Objectives: This study aimed to evaluate the correlation between mast cell (MC) density in rosacea-affected skin and the expression of key inflammatory mediators, including IL-6, TNF-α, and cathelicidin LL-37. By comparing lesions rich in MCs with those having fewer MCs, we sought to elucidate the role of MCs in the inflammatory mechanisms underlying rosacea pathogenesis.

Methods: Specimens were collected from 20 patients diagnosed with rosacea who attended the outpatient clinic between 2008 and 2013. Each specimen underwent staining using hematoxylin/eosin, Giemsa, IL-6, LL-37, and TNF-α for both histopathological and immunohistochemical analyses. The number of stained cells was counted across 10 randomly selected dermal layers at a magnification of ×400 using light microscopy. The results were categorized based on the number of MCs counted: more than 10 MCs were classified as MC-rich, and 10 or fewer MCs as MC-poor.

Results: Among the 20 patients (10 MC-rich and 10 MC-poor), the MC-rich group demonstrated significantly higher MC counts than the MC-poor group (P<0.001). However, there were no significant differences in the expression levels of IL-6, LL-37, or TNF-α between the two groups. Additionally, MC density did not show any significant associations with patient demographics, clinical characteristics, or systemic comorbidities.

Conclusion: Increased MC density was not associated with differences in IL-6, TNF-α, or LL-37 expression in rosacea lesions. These findings suggest that MC infiltration may not directly influence the inflammatory mediator profile in rosacea. Further research is required to identify distinctive pathological features or markers that can elucidate the mechanisms of rosacea.

Purpose: Cancer poses a significant global health challenge, demanding precise genomic testing for individualized treatment strategies. Targeted-panel sequencing (TPS) has improved personalized oncology but often lacks comprehensive coverage of crucial cancer alterations. Whole-genome sequencing (WGS) addresses this gap, offering extensive genomic testing. This study demonstrates the medical potential of WGS. Materials and Methods: This study evaluates target-enhanced WGS (TE-WGS), a clinical-grade WGS method sequencing both cancer and matched normal tissues. Forty-nine patients with various solid cancer types underwent both TE-WGS and TruSight Oncology 500 (TSO500), one of the mainstream TPS approaches. Results: TE-WGS detected all variants reported by TSO500 (100%, 498/498). A high correlation in variant allele fractions was observed between TE-WGS and TSO500 (r=0.978). Notably, 223 variants (44.8%) within the common set were discerned exclusively by TE-WGS in peripheral blood, suggesting their germline origin. Conversely, the remaining subset of 275 variants (55.2%) were not detected in peripheral blood using the TE-WGS, signifying them as bona fide somatic variants. Further, TE-WGS provided accurate copy number profiles, fusion genes, microsatellite instability, and homologous recombination deficiency scores, which were essential for clinical decision-making. Conclusion TE-WGS is a comprehensive approach in personalized oncology, matching TSO500’s key biomarker detection capabilities. It uniquely identifies germline variants and genomic instability markers, offering additional clinical actions. Its adaptability and cost-effectiveness underscore its clinical utility, making TE-WGS a valuable tool in personalized cancer treatment.

Objectives: This study aimed to evaluate the correlation between mast cell (MC) density in rosacea-affected skin and the expression of key inflammatory mediators, including IL-6, TNF-α, and cathelicidin LL-37. By comparing lesions rich in MCs with those having fewer MCs, we sought to elucidate the role of MCs in the inflammatory mechanisms underlying rosacea pathogenesis.

Methods: Specimens were collected from 20 patients diagnosed with rosacea who attended the outpatient clinic between 2008 and 2013. Each specimen underwent staining using hematoxylin/eosin, Giemsa, IL-6, LL-37, and TNF-α for both histopathological and immunohistochemical analyses. The number of stained cells was counted across 10 randomly selected dermal layers at a magnification of ×400 using light microscopy. The results were categorized based on the number of MCs counted: more than 10 MCs were classified as MC-rich, and 10 or fewer MCs as MC-poor.

Results: Among the 20 patients (10 MC-rich and 10 MC-poor), the MC-rich group demonstrated significantly higher MC counts than the MC-poor group (P<0.001). However, there were no significant differences in the expression levels of IL-6, LL-37, or TNF-α between the two groups. Additionally, MC density did not show any significant associations with patient demographics, clinical characteristics, or systemic comorbidities.

Conclusion: Increased MC density was not associated with differences in IL-6, TNF-α, or LL-37 expression in rosacea lesions. These findings suggest that MC infiltration may not directly influence the inflammatory mediator profile in rosacea. Further research is required to identify distinctive pathological features or markers that can elucidate the mechanisms of rosacea.

Objectives: This study aimed to evaluate the correlation between mast cell (MC) density in rosacea-affected skin and the expression of key inflammatory mediators, including IL-6, TNF-α, and cathelicidin LL-37. By comparing lesions rich in MCs with those having fewer MCs, we sought to elucidate the role of MCs in the inflammatory mechanisms underlying rosacea pathogenesis.

Methods: Specimens were collected from 20 patients diagnosed with rosacea who attended the outpatient clinic between 2008 and 2013. Each specimen underwent staining using hematoxylin/eosin, Giemsa, IL-6, LL-37, and TNF-α for both histopathological and immunohistochemical analyses. The number of stained cells was counted across 10 randomly selected dermal layers at a magnification of ×400 using light microscopy. The results were categorized based on the number of MCs counted: more than 10 MCs were classified as MC-rich, and 10 or fewer MCs as MC-poor.

Results: Among the 20 patients (10 MC-rich and 10 MC-poor), the MC-rich group demonstrated significantly higher MC counts than the MC-poor group (P<0.001). However, there were no significant differences in the expression levels of IL-6, LL-37, or TNF-α between the two groups. Additionally, MC density did not show any significant associations with patient demographics, clinical characteristics, or systemic comorbidities.

Conclusion: Increased MC density was not associated with differences in IL-6, TNF-α, or LL-37 expression in rosacea lesions. These findings suggest that MC infiltration may not directly influence the inflammatory mediator profile in rosacea. Further research is required to identify distinctive pathological features or markers that can elucidate the mechanisms of rosacea.

Purpose: Cancer poses a significant global health challenge, demanding precise genomic testing for individualized treatment strategies. Targeted-panel sequencing (TPS) has improved personalized oncology but often lacks comprehensive coverage of crucial cancer alterations. Whole-genome sequencing (WGS) addresses this gap, offering extensive genomic testing. This study demonstrates the medical potential of WGS. Materials and Methods: This study evaluates target-enhanced WGS (TE-WGS), a clinical-grade WGS method sequencing both cancer and matched normal tissues. Forty-nine patients with various solid cancer types underwent both TE-WGS and TruSight Oncology 500 (TSO500), one of the mainstream TPS approaches. Results: TE-WGS detected all variants reported by TSO500 (100%, 498/498). A high correlation in variant allele fractions was observed between TE-WGS and TSO500 (r=0.978). Notably, 223 variants (44.8%) within the common set were discerned exclusively by TE-WGS in peripheral blood, suggesting their germline origin. Conversely, the remaining subset of 275 variants (55.2%) were not detected in peripheral blood using the TE-WGS, signifying them as bona fide somatic variants. Further, TE-WGS provided accurate copy number profiles, fusion genes, microsatellite instability, and homologous recombination deficiency scores, which were essential for clinical decision-making. Conclusion TE-WGS is a comprehensive approach in personalized oncology, matching TSO500’s key biomarker detection capabilities. It uniquely identifies germline variants and genomic instability markers, offering additional clinical actions. Its adaptability and cost-effectiveness underscore its clinical utility, making TE-WGS a valuable tool in personalized cancer treatment.

Objectives: This study aimed to evaluate the correlation between mast cell (MC) density in rosacea-affected skin and the expression of key inflammatory mediators, including IL-6, TNF-α, and cathelicidin LL-37. By comparing lesions rich in MCs with those having fewer MCs, we sought to elucidate the role of MCs in the inflammatory mechanisms underlying rosacea pathogenesis.

Methods: Specimens were collected from 20 patients diagnosed with rosacea who attended the outpatient clinic between 2008 and 2013. Each specimen underwent staining using hematoxylin/eosin, Giemsa, IL-6, LL-37, and TNF-α for both histopathological and immunohistochemical analyses. The number of stained cells was counted across 10 randomly selected dermal layers at a magnification of ×400 using light microscopy. The results were categorized based on the number of MCs counted: more than 10 MCs were classified as MC-rich, and 10 or fewer MCs as MC-poor.

Results: Among the 20 patients (10 MC-rich and 10 MC-poor), the MC-rich group demonstrated significantly higher MC counts than the MC-poor group (P<0.001). However, there were no significant differences in the expression levels of IL-6, LL-37, or TNF-α between the two groups. Additionally, MC density did not show any significant associations with patient demographics, clinical characteristics, or systemic comorbidities.

Conclusion: Increased MC density was not associated with differences in IL-6, TNF-α, or LL-37 expression in rosacea lesions. These findings suggest that MC infiltration may not directly influence the inflammatory mediator profile in rosacea. Further research is required to identify distinctive pathological features or markers that can elucidate the mechanisms of rosacea.

Purpose: Cancer poses a significant global health challenge, demanding precise genomic testing for individualized treatment strategies. Targeted-panel sequencing (TPS) has improved personalized oncology but often lacks comprehensive coverage of crucial cancer alterations. Whole-genome sequencing (WGS) addresses this gap, offering extensive genomic testing. This study demonstrates the medical potential of WGS. Materials and Methods: This study evaluates target-enhanced WGS (TE-WGS), a clinical-grade WGS method sequencing both cancer and matched normal tissues. Forty-nine patients with various solid cancer types underwent both TE-WGS and TruSight Oncology 500 (TSO500), one of the mainstream TPS approaches. Results: TE-WGS detected all variants reported by TSO500 (100%, 498/498). A high correlation in variant allele fractions was observed between TE-WGS and TSO500 (r=0.978). Notably, 223 variants (44.8%) within the common set were discerned exclusively by TE-WGS in peripheral blood, suggesting their germline origin. Conversely, the remaining subset of 275 variants (55.2%) were not detected in peripheral blood using the TE-WGS, signifying them as bona fide somatic variants. Further, TE-WGS provided accurate copy number profiles, fusion genes, microsatellite instability, and homologous recombination deficiency scores, which were essential for clinical decision-making. Conclusion TE-WGS is a comprehensive approach in personalized oncology, matching TSO500’s key biomarker detection capabilities. It uniquely identifies germline variants and genomic instability markers, offering additional clinical actions. Its adaptability and cost-effectiveness underscore its clinical utility, making TE-WGS a valuable tool in personalized cancer treatment.

Objectives: This study aimed to evaluate the correlation between mast cell (MC) density in rosacea-affected skin and the expression of key inflammatory mediators, including IL-6, TNF-α, and cathelicidin LL-37. By comparing lesions rich in MCs with those having fewer MCs, we sought to elucidate the role of MCs in the inflammatory mechanisms underlying rosacea pathogenesis.

Methods: Specimens were collected from 20 patients diagnosed with rosacea who attended the outpatient clinic between 2008 and 2013. Each specimen underwent staining using hematoxylin/eosin, Giemsa, IL-6, LL-37, and TNF-α for both histopathological and immunohistochemical analyses. The number of stained cells was counted across 10 randomly selected dermal layers at a magnification of ×400 using light microscopy. The results were categorized based on the number of MCs counted: more than 10 MCs were classified as MC-rich, and 10 or fewer MCs as MC-poor.

Results: Among the 20 patients (10 MC-rich and 10 MC-poor), the MC-rich group demonstrated significantly higher MC counts than the MC-poor group (P<0.001). However, there were no significant differences in the expression levels of IL-6, LL-37, or TNF-α between the two groups. Additionally, MC density did not show any significant associations with patient demographics, clinical characteristics, or systemic comorbidities.

Conclusion: Increased MC density was not associated with differences in IL-6, TNF-α, or LL-37 expression in rosacea lesions. These findings suggest that MC infiltration may not directly influence the inflammatory mediator profile in rosacea. Further research is required to identify distinctive pathological features or markers that can elucidate the mechanisms of rosacea.

Background: Bulky or multiple lymph node (LN) metastases are associated with poor prognosis in cervical cancer, and the size or number of LN metastases is not yet reflected in the staging system and therapeutic strategy. Although the therapeutic effects of surgical resection of bulky LNs before standard treatment have been reported in several retrospective studies, wellplanned randomized clinical studies are lacking. Therefore, the aim of the Korean Gynecologic Oncology Group (KGOG) 1047/DEBULK trial is to investigate whether the debulking surgery of bulky or multiple LNs prior to concurrent chemoradiation therapy (CCRT) improves the survival rate of patients with cervical cancer IIICr diagnosed by imaging tests. Methods The KGOG 1047/DEBULK trial is a phase III, multicenter, randomized clinical trial involving patients with bulky or multiple LN metastases in cervical cancer IIICr. This study will include patients with a short-axis diameter of a pelvic or para-aortic LN ≥2 cm or ≥3 LNs with a short-axis diameter ≥1 cm and for whom CCRT is planned. The treatment arms will be randomly allocated in a 1:1 ratio to either receive CCRT (control arm) or undergo surgical debulking of bulky or multiple LNs before CCRT (experimental arm). CCRT consists of extended-field external beam radiotherapy/pelvic radiotherapy, brachytherapy and LN boost, and weekly chemotherapy with cisplatin (40 mg/m 2 ), 4–6 times administered intravenously.The primary endpoint will be 3-year progression-free survival rate. The secondary endpoints will be 3-year overall survival rate, treatment-related complications, and accuracy of radiological diagnosis of bulky or multiple LNs.

Purpose: Recently, deep learning techniques have been introduced for age estimation, with automated methods based on radiographic analysis demonstrating high accuracy. In this study, we applied convolutional neural network (CNN) techniques to the lower dentition area on orthopantomograms (OPGs) of children to develop an automated age estimation model and evaluate its accuracy for use in forensic dentistry. Methods: In this study, OPGs of 2,856 subjects aged 3-14 years were analyzed. The You Only Look Once (YOLO) V8 object detection technique was applied to extract the mandibular dentition area on OPGs, designating it as the region of interest (ROI). First, 200 radiographs were randomly selected, and were used to train a model for extracting the ROI. The trained model was then applied to the entire dataset. For the CNN image classification task, 80% of OPGs were allocated to the training set, while the remaining 20% were used as the test set. A transfer learning approach was employed using the ResNet50 and VGG19 backbone models, with an ensemble technique combining these models to improve performance. The mean absolute error (MAE) on the test set was used as the validation metric, and the model with the lowest MAE was selected. Results: In this study, the age estimation model developed using mandibular dentition region from OPGs achieved MAE and root mean squared error (RMSE) values of 0.501 and 0.742, respectively, on the test set, and MAE and RMSE values of 0.273 and 0.354, respectively, on the training set. Conclusions The automated age estimation model developed in this study demonstrated accuracy comparable to that of previous research and shows potential for applications in forensic investigations. Increasing the sample size and incorporating diverse deep learning techniques are expected to further enhance the accuracy of future age estimation models.