Plasma fatty acids and attention deficit hyperactivity disorder: a Mendelian randomization investigation

BackgroundAttention deficit hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder of childhood, and pathogenesis is not fully understood. Observational studies suggest an association between fatty acids abnormalities and ADHD, but there are contradictions and differences between these findings. To address this uncertainty, we employed a two-sample bidirectional Mendelian Randomization (MR) analysis to investigate the causal relationship between fatty acids and ADHD.MethodsWe conducted a two-sample Mendelian Randomization (MR) study, selecting single nucleotide polymorphisms (SNPs) highly correlated with fatty acid levels from the CHARGE Consortium as our instruments. The outcome data were sourced from the Psychiatric Genomics Consortium (PGC) dataset on ADHD, comprising 225,534 individuals, with 162,384 cases and 65,693 controls. Inverse variance weighting, MR-Egger, and weighted median methods were employed to estimate the causal relationship between fatty acids and ADHD. Cochran’s Q-test was used to quantify heterogeneity of instrumental variables. Sensitivity analyses included MR-Egger intercept tests, leave-one-out analyses, and funnel plots.ResultsThe MR analysis revealed no significant associations between genetically predicted levels of various saturated, monounsaturated, and polyunsaturated fatty acids (including omega-3 and omega-6) and ADHD risk in the CHARGE and PGC cohorts. Notably, an initial association with Dihomo-gamma-linolenic acid (DGLA) (OR = 1.009, p = 0.032 by IVW) did not persist after correction for multiple testing (adjusted p-value = 0.286). Sensitivity analysis supported our findings, indicating robustness. Moreover, there was a lack of evidence supporting a causal link from ADHD to fatty acids.ConclusionWhile our study on the basis of genetic data does not provide evidence to support the causal role of fatty acids in ADHD, it does not preclude their potential involvement in reducing the risk of ADHD. Further research is needed to explore this possibility

Matrine Reverses the Warburg Effect and Suppresses Colon Cancer Cell Growth via Negatively Regulating HIF-1α.

The Warburg effect is a peculiar feature of cancer’s metabolism, which is an attractive therapeutic target that could aim tumor cells while sparing normal tissue. Matrine is an alkaloid extracted from the herb root of a traditional Chinese medicine, Sophora flavescens Ait. Matrine has been reported to have selective cytotoxicity toward cancer cells but with elusive mechanisms. Here, we reported that matrine was able to reverse the Warburg effect (inhibiting glucose uptake and lactate production) and suppress the growth of human colon cancer cells in vitro and in vivo . Mechanistically, we revealed that matrine significantly decreased the messenger RNA (mRNA) and protein expression of HIF-1α, a critical transcription factor in reprogramming cancer metabolism toward the Warburg effect. As a result, the expression levels of GLUT1, HK2, and LDHA, the downstream targets of HIF-1α in regulating glucose metabolism, were dramatically inhibited by matrine. Moreover, this inhibitory effect of matrine was significantly attenuated when HIF-1α was knocked down or exogenous overexpressed in colon cancer cells. Together, our results revealed that matrine inhibits colon cancer cell growth via suppression of HIF-1α expression and its downstream regulation of Warburg effect. Matrine could be further developed as an antitumor agent targeting the HIF-1α-mediated Warburg effect for colon cancer treatment

2PL Model: Compare Generalized Linear Mixed Model with Latent Variable Model based IRT framework

Fitting item response theory (IRT) models using the generalized mixed logistic regression model (GLMM) has become more popular in large-scale assessment because GLMM allows combining complicated multilevel structures (i.e., students are nested in classrooms which are nested in schools) with IRT measurement models. However, the estimation accuracy of item parameters between these two models is not well examined. This study aimed to compare the estimation results of the GLMM based 2PL model (using the PLmixed R package) with the traditional IRT model (using flexMIRT software) under different sample sizes (N= 500, 1000, 5000) and test length (J = 15, 21) conditions. The simulation results showed that for both the GLMM-based method and the traditional method, item threshold estimates had lower bias than item discrimination parameters. We also found that according to the simulation study, GLMM estimates via PLmixed had lower accuracy than traditional IRT modeling via flexMIRT for items with high discrimination

The Inhibitory Mechanism of 7H-Pyrrolo[2,3-d]pyrimidine Derivatives as Inhibitors of P21-Activated Kinase 4 through Molecular Dynamics Simulation

The overexpression of p21-activated kinase 4 (PAK4) is associated with a variety of cancers. In this paper, the binding modes and inhibitory mechanisms of four 7H-pyrrolo[2,3-d]pyrimidine competitive inhibitors of PAK4 were investigated at the molecular level, mainly using molecular dynamics simulations and binding free energy calculations. The results show that the inhibitors had strong interactions with the hinge region, the β-sheets, and the residues with charged side chains around the 4-substituent. The terminal amino group of the inhibitor 5n was different from the other three, which could cause the enhancement of hydrogen bonds or electrostatic interactions formed with the surrounding residues. Thus, inhibitor 5n had the strongest inhibition capacity. The different halogen atoms on the 2-substituents of the inhibitors 5h, 5g, and 5e caused differences in the positions of the 2-benzene rings and affected the interactions of the hinge region. It also affected to some extent the orientations of the 4-imino groups and consequently their affinities for the surrounding charged residues. The combined results lead to the weakest inhibitory capacity of inhibitor 5e

Analysis of Accident Severity for Curved Roadways Based on Bayesian Networks

Crashes that occur on curved roadways are often more severe than straight road accidents. Previously, most studies focused on the associations between curved sections and roadway geometric characteristics. In this study, significant factors such as driver behavior, roadway features, vehicle factors, and environmental characteristics are identified and involved in analyzing traffic accident severity. Bayesian network analysis was conducted to deal with data, to explore the associations between variables, and to make predictions using these relationships. The results indicated that factors including point of impact, site of location, accident side of road, alcohol/drugs condition, etc., are relatively critical in crashes on horizontal curves. Accident severity increases when crashes occur on bridges. The sensitivity of accident severity to vehicle use, traffic control, point of impact, and alcohol/drugs condition is relatively high. Moreover, a combination of negative factors will aggravate accident severities. The results also proposed some suggestions regarding the design of vehicles, as well as the construction and improvement of curved roadways

Simulation Analysis on the Characteristics of Aerosol Particles to Inhibit the Infrared Radiation of Exhaust Plumes

Aerosol infrared stealth technology is a highly effective method to reduce the intensity of infrared radiation by releasing aerosol particles around the hot exhaust plume. This paper uses a Computational Fluid Dynamics (CFD) two-phase flow model to simulate the exhaust plume fields of three kinds of engine nozzles containing aerosol particles. The Planck-weighted narrow spectral band gas model and the Reverse Monte Carlo method are used for infrared radiation transfer calculations to analyze the influencing factors and laws for the suppression of the infrared radiation properties of exhaust plumes by four typical aerosol particles. The simulation calculation results show that the radiation suppression efficiency of aerosol particles on the exhaust plume reaches its maximum value at a detection angle (ϕ) of 0° and decreases with increasing ϕ, reaching its minimum value at 90°. Reducing the aerosol particle size and increasing the aerosol mass flux can enhance the suppression effect. In the exhaust plume studied in this paper, the radiation suppression effect is best when the particle size is 1 μm and the mass flux is 0.08 kg/s. In addition, the inhibition of aerosol particles varies among different materials, with graphite having the best inhibition effect, followed by H2O, MgO, and SiO2. Solid particles will increase the radiation intensity and change the spectral radiation characteristics of the exhaust plume at detection angles close to the vertical nozzle axis due to the scattering effect. Finally, this paper analyzed the suppression effects of three standard nozzle configurations under the same aerosol particle condition and found that the S-bend nozzle provides better suppression

CBSX2 is required for the efficient oxidation of chloroplast redox‐regulated enzymes in darkness

Abstract Thiol/disulfide‐based redox regulation in plant chloroplasts is essential for controlling the activity of target proteins in response to light signals. One of the examples of such a role in chloroplasts is the activity of the chloroplast ATP synthase (CFoCF1), which is regulated by the redox state of the CF1γ subunit and involves two cysteines in its central domain. To investigate the mechanism underlying the oxidation of CF1γ and other chloroplast redox‐regulated enzymes in the dark, we characterized the Arabidopsis cbsx2 mutant, which was isolated based on its altered NPQ (non‐photochemical quenching) induction upon illumination. Whereas in dark‐adapted WT plants CF1γ was completely oxidized, a small amount of CF1γ remained in the reduced state in cbsx2 under the same conditions. In this mutant, reduction of CF1γ was not affected in the light, but its oxidation was less efficient during a transition from light to darkness. The redox states of the Calvin cycle enzymes FBPase and SBPase in cbsx2 were similar to those of CF1γ during light/dark transitions. Affinity purification and subsequent analysis by mass spectrometry showed that the components of the ferredoxin‐thioredoxin reductase/thioredoxin (FTR‐Trx) and NADPH‐dependent thioredoxin reductase (NTRC) systems as well as several 2‐Cys peroxiredoxins (Prxs) can be co‐purified with CBSX2. In addition to the thioredoxins, yeast two‐hybrid analysis showed that CBSX2 also interacts with NTRC. Taken together, our results suggest that CBSX2 participates in the oxidation of the chloroplast redox‐regulated enzymes in darkness, probably through regulation of the activity of chloroplast redox systems in vivo

Anlotinib Exerts Inhibitory Effects against Cisplatin-Resistant Ovarian Cancer In Vitro and In Vivo

Background: Anlotinib is a highly potent multi-target tyrosine kinase inhibitor. Accumulating evidence suggests that anlotinib exhibits effective anti-tumor activity against various cancer subtypes. However, the effects of anlotinib against cisplatin-resistant (CIS) ovarian cancer (OC) are yet to be elucidated. The objective of this study was to investigate the inhibitory effect of anlotinib on the pathogenesis of cisplatin-resistant OC. Materials and Methods: Human OC cell lines (A2780 and A2780 CIS) were cultured and treated with or without anlotinib. The effects of anlotinib on cell proliferation were determined using cell-counting kit-8 and colony-formation assays. To evaluate the invasion and metastasis of OC cells, we performed wound-healing and transwell assays. The cell cycle was analyzed via flow cytometry. A xenograft mouse model was used to conduct in vivo studies to verify the effects of anlotinib. The expression of Ki-67 in the tumor tissue was detected via immunohistochemistry. Quantitative real-time polymerase chain reaction and Western blotting were used to measure the mRNA and protein levels. Results: Our study revealed that anlotinib significantly inhibited the proliferation, migration, and invasion of A2780 and A2780 CIS in a dose-dependent way in vitro (p < 0.05). Through R software ‘limma’ package analysis of GSE15372, it was found that, in comparison with A2780, PLK2 was expressed in significantly low levels in the corresponding cisplatin-resistant strains. The ERK1/2/Plk2 signaling axis mediates the inhibitory effect of anlotinib on the proliferation and migration of ovarian cancer cell lines. Moreover, our research found that anlotinib effectively inhibited the growth of tumor cells in an OC xenograft mouse model. Conclusions: In this study, anlotinib showed excellent inhibitory effects against cisplatin-resistant OC both in vitro and in vivo. These results add to the growing body of evidence supporting anlotinib as a potential anticancer agent against OC

Research progress of DNA molecular markers in spinach genetic breeding

The types and characteristics of DNA molecular markers were briefly introduced in this paper,while itemphatically illustrated sex test,disease-resistant spinach breeding,high-yield and high-quality spinach breeding,genetic relationship and diversity and molecular marker-assisted selection in spinach genetic breeding.Then,the future development and application prospects of DNA molecular markers were prospected