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노화 멜라닌세포가 각질형성세포의 기능적 특성에 미치는 영향
No full textDoctorINTRODUCTION 1
MATERIALS AND METHODS 3
RESULTS 9
A. Chronic UVB exposure induces melanocyte senescence 9
B. Impact of UVB-induced senescent melanocytes on keratinocyte dynamics 15
C. Influence of senescent melanocytes on surrounding keratinocytes in senile lentigo 30
D. Stimulatory factors secreted by senescent melanocytes trigger changes in keratinocyte function and skin barrier integrity 41
DISCUSSION 45
CONCLUSION 4
Impact of Patient Head Posture on Lens Radiation Exposure During Cerebral Angiography
No full textBACKGROUND AND PURPOSE: Cerebral angiography remains crucial for detailed characterization and preoperative assessments for intracranial aneurysm. Despite its diagnostic importance, cerebral angiography poses challenges due to its invasiveness, the risk of neurologic complications, and radiation exposure. To investigate the impact of head posture on lens radiation exposure during cerebral angiography, this study focused on the correlation between radiation doses to the eye lens, head flexion angles, and head size. MATERIALS AND METHODS: A retrospective analysis was performed on 20 patients who underwent cerebral angiography for unruptured intracranial aneurysms between October and November 2022. Radiation doses to the lens, which were measured in a prior prospective study by using photoluminescent glass dosimeters, were analyzed alongside head flexion angles, anterior-posterior (AP) head diameters, and kerma-area product (KAP) to evaluate their correlation with lens radiation exposure. The lateral radiation source is located on the left side of the patients. RESULTS: The cohort consisted of 20 patients (60% women, mean age: 62.3 6 9.9 years). The radiation dose to the left eye (the eye closer to the x-ray source) was 2.8 times higher than that to the right eye (9.18 6 3.31 mGy versus 3.3 6 0.60 mGy, P, .001). A strong positive correlation was observed between the left eye lens dose and head flexion angle (R = 0.815, P, .001). While the AP head diameter correlated significantly with the flexion angle, it showed no significant correlation with lens dose. The KAP was inversely correlated with both the left lens dose (R = -0.597, P = .005) and the flexion angle (R = -0.689, P, .001). CONCLUSIONS: Our findings underscore the meaningful impact of head posture on lens radiation exposure during cerebral angiography. Adjusting head positioning may provide a practical approach to reduce radiation exposure to the lens. Furthermore, it is worth noting that the left lens received more radiation than the right, likely due to the x-ray source being on the left side of the patient
Comprehensive molecular characterization to predict immunotherapy response in advanced biliary tract cancer: a phase II trial of pembrolizumab
No full textBackground: Immune checkpoint inhibitors (ICIs) are effective in a subset of patients with metastatic solid tumors. However, the patients who would benefit most from ICIs in biliary tract cancer (BTC) are still controversial. Materials and methods: We molecularly characterized tissues and blood from 32 patients with metastatic BTC treated with the ICI pembrolizumab as second-line therapy. Results: All patients had microsatellite stable (MSS) type tumors. Three of the 32 patients achieved partial response (PR), with an objective response rate (ORR) of 9.4% (95% confidence interval [CI], 2.0–25.2) and nine showed stable disease (SD), exhibiting a disease control rate (DCR) of 37.5% (95% CI, 21.1–56.3). For the 31 patients who had access to PD-1 ligand 1 (PD-L1) combined positive score (CPS) testing (cut-off value ≥1%), the ORR was not different between those who had PD-L1-positive (PD-L1+; 1/11, 9.1%) and PDL1-(2/20, 10.0%) tumors (p = 1.000). The tumor mutational burden (TMB) of PD-L1+ BTC was comparable to that of PD-L1-BTC (p = 0.630). TMB and any exonic somatic mutations were also not predictive of pembrolizumab response. Molecular analysis of blood and tumor samples demonstrated a relatively high natural killer (NK) cell proportion in the peripheral blood before pembrolizumab treatment in patients who achieved tumor response. Moreover, the tumors of these patients presented high enrichment scores for NK cells, antitumor cytokines, and Th1 signatures, and a low enrichment score for cancer-associated fibroblasts. Conclusions: This study shows the molecular characteristics associated with the efficacy of pembrolizumab in BTC of the MSS type
AntiT2DMP-Pred: Leveraging feature fusion and optimization for superior machine learning prediction of type 2 diabetes mellitus
No full textPancreatic α-amylase breaks down starch into isomaltose and maltose, which are further hydrolyzed by α-glucosidase in the intestine into monosaccharides, rapidly raising blood sugar levels and contributing to type 2 diabetes mellitus (T2DM). Synthetic inhibitors of carbohydrate-digesting enzymes are used to manage T2DM but may harm organ function over time. Bioactive peptides offer a safer alternative, avoiding such adverse effects. Computational methods for predicting antidiabetic peptides (ADPs) can significantly reduce the time and cost of experimental testing. While machine learning (ML) has been applied to identify ADPs, advancements in data analysis and algorithms continue to drive progress in the field. To address this, we developed AntiT2DMP-Pred, the first ML-based tool specifically designed for predicting type 2 antidiabetic peptides (T2ADPs). This tool employs a feature fusion strategy, combining ten highly discriminative feature descriptors chosen from a pool of 32 descriptors and eight ML algorithms, tested across a range of baseline models. AntiT2DMP-Pred demonstrated excellent performance, surpassing both baseline and feature-optimized models, with an accuracy (ACC) and Matthews’ correlation coefficient (MCC) of 0.976 and 0.953 on the training dataset, and an ACC and MCC of 0.957 and 0.851 on the independent dataset. The web server (https://balalab-skku.org/AntiT2DMP-Pred) is freely accessible, enabling researchers worldwide to utilize it in their experimental workflows and contribute to the discovery and understanding of T2ADPs, ultimately supporting peptide-based therapeutic development for diabetes management
The urgent need for multidisciplinary approaches in managing alcohol-associated liver disease: Editorial on “The prognostic impact of psychiatric intervention on alcohol-associated liver disease: The UK Biobank cohort study”
No full textThe COVID-19 pandemic and clinical characteristics of colorectal cancer: a multicenter retrospective study
No full textThe spread of COVID-19 has led to numerous hospitals prioritizing case management and to delays in diagnosis and treatment. Consequently, many cancer patients have developed life-threatening complications during the COVID-19 pandemic. The aim of this study was to investigate the impact of COVID-19 pandemic on colorectal cancer (CRC), including its clinical and pathologic characteristics. This multicenter cohort study was performed at six institutions in Korea and included a total of 3871 patients with CRC treated between March 2019 and February 2021. After exclusion of 211 patients who did not undergo surgery, the data of 3660 patients were compared 1 year before and after the COVID-19 pandemic. The patients' baseline characteristics, CRC-related complications, perioperative outcomes including emergency surgery, R0 resection rates, stoma formations, postoperative complications, and pathologic outcomes were assessed. The number of patients decreased during the pandemic (- 18.0%, from 2127 to 1744), but the baseline characteristics did not differ. The pandemic group had greater disease severity given the presence of bleeding, perforation, and obstruction as complications (9.8% vs. 12.7%, P = 0.033). The proportion of patients who had open surgery (15.9% vs. 17.6%, P = 0.049), stoma formation (11.9% vs. 15.4%, P < 0.001), early postoperative complications (13.5% vs. 17.5%, P = 0.001), and adjuvant chemotherapy increased in the pandemic group (45.5% vs. 50.1%, P = 0.003). The clinical and pathologic features of CRC partly worsened during the pandemic. Healthcare providers and governments should prepare to encounter patients with CRC having poor clinical features for years and encourage people to participate in cancer screening programs. The Clinical Research Information Service (No. KCT0008063), January 2, 2023, retrospectively registered
중증 정신질환자의 내재화된 낙인 감소 비약물적 중재의 효과: 체계적 문헌고찰 및 메타분석
No full textPURPOSE: This study systematically reviewed and analyzed the effects of non-pharmacological interventions on internalized stigma among people with severe mental illness. METHODS: A systematic review and meta-analysis were conducted following the Cochrane Intervention Research Systematic Review Manual and Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines. This study targeted people with severe mental illness as the population, interventions aimed at reducing internalized stigma, comparisons with control groups, and internalized stigma as the outcome. A literature search was performed across multiple databases, including PubMed, EMBASE, the Cochrane Library, CINAHL, PsycArticles, RISS, KMbase, and KoreaMed. The risk of bias was evaluated using the Cochrane Risk of Bias 2.0 tool. Effect sizes were computed using Hedges's g, and subgroup analyses were conducted with Comprehensive Meta-Analysis software version 4.0. RESULTS: Of 2,388 papers, 15 were included in the meta-analysis. The overall effect size (Hedges's g) of the intervention was -0.60 (95% confidence interval, -1.01 to -0.19), indicating a statistically significant reduction in internalized stigma (Z=-2.88, p=.004). Subgroup analyses revealed that the intervention type (p=.008) and session length (p=.011) were significant moderators influencing the effectiveness of the interventions. CONCLUSION: Tailoring interventions by considering variables such as the intervention type and session length could enhance the effectiveness of non-pharmacological interventions for reducing internalized stigma among people with severe mental illness (PROSPERO: CRD42023418561)
Clinical Relevance of Discordance Between Physiology- and Imaging-Guided PCI Strategies in Intermediate Coronary Stenosis
No full textBackground: Recent randomized clinical trials have demonstrated the benefits of intravascular imaging (IVI)-guided percutaneous coronary intervention (PCI) over angiography-guided PCI. However, the role of angiography-based physiological assessment during IVI-guided PCI remains unclear. Objectives: This study aimed to explore the discrepancies and significance of angiography-based physiological assessments in IVI-guided PCI. Methods: In the international multicenter randomized FLAVOUR (Fractional Flow Reserve and Intravascular Ultrasound for Clinical Outcomes in Patients With Intermediate Stenosis) trial, angiography-based physiological assessment was retrospectively performed using the Murray law–based quantitative flow ratio (μQFR). In this post hoc analysis, patients were categorized based on intravascular ultrasound (IVUS)-guided treatment decisions (PCI or deferral) and μQFR as follows: negative μQFR with deferral of PCI (DEFER), negative μQFR with PCI (PERFORM), and positive μQFR with PCI (REFERENCE). The primary outcome was major adverse cardiovascular events, defined as a composite of death, myocardial infarction, and target vessel revascularization at the 24-month follow-up. Results: Of the 784 patients, 34.4% (270/784), 29.3% (230/784), and 31.5% (247/784) were categorized into the DEFER, PERFORM, and REFERENCE groups, respectively. Physiological assessment led to substantial reclassification, encompassing 48.2% (230/477) of patients who underwent IVUS-guided PCI. The REFERENCE group showed a higher risk for major adverse cardiovascular events at 2 years compared with the PERFORM group (adjusted HR: 2.46; 95% CI: 1.13-5.35; P = 0.023). However, the primary outcomes in the DEFER and PERFORM groups were similar (adjusted HR: 0.88; 95% CI: 0.37-2.11; P = 0.779). The quality of life at 2 years was comparable among the 3 groups (P = 0.198). Conclusions: Angiography-based physiological assessments can offer additional prognostic insights for patients undergoing IVI-guided PCI. IVUS-guided PCI may not be advantageous in patients with functionally insignificant lesions
Artificial Intelligence-Based Early Prediction of Acute Respiratory Failure in the Emergency Department Using Biosignal and Clinical Data
No full textPURPOSE: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using high-resolution biosignals collected within 4 h of arrival. MATERIALS AND METHODS: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. RESULTS: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. CONCLUSION: Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction
Large-Scale Validation of the Feasibility of GPT-4 as a Proofreading Tool for Head CT Reports
No full textBackground: The increasing workload of radiologists can lead to burnout and errors in radiology reports. Large language models, such as OpenAI's GPT-4, hold promise as error revision tools for radiology. Purpose: To test the feasibility of GPT-4 use by determining its error detection, reasoning, and revision performance on head CT reports with varying error types and to validate its clinical utility by comparison with human readers. Materials and Methods: A total of 10 300 head CT reports were retrospectively extracted from the Medical Information Mart for Intensive Care III public dataset. In experiment 1, among the 300 unaltered reports and 300 versions with applied errors, GPT-4 optimization was initially conducted with 200 reports. The remaining 400 were used for evaluation of error type detection, reasoning, and revision, as well as the analysis of reports with undetected errors. The performance was also compared with that of human readers. In experiment 2, the detection performance of GPT-4 was validated on 10 000 unaltered reports that were deemed error-free by physicians, and an analysis of false-positive results was conducted. A permutation test was conducted to assess differences in performance. Results: GPT-4 demonstrated commendable performance in error detection (sensitivity, 84% for interpretive error and 89% for factual error), reasoning, and revision. Compared with GPT-4, human readers had worse factual error detection sensitivity (0.33-0.69 vs 0.89; P = .008 for radiologist 4, P < .001 for others) and took longer to review (82-121 seconds vs 16 seconds, P < .001). In 10 000 reports, GPT-4 detected 96 errors, with a low positive predictive value of 0.05, yet 14% of the false-positive responses were potentially beneficial. Conclusion: GPT-4 effectively detects, reasons, and revises errors in radiology reports. While it shows excellent performance in identifying factual errors, its ability to prioritize clinically significant findings is limited. Recognizing its strengths and limitations, GPT-4 could serve as a feasible tool