Alzheimer disease (AD) diagnosis is confirmed using a medley of modalities, such as the detection of amyloid-β (Aβ) neuritic plaques and neurofibrillary tangles with positron electron tomography (PET) or the appraisal of irregularities in cognitive function with examinations. Although these methods have been efficient in confirming AD pathology, the rising demand for earlier intervention during pathogenesis has led researchers to explore the diagnostic potential of fluid biomarkers in cerebrospinal fluid (CSF) and plasma. Since CSF sample collection is invasive and limited in quantity, biomarker detection in plasma has become more attractive and modern advancements in technology has permitted more efficient and accurate analysis of plasma biomolecules. In this study, we found that a composite of standard factors, Aβ40 and total tau levels in plasma, divided by the variation factor, plasma Aβ42 level, provide better correlation with amyloid neuroimaging and neuropsychological test results than a level comparison between total tau and Aβ42 in plasma. We collected EDTA-treated blood plasma samples of 53 subjects, of randomly selected 27 AD patients and 26 normal cognition (NC) individuals, who received amyloid-PET scans for plaque quantification, and measured plasma levels of Aβ40, Aβ42, and total tau with digital enzyme-linked immunosorbent assay (ELISA) in a blinded manner. There was difficulty distinguishing AD patients from controls when analyzing biomarkers independently. However, significant differentiation was observed between the two groups when comparing individual ratios of total-tau×Aβ40/Aβ42. Our results indicate that collectively comparing fluctuations of these fluid biomarkers could aid in monitoring AD pathogenesis.

Alzheimer disease (AD) diagnosis is confirmed using a medley of modalities, such as the detection of amyloid-β (Aβ) neuritic plaques and neurofibrillary tangles with positron electron tomography (PET) or the appraisal of irregularities in cognitive function with examinations. Although these methods have been efficient in confirming AD pathology, the rising demand for earlier intervention during pathogenesis has led researchers to explore the diagnostic potential of fluid biomarkers in cerebrospinal fluid (CSF) and plasma. Since CSF sample collection is invasive and limited in quantity, biomarker detection in plasma has become more attractive and modern advancements in technology has permitted more efficient and accurate analysis of plasma biomolecules. In this study, we found that a composite of standard factors, Aβ40 and total tau levels in plasma, divided by the variation factor, plasma Aβ42 level, provide better correlation with amyloid neuroimaging and neuropsychological test results than a level comparison between total tau and Aβ42 in plasma. We collected EDTA-treated blood plasma samples of 53 subjects, of randomly selected 27 AD patients and 26 normal cognition (NC) individuals, who received amyloid-PET scans for plaque quantification, and measured plasma levels of Aβ40, Aβ42, and total tau with digital enzyme-linked immunosorbent assay (ELISA) in a blinded manner. There was difficulty distinguishing AD patients from controls when analyzing biomarkers independently. However, significant differentiation was observed between the two groups when comparing individual ratios of total-tau×Aβ40/Aβ42. Our results indicate that collectively comparing fluctuations of these fluid biomarkers could aid in monitoring AD pathogenesis.

Alzheimer disease (AD) diagnosis is confirmed using a medley of modalities, such as the detection of amyloid-β (Aβ) neuritic plaques and neurofibrillary tangles with positron electron tomography (PET) or the appraisal of irregularities in cognitive function with examinations. Although these methods have been efficient in confirming AD pathology, the rising demand for earlier intervention during pathogenesis has led researchers to explore the diagnostic potential of fluid biomarkers in cerebrospinal fluid (CSF) and plasma. Since CSF sample collection is invasive and limited in quantity, biomarker detection in plasma has become more attractive and modern advancements in technology has permitted more efficient and accurate analysis of plasma biomolecules. In this study, we found that a composite of standard factors, Aβ40 and total tau levels in plasma, divided by the variation factor, plasma Aβ42 level, provide better correlation with amyloid neuroimaging and neuropsychological test results than a level comparison between total tau and Aβ42 in plasma. We collected EDTA-treated blood plasma samples of 53 subjects, of randomly selected 27 AD patients and 26 normal cognition (NC) individuals, who received amyloid-PET scans for plaque quantification, and measured plasma levels of Aβ40, Aβ42, and total tau with digital enzyme-linked immunosorbent assay (ELISA) in a blinded manner. There was difficulty distinguishing AD patients from controls when analyzing biomarkers independently. However, significant differentiation was observed between the two groups when comparing individual ratios of total-tau×Aβ40/Aβ42. Our results indicate that collectively comparing fluctuations of these fluid biomarkers could aid in monitoring AD pathogenesis.

Alzheimer disease (AD) diagnosis is confirmed using a medley of modalities, such as the detection of amyloid-β (Aβ) neuritic plaques and neurofibrillary tangles with positron electron tomography (PET) or the appraisal of irregularities in cognitive function with examinations. Although these methods have been efficient in confirming AD pathology, the rising demand for earlier intervention during pathogenesis has led researchers to explore the diagnostic potential of fluid biomarkers in cerebrospinal fluid (CSF) and plasma. Since CSF sample collection is invasive and limited in quantity, biomarker detection in plasma has become more attractive and modern advancements in technology has permitted more efficient and accurate analysis of plasma biomolecules. In this study, we found that a composite of standard factors, Aβ40 and total tau levels in plasma, divided by the variation factor, plasma Aβ42 level, provide better correlation with amyloid neuroimaging and neuropsychological test results than a level comparison between total tau and Aβ42 in plasma. We collected EDTA-treated blood plasma samples of 53 subjects, of randomly selected 27 AD patients and 26 normal cognition (NC) individuals, who received amyloid-PET scans for plaque quantification, and measured plasma levels of Aβ40, Aβ42, and total tau with digital enzyme-linked immunosorbent assay (ELISA) in a blinded manner. There was difficulty distinguishing AD patients from controls when analyzing biomarkers independently. However, significant differentiation was observed between the two groups when comparing individual ratios of total-tau×Aβ40/Aβ42. Our results indicate that collectively comparing fluctuations of these fluid biomarkers could aid in monitoring AD pathogenesis.

Objectives: This study aimed to investigate the current status of periodontal disease programs implemented by public health centers in the Republic of Korea. Methods: An explanatory survey was conducted by the Ministry of Health and Welfare from October to November 2023. The survey focused on the periodontal programs and the implementation status across different stages. Distributed and collected via Google Forms, the survey targeted 196 oral health teams within public health centers in Korea. A total of 109 public health centers responded to the study questionnaire, yielding a participation rate of 55.6%. Data were analyzed using IBM SPSS Statistics for Windows, version 26. Results: A majority of periodontal disease programs were implemented exclusively by oral health teams, with a rate of 33.0%. The implementation rate of collaboration with home-visiting health teams was 17.4% and with other teams was 10.1%. The implementation rates of periodontal management across stages were as follows: 11.9% for periodontal examination, 18.3% for periodontal treatment, and 11.9% for sustainable periodontal care. Conclusions Periodontal disease programs are predominantly conducted by oral health teams with limited collaboration across other health teams. Additionally, periodontal management activities, such as examinations and treatments, remain insufficient. Integration between oral health teams and other health teams within public health centers or private dental clinics should be improved.

Objectives: This study aimed to investigate the current status of periodontal disease programs implemented by public health centers in the Republic of Korea. Methods: An explanatory survey was conducted by the Ministry of Health and Welfare from October to November 2023. The survey focused on the periodontal programs and the implementation status across different stages. Distributed and collected via Google Forms, the survey targeted 196 oral health teams within public health centers in Korea. A total of 109 public health centers responded to the study questionnaire, yielding a participation rate of 55.6%. Data were analyzed using IBM SPSS Statistics for Windows, version 26. Results: A majority of periodontal disease programs were implemented exclusively by oral health teams, with a rate of 33.0%. The implementation rate of collaboration with home-visiting health teams was 17.4% and with other teams was 10.1%. The implementation rates of periodontal management across stages were as follows: 11.9% for periodontal examination, 18.3% for periodontal treatment, and 11.9% for sustainable periodontal care. Conclusions Periodontal disease programs are predominantly conducted by oral health teams with limited collaboration across other health teams. Additionally, periodontal management activities, such as examinations and treatments, remain insufficient. Integration between oral health teams and other health teams within public health centers or private dental clinics should be improved.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Purpose: To evaluate the correlation between matrix metalloproteinase-9 (MMP-9) point-of-assay and clinical symptoms and signs of dry eye disease. Methods: We performed a retrospective study for patients diagnosed with dry eye. MMP-9 (InflammaDry) was performed on 235 patients. Patients were assessed using Schirmer test, corneal staining score, tear film breakup time (TBUT) and the Ocular Surface Disease Index (OSDI). Results: The score of Schirmer test was lower significantly in MMP-9 positive group than in MMP-9 negative group (for each 4.21 ± 5.80 mm, 5.96 ± 8.14 mm; p = 0.035). TBUT was shorter significantly in MMP-9 positive group than in MMP-9 negative group (for each 5.46 ± 4.06 s, 8.27 ± 4.75 s; p = 0.0008). The ratio of positive corneal stain (for each 83%, 31%) and OSDI even or greater than 13 (for each 80%, 75%) was significantly higher in MMP-9 positive group than in MMP-9 negative group (p = 0.00001, p = 0.0044). The value of MMP-9 point-of-care assay showed showed the negative correlation with Schirmer test (Rs = 0.383, p < 0.001), and TBUT (Rs = 0.310, p < 0.05), and showed the positive correlation with corneal staining score (Rs = 0.527, p < 0.001), OSDI (Rs = 0.510, p < 0.001). Conclusions MMP-9 point-of-assay accords with clinical symptoms and signs of Dry eye disease, and may be helpful in diagnosing Dry eye disease.

Objectives: This study aimed to investigate the current status of periodontal disease programs implemented by public health centers in the Republic of Korea. Methods: An explanatory survey was conducted by the Ministry of Health and Welfare from October to November 2023. The survey focused on the periodontal programs and the implementation status across different stages. Distributed and collected via Google Forms, the survey targeted 196 oral health teams within public health centers in Korea. A total of 109 public health centers responded to the study questionnaire, yielding a participation rate of 55.6%. Data were analyzed using IBM SPSS Statistics for Windows, version 26. Results: A majority of periodontal disease programs were implemented exclusively by oral health teams, with a rate of 33.0%. The implementation rate of collaboration with home-visiting health teams was 17.4% and with other teams was 10.1%. The implementation rates of periodontal management across stages were as follows: 11.9% for periodontal examination, 18.3% for periodontal treatment, and 11.9% for sustainable periodontal care. Conclusions Periodontal disease programs are predominantly conducted by oral health teams with limited collaboration across other health teams. Additionally, periodontal management activities, such as examinations and treatments, remain insufficient. Integration between oral health teams and other health teams within public health centers or private dental clinics should be improved.

Tuberculous pericarditis is an extrapulmonary manifestation of tuberculosis that is most commonly associated with pericardial thickening, effusion, and calcification. We present a case of tuberculous pericarditis mimicking a malignant pericardial tumor in a 77-year-old male. CT revealed an irregular and nodular pericardial thickening. MRI revealed high signal intensity on T1-weighted fat-suppressed images and peripheral rim enhancement after gadolinium administration. MRI can be helpful in determining the differential diagnoses in cases of tuberculous pericarditis with nonspecific imaging findings.