Miracle-dz/UniFAR-FTUs huggingface dataset:
miR-33a hinders the differentiation of adipose mesenchymal stem cells towards urothelial cells in an inductive condition by targeting β-catenin and TGFR

Tissue engineering technology offers an appealing approach for tissue reconstruction of the urothelium. Adipose-derived mesenchymal stem cells (ADSCs) represent an abundant source for tissue engineering applications. However, ASCs primarily possess mesoderm lineage differentiation potential. It is difficult to induce differentiation of ASCs towards urothelial cells that are derived from the endoderm, although a recent findings have reported that a conditioned medium may drive ADSCs towards differentiation into the urothelium phenotype. In the present study, human ADSCs were isolated from abdominal adipose tissues and incubated in this conditioned medium for indicated time periods. Western blotting showed that protein expression levels of urothelial specific marks, including CK7, CK20 and UPIII, were increased after seven days' incubation, but immunofluorescence microscopy determined that cells with CK7 and UPIII staining were scarce, which suggested a low-efficiency for the differentiation. Prolonging the incubation time did not further increase CK20 and UPIII expression. Furthermore, miR-33a expression was increased with ADSC differentiation. Using synthetic miRNAs to mimic or inhibit the action of miR-33a revealed that miR-33a hinders the differentiation of ADSCs towards urothelial cells. Furthermore, luciferase reporter assay confirmed that β-catenin and transforming growth factor-β receptor (TGFR) are targets of miR-33a. Inhibition of miR-33a expression increased β-catenin and TGFR expression and improved the efficiency of ADSCs towards differentiation into the urothelium phenotype. The present novel finding suggests that miR-33 may be an important target in tissue engineering and regenerative medicine for urothelium repair.
Effects of Wx and Its Interaction With SSIII-2 on Rice Eating and Cooking Qualities

The Wx gene encodes a granule-bound starch synthase (GBSS) and plays a key role in determining rice eating and cooking qualities (ECQs). SSIII-2 (SSIIIa), a member of the soluble starch synthases, is responsible for the synthesis of long chains of amylopectin. To investigate the effects of Wx and its interaction with SSIII-2 on grain ECQs, a population from a hybrid combination was established as a research material. The genotypes of SSIII-2 and the single nucleotide polymorphisms (SNPs) on intron1, exon6, and exon10 of Wx, and the physicochemical indicators and rapid visco analyzer (RVA) profile characteristics were analyzed. The results revealed various effects of SSIII-2 on rice quality under different backgrounds of Wx alleles. There was no obvious difference between different SSIII-2 alleles under the same background of Wxa, whereas there was a significant diversity under the same background of Wxb. Wxa had a dominant epistasis to SSIII-2 because the effect of SSIII-2 was masked by the massive synthesis of GBSS under Wxa. The apparent amylose content (AAC) was mainly controlled by the In1G/T SNP, and rice gel consistency (GC) was regulated by the Ex10C/T SNP. The combined effects of three SNPs had a significant influence on all ECQs and RVA profile parameters, except for gelatinization temperature. In1T-Ex6A-Ex10C and In1T-Ex6A-Ex10T were classified as being low AAC type. TT-AA-CC and TT-AA-TT had a low AAC and a soft GC. The combined effects of different SNPs of Wx are very important for rice quality breeding.
On-line integrated routing in dynamic multifiber IP/WDM networks

This paper focuses on dynamic integrated routing in multifiber Internet protocol/wavelength-division multiplexing (IP/WDM) networks, which can be implemented through either one-step routing (OSR) or two-step routing (TSR) approach. Based on an extended layered-graph, two resource assignment strategies, termed channel-level balance (CLB) and link-level balance (LLB), are proposed to balance the traffic in the network at different levels. To further improve the performance, a parameter K is introduced to make a dynamic tradeoff between the logical-layer links and the optical-layer links. Simulation studies are carried out for various topologies. The results show that LLB is better than CLB in most cases, and LLB combined with OSR has the optimal performance. Also, we find that the routing approach and the resource assignment strategy individually play different roles with different values of r/sub l/ that is introduced to indicate the resource richness of the network. As a multifiber network is functionally equivalent to a single-fiber network with limited wavelength conversion, we investigate the effects of wavelength conversion by studying the multifiber IP/WDM networks. The analysis shows that, when the granularity of each connection request is much smaller than the wavelength granularity, wavelength conversion may increase the request blocking probability in the network.
Set Similarity Search for Skewed Data

Set similarity join, as well as the corresponding indexing problem set similarity search, are fundamental primitives for managing noisy or uncertain data. For example, these primitives can be used in data cleaning to identify different representations of the same object. In many cases one can represent an object as a sparse 0-1 vector, or equivalently as the set of nonzero entries in such a vector. A set similarity join can then be used to identify those pairs that have an exceptionally large dot product (or intersection, when viewed as sets). We choose to focus on identifying vectors with large Pearson correlation, but results extend to other similarity measures. In particular, we consider the indexing problem of identifying correlated vectors in a set S of vectors sampled from 0,1d. Given a query vector y and a parameter alpha in (0,1), we need to search for an alpha-correlated vector x in a data structure representing the vectors of S. This kind of similarity search has been intensely studied in worst-case (non-random data) settings. Existing theoretically well-founded methods for set similarity search are often inferior to heuristics that take advantage of skew in the data distribution, i.e., widely differing frequencies of 1s across the d dimensions. The main contribution of this paper is to analyze the set similarity problem under a random data model that reflects the kind of skewed data distributions seen in practice, allowing theoretical results much stronger than what is possible in worst-case settings. Our indexing data structure is a recursive, data-dependent partitioning of vectors inspired by recent advances in set similarity search. Previous data-dependent methods do not seem to allow us to exploit skew in item frequencies, so we believe that our work sheds further light on the power of data dependence.
Senescent cells expose and secrete an oxidized form of membrane-bound vimentin as revealed by a natural polyreactive antibody

Significance Understanding the mechanisms underlying the development of senescence and the consequences related to the accumulation of senescent cells is a major focus of ongoing research. Our report shows that senescent cells express a form of oxidized vimentin on their cell surface and that oxidized vimentin is secreted into the blood of senescence-prone senescence-accelerated mouse prone 8 mice. Given the growing evidence that oxidized proteins are involved in the development of human diseases, the detection and monitoring of secreted proteins like malondialdehyde-modified vimentin is certain to become a vital and noninvasive biomarker for studying senescence and monitoring age-related illnesses. Studying the phenomenon of cellular senescence has been hindered by the lack of senescence-specific markers. As such, detection of proteins informally associated with senescence accompanies the use of senescence-associated β-galactosidase as a collection of semiselective markers to monitor the presence of senescent cells. To identify novel biomarkers of senescence, we immunized BALB/c mice with senescent mouse lung fibroblasts and screened for antibodies that recognized senescence-associated cell-surface antigens by FACS analysis and a newly developed cell-based ELISA. The majority of antibodies that we isolated, cloned, and sequenced belonged to the IgM isotype of the innate immune system. In-depth characterization of one of these monoclonal, polyreactive natural antibodies, the IgM clone 9H4, revealed its ability to recognize the intermediate filament vimentin. By using 9H4, we observed that senescent primary human fibroblasts express vimentin on their cell surface, and MS analysis revealed a posttranslational modification on cysteine 328 (C328) by the oxidative adduct malondialdehyde (MDA). Moreover, elevated levels of secreted MDA-modified vimentin were detected in the plasma of aged senescence-accelerated mouse prone 8 mice, which are known to have deregulated reactive oxygen species metabolism and accelerated aging. Based on these findings, we hypothesize that humoral innate immunity may recognize senescent cells by the presence of membrane-bound MDA-vimentin, presumably as part of a senescence eradication mechanism that may become impaired with age and result in senescent cell accumulation.
The Ups and Downs of Cognitive Function: Neuroticism and Negative Affect Drive Performance Inconsistency.

Objectives Response time inconsistency (RTI)-or trial-to-trial variability in speeded performance-is increasingly recognized as an indicator of transient lapses of attention, cognitive health status, and central nervous system integrity, as well as a potential early indicator of normal and pathological cognitive aging (Hultsch, Strauss, Hunter, & MacDonald, 2008; MacDonald, Li, & Bäckman, 2009). Comparatively, little research has examined personality predictors of RTI across adulthood. Methods We evaluated the association between the personality trait neuroticism and RTI in a community-dwelling sample of 317 adults between the ages of 19 to 83 and tested for two indirect pathways through negative affect (NA) and cognitive interference (CI). Results The personality trait neuroticism predicted greater RTI independent of mean response time performance and demographic covariates; the results were age-invariant. Furthermore, NA (but not CI) accounted for this association and moderated mediation model results indicated that older adults were more vulnerable to the adverse effects of NA. Discussion Neuroticism predicts greater response time inconsistency irrespective of mean performance and this effect is driven largely by heightened negative emotionality that may be particularly detrimental for older adults.
Hypertonic Saline Alleviates Brain Edema After Traumatic Brain Injury via Downregulation of Aquaporin 4 in Rats

Background Hypertonic saline (HS) has been successfully used for treatment of various forms of brain edema. Decreased expression of aquaporin (AQP)4 and pro-inflammatory cytokines such as tumor necrosis factor (TNF)-α and interleukin (IL)-1β have been linked to edema pathogenesis. This study examined the effect of 3% HS on brain edema in a rat model of traumatic brain injury (TBI). Material/Methods Sprague-Dawley rats were subjected to TBI induced by a controlled cortical impactor. The HS group was injected with 3% NaCl until the end of the study period. AQP4, TNF-α, IL-1β, and caspase-3 levels were measured by Western blotting, immunohistochemistry, enzyme-linked immunosorbent assay, and quantitative real-time PCR. Brain water content was also measured. Apoptotic cells in brain tissue were detected with terminal deoxynucleotidyl transferase dUTP nick-end labeling. Brain water content decreased following treatment with 3% HS relative to the TBI group. Results This was accompanied by decreases in AQP4, TNF-α, and IL-1β mRNA and protein levels. TBI resulted in increases in caspase-3 mRNA expression and the number of apoptotic cells; treatment with 3% HS suppressed apoptosis as compared to the TBI group. Conclusions Treatment with 3% HS ameliorated TBI-induced brain edema, possibly by suppressing brain edema, pro-inflammatory cytokine expression, and apoptosis.
A plug-in approach to maximising precision at the top and recall at the top

For information retrieval and binary classification, we show that precision at the top (or precision at k) and recall at the top (or recall at k) are maximised by thresholding the posterior probability of the positive class. This finding is a consequence of a result on constrained minimisation of the cost-sensitive expected classification error which generalises an earlier related result from the literature.
PIANO: Proximity-Based User Authentication on Voice-Powered Internet-of-Things Devices

Voice is envisioned to be a popular way for humans to interact with Internet-of-Things (IoT) devices. We propose a proximity-based user authentication method (called PIANO) for access control on such voice-powered IoT devices. PIANO leverages the built-in speaker, microphone, and Bluetooth that voice-powered IoT devices often already have. Specifically, we assume that a user carries a personal voice-powered device (e.g., smartphone, smartwatch, or smartglass), which serves as the user's identity. When another voice-powered IoT device of the user requires authentication, PIANO estimates the distance between the two devices by playing and detecting certain acoustic signals; PIANO grants access if the estimated distance is no larger than a user-selected threshold. We implemented a proof-of-concept prototype of PIANO. Through theoretical and empirical evaluations, we find that PIANO is secure, reliable, personalizable, and efficient.
Behavioural, physiological and psychological responses of passengers to the thermal environment of boarding a flight in winter

Abstract In practice, passengers actively respond to the thermal environment when they board an aircraft in winter, which is not considered in the current standards. In this study, the behavioural, physiological and psychological responses to the thermal environment were examined at 22 °C (with 68 subjects), 20 °C and 26 °C (with 32 subjects). The results showed that the three air temperature levels had significant effect on nozzle usage and clothing adjustment behaviours, surface skin temperature, and thermal sensation vote (TSV). The walking/waiting states prior to boarding the aircraft cabin had a significant effect on the proportion of jacket removal, TSV and thermal comfort vote. After 10 min in the aircraft cabin, the subjects maintained their comfort in a wider range of the thermal environment when the behavioural adjustments existed compared to when they did not. Thus, a suggestion was made for behavioural adjustments to be provided in aircraft cabins. Practitioner Summary: Experimental investigation of human responses was conducted in an aircraft cabin. Analysis showed that the subjects maintained their comfort in a wider range of the thermal environment when the behavioural adjustments existed compared to when they did not. Thus, a suggestion was made for behavioural adjustments to be provided in aircraft cabins.
Evolution leads to a diversity of motion-detection neuronal circuits

A central goal of evolutionary biology is to explain the origins and distribution of diversity across life. Beyond species or genetic diversity, we also observe diversity in the circuits (genetic or otherwise) underlying complex functional traits. However, while the theory behind the origins and maintenance of genetic and species diversity has been studied for decades, theory concerning the origin of diverse functional circuits is still in its infancy. It is not known how many different circuit structures can implement any given function, which evolutionary factors lead to different circuits, and whether the evolution of a particular circuit was due to adaptive or non-adaptive processes. Here, we use digital experimental evolution to study the diversity of neural circuits that encode motion detection in digital (artificial) brains. We find that evolution leads to an enormous diversity of potential neural architectures encoding motion detection circuits, even for circuits encoding the exact same function. Evolved circuits vary in both redundancy and complexity (as previously found in genetic circuits) suggesting that similar evolutionary principles underlie circuit formation using any substrate. We also show that a simple (designed) motion detection circuit that is optimally-adapted gains in complexity when evolved further, and that selection for mutational robustness led this gain in complexity.
Modeling Popularity in Asynchronous Social Media Streams with Recurrent Neural Networks

Understanding and predicting the popularity of online itemsis an important open problem in social media analysis. Considerable progress has been made recently in data-driven predictions, and in linking popularity to external promotions. However, the existing methods typically focus on a single source of external influence, whereas for many types of online content such as YouTube videos or news articles, attention is driven by multiple heterogeneous sources simultaneously – e.g. microblogs or traditional media coverage. Here, we propose RNN-MAS, a recurrent neural network for modeling asynchronous streams. It is a sequence generator that connects multiple streams of different granularity via joint inference. We show RNN-MAS not only outperforms the current state-of-the-art Youtube popularity prediction system by 17%, but also captures complex dynamics, such as seasonal trends of unseen influence. We define two new metrics: the promotion score quantifies the gain in popularity from one unit of promotion for a Youtube video; the loudness level captures the effects of a particular user tweeting about the video. We use the loudness level to compare the effects of a video being promoted by a single highly-followed user (in the top 1% most followed users) against being promoted by a group of mid-followed users. We find that results depend on the type of content being promoted: superusers are more successful in promoting Howto and Gaming videos, whereas the cohort of regular users are more influential for Activism videos. This work provides more accurate and explainable popularity predictions, as well as computational tools for content producers and marketers to allocate resources for promotion campaigns.
Structured Evolution with Compact Architectures for Scalable Policy Optimization

We present a new method of blackbox optimization via gradient approximation with the use of structured random orthogonal matrices, providing more accurate estimators than baselines and with provable theoretical guarantees. We show that this algorithm can be successfully applied to learn better quality compact policies than those using standard gradient estimation techniques. The compact policies we learn have several advantages over unstructured ones, including faster training algorithms and faster inference. These benefits are important when the policy is deployed on real hardware with limited resources. Further, compact policies provide more scalable architectures for derivative-free optimization (DFO) in high-dimensional spaces. We show that most robotics tasks from the OpenAI Gym can be solved using neural networks with less than 300 parameters, with almost linear time complexity of the inference phase, with up to 13x fewer parameters relative to the Evolution Strategies (ES) algorithm introduced by Salimans et al. (2017). We do not need heuristics such as fitness shaping to learn good quality policies, resulting in a simple and theoretically motivated training mechanism.
Small Data: Applications and Architecture

Small data are the digital traces that individuals generate as a byproduct of their daily activities, such as: communicating through email or text; buying groceries or ordering delivery; or going to work on foot or by car. These traces can empower individuals to gain insights into their behavior, personalize their care, improve their relationships, motivate achievement of goals, and broadly improve their quality of life. As such small data are both byproducts of today’s and drivers of tomorrow’s ubiquitous computing applications. The contributions of this paper are twofold: we motivate the requirements for a small data ecosystem and supporting architecture, and present a critical component – Lifestreams Database (DB) – which is evaluated using three exemplar apps. Lifestreams DB extracts, processes, and models diverse traces from data silos and enables various small data applications through simple SPARQL queries. Its soft-state design provides storage-efficiency, robustness, and query performance for processing small data. Keywords–small data; linked data; knowledge representation.
Effects of Fortunella margarita Fruit Extract on Metabolic Disorders in High-Fat Diet-Induced Obese C57BL/6 Mice

Introduction Obesity is a nutritional disorder associated with many health problems such as dyslipidemia, type 2 diabetes and cardiovascular diseases. In the present study, we investigated the anti-metabolic disorder effects of kumquat (Fortunella margarita Swingle) fruit extract (FME) on high-fat diet-induced C57BL/6 obese mice. Methods The kumquat fruit was extracted with ethanol and the main flavonoids of this extract were analyzed by HPLC. For the preventive experiment, female C57BL/6 mice were fed with a normal diet (Chow), high-fat diet (HF), and high-fat diet with 1% (w/w) extract of kumquat (HF+FME) for 8 weeks. For the therapeutic experiment, female C57BL/6 mice were fed with high-fat diet for 3 months to induce obesity. Then the obese mice were divided into two groups randomly, and fed with HF or HF+FME for another 2 weeks. Body weight and daily food intake amounts were recorded. Fasting blood glucose, glucose tolerance test, insulin tolerance test, serum and liver lipid levels were assayed and the white adipose tissues were imaged. The gene expression in mice liver and brown adipose tissues were analyzed with a quantitative PCR assay. Results In the preventive treatment, FME controlled the body weight gain and the size of white adipocytes, lowered the fasting blood glucose, serum total cholesterol (TC), serum low density lipoprotein cholesterol (LDL-c) levels as well as liver lipid contents in high-fat diet-fed C57BL/6 mice. In the therapeutic treatment, FME decreased the serum triglyceride (TG), serum TC, serum LDL-c, fasting blood glucose levels and liver lipid contents, improved glucose tolerance and insulin tolerance. Compared with the HF group, FME significantly increased the mRNA expression of PPARα and its target genes. Conclusion Our study suggests that FME may be a potential dietary supplement for preventing and ameliorating the obesity and obesity-related metabolic disturbances.