Natural peloids originating from subsea depths of 200 m in the hupo basin, South Korea: physicochemical properties for potential pelotherapy applications.

The present study firstly reports surface sediment from the subsea depth of 200 m as a potential natural peloid. The fine-silt sediment exhibited a consistent clay mineral composition dominated by illite, chlorite, kaolinite, and diatomite. The most abundant clay mineral was illite/mica, with other minerals loosely packed in a face-to-face orientation. The thermal conductivity, specific heat capacity, and cation-exchange capacity of the sediment were in the range 0.855-0.885 W/m K, 2.718-2.821 J/g °C, and 23.06-32.96 cmol/kg, respectively. The concentrations of most toxic elements in the sediment were considerably lower than the limits set by domestic cosmetic regulations and other international standards. The analyzed samples exhibited similar properties to those of previously reported peloids, thus making them suitable for use in the field of pelotherapy; furthermore, the consistency in data across a wide peloid-distribution area is expected to enable economically viable mining. Future investigations should aim to to evaluate the long-term effects on the skin, the bioavailability of potentially hazardous substances, and the therapeutic efficacy for various skin conditions.

Expansive data, extensive model: Investigating discussion topics around LLM through unsupervised machine learning in academic papers and news.

This study presents a comprehensive exploration of topic modeling methods tailored for large language model (LLM) using data obtained from Web of Science and LexisNexis from June 1, 2020, to December 31, 2023. The data collection process involved queries focusing on LLMs, including "Large language model," "LLM," and "ChatGPT." Various topic modeling approaches were evaluated based on performance metrics, including diversity and coherence. latent Dirichlet allocation (LDA), nonnegative matrix factorization (NMF), combined topic models (CTM), and bidirectional encoder representations from Transformers topic (BERTopic) were employed for performance evaluation. Evaluation metrics were computed across platforms, with BERTopic demonstrating superior performance in diversity and coherence across both LexisNexis and Web of Science. The experiment result reveals that news articles maintain a balanced coverage across various topics and mainly focus on efforts to utilize LLM in specialized domains. Conversely, research papers are more concise and concentrated on the technology itself, emphasizing technical aspects. Through the insights gained in this study, it becomes possible to investigate the future path and the challenges that LLMs should tackle. Additionally, they could offer considerable value to enterprises that utilize LLMs to deliver services.

Deep-learning-based stock market prediction incorporating ESG sentiment and technical indicators.

As sustainability emerges as a crucial factor in the development of modern enterprises, integrating environmental, social, and governance (ESG) information into financial assessments has become essential. ESG indicators serve as important metrics in evaluating a company's sustainable practices and governance effectiveness, influencing investor trust and future growth potential, ultimately affecting stock prices. This study proposes an innovative approach that combines ESG sentiment index extracted from news with technical indicators to predict the S&P 500 index. By utilizing a deep learning model and exploring optimal window sizes, the study explores the best model through mean absolute percentage error (MAPE) as an evaluation metric. Additionally, an ablation test clarifies the influence of ESG and its causality with the S&P 500 index. The experimental results demonstrate improved predictive accuracy when considering ESG sentiment compared to relying solely on technical indicators or historical data. This comprehensive methodology enhances the advantage of stock price prediction by integrating technical indicators, which consider short-term fluctuations, with ESG information, providing long-term effects. Furthermore, it offers valuable insights for investors and financial market experts, validating the necessity to consider ESG for financial assets and introducing a new perspective to develop investment strategies and decision-making processes.

A Multicenter, Retrospective Comparison Study of Pregnancy Outcomes According to Placental Location in Placenta Previa.

Background: We investigated the association between placental location and pregnancy outcomes in placenta previa. Methods: This multi-center retrospective study enrolled 781 women who delivered between May 1999 and February 2020. We divided the dataset into anterior (n = 209) and posterior (n = 572) groups and compared the baseline characteristics and obstetric and neonatal outcomes. The adverse obstetric outcomes associated with placenta location were evaluated using a multivariate logistic analysis. Results: Gestational age at delivery in the anterior group (253.0 ± 21.6) was significantly lower than that in the posterior group (257.6 ± 19.1) (p = 0.008). The anterior group showed significantly higher parity, rates of previous cesarean section, non-vertex fetal positions, admissions for bleeding, emergency cesarean sections, transfusions, estimated blood loss, and combined placenta accrete spectrum (p < 0.05). In the multivariate analysis, the anterior group had higher rates of transfusion (OR 2.23; 95% CI 1.50-3.30), placenta accreta spectrum (OR 2.16; 95% CI 1.21-3.97), and non-vertex fetal positions (OR 2.47; 95% CI 1.09-5.88). Conclusions: These findings suggest that more caution is required in the treatment of patients with anterior placenta previa. Therefore, if placenta previa is diagnosed prenatally, it is important to determine the location of the body and prepare for massive bleeding in the anterior group.

ESG2PreEM: Automated ESG grade assessment framework using pre-trained ensemble models.

Incorporating environmental, social, and governance (ESG) criteria is essential for promoting sustainability in business and is considered a set of principles that can increase a firm's value. This research proposes a strategy using text-based automated techniques to rate ESG. For autonomous classification, data were collected from the news archive LexisNexis and classified as E, S, or G based on the ESG materials provided by the Refinitiv-Sustainable Leadership Monitor, which has over 450 metrics. In addition, Bidirectional Encoder Representations from Transformers (BERT), Robustly optimized BERT approach (RoBERTa), and A Lite BERT (ALBERT) models were trained to accurately categorize preprocessed ESG documents using a voting ensemble model, and their performances were measured. The accuracy of the ensemble model utilizing BERT and ALBERT was found to be 80.79% with batch size 20. Additionally, this research validated the performance of the framework for companies included in the Dow Jones Industrial Average (DJIA) and compared it with the grade provided by Morgan Stanley Capital International (MSCI), a globally renowned ESG rating agency known for having the highest creditworthiness. This study supports the use of sophisticated natural language processing (NLP) techniques to attain important knowledge from large amounts of text-based data to improve ESG assessment criteria established by different rating agencies.

Association between health literacy and self-management among middle-aged women: A systematic review.

OBJECTIVE: We aimed to review and synthesize the literature on the association between health literacy (HL) and self-management in middle-aged women aged 35-64 years and examine the definitions and measurements of HL. METHODS: Eleven electronic databases were used for searching specific terms. Experimental and non-experimental studies in English or Korean were included based on the eligibility criteria. Two authors independently conducted study selection, data extraction, and methodological quality assessment. RESULTS: One experimental and 13 non-experimental studies were included. Of the 11 studies that defined HL, nine conceptualized it as reflecting multidimensional HL. Four studies measured HL capturing all dimensions of the concept (i.e., accessing, understanding, appraising, and applying) and two studies used context-specific HL measurements. Women with greater HL challenges generally had lower self-management context, process, and outcomes across the health continuum. CONCLUSIONS: Enhancing HL is a critical strategy for improving self-management in middle-aged women. Future research should investigate the effectiveness of HL interventions on self-management considering multidimensional definitions and measures of HL. PRACTICE IMPLICATIONS: Health professionals should be alert to middle-aged women's HL and implement HL interventions that provide them with opportunities to access, understand, analyze, and utilize health-related information to effectively improve HL and engage in self-management.

A potential role of protein extractions from Metagonimus yokogawai in amelionating inflammation in patients with ankylosing spondylitis.

Helminth infections and their components has been recognized to have a positive impact on the immune system. This study aimed to investigate the potential of Metagonimus yokogawai-derived proteins (MYp) to provide protection against ankylosing spondylitis (AS) through modulation of immune responses. The cytotoxicity of MYp at various doses was first assessed using MTS and flow cytometry. Peripheral blood mononuclear cells (PBMCs) were collected from AS patients, and the production of inflammatory cytokines was analyzed through flow cytometry. In the experiments with SKG mice, MYp or vehicle was administered and inflammation was evaluated through immunohistochemistry and enzyme-linked immunosorbent assay. The results showed that MYp did not decrease cell viability of PBMCs even after 48 h. Additionally, the frequencies of IFN-γ and IL-17A producing cells were significantly reduced after MYp treatment in the PBMC cultures. Furthermore, MYp treatment significantly suppressed arthritis and enthesitis in the SKG mouse model. The results suggest the first evidence that MYp can effectively alleviate clinical symptoms and restore cytokine balance in patients with AS.

Stand age-driven tree size variation and stand type regulate aboveground biomass in alpine-subalpine forests, South Korea.

Alpine and subalpine forests in mountains worldwide are ecologically significant because of their unique biodiversity and increased vulnerability to climate change. This study was conducted to explore the possibilities and ways to preserve the ecological diversity of alpine-subalpine forests and their function as important carbon sinks. In this study, data from 664 plots (400 m2) were collected in the alpine-subalpine zones above 1000 m elevation in South Korea, we divided 664 plots into four stand types: conifer, conifer-dominant mixed, broadleaved-dominant mixed, and broadleaved stands. Abiotic drivers and forest successional stage-related factor including topographic, climatic drivers and stand age class were used. Biotic drivers including taxonomic, phylogenetic, functional, stand structural diversity, and community-weighted mean of functional traits were used to find independent variables controlling aboveground biomass (AGB) for each stand type. We employed multi-model averaging approach as well as piecewise structural equation modeling (pSEM) for the identification of the most influential variables affecting AGB in each stand type of alpine-subalpine forests and to quantify their interrelationships and strengths. The main results showed that tree size variation (i.e., DBH STD) induced by stand age had direct effects on AGB, with varying degrees of significance (ß) ranging from 0.146 to 0.241 across all stand types in alpine-subalpine forests. Following these results, as forest succession progresses, tree species adapted to the specific environmental conditions, such as topography and climate, become dominant by creating their own niche, which increases AGB in each stand type. Additionally, climatic and topographic conditions played an important role in controlling biotic drivers depending on the stand type. In this study, we suggest that AGB should be managed and conserved depending on forest stand types according to forest succession. Furthermore, increasing size variation among tree individuals through proper forest treatments is important for increasing AGB in alpine-subalpine forests.

Exosome-mediated delivery of super-repressor IκBα alleviates inflammation and joint damages in rheumatoid arthritis.

BACKGROUND: This study aims to investigate the potential anti-inflammatory effects of exosomes engineered to carry super-repressor IκB (Exo-srIκB), an exosome-based NF-κB inhibitor, in the context of RA. METHODS: Peripheral blood mononuclear cells (PBMCs) and synovial fluid mononuclear cells (SFMCs) were collected from patients diagnosed with RA and treated with Exo-srIκB to test the therapeutic potential. Flow cytometry analysis was performed to assess the production of inflammatory cytokines (IL-17A and GM-CSF) by the cells. ELISA was utilized to measure the levels of TNF-α, IL-17A, IL-6, and GM-CSF. Arthritis was induced in SKG mice by intraperitoneal injection of curdlan. DBA/1 J mice were used in collagen-induced arthritis (CIA) experiments. After the development of arthritis, mice were injected with either Exo-Naïve (control exosome) or Exo-srIκB. Arthritis scores were recorded biweekly, and histological observations of the ankle joint were conducted using H&E and safranin-O staining. Additionally, bone erosion was evaluated using micro-CT imaging. RESULTS: In the ex vivo study involving human PBMCs and SFMCs, treatment with Exo-srIκB demonstrated a notable reduction in inflammatory cytokines. Furthermore, in both the SKG and CIA models, Exo-srIκB treatment exhibited significant reductions in inflammation, cartilage destruction, and bone erosion within the joint tissues when compared to the Exo-Naive control group. Additionally, the radiographic score assessed through microCT showed a significant decrease compared to the Exo-Naive control group. CONCLUSION: Overall, these findings suggest that Exo-srIκB possesses anti-inflammatory properties in human RA cells and animal models, making it a promising therapeutic candidate for the treatment of RA.

Artificial Intelligence Model Assisting Thyroid Nodule Diagnosis and Management: A Multicenter Diagnostic Study.

CONTEXT: It is not clear how to integrate artificial intelligence (AI)-based models into diagnostic workflows. OBJECTIVE: To develop and validate a deep-learning-based AI model (AI-Thyroid) for thyroid cancer diagnosis, and to explore how this improves diagnostic performance. METHODS: The system was trained using 19 711 images of 6163 patients in a tertiary hospital (Ajou University Medical Center; AUMC). It was validated using 11 185 images of 4820 patients in 24 hospitals (test set 1) and 4490 images of 2367 patients in AUMC (test set 2). The clinical implications were determined by comparing the findings of six physicians with different levels of experience (group 1: 4 trainees, and group 2: 2 faculty radiologists) before and after AI-Thyroid assistance. RESULTS: The area under the receiver operating characteristic (AUROC) curve of AI-Thyroid was 0.939. The AUROC, sensitivity, and specificity were 0.922, 87.0%, and 81.5% for test set 1 and 0.938, 89.9%, and 81.6% for test set 2. The AUROCs of AI-Thyroid did not differ significantly according to the prevalence of malignancies (>15.0% vs ≤15.0%, P = .226). In the simulated scenario, AI-Thyroid assistance changed the AUROC, sensitivity, and specificity from 0.854 to 0.945, from 84.2% to 92.7%, and from 72.9% to 86.6% (all P < .001) in group 1, and from 0.914 to 0.939 (P = .022), from 78.6% to 85.5% (P = .053) and from 91.9% to 92.5% (P = .683) in group 2. The interobserver agreement improved from moderate to substantial in both groups. CONCLUSION: AI-Thyroid can improve diagnostic performance and interobserver agreement in thyroid cancer diagnosis, especially in less-experienced physicians.

Physiological gradient in lumbar spine fat fraction and R2* and its impact on osteoporosis diagnosis.

BACKGROUND: Bone marrow adiposity and R2* have been explored as an imaging biomarker for osteoporosis. Chemical shift-encoded MRI (CSE-MRI) is a method that allows for relatively accurate measurement of adiposity and R2* in bone marrow in a simple manner. Additionally, there are reports of a physiological gradient of fat distribution in the lumbar spine. This physiological gradient of fat distribution can potentially impact the prediction of osteoporosis. Furthermore, the distribution of R2* is not well understood. PURPOSE: This study examined how lumbar spine fat fraction (FF) and R2* change with different levels of the lumbar spine, how they influence osteoporosis prediction, and how they change according to measurement methods. STUDY DESIGN/SETTING: Cross-sectional study using retrospectively collected data. PATIENT SAMPLE: The study included patients who underwent dual-energy X-ray absorptiometry and lumbar spine CSE-MRI within one-month intervals between 2017 and 2022. OUTCOME MEASURES: Reproducibility of FF and R2* based on measurement techniques, changes in FF and R2* according to vertebral level and osteoporosis status, and diagnostic power of osteoporosis based on vertebral level. METHODS: Patients were categorized into the normal bone density, osteopenia, and osteoporosis groups based on bone mineral density. The relationship between groups and spine level before and after BMD adjustment was investigated using generalized estimating equations. Comparisons between the three groups and various measures of reliability were conducted using intraclass correlation coefficient. The diagnostic performance for predicting osteoporosis was evaluated with a receiver operating characteristic curve. RESULTS: Comparing the three groups, FF increased with osteoporosis severity, while R2* decreased (p<.001). The intra/inter-rater agreement for FF and R2* was excellent. A physiological gradient within individuals was observed, where FF increased towards the lower lumbar spine (p=.002). R2* tended to decrease, but it was not statistically significant (p=.218). There was no statistically significant difference in the diagnosis of osteoporosis based on FF or R2* across different lumbar spine levels. CONCLUSIONS: There was an increase in FF and a decrease in R2* from T12 to L5. However, the predictive power of osteoporosis did not significantly differ between each level.

Clinical effects of bacteremia in sepsis patients with community-acquired pneumonia.

BACKGROUND: Data regarding the clinical effects of bacteremia on severe community-acquired pneumonia (CAP) are limited. Thus, we investigated clinical characteristics and outcomes of severe CAP patients with bacteremia compared with those of subjects without bacteremia. In addition, we evaluated clinical factors associated with bacteremia at the time of sepsis awareness. METHODS: We enrolled sepsis patients diagnosed with CAP at emergency departments (EDs) from an ongoing nationwide multicenter observational registry, the Korean Sepsis Alliance, between September 2019 and December 2020. For evaluation of clinical factors associated with bacteremia, we divided eligible patients into bacteremia and non-bacteremia groups, and logistic regression analysis was performed using the clinical characteristics at the time of sepsis awareness. RESULT: During the study period, 1,510 (47.9%) sepsis patients were caused by CAP, and bacteremia was identified in 212 (14.0%) patients. Septic shock occurred more frequently in the bacteremia group than in the non-bacteremia group (27.4% vs. 14.8%; p < 0.001). In multivariable analysis, hematologic malignancies and septic shock were associated with an increased risk of bacteremia. However, chronic lung disease was associated with a decreased risk of bacteremia. Hospital mortality was significantly higher in the bacteremia group than in the non-bacteremia group (27.3% vs. 40.6%, p < 0.001). The most prevalent pathogen in blood culture was Klebsiella pneumoniae followed by Escherichia coli in gram-negative pathogens. CONCLUSION: The incidence of bacteremia in severe CAP was low at 14.0%, but the occurrence of bacteremia was associated with increased hospital mortality. In severe CAP, hematologic malignancies and septic shock were associated with an increased risk of bacteremia.

Differential patterns of lifestyle behaviors among low- and high-income postmenopausal women in Korea: a latent class analysis.

BACKGROUND: Healthy lifestyle behaviors among postmenopausal women are important to prevent chronic diseases and improve health later in life. Heterogeneous lifestyle patterns may exist among postmenopausal women, and socioeconomic status (SES) is a critical determinant of lifestyle behaviors. However, little is known about distinct SES-specific patterns of lifestyle behaviors among postmenopausal women. Thus, this study used latent class analysis to identify subgroups of postmenopausal women with different health behaviors according to income and to examine the predictors of income-specific subgroups. METHODS: We analyzed nationally representative data from the Eighth Korea National Health and Nutrition Examination Survey, collected in 2019 and 2020. We used nine lifestyles (i.e., current smoking and drinking, high-risk drinking, walking, muscle-strengthening exercise, sleep, vegetable and fruit intakes, and weight control efforts). We conducted a multiple-group latent class analysis using monthly household income as a proxy for SES. The monthly household income variable was calculated by standardizing monthly household income by the number of family members and then divided into quintiles. We classified the participants into low- (i.e., Q1 and Q2) and high-income (i.e., Q3, Q4, and Q5) groups. RESULTS: Although the three-class models best fit the data of low- and high-income groups, we found differential patterns by income: (a) for low-income group, "relatively healthy (RH)," "lowest physical activity, insufficient fruit intake, and no intention to control weight," and "high-risk drinking and insufficient fruit intake" classes and (b) for high-income group, "RH," "lowest physical activity," "high-risk drinking and insufficient fruit intake and sleep" classes. The proportion of the RH class was largest in both groups. However, lifestyle patterns in low-income group showed multiple and unhealthy characteristics than those in high-income group. CONCLUSIONS: This study suggests that different underlying lifestyle patterns exist in postmenopausal women with low- and high-income. To promote healthy behaviors among postmenopausal women, health professionals should develop and apply lifestyle interventions tailored to lifestyle pattern characteristics according to income.

Design of an effective small expression tag to enhance GPCR production in E. coli-based cell-free and whole cell expression systems.

G protein-coupled receptors (GPCRs) play crucial roles in sensory, immune, and tumor metastasis processes, making them valuable targets for pharmacological and sensing applications in various industries. However, most GPCRs have low production yields in Escherichia coli (E. coli) expression systems. To overcome this limitation, we introduced AT10 tag, an effective fusion tag that could significantly enhance expression levels of various GPCRs in E. coli and its derived cell-free protein synthesis (CFPS) system. This AT10 tag consisted of an A/T-rich gene sequence designed via optimization of translation initiation rate. It is translated into a short peptide sequence of 10 amino acids at the N-terminus of GPCRs. Additionally, effector proteins could be utilized to suppress cytotoxicity caused by membrane protein expression, further boosting GPCR production in E. coli. Enhanced expression of various GPCRs using this AT10 tag is a promising approach for large-scale production of functional GPCRs in E. coli-based CFPS and whole cell systems, enabling their potential utilization across a wide range of industrial applications.

CT and MR for bone mineral density and trabecular bone score assessment in osteoporosis evaluation.

Dual energy X-ray absorptiometry (DXA) is widely used modality for measuring bone mineral density (BMD). DXA is used to measure the quantitative areal BMD of bone, but has the disadvantage of not reflecting the bone architecture. To compensate for this disadvantage, trabecular bone score (TBS), a qualitative parameter of trabecular microarchitecture, is used. Meanwhile, there have been recent attempts to diagnose osteoporosis using the Hounsfield unit (HU) from CT and MR-based proton density fat fraction (PDFF) measurements. In our study, we aimed to find out the correlation between HU/PDFF and BMD/TBS, and whether osteoporosis can be diagnosed through HU/PDFF. Our study revealed that the HU value showed a moderate to good positive correlation with BMD and TBS. PDFF showed a fair negative correlation with BMD and TBS. In diagnosing osteopenia and osteoporosis, the HU value showed good performance, whereas the PDFF showed fair performance. In conclusion, both HU values and PDFF can play a role in predicting BMD and TBS. Both HU values and PDFF can be used to predict osteoporosis; further, CT is expected to show better results.

Impact of a cumulative positive fluid balance during the first three ICU days in patients with sepsis: a propensity score-matched cohort study.

BACKGROUND: The optimal strategy for fluid management during the first few days of ICU in sepsis patients remains controversial. We aimed to investigate the impact of cumulative fluid balance during the first three days of ICU on the mortality of patients with sepsis. METHODS: This study analyzed prospectively collected data from the Korean Sepsis Alliance Database, which registered 11,981 sepsis patients from 20 hospitals. We selected three propensity score-matched cohorts consisting of patients with a negative or positive cumulative fluid balance during the first three ICU days: from ICU admission to the first midnight as the D1 cohort, until the second midnight as the D2 cohort, and until the third midnight as the D3 cohort. The propensity score for fluid balance was calculated using covariates including the amount of fluid output during the first three ICU days. The primary outcome was mortality at day 28 in the ICU. RESULTS: From a total of 11,981 patients, 2516 patients were included for propensity score matching. After matching in a 1:1 ratio, there were 483, 373, and 392 matched pairs of patients assigned to the D1, D2, and D3 cohorts, respectively. In the D1 cohort, there were no significant differences in mortality at day 28 (hazard ratio [HR], 1.17; 95% confidence interval [CI] 0.85-1.60; P = 0.354) between the two groups. The positive fluid groups in both the D2 (HR, 2.13; 95% CI 1.48-3.06; P < 0.001) and D3 (HR, 1.56; 95% CI 1.10-2.22; P = 0.012) cohorts had significantly higher mortality rates than the negative fluid groups. CONCLUSIONS: In patients with sepsis, a positive fluid balance on the first ICU day was not associated with mortality at day 28. In contrast, cumulative positive fluid balances on the second and third ICU days were associated with higher mortality at day 28.

Associations Between Gender-Specific Substance Use Patterns and Mental Health Among Adolescents in the Republic of Korea: A Latent Class Analysis.

PURPOSE: Although gender differences in adolescent substance use are complex and substance use accompanies mental health problems, most previous studies have focused on gender-specific association between single substance use and mental health. This study aimed to investigate gender-specific substance use patterns and to examine their association with mental health characteristics. METHODS: Nationally representative data from the Korea Youth Risk Behavior Survey collected in 2018 were analyzed. To identify substance use patterns among male adolescents (n = 30,463) and female adolescents (n = 29,577), multiple-group latent class analysis was conducted using eight substance use indicators. In addition, we conducted a latent class analysis with covariates to examine the association between substance use patterns and mental health characteristics. RESULTS: Among both gender samples, the four-class model best fit the data: nonusers (86.4%), frequent smokers (2.9%), risky drinkers (7.1%), and heavy tobacco and alcohol users with lifetime heated tobacco product use (3.6%) for male adolescents, and nonusers (89.8%), frequent smokers (0.5%), risky drinkers (8.0%), and heavy tobacco and alcohol users with a drunkenness episode (1.7%) for female adolescents. Depression, suicidal plans, and suicidal attempts predicted the latent class model for both genders. In addition, stress level predicted the latent class model for female adolescents. CONCLUSIONS: The findings indicate that homogeneous patterns of substance use by gender are differentially associated with mental health problems. Therefore, health professionals should develop interventions tailored to gender-specific substance use patterns, taking into account the mental health characteristics of each pattern.

Body Composition and Bone Mineral Density in Postmenopausal Women with Advanced Knee Osteoarthritis Undergoing Surgical Treatment.

OBJECTIVES: This study aimed to demonstrate the bone mineral density (BMD) and body composition in postmenopausal women with knee osteoarthritis (OA) who underwent surgical treatment, such as total knee arthroplasty, osteotomy, or meniscectomy. METHODS: A total of 254 women with OA aged 50 years who underwent surgical treatment were enrolled in this study. We evaluated obesity-related factors, muscle components, and BMD using dual-energy X-ray absorptiometry. RESULTS: No significant differences were noted in the BMD of the hip joint between the symptomatic side of the leg with knee OA and the contralateral side. However, when comparing the BMD of each component, the results indicated a significantly higher BMD in the obesity group based on body mass index (BMI). When defining sarcopenic obesity (SO) using various indicators of obesity (BMI, the estimated visceral adipose tissue area, android/gynoid ratio, and total body fat percentage), the prevalence of SO in the OA group who underwent surgical treatment ranged from 22.0% to 49.6%. CONCLUSIONS: This study investigated obesity-related factors in patients with advanced knee OA who underwent surgery, revealing a high prevalence of overweight/obese individuals, the presence of SO, and a complex relationship between obesity, body composition, and bone density, highlighting the potential protective effects of weight-bearing on bone health while exploring the impact of sarcopenia on bone density differences in the context of OA. Depending on various definitions of obesity, diverse proportions of SO in patients with OA have been observed, and further detailed research is required to understand its impact on the condition.

Bone-Targeted Delivery of Cell-Penetrating-RUNX2 Fusion Protein in Osteoporosis Model.

The onset of osteoporosis leads to a gradual decrease in bone density due to an imbalance between bone formation and resorption. To achieve optimal drug efficacy with minimal side effects, targeted drug delivery to the bone is necessary. Previous studies have utilized peptides that bind to hydroxyapatite, a mineral component of bone, for bone-targeted drug delivery. In this study, a hydroxyapatite binding (HAB) tag is fused to 30Kc19α-Runt-related transcription factor 2 (RUNX2) for bone-targeting. This recombinant protein can penetrate the nucleus of human mesenchymal stem cells (hMSCs) and act as a master transcription factor for osteogenesis. The HAB tag increases the binding affinity of 30Kc19α-RUNX2 to mineral deposition in mature osteoblasts and bone tissue, without affecting its osteogenic induction capability. In the osteoporosis mouse model, intravenous injection of HAB-30Kc19α-RUNX2 results in preferential accumulation in the femur and promotes bone formation while reducing toxicity in the spleen. These findings suggest that HAB-30Kc19α-RUNX2 may be a promising candidate for bone-targeted therapy in osteoporosis.

Effects of light-emitting diode therapy on hand stiffness and pain in non-steroidal anti-inflammatory drug-refractory patients with tenosynovitis.

Objective: The objective of this study was to evaluate the safety and efficacy of light-emitting diode therapy (LEDT) in the management of pain and stiffness in patients with refractory hand tenosynovitis to non-steroidal anti-inflammatory drugs. Methods: A total of 12 patients were enrolled in the study and received LEDT twice a week for four weeks. Sociodemographic, clinical, and laboratory data were collected, and the visual analog scale (VAS) pain and stiffness scores of each hand were assessed every two weeks. The thickness of the flexor tendon in the patients' hand was evaluated using ultrasonography. To investigate the molecular effects of LEDT, we measured the expression levels of type III collagen in tendon cells, with and without LEDT treatment. Results: After undergoing LEDT, participants showed clinically significant improvements in VAS pain scores at weeks 2, 4, and 8 compared to their baseline, and in VAS stiffness scores at weeks 4 and 8. According to the ultrasonography results, there was a decreasing tendency in tendon thickness for each finger in week 8 compared to the baseline, but the difference was not statistically significant. No adverse events were reported. Additionally, our results indicated a significant increase in type III collagen levels in the LEDT group compared to the control group (1.48±0.18 vs. 0.99±0.02, p=0.031), indicating a potential molecular mechanism for the observed clinical improvements. Conclusion: LEDT may provide a viable alternative to pharmacological treatments in the future, due to its simple and easy method of administration.