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.

To investigate the relationship between depression and AD, water avoidance stress (WAS) was induced for 10 days in both Tg2576 mice and wild-type (WT) mice. After WAS, memory function and depressive-like behavior were investigated in Tg2576 mice. Tg2576 WAS mice exhibited more depressive-like behaviors than WT WAS and Tg2576 control (CON) mice. Strikingly, Tg2576 CON mice showed more depressive-like behaviors than WT mice. Moreover, corticosterone and phospho-glucocorticoid receptor (p-GR) levels were also higher in Tg2576 WAS mice in comparison to Tg2576 CON mice. Spinster homologue 2 (SPNS2) is a member of non-ATP-dependent transporter. The role of SPNS2 was widely known as a sphingosine-1-phosphate (S1P) transporter, which export intracellular S1P from cells. Using GEO database to analyze SPNS2 gene expression changes in patients with AD and depression, we show that SPNS2 gene expression correlates with AD and depression. Interestingly, Tg2576 WAS mice displayed significantly increased levels of SPNS2 w1hen compared to Tg2576 CON counterparts. SPNS2 levels were also higher in Tg2576 CON mice in comparison with WT CON mice. Remarkably, we found a decrease in S1P brain levels and an increase in S1P serum levels of Tg2576 WAS mice in comparison with Tg2576 CON mice. Accordingly, WAS induced group further decreased S1P levels in the brains. However, the level in the serum further increased in comparison with non-induced group. Therefore, these results suggest that AD and depression could be associated, and that Tg2576 transgenic mice are more susceptible to stress-induced depression through the release of S1P by SPNS2 up-regulation.

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.

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: Prostate cancer ranks as the second most common cancer in men globally, representing a significant cause of cancer-related mortality. Metastasis, the spread of cancer cells from the primary site to distant organs, remains a major challenge in managing prostate cancer. Pyruvate dehydrogenase kinase 4 (PDK4) is implicated in the regulation of aerobic glycolysis, emerging as a potential player in various cancers. However, its role in prostate cancer remains unclear. This study aims to analyze PDK4 expression in prostate cancer cells and human samples, and to explore the gene's clinical significance. Materials and Methods: PDK4 expression was detected in cell lines and human tissue samples. Migration ability was analyzed using Matrigel-coated invasion chambers. Human samples were obtained from the Kyungpook National University Chilgok Hospital. Results: PDK4 expression was elevated in prostate cancer cell lines compared to normal prostate cells, with particularly high levels in DU145 and LnCap cell lines. PDK4 knockdown in these cell lines suppressed their invasion ability, indicating a potential role of PDK4 in prostate cancer metastasis. Furthermore, our results revealed alterations in epithelial-mesenchymal transition markers and downstream signaling molecules following PDK4 suppression, suggesting its involvement in the modulation of invasion-related pathways. Furthermore, PDK4 expression was increased in prostate cancer tissues, especially in castration-resistant prostate cancer, compared to normal prostate tissues, with PSA and PDK4 expression showing a significantly positive correlation. Conclusions PDK4 expression in prostate cancer is associated with tumor invasion and castration status. Further validation is needed to demonstrate its effectiveness as a therapeutic target.

To investigate the relationship between depression and AD, water avoidance stress (WAS) was induced for 10 days in both Tg2576 mice and wild-type (WT) mice. After WAS, memory function and depressive-like behavior were investigated in Tg2576 mice. Tg2576 WAS mice exhibited more depressive-like behaviors than WT WAS and Tg2576 control (CON) mice. Strikingly, Tg2576 CON mice showed more depressive-like behaviors than WT mice. Moreover, corticosterone and phospho-glucocorticoid receptor (p-GR) levels were also higher in Tg2576 WAS mice in comparison to Tg2576 CON mice. Spinster homologue 2 (SPNS2) is a member of non-ATP-dependent transporter. The role of SPNS2 was widely known as a sphingosine-1-phosphate (S1P) transporter, which export intracellular S1P from cells. Using GEO database to analyze SPNS2 gene expression changes in patients with AD and depression, we show that SPNS2 gene expression correlates with AD and depression. Interestingly, Tg2576 WAS mice displayed significantly increased levels of SPNS2 w1hen compared to Tg2576 CON counterparts. SPNS2 levels were also higher in Tg2576 CON mice in comparison with WT CON mice. Remarkably, we found a decrease in S1P brain levels and an increase in S1P serum levels of Tg2576 WAS mice in comparison with Tg2576 CON mice. Accordingly, WAS induced group further decreased S1P levels in the brains. However, the level in the serum further increased in comparison with non-induced group. Therefore, these results suggest that AD and depression could be associated, and that Tg2576 transgenic mice are more susceptible to stress-induced depression through the release of S1P by SPNS2 up-regulation.

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.

To investigate the relationship between depression and AD, water avoidance stress (WAS) was induced for 10 days in both Tg2576 mice and wild-type (WT) mice. After WAS, memory function and depressive-like behavior were investigated in Tg2576 mice. Tg2576 WAS mice exhibited more depressive-like behaviors than WT WAS and Tg2576 control (CON) mice. Strikingly, Tg2576 CON mice showed more depressive-like behaviors than WT mice. Moreover, corticosterone and phospho-glucocorticoid receptor (p-GR) levels were also higher in Tg2576 WAS mice in comparison to Tg2576 CON mice. Spinster homologue 2 (SPNS2) is a member of non-ATP-dependent transporter. The role of SPNS2 was widely known as a sphingosine-1-phosphate (S1P) transporter, which export intracellular S1P from cells. Using GEO database to analyze SPNS2 gene expression changes in patients with AD and depression, we show that SPNS2 gene expression correlates with AD and depression. Interestingly, Tg2576 WAS mice displayed significantly increased levels of SPNS2 w1hen compared to Tg2576 CON counterparts. SPNS2 levels were also higher in Tg2576 CON mice in comparison with WT CON mice. Remarkably, we found a decrease in S1P brain levels and an increase in S1P serum levels of Tg2576 WAS mice in comparison with Tg2576 CON mice. Accordingly, WAS induced group further decreased S1P levels in the brains. However, the level in the serum further increased in comparison with non-induced group. Therefore, these results suggest that AD and depression could be associated, and that Tg2576 transgenic mice are more susceptible to stress-induced depression through the release of S1P by SPNS2 up-regulation.

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.

Aging adversely impacts thermoregulatory function, thereby increasing the risk of intraoperative hypothermia. Age-associated alterations-including diminished thermal perception, impaired autonomic responsiveness, reduced thermogenic capacity due to sarcopenia, and decreased cardiovascular adaptability, exacerbate the vulnerability to hypothermia. Concomitant comorbidities and polypharmacy further compromise thermal homeostasis in geriatric patients. Anesthetic agents compound this risk by lowering the thresholds for vasoconstriction and shivering and attenuating the magnitude of thermal responses. Consequently, geriatric populations are predisposed to significant perioperative temperature decline, particularly in cooler operating room (OR) environments. Intraoperative hypothermia is associated with an increased incidence of adverse outcomes, including increased cardiac events, surgical site infections, coagulopathy, protracted pharmacodynamic effects, extended recovery, and hospitalization duration. Although recent investigations suggest a diminished incidence of hypothermia due to minimally invasive surgical techniques and enhanced temperature management protocols, the intrinsic susceptibility of the aged thermoregulatory system persists. Effective temperature management requires precise core temperature monitoring and maintains appropriate OR temperatures. Furthermore, the implementation of multimodal warming strategies, including passive insulation, active warming modalities, warming of intravenous fluids, and prewarming before anesthesia induction, is critical. Therefore, a comprehensive and proactive thermal management approach is essential in mitigating hypothermia-related risks and optimizing perioperative outcomes in the geriatric patients.