Objective: Interpersonal sensitivity, characterized by a heightened awareness of others’ behavior and emotions, is linked to mood disorders. However, current literature lacks a comprehensive analysis of how some items of the Interpersonal Sensitivity Measure (IPSM) interrelate and contribute to the overall construct. This study constructed a network for interpersonal sensitivity symptomatology to identify core IPSM items in patients with mood disorders. Methods: The IPSM, a 36-item self-report scale, was utilized to evaluate interpersonal sensitivity symptoms in 837 participants (major depressive disorder [MDD], n=265; bipolar I disorder [BD I], n=126; and bipolar II disorder [BD II], n=446). We performed exploratory graph analysis, employing regularized partial correlation models to estimate the network structure. Centrality analysis identified core IPSM symptoms for each mood disorder group. Network comparison tests assessed structural differences between the MDD and BD subgroups. Results: Network analysis detected five communities. Item 10 (“I worry about being criticized for things that I have said or done”) showed the highest value in strength. Multiple items on “Interpersonal Worry/Dependency” and “Low Self-Esteem” showed high strength centrality. Network structure invariance and global strength invariance test results indicated no significant differences between the MDD and BD subgroups. Conclusion Our findings emphasize the importance of addressing “Interpersonal Worry/Dependency” and “Low Self-Esteem” in the IPSM network among mood disorder patients based on core items of the network. Additionally, targeted treatments and comprehensive strategies in this aspect could be crucial for managing mood disorders.

Objective: Interpersonal sensitivity, characterized by a heightened awareness of others’ behavior and emotions, is linked to mood disorders. However, current literature lacks a comprehensive analysis of how some items of the Interpersonal Sensitivity Measure (IPSM) interrelate and contribute to the overall construct. This study constructed a network for interpersonal sensitivity symptomatology to identify core IPSM items in patients with mood disorders. Methods: The IPSM, a 36-item self-report scale, was utilized to evaluate interpersonal sensitivity symptoms in 837 participants (major depressive disorder [MDD], n=265; bipolar I disorder [BD I], n=126; and bipolar II disorder [BD II], n=446). We performed exploratory graph analysis, employing regularized partial correlation models to estimate the network structure. Centrality analysis identified core IPSM symptoms for each mood disorder group. Network comparison tests assessed structural differences between the MDD and BD subgroups. Results: Network analysis detected five communities. Item 10 (“I worry about being criticized for things that I have said or done”) showed the highest value in strength. Multiple items on “Interpersonal Worry/Dependency” and “Low Self-Esteem” showed high strength centrality. Network structure invariance and global strength invariance test results indicated no significant differences between the MDD and BD subgroups. Conclusion Our findings emphasize the importance of addressing “Interpersonal Worry/Dependency” and “Low Self-Esteem” in the IPSM network among mood disorder patients based on core items of the network. Additionally, targeted treatments and comprehensive strategies in this aspect could be crucial for managing mood disorders.

Objective: Interpersonal sensitivity, characterized by a heightened awareness of others’ behavior and emotions, is linked to mood disorders. However, current literature lacks a comprehensive analysis of how some items of the Interpersonal Sensitivity Measure (IPSM) interrelate and contribute to the overall construct. This study constructed a network for interpersonal sensitivity symptomatology to identify core IPSM items in patients with mood disorders. Methods: The IPSM, a 36-item self-report scale, was utilized to evaluate interpersonal sensitivity symptoms in 837 participants (major depressive disorder [MDD], n=265; bipolar I disorder [BD I], n=126; and bipolar II disorder [BD II], n=446). We performed exploratory graph analysis, employing regularized partial correlation models to estimate the network structure. Centrality analysis identified core IPSM symptoms for each mood disorder group. Network comparison tests assessed structural differences between the MDD and BD subgroups. Results: Network analysis detected five communities. Item 10 (“I worry about being criticized for things that I have said or done”) showed the highest value in strength. Multiple items on “Interpersonal Worry/Dependency” and “Low Self-Esteem” showed high strength centrality. Network structure invariance and global strength invariance test results indicated no significant differences between the MDD and BD subgroups. Conclusion Our findings emphasize the importance of addressing “Interpersonal Worry/Dependency” and “Low Self-Esteem” in the IPSM network among mood disorder patients based on core items of the network. Additionally, targeted treatments and comprehensive strategies in this aspect could be crucial for managing mood disorders.

Objective: Interpersonal sensitivity, characterized by a heightened awareness of others’ behavior and emotions, is linked to mood disorders. However, current literature lacks a comprehensive analysis of how some items of the Interpersonal Sensitivity Measure (IPSM) interrelate and contribute to the overall construct. This study constructed a network for interpersonal sensitivity symptomatology to identify core IPSM items in patients with mood disorders. Methods: The IPSM, a 36-item self-report scale, was utilized to evaluate interpersonal sensitivity symptoms in 837 participants (major depressive disorder [MDD], n=265; bipolar I disorder [BD I], n=126; and bipolar II disorder [BD II], n=446). We performed exploratory graph analysis, employing regularized partial correlation models to estimate the network structure. Centrality analysis identified core IPSM symptoms for each mood disorder group. Network comparison tests assessed structural differences between the MDD and BD subgroups. Results: Network analysis detected five communities. Item 10 (“I worry about being criticized for things that I have said or done”) showed the highest value in strength. Multiple items on “Interpersonal Worry/Dependency” and “Low Self-Esteem” showed high strength centrality. Network structure invariance and global strength invariance test results indicated no significant differences between the MDD and BD subgroups. Conclusion Our findings emphasize the importance of addressing “Interpersonal Worry/Dependency” and “Low Self-Esteem” in the IPSM network among mood disorder patients based on core items of the network. Additionally, targeted treatments and comprehensive strategies in this aspect could be crucial for managing mood disorders.

Healing process in scarring inevitably produces a considerable amount of non-organized dense collagen-rich matrix called scar thus impairing the native structure of skin. Connective tissue growth factor (CTGF) overexpression within healing tissues is known to play an imperative role in collagen production stimulated by transforming growth factor-beta in cutaneous wound healing. Undoubtedly, the knockdown of CTGF expression through siRNA-mediated gene silencing could simply impede the scarring process. However, the less stability and low transfection of siRNAs themselves urge a safe carrier to protect and transfect them into cells at a high rate avoiding toxicities. Here, we developed a degradable poly(sorbitol-co-PEI) (PSPEI), prepared by polymerization of sorbitol diacrylate with low molecular weight polyethylenimine, which has high transfection efficiency but low cytotoxicity, and utilized it in siCTGF delivery to silence the expression of CTGF in an animal model of cutaneous wound healing. Unlike contracted scar in normal healing, there was no or less contraction in the healed skin of mice treated with siCTGF using PSPEI. Histologically, the healed tissues also had distinct papillary structures and dense irregular connective tissues that were lacking in the control scar tissues. This study exemplifies a successful treatment of cutaneous wound healing using a polymer system coupled with RNA interference. Hence, the approach holds a great promise for developing new treatments with novel targets in regenerative medicines.
Animals ; Cicatrix* ; Collagen ; Connective Tissue ; Connective Tissue Growth Factor ; Gene Silencing ; Mice ; Models, Animal ; Molecular Weight ; Polyethyleneimine ; Polymerization ; Polymers ; Regenerative Medicine ; RNA Interference ; RNA, Small Interfering* ; Skin ; Sorbitol ; Transfection ; Wound Healing* ; Wounds and Injuries*

Background: Bovine tuberculosis (TB) is caused by Mycobacterium bovis, a well-known cause of zoonotic tuberculosis in cattle and deer, and has been investigated in many physiological and molecular studies. However, detailed genome-level studies of M. bovis have not been performed in Korea. Objectives: To survey whole genome-wide single-nucleotide polymorphism (SNP) variants in Korean M. bovis field isolates and to define M. bovis groups in Korea by comparing SNP typing with spoligotyping and variable number tandem repeat typing. Methods: A total of 46 M. bovis field isolates, isolated from laryngopharyngeal lymph nodes and lungs of Korean cattle, wild boar, and Korean water deer, were used to identify SNPs by performing whole-genome sequencing. SNP sites were confirmed via polymerase chain reaction using 87 primer pairs. Results: We identified 34 SNP sites with different frequencies across M. bovis isolates, and performed SNP typing and epidemiological analysis, which divided the 46 field isolates into 16 subtypes. Conclusions Through SNP analysis, detailed differences in samples with identical spoligotypes could be detected. SNP analysis is, therefore, a useful epidemiological tracing tool that could enable better management of bovine TB, thus preventing further outbreaks and reducing the impact of this disease.

Background: Bovine tuberculosis (TB) is caused by Mycobacterium bovis, a well-known cause of zoonotic tuberculosis in cattle and deer, and has been investigated in many physiological and molecular studies. However, detailed genome-level studies of M. bovis have not been performed in Korea. Objectives: To survey whole genome-wide single-nucleotide polymorphism (SNP) variants in Korean M. bovis field isolates and to define M. bovis groups in Korea by comparing SNP typing with spoligotyping and variable number tandem repeat typing. Methods: A total of 46 M. bovis field isolates, isolated from laryngopharyngeal lymph nodes and lungs of Korean cattle, wild boar, and Korean water deer, were used to identify SNPs by performing whole-genome sequencing. SNP sites were confirmed via polymerase chain reaction using 87 primer pairs. Results: We identified 34 SNP sites with different frequencies across M. bovis isolates, and performed SNP typing and epidemiological analysis, which divided the 46 field isolates into 16 subtypes. Conclusions Through SNP analysis, detailed differences in samples with identical spoligotypes could be detected. SNP analysis is, therefore, a useful epidemiological tracing tool that could enable better management of bovine TB, thus preventing further outbreaks and reducing the impact of this disease.

Objective: Mood instability (MI) is a clinically significant trait associated with psychiatric disorders. However, there are no concise measurements to evaluate MI. The initial Mood Instability Questionnaire-Trait (MIQ-T) was developed to fill this gap. The current study aimed to create a short form of MIQ-T (MIQ-T-SF) that measures MI with high validity and reliability in the Korean general population. Methods: Of the 59 items in the MIQ-T, 17 items were chosen for the MIQ-T-SF following the factor analysis process. In total, 540 participants completed the MIQ-T-SF. Cronbach’s alpha and McDonald’s omega were used to evaluate reliability. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to determine construct validity. Concurrent validity was confirmed via comparisons with Personality Assessment Inventory-Borderline Features Scale. Measurement invariance across gender and age groups was confirmed before analyzing differences in scores using Kruskal-Wallis test. Results: The MIQ-T-SF displayed expected correlations and high internal consistency (α=0.71–0.90, Ωt=0.72–0.92). Using EFA and CFA, a five-factor structure was confirmed. Measurement invariance was supported, and gender differences were observed. Conclusion The MIQ-T-SF is an accurate and reliable method to detect MI in the Korean general population. The study’s results offer new perspectives for future studies on MI.

Objective: The Temperament Evaluation of Memphis, Pisa, Paris, and San Diego Autoquestionnaire (TEMPS-A) has been validated in more than 30 languages and is noted for its broad application in research and clinical settings. This study presents the first attempt to examine the reliability and validity of the TEMPS-A in Korea. Methods: A total of 540 non-clinical participants completed the Korean TEMPS-A, which was adapted from the original English version via a comprehensive translation procedure. Reliability was assessed using Cronbach’s α, and associations between temperaments were examined using Spearman’s correlation coefficient. Exploratory factor analysis (EFA) was performed, and differences in TEMPS-A scores between the gender- and age-based groups were examined using Kruskal-Wallis analysis. Results: The Korean TEMPS-A exhibited excellent internal consistency (0.70–0.91) and significant correlations between subscales. EFA resulted in a two-factor structure: Factor I (depressive, cyclothymic, irritable, and anxious) and Factor II (hyperthymic). Gender and age group differences were observed. Conclusion Overall, our results suggest that TEMPS-A is a reliable and valid measure of affective temperaments for the Korean population. This study opens new possibilities for further research on affective temperaments and their related traits.