Table_1_Association between high-density lipoprotein cholesterol and type 2 diabetes mellitus: dual evidence from NHANES database and Mendelian randomization analysis.docx

BackgroundLow levels of high-density lipoprotein cholesterol (HDL-C) are commonly seen in patients with type 2 diabetes mellitus (T2DM). However, it is unclear whether there is an independent or causal link between HDL-C levels and T2DM. This study aims to address this gap by using the The National Health and Nutrition Examination Survey (NHANES) database and Mendelian randomization (MR) analysis.Materials and methodsData from the NHANES survey (2007-2018) with 9,420 participants were analyzed using specialized software. Logistic regression models and restricted cubic splines (RCS) were used to assess the relationship between HDL-C and T2DM incidence, while considering covariates. Genetic variants associated with HDL-C and T2DM were obtained from genome-wide association studies (GWAS), and Mendelian randomization (MR) was used to evaluate the causal relationship between HDL-C and T2DM. Various tests were conducted to assess pleiotropy and outliers.ResultsIn the NHANES study, all groups, except the lowest quartile (Q1: 0.28-1.09 mmol/L], showed a significant association between HDL-C levels and reduced T2DM risk (all P -13), and there was no evidence of pleiotropy or outliers.ConclusionThis study provides evidence supporting a causal relationship between higher HDL-C levels and reduced T2DM risk. Further research is needed to explore interventions targeting HDL-C levels for reducing T2DM risk.</p

Table_1_The association between systemic immune-inflammation index and chronic obstructive pulmonary disease in adults aged 40 years and above in the United States: a cross-sectional study based on the NHANES 2013–2020.docx

BackgroundInflammation is the core of Chronic obstructive pulmonary disease (COPD) development. The systemic immune-inflammation index (SII) is a new biomarker of inflammation. However, it is currently unclear what impact SII has on COPD. This study aims to explore the relationship between SII and COPD.MethodsThis study analyzed patients with COPD aged ≥40 years from the National Health and Nutrition Examination Survey (NHANES) in the United States from 2013 to 2020. Restricted Cubic Spline (RCS) models were employed to investigate the association between Systemic immune-inflammation index (SII) and other inflammatory markers with COPD, including Neutrophil-to-Lymphocyte Ratio (NLR) and Platelet-to-Lymphocyte Ratio (PLR). Additionally, a multivariable weighted logistic regression model was utilized to assess the relationship between SII, NLR and PLR with COPD. To assess the predictive values of SII, NLR, and PLR for COPD prevalence, receiver operating characteristic (ROC) curve analysis was conducted. The area under the ROC curve (AUC) was used to represent their predictive values.ResultsA total of 10,364 participants were included in the cross-sectional analysis, of whom 863 were diagnosed with COPD. RCS models observed non-linear relationships between SII, NLR, and PLR levels with COPD risk. As covariates were systematically adjusted, it was found that only SII, whether treated as a continuous variable or a categorical variable, consistently remained positively associated with COPD risk. Additionally, SII (AUC = 0.589) slightly outperformed NLR (AUC = 0.581) and PLR (AUC = 0.539) in predicting COPD prevalence. Subgroup analyses revealed that the association between SII and COPD risk was stable, with no evidence of interaction.ConclusionSII, as a novel inflammatory biomarker, can be utilized to predict the risk of COPD among adults aged 40 and above in the United States, and it demonstrates superiority compared to NLR and PLR. Furthermore, a non-linear association exists between SII and the increased risk of COPD.</p

Additional file 1 of Heavy metal levels and flavonoid intakes are associated with chronic obstructive pulmonary disease: an NHANES analysis (2007–2010 to 2017–2018)

Additional file 1: Table S1. Participant characteristics divided by Blood_Cadmium levels (NHANES 2007-2010, 2017-2018; N = 7,265). Table S2. Participant characteristics divided by Blood_Lead levels (NHANES 2007-2010, 2017-2018; N = 7,265). Table S3. Participant characteristics divided by Anthocyanidins intake levels (NHANES 2007-2010, 2017-2018; N = 7,265). Table S4. Participant characteristics divided by Isoflavones intake levels (NHANES 2007-2010, 2017-2018; N = 7,265). Table S5. Participant characteristics divided by Flavonesintake levels (NHANES 2007-2010, 2017-2018; N = 7,265). Table S6. Combined effects of Flavonoid intake and blood Cadmium levels on COPD incidence. Table S7. Combined effects of Flavonoid intake and blood Lead levels on COPD incidence. Table S8. Combined effects of Flavonoid intake and blood Mercury levels on COPD incidence. Figure S1. Analysis of the relationship between blood cadmium levels, anthocyanidins intake, and COPD using restricted cubic spline models. Figure represents the relationship between Cadmium, anthocyanidins intake, and COPD adjusted for age, sex, race, PIR (Poverty Index), BMI, marital status, education level, smoking status, alcohol consumption, hypertension, coronary heart disease, and diabetes.   The solid red line represents the combined restricted cubic spline curve model, and the shaded area represents the 95% confidence interval of the combined curve (There is no Log conversion for COPD variables in the figure). The dashed line represents the risk of developing COPD when blood cadmium levels (A) are in Q1 (0.07-0.24ug/L) or anthocyanin intake (B) is in Q1 (0-1.015mg). Table S9. Nutrient reference table for anthocyanin-rich foods. Figure S2. Subgroup analysis of the relationship between blood lead levels and COPD risk

Supporting Information for Study on the optimization of the deposition rate of planetary GaN-MOCVD films based on CFD simulation and the corresponding surface model

The Table S1 is about Eight sets of results based on RSM model predictions and CFD simulation; The Figures S1-S3 are about temperature profile with different regions and different speeds; The Figures S3-S15 are about mass fractions of Ga-containing with different regions and different speeds

Regions of decreased grey matter volume at baseline in antipsychotic-naïve patients with schizophrenia compared to healthy controls. <i>P</i><0.001, uncorrected, threshold = 50.

<p>Regions of decreased grey matter volume at baseline in antipsychotic-naïve patients with schizophrenia compared to healthy controls. <i>P</i><0.001, uncorrected, threshold = 50.</p

Regions of increased grey matter volume from baseline to follow-up in patients with schizophrenia.

<p>Regions of increased grey matter volume from baseline to follow-up in patients with schizophrenia.</p

Modeling Free Nitrous Acid Inhibition on the Removal of Nitrogen and Atenolol during Sidestream Partial Nitritation Processes

Sidestream serves as an important reservoir collecting pharmaceuticals from sludge. However, the knowledge on sidestream pharmaceutical removal is still insufficient. In this work, atenolol biodegradation during sidestream partial nitritation (PN) processes characterized by high free nitrous acid (FNA) accumulation was modeled. To describe the FNA inhibition on ammonia oxidation and atenolol removal, Vadivelu-type and Hellinga-type inhibition kinetics were introduced into the model framework. Four inhibitory parameters along with four biodegradation kinetic parameters were calibrated and validated separately with eight sets of batch experimental data and 60 days’ PN reactor operational data. The developed model could accurately reproduce the dynamics of nitrogen and atenolol. The model prediction further revealed that atenolol biodegradation efficiencies by ammonia-oxidizing bacteria (AOB)-induced cometabolism, AOB-induced metabolism, and heterotrophic bacteria-induced biodegradation were 0, ∼ 60, and ∼35% in the absence of ammonium and FNA; ∼ 14, ∼ 29, and ∼28% at 0.03 mg-N L–1 FNA; and 7, 15, and 5% at 0.19 mg-N L–1 FNA. Model simulation showed that the nitritation efficiency of ∼99% and atenolol removal efficiency of 57.5% in the PN process could be achieved simultaneously by controlling pH at 8.5, while 89.2% total nitrogen and 57.1% atenolol were removed to the maximum at pH of 7.0 in PN coupling with the anammox process. The pH-based operational strategy to regulate FNA levels was mathematically demonstrated to be effective for achieving the simultaneous removal of nitrogen and atenolol in PN-based sidestream processes

Covalently Assembled Black Phosphorus/Conductive C₃N₄ Hybrid Material for Flexible Supercapacitors Exhibiting a Superlong 30,000 Cycle Durability

Black phosphorus (BP) has been demonstrated as a promising electrode material for supercapacitors. Currently, the main limitation of its practical application is the low electrical conductivity and poor structure stability. Hence, BP-based supercapacitors usually severely suffer from low capacitance and poor cycling stability. Herein, a chemically bridged BP/conductive g-C3N4 (BP/c-C3N4) hybrid is developed via a facile ball-milling method. Covalent P–C bonds are generated through the ball-milling process, effectively preventing the structural distortion of BP induced by ion transport and diffusion. In addition, the overall electrical conductivity is significantly enhanced owing to the sufficient coupling between BP and highly conductive c-C3N4. Moreover, the imbalanced charge distribution around the C atom can induce the generation of a local electric field, facilitating the charge transfer behavior of the electrode material. As a result, the BP/c-C3N4-20:1 flexible supercapacitor (FSC) exhibits an outstanding volumetric capacitance of 42.1 F/cm3 at 0.005 V/s, a high energy density of 5.85 mW h/cm3, and a maximum power density of 15.4 W/cm3. More importantly, the device delivers excellent cycling stability with no capacitive loss after 30,000 cycles

DataSheet2_Concordance of the treatment patterns for major depressive disorders between the Canadian Network for Mood and Anxiety Treatments (CANMAT) algorithm and real-world practice in China.pdf

Background: Antidepressant (AD) algorithm is an important tool to support treatment decision-making and improve management of major depressive disorder (MDD). However, little is known about its concordance with real-world practice. This study aimed to assess the concordance between the longitudinal treatment patterns and AD algorithm recommended by a clinical practice guideline in China.Methods: Data were obtained from the electronic medical records of Shanghai Mental Health Center (SMHC), one of the largest mental health institutions in China. We examined the concordance between clinical practice and the Canadian Network for Mood and Anxiety Treatments (CANMAT) algorithm among a cohort composed of 19,955 MDD patients. The longitudinal characteristics of treatment regimen and duration were described to identify the specific inconsistencies. Demographics and health utilizations of the algorithm-concordant and -discordant subgroups with optimized treatment were measured separately.Results: The overall proportion of algorithm-concordant treatment significantly increased from 84.45% to 86.03% during the year of 2015–2017. Among the patients who received recommended first-line drugs with subsequent optimized treatment (n = 2977), the concordance proportion was 27.24%. Mirtazapine and trazodone were the most used drugs for adjunctive strategy. Inadequate or extended duration before optimized treatment are common inconsistency. The median length of follow-up for algorithm-concordant (n = 811) and algorithm-discordant patients (n = 2166) were 153 days (Q1-Q3 = 79–328) and 368 days (Q1-Q3 = 181–577) respectively, and the average number of clinical visits per person-year was 13.07 and 13.08 respectively.Conclusion: Gap existed between clinical practice and AD algorithm. Improved access to evidence-based treatment is required, especially for optimized strategies during outpatient follow-up.</p

The cuing effects on N1 amplitude (μv) at each SOA in patients with schizophrenia and healthy controls (Mean±S.E.).

<p>SOA: stimulus onset asynchrony = time from onset of cue to onset of target.</p><p>The cuing effects on N1 amplitude (μv) at each SOA in patients with schizophrenia and healthy controls (Mean±S.E.).</p