Background: DNA methylation is under investigation as an early diagnostic biomarker for cancers such as hepatocellular carcinoma (HCC). p21-activated protein kinase 1 (PAK1) demonstrates a high methylation tendency in HCC. We assessed the diagnostic and prognostic performance of PAK1 methylation in liver transplantation (LT) recipients with and without HCC. Methods: To assess PAK1 methylation, stored pretransplant blood samples from LT recipients were analyzed by droplet digital polymerase chain reaction. Results: This study included 274 patients with HCC and 100 control patients without the disease. Ten-year survival rates in the HCC and control groups were 60.5% and 80.6%, respectively (P=0.001). The 10-year HCC recurrence rate was 39.0%. Ten-year survival rates in the HCC recurrence and nonrecurrence groups were 13.3% and 91.2%, respectively (P<0.001); median PAK1 methylation levels in the control and HCC groups were 50.0 and 108.0 copies (P=0.102). The area under the receiver operating characteristic curve was 0.599, and the Youden J index was 0.199, indicating 57.9% sensitivity and 62.0% specificity at a cutoff of 78 copies. With a cutoff of 5 copies, sensitivity was 94.1% and specificity was 14.0%. The positive likelihood ratio was 1.09 and the negative likelihood ratio was 0.42, indicating diagnostic accuracy below α-fetoprotein and protein induced by vitamin K absence or antagonist-II. PAK1 cutoffs of 5 and 10 copies did not affect HCC recurrence, but a cutoff of 2 copies appeared associated with lower recurrence. Conclusions These data suggest that PAK1 methylation is not a clinically useful biomarker for HCC in LT recipients. New DNA methylation biomarkers are required for early diagnosis.

Objective: To evaluate the impact of adding CT to ultrasound (US) for nodal assessment in patients with papillary thyroid microcarcinoma (PTMC), particularly in those with US-node-negative disease. Materials and Methods: This single-center retrospective study included consecutive patients with PTMC (≤1 cm on US) who underwent both US and CT for PTMC staging between August 2016 and January 2020, and subsequently underwent surgery including neck dissection. The number of patients with clinical N1 and pathological N1 disease was assessed. The diagnostic performance of US, CT, and combined US + CT (positive if either was positive) for macroscopic lymph node metastasis (LNM) (i.e., metastatic tumor foci >2 mm) was evaluated. Cases with discordant nodal staging between US and CT were identified.The diagnostic utility of CT was also assessed in a subgroup of patients with node-negative findings on US. Results: Among 982 patients (mean age ± standard deviation, 47.3 ± 11.5 years; 774 female), pathological analysis confirmed cervical LNM in 377 patients, including macroscopic, microscopic, and size-unknown LNM in 187, 175, and 15 patients, respectively. The addition of CT to US improved sensitivity for detecting macroscopic LNM compared to US alone (68.4% [128/187] vs. 26.7% [50/187]; P < 0.001), while maintaining high specificity despite a significant decrease (90.9% [709/780] vs. 97.2% [758/780]; P < 0.001). Discordant nodal staging between US and CT regarding macroscopic LNM was observed in 149 cases (15.2% [149/982]), with 131 patients (87.9% [131/149]) being upstaged by CT. In patients with node-negative US findings, CT detected US-undetected macroscopic LNM in 78 patients (8.7% [78/895]) and exhibited a sensitivity of 56.9% (78/137) and specificity of 93.5% (709/758) for macroscopic LNM. Conclusion The integration of CT with US improved sensitivity for detecting macroscopic LNM in patients with PTMC, identifying those who would otherwise be inappropriately considered candidates for active surveillance based solely on US findings. This may assist in refining patient management.

Purpose: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality, necessitating the identification of novel therapeutic targets. The E3 ubiquitin ligase WW domain-containing E3 ubiquitin protein ligase 2 (WWP2) has been implicated in various cancers, yet its specific role and underlying molecular mechanisms in CRC are poorly understood. This study aimed to investigate the functional role of WWP2 in CRC progression and to elucidate its regulatory mechanisms. Methods: WWP2 expression was evaluated in CRC patient tissues and cell lines using immunohistochemistry, quantitative real-time polymerase chain reaction, and western blotting. The biological functions of WWP2 were assessed using in vitro assays for cell proliferation, migration, and invasion following adenovirus-mediated overexpression. The molecular mechanism was investigated by analyzing the protein expression levels of p53 and its downstream target, p21, via western blot. An in vivo xenograft mouse model was used to confirm the oncogenic role of WWP2. Results: WWP2 expression was significantly upregulated in CRC tissues. Overexpression of WWP2 promoted CRC cell proliferation, migration, and invasion. Mechanistically, increased WWP2 expression led to a marked reduction in the protein levels of the tumor suppressor p53. Consequently, the expression of the p53 downstream target, the cell cycle inhibitor p21, was also suppressed. In the xenograft model, WWP2 overexpression significantly enhanced tumor growth. Conclusion Our findings demonstrate that WWP2 functions as an oncogene in CRC. It promotes cancer progression by destabilizing the tumor suppressor p53 and downregulating p21. This study highlights the WWP2-p53-p21 axis as a potential novel therapeutic target for CRC.

This study aimed to develop a predictive model for the early identification of patients at risk of sepsis, using routinely available clinical information and laboratory test results collected during the initial phase of patient care. Methods: This retrospective analysis included electronic medical records of 22,400 adult patients who presented with suspected infection to a tertiary care university hospital in Korea between January 2013 and May 2024. Patients were classified according to Systemic Inflammatory Response Syndrome (score ≥ 2) or Quick Sequential Organ Failure Assessment (score ≥ 2), in combination with sepsis-related International Classification of Diseases, 10th revision codes. Four different machine learning models were trained and validated using five-fold cross-validation. In addition, Shapley additive explanations analysis was performed to interpret the contribution and clinical relevance of key predictive variables. Results: Among the evaluated models, CatBoost demonstrated the strongest predictive performance. Notably, platelet distribution width, alveolar–arterial oxygen difference, procalcitonin, and the arterial/alveolar oxygen ratio consistently emerged as major predictors. Importantly, several variables that did not reach statistical significance in univariate analysis nevertheless contributed substantially to overall model performance, highlighting the importance of complex, multidimensional interactions among clinical factors. Conclusion: These findings indicate that a model based on simple, routinely collected clinical data can achieve high predictive accuracy and strong generalizability. Such a tool may support early clinical decision-making by multidisciplinary teams, including nurses, across diverse real-world care settings. Further prospective studies are warranted to validate its clinical utility and to assess its potential effects on patient outcomes.

Background: Complete revascularization has demonstrated better outcomes in patients with acute myocardial infarction (AMI) and multivessel disease. However, in the case of left main (LM) culprit lesion AMI with multivessel disease, there is limited evidence to suggest that complete revascularization is better. Methods: We reviewed 16,831 patients in the Korea Acute Myocardial Infarction Registry who were treated from July 2016 to June 2020, and 399 patients were enrolled with LM culprit lesion AMI treated with percutaneous coronary intervention. We categorized the patients as those treated with complete revascularization (n=295) or incomplete revascularization (n=104). The study endpoint was major adverse cardiac and cerebrovascular events (MACCE), a composite of all-cause death, myocardial infarction, ischemia-driven revascularization, stent thrombosis, and stroke. We performed propensity score matching (PSM) and analyzed the incidence of MACCE at 1 year. Results: After PSM, the two groups were well balanced. There was no significant difference between the two groups in MACCE at 1 year (12.1% vs. 15.2%; hazard ratio, 1.28; 95% confidence interval, 0.60–2.74; p=0.524) after PSM. The components of MACCE and major bleeding were also not significantly different. Conclusion There was no significant difference in clinical outcomes between the groups treated with complete or incomplete revascularization for LM culprit lesion AMI with multivessel disease.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

PURPOSE: The purpose of this study was to compare the surface characteristics and healing patterns after implantation of implants treated with SLA and those treated with both SLA and femtosecond laser. MATERIALS AND METHODS: A total of 10 male New Zealand white rabbits were used to compare recovery levels between implants treated with SLA (SLA group) and those treated with both SLA and femtosecond laser (SF group). The implants’ surface characteristics were determined through topographic evaluation, element analysis, surface roughness, and wettability evaluation. In total, 4 implants were placed in each rabbit (2 in each tibia), with 20 implants per treatment group. Using the implant stability quotient (ISQ), marginal bone volume, and histological analysis (bone-to-implant contact (BIC), bone volume/tissue volume (BV/TV)), and post implantation outcomes were assessed. Outcome data were analyzed using independent t-tests, Mann-Whitney U tests, Wilcoxon signed-rank tests, and one-way ANOVA (α = 0.05). RESULTS: No significant differences were noted between SLA and SF groups in terms of ISQ, marginal bone volume, BIC, and BV/TV (P > .05). However, significant differences in ISQ were observed within each group over time (P < .05). Furthermore, significant differences were noted in the marginal bone volume of the SF group (P < .05) and the BV/TV of the SLA group between weeks 4 and 6 (P < .05). CONCLUSION Surface treatment via SLA and femtosecond laser is feasible compared with SLA treatment alone in terms of ISQ, marginal bone volume, BIC, and BV/TV. However, further clinical research is warranted.

Renal cell carcinoma (RCC) presents significant clinical challenges, highlighting the importance of understanding its molecular mechanisms. While store-operated Ca2+ entry (SOCE) is known to play an essential role in tumorigenesis and metastasis, its specific implications across various RCC subtypes remain underexplored.This study analyzed SOCE-related mRNA profiles from the KIRC and KIRP projects in The Cancer Genome Atlas (TCGA) database, focusing on differential gene expression and overall survival outcomes. Functional studies in clear cell RCC (Caki-1) and papillary RCC cell lines (pRCC, Caki-2) revealed increased expression of Orai1 and Orai3, along with STIM1, exhibited in both subtypes, with decreased STIM2 and increased Orai2 expression in pRCC. Notably, Orai3 expression had a gender-specific impact on survival, particularly in females with pRCC, where it inversely correlated with STIM2 expression. Functional assays showed Orai3 dominance in Caki-2 and Orai1 in Caki-1. Interestingly, 2-APB inhibited SOCE in Caki-1 but enhanced it in Caki-2, suggesting Orai3 as the primary SOCE channel in pRCC. Knockdown of Orai1 and Orai3 reduced cell migration and proliferation via regulating focal adhesion kinase (FAK) and Cyclin D1 in both cell lines. These findings highlight the critical roles of Orai1 and Orai3 in RCC metastasis, with Orai3 linked to poorer prognosis in females with pRCC. This study offers valuable insights into RCC diagnostics and potential therapeutic strategies targeting ORAI channels and STIM proteins.