Miracle-dz/UniFAR-FTUs huggingface dataset:
The cardioprotective effect of human glucagon‐like peptide‐1 receptor agonist (semaglutide) on cisplatin‐induced cardiotoxicity in rats: Targeting mitochondrial functions, dynamics, biogenesis, and redox status pathways

The cardiotoxic effect of chemotherapeutic agents as cisplatin has become a major issue recently. Interference with mitochondrial dynamics, biogenesis, redox status, and apoptosis are the most possible underlying mechanisms. Semaglutide is a human glucagon‐like peptide‐1 receptor agonist (GLP‐1R), which is used primarily for the treatment of DM. Various recent studies have investigated (GLP‐1R) role in cardiovascular diseases due to antiapoptotic and antioxidant effects. The current study aimed to investigate the curative role of semaglutide's against cisplatin‐ induced cardiotoxicity and its relation to mitochondrial functions, dynamics, biogenesis, apoptosis, and redox status pathways. The study included 30 male rats divided into three groups: control, cisplatin‐induced cardiotoxicity, and cisplatin‐induced cardiotoxicity treated with semaglutide. At the end of the experiment heart index, serum cardiotoxicity markers, SOD, GPX activities and H2O2 level were estimated. Mitochondrial transmembrane potential, complex I and citrate synthase enzyme activities, ATP level, Mfn2 in addition to PGC‐1 α levels were assessed as biogenesis markers. Mitophagy markers PINK1 and Parkin mRNA gene expression were estimated. Histopathological examination of cardiac muscles of all studied groups and immunoassay of P53 and caspase 3 in cardiac tissue were examined to assess apoptosis. Cisplatin has disturbed mitochondrial function and dynamics, dysregulate redox status and induced mitophagy and apoptosis, in the other hand semaglutide treatment has normalized dysregulated mitochondrial function and dynamics, redox status and suppressed mitophagy and apoptosis. Semaglutide has ameliorative effect against cisplatin‐ induced cardiotoxicity via modulation of mitochondrial functions, dynamics, biogenesis, apoptosis, and redox status pathways.
Cone-Beam Pair-Wise Data Consistency Conditions in Helical CT

Data consistency conditions (DCC) are mathematical equations characterizing the redundancy in X-ray projections. They have been used to correct inconsistent projections before computed tomography (CT) reconstruction. This article investigates DCC for a helical acquisition with a cylindrical detector, the geometry of most diagnostic CT scanners. The acquired projections are analyzed pair-by-pair. The intersection of each plane containing the two source positions with the corresponding cone-beams defines two fan-beams for which a DCC can be computed. Instead of rebinning the two fan-beam projections to a conventional detector, we directly derive the DCC in detector coordinates. If the line defined by two source positions intersects the field-of-view (FOV), the DCC presents a singularity which is accounted for in our numerical implementation to increase the number of DCC compared to previous approaches which excluded these pairs of source positions. Axial truncation of the projections is addressed by identifying for which set of planes containing the two source positions the fan-beams are not truncated. The ability of these DCC to detect breathing motion has been evaluated on simulated and real projections. Our results indicate that the DCC can detect motion if the baseline and the FOV do not intersect. If they do, the inconsistency due to motion is dominated by discretization errors and noise. We therefore propose to normalize the inconsistency by the noise to obtain a noise-aware metric which is mostly sensitive to inconsistencies due to motion. Combined with a moving average to reduce noise, the derived DCC can detect breathing motion.
Infection Defects of RNA and DNA Viruses Induced by Antiviral RNA Interference

Immune recognition of viral genome-derived double-stranded RNA (dsRNA) molecules and their subsequent processing into small interfering RNAs (siRNAs) in plants, invertebrates, and mammals trigger specific antiviral immunity known as antiviral RNA interference (RNAi). Immune sensing of viral dsRNA is sequence-independent, and most regions of viral RNAs are targeted by virus-derived siRNAs which extensively overlap in sequence. SUMMARY Immune recognition of viral genome-derived double-stranded RNA (dsRNA) molecules and their subsequent processing into small interfering RNAs (siRNAs) in plants, invertebrates, and mammals trigger specific antiviral immunity known as antiviral RNA interference (RNAi). Immune sensing of viral dsRNA is sequence-independent, and most regions of viral RNAs are targeted by virus-derived siRNAs which extensively overlap in sequence. Thus, the high mutation rates of viruses do not drive immune escape from antiviral RNAi, in contrast to other mechanisms involving specific virus recognition by host immune proteins such as antibodies and resistance (R) proteins in mammals and plants, respectively. Instead, viruses actively suppress antiviral RNAi at various key steps with a group of proteins known as viral suppressors of RNAi (VSRs). Some VSRs are so effective in virus counter-defense that potent inhibition of virus infection by antiviral RNAi is undetectable unless the cognate VSR is rendered nonexpressing or nonfunctional. Since viral proteins are often multifunctional, resistance phenotypes of antiviral RNAi are accurately defined by those infection defects of VSR-deletion mutant viruses that are efficiently rescued by host deficiency in antiviral RNAi. Here, we review and discuss in vivo infection defects of VSR-deficient RNA and DNA viruses resulting from the actions of host antiviral RNAi in model systems.
PASK links cellular energy metabolism with a mitotic self-renewal network to establish differentiation competence

Quiescent stem cells are activated in response to a mechanical or chemical injury to their tissue niche. Activated cells rapidly generate a heterogeneous progenitor population that regenerates the damaged tissues. While the transcriptional cadence that generates heterogeneity is known, the metabolic pathways influencing the transcriptional machinery to establish a heterogeneous progenitor population remains unclear. Here, we describe a novel pathway downstream of mitochondrial glutamine metabolism that confers stem cell heterogeneity and establishes differentiation competence by countering post-mitotic self-renewal machinery. We discovered that mitochondrial glutamine metabolism induces CBP/EP300-dependent acetylation of stem cell-specific kinase, PAS domain-containing kinase (PASK), resulting in its release from cytoplasmic granules and subsequent nuclear migration. In the nucleus, PASK catalytically outcompetes mitotic WDR5-anaphase-promoting complex/cyclosome (APC/C) interaction resulting in the loss of post-mitotic Pax7 expression and exit from self-renewal. In concordance with these findings, genetic or pharmacological inhibition of PASK or glutamine metabolism upregulated Pax7 expression, reduced stem cell heterogeneity, and blocked myogenesis in vitro and muscle regeneration in mice. These results explain a mechanism whereby stem cells co-opt the proliferative functions of glutamine metabolism to generate transcriptional heterogeneity and establish differentiation competence by countering the mitotic self-renewal network via nuclear PASK.
On self-similar solutions to the homogeneous Boltzmann equation

In this note, our results from [ Comm. Pure Appl. Math. 63 (2010), 747--778] on infinite energy solutions to the homogeneous Boltzmann equation for Maxwellian-type molecules are discussed, presented in a different context, and improved by using recent observations by Morimoto and Yang. In particular, similarities between the homogeneous Boltzmann equation and the fractional heat equation are emphasized. Moreover, we show that a certain conjecture by Bobylev and Cercignani on regularity of self-similar solutions to the homogeneous Boltzmann equation for Maxwellian-type molecules has a positive answer.
Engineering mutually orthogonal PylRS/tRNA pairs for dual encoding of functional histidine analogues

The availability of an expanded genetic code opens exciting new opportunities in enzyme design and engineering. In this regard histidine analogues have proven particularly versatile, serving as ligands to augment metalloenzyme function and as catalytic nucleophiles in designed enzymes. The ability to genetically encode multiple functional residues could greatly expand the range of chemistry accessible within enzyme active sites. Here, we develop mutually orthogonal translation components to selectively encode two structurally similar histidine analogues. Transplanting known mutations from a promiscuous Methanosarcina mazei pyrrolysyl‐tRNA synthetase (MmPylRSIFGFF) into a single domain PylRS from Methanomethylophilus alvus (MaPylRSIFGFF) provided a variant with improved efficiency and specificity for 3‐methyl‐L‐histidine (MeHis) incorporation. The MaPylRSIFGFF clone was further characterized using in vitro biochemical assays and x‐ray crystallography. We subsequently engineered the orthogonal MmPylRS for activity and selectivity for 3‐(3‐pyridyl)‐L‐alanine (3‐Pyr), which was used in combination with MaPylRSIFGFF to produce proteins containing both 3‐Pyr and MeHis. Given the versatile roles played by histidine in enzyme mechanisms, we anticipate that the tools developed within this study will underpin the development of enzymes with new and enhanced functions.
Complaining, Regret, Superiority, and Discovery: Chinese Patients’ Sense Making of Depression in an Online Forum

Drawing on observations of a Chinese online depression community, this article explored the members’ sense making of depression by analyzing their narrative accounts of depression. Four types of sense making were predominant among the depression sufferers: complaining, regret, superiority, and discovery. The complaining narrative is the members’ telling about the pain caused by family (parental control or neglect), school bullying, stress from study or work, and social norms. The regret narrative is the members’ reflection on their habit of perfectionism and lack of self-disclosure. The superiority narrative is the members’ attribution of depression to their intelligence and morality that surpass the average people. The discovery narrative is the members’ novel understanding of the self, significant others, and key events. The findings suggest that the social and psychological explanation of the causes of depression, instead of the medical model, is popular among the Chinese patients. Their stories of depression are also stories of marginalization, visions for the future, and realizing the normalization of identity as depression patients. The findings have implications for public policy around support for mental health.
A multispecies corridor in a fragmented landscape: Evaluating effectiveness and identifying high-priority target areas

While Misiones, Argentina contains one of the largest remnants of Upper Paraná Atlantic Forest ecoregion, one of the world’s biodiversity hotspots, only ~50% of this native forest is protected. Each protected area is at risk of becoming an island of native forest surrounded by a matrix of altered habitats due to ongoing land conversion. In an effort to maximize long-term connectivity between existing protected areas, DeMatteo [1] used a multifaceted cost analysis to determine the optimal location for the region’s first multispecies corridor using noninvasive data on jaguars (Panthera onca), pumas (Puma concolor), ocelots (Leopardus pardalis), southern tiger cats (Leopardus guttulus), and bush dogs (Speothos venaticus). This work builds on this framework by integrating new field data that broadens the scope of species-specific data across the region’s heterogeneous landscape, which varies in vegetation, disturbance, human proximity, and protective status. In addition, two different land use layers are compared across the distributions of the five carnivores, the overlap in their independent distributions, and their relationship to the multispecies corridor. Interpretation of these land use data to species-specific habitat suitability goes beyond DeMatteo [1], with a subdivision of suitability into marginal and optimal areas. This refined scale allows a reanalysis of key areas in the multispecies corridor, where connectivity was previously defined as at highly-at-risk, allowing for a more directed development of management strategies. These analyses and their interpretation extend beyond northern-central Misiones, as the threats are not unique to this region. The need to develop management strategies that balance human-wildlife needs will continue to grow as humans expand their footprint. The techniques applied in this analysis provide a way to identify key areas that require specific management strategies, either through restoration, protection, or a combination of both.
Numerical analysis of wake structure and performance of two oscillatory mechanisms of a foil: Pure pitching and undulating

There are various propulsion, maneuvering, and stabilization mechanisms in nature, which can provide inspiration for similar mechanisms in man-made vehicles. This study aims to elucidate and compare the propulsive vortical signature and performance of a foil in two important natural mechanisms of pure pitching and undulatory oscillations. Governing equations are solved with a pressure-based finite volume method solver, in an arbitrary Lagrangian–Eulerian framework domain containing a NACA 0012 foil moving with prescribed kinematics. The results show that in a given Reynolds number (Re), the undulating mechanism produces thrust at a higher Strouhal number (St) and with smaller growth slope, but mostly higher efficiency, versus St, than pitching mechanism. In addition, vortical structures of these mechanisms have significant differences and also vary considerably with St. One of the distinguishable features of vortical signatures is the presence of the leading-edge vortices for the pitching foil, which are not appearing in the undulating foil’s vortical pattern.
Reduced circulating Tregs and positive pANCA were robustly associated with the occurrence of antiphospholipid syndrome in patients with systemic lupus erythematosus

Background Systemic lupus erythematosus (SLE) is a typical chronic immune disorder with clinical heterogeneity. The systemic abnormal immune response not only challenges the diagnosis and treatment of the disease itself but also the secondary antiphospholipid syndrome (APS), characterized by recurrent arterial or venous thrombosis, recurrent spontaneous abortion, or stillbirth. Clinical interest has primarily focused on primary APS’s pathological and clinical features. However, differences in clinical features and laboratory indicators between SLE with or without APS are still lacking, especially differences between circulating lymphocytes, which are critical in the pathogenesis of SLE and its complications. Methods In this retrospective study, we collected and analyzed clinical characteristics, general laboratory indicators, immunological indicators, and circulating lymphocyte subsets of SLE with or without APS. Results Systemic lupus erythematosus with APS (SLE-APS) had elevated SLEDAI scores, hospitalization costs and time, and frequencies of central nervous system symptoms and spontaneous abortion compared with those without APS. SLE-APS had higher positive anti-Cardiolipin antibodies, anti-β2 Glycoprotein 1 antibodies, and perinuclear antineutrophil cytoplasmic antibody (pANCA) than none-APS patients. Compared with healthy controls (HCs), the circulating lymphocyte subsets were altered to some extent in all patients, especially in patients with SLE-APS. Reduced Tregs and positive pANCA were independent risk factors for SLE secondary APS. Conclusion The present study revealed a robust association between APS secondary to SLE and reduced Tregs and positive pANCA, which provides essential information regarding the diagnosis and therapeutic possibilities of APS secondary to SLE.
Symmetry and complexity in object-centric deep active inference models

Humans perceive and interact with hundreds of objects every day. In doing so, they need to employ mental models of these objects and often exploit symmetries in the object’s shape and appearance in order to learn generalizable and transferable skills. Active inference is a first principles approach to understanding and modelling sentient agents. It states that agents entertain a generative model of their environment, and learn and act by minimizing an upper bound on their surprisal, i.e. their free energy. The free energy decomposes into an accuracy and complexity term, meaning that agents favour the least complex model that can accurately explain their sensory observations. In this paper, we investigate how inherent symmetries of particular objects also emerge as symmetries in the latent state space of the generative model learnt under deep active inference. In particular, we focus on object-centric representations, which are trained from pixels to predict novel object views as the agent moves its viewpoint. First, we investigate the relation between model complexity and symmetry exploitation in the state space. Second, we do a principal component analysis to demonstrate how the model encodes the principal axis of symmetry of the object in the latent space. Finally, we also demonstrate how more symmetrical representations can be exploited for better generalization in the context of manipulation.
Emergence of common concepts, symmetries and conformity in agent groups—an information-theoretic model

The paper studies principles behind structured, especially symmetric, representations through enforced inter-agent conformity. For this, we consider agents in a simple environment who extract individual representations of this environment through an information maximization principle. The representations obtained by different agents differ in general to some extent from each other. This gives rise to ambiguities in how the environment is represented by the different agents. Using a variant of the information bottleneck principle, we extract a ‘common conceptualization’ of the world for this group of agents. It turns out that the common conceptualization appears to capture much higher regularities or symmetries of the environment than the individual representations. We further formalize the notion of identifying symmetries in the environment both with respect to ‘extrinsic’ (birds-eye) operations on the environment as well as with respect to ‘intrinsic’ operations, i.e. subjective operations corresponding to the reconfiguration of the agent’s embodiment. Remarkably, using the latter formalism, one can re-wire an agent to conform to the highly symmetric common conceptualization to a much higher degree than an unrefined agent; and that, without having to re-optimize the agent from scratch. In other words, one can ‘re-educate’ an agent to conform to the de-individualized ‘concept’ of the agent group with comparatively little effort.
Optimal Combination of Magnetic Attitude Control with Impulsive Thrusting

A = cross-sectional area of magnetic torquers, m a = semimajor axis, m b = magnetic field vector, T C = rotation matrix between two frames d = coil diameter of magnetic torquers, m E = energy consumption of magnetic torquers, MJ e = eccentricity I = moment of inertia matrix, kg · m i = coil current in magnetic torquers, A i = inclination, rad k = control gain used for reference proportional-derivative controller m = magnetic dipole moment vector, A · m N = total number of impulses N̂ = number of impulses per orbit n = gain of impulsive thrust vector, N · m n = number of turns per coil in magnetic torquers r = position vector, m T = orbital period, s t0 = time of perigee passage, s W = controllability Gramian matrix γ = scaling factor for reference proportional-derivative controller δ t = Dirac delta function ε = vector part of quaternions η = scalar part of quaternions θ = attitude Euler angle vector, rad μ = standard gravitational parameter, m∕s Ξ = hybrid state transition matrix τ = torque vector, N · m Φ = continuous-time state transition matrix φ = angle from Euler axis-angle parameters, rad Ψ = discrete-time state transition matrix Ω = right ascension of ascending node, rad ω = angular velocity vector, rad∕s ω = argument of periapsis, rad 1n×n = n × n identity matrix 0m×n = m × n zero matrix · · = differentiation with respect to time j · j = Euclidean norm of a vector k · k = root-mean-square norm of a quantity · × = skew-symmetric matrix operator
Non-Intrusive Runtime Monitoring for Manycore Prototypes

Rapid prototyping is widely used, essential technique for developing novel computing architectures. While simulation-based approaches allow to examine the Design Under Test, the observability of FPGA-based prototypes is limited as they can behave like a black box. However, for verification and design space exploration purposes it is crucial to obtain detailed information on the internal state of such a prototype. In this work we propose an architecture to gather detailed internal measurements during execution and extract them from the design under test without impacting its runtime behavior. It is specifically designed for low resource usage and minimal impact on timing, leaving more resources for the actual prototyped system. Our proposed architecture offers several different interface modules for various signal sources, including register capturing, event counters and bus snooping. We present an estimate of achievable bandwidth and maximum sample rate as well as a demanding case-study with a tiled manycore platform on a multi-FPGA prototyping platform. Experimental results show up to 32 million 4-byte measurements per second, saturating a gigabit Ethernet connection. The monitoring system has proven to be very useful when working with an FPGA-based manycore prototype, as it is an essential tool to reveal incorrect behavior and bottlenecks in hardware, operating system and applications at an early stage.
Stock Price Trends Prediction Based on the Classical Models with Key Information Fusion of Ontologies

An ontology of the financial field can support effective association and integration of financial knowledge. Based on behavioral finance, social media is increasingly applied as one of the data sources for information fusion in stock forecasting to approximate the patterns of market changes. By predicting Tesla (TSLA) stock price trends, this study finds that satisfactory forecasting results can be achieved using classical models and incorporating key information features from the technical indicator ontology class and the investor behavior ontology class, even in the face of the impact of the COVID-19 epidemic. In the post-epidemic period, the back propagation neural network (BPNN) model is used to predict the price trend of TSLA for the next five trading days with an accuracy of up to 91.34%, an F1 score of 0.91, and a return of up to 268.42% obtained from simulated trading. This study extends the research on stock forecasting using fused information in the ontology of the financial field, providing a new basis for general investors in the selection of fusion information and the application of trading strategies and providing effective support for organizations to make intelligent financial decisions under uncertainty.