Background: Elevated active glucocorticoids (GCs) are implicated in skin barrier dysfunction, notably in aging and diabetes. The enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) converts inactive GCs to active forms, potentially exacerbating this dysfunction. Objective: We aimed to investigate the impact of a novel 11β-HSD1 inhibitor on skin inflammation using both in vitro and in vivo models. Methods: To elucidate the efficacy of a new 11β-HSD1 inhibitor in mitigating skin inflammation induced by various triggers, including dexamethasone treatment, ultraviolet B irradiation, and high glucose levels, in cultured human keratinocytes and the db/db mice as a type 2 diabetes murine model. In cultured keratinocytes, we assessed the effects of the 11β-HSD1 inhibitor on cortisol levels, 11β-HSD1 expression, and cytokine production under conditions simulating inflammation. In db/db mice, we evaluated the inhibitor’s impact on skin barrier function, hemoglobin A1c (HbA1c) levels, corticosterone levels, 11β-HSD1 expression, and cytokine profiles following a 2-week treatment regimen. Results: Our results demonstrated that both the novel 11β-HSD1 inhibitor and a known inhibitor reduced cortisol levels, 11β-HSD1 expression, and inflammatory cytokine production in cultured keratinocytes. In db/db mice, treatment with either inhibitor improved skin barrier function, lowered serum HbA1c levels, and decreased corticosterone, 11β-HSD1, and inflammatory cytokine expression. Conclusion A new 11β-HSD1 inhibitor, “11b-0048,” showed a significant inhibitory effect on the expression of 11β-HSD1 in keratinocytes activated by various conditions and diabetic skin.

Objective: Patients with panic disorder (PD) are approximately four times more likely to experience suicidal thoughts and attempts compared to healthy controls (HCs). Despite the elevated risk compared to HCs, the relationship between cortical thickness (CT) in PD and suicidality remains underexplored. Methods: We recruited 161 right-handed participants, including 82 PD patients and 79 HCs, and assessed them using a comprehensive battery of psychological scales, including the Scale for Suicidal Ideation (SSI), Early Trauma Inventory Self Report-Short Form, Neuroticism-Extraversion-Openness Personality Inventory-Neuroticism (NEO-N), State-Trait Anxiety Inventory-Trait Anxiety (STAI-T), Panic Disorder Severity Scale (PDSS), and Beck Depression Inventory. Results: In whole-brain vertex-wise group comparison, patients with PD demonstrated significantly lower CT values in the insula, lateral occipital sulcus, and precentral gyrus compared to HCs. Notably, paradoxical significant positive correlations were observed between SSI total scores and CT in the above-mentioned regions within the PD cohort.Pearson’s correlation analyses further indicated that CT in these regions may be linked to high levels of early trauma, trait anxiety (e.g., NEO-N, STAI-T), panic symptom severity (e.g., PDSS), and treatment response in patients with PD. Conclusion This study suggest that suicidality in PD may be associated with CT in specific EFN regions related to suicidal brain and that CT in these regions could play a critical role in anxiety symptomatology in PD.

Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

Background: We investigated whether nutritional intake is associated with physical activity (PA) and handgrip strength (HGS) in individuals with airflow limitation. Methods: This study analyzed data from the 2014 and 2016 Korean National Health and Nutrition Examination Survey. We assessed total protein intake (g/day), caloric intake (kcal/day), and other nutritional intakes, using a 24-hour dietary recall questionnaire. HGS was measured three times for each hand using a digital grip strength dynamometer, and PA was assessed as health-enhancing PA. Airflow limitation was defined as a forced expiratory volume/forced vital capacity ratio of 0.7 in individuals over 40 years of age. Participants were categorized into groups based on their PA levels and HGS measurements: active aerobic PA vs. non-active aerobic PA, and normal HGS vs. low HGS. Results: Among the 622 individuals with airflow limitation, those involved in active aerobic PA and those with higher HGS had notably higher total food, calorie, water, protein, and lipid intake. The correlations between protein and caloric intake with HGS were strong (correlation coefficients=0.344 and 0.346, respectively). The forest plots show that higher intakes of food, water, calories, protein, and lipids are positively associated with active aerobic PA, while higher intakes of these nutrients are inversely associated with low HGS. However, in the multivariate logistic regression analysis, no significant associations were observed between nutritional intake and active aerobic PA or HGS. Conclusion Nutritional intake was found to not be an independent factor associated with PA and HGS. However, the observed correlations suggest potential indirect effects that warrant further investigation.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.

Background: Recurrent gynecological clear cell carcinoma (rGCCC) has a low objective response rate (ORR) to chemotherapy. Previous preclinical and clinical data suggest a potential synergy between immune checkpoint inhibitors and bevacizumab in rGCCC.Dostarlimab, a humanized monoclonal antibody targeting programmed cell death protein 1 (PD-1), combined with the anti-angiogenic bevacizumab, presents a novel therapeutic approach. This study will investigate the efficacy of dostarlimab +/− bevacizumab in rGCCC. Methods DOVE is a global, multicenter, international, open-label, randomized phase 2 study of dostarlimab +/− bevacizumab with standard chemotherapy in rGCCC. We will enroll 198 patients with rGCCC and assign them to one of three groups in a 1:1:1 ratio: arm A (dostarlimab monotherapy), B (dostarlimab + bevacizumab), and C (investigator’s choice of chemotherapy [weekly paclitaxel, pegylated liposomal doxorubicin, doxorubicin, or gemcitabine]). Patients with disease progression in arm A or C will be allowed to cross over to arm B. Stratification factors include prior bevacizumab use, prior lines of therapy (1 vs. >1), and primary site (ovarian vs. non-ovarian). Key inclusion criteria are histologically proven recurrent or persistent clear cell carcinoma of the ovary, endometrium, cervix, vagina, or vulva; up to five prior lines of therapy; disease progression within 12 months after platinumbased chemotherapy; and measurable disease. Key exclusion criteria are prior treatment with an anti–PD-1, anti–programmed death-ligand 1, or anti–programmed death-ligand 2 agent.The primary endpoint is progression-free survival determined by investigators. Secondary endpoints are ORR, disease control rate, clinical benefit rate, progression-free survival 2, overall survival, and toxicity. Exploratory objectives include immune biomarkers.

Background: The 16S rRNA-targeted next-generation sequencing (NGS) has been widely used as the primary tool for microbiome analysis. However, whether the sequenced microbial diversity absolutely represents the original sample composition remains unclear. This study aimed to evaluate whether 16S rRNA gene-targeted NGS accurately captures bacterial community composition. Methods: Mock communities were constructed using equal amounts of DNA from 18 bacterial strains in three formats: genomic DNA, recombinant plasmids, and polymerase chain reaction (PCR) templates. The V3V4 region of the 16S rRNA gene was amplified and sequenced using the Illumina MiSeq. Results: Data regression analysis revealed that the recombinant plasmid produced more accurate and precise correlation curve than that by the gDNA and PCR products, with a slope closest to 1 (1.0082) and the highest R² value (0.9975). Despite the same input amount of bacterial DNA, the NGS read distribution varied across all three mock communities. Using multiple regression analysis, we found that the guanine-cytosine (GC) content of the V3V4 region, 16S rRNA gene, size of gDNA, and copy number of 16S rRNA were significantly associated with the NGS output of each bacterial species. Conclusion This study demonstrated that recombinant plasmids are the preferred option for quality control and that NGS output is biased owing to certain bacterial characteristics, such as %GC content, gDNA size, and 16S rRNA gene copy number. Further research is required to develop a system that compensates for NGS process biases using mock communities.