it is informative enough to detect whether the document is consistent or not. We believe this scheme can be applied to various applications including fake news detection, and document screening with qualitative evaluations. We achieve the state-of-the-art on existing tasks using the NELA17 dataset, and YH-News dataset which we release in this paper.

Diabetes mellitus (DM) is associated with increased plasma levels of arginine-vasopressin (AVP), which may aggravate hyperglycemia and nephropathy. However, the mechanisms by which DM may cause the increased AVP levels are not known. Electrophysiological recordings in supraoptic nucleus (SON) slices from streptozotocin (STZ)-induced DM rats and vehicle-treated control rats revealed that γ-aminobutyric acid (GABA) functions generally as an excitatory neurotransmitter in the AVP neurons of STZ rats, whereas it usually evokes inhibitory responses in the cells of control animals. Furthermore, Western blotting analyses of Cl- transporters in the SON tissues indicated that Na+-K+-2Cl- cotransporter isotype 1 (a Cl- importer) was upregulated and K+-Cl- cotransporter isotype 2 (KCC2; a Cl- extruder) was downregulated in STZ rats. Treatment with CLP290 (a KCC2 activator) significantly lowered blood AVP and glucose levels in STZ rats. Last, investigation that used rats expressing an AVP-enhanced green fluorescent protein fusion gene showed that AVP synthesis in AVP neurons was much more intense in STZ rats than in control rats. We conclude that altered Cl- homeostasis that makes GABA excitatory and enhanced AVP synthesis are important changes in AVP neurons that would increase AVP secretion in DM. Our data suggest that Cl- transporters in AVP neurons are potential targets of antidiabetes treatments.

Mice lacking a functional Biogenesis of Lysosome-related Organelles Complex 1 (BLOC-1), such as those of the pallid line, display cognitive and behavioural impairments reminiscent of those presented by individuals with intellectual and developmental disabilities. Although disturbances in the sleep/wake cycle are commonly lamented by these individuals, the underlying mechanisms, including the possible role of the circadian timing system, are still unknown. In this paper, we have explored sleep/circadian malfunctions and underlying mechanisms in BLOC-1-deficient pallid mice. These mutants exhibited less sleep behaviour in the beginning of the resting phase than wild-type mice with a more broken sleeping pattern in normal light-dark conditions. Furthermore, the strength of the activity rhythms in the mutants were reduced with significantly more fragmentation and lower precision than in age-matched controls. These symptoms were accompanied by an abnormal preference for the open arm in the elevated plus maze in the day and poor performance in the novel object recognition at night. At the level of the central circadian clock (the suprachiasmatic nucleus, SCN), loss of BLOC-1 caused subtle morphological changes including a larger SCN and increased expression of the relative levels of the clock gene Per2 product during the day but did not affect the neuronal activity rhythms. In the hippocampus, the pallid mice presented with anomalies in the cytoarchitecture of the Dentate Gyrus granule cells, but not in CA1 pyramidal neurones, along with altered PER2 protein levels as well as reduced pCREB/tCREB ratio during the day. Our findings suggest that lack of BLOC-1 in mice disrupts the sleep/wake cycle and performance in behavioural tests associated with specific alterations in cytoarchitecture and protein expression.

Abstract We investigated the thermographic findings of carpal tunnel syndrome (CTS). We enrolled 304 hands with electrodiagnostically identified CTS and 88 control hands. CTS hands were assigned to duration groups (D1,

Abstract Allopurinol is the first-line agent for patients with gout, including those with moderate‐to‐severe chronic kidney disease. However, increased thyroid-stimulating hormone (TSH) levels are observed in patients with long-term allopurinol treatment. This large-scale, nested case–control, retrospective observational study analysed the association between allopurinol use and increased TSH levels. A common data model based on an electronic medical record database of 19,200,973 patients from seven hospitals between January 1997 and September 2020 was used. Individuals aged > 19 years in South Korea with at least one record of a blood TSH test were included. Data of 59,307 cases with TSH levels > 4.5 mIU/L and 236,508 controls matched for sex, age (± 5), and cohort registration date (± 30 days) were analysed. An association between the risk of increased TSH and allopurinol use in participants from five hospitals was observed. A meta-analysis (I 2 = 0) showed that the OR was 1.51 (95% confidence interval: 1.32–1.72) in both the fixed and random effects models. The allopurinol intake group demonstrated that increased TSH did not significantly affect free thyroxine and thyroxine levels. After the index date, some diseases were likely to occur in patients with subclinical hypothyroidism and hypothyroidism. Allopurinol administration may induce subclinical hypothyroidism.

BackgroundRecent evidence indicates that histamine, acting on histamine 1 receptor (H1R), resets the circadian clock in the mouse suprachiasmatic nucleus (SCN) by increasing intracellular Ca(2+) concentration ([Ca(2+)]i) through the activation of CaV1.3 L-type Ca(2+) channels and Ca(2+)-induced Ca(2+) release from ryanodine receptor-mediated internal stores.ResultsIn the current study, we explored the underlying mechanisms with various techniques including Ca(2+)- and Cl(-)-imaging and extracellular single-unit recording. Our hypothesis was that histamine causes Cl(-) efflux through cystic fibrosis transmembrane conductance regulator (CFTR) to elicit membrane depolarization needed for the activation of CaV1.3 Ca(2+) channels in SCN neurons. We found that histamine elicited Cl(-) efflux and increased [Ca(2+)]i in dissociated mouse SCN cells. Both of these events were suppressed by bumetanide [Na(+)-K(+)-2Cl(-) cotransporter isotype 1 (NKCC1) blocker], CFTRinh-172 (CFTR inhibitor), gallein (Gβγ protein inhibitor) and H89 [protein kinase A (PKA) inhibitor]. By itself, H1R activation with 2-pyridylethylamine increased the level of cAMP in the SCN and this regulation was prevented by gallein. Finally, histamine-evoked phase shifts of the circadian neural activity rhythm in the mouse SCN slice were blocked by bumetanide, CFTRinh-172, gallein or H89 and were not observed in NKCC1 or CFTR KO mice.ConclusionsTaken together, these results indicate that histamine recruits the H1R-Gβγ-cAMP/PKA pathway in the SCN neurons to activate CaV1.3 channels through CFTR-mediated Cl(-) efflux and ultimately to phase-shift the circadian clock. This pathway and NKCC1 may well be potential targets for agents designed to treat problems resulting from the disturbance of the circadian system.

Recently, the need to develop a robust three-dimensional (3D) cell culture system that serves as a valuable in vitro tumor model has been emphasized. This system should closely mimic the tumor growth behaviors observed in vivo and replicate the key elements and characteristics of human tumors for the effective discovery and development of anti-tumor therapeutics. Therefore, in this study, we developed an effective 3D in vitro model of human prostate cancer (PC) using a marine collagen-based biomimetic 3D scaffold. The model displayed distinctive molecular profiles and cellular properties compared with those of the 2D PC cell culture. This was evidenced by (1) increased cell proliferation, migration, invasion, colony formation, and chemoresistance; (2) upregulated expression of crucial multidrug-resistance- and cancer-stemness-related genes; (3) heightened expression of key molecules associated with malignant progressions, such as epithelial–mesenchymal transition transcription factors, Notch, matrix metalloproteinases, and pluripotency biomarkers; (4) robust enrichment of prostate cancer stem cells (CSCs); and (5) enhanced expression of integrins. These results suggest that our 3D in vitro PC model has the potential to serve as a research platform for studying PC and prostate CSC biology, as well as for screening novel therapies targeting PC and prostate CSCs. [ABSTRACT FROM AUTHOR]

The association between leukemic stem cells (LSCs) and leukemia development has been widely established in the context of genetic alterations, epigenetic pathways, and signaling pathway regulation. Hematopoietic stem cells are at the top of the bone marrow hierarchy and can self-renew and progressively generate blood and immune cells. The microenvironment, niche cells, and complex signaling pathways that regulate them acquire genetic mutations and epigenetic alterations due to aging, a chronic inflammatory environment, stress, and cancer, resulting in hematopoietic stem cell dysregulation and the production of abnormal blood and immune cells, leading to hematological malignancies and blood cancer. Cells that acquire these mutations grow at a faster rate than other cells and induce clone expansion. Excessive growth leads to the development of blood cancers. Standard therapy targets blast cells, which proliferate rapidly; however, LSCs that can induce disease recurrence remain after treatment, leading to recurrence and poor prognosis. To overcome these limitations, researchers have focused on the characteristics and signaling systems of LSCs and therapies that target them to block LSCs. This review aims to provide a comprehensive understanding of the types of hematopoietic malignancies, the characteristics of leukemic stem cells that cause them, the mechanisms by which these cells acquire chemotherapy resistance, and the therapies targeting these mechanisms. [ABSTRACT FROM AUTHOR]

BackgroundIncreased secretion of oxytocin and arginine vasopressin (AVP) from hypothalamic magnocellular neurosecretory cells (MNCs) is a key physiological response to lactation. In the current study, we sought to test the hypothesis that the GABAA receptor-mediated inhibition of MNCs is altered in lactating rats.ResultsGramicidin-perforated recordings in the rat supraoptic nucleus (SON) slices revealed that the reversal potential of GABAA receptor-mediated response (EGABA) of MNCs was significantly depolarized in the lactating rats as compared to virgin animals. The depolarizing EGABA shift was much larger in rats in third, than first, lactation such that GABA exerted an excitatory, instead of inhibitory, effect in most of the MNCs of these multiparous rats. Immunohistochemical analyses confirmed that GABAergic excitation was found in both AVP and oxytocin neurons within the MNC population. Pharmacological experiments indicated that the up-regulation of the Cl(-) importer Na(+)-K(+)-2Cl(-) cotransporter isotype 1 and the down-regulation of the Cl(-) extruder K(+)-Cl(-) cotransporter isotype 2 were responsible for the depolarizing shift of EGABA and the resultant emergence of GABAergic excitation in the MNCs of the multiparous rats.ConclusionWe conclude that, in primiparous rats, the GABAergic inhibition of MNCs is weakened during the period of lactation while, in multiparous females, GABA becomes excitatory in a majority of the cells. This reproductive experience-dependent alteration of GABAergic transmission may help to increase the secretion of oxytocin and AVP during the period of lactation.

Objectives Adolescent suicide is a global problem. This study aimed to identify associations between parental marital status and suicidal behavior. Methods This study analyzed 118 715 middle and high school students from the 13th and 14th Korea Youth Risk Behavior Web-based Survey. The odds ratios (ORs) of suicidal ideation, planning, and attempts were calculated based on parental marital status, living situation, and socioeconomic factors. The data were analyzed using multiple logistic regression. Results When compared to those living with 2 married biological parents, the ORs of suicidal ideation among adolescents living with either remarried or no parents were 1.34 (95% confidence interval [CI], 1.17 to 1.53) and 1.36 (95% CI, 1.11 to 1.66), respectively. For suicidal planning, the OR of those living with 1 remarried biological parent was 1.24 (95% CI, 1.01 to 1.52), and that of those living without parents was 1.28 (95% CI, 0.95 to 1.73), when compared to adolescents living with 2 married biological parents. For suicide attempts, when compared to adolescents with 2 married biological parents, the OR of those living with 1 remarried biological parent was 1.48 (95% CI, 1.17 to 1.87) and that of those living without parents was 2.02 (95% CI, 1.44 to 2.83). For adolescents living with 1 remarried biological parent, suicidal behavior was strongly associated with having no siblings and were weakly associated with not living with grandparents. Conclusions Suicidal behavior among adolescents was associated with the remarriage and loss of parents. Therefore, special attention and interventions are needed for adolescents in those situations.

The structural programmability and functionality of peptide materials can be leverage for various next-generation devices such as non-volatile memories. The authors report a proton-coupled mechanism in tyrosine-rich peptides for realizing multimodal memory devices.

This study reviewed the quality addition rate, calculation, and application criteria needed to identify the possibility of additional medical technologists in the field for new certification and professional manpower to provide a superior laboratory. The six institutions that participated in the study were the size of large hospitals with more than 1,000 beds, with an average of five full-time laboratory physicians (also called clinical pathologists) and an average of 53 medical technologists, with 10.6 per laboratory physician. An analysis of the time required for each activity category of medical technologists revealed decreasing behavior during the analysis. In contrast, the ratio of the com-prehensive pre-analysis activities was high due to the strengthening of laboratory operations and quality control. During the analysis, the proportion of biochemistry tests was high, and post-analysis of most of the results was performed. Hence, improving the quality of sample testing requires significant time, and appropriate personnel are required. In conclusion, the recruitment of medical technologists is also a key component to improving the sample quality, and corresponding personnel regulations are necessary.

This study examines and presents reasonable improvement measures for the operation and revision of the relative value scoring system, and the basis for performance of a medical technologist. Seven hospitals were enrolled in the study, and included 5 resident laboratory medicine specialists and 53 medical technologists, giving a ratio of 10.6 technologists per laboratory medicine specialist. The average of professional manpower scores was 18, and the average of each medical institution's total score was 78. Ratings and additional rates were in the range 2∼3%, and quality-added ratios were 2∼3%, with no significance. Excluding pathological testing and assessing physiological functions, the average number of diagnostic tests for health insurance claims were 9,618,062, including 4,378,146 points for 5% of the total relative value scores. According to the DEA, the appropriate number of medical technologist is one person per 49,974 points of relative value. In conclusion, our study results indicate that it would be desirable to set the appropriate workforce for medical technologist to one person per 50,000 points of relative value. Our data could be used as a basis for enhancing productivity of the workforce and balancing health care resources.

With the increase of rich datasets from various online platforms, predicting user behavior has been one of the most active research topics. The user behavior on these online platforms includes listening to music, watching videos, purchasing products, checking-in to places, and joining online sub-communities. Predicting online user behavior is an important challenge for various applications. Personalization, recommendation systems, target advertisements are based on user behavior prediction, where user's next purchases or actions need to be predicted. In this paper, we propose a hybrid generative model that can predict user behavior considering multiple factors. While previous work has been focused on two aspects individually: predicting repeat behavior or predicting new behavior, our model considers both aspects simultaneously during the learning process. The user-specific preference component is used to capture repeat behavior patterns, while the latent group preference component is used to discover new behavior. Besides these two components, we also consider the exogenous effect, which is not captured in the former two. Our experimental results on real-world datasets show how our proposed model outperforms the state-of-the-art model.