The detrimental effects of hyperlipidemia on the healing of rotator cuff tears are well documented. The proposed underlying mechanisms for these effects include alterations in the extracellular matrix, inflammation, and oxidative stress, which hamper the reparative processes in the affected tendon tissues. Recent therapeutic strategies target these pathways, reflecting a growing body of research dedicated to mitigating these effects and promoting healing. This literature review aims to provide a comprehensive understanding of the pathophysiology underlying rotator cuff tears, examine the interplay between hyperlipidemia and rotator cuff tear healing, synthesize current knowledge on contributing biological mechanisms, and outline potential therapeutic interventions to optimize clinical management and treatment outcomes for patients.

Background: Several studies have investigated the morphological risk factors contributing to posterior cruciate ligament (PCL) injury. However, no study has focused on the injury patterns of intrasubstance tears or tibial avulsion fractures in relation to morphologies and regional bone quality. This study aimed to investigate the impact of the knee morphology and regional bone quality of the proximal tibia on the PCL injury pattern. Methods: This retrospective study compared the radiological features of 76 patients with PCL injuries (PI group) and 76 matched patients with normal PCL (control group). The PI group was divided into 2 subgroups: PCL avulsion fracture (PAF subgroup; n = 43) and PCL intrasubstance tear (PIT subgroup; n = 33). Measurements included the coronal notch width index, coronal tibial slope, medial and lateral posterior tibial slopes, and medial tibial depth. Three Hounsfield unit average measurements were taken from the proximal tibia around the PCL insertion site to create a summative measure of overall bone quality. Results: The medial tibial depth and coronal notch width index were significantly lower in the PI group than those in the control group (medial tibial depth: 2.04 ± 0.77 vs. 3.02 ± 1.04, p = 0.017; coronal notch width index: 0.21 ± 0.03 vs. 0.24 ± 0.03, p = 0.041). In the subgroup analysis, medial tibial depth and Hounsfield unit were significantly lower in the PAF subgroup than in the PIT subgroup (medial tibial depth: 1.74 ± 0.66 vs. 2.43 ± 0.77, p = 0.008, Hounsfield unit: 89.48 ± 31.73 vs. 120.15 ± 29.24, p = 0.004). Binary logistic regression analysis showed that medial tibial depth (odds ratio [OR], 0.161; p < 0.001) and Hounsfield unit (OR, 0.950;p < 0.001) were independent risk factors for PCL tibial avulsion fractures. Conclusions Lower notch width index and medial tibial depth are associated with PCL injuries. Shallower medial tibial depth and lower Hounsfield unit measurements around the PCL insertion site were associated with an increased incidence of PCL avulsion fractures. These findings may assist clinicians in identifying patients at risk of distinct PCL injury patterns.

Background: and Purpose: Amyloid-beta (Aβ) plaques are key in Alzheimer’s disease (AD), with Aβ positron emission tomography imaging enabling non-invasive quantification.To address regional Aβ deposition, we developed regional Centiloid scales (rdcCL) and commercialized them through the computed tomography (CT)-based BeauBrain Amylo platform, eliminating the need for three-dimensional T1 magnetic resonance imaging (MRI). Objective: We aimed to establish robust regional Aβ cutoffs using the commercialized BeauBrain Amylo platform and to explore the prevalence of subgroups defined by global, regional, and striatal Aβ cutoffs across cognitive stages. Methods: We included 2,428 individuals recruited from the Korea-Registries to Overcome Dementia and Accelerate Dementia Research project. We calculated regional Aβ cutoffs using Gaussian Mixture Modeling. Participants were classified into subgroups based on global, regional, and striatal Aβ positivity across cognitive stages (cognitively unimpaired [CU], mild cognitive impairment, and dementia of the Alzheimer’s type). Results: MRI-based and CT-based global Aβ cutoffs were highly comparable and consistent with previously reported Centiloid values. Regional cutoffs revealed both similarities and differences between MRI- and CT-based methods, reflecting modality-specific segmentation processes. Subgroups such as global(−)regional(+) were more frequent in non-dementia stages, while global(+)striatal(−) was primarily observed in CU individuals. Conclusions Our study established robust regional Aβ cutoffs using a CT-based rdcCL method and demonstrated its clinical utility in classifying amyloid subgroups across cognitive stages. These findings highlight the importance of regional Aβ quantification in understanding amyloid pathology and its implications for biomarker-guided diagnosis and treatment in AD.

Continuous glucose monitoring (CGM) has revolutionized diabetes management, significantly enhancing glycemic control across diverse patient populations. Recent evidence supports its effectiveness in both type 1 and type 2 diabetes management, with benefits extending beyond traditional glucose monitoring approaches. CGM has demonstrated substantial improvements in glycemic control across multiple metrics. Studies report consistent glycosylated hemoglobin reductions of 0.25%–3.0% and notable time in range improvements of 15%–34%. CGM effectively reduces hypoglycemic events, with studies reporting significant reductions in time spent in hypoglycemia. CGM also serves as an educational tool for lifestyle modification, providing real-time feedback that helps patients understand how diet and physical activity affect glucose levels. While skin-related complications remain a concern, technological advancements have addressed many initial concerns. High satisfaction rates and long-term use suggest that device-related issues are manageable with proper education and support. Despite high initial costs, CGM’s prevention of complications and hospitalizations ultimately reduces healthcare expenditures. With appropriate training and support, CGM represents a transformative technology for comprehensive diabetes care.

Background: Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making. Methods: This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes. Conclusion This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.

Emerging evidence suggests that systemic inflammation may play a critical role in neurological disorders. Recent studies have shown the connection between inflammatory bowel diseases (IBD) and neurological disorders, revealing a bidirectional relationship through the gut-brain axis.Immunotherapies, such as Treg cells infusion, have been proposed for IBD. However, the role of adaptive immune cells in IBD-induced neuroinflammation remains unclear. In this study, we established an animal model for IBD in mice with severe combined immune-deficient (SCID), an adaptive immune deficiency, to investigate the role of adaptive immune cells in IBD-induced neuroinflammation. Mice were fed 1%, 3%, or 5% dextran sulfate sodium (DSS) for 5 days. We measured body weight, colon length, disease activity index (DAI), and crypt damage. Pro-inflammatory cytokines were measured in the colon, while microglial morphology, neuronal count, and inflammatory cytokines were analyzed in the brain. In the 3% DSS group, colitis symptoms appeared at day 7, with reduced colon length and increased crypt damage showing colitis-like symptoms. By day 21, colon length and crypt damage persisted, while DAI showed recovery. Although colonic inflammation peaked at day 7, no significant increase in inflammatory cytokines or microglial hyperactivation was observed in the brain. By day 21, neuroinflammation was detected, albeit with a slight delay, in the absence of adaptive immune cells. The colitis-induced neuroinflammation model provides insights into the fundamental immune mechanisms of the gut-brain axis and may contribute to developing immune cell therapies for IBD-induced neuroinflammation.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Background/Aims: Inflammatory bowel disease (IBD) affects health-related quality of life (HRQoL). The Short Inflammatory Bowel Disease Questionnaire (SIBDQ) score is strongly correlated with HRQoL in IBD patients. This study aimed to assess the factors influencing HRQoL in IBD patients. Methods: In this prospective study, all patients with ulcerative colitis (UC) and Crohn’s disease (CD) completed the SIBDQ at enrollment; some patients also completed a second SIBDQ at follow-up. Multiple linear regression analysis was used to determine associations between SIBDQ scores and clinical factors. Results: A total of 1,020 patients participated (UC, 67%; CD, 33%). The median SIBDQ score was 52 (interquartile range, 44 to 59). In UC patients, the stool frequency (β=–2.333, p<0.001), Physician Global Assessment score (β=–3.950, p<0.001), fecal calprotectin level (β=–4.014, p<0.001), and corticosteroid use (β=–4.809, p=0.006) were negatively correlated with the SIBDQ score. In CD patients, the number of diarrhea episodes per day (β=–1.467, p=0.024) and Crohn's Disease Activity Index score (β=–0.045, p<0.001) were negatively correlated with the SIBDQ score. A total of 202 patients completed the second SIBDQ within a mean of 3.4 years. The distributions of SIBDQ score changes were as follows: decrease >10%, 28%; –10%10%, 43%. In both the initial SIBDQ and follow-up SIBDQ, scores for items pertaining to systemic symptoms (tension and fatigue) were relatively low. Conclusions Bowel movement-related problems significantly affect the HRQoL of both UC and CD patients. IBD patients scored lower on SIBDQ items related to general well-being. After 3 years of follow-up at the IBD clinic, 43% of patients showed a significant improvement in HRQoL.

Background/Aims: This study aimed to evaluate the performance of the Model for End-Stage Liver Disease (MELD) 3.0 for predicting mortality and liver-related complications compared with the Child-Pugh classification, albumin-bilirubin (ALBI) grade, the MELD, and the MELD sodium (MELDNa) score. Methods: We evaluated a multicenter retrospective cohort of incorporated patients with cirrhosis between 2013 and 2019. We conducted comparisons of the area under the receiver operating characteristic curve (AUROC) of the MELD3.0 and other models for predicting 3-month mortality. Additionally, we assessed the risk of cirrhosis-related complications according to the MELD3.0 score. Results: A total of 3,314 patients were included. The mean age was 55.9±11.3 years, and 70.2% of the patients were male. Within the initial 3 months, 220 patients (6.6%) died, and the MELD3.0had the best predictive performance among the tested models, with an AUROC of 0.851, outperforming the Child-Pugh classification, ALBI grade, MELD, and MELDNa. A high MELD3.0score was associated with an increased risk of mortality. Compared with that of the group with a MELD3.0 score <10 points, the adjusted hazard ratio of the group with a score of 10–20 pointswas 2.176, and that for the group with a score of ≥20 points was 4.892. Each 1-point increase inthe MELD3.0 score increased the risk of cirrhosis-related complications by 1.033-fold. The risk of hepatorenal syndrome showed the highest increase, with an adjusted hazard ratio of 1.149, followed by hepatic encephalopathy and ascites. Conclusions The MELD3.0 demonstrated robust prognostic performance in predicting mortality in patients with cirrhosis. Moreover, the MELD3.0 score was linked to cirrhosis-related complications, particularly those involving kidney function, such as hepatorenal syndrome and ascites.

Parkinson’s disease (PD) is a neurodegenerative condition characterized by the loss of midbrain dopaminergic neurons, leading to motor symptoms. While current treatments provide limited relief, they don’t alter disease progression. Stem cell technology, involving patient-specific stem cell-derived neurons, offers a promising avenue for research and personalized regenerative therapies. This article reviews the potential of stem cell-based research in PD, summarizing ongoing efforts, their limitations, and introducing innovative research models. The integration of stem cell technology and advanced models promises to enhance our understanding and treatment strategies for PD.