Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance of hybrid methods for large‐scale unconstrained optimization as applied to models of proteins

Energy minimization plays an important role in structure determination and analysis of proteins, peptides, and other organic molecules; therefore, development of efficient minimization algorithms is important. Recently, Morales and Nocedal developed hybrid methods for large‐scale unconstrained optimization that interlace iterations of the limited‐memory BFGS method (L‐BFGS) and the Hessian‐free Newton method (Computat Opt Appl 2002, 21, 143–154). We test the performance of this approach as compared to those of the L‐BFGS algorithm of Liu and Nocedal and the truncated Newton (TN) with automatic preconditioner of Nash, as applied to the protein bovine pancreatic trypsin inhibitor (BPTI) and a loop of the protein ribonuclease A. These systems are described by the all‐atom AMBER force field with a dielectric constant ϵ = 1 and a distance‐dependent dielectric function ϵ = 2r, where r is the distance between two atoms. It is shown that for the optimal parameters the hybrid approach is typically two times more efficient in terms of CPU time and function/gradient calculations than the two other methods. The advantage of the hybrid approach increases as the electrostatic interactions become stronger, that is, in going from ϵ = 2r to ϵ = 1, which leads to a more rugged and probably more nonlinear potential energy surface. However, no general rule that defines the optimal parameters has been found and their determination requires a relatively large number of trial‐and‐error calculations for each problem. © 2003 Wiley Periodicals, Inc. J Comput Chem 24: 1222–1231, 2003
Tracing Carbon Sources through Aquatic and Terrestrial Food Webs Using Amino Acid Stable Isotope Fingerprinting

Tracing the origin of nutrients is a fundamental goal of food web research but methodological issues associated with current research techniques such as using stable isotope ratios of bulk tissue can lead to confounding results. We investigated whether naturally occurring δ13C patterns among amino acids (δ13CAA) could distinguish between multiple aquatic and terrestrial primary production sources. We found that δ13CAA patterns in contrast to bulk δ13C values distinguished between carbon derived from algae, seagrass, terrestrial plants, bacteria and fungi. Furthermore, we showed for two aquatic producers that their δ13CAA patterns were largely unaffected by different environmental conditions despite substantial shifts in bulk δ13C values. The potential of assessing the major carbon sources at the base of the food web was demonstrated for freshwater, pelagic, and estuarine consumers; consumer δ13C patterns of essential amino acids largely matched those of the dominant primary producers in each system. Since amino acids make up about half of organismal carbon, source diagnostic isotope fingerprints can be used as a new complementary approach to overcome some of the limitations of variable source bulk isotope values commonly encountered in estuarine areas and other complex environments with mixed aquatic and terrestrial inputs.
Bexarotene Induces Cellular Senescence in MMTV-Neu Mouse Model of Mammary Carcinogenesis

Previous studies have shown that retinoids and rexinoids can prevent breast cancer in animal models and in women with increased risk of developing the disease. The cellular effects of these vitamin A analogues have been primarily associated with induction of differentiation and inhibition of proliferation. In this study, we tested the hypothesis that bexarotene (LGD1069, Targretin), a rexinoid, can not only inhibit cell proliferation but also induce cellular senescence in mammary epithelial cells, premalignant lesions, and tumors of the MMTV-Neu model of mammary carcinogenesis, which develops estrogen receptor–negative tumors. Mice with palpable mammary tumors were treated for 4 weeks with bexarotene at 80 or 40 mg/kg body weight, and senescent cells were determined by SA-β-Gal assay. Bexarotene decreased in a dose-dependent manner the multiplicity of premalignant lesions and tumors, and this was associated with inhibition of cell proliferation and induction of cellular senescence and apoptosis. By double labeling of senescent cells, first by SA-β-Gal and then by antibodies against genes related to cellular senescence, we found that p21, p16, and RARβ, but not p53, were upregulated by bexarotene in mammary tumors and in breast cancer cell lines, suggesting involvement of multiple signaling pathways in mediating the senescence program of rexinoids. These findings indicate that, in addition to cell proliferation and apoptosis, cellular senescence could be used as a potential biomarker of response in breast cancer prevention and therapy studies with rexinoids and possibly with other antitumor agents. Cancer Prev Res; 6(4); 299–308. ©2013 AACR.
Orthogonal control of endogenous gene expression in mammalian cells using synthetic ligands

Gene switches have wide utility in synthetic biology, gene therapy, and developmental biology, and multiple orthogonal gene switches are needed to construct advanced circuitry or to control complex phenotypes. Endogenous vascular endothelial growth factor (VEGF‐A) is crucial to angiogenesis, and it has been shown that multiple alternately spliced VEGF‐A isoforms are necessary for proper blood vessel formation. Such a necessity limits the utility of direct transgene delivery, which can provide only one splice variant. To overcome this limitation, we constructed a gene switch that can regulate the (VEGF‐A) locus in mammalian cells by combining an engineered estrogen receptor (ER) ligand‐binding domain (LBD), a p65 activation domain, and an artificial zinc‐finger DNA binding domain (DBD). Our gene switch is specifically and reversibly controlled by 4,4′‐dyhydroxybenzil (DHB), a small molecule, non‐steroid synthetic ligand, which acts orthogonally in a mammalian system. After optimization of the gene switch architecture, an endogenous VEGF‐A induction ratio of >100‐fold can be achieved in HEK293 cells at 1 µM DHB, which is the highest endogenous induction reported to date. In addition, induction has been shown to be reversible, repeatable, and sustainable. Another advantage is that the ligand response is tunable by varying the clonal composition of a stably integrated cell line. The integration of our findings with the technology to change ligand specificity and DNA binding specificity will provide the framework for generating a wide array of orthogonal gene switches that can control multiple genes with multiple orthogonal ligands. Biotechnol. Bioeng. 2013; 110: 1419–1429. © 2012 Wiley Periodicals, Inc.
Inhalation induction with sevoflurane: a double-blind comparison with propofol.

We conducted a randomized, double-blind comparison of 8% sevoflurane and propofol as induction agents for day-case cystoscopy in 102 patients. All patients received an i.v. cannula and breathed oxygen 5 litre min-1. Anaesthesia was induced with propofol i.v. or inhalation of 8% sevoflurane and 10% Intralipid (as a placebo) i.v. , delivered by a blinded observer. Anaesthesia was maintained in all patients with 2% sevoflurane via a face mask. Induction of anaesthesia with sevoflurane was significantly slower compared with propofol (mean 84 (SD 24) s vs 57 (11) s), but was associated with a lower incidence of apnoea (16% vs 65%) and a shorter time to establish spontaneous ventilation (94 (34) s vs 126 (79) s). Induction complications were uncommon in each group but the transition to maintenance was smoother with sevoflurane and was associated with less hypotension compared with propofol. Emergence from anaesthesia induced with sevoflurane occurred significantly earlier compared with propofol (5.2 (2.2) min vs 7.0 (3.2) min) and anaesthetic induction was also significantly cheaper with sevoflurane. According to a postoperative questionnaire, the majority of patients found both anaesthetic techniques acceptable. Nevertheless, significnatly more patients (14%) rated induction with sevoflurane as unpleasant compared with propofol (0) and significantly more patients (24%) would not choose sevoflurane induction compared with propofol (6%). This phenomenon may have been related to the particular patient population studied, however. Inhalation induction with 8% sevoflurane would appear to offer several objective advantages compared with induction with propofol in day-case patients, although a significant minority may dislike this technique.
Lateral inhibition in proneural clusters: cis-regulatory logic and default repression by Suppressor of Hairless

Lateral inhibition, wherein a single cell signals to its neighbors to prevent them from adopting its own fate, is the best-known setting for cell-cell communication via the Notch (N) pathway. During peripheral neurogenesis in Drosophila, sensory organ precursor (SOP) cells arise within proneural clusters (PNCs), small groups of cells endowed with SOP fate potential by their expression of proneural transcriptional activators. SOPs use N signaling to activate in neighboring PNC cells the expression of multiple genes that inhibit the SOP fate. These genes respond transcriptionally to direct regulation by both the proneural proteins and the N pathway transcription factor Suppressor of Hairless [Su(H)], and their activation is generally highly asymmetric; i.e. only in the inhibited (non-SOP) cells of the PNC, and not in SOPs. We show that the substantially higher proneural protein levels in the SOP put this cell at risk of inappropriately activating the SOP-inhibitory genes, even without input from N-activated Su(H). We demonstrate that this is prevented by direct `default' repression of these genes by Su(H), acting through the same binding sites it uses for activation in non-SOPs. We show that de-repression of even a single N pathway target gene in the SOP can extinguish the SOP cell fate. Finally, we define crucial roles for the adaptor protein Hairless and the co-repressors Groucho and CtBP in conferring repressive activity on Su(H) in the SOP. Our work elucidates the regulatory logic by which N signaling and the proneural proteins cooperate to create the neural precursor/epidermal cell fate distinction during lateral inhibition.
Comparison of fractal dimension estimation algorithms for epileptic seizure onset detection

Fractal dimension (FD) is a natural measure of the irregularity of a curve. In this study the performances of three waveform FD estimation algorithms (i.e. Katz's, Higuchi's and the k-nearest neighbour (k-NN) algorithm) were compared in terms of their ability to detect the onset of epileptic seizures in scalp electroencephalogram (EEG). The selection of parameters involved in FD estimation, evaluation of the accuracy of the different algorithms and assessment of their robustness in the presence of noise were performed based on synthetic signals of known FD. When applied to scalp EEG data, Katz's and Higuchi's algorithms were found to be incapable of producing consistent changes of a single type (either a drop or an increase) during seizures. On the other hand, the k-NN algorithm produced a drop, starting close to the seizure onset, in most seizures of all patients. The k-NN algorithm outperformed both Katz's and Higuchi's algorithms in terms of robustness in the presence of noise and seizure onset detection ability. The seizure detection methodology, based on the k-NN algorithm, yielded in the training data set a sensitivity of 100% with 10.10 s mean detection delay and a false positive rate of 0.27 h−1, while the corresponding values in the testing data set were 100%, 8.82 s and 0.42 h−1, respectively. The above detection results compare favourably to those of other seizure onset detection methodologies applied to scalp EEG in the literature. The methodology described, based on the k-NN algorithm, appears to be promising for the detection of the onset of epileptic seizures based on scalp EEG.
Leveraging Gate-Level Properties to Identify Hardware Timing Channels

Modern embedded computing systems such as medical devices, airplanes, and automobiles continue to dominate some of the most critical aspects of our lives. In such systems, the movement of information throughout a device must be tightly controlled to prevent violations of privacy or integrity. Unfortunately, bounding the flow of information can often present a significant challenge, as information can flow through channels that are difficult to detect, such as timing channels. As has been demonstrated by recent research in hardware security, information flow tracking techniques deployed at the hardware or gate level show promise at identifying these “timing flows” but provide no formal statements about this claim NOR mechanisms for separating out timing information from other types of flows. In this paper, we first prove that gate-level information flow tracking can in fact detect timing flows. In addition, we work to identify these timing flows separately from other flows by presenting a framework for identifying a different type of flow that we call functional flows. By using this framework to either confirm or rule out the existence of such flows, we leverage the previous work in hardware information flow tracking to effectively isolate timing flows. To show the effectiveness of this model, we demonstrate its usage on three practical examples: a shared bus (I2C), a cache in a MIPS-based processor, and an RSA encryption core, all of which were written in Verilog/VHDL and then simulated in a variety of scenarios. In each scenario, we demonstrate how our framework can be used to identify timing and functional flows and also analyze our model's overhead.
Choosing Autonomy Modes for Multirobot Search

Objective: The number of robots an operator can supervise increases with the robots’ level of autonomy. The reported study investigates multirobot foraging to identify aspects of the task most suitable for automation. Background: Many envisioned applications of robotics involve multirobot teams. One of the simplest of these applications is foraging, in which robots are operated independently to explore and discover targets. Depending on levels of autonomy and task, operators have been found able to manage 3 to 12 robots. Method: The foraging task can be functionally subdivided into visiting new regions and identifying targets. In the reported experiment, full-task foraging performance was compared with exploration and perceptual search performance for 4-, 8-, and 12-robot teams in a between-groups repeated measures design. Results: Operators in the full-task condition could not successfully manage 12 robots, finding only half as many victims as perceptual search operators. Exploration performance was roughly the same in the full-task and exploration conditions, suggesting that performance of this subtask was limiting the number of robots that could be controlled. Conclusion: Performance and workload measures indicate that exploration (navigation) tasks are the limiting factor in multirobot foraging. This finding suggests that robot navigation is the best candidate for automation. Application: Search tasks, such as foraging or perimeter control, account for many of the near-term applications envisioned for multirobot teams. The results support the choice of task-centered architectures in which the control and coordination of robotic platforms is automated, leaving search and identification of targets to human operators.
Identification of a Coronavirus Transcription Enhancer

ABSTRACT Coronavirus (CoV) transcription includes a discontinuous mechanism during the synthesis of sub-genome-length minus-strand RNAs leading to a collection of mRNAs in which the 5′ terminal leader sequence is fused to contiguous genome sequences. It has been previously shown that transcription-regulating sequences (TRSs) preceding each gene regulate transcription. Base pairing between the leader TRS (TRS-L) and the complement of the body TRS (cTRS-B) in the nascent RNA is a determinant factor during CoV transcription. In fact, in transmissible gastroenteritis CoV, a good correlation has been observed between subgenomic mRNA (sg mRNA) levels and the free energy (ΔG) of TRS-L and cTRS-B duplex formation. The only exception was sg mRNA N, the most abundant sg mRNA during viral infection in spite of its minimum ΔG associated with duplex formation. We postulated that additional factors should regulate transcription of sg mRNA N. In this report, we have described a novel transcription regulation mechanism operating in CoV by which a 9-nucleotide (nt) sequence located 449 nt upstream of the N gene TRS core sequence (CS-N) interacts with a complementary sequence just upstream of CS-N, specifically increasing the accumulation of sg mRNA N. Alteration of this complementarity in mutant replicon genomes showed a correlation between the predicted stability of the base pairing between 9-nt sequences and the accumulation of sg mRNA N. This interaction is exclusively conserved in group 1a CoVs, the only CoV subgroup in which the N gene is not the most 3′ gene in the viral genome. This is the first time that a long-distance RNA-RNA interaction regulating transcriptional activity specifically enhancing the transcription of one gene has been described to occur in CoVs.
Discriminative Batch Mode Active Learning

Active learning sequentially selects unlabeled instances to label with the goal of reducing the effort needed to learn a good classifier. Most previous studies in active learning have focused on selecting one unlabeled instance to label at a time while retraining in each iteration. Recently a few batch mode active learning approaches have been proposed that select a set of most informative unlabeled instances in each iteration under the guidance of heuristic scores. In this paper, we propose a discriminative batch mode active learning approach that formulates the instance selection task as a continuous optimization problem over auxiliary instance selection variables. The optimization is formulated to maximize the discriminative classification performance of the target classifier, while also taking the unlabeled data into account. Although the objective is not convex, we can manipulate a quasi-Newton method to obtain a good local solution. Our empirical studies on UCI datasets show that the proposed active learning is more effective than current state-of-the art batch mode active learning algorithms.
How many cosmological parameters

Constraints on cosmological parameters depend on the set of parameters chosen to define the model that is compared with observational data. I use the Akaike and Bayesian information criteria to carry out cosmological model selection, in order to determine the parameter set providing the preferred fit to the data. Applying the information criteria to the current cosmological data sets indicates, for example, that spatially flat models are statistically preferred to closed models, and that possible running of the spectral index has lower significance than inferred from its confidence limits. I also discuss some problems of statistical assessment arising from there being a large number of 'candidate' cosmological parameters that can be investigated for possible cosmological implications, and argue that 95 per cent confidence is too low a threshold to identify robustly the need for new parameters in model fitting. The best present description of cosmological data uses a scale-invariant (n = 1) spectrum of Gaussian adiabatic perturbations in a spatially flat Universe, with the cosmological model requiring only five fundamental parameters to specify it fully.
Interactions among Positions in the Third and Fourth Membrane-associated Domains at the Intersubunit Interface of the N-Methyl-d-aspartate Receptor Forming Sites of Alcohol Action*

Background: The NMDA receptor is a major target of alcohol action in the brain. Results: Four pairs of residues at the M3-M4 domain intersubunit interfaces interact to regulate gating and alcohol sensitivity. Conclusion: NMDA receptors contain putative sites of alcohol action at the M3-M4 domain interfaces. Significance: Identifying molecular sites of alcohol action on its targets is essential for understanding its actions. The N-methyl-d-aspartate (NMDA) glutamate receptor is a major target of ethanol in the brain. Previous studies have identified positions in the third and fourth membrane-associated (M) domains of the NMDA receptor GluN1 and GluN2A subunits that influence alcohol sensitivity. The predicted structure of the NMDA receptor, based on that of the related GluA2 subunit, indicates a close apposition of the alcohol-sensitive positions in M3 and M4 between the two subunit types. We tested the hypothesis that these positions interact to regulate receptor kinetics and ethanol sensitivity by using dual substitution mutants. In single-substitution mutants, we found that a position in both subunits adjacent to one previously identified, GluN1(Gly-638) and GluN2A(Phe-636), can strongly regulate ethanol sensitivity. Significant interactions affecting ethanol inhibition and receptor deactivation were observed at four pairs of positions in GluN1/GluN2A: Gly-638/Met-823, Phe-639/Leu-824, Met-818/Phe-636, and Leu-819/Phe-637; the latter pair also interacted with respect to desensitization. Two interactions involved a position in M4 of both subunits, GluN1(Met-818) and GluN2A(Leu-824), that does not by itself alter ethanol sensitivity, whereas a previously identified ethanol-sensitive position, GluN2A(Ala-825), did not unequivocally interact with any other position tested. These results also indicate a shift by one position of the predicted alignment of the GluN1 M4 domain. These findings have allowed for the refinement of the NMDA receptor M domain structure, demonstrate that this region can influence apparent agonist affinity, and support the existence of four sites of alcohol action on the NMDA receptor, each consisting of five amino acids at the M3-M4 domain intersubunit interfaces.
Socio-Professional Trajectories of Refugees in France: An Identity Work Perspective

This qualitative study investigates refugees’ socio-professional trajectories in France. Our findings suggest that refugees follow different socio-professional paths shaped by identity work and acculturation mechanisms as they go about integrating in the French context. We identify three socio-professional trajectories: ‘adjusting’, ‘enhancing’, and ‘detaching’. This study contributes, firstly, to research on refugees’ socio-professional adjustment and vocational adaptation, and secondly, to the literature on identity work. It does so by offering novel insights into the processes of repairing, reorienting, and reconstructing cultural and professional identities in the context of refugees’ relocation to host countries, in this case, France.
Safety culture assessment: a tool for improving patient safety in healthcare organizations

Increasingly, healthcare organizations are becoming aware of the importance of transforming organizational culture in order to improve patient safety. Growing interest in safety culture has been accompanied by the need for assessment tools focused on the cultural aspects of patient safety improvement efforts. This paper discusses the use of safety culture assessment as a tool for improving patient safety. It describes the characteristics of culture assessment tools presently available and discusses their current and potential uses, including brief examples from healthcare organizations that have undertaken such assessments. The paper also highlights critical processes that healthcare organizations need to consider when deciding to use these tools.