Molecules of senescent glial cells differentiate Alzheimer's disease from ageing

BACKGROUND: Ageing is a major risk factor for Alzheimer's disease (AD), which is accompanied by cellular senescence and thousands of transcriptional changes in the brain. OBJECTIVES: To identify the biomarkers in the cerebrospinal fluid (CSF) that could help differentiate healthy ageing from neurodegenerative processes. METHODS: Cellular senescence and ageing-related biomarkers were assessed in primary astrocytes and postmortem brains by immunoblotting and immunohistochemistry. The biomarkers were measured in CSF samples from the China Ageing and Neurodegenerative Disorder Initiative cohort using Elisa and the multiplex Luminex platform. RESULTS: The cyclin-dependent kinase inhibitors p16/p21-positive senescent cells in human postmortem brains were predominantly astrocytes and oligodendrocyte lineage cells, which accumulated in AD brains. CCL2, YKL-40, HGF, MIF, S100B, TSP2, LCN2 and serpinA3 are biomarkers closely related to human glial senescence. Moreover, we discovered that most of these molecules, which were upregulated in senescent glial cells, were significantly elevated in the AD brain. Notably, CSF YKL-40 (β=0.5412, p<0.0001) levels were markedly elevated with age in healthy older individuals, whereas HGF (β=0.2732, p=0.0001), MIF (β=0.33714, p=0.0017) and TSP2 (β=0.1996, p=0.0297) levels were more susceptible to age in older individuals with AD pathology. We revealed that YKL-40, TSP2 and serpinA3 were useful biomarkers for discriminating patients with AD from CN individuals and non-AD patients. DISCUSSION: Our findings demonstrated the different patterns of CSF biomarkers related to senescent glial cells between normal ageing and AD, implicating these biomarkers could identify the road node in healthy path off to neurodegeneration and improve the accuracy of clinical AD diagnosis, which would help promote healthy ageing

Precise Measurements of Branching Fractions for Ds+D_s^+ Meson Decays to Two Pseudoscalar Mesons

We measure the branching fractions for seven $D_{s}^{+}$ two-body decays to pseudo-scalar mesons, by analyzing data collected at $\sqrt{s}=4.178\sim4.226$ GeV with the BESIII detector at the BEPCII collider. The branching fractions are determined to be $\mathcal{B}(D_s^+\to K^+\eta^{\prime})=(2.68\pm0.17\pm0.17\pm0.08)\times10^{-3}$, $\mathcal{B}(D_s^+\to\eta^{\prime}\pi^+)=(37.8\pm0.4\pm2.1\pm1.2)\times10^{-3}$, $\mathcal{B}(D_s^+\to K^+\eta)=(1.62\pm0.10\pm0.03\pm0.05)\times10^{-3}$, $\mathcal{B}(D_s^+\to\eta\pi^+)=(17.41\pm0.18\pm0.27\pm0.54)\times10^{-3}$, $\mathcal{B}(D_s^+\to K^+K_S^0)=(15.02\pm0.10\pm0.27\pm0.47)\times10^{-3}$, $\mathcal{B}(D_s^+\to K_S^0\pi^+)=(1.109\pm0.034\pm0.023\pm0.035)\times10^{-3}$, $\mathcal{B}(D_s^+\to K^+\pi^0)=(0.748\pm0.049\pm0.018\pm0.023)\times10^{-3}$, where the first uncertainties are statistical, the second are systematic, and the third are from external input branching fraction of the normalization mode $D_s^+\to K^+K^-\pi^+$. Precision of our measurements is significantly improved compared with that of the current world average values

A Multi-Model Prediction Method for Coal Mine Gas Concentration with Hierarchical Structure

The low concentration of gas in the gas blending process is influenced by a number of factors and is characterized by some time variation and non-linearity. Therefore, the gas concentration needs to be predicted. This paper proposes a multi-model forecasting method with a hierarchical structure. First, because the measured gas concentration time-series data contain a lot of noise, the time-series data are decomposed into several independent eigenmode functions by using empirical mode decomposition, adaptively denoising by low-pass filtering, and then using phase space reconstruction technology to obtain a new time-series sample. Then, the training samples are grouped by conditional fuzzy clustering to determine the number of sub-modules. Finally, the maximum membership method is used to select sub-models and sub-sub-models, and then a multi-model time-series prediction model is established. The model can not only select different sub-models to process data in different regions but also can process each data jointly by multiple sub-models in different sub-models. Experiments were carried out on low-concentration measured data extracted from mines. The experimental results show that the proposed prediction model can capture the nonlinear characteristics of gas concentration time series and is superior to other existing prediction models in accuracy

Micronutrient‐Fortified Milk and Academic Performance among Chinese Middle School Students: A Cluster‐Randomized Controlled Trial

Many children suffer from nutritional deficiencies that may negatively affect their academic performance. This cluster‐randomized controlled trial aimed to test the effects of micronutrient‐fortified milk in Chinese students. Participants received either micronutrient‐fortified (n = 177) or unfortified (n = 183) milk for six months. Academic performance, motivation, and learning strategies were estimated by end‐of‐term tests and the Motivated Strategies for Learning Questionnaire. Blood samples were analyzed for micronutrients. In total, 296 students (82.2%) completed this study. Compared with the control group, students in the intervention group reported higher scores in several academic subjects (p &lt; 0.05), including languages, mathematics, ethics, and physical performance at the end of follow‐up. Students in the intervention group showed greater self‐efficacy and use of cognitive strategies in learning, and reported less test anxiety (p &lt; 0.001). Moreover, vitamin B2 deficiency (odds ratio (OR) = 0.18, 95% confidence interval (CI): 0.11~0.30) and iron deficiency (OR = 0.34, 95% CI: 0.14~0.81) were less likely in the students of the intervention group, whereas vitamin D, vitamin B12, and selenium deficiencies were not significantly different. “Cognitive strategy” had a partial mediating effect on the test scores of English (95% CI: 1.26~3.79) and Chinese (95% CI: 0.53~2.21). Our findings suggest that micronutrient‐fortified milk may improve students’ academic performance, motivation, and learning strategies

Genomic resources for gene discovery, functional genome annotation, and evolutionary studies of maize and its close relatives

Maize is one of the most important food crops and a key model for genetics and developmental biology. A genetically anchored and high-quality draft genome sequence of maize inbred B73 has been obtained to serve as a reference sequence. To facilitate evolutionary studies in maize and its close relatives, much like the Oryza Map Alignment Project (OMAP) (www.OMAP.org) bacterial artificial chromosome (BAC) resource did for the rice community, we constructed BAC libraries for maize inbred lines Zheng58, Chang7-2, and Mo17 and maize wild relatives Zea mays ssp. parviglumis and Tripsacum dactyloides. Furthermore, to extend functional genomic studies to maize and sorghum, we also constructed binary BAC (BIBAC) libraries for the maize inbred B73 and the sorghum landrace Nengsi-1. The BAC/BIBAC vectors facilitate transfer of large intact DNA inserts from BAC clones to the BIBAC vector and functional complementation of large DNA fragments. These seven Zea Map Alignment Project (ZMAP) BAC/BIBAC libraries have average insert sizes ranging from 92 to 148 kb, organellar DNA from 0.17 to 2.3%, empty vector rates between 0.35 and 5.56%, and genome equivalents of 4.7-to 8.4-fold. The usefulness of the Parviglumis and Tripsacum BAC libraries was demonstrated by mapping clones to the reference genome. Novel genes and alleles present in these ZMAP libraries can now be used for functional complementation studies and positional or homology-based cloning of genes for translational genomics

Application of fluorescence in situ hybridization in the detection of bladder transitional-cell carcinoma: A multi-center clinical study based on Chinese population

Objective: To evaluate the diagnostic value of fluorescence in situ hybridization (FISH) in bladder cancer. Methods: We enrolled healthy volunteers and patients who were clinically suspected to have bladder cancer and conducted FISH tests and cytology examinations from August 2007 to December 2008. Receiver operating characteristic (ROC) curve analysis was performed and the area under curve (AUC) values were calculated for both the FISH and urine cytology tests. Results: A cohort of 988 healthy volunteers was enrolled to establish a reference range for the normal population. A total of 4807 patients with hematuria were prospectively, randomly enrolled for the simultaneous analysis of urine cytology, FISH testing, and a final diagnosis as determined by the pathologic findings of a biopsy or a surgically-excised specimen. Overall, the sensitivity of FISH in detecting transitional-cell carcinoma was 82.7%, while that of cytology was 33.4% (p < 0.001). The sensitivity values of FISH for non-muscle invasive and muscle invasive bladder transitional-cell carcinoma were 81.7% and 89.6%, respectively (p = 0.004). The sensitivity values of FISH for low and high grade bladder cancer were 82.6% and 90.1%, respectively (p = 0.002). Conclusion: FISH is significantly more sensitive than voided urine cytology for detecting bladder cancer in patients evaluated for gross hematuria at all cancer grades and stages. Higher sensitivity using FISH was obtained in high grade and muscle invasive tumors. Keywords: Bladder transitional-cell carcinoma, Fluorescence in situ hybridization, Detection, Grade, Stag