Prediction model for treatment response of primary membranous nephropathy with nephrotic syndrome.

OBJECTIVE: To investigate the predictors and establish a nomogram model for the prediction of the response to treatment in primary membranous nephropathy (PMN) with nephrotic syndrome (NS). METHODS: The clinical, laboratory, pathological and follow-up data of patients with biopsy-proven membranous nephropathy at the Affiliated Hospital of Qingdao University were collected. A total of 373 patients were randomly assigned into development group (n = 262) and validation group (n = 111). Logistic regression analysis was performed in the development group to determine the predictors of treatment response. A nomogram model was established based on the multivariate logistic regression analysis and validated in the validation group. The C-index and calibration plots were used for the evaluation of the discrimination and calibration performance, respectively. RESULTS: Serum albumin levels (OR = 1.151, 95% CI 1.078-1.229, P < 0.001) and glomerular C3 deposition (OR = 0.407, 95% CI 0.213-0.775, P = 0.004) were identified as independent predictive factors for treatment response in PMN with NS, then a nomogram was established combining the above indicators and treatment regimen. The C-indices of this model were 0.718 (95% CI 0.654-0.782) and 0.789 (95% CI 0.705-0.873) in the development and validation groups, respectively. The calibration plots showed that the predicted probabilities of the model were consistent with the actual probabilities (P > 0.05), which indicated favorable performance of this model in predicting the treatment response probability. CONCLUSIONS: Serum albumin levels and glomerular C3 deposition were predictors for treatment response of PMN with NS. A novel nomogram model with good discrimination and calibration was constructed to predict treatment response probability at an early stage.

Differential Associations of Erythrocyte Membrane Saturated Fatty Acids with Glycemic and Lipid Metabolic Markers in a Chinese Population: A Cross-Sectional Study.

Mounting evidence indicates a complex link between circulating saturated fatty acids (SFAs) and cardiovascular disease (CVD) risk factors, but research on erythrocyte membrane SFA associations with metabolic markers remains limited. Our study sought to investigate the correlations between erythrocyte membrane SFAs and key metabolic markers within glycemic and lipid metabolism in a Chinese population of 798 residents aged 41 to 71 from Guangzhou. Using gas chromatography-mass spectrometry, we assessed the erythrocyte membrane saturated fatty acid profile and performed multiple linear regression to evaluate the relationship between different SFA subtypes and metabolic markers. Our findings revealed that the odd-chain SFA group (C15:0 + C17:0) exhibited negative associations with fasting blood glucose (FBG), homeostatic model assessment for insulin resistance (HOMA-IR), and triglycerides (TG). Conversely, the very-long-chain SFA group (C20:0 + C22:0 + C23:0 + C24:0) exhibited positive associations with fasting insulins (FINS), HOMA-IR, total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C). Furthermore, there was no evidence supporting an association between the even-chain group (C14:0 + C16:0 + C18:0) and metabolic markers. Our findings suggest that different subtypes of SFAs have diverse effects on glycemic and lipid metabolic markers, with odd-chain SFAs associated with a lower metabolic risk. However, the results concerning the correlations between even-chain SFAs and very-long-chain SFAs with markers of glycemic and lipid metabolism pathways are confusing, highlighting the necessity for further exploration and investigation.

Targeted degradation of naphthalene by peroxymonosulfate activation using molecularly imprinted biochar.

Polycyclic aromatic hydrocarbons (PAHs) in aquatic environments are threatening ecosystems and human health. In this work, an effective and environmentally friendly catalyst based on biochar and molecular imprinting technology (MIT) was developed for the targeted degradation of PAHs by activating peroxymonosulfate. The results show that the adsorption amount of naphthalene (NAP) by molecularly imprinted biochar (MIP@BC) can reach 82% of the equilibrium adsorption capacity within 5 min, and it had well targeted adsorption for NAP in the solution mixture of NAP, QL and SMX. According to the comparison between the removal rates of NAP and QL by MIP@BC/PMS or BC/PMS system in respective pure solutions or mixed solutions, the MIP@BC/PMS system can better resist the interference of competing pollutants (i.e., QL) compared to the BC/PMS system; that is, MIP@BC had a good ability to selectively degrade NAP. Besides, the removal rate of NAP by MIP@BC/PMS gradually decreased as pH increased. The addition of Cl- greatly promoted the targeted removal of NAP in the MIP@BC/PMS system, while HCO3- and CO32- both had an inhibitory effect. Furthermore, SO4•-, O2•- and 1O2 produced by BC activating PMS dominated the NAP degradation, and it was inferred that the vacated imprinted cavities after NAP degradation can continue to selectively adsorb NAP and this could facilitate the reusability of the material. This study can promote the research on the targeted degradation of PAHs through the synergism of biochar/PMS advanced oxidation processes and MIT.

Resource utilization of rice straw to prepare biochar as peroxymonosulfate activator for naphthalene removal: Performances, mechanisms, environmental impact and applicability in groundwater.

Herein, biochar was prepared using rice straw, and it served as the peroxymonosulfate (PMS) activator to degrade naphthalene (NAP). The results showed that pyrolysis temperature has played an important role in regulating biochar structure and properties. The biochar prepared at 900°C (BC900) had the best activation capacity and could remove NAP in a wide range of initial pH (5-11). In the system of BC900/PMS, multi-reactive species were produced, in which 1O2 and electron transfer mainly contributed to NAP degradation. In addition, the interference of complex groundwater components on the NAP removal rate must get attention. Cl- had a significant promotional effect but risked the formation of chlorinated disinfection by-products. HCO3-, CO32-, and humic acid (HA) had an inhibitory effect; surfactants had compatibility problems with the BC900/PMS system, which could lead to unproductive consumption of PMS. Significantly, the BC900/PMS system showed satisfactory remediation performance in spiked natural groundwater and soil, and it could solve the problem of persistent groundwater contamination caused by NAP desorption from the soil. Besides, the degradation pathway of NAP was proposed, and the BC900/PMS system could degrade NAP into low or nontoxic products. These suggest that the BC900/PMS system has promising applications in in-situ groundwater remediation.

Predictive analysis of metabolic syndrome based on 5-years continuous physical examination data.

Metabolic syndrome (MetS) represents a complex group of metabolic disorders. As MetS poses a significant challenge to global public health, predicting the occurrence of MetS and the development of related risk factors is important. In this study, we conducted a predictive analysis of MetS based on machine learning algorithms using datasets of 15,661 individuals. Five consecutive years of medical examination records were provided by Nanfang Hospital, Southern Medical University, China. The specific risk factors used included WC, WHR, TG, HDL-C, BMI, FGLU, etc. We proposed a feature construction method using the examination records over the past four consecutive years, combining the differences between the annual value and the normal limits of each risk factor and the year-to-year variation. The results showed that the feature set, which contained the original features of the inspection record and new features proposed in this study yielded the highest AUC of 0.944, implying that the new features could help identify risk factors for MetS and provide more targeted diagnostic advice for physicians.

A preliminary nomogram model for predicting relapse of patients with primary membranous nephropathy.

OBJECTIVE: To explore the predictive factors and establish a nomogram model for predicting relapse risk in primary membranous nephropathy (PMN). METHODS: The clinical, laboratory, pathological and follow-up data of patients with biopsy-proven membranous nephropathy were collected in the Affiliated Hospital of Qingdao University. A total of 400 PMN patients who achieved remission were assigned to the development group (n = 280) and validation group (n = 120) randomly. Cox regression analysis was performed in the development cohort to determine the predictive factors of relapse in PMN patients, a nomogram model was established based on the multivariate Cox regression analysis and validated in the validation group. C-index and calibration plots were used to evaluate the discrimination and calibration performance of the model respectively. RESULT: Hyperuricemia (HR = 2.938, 95% CI 1.875-4.605, p < 0.001), high C-reactive protein (CRP) (HR = 1.147, 95% CI 1.086-1.211, p < 0.001), and treatment with calcineurin inhibitors with or without glucocorticoids (HR = 2.845, 95%CI 1.361-5.946, p = 0.005) were independent risk factors, while complete remission (HR = 0.420, 95%CI 0.270-0.655, p < 0.001) was a protective factor for relapse of PMN according to multivariate Cox regression analysis, then a nomogram model for predicting relapse of PMN was established combining the above indicators. The C-indices of this model were 0.777 (95%CI 0.729-0.825) and 0.778 (95%CI 0.704-0.853) in the development group and validation group respectively. The calibration plots showed that the predicted relapse probabilities of the model were consistent with the actual probabilities at 1, 2 and 3 years, which indicated favorable performance of this model in predicting the relapse probability of PMN. CONCLUSIONS: Hyperuricemia, remission status, CRP and therapeutic regimen were predictive factors for relapse of PMN. A novel nomogram model with good discrimination and calibration was constructed to predict relapse risk in patients with PMN early.

A PMF-SSD based approach for the source apportionment and source-specific ecological risk assessment of Le'an river in Jiangxi Province, China.

Identifying the contamination characteristics of trace metals in river and targeting their corresponding potential contamination sources and source-specific ecological risk are of very importance for putting forward effective river environment protection strategies. Here, a detailed investigation was conducted to recognize the contamination and ecological risk characteristics of trace metals in Le'an River. To attain this objective, a PMF-SSD model (Positive Matrix Factorization-Species Sensitivity Distribution) was proposed to evaluate the ecological risk of trace metals in Le'an River. The positive matrix factorization (PMF) was employed to identify the potential source of trace metals in surface water and their corresponding contributions. The ecological risks of the sources were quantitatively calculated by PMF-SSD. In addition, the spatial dissimilarity analysis of the source contribution distributions was also conducted in this study. Results showed that the water environment in Jiangxi were considerably contaminated by trace metals (Cd, Cr, Co, Al, Mn, Cu, Zn and Ni). The concentrations of these trace metals in surface water demonstrated significant spatial variations and the ecological risk lay in high level. Mining activities were identified as the main anthropogenic sources, which should to be strictly regulated.

The need for psychological counseling in breast cancer patients before radiotherapy during the COVID-19 pandemic.

The aims of this study were to explore the need for psychological counseling in breast cancer patients before radiotherapy during the COVID-19 pandemic, to distinguish which type of psychological guidance they demanded and to investigate the related factors that could be associated with the need for psychological counseling. A total of 112 eligible patients diagnosed with stage I-IV breast cancer who had received surgery were included. The self-rating depression scale (SDS), self-rating anxiety scale (SAS), Pittsburgh sleep quality index (PSQI), cancer fatigue scale (CFS), and survey for the need for psychological counseling were completed for all subjects prior to radiotherapy. A total of 8.9% and 3.6% of patients suffered from depression and anxiety during the COVID-19 pandemic, respectively. The prevalence of sleep disturbance was 62.5%. Only 12.5% of the patients needed psychological counseling, especially for the type of tumor diagnosis and treatment rather than COVID-19-related protection. The higher the total CFS score was, the lower the need for psychological counseling in breast cancer patients during this pandemic (OR = 0.91, 95% CI = 0.84-0.98). Patients who received 7-8 chemotherapeutic cycles had 6.7 times the risk of needing psychological counseling when compared with those who received 1-6 chemotherapeutic cycles. Fewer breast cancer patients suffered from depression and anxiety before radiotherapy during the COVID-19 pandemic. However, a large number of patients complained of sleep disturbance and fatigue. The majority of patients did not need psychological counseling. More chemotherapeutic cycles or less fatigue could increase their risk of needing psychological counseling, especially for tumor diagnosis and treatment, but not COVID-19-related protection.

Serum free fatty acid elevation is related to acute kidney injury in primary nephrotic syndrome.

The aim of this research was to examine the clinical characteristics of acute kidney injury (AKI) in primary nephrotic syndrome (NS) and discuss the relationship between serum lipids and AKI. A total of 1028 patients diagnosed with primary NS with renal biopsy results were enrolled in this study. The patients were divided into AKI (n = 81) and non-AKI (n = 947) groups, and their characteristics were compared using a propensity score analysis for the best matching. Serum free fatty acid (FFA) was an independent predictor for AKI in the postmatch samples (p = 0.011). No significant difference in FFA levels was observed among AKI stages or different pathological types in the AKI and non-AKI groups. The AUC (area under the ROC curve) was 0.63 for FFA levels to distinguish AKI. In primary NS, elevated FFA levels tend to be related to a high risk of AKI. FFAs have diagnostic value and may serve as biomarkers for AKI in NS.

Serum Free Fatty Acids and G-Coupled Protein Receptors Are Associated With the Prognosis of Epithelial Ovarian Cancer.

Purpose: Fatty acid metabolism plays key role in cancer development, and free fatty acid receptors (FFARs) are involved in many cancers. However, the correlation between serum free fatty acids (FFAs)/FFARs levels and ovarian cancer (OC) prognosis remains largely unclear. Methods: A retrospective review of 534 primary OC patients and 1049 women with benign ovarian tumors was performed. Serum FFA levels data were extracted from the electronic medical record system. Repeated FFA results of 101 OC patients treated with standard chemotherapy were collected. The effects of FFAs on cells migration were evaluated in OC cell lines by Transwell assay. Gene Expression Profiling Interactive Analysis (GEPIA) was used to compare FFAR mRNA expression levels in cancer and noncancer tissues. Kaplan-Meier (KM) plotter was employed to analyze their prognostic values. SPSS 23.0 and Graphpad prism 7.0 software was used for analysis and graph construction. Results: FFA levels in the serum of epithelial ovarian cancer (EOC) women were higher than in women with benign ovarian tumors independent of pathology, tumor stage,and grade. FFA levels decreased gradually after chemotherapy. FFAs enhanced the migration of OVCAR3 cells. FFAR1 mRNA expression was lower in OC cells than in control cells. FFAR3 was related to a better prognosis, and FFAR4 was related to poor prognosis in TP-53wild-type and mutated type OC, while FFAR1 and FFAR2 were related to a better prognosis in TP53 wild-type OC but FFAR2 was related to a poor prognosis in TP53-mutant OC. Conclusion: The FFA levels are increased in OC and decreased with chemotherapy. High expression of FFARs was related to the prognosis of OC. The prognostic value of different FFARs differs depending on whether it is a TP53 wild or TP53 mutant ovarian cancer.Targeting FFARs may be an attractive treatment strategy for EOC.

Contribution of nonpoint source pollution from baseflow of a typical agriculture-intensive basin in northern China.

Baseflow is an essential component of total surface runoff that is widely considered one of the most influential factors regarding water quality via nonpoint source (NPS) pollution. Previously, many researchers and policy makers have directed their efforts toward surface runoff pollution, largely ignoring nutrient delivery via baseflow. Taking a typical agriculture-intensive basin of northern China as an example, this study explored the spatiotemporal characteristics of baseflow and pollution load in relation to NPS pollution. Baseflow was quantified using digital filtering techniques, and the results together with observed pollution data were used to validate a physically based hydrological model, i.e., the Soil and Water Assessment Tool. Then, the spatial and temporal distribution characteristics of NPS and baseflow pollution were investigated using the modeling results. Results indicated that baseflow contribution to total runoff accounted for more than 70% during the studied years (2016-2018), and 84.15% of the basin area showed non-point source pollution dominated by baseflow pollution; both baseflow and its pollution load were greater in the nonflood seasons (spring, autumn, and winter) than in the flood season (summer); the spatial distribution of baseflow total nitrogen and total phosphorus pollution intensity showed higher values in the east and lower values in the west; the scaling effects of baseflow and its pollution load was found with increasing basin area. The results of our study highlighted the necessity for management of pollution load via baseflow in the river basin and provided reference information for improvement of NPS pollution management in other similar basins.

Root-zone soil moisture estimation based on remote sensing data and deep learning.

Soil moisture in the root zone is the most important factor in eco-hydrological processes. Even though soil moisture can be obtained by remote sensing, limited to the top few centimeters (<5 cm). Researchers have attempted to estimate root-zone soil moisture using multiple regression, data assimilation, and data-driven methods. However, correlations between root-zone soil moisture and its related variables, including surface soil moisture, always appear nonlinear, which is difficult to extract and express using typical statistical methods. The artificial intelligence (AI) method, which is advantageous for nonlinear relationship analysis and extraction is applied for root-zone soil moisture estimation, but by only considering its separate temporal or spatial correlations. The convolutional long short-term memory (ConvLSTM) model, known to capture spatiotemporal patterns of large-scale sequential datasets with the advantage of dealing with spatiotemporal sequence-forecasting problem, was used in this study to estimate root-zone soil moisture based on remote sensing-based variables. Owing to limitation of regional soil moisture observation data, the physical model Hydrus-1D was used to generate large and spatiotemporal vertical soil moisture dataset for the ConvLSTM model training and verification. Then, normalized difference vegetation index (NDVI) etc. remote sensing-based factors were selected as predictive variables. Results of the ConvLSTM model showed that the fitting coefficients (R2) of the root-zone soil moisture estimation significantly increased compared to those achieved by Global Land Data Assimilation System products, especially for deep layers. For example, R2 increased from 0.02 to 0.60 at depth of 40 cm. This study suggests that a combination of the physical model and AI is a flexible tool capable of predicting spatiotemporally continuous root-zone soil moisture with good accuracy on a large scale.

Machine learning-aided risk prediction for metabolic syndrome based on 3 years study.

Metabolic syndrome (MetS) is a group of physiological states of metabolic disorders, which may increase the risk of diabetes, cardiovascular and other diseases. Therefore, it is of great significance to predict the onset of MetS and the corresponding risk factors. In this study, we investigate the risk prediction for MetS using a data set of 67,730 samples with physical examination records of three consecutive years provided by the Department of Health Management, Nanfang Hospital, Southern Medical University, P.R. China. Specifically, the prediction for MetS takes the numerical features of examination records as well as the differential features by using the examination records over the past two consecutive years, namely, the differential numerical feature (DNF) and the differential state feature (DSF), and the risk factors of the above features w.r.t different ages and genders are statistically analyzed. From numerical results, it is shown that the proposed DSF in addition to the numerical feature of examination records, significantly contributes to the risk prediction of MetS. Additionally, the proposed scheme, by using the proposed features, yields a superior performance to the state-of-the-art MetS prediction model, which provides the potential of effective prescreening the occurrence of MetS.

Sleep, depression, and anxiety in family caregivers of nasopharyngeal carcinoma patients before therapy.

Sleep disturbance, anxiety, and depression are frequently observed in cancer patients. There have fewer studies about the sleep and emotional status of nasopharyngeal carcinoma (NPC) patient family caregivers (FCs) before treatment. We explored the sleep, depression, and anxiety in NPC patient FCs before therapy, compared sleep quality between caregivers with and without depression and anxiety, and examined and related factors of sleep disturbance in FCs of NPC patients before therapy. FC-patient dyads included from two centers were 92 in total. The proportions of poor sleep, anxiety, and depression in NPC patient FCs were 45.7%, 43.5%, and 54.3%, respectively. FCs with anxiety or depression were more inclined to report decreased sleep quality. Depressed caregivers were 11.11 times more to be poor quality sleep before patients treatment (OR = 11.11, 95%; CI = 2.94-42.05). NPC patient FCs before treatment are at high risk of sleep disturbances, depression, and anxiety, especially those already experiencing anxiety and depression symptoms.

Transport of TiO2 and CeO2 nanoparticles in saturated porous media in the presence of surfactants with environmentally relevant concentrations.

Nanomaterials are threatening the environment and human health, but there has been little discussion about the stability and mobility of nanoparticles (NPs) in saturated porous media at environmentally relevant concentrations of surfactants, which is a knowledge gap in exploring the fate of engineered NPs in groundwater. Therefore, the influences of the anionic surfactant (sodium dodecylbenzene sulfonate, SDBS), the cationic surfactant (cetyltrimethylammonium bromide, CTAB), and the nonionic surfactant (Tween-80) with environmentally relevant concentrations of 0, 5, 10, and 20 mg/L on nano-TiO2 (nTiO2, negatively charged) and nano-CeO2 (nCeO2, positively charged) transport through saturated porous media were examined by column experiments. On the whole, with increasing SDBS concentration from 0 to 20 mg/L, the concentration peak of nTiO2 and nCeO2 in effluents increased by approximately 0.2 and 0.3 (dimensionless concentration, C/C0), respectively, because of enhanced stability and reduced aggregate size resulting from enhanced electrostatic and steric repulsions. By contrast, the transportability of NPs significantly decreased with increasing CTAB concentration due to the attachment of positive charges, which was opposite to the charge on the medium surface and facilitated the NP deposition. On the other hand, the addition of Tween-80 had no significant influence on the stability and mobility of nTiO2 and nCeO2. The results were also demonstrated by the colloid filtration theory (CFT) modeling and the Derjaguin-Landau-Verwey-Overbeek (DLVO) interaction calculations; it might promote the assessment and remediation of NP pollution in subsurface environments.

Review on the contamination and remediation of polycyclic aromatic hydrocarbons (PAHs) in coastal soil and sediments.

The rapid economic and population growth in coastal areas is causing increasingly serious polycyclic aromatic hydrocarbons (PAHs) pollution in these regions. This review compared the PAHs pollution characteristics of different coastal areas, including industrial zones, commercial ports, touristic cities, aquacultural & agricultural areas, oil & gas exploitation areas and megacities. Currently there are various treatment methods to remediate soils and sediments contaminated with PAHs. However, it is necessary to provide a comprehensive overview of all the available remediation technologies up to date, so appropriate technologies can be selected to remediate PAHs pollution. In view of that, we analyzed the characteristics of the remediation mechanism, summarized the remediation methods for soil or sediments in coastal areas, which were physical repair, chemical oxidation, bioremediation and integrated approaches. Besides, this review also reported the development of new multi-functional green and sustainable systems, namely, micro-nano bubble (MNB), biochar, reversible surfactants and peracetic acid. While physical repair, expensive but efficient, was regarded as a suitable method for the PAHs remediation in coastal areas because of land shortage, integrated approaches would produce better results. The ultimate aim of the review was to ensure the successful restructuring of PAHs contaminated soil and sediments in coastal areas. Due to the environment heterogeneity, PAHs pollution in coastal areas remains as a daunting challenge. Therefore, new and suitable technologies are still needed to address the environmental issue.

Development and validation of a nomogram for predicting acute kidney injury after orthotopic liver transplantation.

BACKGROUND: We aim to develop and validate a nomogram model for predicting severe acute kidney injury (AKI) after orthotopic liver transplantation (OLT). METHODS: A total of 576 patients who received OLT in our center were enrolled. They were assigned to the development and validation cohort according to the time of inclusion. Univariable and multivariable logistic regression using the forward variable selection routine were applied to find risk factors for post-OLT severe AKI. Based on the results of multivariable analysis, a nomogram was developed and validated. Patients were followed up to assess the long-term mortality and development of chronic kidney disease (CKD). RESULTS: Overall, 35.9% of patients were diagnosed with severe AKI. Multivariable logistic regression analysis revealed that recipients' BMI (OR 1.10, 95% CI 1.04-1.17, p = 0.012), hypertension (OR 2.32, 95% CI 1.22-4.45, p = 0.010), preoperative serum creatine (sCr) (OR 0.96, 95% CI 0.95-0.97, p < 0.001), and intraoperative fresh frozen plasm (FFP) transfusion (OR for each 1000 ml increase 1.34, 95% CI 1.03-1.75, p = 0.031) were independent risk factors for post-OLT severe AKI. They were all incorporated into the nomogram. The area under the ROC curve (AUC) was 0.73 (p < 0.05) and 0.81 (p < 0.05) in the development and validation cohort. The calibration curve demonstrated the predicted probabilities of severe AKI agreed with the observed probabilities (p > 0.05). Kaplan-Meier survival analysis showed that patients in the high-risk group stratified by the nomogram suffered significantly poorer long-term survival than the low-risk group (HR 1.92, p < 0.01). The cumulative risk of CKD was higher in the severe AKI group than no severe AKI group after competitive risk analysis (HR 1.48, p < 0.05). CONCLUSIONS: With excellent predictive abilities, the nomogram may be a simple and reliable tool to identify patients at high risk for severe AKI and poor long-term prognosis after OLT.

Association of dietary isoflavone consumption with subclinical cardiovascular disease in middle-aged and elderly Chinese people.

BACKGROUND AND AIMS: The association between isoflavone (ISF) consumption and cardiovascular disease (CVD) remains controversial because of limited evidence. Carotid atherosclerosis is an established indicator of subclinical CVD. The study aimed to investigate the relationship between dietary ISF intake and subclinical CVD in middle-aged and elderly adults. METHODS AND RESULTS: A total of 873 subjects aged 40-70 years without CVD were enrolled in this cross-sectional study. A restricted cubic spline was used to investigate the association between ISF intake and subclinical CVD risk. The odds ratio (OR) and 95% confidence interval of the risk of subclinical CVD for ISF were estimated by two-segmented logistic regression analysis. In Model 2, there was a non-linear association between ISF intake and the risk of subclinical CVD among women (Pnon-linear = 0.002), with an inverse association below the change point. The nadir for the risk of subclinical CVD among women was 7.26 mg/day (energy-adjusted). Below the change point, an increase of 1 mg ISF/day reduced the risk of subclinical CVD by 15%. There was no significant association between ISF intake and subclinical CVD risk above the change point (OR = 1.01 [0.99, 1.04]). ISF intake was not associated with subclinical CVD risk in men (Model 2: Pnon-linear = 0.224). CONCLUSIONS: Below the change point (7.26 mg/day), women with a higher intake of ISF had a significantly lower risk of subclinical CVD. Encouraging the consumption of ISF-rich foods may help to lower CVD risk in middle-aged and elderly women. TRIAL REGISTRATION: This study is registered at http://www.chictr.org.cn (ChiCTR 1900022445).

CD36 facilitates fatty acid uptake by dynamic palmitoylation-regulated endocytosis.

Fatty acids (FAs) are essential nutrients, but how they are transported into cells remains unclear. Here, we show that FAs trigger caveolae-dependent CD36 internalization, which in turn delivers FAs into adipocytes. During the process, binding of FAs to CD36 activates its downstream kinase LYN, which phosphorylates DHHC5, the palmitoyl acyltransferase of CD36, at Tyr91 and inactivates it. CD36 then gets depalmitoylated by APT1 and recruits another tyrosine kinase SYK to phosphorylate JNK and VAVs to initiate endocytic uptake of FAs. Blocking CD36 internalization by inhibiting APT1, LYN or SYK abolishes CD36-dependent FA uptake. Restricting CD36 at either palmitoylated or depalmitoylated state eliminates its FA uptake activity, indicating an essential role of dynamic palmitoylation of CD36. Furthermore, blocking endocytosis by targeting LYN or SYK inhibits CD36-dependent lipid droplet growth in adipocytes and high-fat-diet induced weight gain in mice. Our study has uncovered a dynamic palmitoylation-regulated endocytic pathway to take up FAs.

The associations between neutrophil-to-lymphocyte ratio and the Chinese Visceral Adiposity Index, and carotid atherosclerosis and atherosclerotic cardiovascular disease risk.

BACKGROUND: Inflammation and obesity are the main risk factors for the development of carotid atherosclerosis and atherosclerotic cardiovascular disease (ASCVD). The neutrophil-to-lymphocyte ratio (NLR) is a recently developed indicator of inflammation that can be easily calculated from blood cell counts. The Chinese Visceral Adiposity Index (CVAI) was used to assess visceral obesity in the Chinese population. AIMS: To explore the associations between both NLR and CVAI, and carotid atherosclerosis and ASCVD risk in elderly Chinese. METHODS: A total of 4437 participants aged ≥55 years and with no history of cardiovascular disease, were enrolled in this retrospective study. Anthropometric measurements, laboratory results, and carotid ultrasonography results were extracted from a database. We used established formulas to calculate NLR and CVAI, and the Pooled Cohort Equations to generate the 10-year ASCVD risk score. Participants were divided into two groups according to their 10-year ASCVD scores: <7.5% and ≥7.5%. RESULTS: NLR and CVAI were significantly higher in patients with carotid atherosclerosis. Regression analysis showed that NLR (OR 1.23, 95% CI 1.05-1.43, p = 0.01) and CVAI (OR 1.39, 95% CI 1.21-1.61, p = 0.001) were independent risk factors for carotid atherosclerosis. A combination of NLR and CVAI improved the goodness-of-fit (p < 0.001) and discriminability of the model (p = 0.0013). NLR, CVAI and carotid plaques showed positive associations with the 10-year ASCVD risk score (all p < 0.001). CONCLUSIONS: NLR and CVAI are positively associated with the prevalence of carotid atherosclerosis and high risk of ASCVD in elderly adults and could be useful in the identification of a high risk of atherosclerosis.