Examining individual and contextual predictors of disability in Chinese older adults: A machine learning approach.

BACKGROUND: There is a large gap of understanding the determinants of disability, especially the contextual characteristics. Therefore, this study aimed to examine the important predictors of disability in Chinese older adults based on the social ecological framework. METHODS: We used the China Health and Retirement Longitudinal Study to examine predictors of disability, defined as self-report of any difficulty for six activity of daily living items. We restricted analytical sample to older adults aged 65 or above (N=1816). We considered 44 predictors, including personal-, behavioral-, interpersonal-, community-, and policy-level characteristics. The built-in variable importance measure (VIM) of random forest and SHapley Additive exPlanations (SHAP) were applied to assess key predictors of disability. A multilevel logit regression was further used to examine the associations of individual and contextual characteristics with disability. RESULTS: The mean age of study sample was 72.62 years old (standard deviation: 5.77). During a 2-year of follow-up, 518 (28.52 %) of them developed into disability. Walking speed, age, and peak expiratory flow were the top important predictors in both VIM and SHAP. Contextual characteristics such as humidity, PM2.5, temperature, normalized difference vegetation index, and landscape also showed promise in predicting disability. Multilevel logit regression showed that people with male gender, arthritis, vision impairment, unable to finish semi tandem, no social activity, lower grip strength, and higher waist circumference, had much higher risk of disability. CONCLUSION: Disability prevention strategies should specifically focus on multilevel factors such as individual and contextual characteristics, although the latter is warranted to be verified in future studies.

Survival prediction in second primary breast cancer patients with machine learning: An analysis of SEER database.

BACKGROUND: Studies have found that first primary cancer (FPC) survivors are at high risk of developing second primary breast cancer (SPBC). However, there is a lack of prognostic studies specifically focusing on patients with SPBC. METHODS: This retrospective study used data from Surveillance, Epidemiology and End Results Program. We selected female FPC survivors diagnosed with SPBC from 12 registries (from January 1998 to December 2018) to construct prognostic models. Meanwhile, SPBC patients selected from another five registries (from January 2010 to December 2018) were used as the validation set to test the model's generalization ability. Four machine learning models and a Cox proportional hazards regression (CoxPH) were constructed to predict the overall survival of SPBC patients. Univariate and multivariate Cox regression analyses were used for feature selection. Model performance was assessed using time-dependent area under the ROC curve (t-AUC) and integrated Brier score (iBrier). RESULTS: A total of 10,321 female FPC survivors with SPBC (mean age [SD]: 66.03 [11.17]) were included for model construction. These patients were randomly split into a training set (mean age [SD]: 65.98 [11.15]) and a test set (mean age [SD]: 66.15 [11.23]) with a ratio of 7:3. In validation set, a total of 3,638 SPBC patients (mean age [SD]: 66.28 [10.68]) were finally enrolled. Sixteen features were selected for model construction through univariate and multivariable Cox regression analyses. Among five models, random survival forest model showed excellent performance with a t-AUC of 0.805 (95 %CI: 0.803 - 0.807) and an iBrier of 0.123 (95 %CI: 0.122 - 0.124) on testing set, as well as a t-AUC of 0.803 (95 %CI: 0.801 - 0.807) and an iBrier of 0.098 (95 %CI: 0.096 - 0.103) on validation set. Through feature importance ranking, the top one and other top five key predictive features of the random survival forest model were identified, namely age, stage, regional nodes positive, latency, radiotherapy, and surgery. CONCLUSIONS: The random survival forest model outperformed CoxPH and other machine learning models in predicting the overall survival of patients with SPBC, which was helpful for the monitoring of high-risk populations.

Associations between multiple urinary metals and metabolic syndrome: Exploring the mediating role of liver function in Chinese community-dwelling elderly.

BACKGROUND: Multiple metals exposure has been revealed to be related to metabolic syndrome (MetS). However, the associations and interactions between multiple metals exposure and MetS are remains controversial, and the potential mechanism of the above-mentioned is still unclear. METHODS: The associations between urinary metals and the MetS were analyzed by multivariable logistic regression model and restricted cubic spline (RCS). Bayesian kernel machine regression (BKMR) model and quantile-based g-computation (qgcomp) were applied to explore the mixed exposure and interaction effect of metals. Mediation analysis was used to explore the role of liver function. RESULTS: In the single metal model, multiple metals were significantly associated with MetS. RCS analysis further verified the associations between 8 metals and MetS. BKMR model and qgcomp showed that zinc (Zn), iron (Fe), and tellurium (Te) were the main factors affecting the overall effect. In addition, mediation analysis indicated that serum alanine aminotransferase (ALT) mediated 21.54% and 13.29% in the associations of vanadium (V) and Zn with the risk of MetS, respectively. CONCLUSIONS: Elevated urinary concentration of Zn, V, Te, copper (Cu), molybdenum (Mo), and thallium (Tl) were related to the increased risk of MetS. Conversely, Fe and selenium (Se) may be protective factors for MetS in mixed exposure. Liver function may play a key role in the association of V and Zn exposure with MetS.

Surgical treatment outcomes of acetabular posterior wall and posterior column fractures using 3D printing technology and individualized custom-made metal plates: a retrospective study.

BACKGROUND: Fractures involving the posterior acetabulum with its rich vascular and neural supply present challenges in trauma orthopedics. This study evaluates the effectiveness of 3D printing technology with the use of custom-made metal plates in the treatment of posterior wall and column acetabular fractures. METHODS: A retrospective analysis included 31 patients undergoing surgical fixation for posterior wall and column fractures of the acetabulum (16 in the 3D printing group, utilizing 3D printing for a 1:1 pelvic model and custom-made plates based on preoperative simulation; 15 in the traditional group, using conventional methods). Surgical and instrument operation times, intraoperative fluoroscopy frequency, intraoperative blood loss, fracture reduction quality, fracture healing time, preoperative and 12-month postoperative pain scores (Numeric Rating Scale, NRS), hip joint function at 6 and 12 months (Harris scores), and complications were compared. RESULTS: The surgical and instrument operation times were significantly shorter in the 3D printing group (p < 0.001). The 3D printing group exhibited significantly lower intraoperative fluoroscopy frequency and blood loss (p = 0.001 and p < 0.001, respectively). No significant differences were observed between the two groups in terms of fracture reduction quality, fracture healing time, preoperative pain scores (NRS scores), and 6-month hip joint function (Harris scores) (p > 0.05). However, at 12 months, hip joint function and pain scores were significantly better in the 3D printing group (p < 0.05). Although the incidence of complications was lower in the 3D printing group (18.8% vs. 33.3%), the difference did not reach statistical significance (p = 0.433). CONCLUSION: Combining 3D printing with individualized custom-made metal plates for acetabular posterior wall and column fractures reduces surgery and instrument time, minimizes intraoperative procedures and blood loss, enhancing long-term hip joint function recovery. CLINICAL TRIAL REGISTRATION: 12/04/2023;Trial Registration No. ChiCTR2300070438; http://www.chictr.org.cn .

Pathogenic role of different phenotypes of immune cells in airway allergic diseases: a study based on Mendelian randomization.

Background: Airway allergic disease (AAD) is a class of autoimmune diseases with predominantly Th2-type inflammation, mainly including allergic rhinitis (AR), allergic asthma (AS), and chronic sinusitis (CRS). There are very complex regulatory mechanisms between immune cells and AAD; however, previous reports found that the functions of the same immune cells in AAD are not identical. Objective: The aim of this study was to explore the causal relationship between different phenotypic immune cells and their association with AAD. Method: Utilizing the publicly available Genome-Wide Association Studies (GWAS) database, this study conducted a bidirectional Mendelian randomization (MR) to assess the causal relationship between immune cells of 731 different immunophenotypes and AAD. The primary assessment methods included inverse variance weighting, weighted median, and MR Egger. Additionally, sensitivity analyses such as MR-PRESSO, leave-one-out, and scatter plots were employed to eliminate the interference of heterogeneity and pleiotropy, ensuring the stability of the causal inference. Result: A total of 38 immune cells with different immunophenotypes were found to be positively and causally associated with AR, of which 26 were protective factors and 12 were risk factors. Positive associations were found between 33 immune cells and AS, of which 14 were protective factors and 19 were risk factors, as well as between 39 immune cells and CRS, of which 22 were protective factors and 17 were risk factors. Finally, the results of all relevant immune cells for the three diseases were taken and intersected, and it was found that CD3 on CD39+-activated Treg (IVWAR = 0.001, IVWCRS = 0.043, IVWAS = 0.027) may be the key immune cell that inhibits the development of AAD (ORAR = 0.940, ORAS = 0.967, ORCRS = 0.976). Conclusion: This study reveals that different immune phenotypes of immune cells are closely related to AAD at the genetic level, which provides a theoretical basis for future clinical studies.

Study on the therapeutic effect of Kirschner wire tension band combined with anchor cross-stitch technique in the treatment of comminuted patellar inferopolar fractures.

PURPOSES: Fractures of the inferior patellar pole, unlike other patellar fractures, present challenges for traditional surgical fixation methods. This article introduces the clinical technique and outcomes of using Kirschner wire tension band combined with anchor screw cross-stitch fixation for comminuted inferior patellar pole fractures. METHODS: This retrospective case series study included 14 patients with comminuted inferior patellar pole fractures treated at our institution from September 1, 2020, to April 30, 2022. All patients underwent surgery using the Kirschner wire tension band with anchor screw cross-stitch technique. Follow-up assessments involved postoperative X-rays to evaluate fracture healing, as well as clinical parameters such as healing time, Visual Analog Scale (VAS) scores, range of motion (ROM), and Bostman scores. RESULTS: All patients were followed for an average of over 12 months, with no cases of internal fixation failure. Knee joint stability and function were excellent. X-rays revealed an average healing time of approximately 10.79 ± 1.53 weeks, hospitalization lasted 5.64 ± 1.15 days, surgery took approximately 37.86 ± 5.32 minutes, and intraoperative blood loss was 33.29 ± 8.15 ml. One patient experienced irritation from the internal fixation material. At the final follow-up, the Bostman score averaged 28.29 ± 0.83, knee joint flexion reached 131.07° ± 4.88°, all patients achieved full knee extension, and the VAS score was 0.36 ± 0.63. CONCLUSION: Kirschner wire tension band with anchor screw cross-stitch fixation for comminuted inferior patellar pole fractures delivered satisfactory clinical outcomes. This surgical method, characterized by its simplicity and reliability, is a valuable addition to clinical practice.

Treatment of complex limb fractures with 3D printing technology combined with personalized plates: a retrospective study of case series and literature review.

Background: In recent years, 3D printing technology has made significant strides in the medical field. With the advancement of orthopedics, there is an increasing pursuit of high surgical quality and optimal functional recovery. 3D printing enables the creation of precise physical models of fractures, and customized personalized steel plates can better realign and more comprehensively and securely fix fractures. These technologies improve preoperative diagnosis, simulation, and planning for complex limb fractures, providing patients with better treatment options. Patients and methods: Five typical cases were selected from a pool of numerous patients treated with 3D printing technology combined with personalized custom steel plates at our hospital. These cases were chosen to demonstrate the entire process of printing 3D models and customizing individualized steel plates, including details of the patients' surgeries and treatment procedures. Literature reviews were conducted, with a focus on highlighting the application of 3D printing technology combined with personalized custom steel plates in the treatment of complex limb fractures. Results: 3D printing technology can produce accurate physical models of fractures, and personalized custom plates can achieve better fracture realignment and more comprehensive and robust fixation. These technologies provide patients with better treatment options. Conclusion: The use of 3D printing models and personalized custom steel plates can improve preoperative diagnosis, simulation, and planning for complex limb fractures, realizing personalized medicine. This approach helps reduce surgical time, minimize trauma, enhance treatment outcomes, and improve patient functional recovery.

Associations of polycyclic aromatic hydrocarbons mixtures with cardiovascular diseases mortality and all-cause mortality and the mediation role of phenotypic ageing: A time-to-event analysis.

The associations of polycyclic aromatic hydrocarbons (PAHs) with cardiovascular diseases (CVDs) and all-cause mortality are unclear, especially the joint effects of PAHs exposure. Meanwhile, no studies have examined the effect of phenotypic ageing on the relationship between PAHs and mortality. Therefore, this study aimed to investigate the independent and joint associations between PAHs and CVDs, all-cause mortality, and assess whether phenotypic age acceleration (PhenoAgeAccel) mediate this relationship. We retrospectively collected data of 11,983 adults from the National Health and Nutrition Examination Survey database. Firstly, Cox proportional hazards regression and restricted cubic splines were applied to evaluate the independent association of single PAH on mortality. Further, time-dependent Probit extension of Bayesian Kernel Machine Regression and quantile-based g-computation models were conducted to test the joint effect of PAHs on mortality. Then, difference method was used to calculate the mediation proportion of PhenoAgeAccel in the association between PAHs and mortality. Our results revealed that joint exposure to PAHs showed positive association with CVDs and all-cause mortality. By controlling potential confounders, 1-Hydroxynapthalene (1-NAP) (HR = 1.24, P = 0.035) and 2-Hydroxyfluorene (2-FLU) (HR = 1.25, P < 0.001) showed positive association with CVDs mortality, and they were the top 2 predictors (weight: 0.82 for 1-NAP, 0.14 for 2-FLU) of CVDs mortality. 1-NAP (HR = 1.15, P < 0.001) and 2-FLU (HR = 1.13, P < 0.001) also showed positive association with all-cause mortality, and they were also the top 2 predictors of all-cause mortality (weight: 0.66 for 1-NAP, 0.34 for 2-FLU). PhenoAgeAccel mediated the relationship between 1-NAP, 2-FLU and CVDs, all-cause mortality, with a mediation proportion of 10.00 % to 24.90 % (P < 0.05). Specifically, the components of PhenoAgeAccel including C-reactive protein, lymphocyte percent, white blood cell count, red cell distribution width, and mean cell volume were the main contributors of mediation effects. Our study highlights the hazards of joint exposure of PAHs and the importance of phenotypic ageing on the relationship between PAHs and mortality.

Unveiling student academic resilience in language learning: a structural equation modelling approach.

This paper aims to investigate the internal structure of student academic resilience in language learning, to assess its global and dimensional levels and to examine the gender and age-related differences. Therefore, 1,653 English as a foreign language (EFL) learners, including junior and senior high school students were selected as participants to complete the questionnaires. The results of exploratory and confirmatory factor analyses unveiled a four-factorial structure of student academic resilience in English learning, including positive individual characteristics, family support, teacher support and peer support. In addition, there were no significant differences between male and female students in terms of academic resilience in English learning and its four subdimensions. Only the level of family support for junior high school students was significantly higher than that of senior high school students. The findings, implications, and limitations of language learning academic resilience were discussed.

Linear and phase controllable terahertz frequency conversion via ultrafast breaking the bond of a meta-molecule.

The metasurface platform with time-varying characteristics has emerged as a promising avenue for exploring exotic physics associated with Floquet materials and for designing photonic devices like linear frequency converters. However, the limited availability of materials with ultrafast responses hinders their applications in the terahertz range. Here we present a time-varying metasurface comprising an array of superconductor-metal hybrid meta-molecules. Each meta-molecule consists of two meta-atoms that are "bonded" together by double superconducting microbridges. Through experimental investigations, we demonstrate high-efficiency linear terahertz frequency conversion by rapidly breaking the bond using a coherent ultrashort terahertz pump pulse. The frequency and relative phase of the converted wave exhibit strong dependence on the pump-probe delay, indicating phase controllable wave conversion. The dynamics of the meta-molecules during the frequency conversion process are comprehensively understood using a time-varying coupled mode model. This research not only opens up new possibilities for developing innovative terahertz sources but also provides opportunities for exploring topological dynamics and Floquet physics within metasurfaces.

Identifying and predicting physical limitation and cognitive decline trajectory group of older adults in China: A data-driven machine learning analysis.

OBJECTIVE: This study aimed to utilize data-driven machine learning methods to identify and predict potential physical and cognitive function trajectory groups of older adults and determine their crucial factors for promoting active ageing in China. METHODS: Longitudinal data on 3026 older adults from the Chinese Longitudinal Healthy Longevity and Happy Family Survey was used to identify potential physical and cognitive function trajectory groups using a group-based multi-trajectory model (GBMTM). Predictors were selected from sociodemographic characteristics, lifestyle factors, and physical and mental conditions. The trajectory groups were predicted using data-driven machine learning models and dynamic nomogram. Model performance was evaluated by area under the receiver operating characteristics curve (AUROC), area under the precision-recall curve (PRAUC), and confusion matrix. RESULTS: Two physical and cognitive function trajectory groups were determined, including a trajectory group with physical limitation and cognitive decline (14.18 %) and a normal trajectory group (85.82 %). Logistic regression performed well in predicting trajectory groups (AUROC = 0.881, PRAUC = 0.649). Older adults with lower baseline score of activities of daily living, older age, less frequent housework, and fewer actual teeth were more likely to experience physical limitation and cognitive decline trajectory group. LIMITATION: This study didn't carry out external validation. CONCLUSIONS: This study shows that GBMTM and machine learning models effectively identify and predict physical limitation and cognitive decline trajectory group. The identified predictors might be essential for developing targeted interventions to promote healthy ageing.

Associations of urinary metal concentrations with anemia: A cross-sectional study of Chinese community-dwelling elderly.

BACKGROUND: Anemia seriously affects the health and quality of life of the older adult population and may be influenced by various types of environmental metal exposure. Current studies on metals and anemia are mainly limited to single metals, and the association between polymetals and their mixtures and anemia remains unclear. METHODS: We determined 11 urinary metal concentrations and hemoglobin levels in 3781 participants. Binary logistic regression and restricted cubic spline (RCS) model were used to estimate the association of individual metals with anemia. We used Bayesian kernel machine regression (BKMR) and Quantile g-computation (Q-g) regression to assess the overall association between metal mixtures and anemia and identify the major contributing elements. Stratified analyses were used to explore the association of different metals with anemia in different populations. RESULTS: In a single-metal model, nine urinary metals significantly associated with anemia. RCS analysis further showed that the association of arsenic (As) and copper (Cu) with anemia was linear, while cobalt, molybdenum, thallium, and zinc were non-linear. The BKMR model revealed a significant positive association between the concentration of metal mixtures and anemia. Combined Q-g regression analysis suggested that metals such as Cu, As, and tellurium (Te) were positively associated with anemia, with Te as the most significant contributor. Stratified analyses showed that the association of different metals with anemia varied among people of different sexes, obesity levels, lifestyle habits, and blood pressure levels. CONCLUSIONS: Multiple metals are associated with anemia in the older adult population. A significant positive association was observed between metal mixture concentrations and anemia, with Te being the most important factor. The association between urinary metal concentrations and anemia is more sensitive in the non-hypertensive populations.

Development of interpretable machine learning models associated with environmental chemicals to predict all-cause and specific-cause mortality：A longitudinal study based on NHANES.

Limited information is available on potential predictive value of environmental chemicals for mortality. Our study aimed to investigate the associations between 43 of 8 classes representative environmental chemicals in serum/urine and mortality, and further develop the interpretable machine learning models associated with environmental chemicals to predict mortality. A total of 1602 participants were included from the National Health and Nutrition Examination Survey (NHANES). During 154,646 person-months of follow-up, 127 deaths occurred. We found that machine learning showed promise in predicting mortality. CoxPH was selected as the optimal model for predicting all-cause mortality with time-dependent AUROC of 0.953 (95%CI: 0.951-0.955). Coxnet was the best model for predicting cardiovascular disease (CVD) and cancer mortality with time-dependent AUROCs of 0.935 (95%CI: 0.933-0.936) and 0.850 (95%CI: 0.844-0.857). Based on clinical variables, adding environmental chemicals could enhance the predictive ability of cancer mortality (P < 0.05). Some environmental chemicals contributed more to the models than traditional clinical variables. Combined the results of association and prediction models by interpretable machine learning analyses, we found urinary methyl paraben (MP) and urinary 2-napthol (2-NAP) were negatively associated with all-cause mortality, while serum cadmium (Cd) was positively associated with all-cause mortality. Urinary bisphenol A (BPA) was positively associated with CVD mortality.

3D printing technology combined with personalized plates for complex distal intra-articular fractures of the trimalleolar ankle.

This study investigated the effectiveness of 3D printing technology in combination with personalized custom-made steel plates in the treatment of complex distal intra-articular trimalleolar fractures, with the aim of providing a new approach to improve ankle joint function in patients. The 48 patients with complex distal intra-articular trimalleolar fractures included in the study were randomly divided into two groups: the personalized custom-made steel plate group (n = 24) and the conventional steel plate group (n = 24). A comparison was made between the two groups in terms of preoperative preparation time, hospitalization duration, surgical time, fracture reduction and internal fixation time, intraoperative fluoroscopy instances, surgical incision length, fracture healing time, follow-up duration, degree of fracture reduction, ankle joint functional recovery, and the occurrence of complications. The personalized steel plate group exhibited longer preoperative preparation time and hospitalization duration compared to the conventional steel plate group (p < 0.001). However, the personalized steel plate group demonstrated significantly shorter surgical duration, time for fracture reduction and internal fixation, reduced intraoperative fluoroscopy frequency, and a shorter overall surgical incision length (p < 0.001). Both groups displayed similar fracture healing times and follow-up durations (p > 0.05). The personalized steel plate group showed a higher rate of successful fracture reduction (87.5% vs. 79.2%, p > 0.05) and a lower incidence of complications (8.3% vs. 20.8%, p = 0.22), although these differences did not reach statistical significance. Furthermore, the personalized steel plate group exhibited superior ankle joint function scores during follow-up compared to the conventional steel plate group (p < 0.05). By utilizing 3D printing technology in conjunction with personalized custom-made steel plates, personalized treatment plans are provided for patients with complex comminuted tri-malleolar ankle fractures, enabling safer, more efficient, and satisfactory orthopedic surgeries.

Surgical options for distal radius fractures of type C in elderly patients over 65 years old: a comparison of external fixation with Kirschner wires and volar locking plate.

BACKGROUND: ue to the lack of consensus on the optimal surgical treatment for distal radius fractures (DRF) in elderly patients over 65 years old, the purpose of this study was to compare the efficacy of external fixation (EF) with Kirschner wires and volar locking plate (VLP) in the treatment of DRF through a retrospective cohort study. We hypothesized that there would be no significant difference in overall complications and functional recovery between the two methods. METHODS: We retrospectively analyzed 62 patients over 65 years old who underwent surgical treatment for C-type DRF between 2019 and 2022. Based on the different treatment methods, they were divided into the EF group and the VLP group. General data, inpatient data, and postoperative complications during follow-up were recorded. The X-ray images before surgery, after surgery, and at the last follow-up were analyzed, and the results of wrist motion range, Gartland-Werley wrist joint score, and DASH score were evaluated 6 months after surgery for both groups. RESULT: Thirty patients underwent closed reduction and external fixation combined with Kirschner wire fixation, while 32 underwent open reduction and VLP fixation. The EF group had significantly shorter operation time, intraoperative blood loss, injury-to-surgery time, and hospital stay compared to the VLP group (all p < 0.001). At the last follow-up, the radiographic parameters (ulnar variance and radial inclination) and wrist joint function (wrist dorsiflexion and forearm supination) were better in the VLP group than in the EF group (p = 0.04, p = 0.01, p = 0.001, p = 0.02, respectively). However, there was no significant difference in overall Gartland-Werley wrist joint score, DASH score, and incidence of postoperative complications between the two groups (p = 0.31, p = 0.25, p = 0.47, respectively). CONCLUSION: For patients aged 65 and above with distal radius fractures (DRF) of type C, VLP and external fixation with Kirschner wires yield comparable functional outcome and complications rate at the short term. However, VLP allowed restoration of better radiological parameters.

Study on the correlation and interaction between metals and dyslipidemia: a case-control study in Chinese community-dwelling elderly.

Previous studies on the association between metals and dyslipidemia are not completely consistent. There are few studies investigating the relationship between mixed metal exposure and dyslipidemia as well as the effects of metals on dyslipidemia in community-dwelling elderly. To evaluate the correlations and interaction effect between the urinary concentrations of metals and the risk of dyslipidemia in community-dwelling elderly. We designed a case-control study to assess the correlation between urine metals and dyslipidemia in elderly people in the Yinchuan. The urinary levels of 13 metals, including calcium, vanadium, iron, cobalt, zinc, copper, arsenic, selenium, molybdenum, cadmium, tellurium, and thallium, were measured by inductively coupled plasma-mass spectrometry (ICP-MS), and the blood biochemical analyzer was used to measure the blood lipid levels of 3384 senior individuals from four different areas of Yinchuan city. Logistic regression and restricted cubic splines (RCS) were used to explore the correlation and dose-response relationship between urinary metals and the risk of dyslipidemia. Least absolute shrinkage and selection operator (LASSO) regression was used to select metals, and then weighted quantile sum (WQS) regression was used to explore the weight of each metal in mixed metals. Bayesian kernel machine regression (BKMR) was used to explore the interactions between metals on dyslipidemia risk. (1) After selection by LASSO regression, in the multi-metal model, compared with the lowest quartile, the adjusted ORs (95%CI) of the highest quartiles were 0.47 (0.37-0.60) for Fe, 1.43 (1.13-1.83) for Zn, 1.46 (1.11-1.92) for As, 0.59 (0.44-0.80) for Se, 1.53 (1.18-2.00) for Mo, and 1.36 (1.07-1.73) for Te. (2) In the WQS regression model, Fe and Mo accounted for the largest weight in the negative and positive effects of dyslipidemia, respectively. (3) In the BKMR model, there may be a positive interaction between Te and Se on dyslipidemia. Among the mixed metals, Fe, As, Se, Mo, and Te were associated with the prevalence of dyslipidemia, with Fe and Mo contributing the most. There may be certain interactions between Te and Se.

Loss of ACOX1 in clear cell renal cell carcinoma and its correlation with clinical features.

Clear cell renal cell carcinoma (ccRCC) is a major pathological type of kidney cancer with a poor prognosis due to a lack of biomarkers for early diagnosis and prognosis prediction of ccRCC. In this study, we investigated the aberrant expression of Acyl-coenzyme A oxidase 1 (ACOX1) in ccRCC and evaluated its potential in diagnosis and prognosis. ACOX1 is the first rate-limiting enzyme in the peroxidation ß-oxidation pathway and is involved in the regulation of fatty acid oxidative catabolism. The mRNA and protein levels of ACOX1 were significantly downregulated in ccRCC, and its downregulation was closely associated with the tumor-node-metastasis stage of patients. The ROC curves showed that ACOX1 possesses a high diagnostic value for ccRCC. The OS analysis suggested that lower expression of ACOX1 was closely related to the worse outcome of patients. In addition, gene set enrichment analysis suggested that expression of ACOX1 was positively correlated with CDH1, CDH2, CDKL2, and EPCAM, while negatively correlated with MMP9 and VIM, which strongly indicated that ACOX1 may inhibit the invasion and migration of ccRCC by reversing epithelial-mesenchymal transition. Furthermore, we screened out that miR-16-5p is upregulated at the mRNA transcript level in ccRCC and negatively correlated with ACOX1. In conclusion, our results showed that ACOX1 is abnormally low expressed in ccRCC, suggesting that it could serve as a diagnostic and prognostic biomarker for ccRCC. Overexpression of miR-16-5p may be responsible for the inactivation of ACOX1.

Predictive value of blood urea nitrogen in heart failure: a systematic review and meta-analysis.

Background: The mortality rate of patients with heart failure (HF) remains high, and when heart failure occurs, blood urea nitrogen (BUN) is involved in the perfusion of renal blood flow. Some studies have shown an association between heart failure prognosis and blood urea nitrogen, but the results of some other studies were inconsistent. Therefore, we conducted a comprehensive meta-analysis to investigate the value of BUN on the prognosis of patients with heart failure. Methods: A computerized systematic search of all English literature was performed in four databases, PubMed, Cochrane, Embase and Web of Science, from their inception to May 2022. The data of BUN were classified into continuous and categorical variables after passing the inclusion and exclusion criteria. The BUN data of both types were extracted separately into stata15.0 for statistical analysis. Results: A total of 19 cohort studies involving 56,003 patients were included. When BUN was used as a categorical variable, the risk of death in heart failure was 2.29 times higher for high levels of BUN than for low levels of BUN (RR = 2.29, 95% CI:1.42-3.70, P < 0.001). The results showed statistical significance in multifactorial and univariate groups, the prospective cohort, and European and Asian groups. When BUN was used as a continuous variable, the risk of death in heart failure was 1.02 times higher for each unit increase in BUN (RR = 1.02, 95% CI:1.01-1.03, p < 0.001). Subgroup analysis showed statistical significance in retrospective cohort, American and Asian. Conclusion: High BUN is an independent predictor of all-cause mortality in heart failure. Lower BUN was associated with better prognosis in patients with heart failure.

Association between urinary neonicotinoid insecticide levels and dyslipidemia risk: A cross-sectional study in Chinese community-dwelling elderly.

Experimental evidence has demonstrated that neonicotinoids (NEOs) exposure can cause lipid accumulation and increased leptin levels. However, the relationship between NEOs exposure and dyslipidemia in humans remains unclear, and the interactive effects of NEOs and their characteristic metabolites on dyslipidemia remain unknown. We detected 14 NEOs and their metabolites in urine samples of 500 individuals (236 and 264 with and without dyslipidemia, respectively) randomly selected from the baseline of the Yinchuan community-dwelling elderly cohort (Ningxia, China). The NEOs and their metabolites were widely detected in urine (87.2-99.6 %) samples, and the median levels ranged within 0.06-0.55 µg/g creatinine. The positive associations and dose-dependent relationships of thiacloprid, imidacloprid-olefin, and imidacloprid-equivalent total with dyslipidemia were validated using restricted cubic spline analysis. Mixture models revealed a positive association between the NEOs mixture and dyslipidemia risk, with urine desnitro-imidacloprid ranked as the top contributor. The Bayesian Kernel Machine Regression models showed that the NEOs mixtures were associated with increased dyslipidemia when the chemical mixtures were ≥ 25th percentile compared to their medians, and desnitro-imidacloprid and imidacloprid-olefin were the major contributors to the combined effect. Given the widespread use of NEOs and the dyslipidemia pandemic, further investigations are urgently needed to confirm our findings and elucidate the underlying mechanisms.

Berry curvature dipole generation and helicity-to-spin conversion at symmetry-mismatched heterointerfaces.

The Berry curvature dipole (BCD) is a key parameter that describes the geometric nature of energy bands in solids. It defines the dipole-like distribution of Berry curvature in the band structure and plays a key role in emergent nonlinear phenomena. The theoretical rationale is that the BCD can be generated at certain symmetry-mismatched van der Waals heterointerfaces even though each material has no BCD in its band structure. However, experimental confirmation of such a BCD induced via breaking of the interfacial symmetry remains elusive. Here we demonstrate a universal strategy for BCD generation and observe BCD-induced gate-tunable spin-polarized photocurrent at WSe2/SiP interfaces. Although the rotational symmetry of each material prohibits the generation of spin photocurrent under normal incidence of light, we surprisingly observe a direction-selective spin photocurrent at the WSe2/SiP heterointerface with a twist angle of 0°, whose amplitude is electrically tunable with the BCD magnitude. Our results highlight a BCD-spin-valley correlation and provide a universal approach for engineering the geometric features of twisted heterointerfaces.