Normative Analysis of Individual Brain Differences Based on a Population MRI-Based Atlas of Cynomolgus Macaques

The developmental trajectory of the primate brain varies substantially with aging across subjects. However, this ubiquitous variability between individuals in brain structure is difficult to quantify and has thus essentially been ignored. Based on a large-scale structural magnetic resonance imaging dataset acquired from 162 cynomolgus macaques, we create a species-specific 3D template atlas of the macaque brain, and deploy normative modeling to characterize individual variations of cortical thickness (CT) and regional gray matter volume (GMV). We observed an overall decrease in total GMV and mean CT, and an increase in white matter volume from juvenile to early adult. Specifically, CT and regional GMV were greater in prefrontal and temporal cortices relative to early unimodal areas. Age-dependent trajectories of thickness and volume for each cortical region revealed an increase in the medial temporal lobe, and decreases in all other regions. A low percentage of highly individualized deviations of CT and GMV were identified (0.0021%, 0.0043%, respectively, P \u3c 0.05, false discovery rate [FDR]-corrected). Our approach provides a natural framework to parse individual neuroanatomical differences for use as a reference standard in macaque brain research, potentially enabling inferences regarding the degree to which behavioral or symptomatic variables map onto brain structure in future disease studies

Driver Genes and Its Clinical Significance in Non-small Cell Lung Cancer

With the development of molecular biology technology and the transforming patterns of drug research, guiding molecular targeted therapy according to the drive gene mutation spectrum in lung cancer has gradually become a reality. Definition of the mutation incidence and whether existing advantage population groups in non-small cell lung cancer (NSCLC) have important guiding significance in clinical practice. The purpose of this paper will draw a summary on the general characteristics, demographic features and clinical significance of driver genes in NSCLC

A Peel Test Method to Characterize the Decay Law of Prepreg Tape Tack at Different Temperatures

The tack of prepreg is a key factor affecting the automatic tape laying process. During the manufacturing process of large composite parts, prepreg material may be stored at room temperature for several days, resulting in a decrease in its tack. In this study, a new tack test tool was designed, and the decay rate of prepreg tack at different temperatures was tested. We proposed a prepreg tack decay model, which assumes that the main factor in tack decay is the reduction in resin chain activity during storage. The maximum deviation between the model calculation results and the experimental results of the tack decay rate is 9.7%. This study also proposed a new statistical unit for prepreg tack, which can establish the relationship between the tack of prepreg and its remaining storage time and reduce prepreg management costs

A potential role of microRNAs in protein accumulation in cellular senescence analyzed by bioinformatics.

Cellular senescence is an important protective mechanism against cell proliferation and has critical roles in aging and aging-related disease. Recently, one interesting observation is that the protein abundance is higher in senescent cells than that in young cells. So far, some factors were presented to interpret this observation, such as active protein synthesis linked with autophagy, mTOR, and oxidative stress. Here, applying bioinformatic analysis of microRNA profiles in young cells and aging cells, we revealed that globally senescent cells show lower miRNA abundance than that in young cells, suggesting that the repression of protein synthesis by miRNA in senescent cells could be largely attenuated. This finding provides clues that protein accumulation in cellular senescence could be associated with lower miRNA abundance in aging cells

Identification of time-varying cable tension forces based on adaptive sparse time-frequency analysis of cable vibrations

For cable bridges, the cable tension force plays a crucial role in their construction, assessment and long-term structural health monitoring. Cable tension forces vary in real time with the change of the moving vehicle loads and environmental effects, and this continual variation in tension force may cause fatigue damage of a cable. Traditional vibration-based cable tension force estimation methods can only obtain the time-averaged cable tension force and not the instantaneous force. This paper proposes a new approach to identify the time-varying cable tension forces of bridges based on an adaptive sparse time-frequency analysis method. This is a recently developed method to estimate the instantaneous frequency by looking for the sparsest time-frequency representation of the signal within the largest possible time-frequency dictionary (i.e. set of expansion functions). In the proposed approach, first, the time-varying modal frequencies are identified from acceleration measurements on the cable, then, the time-varying cable tension is obtained from the relation between this force and the identified frequencies. By considering the integer ratios of the different modal frequencies to the fundamental frequency of the cable, the proposed algorithm is further improved to increase its robustness to measurement noise. A cable experiment is implemented to illustrate the validity of the proposed method. For comparison, the Hilbert–Huang transform is also employed to identify the time-varying frequencies, which are then used to calculate the time-varying cable-tension force. The results show that the adaptive sparse time-frequency analysis method produces more accurate estimates of the time-varying cable tension forces than the Hilbert–Huang transform method

Identification of time-varying cable tension forces based on adaptive sparse time-frequency analysis of cable vibrations

For cable bridges, the cable tension force plays a crucial role in their construction, assessment and long-term structural health monitoring. Cable tension forces vary in real time with the change of the moving vehicle loads and environmental effects, and this continual variation in tension force may cause fatigue damage of a cable. Traditional vibration-based cable tension force estimation methods can only obtain the time-averaged cable tension force and not the instantaneous force. This paper proposes a new approach to identify the time-varying cable tension forces of bridges based on an adaptive sparse time-frequency analysis method. This is a recently developed method to estimate the instantaneous frequency by looking for the sparsest time-frequency representation of the signal within the largest possible time-frequency dictionary (i.e. set of expansion functions). In the proposed approach, first, the time-varying modal frequencies are identified from acceleration measurements on the cable, then, the time-varying cable tension is obtained from the relation between this force and the identified frequencies. By considering the integer ratios of the different modal frequencies to the fundamental frequency of the cable, the proposed algorithm is further improved to increase its robustness to measurement noise. A cable experiment is implemented to illustrate the validity of the proposed method. For comparison, the Hilbert–Huang transform is also employed to identify the time-varying frequencies, which are then used to calculate the time-varying cable-tension force. The results show that the adaptive sparse time-frequency analysis method produces more accurate estimates of the time-varying cable tension forces than the Hilbert–Huang transform method

Blocking Adenosine/A2AR Pathway for Cancer Therapy

Adenosine is a metabolite produced abundantly in the tumor microenvironment, dampening immune response in inflamed tissues via adenosine A2A receptor (A2AR) which is widely expressed on immune cells, inhibiting anti-tumor immune response accordingly. Therefore, blocking adenosine signaling pathway is of potential to promote anti-tumor immunity. This review briefly introduces adenosine signaling pathway, describes its role in regulating tumor immunity and highlights A2AR blockade in cancer therapy. Prospective anti-tumor activity of adenosine/A2AR inhibition has been revealed by preclinical data, and a number of clinical trials of A2AR antagonists are under way. Primary results from clinical trials suggest that A2AR antagonists are well tolerated in cancer patients and are effective both as monotherapy and in combination with other therapies. In the future, finding predictive biomarkers are critical to identify patients most likely to benefit from adenosine pathway blockade, and further researches are needed to rationally combine A2AR antagonists with other anti-tumor therapies

Result of enrichment analysis of deregulated miRNAs during cellular senescence in two cancer miRNA sets.

<p>(A) Tumor suppressing miRNAs. (B) oncogenic miRNAs. Red color represents senescent cells. Green color represents young cell. 1 Replicative senescence in HUVECs. 2 Oncogene-induced senescence in IMR90 cells. 3 Aging tissues in rhesus macaque brain.</p

Model of relationship between miRNA abundance and protein accumulation during cellular senescence.

<p>Globally low expression of miRNAs in senescent cells decreased the suppression of RNA translating into proteins, which results in the accumulation of proteins accompanied with the increased proteins synthesis mediated by autophagy.</p

Comparative expression levels miRNAs in young cells (or tissues) (x axis) and senescent cells (or tissues) (y axis).

<p>(A) replicative senescence in HUVECs (the expression data was log2 transformed). (B) Oncogene-induced senescence in IMR90 cells. (C) Aging tissues in rhesus macaque brain.</p