Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Analyses Reveal Novel Aspects of ALS Pathogenesis

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease characterized by selective loss of motor neurons, muscle atrophy and paralysis. Mutations in the human VAMP-associated protein B (hVAPB) cause a heterogeneous group of motor neuron diseases including ALS8. Despite extensive research, the molecular mechanisms underlying ALS pathogenesis remain largely unknown. Genetic screens for key interactors of hVAPB activity in the intact nervous system, however, represent a fundamental approach towards understanding the in vivo function of hVAPB and its role in ALS pathogenesis. Targeted expression of the disease-causing allele leads to neurodegeneration and progressive decline in motor performance when expressed in the adult Drosophila, eye or in its entire nervous system, respectively. By using these two phenotypic readouts, we carried out a systematic survey of the Drosophila genome to identify modifiers of hVAPB-induced neurotoxicity. Modifiers cluster in a diverse array of biological functions including processes and genes that have been previously linked to hVAPB function, such as proteolysis and vesicular trafficking. In addition to established mechanisms, the screen identified endocytic trafficking and genes controlling proliferation and apoptosis as potent modifiers of ALS8-mediated defects. Surprisingly, the list of modifiers was mostly enriched for proteins linked to lipid droplet biogenesis and dynamics. Computational analysis reveals that most modifiers can be linked into a complex network of interacting genes, and that the human genes homologous to the Drosophila modifiers can be assembled into an interacting network largely overlapping with that in flies. Identity markers of the endocytic process were also found to abnormally accumulate in ALS patients, further supporting the relevance of the fly data for human biology. Collectively, these results not only lead to a better understanding of hVAPB function but also point to potentially relevant targets for therapeutic intervention.
Closure of autobiographical memories: The effects of written recounting from first- or third-person visual perspective

Autobiographical memories are recalled with varying degrees of psychological closure. Closure is a subjective assessment of how far a remembered experience feels resolved, and it has been suggested that one predictor of closure is the amount of emotional detail in the memory. Study 1 examined which aspect of emotional detail is important for closure, and showed that open and closed negative memories were distinguished by ratings of emotion evoked during recall, not by remembered emotion from the time of the event. The recall of open memories was accompanied by more intense, more negative, and less positive emotion than the recall of closed memories. Biased retelling of memories has been shown to influence closure and on the basis of evidence that third-person recall serves a distancing function, Study 2 examined whether instructions to repeatedly recount an open memory from a third-person perspective would increase closure compared with a single or repeated recounting from a first-person perspective. While repeated third-person recounting had the greatest influence on closure, there were also increases in the first-person recounting groups. The results suggest that closure can be increased by reporting memories in written narrative form, particularly if repeatedly expressed from the third-person perspective.
Digital product innovation within four classes of innovation networks

The increased digitization of organizational processes and products poses new challenges for understanding product innovation. It also opens new horizons for information systems research. We analyse how ongoing pervasive digitization of product innovation reshapes knowledge creation and sharing in innovation networks. We argue that advances in digital technologies (1) increase innovation network connectivity by reducing communication costs and increasing its reach and scope and (2) increase the speed and scope of digital convergence, which increases network knowledge heterogeneity and need for integration. These developments, in turn, stretch existing innovation networks by redistributing control and increasing the demand for knowledge coordination across time and space presenting novel challenges for knowledge creation, assimilation and integration. Based on this foundation, we distinguish four types of emerging innovation networks supported by digitalization: (1) project innovation networks; (2) clan innovation networks; (3) federated innovation networks; and (4) anarchic innovation networks. Each network involves different cognitive and social translations – or ways of identifying, sharing and assimilating knowledge. We describe the role of five novel properties of digital infrastructures in supporting each type of innovation network: representational flexibility, semantic coherence, temporal and spatial traceability, knowledge brokering and linguistic calibration. We identify several implications for future innovation research. In particular, we focus on the emergence of anarchic network forms that follow full‐fledged digital convergence founded on richer innovation ontologies and epistemologies calling to critically re‐examine the nature and impact of modularization for innovation.
Computational RNA Structure Prediction

The view of RNA as simple information transfer molecule has been continuously challenged since the discov- ery of ribozymes, a class of RNA molecules with enzyme-like function. Moreover, the recent discovery of tiny RNA molecules such asRNAs and small interfering RNA, is transforming our thinking about how gene expression is regu- lated. Thus, RNA molecules are now known to carry a large repertory of biological functions within cells including in- formation transfer, enzymatic catalysis and regulation of cellular processes. Similar to proteins, functional RNA mole- cules fold into their native three-dimensional (3D) conformation, which is essential for performing their biological activ- ity. Despite advances in understanding the folding and unfolding of RNA, our knowledge of the atomic mechanism by which RNA molecules adopt their biological active structure is still limited. In this review, we outline the general princi- ples that govern RNA structure and describe the databases and algorithms for analyzing and predicting RNA secondary and tertiary structure. Finally, we assess the impact of the current coverage of the RNA structural space on comparative modeling RNA structures.
Chaperones Ameliorate Beta Cell Dysfunction Associated with Human Islet Amyloid Polypeptide Overexpression

In type 2 diabetes, beta-cell dysfunction is thought to be due to several causes, one being the formation of toxic protein aggregates called islet amyloid, formed by accumulations of misfolded human islet amyloid polypeptide (hIAPP). The process of hIAPP misfolding and aggregation is one of the factors that may activate the unfolded protein response (UPR), perturbing endoplasmic reticulum (ER) homeostasis. Molecular chaperones have been described to be important in regulating ER response to ER stress. In the present work, we evaluate the role of chaperones in a stressed cellular model of hIAPP overexpression. A rat pancreatic beta-cell line expressing hIAPP exposed to thapsigargin or treated with high glucose and palmitic acid, both of which are known ER stress inducers, showed an increase in ER stress genes when compared to INS1E cells expressing rat IAPP or INS1E control cells. Treatment with molecular chaperone glucose-regulated protein 78 kDa (GRP78, also known as BiP) or protein disulfite isomerase (PDI), and chemical chaperones taurine-conjugated ursodeoxycholic acid (TUDCA) or 4-phenylbutyrate (PBA), alleviated ER stress and increased insulin secretion in hIAPP-expressing cells. Our results suggest that the overexpression of hIAPP induces a stronger response of ER stress markers. Moreover, endogenous and chemical chaperones are able to ameliorate induced ER stress and increase insulin secretion, suggesting that improving chaperone capacity can play an important role in improving beta-cell function in type 2 diabetes.
Impact of Computerized Prescriber Order Entry on the Incidence of Adverse Drug Events in Pediatric Inpatients

OBJECTIVES. This study was conducted to determine the impact of a computerized physician order entry system with substantial decision support on the incidence and types of adverse drug events in hospitalized children. METHODS. A prospective methodology was used for the collection of adverse drug events and potential adverse drug events from all patients admitted to the pediatric intensive care and general pediatric units over a 6-month period. Data from a previous adverse drug event study of the same patient care units before computerized physician order entry implementation were used for comparison purposes. RESULTS. Data for 1197 admissions before the introduction of computerized physician order entry were compared with 1210 admissions collected after computerized physician order entry implementation. After computerized physician order entry implementation, it was observed that the number of preventable adverse drug events (46 vs 26) and potential adverse drug events (94 vs 35) was reduced. Reductions in overall errors, dispensing errors, and drug-choice errors were associated with computerized physician order entry. There were reductions in significant events, as well as those events rated as serious or life threatening, after the implementation of computerized physician order entry. Some types of adverse drug events continued to persist, specifically underdosing of analgesics. There were no differences in length of stay or patient disposition between preventable adverse drug events and potential adverse drug events in either study period. CONCLUSIONS. This study demonstrated that a computerized physician order entry system with substantive decision support was associated with a reduction in both adverse drug events and potential adverse drug events in the inpatient pediatric population. Additional system refinements will be necessary to affect remaining adverse drug events. Preventable events did not predict excess length of stay and instead may represent a sign, rather than a cause, of more complicated illness.
Phase Retrieval for Radar Waveform Optimization

An important problem in radar waveform optimization is the synthesis of discrete time constant modulus signals from Fourier magnitude data. Iterative algorithms for solving this problem have been proposed in the literature, but the algorithms are only applicable in limited cases, and the convergent behavior of these algorithms has not been established. We connect waveform design to the well-studied problem of phase retrieval. This is useful for explaining the success of the proposed iterative methods. We generalize and extend the existing algorithms to handle the case in which the dimensions of the time domain waveform and the frequency domain data are unequal, and we provide a convergence analysis. We also relate the phase retrieval problem to the problem of synthesizing discrete time constant modulus signals from power spectral density (PSD) data, which is different and more appropriate for the waveform design problem. We compare the iterative methods to direct search gradient methods for both problems, and establish that the proposed algorithms can provide comparable performance with reduced computational complexity.
Optimal integrated control and scheduling of networked control systems with communication constraints: application to a car suspension system

This brief addresses the problem of the optimal control and scheduling of networked control systems over limited bandwidth deterministic networks. Multivariable linear systems subject to communication constraints are modeled in the mixed logical dynamical (MLD) framework. The translation of the MLD model into the mixed integer quadratic programming (MIQP) formulation is described. This formulation allows the solving of the optimal control and scheduling problem using efficient branch and bound algorithms. Advantages and drawbacks of online and offline scheduling algorithms are discussed. Based on this discussion, a computationally efficient online scheduling algorithm, which can be seen as a compromise, is presented and its performance is evaluated. Finally, this algorithm, called optimal pointer placement (OPP) scheduling algorithm, is applied to the control and scheduling of a car suspension system.
Pesticide Exposure and Risk of Rheumatoid Arthritis among Licensed Male Pesticide Applicators in the Agricultural Health Study

Background: The occupation of farming has been associated with rheumatoid arthritis (RA); pesticides may account for this association, but there are few studies. Objectives: We investigated associations between RA and use of pesticides in the Agricultural Health Study. Methods: The study sample was drawn from male pesticide applicators enrolled in 1993–1997 who provided questionnaire data at baseline and at least once during follow-up (over a median 18 y; interquartile range 16–19). Incident RA cases (n=220), confirmed by physicians or by self-reported use of disease-modifying antirheumatic drugs, were compared with noncases (n=26,134) who did not report RA. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression, adjusting for enrollment age, state, smoking pack-years, and education. We evaluated the association of RA with the use of 46 pesticides and across 4 levels (never use and tertiles) of lifetime days of use for 16 pesticides with OR≥1.2 for ever use. Results: Incident RA was associated with ever use of fonofos (OR = 1.70; 95% CI: 1.22, 2.37), carbaryl (OR = 1.51; 95% CI: 1.03, 2.23), and chlorimuron ethyl (OR = 1.45; 95% CI: 1.01, 2.07) compared with never use. Statistically significant exposure–response trends in association with RA were observed for lifetime days of use of atrazine [ORtertile3= 1.62 (95% CI: 1.09, 2.40); ptrend=0.01] and toxaphene [ORtertile3= 2.42 (95% CI: 1.03, 5.68); ptrend=0.02]. Exposure–response was nonlinear for fonofos [ORtertile1= 2.27 (95% CI: 1.44, 3.57); ORtertile2= 0.98 (95% CI: 0.54, 1.80); ORtertile3= 2.10 (95% CI: 1.32, 3.36); ptrend=0.005] and suggestive for carbaryl (ptrend=0.053). Conclusions: Our results provide novel evidence of associations between exposure to some pesticides and RA in male farmers. https://doi.org/10.1289/EHP1013
Voronoi-Based Curvature and Feature Estimation from Point Clouds

We present an efficient and robust method for extracting curvature information, sharp features, and normal directions of a piecewise smooth surface from its point cloud sampling in a unified framework. Our method is integral in nature and uses convolved covariance matrices of Voronoi cells of the point cloud which makes it provably robust in the presence of noise. We show that these matrices contain information related to curvature in the smooth parts of the surface, and information about the directions and angles of sharp edges around the features of a piecewise-smooth surface. Our method is applicable in both two and three dimensions, and can be easily parallelized, making it possible to process arbitrarily large point clouds, which was a challenge for Voronoi-based methods. In addition, we describe a Monte-Carlo version of our method, which is applicable in any dimension. We illustrate the correctness of both principal curvature information and feature extraction in the presence of varying levels of noise and sampling density on a variety of models. As a sample application, we use our feature detection method to segment point cloud samplings of piecewise-smooth surfaces.
Bipolar radiofrequency ablation of benign thyroid nodules using a multiple overlapping shot technique in a 3-month follow-up

Abstract Purpose The aim of this study was to evaluate the decrease of benign thyroid nodules after bipolar radiofrequency ablation (RFA) in a 3-month follow-up using a multiple overlapping shot technique (‘MOST’). Methods A total of 18 patients with 20 symptomatic benign thyroid nodules (17 cold nodules, 3 hyperfunctioning nodules) were treated in one single session by bipolar RFA. Bipolar ablation was performed using MOST. The nodule volumes were measured prior to ablation and 3 months after the procedure using ultrasound. The population consisted of either solid (>80% solid tissue within the volume of interest), complex, or cystic nodules (<20% solid tissue within the volume of interest). Results Bipolar RFA resulted in a highly significant (p < 0.0001) decrease of nodule volume (ΔV), median 5.3 mL (range 0.13–43.1 mL), corresponding to a relative reduction in mean of 56 ± 17.9%. Median initial volume was 8 mL (range 0.48–62 mL); 3 months after ablation a median volume of 2.3 mL (range 0.3–32 mL) was measured. Nodule growth ≥50% occurred in 70% (14 nodules). At the follow-up no complications such as infections, persisting pain, nerve injuries or immunogen stimulation occurred. Patients with cold nodules (15) remained euthyroid, with hyperfunctioning nodules either euthyroid (2) or latent hypofunctional (1). Conclusion The use of bipolar RFA is an effective, safe and suitable thermoablative technique to treat benign thyroid nodules. Combined with the multiple overlapping shot technique it allows sufficient ablation.
Efficient language model lookahead through polymorphic linguistic context assignment

In this study, we examine how fast decoding of conversational speech with large vocabularies profits from efficient use of linguistic information, i.e. language models and grammars. Based on a re-entrant single pronunciation prefix tree, we use the concept of linguistic context polymorphism to achieve an early incorporation of language model information. This approach allows us to use all available language model information in a one-pass decoder, using the same engine to decode with statistical n-gram language models as well as context free grammars or re-scoring of lattices in an efficient way. We compare this approach to our previous decoder, which needed three passes to incorporate all available information. The results on a very large vocabulary task show that the search can be speeded up by almost a factor of three, without introducing additional search errors. On all examined tasks, we observed significant improvements by using an exact language model lookahead over usual bigram lookahead strategies, even for very hard tasks with unmatched conditions, without introducing extra memory overhead.
Improved call graph comparison using simulated annealing

The amount of suspicious binary executables submitted to Anti-Virus (AV) companies are in the order of tens of thousands per day. Current hash-based signature methods are easy to deceive and are inefficient for identifying known malware that have undergone minor changes. Examining malware executables using their call graphs view is a suitable approach for overcoming the weaknesses of hash-based signatures. Unfortunately, many operations on graphs are of high computational complexity. One of these is the Graph Edit Distance (GED) between pairs of graphs, which seems a natural choice for static comparison of malware. We demonstrate how Simulated Annealing can be used to approximate the graph edit distance of call graphs, while outperforming previous approaches both in execution time and solution quality. Additionally, we experiment with opcode mnemonic vectors to reduce the problem size and examine how Simulated Annealing is affected.
Cell Therapy for Modification of the Myocardial Electrophysiological Substrate

Background— Traditional antiarrhythmic pharmacological therapies are limited by their global cardiac action, low efficacy, and significant proarrhythmic effects. We present a novel approach for the modification of the myocardial electrophysiological substrate using cell grafts genetically engineered to express specific ionic channels. Methods and Results— To test the aforementioned concept, we performed ex vivo, in vivo, and computer simulation studies to determine the ability of fibroblasts transfected to express the voltage-sensitive potassium channel Kv1.3 to modify the local myocardial excitable properties. Coculturing of the transfected fibroblasts with neonatal rat ventricular myocyte cultures resulted in a significant reduction (68%) in the spontaneous beating frequency of the cultures compared with baseline values and cocultures seeded with naive fibroblasts. In vivo grafting of the transfected fibroblasts in the rat ventricular myocardium significantly prolonged the local effective refractory period from an initial value of 84±8 ms (cycle length, 200 ms) to 154±13 ms (P<0.01). Margatoxin partially reversed this effect (effective refractory period, 117±8 ms; P<0.01). In contrast, effective refractory period did not change in nontransplanted sites (86±7 ms) and was only mildly increased in the animals injected with wild-type fibroblasts (73±5 to 88±4 ms; P<0.05). Similar effective refractory period prolongation also was found during slower pacing drives (cycle length, 350 to 500 ms) after transplantation of the potassium channels expressing fibroblasts (Kv1.3 and Kir2.1) in pigs. Computer modeling studies confirmed the in vivo results. Conclusions— Genetically engineered cell grafts, transfected to express potassium channels, can couple with host cardiomyocytes and alter the local myocardial electrophysiological properties by reducing cardiac automaticity and prolonging refractoriness.
Stacked Conditional Random Fields Exploiting Structural Consistencies

Conditional Random Fields (CRF) are popular methods for labeling unstructured or textual data. Like many machine learning approaches these undirected graphical models assume the instances to be independently distributed. However, in real world applications data is grouped in a natural way, e.g., by its creation context. The instances in each group often share additional consistencies in the structure of their information. This paper proposes a domain-independent method for exploiting these consistencies by combining two CRFs in a stacked learning framework. The approach incorporates three successive steps of inference: First, an initial CRF processes single instances as usual. Next, we apply rule learning collectively on all labeled outputs of one context to acquire descriptions of its specific properties. Finally, we utilize these descriptions as dynamic and high quality features in an additional (stacked) CRF. The presented approach is evaluated with a real-world dataset for the segmentation of references and achieves a significant reduction of the labeling error.
A new minimax theorem and a perturbed James's theorem

The main result of this paper is a sufficient condition for the minimax relation to hold for the canonical bilinear form on X × Y, where X is a nonempty convex subset of a real locally convex space and Y is a nonempty convex subset of its dual. Using the known “converse minimax theorem”, this result leads easily to a nonlinear generalisation of James's (“sup”) theorem. We give a brief discussion of the connections with the “sup-limsup theorem” and, in the appendix to the paper, we give a simple, direct proof (using Goldstine's theorem) of the converse minimax theorem referred to above, valid for the special case of a normed space.