Eye-brain connections revealed by multimodal retinal and brain imaging genetics.

The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

Multi-organ imaging-derived polygenic indexes for brain and body health.

The UK Biobank (UKB) imaging project is a crucial resource for biomedical research, but is limited to 100,000 participants due to cost and accessibility barriers. Here we used genetic data to predict heritable imaging-derived phenotypes (IDPs) for a larger cohort. We developed and evaluated 4,375 IDP genetic scores (IGS) derived from UKB brain and body images. When applied to UKB participants who were not imaged, IGS revealed links to numerous phenotypes and stratified participants at increased risk for both brain and somatic diseases. For example, IGS identified individuals at higher risk for Alzheimer's disease and multiple sclerosis, offering additional insights beyond traditional polygenic risk scores of these diseases. When applied to independent external cohorts, IGS also stratified those at high disease risk in the All of Us Research Program and the Alzheimer's Disease Neuroimaging Initiative study. Our results demonstrate that, while the UKB imaging cohort is largely healthy and may not be the most enriched for disease risk management, it holds immense potential for stratifying the risk of various brain and body diseases in broader external genetic cohorts.

Analyzing bivariate cross-trait genetic architecture in GWAS summary statistics with the BIGA cloud computing platform.

As large-scale biobanks provide increasing access to deep phenotyping and genomic data, genome-wide association studies (GWAS) are rapidly uncovering the genetic architecture behind various complex traits and diseases. GWAS publications typically make their summary-level data (GWAS summary statistics) publicly available, enabling further exploration of genetic overlaps between phenotypes gathered from different studies and cohorts. However, systematically analyzing high-dimensional GWAS summary statistics for thousands of phenotypes can be both logistically challenging and computationally demanding. In this paper, we introduce BIGA (https://bigagwas.org/), a website that aims to offer unified data analysis pipelines and processed data resources for cross-trait genetic architecture analyses using GWAS summary statistics. We have developed a framework to implement statistical genetics tools on a cloud computing platform, combined with extensive curated GWAS data resources. Through BIGA, users can upload data, submit jobs, and share results, providing the research community with a convenient tool for consolidating GWAS data and generating new insights.

Combatting ageing in dermal papilla cells and promoting hair follicle regeneration using exosomes from human hair follicle dermal sheath cup cells.

Dermal papilla cells (DPCs) undergo premature ageing in androgenetic alopecia and senescent alopecia. As critical components of hair follicle reconstruction, DPCs are also prone to senescence in vitro, resulting in a diminished hair follicle inductivity capacity. Dermal sheath cup cells (DSCCs), a specific subset of hair follicle mesenchymal stem cells, intimately linked to the function of DPCs. The primary objective of this research is to investigate the anti-ageing effect of exosomes derived from DSCCs (ExoDSCCs ) on DPCs. Exosomes were utilized to treat H2 O2 -induced DPCs or long-generation DPCs(P10). Our findings demonstrate that ExoDSCCs(P3) promote the proliferation, viability and migration of senescent DPCs while inhibiting cell apoptosis. The expression of senescence marker SA-ß-Gal were significantly downregulated in senescent DPCs. When treated with ExoDSCCs(P3) , expression of inducibility related markers alkaline phosphatase and Versican were significantly upregulated. Additionally, ExoDSCCs(P3) activated the Wnt/ß-catenin signalling in vitro. In patch assay, ExoDSCCs(P3) significantly promoted hair follicle reconstruction in senescent DPCs. In summary, our work highlights that ExoDSCCs(P3) may restore the biological functions and improve the hair follicle induction ability of senescent DPCs. Therefore, ExoDSCCs(P3) may represent a new strategy for intervening in the ageing process of DPCs, contributing to the prevention of senile alopecia.

Heart-brain connections: Phenotypic and genetic insights from magnetic resonance images.

Cardiovascular health interacts with cognitive and mental health in complex ways, yet little is known about the phenotypic and genetic links of heart-brain systems. We quantified heart-brain connections using multiorgan magnetic resonance imaging (MRI) data from more than 40,000 subjects. Heart MRI traits displayed numerous association patterns with brain gray matter morphometry, white matter microstructure, and functional networks. We identified 80 associated genomic loci (P < 6.09 × 10-10) for heart MRI traits, which shared genetic influences with cardiovascular and brain diseases. Genetic correlations were observed between heart MRI traits and brain-related traits and disorders. Mendelian randomization suggests that heart conditions may causally contribute to brain disorders. Our results advance a multiorgan perspective on human health by revealing heart-brain connections and shared genetic influences.

Eye-brain connections revealed by multimodal retinal and brain imaging genetics in the UK Biobank.

As an anatomical extension of the brain, the retina of the eye is synaptically connected to the visual cortex, establishing physiological connections between the eye and the brain. Despite the unique opportunity retinal structures offer for assessing brain disorders, less is known about their relationship to brain structure and function. Here we present a systematic cross-organ genetic architecture analysis of eye-brain connections using retina and brain imaging endophenotypes. Novel phenotypic and genetic links were identified between retinal imaging biomarkers and brain structure and function measures derived from multimodal magnetic resonance imaging (MRI), many of which were involved in the visual pathways, including the primary visual cortex. In 65 genomic regions, retinal imaging biomarkers shared genetic influences with brain diseases and complex traits, 18 showing more genetic overlaps with brain MRI traits. Mendelian randomization suggests that retinal structures have bidirectional genetic causal links with neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, cross-organ imaging genetics reveals a genetic basis for eye-brain connections, suggesting that the retinal images can elucidate genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

The development of multifunctional sulfated polyguluronic acid-based polymeric micelles for anticancer drug delivery.

Numerous disseminated tumor cells specifically overexpress P-selectin. Therefore, it was thought to be a potential target for tumor therapy. Herein, we described a novel P-selectin-targeted glycosyl ligand-sulfated polyguluronic acid (PGS), as an oriented carrier of P-selectin-targeted drug delivery system. Specifically, the PGS-SS-DOX polymeric micelles were constructed to confirm the practicability of the PGS carrier as a new P-selectin-targeted ligand. PGS-SS-DOX micelles comprised P-selectin-targeted PGS, doxorubicin (DOX) as an anticarcinogen, and pH/redox dual-sensitive bio-linker facilitating drug release in tumor tissues. In vitro and in vivo data showed that PGS-SS-DOX micelles significantly increased tumor cell killing capacity and exhibited a favorable biocompatibility comparison with Free-DOX. This work proved that PGS was an ideal low immunogenic, biodegradable drug carrier for the delivery of anti-cancer drugs. The facile PGS-SS-drug micelle system provided enormous opportunities for treating disseminated tumors utilizing many irreplaceable anticarcinogens.

An atlas of trait associations with resting-state and task-evoked human brain functional organizations in the UK Biobank.

Functional magnetic resonance imaging (fMRI) has been widely used to identify brain regions linked to critical functions, such as language and vision, and to detect tumors, strokes, brain injuries, and diseases. It is now known that large sample sizes are necessary for fMRI studies to detect small effect sizes and produce reproducible results. Here we report a systematic association analysis of 647 traits with imaging features extracted from resting-state and task-evoked fMRI data of more than 40,000 UK Biobank participants. We used a parcellation-based approach to generate 64,620 functional connectivity measures to reveal fine-grained details about cerebral cortex functional organizations. The difference between functional organizations at rest and during task was examined, and we have prioritized important brain regions and networks associated with a variety of human traits and clinical outcomes. For example, depression was most strongly associated with decreased connectivity in the somatomotor network. We have made our results publicly available and developed a browser framework to facilitate the exploration of brain function-trait association results (http://fmriatlas.org/).

Characterization and Comparison of Corrosion Layer Microstructure between Cement Mortar and Alkali-Activated Fly Ash/Slag Mortar Exposed to Sulfuric Acid and Acetic Acid.

In this study, we investigated the formation and evolution of the corrosion layers in alkali-activated mortar and ordinary Portland cement mortar exposed to sulfuric acid and acetic acid environments with different pH values, and explored the differences in the deterioration mechanisms. The experimental results indicated that ordinary Portland cement (OPC) mortars experienced more severe deterioration in terms of appearance, mass loss, and strength loss as compared with alkali-activated mortars exposed to an acetic acid environment, but their neutralization depths were smaller. Alkali-activated fly ash (AAF) mortar had a the relatively intact appearance but the greatest neutralization depth, which was due to its stable three-dimensional network but highly porous structure. To sum up, alkali-activated fly ash/slag (AFS) mortar had the best resistance to acid attack. In addition, the mortars exposed to acetic acid suffered greater deterioration than those exposed to sulfuric acid with the same pH values, which was mainly due to the highly porous corrosion layer formed in acetic acid, whereas crystallization of gypsum in sulfuric acid had a pore filling effect. However, for alkali-activated slag (AAS) and OPC mortars exposed to a sulfuric acid environment, extensive gypsum resulted in the formation of micro-cracks, and the corrosion layer of OPC mortar was more prone to fall off. OPC mortar also had the greatest resistance difference values of the continuously connected micro-pores before and after acid corrosion, followed by AAS, AAF, and AFS mortars, and these values for all the specimens were smaller in sulfuric acid. Furthermore, the gaps between acetic and sulfuric acid attacks increased with increased calcium content in binders, which were 7%, 13%, 21%, and 29% for AAF, AFS, AAS, and OPC mortars, respectively. Thus, it can be inferred that an appropriate amount of gypsum existed in the corrosion layer which could act as a barrier to some extent ina sulfuric acid environment.

DBDNet for denoising in ESPI wrapped phase patterns with high density and high speckle noise.

In this paper, we propose a dilated-blocks-based deep convolution neural network, named DBDNet, for denoising in electronic speckle pattern interferometry (ESPI) wrapped phase patterns with high density and high speckle noise. In our method, the proposed dilated blocks have a specific sequence of dilation rate and a multilayer cascading fusion structure, which can better improve the effect of speckle noise reduction, especially for phase patterns with high noise and high density. Furthermore, we have built an abundant training dataset with varieties of densities and noise levels to train our network; thus, the trained model has a good generalization and can denoise ESPI wrapped phase in various circumstances. The network can get denoised results directly and does not need any pre-process or post-process. We test our method on one group of computer-simulated ESPI phase patterns and one group of experimentally obtained ESPI phase patterns. The test images have a high degree of speckle noise and different densities. We compare our method with two representative methods in the spatial domain and frequency domain, named oriented-couple partial differential equation and windowed Fourier low pass filter (LPF), and a method based on deep learning, named fast and flexible denoising convolutional neural network (FFDNet). The denoising performance is evaluated quantitatively and qualitatively. The results demonstrate that our method can reduce high speckle noise and restore the dense areas of ESPI phase patterns, and get better results than the compared methods. We also apply our method to a series of phase patterns from a dynamic measurement and get successful results.

Preparation and Evaluation of a Self-Nanoemulsifying Drug Delivery System Loaded with Heparin Phospholipid Complex.

A self-nanoemulsifying drug delivery system (SNEDDS) was developed to enhance the absorption of heparin after oral administration, in which heparin was compounded with phospholipids to achieve better fat solubility in the form of heparin-phospholipid (HEP-Pc) complex. HEP-Pc complex was prepared using the solvent evaporation method, which increased the solubility of heparin in n-octanol. The successful preparation of HEP-Pc complex was confirmed by differential scanning calorimetry (DSC), Fourier-transform infrared (FT-IR) spectroscopy, NMR, and SEM. A heparin lipid microemulsion (HEP-LM) was prepared by high-pressure homogenization and characterized. HEP-LM can enhance the absorption of heparin after oral administration, significantly prolong activated partial thromboplastin time (APTT) and thrombin time (TT) in mice, and reduce fibrinogen (FIB) content. All these outcomes indicate that HEP-LM has great potential as an oral heparin formulation.

Microbiome and Blood Analyte Differences Point to Community and Metabolic Signatures in Lean and Obese Horses.

Due to modern management practices and the availability of energy dense feeds, obesity is a serious and increasingly common health problem for horses. Equine obesity is linked to insulin resistance and exacerbation of inflammatory issues such as osteoarthritis and laminitis. While the gut microbiome is thought to play a part in metabolic status in horses, bacterial communities associated with obesity have yet to be described. Here we report differences in metabolic factors in the blood of obese, normal and lean horses correlated with differences in gut microbiome composition. We report that obese horses had higher levels of leptin, triglycerides, glucose, and cortisol in their blood, and more diverse gut microbiome communities with higher relative abundance of Firmicutes, and lower numbers of Bacteroidetes and Actinobacteria. Network analyses of correlations between body condition, blood analytes, and microbial composition at the genus level revealed a more nuanced picture of microbe-host interactions, pointing to specific bacterial species and assemblages that may be signatures of obesity and leanness in the horse gut. In particular, bacteria groups positively associated with two blood analytes and obesity included Butyrivibrio spp., Prevotellaceae, Blautia spp., two members of Erysipelotrichaceae, and a Lachnospiraceae taxa. These results are an important first step in unraveling the metabolic differences between obese and lean horse gut communities, and designing targeted strategies for microbial intervention.