Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross Talk Between Brain Innate Immunity and Serotonin Signaling Underlies Depressive-Like Behavior Induced by Alzheimer's Amyloid-β Oligomers in Mice

Considerable clinical and epidemiological evidence links Alzheimer's disease (AD) and depression. However, the molecular mechanisms underlying this connection are largely unknown. We reported recently that soluble Aβ oligomers (AβOs), toxins that accumulate in AD brains and are thought to instigate synapse damage and memory loss, induce depressive-like behavior in mice. Here, we report that the mechanism underlying this action involves AβO-induced microglial activation, aberrant TNF-α signaling, and decreased brain serotonin levels. Inactivation or ablation of microglia blocked the increase in brain TNF-α and abolished depressive-like behavior induced by AβOs. Significantly, we identified serotonin as a negative regulator of microglial activation. Finally, AβOs failed to induce depressive-like behavior in Toll-like receptor 4-deficient mice and in mice harboring a nonfunctional TLR4 variant in myeloid cells. Results establish that AβOs trigger depressive-like behavior via a double impact on brain serotonin levels and microglial activation, unveiling a cross talk between brain innate immunity and serotonergic signaling as a key player in mood alterations in AD. SIGNIFICANCE STATEMENT Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the main cause of dementia in the world. Brain accumulation of amyloid-β oligomers (AβOs) is a major feature in the pathogenesis of AD. Although clinical and epidemiological data suggest a strong connection between AD and depression, the underlying mechanisms linking these two disorders remain largely unknown. Here, we report that aberrant activation of the brain innate immunity and decreased serotonergic tonus in the brain are key players in AβO-induced depressive-like behavior in mice. Our findings may open up new possibilities for the development of effective therapeutics for AD and depression aimed at modulating microglial function.
Why Are Most University Students Women? Evidence Based on Academic Performance, Study Habits and Parental Influences

In this study, we use new Canadian data containing detailed information on standardized test scores, school marks, parental and peer influences, and other socio-economic background characteristics of boys and girls to try to account for the large gender gap in university attendance. Among 19-year-old youth in 2003, 38.8% of girls had attended university, compared with only 25.7% of boys. However, young men and women were about equally likely to attend college. We find that differences in observable characteristics between boys and girls account for more than three quarters (76.8%) of the gap in university participation. In order of importance, the main factors are differences in school marks at age 15, standardized test scores in reading at age 15, study habits, parental expectations and the university earnings premium relative to high school. Altogether, the four measures of academic abilities used in the study "overall marks, performance on standardized reading tests, study habits and repeating grade" collectively account for 58.9% of the gender gap in university participation. These results suggest that understanding why girls outperform boys in the classroom may be a key to understanding the gender divide in university participation.
English Idioms and How to Use Them

A solution to get the problem off, have you found it? Really? What kind of solution do you resolve the problem? From what sources? Well, there are so many questions that we utter every day. No matter how you will get the solution, it will mean better. You can take the reference from some books. And the english idioms and how to use them is one book that we really recommend you to read, to get more solutions in solving this problem.
Race/Ethnicity, Income, Chronic Asthma, and Mental Health: A Cross-Sectional Study Using the Behavioral Risk Factor Surveillance System

Objective: To examine the relationships among race/ethnicity, income, and asthma on mental health outcomes in individuals surveyed as part of the Centers for Disease Control and Prevention 2004 Behavioral Risk Factor Surveillance System (BRFSS). Racial and ethnic disparities in asthma prevalence exist, which may be explained in part by socioeconomic status. Individuals with asthma often have comorbid mental health conditions, the rates of which are also marked by significant racial and ethnic disparities. Methods: We obtained 2004 BRFSS demographic, asthma, and mental health data on Hispanics, non-Hispanic Whites, and non-Hispanic Blacks. Linear regression analysis was used to examine the main and interaction effects of race/ethnicity, income, and history of asthma on poor mental health (n = 282,011), as well as on depression (n = 14,907) and anxiety (n = 14,871) specifically. Results: A significant three-way interaction emerged among race/ethnicity, income, and history of chronic asthma on number of days of poor mental health. Among the most impoverished (income <$15,000/yr), Hispanics with asthma reported greater number of days of poor mental health than non-Hispanic Whites with asthma. However, among those with slightly greater economic resources, Hispanics with asthma reported fewer number of days of poor mental health than non-Hispanic Whites. Conclusions: The results of this study highlight the complex interactions among race/ethnicity, income, and asthma on mental health outcomes. BRFSS = Behavioral Risk Factor Surveillance System.
Fractionated manganese injections: effects on MRI contrast enhancement and physiological measures in C57BL/6 mice

Manganese‐enhanced MRI (MEMRI) is an increasingly used imaging method in animal research, which enables improved T1‐weighted tissue contrast. Furthermore accumulation of manganese in activated neurons allows visualization of neuronal activity. However, at higher concentrations manganese (Mn2+) exhibits toxic side effects that interfere with the animals' behaviour and well‐being. Therefore, when optimizing MEMRI protocols, a compromise has to be found between minimizing side effects and intensifying image contrast. Recently, a low concentrated fractionated Mn2+ application scheme has been proposed as a promising alternative. In this study, we investigated effects of different fractionated Mn2+ dosing schemes on vegetative, behavioural and endocrine markers, and MEMRI signal contrast in C57BL/6N mice. Measurements of the animals' well‐being included telemetric monitoring of body temperature and locomotion, control of weight and observation of behavioural parameters during the time course of the injection protocols. Corticosterone levels after Mn2+ application served as endocrine marker of the stress response. We compared three MnCl2 · 4H2O application protocols: 3 times 60 mg/kg with an inter‐injection interval of 48 h, six times 30 mg/kg with an inter‐injection interval of 48 h, and 8 times 30 mg/kg with an inter‐injection interval of 24 h (referred to as 3 × 60/48, 6 × 30/48 and 8 × 30/24, respectively). Both the 6 × 30/48 and the 8 × 30/24 protocols showed attenuated effects on animals' well‐being as compared to the 3 × 60/48 scheme. Best MEMRI signal contrast was observed for the 8 × 30/24 protocol. Together, these results argue for a fractionated application scheme such as 30 mg/kg every 24 h for 8 days to provide sufficient MEMRI signal contrast while minimizing toxic side effects and distress. Copyright © 2010 John Wiley & Sons, Ltd.
The Efficacy of Cognitive Stimulation on Depression and Cognition in Elderly Patients with Cognitive Impairment: A Retrospective Cohort Study

Cognitive decline due to neurodegenerative diseases is a prevalent worldwide problem. Both pharmacological and non-pharmacological treatments to improve, delay or stop disease progression are of vital importance. Cognitive stimulation is frequently used in clinical practice; however, there are few studies that demonstrate its efficacy. Aim: To evaluate the efficacy of cognitive stimulation in patients with mild cognitive impairment (CDR = 0.5) and dementia (CDR = 1). Methods: A retrospective cohort study was performed. Patients with cognitive impairment receiving weekly cognitive stimulation (16 or 24 sessions) were evaluated with a complete neuropsychological battery before and after the stimulation program. Each stimulation session was carried out by a trained neuropsychologist. Results: Forty two patients receiving cognitive stimulation were evaluated over a period of 12.53 months (SD 5.5). Patients were grouped as 11 amnesic mild cognitive impairment (aMCI), 23 multi domain mild cognitive impairment (mMCI) and 8 Mild Alzheimer's Dementia (CDR 1). None of the groups improved their cognitive functions after the cognitive stimulation program. MCI group was also divided according to their global intelligence quotient (IQ) into two groups: low (IQ 98.5). Each group was compared before and after the stimulation program and no significant difference was found ( p ≥ 0.05). Moreover, MCI group was also analyzed according to the duration of the stimulation program: less than 9, between 9 and 13 and more than 13 months. Different duration groups were compared before and after the cognitive stimulation program and no significant differences were found. Depression, anxiety and subjective memory symptoms were also analysed and neither improvement nor worsening could be demonstrated. Conclusions: Patients remained stable, both in cognitive and behavioural domains, for more than 18 months. However, no significant cognitive or behavioural improvement can be reported in these patients after the stimulation program (duration time: 12.53 months SD 5.5).
Quantification of Translocator Protein (18 kDa) in the Human Brain with PET and a Novel Radioligand, 18F-PBR06

Translocator protein (TSPO) (18 kDa), formerly called the peripheral benzodiazepine receptor, is upregulated on activated microglia and macrophages and is, thus, a biomarker of inflammation. We previously reported that an 11C-labeled aryloxyanilide (half-life, 20 min) was able to quantify TSPOs in the healthy human brain. Because many PET centers would benefit from a longer-lived 18F-labeled radioligand (half-life, 110 min), the objective of this study was to evaluate the ability of a closely related aryloxyanilide (18F-N-fluoroacetyl-N-(2,5-dimethoxybenzyl)-2-phenoxyaniline [18F-PBR06]) to quantify TSPOs in the healthy human brain. Methods: A total of 9 human subjects were injected with 18F-PBR06 (∼185 MBq) and scanned for 5 h, with rest periods outside the camera. The concentrations of 18F-PBR06, separated from radiometabolites, were measured in arterial plasma. Results: Modeling of regional brain and plasma data showed that a 2-tissue-compartment model was superior to a 1-tissue-compartment model. Even if data for all time points were used for the fitting, concentrations of brain activity measured with PET were consistently greater than the modeled values at late (280–300 min) but not at early time points. The greater values may have been caused by the slow accumulation of radiometabolites in the brain. To determine an adequate time for more accurate measurement of distribution volume (VT), which is the summation of receptor binding and nondisplaceable activity, we investigated which scan duration would be associated with maximal or near-maximal identifiability. We found that a scan of 120 min provided the best identifiability of VT (∼2%). The images showed no significant defluorination. Conclusion: 18F-PBR06 can quantify TSPOs in the healthy human brain using 120 min of image acquisition and concurrent measurements of radioligand in plasma. Although brain activity is likely contaminated with radiometabolites, the percentage contamination is thought to be small (<10%), because values of distribution volume are stable during 60–120 min and vary by less than 10%. 18F-PBR06 is a longer-lived and promising alternative to 11C-labeled radioligands to measure TSPOs as a biomarker of inflammation in the brain.
A New Cre Driver Mouse Line, Tcf21/Pod1-Cre, Targets Metanephric Mesenchyme

Conditional gene targeting in mice has provided great insight into the role of gene function in kidney development and disease. Although a number of Cre-driver mouse strains already exist for the kidney, development of additional strains with unique expression patterns is needed. Here we report the generation and validation of a Tcf21/Pod1-Cre driver strain that expresses Cre recombinase throughout the condensing and stromal mesenchyme of developing kidneys and in their derivatives including epithelial components of the nephron and interstitial cells. To test the efficiency of this line, we crossed it to mice transgenic for either loss or gain of function β-catenin conditional alleles. Mice with deletion of β-catenin from Tcf21-expressing cells are born with hypoplastic kidneys, hydroureters and hydronephrosis. By contrast, Tcf21-Cre driven gain of function for β-catenin in mice results in fused midline kidneys and hypoplastic kidneys. Finally, we report the first renal mesenchymal deletion of Patched1 (Ptch1), the receptor for sonic hedgehog (Shh), which results in renal cysts demonstrating a functional role of Shh signaling pathway in renal cystogensis. In summary, we report the generation and validation of a new Cre driver strain that provides robust excision in metanephric mesenchyme.
Organizations in Action: Competition between Contexts

From the Publisher: This original and ambitious work provides a fascinating examination of organizations from both a postmodern and new organizational economics perspective. Combining strategy, international business and organizational theory, Organizations In Action represents a ground-breaking critique of prevailing mainstream modernist theories of organisation. Distinctive features include: DT a comprehensive analysis of social and organizational theory DT a discussion and exploration of knowledge capitalism a critique of core comeptencies and resource based approaches to strategy, human resource management and organizational behaviour
A cluster of methylations in the domain IV of 25S rRNA is required for ribosome stability

In all three domains of life ribosomal RNAs are extensively modified at functionally important sites of the ribosome. These modifications are believed to fine-tune the ribosome structure for optimal translation. However, the precise mechanistic effect of modifications on ribosome function remains largely unknown. Here we show that a cluster of methylated nucleotides in domain IV of 25S rRNA is critical for integrity of the large ribosomal subunit. We identified the elusive cytosine-5 methyltransferase for C2278 in yeast as Rcm1 and found that a combined loss of cytosine-5 methylation at C2278 and ribose methylation at G2288 caused dramatic ribosome instability, resulting in loss of 60S ribosomal subunits. Structural and biochemical analyses revealed that this instability was caused by changes in the structure of 25S rRNA and a consequent loss of multiple ribosomal proteins from the large ribosomal subunit. Our data demonstrate that individual RNA modifications can strongly affect structure of large ribonucleoprotein complexes.
Play Ball!

The visual detection and identification of robots will become more and more important as individual robots will need to interact and in some cases collaborate with other robots while performing different tasks in a common environment. The efficient detection and identification of other robots is a very important issue as most mobile robots have low-processing capabilities and need to manage several different processes in real time (e.g., walking machine). In collaborative scenarios, robots will have to determine behaviors of other robots, in addition to their location. One of the important clues to predicting the future behavior of a robot is to know its line of gaze. In addition, surveillance and/or augmented reality systems operating in scenarios with the presence of robots will also require detecting and identifying them, as well as their behaviors.
Fall estimation of microstrip antenna array side lobe levels by using cosine-type distribution

Cosine-type microstrip feeding structure, has been modeled, designed and fabricated for array with 16-radiating elements. Analytical data show good agreement with experimental results of considered structure fabricated on RT-Duroid substrate material with thickness h=1.27 mm and electric permittivity /spl epsi//sub r/=10.2 for midband frequency around 1 GHz. Cosine distribution possesses the widest realizable dynamic amplitude range of excitation coefficients, which makes it more eligible to estimate side lobe levels fall of the feeding structure for other tapered distributions. This approach is applied before the fabrication process in which it is considered to be as time and money saving strategy.
Automatic Genre Classification as a Study of the Viability of High-Level Features for Music Classification

This paper examines the potential of high-level features extracted from symbolic musical representations in regards to musical classification. Twenty features are implemented and tested by using them to classify 225 MIDI files by genre. This system differs from previous automatic genre classification systems, which have focused on low-level features extracted from audio data. Files are classified into three parent genres and nine sub-genres, with average success rates of 84.8% for the former and 57.8% for the latter. Classification is performed by a novel configuration of feed-forward neural networks that independently classify files by parent genre and sub-genre and combine the results using weighted averages.
Scale-sensitive dimensions, uniform convergence, and learnability

Learnability in Valiant's PAC learning model has been shown to be strongly related to the existence of uniform laws of large numbers. These laws define a distribution-free convergence property of means to expectations uniformly over classes of random variables. Classes of real-valued functions enjoying such a property are also known as uniform Gliveako-Cantelli classes. In this paper we prove, through a generalization of Sauer's lemma that may be interesting in its own right, a new characterization of uniform Glivenko-Cantelli classes. Our characterization yields Dudley, Gine, and Zinn's previous characterization as a corollary. Furthermore, it is the first based on a simple combinatorial quantity generalizing the Vapnik-Chervonenkis dimension. We apply this result to characterize PAC learnability in the statistical regression framework of probabilistic concepts, solving an open problem posed by Kearns and Schapire. Our characterization shows that the accuracy parameter plays a crucial role in determining the effective complexity of the learner's hypothesis class. <<ETX>>
The impact of a brief intervention on maternal smoking behavior.

OBJECTIVE To determine if mothers receiving a smoking cessation intervention emphasizing health risks of environmental tobacco smoke (ETS) for their children have a higher quit rate than 1) mothers receiving routine smoking cessation advice or 2) a control group. DESIGN Randomized, controlled trial. SETTING Primary care center in a large urban children's hospital. INTERVENTION Four hundred seventy-nine mothers were randomly assigned to a smoking cessation intervention either aimed at their child's health or their own health, or to a control group receiving safety information. OUTCOME MEASURES Smoking status, stage of change, cigarettes/day, location smoking occurred, and knowledge of ETS effects. RESULTS Complete data (baseline and both follow-ups) were available for 166 subjects. There was no impact of group assignment on the quit rate, cigarettes/day, or stage of change. The Child Health Group intervention had a sustained effect on location where smoking reportedly occurred (usually outside) and on improved knowledge of ETS effects. CONCLUSIONS Further research is needed to devise more effective methods of using the pediatric health care setting to influence adult smoking behaviors.
Learning from Video and Text via Large-Scale Discriminative Clustering

Discriminative clustering has been successfully applied to a number of weakly supervised learning tasks. Such applications include person and action recognition, text-to-video alignment, object co-segmentation and co-localization in videos and images. One drawback of discriminative clustering, however, is its limited scalability. We address this issue and propose an online optimization algorithm based on the Block-Coordinate Frank-Wolfe algorithm. We apply the proposed method to the problem of weakly supervised learning of actions and actors from movies together with corresponding movie scripts. The scaling up of the learning problem to 66 feature-length movies enables us to significantly improve weakly supervised action recognition.
Shaping the Display of the Future: The Effects of Display Size and Curvature on User Performance and Insights

ABSTRACT As display technology continues to improve, there will be an increasing diversity in the available display form factors and scales. Empirical evaluation of how display attributes affect user perceptions and performance can help designers understand the strengths and weaknesses of different display forms, provide guidance for effectively designing multiple display environments, and offer initial evidence for developing theories of ubiquitous display. Although previous research has shown user performance benefits when tiling multiple monitors to increase the number of pixels, little research has analyzed the performance and behavioral impacts of the form factors of much larger, high-resolution displays. This article presents two experiments in which user performance was evaluated on a high-resolution (96 DPI), high pixel-count (approximately 32 million pixels) display for single-user scenarios in both flat and curved forms. We show that for geospatial visual analytics tasks there is a benefit to larger displays, and a distinct advantage to curving the display to make all portions of the display more accessible to the user. In addition, we found that changing the form factor of the display does have an impact on user perceptions that will have to be considered as new display environments are developed.
Applying sentiment and emotion analysis on brand tweets for digital marketing

As digital marketing is becoming more popular, the number of customer views on brands is increasing rapidly. This makes it harder for companies to assess their brand image or digitally market their products on the web. We present a lexicon-based approach to extracting sentiment and emotion from tweets for digital marketing purposes. We collect ten thousand tweets related to ten technology brands: Apple, Google, Microsoft, Samsung, GE, IBM, Intel, Facebook, Oracle and HP. We perform sentiment analysis using SentiWordNet while we detect emotions using the NRC Hashtag Emotion Lexicon. We compare and combine the scores obtained from the two lexicons into one result per tweet. We describe the execution process of our experiment and show that the accuracy of the combined approach of sentiment and emotion analysis is enhanced over the independent approaches of sentiment analysis or emotion analysis.