Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

Rare endocrine diseases are complex conditions that require lifelong specialized care due to their chronic nature and associated long-term complications. In Korea, a lack of nationwide data on clinical practice and outcomes has limited progress in patient care. Therefore, the Multicenter Networks for Ideal Outcomes of Pediatric Rare Endocrine and Metabolic Disease (OUTSPREAD) study was initiated. This study involves 30 centers across Korea. The study aims to improve the long-term prognosis of Korean patients with rare endocrine diseases by collecting comprehensive clinical data, biospecimens, and patient-reported outcomes to identify complications and unmet needs in patient care. Patients with childhood-onset pituitary, adrenal, or gonadal disorders, such as craniopharyngioma, congenital adrenal hyperplasia (CAH), and Turner syndrome were prioritized. The planned enrollment is 1,300 patients during the first study phase (2022–2024). Clinical, biochemical, and imaging data from diagnosis, treatment, and follow-up during 1980–2023 were retrospectively reviewed. For patients who agreed to participate in the prospective cohort, clinical data and biospecimens will be prospectively collected to discover ideal biomarkers that predict the effectiveness of disease control measures and prognosis. Patient-reported outcomes, including quality of life and depression scales, will be evaluated to assess psychosocial outcomes. Additionally, a substudy on CAH patients will develop a steroid hormone profiling method using liquid chromatography-tandem mass spectrometry to improve diagnosis and monitoring of treatment outcomes. This study will address unmet clinical needs by discovering ideal biomarkers, introducing evidence-based treatment guidelines, and ultimately improving long-term outcomes in the areas of rare endocrine and metabolic diseases.

Background: Uncoupling protein 1 (UCP1) is a proton uncoupler located across the mitochondrial membrane gener‑ ally involved in thermogenesis of brown adipose tissues. Although UCP1 is known to be strongly expressed in brown adipocytes, recent evidence suggest that white adipocytes can also express UCP1 under certain circumstances such as cold- or β-adrenergic receptor-stimulation, allowing them to acquire brown adipocyte-like features thereby becoming ’beige’ adipocytes. Results: In this study, we report that UCP1 can be expressed in adipose-tissue macrophages (ATM) lacking func‑ tional hypoxia-inducible factor-1 (HIF-1) and this does not require cold- nor β-adrenergic receptor activation. By using myeloid-specific Hif-1α knockout (KO) mice, we observed that these mice were protected from diet-induced obesity and exhibited an improved thermogenic tolerance upon cold challenge. ATM isolated from white adipose tissues (WAT) of these mice fed with high fat diet exhibited significantly higher M2-polarization, decreased gly‑ colysis, increased mitochondrial functions and acetyl-CoA levels, along with increased expression of Ucp1, peroxisome proliferator activated receptor-gamma co-activator-1a, and others involved in histone acetylation. Consistent with the increased Ucp1 gene expression, these ATM produced a significant amount of heat mediating lipolysis of cocultured adipocytes liberating free fatty acid. Treating ATM with acetate, a substrate for acetyl-CoA synthesis was able to boost the heat production in wild-type or Hif-1α-deficient but not UCP1-deficient macrophages, indicating that UCP1 was necessary for the heat production in macrophages. Lastly, we observed a significant inverse correlation between the number of UCP1-expressing ATM in WAT and the body mass index of human individuals. Conclusions UCP1-expressing ATM produce the heat to mediate lipolysis of adipocytes, indicating that this can be a novel strategy to treat and prevent diet-induced obesity.

Objectives: We analyzed the correlation between the infectivity and transmissibility of the severe acute respiratory syndrome coronavirus 2 Omicron sublineages BA.1, BA. 2, BA.4, and BA.5. Methods: We assessed viral replication kinetics and infectivity at the cellular level. Nasopharyngeal and oropharyngeal specimens were obtained from patients with coronavirus disease 2019, confirmed using whole-genome sequencing to be caused by the Omicron sublineages BA.1, BA.2, BA.4, or BA.5. These specimens were used to infect Vero E6 cells, derived from monkey kidneys, for the purpose of viral isolation. Viral stocks were then passaged in Vero E6 cells at a multiplicity of infection of 0.01, and culture supernatants were harvested at 12-hour intervals for 72 hours. To evaluate viral replication kinetics, we determined the cycle threshold values of the supernatants using real-time reverse transcription polymerase chain reaction and converted these values to genome copy numbers. Results: The viral load was comparable between BA.2, BA.4, and BA.5, whereas BA.1 exhibited a lower value. The peak infectious load of BA.4 was approximately 3 times lower than that of BA.2 and BA.5, while the peak load of BA.2 and BA.5 was about 7 times higher than that of BA.1. Notably, BA.1 demonstrated the lowest infectivity over the entire study period. Conclusion Our results suggest that the global BA.5 wave may have been amplified by the higher viral replication and infectivity of BA.5 compared to other Omicron sublineages. These analyses could support the rapid assessment of the impact of novel variants on case incidence.

Objective: This study was performed to evaluate the efficacy and safety of lurasidone (160 mg/day) compared to quetiapine XR (QXR; 600 mg/day) in the treatment of acutely psychotic patients with schizophrenia. Methods: Patients were randomly assigned to 6 weeks of double-blind treatment with lurasidone 160 mg/day (n=105) or QXR 600 mg/day (n=105). Primary efficacy measure was the change from baseline to week 6 in Positive and Negative Syndrome Scale (PANSS) total score and Clinical Global Impressions severity (CGI-S) score. Adverse events, body measurements, and laboratory parameters were assessed. Results: Lurasidone demonstrated non-inferiority to QXR on the PANSS total score. Adjusted mean±standard error change at week 6 on the PANSS total score was -26.42±2.02 and -27.33±2.01 in the lurasidone and QXR group, respectively. The mean difference score was -0.91 (95% confidence interval -6.35–4.53). The lurasidone group showed a greater reduction in PANSS total and negative subscale on week 1 and a greater reduction in end-point CGI-S score compared to the QXR group. Body weight, body mass index, and waist circumference in the lurasidone group were reduced, with significantly lower mean change compared to QXR. Endpoint changes in glucose, cholesterol, triglycerides, and low-density lipoprotein levels were also significantly lower. The most common adverse drug reactions with lurasidone were akathisia and nausea. Conclusion Lurasidone 160 mg/day was found to be non-inferior to QXR 600 mg/day in the treatment of schizophrenia with comparable efficacy and tolerability. Adverse effects of lurasidone were generally tolerable, and beneficial effects on metabolic parameters can be expected.

Background: Uncoupling protein 1 (UCP1) is a proton uncoupler located across the mitochondrial membrane gener‑ ally involved in thermogenesis of brown adipose tissues. Although UCP1 is known to be strongly expressed in brown adipocytes, recent evidence suggest that white adipocytes can also express UCP1 under certain circumstances such as cold- or β-adrenergic receptor-stimulation, allowing them to acquire brown adipocyte-like features thereby becoming ’beige’ adipocytes. Results: In this study, we report that UCP1 can be expressed in adipose-tissue macrophages (ATM) lacking func‑ tional hypoxia-inducible factor-1 (HIF-1) and this does not require cold- nor β-adrenergic receptor activation. By using myeloid-specific Hif-1α knockout (KO) mice, we observed that these mice were protected from diet-induced obesity and exhibited an improved thermogenic tolerance upon cold challenge. ATM isolated from white adipose tissues (WAT) of these mice fed with high fat diet exhibited significantly higher M2-polarization, decreased gly‑ colysis, increased mitochondrial functions and acetyl-CoA levels, along with increased expression of Ucp1, peroxisome proliferator activated receptor-gamma co-activator-1a, and others involved in histone acetylation. Consistent with the increased Ucp1 gene expression, these ATM produced a significant amount of heat mediating lipolysis of cocultured adipocytes liberating free fatty acid. Treating ATM with acetate, a substrate for acetyl-CoA synthesis was able to boost the heat production in wild-type or Hif-1α-deficient but not UCP1-deficient macrophages, indicating that UCP1 was necessary for the heat production in macrophages. Lastly, we observed a significant inverse correlation between the number of UCP1-expressing ATM in WAT and the body mass index of human individuals. Conclusions UCP1-expressing ATM produce the heat to mediate lipolysis of adipocytes, indicating that this can be a novel strategy to treat and prevent diet-induced obesity.