Miracle-dz/UniFAR-FTUs huggingface dataset:
How zebrafish research has helped in understanding thyroid diseases

Next-generation sequencing technologies have revolutionized the identification of disease-causing genes, accelerating the discovery of new mutations and new candidate genes for thyroid diseases. To face this flow of novel genetic information, it is important to have suitable animal models to study the mechanisms regulating thyroid development and thyroid hormone availability and activity. Zebrafish ( Danio rerio), with its rapid external embryonic development, has been extensively used in developmental biology. To date, almost all of the components of the zebrafish thyroid axis have been characterized and are structurally and functionally comparable with those of higher vertebrates. The availability of transgenic fluorescent zebrafish lines allows the real-time analysis of thyroid organogenesis and its alterations. Transient morpholino-knockdown is a solution to silence the expression of a gene of interest and promptly obtain insights on its contribution during the development of the zebrafish thyroid axis. The recently available tools for targeted stable gene knockout have further increased the value of zebrafish to the study of thyroid disease. All of the reported zebrafish models can also be used to screen small compounds and to test new drugs and may allow the establishment of experimental proof of concept to plan subsequent clinical trials.
Predicting diafiltration solution compositions for final ultrafiltration/diafiltration steps of monoclonal antibodies

Many liquid formulations for monoclonal antibodies (MAbs) require the final ultrafiltration/diafiltration step to operate at high protein concentrations, often at or above 100 g/L. When operating under these conditions, the excipient concentrations and pH of the final diafiltered retentate are frequently not equal to the corresponding excipient concentrations and pH of the diafiltration buffer. A model based on the Poisson–Boltzmann equation combined with volume exclusion was extended to predict both pH and excipient concentrations in the retentate for a given diafiltration buffer. This model was successfully applied to identify the diafiltration buffer composition required to achieve the desired pre‐formulated bulk drug substance (retentate) conditions. Predictions were in good agreement with the experimental results, and reduced the number of experimental iterations needed to define the diafiltration buffer composition. Additionally, the predictive model was applied in a sensitivity analysis across ranges of protein charge, protein concentration, and diafiltration buffer pH and excipient concentration. This sensitivity analysis can facilitate the design of experiments for robustness testing, and allow for generalized predictions across classes of molecules such as MAbs. Biotechnol. Bioeng. 2011; 108:1338–1346. © 2011 Wiley Periodicals, Inc.
Regional extraction of endothelins and conversion of big endothelin to endothelin-1 in the pig.

Endothelin-like immunoreactivity (ET-LI), mean arterial blood pressure (MABP) and vascular resistance in the spleen, kidney and femoral vascular bed were measured during intravenous infusions (20 pmol.kg-1.min) of endothelin-2 (ET-2), endothelin-3 (ET-3), big endothelin-1 (big ET) and sarafotoxin 6b in the pig. All peptides (especially endothelin-2 and sarafotoxin 6b) caused vasoconstrictor effects in the kidney. Endothelin-2, endothelin-3 and sarafotoxin 6b also evoked significant increases in splenic and femoral vascular resistance. The relative vasoconstrictor response to endothelin-2 was larger in the kidney and spleen than in the femoral vascular bed whereas the opposite was observed for endothelin-3. A high degree of plasma clearance for endothelin-like immunoreactivity was observed. Thus, for ET-2 and ET-3 about 70% of arterial endothelin-like immunoreactivity was removed over the kidney while over the spleen and femoral vascular bed an extraction of 50% for plasma endothelin-2 and 30-40% for endothelin-3 was observed. Big endothelin-1 was only extracted by 34% over the kidney and not at all in the splenic or femoral vascular bed. The metabolic plasma half-lifes of endothelin-2 and endothelin-3 in vivo were in the same range, 1-2 minutes, whereas the half-life of big endothelin-1 was 9 minutes. HPLC-characterization of the plasma endothelin-like immunoreactivity during and after big endothelin-1 infusion as well as measurements using a specific endothelin-1 antiserum revealed formation of endothelin-1 from circulating big endothelin-1 in vivo but not in plasma in vitro. It is concluded that there exists specificity concerning the vasoconstrictor effects and the removal of endothelin-peptides from the circulation, both mechanisms being most prominent in the kidney. Big endothelin-1 has a much longer metabolic half-life, less regional clearance and poor vasoconstrictor activity compared with endothelin-1. Furthermore, endothelin-1 is formed from circulating big endothelin-1 probably by an endothelin-converting enzyme.
RecA homology search is promoted by mechanical stress along the scanned duplex DNA

A RecA–single-stranded DNA (RecA–ssDNA) filament searches a genome for sequence homology by rapidly binding and unbinding double-stranded DNA (dsDNA) until homology is found. We demonstrate that pulling on the opposite termini (3′ and 5′) of one of the two DNA strands in a dsDNA molecule stabilizes the normally unstable binding of that dsDNA to non-homologous RecA–ssDNA filaments, whereas pulling on the two 3′, the two 5′, or all four termini does not. We propose that the ‘outgoing’ strand in the dsDNA is extended by strong DNA–protein contacts, whereas the ‘complementary’ strand is extended by the tension on the base pairs that connect the ‘complementary’ strand to the ‘outgoing’ strand. The stress resulting from different levels of tension on its constitutive strands causes rapid dsDNA unbinding unless sufficient homology is present.
Personality and Vulnerability to Depression in Stroke Patients: A 1-Year Prospective Follow-Up Study

Background and Purpose— Depression is a frequent sequela of stroke that negatively interferes with rehabilitation outcome. Personality traits have been neglected as potential vulnerability factors for poststroke depression (PSD). In a 1-year prospective study, the influence of the 5 main personality traits (ie, neuroticism, extraversion, openness, agreeableness, and conscientiousness) on the development of PSD was studied. Methods— One month after stroke, 190 consecutive patients with a first-ever supratentorial infarct were asked to complete a personality inventory, the NEO-Five Factor Inventory, which is based on the Five Factor Model of personality. Depressive symptoms were assessed 1, 3, 6, 9, and 12 months after stroke with 3 self-rating questionnaires as screening instruments for depression. PSD was diagnosed as major or minor depression through the use of the Structured Clinical Interview from the Diagnostic and Statistical Manual of Mental Disorders. Results— The 1-year cumulative incidence of depression was 38.7%. Cox regression analysis showed that patients with high neuroticism scores had a 4.6-times-higher risk of developing PSD than patients with low neuroticism scores (P =0.001) regardless of lesion location. Level of handicap was the only other factor that showed an independent effect on the occurrence of PSD. Conclusions— Neuroticism is an important predictor of PSD, a finding that emphasizes the need to take personality into account as a potential vulnerability factor for depression in stroke patients. Research on PSD should aim at delineating the interplay between neurological and psychological factors in the development of PSD.
Analyzing Information and Value Flows in High-Frequency Capital Markets

High-frequency trading has significant influence on today’s capital markets and has received massive attention in the media. This research aims to provide a conceptual understanding of high-frequency capital markets by analysing information and value flows between relevant high-frequency trading market participants. In a first step, market participants including traders, brokers, market platforms, technology providers, information providers, and clearing agencies are introduced. Second, the trading process is described focusing on the three most important phases, namely the information phase, order routing phase, and order matching phase. Furthermore, we review widely adopted high-frequency trading strategies such as market making, arbitrage trading, and pinging. Expert interviews are used to provide practical insights on the perception of high-frequency trading and the necessity for improved regulation. We merge theoretical knowledge and our findings from practice to develop the HFT Value Information Framework visualizing information and value flows between market participants. We discuss the interrelations between market participants in current high-frequency capital markets and describe implications for different stakeholders. Finally, the implications for regulatory bodies are discussed and possible future research opportunities are identified.
Manipulation in MRI devices using electrostrictive polymer actuators: with an application to reconfigurable imaging coils

MRI (magnetic resonance imaging) is a powerful medical diagnostic tool. Its value would be greatly increased if it were possible to physically manipulate objects within the MRI during imaging. However, the extraordinarily strong magnetic fields used by the MRI make conventional electromagnetic components, such as actuators and sensors, unusable. In this paper, it is shown that devices constructed using binary polymer based actuators, called electrostrictive polymer actuators (EPAM) are able to function effectively within the MRI without degrading its imaging performance. These actuators eliminate the need for conventional electromagnetic actuators and their associated electronics. The binary nature of the actuators eliminates the need for feedback sensors to control the devices motion. The basic concept called digital mechatronics is briefly summarized in this paper. Its application to a reconfigurable MRI surface-imaging coil (RMIC) is also presented. Experimental results are presented that show the EPAM RMIC is completely compatible in the MRI and can be used to enhance the diagnostic capabilities of MRI. The paper also suggests other applications of binary EPAM based actuators for use in MRI systems.
Integrating Surface and Abstract Features for Robust Cross-Domain Chinese Word Segmentation

Current character-based approaches are not robust for cross domain Chin ese word segmentation. In this paper, we alleviate this problem by deriving a novel enhanced ch aracter-based generative model with a new abstract aggregate candidate-feature, which indicates if th e given candidate prefers the corresponding position-tag of the longest dictionary matching wo rd. Since the distribution of the proposed feature is invariant across domains, our model thus possesses better generalization ability. Open tests on CIPS-SIGHAN-2010 show that the enhanced generative model achieves robust cross-domain performance for various OOV coverage rates and obtains the best performance on three out of four domains. The enhanced gen erative model is then further integrated with a discriminative model which also utilizes dictionary information . This integrated model is shown to be either superior or comparable to all other models repo rted in the literatur e on every domain of this task.
The density recovery profile: A method for the analysis of points in the plane applicable to retinal studies

Abstract The density recovery profile is a plot of the spatial density of a set of points as a function of the distance of each of those points from all the others. It is based upon a two-dimensional point autocorrelogram. If the points are randomly distributed, then the profile is flat, with a value equal to the mean spatial density. Thus, any deviation from this value indicates that the presence of the object represented by the point alters the probability of encountering nearby objects of the same set. Increased value near an object indicates clustering, decreased value near an object indicates anticlustering. The method appears to be unique in its ability to provide quantitative measures of the anticlustered state. Two examples are presented. The first is based upon a sample of the distribution of the somata of starburst amacrine cells in the macaque retina; the second is based upon the distribution of the terminal enlargements on the dendrites of a single macaque ganglion cell that projects to the superior colliculus. In both cases, the density recovery profile is initially lower than the mean density, and increases up to the plateau at the value of the mean density. Two useful measures can be derived from this profile: an intensive parameter termed the effective radius, which quantifies the extent of the region of decreased probability and is insensitive to random undersampling of the underlying distribution, and an extensive parameter termed the packing factor, which quantifies the degree of packing possible for a given effective radius, and is insensitive to scaling. An extension of this method, applicable to correlations between two superimposed distributions, and based upon a two-dimensional point cross-correlogram, is also described.
Discriminative label consistent dictionary learning

The goal of this work is to improve dictionary learning techniques for classification. We primarily focus on the label consistent K-SVD technique. We improve the consistency between the linear classification and class labels by introducing a sigmoid function. The second improvement is in replacing the Euclidean norm for the consistency constraint by a robust lp-norm (0<;p<;1); this makes the inconsistency robust to changes in magnitude. We compare our proposed modifications with existing work on label consistent KSVD and Sparse Classifier on the Extended YaleB and the AR face databases. Our proposed formulations show considerable improvement in accuracy compared to the baselines.
Prognostic Significance of Programmed Cell Death Ligand 1 (PD-L1), CD8+ Tumor-Infiltrating Lymphocytes and p53 in Non-Small Cell Lung Cancer: An Immunohistochemical Study.

OBJECTIVE Programmed cell death ligand-1 interacts with the immune receptors on the surface of CD8+ tumor infiltrating lymphocytes and PD-1, thereby blocking its anti-tumor activity. Therapeutics suppression of this interaction will show a promise in the treatment of non-small cell lung cancer by restoring the functional anti-tumor T-cell activity. We aimed to evaluate the association between the immunohistochemical expression of PD-L1, stromal CD8+ tumor infiltrating lymphocytes and p53 with the clinicopathological characteristics, response to chemotherapy, progression-free-survival, and overall survival. MATERIAL AND METHOD We examined the immunohistochemical expression of PD-L1, stromal CD8+ TILs, and p53 expression in 50 patients with advanced stage (III&IV) non-small cell lung cancer. RESULTS PD-L1 was expressed in 56% of the studied cases. PD-L1 expression was related to unfavorable response to the therapy without significant difference. PD-L1 expression was significantly associated with disease progression, poor progression-free-survival & overall survival. CD8+ TILs were high in 32% of the cases. Tumors with high CD8+ TILs showed a partial response to therapy and had a better progression-free-survival and overall survival. p53 expressed in 82% of the studied cases. There was a significant negative association between PD-L1 and CD8+ TILs (p=0.009), while a non-significant association was found between p53 and PD-L1 (p=0.183). CONCLUSION PD-L1 overexpression is an unfavorable prognostic marker, while the high CD8 + TILs is a good prognostic marker in non-small cell lung cancer. PD-L1 immunohistochemical assessment may be used for the selection of patients legible for treatment with anti-PD-L1 therapy.
The Causal Frame Problem: An Algorithmic Perspective

The Frame Problem (FP) is a puzzle in philosophy of mind and epistemology, articulated by the Stanford Encyclopedia of Philosophy as follows: "How do we account for our apparent ability to make decisions on the basis only of what is relevant to an ongoing situation without having explicitly to consider all that is not relevant? " In this work, we focus on the causal variant of the FP, the Causal Frame Problem (CFP). Assuming that a reasoner's mental causal model can be (implicitly) represented by a causal Bayes net, we first introduce a notion called Potential Level (PL). PL, in essence, encodes the relative position of a node with respect to its neighbors in a causal Bayes net. Drawing on the psychological literature on causal judgment, we substantiate the claim that PL may bear on how time is encoded in the mind. Using PL, we propose an inference framework, called the PL-based Inference Framework (PLIF), which permits a boundedly-rational approach to the CFP to be formally articulated at Marr's algorithmic level of analysis. We show that our proposed framework, PLIF, is consistent with a wide range of findings in causal judgment literature, and that PL and PLIF make a number of predictions, some of which are already supported by existing findings.
Teachers’ Interactions in an Online Graduate Course on Moodle: A Social Network Analysis Perspective

A combination of social network analysis and content analysis was used to investigate the interactions that took place in an online Moodle course among 22 participants that were enrolled in a teacher education graduate program. The purpose of this study was to examine both the patterns and quality of the online interactions, which were assessed using a content analysis schema. The social network measures of the online learning network demonstrated that Moodle may have the capability to help establish a cohesive online learning community where members are able to participate in meaningful social interactions. Results from the coding of discussion posts demonstrated that, despite active online interactions, participants still lacked higher level knowledge co-construction. Factors that might impede online knowledge construction processes are examined and discussed so that higher levels of knowledge construction can be encouraged and eventually realized.
Knowledge of Thrombolytic Therapy Amongst Hospital Staff: Preliminary Results and Treatment Implications

Background and Purpose— In-hospital stroke is associated with slower access to thrombolysis than community-occurring stroke. It has been suggested that lack of knowledge regarding appropriate stroke response among hospital staff may contribute to delays in referral, assessment, and treatment of in-hospital stroke. Method— A survey was conducted among hospital ward staff members using the Stroke Awareness Questionnaire, which was adapted for use among hospital staff to assess their knowledge of stroke symptoms, acute treatments, and hospital protocols for treatment of stroke. Results— Ninety-six staff members were interviewed, 81% of whom were clinical staff (medical, nursing, allied health professionals). Ninety-two percent of staff could name ≥3 stroke symptoms. Only 49% of staff were aware of thrombolysis treatment, and only 48% could identify the time window for thrombolysis administration, with staff from stroke-related specialties likely to name thrombolysis as an acute treatment for stroke (71%; odds ratio =3.36, 95% confidence interval 1.17–9.61) and identify the correct treatment window (71%; odds ratio =3.55, 95% confidence interval 1.24–10.16). Only 52% of staff on general wards were aware of an in-hospital stroke protocol. Conclusions— Hospital staff had adequate knowledge of stroke signs and symptoms; however, there was low awareness of thrombolysis therapy and its correct treatment time window among hospital staff. Targeted educational programmes among hospital staff regarding stroke are required to optimize acute stroke care.
4-(9-Anthryl)-1-(1-naphthyl)spiro[azetidine-3,9′-xanthen]-2-one n-hexane hemisolvate

In the title compound, C39H25NO2·0.5C6H14, the β-lactam ring is nearly planar [maximum deviation of 0.012 (2) Å from the mean plane] and makes dihedral angles of 36.41 (13), 88.87 (13) and 54.16 (12)°, respectively, with the naphthalene, xanthene and anthracene ring systems. The molecular conformation is stabilized by intramolecular C—H⋯O and C—H⋯N contacts. The complete solvent molecule is generated by inversion. In the crystal structure, molecules are linked to each other by C—H⋯π interactions.
Error Bounds for Monotone Approximation Schemes for Hamilton-Jacobi-Bellman Equations

We obtain error bounds for monotone approximation schemes of Hamilton--Jacobi--Bellman equations. These bounds improve previous results of Krylov and the authors. The key step in the proof of these new estimates is the introduction of a switching system which allows the construction of approximate, (almost) smooth supersolutions for the Hamilton--Jacobi--Bellman equation.
Volumetric Collision Detection for Derformable Objects

We present a new algorithm for the efficient detection of collisions of geometrically complex objects. Our approach requires neither expensive setup nor sophisticated spatial data structures and is hence specifically suitable for handling deformable objects with arbitrarily shaped, closed surfaces. The algorithm is based on a Layered Depth Image (LDI) decomposition of the intersection volume. Currently, we have implemented two types of collision queries. The first one comprises an explicit representation of the intersection volume. The second one computes vertex-in-volume tests. All queries are processed on the LDI–based volume representation. Our algorithm is very easy to implement and can be accelerated in graphics hardware by using OpenGL.
An Analytical Study of Loop Tiling for a Large-Scale Unstructured Mesh Application

Increasingly, the main bottleneck limiting performance on emerging multi-core and many-core processors is the movement of data between its different cores and main memory. As the number of cores increases, more and more data needs to be exchanged with memory to keep them fully utilized. This critical bottleneck is already limiting the utility of processors and our ability to leverage increased parallelism to achieve higher performance. On the other hand, considerable computer science research exists on tiling techniques (also known as sparse tiling), for reducing data transfers. Such work demonstrates how the increasing memory bottleneck could be avoided but the difficulty has been in extending these ideas to real-world applications. These algorithms quickly become highly complicated, and it has be very difficult to for a compiler to automatically detect the opportunities and implement the execution strategy. Focusing on the unstructured mesh application class, in this paper, we present a preliminary analytical investigation into the performance benefits of tiling (or loop-blocking) algorithms on a realworld industrial CFD application. We analytically estimate the reductions in communications or memory accesses for the main parallel loops in this application and predict quantitatively the performance benefits that can be gained on modern multi-core and many core hardware. The analysis demonstrates that in general a factor of four reduction in data movement can be achieved by tiling parallel loops. A major part of the savings come from contraction of temporary or transient data arrays that need not be written back to main memory, by holding them in the last level cache (LLC) of modern processors.