Learning site-invariant features of connectomes to harmonize complex network measures.

Multi-site diffusion MRI data is often acquired on different scanners and with distinct protocols. Differences in hardware and acquisition result in data that contains site dependent information, which confounds connectome analyses aiming to combine such multi-site data. We propose a data-driven solution that isolates site-invariant information whilst maintaining relevant features of the connectome. We construct a latent space that is uncorrelated with the imaging site and highly correlated with patient age and a connectome summary measure. Here, we focus on network modularity. The proposed model is a conditional, variational autoencoder with three additional prediction tasks: one for patient age, and two for modularity trained exclusively on data from each site. This model enables us to 1) isolate site-invariant biological features, 2) learn site context, and 3) re-inject site context and project biological features to desired site domains. We tested these hypotheses by projecting 77 connectomes from two studies and protocols (Vanderbilt Memory and Aging Project (VMAP) and Biomarkers of Cognitive Decline Among Normal Individuals (BIOCARD) to a common site. We find that the resulting dataset of modularity has statistically similar means (p-value <0.05) across sites. In addition, we fit a linear model to the joint dataset and find that positive correlations between age and modularity were preserved.

T1 and T2 measurements across multiple 0.55T MRI systems using open-source vendor-neutral sequences.

PURPOSE: To compare T1 and T2 measurements across commercial and prototype 0.55T MRI systems in both phantom and healthy participants using the same vendor-neutral pulse sequences, reconstruction, and analysis methods. METHODS: Standard spin echo measurements and abbreviated protocol measurements of T1, B1, and T2 were made on two prototype 0.55 T systems and two commercial 0.55T systems using an ISMRM/NIST system phantom. Additionally, five healthy participants were imaged at each system using the abbreviated protocol for T1, B1, and T2 measurement. The phantom measurements were compared to NMR-based reference measurements to determine accuracy, and both phantom and in vivo measurements were compared to assess reproducibility and differences between the prototype and commercial systems. RESULTS: Vendor-neutral sequences were implemented across all four systems, and the code for pulse sequences and reconstruction is freely available. For participants, there was no difference in the mean T1 and T2 relaxation times between the prototype and commercial systems. In the phantom, there were no significant differences between the prototype and commercial systems for T1 and T2 measurements using the abbreviated protocol. CONCLUSION: Quantitative T1 and T2 measurements at 0.55T in phantom and healthy participants are not statistically different across the prototype and commercial systems.

A Computation-guided Design of Highly Defined and Dense Bimetallic Active Sites on a Two-dimensional Conductive Metal-organic Framework for Efficient H2O2 Electrosynthesis.

Electrochemical synthesis of hydrogen peroxide (H2O2) via the two-electron oxygen reduction reaction (2e--ORR) provides an alternative method to the energy-intensive anthraquinone method. Metal macrocycles with precise coordination are widely used for 2e--ORR electrocatalysis, but they have to be commonly loaded on conductive substrates, thus exposing a large number of 2e--ORR-inactive sites that result in poor H2O2 production rate and efficiency. Herein, guided by first-principle predictions, a substrate-free and two-dimensional conductive metal-organic framework (Ni-TCPP(Co)), composed of Co-N4 sites in porphine(Co) centers and Ni2O8 nodes, is designed as a multi-site catalyst for H2O2 electrosynthesis. The approperiate distance between the CoN4 and Ni2O8 sites in Ni-TCPP(Co) weakens the electron transfer between them, thus ensuring their inherent activities and creating high-density active sites. Meanwhile, the intrinsic electronic conductivity and porosity of Ni-TCPP(Co) further facilitate rapid reaction kinetics. Therefore, outstanding 2e--ORR electrocatalytic performance has been achieved in both alkaline and neutral electrolytes (>90%/85% H2O2 selectivity within 0-0.8 V vs. RHE and >18.2/18.0 mol g-1 h-1 H2O2 yield under alkaline/neutral conditions), with confirmed feasibility for water purification and disinfection applications. This strategy thus provides a new avenue for designing catalysts with precise coordination and high-density active sites, promoting high-efficiency electrosynthesis of H2O2 and beyond.

Detection of residual pluripotent stem cells in cell therapy products utilizing droplet digital PCR: an international multisite evaluation study.

The presence of residual undifferentiated pluripotent stem cells (PSCs) in PSC-derived cell therapy products (CTPs) is a major safety issue for their clinical application, due to the potential risk of PSC-derived tumor formation. An international multidisciplinary multisite study to evaluate a droplet digital PCR (ddPCR) approach to detect residual undifferentiated PSCs in PSC-derived CTPs was conducted as part of the Health and Environmental Sciences Institute Cell Therapy-TRAcking, Circulation & Safety Technical Committee. To evaluate the use of ddPCR in quantifying residual iPSCs in a cell sample, different quantities of induced pluripotent stem cells (iPSCs) were spiked into a background of iPSC-derived cardiomyocytes (CMs) to mimic different concentrations of residual iPSCs. A one step reverse transcription ddPCR (RT-ddPCR) was performed to measure mRNA levels of several iPSC-specific markers and to evaluate the assay performance (precision, sensitivity, and specificity) between and within laboratories. The RT-ddPCR assay variability was initially assessed by measuring the same RNA samples across all participating facilities. Subsequently, each facility independently conducted the entire process, incorporating the spiking step, to discern the parameters influencing potential variability. Our results show that a RT-ddPCR assay targeting ESRG, LINC00678, and LIN28A genes offers a highly sensitive and robust detection of impurities of iPSC-derived CMs and that the main contribution to variability between laboratories is the iPSC-spiking procedure, and not the RT-ddPCR. The RT-ddPCR assay would be generally applicable for tumorigenicity evaluation of PSC-derived CTPs with appropriate marker genes suitable for each CTP.

Factors associated with nursing students' mental health-related stigma: A multisite cross-sectional study.

BACKGROUND: Mental health-related stigma remains a complex and pervasive issue globally. It not only inhibits individuals from seeking help but also influences the quality of healthcare they receive. Despite extensive research on mental health-related stigma, there is still limited understanding of factors influencing mental health-related stigma among nursing students. OBJECTIVES: This study aimed to assess the level of mental health-related stigma among Chinese nursing students and investigate possible associated factors. METHODS: Data were collected from the 2023 Psychology and Behavior Investigation of Chinese Residents (PBICR) survey. A total of 967 nursing students were included in the study. Multivariate stepwise linear regression analysis was conducted to examine the influencing factors of mental health stigma. RESULTS: The mean mental health-related stigma score among nursing students was 15.31 ± 5.23 (range = 0-27). Perceived stress (ß = 0.14, P = 0.001), self-efficacy (ß = 0.22, P < 0.001), academic stage (ß = 0.17, P < 0.001), depression (ß = 0.15, P < 0.001), and adverse life events (ß = 0.06, P = 0.044) were significantly associated with mental health-related stigma among nursing students (R2 = 0.147, adjusted R2 = 0.143, F = 33.214, P < 0.001). CONCLUSIONS: Nursing students in China exhibit a moderate level of mental health-related stigma, suggesting room for improvement. Perceived stress, self-efficacy, academic stage, depression, and adverse life events emerged as significant influencing factors for mental health-related stigma. These findings provide valuable insights for developing interventions to reduce mental health-related stigma among nursing students, ultimately enhancing their well-being and preparing them for becoming competent healthcare professionals in the future.

Multi-site EEG studies in early infancy: Methods to enhance data quality.

Brain differences linked to autism spectrum disorder (ASD) can manifest before observable symptoms. Studying these early neural precursors in larger and more diverse cohorts is crucial for advancing our understanding of developmental pathways and potentially facilitating earlier identification. EEG is an ideal tool for investigating early neural differences in ASD, given its scalability and high tolerability in infant populations. In this context, we integrated EEG into an existing multi-site MRI study of infants with a higher familial likelihood of developing ASD. This paper describes the comprehensive protocol established to collect longitudinal, high-density EEG data from infants across five sites as part of the Infant Brain Imaging Study (IBIS) Network and reports interim feasibility and data quality results. We evaluated feasibility by measuring the percentage of infants from whom we successfully collected each EEG paradigm. The quality of task-free data was assessed based on the duration of EEG recordings remaining after artifact removal. Preliminary analyses revealed low data loss, with average in-session loss rates at 4.16 % and quality control loss rates at 11.66 %. Overall, the task-free data retention rate, accounting for both in-session issues and quality control, was 84.16 %, with high consistency across sites. The insights gained from this preliminary analysis highlight key sources of data attrition and provide practical considerations to guide similar research endeavors.

Multi-site enhancement of osteogenesis: peptide-functionalized GelMA hydrogels with three-dimensional cultures of human dental pulp stem cells.

Human dental pulp stem cells (hDPSCs) have demonstrated greater proliferation and osteogenic differentiation potential in certain studies compared to other types of mesenchymal stem cells, making them a promising option for treating craniomaxillofacial bone defects. However, due to low extracting concentration and long amplifying cycles, their access is limited and utilization rates are low. To solve these issues, the principle of bone-forming peptide-1 (BFP1) in situ chemotaxis was utilized for the osteogenic differentiation of hDPSCs to achieve simultaneous and synergistic osteogenesis at multiple sites. BFP1-functionalized gelatin methacryloyl hydrogel provided a 3D culture microenvironment for stem cells. The experimental results showed that the 3D composite hydrogel scaffold constructed in this study increased the cell spread area by four times compared with the conventional GelMA scaffold. Furthermore, the problems of high stem cell dosage and low rate of utilization were alleviated by orchestrating the programmed proliferation and osteogenic differentiation of hDPSCs. In vivo, high-quality repair of critical bone defects was achieved using hDPSCs extracted from a single tooth, and multiple 'bone island'-like structures were successfully observed that rapidly induced robust bone regeneration. In conclusion, this study suggests that this kind of convenient, low-cost, island-like osteogenesis strategy involving a low dose of hDPSCs has great potential for repairing craniomaxillofacial critical-sized bone defects.

Uncovering the hidden effects of repetitive subconcussive head impact exposure: A mega-analytic approach characterizing seasonal brain microstructural changes in contact and collision sports athletes.

Repetitive subconcussive head impacts (RSHI) are believed to induce sub-clinical brain injuries, potentially resulting in cumulative, long-term brain alterations. This study explores patterns of longitudinal brain white matter changes across sports with RSHI-exposure. A systematic literature search identified 22 datasets with longitudinal diffusion magnetic resonance imaging data. Four datasets were centrally pooled to perform uniform quality control and data preprocessing. A total of 131 non-concussed active athletes (American football, rugby, ice hockey; mean age: 20.06 ± 2.06 years) with baseline and post-season data were included. Nonparametric permutation inference (one-sample t tests, one-sided) was applied to analyze the difference maps of multiple diffusion parameters. The analyses revealed widespread lateralized patterns of sports-season-related increases and decreases in mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) across spatially distinct white matter regions. Increases were shown across one MD-cluster (3195 voxels; mean change: 2.34%), one AD-cluster (5740 voxels; mean change: 1.75%), and three RD-clusters (817 total voxels; mean change: 3.11 to 4.70%). Decreases were shown across two MD-clusters (1637 total voxels; mean change: -1.43 to -1.48%), two RD-clusters (1240 total voxels; mean change: -1.92 to -1.93%), and one AD-cluster (724 voxels; mean change: -1.28%). The resulting pattern implies the presence of strain-induced injuries in central and brainstem regions, with comparatively milder physical exercise-induced effects across frontal and superior regions of the left hemisphere, which need further investigation. This article highlights key considerations that need to be addressed in future work to enhance our understanding of the nature of observed white matter changes, improve the comparability of findings across studies, and promote data pooling initiatives to allow more detailed investigations (e.g., exploring sex- and sport-specific effects).

Multi-site and long-term estimation of phosphorus dynamics for paddy surface water in China based on new MLEpaddy-P.

Paddy surface water serves as the primary source of artificial drainage and rainfall runoff leading to phosphorus (P) loss from paddy fields. The quantification of P dynamics in paddy surface water on a large scale is challenging due to the spatiotemporal heterogeneity of influencing factors and the limitations of field measurements. Based on 1226 data sets from 33 field sites covering the three main rice-growing regions of China (the Southeast Coast, the Yangtze River Basin, and the Northeast Plain), we analyzed the spatiotemporal characteristics of P attenuation in paddy surface water and its influencing factors. A new multi-site and long-term phosphorus estimation model for paddy (MLEpaddy-P) was proposed to evaluate the total phosphorus (TP) dynamics at national scale by improving the initial concentration (C0) and attenuation coefficient (k) of the first-order kinetic model (Ct=C0∙e-k(t-1)). Our study showed that: (1) Fertilizer amounts, soil organic matter content, soil Olsen-P content, soil pH, and soil total phosphorus are the primary factors affecting the variation of C0 and k; (2) Yangtze River Basin possessed the highest C0 (6.87 ± 12.97 mg/L) and high k ≤ 7 (0.262 in 1-7 days after fertilization), followed by Southeast Coast (4.15 ± 5.33 mg/L; 0.263) and Northeast Plain (1.33 ± 1.50 mg/L; 0.239), respectively; (3) MLEpaddy-P performed well in daily TP dynamics estimation at national scale with R2 of 0.74-0.85; (4) Middle and lower reaches of the Yangtze River Basin were the critical regions with high TP concentration due to high fertilizer amount and soil Olsen-P content. The new universal model realizes the multi-site and long-term estimation of P dynamics while greatly saving multi-site monitoring costs. This study provides a basis for early warning and targeted control of P loss from paddies.

Multisite Musculoskeletal Pain Is Associated with Long-Term Declined Physical Quality of Life and Knee-Related Quality of Life in Older Adults with or at Risk of Knee Osteoarthritis.

Background and Objectives: This study aimed to examine the longitudinal impact of multisite musculoskeletal pain on physical and mental health-related quality of life among individuals with or at risk of knee osteoarthritis. Materials and Methods: This study is a prospective longitudinal design over 8 years of follow-up. Data from 4796 participants aged between 45 and 79 years were acquired from the Osteoarthritis Initiative. Based on self-reported physician-diagnosed osteoarthritis and grade ≥2 in either knee using Kellgren and Lawrence grade at baseline, individuals at risk were classified as those who did not have knee osteoarthritis at baseline but could develop osteoarthritis throughout the study. Physical and mental components of health-related quality were assessed over an 8-year follow-up period using both knee injury and osteoarthritis outcome scores and the 12-item Short-Form Health Survey. Multisite pain was examined using a self-reported questionnaire for 20 sites. Two separate generalized estimating equations modeled with a linear regression analysis were utilized. Results: The results showed that participants with one painful site (Beta [B] = -0.92, p = 0.01), two painful sites (B = -1.94, p < 0.001), and multisite pain (≥3 painful sites) (B = -4.68, p < 0.001) were significantly associated with declined physical health-related quality of life over time when compared to those with no painful site at baseline after adjustments for covariates. However, there was no significant association with declined mental health-related quality of life over time. Conclusions: This study revealed that baseline multisite musculoskeletal pain was linked to declining physical and knee injury and osteoarthritis outcome score quality of life among individuals with or at risk of knee osteoarthritis. Moreover, having baseline multisite pain and two painful sites were associated with a decline in physical and knee injury and osteoarthritis outcome score quality of life, while mental health-related quality of life did not show a significant association with multisite pain. Therefore, it is imperative for primary healthcare settings to prioritize the assessment of multisite musculoskeletal pain and develop interventions aimed at preserving and enhancing physical health-related quality of life in people with or at risk of osteoarthritis.

Multisite studies for optimization of a highly efficient culture assay used for in vitro detection of residual undifferentiated human pluripotent stem cells intermingled in cell therapy products.

Introduction: MEASURE2 (Multisite Evaluation Study on Analytical Methods for Non-clinical Safety Assessment of HUman-derived REgenerative Medical Products 2) is a Japanese experimental public-private partnership initiative that aims to standardize testing methods for tumorigenicity evaluation of human pluripotent stem cell (hPSC)-derived cell therapy products (CTPs). MEASURE2 organized multisite studies to optimize the methodology of the highly efficient culture (HEC) assay, a sensitive culture-based in vitro assay for detecting residual undifferentiated hPSCs in CTPs. Methods: In these multisite studies, 1) the efficiency of colony formation by human induced pluripotent stem cells (hiPSCs) under two different culture conditions and 2) the sorting efficiency of microbeads conjugated to various anti-hPSC markers during hiPSC enrichment were evaluated using samples in which hiPSCs were spiked into hiPSC-derived mesenchymal stem cells. Results: The efficiency of colony formation was significantly higher under culture conditions with the combination of Chroman 1, Emricasan, Polyamines, and Trans-ISRIB (CEPT) than with Y-27632, which is widely used for the survival of hPSCs. Between-laboratory variance was also smaller under the condition with CEPT than with Y-27632. The sorting efficiency of microbeads conjugated with the anti-Tra-1-60 antibody was sufficiently higher (>80%) than those of the other various microbeads investigated. Conclusions: Results of these multisite studies are expected to contribute to improvements in the sensitivity and robustness of the HEC assay, as well as to the future standardization of the tumorigenicity risk assessment of hPSC-derived CTPs.

Exploring the bidirectional causal associations between pain and circulating inflammatory proteins: A Mendelian randomization study.

Multisite chronic pain (MCP) and site-specific chronic pain (SSCP) may be influenced by circulating inflammatory proteins, but the causal relationship remains unknown. To overcome this limitation, two-sample bidirectional Mendelian randomization (MR) analysis was used to analyse data for 91 circulating inflammatory proteins, MCP and SSCP encompassing headache, back pain, shoulder pain, hip pain, knee pain, stomach abdominal pain and facial pain. The primary MR method used was inverse variance weighting, sensitivity analyses included weighted median, MR pleiotropy residual sum and outlier and the Egger intercept method. Heterogeneity was also detected using Cochrane's Q test and leave-one-out analyses. Finally, a causal relationship between 29 circulating inflammatory proteins and chronic pain was identified. Among these proteins, 14 exhibited a protective effect, including MCP (T-cell surface glycoprotein cluster of differentiation 5), headache (4E-binding protein 1 [4EBP1], cluster of differentiation 40, cluster of differentiation 6 and C-X-C motif chemokine [CXCL] 11), back pain (leukaemia inhibitory factor), shoulder pain (fibroblast growth factor [FGF]-5 and interleukin [IL]-18R1), stomach abdominal pain (tumour necrosis factor [TNF]-α), hip pain (CXCL1, IL-20 and signalling lymphocytic activation molecule 1) and knee pain (IL-7 and TNF-ß). Additionally, 15 proteins were identified as risk factors for MCP and SSCP: MCP (colony-stimulating factor 1, human glial cell line-derived neurotrophic factor and IL-17C), headache (fms-related tyrosine kinase 3 ligand, IL-20 receptor subunit α [IL-20RA], neurotrophin-3 and tumour necrosis factor receptor superfamily member 9), facial pain (CXCL1), back pain (TNF), shoulder pain (IL-17C and matrix metalloproteinase-10), stomach abdominal pain (IL-20RA), hip pain (C-C motif chemokine 11/eotaxin-1 and tumour necrosis factor ligand superfamily member 12) and knee pain (4EBP1). Importantly, in the opposite direction, MCP and SSCP did not exhibit a significant causal impact on circulating inflammatory proteins. Our study identified potential causal influences of various circulating inflammatory proteins on MCP and SSCP and provided promising treatments for the clinical management of MCP and SSCP.

Combined quantitative amyloid-ß PET and structural MRI features improve Alzheimer's Disease classification in random forest model - A multicenter study.

RATIONALE AND OBJECTIVES: Prior to clinical presentations of Alzheimer's Disease (AD), neuropathological changes, such as amyloid-ß and brain atrophy, have accumulated at the earlier stages of the disease. The combination of such biomarkers assessed by multiple modalities commonly improves the likelihood of AD etiology. We aimed to explore the discriminative ability of Aß PET features and whether combining Aß PET and structural MRI features can improve the classification performance of the machine learning model in older healthy control (OHC) and mild cognitive impairment (MCI) from AD. MATERIAL AND METHODS: We collected 94 AD patients, 82 MCI patients, and 85 OHC from three different cohorts. 17 global/regional Aß features in Centiloid, 122 regional volume, and 68 regional cortical thickness were extracted as imaging features. Single or combined modality features were used to train the random forest model on the testing set. The top 10 features were sorted based on the Gini index in each binary classification. RESULTS: The results showed that AUC scores were 0.81/0.86 and 0.69/0.68 using sMRI/Aß PET features on the testing set in differentiating OHC and MCI from AD. The performance was improved while combining two-modality features with an AUC of 0.89 and an AUC of 0.71 in two classifications. Compared to sMRI features, particular Aß PET features contributed more to differentiating AD from others. CONCLUSION: Our study demonstrated the discriminative ability of Aß PET features in differentiating AD from OHC and MCI. A combination of Aß PET and structural MRI features can improve the RF model performance.

Dual-Intermetallic Heterostructure on Hierarchical Nanoporous Metal for Highly Efficient Alkaline Hydrogen Electrocatalysis.

Constructing well-defined active multisites is an effective strategy to break linear scaling relationships to develop high-efficiency catalysts toward multiple-intermediate reactions. Here, dual-intermetallic heterostructure composed of tungsten-bridged Co3W and WNi4 intermetallic compounds seamlessly integrated on hierarchical nanoporous nickel skeleton is reported as a high-performance nonprecious electrocatalyst for alkaline hydrogen evolution and oxidation reactions. By virtue of interfacial tungsten atoms configuring contiguous multisites with proper adsorptions of hydrogen and hydroxyl intermediates to accelerate water dissociation/combination and column-nanostructured nickel skeleton facilitating electron and ion/molecule transportations, nanoporous nickel-supported Co3W-WNi4 heterostructure exhibits exceptional hydrogen electrocatalysis in alkaline media, with outstanding durability and impressive catalytic activities for hydrogen oxidation reaction (geometric exchange current density of ≈6.62 mA cm-2) and hydrogen evolution reaction (current density of ≈1.45 A cm-2 at overpotential of 200 mV). Such atom-ordered intermetallic heterostructure alternative to platinum group metals shows genuine potential for hydrogen production and utilization in hydroxide-exchange-membrane water electrolyzers and fuel cells.

A simple Cox approach to estimating risk ratios without sharing individual-level data in multi-site studies.

Epidemiologic studies frequently use risk ratios to quantify associations between exposures and binary outcomes. When the data are physically stored at multiple data partners, it can be challenging to perform individual-level analysis if data cannot be pooled centrally due to privacy constraints. Existing methods either require multiple file transfers between each data partner and an analysis center (e.g., distributed regression) or only provide approximate estimation of the risk ratio (e.g., meta-analysis). Here we develop a practical method that requires a single transfer of eight summary-level quantities from each data partner. Our approach leverages an existing risk-set method and software originally developed for Cox regression. Sharing only summary-level information, the proposed method provides risk ratio estimates and confidence intervals identical to those that would be provided - if individual-level data were pooled - by the modified Poisson regression. We justify the method theoretically, confirm its performance using simulated data, and implement it in a distributed analysis of COVID-19 data from the U.S. Food and Drug Administration's Sentinel System.

A Novel Ultrasound-Guided Bilateral Vagal Nerve Hydrodissection With 5% Dextrose Without Local Anesthetic for Recalcitrant Chronic Multisite Pain and Autonomic Dysfunction.

Chronic pain is a complex condition that often poses diagnostic and management challenges due to its multifactorial etiology. This case report describes a 49-year-old pastor who presented with a three-year history of chronic pain affecting multiple sites, including the neck, bilateral shoulders, thoracic region, lower back, and bilateral knees. Additionally, he experienced shortness of breath on mild exertion, which adversely affected his ability to converse and speak publicly. The patient had a rapid resting heart rate of 100-120 beats per minute, occasional palpitations, and a 24-hour electrocardiogram that confirmed 15% premature ventricular complexes with bigeminy and trigeminy. He complained of limited appetite with early satiety, intermittent nausea, and regurgitation. Despite consultations with multiple specialists, no underlying causes were identified in the cardiac, respiratory, gastrointestinal, or psychological domains. Ultrasound-guided bilateral vagus nerve hydrodissection using 5% dextrose without local anesthetics was administered three times at monthly intervals, resulting in remarkable pain relief within three months and the effects persisted at the nine-month follow-up. Tachycardia was no longer perceived, resting heart rate slowed to 70-80 beats per minute, shortness of breath improved, and public speaking ability was restored. The patient's early satiety, nausea, and reflux complaints were resolved. This case report highlights the potential effectiveness of this novel intervention for chronic pain. Further research is warranted to validate these findings and explore the mechanism of action.

Connectome predictive modeling of trait mindfulness.

Introduction: Trait mindfulness refers to one's disposition or tendency to pay attention to their experiences in the present moment, in a non-judgmental and accepting way. Trait mindfulness has been robustly associated with positive mental health outcomes, but its neural underpinnings are poorly understood. Prior resting-state fMRI studies have associated trait mindfulness with within- and between-network connectivity of the default-mode (DMN), fronto-parietal (FPN), and salience networks. However, it is unclear how generalizable the findings are, how they relate to different components of trait mindfulness, and how other networks and brain areas may be involved. Methods: To address these gaps, we conducted the largest resting-state fMRI study of trait mindfulness to-date, consisting of a pre-registered connectome predictive modeling analysis in 367 adults across three samples collected at different sites. Results: In the model-training dataset, we did not find connections that predicted overall trait mindfulness, but we identified neural models of two mindfulness subscales, Acting with Awareness and Non-judging. Models included both positive networks (sets of pairwise connections that positively predicted mindfulness with increasing connectivity) and negative networks, which showed the inverse relationship. The Acting with Awareness and Non-judging positive network models showed distinct network representations involving FPN and DMN, respectively. The negative network models, which overlapped significantly across subscales, involved connections across the whole brain with prominent involvement of somatomotor, visual and DMN networks. Only the negative networks generalized to predict subscale scores out-of-sample, and not across both test datasets. Predictions from both models were also negatively correlated with predictions from a well-established mind-wandering connectome model. Conclusions: We present preliminary neural evidence for a generalizable connectivity models of trait mindfulness based on specific affective and cognitive facets. However, the incomplete generalization of the models across all sites and scanners, limited stability of the models, as well as the substantial overlap between the models, underscores the difficulty of finding robust brain markers of mindfulness facets.

Structure-function coupling reveals the brain hierarchical structure dysfunction in Alzheimer's disease: A multicenter study.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition characterized by cognitive decline. To date, the specific dysfunction in the brain's hierarchical structure in AD remains unclear. METHODS: We introduced the structural decoupling index (SDI), based on a multi-site data set comprising functional and diffusion-weighted magnetic resonance imaging data from 793 subjects, to assess their brain hierarchy. RESULTS: Compared to normal controls (NCs), individuals with AD exhibited increased SDI within the posterior superior temporal sulcus, insular gyrus, precuneus, hippocampus, amygdala, postcentral gyrus, and cingulate gyrus; meanwhile, the patients with AD demonstrated decreased SDI in the frontal lobe. The SDI in those regions also showed a significant correlation with cognitive ability. Moreover, the SDI was a robust AD neuroimaging biomarker capable of accurately distinguishing diagnostic status (area under the curve [AUC] = 0.86). DISCUSSION: Our findings revealed the dysfunction of the brain's hierarchical structure in AD. Furthermore, the SDI could serve as a promising neuroimaging biomarker for AD. HIGHLIGHTS: This study utilized multi-center, multi-modal data from East Asian populations. We found an increased spatial gradient of the structure decoupling index (SDI) from sensory-motor to higher-order cognitive regions. Changes in SDI are associated with energy metabolism and mitochondria. SDI can identify Alzheimer's disease (AD) and further uncover the disease mechanisms of AD.

[Transport Characteristics and Potential Source Areas of PM2.5 in Yangquan City Under Different Pollution Levels].

Based on the PM2.5 monitoring data, NCEP data, and the meteorological data of the weather situation analysis at the corresponding time in Yangquan City from 2020 to 2022, using the HYSPLIT4 backward trajectory model, multi-station potential source contribution factor analysis （MS-PSCF） and trajectory density analysis （TDA） were introduced to study the differentiation and classification of PM2.5 transport channels and potential sources in Yangquan City. The results showed that： ① The PM2.5 pollution in Yangquan was mainly concentrated in Yangquan and Pingding, whereas the pollution in Yuxian was relatively light. The proportion of days with different pollution levels and the average and maximum values of PM2.5 concentration in Yangquan and Pingding were significantly higher than those in Yuxian, and the distribution characteristics of PM2.5 were closely related to the local special terrain. ② The amount of PM2.5 pollution and the concentration of PM2.5 in different pollution levels were the highest in light wind weather. The influence of east-west regional transport on PM2.5 pollution times and PM2.5 concentration of Yangquan and Pingding was obvious, and the contribution of east wind was significant. The influence of local pollution sources was the main factor in the moderate pollution weather in Yuxian County. ③ There were four main ground conditions for the generation and maintenance of moderate or above pollution weather： warm low pressure type （22%）, high pressure front （bottom） type （54%）, high pressure back type （14%）, and pressure equalization field （10%）. High pressure front （bottom） type was the main ground situation causing the increase in PM2.5 concentration. There were two types of upper air conditions, namely, flat westerly flow type （78%） and northwest flow type （22%）. The upper westerly flow type was the main upper air condition that caused the increase in PM2.5 concentration. ④ The results of transport channels and potential source areas of PM2.5 with different pollution levels obtained by MS-PSCF and TDA were consistent. The main transport channels of PM2.5 were the northeast, southeast, and northwest channels, whereas the northeast and southeast channels were short-distance transport routes, which were the main routes causing the increase in PM2.5 concentration. The northwest channel was consistent with the northwest dust transport channel, belonging to long-distance transmission. The main potential source areas of PM2.5 pollution were located in the central and western parts of Hebei and the southeast part of Hebei, the northeast part of Henan and its junction with the southwest part of Shandong, and the southeast part of Shanxi.

Single IRB Review and Local Context Considerations: A Scoping Review.

A leading concern about single IRB (sIRB) review for multisite studies, as is now required by federal policies, is whether and how sIRBs consider local context in their review. While several types of local context considerations have been proposed, there is no shared agreement among those charged with the ethics oversight of human subjects research as to the goals and content of local context review, nor the types of research studies for which sIRB review might be inappropriate. Through a scoping review of published scholarship, public comments, and federal guidance documents, we identified five assumed goals for local context review: protecting the rights and welfare of local participants; ensuring compliance with applicable laws and policies; assessing feasibility; promoting the quality of research; and promoting procedural justice. While a variety of content was proposed to be relevant, it was largely grouped into four domains: population/participant-level characteristics; investigator and research team characteristics; institution-level characteristics; and state and local laws. Proposed characteristics for exclusion from sIRB requirements reflected both protection- and efficiency-based concerns. These findings can inform ongoing efforts to assess the implications of policies mandating sIRB review, and when exceptions to those policies might be appropriate.