Rosmarinic acid suppresses the progression of COPD via Syk by modulating airway inflammation and epithelial apoptosis in vivo and in vitro.

Rosmarinic acid (RosA), a hydrophilic phenolic compound found in various plants, has several biological effects such as anti-inflammatory and anti-apoptosis activities. However, its potential impact on chronic obstructive pulmonary disease (COPD) and its underlying mechanism has not been investigated. In this study, we explored the potential therapeutic effects and mechanism of RosA on COPD airway inflammation and alveolar epithelial apoptosis in vivo and in vitro. Our data suggested that RosA may be a therapeutic candidate for COPD with low toxicity. The corresponding mechanism lies in its anti-inflammatory effect on macrophage and bronchial epithelial cells, as well as protective effect on lung epithelial apoptosis via the jointly cross-target spleen tyrosine kinase (Syk).

Compressed cerebro-cerebellar functional gradients in children and adolescents with attention-deficit/hyperactivity disorder.

Both cortical and cerebellar developmental differences have been implicated in attention-deficit/hyperactivity disorder (ADHD). Recently accumulating neuroimaging studies have highlighted hierarchies as a fundamental principle of brain organization, suggesting the importance of assessing hierarchy abnormalities in ADHD. A novel gradient-based resting-state functional connectivity analysis was applied to investigate the cerebro-cerebellar disturbed hierarchy in children and adolescents with ADHD. We found that the interaction of functional gradient between diagnosis and age was concentrated in default mode network (DMN) and visual network (VN). At the same time, we also found that the opposite gradient changes of DMN and VN caused the compression of the cortical main gradient in ADHD patients, implicating the co-occurrence of both low- (visual processing) and high-order (self-related thought) cognitive dysfunction manifesting in abnormal cerebro-cerebellar organizational hierarchy in ADHD. Our study provides a neurobiological framework to better understand the co-occurrence and interaction of both low-level and high-level functional abnormalities in the cortex and cerebellum in ADHD.

Reference genome sequence and population genomic analysis of peas provide insights into the genetic basis of Mendelian and other agronomic traits.

Peas are essential for human nutrition and played a crucial role in the discovery of Mendelian laws of inheritance. In this study, we assembled the genome of the elite vegetable pea cultivar 'Zhewan No. 1' at the chromosome level and analyzed resequencing data from 314 accessions, creating a comprehensive map of genetic variation in peas. We identified 235 candidate loci associated with 57 important agronomic traits through genome-wide association studies. Notably, we pinpointed the causal gene haplotypes responsible for four Mendelian traits: stem length (Le/le), flower color (A/a), cotyledon color (I/i) and seed shape (R/r). Additionally, we discovered the genes controlling pod form (Mendelian P/p) and hilum color. Our study also involved constructing a gene expression atlas across 22 tissues, highlighting key gene modules related to pod and seed development. These findings provide valuable pea genomic information and will facilitate the future genome-informed improvement of pea crops.

Youthful small extracellular vesicles restore the function and reparative capacity of inflammatory-impaired periodontal ligament stem cells via delivering protein biglycan for bone regeneration.

Regenerating inflamed bone defects represents a severe clinical challenge due to the undesirable inflammatory microenvironment. The inflammatory stimulus poses a weighty threat to the regenerative capacity of endogenously derived mesenchymal stem cells (MSCs), which are mainly responsible for osteogenic differentiation, thereby resulting in compromised endogenous bone formation. Consequently, alleviating the biological characteristics of inflammatory-impaired MSCs is crucial for promoting inflamed bone regeneration. Nano-sized small extracellular vesicles (sEVs) have emerged as promising therapeutic tools to orchestrate MSCs fate due to their intrinsic biocompatibility and encapsulated bioactive contents. In the present study, we extracted sEVs from youthful and adult dental pulp MSCs and explored their ability to recover inflammation-compromised periodontal ligament stem cells (IPDLSCs). The results indicated that both types of sEVs were capable of facilitating IPDLSCs osteogenesis. However, young sEVs exhibited a more robust potential at a lower concentration compared to adult sEVs. Mechanically, young sEVs enhanced the expression of bone morphogenetic protein 4 (BMP4) via delivering the protein Biglycan, which correspondingly promoted the osteogenic capability of IPDLSCs. Collectively, our findings emphasized that young sEVs hold enormous potential to rescue the inherent function and regenerative competence of inflammation-impaired MSCs, shedding light on their promising therapeutic prospects for infected bone regeneration.

Novel glucomannan-like polysaccharide from Lycium barbarum L. ameliorates renal fibrosis via blocking macrophage-to-myofibroblasts transition.

The macrophage to myofibroblasts transition (MMT) has been reported as a newly key target in renal fibrosis. Lycium barbarum L. is a traditional Chinese medicine for improving renal function, in which its polysaccharides (LBPs) are the mainly active components. However, whether the role of LBPs in treating renal fibrosis is related to MMT process remain unclear. The purpose of this study was to explore the relationship between the regulating effect on MMT process and the anti-fibrotic effect of LBPs. Initially, small molecular weight LBPs fractions (LBP-S) were firstly isolated via Sephadex G-100 column. Then, the potent inhibitory effect of LBP-S on MMT process was revealed on bone marrow-derived macrophages (BMDM) model induced by TGF-ß. Subsequently, the chemical structure of LBP-S was elucidated through monosaccharide, methylation and NMR spectrum analysis. In vivo biodistribution characteristics studies demonstrated that LBP-S exhibited effectively accumulation in kidney via intraperitoneal administration. Finally, LBP-S showed a satisfactory anti-renal fibrotic effect on unilateral ureteral obstruction operation (UUO) mice, which was significantly reduced following macrophage depletion. Overall, our findings indicated that LPB-S could alleviate renal fibrosis through regulating MMT process and providing new candidate agents for chronic kidney disease (CKD) related fibrosis treatment.

Photonic stepped-frequency radar with 150-m unambiguous detection and centimeter range resolution.

Photonic stepped-frequency radars based on optical frequency-shifting modulation have shown attractive properties such as wide bandwidth, centimeter range resolution, inherent frequency-time linearity with low spectrum spurs, and reduced system complexity. However, existing approaches typically exhibit meter- or centimeter-level radar range ambiguity, inversely proportional to the frequency step, due to the large frequency shift determined by acousto-optic or electro-optic (EO) modulators. Here, we overcome this limitation by injecting a narrowband, stepped-frequency signal into an optical frequency-shifting fiber cavity to achieve, for the first time, to our knowledge, a broadband photonic stepped-frequency radar with 150-m unambiguous detection and centimeter range resolution, surpassing the reported photonic- and electronic-based counterparts. The demonstrated approach effectively resolves the trade-off between ambiguity range and shifting frequency while maintaining the signal quality and bandwidth, bringing its practicality into reach for outdoor applications.

Unearthing New ccr Genes and Staphylococcal Cassette Chromosome Elements in Staphylococci Through Genome Mining.

Staphylococcal cassette chromosome mec (SCCmec) typing is crucial for investigating methicillin-resistant Staphylococcus aureus (MRSA), relying primarily on the combination of ccr and mec gene complexes. To date, 19 ccr genes and 10 ccr gene complexes have been identified, forming 15 SCCmec types. With the vast release of bacterial genome sequences, mining the database for novel ccr gene complexes and SCC/SCCmec elements could enhance MRSA epidemiological studies. In this study, we identified 12 novel ccr genes (6 ccrA, 3 ccrB, and 3 ccrC) through mining of the National Center for Biotechnology Information (NCBI) database, forming 12 novel ccr gene complexes and 10 novel SCC elements. Overexpression of 5 groups of novel Ccr recombinases (CcrA9B3, CcrA10B1, CcrC3, CcrC4, and CcrC5) in a mutant MRSA strain lacking the ccr gene and extrachromosomal circular intermediate (ciSCC) production significantly promoted ciSCC production, demonstrating their biological activity. This discovery provides an opportunity to advance MRSA epidemiological research and develop database-based bacterial typing methods.

Multiagent Continual Coordination via Progressive Task Contextualization.

Cooperative multiagent reinforcement learning (MARL) has attracted significant attention and has the potential for many real-world applications. Previous arts mainly focus on facilitating the coordination ability from different aspects (e.g., nonstationarity and credit assignment) in single-task or multitask scenarios, ignoring the stream of tasks that appear in a continual manner. This ignorance makes the continual coordination an unexplored territory, neither in problem formulation nor efficient algorithms designed. Toward tackling the mentioned issue, this article proposes an approach, multiagent continual coordination via progressive task contextualization (MACPro). The key point lies in obtaining a factorized policy, using shared feature extraction layers but separated independent task heads, each specializing in a specific class of tasks. The task heads can be progressively expanded based on the learned task contextualization. Moreover, to cater to the popular centralized training with decentralized execution (CTDE) paradigm in MARL, each agent learns to predict and adopt the most relevant policy head based on local information in a decentralized manner. We show in multiple multiagent benchmarks that existing continual learning methods fail, while MACPro is able to achieve close-to-optimal performance. More results also disclose the effectiveness of MACPro from multiple aspects, such as high generalization ability.

Polycyclic aromatic hydrocarbons exposure and arterial stiffness-related plasma miRNAs: A panel study.

The underlying mechanisms between polycyclic aromatic hydrocarbons (PAHs) exposure and arterial stiffness are poorly understood. We carried out a panel study involving three repeated surveys to examine the associations of individual and mixture of PAHs exposure with arterial stiffness-related miRNAs among 123 community adults. In linear mixed-effect (LME) models, we found that urinary 9-hydroxyfluorene (9-OHFlu), 2-hydroxyphenanthrene (2-OHPh), 9-hydroxyphenanthrene (9-OHPh) at lag 0 day were positively linked to miR-146a and/or miR-222. The Bayesian kernel machine regression (BKMR) analyses revealed positive overall associations of PAHs mixture at lag 0 day with miR-146a and miR-222, and urinary 9-OHFlu contributed the most. In addition, an inter-quartile range (IQR) increase in urinary 9-OHFlu at lag 0 day was associated with elevated miR-146a and miR-222 by 0.16 (95% CI: 0.02, 0.30) to 0.34 (95% CI: 0.13, 0.54). Accordingly, exposure to PAHs, especially 9-OHFlu at lag 0 day, was related to elevated arterial stiffness-related plasma miRNAs.

Periodontal disease increases the severity of chronic obstructive pulmonary disease: a Mendelian randomization study.

BACKGROUND: Recent research suggests that periodontitis can increase the risk of chronic obstructive pulmonary disease (COPD). In this study, we performed two-sample Mendelian randomization (MR) and investigated the causal effect of periodontitis (PD) on the genetic prediction of COPD. The study aimed to estimate how exposures affected outcomes. METHODS: Published data from the Gene-Lifestyle Interaction in the Dental Endpoints (GLIDE) Consortium's genome-wide association studies (GWAS) for periodontitis (17,353 cases and 28,210 controls) and COPD (16,488 cases and 169,688 controls) from European ancestry were utilized. This study employed a two-sample MR analysis approach and applied several complementary methods, including weighted median, inverse variance weighted (IVW), and MR-Egger regression. Multivariable Mendelian randomization (MVMR) analysis was further conducted to mitigate the influence of smoking on COPD. RESULTS: We chose five single-nucleotide polymorphisms (SNPs) as instrumental variables for periodontitis. A strong genetically predicted causal link between periodontitis and COPD, that is, periodontitis as an independent risk factor for COPD was detected. PD (OR = 1.102951, 95% CI: 1.005-1.211, p = 0.039) MR-Egger regression and weighted median analysis results were coincident with those of the IVW method. According to the sensitivity analysis, horizontal pleiotropy's effect on causal estimations seemed unlikely. However, reverse MR analysis revealed no significant genetic causal association between COPD and periodontitis. IVW (OR = 1.048 > 1, 95%CI: 0.973-1.128, p = 0.2082) MR Egger (OR = 0.826, 95%CI:0.658-1.037, p = 0.1104) and weighted median (OR = 1.043, 95%CI: 0.941-1.156, p = 0.4239). The results of multivariable Mendelian randomization (MVMR) analysis, after adjusting for the confounding effect of smoking, suggest a potential causal relationship between periodontitis and COPD (P = 0.035). CONCLUSION: In this study, periodontitis was found to be independent of COPD and a significant risk factor, providing new insights into periodontitis-mediated mechanisms underlying COPD development.

HRD-Net: High resolution segmentation network with adaptive learning ability of retinal vessel features.

Retinal segmentation is a crucial step in the early warning of human health conditions. However, retinal blood vessels possess complex curvature, irregular distribution, and contain multi-scale fine structures, which make the limited receptive field of regular convolution challenging to process their vascular details efficiently. Additionally, the encoder-decoder based network leads to irreversible spatial information loss because of multiple downsampling, resulting in over-segmentation and missed segmentation of the vessels. For this reason, we develop a high-resolution network based on Deformable Convolution v3, called HRD-Net. By constructing a high-resolution representation, the network allows special attention to be paid to the details of tiny blood vessels. The proposed feature enhancement cascade module based on Deformable Convolution v3 can flexibly adapt and capture the ever-changing morphology and intricate connections of retinal blood vessels, ensuring the continuity of vessel segmentation. In the output phase of the network, the proposed global aggregation module integrates full-resolution feature maps while suppressing redundant features, achieving an effective fusion of high-level semantic information and spatial detail information. In addition, we have re-examined the selection criteria for activation and normalization methods, and also refine the network architectures from a spatial domain perspective to release redundant computational loads. Testing on the DRIVE, STARE, and CHASE_DB1 datasets indicates that HRD-Net, with fewer parameters, outperforms existing segmentation methods on several evaluation metrics such as F1, ACC, SE, SP, AUC, and IOU.

Clinical prediction of microvascular invasion in hepatocellular carcinoma using an MRI-based graph convolutional network model integrated with nomogram.

OBJECTIVES: Based on enhanced MRI, a prediction model of microvascular invasion (MVI) for hepatocellular carcinoma (HCC) was developed using graph convolutional network (GCN) combined nomogram. METHODS: We retrospectively collected 182 HCC patients confirmed histopathologically, all of them performed enhanced MRI before surgery. The patients were randomly divided into training and validation groups. Radiomics features were extracted from the arterial phase (AP), portal venous phase (PVP), and delayed phase (DP), respectively. After removing redundant features, the graph structure by constructing the distance matrix with the feature matrix was built. Screening the superior phases and acquired GCN Score (GS). Finally, combining clinical, radiological and GS established the predicting nomogram. RESULTS: 27.5% (50/182) patients were with MVI positive. In radiological analysis, intratumoural artery (P = 0.007) was an independent predictor of MVI. GCN model with grey-level cooccurrence matrix-grey-level run length matrix features exhibited area under the curves of the training group was 0.532, 0.690, and 0.885 and the validation group was 0.583, 0.580, and 0.854 for AP, PVP, and DP, respectively. DP was selected to develop final model and got GS. Combining GS with diameter, corona enhancement, mosaic architecture, and intratumoural artery constructed a nomogram which showed a C-index of 0.884 (95% CI: 0.829-0.927). CONCLUSIONS: The GCN model based on DP has a high predictive ability. A nomogram combining GS, clinical and radiological characteristics can be a simple and effective guiding tool for selecting HCC treatment options. ADVANCES IN KNOWLEDGE: GCN based on MRI could predict MVI on HCC.

The Active Glucuronide Metabolite of the Brain Protectant IMM-H004 with Poor Blood-Brain Barrier Permeability Demonstrates a High Partition in the Rat Brain via Multiple Mechanisms.

BACKGROUND: Glucuronidation is an essential metabolic pathway for a variety of drugs. IMM-H004 is a novel neuroprotective agent against ischemic stroke, and its glucuronide metabolite IMM-H004G exhibits similar pharmacological activity. Despite possessing a higher molecular weight and polarity, brain exposure of IMM-H004G is much higher than that of IMM-H004. This study aimed to investigate the brain metabolism and transport mechanisms of IMM-H004 and IMM-H004G. METHODS: First, the possibility of IMM-H004 glucuronidation in the brain was evaluated in several human brain cell lines and rat homogenate. Subsequently, the blood-brain barrier carrier-mediated transport mechanism of IMM-H004 and IMM-H004G was studied using overexpression cell models. In addition, intracerebroventricular injection, in situ brain perfusion model, and microdialysis/microinjection techniques were performed to study the distribution profiles of IMM-H004 and IMM-H004G. RESULTS: IMM-H004 could be metabolized to IMM-H004G in both rat brain and HEB cells mediated by UGT1A7. However, IMM-H004G could not be hydrolyzed back into IMM-H004. Furthermore, the entry and efflux of IMM-H004 in the brain were mediated by the pyrilamine-sensitive H+/OC antiporter and P-gp, respectively, while the transport of IMM-H004G from the blood to the brain was facilitated by OATP1A2 and OATP2B1. Ultimately, stronger concentration gradients and OATP-mediated uptake played a critical role in promoting greater brain exposure of IMM-H004G. CONCLUSIONS: The active glucuronide metabolite of the brain protectant IMM-H004 with poor blood-brain barrier permeability demonstrates a high partition in the rat brain via multiple mechanisms, and our findings deepen the understanding of the mechanisms underlying the blood-brain barrier metabolism and transport of active glucuronide conjugates.

Inhibition of iRhom1 by CD44-targeting nanocarrier for improved cancer immunochemotherapy.

The multifaceted chemo-immune resistance is the principal barrier to achieving cure in cancer patients. Identifying a target that is critically involved in chemo-immune-resistance represents an attractive strategy to improve cancer treatment. iRhom1 plays a role in cancer cell proliferation and its expression is negatively correlated with immune cell infiltration. Here we show that iRhom1 decreases chemotherapy sensitivity by regulating the MAPK14-HSP27 axis. In addition, iRhom1 inhibits the cytotoxic T-cell response by reducing the stability of ERAP1 protein and the ERAP1-mediated antigen processing and presentation. To facilitate the therapeutic translation of these findings, we develop a biodegradable nanocarrier that is effective in codelivery of iRhom pre-siRNA (pre-siiRhom) and chemotherapeutic drugs. This nanocarrier is effective in tumor targeting and penetration through both enhanced permeability and retention effect and CD44-mediated transcytosis in tumor endothelial cells as well as tumor cells. Inhibition of iRhom1 further facilitates tumor targeting and uptake through inhibition of CD44 cleavage. Co-delivery of pre-siiRhom and a chemotherapy agent leads to enhanced antitumor efficacy and activated tumor immune microenvironment in multiple cancer models in female mice. Targeting iRhom1 together with chemotherapy could represent a strategy to overcome chemo-immune resistance in cancer treatment.

Prediction of jaywalker-vehicle conflicts based on encoder-decoder framework utilizing multi-source data.

Jaywalker-vehicle (J-V) conflicts at mid-blocks without crossing facilities in China are frequent and hazardous. Due to the unexpected and sudden nature of jaywalking activity, it is crucial to develop predictive models for J-V conflicts to offer pre-conflict warnings for road users. This study introduces a novel encoder-decoder framework that utilizes multi-source data to predict J-V conflict severity. We define three encoders to represent three types of input data, (1) J-V interaction encoder (Bi-LSTM), (2) jaywalker motion encoder (Bi-LSTM) and (3) background information encoder (MLP). Subsequently, features extracted by these three encoders are concatenated and transferred to the conflict severity decoder (MLP) to obtain the predicted severity level. We further conduct a case study using the surveyed video data at three mid-blocks without crossing facilities in Nanjing, China. The experimental results indicate that, compared to classical models, our proposed encoder-decoder (Proposed ED) model exhibits the best and stable predictive metrics. Furthermore, the results of the ablation study suggest that the incorporation of background information significantly enhances the four evaluative metrics of the Proposed ED model, with an average improvement of 24.291%. Additionally, the results of transferability analysis suggest that, when the ratio of added samples from the new mid-block reaches 40% to 50%, the predictive metrics of the updated models could stabilize at around 80% to 95%, indicating a notably good performance. Eventually, we derive several practical suggestions from the above findings, in order to help with J-V conflict prediction and jaywalking safety improvement.

Spatial and temporal prediction of secondary crashes combining stacked sparse auto-encoder and long short-term memory.

Secondary crashes occur within the spatial and temporal impact area of primary crashes, resulting in traffic delays and safety problems. While most existing studies focus on the likelihood of secondary crashes, predicting the spatio-temporal location of secondary crashes could offer valuable insights for implementing prevention strategies. This includes guiding the deployment of emergency response measures and determining appropriate speed limits. The main objective of this study is to develop a prediction method for the spatial and temporal locations of secondary crashes. A hybrid deep learning model SSAE-LSTM is proposed by combining stacked sparse auto-encoder (SSAE) and long short-term memory network (LSTM). Traffic and crash data on the California I-880 highway covering the period of 2017-2021 are collected. The identification of secondary crashes is performed by the speed contour map method. The time and distance gaps between primary and secondary crashes are modeled using multiple 5-minute interval traffic variables as inputs. Multiple models are developed for benchmarking purposes, including PCA-LSTM, which incorporates principal component analysis (PCA) and LSTM, SSAE-SVM, which incorporates SSAE and support vector machine (SVM), and back propagation neural network (BPNN). The performance comparison indicates that the hybrid SSAE-LSTM model outperforms the other models in terms of both spatial and temporal prediction. In particular, SSAE4-LSTM1 (with 4 SSAE layers and 1 LSTM layer) demonstrates superior spatial prediction performance, while SSAE4-LSTM2 (with 4 SSAE layers and 2 LSTM layers) excels in temporal prediction. A joint spatio-temporal evaluation is also conducted to measure the overall accuracy of the optimal models over different permitted spatio-temporal ranges. Finally, practical suggestions are provided for secondary crash prevention.

Investigating jaywalker crossing risks from the sequential-conflict perspective: A grouped random parameters generalized ordered probit model.

Jaywalking at the mid-blocks without crossing facilities has been widely acknowledged as a dangerous crossing behavior. Due to the "unexpected" nature of jaywalking activities, jaywalkers may encounter multiple conflicts in sequence, called sequential jaywalker-vehicle (J-V) conflicts in this study. Sequential conflicts are usually complex and hazardous, but receive little attention in previous studies. To fill such research gaps, this study investigates the jaywalking risks from the sequential-conflict perspective, providing a more comprehensive depiction of the jaywalking hazards. Moreover, the "lagged effects" of the previous conflict-related factors on the subsequent conflict are also explored. Such considerations could help with predicting J-V conflicts in advance, further assisting the drivers to adopt precautionary actions. The results indicate that, as the conflict sequence increases, a higher proportion of jaywalkers would behave aggressively, and the proportion of slight conflicts increases accordingly. Furthermore, the grouped random parameters generalized ordered probit model is established to identify the influencing factors of sequential conflicts, which could account for the panel effects and unobserved heterogeneity simultaneously. The model results indicate that jaywalkers' previous evasive actions, such as "decelerating while swerving behind the vehicle", could lead to severer subsequent conflicts. In addition, jaywalkers' previous risky actions (i.e. rushing before the vehicle, using phones) are prone to convey to the subsequent conflicts, further increasing the subsequent conflict severity level. Moreover, non-motor vehicles are found to be a threat to the jaywalkers at mid-blocks without crossing facilities. In light of the above-mentioned results, practical suggestions are provided to reduce the jaywalking activities and prevent the jaywalker-involved accidents.

Modeling of Fiber-Constrained Planar PVC Gel Actuators.

In recent years, plasticized poly (vinyl chloride) (PVC) gel has attracted increasing attention in soft robotics. However, there is scarce research on the deformation mechanism and modeling of PVC gel actuators. In this study, to investigate the deformation mechanism of fiber-constrained planar PVC gel actuators, we propose a complex nonlinear model based on traditional thermodynamic electroactive polymer (EAP) multi-field coupling theory. The proposed model can reveal the dielectric breakdown strength of PVC gels and predict the deformation of planar PVC gel actuators with varying levels of pre-stretching. The theoretical results were in good agreement with the experimental results, indicating the feasibility of the proposed model.

Genetic Predisposition to Periodontitis and Risk of Migraine: A Two-Sample Mendelian Randomization Study.

INTRODUCTION: Previous observational studies have associated periodontitis (PD) with migraine; however, the results are inconclusive and the causality of the association between PD and migraine remains unclear. This two-sample Mendelian randomization (MR) study was performed to explore the bi-directional causal relationship between PD and migraine. METHODS: To investigate the relationship between PD (17,353 cases; 28,210 controls) and migraine (1072 cases; 360,122 controls), we used genetic tools from the largest available genome-wide association study of European descent. Inverse variance-weighted (IVW) and a series of sensitivity analyses were used to explore the association between migraine and PD. We performed an MR study using seven SNPs (single nucleotide polymorphisms) as instrumental variables for PD to investigate the causal relationship between migraine and PD. RESULTS: We found no significant causal relationship between PD and migraine (odds ratio, OR = 1.000; 95% confidence interval, CI = 0.99-1.00; p = 0.65). Similarly, no evidence supported a causal relationship between migraine and PD (OR = 0.07; CI = 2.04 × 10-9-2.65 × 106; p = 0.77). A sensitivity analysis revealed that no potential polymorphic effect (p = 0.356) and heterogeneity (p = 0.652) exists for the variants used in constructing the genetic instrument. CONCLUSIONS: Based on the results of our MR study, there is no causal relationship between PD and migraines or migraines and PD.

Urinary phthalate metabolites and heart rate variability: A panel study.

Phthalates exposure is linked with cardiovascular disease. Decreased heart rate variability (HRV) is an early indicator of cardiac autonomic imbalance. We conducted a longitudinal panel study in 127 Chinese adults with 3 repeated visits to explore the associations of individual and mixtures of phthalates exposure with HRV. We quantified 10 urinary phthalate metabolites by gas chromatograph-tandem mass spectrometer (GC-MS/MS) and 6 HRV indices by 3-channel digital Holter monitors. Linear mixed-effect (LME) models and Bayesian kernel machine regression (BKMR) models were separately implemented to evaluate the associations. After multivariate adjustments, we found that urinary mono-ethyl phthalate (MEP), mono-iso-butyl phthalate (MiBP), and mono-n-butyl phthalate (MBP) at lag 0 day were inversely associated with low-frequency power (LF) or total power (TP) (all P-FDR <0.05). In mixture analysis, we observed negative overall associations of phthalate mixtures at lag 0 day with LF or TP, and MiBP was the major contributor. Moreover, stratified analysis suggested that the inverse relationships of MiBP at lag 0 day with LF and TP were more prominent in subjects aged >50 years (all Pinteraction < 0.01). Our findings revealed that exposure to individual and mixtures of phthalates, especially MiBP, were related to decreased HRV.