Miracle-dz/UniFAR-FTUs huggingface dataset:
A Multi-Phenotype System to Discover Therapies for Age-Related Dysregulation of the Immune Response to Viral Infections

Age-related immune dysregulation contributes to increased susceptibility to infection and disease in older adults. We combined high-throughput laboratory automation with machine learning to build a multi-phenotype aging profile that models the dysfunctional immune response to viral infection in older adults. From a single well, our multi-phenotype aging profile can capture changes in cell composition, physical cell-to-cell interaction, organelle structure, cytokines, and other hidden complexities contributing to age-related dysfunction. This system allows for rapid identification of new potential compounds to rejuvenate older adults’ immune response. We used our technology to screen thousands of compounds for their ability to make old immune cells respond to viral infection like young immune cells. We observed beneficial effects of multiple compounds, of which two of the most promising were disulfiram and triptonide. Our findings indicate that disulfiram could be considered as a treatment for severe coronavirus disease 2019 and other inflammatory infections.
Inverse spectral problems for differential operators with non-separated boundary conditions

Abstract We give a short review of results on inverse spectral problems for second-order differential operators on an interval with non-separated boundary conditions. We pay the main attention to the most important nonlinear inverse problems of recovering coefficients of differential operators from given spectral characteristics. In the first part of the review, we provide the main results and methods related to inverse problems for Sturm–Liouville operators with non-separated boundary conditions: periodic, quasi-periodic and Robin-type boundary conditions. At the end, we present the main results on inverse problems for differential pencils with non-separated boundary conditions.
Implementation of Presolving and Interior-Point Algorithm for Linear & Mixed Integer Programming: SOFTWARE

Abstract Linear and mixed integer programming are very popular and important methods to make efficient scientific management decision. With large size of real application data, the use of linear-mixed integer programming is facing problems with more complexity; therefore, preprocessing techniques become very important. Preprocessing aims to check and delete redundant information from the problem formulation. It is a collection of techniques that reduce the size of the problem and try to strengthen the formulation. Fast and effective preprocessing techniques are very important and essential for solving linear or mixed integer programming instances. In this paper, we demonstrate a set of techniques to presolve linear and mixed integer programming problems. Experiment results showed that when preprocessing is well done, then it becomes easier for the solver; we implemented interior-point algorithm for computational experiment. However, preprocessing is not enough to reduce the size and total nonzero elements from the constraints matrix. Moreover, we also demonstrate the impact of minimum degree reordering on the speed and storage requirements of a matrix operation. All techniques mentioned above are presented in a multifunctional software to facilitate users.
Resource Allocation Strategy of Edge Systems Based on Task Priority and an Optimal Integer Linear Programming Algorithm

With the emergence of increasingly computing-intensive and delay-sensitive tasks, the processing of computing tasks on cloud servers cannot meet the current needs any longer. The emergence of mobile edge computing (MEC) technology and the popularity of 5G applications can solve these demands. Offloading tasks to the MEC server reduces the energy consumption of local devices, and also has a lower latency than offloading to the cloud server. In this paper, an MEC–edge cloud server collaborative system model with energy harvesting technology is designed to minimize the processing delay of computing tasks by allocating computing resources. We propose an optimal integer linear programming (OILP) algorithm with two steps. Firstly, we propose a Lyapunov stability optimization algorithm based on task priority. With the constraints of local mobile device power stability, the divide-and-conquer idea is used for solving the target values of the processing tasks locally, and the MEC and edge cloud servers separately. Therefore, the objective problem is transformed into an integer linear programming problem, and then an integer linear programming algorithm based on CPU utilization optimization is proposed to obtain a resource allocation scheme. Simulation results show that the proposed OILP algorithm can further reduce the delay, improve the CPU’s utilization of the MEC server, and reduce the number of the tasks that cannot be processed under the condition of the energy stability of the local device.
An Extended Analysis on Robust Dissipativity of Uncertain Stochastic Generalized Neural Networks with Markovian Jumping Parameters

The main focus of this research is on a comprehensive analysis of robust dissipativity issues pertaining to a class of uncertain stochastic generalized neural network (USGNN) models in the presence of time-varying delays and Markovian jumping parameters (MJPs). In real-world environments, most practical systems are subject to uncertainties. As a result, we take the norm-bounded parameter uncertainties, as well as stochastic disturbances into consideration in our study. To address the task, we formulate the appropriate Lyapunov–Krasovskii functional (LKF), and through the use of effective integral inequalities, simplified linear matrix inequality (LMI) based sufficient conditions are derived. We validate the feasible solutions through numerical examples using MATLAB software. The simulation results are analyzed and discussed, which positively indicate the feasibility and effectiveness of the obtained theoretical findings.
Studies on C. elegans probed with estradiol, elucidate the critical role of Na+/H+ exchanger, nhx-2 in reproductive senescence and neuronal health

Setting in of reproductive senescence (RS) gives rise to several changes, making aged individuals susceptible to neurodegenerative diseases, cardiovascular and bone disorders amongst others. The present study deciphers the association of reproductive senescence, presence/absence of the sex hormone estradiol with age-associated neurodegenerative diseases. We employed RNAi induced silencing of a subset of 22 genes that are known to delay RS, followed by studies on alpha-Synuclein aggregation and associated effects in the transgenic C. elegans. These studies led us to fuctional characterisation of the Na+/H+ exchanger, expressed exclusively in gut. We found that RNAi of nhx-2 ameliorates the affects associated with alpha-Synuclein aggregation via mimicking dietary restriction as it alters food absorption from the gut. Our studies further elucidated that such effects are Sir-2.1 driven as nhx-2 RNAi did not delay reproductive senescence when sir-2.1 was silenced concurrently. As estradiol plays a central role in both reproductive health as well as neuronal health, we performed structural binding analysis that demonstrated the binding potential of the estradiol receptor NHR-14 with nhx-2 gene. Hence, we treated the worms with estradiol and observed that the transcription levels of nhx-2 were elevated above the endogenous level. To unravel the underlying molecular mechanism of induction we performed ChIP analysis and it revealed that estradiol treatment gives rise to enhanced NHX-2 levels through inducing the promoter specific histone H3 acetylation (H3K9) and lysine methylation (H3K4me3). Graphical abstract HIGHLIGHTS Silencing of a sodium proton antiporter nhx-2 of gut ameliorates effects associated with alpha-Synuclein aggregation via mimicking dietary restriction in C. elegans. We have established a genetic cross to construct a strain that expresses mCherry SIR-2.1 ubiquitously and α-Synuclein in muscles, that assists in corroborating the link between NHX-2 and SIR-2.1. Human 17-β-Estradiol treatment induces the expression of nhx-2, through inducing the promoter specific histone H3 acetylation (H3K9) and lysine methylation (H3K4me3). Effects associated with nhx-2, including prolonged reproductive span and neuroprotective effects, are SIR-2.1 driven. nhx-2 silencing decreases alpha-Synuclein aggregation however estradiol mediated overexpression above the endogenus level, does not amend the aggregation any further.
Repression of Pdzrn3 is required for heart maturation and protects against heart failure

Heart failure is the final common stage of most cardiopathies. Cardiomyocytes connect with others via their extremities by intercalated disk protein complexes. This planar and directional organization of myocytes is crucial for mechanical coupling and anisotropic conduction of the electric signal in the heart. One of the hallmarks of heart failure is alterations in the contact sites between cardiomyocytes. Yet no factor on its own is known to coordinate cardiomyocyte polarized organization. We report enhanced levels of an ubiquitine ligase Pdzrn3 in diseased hypertrophic human and mouse myocardium, which correlates with a loss of cardiomyocyte polarized elongation. We provide evidence that Pdzrn3 has a causative role in heart failure. We found that cardiac Pdzrn3 deficiency protected against heart failure while over expression of Pdzrn3 in mouse cardiomyocytes during the first weeks of life, impaired postnatal cardiomyocyte maturation leading to premature death. Our results reveal a novel signaling pathway that controls a genetic program essential for heart maturation and maintenance of overall geometry, as well as the contractile function of cardiomyocytes, and implicates PDZRN3 as a potential therapeutic target for the prevention of human heart failure.
Anatomical Considerations and Study of the Fractal Dimension around the Posterior Superior Alveolar Artery

The Posterior Superior Alveolar Artery (PSAA) provides vascular support to molars, gingiva, and maxillary sinus. A tear of the PSAA may cause profuse hemorrhages which may lead to complications at a surgical level. As such, it becomes crucial to anatomically analyse several features regarding the PSAA as well as the area surrounding it. In this paper, we are particularly interested in the study of the complexity of the periodontal tissue structure which appears close to the location of the PSAA. A total amount of 400 cone beam computed tomography (CBCT) scans (two per subject) were performed to explore the presence of the PSAA, the thickness of the Schneider’s membrane, and the existence of septa. Several parameters were evaluated including the location of the artery in the maxillary sinus, the distance from the PSAA to the alveolar ridge, the thickness of the membrane, the diameter of the cavities produced by the septa, and the fractal dimension of the trabecular tissue that surrounds the PSAA. They were found strong linear relationships between Distal and Central Measures (a Pearson’s R 2 = 0.9952 ), Mesial and Central Measures ( R 2 = 0.9950 ), and Distal and Mesial Measure ( R 2 = 0.997 ). We hypothesised that the loss of dental pieces would imply a distinct complexity of the trabecular tissue structure surrounding the PSAA. In this way, a p-value equal to 0.001 was provided by the Mann-Whitney test, which supports our hypothesis. Furthermore, the mean of the fractal dimensions of the group of edentulous patients (equal to 1.56 ) was found to be lower than the one of the group of non-edentulous patients (equal to 1.61 ) with small standard deviations in both cases. Our study suggests that accurate calculations of the fractal dimension combined with the use of CBCT do provide valuable information regarding the area that surrounds the PSAA.
Biquaternionic Dirac Equation Predicts Zero Mass for Majorana Fermions

A biquaternionic version of the Dirac Equation is introduced, with a procedure for converting four-component spinors to elements of the Pauli algebra. In this version, mass appears as a coefficient between the 4-gradient of a spinor and its image under an outer automorphism of the Pauli algebra. The charge conjugation operator takes a particulary simple form in this formulation and switches the sign of the mass coefficient, so that for a solution invariant under charge conjugation the mass has to equal zero. The multiple of the charge conjugation operator by the imaginary unit turns out to be a complex Lorentz transformation. It commutes with the outer automorphism, while the charge conjugation operator itself anticommutes with it, providing a second more algebraic proof of the main theorem. Considering the Majorana equation, it is shown that non-zero mass of its solution is imaginary.
Enzymatic Degradation of 2, 4, 6-Trichlorophenol in a Microreactor using Soybean Peroxidase

Soybean peroxidase is an enzyme extracted from soybean seed hulls. In the presence of hydrogen peroxide, the enzyme has the potential to catalyze the biodegradation of toxic substances like chlorophenols. For this reason, its use in wastewater treatment processes is environmentally friendly since the enzyme can be obtained from a renewable and abundant raw material. In this work, enzymatic biodegradation of 2,4,6-trichlorophenol performed by soybean peroxidase in a microreactor was studied experimentally and theoretically. The experimental data set was obtained with a volume of 250 μL by using different soybean peroxidase concentrations and different reaction times. The fluid dynamics of the microreactor was modeled as well, using ANSYS CFX. The simulations exhibited secondary flows, which enhanced mixing. Although the laminar flow was developed, it can be assumed to be a well-mixed medium. The kinetic data were evaluated through a mechanistic model, the modified bi-bi ping-pong model, which is adequate to represent the enzymatic degradation using peroxidases. The model was composed of an initial value problem for ordinary differential equations that were solved using MATLAB. Some kinetic constants were estimated using the least square function. The results of the model fit well the experimental data.
Associations between individual gliadin proteins and quality, agronomic and morphological attributes of wheat cultivars

The gliadin protein compositions of 79 wheat genotypes from Australia, New Zealand and North America, and one rye cultivar have been examined by starch gel electrophoresis. Interrelationships in the patterns thus obtained were investigated using a computer-generated inverse minimum spanning tree. Certain components were frequently found to occur together, presumably because their synthesis is controlled by closely linked genes. In addition, by using a network-generating program, associations between gliadins and many morphological (plant, head and grain), agronomic and quality attributes were studied. In many cases, specific gliadin components were found to be closely associated with certain attributes. In such cases a direct cause and effect cannot be inferred, but the approach indicates associations that warrant further study.
NK cells integrate signals over large areas when building immune synapses but require local stimuli for degranulation

The spatial distribution of activating ligands dictates NK cell synapse formation, stability, and function. Ligand-patterned immune synapses Natural killer (NK) cells execute virus-infected and tumor cells by forming immunological synapses with the target cells and releasing cytotoxic granules. The NK cell receptors LFA-1 and CD16 drive target cell recognition, synapse formation, and degranulation. Using artificial immune synapses (AIS) consisting of LFA-1 and CD16 ligands, Verron et al. found that the spatial distribution of receptor activation influenced the stability of synapses and subsequent degranulation. Although human NK cells formed synapses and properly positioned the lytic machinery on both dot- and donut-shaped AIS, degranulation did not occur in the central regions of donut-shaped AIS. The dependence of degranulation on local signaling suggests the existence of a late checkpoint for degranulation and suggests that target cells might be able to evade execution by controlling the spatial distribution of ligands (see also the Focus by Veillette). Immune synapses are large-scale, transient molecular assemblies that serve as platforms for antigen presentation to B and T cells and for target recognition by cytotoxic T cells and natural killer (NK) cells. The formation of an immune synapse is a tightly regulated, stepwise process in which the cytoskeleton, cell surface receptors, and intracellular signaling proteins rearrange into supramolecular activation clusters (SMACs). We generated artificial immune synapses (AIS) consisting of synthetic and natural ligands for the NK cell–activating receptors LFA-1 and CD16 by microcontact printing the ligands into circular-shaped SMAC structures. Live-cell imaging and analysis of fixed human NK cells in this reductionist system showed that the spatial distribution of activating ligands influenced the formation, stability, and outcome of NK cell synapses. Whereas engagement of LFA-1 alone promoted synapse initiation, combined engagement of LFA-1 and CD16 was required for the formation of mature synapses and degranulation. Organizing LFA-1 and CD16 ligands into donut-shaped AIS resulted in fewer long-lasting, symmetrical synapses compared to dot-shaped AIS. NK cells spreading evenly over either AIS shape exhibited similar arrangements of the lytic machinery. However, degranulation only occurred in regions containing ligands that therefore induced local signaling, suggesting the existence of a late checkpoint for degranulation. Our results demonstrate that the spatial organization of ligands in the synapse can affect its outcome, which could be exploited by target cells as an escape mechanism.
Automatic segmentation of dentate nuclei for microstructure assessment: example of application to temporal lobe epilepsy patients

Dentate nuclei (DNs) segmentation is helpful for assessing their potential involvement in neurological diseases. Once DNs have been segmented, it becomes possible to investigate whether DNs they are microstructurally affected, through analysis of quantitative MRI parameters, such as the ones derived from diffusion weighted imaging (DWI). This study, therefore, aimed to develop a fully automated segmentation method using the non-DWI (b0) images from a DWI dataset to obtain DN masks inherently registered with parameter maps. Three different automatic methods were applied to healthy subjects in order to segment the DNs: registration to SUIT (a spatially unbiased atlas template of the cerebellum and brainstem), OPAL (Optimized Patch Match for Label fusion) and CNN (Convolutional Neural Network). DNs manual segmentation was considered the gold standard. Results show that the segmentation obtained with SUIT has an average Dice Similarity Coefficient (DSC) of 0.4907±0.0793 between the automatic SUIT masks and the gold standard. A comparison with manual masks was also performed for OPAL (DSC = 0.7624 ± 0.1786) and CNN (DSC = 0.8658 ± 0.0255), showing a better performance when using CNN. OPAL and CNN were optimised on heathy subjects’ data with high spatial resolution from the Human Connectome Project. The three methods were further used to segment the DNs of a subset of subjects affected by Temporal Lobe Epilepsy (TLE). This subset was derived from a 3T MRI research study which included DWI data acquired with a coarser resolution. In TLE dataset, SUIT performed similarly to using the HCP dataset, with a DSC = 0.4145 ± 0.1023. Using TLE data, OPAL performed worse than using HCP data: after changing the probability threshold the DSC was 0.4522 ± 0.1178. CNN was able to extract the DNs using the TLE data without need for retraining and with a good DSC = 0.7368 ± 0.0799. Statistical comparison of quantitative parameters derived from DWI analysis, as well as volumes of each DN, revealed altered and lateralised changes in TLE patients compared to healthy controls. The proposed CNN is therefore a viable option for accurate extraction of DNs from b0 images of DWI data with different resolutions and acquired at different sites.
Development of a routine procedure for single nucleotide polymorphism marker design based on the Tm-shift genotyping method

To establish a routine procedure for SNP marker development, the previously reported Tm-shift SNP genotyping procedure was validated and extensively improved. The effect of introducing mismatched nucleotides into allele-specific primers, using alternative fluorescent dyes, and varying the DNA polymerase species on SNP discrimination was examined at more than 100 known SNP loci in a solanaceous crop, eggplant. As a result, it has been shown that a success rate over 80% can be achieved with Tm-shift SNP genotyping using directional trials with automatically designed primer sets and a routine protocol for the reaction condition tests.
Profiles of 14C fixation through spinach leaves in relation to light absorption and photosynthetic capacity

The profile of photosynthetic rate with depth through a leaf depends on the profiles of light absorption and photosynthetic capacity. Using a combination of several techniques, a comprehensive description of spinach leaves has been obtained. Profiles of CO2 fixation were obtained by exposing leaves to 14CO2 for 10 s under blue or green light before freeze clamping and paradermal sectioning. Profiles of light absorption were measured on adjacent parts of the leaf by quantifying chlorophyll fluorescence images of the transversely cut face obtained when blue or green light was applied to the adaxial or abaxial surface. The profile of CO2 fixation was modelled using the measured profiles of light absorption and photosynthetic capacity. There was remarkably good agreement between the observed and modelled CO2 fixation profiles for the eight combinations of colour, orientation and irradiance tested. Gas exchange of an intact leaf was also measured concurrently with conventional chlorophyll fluorescence under blue or green light. These data were consistent with the multi-layer leaf model with the exception of blue light applied to the abaxial surface, where chlorophyll fluorescence appeared to come from layers deeper than expected. Photosynthetic capacity matched the profile of green but not white light absorption through the leaf.
Implicit Extragradient-Like Method for Fixed Point Problems and Variational Inclusion Problems in a Banach Space

In a uniformly convex and q-uniformly smooth Banach space with q ∈ ( 1 , 2 ] , one use VIP to indicate a variational inclusion problem involving two accretive mappings and CFPP to denote the common fixed-point problem of an infinite family of strict pseudocontractions of order q. In this paper, we introduce a composite extragradient implicit method for solving a general symmetric system of variational inclusions (GSVI) with certain VI and CFPP. We then investigate its convergence analysis under some weak conditions. Finally, we consider the celebrated LASSO problem in Hilbert spaces.