This case report presents an 81-year-old edentulous female patient with congenital cleft lip and palate, rehabilitated with a maxillary obturator and a mandibular complete denture. A defect in the hard palate causes nasal leakage and hypernasalization of speech. Velopharyngeal insufficiency due to a defect in the soft palate causes reflux during swallowing and decreased clarity of pronunciation.The anatomical structures, such as Passavant’s ridge, were considered to prevent respiratory problems when impression taking. We achieved satisfactory results including velopharyngeal closure for pronunciation, mastication, and swallowing, as well as improved aesthetics. Therefore, we report the process and considerations of the treatment.

Microglial activation during aging is associated with neuroinflammation and cognitive impairment. Galectin-3 plays a crucial role in microglial activation and phagocytosis. However, the role of galectin-3 in the aged brain is not completely understood. In the present study, we investigated aging-related mechanisms and microglial galectin-3 expression in the mouse hippocampus using female 6-, 12-, and 24-month-old C57BL/6 mice. Western blot analysis revealed neurodegeneration, blood-brain barrier leakage, and increased levels of neuroinflammation-related proteins in 24-month-old mice compared to 6- and 12-month-old mice. Immunohistochemistry revealed an increase in activated microglia in the hippocampus of 24-month-old mice compared to 6- and 12-month-old mice. Furthermore, we found more galectin-3 and triggering receptor expressed on myeloid cells-2-positive microglia in 24-month-old mice compared to 6- and 12-month-old mice. Using primary mouse microglial cells, galectin -3 was also increased by lipopolysaccharide treatment. These findings suggest that galectin-3 may play an important role in microglial activation and neuroinflammation during brain aging.

Background: Recombinant human follicle-stimulating hormone (rhFSH) is commonly used to treat female infertility, but its short half-life necessitates multiple doses. Even corifollitropin alfa, with an extended half-life, requires supplementary injections of rhFSH after 7 days. This study aimed to develop and evaluate a long-acting follicle-stimulating hormone (FSH) formulation using anti-serum albumin Fab-associated (SAFA) technology to avoid additional injections and enhance ovarian function. Methods: SAFA-FSH was synthesized using a Chinese hamster ovary expression system. Its biological efficacy was confirmed through assays measuring its ability to stimulate cyclic adenosine monophosphate (cAMP) production, estradiol synthesis, and the expression of human cytochrome P450 family 19 subfamily A member 1 (hCYP19α1) and human steroidogenic acute regulatory protein (hSTAR) in human ovarian granulosa (KGN) cells. To evaluate the effects of SAFA-FSH, we compared its impact on serum estradiol levels and ovarian weight increase with that of rhFSH in Sprague-Dawley (SD) rats using the modified Steelman-Pohley test. Results: The results indicated that SAFA-FSH induces cAMP synthesis in KGN cells and upregulates the expression of hCYP19α1 and hSTAR in a dose-dependent manner. Female SD rats, aged 21 days, receiving daily subcutaneous human chorionic gonadotropin injections for 5 days exhibited a significant increase in serum estradiol levels and ovarian weight when administered SAFA-FSH on the first day or when given nine injections of rhFSH over 5 days. Notably, the group receiving SAFA-FSH on the first and third days demonstrated an even greater rise in serum estradiol levels and ovarian weight. Conclusion These findings suggest that SAFA-FSH presents a promising alternative to current rhFSH treatments for female infertility. However, further research is essential to thoroughly assess its safety and efficacy in clinical contexts.

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.

We describe the updated Korean Society of Gynecologic Oncology (KSGO) practice guideline for the management of cervical cancer, version 5.1. The KSGO announced the fifth version of its clinical practice guidelines for the management of cervical cancer in March 2024. The selection of the key questions and the systematic reviews were based on data available up to December 2022. Between 2023 and 2024, substantial findings from large-scale clinical trials and new advancements in cervical cancer research remarkably emerged. Therefore, based on the existing version 5.0, we updated the guidelines with newly accumulated clinical data and added 4 new key questions reflecting the latest insights in the field of cervical cancer. For each question, recommendation was formulated with corresponding level of evidence and grade of recommendation, all established through expert consensus.

Background: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize transplant benefits. Methods: This study retrospectively analyzed data from the Korean Network for Organ Sharing database, including 1,599 lung transplant candidates between September 2009 and December 2020. We developed the MaxBenefit LAS, combining a waitlist mortality model and a post-transplant survival model using elastic-net Cox regression, was assessed using area under the curve (AUC) values and Uno’s C-index. Its performance was compared to the US LAS in an independent cohort. Results: The waitlist mortality model showed strong predictive performance with AUC values of 0.834 and 0.818 in the training and validation cohorts, respectively. The post-transplant survival model also demonstrated good predictive ability (AUC: 0.708 and 0.685). The MaxBenefit LAS effectively stratified patients by risk, with higher scores correlating with increased waitlist mortality and decreased post-transplant mortality. The MaxBenefit LAS outperformed the conventional LAS in predicting waitlist death and identifying candidates with higher transplant benefits. Conclusion The MaxBenefit LAS offers a promising approach to optimizing lung allocation by balancing the urgency of candidates with their likelihood of survival post-transplant. This novel system has the potential to improve outcomes for lung transplant recipients and reduce waitlist mortality, providing a more equitable allocation of donor lungs.

Background: Recombinant human follicle-stimulating hormone (rhFSH) is commonly used to treat female infertility, but its short half-life necessitates multiple doses. Even corifollitropin alfa, with an extended half-life, requires supplementary injections of rhFSH after 7 days. This study aimed to develop and evaluate a long-acting follicle-stimulating hormone (FSH) formulation using anti-serum albumin Fab-associated (SAFA) technology to avoid additional injections and enhance ovarian function. Methods: SAFA-FSH was synthesized using a Chinese hamster ovary expression system. Its biological efficacy was confirmed through assays measuring its ability to stimulate cyclic adenosine monophosphate (cAMP) production, estradiol synthesis, and the expression of human cytochrome P450 family 19 subfamily A member 1 (hCYP19α1) and human steroidogenic acute regulatory protein (hSTAR) in human ovarian granulosa (KGN) cells. To evaluate the effects of SAFA-FSH, we compared its impact on serum estradiol levels and ovarian weight increase with that of rhFSH in Sprague-Dawley (SD) rats using the modified Steelman-Pohley test. Results: The results indicated that SAFA-FSH induces cAMP synthesis in KGN cells and upregulates the expression of hCYP19α1 and hSTAR in a dose-dependent manner. Female SD rats, aged 21 days, receiving daily subcutaneous human chorionic gonadotropin injections for 5 days exhibited a significant increase in serum estradiol levels and ovarian weight when administered SAFA-FSH on the first day or when given nine injections of rhFSH over 5 days. Notably, the group receiving SAFA-FSH on the first and third days demonstrated an even greater rise in serum estradiol levels and ovarian weight. Conclusion These findings suggest that SAFA-FSH presents a promising alternative to current rhFSH treatments for female infertility. However, further research is essential to thoroughly assess its safety and efficacy in clinical contexts.

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.

Purpose: This study investigated the impact of nusinersen on health-related quality of life (HRQoL), functional performance, and caregiver burden in patients with infantile-onset spinal muscular atrophy (SMA), addressing a growing interest in disease-modifying treatments. Methods: A 14-month observational study was conducted to evaluate changes in HRQoL and functional performance using the Pediatric Quality of Life Inventory (PedsQL) Infant Scales and the Pediatric Evaluation of Disability Inventory Computer Adaptive Test (PEDI-CAT). Caregiver burden was assessed through the Assessment of Caregiver Experience with Neuromuscular Disease (ACEND). Motor function was evaluated using the Children’s Hospital of Philadelphia Infant Test of Neuromuscular Disorders (CHOP INTEND). Correlations between CHOP INTEND scores, functional performance, and caregiver burden were analyzed. Results: Eight patients with infantile-onset SMA and their caregivers participated, with a median treatment initiation age of 4.6 months (range, 1.1 to 15.1). CHOP INTEND scores showed significant improvement (P<0.001), whereas all PedsQL Infant Scale scores declined. Conversely, the PEDI-CAT revealed significant enhancements in daily activities, mobility, and social-cognitive domains (all P<0.001). Caregiver burden lessened across most dimensions (P<0.001), with the exception of the time-related burden (P=0.731). Higher CHOP INTEND scores correlated with improvements in PEDI-CAT domains and a reduction in caregiver burden related to sitting/play and transfer activities. Conclusion The study demonstrates the positive effects of nusinersen on functional performance and caregiver burden in patients with infantile-onset SMA. However, discrepancies were observed in HRQoL outcomes, suggesting a need for further research that includes SMA-specific outcome measures to comprehensively assess the treatment's impact on patients' lives.