Tissue microstructural changes in dementia with Lewy bodies revealed by quantitative MRI.

We aimed to characterize dementia with Lewy bodies (DLB) by the quantitative MRI parameters of longitudinal relaxation time (qT1) and transverse relaxation time (qT2). These parameters reflect potential pathological changes in tissue microstructures, which may be detectable noninvasively in brain areas without evident atrophy, so may have potential value in revealing the early neuropathological changes in DLB. We conducted a cross-sectional study of subjects with DLB (N = 35) and similarly aged control participants (N = 35). All subjects underwent a detailed clinical and neuropsychological assessment and structural and quantitative 3T MRI. Quantitative MRI maps were obtained using relaxation time mapping methods. Statistical analysis was performed on gray matter qT1 and qT2 values. We found significant alterations of quantitative parameters in DLB compared to controls. In particular, qT1 decreases in bilateral temporal lobes, right parietal lobes, basal ganglia including left putamen, left caudate nucleus and left amygdala, and left hippocampus/parahippocampus; qT2 decreases in left putamen and increases in left precuneus. These regions showed only partial overlap with areas where grey matter loss was found, making atrophy an unlikely explanation for our results. Our findings support that DLB is predominantly associated with changes in posterior regions, such as visual association areas, and subcortical structures, and that qT1 and qT2 measurement can detect subtle changes not seen on structural volumetric imaging. Hence, quantitative MRI may compliment other imaging techniques in detecting early changes in DLB and in understanding neurobiological changes associated with the disorder.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s00415-014-7541-

Longitudinal and quantitative MRI in AD

Quantitative MRI provides important information about tissue properties in brain both in normal ageing and in degenerative disorders. Although it is well known that those with Alzheimer's disease (AD) show a specific pattern and faster rate of atrophy than controls, the precise spatial and temporal patterns of quantitative MRI in AD are unknown. We aimed to investigate neuroimaging correlates of AD using serial quantitative MRI. In our study, twenty-one subjects with AD and thirty-two similar-aged healthy controls underwent two serial MRI scans at baseline and 12 months. Tissue characteristics were captured using two quantitative MRI parameters: longitudinal relaxation time (qT1) and transverse relaxation time (qT2). The two groups (AD and controls) were statistically compared using a voxel based quantification (VBQ) method based on Matlab and SPM8. At baseline, subjects with AD showed a significant reduction of qT1 and qT2 compared to controls in bilateral temporal and parietal lobes, hippocampus, and basal ganglia. This pattern was also observed at follow-up. Longitudinally, in AD we found a significant increase rather than further reduction of qT1 and qT2 from the baseline in bilateral hippocampus, thalamus and right caudate nucleus. In addition, the longitudinal change of qT1 in left hippocampus was negatively correlated with cognitive decline in AD over the 1-year period, and the general disease severity significantly predicted the amount of increase of qT1 in bilateral hippocampus over 12 months. The longitudinal change of qT2 in left parahippocampus correlated with change in neuropsychiatric features over time. In summary, quantitative MRI parameters were reduced in AD cross-sectionally, but increased over time, showing distinct spatiotemporal patterns from the atrophy in AD. We also showed the clinical relevance of quantitative MRI parameters, indicating their potential promise as new imaging markers in AD.The study was funded by the Sir Jules Thorn Charitable Trust (grant ref: 05/JTA) and was supported by the National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre and the Biomedical Research Unit in Lewy Body Dementia based at Newcastle upon Tyne Hospitals National Health Service (NHS) Foundation Trust and Newcastle University and the NIHR Biomedical Research Centre and Biomedical Research Unit in Dementia based at Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. L. Su, A. Blamire, R. Watson, J. He and B. Aribisala report no disclosures. J. O’Brien has been a consultant for GE Healthcare, Servier, and Bayer Healthcare and has received honoraria for talks from Pfizer, GE Healthcare, Eisai, Shire, Lundbeck, Lilly, and Novartis.This is the author accepted manuscript. The final version is available from Bentham Science via http://dx.doi.org/10.2174/156720501366615111614141

Microarray‑based analysis of COL11A1 and TWIST1 as important differentially‑expressed pathogenic genes between left and right‑sided colon cancer.

Colonic cancer has become a main reason of mortality associated with cancer; however, left and right‑sided colonic cancer have diverse outcomes in terms of epidemiological, histological, clinical parameters and prognosis. We aimed to examine the discrepancies between these two types of colon cancers to identify potential therapeutic targets. In the present study, three gene expression profiles (GSE44076, GSE31595, GSE26906) from Gene Expression Omnibus (GEO) database were downloaded and further analyzed. A PPI (protein‑protein interaction) network of the differentially‑expressed genes (DEGs) of GSE44076 between tumor and normal was established with the Search Tool for the Retrieval of Interacting Genes database. Then, the DEGs of these two colon cancers (left, right) samples were identified. Subsequently, the intersection of DEGs of left and right‑sided colon cancer samples obtained from three databases, and DEGs of tumor and normal samples were analyzed. Collagen type XI α1 chain (COL11A1), Twist family bHLH transcription factor 1 (TWIST1), insulin‑like 5 and chromogranin A were upregulated proteins, while 3β‑hydroxysteroid dehydrogenase was downregulated protein in right colon cancer than in left‑sided tumor samples. Through further experimental verification, we revealed that COL11A1 and TWIST1 were significantly upregulated at the mRNA and protein levels within right‑sided colon cancer compared with in left‑sided colon cancer samples (P<0.05), consistent with bioinformatical analysis. Furthermore, a positive correlation between COL11A1 and TWIST1 protein expression was observed (P<0.0276). Collectively, our data showed that COL11A1 and TWIST1 may be potential prognostic indicators and molecular targets for the treatment of right‑sided colon cancer

Inhibition of protein FAK enhances 5-FU chemosensitivity to gastric carcinoma via p53 signaling pathways

Abstract(#br)The small molecule drug 5-fluorouracil (5-FU) is widely used in the treatment for gastric cancer (GC), however, it exerts poor efficacy and is associated with acquired and intrinsic resistance. Focal adhesion kinase (FAK), a non-receptor tyrosine kinase, plays a key role in adhesion, migration, and proliferation of gastric carcinoma cells, suggesting that this kinase may be a promising therapeutic target. Differentially expressed FAK in GC tissue was detected by RT-qPCR and TCGA database analysis. To investigate the biological functions of FAK, loss-of-function experiments were performed. CCK-8 assay, colony formation assay, flow cytometry, dual-luciferase reporter assays, and western blot assays were conducted to determine the underlying mechanisms of FAK in 5-FU chemosensitivity in GC. FAK is overexpressed in GC patients, and positively correlated with poor prognosis. The use of shRNA interference to target FAK decreased proliferation and increased apoptosis of GC cells in vitro. Importantly, FAK silencing enhanced the therapeutic efficacy of 5-FU, leading to reduced tumor growth in vivo . We further demonstrated that FAK silencing increased 5-FU-induced caspase-3 activity, and promoted p53 transcriptional activities. Clinical data also has shown that patients with higher levels of FAK had significantly shorter overall survival (OS) and time to first progression (FP) than those with lower levels of FAK. These findings indicate that FAK plays a critical role in 5-FU chemosensitivity in GC, and the use of FAK inhibitors as an adjunct to 5-FU might be an effective strategy for patients who undergo chemotherapy

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe

Polyploidy underlies co-option and diversification of biosynthetic triterpene pathways in the apple tribe

Whole-genome duplication (WGD) plays important roles in plant evolution and function, yet little is known about how WGD underlies metabolic diversification of natural products that bear significant medicinal properties, especially in nonmodel trees. Here, we reveal how WGD laid the foundation for co-option and differentiation of medicinally important ursane triterpene pathway duplicates, generating distinct chemotypes between species and between developmental stages in the apple tribe. After generating chromosome-level assemblies of a widely cultivated loquat variety and Gillenia trifoliata, we define differentially evolved, duplicated gene pathways and date the WGD in the apple tribe at 13.5 to 27.1 Mya, much more recent than previously thought. We then functionally characterize contrasting metabolic pathways responsible for major triterpene biosynthesis in G. trifoliata and loquat, which pre- and postdate the Maleae WGD, respectively. Our work mechanistically details the metabolic diversity that arose post-WGD and provides insights into the genomic basis of medicinal properties of loquat, which has been used in both traditional and modern medicines