Network Structure of Depressive Symptomatology in Elderly with Cognitive Impairment.

Objective and objectives: Patients with cognitive disorders such as Alzheimer's disease (AD) and mild cognitive impairment (MCI) frequently exhibit depressive symptoms. Depressive symptoms can be evaluated with various measures and questionnaires. The geriatric depression scale (GDS) is a scale that can be used to measure symptoms in geriatric age. Many questionnaires sum up symptom scales. However, core symptoms of depression in these patients and connections between these symptoms have not been fully explored yet. Thus, the objectives of this study were (1) to determine core symptoms of two cognitive disorders, Alzheimer's disease and mild cognitive impairment, and (2) to investigate the network structure of depressive symptomatology in individuals with cognitive impairment in comparison with those with Alzheimer's disease. Materials and Methods: This study encompassed 5354 patients with cognitive impairments such as Alzheimer's disease (n 1889) and mild cognitive impairment (n = 3464). The geriatric depression scale, a self-administered questionnaire, was employed to assess depressive symptomatology. Using exploratory graph analysis (EGA), a network analysis was conducted, and the network structure was evaluated through regularized partial correlation models. To determine the centrality of depressive symptoms within each cohort, network parameters such as strength, betweenness, and closeness were examined. Additionally, to explore differences in the network structure between Alzheimer's disease and mild cognitive impairment groups, a network comparison test was performed. Results: In the analysis of centrality indices, "worthlessness" was identified as the most central symptom in the geriatric depression scale among patients with Alzheimer's disease, whereas "emptiness" was found to be the most central symptom in patients with mild cognitive impairment. Despite these differences in central symptoms, the comparative analysis showed no statistical difference in the overall network structure between Alzheimer's disease and mild cognitive impairment groups. Conclusions: Findings of this study could contribute to a better understanding of the manifestation of depressive symptoms in patients with cognitive impairment. These results are expected to aid in identifying and prioritizing core symptoms in these patients. Further research should be conducted to explore potential interventions tailored to these core symptoms in patients with Alzheimer's disease and mild cognitive impairment. Establishing core symptoms in those groups might have clinical importance in that appropriate treatment for neuropsychiatric symptoms in patients with cognitive impairment could help preclude progression to further impairment.

Network structure of symptomatology of adult attention-deficit hyperactivity disorder in patients with mood disorders.

Patients with mood disorders commonly manifest comorbid psychiatric disorders, including attention-deficit/hyperactivity disorder (ADHD). However, few studies have evaluated ADHD symptoms in this population. The current study aimed to explore the network structure of ADHD symptomology and identify central symptoms in patients with mood disorders. The Korean version of the Adult ADHD Self-Report Scale was used to assess the overall ADHD symptoms in 1,086 individuals diagnosed with mood disorders (major depressive disorder [n = 373], bipolar I disorder [n = 314], and bipolar II disorder [n = 399]). We used exploratory graph analysis to detect the number of communities, and the network structure was analyzed using regularized partial correlation models. We identified the central ADHD symptom using centrality indices. Network comparison tests were conducted with different subgroups of patients with mood disorders, including three mood diagnosis groups, between the patients who met the diagnostic criteria for ADHD [ADHD-suspected, n = 259] in their self-report and the others [ADHD-non-suspected, n = 827], and groups with high [n = 503] versus low [n = 252] levels of depressive state. The network analysis detected four communities: disorganization, agitation/restlessness, hyperactivity/impulsivity, and inattention. The centrality indices indicated that "feeling restless" was the core ADHD symptom. The result was replicated in the subgroup analyses within our clinically diverse population of mood disorders, encompassing three presentations: Patients with suspected ADHD, patients without suspected ADHD, and patients with a high depressive state. Our findings reveal that "feeling restless" is the central ADHD symptom. The treatment intervention for "feeling restless" may thus play a pivotal role in tackling ADHD symptoms in adult patients with mood disorders.

Understanding of Depressive Symptomatology across Major Depressive Disorder and Bipolar Disorder: A Network Analysis.

Background and Objectives: Depressive symptoms are prominent in both major depressive disorder (MDD) and bipolar disorder (BD). However, comparative research on the network structure of depressive symptoms in these two diagnostic groups has been limited. This study aims to compare the network structure of depressive symptoms in MDD and BD, providing a deeper understanding of the depressive symptomatology of each disorder. Materials and Methods: The Zung Self-Rating Depressive Scale, a 20-item questionnaire, was administered to assess the depressive symptoms in individuals with MDD (n = 322) and BD (n = 516). A network analysis was conducted using exploratory graph analysis (EGA), and the network structure was analyzed using regularized partial correlation models. To validate the dimensionality of the Zung SDS, principal component analysis (PCA) was adopted. Centrality measures of the depressive symptoms within each group were assessed, followed by a network comparison test between the two groups. Results: In both diagnostic groups, the network analysis revealed four distinct categories, aligning closely with the PCA results. "Depressed affect" emerged as the most central symptom in both MDD and BD. Furthermore, non-core symptoms, "Personal devaluation" in MDD and "Confusion" in BD, displayed strong centrality. The network comparison test did not reveal significant differences in the network structure between MDD and BD. Conclusions: The absence of significant differences in the network structures between MDD and BD suggests that the underlying mechanisms of depressive symptoms may be similar across these disorders. The identified central symptoms, including "Depressed affect", in both disorders and the distinct non-core symptoms in each highlight the complexity of the depressive symptomatology. Future research should focus on validating these symptoms as therapeutic targets and incorporate various methodologies, including non-metric dimension reduction techniques or canonical analysis.

The Effects of Microbial Additive Supplementation on Growth Performance, Blood Metabolites, Fecal Microflora, and Carcass Characteristics of Growing-Finishing Pigs.

This study aimed to assess the effects of microbial additives that produce antimicrobial and digestive enzymes on the growth performance, blood metabolites, fecal microflora, and carcass characteristics of growing-finishing pigs. A total of 180 growing-finishing pigs (Landrace × Yorkshire × Duroc; mixed sex; 14 weeks of age; 58.0 ± 1.00 kg) were then assigned to one of three groups with three repetitions (20 pigs) per treatment for 60 days of adaptation and 7 days of collection. Dietary treatments included 0, 0.5, and 1.0% microbial additives in the basal diet. For growth performance, no significant differences in the initial and final weights were observed among the dietary microbial additive treatments, except for the average daily feed intake, average daily gain, and feed efficiency. In terms of blood metabolites and fecal microflora, immunoglobulin G (IgG), blood urea nitrogen, blood glucose, and fecal lactic acid bacteria count increased linearly, and fecal E. coli counts decreased linearly with increasing levels of microbial additives but not growth hormones and Salmonella. Carcass quality grade was improved by the microbial additive. In addition, carcass characteristics were not influenced by dietary microbial additives. In conclusion, dietary supplementation with 1.0% microbial additive improved average daily gain, feed efficiency, IgG content, and fecal microflora in growing-finishing pigs.

Network Structure of Interpersonal Sensitivity in Patients With Mood Disorders: A Network Analysis.

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.

Effect of Impurities Control on the Crystallization and Densification of Polymer-Derived SiC Fibers.

The polymer-derived SiC fibers are mainly used as reinforcing materials for ceramic matrix composites (CMCs) because of their excellent mechanical properties at high temperature. However, decomposition reactions such as release of SiO and CO gases and the formation of pores proceed above 1400 °C because of impurities introduced during the curing process. In this study, polycrystalline SiC fibers were fabricated by applying iodine-curing method and using controlled pyrolysis conditions to investigate crystallization and densification behavior. Oxygen and iodine impurities in amorphous SiC fibers were reduced without pores by diffusion and release to the fiber surface depending on the pyrolysis time. In addition, the reduction of the impurity content had a positive effect on the densification and crystallization of polymer-derived SiC fibers without a sintering aid above the sintering temperature. Consequently, dense Si-Al-C-O polycrystalline fibers containing ß-SiC crystal grains of 50~100 nm were easily fabricated through the blending method and controlled pyrolysis conditions.

Impact of Supplementary Microbial Additives Producing Antimicrobial Substances and Digestive Enzymes on Growth Performance, Blood Metabolites, and Fecal Microflora of Weaning Pigs.

The present study investigated the effects of microbial additives producing antimicrobial and digestive-enzyme activities on the growth performance, blood metabolites, and fecal microflora of weaning pigs from 21 to 42 d of age. A total of 144 weaning pigs (1:1 ratio of gilt and boar; 21 d of age; 7.40 ± 0.53 kg of average body weight) were randomly distributed into four supplementary levels of microbial additive (0 vs. 0.5 vs. 1.0 vs. 1.5% of fresh weight) with three pens of replication, consisting of 12 weaning pigs per pen. All weaning pigs were maintained with the same basal diet for 21 d. Blood and feces were subsampled at day 21. Feed efficiency tended to increase linearly (p = 0.069) with an increasing supplementation level. Insulin, insulin-like growth factor 1, and blood glucose presented a quadratic effect (p < 0.05) with an increasing supplementation level, and these blood metabolites were highest at the 1% supplementation level. Immunoglobulin G in blood increased linearly by (p < 0.05) increasing the supplementation level. Salmonella and Escherichia coli in feces were decreased linearly by (p < 0.05) increasing the supplementation level. In conclusion, supplementation of microbial additive at 1.0% improved the feed efficiency, blood metabolites, and fecal microflora of weaning pigs.