Miracle-dz/UniFAR-FTUs huggingface dataset:
Gli3 is a negative regulator of Tas1r3-expressing taste cells

Mouse taste receptor cells survive from 3–24 days, necessitating their regeneration throughout adulthood. In anterior tongue, sonic hedgehog (SHH), released by a subpopulation of basal taste cells, regulates transcription factors Gli2 and Gli3 in stem cells to control taste cell regeneration. Using single-cell RNA-Seq we found that Gli3 is highly expressed in Tas1r3-expressing taste receptor cells and Lgr5+ taste stem cells in posterior tongue. By PCR and immunohistochemistry we found that Gli3 was expressed in taste buds in all taste fields. Conditional knockout mice lacking Gli3 in the posterior tongue (Gli3CKO) had larger taste buds containing more taste cells than did control wild-type (Gli3WT) mice. In comparison to wild-type mice, Gli3CKO mice had more Lgr5+ and Tas1r3+ cells, but fewer type III cells. Similar changes were observed ex vivo in Gli3CKO taste organoids cultured from Lgr5+ taste stem cells. Further, the expression of several taste marker and Gli3 target genes was altered in Gli3CKO mice and/or organoids. Mirroring these changes, Gli3CKO mice had increased lick responses to sweet and umami stimuli, decreased lick responses to bitter and sour taste stimuli, and increased glossopharyngeal taste nerve responses to sweet and bitter compounds. Our results indicate that Gli3 is a suppressor of stem cell proliferation that affects the number and function of mature taste cells, especially Tas1r3+ cells, in adult posterior tongue. Our findings shed light on the role of the Shh pathway in adult taste cell regeneration and may help devise strategies for treating taste distortions from chemotherapy and aging.
Densely connected deconvolutional network for semantic segmentation

Recent progress in semantic segmentation has been driven by improving the spatial resolution under Fully Convolutional Networks(FCNs). To address this problem, we propose a Densely Connected Deconvolutional Network (DCDN) for semantic segmentation. In DCDN, multiple shallow deconvolutional networks, which are called as DCDN units, are stacked one by one to make the structure deeper and guarantee the fine recovery of localization information, meanwhile, the inter-unit and intra-unit dense connections are designed to make the network easy to train since the connections improve the flow of information and gradients throughout the network. Besides, the intermediate supervisions are applied to each DCDN unit to ensure the fast convergence. Extensive experiments on two urban scene datasets, i.e., CamVid and GATECH, demonstrate that the proposed model achieves better performance than some state-of-the-art methods without using any post-processing, pretrained model, nor temporal information, whilst requiring less parameters.
Realistic nano-polycrystalline microstructures: beyond the classical Voronoi tessellation

A modified Voronoi tessellation (MVT) is proposed for the computer simulation of realistic microstructures. Compared with standard tessellations, the present algorithm provides the desired grain size distribution in a one-step, non-evolutionary procedure. This is obtained by relaxing the constraints of Voronoi tessellation on position and orientation of the grain boundaries, with the only side effect being the formation of a limited amount of eliminable voids. As an example, it is shown how to directly obtain a distribution of grains of given variance and with a shape statistically close to the lognormal one.
Comparison of computational methods in the electronic structure of carbon nanotubes of single walled (8, 0)

The carbon nanotubes have attracted much interest for their electronic properties which go from metallic to semiconducting behavior, depending both on diameter, number of layers and chirality. The value of their band gap is obviously a crucial point to be addressed because it enters in the nanbotube application as microelectronic devices. This work was developed through an estimate of the behavior of the electronic structure of carbon nanotubes of single walled 8,0 and the assessment of electrical conduction through various methodologies such as LSDA, B3PW91, B3LYP and HF ab initio methods and PM3 and AM1semi-empirical methods. The methods showed similarities with the geometrical parameters reported in the literature. The hybrid methods based on density functional generated a good approximation in the energy gap value of single-walled carbon nanotubes 8,0. Results will be presented.
Emotional manifestations of PD: Neurobiological basis

Neuropsychiatric symptoms are common and disabling in PD. Their neurobiological bases are complex, partly because of the disease itself and partly because of the dopaminergic treatment. The aim of this review is to focus on the emotional manifestations stemming from the neurodegenerative process itself. We focus on depression, anxiety, apathy, and fatigue, which can all be part of the clinical spectrum of premotor disease and may be improved or masked by medications targeting parkinsonian motor signs or psychiatric symptoms as the disease progresses. Findings from clinical, neuroimaging, and animal studies are reviewed, showing a major contribution of the dopaminergic system to the pathophysiology of these disabling symptoms. Degeneration of noradrenergic and serotonergic projection systems also has an impact on psychiatric symptoms of PD. The available literature is reviewed, but at present there is a lack of studies that would allow disentangling the separate contribution of each of the monoaminergic systems. The use of a pragmatic classification of all these symptoms under the umbrella of hypodopaminergic behavioral syndrome seems clinically useful, as it emphasizes the crucial, although not exclusive, nature of their dopaminergic neurobiological basis, which has important implications in the clinical management of PD. © 2016 International Parkinson and Movement Disorder Society
Caching reduces kleptoparasitism in a solitary, large felid

Food caching is a common strategy used by a diversity of animals, including carnivores, to store and/or secure food. Despite its prevalence, the drivers of caching behaviour, and its impacts on individuals, remain poorly understood, particularly for short-term food cachers. Leopards Panthera pardus exhibit a unique form of short-term food caching, regularly hoisting, storing and consuming prey in trees. We explored the factors motivating such behaviour among leopards in the Sabi Sand Game Reserve, South Africa, associated with four not mutually exclusive hypotheses: food-perishability, consumption-time, resource-pulse and kleptoparasitism-avoidance. Using data from 2032 prey items killed by 104 leopards from 2013 to 2015, we built generalized linear mixed models to examine how hoisting behaviour, feeding time and the likelihood of a kill being kleptoparasitized varied with leopard sex and age, prey size and vulnerability, vegetation, elevation, climate, and the immediate and long-term risk posed by dominant competitors. Leopards hoisted 51% of kills. They were more likely to hoist kills of an intermediate size, outside of a resource pulse and in response to the presence of some competitors. Hoisted kills were also fed on for longer than non-hoisted kills. At least 21% of kills were kleptoparasitized, mainly by spotted hyaenas Crocuta crocuta. Kills were more likely to be kleptoparasitized at lower temperatures and if prey were larger, not hoisted, and in areas where the risk of encountering hyaenas was greatest. Female leopards that suffered higher rates of kleptoparasitism exhibited lower annual reproductive success than females that lost fewer kills. Our results strongly support the kleptoparasitism-avoidance hypothesis and suggest hoisting is a key adaptation that enables leopards to coexist sympatrically with high densities of competitors. We further argue that leopards may select smaller-sized prey than predicted by optimal foraging theory, to balance trade-offs between kleptoparasitic losses and the energetic gains derived from killing larger prey. Although caching may provide the added benefits of delaying food perishability and enabling consumption over an extended period, the behaviour primarily appears to be a strategy for leopards, and possibly other short-term cachers, to reduce the risks of kleptoparasitism.
Vitamin D Insufficiency Is Associated With Diabetes Risk in Native American Children

Aims/Hypothesis. Vitamin D insufficiency has not been well studied in Native American (NA) children, who are at risk for obesity and diabetes. The authors examined vitamin D insufficiency and its association with body mass index (BMI) and insulin resistance. Methods. In a cross-section of NA children 5 to 18 years old (N = 198), anthropometrics, biomarkers of insulin resistance, and 25-hydroxy-vitamin D concentration [25(OH) vitamin D] were measured. BMI% and homeostatic model assessment of insulin resistance (HOMA-IR) were calculated. Results. Mean age was 10.8 ± 0.3 years (mean ± SEM). Mean serum 25(OH) vitamin D was 17.8 ± 0.4 ng/mL and 97% had vitamin D insufficiency [25(OH) vitamin D <30 ng/mL]. After adjusting for BMI, 25(OH) vitamin D was inversely associated with HOMA-IR (P < .0001) and several other markers of insulin resistance. Conclusions/Interpretation. Vitamin D insufficiency was nearly universal in this cohort of NA children and was associated with diabetes and vascular risk markers. Whether vitamin D supplementation can improve insulin resistance must be studied further.
Genetic Risk as a Marker of Amyloid-β and Tau Burden in Cerebrospinal Fluid

Background: The search for a biomarker of Alzheimer’s disease (AD) pathology (amyloid-β (Aβ) and tau) is ongoing, with the best markers currently being measurements of Aβ and tau in cerebrospinal fluid (CSF) and via positron emission tomography (PET) scanning. These methods are relatively invasive, costly, and often have high screening failure rates. Consequently, research is aiming to elucidate blood biomarkers of Aβ and tau. Objective: This study aims to investigate a case/control polygenic risk score (PGRS) as a marker of tau and investigate blood markers of a combined Aβ and tau outcome for the first time. A sub-study also considers plasma tau as markers of Aβ and tau pathology in CSF. Methods: We used data from the EDAR*, DESCRIPA**, and Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohorts in a logistic regression analysis to investigate blood markers of Aβ and tau in CSF. In particular, we investigated the extent to which a case/control PGRS is predictive of CSF tau, CSF amyloid, and a combined amyloid and tau outcome. The predictive ability of models was compared to that of age, gender, and APOE genotype (‘basic model’). Results: In EDAR and DESCRIPA test data, inclusion of a case/control PGRS was no more predictive of Aβ, and a combined Aβ and tau endpoint than the basic models (accuracies of 66.0%, and 73.3% respectively). The tau model saw a small increase in accuracy compared to basic models (59.6%). ADNI 2 test data also showed a slight increase in accuracy for the Aβ model when compared to the basic models (61.4%). Conclusion: We see some evidence that a case/control PGRS is marginally more predictive of Aβ and tau pathology than the basic models. The search for predictive factors of Aβ and tau pathologies, above and beyond demographic information, is still ongoing. Better understanding of AD risk alleles, development of more sensitive assays, and studies of larger sample size are three avenues that may provide such factors. However, the clinical utility of possible predictors of brain Aβ and tau pathologies must also be investigated. *‘Beta amyloid oligomers in the early diagnosis of AD and as marker for treatment response’ **‘Development of screening guidelines and criteria for pre-dementia Alzheimer’s disease’
Revealing Hidden Impression Topics in Students’ Journals Based on Nonnegative Matrix Factorization

Students' reflective writings are useful not only for students themselves but also teachers. It is important for teachers to know which concepts were understood well by students and which concepts were not, to continuously improve their classes. However, it is difficult for teachers to thoroughly read the journals of more than one hundred students. In this paper, we propose a novel method to extract common topics and students' common impressions against them from students' journals. Weekly keywords are discovered from journals by scoring noun words with a measure based on TF-IDF term weighting scheme, and then we analyze co-occurrence relationships between extracted keywords and adjectives. We employs nonnegative matrix factorization, one of the topic modeling techniques, to discover the hidden impression topics from the co-occurrence relationships. As a case study, we applied our method on students' journals of the course "Information Science" held in our university. Our experimental results show that conceptual keywords are successfully extracted, and four significant impression topics are identified. We conclude that our analysis method can be used to collectively understand the impressions of students from journal texts.
Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making

In multi-objective decision planning and learning, much attention is paid to producing optimal solution sets that contain an optimal policy for every possible user preference profile. We argue that the step that follows, i.e, determining which policy to execute by maximising the user's intrinsic utility function over this (possibly infinite) set, is under-studied. This paper aims to fill this gap. We build on previous work on Gaussian processes and pairwise comparisons for preference modelling, extend it to the multi-objective decision support scenario, and propose new ordered preference elicitation strategies based on ranking and clustering. Our main contribution is an in-depth evaluation of these strategies using computer and human-based experiments. We show that our proposed elicitation strategies outperform the currently used pairwise methods, and found that users prefer ranking most. Our experiments further show that utilising monotonicity information in GPs by using a linear prior mean at the start and virtual comparisons to the nadir and ideal points, increases performance. We demonstrate our decision support framework in a real-world study on traffic regulation, conducted with the city of Amsterdam.
Interference Management for In-Band Full-Duplex Vehicular Access Networks

We consider in-band full-duplex (FD) vehicular access networks in which a FD vehicular access point (AP) with high mobility simultaneously supports half-duplex (HD) downlink and uplink users with low mobility. We assume no self-interference due to FD operation at the AP and no channel state information known at the transmit side (no channel state information at the transmitter side). We completely characterize the sum degrees of freedom (DoF) by proposing an optimal blind interference alignment scheme, which exploits the difference of channel's temporal correlations between the AP and users, and establishing the matching upper bound on the sum DoF. Performance evaluation shows that the proposed scheme improves the sum rate at the finite signal-to-noise ratio regime compared to the conventional HD system.
Provably noise-robust, regularised k-means clustering

We consider the problem of clustering in the presence of noise. That is, when on top of cluster structure, the data also contains a subset of points which are unstructured. Our goal is to detect this structure despite the presence of the unstructured points. Any algorithm which achieves this goal is noise-robust. We consider a regularization method which converts any center-based clustering objective into a noise-robust one and provide robustness guarantees for our method. More specifically, in this paper, we focus on the popular $k$-means objective. We first show that the regularised version of $k$-means is also NP-Hard. We propose an algorithm based on the convex (sdp) relaxation of the regularised objective. We then prove robustness guarantee for our sdp-based algorithm w.r. t existing robustness measures. We complement our findings with experiments showing the efficiency of our algorithm.
Clinical benefit of a precision medicine based approach for guiding treatment of refractory cancers

Patients and Methods Patients with metastatic solid tumors who had progressed on at least one line of standard of care therapy were referred to the Indiana University Health Precision Genomics Program. Tumor samples were submitted for DNA & RNA next-generation sequencing, fluorescence in situ hybridization, and immunohistochemistry for actionable targets. A multi-disciplinary tumor board reviewed all results. For each patient, the ratio of progression-free survival (PFS) of the genomically guided line of therapy divided by the PFS of their prior line was calculated. Patients whose PFS ratio was ≥ 1.3 were deemed to have a meaningful improvement in PFS. Results From April 2014–October 2015, 168 patients were evaluated and 101 patients achieved adequate clinical follow-up for analysis. 19 of 44 (43.2%) patients treated with genomically guided therapy attained a PFS ratio ≥ 1.3 vs. 3 of 57 (5.3%) treated with non-genomically guided therapy (p < 0.0001). Similarly, overall PFS ratios (irrespective of cutoff) were higher for patients with genomically guided therapy vs non-genomically guided therapy (p = 0.05). Further, patients treated with genomically guided therapy had a superior median PFS compared to those treated with non-genomically guided therapy (86 days vs. 49 days, p = 0.005, H.R. = 0.55, 95% C.I.:0.37-0.84). Conclusion Patients with refractory metastatic cancer who receive genomically guided therapy have improved PFS ratios and longer median PFS compared to patients who do not receive genomically guided therapy.
Interplay between Experimental Dental Pellicles and Stannous-Containing Toothpaste on Dental Erosion-Abrasion

The interaction between stannous-containing dentifrice slurry and experimentally formed pellicles was investigated on enamel and root dentin using an erosion-remineralization-abrasion cycling model. The remineralizing solutions contained no proteins (negative control), mucin, casein, mucin + casein or albumin, for experimental pellicle formation. Toothbrushing was performed with fluoride toothpaste, with (TP + Sn) and without (TP) 3,500 ppm Sn. TP + Sn reduced surface loss for both enamel and root dentin (p < 0.05). The association between TP + Sn and albumin resulted in a significantly lower enamel surface loss (p < 0.05), suggesting positive interaction of stannous ion and albumin on dental erosion-abrasion protection. A similar trend was observed for root dentin, although less pronounced.
Social moms and health: A multi-platform analysis of mommy communities

The explosion of online social media has increased people's ability to share content and link with others, thus allowing diverse communities to emerge naturally as a product of interaction among participants. Mothers have certainly not been foreign to this development. Many have embraced the new technology to share experiences, thoughts, current events, reactions, and tips with their peers. Recognizing the role of mothers as decision-makers in their families, especially in the context of health, we focus our attention on “mommy-communities” in Twitter and the blogosphere. We consider what health topics are discussed by mothers in these communities, identify and compare implicit affinities to explicit links, and highlight differences and similarities across the two social media platforms.
Interference Alignment and Its Applications: A Survey, Research Issues, and Challenges

The capacity of interference network is a fundamental issue that eludes the researchers for decades. Interference alignment (IA) is an emerging interference management technique that is degrees of freedom (DoFs) optimal, which means it can approach the capacity of interference network at very high signal-to-noise ratio (SNR). In IA networks, the signals are constrained into the same subspaces at the unintended receivers through cooperative precoding, and the desired signal can be recovered at each receiver by eliminating the aligned interferences using decoding matrix. Due to its promising performance in interference management, IA has successfully been applied to many kinds of multiuser wireless networks with excellent performance. Nevertheless, there are still some challenges for the practical utilization of IA, e.g., the overhead of channel state information (CSI) feedback, performance degradation at low and moderate SNRs, etc. In this review, we provide a survey on IA and its applications and discuss some research issues and challenges. The dimensions, networks topologies, and applications of IA are first introduced. Then some fundamental aspects of IA are discussed, including feasibility condition, performance metrics, iterative algorithms, and CSI. We also present some recent research issues of opportunistic IA, spectrum sharing, green IA, topology management, and physical layer security. Finally, some research challenges of IA are identified.
Risk Perception of Prescription Drugs

Background. Experts are perceived to be veridical and to focus only on objective data when evaluating risk. Only a few research studies have attempted to characterize the subjectivity in risk evaluation among experts. Objective. The hypothesis of this study is that expert evaluation of a pharmaceutical drug can be partly explained by dimensions that describe the drug and by individual characteristics. Design. Seventy-five medical assessors in 9 EU countries evaluated a list of 28 pharmaceutical drugs using 4 scales: risk, benefit, seriousness of harm, and patients’ knowledge of the risk. They were also given a mock “clinical dossier” and asked to rate it on 8 dimensions: risk, benefit, worry, magnitude of the exposure, scientific knowledge of the risk, familiarity of the risk, ethical concerns, and risk acceptability. Results. Female assessors perceived significantly higher benefits than men for a large number of the 28 drugs. Principal component analysis of the ratings for the clinical dossiers revealed 2 underlying components: seriousness of harm and scientific evidence. A regression model predicting the risk perception of the drug showed that the variables seriousness of harm (benefit, worry, magnitude of exposure, ethical concerns, and risk acceptability), years of regulatory experience, gender, and type of drug explained 54% of the variability among assessors. Conclusion. Assessors’ view of the risks associated with pharmaceutical drugs is influenced by worry for patient safety, magnitude of patient exposure, and ethical concerns. These dimensions may influence their perceptions of benefit and risk acceptability. Senior assessors are more risk averse than junior assessors, and female assessors seem to be sensitive to the promise of benefit from medicines and consequently may be less risk averse than male assessors.
Processing of polymer-derived porous SiC body using allylhydridopolycarbosilane (AHPCS) and PMMA microbeads

A simple method for making a porous SiC body through a polymeric route at one firing processing was demonstrated by the sacrificial filler template approach. By incorporating sacrificial pore-forming plastic powder, PMMA microbeads, into liquid preceramic polymer, AHPCS, and losing it after the polymer was hardened, a preceramic porous body was formed. As a consequence of systematic examination of the effects of particle size and mixture ratio of the powder, an AHPCS-derived porous SiC body was reproducibly formed without critical crack initiation. It was enabled only when the polymer was sufficiently contained to make a strong skeletal structure with the sacrificial plastic particles closely distributed. The porous microstructure would contribute to efficient gas emission and uniform thermal shrinkage during polymer pyrolysis, which reduced internal pressure and crack-causing thermal stress.