Purpose: Metabolic abnormalities in hepatic encephalopathy (HE) cause brain edema or demyelinating disease, resulting in symmetric regional cerebral edema (SRCE) on MRI. This study aimed to investigate the usefulness of the clustering analysis of SRCE in predicting the development of brain failure. Materials and Methods: MR findings and clinical data of 98 consecutive patients with HE were retrospectively analyzed. The correlation between the 12 regions of SRCE was calculated using the phi (φ) coefficient, and the pattern was classified using hierarchical clustering using the φ 2distance measure and Ward’s method. The classified patterns of SRCE were correlated with clinical parameters such as the model for end-stage liver disease (MELD) score and HE grade. Results: Significant associations were found between 22 pairs of regions of interest, including the red nucleus and corpus callosum (φ = 0.81, p < 0.001), crus cerebri and red nucleus (φ = 0.72, p < 0.001), and red nucleus and dentate nucleus (φ = 0.66, p < 0.001). After hierarchical clustering, 24 cases were classified into Group I, 35 into Group II, and 39 into Group III. Group III had a higher MELD score (p = 0.04) and HE grade (p = 0.002) than Group I. Conclusion Our study demonstrates that the SRCE patterns can be useful in predicting hepatic preservation and the occurrence of cerebral failure in HE.

Purpose: Metabolic abnormalities in hepatic encephalopathy (HE) cause brain edema or demyelinating disease, resulting in symmetric regional cerebral edema (SRCE) on MRI. This study aimed to investigate the usefulness of the clustering analysis of SRCE in predicting the development of brain failure. Materials and Methods: MR findings and clinical data of 98 consecutive patients with HE were retrospectively analyzed. The correlation between the 12 regions of SRCE was calculated using the phi (φ) coefficient, and the pattern was classified using hierarchical clustering using the φ 2distance measure and Ward’s method. The classified patterns of SRCE were correlated with clinical parameters such as the model for end-stage liver disease (MELD) score and HE grade. Results: Significant associations were found between 22 pairs of regions of interest, including the red nucleus and corpus callosum (φ = 0.81, p < 0.001), crus cerebri and red nucleus (φ = 0.72, p < 0.001), and red nucleus and dentate nucleus (φ = 0.66, p < 0.001). After hierarchical clustering, 24 cases were classified into Group I, 35 into Group II, and 39 into Group III. Group III had a higher MELD score (p = 0.04) and HE grade (p = 0.002) than Group I. Conclusion Our study demonstrates that the SRCE patterns can be useful in predicting hepatic preservation and the occurrence of cerebral failure in HE.

Purpose: Metabolic abnormalities in hepatic encephalopathy (HE) cause brain edema or demyelinating disease, resulting in symmetric regional cerebral edema (SRCE) on MRI. This study aimed to investigate the usefulness of the clustering analysis of SRCE in predicting the development of brain failure. Materials and Methods: MR findings and clinical data of 98 consecutive patients with HE were retrospectively analyzed. The correlation between the 12 regions of SRCE was calculated using the phi (φ) coefficient, and the pattern was classified using hierarchical clustering using the φ 2distance measure and Ward’s method. The classified patterns of SRCE were correlated with clinical parameters such as the model for end-stage liver disease (MELD) score and HE grade. Results: Significant associations were found between 22 pairs of regions of interest, including the red nucleus and corpus callosum (φ = 0.81, p < 0.001), crus cerebri and red nucleus (φ = 0.72, p < 0.001), and red nucleus and dentate nucleus (φ = 0.66, p < 0.001). After hierarchical clustering, 24 cases were classified into Group I, 35 into Group II, and 39 into Group III. Group III had a higher MELD score (p = 0.04) and HE grade (p = 0.002) than Group I. Conclusion Our study demonstrates that the SRCE patterns can be useful in predicting hepatic preservation and the occurrence of cerebral failure in HE.

Background: Burnout is a syndrome resulting from chronic work-related stress, characterized by symptoms including “feelings of exhaustion, increased mental distance from one’s job, and reduced professional efficacy.” Human service providers are susceptible to burnout. Thus, this study aimed to investigate community mental health workers’ job stress, experiences with client violence, and burnouts and to analyze factors that affect burnout. Methods: This study used retrospective data from a survey of mental health workers at a mental health-related institution in a city. The data included sociodemographic characteristics, job stress, client violence, and quality of life. Results: From a total of 170 mental health workers, 67.6% were female. Subjects who were in lower age groups, had <1 year of work experience, were married, and were irregular workers were vulnerable to various job stressors. Factors associated with burnout were job demand, lack of reward, job insecurity, physical environment, other violence, and level of education. Conclusion We should create an environment wherein community mental health workers can be safe and satisfied with their work, which could lower workers’ job stress and prevent burnouts due to work. This, in turn, enhances the quality of care provided to people with mental health problems.

Objective: Following the coronavirus disease-2019 (COVID-19) outbreak, the importance of addressing acute stress induced by psychological burdens of diseases became apparent. This study attempted to evaluate the effectiveness of a new mode of psychiatric intervention designed to target similar psychological crises. Methods: Participants included 32 out of 114 COVID inpatients at a hospital in Daegu, Korea, who were assessed between March 30 and April 7, 2020. Multiple scales for screening psychological difficulties such as depressed mood, anxiety, insomnia, acute stress, and suicidality were done. Psychological problem evaluations and interventions were conducted in the form of consultations to alleviate participants’ psychological challenges via telepsychiatry. The interventions’ effects, as well as clinical improvements before and after the intervention, were analyzed. Results: As a result of screening, 21 patients were experiencing psychological difficulties beyond clinical thresholds after COVID-19 infection (screening positive group). The remaining 11 were screening negative groups. The two groups differed significantly in past psychiatric histories (p=0.034), with the former having a higher number of diagnoses. The effect of the intervention was analyzed, and clinical improvement before and after the intervention was observed. Our intervention was found to be effective in reducing the overall emotional difficulties. Conclusion This study highlighted the usefulness of new interventions required in the context of healthcare following the COVID-19 pandemic.

Foeniculum vulgare Mill. (fennel) is used to flavor food, in cosmetics, as an antioxidant, and to treat microbial, diabetic and common inflammation. No study to date, however, has assessed the anti-inflammatory effects of fennel in experimental models of inflammation. The aims of this study were to investigate the anti-inflammatory effects of fennel in model of lipopolysaccharide (LPS)-induced acute lung injury. Mice were randomly assigned to seven groups (n=7~10). In five groups, the mice were intraperitoneally injected with 1% Tween 80-saline (vehicle), fennel (125, 250, 500micro l/kg), or dexamethasone (1 mg/kg), followed 1 h later by intratracheal instillation of LPS (1.5 mg/kg). In two groups, the mice were intraperitoneally injected with vehicle or fennel (250microl/kg), followed 1 h later by intratracheal instillation of sterile saline. Mice were sacrificed 4 h later, and bronchoalveolar lavage fluid (BALF) and lung tissues were obtained. Fennel significantly and dose-dependently reduced LDH activity and immune cell numbers in LPS treated mice. In addition fennel effectively suppressed the LPS-induced increases in the production of the inflammatory cytokines interleukin-6 and tumor necrosis factor-alpha, with 500microl/kg fennel showing maximal reduction. Fennel also significantly and dose-dependently reduced the activity of the proinflammatory mediator matrix metalloproteinase 9 and the immune modulator nitric oxide (NO). Assessments of the involvement of the MAPK signaling pathway showed that fennel significantly decreased the LPS-induced phosphorylation of ERK. Fennel effectively blocked the inflammatory processes induced by LPS, by regulating pro-inflammatory cytokine production, transcription factors, and NO.
Acute Lung Injury* ; Animals ; Bronchoalveolar Lavage Fluid ; Cell Count ; Cytokines ; Dexamethasone ; Foeniculum* ; Inflammation ; Interleukin-6 ; Lung ; Matrix Metalloproteinase 9 ; Mice* ; Models, Theoretical ; NF-kappa B* ; Nitric Oxide ; Phosphorylation ; Transcription Factors ; Tumor Necrosis Factor-alpha

Objective: Discriminating between pulmonary embolism (PE) and pneumonia in the emergency department (ED) is one of the fastidious tasks. Elderly patients are at more risk of PE and pneumonia than younger patients. This study aimed to determine whether the ratio of D-dimer to C-reactive protein (CRP) could be used as an adjunctive method to differentiate between PE and pneumonia in elderly patients. Methods: Medical records of patients visiting the ED diagnosed with PE and pneumonia were examined. Cutoff values of D-dimer (μg/mL) and the ratio of D-dimer to CRP ([μg/mL]/[mg/dL]) of subjects with PE or pneumonia were analyzed. Results: There were a total of 60 patients with PE and 152 patients with pneumonia. In addition, 15 patients had both PE and pneumonia. The cutoff value of D-dimer to differentiate between PE and pneumonia was 4.26 μg/mL (4,260 ng/mL) (area under curve [AUC], 0.861; sensitivity, 80.0%; specificity, 80.3%; 95% confidence interval [CI], 0.805-0.917). The cutoff value of the ratio of D-dimer to CRP to differentiate between PE and pneumonia was 1.24 ([μg/mL]/[mg/dL]) (AUC, 0.919; sensitivity, 84.4%; specificity, 84.2%; 95% CI, 0.878-0.960). Conclusion The ratio of D-dimer to CRP can be used as an adjunctive method to determine whether a computed tomography pulmonary angiography or a ventilation-perfusion scan can be performed to differentiate between PE and pneumonia in elderly patients.

Purpose: This study evaluated volumetric analysis using automatic whole-brain segmentation as a potential tool to enhance diagnostic accuracy alongside traditional magnetic resonance imaging (MRI) markers in the diagnosis of idiopathic normal pressure hydrocephalus (INPH). Materials and Methods: Twenty-six patients diagnosed with INPH exhibited progressive symptoms, including gait dysfunction and cognitive impairment, confirmed by MRI evidence of enlarged ventricles and normal cerebrospinal fluid pressure. Automatic segmentation was performed on sagittal T1-weighted volumetric images using LesionQuant. Age- and sex-matched groups with Alzheimer’s disease (AD) and normal control (NC) groups were included. Multinomial logistic regression was applied to predict diagnoses (NC, INPH, or AD) based on volumetric parameters. Results: Compared to the AD and NC groups, enlarged inferior lateral ventricles were observed in the INPH group. The inferior lateral ventricle volume showed a positive linear correlation with the Evans’ index (R2 = 0.639) and a negative linear correlation with the callosal angle (R2 = 0.482). High classification accuracy was achieved, with 87.5% of NC cases, 88.5% of INPH cases, and 76% of AD cases correctly identified. Conclusion Automated volumetric markers appear valuable for diagnosing INPH and distinguishing it from other neurodegenerative diseases.

Purpose: This study evaluated volumetric analysis using automatic whole-brain segmentation as a potential tool to enhance diagnostic accuracy alongside traditional magnetic resonance imaging (MRI) markers in the diagnosis of idiopathic normal pressure hydrocephalus (INPH). Materials and Methods: Twenty-six patients diagnosed with INPH exhibited progressive symptoms, including gait dysfunction and cognitive impairment, confirmed by MRI evidence of enlarged ventricles and normal cerebrospinal fluid pressure. Automatic segmentation was performed on sagittal T1-weighted volumetric images using LesionQuant. Age- and sex-matched groups with Alzheimer’s disease (AD) and normal control (NC) groups were included. Multinomial logistic regression was applied to predict diagnoses (NC, INPH, or AD) based on volumetric parameters. Results: Compared to the AD and NC groups, enlarged inferior lateral ventricles were observed in the INPH group. The inferior lateral ventricle volume showed a positive linear correlation with the Evans’ index (R2 = 0.639) and a negative linear correlation with the callosal angle (R2 = 0.482). High classification accuracy was achieved, with 87.5% of NC cases, 88.5% of INPH cases, and 76% of AD cases correctly identified. Conclusion Automated volumetric markers appear valuable for diagnosing INPH and distinguishing it from other neurodegenerative diseases.

Purpose: This study evaluated volumetric analysis using automatic whole-brain segmentation as a potential tool to enhance diagnostic accuracy alongside traditional magnetic resonance imaging (MRI) markers in the diagnosis of idiopathic normal pressure hydrocephalus (INPH). Materials and Methods: Twenty-six patients diagnosed with INPH exhibited progressive symptoms, including gait dysfunction and cognitive impairment, confirmed by MRI evidence of enlarged ventricles and normal cerebrospinal fluid pressure. Automatic segmentation was performed on sagittal T1-weighted volumetric images using LesionQuant. Age- and sex-matched groups with Alzheimer’s disease (AD) and normal control (NC) groups were included. Multinomial logistic regression was applied to predict diagnoses (NC, INPH, or AD) based on volumetric parameters. Results: Compared to the AD and NC groups, enlarged inferior lateral ventricles were observed in the INPH group. The inferior lateral ventricle volume showed a positive linear correlation with the Evans’ index (R2 = 0.639) and a negative linear correlation with the callosal angle (R2 = 0.482). High classification accuracy was achieved, with 87.5% of NC cases, 88.5% of INPH cases, and 76% of AD cases correctly identified. Conclusion Automated volumetric markers appear valuable for diagnosing INPH and distinguishing it from other neurodegenerative diseases.