Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal stability of Clostridium pasteurianum rubredoxin: Deconvoluting the contributions of the metal site and the protein

To provide a framework for understanding the hyperthermostability of some rubredoxins, a comprehensive analysis of the thermally induced denaturation of rubredoxin (Rd) from the mesophile, Clostridium pasteurianum was undertaken. Rds with three different metals in its M(SCys)4 site (M = Fe3+/2+, Zn2+, or Cd2+) were examined. Kinetics of metal ion release were monitored anaerobically at several fixed temperatures between 40 and 100 °C, and during progressive heating of the iron‐containing protein. Both methods gave a thermal stability of metal binding in the order Fe2+ « Fe3+ < Zn2+ < Cd2+. The temperature at which half of the iron was released from the protein in temperature ramp experiments was 69 °C for Fe2+Rd and 83 °C for Fe3+Rd. Temperature‐dependent changes in the protein structure were monitored by differential scanning calorimetry, tryptophan fluorescence, binding of a fluorescent hydrophobic probe, and 1H NMR. Major but reversible structural changes, consisting of swelling of the hydrophobic core and opening of a loop region, were found to occur at temperatures (50‐70 °C) much lower than those required for loss of the metal ion. For the three divalent metal ions, the results suggest that the onset of the reversible, lower‐temperature structural changes is dependent on the size of the MS4 site, whereas the final, irreversible loss of metal ion is dependent on the inherent M‐SCys bond strength. In the case of Fe3+Rd, stoichiometric Fe3+/cysteine‐ligand redox chemistry also occurs during metal ion loss. The results indicate that thermally induced unfolding of the native Cp Rd must surmount a significant kinetic barrier caused by stabilizing interactions both within the protein and within the M(SCys)4 site.
A review of the use of a dermal skin substitute in burns care.

The National Burn Care Review estimates that a quarter of a million people present to burn treatment centres in the UK each year. A burn injury is first and foremost an injury to the skin. However, the visible skin injury is only one component of a disease process that has life-threatening systemic and metabolic effects remote from the site of injury. There are three phases to recovery from a burn injury:
Household Demand for Assets: A Model of Short-Run Adjustments

M OST recent studies of the demand for assets (real or financial) restrict themselves to the examination of the market for a single asset or small group of similar assets. This approach contrasts with the usual treatment of the demand for consumer goods in which complete systems of equations are estimated. This paper reports an attempt to develop a complete set of asset-demand functions for the household sector and to present estimates of the parameters derived from postwar United States data.
A chronic kidney disease risk score to determine tenofovir safety in a prospective cohort of HIV-positive male veterans

Objective:Tenofovir disoproxil fumarate is a widely used antiretroviral for HIV infection that has been associated with an increased risk of chronic kidney disease (CKD). Our objective was to derive a scoring system to predict 5-year risk of developing CKD in HIV-infected individuals and to estimate difference in risk associated with tenofovir use. Design:We evaluated time to first occurrence of CKD (estimated glomerular filtration rate <60 ml/min per 1.73 m2) in 21 590 HIV-infected men from the Veterans Health Administration initiating antiretroviral therapy from 1997 to 2010. Methods:We developed a point-based score using multivariable Cox regression models. Median follow-up was 6.3 years, during which 2059 CKD events occurred. Results:Dominant contributors to the CKD risk score were traditional kidney risk factors (age, glucose, SBP, hypertension, triglycerides, proteinuria); CD4+ cell count was also a component, but not HIV RNA. The overall 5-year event rate was 7.7% in tenofovir users and 3.8% in nonusers [overall adjusted hazard ratio 2.0, 95% confidence interval (CI) 1.8–2.2]. There was a progressive increase in 5-year CKD risk, ranging from less than 1% (zero points) to 16% (≥9 points) in nonusers of tenofovir, and from 1.4 to 21.4% among tenofovir users. The estimated number-needed-to-harm (NNH) for tenofovir use ranged from 108 for those with zero points to 20 for persons with at least nine points. Among tenofovir users with at least 1 year exposure, NNH ranged from 68 (zero points) to five (≥9 points). Conclusion:The CKD risk score can be used to predict an HIV-infected individual's absolute risk of developing CKD over 5 years and may facilitate clinical decision-making around tenofovir use.
Intra-laboratory validation of microplate methods for total phenolic content and antioxidant activity on polyphenolic extracts, and comparison with conventional spectrophotometric methods.

BACKGROUND Total phenolic content (TPC) and antioxidant activity (AA) assays in microplates save resources and time, therefore they can be useful to overcome the fact that the conventional methods are time-consuming, labour intensive and use large amounts of reagents. An intra-laboratory validation of the Folin-Ciocalteu microplate method to measure TPC and the 2,2-diphenyl-1-picrylhydrazyl (DPPH) microplate method to measure AA was performed and compared with conventional spectrophotometric methods. RESULTS To compare the TPC methods, the confidence intervals of a linear regression were used. In the range of 10-70 mg L(-1) of gallic acid equivalents (GAE), both methods were equivalent. To compare the AA methodologies, the F-test and t-test were used in a range from 220 to 320 µmol L(-1) of Trolox equivalents. Both methods had homogeneous variances, and the means were not significantively different. The limits of detection and quantification for the TPC microplate method were 0.74 and 2.24 mg L(-1) GAE and for the DPPH 12.07 and 36.58 µmol L(-1) of Trolox equivalents. The relative standard deviation of the repeatability and reproducibility for both microplate methods were ≤ 6.1%. The accuracy ranged from 88% to 100%. CONCLUSION The microplate and the conventional methods are equals in a 95% confidence level.
Estimating Electron Density Support for Individual Atoms and Molecular Fragments in X-ray Structures

Macromolecular structures resolved by X-ray crystallography are essential for life science research. While some methods exist to automatically quantify the quality of the electron density fit, none of them is without flaws. Especially the question of how well individual parts like atoms, small fragments, or molecules are supported by electron density is difficult to quantify. While taking experimental uncertainties correctly into account, they do not offer an answer on how reliable an individual atom position is. A rapid quantification of this atomic position reliability would be highly valuable in structure-based molecular design. To overcome this limitation, we introduce the electron density score EDIA for individual atoms and molecular fragments. EDIA assesses rapidly, automatically, and intuitively the fit of individual as well as multiple atoms (EDIAm) into electron density accompanied by an integrated error analysis. The computation is based on the standard 2fo - fc electron density map in combination with the model of the molecular structure. For evaluating partial structures, EDIAm shows significant advantages compared to the real-space R correlation coefficient (RSCC) and the real-space difference density Z score (RSZD) from the molecular modeler's point of view. Thus, EDIA abolishes the time-consuming step of visually inspecting the electron density during structure selection and curation. It supports daily modeling tasks of medicinal and computational chemists and enables a fully automated assembly of large-scale, high-quality structure data sets. Furthermore, EDIA scores can be applied for model validation and method development in computer-aided molecular design. In contrast to measuring the deviation from the structure model by root-mean-squared deviation, EDIA scores allow comparison to the underlying experimental data taking its uncertainty into account.
Author-aware Aspect Topic Sentiment Model to Retrieve Supporting Opinions from Reviews

User generated content about products and services in the form of reviews are often diverse and even contradictory. This makes it difficult for users to know if an opinion in a review is prevalent or biased. We study the problem of searching for supporting opinions in the context of reviews. We propose a framework called SURF, that first identifies opinions expressed in a review, and then finds similar opinions from other reviews. We design a novel probabilistic graphical model that captures opinions as a combination of aspect, topic and sentiment dimensions, takes into account the preferences of individual authors, as well as the quality of the entity under review, and encodes the flow of thoughts in a review by constraining the aspect distribution dynamically among successive review segments. We derive a similarity measure that considers both lexical and semantic similarity to find supporting opinions. Experiments on TripAdvisor hotel reviews and Yelp restaurant reviews show that our model outperforms existing methods for modeling opinions, and the proposed framework is effective in finding supporting opinions.
Adipokines: A treasure trove for the discovery of biomarkers for metabolic disorders

Adipose tissue is a major endocrine organ, releasing signaling and mediator proteins, termed adipokines, via which adipose tissue communicates with other organs. Expansion of adipose tissue in obesity alters adipokine secretion which may contribute to the development of metabolic diseases. Consequently, this correlation has emphasized the importance to further characterize the adipocyte secretion profile, and several attempts have been made to characterize the complex nature of the adipose tissue secretome by utilizing diverse proteomic profiling approaches. Although the entirety of human adipokines is still incompletely characterized, to date more than 600 potentially secretory proteins were identified providing a rich source to identify putative novel biomarkers associated with metabolic diseases.
A new model for studying tissue-specific mdr1a gene expression in vivo by live imaging

Multidrug resistance continues to be a major impediment to successful chemotherapy in cancer patients. One cause of multidrug resistance is enhanced expression of the mdr1 gene, but the precise factors and physiological conditions controlling mdr1 expression are not entirely known. To gain a better understanding of mdr1 transcriptional regulation, we created a unique mouse model that allows noninvasive bioimaging of mdr1 gene expression in vivo and in real time. The model uses a firefly luciferase (fLUC) gene inserted by homologous recombination into the murine mdr1a genetic locus. The inserted fLUC gene is preceded by a neo expression cassette flanked by loxP sites, so that Cre-mediated recombination is required to configure the fLUC gene directly under the control of the endogenous mdr1a promoter. We now demonstrate that the mdr1a.fLUC knock-in is a faithful reporter for mdr1a expression in naive animals, in which fLUC mRNA levels and luminescence intensities accurately parallel endogenous mdr1a mRNA expression. We also demonstrate xenobiotic-inducible regulation of mdr1a.fLUC expression in real time, in parallel with endogenous mdr1a expression, resulting in a more detailed understanding of the kinetics of mdr1a gene induction. This mouse model demonstrates the feasibility of using bioimaging coupled with Cre/loxP conditional knock-in to monitor regulated gene expression in vivo. It represents a unique tool with which to study the magnitude and kinetics of mdr1a induction under a variety of physiologic, pharmacologic, genetic, and environmental conditions.
Novel features from autocorrelation and spectrum to classify Phonocardiogram quality

Phonocardiogram (PCG) or auscultation via a stethoscope forms the basis of preliminary medical screening. But PCG recorded in an uncontrolled environment is inherently noisy. In this paper we have derived novel features from the spectral domain and autocorrelation waveforms. These are used to identify the quality of a PCG recording and accepting only diagnosable quality recordings for further analysis. These features proved to be robust irrespective of variations in devices and in data collection protocols employed to ensure consistent data quality. A freely available, large, diverse, medical-grade PCG dataset was used for creating the training models. Results show that the proposed methodology yields an accuracy score of ∼75% on our in-house PCG dataset, collected using a low-cost smartphone-based digital stethoscope.
Epidemiology and impact of multimorbidity in primary care: a retrospective cohort study.

BACKGROUND In developed countries, primary health care increasingly involves the care of patients with multiple chronic conditions, referred to as multimorbidity. AIM To describe the epidemiology of multimorbidity and relationships between multimorbidity and primary care consultation rates and continuity of care. DESIGN OF STUDY Retrospective cohort study. SETTING Random sample of 99 997 people aged 18 years or over registered with 182 general practices in England contributing data to the General Practice Research Database. METHOD Multimorbidity was defined using two approaches: people with multiple chronic conditions included in the Quality and Outcomes Framework, and people identified using the Johns Hopkins University Adjusted Clinical Groups (ACG®) Case-Mix System. The determinants of multimorbidity (age, sex, area deprivation) and relationships with consultation rate and continuity of care were examined using regression models. RESULTS Sixteen per cent of patients had more than one chronic condition included in the Quality and Outcomes Framework, but these people accounted for 32% of all consultations. Using the wider ACG list of conditions, 58% of people had multimorbidity and they accounted for 78% of consultations. Multimorbidity was strongly related to age and deprivation. People with multimorbidity had higher consultation rates and less continuity of care compared with people without multimorbidity. CONCLUSION Multimorbidity is common in the population and most consultations in primary care involve people with multimorbidity. These people are less likely to receive continuity of care, although they may be more likely to gain from it.
Partial Revelation of Information in Experimental Asset Markets

The authors develop a model of market efficiency assuming private information is partially revealed to uninformed traders via the behavior of those who are informed. This partial revelation of information model is tested in fourteen computerized double auction laboratory markets. It explains the market value and allocation of purchased information, and asset allocations, better than either a fully revealing information model (FRE strong-form efficiency) or a nonrevealing expectations model; but it takes second place to FRE in explaining asset prices. The authors conjecture that refined versions of partial revelation of information may provide insight into "technical analysis" and minibubbles in securities markets. Copyright 1991 by American Finance Association.
Bis[N 3-(2-hydroxybenzoyl)pyridine-2-carboxamidrazonato-κ3 N 1,N 2,O]manganese(II)

In the title compound, [Mn(C13H11N4O2)2], the Mn atom is coordinated in a distorted octahedral manner by pyridyl N atoms, amidrazonato N atoms and carbamoy O atoms from two tridentate N 3-salicyloylpyridine-2-carboxamidrazonato ligands. N—H⋯O hydrogen bonds result in the formation of two chains, one parallel to the b axis and the other one parallel to the c axis. These two chains are cross-linked, building up layers parallel to the (100) plane.
2-D Ultrasound Sparse Arrays Multidepth Radiation Optimization Using Simulated Annealing and Spiral-Array Inspired Energy Functions

Full matrix arrays are excellent tools for 3-D ultrasound imaging, but the required number of active elements is too high to be individually controlled by an equal number of scanner channels. The number of active elements is significantly reduced by the sparse array techniques, but the position of the remaining elements must be carefully optimized. This issue is faced here by introducing novel energy functions in the simulated annealing (SA) algorithm. At each iteration step of the optimization process, one element is freely translated and the associated radiated pattern is simulated. To control the pressure field behavior at multiple depths, three energy functions inspired by the pressure field radiated by a Blackman-tapered spiral array are introduced. Such energy functions aim at limiting the main lobe width while lowering the side lobe and grating lobe levels at multiple depths. Numerical optimization results illustrate the influence of the number of iterations, pressure measurement points, and depths, as well as the influence of the energy function definition on the optimized layout. It is also shown that performance close to or even better than the one provided by a spiral array, here assumed as reference, may be obtained. The finite-time convergence properties of SA allow the duration of the optimization process to be set in advance.
Energy-Efficient MIMO Detection Using Link-Adaptive Parameter Adjustment

This paper presents a link-adaptive parameter adjustment scheme for energy efficient signal detection in multiple-input multiple-output (MIMO) systems. Equipped with multiple detection schemes of different performance-energy levels, the proposed detector adapts to instantaneous channel conditions and is adjusted at run-time with the detection scheme satisfying performance requirements with minimum power. To enable an efficient link adaptation, we develop a performance prediction method based on the equivalent SNR mapping technique. It provides accurate-enough BER estimation for non-linear signal detection under selectively fading channels. To demonstrate the effectiveness of the link adaptation technique on power saving, we carried out case studies by simulating a simplified LTE downlink system, where the parameter K of K-Best detection is adaptively adjusted. Simulation results demonstrate that the proposed link-adaptive detection offers significant power savings (53% on average and up to 86% for a 4×4 64-QAM system) compared to the static detection scheme targeting the worst-case environment.
Dysfunctional Cognitions Mediate the Relationship between Symptoms of Depression , Anxiety , and Sleep Quality in a Non-Clinical Population

Dysfunctional beliefs and attitudes about sleep such as faulty beliefs, worry, and attentional bias have been shown to perpetuate or even exacerbate poor sleep. Additionally, individuals with depressive or anxiety disorders have been shown to have decreased sleep quality. This study, however, will examine the mediating effects of dysfunctional cognitions about sleep between depressive and anxiety related symptoms and sleep quality in a non-clinical population. A total of 446 participants completed an online survey including the Pittsburgh Sleep Quality Index (PSQI), the Hospital Anxiety and Depression Scale (HADS), and the Dysfunctional Beliefs and Attitudes about Sleep (DBAS-16). Mediation analysis indicated that the relationship between depressive symptoms and sleep quality was significantly mediated by DBAS-16 scores (z = 6.258, p< .001). Additionally, the relationship between anxiety symptoms and sleep quality was significantly mediated by DBAS-16 scores (z = 6.433, p< .001). Based on our data, dysfunctional beliefs and attitudes about sleep are potential mechanisms by which depressive and anxiety disorders may lead to poor sleep quality in the general population. This research highlights the importance of incorporating belief-targeted insomnia treatment into the cognitive behavioral therapy for depressive and anxiety disorders.
Learning how a tool affords by simulating 3D models from the web

Robots performing everyday tasks such as cooking in a kitchen need to be able to deal with variations in the household tools that may be available. Given a particular task and a set of tools available, the robot needs to be able to assess which would be the best tool for the task, and also where to grasp that tool and how to orient it. This requires an understanding of what is important in a tool for a given task, and how the grasping and orientation relate to performance in the task. A robot can learn this by trying out many examples. This learning can be faster if these trials are done in simulation using tool models acquired from the Web. We provide a semi-automatic pipeline to process 3D models from the Web, allowing us to train from many different tools and their uses in simulation. We represent a tool object and its grasp and orientation using 21 parameters which capture the shapes and sizes of principal parts and the relationships among them. We then learn a ‘task function' that maps this 21 parameter vector to a value describing how effective it is for a particular task. Our trained system can then process the unsegmented point cloud of a new tool and output a score and a way of using the tool for a particular task. We compare our approach with the closest one in the literature and show that we achieve significantly better results.
A Hilbert-based framework for preserving privacy in location-based services

Preserving user's privacy has recently drawn special attention in the field of location-based services and many techniques such as k-anonymity or obfuscation have been suggested to protect user's privacy. All of these traditional techniques are, however, geometry-based and separated from the database level. This separation causes the query processing to involve in two phases, querying the database to retrieve the exact locations of users and then modifying them to decrease the quality of this information. This two-phase process is time-consuming due to the number of disk accesses required to retrieve the user's exact location. Also, these geometry-based techniques cannot guarantee location privacy when the adversary gains knowledge about the geography of the obfuscated region. We address these problems by proposing Hilbert-based framework for preserving user's privacy and B
Viewpoint Students as Agents of Social Change: Student Initiatives at Rhodes University, South Africa

Rhodes University has a diversity of sustainable development initiatives meant for students and in a range of cases activities are initiated by students themselves with the support of the university. Results of a sustainability assessment revealed the involvement of students in environmental societies, environmental awareness campaigns, campus sustainability initiatives and community sustainability projects. Though most of the projects are still in their infancy and some challenges are yet to be overcome, the sustainability initiatives are gaining momentum and have contributed to improving the overall picture of sustainability at the university. Based on the results of the Rhodes University case study, the underpinning viewpoint in this paper is that university students are not merely recipients of Education for Sustainable Development but have the capacity to become agents for social change.