Purpose: The objectives of this study were to identify the types of recovered alcoholics based on the factors that influence recovery, using the Q methodology. Methods: Forty-six statements were selected from in-depth interviews with eight psychiatric healthcare professionals and four abstinent alcoholics and literature review. Then, 50 participants sorted these statements in a forced grid with normal distribution from -4 to 4. Finally, factor analysis was performed with the PC-QUANL program. Results: Three types of recovered alcoholics were identified. Firstly, the ‘positive-centered recovery type’ emphasized on self-affirmation and self-confidence and acted on the belief of the possibility of recovery from alcoholism. The second type was the ‘temperance-centered recovery type’, which focused on complete control over daily life to stay sober. Finally, the ‘acceptance-centered type’ was likely to admit the weakness of human beings and pursue spirituality. Conclusion This study found three types of recovered alcoholics, focusing on the factors that had an impact on recovery and analyzed their characteristics. These findings provided useful information to understand recovered alcoholics, and they can be used to develop a tailored intervention to prevent a relapse of alcoholism.

No abstract available.
Glomerulosclerosis, Focal Segmental* ; Polycystic Kidney Diseases*

PURPOSE: Zirconia has exceptional biocompatibility and good mechanical properties in clinical situations. However, finite element analysis (FEA) studies on the biomechanical stability of two-piece zirconia implant systems are limited. Therefore, the aim of this study was to compare the biomechanical properties of the two-piece zirconia and titanium implants using FEA. MATERIALS AND METHODS: Two groups of finite element (FE) models, the zirconia (Zircon) and titanium (Titan) models, were generated for the exam. Oblique (175 N) and vertical (175 N) loads were applied to the FE model generated for FEA simulation, and the stress levels and distributions were investigated. RESULTS: In oblique loading, von Mises stress values were the highest in the abutment of the Zircon model. The von Mises stress values of the Titan model for the abutment screw and implant fixture were slightly higher than those of the Zircon model. Minimum principal stress in the cortical bone was higher in the Titan model than Zircon model under oblique and vertical loading. Under both vertical and oblique loads, stress concentrations in the implant components and bone occurred in the same area. Because the material itself has high stiffness and elastic modulus, the Zircon model exhibited a higher von Mises stress value in the abutments than the Titan model, but at a level lower than the fracture strength of the material. CONCLUSION Owing to the good esthetics and stress controllability of the Zircon model, it can be considered for clinical use.

BACKGROUND AND OBJECTIVES: Few studies were evaluated the effect of blindness on outcome in animal models, though a potential effect of blinding has been reported in clinical trials. We evaluated the effects of adipose tissue-derived stem cells (ADSCs) on cavernous nerve injury (CNI)-induced erectile dysfunction (ED) in the rat and examined how proper blinding of the outcome assessor affected treatment effect. METHODS AND RESULTS: We searched in Pubmed, EMBASE, Cochrane and Web of Science databases from inception to January 2019. We included CNI animal model, randomized controlled experiments, and ADSC intervention. Erectile function and structural changes were assessed by intracavernous pressure and mean arterial pressure (ICP/MAP) ratios, neuronal nitric oxide synthase (nNOS) levels, cavernous smooth muscle and collagen (CSM/collagen) ratios, and cyclic guanosine monophosphate (cGMP). RESULTS: Nineteen studies were included in the final meta-analysis. The ICP/MAP ratio of the ADSC treatment group increased compared to the control group (SMD=1.33, 95%CI: 1.11~1.56, I²=72%). The nNOS level (SMD=2.29, 95%CI: 1.74~2.84, I²=75%), CSM/collagen (SMD=2.57, 95%CI: 1.62~3.52; I²=85%), and cGMP (SMD=2.96, 95%CI: 1.82~4.10, I²=62%) were also increased in the ADSC treatment group. Preplanned subgroup analysis was conducted to explore the source of heterogeneity. Five studies with blinded outcome assessment were significantly less effective than the unblinded studies (SMD=1.33, 95%CI: 0.86~1.80; SMD=1.81, 95%CI: 1.17~2.46, respectively). CONCLUSIONS: ADSCs might be effective in improving erectile function and structural change in CNI-induced ED. However, non-blinded outcome assessors might cause detection bias and overestimate treatment efficacy. Therefore, the ADSC efficacy must be further evaluated with a rigorous study design to avoid bias.
Animals ; Arterial Pressure ; Bias (Epidemiology) ; Blindness ; Collagen ; Erectile Dysfunction ; Guanosine Monophosphate ; Male ; Models, Animal ; Muscle, Smooth ; Nitric Oxide Synthase Type I ; Population Characteristics ; Rats ; Stem Cells ; Treatment Outcome

BACKGROUND AND OBJECTIVES: This study was performed to investigate whether stem cell therapy enhances β cell function by meta-analysis with proper consideration of variability of outcome measurements in controlled trial of type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) patients. METHODS: A systematic search was performed from inception to January 2018 in PubMed, EMBASE, and Cochrane databases. β cell function was assessed by stimulated C-peptide, fasting C-peptide, normal glycosylated hemoglobin levels (HbA1C), and exogenous insulin dose patterns. The quality of the studies were assessed by both the Cochrane Collaboration's Risk of Bias (ROB) for Randomized controlled trials and the Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) for non-randomized controlled trials. RESULTS: From the selected final 15 articles, total of 16 trials were analyzed. There were 6 T1DM trials (total 153 cases) and 10 T2DM trials (total 457 cases). In T2DM patients, the changes in stimulated C-peptide, HbA1c, and exogenous insulin dose versus baseline showed a favorable pattern with a significant heterogeneity in stem cell therapy. In T1DM, there was no significant difference between control group and stem cell therapy group in three indicators except for HbA1c. Most of the studies were rated as having high risk of bias in the quality assessment. CONCLUSIONS: The stem cell therapy for DM patients is not effective in T1DM but seems to be effective in improving the β cell function in T2DM. However the observed effect should be interpreted with caution due to the significant heterogeneity and high risk of bias within the studies. Further verification through a rigorously designed study is warranted.
Bias (Epidemiology) ; C-Peptide ; Diabetes Mellitus ; Diabetes Mellitus, Type 1 ; Diabetes Mellitus, Type 2 ; Fasting ; Hemoglobin A, Glycosylated ; Humans ; Insulin ; Population Characteristics ; Stem Cells

Objective: This study aimed to investigate the feasibility of using artificial intelligence (AI) to identify normal chest radiography (CXR) from the worklist of radiologists in a health-screening environment. Materials and Methods: This retrospective simulation study was conducted using the CXRs of 5887 adults (mean age ± standard deviation, 55.4 ± 11.8 years; male, 4329) from three health screening centers in South Korea using a commercial AI (Lunit INSIGHT CXR3, version 3.5.8.8). Three board-certified thoracic radiologists reviewed CXR images for referable thoracic abnormalities and grouped the images into those with visible referable abnormalities (identified as abnormal by at least one reader) and those with clearly visible referable abnormalities (identified as abnormal by at least two readers). With AI-based simulated exclusion of normal CXR images, the percentages of normal images sorted and abnormal images erroneously removed were analyzed. Additionally, in a random subsample of 480 patients, the ability to identify visible referable abnormalities was compared among AI-unassisted reading (i.e., all images read by human readers without AI), AI-assisted reading (i.e., all images read by human readers with AI assistance as concurrent readers), and reading with AI triage (i.e., human reading of only those rendered abnormal by AI). Results: Of 5887 CXR images, 405 (6.9%) and 227 (3.9%) contained visible and clearly visible abnormalities, respectively. With AI-based triage, 42.9% (2354/5482) of normal CXR images were removed at the cost of erroneous removal of 3.5% (14/405) and 1.8% (4/227) of CXR images with visible and clearly visible abnormalities, respectively. In the diagnostic performance study, AI triage removed 41.6% (188/452) of normal images from the worklist without missing visible abnormalities and increased the specificity for some readers without decreasing sensitivity. Conclusion This study suggests the feasibility of sorting and removing normal CXRs using AI with a tailored cut-off to increase efficiency and reduce the workload of radiologists.

Autosomal dominant polycystic kidney disease (ADPKD), one of the most common human monogenic diseases, is characterized by the presence of numerous fluid-filled renal cysts and is a leading cause of end-stage renal disease (ESRD). Urinary biomarkers may be useful for predicting the variable course of ADPKD progression from cyst growth to ESRD. Methods: To identify candidate urinary biomarkers of ADPKD progression, we used CRISPR/Cas9 genome editing to generate porcine fibroblasts with mono- and biallelic ADPKD gene knockout (PKD2+/– and PKD2–/–, respectively). We then performed RNA-sequencing analysis on these cells. Results: Levels of osteopontin (OPN), which is expressed by renal epithelial tubular cells and excreted into urine, were reduced in PKD2–/– cells but not in PKD2+/– cells. OPN levels were also reduced in the renal cyst cells of ADPKD patients. Next, we investigated whether OPN excretion was decreased in patients with ADPKD via enzyme-linked immunosorbent assay. OPN levels excreted into renal cyst cell culture media and urine from ADPKD patients were decreased. To investigate whether OPN can predict the rate of ADPKD progression, we compared urinary excretion of OPN in ADPKD patients with slow progression and those with rapid progression. Those with rapid progression had an estimated glomerular filtration rate of >60 mL/min/1.73 m2 . Urinary OPN excretion levels were lower in rapid progressors than in slow progressors. Conclusion: These findings suggest that OPN is a useful urinary biomarker for predicting ADPKD progression.

Background: Dietary intervention at the early stage of chronic kidney disease (CKD) is important for preventing progression to the end-stage renal disease (ESRD). However, few studies have investigated dietary intake of CKD patients in non-dialysis stage. Therefore, we investigated the dietary intake of Korean non-dialysis CKD patients and aimed to establish baseline data for the development of dietary education and intervention strategies for CKD patients. Methods: Three hundred fifty CKD patients who visited Seoul National University Hospital outpatient clinic from February 2016 to January 2017 were recruited for this cross-sectional study. Subjects on dialysis and those who had undergone kidney transplantation were excluded. Dietary intake, demographic information, and biochemical characteristics of 256 subjects who completed three-day dietary records were analyzed. Subjects were divided into four groups based on diabetes mellitus (DM) (DM-CKD and Non-DM-CKD groups) and kidney function (Early-CKD and Late-CKD groups). Results: Total energy intake was lower in the Late-CKD group compared with the Early-CKD group. In men, carbohydrate intake was higher and protein and fat intakes tended to be lower in the Late-CKD group compared with the Early-CKD group. In women, carbohydrate intake tended to be lower in the DM-CKD group than the Non-DM-CKD group. Protein intake tended to be higher in the DM-CKD groups. Phosphorus and sodium intakes were higher in the DM-CKD groups compared with the Non-DM-CKD groups in women, and tended to be higher in the DM-CKD groups in men. Conclusion DM and kidney function affected energy and nutrient intakes. Subjects in the Late-CKD group consumed less energy than those in the Early-CKD group. Non-DM subjects seemed to restrict protein intake starting from the Early-CKD stage than subjects with DM. Subjects in this study had low energy and high sodium intakes compared with recommended levels. Protein intake was lower in advanced CKD patients, but their intake level was still higher than the recommendation. Dietary intervention strategies for non-dialysis CKD patients need to be customized depending on the presence of DM and kidney function.

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.