Background: Vitiligo is a skin disorder characterized by the loss of melanocytes (MCs), leading to depigmentation.While the exact mechanisms are unclear, the transcription factor Ets-1, known for its role in regulating matrix metalloproteinase expression and MC migration, is suspected to play a part. Ets-1 gene-deficient mice exhibit a vitiligo-like phenotype with spontaneous skin depigmentation, suggesting a direct link between Ets-1 deficiency and MC dysfunction. This study aimed to characterize the molecular and histological features of Ets-1 gene knockout (KO) mice to understand the underlying mechanisms of this depigmentation. Results: Transcriptomic analysis of depigmented and normal skin from Ets-1 KO and wild-type mice revealed significant differentially expressed genes (DEGs). KEGG pathway enrichment analysis demonstrated alterations in metabolic and signal transduction pathways, notably the downregulation of melanogenesis-related genes. RT-qPCR and immunohistochemistry confirmed reduced tyrosinase expression at both transcript and protein levels in the depigmented skin of KO mice. Protein-protein interaction network analysis of the DEGs highlighted a central network involving keratin proteins and discrete interactions regulating melanogenesis, stress response, and cellular signaling pathways. Conclusions These findings demonstrate that Ets-1 deficiency in mice leads to significant molecular and histological changes consistent with MC dysfunction and depigmentation. The observed downregulation of melanogenesisrelated genes and alterations in key signaling pathways provide valuable insights into the molecular basis of Ets-1’s role in MC maintenance and suggest potential therapeutic targets for skin pigmentation disorders, including vitiligo.

BACKGROUND: Depression among older adults is an important public health issue, and air and noise pollution have been found to contribute to exacerbation of depressive symptoms. This study examined the association of exposure to air and noise pollutants with clinically-newly-diagnosed depressive disorder. The mediating role of individual pro-inflammatory markers was explored. METHODS: We linked National Health Insurance claim data with 2998 healthy community-dwellers aged 55 and above who participated in the Healthy Aging Longitudinal Study between 2009 and 2013. Newly diagnosed depressive disorder was identified using diagnostic codes from the medical claim data. Pollutants were estimated using nationwide land use regression, including PM_2.5 and PM₁₀, carbon monoxide, ozone, nitrogen dioxide, sulfur dioxide, and road traffic noise. Cox proportional hazard models were employed to examine the association between pollutants and newly developed depressive disorders. The mediating effect of serum pro-inflammatory biomarkers on the relationship was examined. RESULTS: Among the 2998 participants, 209 had newly diagnosed depressive disorders. In adjusted Cox proportional hazard models, one interquartile range increase in PM_2.5 (8.53 µg/m³) was associated with a 17.5% increased hazard of developing depressive disorders. Other air pollutants and road traffic noise were not linearly associated with depressive disorder incidence. Levels of serum tumor necrosis factor receptor 1 mediated the relationship between PM_2.5 and survival time to newly onset depressive disorder. CONCLUSION PM_2.5 is related to an increased risk of newly developed depressive disorder among middle-aged and older adults, and the association is partially mediated by the pro-inflammatory marker TNF-R1.
Humans ; Particulate Matter/analysis* ; Male ; Female ; Middle Aged ; Longitudinal Studies ; Aged ; Incidence ; Air Pollutants/analysis* ; Environmental Exposure/adverse effects* ; Taiwan/epidemiology* ; Receptors, Tumor Necrosis Factor, Type I/blood* ; Proportional Hazards Models ; Biomarkers/blood* ; Depression/epidemiology* ; Aged, 80 and over ; Depressive Disorder/chemically induced* ; Risk Factors ; Air Pollution/adverse effects*

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

Objectives: Bipolar hemiarthroplasty is commonly performed to treat displaced femoral neck fractures in osteo porotic patients. This study aimed to assess the occurrence and outcomes of unplanned return visits to the emergency department (ED) within 90 days following bipolar hemiarthroplasty for displaced femoral neck fractures. Methods: The clinical data of 1322 consecutive patients who underwent bipolar hemiarthroplasty for osteoporotic femoral neck fractures at a tertiary medical center were analyzed. Data from the patients’ electronic medical records, including demographic information, comorbidities, and operative details, were collected. The risk factors and mortality rates were analyzed. Results: Within 90 days after surgery, 19.9% of patients returned to the ED. Surgery-related reasons accounted for 20.2% of the patient’s returns. Older age, a high Charlson comorbidity index score, chronic kidney disease, and a history of cancer were identified as significant risk factors for unplanned ED visits. Patients with uncemented implants had a significantly greater risk of returning to the ED due to periprosthetic fractures than did those with cemented implants (P = 0.04). Patients who returned to the ED within 90 days had an almost fivefold greater 1-year mortality rate (15.2% vs 3.1%, P < 0.001) and a greater overall mortality rate (26.2% vs 10.5%, P < 0.001). Conclusions This study highlights the importance of identifying risk factors for unplanned ED visits after bipolar hemiarthroplasty, which may contribute to a better prognosis. Consideration should be given to the use of cemented implants for hemiarthroplasty, as uncemented implants are associated with a greater risk of peri prosthetic fractures.

Objectives: This study aimed to present the Asia-Pacific consensus on long-term and sequential therapy for osteoporosis, offering evidence-based recommendations for the effective management of this chronic condition.The primary focus is on achieving optimal fracture prevention through a comprehensive, individualized approach. Methods: A panel of experts convened to develop consensus statements by synthesizing the current literature and leveraging clinical expertise. The review encompassed long-term anti-osteoporosis medication goals, first-line treatments for individuals at very high fracture risk, and the strategic integration of anabolic and anti resorptive agents in sequential therapy approaches. Results: The panelists reached a consensus on 12 statements. Key recommendations included advocating for anabolic agents as the first-line treatment for individuals at very high fracture risk and transitioning to anti resorptive agents following the completion of anabolic therapy. Anabolic therapy remains an option for in dividuals experiencing new fractures or persistent high fracture risk despite antiresorptive treatment. In cases of inadequate response, the consensus recommended considering a switch to more potent medications. The consensus also addressed the management of medication-related complications, proposing alternatives instead of discontinuation of treatment. Conclusions This consensus provides a comprehensive, cost-effective strategy for fracture prevention with an emphasis on shared decision-making and the incorporation of country-specific case management systems, such as fracture liaison services. It serves as a valuable guide for healthcare professionals in the Asia-Pacific region, contributing to the ongoing evolution of osteoporosis management.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.