Association Between Helicobacter pylori and Laryngopharyngeal Reflux Disease: A Systematic Review and Meta-Analysis.

BACKGROUND: It is controversial that Helicobacter pylori (H pylori) is involved in the pathogenesis or development of laryngopharyngeal reflux disease (LPRD). OBJECTIVE: To investigate the potential association between LPRD and H pylori infection. MATERIAL AND METHODS: A systematic review was performed of studies assessing the diagnosis or treatment of LPRD among patients with H pylori infection. Data sources are PubMed/MEDLINE, EMBASE[Ovid], Cochrane Library, and Web of Science, and ClinicalTrials.gov. RESULTS: Fifteen studies were analyzed in the review, with all eligible for the meta-analysis. A significant association between H pylori infection and LPRD was detected for higher rates of H pylori infection in patients with LPRD than in non-LPRD patients (relative risk (RR), 1.35; 95% CI, 1.12-1.63; P = 0.002), and H pylori-positive patients had a higher prevalence of LPRD than H pylori-negative patients (RR, 1.19; 95% CI, 1.07-1.31; P = 0.001). The prevalence of H pylori among patients with LPRD was 49% (95% CI, 36-61), the prevalence of H pylori among patients with non-LPRD was 35% (95% CI, 23-49). CONCLUSION AND SIGNIFICANCE: The limited evidence indicated the association between LPRD risk and increased H pylori infection. Different population races, diagnostic approach to LPRD, variant H pylori testing methods, age and sex may contribute to the heterogeneity. Further well-designed studies regarding the efficacy of H pylori eradication in the treatment of LPRD are strongly recommended in the future.

Family risk, parental cortisol contagion, and parenting: A process-oriented approach to spillover.

This multi-method longitudinal study sought to investigate linkage in parental neuroendocrine functioning - indicated by cortisol - over two measurement occasions. In addition, we examined how parental cortisol linkage may operate as an intermediate factor in the cascade of contextual risks and parenting. Participants were 235 families with a young child (Mage = 33.56, 36.00 years for mothers and fathers respectively), who were followed for two annual measurement occasions. Parental cortisol linkage was measured around a laboratory conflict discussion task at both measurement occasions (i.e., pre-discussion, 20- and 40-minute post-discussion for each measurement occasion). Maternal and paternal parenting behavior was observed during a parent-child discipline discussion task. Findings indicated similar levels of cortisol linkage between parents over the two measurement occasions. Furthermore, cortisol linkage between parents operated as an intermediate factor between contextual risks and more compromised parenting behavior. That is, greater contextual risks, indicated by greater neighborhood risk and interparental conflict, were linked to greater cortisol linkage between parents over time, which was in turn linked to greater authoritarian parenting during parent-child interaction. Findings highlighted the importance of understanding physiological-linkage processes with respect to the impact of contextual risks on family functioning and may have crucial implications for clinical work.

Achieving Record External Quantum Efficiency of 11.5% in Solution-Processable Deep-Blue Organic Light-Emitting Diodes Utilizing Hot Exciton Mechanism.

High performance solution-processable deep-blue emitters with a Commission International de l'Eclairage (CIE) coordinate of CIEy ≤ 0.08 are highly desired in ultrahigh-definition display. Although, deep-blue materials with hybridized local and charge-transfer (HLCT) excited-state feature are promising candidates, their rigidity and planar molecular structures limit their application in solution-processing technique. Herein, four novel deep-blue solution-processable HLCT emitters were first proposed by attaching rigid imide aliphatic rings as functional units onto the HLCT emitting core. The functional units not only improve solubility, enhance thermal properties and morphological stability of the emitting core, but also promote photoluminescence efficiency, balance charge carrier transport, and inhibit aggregation-caused quenching effect due to the weak electron-withdrawing property as well as steric hindrance. The corresponding solution-processable organic light-emitting diodes (OLEDs) substantiate an unprecedented maximum external quantum efficiency (EQEmax) of 11.5% with an emission peak at 456 nm and excellent colour purity (full width at half maximum = 56 nm and CIEy = 0.09). These efficiencies represent the state-of-the-art device performance among the solution-processable blue OLEDs based on the "hot exciton" mechanism. This simple strategy opens up a new avenue for designing highly efficient solution-processable deep-blue organic luminescent materials.

Interparental Conflict and Early Adolescent Depressive Symptoms: Parent-Child Triangulation as the Mediator and Grandparent Support as the Moderator.

A notable ambiguity persists concerning whether distinct forms of parent-child triangulation (unstable coercive coalition, stable coalition, detouring-attacking, detouring supportive, parentification) might mediate the association between interparental conflict and early adolescent depressive symptoms similarly within the context of Chinese Confucianism. Filling this research gap, this study aimed to examine the mediating role of the five dimensions of parent-child triangulation in the association between interparental conflict and early adolescent depressive symptoms, as well as the moderating effect of grandparent support on this mediating pathway. Data were drawn from a sample of 761 Chinese adolescents (M age = 12.82 ± 0.47, 49.1% girls). Structural equation model analyses indicated that unstable coercive coalition, stable coalition, and detouring-attacking behaviors partially mediated the association between interparental conflict and adolescent depressive symptoms, while detouring-supportive behaviors and parentification did not demonstrate such mediating effects. Unlike Western societies, a negative correlation was observed between interparental conflict and parentification in the context of China. Grandparent support mitigated the adverse effects of both interparental conflict and the unstable coercive coalition on early adolescent depressive symptoms.

Using cross-validation methods to select time series models: Promises and pitfalls.

Vector autoregressive (VAR) modelling is widely employed in psychology for time series analyses of dynamic processes. However, the typically short time series in psychological studies can lead to overfitting of VAR models, impairing their predictive ability on unseen samples. Cross-validation (CV) methods are commonly recommended for assessing the predictive ability of statistical models. However, it is unclear how the performance of CV is affected by characteristics of time series data and the fitted models. In this simulation study, we examine the ability of two CV methods, namely,10-fold CV and blocked CV, in estimating the prediction errors of three time series models with increasing complexity (person-mean, AR, and VAR), and evaluate how their performance is affected by data characteristics. We then compare these CV methods to the traditional methods using the Akaike (AIC) and Bayesian (BIC) information criteria in their accuracy of selecting the most predictive models. We find that CV methods tend to underestimate prediction errors of simpler models, but overestimate prediction errors of VAR models, particularly when the number of observations is small. Nonetheless, CV methods, especially blocked CV, generally outperform the AIC and BIC. We conclude our study with a discussion on the implications of the findings and provide helpful guidelines for practice.

Messages are Never Propagated Alone: Collaborative Hypergraph Neural Network for Time-Series Forecasting.

This paper delves into the problem of correlated time-series forecasting in practical applications, an area of growing interest in a multitude of fields such as stock price prediction and traffic demand analysis. Current methodologies primarily represent data using conventional graph structures, yet these fail to capture intricate structures with non-pairwise relationships. To address this challenge, we adopt dynamic hypergraphs in this study to better illustrate complex interactions, and introduce a novel hypergraph neural network model named CHNN for correlated time series forecasting. In more detail, CHNN leverages both semantic and topological similarities via an interaction model and hypergraph diffusion process, thereby constructing comprehensive collaborative correlation scores that effectively guide spatial message propagation. In addition, it incorporates short-term temporal information to generate efficient spatio-temporal feature maps. Lastly, a long-term temporal module is proposed to generate future predictions utilizing both temporal attention and a gated recurrent network. Comprehensive experiments conducted on four real-world datasets, i.e., Tiingo, Stocktwits, NYC-Taxi, and Social Network demonstrate that the proposed CHNN markedly outperforms a range of benchmark methods.

Active polarization controller based on micro-ring resonators.

On-chip polarization handling is of great significance for optical interconnects to overcome polarization sensitivity. In this Letter, we propose and experimentally demonstrate a novel, to the best of our knowledge, on-chip polarization controller (PC) on a 220 nm silicon-on-insulator (SOI) platform. It is the first demonstration of a PC based on micro-ring resonators. Any input polarization states can be actively converted to the standard transverse-electric (TE) mode under the phase manipulation. Experimental results show that the insertion loss is less than 0.8 dB and the polarization dependent loss (PDL) is around 0.5 dB. The proposed device also exhibits excellent performances in wavelength tunability over the C band and 35 Gbps data transmission.

Deep-learning-based separation of shallow and deep layer blood flow rates in diffuse correlation spectroscopy.

Diffuse correlation spectroscopy faces challenges concerning the contamination of cutaneous and deep tissue blood flow. We propose a long short-term memory network to directly quantify the flow rates of shallow and deep-layer tissues. By exploiting the different contributions of shallow and deep-layer flow rates to auto-correlation functions, we accurately predict the shallow and deep-layer flow rates (RMSE = 0.047 and 0.034 ml/min/100 g of simulated tissue, R2 = 0.99 and 0.99, respectively) in a two-layer flow phantom experiment. This approach is useful in evaluating the blood flow responses of active muscles, where both cutaneous and deep-muscle blood flow increase with exercise.

HMCDA: a novel method based on the heterogeneous graph neural network and metapath for circRNA-disease associations prediction.

Circular RNA (CircRNA) is a type of non-coding RNAs in which both ends are covalently linked. Researchers have demonstrated that many circRNAs can act as biomarkers of diseases. However, traditional experimental methods for circRNA-disease associations identification are labor-intensive. In this work, we propose a novel method based on the heterogeneous graph neural network and metapaths for circRNA-disease associations prediction termed as HMCDA. First, a heterogeneous graph consisting of circRNA-disease associations, circRNA-miRNA associations, miRNA-disease associations and disease-disease associations are constructed. Then, six metapaths are defined and generated according to the biomedical pathways. Afterwards, the entity content transformation, intra-metapath and inter-metapath aggregation are implemented to learn the embeddings of circRNA and disease entities. Finally, the learned embeddings are used to predict novel circRNA-disase associations. In particular, the result of extensive experiments demonstrates that HMCDA outperforms four state-of-the-art models in fivefold cross validation. In addition, our case study indicates that HMCDA has the ability to identify novel circRNA-disease associations.

Different Responses of Bacteria and Archaea to Environmental Variables in Brines of the Mahai Potash Mine, Qinghai-Tibet Plateau.

Salt mines feature both autochthonous and allochthonous microbial communities introduced by industrialization. It is important to generate the information on the diversity of the microbial communities present in the salt mines and how they are shaped by the environment representing ecological diversification. Brine from Mahai potash mine (Qianghai, China), an extreme hypersaline environment, is used to produce potash salts for hundreds of millions of people. However, halophiles preserved in this niche during deposition are still unknown. In this study, using high-throughput 16S rRNA gene amplicon sequencing and estimation of physicochemical variables, we examined brine samples collected from locations with the gradient of industrial activity intensity and discrete hydrochemical compositions in the Mahai potash mine. Our findings revealed a highly diverse bacterial community, mainly composed of Pseudomonadota in the hypersaline brines from the industrial area, whereas in the natural brine collected from the upstream Mahai salt lake, most of the 16S rRNA gene reads were assigned to Bacteroidota. Halobacteria and halophilic methanogens dominated archaeal populations. Furthermore, we discovered that in the Mahai potash mining area, bacterial communities tended to respond to anthropogenic influences. In contrast, archaeal diversity and compositions were primarily shaped by the chemical properties of the hypersaline brines. Conspicuously, distinct methanogenic communities were discovered in sets of samples with varying ionic compositions, indicating their strong sensitivity to the brine hydrochemical alterations. Our findings provide the first taxonomic snapshot of microbial communities from the Mahai potash mine and reveal the different responses of bacteria and archaea to environmental variations in this high-altitude aquatic ecosystem.

Sequence pre-training-based graph neural network for predicting lncRNA-miRNA associations.

MicroRNAs (miRNAs) silence genes by binding to messenger RNAs, whereas long non-coding RNAs (lncRNAs) act as competitive endogenous RNAs (ceRNAs) that can relieve miRNA silencing effects and upregulate target gene expression. The ceRNA association between lncRNAs and miRNAs has been a research hotspot due to its medical importance, but it is challenging to verify experimentally. In this paper, we propose a novel deep learning scheme, i.e. sequence pre-training-based graph neural network (SPGNN), that combines pre-training and fine-tuning stages to predict lncRNA-miRNA associations from RNA sequences and the existing interactions represented as a graph. First, we utilize a sequence-to-vector technique to generate pre-trained embeddings based on the sequences of all RNAs during the pre-training stage. In the fine-tuning stage, we use Graph Neural Network to learn node representations from the heterogeneous graph constructed using lncRNA-miRNA association information. We evaluate our proposed scheme SPGNN on our newly collected animal lncRNA-miRNA association dataset and demonstrate that combining the $k$-mer technique and Doc2vec model for pre-training with the Simple Graph Convolution Network for fine-tuning is effective in predicting lncRNA-miRNA associations. Our approach outperforms state-of-the-art baselines across various evaluation metrics. We also conduct an ablation study and hyperparameter analysis to verify the effectiveness of each component and parameter of our scheme. The complete code and dataset are available on GitHub: https://github.com/zixwang/SPGNN.

Ultralow Coefficient of Thermal Expansion and a High Colorless Transparent Polyimide Film Realized Through a Reinforced Hydrogen-Bond Network by In Situ Polymerization of Aromatic Polyamide in Colorless Polyimide.

Colorless polyimides (CPIs) are a key substrate material for flexible organic light-emitting diode (OLED) displays and have attracted worldwide attention. Here, in this paper, the dispersion and interfacial interaction of aromatic polyamide (PA) in CPI (synthesized from 4,4'-(hexafluoroisopropylidene) diphthalic anhydride (6FDA) and 2,2'-bis(trifluoromethyl)benzidine (TFMB)) were significantly improved by in situ polymerization, and colorless transparent macromolecular polyimide composites (CPI-PAx) were successfully prepared by PA and CPI. By adjusting the ratio of PA to CPI, a high-performance engineering plastic with excellent film-forming properties was obtained. Molecular simulations confirmed the uniform distribution of PA in CPI and its interaction in polymers. In CPI-PAx, the CPI was locked by the PA chain, and numerous molecular chains were mutually entangled to form a hydrogen-bond network structure. Due to the strong interaction between the chains imparted by the hydrogen bonds of the PA, they do not slide under external forces and heating. In addition, the additive PA has excellent dimensional stability, thermal, and mechanical properties, and CPI has outstanding optical properties, so the synthesized CPI-PAx combines the comprehensive properties of PA and CPI. The CPI-PAx has excellent thermal and mechanical properties, with a thermal decomposition temperature of 499 °C, a glass transition temperature of 385 °C, a coefficient of thermal expansion of 0.8 ppm K-1, a tensile strength of 50.9 MPa, and an elastic modulus of 3.9 GPa. Particularly, CPI-PAx has a 90% transmittance in the visible region. These data prove that the strategy of combining PA and CPI by in situ polymerization is an effective method to circumvent the bottleneck of CPI in the current flexible window application, and this design strategy is universal.

White matter alterations in Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review of 129 diffusion imaging studies with meta-analysis.

Aberrant anatomical brain connections in attention-deficit/hyperactivity disorder (ADHD) are reported inconsistently across diffusion weighted imaging (DWI) studies. Based on a pre-registered protocol (Prospero: CRD42021259192), we searched PubMed, Ovid, and Web of Knowledge until 26/03/2022 to conduct a systematic review of DWI studies. We performed a quality assessment based on imaging acquisition, preprocessing, and analysis. Using signed differential mapping, we meta-analyzed a subset of the retrieved studies amenable to quantitative evidence synthesis, i.e., tract-based spatial statistics (TBSS) studies, in individuals of any age and, separately, in children, adults, and high-quality datasets. Finally, we conducted meta-regressions to test the effect of age, sex, and medication-naïvety. We included 129 studies (6739 ADHD participants and 6476 controls), of which 25 TBSS studies provided peak coordinates for case-control differences in fractional anisotropy (FA)(32 datasets) and 18 in mean diffusivity (MD)(23 datasets). The systematic review highlighted white matter alterations (especially reduced FA) in projection, commissural and association pathways of individuals with ADHD, which were associated with symptom severity and cognitive deficits. The meta-analysis showed a consistent reduced FA in the splenium and body of the corpus callosum, extending to the cingulum. Lower FA was related to older age, and case-control differences did not survive in the pediatric meta-analysis. About 68% of studies were of low quality, mainly due to acquisitions with non-isotropic voxels or lack of motion correction; and the sensitivity analysis in high-quality datasets yielded no significant results. Findings suggest prominent alterations in posterior interhemispheric connections subserving cognitive and motor functions affected in ADHD, although these might be influenced by non-optimal acquisition parameters/preprocessing. Absence of findings in children may be related to the late development of callosal fibers, which may enhance case-control differences in adulthood. Clinicodemographic and methodological differences were major barriers to consistency and comparability among studies, and should be addressed in future investigations.

Homogeneity Assumptions in the Analysis of Dynamic Processes.

With the increased use of time series data in human research, ranging from ecological momentary assessments to data passively obtained, researchers can explore dynamic processes more than ever before. An important question researchers must ask themselves is, do I think all individuals have similar processes? If not, how different, and in what ways? Dr. Peter Molenaar's work set the foundation to answer these questions by providing insight into individual-level analysis for processes that are assumed to differ across individuals in at least some aspects. Currently, such assumptions do not have a clear taxonomy regarding the degree of homogeneity in the patterns of relations among variables and the corresponding parameter values. This paper provides the language with which researchers can discuss assumptions inherent in their analyses. We define strict homogeneity as the assumption that all individuals have an identical pattern of relations as well as parameter values; pattern homogeneity assumes the same pattern of relations but parameter values can differ; weak homogeneity assumes there are some (but not all) generalizable aspects of the process; and no homogeneity explicitly assumes no population-level similarities in dynamic processes across individuals. We demonstrate these assumptions with an empirical data set of daily emotions in couples.

A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis.

Psychotic symptoms occur in a majority of schizophrenia patients and in ~50% of all Parkinson's disease (PD) patients. Altered grey matter (GM) structure within several brain areas and networks may contribute to their pathogenesis. Little is known, however, about transdiagnostic similarities when psychotic symptoms occur in different disorders, such as in schizophrenia and PD. The present study investigated a large, multicenter sample containing 722 participants: 146 patients with first episode psychosis, FEP; 106 individuals in at-risk mental state for developing psychosis, ARMS; 145 healthy controls matching FEP and ARMS, Con-Psy; 92 PD patients with psychotic symptoms, PDP; 145 PD patients without psychotic symptoms, PDN; 88 healthy controls matching PDN and PDP, Con-PD. We applied source-based morphometry in association with receiver operating curves (ROC) analyses to identify common GM structural covariance networks (SCN) and investigated their accuracy in identifying the different patient groups. We assessed group-specific homogeneity and variability across the different networks and potential associations with clinical symptoms. SCN-extracted GM values differed significantly between FEP and Con-Psy, PDP and Con-PD, PDN and Con-PD, as well as PDN and PDP, indicating significant overall grey matter reductions in PD and early schizophrenia. ROC analyses showed that SCN-based classification algorithms allow good classification (AUC ~0.80) of FEP and Con-Psy, and fair performance (AUC ~0.72) when differentiating PDP from Con-PD. Importantly, the best performance was found in partly the same networks, including the thalamus. Alterations within selected SCNs may be related to the presence of psychotic symptoms in both early schizophrenia and PD psychosis, indicating some commonality of underlying mechanisms. Furthermore, results provide evidence that GM volume within specific SCNs may serve as a biomarker for identifying FEP and PDP.

Bortezomib-loaded mixed micelles realize a "three-in-one" effect for enhanced breast cancer treatment.

Comprehensively regulating the TME is now regarded as a promising approach for cancer treatment. Herein, a novel "three-in-one" effect is presented for simultaneously killing tumor cells, inhibiting the EMT of CAFs, and improving immune responses. In this study, bortezomib (BTZ) is selected for the treatment of breast cancer; it has multiple pharmacological mechanisms for killing tumor cells through the NF-κB signaling pathway, inhibiting the activity of CAFs by activating caspase-3, and enhancing the function of CD8+ T cells by regulating the expression of immune-stimulating factors. To improve the druggability of BTZ in solid tumors, BTZ-loaded lipid/glycocholic acid mixed micelles (BTZ-LGs) were prepared to verify the "three-in-one" effect in killing tumor cells, inhibiting CAFs, and improving immune responses. In the present work, BTZ-LGs were verified to show enhanced in vitro cytotoxicity in both 4T1 cells and 4T1/NIH3T3 co-cultured cells, as well as a superior in vivo treatment effect in different tumor-bearing mouse models. Additionally, BTZ-LGs could regulate the expression of α-SMA, caspase-3, E-cadherin, and N-cadherin, indicating their good inhibiting ability on both tumor cells and CAFs. More importantly, immunological analysis revealed that BTZ-LGs promoted the expression of the immunostimulatory factor IL-2 in tumor tissues, activated anti-tumor T cells, and overcame tumor-induced CD8+ T cell dysfunction. All these findings suggest that BTZ-LGs can achieve a "three-in-one" effect in terms of killing tumor cells, suppressing CAFs, and improving immune responses. This simple and multi-effective therapeutic strategy offers a promising approach for cancer therapy.

Grafting Polyethyleneimine-Poly(ethylene glycol) Gel onto a Heat-Resistant Polyimide Nanofiber Separator for Improving Lithium-Ion Transporting Ability in Lithium-Ion Batteries.

To improve the lithium-ion transporting ability in lithium-ion batteries, a high-performance polyimide-based lithium-ion battery separator (PI-mod) was prepared by chemically grafting poly(ethylene glycol) (PEG) onto the surface of a heat-resistant polyimide nanofiber matrix with the assistance of amino-rich polyethyleneimine (PEI). The resulted PEI-PEG polymer coating exhibited unique gel-like properties with an electrolyte uptake rate of 168%, an area resistance as low as 2.60 Ω·cm2, and an ionic conductivity up to 2.33 mS·cm-1, which are 3.5, 0.10, and 12.3 times that of the commercial separator Celgard 2320, respectively. Meanwhile, the heat-resistant polyimide skeleton can effectively avoid thermal shrinkage of the modified separator even after 200 °C treatment for 0.5 h, which ensures the safety of the battery working under extreme conditions. The modified PI separator possessed a high electrochemical stability window of 4.5 V. Compared with the batteries from the commercial separator Celgard 2320 and the pure polyimide matrix, the assembled coin cell with the PI-mod separator showed much better rate capabilities and capacity retention due to the high electrolyte affinity of the PEI-PEG polymer coating. The developed strategy of using the electrolyte-swollen polymer to modify the thermal-resistant separator network provides an efficient way for establishing high-power lithium-ion batteries with good safety performance.

A pH­responsive hyaluronic acid nano­vehicle co­encapsulating doxorubicin and all­trans retinoic acid for the inhibition of hepatic stellate cell­induced tumor growth and metastasis.

All­trans retinoic acid (ATRA) has been implicated in the differentiation of hepatic stellate cells (HSCs). In the present study, the liver­targeting hyaluronic acid micelles (ADHG) were prepared for co­delivery of ATRA and doxorubicin (DOX) to block the HSC­hepatoma interrelation. To simulate the tumor microenvironment, an in vitro dual­cell model and an in vivo co­implantation mouse model were established for anticancer studies. The experimental methods involved the MTT assay, wound­healing assay, cellular uptake, flow cytometry and and in vivo antitumor study. The results revealed that the HSCs in the research models notably promoted tumor proliferation and migration. Furthermore, ADHG were readily internalized by cancer cells and HSCs simultaneously, and widely distributed in cancer regions. The in vivo antitumor studies demonstrated that ADHG could notably decrease HSC activation and extracellular matrix deposition, as well as constrain tumor growth and metastasis. Therefore, ATRA could facilitate DOX­induced anti­proliferation and anti­metastasis effects, and ADHG are a promising nano­sized formulation for the combination therapy of hepatocellular carcinoma.

Associations of Blood Cardiovascular Biomarkers With Brain Free Water and Its Relationship to Cognitive Decline: A Diffusion-MRI Study.

BACKGROUND AND OBJECTIVES: There is an increasing awareness of the "Heart-Brain Connection," whereby cardiovascular function is connected with cognition. Diffusion-MRI studies reported higher brain free water (FW) was associated with cerebrovascular disease (CeVD) and cognitive impairment. In this study, we investigated whether higher brain FW was related to blood cardiovascular biomarkers and whether FW mediated the associations between blood biomarkers and cognition. METHODS: Participants recruited from 2 Singapore memory clinics between 2010 and 2015 underwent collection of blood samples and neuroimaging at baseline and longitudinal neuropsychological assessments up to 5 years. We examined the associations of blood cardiovascular biomarkers (high-sensitivity cardiac troponin-T [hs-cTnT], N-terminal pro-hormone B-type natriuretic peptide [NT-proBNP], and growth/differentiation factor 15 [GDF-15]) with brain white matter (WM) and cortical gray matter (GM) FW derived from diffusion MRI using whole brain voxel-wise general linear regression. We then assessed the relationships among baseline blood biomarkers, brain FW, and cognitive decline using path models. RESULTS: A total of 308 older adults (76 with no cognitive impairment, 134 with cognitive impairment no dementia, and 98 with Alzheimer disease dementia and vascular dementia; mean [SD] age: 72.1 [8.3]) were included. We found that blood cardiovascular biomarkers were associated with higher FW in widespread WM regions and in specific GM networks including the default mode, executive control, and somatomotor networks at baseline (p < 0.01, family-wise error corrected). Baseline FW in widespread WM and network-specific GM fully mediated the associations of blood biomarkers with longitudinal cognitive decline over 5 years. Specifically, in GM, higher FW in the default mode network mediated the relationship with memory decline (hs-cTnT: ß = -0.115, SE = 0.034, p = 0.001; NT-proBNP: ß = -0.154, SE = 0.046, p = 0.001; GDF-15: ß = -0.073, SE = 0.027, p = 0.006); by contrast, higher FW in the executive control network was responsible for executive function decline (hs-cTnT: ß = -0.126, SE = 0.039, p = 0.001; NT-proBNP: ß = -0.110, SE = 0.038, p = 0.004; GDF-15: ß = -0.117, SE = 0.035, p = 0.001). Similar full mediation effects of brain FW were also identified for baseline cognition. DISCUSSION: Results suggested a role of brain FW in linking cardiovascular dysfunction to cognitive decline. These findings provide new evidence for brain-heart interactions, paving the way for prediction and monitoring of domain-specific cognitive trajectory.