To clarify the relationships among critical temperature, critical magnetic field, and critical current density, this paper describes many-body interactions of quantum magnetic fluxes (i.e., vortices) and calculates pinning-related critical current density. All calculations are analytically derived, without numerical or fitting methods. Afteralculating a magnetic flux quantum mass, we theoretically obtain the critical temperature in a many-body interaction scenario (which can be handled by our established method). We also derive the critical magnetic field and inherent critical current density at each critical temperature. Finally, we determine the pinning-related critical current density with self-fields. The relationships between the critical magnetic field and critical temperature, inherent critical current density and critical temperature, and pinning critical current density and temperature were consistent with experimental observations. From the critical current density and critical magnetic field, we clarified the magnetic field transition. It appears that a magnetic flux quantum collapses when the lattice of magnetic flux quanta melts. Our results, combined with our previously published papers, provide a comprehensive understanding of the transition points in high-T_c cuprates.

The Zika virus (ZIKV) is a mosquito-borne Flavivirus and can be transmitted through an infected mosquito bite or through human-to-human interaction by sexual activity, blood transfusion, breastfeeding or perinatal exposure. After the 2015-2016 outbreak in Brazil, a strong link between ZIKV infection and microcephaly emerged. ZIKV specifically targets human neural progenitor cells, suggesting that proteins encoded by ZIKV bind and inactivate host cell proteins leading to microcephaly. Here, we present a systematic annotation of interactions between human proteins and the seven non-structural ZIKV proteins corresponding to a Brazilian isolate. The interaction network was generated by combining tandem-affinity purification followed by mass spectrometry with yeast two-hybrid screens. We identified 150 human proteins, involved in distinct biological processes, as interactors to ZIKV non-structural proteins. Our interacting network is composed of proteins that have been previously associated with microcephaly in human genetic disorders and/or animal models. This study builds on previously published interacting networks of ZIKV and genes related to autosomal recessive primary microcephaly to generate a catalog of human cellular targets of ZIKV proteins implicated in processes related to microcephaly in humans. Collectively, this data can be used as a resource for future characterization of ZIKV infection biology and help create a basis for the discovery of drugs which may disrupt the interaction and reduce the health damage to the fetus.

Glycosphingolipids (GSL) represent a highly heterogeneous class of lipids with many cellular functions, implicated in a wide spectrum of human diseases. Their isolation, detection, and comprehensive structural analysis is a challenging task due to the structural diversity of GSL molecules. In this work, GSL subclasses are isolated from human plasma using an optimized monophasic ethanol–water solvent system capable to recover a broad range of GSL species. Obtained deproteinized plasma is subsequently purified and concentrated by C18-based solid-phase extraction (SPE). The hydrophilic interaction liquid chromatography (HILIC) coupled to electrospray ionization linear ion trap tandem mass spectrometry (ESI-LIT-MS/MS) is used for GSL analysis in the human plasma extract. Our results provide an in-depth profiling and structural characterization of glycosphingolipid and some phospholipid subclasses identified in the human plasma based on their retention times and the interpretation of tandem mass spectra. The structural composition of particular lipid species is readily characterized based on the detailed interpretation of MS and MS/MS spectra and further confirmed by specific fragmentation behavior following predictable patterns, which yields to the unambiguous identification of 154 GSL species within 7 lipid subclasses and 77 phospholipids representing the highest number of GSL species ever reported in the human plasma. The developed HILIC-ESI-MS/MS method can be used for further clinical and biological research of GSL in the human blood or other biological samples.

This paper discovers that current variational principle and Noether theorem for different physics systems with (in)finite freedom systems have missed the double extremum processes of the general extremum functional that both is deduced by variational principle and is necessarily taken in deducing all the physics laws, but these have not been corrected for over a century since Noether's proposing her famous theorem, which result in the crisis deducing relevant mathematical laws and all physics laws. This paper discovers there is the hidden logic cycle that one assumes Euler-Lagrange equations, and then he finally deduces Euler-Lagrange equations via the equivalent relation in the whole processes in all relevant current references. This paper corrects the current key mistakes that when physics systems choose the variational extreme values, the appearing processes of the physics systems are real physics processes, otherwise, are virtual processes in all current articles, reviews and (text)books. The real physics should be after choosing the variational extreme values of physics systems, the general extremum functional of the physics systems needs to further choose the minimum absolute extremum zero of the general extremum functional, otherwise, the appearing processes of physics systems are still virtual processes. Using the double extremum processes of the general extremum functionals, the crisis and the hidden logic cycle in current variational principle and current Noether theorem are solved. Furthermore, the new mathematical and physical double extremum processes and their new mathematical pictures and physics for (in)finite freedom systems are discovered. This paper gives both general variational principle and general Noether theorem as well as their classical and quantum new physics, which would rewrite all relevant current different branches of science, as key tools of studying and processing them.

Exposure of phosphatidylserine (PS) in the outer leaflet of the plasma membrane is induced by infection with several members of the Alphaherpesvirinae subfamily. There is evidence that PS is used by the equine herpesvirus type 1 (EHV-1) during entry, but the exact role of PS and other phospholipids in the entry process remains unknown. Here, we investigated the interaction of differently charged phospholipids with virus particles and determined their influence on infection. Our data show that liposomes containing negatively charged PS or positively charged DOTAP [N-[1-(2,3-Dioleoyloxy)propyl]-N,N,N-trimethylammonium)] inhibited EHV-1 infection, while neutral phosphatidylcholine (PC) had no effect. Inhibition of infection with PS was transient, decreased with time, and was dose dependent. Our findings indicate that both cationic and anionic phospholipids can interact with the virus and reduce infectivity, while acting through different mechanisms. Charged phospholipids were found to have antiviral effects and can may be used to inhibit EHV-1 infection.

The anode of a microbial fuel cell (MFC) was formed on a graphite electrode and immobilized Gluconobacter oxydans VKM-1280 bacterial cells. Immobilization was performed in chitosan, poly(vinyl alcohol) or N-vinylpyrrolidone-modified poly(vinyl alcohol). Ethanol was used as substrate. The anode was modified using multiwalled carbon nanotubes. The aim of the modification was to create a conductive network between cell lipid membranes, containing exposed PQQ-dependent alcoholdehydrogenases, and the electrode to facilitate electron transfer in the system. The bioelectrochemical characteristics of modified anodes at various cell/polymer ratios were assessed via current density, power density, polarization curves and impedance spectres. MFCs based on chitosan at a matrix/cell volume ratio of 5:1 produced maximal power characteristics of the system (8.3 μW/cm2) at a minimal resistance (1111 Ohm cm2). Modification of the anode by multiwalled carbon nanotubes led to a slight decrease of internal resistance (down to 1078 Ohm cm2) and to an increase of generated power density up to 10.6 μW/cm2. We explored the possibility of accumulating electric energy from an MFC on a 6,800-μF capacitor via a boost converter. Generated voltage was increased from 0.3 V up to 3.2 V. Accumulated energy was used to power a Clark-type biosensor and a bluetooth transmitter with three sensors, a miniature electric motor and a light-emitting diode.

Considerable attention has been given to the research field of bioorganometallic chemistry, which is a hybrid chemistry field between biology and organometallic chemistry. The introduction of biomolecules, which have hydrogen bonding sites and chiral centers, into organometallic compounds is considered to be a promising strategy to construct chirality-organized bioorganometallic conjugates. This feature paper sketches an outline of induction of helical chirality into bioorganometallic conjugates. Topics covered include control of the helical chirality of 1,n’-disubstituted ferrocene moieties in ferrocene-dipeptide conjugates and the chirality induction of the Au(I)–Au(I) axis in the dinuclear organogold(I)-uracil conjugates.

In this study, a novel theory to investigate the mass oscillation of particles is proposed. It has been proven that, at high-energy conditions, the fermion field described by Dirac’s Lagrangian interacts with the half-integer spin tachyon field with negative energy, causing the formation of composite particles whose mass depends on the total angular momentum. The proposed theory is based on a new interpretation of the Majorana equation for particles with arbitrary spin and shows that mass oscillation is a phenomenon in which the component of particle decay prevails over that of mixing mass states. Using the kinematic of Lemke for spacelike particle decay, we propose a mechanism able to explain the neutrino flavour change. The proposed mechanism is also investigated concerning the shape of its spectrum. Finally, the Lagrangian field of composite particles is formulated.

In quantum approaches to consciousness, the authors try to propose a model and mechanism for the mind-brain interaction using modern physics and some quantum concepts which do not exist in the classical physics. The independent effect of mind on the brain has been one of the challenging issues in the history of science and philosophy. In some recent mind-brain interaction models, the direct influence of mind on matter is either not accepted (as in Stapp’s model) or not clear, and there have not been any clear mechanism for it (as in Penrose-Hameroff’s model or in Eccles’s model). In this manuscript we propose a model and mechanism for mind’s effect on the matter using an extended Bohmian quantum mechanics and Avicenna’s ideas. We show that mind and mental states can affect brain’s activity without any violation of physical laws. This is a mathematical and descriptive model which shows the possibility of providing a causal model for mind’s effect on matter. It is shown that this model guarantees the realistic philosophical constraints and respects the laws of nature. In addition, it is shown that it is in agreement with the Libet style experimental results and parapsychological data. To propose this model, we obtained a modified (non-unitary) Schrödinger equation via second quantization method which affects the particle through a modified quantum potential and a new term in the continuity equation. At the second quantized level, which is equivalent to quantum field theory level (QFT), we can use the path integral formalism of Feynman. We show that there are three methods to extend Bohmian QM via path integral formalism, which has different interpretations. By numerical simulation of trajectories in the two-slits experiment, we show their differences and choose one of these methods for our mind-brain model which can be the basis for explaining some phenomena which are not possible to explain in the standard Bohmian QM.

In atomic GdFe$_2$ films capped by 4$d$ and 5$d$ transition metals, we show that skyrmions with diameters smaller than 12 nm can emerge. The Dzyaloshinskii--Moriya interaction (DMI), exchange energy, and the magnetocrystalline anisotropy (MCA) energy were investigated based on density functional theory. Since DMI and MCA are caused by spin--orbit coupling (SOC), they are increased with 5$d$ capping layers which exhibit strong SOC strength. We discover a skyrmion phase by using atomistic spin dynamic simulations at small magnetic fields of $\sim$1 T. In addition, a ground state that a spin spiral phase is remained even at zero magnetic field for both films with 4$d$ and 5$d$ capping layers.

With the long-term and large-scale use, herbicides have been well known to influence tritrophic interactions particularly natural enemies of pests in agro-ecosystems. On the other hand, herbivorous insects, especially the generalist pests, have developed antagonistic interaction to different insecticides, toxic plant secondary metabolites and even heavy metals. However, whether exposure to herbicides would affect resistance of insects against insecticides is largely unknown, especially in agricultural pests. Here, we first reported that pre-exposure to two widely used herbicides butachlor and haloxyfop-methyl for 48 h can prime resistance of a generalist agricultural pest Helicoverpa armigera Hübner against insecticide methomyl and fungal toxin aflatoxin B1. In addition, there were no significant differences between control and herbicides-treated caterpillars on weight gain, pupal weight and pupation rates, suggesting that exposure to herbicides induce resistance of H. armigera accompanied with no fitness cost. Moreover, by determining detoxifying enzyme activities and toxicity bioassay with additional inhibitor of cytochrome P450 piperonyl butoxide (PBO), we showed that exposure to herbicides might prime P450-mediated detoxification of H. armigera against insecticide. Based on these results, we propose that exposure to herbicides primes resistance of H. armigera against insecticide by eliciting a clear elevation of predominantly P450 monooxygenase activities in midgut and fat body.

This paper presents a computational approach designed to construct and query a literature-based knowledge graph for predicting novel drug therapeutics. The main objective is to offer a platform that discovers drug combinations from FDA-approved drugs and accelerates their investigations by domain scientists. Specifically, the paper introduced the following algorithms: (1) an algorithm for constructing the knowledge graph from drug, gene, and disease mentions in the biomedical literature; (2) an algorithm for vetting the knowledge graph from drug combinations that may pose a risk of drug interaction; (3) and two querying algorithms for searching the knowledge graph by a single drug or a combination of drugs. The resulting knowledge graph had 844 drugs, 306 gene/protein features, and 19 disease mentions. The original number of drug combinations generated was 2,001. We queried the knowledge graph to eliminate noise generated from chemicals that are not drugs. This step resulted in 614 drug combinations. When vetting the knowledge graph to eliminate the potentially risky drug combinations, it resulted in predicting 200 combinations. Our domain expert manually eliminated extra 54 combinations which left only 146 combination candidates. Our three-layered knowledge graph, empowered by our algorithms, offered a tool that predicted drug combination therapeutics for scientists who can further investigate from the viewpoint of drug targets and side effects.

Humans are evolutionary-driven to adult mating and conceive social expectations on the quality of their affiliations. The genetic susceptibility to adverse environments in critical periods can alter close relationships. The current research investigates how the promoter region of the Serotonin Transporter Gene (5-HTTLPR) and perceived caregiving behavior in childhood could influence the social expectations on close adult relationships. For this purpose, 5-HTTLPR data was collected from the buccal mucosa of 65 Italian individuals (33 males). The participants filled a) the Parental Bonding Instrument (PBI) to provide the levels of care and overprotection from mother and father, and b) the Experience in Close Relationships-Revised (ECR-R) to report the social expectations on the intimate relationship assessed in terms of anxiety and avoidance from the partner. An interaction effect between 5-HTTLPR and PBI dimensions on the ECR-R scores was hypothesized. Results confirmed that the interplay between the genetic groups and history of maternal overprotection predicted avoidance experienced in romantic relationships in adulthood. Moreover, both adult anxiety and avoidance felt in an intimate relationship were found to covary as a function of maternal overprotection. The present work proposes further evidence of the genetic and parental mechanisms regulating social expectations involved in close relationships.

Myelin ensheathes selected axonal segments within the nervous system, resulting primarily in nerve impulse acceleration, as well as mechanical and trophic support for neurons. In the central and peripheral nervous systems, various proteins that contribute to the formation and stability of myelin are present, which also harbour pathophysiological roles in myelin disease. Many myelin proteins share common attributes, including small size, high hydrophobicity, multifunctionality, longevity, and intrinsic disorder. With recent advances in protein biophysical characterization and bioinformatics, it has become evident that intrinsically disordered proteins (IDPs) are abundant in myelin, and their flexible nature enables multifunctionality. Here, we review known myelin IDPs, their conservation, molecular characteristics and functions, and their disease relevance, along with open questions and speculations. We place emphasis on classifying the molecular details of IDPs in myelin and correlate these with their various functions, including susceptibility to post-translational modifications, function in protein-protein and protein-membrane interactions, as well as their role as extended entropic chains. We discuss how myelin pathology can relate to IDPs and which molecular factors are potentially involved.

In this article, we report how we constructed a dataset that contains the responses to a survey designed for investigating the relationship that humans have with their smart devices. The dataset has been collected in May-July 2020 and is a sample of over 500 respondents of various different ethnicities and backgrounds. These data have been used for modelling the ways people relate to their devices using the notion of agency. However, the data can be used for complementing any study that intends to investigate a tool-mediated communication from the perspective of the users and via a variety of attitudes and expectations the users invest in their devices and in themselves as users. This article presents the survey items as well as some preliminary data insights. The data have been collected in English and answers have been anonymized in order to ensure GDPR compliance. They are stored in a .csv file containing the respondents’ answers to the questions.

Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting variety of hydrophobic ligands including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth and this can be attributed to its estrogen-binding ability. Despite AFP has long been investigated, its three-dimensional (3D) structure has not been experimentally resolved and molecular mechanisms underlying AFP-ligand interaction remain obscure. In our study we constructed homology-based 3D model of human AFP (HAFP) with the purpose to perform docking of ERα ligands, three agonists (17β-estradiol, estrone and diethylstilbestrol) and three antagonists (tamoxifen, afimoxifene and endoxifen) into the obtained structure. Based on ligand docked scoring function, we identified three putative estrogen- and antiestrogen-binding sites with different ligand binding affinities. Two high-affinity sites were located in (i) a tunnel formed within HAFP subdomains IB and IIA and (ii) opposite side of the molecule in a groove originating from cavity formed between domains I and III, while (iii) the third low-affinity site was found at the bottom of the cavity. 100 ns MD simulation allowed studying their geometries and showed that HAFP-estrogen interactions occur due to van der Waals forces, while both hydrophobic and electrostatic interactions were almost equally involved in HAFP-antiestrogen binding. MM/GBSA rescoring method estimated binding free energies (ΔG_bind) and showed that antiestrogens have higher affinities to HAFP as compared to estrogens. We performed in silico point substitutions of amino acid residues to confirm their roles in HAFP-ligand interactions and showed that Thr132, Leu138, His170, Phe172, Ser217, Gln221, His266, His316, Lys453, and Asp478 residues along two disulfide bonds, Cys224-Cys270 and Cys269-Cys277 have key roles in both HAFP-estrogen and HAFP-antiestrogen binding. Data obtained in our study contribute to understanding mechanisms underlying protein-ligand interactions and anti-cancer therapy strategies based on ER-binding ligands.

Purpose: To improve numerical simulation of the non-contact tonometry test by using Arbitrary Eulerian-Lagrangian deforming mesh in the coupling between computational fluid dynamics model of an air jet and finite element model of the human eye. Methods: Computational fluid dynamics model simulated impingement of the air puff and consisted of 25920 wedge6 elements and employed Spallart-Allmaras model to simulate capture turbulence of the air jet. The time span of the jet wais 30 ms and maximum Reynolds number

Stenting is a common method for treating atherosclerosis. A metal or polymer stent is deployed to open the stenosed artery or vein. After the stent is deployed, the blood flow dynamics influence the mechanics by compressing and expanding the structure. If the stent does not respond properly to the resulting stress, vascular wall injury or re-stenosis can occur. In this work, Discrete Multiphysics is used to study the mechanical deformation of the coronary stent and its relationship with the blood flow dynamics. The major parameters responsible for deforming the stent are sort in terms of dimensionless numbers and a relationship between the elastic forces in the stent and pressure forces in the fluid is established. The blood flow and the stiffness of the stent material contribute significantly to the stent deformation and affect the rate of deformation. The stress distribution in the stent is not uniform with the higher stresses occurring at the nodes of the structure.

The work is devoted to the investigation of virus quasispecies evolution and diversification due to mutations, competition for host cells, and cross-reactive immune responses. The model consists of a nonlocal reaction-diffusion equation for the virus density depending on the genotype considered as a continuous variable and on time. This equation contains two integral terms corresponding to the nonlocal effects of virus interaction with host cells and with immune cells. In the model, a virus strain is represented by a localized solution concentrated around some given genotype. Emergence of new strains corresponds to a periodic wave propagating in the space of genotypes. The conditions of appearance of such waves and their dynamics are described.

Alzheimer’s disease (AD) is the most common cause of dementia worldwide. Pathological deposits of neurotoxin proteins within the brain, such as amyloid-Beta and hyperphosphorylated tau tangles, are prominent features in AD. The prion protein (PrP) is involved in neurodegeneration via its conversion from the normal cellular form PrPc, to the infection form PrP Sc. Some studies indicated that posttranslationally modified PrPc isoforms plays a fundamental role in AD pathological progression. Several studies have shown that interaction of Aβ oligomers with N-terminal residues of the PrPc protein region appears critical for neuronal toxicity. The PrPc-Aβ binding always occur in AD brains and is never detected in nondemented controls and the binding of Aβ aggregates to PrPc is restricted to the N-terminus of PrPc.

Globally mangrove forests are substantially declining and a globally synthesized database of the drivers of deforestation and drivers’ interaction is scarce. Here we synthesized the key social-ecological drivers of global mangrove deforestation by reviewing about two hundred published scientific studies over the last four decades (from 1980 to 2021). Our focus was on both natural and anthropogenic drivers with gradual and abrupt impacts and their geographic ranges of effects and how these drivers interact. We also summarized the patterns of global mangrove coverage decline between 1990 and 2020 and identified the threatened mangrove species and their geographic ranges. Our consolidated studies reported a 8,600 km2 decline in the global mangrove coverage between 1990 and 2020 with the highest decline occurring in South and Southeast Asia (3870 km2). We could identify 11 threatened mangrove species, two of which are critically endangered (Sonneratia griffithii and Bruguiera hainseii). Our reviewed studies pointed to aquaculture and agriculture as the predominant driver of global mangrove deforestation though the spatial distribution of their impacts varied. Gradual climate variations, i.e. seal-level rise, long-term precipitation and temperature changes and driven coastline erosion, constitute the second major group of drivers. Our findings underline a strong interaction across natural and anthropogenic drivers with the strongest interaction between the driver groups aquaculture and agriculture and industrialization and pollution. Our results suggest prioritizing globally coordinated empirical studies linking drivers and mangrove changes and a global development of policies for mangrove conservation.

OpenAI has managed to turn 100 million heads in two months towards their new Language model tool (LM) ChatGPT. The third generation Generative Pretrained Transformer (GPT-3) has the capacity to tackle simple to complex and sophisticated problems, while providing reasoning behind its generated answers. ChatGPT can be used to increase productivity and improve efficiency and face challenging problems. Programming mobile applications is a challenging task that requires professional software engineers, skills and abilities to be developed. The following paper takes a case study approach to assess how novice app developers can use ChatGPT to generate Java scripts that will be used in Android studio to create a functional application. The results after, many iterations and ongoing conversations with ChatGPT managed to create an application for the anticipated function. Important insights have been drawn from the case study that could set the ground for any novice user seeking to create applications using Java scripting and Android Studio.

Long-term potentiation (LTP) is a molecular basis of memory formation. Here, we demonstrate that LTP critically depends on muscle fructose 1,6-bisphosphatase 2 (Fbp2) – a glyconeogenic enzyme and moonlighting protein protecting mitochondria against stress. We show that LTP induction regulates Fbp2 association with neuronal mitochondria and Camk2, and that the Fbp2-Camk2 interaction correlates with Camk2 autophosphorylation. Silencing of Fbp2 expression or simultaneous inhibition and tetramerization of the enzyme with a synthetic effector mimicking the action of physiological inhibitors (NAD⁺ and AMP) abolishes Camk2 autoactivation and blocks formation of the early phase of LTP and expression of the late phase LTP markers. Astrocyte-derived lactate reduces NAD⁺/NADH ratio in neurons and thus, diminishes the pool of tetrameric and increases the fraction of dimeric Fbp2. We therefore hypothesize that this NAD⁺-level-dependent increase of the Fbp2 dimer/tetramer ratio might be a crucial mechanism in which astrocyte-neuron lactate shuttle stimulates LTP formation.

Accurate prediction of the self-propulsion performance is one of the most important factors for energy-efficient design of a ship. In general, the hydrodynamic performance of a full-scale ship could be achieved by model-scale simulation or towing tank test with extrapolations. With the development of CFD methods and computing power, directly predict ship performance with full-scale CFD is an important approach. In this article, a numerical study on the full-scale self-propulsion performance with propeller operating behind ship at model- and full-scale is presented. The study includes numerical simulations using RANS method with double-model and VOF model respectively and scale effect analysis based on overall performance, local flow fields and detailed vortex identification. Verification study on grid convergence is also performed for full-scale simulation with global and local mesh refinements. And a series of sea trail tests were performed to collect reliable data for the validation of CFD predictions. The analysis of scale effect on hull-propeller interaction shows that the difference on hull boundary layer and flow separation is the main source of scale effect on ship wake. And the results of the fluctuations of propeller thrust and torque along with circulation distribution and local flow field show that propeller’s loading is significantly higher for model-scale ship. It is suggested that the difference on vortex evolution and interaction is more pronounced and have larger effects on ship’s powering performance at model-scale than full-scale according to the simulation results. From the study on self-propulsion prediction, it could be concluded that the simplification on free surface treatment does not only affect the wave-making resistance for bare hull but also the propeller performance and propeller induced ship resistance which can produced up to 5% uncertainty to the power prediction. Roughness is another important factor in full-scale simulation because it has up to approximately 7% effect on the delivery power. As a result of validation study, the numerical simulations of full-scale ship self-propulsion shows good agreement with the sea trail data especially for cases that have considered both roughness and free surface effects. This result will largely enhance our confidence to apply full-scale simulation in the prediction of ship’s self-propulsion performance in the future ship designs.

The Aβ cascade and alternations of biomarkers in neuro-inflammation, synaptic dysfunction and neuronal injury followed by Aβ have progressed. But the question is how to use the biomarkers. Here, we examine the evidence and pathogenic implications of protein interactions and the time order of alternation. After the deposition of Aβ, the change of tau, NfL and NG is the main alternation and connection to others. The neuro-inflammation, synaptic dysfunction and neuronal injury function is exhibited prior the structural and metabolic changes in the brain following Aβ deposition. The time order of such biomarkers compared to the tau protein is not clear. Despite the close relationship between biomarkers and plaque Aβ deposition, several factors favor one or the other. There is an interaction between the proteins that CSF SNAP-25, VILIP-1 and YKL-40 can predict the brain amyloid burden. The Aβ cascade hypothesis could be the pathway, but not all subjects are converted to AD, even with very high elevated Aβ. The interaction of biomarkers and the time order of change require further research to identify the right subjects and right molecular target for precision medicine therapies.

Congenital Pouch Colon (CPC) is a rare anorectal anomaly common to North Western India specifically Rajasthan. Despite efforts to understand the clinical genetic makeup of CPC, no attempt on identifying non-coding RNAs was done. We have earlier reported CPC's rare variants from whole exome sequencing across 18 affected samples in a total of 64 subjects. A Smith-Waterman algorithm was used to infer a couple of lncRNAs from WES samples of CPC with predictions from the Noncode database. Further screening and quantification using PCR, we ascertained interactions using Micro Scale Thermophoresis (MST). We report the role of lnc-EPB41-1-1 shown to be promiscuously interacting with KIF13A substantiating their role in regulation.

In this work we report on our effort to design and implement an early introduction to basic robotics principles for children at kindergarten age. The humanoid robot Pepper, which is a great platform for human-robot interaction experiments, was presenting the lecture by reading out the contents to the children making use of its speech synthesis capability. One of the main challenges of this effort was to explain complex robotics contents in a way that pre-school children could follow the basic principles and ideas using examples from their world of experience. A quiz in a Runaround-game-show style after the lecture activated the children to recap the contents they acquired about how mobile robots work in principle. Besides the thrill being exposed to a mobile robot that would also react to the children, they were very excited and at the same time very concentrated. What sets apart our effort from other work is that part of the lecturing is actually done by a robot itself and that a quiz at the end of the lesson is done using robots as well. To the best of our knowledge this is one of only few attempts to use Pepper not as a tele-teaching tool, but as the teacher itself in order to engage pre-school children with complex robotics contents. We got very positive feedback from the children as well as from their educators.

This study, based on the AISAS model, explores the impact of the interaction effect between visual and auditory signals on consumer purchase behavior. Using experimental methods, 120 participants were randomly assigned to four different visual and auditory signal combinations, and their purchase intentions and actual purchase behavior were measured. The results show that the interaction effect between visual and auditory signals has a significant impact on both purchase intentions and actual purchase behavior, and there is a significant positive relationship. Specifically, when visual and auditory signals are mutually consistent, consumers have the highest purchase intentions and actual purchase behavior; when both visual and auditory signals are absent, consumers have the lowest purchase intentions and actual purchase behavior; when either the visual or auditory signal is missing, consumers' purchase intentions and actual purchase behavior are in between the two extremes. This study provides a new perspective for understanding consumers' decision-making processes in multi-sensory environments and offers valuable insights for the development of marketing strategies.

Manipulating cloth-like deformable objects (CDOs) is a long-standing problem in the robotics community. CDOs are flexible (non-rigid) objects that do not show a detectable level of com- pression strength while two points on the article are pushed towards each otherand include objects such as ropes (1D), fabrics (2D) and bags (3D). In general, CDOs’ many degrees of freedom (DoF) introduce severe self-occlusion and complex state-action dynamics as significant obstacles for perception and manipulation systems. These challenges exacerbate existing issues of modern robotic control methods such as imitation learning (IL) and reinforcement learning (RL). This review focuses on the application details of data-driven control methods on four major task families in this domain: cloth-shaping, rope manipulation, dressing and bag manip- ulation. Furthermore, we identify specific inductive biases in these four domains that present challenges for more general IL and RL algorithms, and summarise the future direction for the development of the field.

We put forward a co-axial pump(optical)-probe(X-rays) experimental concept and show performance of the optical component. A Bessel beam generator with a central 100 micrometers-diameter hole (on the optical axis) was fabricated using femtosecond (fs) laser structuring inside a silica plate. This flat-axicon optical element produces a needle-like axial intensity distribution which can be used for the optical pump pulse. The fs-X-ray free electron laser (X-FEL) beam of sub-1 micrometer diameter can be introduced through the central hole along the optical axis onto a target as a probe. Different realisations of optical pump are discussed. Such optical elements facilitate alignment of ultra-short fs-pulses in space and time and can be used in light-matter interaction experiments at extreme energy densities on the surface and in the volume of targets. Full advantage of ultra-short 10 fs X-FEL probe pulses with fs-pump(optical) opens an unexplored temporal dimension of phase transitions and the fastest laser-induced rates of material heating and quenching. A wider field of applications of fs-laser-enabled structuring of materials and design of specific optical elements for astrophotonics is presented.

As the global population rapidly ages with longer life expectancy and declining birth rates, the need for healthcare services and caregivers for older adults is increasing. Current research envisions addressing this shortage by introducing domestic service robots to assist with daily activities. The successful integration of robots as domestic service providers in our lives requires them to possess efficient manipulation capabilities, provide effective physical assistance, and have adaptive control frameworks that enable them to develop social understanding during human-robot interaction. In this context, human factors, especially quantifiable ones, represent a necessary component. The objective of this paper is to conduct an unbiased review encompassing studies on human factors studied in research involving physical interactions and strong manipulation capabilities. We identified the prevalent human factors in physical human-robot interaction (pHRI), noted the factors typically addressed together and determined the frequently utilized assessment approaches. Additionally, we gathered and categorized proposed quantification approaches based on measurable data for each human factor. We also formed a map of common contexts and applications addressed in pHRI for a comprehensive understanding and easier navigation of the field. We found out that most of the studies in direct pHRI (when there is direct physical contact) focus on social behaviors with belief being the most commonly addressed human factor type. Task collaboration is moderately investigated, while physical assistance is rarely studied. In contrast, indirect pHRI (when the physical contact is mediated via a third item) studies often involve industrial settings, with physical ergonomics being the most frequently investigated human factor. More research is needed on human factors in direct and indirect physical assistance applications, including studies that combine physical social behaviors with physical assistance tasks. We also found that while the predominant approach in most studies involves the use of questionnaires as the main method of quantification, there is a recent trend that seeks to address quantification approaches based on measurable data.

In response to the need to address the safety challenges in the use of artificial intelligence (AI), this research aimed to develop a framework for a safety controlling system (SCS) to address the AI black-box mystery in the healthcare industry. The main objective was to propose safety guidelines for implementing AI black-box models to reduce the risk of potential healthcare-related incidents and accidents. The system was developed by adopting the multi-attribute value model approach (MAVT), which comprises four symmetrical parts: extracting attributes, generating weights for the attributes, developing a rating scale, and finalizing the system. On the basis of the MAVT approach, three layers of attributes were created. The first level contained 6 key dimensions, the second level included 14 attributes, and the third level comprised 78 attributes. The key first level dimensions of the SCS included safety policies, incentives for clinicians, clinician and patient training, communication and interaction, planning of actions, and control of such actions. The proposed system may provide a basis for detecting AI utilization risks, preventing incidents from occurring, and developing emergency plans for AI-related risks. This approach could also guide and control the implementation of AI systems in the healthcare industry.

Transient flows result in unbalanced forces and high pressure in pipelines. Under these conditions, the combined effects of flow-induced forces along with sudden pipe displacements can create cracks in the pipeline, especially at the junctions. This situation consequently results in water leakage and reduced operational efficiency of the pipeline. In this study, displacements and stresses in a buried pressurized water transmission pipe installed by pipe jacking method are investigated using numerical modeling and considering interactions between fluid, pipe, and soil. The analyses were performed consecutively under no-flow, steady flow, and transient flow conditions, in order to investigate the effects of flow conditions on displacements and stresses in the system. Analyses of the results show that displacements and stresses in the jointed concrete pipes are significant under transient flow conditions. Moreover, because of pressure transient effects, maximum tensile stresses exceed the tensile strength of concrete at the junctions, leading to cracks and consequent water leakage.

To investigate the optimum layouts of small vertical axis wind turbines, a two-dimensional analysis of dynamic fluid body interaction is performed via computational fluid dynamics for a rotor pair in various configurations. The rotational speed of each turbine rotor (diameter: D = 50 mm) varies based on the equation of motion. First, the dependence of rotor performance on the gap distance (gap) between two rotors is investigated. For parallel layouts, counter-down (CD) layouts with blades moving downwind in the gap region yield a higher mean power than counter-up (CU) layouts with blades moving upwind in the gap region. CD layouts with gap/D = 0.5–1.0 yield a maximum average power that is 23% higher than that of an isolated single rotor. Assuming isotropic bidirectional wind speed, co-rotating (CO) layouts with the same rotational direction are superior to the combination of CD and CU layouts regardless of the gap distance. For tandem layouts, the inverse-rotating configuration (IR) shows an earlier wake recovery than the CO configuration. For 16-wind-direction layouts, both the IR and CO configurations indicate similar power distribution at gap/D = 2.0. For the first time, this study demonstrates the phase synchronization of two rotors via numerical simulation.

We extend the standard solid-state quantum mechanical Hamiltonian containing only Coulomb interactions between the charged particles by inclusion of the (transverse) current-current diamagnetic interaction starting form the non-relativistic QED restricted to the states without photons and neglecting the retardation in the photon propagator. This derivation is supplemented with a derivation of an analogous result along the non-rigorous old classical Darwin-Landau-Lifshitz argumentation within the physical Coulomb gauge.

With reference to electromagnetic interaction and Abdus Salam’s strong (nuclear) gravity, 1) Square root of ‘reciprocal’ of the strong coupling constant can be considered as the strength of nuclear elementary charge. 2) ‘Reciprocal’ of the strong coupling constant can be considered as the maximum strength of nuclear binding energy. 3) In deuteron, strength of nuclear binding energy is around unity and there exists no strong interaction in between neutron and proton. $G_s\cong 3.32688\times {10}^{28}{\mathrm{m}}^3{\mathrm{kg}}^{-1}{\sec }^{-2}$ being the nuclear gravitational constant, nuclear charge radius can be shown to be, $R_0\cong \frac{2G_s{m}_p}{c^2}\cong 1.24\mathrm{fm}.$ $e_s\cong \left(\frac{G_s{m}_p^2}{\hslash c}\right)e\cong 4.716785\times {10}^{-19}\mathrm{C}$ being the nuclear elementary charge, proton magnetic moment can be shown to be, ${\mu }_p\cong \frac{e_s\hslash }{2m_p}\cong \frac{e{G}_s{m}_p}{2c}\cong 1.48694\times {10}^{-26}\mathrm{J}{.\mathrm{T}}^{-1}.$ ${\alpha }_s\cong {\left(\frac{\hslash c}{G_s{m}_p^2}\right)}^2\cong 0.1153795$ being the strong coupling constant, strong interaction range can be shown to be proportional to $\exp \left(\frac{1}{{\alpha }_s^2}\right).$ Interesting points to be noted are: An increase in the value of ${\alpha }_s$ helps in decreasing the interaction range indicating a more strongly bound nuclear system. A decrease in the value of ${\alpha }_s$ helps in increasing the interaction range indicating a more weakly bound nuclear system. From $Z\cong 30$ onwards, close to stable mass numbers, nuclear binding energy can be addressed with, ${\left(B\right)}_{A_s}\cong Z\times \left\{\left(\frac{1}{{\alpha }_s}+1\right)+\sqrt{\sqrt{30\times 31}}\right\}\left(m_n-m_p\right)c^2\approx Z\times 19.66\mathrm{MeV}.$ With further study, magnitude of the Newtonian gravitational constant can be estimated with nuclear elementary physical constants. One sample relation is, $\left(\frac{G_N}{G_s}\right)\cong \frac{1}{2}{\left(\frac{m_e}{m_p}\right)}^{10}\left[\sqrt{\frac{G_F}{\hslash c}}/\left(\frac{\hslash }{m_{e}c}\right)\right]$ where $G_N$ represents the Newtonian gravitational constant and $G_F$ represents the Fermi’s weak coupling constant. Two interesting coincidences are, ${\left(m_p/m_e\right)}^{10}\cong \exp \left(1/{\alpha }_s^2\right)$ and $2G_s{m}_e/c^2\cong \sqrt{G_F/\hslash c}.$

The objective was to model the teams’ style of play (SoP) in elite football and relate them to the match result. For this, the twenty Spanish first division teams in the 2016-17 season were analysed, using nine interaction performance indicators (IRi). A principal component (PC) analysis was applied. From two PCs four SoPs were established: deep or high-pressure defending, and elaborate or direct attack. The SoPs were distributed according to average performance obtained throughout the championship. The connection between the preferred SoP and the final result was estimated. Teams with elaborate offensive styles and teams defensively minded got better results. In addition, most of the teams showed variability in their SoP. The applications of the study are: 1) the IRi have served to identify SoP and can be used as a reference to optimize team performance; 2) teams should have a varied SoP repertoire, as well as being prepared to deal with different SoPs; 3) particular player profiles should be connected with the desired SoP when creating the squad. 4) clubs should develop a varied range of SoPs at their academies.

Insects possess an array of defense molecules allowing them to fight infections. They can also show a form of immune memory, named priming. However, the involvement of insect immune defense mechanisms in priming is unclear, since invertebrates lack the molecular machinery present in vertebrates to build an immune memory. In the red flour beetle Tribolium castaneum, larvae can be primed via the oral route with Bacillus thurigiensis var. tenebrionids (Btt). This results in changes in the expression of a large number of genes, among which some belong to families of ancient defense genes. In the present work, we tested whether three chosen candidate genes (a Thaumatin, a C-type Lectin and an Osiris-like gene) could be involved in the survival to a Btt exposure, as well as in the priming phenotype. We assessed changes in their expression over time and according to the priming treatment, knocked them down individually by RNA interference (RNAi), and observed how it affected survival upon challenge. The quantification of gene expression patterns in our larvae with RT-qPCR showed that up- and/or down-regulation of the genes, after the priming treatment, was quite volatile and time dependent. Upon knock-down, we did not observe the expected decrease in survival to Btt or the abolishment of the priming phenotype. We conclude that knocking down genes individually is probably insufficient to affect survival and priming in our system. This gives us insight into the complexity of the molecular processes underpinning priming.

Immune checkpoint blockade (ICB)-based therapy is revolutionizing cancer treatment by fostering successful immune surveillance and effector cell responses against various types of cancers. However, patients with HER2+ cancers are yet to benefit from this therapeutic strategy. Precisely, several questions regarding the right combination of drugs, drug modality, and effective dose recommendations pertaining to the use of ICB-based therapy for HER2+ patients remain unanswered. In this study, we use a mathematical modeling-based approach to quantify the growth inhibition of HER2+ breast cancer (BC) cell colonies (ZR75) when treated with anti-HER2; trastuzumab (TZ) and anti-PD-1/PD-L1 (BMS-202) agents. Our data show that a combination therapy of TZ and BMS-202 can significantly reduce the viability of ZR75 cells and trigger several morphological changes. The combination decreased the cell’s invasiveness along with altering several key pathways, such as Akt/mTor and ErbB2 compared to monotherapy. In addition, BMS-202 causes dose-dependent growth inhibition of HER2+ BC cell colonies alone, while this effect is significantly improved when used in combination with TZ. Based on the in-vitro monoculture experiments conducted, we argue that BMS-202 can cause tumor growth suppression not only by mediating immune response but also by interfering with the growth signaling pathways of HER2+ BC. Nevertheless, further studies are imperative to substantiate this argument and to uncover the potential crosstalk between PD-1/PD-L1 inhibitors and HER2 growth signaling pathways in breast cancer.

Myelin protein zero (P0), a type I transmembrane protein, is the most abundant protein in peripheral nervous system (PNS) myelin – the lipid-rich, periodic structure that concentrically encloses long axonal segments. Schwann cells, the myelinating glia of the PNS, express P0 throughout their development until the formation of mature myelin. In the intramyelinic compartment, the immunoglobulin-like domain of P0 bridges apposing membranes together via homophilic adhesion, forming a dense, macroscopic ultrastructure known as the intraperiod line. The C-terminal tail of P0 adheres apposing membranes together in the narrow cytoplasmic compartment of compact myelin, much like myelin basic protein (MBP). In mouse models, the absence of P0, unlike that of MBP or P2, severely disturbs the formation of myelin. Therefore, P0 is the executive molecule of PNS myelin maturation. How and when is P0 trafficked and modified to enable myelin compaction, and how disease mutations that give rise to incurable peripheral neuropathies alter the function of P0, are currently open questions. The potential mechanisms of P0 function in myelination are discussed, providing a foundation for the understanding of mature myelin development and how it derails in peripheral neuropathies.

Hemorrhage is a detrimental event present in traumatic injury, surgery, and disorders of bleeding, that can become life-threatening if not properly managed. Moreover, uncontrolled bleeding can complicate surgical interventions, altering the outcome of surgical procedures. Therefore, to reduce the risk of complications and decrease the risk of morbidity and mortality associated with hemorrhage, it is necessary to use an effective hemostatic agent that ensures immediate control of bleeding. In recent years, there have been increasingly rapid advances in developing novel generation of biomaterials with hemostatic properties. Nowadays, a wide array of topical hemostatic agents is available, including chitosan-based biomaterials that have shown outstanding properties such as: antibacterial, antifungal, hemostatic, analgesic activity, in addition to their biocompatibility, biodegradability, and wound-healing effects. This review provides an analysis of chitosan-based hemostatic and discusses the progress made in their performance, mechanism of action, efficacy, cost, and safety in recent years.

Penicillium digitatum is the major postharvest pathogen of citrus fruit under Mediterranean climate conditions. In the present work, we have addressed the study of the role of P. digitatum’s proteases in virulence following two complementary approaches. In a first approach, we have undertaken the functional characterization of the P. digitatum prtT gene, which codes for a transcription factor previously shown to regulate extracellular proteases in other filamentous fungi. Deletion of prtT caused a significant loss in secreted protease activity during in vitro growth assays. However, there was no effect on virulence. Gene expression of the two major secreted acid proteases was barely affected in the ΔprtT deletant during infection of citrus fruit. Hence, no conclusion could be drawn on the role of these secreted acidic proteases on the virulence of P. digitatum. In a second approach, we have studied the effect of different protease inhibitors and chelators in virulence. Co-inoculation of citrus fruit with P. digitatum conidia and a cocktail of protease inhibitors resulted in almost a complete absence of disease development. Analysis of individual inhibitors revealed that the metalloprotease inhibitor 1,10-phenanthroline was responsible for the observed effect. The application of metal ions reverted the protective effect caused by the metallopeptidase inhibitor. These results may set the basis for the development of new alternative treatments to combat this important postharvest pathogen.

Tumor necrosis factor (TNF) inhibitors (anti-TNFs) represent a cornerstone of the treatment of various immune-mediated inflammatory diseases and are among the most commercially successful therapeutic agents. Knowledge of TNF binding partners is critical for identification of the factors able to affect clinical efficacy of the anti-TNFs. Here we report that among eighteen representatives of the multifunctional S100 protein family only S100A11, S100A12 and S100A13 interact with the soluble form of TNF (sTNF) in vitro. The lowest equilibrium dissociation constants (Kd) for the complexes with monomeric sTNF determined using surface plasmon resonance spectroscopy range from 2 nM to 28 nM. The apparent Kd values for the complexes of multimeric sTNF with S100A11/A12 estimated from fluorimetric titrations are 0.1-0.3 µM. S100A12/A13 suppress the cytotoxic activity of sTNF against Huh-7 cells, as evidenced by the MTT assay. Structural modeling indicates that the sTNF-S100 interactions may interfere with the sTNF recognition by the therapeutic anti-TNFs. Bioinformatic analysis reveals dysregulation of TNF and S100A11/A12/A13 in numerous disorders. Overall, we have shown a novel potential regulatory role of the extracellular forms of specific S100 proteins that may affect efficacy of anti-TNF treatment in various diseases.

Is immediate action at a distance, like gravitational attraction, imaginable using the contrary concept of close up, tactile, events? Tactile events, defined with the term ‘tap-tapping’ as a blind man does, described in a two-way spiritual interaction theory, are implemented in physics to understand gravitation from this respect. The quantum mechanical wave function reduction during measurements receives a new approach. Formulated is a new proof for Einstein’s Equivalence Principle, extending it beyond locality, and a sketch of how tactile interaction could explain dark energy and an accelerated expansion of the universe. Dark energy and dark matter are examples starting from which to discuss properties of matter and space and gravitation as immediate tactile action rather than mediated action such as electromagnetism.

The COVID-19 was described as a respiratory illness, however further studies recognize it as a complex heterogeneous multisystemic disorder. Global efforts have been proposed to combat COVID-19, emerging diverse therapeutic options, in which discovering new drug therapies, development of vaccines and drug repurposing have been considered the most promising approaches to fight the virus. This study aimed to repurpose known drugs for use against the COVID-19, finding better therapeutic options. Seventeen biological databases were used in this study. The genetic algorithm (GA) was performed for a set of drug target classes and COVID-19 proteins as input, whose drug candidates are obtained according to the target similarities found in the target-target similarity predictive network, resulting in a drug-target interaction network. Thus, recommended drugs correspond to the union of the drug subsets found during each GA execution. Twenty-eight drugs were indicated to be the best therapeutic targets for the virus, in special, the Cyclosporine drug was administered as adjuvant to steroid treatment for COVID-19 patients which showed positive outcomes, reducing mortality in moderate and severe cases. The drugs found have used to treat other diseases, evidencing that the COVID-19 is a multisystemic disorder and suggests that the viruses’ mechanism of action presents some comorbidity with other human diseases. Evidence shows that the drugs found in this research might act together to fight the virus in a broader fashion, however further studies including in vitro and in vivo experiments are needed to find the best combination of these drugs.

A recent paper demonstrates the importance of the linker region joining the two SNARE motifs of the neuronal t-SNARE SNAP25 for maintaining rates of secretion with roles for distinct segments in speeding fusion pore expansion (Shaaban et al., 2019, Elife. 8). Remarkably, lipid perturbing agents rescue a palmitoylation-deficient phenotype that includes slow fusion pore expansion, suggesting that protein-protein interactions have a role not only in bringing together the granule or vesicle membrane with the plasma membrane but also in orchestrating protein-lipid interactions leading to the fusion reaction. Furthermore, biochemical investigations demonstrate the importance of the C-terminal domain of the linker in the formation of the plasma membrane t-SNARE acceptor complex for synaptobrevin2 (Jiang, et al., 2019, FASEB J. 33:7985-7994;Shaaban et al., 2019, Elife. 8). This insight, together with biophysical and optical studies from other laboratories (Wang, et al., 2008, Molecular Biology of the Cell. 19:3944-3955; Zhao, et al., 2013, Proc Natl Acad Sci U S A. 110:14249-14254) suggests that the plasma membrane SNARE acceptor complex between SNAP25 and syntaxin and the resulting trans SNARE complex with the v-SNARE synaptobrevin form just milliseconds before fusion.

Studying the two famous old problems that why the moon can move around the Sun and why the orbit of the Moon around the Earth cannot be broken off by the Sun under the condition that calculating with F=GMm/R^2, the attractive force of the Sun on the Moon is almost 2.2 times that of the Earth. We found that the planet and moon are unified as one single gravitational unit which results in that the Sun cannot have the force of F=GMm/R^2 on the moon. The moon is moved by the gravitational unit orbiting around the Sun. It could indicate that the gravitational field of the moon is limited inside the unit and the gravitational fields of both the planet and moon is unified as one single field interacting with the Sun. The findings are further clarified by reestablishing Newton’s repulsive gravity.

In our study we used the data set on morphimetric traits in beetles species. It has been constantly replenishing for 20 years by the samples, received from different regions of Russia and abroad. In this case we have selected data on nine species for which the left and right sides had been measured and fluctuating asymmetry (FA) could be estimated. The samples were from 6 provinces of Russia and Belarus, which ranged in 3 degrees in latitude and 57 degrees in longitude and included more than 150 plots in different types of biotopes. FA was assessed according to the standard method in 5265 specimen in one dimensional trait and one - meristic. ANOVA showed that biotope, species and their interaction affected FA in both traits, that is different species reacted differently to biotope type. In uncommon biotopes (according to accepted in carabidology classification) FA was increased. In forest species the negative relationship between FA in dimensional and meristic traits in the range in biotopes was revealed. In those species only FA values were higher in males than in females. In generalist species FA varieв similarly in both sexes and in both traits being the highest in open biotopes. In eudomonant of arable lands biotopes – Poecilus cupreus – the highest values of FA were recorded in the meadows, being about equal in all types of crops.

Staphylococcus aureus is a Gram-positive bacterium causing a range of mild to life-threatening infections including bone infections such as osteomyelitis. S. aureus is able to invade and persist within non-professional phagocytic cells such as osteoblasts. In the present study four different S. aureus strains, 2SA-ST239-III, 5SA-ST5-II, 10SA-ST228-I, and 14SA-ST22-IVh were tested for their ability to modulate cell viability in MG-63 osteoblast-like cells following a successful invasion and persistence. Methicillin-sensitive S. aureus (MSSA) ATCC-12598-ST30 was used as control. Despite the demonstrated similar abilities of internalization and persistence of ATCC-12598-ST30, 2SA-ST239-III, and 14SA-ST22-IVh strains in MG-63 osteoblast-like cells under our experimental conditions, we demonstrated that the decrease in cell viability was due to the different behavior of the considered strains, with the number of intracellular bacteria playing a limited role. We focused our attention on different cellular biochemical functions related to inflammation, cell metabolism, and oxidative stress during osteoblast infections. We were able to show that: 1) ATCC-12598-ST30 and 2SA-ST239-III were the only two clones able to persist and maintain their number into the cellular hostile environment during the entire period of infection; 2) 2SA-ST239-III was the only clone able to significantly increase the gene expression (3 and 24 h) and protein secretion (24 h) of both interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α) in MG-63 osteoblast-like cells; 3) the same clone determined a significant up-regulation of transforming growth factor-β1 (TGF-β1) and the metabolic marker glyceraldehyde 3-phosphate dehydrogenase (GAPDH) mRNAs at 24 h post infection; 3) neither the MSSA nor the four MRSA strains induced oxidative stress phenomena in MG-63 cells, although a very different expression pattern towards nuclear factor E2-related factor 2 (Nrf2) and its downstream gene heme oxygenase 1 (HO-1) activation was observed among the different clones. Our results can open a new way of considering therapies, going in the direction of an individualized therapeutic strategy that should take into account the difference existing between MSSA and MRSA as well as the distinctive features of the different clones. Not only, therefore, a different antibiotic approach but also a starting point for considering different host factors, i.e. the modulation of specific cytokines such as IL-6, TNF-α, and TGF-β1.

In current efforts to digitize manufacturing and move it into the fourth stage of the industrial revolution, a wide range of integration solutions is being considered to enable manufacturing to adapt to change. In transforming a factory into a self-organized, autonomous factory, companies are currently struggling with rapidly changing requirements and production factors, among other things. This is a particular problem for the human being as an actor within the factory, as the amount of new technologies and protocols increases the training effort. Proprietary interfaces of the control providers, a wide range of different communication protocols, complicate the understanding of the production processes, the evaluation and testability of new use cases and increase the danger of creating silos of knowledge as well as building collaboration barriers. As a solution to these problems, we propose an open software platform and define a way to model use case driven domain specific asset representation (DSA) that focuses on the human being and his needs for representing the factory in a way that it meets his requirements for the current production needs. We therefore conducted research on google scholar on human factors in industry 4.0 and used technologies as well as already existing platforms and their architecture.

Time evolution operators of a strongly ionizing medium are calculated by a time-dependent unitary transformation (TDUT) method. The TDUT method has been employed in quantum mechanical system composed of discrete states. This method is especially helpful for solving molecular rotational dynamics in quasi-adiabatic regimes because the strict unitary nature of the propagation operator allows us to set the temporal step size large; a tight limitation on the temporal step size ($\delta t <<1$) can be circumvented by the strict unitary nature. On the other hand, in a strongly ionizing system where the Hamiltonian is not Hermitian, the same approach cannot be directly applied because it is demanding to define a set of field-dressed eigenstates. In this study, the TDUT method was applied to the ionizing regime using the Kramers-Henneberger frame, in which the strong-field-dressed discrete eigenstates are given by the field-free discrete eigenstates in a moving frame. Although the present work verifies the method for a one-dimensional atom as a prototype, the method can be applied to three-dimensional atoms, and molecules exposed to strong laser fields.

This study reports an empirical analysis of an all-electric, Net Zero Energy Housing (NZEH) development located in a mixed-humid climate zone (4A, Virginia, USA). Circuit-level energy monitors were used to measure energy consumption and energy production data (solar photovoltaic) at 1-hr intervals in six identical apartments over 24 months. The study employs a multi-step case study methodology to a) empirically evaluate energy consumption and production data, b) identify the temporal variability of energy consumption and production data at different time scales, c) understand the impact(s) of weather and human-building interaction on energy consumption and production, and d) synthesize the study’s “lessons learned” toward data-driven recommendations for future NZEH researchers and practitioners. The study found that the development’s net zero energy goal was achieved in three of six case units and that NZEH housing performance was more influenced by human-building interaction than weather variability. The analysis also found the solar photovoltaic (PV) performance to be reliable across the sampled units over the periods of measurement, suggesting that solar PV could be oversized as an approach to overcome verifiability in HBI and achieve NZEH performance goals.

Our brain continuously interacts with the body as we engage with the world. Although we are mostly unaware of internal bodily processes, such as our heartbeats, they may be influenced by and in turn influence our perception and emotional feelings. While there is a recent focus on understanding cardiac interoceptive activity and interaction with brain activity during emotion processing, the investigation of cardiac-brain interactions with more ecologically valid naturalistic emotional stimuli is still very limited. We also do not understand how an essential aspect of emotions like context familiarity influences affective feelings and is linked to cardiac-brain interactions. Hence to answer these questions, we designed an exploratory study by recording ECG and EEG signals for the emotional events while participants were watching emotional movie clips. Participants also rated their familiarity with the stimulus on the familiarity scale. Linear mixed effect modelling was performed in which the ECG power and familiarity were considered as predictors of EEG power. We focused on three brain regions, including prefrontal (PF), frontocentral (FC) and parietooccipital (PO). The analyses showed that cardiac-brain interaction is dependent on familiarity such that the interaction is stronger with high familiarity. In addition, the results indicate that arousal is predicted by cardiac-brain interaction, which also depends on familiarity. The results support emotional theories that emphasize context dependency and interoception. Multimodal studies with more realistic stimuli would further enable us to understand and predict different aspects of emotional experience.

Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with numerous negative impacts in the Chilean salmon farming industry. Although transcriptomic studies of P. salmonis and its host have been performed, dual host-pathogen proteomic approaches during infection are still missing. Considering that gene expression not always corresponds with observed phenotype, and bacteriological culture studies inadequately reflect infection conditions, to improve the existing knowledge for the pathogenicity of P. salmonis we present here a global proteomic profiling of Salmon salar macrophage-like cell cultures infected with P. salmonis LF-89. The proteomic analyses identified several P. salmonis proteins from two temporally different stages of macrophages infection; some of them related to key functions for bacterial survival in other intracellular pathogens. Metabolic differences were observed in early-stage infection bacteria, compared to late-stage infections. Virulence factors related to membrane, LPS and surface component modifications, cell motility, toxins and secretion systems also varied between the infection stages. Pilus proteins, beta-hemolysin and the T6SS were characteristic of the early-infection stage, while fimbria, upregulation of 10 toxins or effector proteins, and the Dot/Icm T4SS were representative of the late-infection stage bacteria. Previously described virulence-related genes in P. salmonis plasmids were identified by proteomic assays during infection in SHK-1 cells, accompanied by an increase of mobile-related elements. By comparing the infected and un-infected proteome of SHK-1 cells, we observed changes in cellular and ROS homeostasis, innate immune response, microtubules and actin cytoskeleton organization and dynamics, alteration in phagosome components, iron transport and metabolism, and amino acids, nucleoside and nucleotide metabolism, together with an overall energy and ATP production alteration. Our global proteomic profiling and the current knowledge of the P. salmonis infection process allowed us to propose a model of the macrophage-P. salmonis interaction.

Arginine shows Jekyll and Hyde behavior in several respects. It participates in protein folding via ionic and H-bonds and cation-pi interactions; the charge and hydrophobicity of its side chain makes it a disorder-promoting amino acid. Its methylation in histones; RNA binding proteins; chaperones regulates several cellular processes. The arginine-centric modifications are important in oncogenesis and as biomarkers in several cardiovascular diseases. The cross-links involving arginine in collagen and cornea are involved in pathogenesis of tissues but have also been useful in tissue engineering and wound-dressing materials. Arginine is a part of active site of several enzymes such as GTPases, peroxidases, and sulfotransferases. Its metabolic importance is obvious as it is involved in production of urea, NO, ornithine and citrulline. It can form unusual functional structures such as molecular tweezers in vitro and sprockets which engage DNA chains as part of histones in vivo. It has been used in design of cell-penetrating peptides as drugs. Arginine has been used as an excipient in both solid and injectable drug formulations; its role in suppressing opalescence due to liquid-liquid phase separation is particularly very promising. It has been known as a suppressor of protein aggregation during protein refolding. It has proved its usefulness in protein bioseparation processes like ion-exchange, hydrophobic and affinity chromatographies. Arginine is an amino acid, whose importance in biological sciences and biotechnology continues to grow in diverse ways.

Analysis of the hourly Canadian Prairie data for the past 60 years has transformed our quantitative understanding of land-atmosphere-cloud coupling. The key reason is that trained observers made hourly estimates of opaque cloud fraction that obscures the sun, moon or stars, following the same protocol for 60 years at all stations. These 24 daily estimates of opaque cloud data are of sufficient quality that they can be calibrated against Baseline Surface Radiation Network data to give the climatology of the daily short-wave, longwave and total cloud forcing (SWCF, LWCF and CF). This key radiative forcing has not been available previously for climate datasets. Net cloud radiative forcing reverses sign from negative in the warm season to positive in the cold season, when reflective snow reduces the negative SWCF below the positive LWCF. This in turn leads to a large climate discontinuity with snow cover, with a systematic cooling of 10°C or more with snow cover. In addition, snow cover transforms the coupling between cloud cover and the diurnal range of temperature. In the warm season, maximum temperature increases with decreasing cloud, while minimum temperature barely changes; while in the cold season with snow cover, maximum temperature decreases with decreasing cloud and minimum temperature decreases even more. In the warm season, the diurnal ranges of temperature, relative humidity, equivalent potential temperature and the pressure height of the lifting condensation level are all tightly coupled to opaque cloud cover. Given over 600 station-years of hourly data, we are able to extract, perhaps for the first time, the coupling between cloud forcing and the warm season imbalance of the diurnal cycle; which changes monotonically from a warming and drying under clear skies to a cooling and moistening under cloudy skies with precipitation. Because we have the daily cloud radiative forci, which is large, we are able to show that the memory of water storage anomalies, from precipitation and the snowpack, goes back many months. The spring climatology shows the memory of snowfall back through the entire winter, and the memory in summer goes back to the months of snowmelt. Lagged precipitation anomalies modify the thermodynamic coupling of the diurnal cycle to the cloud forcing, and shift the diurnal cycle of mixing ratio which has a double peak. The seasonal extraction of the surface total water storage is a large damping of the interannual variability of precipitation anomalies in the growing season. The large land-use change from summer fallow to intensive cropping, which peaked in the early 1990s, has led to a coupled climate response that has cooled and moistened the growing season, lowering cloud-base, increasing equivalent potential temperature, and increasing precipitation. We show a simplified energy balance of the Prairies during the growing season and its dependence on reflective cloud.

Dalbergia sissoo (shisham), an important timber yielding multipurpose tree species of the Indian subcontinent, has been afflicted with large scale mortality due to wilt in natural forests and plantations, causing huge economic losses. Fusarium solani f. sp. dalbergiae (Fsd) has been identified as one of the causal organisms for wilt disease in D. sissoo. Present study comprises in vitro screening of ten selected genotypes of D. sissoo against two strains of Fsd in a dual culture set up under axenic condition. Callus and plantlets of ten genotypes of host plant were multiplied in vitro and were inoculated with conidial suspension of two strains of Fsd at three concentrations; 1× 10¹, 1× 10³, and 1× 10⁵ conidia/ml. Gnotobiotic evaluation of dual culture set up shows variations among D. sissoo genotypes in their response towards in vitro Fsd infection; and two genotypes (14 and 66) exhibited resistance against the pathogen strains. Callus of genotypes 14 and 66 significantly restricted the fungal mycelium growth whereas callus of remaining eight genotypes were completely infested by Fsd mycelium within 9 days. Similarly, plantlets of genotype 14 and 66, had lesser disease severity and remained green, and had fewer necrotic lesions in the roots whereas plantlets of remaining eight genotypes died within 15 days.

Malassezia is a lipid-dependent genus of yeasts known for being an important part of the skin mycobiota. These yeasts have been associated in the development of skin disorders and cataloged as a causal agent of systemic infections under specific conditions, making them opportunistic pathogens. Little is known about the host-microbe interaction of Malassezia spp., and unraveling this implies the implementation of infection models. In this mini review we present different models that have been implemented in the fungal infections study with greater attention in Malassezia spp. infections. These models range from in vitro (cell cultures and ex vivo tissue), to in vivo (murine models, rabbits, guinea pigs, insects, nematodes, and amoebas). We additionally highlight the alternative models that reduce the use of mammals as model organisms, which have been gaining importance in the study of fungal host-microbe interactions. This is due to the fact that these systems have shown to have reliable results, which correlate with those obtained from mammalian models. Example of alternative models are Caenorhabditis elegans, Drosophila melanogaster, Tenebrio molitor, and Galleria mellonella. These are invertebrates that have been implemented in the study of Malassezia spp. infections in order to identify differences in virulence between Malassezia species.

Modularity and organizational hierarchy are important concepts in understanding the structure and evolution of interactions in complex biological systems. In this work, we introduce and use a spectral characterization measure (Spectral Entropy) to quantify modularity in protein-to-protein interaction (PPI) networks in species across the tree of life. We evaluated the relation between the size of a PPI network and its (Spectral Entropy-based) modularity, and found a sigmoidal response between the two. We also found significant differences in the distribution of Spectral Entropy values among the three domains of life (Bacteria, Archaea, Eukaryotes). To explore further correlations with biological traits, we focused solely on bacterial PPI networks, which are the most numerous among the three domains and had associated trait metadata, and investigated how modularity impacts or is impacted by growth, aerobicity, selection and location on the tree of life. We found no relation between maximal growth rate and Spectral Entropy, but a strong dependence between G-C content (a proxy for selection) and Spectral Entropy. We also discovered that Spectral Entropy is negatively affected by phylogenetic placement (evolutionary distance from the last universal common ancestor). The general nature of the Spectral Entropy measure of hierarchical modularity in networks suggests that it will be useful in other settings where structural properties of real-world networks are being compared.

Abstract The present work was designed to investigate antiviral potential of novel mono and oligomeric Chitosan derivatives through in-silico approaches to find potent broad-spectrum anti-viral and promising drug candidates against SARS-CoV-2 and augmentation of their mode of action. Chitosan biopolymer and its derivatives were screened virtually against spike glycoprotein and human ACE2 receptor of nCoV-19. HTCC a polymeric Chitosan has been reported to interact with the corona viral Spike (S) protein and blocks its interaction with ACE2 receptor. Better biocompatibility, structural correlations, variation in degree of decetylation and molecular weight of modified Chitosan derivatives are the key attributes for enhancement of anti-viral activity. The Chitosan derivatives constructively interact with viral S protein. N-Carboxy methyl Chitosan (NCMC) among the Chitosan derivatives displayed efficient binding affinity. NCMC, when compared to mHTCC, a monomeric Chitosan for its interaction with the S protein, RBD site and ACE2 receptor, displayed efficient binding affinity with binding energy of -7.9, -6.3 and -7.4; -6.2, -4.8 and -5.5 Kcal/mol respectively. The interaction of S protein with ACE2 and ligand mHTCC-S protein complex and NCMC-S protein complex with ACE2 was calculated through flexible docking resulted in efficient reduction of binding energy from -901.2kJ/mol to -765.06kJ/mol and-814.72kJ/mol respectively, elucidated that the binding affinity of the viral S protein for its receptor ACE2 decreases in the presence of NCMC/mHTCC. The computational study envisages the antiviral efficiency of NCMC, mHTCC and biocompatible Chitosan derivatives for the first time,as preventive intervention against Covid-19.

Radiation is the major driver of snowmelt, and hence its estimation is critically important. Net radiation reaching the forest floor is influenced by vegetation density. Previous studies in mid-latitude conifer forests have confirmed that net radiation decreases and then subsequently increases with increasing vegetation density, for clear sky conditions. This leads to existence of a net radiation minimum at an intermediate vegetation density. With increasing cloud cover, the minimum radiation shifts toward lower densities, sometimes resulting in a monotonically increasing radiation with vegetation density. The net radiation trend, however, is expected to change across sites, affecting the magnitude and timing of individual radiation components. This research explores the variability of net radiation on snow-covered forest floor for different vegetation densities along a latitudinal gradient. We especially investigate how the magnitude of minimum/maximum radiation and the corresponding vegetation density change with the site geographical location. To evaluate these, the net radiation is evaluated using the Forest Radiation Model at six different locations in predominantly white spruce (Picea glauca) canopy cover across North America, ranging from 45 to 66°N latitudes. Results show that the variation of net radiation with vegetation density considerably varies with latitude. In higher latitude forests, the magnitude of net radiation is generally smaller, and the minimum radiation is exhibited at relatively sparser vegetation densities, under clear sky conditions. For interspersed cloudy sky conditions, net radiation non-monotonically varies with latitude across the sites, depending on the seasonal sky cloudiness and air temperature. Latitudinal sensitivity of net radiation is lower on north-facing hillslopes than on south-facing sites.

Mutations, especially those at the protein-protein interaction (PPI) interface, have been associated with various diseases. Meanwhile, though de novo mutations (DNMs) have been proven important in neuropsychiatric disorders, such as developmental delay (DD), the relationship between PPI interface DMNs and DD has not been well studied. Here we curated developmental delay DNM datasets from the PsyMuKB database and showed that DD patients showed a higher rate and deleteriousness in DNM missense on the PPI interface than sibling control. Next, we identified 302 DD-related PsychiPPIs, defined as PPI harboring a statistically significant number of DNM missenses at their interface, and 42 DD candidate genes from PsychiPPI. We then observed that PsychiPPIs preferentially affected hub proteins in the human protein interactome network. When analyzing DD candidate genes using gene ontology and gene spatio-expression, we found that PsychiPPI genes carrying PPI interface mutations, such as FGFR3 and ALOX5, were enriched in development-related pathways and the development of the neocortex, and cerebellar cortex, suggesting their potential involvement in the etiology of DD. Our results demonstrated that DD patients carried an excess burden of PPI-truncating DNM, which could be used to efficiently search for disease-related genes and mutations in large-scale sequencing studies. In conclusion, our comprehensive study indicated the significant role of PPI interface DNMs in developmental delay pathogenicity.

Rapid post-earthquake damage diagnosis of bridges can guide decision-making for emergency response management and recovery. This can be facilitated using digital technologies to remove the barriers of manual post-event inspections. Prior mechanics-based Finite Element (FE) models can be used for post-event response simulation using the measured ground motions at nearby stations; however, the damage assessment outcomes would suffer from uncertainties in structural and soil material properties, input excitations, etc. For instrumented bridges, these uncertainties can be reduced by integrating sensory data with prior models through a model updating approach. This study presents a sequential Bayesian model updating technique, through which a linear/nonlinear FE model, including soil-structure interaction effects, and the foundation input motions are jointly identified from measured acceleration responses. The efficacy of the presented model updating technique is first examined through a numerical verification study. Then, seismic data recorded from the San Rogue Canyon Bridge in California are used for a real-world case study. Comparison between the free-field and the foundation input motions reveals valuable information regarding the soil-structure interaction effects at the bridge site. Moreover, the reasonable agreement between the recorded and estimated bridge responses shows the potentials of the presented model updating technique for real-world applications. The updated FE model is considered as the digital twin of the bridge and can be used to analyze the bridge and monitor the structural response at element, section, and fiber levels to diagnose the location and severity of any potential damage mechanism.

Herpes simplex virus 1 (HSV-1) expresses a large number of miRNAs, and their function is still not completely understood. In addition, HSV-1 has been found to deregulate host miRNAs, which adds to the complexity of regulation of efficient virus replication. In this study, we comprehen-sively addressed the deregulation of host miRNAs by massive-parallel sequencing. We found that only miRNAs expressed from a single cluster, miR-183/96/182 are reproducibly deregulated dur-ing productive infection. These miRNAs are predicted to regulate a great number of potential tar-gets involved in different cellular processes and have only 33 shared targets. Among these, mem-bers of the FoxO family of proteins were identified as potential targets for all three miRNAs. However, our study shows that the upregulated miRNAs do not affect the expression of FoxO proteins, moreover these proteins were upregulated in HSV-1 infection. Furthermore, we show that the individual FoxO proteins are not required for efficient HSV-1 replication. Taken together, our results indicate a complex and redundant response of infected cells to the virus infection that is efficiently inhibited by the virus.

Various peptides or non-structural amino acids are recognized by their specific target proteins and perform biological role in various pathways in vivo. Understanding the interactions between target protein and peptides (or non-structural amino acids) provides key information on the molecular interactions, which can be potentially translated to the development of novel drugs. However, it is experimentally challenging to determine the crystal structure of protein-peptide complexes. To obtain structural information on substrate recognition of peptide-recognizing enzyme, X-ray crystallographic studies were performed using triglycine (Gly-Gly-Gly) as main-chain of peptide. The crystal structure of Parengyodontium album Proteinase K in complex with triglcyine was determined at 1.4 Å resolution. Two different bound conformations of triglycine were observed at the substrate recognition site. The triglycine backbone forms stable interactions with β5-α4 and α5-β6 loops of main-chain. One of the triglycine-binding conformations was identical with the binding mode of a peptide-based inhibitor from a previously reported crystal structure of Proteinase K. Triglycine has potential application X-ray crystallography to identify substrate recognition sites in peptide binding enzymes.

Information-related measures are useful tools for multi-variable data analysis, as measures of dependence among variables, and as descriptions of order and disorder in biological and physical systems. Measures, like marginal entropies, mutual / interaction / multi -information, have long been used in a number of fields including descriptions of systems complexity and biological data analysis. The mathematical relationships among these measures are therefore of significant inherent interest. Relations between common information measures include the duality relations based on Möbius inversion on lattices. These are the direct consequence of the symmetries of the lattices of the sets of variables (subsets ordered by inclusion). While these relationships are of significant interest there has been, to our knowledge, no systematic examination of the full range of relationships of this diverse range of functions into a unifying formalism as we do here. In this paper we define operators on functions on these lattices based on the Möbius inversions that map functions into one another (Möbius operators). We show that these operators form a simple group isomorphic to the symmetric group S₃. Relations among the set of functions on the lattice are transparently expressed in terms of the operator algebra, and, applied to the information measures, can be used to derive a wide range of relationships among diverse information measures. The Möbius operator algebra is naturally generalized which yields extensive new relationships. This formalism now provides a fundamental unification of information-related measures, and the isomorphism of all distributive lattices with the subset lattice implies an even broader application of these results.

Intrinsically disordered proteins mediate crucial biological functions through their interactions with other proteins. Mutual synergistic folding (MSF) occurs when all interacting proteins are disordered, folding into a stable structure in the course of the complex formation. In these cases, the folding and binding processes occur in parallel, lending the resulting structures uniquely heterogeneous features. Currently there are no dedicated classification approaches that would take into account the particular biological and biophysical properties of MSF complexes. Here we present a scalable clustering-based classification scheme, built on redundancy-filtered features that describe the sequence and structure properties of the complexes, and the role of the interaction, which is directly responsible for structure formation. Using this approach, we define six major types of MSF complexes, corresponding to biologically meaningful groups. Hence, the presented method also shows that differences in binding strength, subcellular localization, and regulation are encoded in the sequence and structural properties of proteins. While current structure classification methods can also handle complex structures, we show that the developed scheme is fundamentally different, and since it takes into account defining features of MSF complexes, it serves as a better representation of structures arising through this specific interaction mode.

Rationale: The 14-3-3 protein family is known to interact with many proteins in non-cardiac cell types to regulate multiple signaling pathways, particularly those relating to energy and protein homeostasis; and the 14-3-3 network is a therapeutic target of critical metabolic and proteostatic signaling in cancer and neurological diseases. Although the heart is critically sensitive to nutrient and energy alterations, and multiple signaling pathways coordinate to maintain the cardiac cell homeostasis, neither the structure of cardiac 14-3-3 protein interactome, nor potential functional roles of 14-3-3 protein-protein interactions (PPIs) in heart has been explored. Objective: To establish the comprehensive landscape and characterize the functional role of cardiac 14-3-3 PPIs. Methods and Results: We evaluated both RNA expression and protein abundance of 14-3-3 isoforms in mouse heart, followed by co-immunoprecipitation of 14-3-3 proteins and mass spectrometry in left ventricle. We identified 52 proteins comprising the cardiac 14-3-3 interactome. Multiple bioinformatic analyses indicated that more than half of the proteins bound to 14-3-3 are related to mitochondria; and the deduced functions of the mitochondrial 14-3-3 network are to regulate cardiac ATP production via interactions with mitochondrial inner membrane proteins, especially those in mitochondrial complex I. Binding to ribosomal proteins, 14-3-3 proteins likely coordinate protein synthesis and protein quality control. Localizations of 14-3-3 proteins to mitochondria and ribosome were validated via immunofluorescence assays. The deduced function of cardiac 14-3-3 PPIs is to regulate cardiac metabolic homeostasis and proteostasis. Conclusions: Thus, the cardiac 14-3-3 interactome may be a potential therapeutic target in cardiovascular metabolic and proteostatic disease states, as it already is in cancer therapy.

We introduce a new, and quite general variational model for opinion dynamics based on pairwise interaction potentials and a range of opinion evolution protocols ranging from random interactions to global synchronous flows in the opinion state space. The model supports the concept of topic “coupling”, allowing opinions held by individuals to be changed via indirect interaction with others on different subjects. Interaction topology is governed by a graph that determines interactions. Our model, which is really a family of variational models, has, as special cases, many of the previously established models for the opinion dynamics. After introducing the model, we study the dynamics of the special case in which the potential is either a tent function or a constructed bell-like curve. We find that even in these relatively simple potential function examples there emerges interesting behavior. We also present results of preliminary numerical explorations of the behavior of the model to motivate questions that can be explored analytically

Protein tyrosine sulfation (PTS), a vital post-translational modification, facilitates protein–protein interactions and regulates many physiological and pathological responses. Monitoring PTS has been difficult owing to the instability of sulfated proteins and the lack of a suitable method for detecting the protein sulfate ester. In this study, we combined an in situ PTS system with an ultra-high-sensitivity polysilicon nanowire field-effect transistor (pSNWFET)-based sensor to directly monitor PTS formation. A peptide containing the tyrosine sulfation site of P-selectin glycoprotein ligand (PSGL)-1 was immobilized onto the surface of the pSNWFET by using 3-aminopropyltriethoxysilane and glutaraldehyde as linker molecules. A coupled enzyme sulfation system consisting of tyrosylprotein sulfotransferase and phenol sulfotransferase was used to catalyze PTS of the immobilized PSGL-1 peptide. Enzyme-catalyzed sulfation of the immobilized peptide was readily observed through the shift of the drain current–gate voltage curves of the pSNWFET before and after PTS. To the best of our knowledge, this is the first study to describe in situ PTS and its direct observation by using semiconductor devices. We expect that this approach can be developed as a next generation biochip for biomedical research and industries.

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disorder affecting 1 in 500 people in the general population. Although characterized by asymmetric left ventricular hypertrophy, cardiomyocyte disarray and cardiac fibrosis, HCM is in fact a highly complex disease with heterogenous clinical presentation, onset and complications. While HCM is generally accepted as a disease of the sarcomere, variable penetrance in families with identical genetic mutations challenges the monogenic origin of HCM and instead implies a multifactorial cause. Furthermore, large scale genome sequencing studies revealed that many genes previously reported as causative of HCM in fact have little or no evidence of disease association. These findings thus call for a re-evaluation of the sarcomere-centered view of HCM pathogenesis. Here, we summarize our current understanding of sarcomere-independent mechanisms of cardiomyocyte hypertrophy, highlight the role of extracellular signals in cardiac fibrosis, and propose an alternative but integrated model of HCM pathogenesis.

Glutathione peroxidases (GPxs) form a broad family of antioxidant proteins essential for maintaining redox homeostasis in eukaryotic cells. In this study, we used an integrative approach that combines bioinformatics, molecular biology, and biochemistry to investigate the role of GPxs in reactive oxygen species detoxification in the unicellular eukaryotic model organism Tetrahymena thermophila. Both phylogenetic and mechanistic empirical model analyses provided indications about the evolutionary relationships among the GPXs of Tetrahymena and the orthologous enzymes of phylogenetically related species. In-silico gene characterization and text mining were used to predict the functional relationships between GPxs and other physiologically-relevant processes. The GPx genes contain conserved transcriptional regulatory elements in the promoter region, which suggest that transcription is under tight control of specialized signaling pathways. The bioinformatic findings were next experimentally validated by studying the time course of copper (Cu)-dependent regulation of gene transcription and enzymatic activity. Results emphasize the role of GPxs in the detoxification pathways that, by complex regulation of Cu-dependent GPx gene expression, enables Tetrahymena to survive in high Cu concentrations and the associated redox environment.

A large variety of molecular interactions occurs between biomolecular components in cells. When one or a cascade of molecular interactions results in a regulatory effect, by one component onto a downstream component, a so-called ‘causal interaction’ takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These causal interactions and the biological processes they enable (e.g., gene regulation) need to be described with a careful appreciation of molecular interactions that occur between entities. A proper description of this information enables archiving, sharing, and reuse by humans and for computational science. Various representations of causal relationships between biological components are currently used in a variety of resources. Here, we propose a checklist that accommodates current representations, and call it the Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating causal statements, while assuring uniformity and interoperability of the data across resources.

Complex systems exhibit critical thresholds at which they transition among alternative phases. Complex systems theory has been applied to analyze disease progression, distinguishing three stages along progression: (i) a normal non-infected state, (ii) a pre-disease state in which the host is infected and responds; therapeutic interventions could still be effective, (iii) an irreversible state, where the system is seriously threatened. The Dynamical Network Biomarker (DNB) theory sought for early-warnings of the transition from health to disease. Such DNBs might range from individual genes to complex structures in transcriptional regulatory or protein-protein interaction networks. Here we revisit transcriptomic data obtained during infection of tobacco plants with tobacco etch potyvirus to identify DNBs signaling the transition from mild/reversible to severe/irreversible disease. We identified genes showing a sudden transition in expression along disease. Some of these genes cluster in modules that show the properties of DNBs. These modules contain both genes known to be involved in response to pathogens (e.g., ADH2, CYP19, ERF1, KAB1, LAP1, MBF1C, PR1, or TPS5) and other genes not previously related to biotic stress responses (e.g., ABCI6, BBX21, NAP1, OSM34, or ZPN1).

This paper discovers that current canonical variational principle and canonical Noether theorem of (in)finite freedom systems for different physics systems have neglected doublet extreme value processes of the general extreme value functional that both is derived by variational principle and is necessarily be taken in deriving all ( quantum ) physics laws in phase space, but which have not been done for over one century since Noether's showing her distinguished theorem, which lead to the crisis deriving all (quantum) physics laws (necessary) in phase space. We discover there is the hidden logic cycle that people assume canonical equations, and then they finally deduce canonical equations by the equivalent relation in the whole processes in all current references. We correct the current key mistake concepts that when physics systems take the variational extreme values, the appearing processes of the physics systems are real physics processes, otherwise, are virtual processes in all current references. The real physics should be what after taking the physics systems' variational extreme values, the physics systems' general extremum functional needs to further take the general extremum functional's minimum absolute extremum zero, otherwise, the appearing processes of physics systems still are virtual processes. Conservation current equations and conservation currents, in phase space, of general canonical variational principle and general canonical Noether theorem are, respectively, deduced for the first time. Using the general extremum functionals' doublet extreme value processes, the hidden logic cycle and the crisis in current canonical variational principle and current canonical Noether theorem are solved. Consequently, the new mathematical pictures, classical and quantum new physics in phase space and the new mathematical and physical doublet extremum processes for (in)finite freedom systems are discovered. General canonical variational principle and general canonical Noether theorem naturally are given, which would rewrite all the different sciences in phase space, as key tools of studying and dealing with them.

Infrastructure monitoring, inspection, repair, and replacement in space is crucial for continued usage and safety, yet it is expensive, time-consuming, and technical very challenging. New robotics technologies and artificial intelligence algorithms are potentially novel approaches that may alleviate such demanding operations using existing or novel sensing technologies. Space structures must necessarily be very light weight due to high costs of placing robots in space. Several methods are proposed and compared to control highly flexible space robotics, where a key challenge is the presence of flexible resonant modes at frequencies so low as to reside inside typical feedback controller bandwidths. Such conditions imply the very action of sending control signals to the ultra-light weight robotics will cause structural resonance. Implementations of incrementally increasing order are offered, achieving over ninety percent performance improvement in trajectory tracking errors, while improvement using unshaped methods merely achieve twenty-four percent improvement in direct comparison (where the only modification is the proposed control methodology). Based on superior performance, single-sinusoidal trajectory shaping is recommended with a corollary benefit of preparing future research into applying deterministic artificial intelligence whose current instantiation relies on single-sinusoidal, autonomous trajectory generation.

In this age of Facebook, Instagram, and Twitter, there is rapidly growing interest in understanding network-enabled opinion dynamics in large groups of autonomous agents. The phenomena of opinion polarization, the spread of propaganda and fake news, and the manipulation of sentiment is of interest to large numbers of organizations and people. Whether it is the more nefarious players such as foreign governments that are attempting to sway elections or it is more open and above board, such as researchers who want to make large groups of people aware of helpful innovations, what is at stake is often significant. In this paper, we review opinion dynamics including the extensions of many classical models as well as some new models that deepen understanding. For example, we look at models that track the evolution of an individual’s power, that include noise, and that feature sequentially dependent topics, to name a few. While the first papers studying opinion dynamics appeared over 60 years ago, there is still a great deal of room for innovation and exploration. We believe that the political climate and the extraordinary (even unprecedented) events in the sphere of politics in the last few years will inspire new interest and new ideas. It is our aim to help those interested researchers understand what has already been explored in a significant portion of the field of opinion dynamics. We believe that in doing this, it will become clear that there is still much to be done.

Parkinson’s disease and Alzheimer’s disease are the most commonly diagnosed neurodegenerative disorders. Though these disorders differ in terms of their underlying pathophysiology as well as in their clinical features and course, there is a certain degree of overlap between them. This overlap may be partly related to α-synuclein-mediated neuropathological changes. Recent evidence has found that depression is associated with an increased subsequent risk of both these neurological disorders, and that α-synuclein may also play a pathogenic role in depression. The current study examines epidemiological, population genetic and environmental exposure data in relation to the estimated prevalence of depressive disorders, Parkinson’s disease and Alzheimer’s disease using a cross-sectional, country-level analysis. The results of this study are consistent with a significant relationship between depressive disorders and neurodegenerative disorders, a possible shared genetic vulnerability related to functional polymorphisms of the α-synuclein gene SNCA, and potential gene-environment interactions involving fine particulate matter pollution. The significance of these results is discussed in the light of existing translational, clinical and epidemiological research on the links between these disorders.

When participants in a statistical learning paradigm are asked to learn from two incompatible or competing inputs, they often fail to learn from one or both inputs. This study presents the results of two experiments that were both completed by one group of typically developing four-year-old children. One experiment targeted word-medial consonant patterns (phonotactics), whereas the other targeted strong-weak and weak-strong stress patterns (prosody). The order of the experiments was critical for learning outcomes in the phonotactics experiment: When children learned phonotactics first, their production accuracy increased following exposure to a high frequency input. When children learned phonotactics second, however, their production accuracy dropped when they were exposed to the high frequency input. Results from the prosody experiment were inconclusive, with limited evidence of any learning effect. Overall, the results suggest that children may conflate learning experiences, and patterns learned from an initial experimental input compete with patterns in a subsequent experiment. When considering natural language acquisition, the results suggest that an isolated episode of learning may lead to generalizations that are incompatible with later input, and possibly, with larger patterns in the language.

In the new period, the state has made every effort to promote the new urbanization of public sports service. Entropy method, coupled coordination model, cold hot spot analysis is used to explore the dynamic relationship between public sports services and the development of new urbanization in China from 2008 to 2017. The results show that: (1) The development of the internal subsystem of public sports service is not balanced, the sports financial investment system grows rapidly, but the development of professional sports talent team is slow. (2) The imbalance of regional development cannot be ignored, and the public sports service level shows a decreasing gradient from east to west. (3) The regional development features are different. The eastern region is dominated by the coordinated development of sports public service and urbanization, while the central region is mainly in the type of public sports service lag, while the western region has multiple complex characteristics of low-level coordination and public sports service lag. Therefore, it is proposed that the construction of modern public sports service system should be investigated in the context of the development of new urbanization. It should be promoted from the following aspects: promoting the extension of public sports service to rural areas, engendering the "citizen's right" of sports health to the migrant population, conforming to the trend of mass sports intelligence, developing green sports and revitalizing idle sports assets in cities.

Grapevine is one of the most relevant crops in the world being used for economically important products such as wine. Yet, relevant grapevine cultivars are heavily affected by diseases such as the downy mildew disease caused by Plasmopara viticola. Improvements on grapevine resistance are made mainly by breeding techniques where resistance traits are introgressed into cultivars with desired grape characteristics. However, there is still a lack of knowledge on how resistant or tolerant cultivars tackle the P. viticola pathogen. In this study, using a shotgun proteomics LC-MS/MS approach, we unravel the protein modulation of a highly tolerant grapevine cultivar, V. vinifera ‘Regent’, in the first hours post inoculation (hpi) with P. viticola. At 6 hpi, proteins related to defence and to response to stimuli are negatively modulated while at 12 hpi there is an accumulation of proteins belonging to both categories. The co-occurrence of effector-triggered susceptibility (ETS) and effector-triggered immunity (ETI) is detected at both time-points, showing that these defence processes present high plasticity. The results obtained in this study unravel the tolerant grapevine defence strategy towards P. viticola and may provide valuable insights on resistance associated candidates and mechanisms, which may play an important role in the definition of new strategies on breeding approaches.

The Sugarcane yellow leaf virus (SCYLV) is associated with sugarcane yellow leaf disease (SCYLD) and is considered to be the most economically deleterious emerging pathogen that represents a potential threat and danger to sugarcane cultivation in China. Over the last two decades, high genetic diversity in the SCYLV genotypes was observed worldwide, with a greater chance of YLD incidence for sugarcane injury. SCYLV infection has significantly damaged its economic traits and is responsible for substantial losses in biomass production in sugarcane cultivars. This study aims to identify and comprehensively analyze sugarcane microRNAs (miRNAs) as therapeutic targets against SCYLV using plant miRNA prediction tools. Mature sugarcane miRNAs are retrieved and are used for hybridization of the SCYLV. A total of seven common sugarcane miRNAs were selected based on consensus genomic positions. The biologically significant, top ranked ssp-miR528 was consensually predicted to have a potentially unique hybridization site at nucleotide position 4162 for targeting the ORF5 of the SCYLV genome; this was predicted by all the algorithms used in this study. Then, the miRNA–mRNA regulatory network was generated using the Circos algorithm, which was used to predict novel targets. There are no acceptable commercial SCYLV-resistant sugarcane varieties available at present. Therefore, the predicted biological data offer valuable evidence for the generation of SCYLV-resistant sugarcane plants.

This study addressed a Fluid-Structure Interaction of an open Water test for vp1304 propeller to predict pressure and stress distributions with a low cost and high precision method. The most striking aspect of such a method(one-way coupling) is to use one hydrodynamic solution for the number of different structural sets involved in other materials or different layup methods and combinations of layers. An open-access software(OpenFOAM) with an open-source code solver is used to simulate the fluid domain. Abaqus is used To evaluate and predict the deformation and strength of the blade with the Finite Element Method(FEM). The coupling approach is based on dry condition, which means the added mass effects due to propeller blades vibration is neglected. The pressures imposed on the blades are extracted from the fluid solver for each time step. Then, These pressures role as a load condition for the structure solver. This approach was verified in the last paper(wedge impact); a key factor for the present solution is the rotational rate interrelated between two solution domains, which is explained in this paper. Finally, the blades' stress and strain are calculated and compared in each advance coefficient.

Applications in security and electronic surveillance require combination of excellent magnetic softness with good mechanical and anti-corrosive properties and low dimensionality. We overviewed the properties of soft magnetic glass-coated microwires and different post-processing making them quite attractive for electronic article surveillance and security applications. We studied the magnetostatic interaction between the microwires and routes to tune the non-linear hysteresis loops by using the arrays of different types of amorphous microwires. The presence of neighbouring microwire (either Fe or Co-based) significantly affects the hysteresis loop of the whole microwires array. In a microwires array containing magnetically bistable microwires we observed splitting of the initially rectangular hysteresis loop with a number of Barkhausen jumps correlated with the number of magnetically bistable microwires. Essentially, non-linear and irregular hysteresis loops have been observed in mixed arrays containing Fe and Co-rich microwires. The observed non-linearity in hysteresis loops allowed to increase the harmonics and tune their magnetic field dependencies. Non-linear hysteresis loops have been also observed upon devitrification of amorphous microwires. On the other hand, several routes allowing to tune the switching field by either post-processing or modifying the magnetoelastic anisotropy have been reviewed. Observed unique combination of magnetic properties together with thin dimensions and excellent mechanical and anti-corrosive properties provide excellent perspectives for the use of glass-coated microwires for security and electronic surveillance applications.

In this work, we analytically describe a superconducting transition in a non-equilibrium state taking into account many-body interactions; the obtained transition temperatures indicate the presence of superconductivity at room temperatures.First, we consider many-body interactions and discuss the case of locally thermal equilibrium with many-body interactions; in this section, we derive statistical equations that describe many-body interactions at locally thermal equilibrium state. Then, the same theory is used to derive a many-body statistical equation that is expanded to include the case of non-equilibrium states; in this case a transition temperature is derived. Moreover, a wave function of an Einstein–Podolsky–Rosen pair (EPR pair) is calculated according to the Lorentz conservation, and a specific condensation is observed and the Meissner effect is found to be present.Furthermore, considering the Lorentz conservations, relativistic energy, and Boltzmann statistics, algorithms are presented to calculate charge density, current density, and internal local energy. We note that these calculations do not require a specific code but instead utilize the software Microsoft Excel.We present plots showing the charge density and current density vs. the applied electric potential, which demonstrate the practical applicability of the theory. Moreover, internal local energy was found to be close to zero for sufficiently large electric potentials at room temperature.In the discussion section, the universally induced superconducting current is derived, which can be employed as the renewable energy.This paper describes non-equilibrium and EPR-pair type superconductivity, with the complete consideration of many-body interactions.

Application of the Ramsey graph theory to the analysis of physical systems is reported. Physical interactions may be very generally classified as attractive and repulsive. This classification creates the premises for the application of the Ramsey theory to the analysis of physical systems built of electrical charges, electric and magnetic dipoles. The notions of mathematical logic, such as transitivity and intransitivity relations, become crucial for understanding of the behavior of physical systems. The Ramsey theory explains why nature prefers cubic lattices over hexagonal ones for systems built of electric or magnetic dipoles. The Ramsey approach may be applied to the analysis of mechanical systems when actual and virtual paths between the states in the configurational space are considered. Irreversible mechanical and thermodynamic processes are seen within the reported approach as directed graphs. Chains of irreversible processes appear as transitive tournaments. These tournaments are acyclic; the transitive tournaments necessarily contain the Hamiltonian path. The set of states in the phase space of the physical system, between which irreversible processes are possible, is considered. The Hamiltonian path of the tournament emerging from the graph uniting these states is a relativistic invariant. Applications of the Ramsey theory to the general relativity become possible when the discrete changes in the metric tensor are assumed. Reconsideration of the concept of “simultaneity” within the Ramsey approach is reported.

Live cell imaging is a powerful technique to study the dynamics and mechanics of various biological molecules like proteins, organelles, DNA, and RNA. With the rapid evolution of optical microscopy, our understanding of how these molecules is implicated in the cells’ most critical physiological roles deepens. Here in this review, we focus on how spatiotemporal nanoscale live cell imaging on a single molecule level allows for profound contributions towards new discoveries in life science. This review will start by summarizing how single molecule tracking has been used to analyze membrane dynamics, receptor ligand interactions, protein-protein interactions, inner- and extracellular transport, gene expression/transcription, and whole organelle tracking. We then move on to how current authors are trying to improve single molecule tracking and overcome current limitations by offering new ways in labeling protein of interests, multi-channel/color detection, improvements in time laps imaging, and new methods and programs to analyze colocalization and movement of targets. We later discuss how single molecule tracking can be a beneficial tool used for medical diagnosis. Finally wrapping up with limitation and future perspective of single molecule tracking and total internal refection microscopy.

Background: Studies have linked bats to outbreaks in human populations such as SARS-CoV-1 and MERS-CoV and the ongoing SARS-CoV-2 pandemic. Method: We carried out a longitudinal survey from August 2020 to July 2021 at two sites in Zimbabwe with bat-human interactions: Magweto cave and Chirundu farm. A total 1732 and 1866 individual bat faecal samples were collected respectively. Coronaviruses and bat species were amplified using PCR systems respectively. Results: Analysis of the coronavirus sequences revealed a high genetic diversity and we identified different sub-viral groups in the Alphacoronavirus and Betacoronavirus genus. The established sub-viral groups fell within the described Alphacoronavirus sub-genera: Decacovirus, Duvinacovirus, Rhinacovirus, Setracovirus and Minunacovirus and for Betacoronavirus sub-genera: Sarbecoviruses, Merbecovirus and Hibecovirus. Our results showed an overall proportion for CoV positive PCR tests of 23.7% at Chirundu site, 16.5% and 38.9% at Magweto site for small insectivorous bats and Macronycteris gigas respectively. Conclusion: The higher risk of bat coronaviruses exposure for humans ranged from December to March in relation to higher viral shedding peaks of coronaviruses in the parturition, lactation and weaning months of the bat populations at both sites. We also highlight the need to further document viral infectious risk in human/domestic animal populations surrounding bat habitats in Zimbabwe.

Tracking information diffusion is a non-trivial task and it has been widely studied across different domains and platforms. The advent of social media has led to even more challenges, given the higher speed of information propagation and the growing impact of social bots and anomalous accounts. Nevertheless, it is crucial to derive a trustworthy information diffusion graph, which is capable of highlighting the importance of specific nodes in spreading the original message. The paper introduces the interaction strength, a novel metric to model retweet cascade graphs by exploring users’ interactions. Initial findings show the soundness of the approaches based on this new metric with respect to the state-of-the-art model, and its ability to generate a denser graph, revealing crucial nodes that participated in the retweet propagation. Reliable retweet graph generation will enable a better understanding of the diffusion path of a specific tweet.

Abstract Introduction Exercise is an effective component in rehabilitation of a range of chronic conditions. There is a growing interest in the use of exercise-based nature interacted rehabilitation (EBNIR), but an overview of current evidence is missing. To provide an informed base for future work within this field of EBNIR, the objective of this scoping review was to map existing exercise-based rehabilitation interventions conducted with incidental or intentional nature interaction focusing on its populations, types of outcomes, and theoretical rationale for people with physical and mental disabilities. Methods This scoping review identified peer-reviewed publications, registered upcoming trials and grey literature. To map all available knowledge, we performed a comprehensive search of selected databases (MEDLINE; EMBASE; CINAHL; Cochrane; Web of Science; Pedro) from inception to October 2022. Data was synthesised in a thematic presentation guided by TIDieR, supplemented by a checklist developed for this study accounting nature incidental or intentional interaction by measuring all nature elements implemented in the intervention. Results Twelve studies including 856 participants met the inclusion criteria. 11 were completed trials and 1 was registered in clinicaltrials.gov to be run in 2023. A total of 856 patients were enrolled in the 12 studies (range 18-262, median 50). The included studies were different in terms of design (observational n=4, qualitative n=1, RCT=7), intervention dosage and frequency, control intervention, diagnosis, number of patients, and outcomes included. The used exercise-based interventions consisted of outdoor walks, neck exercises and surfing interventions in patients with physical or mental health conditions. The interventions were incidental or intentional interacted with nature to a varying degree. Conclusion This scoping review presents an overview of limited and diverse evidence within the field of exercise-based rehabilitation incidental or intentional interacting with nature, in patients with physical or mental health conditions. Our review provides an overview that will be helpful in the design of future EBNIR trials.

Genes that affect adaptive traits have been identified, but our knowledge of the genetic basis of adaptation in a more general sense (across multiple traits) remains limited. We combined population-genomic analyses of evolve and resequence experiments, genome-wide association mapping of performance traits, and analyses of gene expression to fill this knowledge gap, and shed light on the genomics of adaptation to a marginal host (lentil) by the seed beetle Callosobruchus maculatus. Using population-genomic approaches, we detected modest parallelism in allele frequency change across replicate lines during adaptation to lentil. Mapping populations derived from each lentil-adapted line revealed a polygenic basis for two host-specific performance traits (weight and development time), which had low to modest heritabilities. We found less evidence of parallelism in genotype-phenotype associations across these lines than in allele frequency changes during the experiments. Differential gene expression caused by differences in recent evolutionary history exceeded that caused by immediate rearing host. Together, the three genomic data sets suggest that genes affecting traits other than weight and development time are likely to be the main causes of parallel evolution, and that detoxification genes (especially cytochrome P450s and beta-glucosidase) could be especially important for colonization of lentil by C. maculatus.

Three body systems in which one of the bodies is ejected without escaping the binary system have previously been studied in various restricted forms. However, none of these studies dwells on the problem in a general setting. Thus, to study this phenomenon qualitatively, we try to expand this problem's scope to unequal mass systems and generalize them by considering various configurations of fixed initial points with precisely calculated initial velocities, some zero velocity models and some optimized models. We will see the use of terminology similar to the previous studies done in this domain but incorporate different analytical and evaluation methods.

Background: Night-migratory birds sense the Earth´s magnetic field by an unknown molecular mechanism. Theoretical and experimental evidence support the hypothesis that light-induced formation of a radical-pair in European robin cryptochrome 4a, ErCry4a, is the primary signalling step in the retina of the bird. In the present work, we investigated a possible route of cryptochrome signalling involving the α-subunit of the cone specific heterotrimeric G protein from European robin. Methods: Protein-protein interaction studies include surface plasmon resonance, pulldown affinity binding and Förster resonance energy transfer. Results: Surface plasmon resonance studies showed direct interaction revealing high to moderate affinity for binding of non-myristoylated and myristoylated G protein to ErCry4a, respectively. Pulldown affinity experiments confirmed this complex formation in solution. We validated these in vitro data by monitoring the interaction between ErCry4a and G protein in a transiently transfected neuroretinal cell line using Förster resonance energy transfer. Conclusions: Our results suggest that ErCry4a and the G protein also interact in vivo and might constitute the first biochemical signalling step in radical-pair-based magnetoreception.

Macroautophagy/autophagy plays an important role in cellular copper clearance. The means by which the copper metabolism and autophagy pathways interact mechanistically is vastly unexplored. Dysfunctional ATP7B, a copper-transporting ATPase, is involved in the development of monogenic Wilson disease, a disorder characterized by disturbed copper transport. Using in silico prediction, we found that ATP7B contains a number of potential binding sites for LC3, a central protein in autophagy pathway, so-called LC3 interaction regions (LIRs). The conserved LIR3, located at the C-terminal end of ATP7B, was found to directly interact with LC3B in vitro. Replacing the two conserved hydrophobic residues W1452 and L1455 of LIR3 significantly reduced interaction. Furthermore, autophagy was induced in normal human hepatocellular carcinoma cells (HepG2) leading to enhanced colocalization of ATP7B and LC3B on the autophagosome membranes. By contrast, HepG2 cells deficient of ATP7B (HepG2 ATP7B-/-) showed autophagy deficiency at elevated copper condition. This phenotype was complemented by heterologous ATP7B expression. These findings suggest a cooperative role of ATP7B and LC3B in autophagy-mediated copper clearance.

The current article examined stoma self-care and health-related quality of life in patients with drainage enterostomy, describe clinical and sociodemographic variables and analyze the relations between all of them. Trained interviewers collected data using a standardized form that queried sociodemographic and clinical variables, collected from the electronic medical record, in addition to the Specific Self-Care for Ostomized Patients Questionnaire (CAESPO) and Stoma Quality of life (S-QoL) from January 2016 to January 2017. This was a multicenter, cross sectional study conducted in four hospitals of the province of Castellon (Spain) where 120 participants were studied. Significant differences were found in Self Care according to sex (p = .043); married participants show higher score (p < .01); also, significant differences according to work activity were observed (p < .01). Regarding the clinical variables, differences were observed according to the autonomy of care, the presence of complications in the stoma, the use of irrigation and the type of effluent (p < .01). We can highlight the importance of the skills related to self-care by ostomized patients has for a good level of quality of life related to health. In this learning process, the figure of the stoma therapist plays a very important role.

In this paper, we present a finite element simulation of an adaptive piezoelectric fluid-membrane lens modeled in COMSOL Multiphysics. The simulation couples the piezoelectric effect with the fluid dynamics to model the interaction between piezoelectric forces and fluid forces. Also, the simulation is extended to model the thermal expansion of the fluid. Finally, we compare the simulation and experimental results of the adaptive lens refractive power at different actuation levels and temperatures.

The 2-oxoglutarate dehydrogenase complex (OGDHc) is a key enzyme in the TCA cycle and represents one of the major regulators of mitochondrial metabolism through NADH and reactive oxygen species levels. The OGDHc impacts cell metabolic and cell signaling pathways through the coupling of 2-oxoglutarate metabolism to gene transcription related to tumor cell proliferation and aging. DHTKD1 is a gene encoding 2-oxoadipate dehydrogenase (E1a), which functions in the L-lysine degradation pathway. The potentially damaging variants in DHTKD1 have been associated to the (neuro) pathogenesis of several diseases. Evidence was obtained for the formation of a hybrid complex between the OGDHc and E1a, suggesting a potential cross talk between the two metabolic pathways and raising fundamental questions about their assembly. Here we reviewed the recent findings and advances in understanding of protein-protein interactions in OGDHc and 2-oxoadipate dehydrogenase complex (OADHc), an understanding that will create a scaffold to help design approaches to mitigate the effects of diseases associated with dysfunction of the TCA cycle or lysine degradation. A combination of biochemical, biophysical and structural approaches such as chemical cross-linking MS and cryo-EM appears particularly promising to provide vital information for the assembly of 2-oxo acid dehydrogenase complexes, their function and regulation.

At present there is a renewed interest in theories of ”modified” gravity. Here, under a more drastic modification enforced by Galilei group, we obtain a completely new gravitational structure, and which exists in addition to the already available general relativity of today. Correlated with this, we show that in addition, there is a new ”modified” quantum mechanics, in as much as it exists as an independent and new ”pure” non-relativistic quantum me- chanics, and which has no relativistic counterpart. This is in addition to the present quantum mechanics, where the relativistic and non-relativistic structures are counterparts of each other. The above holds, firstly due to the correlation between Galilei group and quantum mechanics. These math- ematical conclusions are consolidated by the fact that there exists a physical Majorana interaction between each neutron- proton pairs in nuclei. Galilei invariance of Majorana exchange in Majorana interaction, shows that the mass here is of pure gravitational nature, and which is immune to the other three forces. This makes an amazing connection between the gravitational force and the quantum mechanics. This pure gravitational mass would man- ifest itself as dark matter of the universe. It is our new modified gravity that generates the dark matter.

The clinical interaction between stroke and periodontitis has been consistently studied and confirmed. Hence, forecasting potentially new protein interactions in this association using bioinformatic strategies presents potential interest. In this exploratory study, we conducted a protein-protein network interaction (PPI) search with documented encoded proteins for both stroke and periodontitis. Genes of interest were collected via GWAS database. The STRING database was used to predict the PPI networks, first in a sensitivity purpose (confidence cut-off of 0.7), and then with a highest confidence cut-off (0.9). Genes over-representation was inspected in the final network. As a result, we foresee a prospective protein network of interaction between stroke and periodontitis. Inflammation, pro-coagulant/pro-thrombotic state and ultimately atheroma plaque rupture is the main biological mechanism derived from the network. These pilot results may pave the way to future molecular and therapeutic studies to further comprehend the mechanisms between these two conditions.

Charles Darwin’s theory of evolution, his note as regards descent with modification, added greatly to the knowledge that we already possess of how species have survived down the ages. It is evident that this does not provide the necessary knowledge about the origin of the life on earth. However, it provides remarkable evidence about how life has survived. Looking fundamentally at the cellular construct of organisms, we arrive at the fact that cells, both unicellular and multicellular, have organelles that enable them communicate with one another. This ability for living organisms, down to the lowest - cellular life - to communicate is what I refer to as Biological interaction. It is necessary that we articulate more about this concept and see how this all comes to bear as regards Homeostasis. In reference to the latter, it is to be made known that every living organism is also intrinsically aimed towards a projected linear motion in its time riddled existence. This is to say that every living organism operates on an foundational process, amongst others, known as Homeostasis. We understand this term to mean balance that the living system strives to maintain. However etymologically speaking it means staying the same. How has this homeostatic process added to the fostering of life via biological interaction? How is biological interaction fundamental to the theory of evolution?