Purpose: Panic disorder (PD) and PD with comorbid agoraphobia (PDA) share similar clinical characteristics but possess distinct symptom structures. However, studies specifically investigating the differences between PD and PDA are rare. Thus, the present study conducted a network analysis to examine the clinical networks of PD and PDA, focusing on panic symptom severity, anxiety sensitivity, anticipatory fear, and avoidance responses. By comparing the differences in network structures between PD and PDA, with the goal of identifying the central and bridge, we suggest clinical implications for the development of targeted interventions. Materials and Methods: A total sample (n=147; 55 male, 92 female) was collected from the psychiatric outpatient clinic of the university hospital. We conducted network analysis to examine crucial nodes in the PD and PDA networks and compared the two networks to investigate disparities and similarities in symptom structure. Results The most influential node within the PD network was Anxiety Sensitivity Index-Revised (ASI-R1; fear of respiratory symptom), whereas Panic Disorder Severity Scale (PDSS5; phobic avoidance of physical sensations) had the highest influence in the PDA network. Additionally, bridge centrality estimates indicated that each of the two nodes met the criteria for “bridge nodes” within their respective networks: ASI-R1 (fear of respiratory symptom) and Albany Panic and Phobic Questionnaire (APPQ3; interoceptive fear) for the PD group, and PDSS5 (phobic avoidance of physical sensation) and APPQ1 (panic frequency) for the PDA group Conclusion: Although the network comparison test did not reveal statistical differences between the two networks, disparities in community structure, as well as central and bridging symptoms, were observed, suggesting the possibility of distinct etiologies and treatment targets for each group. The clinical implications derived from the similarities and differences between PD and PDA networks are discussed.

Purpose: Panic disorder (PD) and PD with comorbid agoraphobia (PDA) share similar clinical characteristics but possess distinct symptom structures. However, studies specifically investigating the differences between PD and PDA are rare. Thus, the present study conducted a network analysis to examine the clinical networks of PD and PDA, focusing on panic symptom severity, anxiety sensitivity, anticipatory fear, and avoidance responses. By comparing the differences in network structures between PD and PDA, with the goal of identifying the central and bridge, we suggest clinical implications for the development of targeted interventions. Materials and Methods: A total sample (n=147; 55 male, 92 female) was collected from the psychiatric outpatient clinic of the university hospital. We conducted network analysis to examine crucial nodes in the PD and PDA networks and compared the two networks to investigate disparities and similarities in symptom structure. Results The most influential node within the PD network was Anxiety Sensitivity Index-Revised (ASI-R1; fear of respiratory symptom), whereas Panic Disorder Severity Scale (PDSS5; phobic avoidance of physical sensations) had the highest influence in the PDA network. Additionally, bridge centrality estimates indicated that each of the two nodes met the criteria for “bridge nodes” within their respective networks: ASI-R1 (fear of respiratory symptom) and Albany Panic and Phobic Questionnaire (APPQ3; interoceptive fear) for the PD group, and PDSS5 (phobic avoidance of physical sensation) and APPQ1 (panic frequency) for the PDA group Conclusion: Although the network comparison test did not reveal statistical differences between the two networks, disparities in community structure, as well as central and bridging symptoms, were observed, suggesting the possibility of distinct etiologies and treatment targets for each group. The clinical implications derived from the similarities and differences between PD and PDA networks are discussed.

Purpose: Panic disorder (PD) and PD with comorbid agoraphobia (PDA) share similar clinical characteristics but possess distinct symptom structures. However, studies specifically investigating the differences between PD and PDA are rare. Thus, the present study conducted a network analysis to examine the clinical networks of PD and PDA, focusing on panic symptom severity, anxiety sensitivity, anticipatory fear, and avoidance responses. By comparing the differences in network structures between PD and PDA, with the goal of identifying the central and bridge, we suggest clinical implications for the development of targeted interventions. Materials and Methods: A total sample (n=147; 55 male, 92 female) was collected from the psychiatric outpatient clinic of the university hospital. We conducted network analysis to examine crucial nodes in the PD and PDA networks and compared the two networks to investigate disparities and similarities in symptom structure. Results The most influential node within the PD network was Anxiety Sensitivity Index-Revised (ASI-R1; fear of respiratory symptom), whereas Panic Disorder Severity Scale (PDSS5; phobic avoidance of physical sensations) had the highest influence in the PDA network. Additionally, bridge centrality estimates indicated that each of the two nodes met the criteria for “bridge nodes” within their respective networks: ASI-R1 (fear of respiratory symptom) and Albany Panic and Phobic Questionnaire (APPQ3; interoceptive fear) for the PD group, and PDSS5 (phobic avoidance of physical sensation) and APPQ1 (panic frequency) for the PDA group Conclusion: Although the network comparison test did not reveal statistical differences between the two networks, disparities in community structure, as well as central and bridging symptoms, were observed, suggesting the possibility of distinct etiologies and treatment targets for each group. The clinical implications derived from the similarities and differences between PD and PDA networks are discussed.

Purpose: Panic disorder (PD) and PD with comorbid agoraphobia (PDA) share similar clinical characteristics but possess distinct symptom structures. However, studies specifically investigating the differences between PD and PDA are rare. Thus, the present study conducted a network analysis to examine the clinical networks of PD and PDA, focusing on panic symptom severity, anxiety sensitivity, anticipatory fear, and avoidance responses. By comparing the differences in network structures between PD and PDA, with the goal of identifying the central and bridge, we suggest clinical implications for the development of targeted interventions. Materials and Methods: A total sample (n=147; 55 male, 92 female) was collected from the psychiatric outpatient clinic of the university hospital. We conducted network analysis to examine crucial nodes in the PD and PDA networks and compared the two networks to investigate disparities and similarities in symptom structure. Results The most influential node within the PD network was Anxiety Sensitivity Index-Revised (ASI-R1; fear of respiratory symptom), whereas Panic Disorder Severity Scale (PDSS5; phobic avoidance of physical sensations) had the highest influence in the PDA network. Additionally, bridge centrality estimates indicated that each of the two nodes met the criteria for “bridge nodes” within their respective networks: ASI-R1 (fear of respiratory symptom) and Albany Panic and Phobic Questionnaire (APPQ3; interoceptive fear) for the PD group, and PDSS5 (phobic avoidance of physical sensation) and APPQ1 (panic frequency) for the PDA group Conclusion: Although the network comparison test did not reveal statistical differences between the two networks, disparities in community structure, as well as central and bridging symptoms, were observed, suggesting the possibility of distinct etiologies and treatment targets for each group. The clinical implications derived from the similarities and differences between PD and PDA networks are discussed.

Purpose: Panic disorder (PD) and PD with comorbid agoraphobia (PDA) share similar clinical characteristics but possess distinct symptom structures. However, studies specifically investigating the differences between PD and PDA are rare. Thus, the present study conducted a network analysis to examine the clinical networks of PD and PDA, focusing on panic symptom severity, anxiety sensitivity, anticipatory fear, and avoidance responses. By comparing the differences in network structures between PD and PDA, with the goal of identifying the central and bridge, we suggest clinical implications for the development of targeted interventions. Materials and Methods: A total sample (n=147; 55 male, 92 female) was collected from the psychiatric outpatient clinic of the university hospital. We conducted network analysis to examine crucial nodes in the PD and PDA networks and compared the two networks to investigate disparities and similarities in symptom structure. Results The most influential node within the PD network was Anxiety Sensitivity Index-Revised (ASI-R1; fear of respiratory symptom), whereas Panic Disorder Severity Scale (PDSS5; phobic avoidance of physical sensations) had the highest influence in the PDA network. Additionally, bridge centrality estimates indicated that each of the two nodes met the criteria for “bridge nodes” within their respective networks: ASI-R1 (fear of respiratory symptom) and Albany Panic and Phobic Questionnaire (APPQ3; interoceptive fear) for the PD group, and PDSS5 (phobic avoidance of physical sensation) and APPQ1 (panic frequency) for the PDA group Conclusion: Although the network comparison test did not reveal statistical differences between the two networks, disparities in community structure, as well as central and bridging symptoms, were observed, suggesting the possibility of distinct etiologies and treatment targets for each group. The clinical implications derived from the similarities and differences between PD and PDA networks are discussed.

Background: Diabetes mellitus is one of the most common chronic diseases worldwide, and cardiovascular disease is the leading cause of morbidity and mortality in diabetic patients. Diabetic cardiomyopathy (DCM) is a phenomenon characterized by a deterioration in cardiac function and structure, independent of vascular complications. Among many possible causes, the renin-angiotensin-aldosterone system and angiotensin II have been proposed as major drivers of DCM development. In the current study, we aimed to investigate the effects of pharmacological activation of angiotensin-converting enzyme 2 (ACE2) on DCM. Methods: The ACE2 activator diminazene aceturate (DIZE) was administered intraperitoneally to male db/db mice (8 weeks old) for 8 weeks. Transthoracic echocardiography was used to assess cardiac mass and function in mice. Cardiac structure and fibrotic changes were examined using histology and immunohistochemistry. Gene and protein expression levels were examined using quantitative reverse transcription polymerase chain reaction and Western blotting, respectively. Additionally, RNA sequencing was performed to investigate the underlying mechanisms of the effects of DIZE and identify novel potential therapeutic targets for DCM. Results: Echocardiography revealed that in DCM, the administration of DIZE significantly improved cardiac function as well as reduced cardiac hypertrophy and fibrosis. Transcriptome analysis revealed that DIZE treatment suppresses oxidative stress and several pathways related to cardiac hypertrophy. Conclusion DIZE prevented the diabetes mellitus-mediated structural and functional deterioration of mouse hearts. Our findings suggest that the pharmacological activation of ACE2 could be a novel treatment strategy for DCM.

Fascial plane blocks are useful for multimodal analgesia after cardiac surgery since they can provide effective analgesia without the serious risks associated with conventional techniques such as neuraxial hematoma and pneumothorax. This narrative review covers blocks performed at the parasternal intercostal, interpectoral, pectoserratus, serratus anterior, erector spinae, and retrolaminar planes, which are targets for fascial plane blocks in cardiac surgery. Brief anatomical considerations, mechanisms, and currently available evidence are reviewed. Additionally, recent evidence on fascial plane blocks for subcutaneous-implantable cardioverter-defibrillator implantation are also reviewed.

Objective: Alzheimer's disease (AD) is the most common cause of dementia. The statins have shown beneficial effects on cognitive functions and reduced the risk of dementia development. However, the exact mechanisms of statin effects in AD are not yet fully understood. In this study, we aimed to explore the underlying mechanisms of statin on AD. Methods: We downloaded AD blood dataset (GSE63060) and statin-related blood gene expression dataset (GSE86216). Then we performed gene expression analysis of each dataset and compared blood gene expressions between AD patients and statin-treated patients. Then, we downloaded mouse embryonic neural stem cell dataset (GSE111945) and performed gene expression analysis. Results: From the human blood dataset, we identified upregulated/downregulated genes in AD patients and statin-treated patients. Some of the upregulated genes (AEN, MBTPS1, ABCG1) in the blood of AD patients are downregulated in statin-treated patients. Several downregulated genes (FGL2, HMGCS1, PSME2, SRSF3, and ATG3) are upregulated in statintreated patients. Gene set enrichment analysis using mouse stem cell dataset revealed a significant relationship of Kyoto Encyclopedia of Genes and Genomes-defined pathway of AD in statin-treated neural stem cells compared to vehicle-treated neural stem cells (normalized enrichment score: −2.24 in male and −1.6 in female). Conclusion These gene expression analyses from human blood and mouse neural stem cell demonstrate the important clues on the molecular mechanisms of impacts of statin on AD disease. Further studies are needed to investigate the exact role of candidate genes and pathways suggested in our AD pathogenesis study.

Extramammary Paget disease (EMPD) is a rare adenocarcinoma that usually occurs in areas of the body that are rich in apocrine sweat glands. Great depth of tumor invasion is a well-known risk factor for worse prognosis. Paget cells usually are limited to the epidermis, whereas invasive EMPD, which infiltrates the dermis, is relatively rare. It is even rarer for the tumor to spread beyond the dermis. Only 3.1% of patients with EMPD of the penis and scrotum have exhibited infiltration of the subcutaneous fat layer. We report a case of a 62-year-old male with EMPD that invaded the subcutaneous fat layer. He presented with a several-year history of a slowly expanding erythematous plaque with the hypopigmented area on the left penoscrotum. One month before presentation, the patient had undergone punch biopsy at another hospital and diagnosed with EMPD. He had no personal history of urogenital cancers. The patient was treated with Mohs micrographic surgery, and negative margins were achieved after four stages. The histopathologic findings revealed Paget cells scattered throughout the epidermis. At the hypopigmented area, Paget cells extended to the subcutaneous fat layer with lymphovascular invasion. There was no evidence of recurrence at seven months postoperatively. Herein, we describe a case of hypopigmented EMPD that infiltrated the subcutaneous layer, which rarely has been reported in Korea.

Background: Among the various diaphragm-sparing alternatives to interscalene block, costoclavicular block (CCB) demonstrated a low hemidiaphragmatic paresis (HDP) occurrence but an inconsistent analgesic effect in arthroscopic shoulder surgery. We hypothesized that a larger volume of local anesthetic for CCB could provide sufficient analgesia by achieving sufficient supraclavicular spreading. Methods: Sixty patients scheduled for arthroscopic rotator cuff repair were randomly assigned to receive CCB using one of two volumes of local anesthetic (CCB20, 0.75% ropivacaine 20 ml; CCB40, 0.375% ropivacaine 40 ml). The primary outcome was the rate of complete analgesia (0 on the numeric rating scale of pain) at 1 h postoperatively. The secondary outcomes included a sonographic assessment of local anesthetic spread, diaphragmatic function, pulmonary function, postoperative opioid use, and other pain-related experiences within 24 h postoperatively. Results: The rates of complete analgesia were not significantly different (23.3% [7/30] and 33.3% [10/30] in the CCB20 and CCB40 groups, respectively; risk difference 10%, 95% CI [–13, 32], P = 0.567). There were no significant differences in other pain-related outcomes. Among the clinical factors considered, the only factor significantly associated with postoperative pain was the sonographic observation of supraclavicular spreading. There were no significant differences in the incidence of HDP and the change in pulmonary function between the two groups. Conclusions Using 40 ml of local anesthetic does not guarantee supraclavicular spread during CCB. Moreover, it does not result in a higher rate of complete analgesia compared to using 20 ml of local anesthetic in arthroscopic shoulder surgery.