Influence of partition layouts on speech privacy in open-plan offices.

Different partition layouts were compared to determine how to increase speech privacy while maintaining communication efficiency between workers in an open-plan office. A preliminary survey was used to determine current usage and conditions of partitions in open-plan offices. The survey results were used to select four partition layouts for testing: face-to-face, parallel, crossed-rod, and orthogonal. A computer modeling was used to test the partition layouts at three different partition heights: 1.2, 1.5, and 1.8 m. The modeling results showed that the parallel- and crossed-rod-type layouts offered the best speech privacy at the lowest partition height, but the differences among layouts disappeared as the partition height was increased. Furthermore, an acoustic field experiment was performed using partitions with a 1.5 m height following the ISO 3382-3 standard. The experimental results showed that the face-to-face layout resulted in the least speech privacy. Based on these results, an open-plan office needs to ensure that workers are spaced a sufficient distance apart and that they do not face each other to ensure speech privacy. Additionally, speech privacy should be considered in the design stage of the office space.

A Bedside Electronic Whiteboard System for Patient Care in Isolation Rooms: A Scenario-Based Preliminary Study.

AIM: To assess a commercially available electronic whiteboard's usability and acceptability in isolation rooms, focusing on improving nurse-patient communication and supporting data input. DESIGN: A cross-sectional study with quantitative and qualitative mixed methods. METHODS: We evaluated the usability and acceptability of electronic whiteboards among nurses using scenarios in a virtual isolation room environment. RESULTS: Nurses recognised the electronic whiteboard as a valuable tool for communication and error reductions in record-keeping but noted a learning curve for less tech-savvy users. Positive correlations were found between perceived usefulness, ease of use and adoption intent. Despite challenges, electronic whiteboards show promise for enhancing patient care, requiring comprehensive training and management systems. Time allocation in patient wards and nurse-patient interactions are crucial considerations. CONCLUSION: Electronic whiteboards have usability and acceptability as a tool to improve nurse-patient communication. However, considering technical issues and staff resistance, a management system and user training are necessary. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Nurses perceive electronic whiteboards as user-friendly and as facilitating data input. REPORTING METHOD: TREND (Nonrandomised evaluations of behavioural and public health interventions). PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Clonal hematopoiesis with DNMT3A mutations is associated with multiple system atrophy.

BACKGROUND: Clonal hematopoiesis of indeterminate potential (CHIP) is associated with cardiovascular diseases and other disorders, possibly via inflammation. Recent research suggests a connection of CHIP with neurodegenerative disorders. OBJECTIVE: We aimed to investigate the association between multiple system atrophy (MSA) and CHIP. METHODS: We included 100 patients with MSA and 4457 controls. Targeted sequencing of peripheral blood DNA samples was performed, focusing on a panel of 25 genes commonly. LINKED TO CHIP: The prevalence of CHIP in patients with MSA was assessed against controls at variant allele frequency (VAF) thresholds of 1.5 % and 2.0 %. RESULTS: DNMT3A mutation rates were significantly higher in patients with MSA, with a VAF of 1.5 %, which remained significant after adjusting for age and sex (adjusted odds ratio, 1.848; 95 % CI, 1.024-3.335; p = 0.0416). CONCLUSION: Our results suggest an association between DNMT3A mutations and MSA.

Real-Time Tunable Gas Sensing Platform Based on SnO2 Nanoparticles Activated by Blue Micro-Light-Emitting Diodes.

Micro-light-emitting diodes (µLEDs) have gained significant interest as an activation source for gas sensors owing to their advantages, including room temperature operation and low power consumption. However, despite these benefits, challenges still exist such as a limited range of detectable gases and slow response. In this study, we present a blue µLED-integrated light-activated gas sensor array based on SnO2 nanoparticles (NPs) that exhibit excellent sensitivity, tunable selectivity, and rapid detection with micro-watt level power consumption. The optimal power for µLED is observed at the highest gas response, supported by finite-difference time-domain simulation. Additionally, we first report the visible light-activated selective detection of reducing gases using noble metal-decorated SnO2 NPs. The noble metals induce catalytic interaction with reducing gases, clearly distinguishing NH3, H2, and C2H5OH. Real-time gas monitoring based on a fully hardware-implemented light-activated sensing array was demonstrated, opening up new avenues for advancements in light-activated electronic nose technologies.

Highly Efficient Wide Bandgap Perovskite Solar Cells With Tunneling Junction by Self-Assembled 2D Dielectric Layer.

Reducing non-radiative recombination and addressing band alignment mismatches at interfaces remain major challenges in achieving high-performance wide-bandgap perovskite solar cells. This study proposes the self-organization of a thin two-dimensional (2D) perovskite BA2PbBr4 layer beneath a wide-bandgap three-dimensional (3D) perovskite Cs0.17FA0.83Pb(I0.6Br0.4)3, forming a 2D/3D bilayer structure on a tin oxide (SnO2) layer. This process is driven by interactions between the oxygen vacancies on the SnO2 surface and hydrogen atoms of the n-butylammonium cation, aiding the self-assembly of the BA2PbBr4 2D layer. The 2D perovskite acts as a tunneling layer between SnO2 and the 3D perovskite, neutralizing the energy level mismatch and reducing non-radiative recombination. This results in high power conversion efficiencies of 21.54% and 19.16% for wide-bandgap perovskite solar cells with bandgaps of 1.7 and 1.8 eV, with open-circuit voltages over 1.3 V under 1-Sun illumination. Furthermore, an impressive efficiency of over 43% is achieved under indoor conditions, specifically under 200 lux white light-emitting diode light, yielding an output voltage exceeding 1 V. The device also demonstrates enhanced stability, lasting up to 1,200 hours.

Multiclassification of the symptom severity of social anxiety disorder using digital phenotypes and feature representation learning.

Objective: Social anxiety disorder (SAD) is characterized by heightened sensitivity to social interactions or settings, which disrupts daily activities and social relationships. This study aimed to explore the feasibility of utilizing digital phenotypes for predicting the severity of these symptoms and to elucidate how the main predictive digital phenotypes differed depending on the symptom severity. Method: We collected 511 behavioral and physiological data over 7 to 13 weeks from 27 SAD and 31 healthy individuals using smartphones and smartbands, from which we extracted 76 digital phenotype features. To reduce data dimensionality, we employed an autoencoder, an unsupervised machine learning model that transformed these features into low-dimensional latent representations. Symptom severity was assessed with three social anxiety-specific and nine additional psychological scales. For each symptom, we developed individual classifiers to predict the severity and applied integrated gradients to identify critical predictive features. Results: Classifiers targeting social anxiety symptoms outperformed baseline accuracy, achieving mean accuracy and F1 scores of 87% (with both metrics in the range 84-90%). For secondary psychological symptoms, classifiers demonstrated mean accuracy and F1 scores of 85%. Application of integrated gradients revealed key digital phenotypes with substantial influence on the predictive models, differentiated by symptom types and levels of severity. Conclusions: Leveraging digital phenotypes through feature representation learning could effectively classify symptom severities in SAD. It identifies distinct digital phenotypes associated with the cognitive, emotional, and behavioral dimensions of SAD, thereby advancing the understanding of SAD. These findings underscore the potential utility of digital phenotypes in informing clinical management.

A survey on the real-world clinical utilization of a traditional acupuncture in Republic of Korea: Sa-am acupuncture.

OBJECTIVE: This study investigated the clinical details and usage of Sa-am acupuncture in Korean medicine clinics and explored how practicing Korean medicine doctors (KMDs) think about Sa-am acupuncture. METHODS: We conducted a questionnaire-based survey of KMDs who utilize Sa-am acupuncture in their practice. The study comprehensively investigated issues related to clinical application of Sa-am acupuncture, needling techniques used during treatment, training methods, and directions for its future improvement. RESULTS: We analyzed 572 responses. An average of 50% of the patients visiting Korean medicine clinics were receiving Sa-am acupuncture. The most prevalent indication for Sa-am acupuncture use was digestive disorders. The patients' appetite level and digestive function were most frequently used indicators for selecting acupuncture points. Regarding prescription compositions, Jung-Gyuk formulas were more frequently used than Seung-Gyuk formulas. Inserting the needle along the flow of the channel or against the flow of the channel was most popular. The acupuncture style most frequently used in combination with Sa-am acupuncture was Ashi point acupuncture. Strengths of Sa-am acupuncture included its versatility, easy application, and good outcomes. Limitations included the lack of rigorous education and training programs, difficulty in applying the principles for beginners, and insufficient clinical research evidence. CONCLUSION: In clinics where Sa-am acupuncture is available, KMDs were providing Sa-am acupuncture to about half of their patients. Practitioners were not using all of the tonification and sedation techniques which may be due to time constraints or simply a lack of necessity. Sa-am acupuncture demonstrated high utility in clinical practice and high satisfaction based on the efficacy and safety. More training programs and high-quality research are needed to help expand the use of Sa-am acupuncture. Please cite this article as: Park JY, Lee YS, Park HJ, Lee SK, Lee JW, Kim SY. A survey on the real-world clinical utilization of a traditional acupuncture in Republic of Korea: Sa-am acupuncture. J Integr Med. 2024; Epub ahead of print.

Using Directed Acyclic Graphs (DAGs) to Determine if the Total Causal Effect of an Individual Randomized Physical Activity-Promoting Intervention is Identifiable.

Physical activity promotion is a best buy for public health because it has the potential to help individuals feel better, sleep better, and perform daily tasks more easily, in addition to providing disease prevention benefits. There is strong evidence that individual-level theory-based behavioral interventions are effective for increasing physical activity levels in adult populations but causal inference from these interventions often is unclearly articulated. A directed acyclic graph (DAG) can be, but rarely is, used to determine if the causal effect of an individual-level theory-based physical activity-promoting intervention is identifiable (e.g. stripped of any spurious association). The primary objective of the current study was to demonstrate how a DAG can be used to determine if the total causal effect of an individual randomized physical activity-promoting intervention is identifiable. The demonstration was based on the Well-Being and Physical Activity study (ClinicalTrials.gov, identifier: NCT03194854). Annotated files from DAGitty and Mplus are provided.

Coadministration of 6-Shogaol and Levodopa Alleviates Parkinson's Disease-Related Pathology in Mice.

Parkinson's disease (PD) is a neurodegenerative disease caused by the death of dopaminergic neurons in the nigrostriatal pathway, leading to motor and non-motor dysfunctions, such as depression, olfactory dysfunction, and memory impairment. Although levodopa (L-dopa) has been the gold standard PD treatment for decades, it only relieves motor symptoms and has no effect on non-motor symptoms or disease progression. Prior studies have reported that 6-shogaol, the active ingredient in ginger, exerts a protective effect on dopaminergic neurons by suppressing neuroinflammation in PD mice. This study investigated whether cotreatment with 6-shogaol and L-dopa could attenuate both motor and non-motor symptoms and dopaminergic neuronal damage. Both 6-shogaol (20 mg/kg) and L-dopa (80 mg/kg) were orally administered to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine/probenecid- induced PD model mice for 26 days. The experimental results showed that L-dopa alleviated motor symptoms, but had no significant effect on non-motor symptoms, loss of dopaminergic neuron, or neuroinflammation. However, when mice were treated with 6-shogaol alone or in combination L-dopa, an amelioration in both motor and non-motor symptoms such as depression-like behavior, olfactory dysfunction and memory impairment was observed. Moreover, 6-shogaol-only or co-treatment with 6-shogaol and L-dopa protected dopaminergic neurons in the striatum and reduced neuroinflammation in the striatum and substantia nigra. Overall, these results suggest that 6-shogaol can effectively complement L-dopa by improving non-motor dysfunction and restoring dopaminergic neurons via suppressing neuroinflammation.

Baseline self-efficacy predicts subsequent engagement behavior in an online physical activity intervention.

Background: The purported benefits of online physical activity interventions, in terms of reduced costs, high reach, and easy access, may not be fully realized if participants do not engage with the programs. However, there is a lack of research on modifiable predictors (e.g., beliefs) of engagement with online physical activity interventions. The objective of this brief report was to investigate if self-efficacy to engage at baseline predicted subsequent engagement behavior in an online physical activity intervention at post-baseline. Methods: Data (N = 331) from the 2018 Fun For Wellness effectiveness trial (ClinicalTrials.gov, identifier: NCT03194854) were analyzed in this brief report. Multiple logistic regression was fit in Mplus 8 using maximum-likelihood estimation. Results: There was evidence that self-efficacy to engage beliefs at baseline positively predicted subsequent engagement behavior in the Fun For Wellness intervention at 30 days post-baseline. Conclusions: Some recommendations to increase self-efficacy to engage in future online physical activity intervention studies were provided consistent with self-efficacy theory.

Rhei Undulati Rhizoma attenuates memory decline and reduces amyloid-ß induced neuritic dystrophy in 5xFAD mouse.

BACKGROUND: Alzheimer's disease (AD) is a common type of dementia characterized by amyloid-ß (Aß) accumulation, lysosomal dysfunction, and tau hyperphosphorylation, leading to neurite dystrophy and memory loss. This study aimed to investigate whether Rhei Undulati Rhizoma (RUR), which has been reported to have anti-neuroinflammatory effect, attenuates Aß-induced memory impairment, neuritic dystrophy, and tau hyperphosphorylation, and to reveal its mode of action. METHODS: Five-month-old 5xFAD mice received RUR (50 mg/kg) orally for 2 months. The Y-maze test was used to assess working memory. After behavioral testing, brain tissue was analyzed using thioflavin S staining, western blotting, and immunofluorescence staining to investigate the mode of action of RUR. To confirm whether RUR directly reduces Aß aggregation, a thioflavin T assay and dot blot were performed after incubating Aß with RUR. RESULTS: RUR administration attenuated the Aß-induced memory impairment in 5xFAD mice. Furthermore, decreased accumulation of Aß was observed in the hippocampus of the RUR-treated 5xFAD group compare to the vehicle-treated 5xFAD group. Moreover, RUR reduced the dystrophic neurites (DNs) that accumulate impaired endolysosomal organelles around Aß. In particular, RUR treatment downregulated the expression of ß-site amyloid precursor protein cleaving enzyme 1 and the hyperphosphorylation of tau within DNs. Additionally, RUR directly suppressed the aggregation of Aß, and eliminated Aß oligomers in vitro. CONCLUSIONS: This study showed that RUR could attenuate Aß-induced pathology and directly regulate the aggregation of Aß. These results suggest that RUR could be an efficient material for AD treatment through Aß regulation.

Unraveling the mechanisms of benzo[a]pyrene degradation by Pigmentiphaga kullae strain KIT-003 using a multi-omics approach.

Polycyclic aromatic hydrocarbons (PAHs), notably benzo[a]pyrene (BaP), are environmental contaminants with multiple adverse ecological implications. Numerous studies have suggested the use of BaP biodegradation using various bacterial strains to remove BaP from the environment. This study investigates the BaP biodegradation capability of Pigmentiphaga kullae strain KIT-003, isolated from the Nak-dong River (South Korea) under specific environmental conditions. The optimum conditions of biodegradation were found to be pH 7.0, 35°C, and a salinity of 0 %. GC-MS analysis suggested alternative pathways by which KIT-003 produced catechol from BaP through several intermediate metabolites, including 4-formylchrysene-5-carboxylic acid, 5,6-dihydro-5,6-dihydroxychrysene-5-carboxylic acid (isomer: 3,4-dihydro-3,4-dihydroxychrysene-4-carboxylic acid), naphthalene-1,2-dicarboxylic acid, and 2-hydroxy-1-naphthoic acid. Proteomic profiles indicated upregulation of enzymes associated with aromatic compound degradation, such as nahAc and nahB, and of those integral to the tricarboxylic acid cycle, reflecting the strain's adaptability to and degradation of BaP. Lipidomic analysis of KIT-003 demonstrated that BaP exposure induced an accumulation of glycerolipids such as diacylglycerol and triacylglycerol, indicating their crucial role in bacterial adaptation mechanisms under BaP stress. This study provides significant scientific knowledge regarding the intricate mechanisms involved in BaP degradation by microorganisms.

Exploring gender differences in pharmacokinetics of central nervous system related medicines based on a systematic review approach.

Due to the inevitable differences in physiological and/or genetic factors between genders, the possibility that differences in pharmacokinetics between genders may occur when exposed to the same dose of the same drug is subject to reasonable inference and suspicion. Nevertheless, a significant number of medicines still rely on empirical usage and uniform clinical application without consideration of inter-individual diversity factors. In particular, in the pharmacokinetic diversity of medicines related to central nervous system (CNS) activity, consideration of gender factors and access to comparative analysis are very limited. The purpose of this study was to conduct an integrated analysis and review of differences in pharmacokinetics between genders that have not been specifically reported to date for medicines related to CNS effects, which are a group of drugs with relatively significant concerns about systemic side effects. This study was accessible through extensive data collection and analyzes using a web-based scientific literature search engine of pharmacokinetic results of CNS-related drugs performed on humans, taking gender into account. As a result, significant differences in pharmacokinetics between genders were identified for many drugs related to CNS. And most of the pharmacokinetic differences between genders suggested a higher in vivo exposure in females. This study suggests that consideration of gender factors cannot be ignored and will be an important point of interest in the precision medicine application of CNS-related medicines.

Immune signature and therapeutic approach of natural killer cell in chronic liver disease and hepatocellular carcinoma.

Natural killer (NK) cells are one of the key members of innate immunity that predominantly reside in the liver, potentiating immune responses against viral infections or malignant tumors. It has been reported that changes in cell numbers and function of NK cells are associated with the development and progression of chronic liver diseases (CLDs) including non-alcoholic fatty liver disease, alcoholic liver disease, and chronic viral hepatitis. Also, it is known that the crosstalk between NK cells and hepatic stellate cells plays an important role in liver fibrosis and cirrhosis. In particular, the impaired functions of NK cells observed in CLDs consequently contribute to occurrence and progression of hepatocellular carcinoma (HCC). Chronic infections by hepatitis B or C viruses counteract the anti-tumor immunity of the host by producing the sheddases. Soluble major histocompatibility complex class I polypeptide-related sequence A (sMICA), released from the cell surfaces by sheddases, disrupts the interaction and affects the function of NK cells. Recently, the MICA/B-NK stimulatory receptor NK group 2 member D (NKG2D) axis has been extensively studied in HCC. HCC patients with low membrane-bound MICA or high sMICA concentration have been associated with poor prognosis. Therefore, reversing the sMICA-mediated downregulation of NKG2D has been proposed as an attractive strategy to enhance both innate and adaptive immune responses against HCC. This review aims to summarize recent studies on NK cell immune signatures and its roles in CLD and hepatocellular carcinogenesis and discusses the therapeutic approaches of MICA/B-NKG2D-based or NK cell-based immunotherapy for HCC.

Multifunctional and Flexible Neural Probe with Thermally Drawn Fibers for Bidirectional Synaptic Probing in the Brain.

Synapses in the brain utilize two distinct communication mechanisms: chemical and electrical. For a comprehensive investigation of neural circuitry, neural interfaces should be capable of both monitoring and stimulating these types of physiological interactions. However, previously developed interfaces for neurotransmitter monitoring have been limited in interaction modality due to constraints in device size, fabrication techniques, and the usage of flexible materials. To address this obstacle, we propose a multifunctional and flexible fiber probe fabricated through the microwire codrawing thermal drawing process, which enables the high-density integration of functional components with various materials such as polymers, metals, and carbon fibers. The fiber enables real-time monitoring of transient dopamine release in vivo, real-time stimulation of cell-specific neuronal populations via optogenetic stimulation, single-unit electrophysiology of individual neurons localized to the tip of the neural probe, and chemical stimulation via drug delivery. This fiber will improve the accessibility and functionality of bidirectional interrogation of neurochemical mechanisms in implantable neural probes.

DeepPI: Alignment-Free Analysis of Flexible Length Proteins Based on Deep Learning and Image Generator.

With the rapid development of NGS technology, the number of protein sequences has increased exponentially. Computational methods have been introduced in protein functional studies because the analysis of large numbers of proteins through biological experiments is costly and time-consuming. In recent years, new approaches based on deep learning have been proposed to overcome the limitations of conventional methods. Although deep learning-based methods effectively utilize features of protein function, they are limited to sequences of fixed-length and consider information from adjacent amino acids. Therefore, new protein analysis tools that extract functional features from proteins of flexible length and train models are required. We introduce DeepPI, a deep learning-based tool for analyzing proteins in large-scale database. The proposed model that utilizes Global Average Pooling is applied to proteins of flexible length and leads to reduced information loss compared to existing algorithms that use fixed sizes. The image generator converts a one-dimensional sequence into a distinct two-dimensional structure, which can extract common parts of various shapes. Finally, filtering techniques automatically detect representative data from the entire database and ensure coverage of large protein databases. We demonstrate that DeepPI has been successfully applied to large databases such as the Pfam-A database. Comparative experiments on four types of image generators illustrated the impact of structure on feature extraction. The filtering performance was verified by varying the parameter values and proved to be applicable to large databases. Compared to existing methods, DeepPI outperforms in family classification accuracy for protein function inference.