Missing a Lipiodol-laden hepatocellular carcinoma?: Silent iatrogenic hepatoduodenal fistula after transarterial chemoembolization: a case report.

RATIONALE: Owing to the abundant collateral blood supply to the duodenum, the development of a hepatoduodenal fistula after transarterial chemoembolization (TACE) is an extremely rare complication that usually requires hospitalization and intensive medical intervention. Here, we report a case of a silent hepatoduodenal fistula following TACE. PATIENT CONCERNS: A 74-year-old man with a history of alcoholic liver cirrhosis and type 2 diabetes. He had undergone a partial hepatectomy due to hepatocellular carcinoma (HCC) 7 years ago. In addition, he had undergone 4 TACEs for the treatment of recurrent HCCs but still had a viable tumor in S4b of the liver, which abuts the duodenal 1st portion. DIAGNOSES: HCC. INTERVENTIONS: The patient underwent a 5th TACE and was discharged from the hospital without major adverse events. OUTCOMES: Follow-up computed tomography scans showed a 2 cm-sized air cavity instead of a compact Lipiodol-laden tumor in S4b, which had shrunk over time. The patient had experienced a fluctuating nonspecific mild fever for 3 months, with improvements in symptoms and laboratory findings following conservative treatment alone. LESSONS: Hepatic fistulas may arise following TACE for HCCs near the gastrointestinal tract and may be present with nonspecific symptoms. This case suggests that increased efforts should be directed toward achieving selective embolization when treating HCC adjacent to the gastrointestinal tract, with close monitoring required after treatment.

Effects of perceived sleep quality on creative behavior via work engagement: the moderating role of gender.

BACKGROUND: Sleep quality significantly impacts employees' attitudes and behaviors. Using ego depletion theory, we examined the influence of sleep quality on work engagement and creative behavior, also investigating gender differences in these effects. METHODS: A multi-wave survey approach was employed with a six-week interval between waves for data collection. Participants were recruited online across two waves, totaling 322 employees from the United Kingdom and the United States. RESULTS: Regression analyses revealed a statistically significant positive relationship between sleep quality and creative behavior, mediated by work engagement. Additionally, gender moderated both the direct and indirect effects of sleep quality. CONCLUSION: The study found a positive relationship between sleep quality and creative behavior, mediated by work engagement, with notable gender differences. Sleep quality had a stronger impact on work engagement for men than women, and a stronger indirect effect on creative behavior through work engagement. These findings add to the existing literature on the influence of sleep quality on creative behavior.

Unraveling the Link between Perceived ESG and Psychological Well-Being: The Moderated Mediating Roles of Job Meaningfulness and Pay Satisfaction.

Enhancing corporate accountability in areas such as environment, social, and governance (ESG) has solidified its role in the discussion on improving corporate resilience and growth. ESG management activities not only augment corporate sustainability and risk control but also influence the professional roles and personal lives of members through their perceived ESG. Historically, most ESG research has centered on the interrelation of corporate ESG endeavors and outcomes, while studies focusing on the influence of perceived ESG on members have been sparse. In this light, our investigation, rooted in the conservation of resources theory, aimed to delineate the mechanistic link between perceived ESG and members' psychological well-being. This study employed a stratified random sampling technique and collected data across three waves, each spaced four weeks apart. Our sample comprised 325 Korean employees working in administrative, technical, service, and sales roles. This study recruited 325 Korean employees across three time-lagged phases and found that ESG comprehension enhances job meaningfulness, subsequently amplifying psychological wellness. Intriguingly, as pay satisfaction escalates, the mediating role of job meaningfulness between perceived ESG and well-being intensifies. Our study underscores that for organizations to harness perceived ESG to boost psychological well-being via job meaningfulness, managing pay satisfaction is imperative. These findings highlight a crucial policy implication: policymakers must actively promote ESG awareness and incorporate it into employee compensation strategies. This integration is essential to cultivating a healthier, more engaged workforce and driving long-term organizational success.

Fatigue in Parkinson's Disease Is Due to Decreased Efficiency of the Frontal Network: Quantitative EEG Analysis.

OBJECTIVE: Fatigue is a common, debilitating nonmotor symptom of Parkinson's disease (PD), but its mechanism is poorly understood. We aimed to determine whether electroencephalography (EEG) could objectively measure fatigue and to explore the pathophysiology of fatigue in PD. METHODS: We studied 32 de novo PD patients who underwent EEG. We compared brain activity between 19 PD patients without fatigue and 13 PD patients with fatigue via EEG power spectra and graphs, including the global efficiency, characteristic path length, clustering coefficient, small-worldness, local efficiency, degree centrality, closeness centrality, and betweenness centrality. RESULTS: No significant differences in absolute or relative power were detected between PD patients without or with fatigue (all p > 0.02, Bonferroni-corrected). According to our network analysis, brain network efficiency differed by frequency band. Generally, the brain network in the frontal area for theta and delta bands showed greater efficiency, and in the temporal area, the alpha1 band was less efficient in PD patients without fatigue (p < 0.0001, p = 0.0011, and p = 0.0007, respectively, Bonferroni-corrected). CONCLUSION: Our study suggests that PD patients with fatigue have less efficient networks in the frontal area than PD patients without fatigue. These findings may explain why fatigue is common in PD, a frontostriatal disorder. Increased efficiency in the temporal area in PD patients with fatigue is assumed to be compensatory. Brain network analysis using graph theory is more valuable than power spectrum analysis in revealing the brain mechanism related to fatigue.

The dark side of mobile work during non-work hours: moderated mediation model of presenteeism through conservation of resources lens.

Owing to the development of Information and Communication Technology (ICT) and the inevitability of telecommuting in the COVID-19 environment, the boundary between working and non-working hours has become blurred. mWork, that is, ICT-based off-hour work, which has increased through the pandemic, affects employees' work attitudes, such as presenteeism. Hence, we designed a study to investigate the antecedents and mechanisms of employee presenteeism from the perspective of the conservation of resources theory. We supported our hypothesis using a sample of 325 Korean office workers obtained through three rounds of time-delay surveys. The results show that presenteeism is higher among employees with high mWork. In addition, employees' mWork increases sleep deprivation and presenteeism, and the exchange ideology of employees reinforces the positive effect of sleep deprivation on presenteeism. Additionally, the higher the level of exchange ideology, the stronger the mediating effect of mWork on presenteeism through sleep deprivation. This study verified the conservation of resources theory by identifying the mechanism by which mWork affects an employee's life, which in turn affects their work, and provides practical implications for managing productivity loss due to presenteeism.

A Longitudinal Study on Memory Enhancement in Subjective Cognitive Decline Patients: Clinical and Neuroimaging Perspectives.

BACKGROUND: Subjective cognitive decline (SCD) refers to the self-reported persistent cognitive decline despite normal objective testing, increasing the risk of dementia compared to cognitively normal individuals. OBJECTIVE: This study aims to investigate the attributes of SCD patients who demonstrated memory function improvement. METHODS: In this prospective study of SCD, a total of 120 subjects were enrolled as part of a multicenter cohort study aimed at identifying predictors for the clinical progression to mild cognitive impairment or dementia (CoSCo study). All subjects underwent 18F-florbetaben PET and brain MRI scans at baseline and annual neuropsychological tests. At the 24-month follow-up, we classified SCD patients based on changes in memory function, the z-score of the Seoul verbal learning test delayed recall. RESULTS: Of the 120 enrolled patients, 107 successfully completed the 24-month follow-up assessment. Among these, 80 patients (74.8%) with SCD exhibited memory function improvements. SCD patients with improved memory function had a lower prevalence of coronary artery disease at baseline and performed better in the trail-making test part B compared to those without improvement. Anatomical and biomarker analysis showed a lower frequency of amyloid PET positivity and larger volumes in the left and right superior parietal lobes in subjects with improved memory function. CONCLUSIONS: Our prospective study indicates that SCD patients experiencing memory improvement over a 24-month period had a lower amyloid burden, fewer cardiovascular risk factors, and superior executive cognitive function. Identifying these key factors associated with cognitive improvement may assist clinicians in predicting future memory function improvements in SCD patients.

Machine learning-based prediction of post-stroke cognitive status using electroencephalography-derived brain network attributes.

Objectives: More than half of patients with acute ischemic stroke develop post-stroke cognitive impairment (PSCI), a significant barrier to future neurological recovery. Thus, predicting cognitive trajectories post-AIS is crucial. Our primary objective is to determine whether brain network properties from electroencephalography (EEG) can predict post-stroke cognitive function using machine learning approach. Methods: We enrolled consecutive stroke patients who underwent both EEG during the acute stroke phase and cognitive assessments 3 months post-stroke. We preprocessed acute stroke EEG data to eliminate low-quality epochs, then performed independent component analysis and quantified network characteristics using iSyncBrain®. Cognitive function was evaluated using the Montreal cognitive assessment (MoCA). We initially categorized participants based on the lateralization of their lesions and then developed machine learning models to predict cognitive status in the left and right hemisphere lesion groups. Results: Eighty-seven patients were included, and the accuracy of lesion laterality prediction using EEG attributes was 97.0%. In the left hemispheric lesion group, the network attributes of the theta band were significantly correlated with MoCA scores, and higher global efficiency, clustering coefficient, and lower characteristic path length were associated with higher MoCA scores. Most features related to cognitive scores were selected from the frontal lobe. The predictive powers (R-squared) were 0.76 and 0.65 for the left and right stroke groups, respectively. Conclusion: Estimating EEG-based network properties in the acute phase of ischemic stroke through a machine learning model has a potential to predict cognitive outcomes after ischemic stroke.

The influence of sleep on job satisfaction: examining a serial mediation model of psychological capital and burnout.

Introduction: This study draws on the conservation of resources theory to investigate whether the loss of sleep can trigger the loss of additional resources that are necessary for work. Methods: Using cross-sectional design of 322 call center employees working at a government-owned public bank in South Korea, we test the study hypotheses using regression and bootstrapping indirect effects analyses. Results: The results of analyses show that insufficient sleep increases employee burnout and that psychological capital mediates this relationship. We also find that insufficient sleep decreases job satisfaction via a serial mediation model such that insufficient sleep reduces psychological capital, which in turn increases burnout, and ultimately results in lower job satisfaction. Discussion: The findings reinforce the previous assessment that although sleep is a non-work factor, its impact spills over to the workplace. Theoretically, this study goes beyond direct effect to uncover the underlying or mediating mechanisms that account for the impact of the sleep-burnout relationship and the sleep-job satisfaction relationship. For managers, the results highlight the significance of sleep to employees' overall health and well-being and thus underscore the need to foster a work culture that recognizes and prioritizes employee sleep needs.

An Empirical Study of Social Loafing Behavior among Public Officers in South Korea: The Role of Trust in a Supervisor, Perceived Organizational Support, and Perceived Organizational Politics.

This study explored the effects of trust in a supervisor (TIS) on social loafing behaviors of employees. In addition, this study examined the mediating effect of perceived organizational support (POS) on the relationship between trust in a supervisor and employees' social loafing behaviors. It also examined the moderating effects of perceived organizational politics (POP) on the relationship between TIS and POS, TIS and social loafing behaviors, and POS and social loafing behaviors. Data were collected from local government employees in Korea, and the final sample was 260. Our results indicate that trust in a supervisor has indirect negative effects on social loafing behaviors mediated by POS. In addition, it was found that the effects of TIS on POS and POS on social loafing behaviors were moderated by POP. The results of this study contribute to the extant literature on social loafing behaviors. Moreover, the findings imply that political behaviors in organizations might induce social loafing behaviors.

PET-validated EEG-machine learning algorithm predicts brain amyloid pathology in pre-dementia Alzheimer's disease.

Developing reliable biomarkers is important for screening Alzheimer's disease (AD) and monitoring its progression. Although EEG is non-invasive direct measurement of brain neural activity and has potentials for various neurologic disorders, vulnerability to noise, difficulty in clinical interpretation and quantification of signal information have limited its clinical application. There have been many research about machine learning (ML) adoption with EEG, but the accuracy of detecting AD is not so high or not validated with Aß PET scan. We developed EEG-ML algorithm to detect brain Aß pathology among subjective cognitive decline (SCD) or mild cognitive impairment (MCI) population, and validated it with Aß PET. 19-channel resting-state EEG and Aß PET were collected from 311 subjects: 196 SCD(36 Aß +, 160 Aß -), 115 MCI(54 Aß +, 61Aß -). 235 EEG data were used for training ML, and 76 for validation. EEG features were standardized for age and sex. Multiple important features sets were selected by 6 statistics analysis. Then, we trained 8 multiple machine learning for each important features set. Meanwhile, we conducted paired t-test to find statistically different features between amyloid positive and negative group. The best model showed 90.9% sensitivity, 76.7% specificity and 82.9% accuracy in MCI + SCD (33 Aß +, 43 Aß -). Limited to SCD, 92.3% sensitivity, 75.0% specificity, 81.1% accuracy (13 Aß +, 24 Aß -). 90% sensitivity, 78.9% specificity and 84.6% accuracy for MCI (20 Aß +, 19 Aß -). Similar trends of EEG power have been observed from the group comparison between Aß + and Aß -, and between MCI and SCD: enhancement of frontal/ frontotemporal theta; attenuation of mid-beta in centroparietal areas. The present findings suggest that accurate classification for beta-amyloid accumulation in the brain based on QEEG alone could be possible, which implies that QEEG is a promising biomarker for beta-amyloid. Since QEEG is more accessible, cost-effective, and safer than amyloid PET, QEEG-based biomarkers may play an important role in the diagnosis and treatment of AD. We expect specific patterns in QEEG could play an important role to predict future progression of cognitive impairment in the preclinical stage of AD. Further feature engineering and validation with larger dataset is recommended.

Coaching leadership and creative performance: A serial mediation model of psychological empowerment and constructive voice behavior.

This study empirically analyzes the role of coaching leadership in enhancing an organization's creative performance, discussing and evaluating important mediating paths of coaching leadership regarding creative performance. As a result of an empirical analysis based on survey data collected from 332 employees of Korean companies, this study first confirms that coaching leadership has a positive effect on both employees' creative performance. We also found that psychological empowerment and constructive voice behavior positively mediated the relationship between coaching leadership and creative performance. Finally, the serial mediating effect of coaching leadership on creative performance was tested through psychological empowerment and constructive voice behavior and confirmed to have a positive effect. This study indicates the importance of leadership as a critical variable that promotes employees' creative performance. In addition, by confirming the serial mediating role of psychological empowerment and constructive voice behavior, this study improves understanding of key mechanism in which coaching leadership leads to creative performance.

Prognostic significance of location index in resected T1-sized early-stage non-small cell lung cancer.

BACKGROUND: While the central location is a known adverse prognostic factor in lung cancer, a precise definition of central lung cancer has not yet emerged. PURPOSE: To determine the prognostic significance of central lung cancer (defined by location index) in resected T1-sized early-stage non-small cell lung cancer (NSCLC). MATERIAL AND METHODS: Patients with resected T1-sized early-stage NSCLC between 2010 and 2015 at a single tertiary cancer center were retrospectively reviewed. Central lung cancer was defined by a location index of the second tertile or less. Kaplan-Meier analysis with log-rank test and multivariable Cox regression analysis were performed to analyze the relationship between central lung cancer and the prognosis of relapse-free survival (RFS) and overall survival (OS). Inter-observer agreement was assessed using Cohen's kappa value and intraclass correlation coefficient (ICC). RESULTS: Overall, 289 patients (169 men; median age 65 years; interquartile range 58-70 years) were evaluated. Central lung cancer (defined by location index) was adversely associated with RFS (P = 0.005) and OS (P = 0.01). Multivariable Cox regression analysis showed that central lung cancer was independently associated with poor RFS (adjusted hazard ratio 1.91; 95% confidence interval [CI] 1.12-3.24; P = 0.017) and OS (adjusted hazard ratio 1.69; 95% CI 1.04-2.74; P = 0.033). Location index demonstrated excellent inter-observer agreement (Cohen's kappa value 0.88; 95% CI 0.82-0.93) with a high ICC (0.98; 95% CI 0.97-0.98). CONCLUSION: Central lung cancer defined by a location index of the second tertile or lower is an independent adverse prognostic factor in resected T1-sized early-stage NSCLC.

Malignant Apocrine Lesions of the Breast: Multimodality Imaging Findings and Biologic Features.

The apocrine morphology of the breast is observed in a broad pathological spectrum, ranging from benign cysts to invasive carcinomas. However, the number of clinical research investigating malignant apocrine lesions is limited. This study retrospectively reviewed the data of patients with malignant apocrine lesions admitted in a tertiary center between January 2004 and December 2021, based on the radiology-pathology correlation and the recent advances in their status to enhance the therapeutic implications of androgen receptor (AR). Among the 37 patients with lesions, 27 (73.0%) had triple-negative subtypes with predominant AR expression. The radiological features of malignant apocrine lesions did not differ from those of typical invasive ductal carcinoma or ductal carcinoma in situ. This study demonstrated that knowledge on the imaging features of malignant apocrine lesions and their histological basis could enhance the adoption of new targeted therapies in patients with this particular type of breast cancer.

Implication of EEG theta/alpha and theta/beta ratio in Alzheimer's and Lewy body disease.

We evaluated the patterns of quantitative electroencephalography (EEG) in patients with Alzheimer's disease (AD), Lewy body disease (LBD), and mixed disease. Sixteen patients with AD, 38 with LBD, 20 with mixed disease, and 17 control participants were recruited and underwent EEG. The theta/alpha ratio and theta/beta ratio were measured. The relationship of the log-transformed theta/alpha ratio (TAR) and theta/beta ratio (TBR) with the disease group, the presence of AD and LBD, and clinical symptoms were evaluated. Participants in the LBD and mixed disease groups had higher TBR in all lobes except for occipital lobe than those in the control group. The presence of LBD was independently associated with higher TBR in all lobes and higher central and parietal TAR, while the presence of AD was not. Among cognitively impaired patients, higher TAR was associated with the language, memory, and visuospatial dysfunction, while higher TBR was associated with the memory and frontal/executive dysfunction. Increased TBR in all lobar regions and temporal TAR were associated with the hallucinations, while cognitive fluctuations and the severity of Parkinsonism were not. Increased TBR could be a biomarker for LBD, independent of AD, while the presence of mixed disease could be reflected as increased TAR.

Electroencephalography for Early Detection of Alzheimer's Disease in Subjective Cognitive Decline.

Background and Purpose: Early detection of subjective cognitive decline (SCD) due to Alzheimer's disease (AD) is important for clinical research and effective prevention and management. This study examined if quantitative electroencephalography (qEEG) could be used for early detection of AD in SCD. Methods: Participants with SCD from 6 dementia clinics in Korea were enrolled. 18F-florbetaben brain amyloid positron emission tomography (PET) was conducted for all the participants. qEEG was performed to measure power spectrum and source cortical activity. Results: The present study included 95 participants aged over 65 years, including 26 amyloid PET (+) and 69 amyloid PET (-). In participants with amyloid PET (+), relative power at delta band was higher in frontal (p=0.025), parietal (p=0.005), and occipital (p=0.022) areas even after adjusting for age, sex, and education. Source activities of alpha 1 band were significantly decreased in the bilateral fusiform and inferior temporal areas, whereas those of delta band were increased in the bilateral cuneus, pericalcarine, lingual, lateral occipital, precuneus, posterior cingulate, and isthmus areas. There were increased connections between bilateral precuneus areas but decreased connections between left rostral middle frontal area and bilateral frontal poles at delta band in participants with amyloid PET (+) showed. At alpha 1 band, there were decreased connections between bilateral entorhinal areas after adjusting for covariates. Conclusions: SCD participants with amyloid PET (+) showed increased delta and decreased alpha 1 activity. qEEG is a potential means for predicting amyloid pathology in SCD. Further longitudinal studies are needed to confirm these findings.

Characteristics of Attention-Deficit/Hyperactivity Disorder Subtypes in Children Classified Using Quantitative Electroencephalography.

Purpose: This study used quantitative electroencephalography (QEEG) to investigate the characteristics of attention-deficit/hyperactivity disorder (ADHD) subtypes in children. Patients and Methods: There were 69 subjects (42 with ADHD and 27 neurotypical (NT)) in this study. A semi-structured interview was conducted with each participant for psychiatric diagnostic evaluation. We measured the absolute and relative power in 19 channels and analyzed QEEG using the following frequency ranges: delta (1-4 Hz), theta (4-8 Hz), alpha 1 (8-10 Hz), alpha 2 (10-12 Hz), beta 1 (12-15 Hz), beta 2 (15-20 Hz), beta 3 (20-30 Hz), and gamma (30-45 Hz). Group analyses and EEG noise preprocessing were conducted using iSyncBrain, a cloud-based, artificial intelligence EEG analysis platform. Analysis of covariance adjusted for IQ, age, and sex was used. Results: QEEG analysis revealed three ADHD subtypes, characterized by (A) elevated relative fast alpha and beta power, (B) elevated absolute slow frequency (delta and theta power), or (C) elevated absolute and relative beta power. A significant difference was found in the Korean ADHD Rating Scale (K-ARS) among the four groups (df=3, F=8.004, p<0.001); group C had the highest score (25.31±11.16), followed by group A (21.67±13.18). The score of group B (12.64±7.84) was similar to that of the NT group (11.07±6.12) and did not reach the cut-off point of the K-ARS. In the Wender-Utah Rating Scale (WURS), group B score (55.82±23.17) was significantly higher than the NT group score (42.81±13.26). Conclusion: These results indicate that children with ADHD do not constitute a neurophysiologically homogenous group. Children with QEEG subtype B (elevated slow frequency) may be difficult to distinguish from normal children using the K-ARS, which is the most common screening tool for ADHD. Moreover, parents of children with this subtype may be less sensitive to observing ADHD symptoms.

Novel quantitative electroencephalogram feature image adapted for deep learning: Verification through classification of Alzheimer's disease dementia.

Quantitative electroencephalography (QEEG) analysis is commonly adopted for the investigation of various neurological disorders, revealing electroencephalogram (EEG) features associated with specific dysfunctions. Conventionally, topographies are widely utilized for spatial representation of EEG characteristics at specific frequencies or frequency bands. However, multiple topographies at various frequency bands are required for a complete description of brain activity. In consequence, use of topographies for the training of deep learning algorithms is often challenging. The present study describes the development and application of a novel QEEG feature image that integrates all required spatial and spectral information within a single image, overcoming conventional obstacles. EEG powers recorded at 19 channels defined by the international 10-20 system were pre-processed using the EEG auto-analysis system iSyncBrain®, removing the artifact components selected through independent component analysis (ICA) and rejecting bad epochs. Hereafter, spectral powers computed through fast Fourier transform (FFT) were standardized into Z-scores through iMediSync, Inc.'s age- and sex-specific normative database. The standardized spectral powers for each channel were subsequently rearranged and concatenated into a rectangular feature matrix, in accordance with their spatial location on the scalp surface. Application of various feature engineering techniques on the established feature matrix yielded multiple types of feature images. Such feature images were utilized in the deep learning classification of Alzheimer's disease dementia (ADD) and non-Alzheimer's disease dementia (NADD) data, in order to validate the use of our novel feature images. The resulting classification accuracy was 97.4%. The Classification criteria were further inferred through an explainable artificial intelligence (XAI) algorithm, which complied with the conventionally known EEG characteristics of AD. Such outstanding classification performance bolsters the potential of our novel QEEG feature images in broadening QEEG utility.

Paradoxical Leadership and Involvement in Creative Task via Creative Self-Efficacy: A Moderated Mediation Role of Task Complexity.

Modern organizational environments encounter serious competition and paradoxical situations. This study discusses the effect of paradoxical leadership on overcoming competitive and paradoxical situations happening in the Korean workplace. More specifically, it investigates the dynamic relationship between paradoxical leadership and involvement in creative tasks in a Korean context and examines whether creative self-efficacy positively mediates this relationship. Our research design addresses the moderating role and moderated mediating role of task complexity in the relationship between paradoxical leadership and the involvement in creative tasks via creative self-efficacy. The main hypotheses were tested by using a cross-sectional design and administering questionnaires to 268 employees working in Korean firms. Empirical analysis revealed that paradoxical leadership is positively related to involvement in creative tasks and creative self-efficacy and that creative self-efficacy positively mediated the relationship between paradoxical leadership and involvement in creative tasks. Importantly, as the relationship between paradoxical leadership and creative self-efficacy depends on task complexity, the mediated relationship was effective under high task complexity. Uncovering the relationship between paradoxical leadership and involvement in creative tasks with the mediating role of creative self-efficacy and the moderated mediating role of task complexity can provide useful theoretical and managerial implications.

What hinders team innovation performance? Three-way interaction of destructive leadership, intra-team conflict, and organizational diversity.

This paper aims to clarify the impact of destructive leadership on team innovation performance. It also explores the relevant conditions that maximize the above relationship. Specifically we examine how intra-team conflict organizational diversity moderate the relationship between destructive leadership team innovation performance. Finally the three-way interaction between destructive leadership intra-team conflict organizational diversity is analyzed for the worst conditions to maximize the negative effect of destructive leadership on team innovation performance. This paper used a cross-sectional design with questionnaires administered to 87 teams with 479 team members working in Korean manufacturing service firms. It applied a hierarchical regression analysis to test the hypothesized relationships including three-way interaction effect among destructive leadership intra-team conflict organizational diversity on team innovation performance. This paper provided empirical insights about how destructive behaviors of team leader hindered team innovation performance. The three-way interaction effects also revealed that the higher the levels of both intra-team conflict organizational diversity the greater the negative effect of destructive leadership on team innovation performance. This paper demonstrates how team leaders' behavior team organizational conditions result in discouraging overall innovation outcomes. This paper contributes to the innovation leadership literatures by identifying possible leadership type hindering innovation performance at team level the specific conditions their dynamic interaction strengthening the negative effect of destructive leadership on team innovation performance.

Functional brain changes using electroencephalography after a 24-week multidomain intervention program to prevent dementia.

Quantitative electroencephalography (QEEG) has proven useful in predicting the response to various treatments, but, until now, no study has investigated changes in functional connectivity using QEEG following a lifestyle intervention program. We aimed to investigate neurophysiological changes in QEEG after a 24-week multidomain lifestyle intervention program in the SoUth Korean study to PrEvent cognitive impaiRment and protect BRAIN health through lifestyle intervention in at-risk elderly people (SUPERBRAIN). Participants without dementia and with at least one modifiable dementia risk factor, aged 60-79 years, were randomly assigned to the facility-based multidomain intervention (FMI) (n = 51), the home-based multidomain intervention (HMI) (n = 51), and the control group (n = 50). The analysis of this study included data from 44, 49, and 34 participants who underwent EEG at baseline and at the end of the study in the FMI, HMI, and control groups, respectively. The spectrum power and power ratio of EEG were calculated. Source cortical current density and functional connectivity were estimated by standardized low-resolution brain electromagnetic tomography. Participants who received the intervention showed increases in the power of the beta1 and beta3 bands and in the imaginary part of coherence of the alpha1 band compared to the control group. Decreases in the characteristic path lengths of the alpha1 band in the right supramarginal gyrus and right rostral middle frontal cortex were observed in those who received the intervention. This study showed positive biological changes, including increased functional connectivity and higher global efficiency in QEEG after a multidomain lifestyle intervention. Clinical trial registration: [https://clinicaltrials.gov/ct2/show/NCT03980392] identifier [NCT03980392].