Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrating Murine Gene Expression Studies to Understand Obstructive Lung Disease Due to Chronic Inhaled Endotoxin

Rationale Endotoxin is a near ubiquitous environmental exposure that that has been associated with both asthma and chronic obstructive pulmonary disease (COPD). These obstructive lung diseases have a complex pathophysiology, making them difficult to study comprehensively in the context of endotoxin. Genome-wide gene expression studies have been used to identify a molecular snapshot of the response to environmental exposures. Identification of differentially expressed genes shared across all published murine models of chronic inhaled endotoxin will provide insight into the biology underlying endotoxin-associated lung disease. Methods We identified three published murine models with gene expression profiling after repeated low-dose inhaled endotoxin. All array data from these experiments were re-analyzed, annotated consistently, and tested for shared genes found to be differentially expressed. Additional functional comparison was conducted by testing for significant enrichment of differentially expressed genes in known pathways. The importance of this gene signature in smoking-related lung disease was assessed using hierarchical clustering in an independent experiment where mice were exposed to endotoxin, smoke, and endotoxin plus smoke. Results A 101-gene signature was detected in three murine models, more than expected by chance. The three model systems exhibit additional similarity beyond shared genes when compared at the pathway level, with increasing enrichment of inflammatory pathways associated with longer duration of endotoxin exposure. Genes and pathways important in both asthma and COPD were shared across all endotoxin models. Mice exposed to endotoxin, smoke, and smoke plus endotoxin were accurately classified with the endotoxin gene signature. Conclusions Despite the differences in laboratory, duration of exposure, and strain of mouse used in three experimental models of chronic inhaled endotoxin, surprising similarities in gene expression were observed. The endotoxin component of tobacco smoke may play an important role in disease development.
DNMT3A R882 Mutations Predict a Poor Prognosis in AML

AbstractDNA (cytosine-5)-methyltransferase 3 alpha (DNMT3A) mutations were widely believed to be independently associated with inferior prognosis in acute myeloid leukemia (AML) patients. As dominant missense alterations in DNMT3A mutations, R882 mutations cause the focal hypomethylation phenotype. However, there remains debate on the influence of R882 mutations on AML prognosis. Thus, this meta-analysis aimed at further illustrating the prognostic power of DNMT3A R882 mutations in AML patients.Eligible studies were identified from 5 databases containing PubMed, Embase, Web of Science, Clinical Trials, and the Cochrane Library (up to October 25, 2015). Effects (hazard ratios [HRs] with 95% confidence interval [CI]) of relapse-free survival (RFS) and overall survival (OS) were pooled to estimate the prognostic power of mutant DNMT3A R882 in overall patients and subgroups of AML patients.Eight competent studies with 4474 AML patients including 694 with DNMT3A R882 mutations were included. AML patients with DNMT3A R882 mutations showed significant shorter RFS (HR = 1.40, 95% CI = 1.24–1.59, P < 0.001) and OS (HR = 1.47, 95% CI = 1.17–1.86, P = 0.001) in the overall population. DNMT3A R882 mutations predicted worse RFS and OS among the subgroups of patients under age 60 (RFS: HR = 1.44, 95% CI = 1.25–1.66, P < 0.001; OS: HR = 1.48, 95% CI = 1.15–1.90, P = 0.002), over age 60 (RFS: HR = 2.03, 95% CI = 1.40–2.93, P < 0.001; OS: HR = 1.85, 95% CI = 1.36–2.53, P < 0.001), cytogenetically normal (CN)-AML (RFS: HR = 1.52, 95% CI = 1.26–1.83, P < 0.001; OS: HR = 1.67, 95% CI = 1.16–2.41, P = 0.006), and non-CN-AML (RFS: HR = 1.96, 95% CI = 1.20–3.21, P = 0.006; OS: HR = 2.51, 95% CI = 1.52–4.15, P = 0.0038). DNMT3A R882 mutations possessed significant unfavorable prognostic influence on RFS and OS in AML patients.
Learning a Forward Model of a Reflex

We develop a systems theoretical treatment of a behavioural system that interacts with its environment in a closed loop situation such that its motor actions influence its sensor inputs. The simplest form of a feedback is a reflex. Reflexes occur always "too late"; i.e., only after a (unpleasant, painful, dangerous) reflex-eliciting sensor event has occurred. This defines an objective problem which can be solved if another sensor input exists which can predict the primary reflex and can generate an earlier reaction. In contrast to previous approaches, our linear learning algorithm allows for an analytical proof that this system learns to apply feedforward control with the result that slow feedback loops are replaced by their equivalent feed-forward controller creating a forward model. In other words, learning turns the reactive system into a pro-active system. By means of a robot implementation we demonstrate the applicability of the theoretical results which can be used in a variety of different areas in physics and engineering.
Modeling Attractiveness and Multiple Clicks in Sponsored Search Results

Click models are an important tool for leveraging user feedback, and are used by commercial search engines for surfacing relevant search results. However, existing click models are lacking in two aspects. First, they do not share information across search results when computing attractiveness. Second, they assume that users interact with the search results sequentially. Based on our analysis of the click logs of a commercial search engine, we observe that the sequential scan assumption does not always hold, especially for sponsored search results. To overcome the above two limitations, we propose a new click model. Our key insight is that sharing information across search results helps in identifying important words or key-phrases which can then be used to accurately compute attractiveness of a search result. Furthermore, we argue that the click probability of a position as well as its attractiveness changes during a user session and depends on the user's past click experience. Our model seamlessly incorporates the effect of externalities (quality of other search results displayed in response to a user query), user fatigue, as well as pre and post-click relevance of a sponsored search result. We propose an efficient one-pass inference scheme and empirically evaluate the performance of our model via extensive experiments using the click logs of a large commercial search engine.
Cogen in six lines

We have designed and implemented a program-generator generator (PGG) for an untyped higher-order functional programming language. The program generators perform continuation-based multi-level offline specialization and thus combine the most powerful and general offline partial evaluation techniques. The correctness of the PGG is ensured by deriving it from a multi-level specialize. Our PGG is extremely simple to implement due to the use of multi-level techniques and higher-order abstract syntax.
Towards an Extrinsic Evaluation of Referring Expressions in Situated Dialogs

In the field of referring expression generation, while in the static domain both intrinsic and extrinsic evaluations have been considered, extrinsic evaluation in the dynamic domain, such as in a situated collaborative dialog, has not been discussed in depth. In a dynamic domain, a crucial problem is that referring expressions do not make sense without an appropriate preceding dialog context. It is unrealistic for an evaluation to simply show a human evaluator the whole period from the beginning of a dialog up to the time point at which a referring expression is used. Hence, to make evaluation feasible it is indispensable to determine an appropriate shorter context. In order to investigate the context necessary to understand a referring expression in a situated collaborative dialog, we carried out an experiment with 33 evaluators and a Japanese referring expression corpus. The results contribute to finding the proper contexts for extrinsic evalution in dynamic domains.
Initial Response to Chemotherapy, Not Delay in Diagnosis, Predicts Overall Survival in Inflammatory Breast Cancer Cases

Objectives:To determine whether chemotherapy response and diagnostic delay affect overall survival (OS) of classic inflammatory breast cancer (IBC) cases receiving chemotherapy as initial treatment and to determine whether OS differs between classic and “atypical” IBC cases. Methods:This is a prospective cohort study of 155 patients enrolled in the IBC Registry. “Classic” IBC cases met AJCC or SEER case definitions. “Atypical” IBC cases exhibited classic features but involved <1/2 breast without documented dermal lymphatic invasion. Variables included OS (years from initial chemotherapy treatment until death or last contact), chemotherapy response (complete, partial, or none), diagnostic delay (days from first medical contact for signs/symptoms of abnormal breast to definitive pathologic IBC diagnosis), age at diagnosis (y), and triple-negative status (yes or no). OS curves stratified by individual predictors were estimated and compared using Kaplan-Meier methods and log-rank tests. Associations between OS and predictors were examined collectively using Cox proportional hazards regression. Results:Classic IBC cases with complete, partial, or no response had respective median (95% confidence interval [CI]) OS times of 10.30 (6.78, +), 6.27 (4.42, +), and 2.86 (1.11, 11.42) years (P=0.0072). Chemotherapy response was significantly associated with OS after controlling for covariates (P=0.003). Women not responding to chemotherapy had a significantly higher hazard of death compared with women with complete (hazard ratio [HR]=5.76; 95% CI, 2.09-15.84) or partial (HR=3.40; 95% CI, 1.27-9.10) response. Diagnostic delay was not significantly associated with OS (HR=1.003; 95% CI, 0.999-1.007). OS did not differ significantly between classic and “atypical” IBC cases (P=0.60). Conclusions:Response to standard IBC chemotherapy is a dominant prognostic factor in determining patient outcomes. In our study, with limited statistical power, delay in diagnosis defined as >60 days from the time of first physician contact did not seem to affect patient outcomes. Data support similarities between classic and “atypical” IBC.
Proving that non-blocking algorithms don't block

A concurrent data-structure implementation is considered non-blocking if it meets one of three following liveness criteria: wait-freedom, lock-freedom, or obstruction-freedom. Developers of non-blocking algorithms aim to meet these criteria. However, to date their proofs for non-trivial algorithms have been only manual pencil-and-paper semi-formal proofs. This paper proposes the first fully automatic tool that allows developers to ensure that their algorithms are indeed non-blocking. Our tool uses rely-guarantee reasoning while overcoming the technical challenge of sound reasoning in the presence of interdependent liveness properties.
Chronic Blockade of Glutamate Receptors Enhances Presynaptic Release and Downregulates the Interaction between Synaptophysin-Synaptobrevin–Vesicle-Associated Membrane Protein 2

During development of neuronal circuits, presynaptic and postsynaptic functions are adjusted in concert, to optimize interneuronal signaling. We have investigated whether activation of glutamate receptors affects presynaptic function during synapse formation, when constitutive synaptic vesicle recycling is downregulated. Using primary cultures of hippocampal neurons as a model system, we have found that chronic exposure to both NMDA and non-NMDA glutamate receptor blockers during synaptogenesis produces an increase in miniature EPSC (mEPSC) frequency, with no significant changes in mEPSC amplitude or in the number of synapses. Enhanced synaptic vesicle recycling, selectively in glutamatergic nerve terminals, was confirmed by the increased uptake of antibodies directed against the lumenal domain of synaptotagmin. No increased uptake was detected in neuronal cultures grown in the chronic presence of TTX, speaking against an indirect effect caused by decreased electrical activity. Enhanced mEPSC frequency correlated with a reduction of synaptophysin-synaptobrevin–vesicle-associated membrane protein 2 (VAMP2) complexes detectable by immunoprecipitation. Intracellular perfusion with a peptide that inhibits the binding of synaptophysin to synaptobrevin–VAMP2 induced a remarkable increase of mEPSC frequency in control but not in glutamate receptor blocker-treated neurons. These findings suggest that activation of glutamate receptors plays a role in the downregulation of the basal rate of synaptic vesicle recycling that accompanies synapse formation. They also suggest that one of the mechanisms through which this downregulation is achieved is an increased interaction of synaptophysin with synaptobrevin–VAMP2.
Early Detection of Diabetes from Health Claims

Early detection of Type 2 diabetes poses challenges to both the machine learning and medical communities. Current clinical practices focus on narrow patientspecific courses of action whereas electronic health records and insurance claims data give us the ability to generalize that knowledge across large sets of populations. Advances in population health care have the potential to improve the quality of health of the patient as well as decrease future medical costs, at least in part by prevention of long-term complications accruing during undiagnosed diabetes. Based on patient data from insurance claims, we present the results of our initial experiments into identification of patients who will develop diabetes. We motivate future work in this area by considering the need to develop machine learning algorithms that can effectively deal with the depth and the variety of the data.
A Visual Servoing-Based Method for ProCam Systems Calibration

Projector-camera systems are currently used in a wide field of applications, such as 3D reconstruction and augmented reality, and can provide accurate measurements, depending on the configuration and calibration. Frequently, the calibration task is divided into two steps: camera calibration followed by projector calibration. The latter still poses certain problems that are not easy to solve, such as the difficulty in obtaining a set of 2D–3D points to compute the projection matrix between the projector and the world. Existing methods are either not sufficiently accurate or not flexible. We propose an easy and automatic method to calibrate such systems that consists in projecting a calibration pattern and superimposing it automatically on a known printed pattern. The projected pattern is provided by a virtual camera observing a virtual pattern in an OpenGL model. The projector displays what the virtual camera visualizes. Thus, the projected pattern can be controlled and superimposed on the printed one with the aid of visual servoing. Our experimental results compare favorably with those of other methods considering both usability and accuracy.
Anisotropic Gold Nanostructures: Optimization via in Silico Modeling for Hyperthermia

Protein- and peptide-based manufacturing of self-assembled supramolecular functional materials has been a formidable challenge for biomedical applications, being complex in structure and immunogenic in nature. In this context, self-assembly of short amino acid sequences as simplified building blocks to design metal–biomolecule frameworks (MBioFs) is an emerging field of research. Here, we report a facile, bioinspired route of anisotropic nanostructure synthesis using gold binding peptides (10–15mers) secreted by cancer cells. The bioinformatics tool i-TASSER predicts the effect of amino acid sequences on metal binding sites and the secondary structures of the respective peptide sequence. Electron microscopy, X-ray, infrared, and Raman spectroscopy validated the versatile anisotropic gold nanostructures and the metal–bioorganic nature of this biomineralization. We studied the influence of precursor salt, pH, and peptide concentration on the evolution of nanoleaf, nanoflower, nanofiber, and dendrimer-like a.
Security Proofs for Participation Privacy, Receipt-Freeness and Ballot Privacy for the Helios Voting Scheme

The Helios voting scheme is well studied including formal proofs for verifiability and ballot privacy. However, depending on its version, the scheme provides either participation privacy (hiding who participated in the election) or verifiability against malicious bulletin board (preventing election manipulation by ballot stuffing), but not both at the same time. It also does not provide receipt-freeness, thus enabling vote buying by letting the voters construct receipts proving how they voted. Recently, an extension to Helios, further referred to as KTV-Helios, has been proposed that claims to provide these additional security properties. However, the authors of KTV-Helios did not prove their claims. Our contribution is to provide formal definitions for participation privacy and receipt-freeness that we applied to KTV-Helios. In order to evaluate the fulfillment of participation privacy and receipt-freeness, we furthermore applied the existing definition of ballot privacy, which was also used for evaluating the security of Helios, in order to show that ballot privacy also holds for KTV-Helios.
Molecular characterization of the humoral responses to Cryptococcus neoformans infection and glucuronoxylomannan-tetanus toxoid conjugate immunization

The molecular characteristics of the humoral immune response to a serotype A Cryptococcus neoformans infection were compared with the response elicited by a cryptococcal glucuronoxylomannan-tetanus toxoid (GXM-TT) conjugate. Anticryptococcal monoclonal antibodies (mAbs) isolated from both responses have previously been shown to recognize the same antigenic determinant of cryptococcal GXM. Southern blot and sequence analyses indicate that the hybridomas isolated from each response arose from only a few precursor B cells. All the mAbs generated from the infected and GXM-TT conjugate-immunized mice utilize the same VH7183 family member: JH2/JH4, v kappa 5.1, and J kappa 1; mAbs generated by different B cells had complementarity-determining region 3's (CDR3s) composed of seven amino acids with a common sequence motif. Thus, the molecular analysis of these anticryptococcal mAb- producing hybridomas indicated that the response to both cryptococcal infection and conjugate immunization was oligoclonal and highly restricted with regard to immunoglobulin gene utilization. The GXM-TT conjugate primarily stimulated isotype switching and clonal proliferation, and did not result in hybridomas expressing additional immunoglobulin repertoires. The mAbs from both responses had a number of replacement mutations at the 5' end of CDR2 that appear to be the result of antigen-driven selection. Somatic mutation also resulted in altered epitope specificity for one mAb, 13F1. Passive administration of representative mAbs from different clones generated in response to the GXM-TT conjugate prolonged survival of lethally infected mice.
Looking ahead: how field trials can work in iterative and exploratory design of ubicomp systems

We investigate in which forms field trials are a workable model as part of an exploratory design process for sporadic, mobile, non-work settings. A major concern of evaluating ubicomp systems is to study how practices and context of use emerge and develop over time when new technology is introduced. To introduce a sophisticated version of our own prototype in the course of an iterative design process, we conducted a public field trial of the system---a new platform for mobile democratic discussions in municipal planning---that we distributed via the Android Market. However, it turned out to be surprisingly difficult to evaluate our design in a setting that stretches over time, place, and without a preselected set of users. Analyzing our difficulties, we develop a general model for methods studying ubicomp systems. On the basis of this model, we characterize an openly interactive approach to field trials in order to look ahead rather than back.
Automatic Design of Area-Efficient Configurable ASIC Cores

Reconfigurable hardware has been shown to provide an efficient compromise between the flexibility of software and the performance of hardware. However, even coarse-grained reconfigurable architectures target the general case and miss optimization opportunities present if characteristics of the desired application set are known. Restricting the structure to support a class or a specific set of algorithms can increase efficiency while still providing flexibility within that set. By generating a custom array for a given computation domain, we explore the design space between an ASIC and an FPGA. However, the manual creation of these customized reprogrammable architectures would be a labor-intensive process, leading to high design costs. Instead, we propose automatic reconfigurable architecture generation specialized to given application sets. This paper discusses configurable ASIC (cASIC) architecture generation that creates hardware on average up to 12.3x smaller than an FPGA solution with embedded multipliers and 2.2x smaller than a standard cell implementation of individual circuits
Small-scale reconfigurability for improved performance and double-precision in graphics hardware

We explore the application of small-scale reconfigurability (SSR) to graphics hardware. SSR is an architectural technique wherein functionality common to multiple subunits is reused rather than replicated, yielding high-performance reconfigurable hardware with reduced area requirements (Vijay Kumar and Lach “Designing, scheduling, and allocating flexible arithmetic components”, in Proceedings of the International Conference on Field Programmable Logic and Applications, 2003). We show that SSR can be used effectively in programmable graphics architectures to allow double-precision computation without affecting the performance of single-precision calculations and to increase fragment shader performance with a minimal impact on chip area.