Ephs in cancer progression: complexity and context-dependent nature in signaling, angiogenesis and immunity.

Eph receptors constitute the largest family of receptor tyrosine kinases, comprising 14 distinct members classified into two subgroups: EphAs and EphBs.. Despite their essential functions in normal physiological processes, accumulating evidence suggests that the involvement of the Eph family in cancer is characterized by a dual and often contradictory nature. Research indicates that Eph/ephrin bidirectional signaling influences cell-cell communication, subsequently regulating cell migration, adhesion, differentiation and proliferation. The contradictory functionalities may arise from the diversity of Eph signaling pathways and the heterogeneity of different cancer microenvironment. In this review, we aim to discuss the dual role of the Eph receptors in tumor development, attempting to elucidate the paradoxical functionality through an exploration of Eph receptor signaling pathways, angiogenesis, immune responses, and more. Our objective is to provide a comprehensive understanding of the molecular mechanisms underlying tumor development. Additionally, we will explore the evolving landscape of utilizing Eph receptors as potential targets for tumor therapy and diagnostic tools.

Online-merge-offline (OMO)-based music therapy for asthmatic children during the COVID-19 pandemic in China.

The purpose of this study is to evaluate online-merge-offline (OMO)-based music therapy (MT) as a complementary option for asthma management in pediatric patients. A total of 86 children diagnosed with mild asthma were enrolled and treated with the same drug therapy. They were assigned into three groups: Music I group (standard medical care plus a single individualized MT session along with singing training and breathing exercise), Music II group (similar as Music I as well as further wind instrument playing), and Control group (standard medical care). Primary endpoints included pulmonary function tests FEV1, FVC, FEV1/FVC, MMEF 75/25, and PEF, c-ACT, PAQLQ, and PACQLQ. After 6 months of continuous intervention of MT, significant differences in FEV1, FVC, MMEF75/25, PEF, c-ACT score, PAQLQ, PACQLQ (p < 0.001), and FEV1/FVC (p < 0.05) were observed among Music I, Music II, and Control groups. Besides, FEV1, FVC, FEV1/FVC, MMEF75/25, and PEF showed positive trends in Music I and Music II groups compared to those in Control group (p < 0.05). The c-ACT score of children was significantly increased in Music I (p < 0.001) and II (p < 0.001) groups in contrast with Control group. Children in Music I and II groups had better quality of life than those in Control group (PAQLQ, p < 0.001), and the parents in Music I and II groups also showed better quality of life than those in Control group (PACQLQ, p < 0.001).     Conclusion: As a child-friendly, low-risk, and convenient intervention, the OMO-based MT has a positive impact on pediatric asthma management during the COVID-19 pandemic. What is Known: • A few findings proved the positive effect of MT on pediatric asthma. What is New: • Our study further proving the validation and effectiveness of MT with OMO-based model on pediatric asthma, wind instrument playing has a greater impact on pediatric asthma control via small airways and might be recommended to mix to singing and breathing to improve effectiveness of MT for asthmatic children.

Develop a bone mineral density T-score distribution nomograms based on osteoporosis risk factors for middle-aged and older adults.

PURPOSE: This study aimed to understand how age, health status, and lifestyle impact bone mineral density (BMD) in middle-aged and older adults, focusing on predicting osteoporosis risk. METHODS: This study included 2836 participants aged 50-88 from the Health Improvement Program of Bone (HOPE) conducted from 2021 to 2023. We used logistic regression to make a prediction tool. Then checked its accuracy and reliability using receiver operating characteristic (ROC) and calibration curves. RESULTS: Factors like age, body weight, prior fractures, and smoking were independently found to affect BMD T-score distribution in men. In women, age and body weight were identified as independent factors influencing BMD T-score distribution. A nomogram was created to visually illustrate these predictive relationships. CONCLUSIONS: The nomogram proved highly accurate in identifying men aged 50 and above and postmenopausal women based on their BMD T-score distribution, improving clinical decision-making and patient care in osteoporosis evaluation and treatment.

Clinical value of lymphocyte count in autoimmune diabetic nephropathy. / æ·‹å·´ç»†èƒžè®¡æ•°åœ¨è‡ªèº«å ç–«æ€§ç³–å°¿ç— è‚¾ç— ä¸­çš„ä¸´åºŠä»·å€¼ï¼ˆè‹±æ–‡ï¼‰.

OBJECTIVES: In recent years, the prevalence of diabetic nephropathy (DN) has increased significantly. An increasing number of studies have shown that lymphocyte-associated inflammatory responses play a role in DN. This study aims to investigate the relationship between lymphocytes and DN in patients with autoimmune diabetes. METHODS: The clinical data of 226 patients with Type 1 diabetes (T1D) and 79 patients with latent autoimmune diabetes in adults (LADA) were retrospectively studied and stratified according to the urinary albumin to creatinine ratio (ACR). Risk factors associated with DN were analyzed using correlation analysis and logistic regression. RESULTS: In T1D and LADA patients, systolic blood pressure (SBP), uric acid duration, and diabetes duration in patients with normoalbuminuria were lower or shorter than those in patients with macroalbuminuria (P<0.05). The lymphocyte count of T1D patients was significantly higher than that in LADA patients (P<0.05), while the neutrophil to lymphocyte ratio (NLR) of T1D patients was significantly lower than that in LADA patients (P<0.05). The lymphocyte count in the T1D patients with normoalbuminuria was lower than that those with macroalbuminuria (P<0.05). The NLR was lower in the T1D patients with macroalbuminuria than those with microalbuminuria and normoproteinuria (all P<0.01). Based on logistic regression analysis, lymphocytes were independently associated with DN in T1D after adjusting for various known risk factors such as course of disease, age, gender, dyslipidemia, hypertension, and smoking status. Analysis of the receiver operating characteristic curve of subjects predicting lymphocytes in normoalbuminuria showed that the area under the curve was 0.601 (95% CI 0.510 to 0.693, P=0.039), and when the cutoff value of lymphocytes was 2.332, the sensitivity was 37.0%, and the specificity was 82.5%. CONCLUSIONS: Lymphocyte counts in autoimmune diabetic patients are closely associated with DN, suggesting that lymphocyte-mediated inflammation may be involved in the pathogenesis of DN in autoimmune diabetic patients. This study provides a possible perspective for using lymphocytes as a potential biomarker for the early identification of individuals at risk for DN and potential therapeutic targets for DN.

Using machine learning algorithm to predict the risk of post-traumatic stress disorder among firefighters in Changsha. / ç”¨æœºå™¨å­¦ä¹ ç®—æ³•é¢„æµ‹é•¿æ²™æ¶ˆé˜²å‘˜æ‚£åˆ›ä¼¤åŽåº”æ¿€éšœç¢çš„é£Žé™©.

OBJECTIVES: Firefighters are prone to suffer from psychological trauma and post-traumatic stress disorder (PTSD) in the workplace, and have a poor prognosis after PTSD. Reliable models for predicting PTSD allow for effective identification and intervention for patients with early PTSD. By collecting the psychological traits, psychological states and work situations of firefighters, this study aims to develop a machine learning algorithm with the aim of effectively and accurately identifying the onset of PTSD in firefighters, as well as detecting some important predictors of PTSD onset. METHODS: This study conducted a cross-sectional survey through convenient sampling of firefighters from 20 fire brigades in Changsha, which were evenly distributed across 6 districts and Changsha County, with a total of 628 firefighters. We used the synthetic minority oversampling technique (SMOTE) to process data sets and used grid search to finish the parameter tuning. The predictive capability of several commonly used machine learning models was compared by 5-fold cross-validation and using the area under the receiver operating characteristic curve (ROC-AUC), accuracy, precision, recall, and F1 score. RESULTS: The random forest model achieved good performance in predicting PTSD with an average AUC score at 0.790. The mean accuracy of the model was 90.1%, with an F1 score of 0.945. The three most important predictors were perseverance, forced thinking, and reflective deep thinking, with weights of 0.165, 0.158, and 0.152, respectively. The next most important predictors were employment time, psychological power, and optimism. CONCLUSIONS: PTSD onset prediction model for Changsha firefighters constructed by random forest has strong predictive ability, and both psychological characteristics and work situation can be used as predictors of PTSD onset risk for firefighters. In the next step of the study, validation using other large datasets is needed to ensure that the predictive models can be used in clinical setting.

Prescreening for osteoporosis with forearm bone densitometry in health examination population.

BACKGROUND: Early detection and timely prophylaxis can retard the progression of osteoporosis. The purpose of this study was to determine the validity of peripheral Dual Energy X-ray Absorptiometry (DXA) test for osteoporosis screening. We examined peripheral bone mineral density (BMD) using AKDX-09 W-I DXA densitometer. Firstly, we acquired BMD data from manufacturer-supplied density-gradient phantoms and 30 volunteers to investigate its accuracy and precision, then we measured BMD for 150 volunteers using both AKDX (left forearm) and Hologic Discovery Wi (left forearm, left hip and L1 - L4 vertebrae) simultaneously. Correlation relationship of BMD results acquired from two instruments was assessed by simple linear regression analysis, the Receiver Operating Characteristic (ROC) curves and Areas Under the Curves (AUCs) were evaluated for the diagnostic value of left forearm BMD measured by AKDX in detecting osteoporosis. RESULTS: In vitro precision errors of AKDX BMD were 0.40, 0.20, 0.19%, respectively, on low-, medium-, and high-density phantom; in vivo precision was 1.65%. Positive correlation was observed between BMD measured by AKDX and Hologic at the forearm (r = 0.670), L1-L4 (r = 0.430, femoral neck (r = 0.449), and total hip (r = 0.559). With Hologic measured T-score as the gold standard, the sensitivity of AKDX T-score < - 1 for identifying suboptimal bone health was 63.0 and 76.1%, respectively, at the distal one-third radius and at any site, and the specificity was 73.9 and 90.0%, respectively; the AUCs were 0.708 and 0.879. The sensitivity of AKDX T-score ≤ - 2.5 for identifying osteoporosis at the distal one-third radius and at any site was 76.9 and70.4%, respectively, and the specificity was 80.4 and 78.0%, respectively; the AUCs were 0.823 and 0.778. CONCLUSIONS: Peripheral DXA appears to be a reliable tool for prescreening for osteoporosis.

Changes of new coagulation markers in healthy pregnant women and establishment of reference intervals in Changsha. / é•¿æ²™å¥åº·å¦Šå¨ å¦‡å¥³æ–°å‡è¡€æ ‡å¿—ç‰©æ°´å¹³å˜åŒ–åŠå ¶å‚è€ƒåŒºé—´çš„å»ºç«‹.

OBJECTIVES: There is a high coagulation state in pregnant women, which is prone to coagulation and fibrinolysis system dysfunction. This study aims to explore the latest coagulation markers-thrombomodulin (TM), thrombin-antithrombin complex (TAT), plasmin-α2 plasmin inhibitor complex (PIC), and tissue plasminogen activator/plasminogen activator inhibitor compound (tPAI-C) in different stages of pregnancy, establish reference intervals (RIs) for healthy pregnant women of Chinese population, and to provide an effective and reliable reference for clinicians. METHODS: A total of 492 healthy pregnant women, who underwent pregnancy examination and delivery in the Department of Obstetrics, Second Xiangya Hospital of Central South University from October 2019 to October 2020, were enrolled for this study. They were assigned into the first trimester group, the second trimester group, the third trimester group, and the puerperium group according to the pregnancy period, and 123 healthy non-pregnant women were selected as the controls. Plasma levels of TM, TAT, PIC and tPAI-C were analyzed by automatic chemiluminescence immunoassay analyzer. The RIs for TM, TAT, PIC, and tPAI-C were defined using non-parametric 95% intervals, determined following Clinical and Laboratory Standards Institute Document C28-A3c (CLSI C28-A3c), and Formulation of Reference Intervals for the Clinical Laboratory Test Items (WS/T402-2012). RESULTS: TM and TAT levels increased gradually in the first, second, and third trimester women and decreased in the puerperium women (P<0.05 or P<0.01). PIC level of healthy non-pregnant women was lower than that of pregnant women (P<0.05 or P<0.01), but PIC level of pregnant and puerperium women did not differ significantly (P>0.05). tPAI-C level in healthy non-pregnant women was lower than that of pregnant women (P<0.05 or P<0.01), and tPAI-C level was significantly decreases in the puerperium women (P<0.01). The RIs for TM were as follows: Healthy non-pregnant women at 3.20-4.60 TU/mL, the first and second trimester at 3.12-7.90 TU/mL, the third trimester at 3.42-8.29 TU/mL, puerperium at 2.70-6.40 TU/mL. The RIs for TAT were as follows: Healthy non-pregnant women at 0.50-1.64 ng/mL, the first and second trimester at 0.52-6.91 ng/mL, the third trimester at 0.96-12.92 ng/mL, puerperium at 0.82-3.75 ng/mL. The RIs for PIC were as follows: Healthy non-pregnant women at 0.160-0.519 ng/mL, pregnant women at 0.162-0.770 µg/mL. The RIs for tPAI-C were as follows: Healthy non-pregnant women at 1.90-4.80 ng/mL, the first and second trimester at 2.03-9.33 ng/mL, the third trimester at 2.80-14.20 ng/mL, puerperium at 1.10-8.40 ng/mL. CONCLUSIONS: The levels of 4 new coagulation markers TM, TAT, PIC, and tPAI-C in pregnant women are increased significantly during pregnancy and gradually return to normal after delivery. The RIs for TM, TAT, PIC, and tPAI-C in pregnant women by trimester are established according to CLSI C28-A3c, thus providing a clinical reference for clinician in judgement of thrombotic risk.

Circulating levels of IL-33 are elevated by obesity and positively correlated with metabolic disorders in Chinese adults.

BACKGROUND: Interleukin-33 (IL-33) plays a pivotal role in regulating innate immune response and metabolic homeostasis. However, whether its circulating level is correlated with obesity and metabolic disorders in humans remains largely unknown. We aimed to address this gap by determining IL-33 serum level and its downstream type 2 inflammatory cytokines interleukin-5 (IL-5) and interleukin-13 (IL-13) in overweight/obese population, and analyzing the specific associations between IL-33 and obesity metabolic phenotypes. METHODS: 217 subjects were enrolled and divided into three groups: healthy control (HC) subjects, metabolically healthy overweight/obese (MHOO) subjects and metabolically unhealthy overweight/obese (MUOO) subjects. Circulating levels of IL-33, IL-5 and IL-13 were measured using ELISA analyses. Multivariate regression analyses were further performed to determine the independent association between IL-33 and obesity metabolic phenotypes. RESULTS: Circulating levels of IL-33 were significantly elevated in subjects of MUOO group compared with HC group and MHOO group, while no significant difference was observed between the latter two groups in IL-33 levels. Consistent with this, serum levels of IL-5/13 were higher in the MUOO group compared with HC and MHOO groups. After adjusted for all confounders, MUOO phenotype was significantly associated with increased IL-33 serum levels (OR = 1.70; 95% CI 1.09-2.64; p = 0.019). With the MHOO group as the reference population, higher circulating level of IL-33 was also positively associated with MUOO phenotype after adjusting for confounders (OR = 1.50; 95% CI 1.20-1.88; p = 2.91E-4). However, there was no significant association between MHOO phenotype and IL-33 levels (p = 0.942). Trend analysis further confirmed the positive correlation between MUOO phenotype and IL-33 level (p for trend = 0.019). Additionally, IL-33 was significantly and positively correlated with diastolic blood pressure (DBP), total cholesterol (TC), alanine aminotransferase (ALT), aspartate aminotransferase (AST), white blood cell (WBC), neutrophil and IL-5 only in MUOO group, while inversely correlated with high density lipoprotein cholesterol (HDL-C) in MHOO subjects. CONCLUSION: Circulating levels of IL-33 were significantly elevated in overweight/obese Chinese adults with metabolic disorders. Increased levels of IL-33 were positively associated with metabolically unhealthy overweight/obese phenotype and several metabolic syndrome risk factors.

Integrative Omics Analysis Reveals Metabolic Features of Ground-Glass Opacity-Associated Lung Cancer.

Background: Ground-glass opacity (GGO)-associated cancers are increasingly prevalent, exhibiting unique clinical and molecular features that suggest the need for a distinct treatment strategy. However, the metabolic characteristics and vulnerabilities of GGO-associated lung cancers remain unexplored. Methods: We conducted metabolomic and transcriptomic analyses on 40 pairs of GGO-associated lung cancer tissues and adjacent normal tissues. By integrating data from TCGA database and single-cell RNA sequencing, we aimed to identify aberrant metabolic pathways, establish a metabolite-associated gene signature, and pinpoint key metabolic genes. The physiological effect of key genes was detected in vitro and vivo assays. Results: We identified a 30-gene metabolite-associated signature and discovered aberrant metabolic pathways for GGO-associated lung cancer at both metabolic and transcriptional levels. Patients with this signature displayed specific prognostic and molecular features. Cox regression analysis, based on the Cancer Genome Atlas Program (TCGA) data, further narrowed down the metabolite-related gene signature, resulting in a 5-gene signature. Confirmed by single-cell RNA sequencing (GSE203360), the 5-gene signature was mainly expressed in cancer cells of GGO tissue. Real-time quantitative PCR (RT-qPCR) further validated the differential expression of these genes between GGO and adjacent normal tissue obtained from pulmonary surgery. Finally, our integrative analysis unveiled aberrant histidine metabolism at both the multi-omics and single-cell levels. Moreover, we identified MAOB as a key metabolic gene, demonstrating its ability to suppress cell proliferation, migration, and invasion in LUAD cell lines, both in vitro and in vivo. Conclusions: We identified a specific metabolite-associated gene signature and identified aberrant histidine metabolism in GGO-associated lung cancer from multiple perspectives. Notably, MAOB, a crucial component in histidine metabolism, demonstrated a significant inhibitory effect on the proliferation and metastasis of LUAD, indicating its potential significance in pathogenesis and therapeutic interventions.

EphB1 promotes the differentiation and maturation of dendritic cells in non-small cell lung cancer.

EphB1 is implicated in numerous physiological and pathological processes, including nervous system diseases, cardiovascular diseases and cancers. It binds to membrane-bound ligands and drives bidirectional signaling. EphB1, along with its ligand ehrinB, plays a pivotal role in activating immune cells. However, despite its presence in dendritic cells (DCs), EphB1's involvement in the differentiation and maturation of DCs in cancers remains inadequately understood. In this study, we found compromised differentiation and maturation of DCs in EphB1-/- mice bearing lung adenocarcinoma syngeneic tumors. Our in vitro assays revealed that EphB1 phosphorylation induced DC differentiation and maturation. Cox-2, a key enzyme involved in the production of proinflammatory molecules, is implicated in DC differentiation induced by phosphorylated EphB1. Additionally, the study has identified lead compounds that specifically target EphB1 phosphorylation sites. Collectively, this research on EphB1 phosphorylation has provided valuable insights into the regulation of immune cell functionality and holds the potential for the development of innovative therapeutic strategies for a range of diseases.

Utilizing machine learning for early screening of thyroid nodules: a dual-center cross-sectional study in China.

Background: Thyroid nodules, increasingly prevalent globally, pose a risk of malignant transformation. Early screening is crucial for management, yet current models focus mainly on ultrasound features. This study explores machine learning for screening using demographic and biochemical indicators. Methods: Analyzing data from 6,102 individuals and 61 variables, we identified 17 key variables to construct models using six machine learning classifiers: Logistic Regression, SVM, Multilayer Perceptron, Random Forest, XGBoost, and LightGBM. Performance was evaluated by accuracy, precision, recall, F1 score, specificity, kappa statistic, and AUC, with internal and external validations assessing generalizability. Shapley values determined feature importance, and Decision Curve Analysis evaluated clinical benefits. Results: Random Forest showed the highest internal validation accuracy (78.3%) and AUC (89.1%). LightGBM demonstrated robust external validation performance. Key factors included age, gender, and urinary iodine levels, with significant clinical benefits at various thresholds. Clinical benefits were observed across various risk thresholds, particularly in ensemble models. Conclusion: Machine learning, particularly ensemble methods, accurately predicts thyroid nodule presence using demographic and biochemical data. This cost-effective strategy offers valuable insights for thyroid health management, aiding in early detection and potentially improving clinical outcomes. These findings enhance our understanding of the key predictors of thyroid nodules and underscore the potential of machine learning in public health applications for early disease screening and prevention.

Prediction of Fatty Liver Disease in a Chinese Population Using Machine-Learning Algorithms.

BACKGROUND: Fatty liver disease (FLD) is an important risk factor for liver cancer and cardiovascular disease and can lead to significant social and economic burden. However, there is currently no nationwide epidemiological survey for FLD in China, making early FLD screening crucial for the Chinese population. Unfortunately, liver biopsy and abdominal ultrasound, the preferred methods for FLD diagnosis, are not practical for primary medical institutions. Therefore, the aim of this study was to develop machine learning (ML) models for screening individuals at high risk of FLD, and to provide a new perspective on early FLD diagnosis. METHODS: This study included a total of 30,574 individuals between the ages of 18 and 70 who completed abdominal ultrasound and the related clinical examinations. Among them, 3474 individuals were diagnosed with FLD by abdominal ultrasound. We used 11 indicators to build eight classification models to predict FLD. The model prediction ability was evaluated by the area under the curve, sensitivity, specificity, positive predictive value, negative predictive value, and kappa value. Feature importance analysis was assessed by Shapley value or root mean square error loss after permutations. RESULTS: Among the eight ML models, the prediction accuracy of the extreme gradient boosting (XGBoost) model was highest at 89.77%. By feature importance analysis, we found that the body mass index, triglyceride, and alanine aminotransferase play important roles in FLD prediction. CONCLUSION: XGBoost improves the efficiency and cost of large-scale FLD screening.

Music Therapy in Pediatric Asthma: A Short Review.

Music therapy (MT) is a common modality that performs a complementary and integrative role along with standard treatments for many pediatric diseases. This article briefly reviewed the effects of MT on children aged 5-11 years old and adolescents with asthma from previous studies, specified its functional target towards asthma symptoms, and sorted out the design and investigation of selected research. Medline/PubMed, Embase, SportDis-cus, Cochrane Library, Teacher Reference Centre, Web of Science, Academic Search Complete, PsycARTICLES, and Scopus were queried for experimental and observational studies published between 1990 and 2021. Then, researchers showed that MT lessened patients' asthma symptoms, improved medication compliance, pulmonary function, and quality of life, and helped children and their parents manage anxiety and depression. This article may serve as a reference for clinical research for pediatric asthma therapies and lay the foundation for future research on MT and its clinical practice.

Utilizing machine learning algorithms for the prediction of carotid artery plaques in a Chinese population.

Background: Ischemic stroke is a significant global health issue, imposing substantial social and economic burdens. Carotid artery plaques (CAP) serve as an important risk factor for stroke, and early screening can effectively reduce stroke incidence. However, China lacks nationwide data on carotid artery plaques. Machine learning (ML) can offer an economically efficient screening method. This study aimed to develop ML models using routine health examinations and blood markers to predict the occurrence of carotid artery plaques. Methods: This study included data from 5,211 participants aged 18-70, encompassing health check-ups and biochemical indicators. Among them, 1,164 participants were diagnosed with carotid artery plaques through carotid ultrasound. We constructed six ML models by employing feature selection with elastic net regression, selecting 13 indicators. Model performance was evaluated using accuracy, sensitivity, specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), F1 score, kappa value, and Area Under the Curve (AUC) value. Feature importance was assessed by calculating the root mean square error (RMSE) loss after permutations for each variable in every model. Results: Among all six ML models, LightGBM achieved the highest accuracy at 91.8%. Feature importance analysis revealed that age, Low-Density Lipoprotein Cholesterol (LDL-c), and systolic blood pressure were important predictive factors in the models. Conclusion: LightGBM can effectively predict the occurrence of carotid artery plaques using demographic information, physical examination data and biochemistry data.

Economic evaluation of four treatment strategies for postmenopausal patients with osteoporosis and a recent fracture in mainland China: a cost-effectiveness analysis.

Postmenopausal patients with osteoporosis who have a recent fracture are at very high risk of fracture, and this study finds that stratified treatment based on fracture risk would be a cost-effective treatment option for this population. PURPOSE: To evaluate the cost-effectiveness of four anti-osteoporosis medications (denosumab, zoledronate, teriparatide, and alendronate) for postmenopausal osteoporotic women in mainland China, using a stratified treatment strategy recommended by the American Association of Clinical Endocrinologists and the American College of Endocrinology (AACE/ACE). METHODS: A microsimulation Markov model was used to compare the cost-effectiveness of the four treatments in postmenopausal osteoporotic patients of different ages (65, 70, 75, and 80 years), with a recent fracture from the Chinese healthcare perspective. The primary outcome was the incremental cost-effectiveness ratio (ICER), which represent the incremental cost per quality-adjusted life-year (QALY) obtained. One-way deterministic sensitivity analysis (DSA) and probabilistic sensitivity analysis (PSA) were performed to assess the robustness of model findings. RESULTS: Alendronate was dominated by denosumab-to-alendronate and zoledronate at all ages examined, indicating that the costs of the two drugs were lower, but QALYs was greater. However, teriparatide-to-alendronate yielded an ICER of $76,432.07/ QALY, compared with alendronate at age 65, which exceeded the pre-determined willingness-to-pay threshold of $37,653/ QALY. The results were similar at other ages. The DSA showed that the most sensitive parameters were drug efficacy for vertebral and wrist fractures, the relative risk of vertebral fractures, and the persistence of the drugs. The PSA showed that zoledronate had a 100% probability of being the most cost-effective treatment, with a willingness-to-pay threshold of $37,653/ QALY. CONCLUSION: Stratified treatment based on very high fracture risk is more cost-effective than conventional pills in mainland China. Among the stratified treatments, zoledronate is the optimal option.

Comparison of the predictive value of anthropometric indicators for the risk of benign prostatic hyperplasia in southern China.

This study aimed to compare the predictive value of six selected anthropometric indicators for benign prostatic hyperplasia (BPH). Males over 50 years of age who underwent health examinations at the Health Management Center of the Second Xiangya Hospital, Central South University (Changsha, China) from June to December 2020 were enrolled in this study. The characteristic data were collected, including basic anthropometric indices, lipid parameters, six anthropometric indicators, prostate-specific antigen, and total prostate volume. The odds ratios (ORs) with 95% confidence intervals (95% CIs) for all anthropometric parameters and BPH were calculated using binary logistic regression. To assess the diagnostic capability of each indicator for BPH and identify the appropriate cutoff values, receiver operating characteristic (ROC) curves and the related areas under the curves (AUCs) were utilized. All six indicators had diagnostic value for BPH (all P ≤ 0.001). The visceral adiposity index (VAI; AUC: 0.797, 95% CI: 0.759-0.834) had the highest AUC and therefore the highest diagnostic value. This was followed by the cardiometabolic index (CMI; AUC: 0.792, 95% CI: 0.753-0.831), lipid accumulation product (LAP; AUC: 0.766, 95% CI: 0.723-0.809), waist-to-hip ratio (WHR; AUC: 0.660, 95% CI: 0.609-0.712), waist-to-height ratio (WHtR; AUC: 0.639, 95% CI: 0.587-0.691), and body mass index (BMI; AUC: 0.592, 95% CI: 0.540-0.643). The sensitivity of CMI was the highest (92.1%), and WHtR had the highest specificity of 94.1%. CMI consistently showed the highest OR in the binary logistic regression analysis. BMI, WHtR, WHR, VAI, CMI, and LAP all influence the occurrence of BPH in middle-aged and older men (all P ≤ 0.001), and CMI is the best predictor of BPH.

Suppression of polycyclic aromatic hydrocarbon formation during pyrolytic production of lignin-based biochar via nitrogen and boron co-doping.

Polycyclic aromatic hydrocarbons are toxic byproducts of biochar production. The effects of pyrolysis atmosphere (i.e., N2 and CO2) and temperature (i.e., 300-900 °C) and element doping (i.e., N, B, O, and S) on the production of sixteen high priority polycyclic aromatic hydrocarbons in lignin-based biochar was investigated. N2 atmosphere at 300 °C produced the highest total polycyclic aromatic hydrocarbon content (1698 ± 50 ng/g). Polycyclic aromatic hydrocarbon formation decreased with increase in temperature (31 ± 15 ng/g at 900 °C). CO2 atmosphere significantly decreased yield of polycyclic aromatic hydrocarbons. The effects of heteroatom doping on polycyclic aromatic hydrocarbon formation were investigated for the first time in the pyrolysis synthesis of lignin-based biochar. N-, B-, O, N-B-, and N-S-doping of biochar reduced polycyclic aromatic hydrocarbon formation by 90, 85, 87, 97, and 89%, respectively. Results bring new insights into the role of heteroatom-doping and pyrolysis conditions in controlling polycyclic aromatic hydrocarbon formation in biochars.

The Association Between Hyperuricemia and Obesity Metabolic Phenotypes in Chinese General Population: A Retrospective Analysis.

Purpose: Serum uric acid (UA) not only affects the development of obesity but also alters the metabolic status in obese subjects; thus we investigated the relationship between serum UA and the overweight/obese metabolic phenotypes. Methods: The demographic, biochemical, and hematological data were collected for 12,876 patients undergoing routine physical examination, and 6,912 participants were enrolled in our study. Participants were classified into four obesity metabolic phenotypes according to their BMI and the presence of metabolic syndrome: metabolically healthy overweight/obese (MHOO), metabolically healthy and normal weighted (MHNW), metabolically abnormal and overweight/obese (MAOO), and metabolically abnormal but normal weighted (MANW). Univariate and multivariate logistic regression analysis, stratified analysis, and also interaction analysis were conducted to analyze the relationship between serum UA and obesity metabolic phenotypes. Results: Multivariable logistic regression analysis showed that hyperuricemia was positively associated with MHOO, MANW, and MAOO phenotypes relative to MHNW. After adjusting for the confounding factors, the odds ratios (OR) for individuals with hyperuricemia to be MHOO, MANW, and MAOO phenotypes were 1.86 (1.42-2.45), 2.30 (1.44-3.66), and 3.15 (2.34-4.24), respectively. The ORs for having MHOO, MANW, and MAOO increased 6% [OR: 1.06 (1.05-1.07), P < 0.0001], 5% [OR: 1.05 (1.03-1.07), P < 0.0001], and 11% [OR: 1.11 (1.10-1.13), P < 0.0001] for each 10 unit (µmol/L) of increase in serum UA level. Stratification analysis as well as an interaction test showed that sex and age did not interfere with the association of hyperuricemia with each metabolic phenotype. In terms of the components of the metabolic syndrome, after adjusting for other confounding factors including all of the metabolic indicators except itself, hyperuricemia was positively associated with increased BMI [OR: 1.66 (1.32-2.09), P < 0.0001], hypertriglyceridemia [OR: 1.56 (1.21-2.02), P = 0.0006], and hypertension [OR: 1.22 (1.03-1.46), P = 0.0233], while it had no significant association with hyperglycemia and low HDL-C (all P > 0.05). Conclusion: In our study, we discovered that hyperuricemia was positively associated with MHOO, MANW, and MAOO phenotypes, and this relationship was independent of sex and age.

Performance and bacterial community dynamics of lignin-based biochar-coupled calcium peroxide pretreatment of waste-activated sludge for the removal of 4-nonylphenol.

Waste activated sludge contaminated with high levels of 4-nonylphenol (4-NP) is a major environmental concern. We have synthesized lignin-based biochar (LGBC) for use as a carbocatalyst in calcium peroxide (CP)-mediated sewage sludge pretreatment. Treatment of sewage sludge with 3.1 × 10-4 M of CP and 3.0 g L-1 of LGBC removed 76% of 4-NP in 12 h, which were 3.8 and 2.4 times higher than that with the LGBC and CP alone, respectively. There was synergy between reactive oxygen species (HO•, O2•-, and 1O2) and graphitic frameworks of LGBC. Pretreatment using the LGBC/CP system enhanced the release of biodegradable organic xenobiotics from the sludge. LGBC/CP enriched Proteobacteria and Thermostilla bacterial consortium (Planctomycetes) in the sludge and promoted 4-NP biodegradation. This work provides new insights into the chemical and biological mechanisms by which LGBC promotes 4-NP biodegradation in waste activated sludge via hydroxyl radical-driven carbon advanced oxidation pretreatment.

Development of a Nomogram for Predicting Very Low Bone Mineral Density (T-Scores <-3) in the Chinese Population.

PURPOSE: Fragility fractures, the most serious complication of osteoporosis, affect life quality and increase medical expenses and economic burden. Strategies to identify populations with very low bone mineral density (T-scores <-3), indicating very high fracture risk according to the American Association of Clinical Endocrinologists/American College of Endocrinology (AACE/ACE), are necessary to achieve acceptable fracture risk levels. In this study, the characteristics of persons with T-scores <-3 were analyzed in the Chinese population to identify risk factors and develop a nomogram for very low bone mineral density (T-scores <-3) identification. MATERIALS AND METHODS: We conducted a cross-sectional study using the datasets of the Health Improvement Program of Bone (HOPE), with 602 men aged ≥50 years and 482 postmenopausal women. Bone mineral density (BMD) was measured using dual energy X-ray absorptiometry (DXA). Data on clinical risk factors, including age, sex, weight, height, previous fracture, parental hip fracture history, smoking, alcohol intake >3 units/day, glucocorticoid use, rheumatoid arthritis, and secondary osteoporosis were collected. A multivariate logistic regression to evaluate the relationship between the clinical risk factors and very low BMD (T-scores <-3) was conducted. Parameter estimates of the final model were then used to construct a nomogram. RESULTS: Sixty-three of 1084 participants (5.8%) had BMD T-score <-3. In multivariable regression analysis, age (odds ratio [OR] = 1.068, 95% confidence interval [CI]: 1.037-1.099) and weight (OR = 0.863, 95% CI: 0.830-0.897) were significant factors that were associated with very low BMD (T-scores <-3). These variables were the factors considered in developing the nomogram. The area under the receiver operating characteristic (ROC) curve for the model was 0.861. The cut-off value of the ROC curve was 0.080. CONCLUSION: The nomogram can effectively assist clinicians to identify persons with very low BMD (T-scores <-3) and very high fracture risk in the Chinese population.