Aortic Stiffness, White Matter Integrity and Depressive Symptoms among Older Adults

Background: Aortic stiffness is a hallmark of aging and is associated with neurocognitive outcomes among older adults. Late-life depression, often associated with structural damage in cerebral white matter integrity, is an important public health burden. This doctoral research examined the associations of aortic stiffness with white matter microstructural integrity and depressive symptoms among older adults. Methods: Data from the 5th and 6th examinations of the Atherosclerosis Risk in Communities cohort (2011-2013, 2016-2018) were analyzed. A total of 1,484 participants (aged 67 to 90 years) were included in the analysis of aortic stiffness and white matter microstructural integrity, and 4,511 participants (aged 66 to 90 years) were included in the analysis on aortic stiffness and depressive symptoms. Aortic stiffness was measured as carotid-femoral pulse wave velocity (cfPWV). Cerebral white matter microstructural integrity was measured as fractional anisotropy (FA) and mean diffusivity (MD) using diffusion tensor imaging. Depressive symptoms were assessed using the 11-item Centers for Epidemiologic Studies-Depression (CES-D) Scale. A CES-D score ≥9 was considered indicative of clinically significant depressive symptoms (CSDS). Results: Relating aortic stiffness and white matter microstructural integrity, each 1 m/s increment in cfPWV was associated with lower overall FA (β=-0.03, 95% confidence interval (CI): -0.05, -0.02) and higher overall MD (β=0.03, 95% CI: 0.02, 0.04). Elevated cfPWV (upper 25thpercentile) was associated with lower FA (β=-0.26, 95% CI: -0.39, -0.14) and higher overall MD (β=0.21, 95% CI: 0.11, 0.32). Similar associations were observed at individual cerebral regions of interest. In cross-sectional analyses of aortic stiffness and depressive symptoms we observed a positive association of elevated cfPWV with the greater CES-D score (standardized beta (β)=0.07, 95% CI: 0.004, 0.15) and greater odds of CSDS (odds ratio (OR)=1.37, 95% CI: 1.01, 1.85). No association was observed between baseline cfPWV and temporal change in depressive symptoms or incident CSDS. Conclusions: These results add to the evidence suggesting that aortic stiffness may serve as a modifiable target for the prevention of poor cerebral white matter microstructural integrity. Given the limited evidence, the longitudinal association between aortic stiffness and depressive symptoms among older adults warrants further investigation.Doctor of Philosoph

Adversarial Score Distillation: When score distillation meets GAN

Existing score distillation methods are sensitive to classifier-free guidance (CFG) scale: manifested as over-smoothness or instability at small CFG scales, while over-saturation at large ones. To explain and analyze these issues, we revisit the derivation of Score Distillation Sampling (SDS) and decipher existing score distillation with the Wasserstein Generative Adversarial Network (WGAN) paradigm. With the WGAN paradigm, we find that existing score distillation either employs a fixed sub-optimal discriminator or conducts incomplete discriminator optimization, resulting in the scale-sensitive issue. We propose the Adversarial Score Distillation (ASD), which maintains an optimizable discriminator and updates it using the complete optimization objective. Experiments show that the proposed ASD performs favorably in 2D distillation and text-to-3D tasks against existing methods. Furthermore, to explore the generalization ability of our WGAN paradigm, we extend ASD to the image editing task, which achieves competitive results. The project page and code are at https://github.com/2y7c3/ASD

Artificial intelligence-aided rapid and accurate identification of clinical fungal infections by single-cell Raman spectroscopy

Integrating artificial intelligence and new diagnostic platforms into routine clinical microbiology laboratory procedures has grown increasingly intriguing, holding promises of reducing turnaround time and cost and maximizing efficiency. At least one billion people are suffering from fungal infections, leading to over 1.6 million mortality every year. Despite the increasing demand for fungal diagnosis, current approaches suffer from manual bias, long cultivation time (from days to months), and low sensitivity (only 50% produce positive fungal cultures). Delayed and inaccurate treatments consequently lead to higher hospital costs, mobility and mortality rates. Here, we developed single-cell Raman spectroscopy and artificial intelligence to achieve rapid identification of infectious fungi. The classification between fungi and bacteria infections was initially achieved with 100% sensitivity and specificity using single-cell Raman spectra (SCRS). Then, we constructed a Raman dataset from clinical fungal isolates obtained from 94 patients, consisting of 115,129 SCRS. By training a classification model with an optimized clinical feedback loop, just 5 cells per patient (acquisition time 2 s per cell) made the most accurate classification. This protocol has achieved 100% accuracies for fungal identification at the species level. This protocol was transformed to assessing clinical samples of urinary tract infection, obtaining the correct diagnosis from raw sample-to-result within 1 h

Enhancing Security Patch Identification by Capturing Structures in Commits

With the rapid increasing number of open source software (OSS), the majority of the software vulnerabilities in the open source components are fixed silently, which leads to the deployed software that integrated them being unable to get a timely update. Hence, it is critical to design a security patch identification system to ensure the security of the utilized software. However, most of the existing works for security patch identification just consider the changed code and the commit message of a commit as a flat sequence of tokens with simple neural networks to learn its semantics, while the structure information is ignored. To address these limitations, in this paper, we propose our well-designed approach E-SPI, which extracts the structure information hidden in a commit for effective identification. Specifically, it consists of the code change encoder to extract the syntactic of the changed code with the BiLSTM to learn the code representation and the message encoder to construct the dependency graph for the commit message with the graph neural network (GNN) to learn the message representation. We further enhance the code change encoder by embedding contextual information related to the changed code. To demonstrate the effectiveness of our approach, we conduct the extensive experiments against six state-of-the-art approaches on the existing dataset and from the real deployment environment. The experimental results confirm that our approach can significantly outperform current state-of-the-art baselines

ASM: Adaptive Skinning Model for High-Quality 3D Face Modeling

The research fields of parametric face models and 3D face reconstruction have been extensively studied. However, a critical question remains unanswered: how to tailor the face model for specific reconstruction settings. We argue that reconstruction with multi-view uncalibrated images demands a new model with stronger capacity. Our study shifts attention from data-dependent 3D Morphable Models (3DMM) to an understudied human-designed skinning model. We propose Adaptive Skinning Model (ASM), which redefines the skinning model with more compact and fully tunable parameters. With extensive experiments, we demonstrate that ASM achieves significantly improved capacity than 3DMM, with the additional advantage of model size and easy implementation for new topology. We achieve state-of-the-art performance with ASM for multi-view reconstruction on the Florence MICC Coop benchmark. Our quantitative analysis demonstrates the importance of a high-capacity model for fully exploiting abundant information from multi-view input in reconstruction. Furthermore, our model with physical-semantic parameters can be directly utilized for real-world applications, such as in-game avatar creation. As a result, our work opens up new research directions for the parametric face models and facilitates future research on multi-view reconstruction

Enhanced Interfacial Electronic Transfer of BiVO4 Coupled with 2D g‐C3N4 for Visible‐light Photocatalytic Performance

A BiVO4/2D g‐C3N4 direct dual semiconductor photocatalytic system has been fabricated via electrostatic self‐assembly method of BiVO4 microparticle and g‐C3N4 nanosheet. According to experimental measurements and first‐principle calculations, the formation of built‐in electric field and the opposite band bending around the interface region in BiVO4/2D g‐C3N4 as well as the intimate contact between BiVO4 and 2D g‐C3N4 will lead to high separation efficiency of charge carriers. More importantly, the intensity of bulid‐in electric field is greatly enhanced due to the ultrathin nanosheet structure of 2D g‐C3N4. As a result, BiVO4/2D g‐C3N4 exhibits excellent photocatalytic performance with the 93.0% Rhodamine B (RhB) removal after 40 min visible light irradiation, and the photocatalytic reaction rate is about 22.7 and 10.3 times as high as that of BiVO4 and 2D g‐C3N4, respectively. In addition, BiVO4/2D g‐C3N4 also displays enhanced photocatalytic performance in the degradation of tetracycline (TC). It is expected that this work may provide insights into the understanding the significant role of built‐in electric field in heterostructure and fabricating highly efficient direct dual semiconductor systems

The association and dose–response relationship between dietary intake of α-linolenic acid and risk of CHD: a systematic review and meta-analysis of cohort studies

Abstract Previous studies show inconsistent associations between α -linolenic acid (ALA) and risk of CHD. We aimed to examine an aggregate association between ALA intake and risk of CHD, and assess for any dose–response relationship. We searched the PubMed, EMBASE and Web of Science databases for prospective cohort studies examining associations between ALA intake and CHD, including composite CHD and fatal CHD. Data were pooled using random-effects meta-analysis models, comparing the highest category of ALA intake with the lowest across studies. Subgroup analysis was conducted based on study design, geographic region, age and sex. For dose–response analyses, we used two-stage random-effects dose–response models. In all, fourteen studies of thirteen cohorts were identified and included in the meta-analysis. The pooled results showed that higher ALA intake was associated with modest reduced risk of composite CHD (risk ratios (RR)=0·91; 95 % CI 0·85, 0·97) and fatal CHD (RR=0·85; 95 % CI 0·75, 0·96). The analysis showed a J-shaped relationship between ALA intake and relative risk of composite CHD ( χ 2 =21·95, P <0·001). Compared with people without ALA intake, only people with ALA intake <1·4 g/d showed reduced risk of composite CHD. ALA intake was linearly associated with fatal CHD – every 1 g/d increase in ALA intake was associated with a 12 % decrease in fatal CHD risk (95 % CI −0·21, −0·04). Though a higher dietary ALA intake was associated with reduced risk of composite and fatal CHD, the excess composite CHD risk at higher ALA intakes warrants further investigation, especially through randomised controlled trials

Zinc finger and interferon-stimulated genes play a vital role in TB-IRIS following HAART in AIDS

Aim: Co-infection in HIV-1 patients with Mycobacterium tuberculosis poses considerable risk of developing the immune reconstitution inflammatory syndrome (IRIS), especially upon the initiation of antiretroviral therapy (ART). Methodology & results: For transcriptomic analysis, peripheral blood mononuclear cells’ whole gene expression was used from three patient groups: HIV+ (H), HIV-TB+ (HT), HIV-TB+ with IRIS (HTI). Pathway enrichment and functional analysis was performed before and after highly active ART. Genes in the interferon-stimulating and ZNF families maintained tight functional interaction and tilted the balance in favor of TB-IRIS. Discussion & conclusion: The functional impairment of interaction between ZNF genes and interferon-stimulated genes, along with higher expression of S100A8/S100A9 genes possibly forms the genomic basis of TB-IRIS in a subset of HIV patients while on highly active ART

A Systematic Review of Diet Quality Index and Obesity among Chinese Adults

Diet quality scores are designed mainly based on Western-style dietary patterns. They were demonstrated to be good indicators of obesity in developed but not developing countries. Several diet quality scores were developed based on the Chinese dietary guidelines, yet no systematic review exists regarding how they were related to obesity. We searched research articles published between 2000 and 2021 in PubMed, CINAHL, and Scopus databases. Both cross-sectional and prospective studies that examined the relationship between a diet quality score and weight, body mass index, obesity, or waist circumference conducted in a Chinese population were selected. From the 602 articles searched, 20 articles were selected (12 are cross-sectional studies and 8 are prospective cohort studies). The relationship between internationally used scores and obesity was inconsistent among studies. Scores tailored to the Chinese diet demonstrated a strong relationship with both being underweight and obesity. The heterogeneity of the populations and the major nutrition transition in China may partially explain the discrepancies among studies. In conclusion, diet quality scores tailored to the Chinese diet may be associated with both undernutrition and overnutrition, as well as being underweight and obesity outcomes