Background: Varus malalignment is a risk factor for nonunion and mechanical complications in subtrochanteric femoral fractures (SFFs). Although various reduction techniques have been reported to avoid varus malalignment in SFFs, achieving anatomic reduction remains challenging, often resulting in residual varus alignment (RVA) after reduction. This study aimed to investigate the radiographic and clinical outcomes of a novel method resolving RVA by abducting the ipsilateral hip after cephalomedullary fixation with an intramedullary nail and subsequently inserting distal interlocking screws. Methods: This retrospective study, conducted between March 2016 and March 2022, included patients who underwent hip abduction during intramedullary nailing due to RVA. Demographics and fracture patterns (Arbeitsgemeinschaft für Osteosynthesefragen/Orthopedic Trauma Association [AO/OTA]) and types (typical or atypical) were analyzed. Radiographic outcomes included Baumgaertner reduction quality criteria (BRQC), tip-apex distance (TAD), neck-shaft angle (NSA), lateral cortex residual gap, union, and time to union. Clinical outcomes included ambulatory level using the Palmer-Parker Mobility Score (PPM), complications, and reoperation. Results: This study included 45 patients (mean age, 65.8 years; mean follow-up period, 18.4 months). The most common fracture pattern was 32A2 in 15 patients and 29 were typical and 16 were atypical fractures. The BRQC was good in 36 patients, and TAD was < 25 mm in 43 patients. Pre-abduction NSA (126.0° ± 3.8°) was significantly smaller than post-abduction NSA (129.9° ± 3.4°, p < 0.001). Post-abduction NSA was comparable to contralateral NSA of 128.9° ± 2.8° (p = 0.155). Residual gap was significantly reduced from 6.1 ± 2.9 mm pre-abduction to 1.7 ± 1.0 mm post-abduction (p < 0.001). Union was achieved in 44 patients (97.8%;mean duration, 5.9 months). PPM decreased from 7.8 ± 2.0 pre-injury to 7.0 ± 2.1 1-year postoperatively. One nonunion case required reoperation. Radiographic outcomes did not significantly differ by fracture pattern (p = 0.470 for NSA and p = 0.334 for residual gap). Conclusions Hip abduction during intramedullary nailing corrects alignment and reduces the gap in SFFs with residual varus alignment. This method can be applied to various fracture patterns in a straightforward manner and considered valuable for managing SFFs.

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.

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.

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.

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.

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.

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.

Objective: Acute coronary syndrome often requires urgent intervention. The 2023 European Society of Cardiology guidelines recommend invasive procedures within 24 hours for high-risk cases. Nevertheless, there have been limited studies on non-ST-segment elevation myocardial infarction (NSTEMI) in South Korea. This study compared the risk of complications based on the timing of intervention. Methods: A retrospective observational study was conducted on patients with chest pain and elevated high-sensitivity troponin T from January to December 2021 in the emergency department. Patients were categorized into early (≤24 hr) and late (>24 hr) intervention groups. Primary outcomes (death, restenosis, or stroke) at 12 months were compared. Survival and subgroup analyses were performed to examine the factors affecting the outcomes in the two groups. Results: Three hundred seventy six patients were enrolled in the study, and 115 patients were excluded. Among 261 patients, 106 and 155 patients were in the early intervention group (≤24 hr), and late intervention group (>24 hr), respectively. The primary outcome (death or restenosis) showed no significant difference (hazard ratio [HR] in the early intervention group at 12 mo; 1.03; 95% confidence interval [CI], 0.63-1.70; P=0.905). However, risk of stroke was lower in the early intervention group (HR in the early, 0.08; 95% CI, 0.00-0.66; P=0.013). Subgroup analysis showed no significant advantage for early intervention. Conclusion In NSTEMI patients, early intervention does not reduce death or restenosis but lowers stroke incidence. No specific risk factors favored early intervention.

Purpose: This study evaluated the postoperative quality of life (QoL) after various types of gastrectomy for gastric cancer. Materials and Methods: A multicenter prospective observational study was conducted in Korea using the Korean Quality of Life in Stomach Cancer Patients Study (KOQUSS)-40, a new QoL assessment tool focusing on postgastrectomy syndrome. Overall, 496 patients with gastric cancer were enrolled, and QoL was assessed at 5 time points: preoperatively and at 1, 3, 6, and 12 months after surgery. Results: Distal gastrectomy (DG) and pylorus-preserving gastrectomy (PPG) showed significantly better outcomes than total gastrectomy (TG) and proximal gastrectomy (PG) with regard to total score, indigestion, and dysphagia. DG, PPG, and TG also showed significantly better outcomes than PG in terms of dumping syndrome and worry about cancer. Postoperative QoL did not differ significantly according to anastomosis type in DG, except for Billroth I anastomosis, which achieved better bowel habit change scores than the others. No domains differed significantly when comparing double tract reconstruction and esophagogastrostomy after PG. The total QoL score correlated significantly with postoperative body weight loss (more than 10%) and extent of resection (P<0.05 for both).Reflux as assessed by KOQUSS-40 did not correlate significantly with reflux observed on gastroscopy 1 year postoperatively (P=0.064). Conclusions Our prospective observation using KOQUSS-40 revealed that DG and PPG lead to better QoL than TG and PG. Further study is needed to compare postoperative QoL according to anastomosis type in DG and PG.

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.