Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Vitamin D Supplementation on Glucose and Insulin Homeostasis and Incident Diabetes among Nondiabetic Adults: A Meta-Analysis of Randomized Controlled Trials

Aims Emerging evidence has suggested a mechanistic link from vitamin D metabolism to glucose and insulin homeostasis. This study is aimed at specifically quantifying the direct effects of vitamin D supplementation on indexes of glucose and insulin homeostasis as well as incidence of type 2 diabetes (T2D) among nondiabetic adults. Methods We systematically searched randomized controlled trials (RCTs) of vitamin D supplementation in nondiabetic adults in PubMed, EMBASE, and CENTRAL. Random-effects meta-analysis was conducted to pool the estimates. Results Our meta-analysis included 47 RCTs involving 44,161 nondiabetic individuals with a median trial duration of 4 months and a median dose of 4000 IU/d. Vitamin D supplementation significantly reduced fasting glucose by 0.11 mmol/L, fasting insulin by 1.47 mIU/L, and HOMA-IR by 0.32 while increasing total 25 (OH) D levels by 40.14 nmol/L. We found no significant effects of vitamin D supplementation on insulin secretion or beta cell function indexes. Based on the data from six trials involving 39,633 participants and 2533 incident T2D cases, vitamin D supplementation was not associated with the risk of incident diabetes compared to placebo (pooled relative risk: 1.01, 95% confidence interval: 0.93 to 1.08). Conclusions Our meta-analysis found that vitamin D supplementation might improve glucose and insulin metabolism without affecting the risk of T2D among nondiabetic adults.
Frequency of Circulating Tumor Cells (CTC) in Patients with Brain Metastases: Implications as a Risk Assessment Marker in Oligo-Metastatic Disease

Forty percent of non-small cell lung cancer (NSCLC) patients develop brain metastases, resulting in a dismal prognosis. However, patients in an oligo-metastatic brain disease setting seem to have better outcomes. Here, we investigate the possibility of using circulating tumor cells (CTCs) as biomarkers to differentiate oligo-metastatic patients for better risk assessment. Using the CellSearch® system, few CTCs were detected among NSCLC patients with brain metastases (n = 52, 12.5% ≥ two and 8.9% ≥ five CTC/7.5 mL blood) and especially oligo-metastatic brain patients (n = 34, 5.9%, and 2.9%). Still, thresholds of both ≥ two and ≥ five CTCs were independent prognostic indicators for shorter overall survival time among all of the NSCLC patients (n = 90, two CTC ≥ HR: 1.629, p = 0.024, 95% CI: 1.137–6.465 and five CTC ≥ HR: 2.846, p = 0.0304, CI: 1.104–7.339), as well as among patients with brain metastases (two CTC ≥ HR: 4.694, p = 0.004, CI: 1.650–13.354, and five CTC ≥ HR: 4.963, p = 0.003, CI: 1.752–14.061). Also, oligo-brain NSCLC metastatic patients with CTCs had a very poor prognosis (p = 0.019). Similarly, in other tumor entities, only 9.6% of patients with brain metastases (n = 52) had detectable CTCs. Our data indicate that although patients with brain metastases more seldom harbor CTCs, they are still predictive for overall survival, and CTCs might be a useful biomarker to identify oligo-metastatic NSCLC patients who might benefit from a more intense therapy.
Beyond Query-Oriented Highlighting: Investigating the Effect of Snippet Text Highlighting in Search User Behavior

Search users rely on result captions including titles, snippets, and URLs to decide whether they should read and click a particular result or not. Snippet usually serves as a query-dependent summary of its corresponding landing page and is therefore treated as one of the most important factors in search interaction process. Although there exist many efforts in improving snippet generation algorithms and incorporating more powerful interaction functions into snippets, little attention is paid to the effect of text highlighting in user behaviors. The highlighting of query terms in search snippets has been regarded as a matter of course and whether there exists a better way in snippet text highlighting remains uninvestigated. In this paper, we try to find out whether the default strategy of highlighting query terms employed by most commercial search engines is the best for search users. Through carefully designed experiments, we show that the retrieval efficiency can be affected by different term-highlighting strategies without changes in snippet contents. We also propose an automatic method which adopts CRF to learn to highlight terms based on word embedding, Wikipedia, and snippet content information. Experimental results show that the proposed method could predict highlighted terms selected by crowd workers with moderate performance.
The Structures, Spectroscopic Properties, and Photodynamic Reactions of Three [RuCl(QN)NO]− Complexes (HQN = 8-Hydroxyquinoline and Its Derivatives) as Potential NO-Donating Drugs

The structures and spectral properties of three ruthenium complexes with 8-hydroxyquinoline (Hhqn) and their derivatives 2-methyl-8-quinolinoline (H2mqn) and 2-chloro-8-quiolinoline (H2cqn) as ligands (QN = hqn, 2mqn, or 2cqn) were calculated with density functional theory (DFT) at the B3LYP level. The UV-Vis and IR spectra of the three [RuCl(QN)NO]− complexes were theoretically assigned via DFT calculations. The calculated spectra reasonably correspond to the experimentally measured spectra. Photoinduced NO release was confirmed through spin trapping of the electron paramagnetic resonance spectroscopy (EPR), and the dynamic process of the NO dissociation upon photoirradiation was monitored using time-resolved infrared (IR) spectroscopy. Moreover, the energy levels and related components of frontier orbitals were further analyzed to understand the electronic effects of the substituent groups at the 2nd position of the ligands on their photochemical reactivity. This study provides the basis for the design of NO donors with potential applications in photodynamic therapy.
Side Population: Its Use in the Study of Cellular Heterogeneity and as a Potential Enrichment Tool for Rare Cell Populations

There is still much to learn about the cells used for cell- and gene-based therapies in the clinical setting. Stem cells are found in virtually all tissues in the human body. As a result, cells isolated from these tissues are a heterogeneous population consisting of various subpopulations including stem cells. Several strategies have been used to isolate and define the subpopulations that constitute these heterogeneous populations, one of which is the side population (SP) assay. SP cells are identified by their ability to efflux a fluorescent dye at a rate that is greater than the main cell population. This elevated rate of dye efflux has been attributed to the expression of members of the ATP-binding cassette (ABC) transporter protein family. SP cells have been identified in various tissues. In this review, we discuss the research to date on SP cells, focussing on SP cells identified in haematopoietic stem cells, adipose-derived stromal cells, and dental pulp.
Preliminary Evaluation of the Diagnostic Usefulness of Uroplakin 2 with an Assessment of the Antioxidant Potential of Patients with Bladder Cancer

Background Urothelial carcinoma is the most common type of bladder cancer (BC). It makes up more than 90% of all bladder cancers. Uroplakins are tissue-specific, glycoproteins, playing a role in the construction and function of urothelium. The emergence of uroplakins in the urine and/or plasma may be of potential importance in the early detection of BC. In our study, the diagnostic value of plasma and urine uroplakin 2 (UP2) concentration in bladder cancer was investigated, with an assessment of the antioxidant potential of BC patients. The correlation between UP2, total antioxidant capacity (TAC), and concentration of glutathione (GSH) was also examined. Materials and Methods This study included 61 BC patients and 33 healthy controls. UP2 concentration was estimated by the immunoenzymatic method (ELISA). TAC and GSH were determined in spectrophotometrically methods. Results UP2 concentration in BC patients was significantly higher (p≤0.001) both in plasma and in urine compared to the control groups (C). TAC concentration in urine (p≤0.001) and GSH concentration in plasma (p=0.047) were significantly lower in BC group compared to the C group. The high specificity and sensitivity for UPK2 in plasma (76%, 80%, respectively) and urine (88%, 84%, respectively) were observed. Positive correlations were observed between concentration of UP2 in plasma and TAC concentration in urine and between UP2 concentration in plasma and GSH concentration in the same material. Conclusion The study showed the early diagnostic value of urine and plasma UP2 in BC. There was a decrease in UP2 concentration in the urine of patients with the development of BC. The decrease of antioxidant systems (TAC, GSH) indicates their relationship with the BC process. Based on the obtained results, it is justified to continue the study in a larger group of patients with BC.
Time-resolved mapping of genetic interactions to model rewiring of signaling pathways

Context-dependent changes in genetic vulnerabilities are important to understand the wiring of cellular pathways and variations in different environmental conditions. However, methodological frameworks to investigate the plasticity of genetic networks over time or in response to external stresses are lacking. To analyze the plasticity of genetic interactions, we performed an arrayed combinatorial RNAi screen in Drosophila cells at multiple time points and after pharmacological inhibition of Ras signaling activity. Using an image-based morphology assay to capture a broad range of phenotypes, we assessed the effect of 12768 pairwise RNAi perturbations in six different conditions. We found that genetic interactions form in different trajectories and developed an algorithm, termed MODIFI, to analyze how genetic interactions rewire over time. Using this framework, we identified more statistically significant interactions compared to endpoints assays and further observed several examples of context-dependent crosstalk between signaling pathways such as an interaction between Ras and Rel which is dependent on MEK activity.
Transcranial Direct Current Stimulation (tDCS) Paired with Occupation-Centered Bimanual Training in Children with Unilateral Cerebral Palsy: A Preliminary Study

Objective We investigated the preliminary efficacy of cathodal transcranial direct current stimulation (tDCS) combined with bimanual training in children and young adults with unilateral cerebral palsy based on the principle of exaggerated interhemispheric inhibition (IHI). Methods Eight participants with corticospinal tract (CST) connectivity from the lesioned hemisphere participated in an open-label study of 10 sessions of cathodal tDCS to the nonlesioned hemisphere (20 minutes) concurrently with bimanual, goal-directed training (120 minutes). We measured the frequency of adverse events and intervention efficacy with performance (bimanual—Assisting Hand Assessment (AHA)—and unimanual—Box and Blocks), self-report (Canadian Occupational Performance Measure (COPM), ABILHAND), and neurophysiologic (motor-evoked potential amplitude, cortical silent period (CSP) duration, and motor mapping) assessments. Results All participants completed the study with no serious adverse events. Three of 8 participants showed gains on the AHA, and 4 of 8 participants showed gains in Box and Blocks (more affected hand). Nonlesioned CSP duration decreased in 6 of 6 participants with analyzable data. Cortical representation of the first dorsal interosseous expanded in the nonlesioned hemisphere in 4 of 6 participants and decreased in the lesioned hemisphere in 3 of 4 participants with analyzable data. Conclusions While goal achievement was observed, objective measures of hand function showed inconsistent gains. Neurophysiologic data suggests nonlinear responses to cathodal stimulation of the nonlesioned hemisphere. Future studies examining the contributions of activity-dependent competition and cortical excitability imbalances are indicated.
Maximally Recoverable Codes with Hierarchical Locality

Maximally recoverable codes are a class of codes which recover from all potentially recoverable erasure patterns given the locality constraints of the code. In earlier works, these codes have been studied in the context of codes with locality. The notion of locality has been extended to hierarchical locality, which allows for locality to gradually increase in levels with the increase in the number of erasures. We consider the locality constraints imposed by codes with two-level hierarchical locality and define maximally recoverable codes with data-local and local hierarchical locality. We derive certain properties related to their punctured codes and minimum distance. We give a procedure to construct hierarchical data-local MRCs from hierarchical local MRCs. We provide a construction of hierarchical local MRCs for all parameters. For the case of one global parity, we provide a different construction of hierarchical local MRC over a lower field size.
duneuro - A software toolbox for forward modeling in neuroscience

This paper describes duneuro, a software toolbox for forward modeling in neuroscience. Its purpose is to provide extendible and easy-to-use interfaces and enable a closer integration into existing analysis pipelines. It provides implementations of fitted and unfitted finite element methods and makes use of the Dune framework. The forward problems consist of the electroencephalography (EEG) and magnetoencephalography (MEG) forward problems. For the incorporation into existing analysis pipelines, Python and Matlab interfaces are provided. The practical use is demonstrated on a source analysis example of evoked potentials.
On the design of new classes of predefined-time stable systems: A time-scaling approach

A methodology, based on time-scale transformations and Lyapunov analysis, for designing autonomous and non-autonomous dynamical systems exhibiting the predefined-time stability property is provided in this paper. Thus, the current proposal allows characterizing a broad class of predefined-time stable systems, placing them under a common framework with existing methods which use time-varying gains based on time-base generators. What follows from this construction is that the bound of the convergence time for this class of systems is the lowest possible. Moreover, it is independent of the initial conditions and is set \textit{a priori} through a tuning parameter. This design procedure is a relevant contribution when compared to traditional fixed-time convergent algorithms since the current convergence time bounds are conservative. Finally, we analyze several existing and novel algorithms for autonomous and non-autonomous systems showing the effectiveness of the method.
Improving In-Network Computing in IoT Through Degeneracy

We present a novel way of considering in-network computing (INC), using ideas from statistical mechanics. We model the execution of a distributed computation with graphs called functional topologies, which allows us to provide a formal definition for degeneracy and redundancy in the context of INC. Degeneracy for INC is defined as the structural multiplicity of possible options available within the network to perform the same function with a given macroscopic property (e.g., delay). Two degenerate structures can partially overlap. Redundancy, on the other hand, does not allow overlapping between the functional graphs. We present an efficient algorithm to determine all these multiple options and compute both degeneracy and redundancy. Our results show that by exploiting the set of possible degenerate alternatives, we can significantly improve the successful computation rate of a symmetric function, while still being able to satisfy requirements such as delay or energy consumption.
Incentivising Privacy in Cryptocurrencies

Privacy was one of the key points mentioned in Nakamoto's Bitcoin whitepaper, and one of the selling points of Bitcoin in its early stages. In hindsight, however, de-anonymising Bitcoin users turned out to be more feasible than expected. Since then, privacy focused cryptocurrencies such as Zcash and Monero have surfaced. Both of these examples cannot be described as fully successful in their aims, as recent research has shown. Incentives are integral to the security of cryptocurrencies, so it is interesting to investigate whether they could also be aligned with privacy goals. A lack of privacy often results from low user counts, resulting in low anonymity sets. Could users be incentivised to use the privacy preserving implementations of the systems they use? Not only is Zcash much less used than Bitcoin (which it forked from), but most Zcash transactions are simply transparent transactions, rather than the (at least intended to be) privacy-preserving shielded transactions. This paper and poster briefly discusses how incentives could be incorporated into systems like cryptocurrencies with the aim of achieving privacy goals. We take Zcash as example, but the ideas discussed could apply to other privacy-focused cryptocurrencies. This work was presented as a poster at OPERANDI 2018, the poster can be found within this short document.
A C-DAG task model for scheduling complex real-time tasks on heterogeneous platforms: preemption matters

Recent commercial hardware platforms for embedded real-time systems feature heterogeneous processing units and computing accelerators on the same System-on-Chip. When designing complex real-time application for such architectures, the designer needs to make a number of difficult choices: on which processor should a certain task be implemented? Should a component be implemented in parallel or sequentially? These choices may have a great impact on feasibility, as the difference in the processor internal architectures impact on the tasks' execution time and preemption cost. To help the designer explore the wide space of design choices and tune the scheduling parameters, in this paper we propose a novel real-time application model, called C-DAG, specifically conceived for heterogeneous platforms. A C-DAG allows to specify alternative implementations of the same component of an application for different processing engines to be selected off-line, as well as conditional branches to model if-then-else statements to be selected at run-time. We also propose a schedulability analysis for the C-DAG model and a heuristic allocation algorithm so that all deadlines are respected. Our analysis takes into account the cost of preempting a task, which can be non-negligible on certain processors. We demonstrate the effectiveness of our approach on a large set of synthetic experiments by comparing with state of the art algorithms in the literature.
Automated Customized Bug-Benchmark Generation

We introduce Bug-Injector, a system that automatically creates benchmarks for customized evaluation of static analysis tools. We share a benchmark generated using Bug-Injector and illustrate its efficacy by using it to evaluate the recall of two leading open-source static analysis tools: Clang Static Analyzer and Infer. Bug-Injector works by inserting bugs based on bug templates into real-world host programs. It runs tests on the host program to collect dynamic traces, searches the traces for a point where the state satisfies the preconditions for some bug template, then modifies the host program to "inject" a bug based on that template. Injected bugs are used as test cases in a static analysis tool evaluation benchmark. Every test case is accompanied by a program input that exercises the injected bug. We have identified a broad range of requirements and desiderata for bug benchmarks; our approach generates on-demand test benchmarks that meet these requirements. It also allows us to create customized benchmarks suitable for evaluating tools for a specific use case (e.g., a given codebase and set of bug types). Our experimental evaluation demonstrates the suitability of our generated benchmark for evaluating static bug-detection tools and for comparing the performance of different tools.
On the Capabilities and Limitations of Reasoning for Natural Language Understanding

Recent systems for natural language understanding are strong at overcoming linguistic variability for lookup style reasoning. Yet, their accuracy drops dramatically as the number of reasoning steps increases. We present the first formal framework to study such empirical observations, addressing the ambiguity, redundancy, incompleteness, and inaccuracy that the use of language introduces when representing a hidden conceptual space. Our formal model uses two interrelated spaces: a conceptual meaning space that is unambiguous and complete but hidden, and a linguistic symbol space that captures a noisy grounding of the meaning space in the symbols or words of a language. We apply this framework to study the connectivity problem in undirected graphs---a core reasoning problem that forms the basis for more complex multi-hop reasoning. We show that it is indeed possible to construct a high-quality algorithm for detecting connectivity in the (latent) meaning graph, based on an observed noisy symbol graph, as long as the noise is below our quantified noise level and only a few hops are needed. On the other hand, we also prove an impossibility result: if a query requires a large number (specifically, logarithmic in the size of the meaning graph) of hops, no reasoning system operating over the symbol graph is likely to recover any useful property of the meaning graph. This highlights a fundamental barrier for a class of reasoning problems and systems, and suggests the need to limit the distance between the two spaces, rather than investing in multi-hop reasoning with "many" hops.
Construction and Analysis of Posterior Matching in Arbitrary Dimensions via Optimal Transport

The posterior matching scheme, for feedback encoding of a message point lying on the unit interval over memoryless channels, maximizes mutual information for an arbitrary number of channel uses. However, it in general does not always achieve any positive rate; so far, elaborate analyses have been required to show that it achieves any positive rate below capacity. More recent efforts have introduced a random "dither" shared by the encoder and decoder to the problem formulation, to simplify analyses and guarantee that the randomized scheme achieves any rate below capacity. Motivated by applications (e.g. human-computer interfaces) where (a) common randomness shared by the encoder and decoder may not be feasible and (b) the message point lies in a higher dimensional space, we focus here on the original formulation without common randomness, and use optimal transport theory to generalize the scheme for a message point in a higher dimensional space. By defining a stricter, almost sure, notion of message decoding, we use classical probabilistic techniques (e.g. change of measure and martingale convergence) to establish succinct necessary and sufficient conditions on when the message point can be recovered from infinite observations: Birkhoff ergodicity of a random process sequentially generated by the encoder. We also show a surprising "all or nothing" result: the same ergodicity condition is necessary and sufficient to achieve any rate below capacity. We provide applications of this message point framework in human-computer interfaces and multi-antenna communications.