This study takes a stratified random sample of articles published in 2014 from the top 10 journals in the disciplines of biology, chemistry, mathematics, and physics, as ranked by impact factor. Sampled articles were examined for their reporting of original data or reuse of prior data, and were coded for whether the data was publicly shared or otherwise made available to readers. Other characteristics such as the sharing of software code used for analysis and use of data citation and DOIs for data were examined. The study finds that data sharing practices are still relatively rare in these disciplines' top journals, but that the disciplines have markedly different practices. Biology top journals share original data at the highest rate, and physics top journals share at the lowest rate. Overall, the study finds that within the top journals, only 13% of articles with original data published in 2014 make the data available to others.

Simulating human body dynamics requires detailed and accurate mathematical models. When solved inversely, these models provide a comprehensive description of force generation that considers subject morphology and can be applied to control real-time assistive technology, for example, orthosis or muscle/nerve stimulation. Yet, model complexity hinders the speed of its computations and may require approximations as a mitigation strategy. Here, we use machine learning algorithms to provide a method for accurate physics simulations and subject-specific parameterization. Several types of artificial neural networks (ANNs) with varied architecture were tasked to generate the inverse dynamic transformation of realistic arm and hand movement (23 degrees of freedom). Using a physical model, we generated representative limb movements with bell-shaped end-point velocity trajectories within the physiological workspace. This dataset was used to develop ANN transformations with low torque errors (less than 0.1 Nm). Multiple ANN implementations using kinematic sequences solved accurately and robustly the high-dimensional kinematic Jacobian and inverse dynamics of arm and hand. These results provide further support for the use of ANN architectures that use temporal trajectories of time-delayed values to make accurate predictions of limb dynamics.

Sound-symbolic word classes are found in different cultures and languages worldwide. These words are continuously produced to code complex information about events. Here we explore the capacity of creative language to transport complex multisensory information in a controlled experiment, where our participants improvised onomatopoeias from noisy moving objects in audio, visual and audiovisual formats. We found that consonants communicate movement types (slide, hit or ring) mainly through the manner of articulation in the vocal tract. Vowels communicate shapes in visual stimuli (spiky or rounded) and sound frequencies in auditory stimuli through the configuration of the lips and tongue. A machine learning model was trained to classify movement types and used to validate generalizations of our results across formats. We implemented the classifier with a list of cross-linguistic onomatopoeias simple actions were correctly classified, while different aspects were selected to build onomatopoeias of complex actions. These results show how the different aspects of complex sensory information are coded and how they interact in the creation of novel onomatopoeias.

It has been well established that the architecture of chromatin in cell nuclei is not random but functionally correlated. Chromatin damage caused by ionizing radiation raises complex repair machineries. This is accompanied by local chromatin rearrangements and structural changes which may for instance improve the accessibility of damaged sites for repair protein complexes. Using stably transfected HeLa cells expressing either green fluorescent protein (GFP) labelled histone H2B or yellow fluorescent protein (YFP) labelled histone H2A, we investigated the positioning of individual histone proteins in cell nuclei by means of high resolution localization microscopy (Spectral Position Determination Microscopy = SPDM). The cells were exposed to ionizing radiation of different doses and aliquots were fixed after different repair times for SPDM imaging. In addition to the repair dependent histone protein pattern, the positioning of antibodies specific for heterochromatin and euchromatin was separately recorded by SPDM. The present paper aims to provide a quantitative description of structural changes of chromatin after irradiation and during repair. It introduces a novel approach to analyse SPDM images by means of statistical physics and graph theory. The method is based on the calculation of the radial distribution functions as well as edge length distributions for graphs defined by a triangulation of the marker positions. The obtained results show that through the cell nucleus the different chromatin re-arrangements as detected by the fluorescent nucleosomal pattern average themselves. In contrast heterochromatic regions alone indicate a relaxation after radiation exposure and re-condensation during repair whereas euchromatin seemed to be unaffected or behave contrarily. SPDM in combination with the analysis techniques applied allows the systematic elucidation of chromatin re-arrangements after irradiation and during repair, if selected sub-regions of nuclei are investigated.

This study examines the completeness and overlap of coverage in physics of six open access scholarly communication systems, including two search engines (Google Scholar and Microsoft Academic), two aggregate institutional repositories (OAIster and OpenDOAR), and two physics-related open sources (arXiv.org and Astrophysics Data System). The 2001-2013 Nobel Laureates in Physics served as the sample. Bibliographic records of their publications were retrieved and downloaded from each system, and a computer program was developed to perform the analytical tasks of sorting, comparison, elimination, aggregation and statistical calculations. Quantitative analyses and cross-referencing were performed to determine the completeness and overlap of the system coverage of the six open access systems. The results may enable scholars to select an appropriate open access system as an efficient scholarly communication channel, and academic institutions may build institutional repositories or independently create citation index systems in the future. Suggestions on indicators and tools for academic assessment are presented based on the comprehensiveness assessment of each system.

Prior research shows that in a particular science domain, students' identity depends on their self-efficacy, perceived recognition by others, and their interest in that domain. In this study, we investigated how the end of the semester physics self-efficacy and perceived recognition by others for bioscience majors enrolled in the second semester of a traditionally taught mandatory physics course sequence predict their overall science identity aligned with their disciplinary major. We find that bioscience majors' physics self-efficacy and perceived recognition not only predict their physics identity but also their overall science identity. These relations between physics self-efficacy and perceived recognition and the overall science identity of bioscience majors suggest interdisciplinary connections that may provide additional pathways for boosting students' science identity, e.g., by enhancing their self-efficacy and perceived recognition in their other mandatory courses such as physics. We also find that on average, women majoring in bioscience had lower physics self-efficacy, perceived recognition, physics identity, and overall science identity than men even though women were not underrepresented in the physics course. One possible reason is that the societal stereotypes and biases pertaining to who can excel in physics can impact women who are constantly exposed to them throughout their life.

We propose an original approach to describe the scientific progress in a quantitative way. Using innovative Machine Learning techniques we create a vector representation for the PACS codes and we use them to represent the relative movements of the various domains of Physics in a multi-dimensional space. This methodology unveils about 25 years of scientific trends, enables us to predict innovative couplings of fields, and illustrates how Nobel Prize papers and APS milestones drive the future convergence of previously unrelated fields.

Human fetal thermoregulation, maternal-fetal heat exchange, and the role of the umbilical cord in these processes are not well understood. Ethical and technical limitations have restricted current knowledge to animal studies, that do not reflect human morphology. Here, we present the first 3-dimensional computational model of the human umbilical cord with finite element analysis, aiming to compute the maternal-fetal heat exchange. By modelling both the umbilical vein and the two umbilical arteries, we found that the coiled geometry of the umbilical artery, in comparison with the primarily straight umbilical vein, affects blood flow parameters such as velocity, pressure, temperature, shear strain rate and static entropy. Specifically, by enhancing the heat transfer coefficient, we have shown that the helical structure of the umbilical arteries plays a vital role in the temperature drop of the blood, along the arterial length from the fetal end to the placental end. This suggests the importance of the umbilical cord structure in maternal-fetal heat exchange and fetal heat loss, opening the way for future research with modified models and scenarios, as the basis for early detection of potential heat-transfer related complications, and/or assurance of fetal wellbeing.

Science is a social process with far-reaching impact on our modern society. In recent years, for the first time we are able to scientifically study the science itself. This is enabled by massive amounts of data on scientific publications that is increasingly becoming available. The data is contained in several databases such as Web of Science or PubMed, maintained by various public and private entities. Unfortunately, these databases are not always consistent, which considerably hinders this study. Relying on the powerful framework of complex networks, we conduct a systematic analysis of the consistency among six major scientific databases. We found that identifying a single "best" database is far from easy. Nevertheless, our results indicate appreciable differences in mutual consistency of different databases, which we interpret as recipes for future bibliometric studies.

Currently, considerable interest exists with regard to the dissociation of close packed aminoacids within proteins, in the course of unfolding, which could result in either wet or dry moltenglobules. The progressive disjuncture of residues constituting the hydrophobic core ofcyclophilin from L. donovani (LdCyp) has been studied during the thermal unfolding of the molecule, by molecular dynamics simulations. LdCyp has been represented as a surface contactnetwork (SCN) based on the surface complementarity (Sm) of interacting residues within themolecular interior. The application of Sm to side chain packing within proteins make it a very sensitive indicator of subtle perturbations in packing, in the thermal unfolding of the protein. Network based metrics have been defined to track the sequential changes in the disintegration ofthe SCN spanning the hydrophobic core of LdCyp and these metrics prove to be highly sensitive compared to traditional metrics in indicating the increased conformational (and dynamical) flexibility in the network. These metrics have been applied to suggest criteria distinguishing DMG, WMG and transition state ensembles and to identify key residues involved in crucial conformational/topological events during the unfolding process.

From work contracts and group buying platforms to political coalitions and international climate and economical summits, often individuals assemble in groups that must collectively reach decisions that may favor each part unequally. Here we quantify to which extent our network ties promote the evolution of collective fairness in group interactions, modeled by means of Multiplayer Ultimatum Games (MUG). We show that a single topological feature of social networks-which we call structural power-has a profound impact on the tendency of individuals to take decisions that favor each part equally. Increased fair outcomes are attained whenever structural power is high, such that the networks that tie individuals allow them to meet the same partners in different groups, thus providing the opportunity to strongly influence each other. On the other hand, the absence of such close peer-influence relationships dismisses any positive effect created by the network. Interestingly, we show that increasing the structural power of a network leads to the appearance of well-defined modules-as found in human social networks that often exhibit community structure-providing an interaction environment that maximizes collective fairness.

Papain-like proteases contain an N-terminal pro-peptide in their zymogen form that is important for correct folding and spatio-temporal regulation of the proteolytic activity of these proteases. Catalytic removal of the pro-peptide is required for the protease to become active. In this study, we have generated three different mutants of papain (I86F, I86L and I86A) by replacing the residue I86 in its pro-peptide region, which blocks the specificity determining S2-subsite of the catalytic cleft of the protease in its zymogen form with a view to investigate the effect of mutation on the catalytic activity of the protease. Steady-state enzyme kinetic analyses of the corresponding mutant proteases with specific peptide substrates show significant alteration of substrate specificity-I86F and I86L have 2.7 and 29.1 times higher kcat/Km values compared to the wild-type against substrates having Phe and Leu at P2 position, respectively, while I86A shows lower catalytic activity against majority of the substrates tested. Far-UV CD scan and molecular mass analyses of the mature form of the mutant proteases reveal similar CD spectra and intact masses to that of the wild-type. Crystal structures of zymogens of I86F and I86L mutants suggest that subtle reorganization of active site residues, including water, upon binding of the pro-peptide may allow the enzyme to achieve discriminatory substrate selectivity and catalytic efficiency. However, accurate and reliable predictions on alteration of substrate specificity require atomic resolution structure of the catalytic domain after zymogen activation, which remains a challenging task. In this study we demonstrate that through single amino acid substitution in pro-peptide, it is possible to modify the substrate specificity of papain and hence the pro-peptide of a protease can also be a useful target for altering its catalytic activity/specificity.

Recovery of sensory and motor functions following traumatic spinal cord injury (SCI) is dependent on injury severity. Here we identified 49 proteins from cerebrospinal fluid (CSF) of SCI patients, eight of which were differentially abundant among two severity groups of SCI. It was observed that the abundance profiles of these proteins change over a time period of days to months post SCI. Statistical analysis revealed that these proteins take part in several molecular pathways including DNA repair, protein phosphorylation, tRNA transcription, iron transport, mRNA metabolism, immune response and lipid and ATP catabolism. These pathways reflect a set of mechanisms that the system may adopt to cope up with the assault depending on the injury severity, thus leading to observed physiological responses. Apart from putting forward a picture of the molecular scenario at the injury site in a human study, this finding further delineates consequent pathways and molecules that may be altered by external intervention to restrict neural degeneration.

Bacteriorhodopsins are a large family of seven-helical transmembrane proteins that function as light-driven proton pumps. Here, we present the crystal structure of a new member of the family, Haloarcula marismortui bacteriorhodopsin I (HmBRI) D94N mutant, at the resolution of 2.5 Å. While the HmBRI retinal-binding pocket and proton donor site are similar to those of other archaeal proton pumps, its proton release region is extended and contains additional water molecules. The protein's fold is reinforced by three novel inter-helical hydrogen bonds, two of which result from double substitutions relative to Halobacterium salinarum bacteriorhodopsin and other similar proteins. Despite the expression in Escherichia coli and consequent absence of native lipids, the protein assembles as a trimer in crystals. The unique extended loop between the helices D and E of HmBRI makes contacts with the adjacent protomer and appears to stabilize the interface. Many lipidic hydrophobic tail groups are discernible in the membrane region, and their positions are similar to those of archaeal isoprenoid lipids in the crystals of other proton pumps, isolated from native or native-like sources. All these features might explain the HmBRI properties and establish the protein as a novel model for the microbial rhodopsin proton pumping studies.

Mosquito-borne diseases have become a significant health issue in many regions around the world. For tropical countries, diseases such as Dengue, Zika, and Chikungunya, became epidemic in the last decades. Health surveillance reports during this period were crucial in providing scientific-based information to guide decision making and resources allocation to control outbreaks. In this work, we perform data analysis of the last Chikungunya epidemics in the city of Rio de Janeiro by applying a compartmental mathematical model. Sensitivity analyses were performed in order to describe the contribution of each parameter to the outbreak incidence. We estimate the "basic reproduction number" for those outbreaks and predict the potential epidemic outbreak of the Mayaro virus. We also simulated several scenarios with different public interventions to decrease the number of infected people. Such scenarios should provide insights about possible strategies to control future outbreaks.

The toxic effect of strained hydrocarbon 2,2'-bis (bicyclo[2.2.1]heptane) (BBH) was studied using whole-cell bacterial lux-biosensors based on Escherichia coli cells in which luciferase genes are transcriptionally fused with stress-inducible promoters. It was shown that BBH has the genotoxic effect causing bacterial SOS response however no alkylating effect has been revealed. In addition to DNA damage, there is an oxidative effect causing the response of OxyR/S and SoxR/S regulons. The most sensitive to BBH lux-biosensor was E. coli pSoxS-lux which reacts to the appearance of superoxide anion radicals in the cell. It is assumed that the oxidation of BBH leads to the generation of reactive oxygen species, which provide the main contribution to the genotoxicity of this substance.

Currently available genetically encoded calcium indicators (GECIs) utilize calmodulins (CaMs) or troponin C from metazoa such as mammals, birds, and teleosts, as calcium-binding domains. The amino acid sequences of the metazoan calcium-binding domains are highly conserved, which may limit the range of the GECI key parameters and cause undesired interactions with the intracellular environment in mammalian cells. Here we have used fungi, evolutionary distinct organisms, to derive CaM and its binding partner domains and design new GECI with improved properties. We applied iterative rounds of molecular evolution to develop FGCaMP, a novel green calcium indicator. It includes the circularly permuted version of the enhanced green fluorescent protein (EGFP) sandwiched between the fungal CaM and a fragment of CaM-dependent kinase. FGCaMP is an excitation-ratiometric indicator that has a positive and an inverted fluorescence response to calcium ions when excited at 488 and 405 nm, respectively. Compared with the GCaMP6s indicator in vitro, FGCaMP has a similar brightness at 488 nm excitation, 7-fold higher brightness at 405 nm excitation, and 1.3-fold faster calcium ion dissociation kinetics. Using site-directed mutagenesis, we generated variants of FGCaMP with improved binding affinity to calcium ions and increased the magnitude of FGCaMP fluorescence response to low calcium ion concentrations. Using FGCaMP, we have successfully visualized calcium transients in cultured mammalian cells. In contrast to the limited mobility of GCaMP6s and G-GECO1.2 indicators, FGCaMP exhibits practically 100% molecular mobility at physiological concentrations of calcium ion in mammalian cells, as determined by photobleaching experiments with fluorescence recovery. We have successfully monitored the calcium dynamics during spontaneous activity of neuronal cultures using FGCaMP and utilized whole-cell patch clamp recordings to further characterize its behavior in neurons. Finally, we used FGCaMP in vivo to perform structural and functional imaging of zebrafish using wide-field, confocal, and light-sheet microscopy.

The routine prediction of three-dimensional protein structure from sequence remains a challenge in computational biochemistry. It has been intuited that calculated energies from physics-based scoring functions are able to distinguish native from nonnative folds based on previous performance with small proteins and that conformational sampling is the fundamental bottleneck to successful folding. We demonstrate that as protein size increases, errors in the computed energies become a significant problem. We show, by using error probability density functions, that physics-based scores contain significant systematic and random errors relative to accurate reference energies. These errors propagate throughout an entire protein and distort its energy landscape to such an extent that modern scoring functions should have little chance of success in finding the free energy minima of large proteins. Nonetheless, by understanding errors in physics-based score functions, they can be reduced in a post-hoc manner, improving accuracy in energy computation and fold discrimination.

Here we present a study of the thermal inactivation and the refolding of the proteins in Gram positive Bacillus subtilis. To enable use of bacterial luciferases as the models for protein thermal inactivation and refolding in B. subtilis cells, we developed a variety of bright luminescent B. subtilis strains which express luxAB genes encoding luciferases of differing thermolability. The kinetics of the thermal inactivation and the refolding of luciferases from Photorhabdus luminescens and Photobacterium leiognathi were compared in Gram negative and Gram positive bacteria. In B. subtilis cells, these luciferases are substantially more thermostable than in Escherichia coli. Thermal inactivation of the thermostable luciferase P. luminescens in B. subtilis at 48.5°С behaves as a first-order reaction. In E.coli, the first order rate constant (Kt) of the thermal inactivation of luciferase in E. coli exceeds that observed in B. subtilis cells 2.9 times. Incubation time dependence curves for the thermal inactivation of the thermolabile luciferase of P. leiognathi luciferase in the cells of E. coli and B. subtilis may be described by first and third order kinetics, respectively. Here we shown that the levels and the rates of refolding of thermally inactivated luciferases in B. subtilis cells are substantially lower that that observed in E. coli. In dnaK-negative strains of B. subtilis, both the rates of thermal inactivation and the efficiency of refolding are similar to that observed in wild-type strains. These experiments point that the role that DnaKJE plays in thermostability of luciferases may be limited to bacterial species resembling E. coli.

As the microenvironment of a cell changes, associated mechanical cues may lead to changes in biochemical signaling and inherently mechanical processes such as mitosis. Here we explore the effects of confined mechanical environments on cellular responses during mitosis. Previously, effects of mechanical confinement have been difficult to optically observe in three-dimensional and in vivo systems. To address this challenge, we present a novel microfluidic perfusion culture system that allows controllable variation in the level of confinement in a single axis allowing observation of cell growth and division at the single-cell level. The device is capable of creating precise confinement conditions in the vertical direction varying from high (3 µm) to low (7 µm) confinement while also varying the substrate stiffness (E = 130 kPa and 1 MPa). The Human cervical carcinoma (HeLa) model with a known 3N+ karyotype was used for this study. For this cell line, we observe that mechanically confined cell cycles resulted in stressed cell divisions: (i) delayed mitosis, (ii) multi- daughter mitosis events (from 3 up to 5 daughter cells), (iii) unevenly sized daughter cells, and (iv) induction of cell death. In the highest confined conditions, the frequency of divisions producing more than two progeny was increased an astounding 50-fold from unconfined environments, representing about one half of all successful mitotic events. Notably, the majority of daughter cells resulting from multipolar divisions were viable after cytokinesis and, perhaps suggesting another regulatory checkpoint in the cell cycle, were in some cases observed to re-fuse with neighboring cells post-cytokinesis. The higher instances of abnormal mitosis that we report in confined mechanically stiff spaces, may lead to increased rates of abnormal, viable, cells in the population. This work provides support to a hypothesis that environmental mechanical cues influences structural mechanisms of mitosis such as geometric orientation of the mitotic plane or planes.