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Hyperinflammation present in individuals with severe COVID-19 has been associated with an exacerbated cytokine production and hyperactivated immune cells. Endoplasmic reticulum stress leading to the unfolded protein response has been recently reported as an active player in inducing inflammatory responses. Once unfolded protein response is activated, GRP78, an endoplasmic reticulum–resident chaperone, is translocated to the cell surface (sGRP78), where it is considered a cell stress marker; however, its presence has not been evaluated in immune cells during disease. Here we assessed the presence of sGRP78 on different cell subsets in blood samples from severe or convalescent COVID-19 patients. The frequency of CD45+sGRP78+ cells was higher in patients with the disease compared to convalescent patients. The latter showed similar frequencies to healthy controls. In patients with COVID-19, the lymphoid compartment showed the highest presence of sGRP78+ cells versus the myeloid compartment. CCL2, TNF-α, C-reactive protein, and international normalized ratio measurements showed a positive correlation with the frequency of CD45+sGRP78+ cells. Finally, gene expression microarray data showed that activated T and B cells increased the expression of GRP78, and peripheral blood mononuclear cells from healthy donors acquired sGRP78 upon activation with ionomycin and PMA. Thus, our data highlight the association of sGRP78 on immune cells in patients with severe COVID-19.

Density functional theory calculations support the possibility that Li10Si4 and Li6Si5 clusters can be combined to assemble structures, opening opportunities for silicon–lithium cluster assembled materials.

Aromaticity is a useful tool to rationalize the structure, stability, and reactivity in several compounds. Although aromaticity is not directly an observable, it is well accepted that electronic delocalization around the molecular ring is a key stabilizing feature of aromatic compounds. This contribution presents a systematic evaluation of the capability of delocalization and reactivity criteria to describe aromaticity in a set of fluorinated benzenes. The aromaticity indices are compared with quantities obtained from the magnetic criteria of aromaticity, i.e., the strength of the ring current induced by an external magnetic field and the popular NICS

The quality of life in patients with inflammatory bowel diseases (IBD) is strongly impaired. Alterations of intestinal epithelial homeostasis contribute to the development and establishment of IBD. Intestinal Paneth and Paneth-like cells produce and secrete luminal proteins sustaining epithelial homeostasis. Here we show that IFN-γ stimulates Paneth and Paneth-like cells degranulation that triggers the proliferation of intestinal epithelial cells (IEC) in a Wnt/β-catenin independent manner. Degranulation in Paneth and Paneth-like cells was mTORC1 and necroptosis dependent. Remarkably, lack of IFN-γ, inhibition of mTORC1, or impeding necroptosis reduces IEC proliferation cytokine-mediated. Our findings identify a new role for IFN-γ in stimulating IEC proliferation through inducing degranulation of Paneth and Paneth-like cells which is mTORC1 and necroptosis- dependent. In a mouse model of colitis, mTORC1 activation and necroptosis regulate Paneth and Paneth-like cell secretion. Furthermore, the colitogenic environment triggers PC metaplasia in the distal region of the large intestine to simulate cell proliferation.Highlights:IFN-γ stimulates proliferation,β-catenin independent.IFN-γ enhances mitochondrial activity and proliferationIFN-γ regulates PC biogenesis.mTORC1-dependent necroptosis mediates secretion in Paneth and Paneth-like cells.

A series of 2-phenylamino-3-acyl-1,4-naphtoquinones were evaluated regarding their in vitro antiproliferative activities using DU-145, MCF-7 and T24 cancer cells. Such activities were discussed in terms of molecular descriptors like half-wave potentials, hydrophobicity and molar refractivity. Compounds 4 and 11 display the highest antiproliferative activity against the three cancer cells, therefore, they were subject to further studies. The in silico prediction of drug likeness, using pkCSM and SwissADME explorer online, shows that compound 11 is a suitable lead molecule to be developed. Furthermore, the expression of some key genes was studied in DU-145 cancer cells. They include genes involved in apoptosis (Bcl-2), tumor metabolism regulation (mTOR), redox homeostasis (GSR), cell cycle regulation (CDC25A), cell cycle progression (TP53), epigenetic (HDAC4), cell-cell communication (CCN2) and inflammatory pathways (TNF). Compound 11 displays an interesting profile because among these genes, mTOR was significantly less expressed as compared to control conditions. Molecular docking show that compound 11 has good affinity with mTOR, unraveling a potential inhibitory effect on this protein. Due to the key role of mTOR on tumor metabolism, we suggest that impaired DU-145 cells proliferation by compound 11 is caused by a reduced mTOR expression (less mTOR protein) and inhibitory activity on mTOR protein.

We propose in this work a new method for estimating the main mode of multivariate distributions, with application to eye-tracking calibration. When performing eye-tracking experiments with poorly cooperative subjects, such as infants or monkeys, the calibration data generally suffer from high contamination. Outliers are typically organized in clusters, corresponding to fixations in the time intervals when subjects were not looking at the calibration points. In this type of multimodal distributions, most central tendency measures fail at estimating the principal fixation coordinates (the first mode), resulting in errors and inaccuracies when mapping the gaze to the screen coordinates. Here, we developed a new algorithm to identify the first mode of multivariate distributions, named BRIL, which relies on recursive depth-based filtering. This novel approach was tested on artificial mixtures of Gaussian and Uniform distributions, and compared to existing methods (conventional depth medians, robust estimators of location and scatter, and clustering-based approaches). We obtained outstanding performances, even for distributions containing very high proportions of outliers, both grouped in clusters and randomly distributed. Finally, we demonstrate the strength of our method in a real-world scenario using experimental data from eye-tracking calibrations with Capuchin monkeys, especially for highly contaminated distributions where other algorithms typically lack accuracy.

Raw data for the paper "Differentiation of white matter histopathology using b-tensor encoding and machine learning" by Ricardo Rios-Carrillo, Alonso Ramírez-Manzanares, Hiram Luna-Munguía, Mirelta Regalado, and Luis Concha. DOI: https://doi.org/10.1371/journal.pone.0282549

Photophysical, photovoltaic, and charge transport properties of fused core-modified expanded porphyrins containing two pyrroles, one dithienothiophene (DTT) unit, and 1–4 thiophenes (1–4) were inspected by using density functional theory (DFT) and time-dependent DFT. Compounds 1–3 have been investigated experimentally before, but 4 is a theoretical proposal whose photophysical features match those extrapolated from 1 to 3. They exhibit absorption in the range of 700–970 nm for their Q bands and 500–645 nm for their Soret bands. The rise of thiophene rings placed in front of the DTT unit in the expanded porphyrin ring causes a bathochromic shift of the longest absorption wavelength, leading to near-infrared absorptions, which represent 49% of the solar energy. All the systems show a thermodynamically favorable process for the electron injection from the dye to TiO2 and adsorption on a finite TiO2 model. The electron regeneration of the dye is only thermodynamically feasible for the smallest expanded porphyrins 1 and 2 when I−/I3− electrolyte is used. The charge transport study shows that for voltages lower than 0.4 V, junctions featuring pentaphyrin 1 and octaphyrin 4 are more conductive than those containing hexaphyrin 2 or heptaphyrin 3. The results showed that the four fused core-modified expanded porphyrins investigated are potential dyes for applications in dye-sensitized solar cells, mainly pentaphyrin 1 and hexaphyrin 2. Moreover, increasing the number of thiophene rings in the macrocycle proved fruitful in favoring absorption in the near-infrared region, which is highly desired for dye-sensitized solar cells.

Summary Blood coagulation is a vital process for humans and other species. Following an injury to a blood vessel, a cascade of molecular signals is transmitted, inhibiting and activating more than a dozen coagulation factors and resulting in the formation of a fibrin clot that ceases the bleeding. In this process, antithrombin (AT), encoded by the SERPINC1 gene is a key player regulating the clotting activity and ensuring that it stops at the right time. In this sense, mutations to this factor often result in thrombosis—the excessive coagulation that leads to the potentially fatal formation of blood clots that obstruct veins. Although this process is well known, it is still unclear why even single residue substitutions to AT lead to drastically different phenotypes. In this study, to understand the effect of mutations throughout the AT structure, we created a detailed network map of this protein, where each node is an amino acid, and two amino acids are connected if they are in close proximity in the three-dimensional structure. With this simple and intuitive representation and a machine-learning framework trained using genetic information from more than 130 patients, we found that different types of thrombosis have emerging patterns that are readily identifiable. Together, these results demonstrate how clinical features, genetic data and in silico analysis are converging to enhance the diagnosis and treatment of coagulation disorders. Supplementary information Supplementary data are available at Bioinformatics Advances online.

In this work, we explore, using high-level calculations, the ability of BH

Here, we introduce a hybrid method, named Kick-Fukui, to explore the potential energy surface (PES) of clusters and molecules using the Coulombic integral between the Fukui functions in the first screening of the best individuals. In the process, small stable molecules or clusters whose combination has the stoichiometry of the explored species are used as assembly units. First, a small set of candidates has been selected from a large and stochastically generated (Kick) population according to the maximum value of the Coulombic integral between the Fukui functions of both fragments. Subsequently, these few candidates are optimized using a gradient method and density functional theory (DFT) calculations. The performance of the program has been evaluated to explore the PES of various systems, including atomic and molecular clusters. In most cases studied, the global minimum (GM) has been identified with a low computational cost. The strategy does not allow to identify the GM of some silicon clusters; however, it predicts local minima very close in energy to the GM that could be used as the initial population of evolutionary algorithms.

Mucosal innate immunity functions as the first line of defense against invading pathogens. Members of the IL-1 family are key cytokines upregulated in the inflamed mucosa. Inflammatory cytokines are regulated by limiting their function and availability through their activation and secretion mechanisms. IL-1 cytokines secretion is affected by the lack of a signal peptide on their sequence, which prevents them from accessing the conventional protein secretion pathway; thus, they use unconventional protein secretion pathways. Here we show in mouse macrophages that LPS/ATP stimulation induces cytokine relocalization to the plasma membrane, and conventional secretion blockade using monensin or Brefeldin A triggers no IL-36γ accumulation within the cell. In silico modeling indicates IL-36γ can pass through both the P2X7R and Gasdermin D pores, and both IL-36γ, P2X7R and Gasdermin D mRNA are upregulated in inflammation; further, experimental blockade of these receptors’ limits IL-36γ release. Our results demonstrate that IL-36γ is secreted mainly by an unconventional pathway through membrane pores formed by P2X7R and Gasdermin D.

Hemophilia A is a relatively rare hereditary coagulation disorder caused by a defective F8 gene resulting in a dysfunctional Factor VIII protein (FVIII). This condition impairs the coagulation cascade, and if left untreated, it causes permanent joint damage and poses a risk of fatal intracranial hemorrhage in case of traumatic events. To develop prophylactic therapies with longer half-lives and that do not trigger the development of inhibitory antibodies, it is essential to have a deep understanding of the structure of the FVIII protein. In this study, we explored alternative ways of representing the FVIII protein structure and designed a machine-learning framework to improve the understanding of the relationship between the protein structure and the disease severity. We verified a close agreement between in silico, in vitro and clinical data. Finally, we predicted the severity of all possible mutations in the FVIII structure – including those not yet reported in the medical literature. We identified several hotspots in the FVIII structure where mutations are likely to induce detrimental effects to its activity. The combination of protein structure analysis and machine learning is a powerful approach to predict and understand the effects of mutations on the disease outcome.

It is here reported that the NaBH3- cluster exhibits a Na⋅B one-electron bond, a well-established type of electron-deficient bonding in the literature. The topological analysis of the electron localization function, at the correlated level, reveals that Na- , when approaching the bonding distance, fairly distributes its valence electron pair between two lobes. One of these electrons is used to bond with BH3 , which participates through its boron empty p-orbital. Furthermore, the bonding situation of LiBH3- , KBH3- , MgBH3 , and CaBH3 global minima structures are similar to that of NaBH3- , extending the family of these new one-electron bond systems with biradicaloid character.

Expanded porphyrins arise as an alternative for potential application as chromophores in dye-sensitized solar cells. (DSSCs). The modification of the core of these compounds provides remarkable changes in the photoelectronic behavior. In the present article, the improvement of its properties for a potential application as UV/vis/NIR chromophores in DSSCs has been studied, when an oxazolone moiety has replaced an imine ring in analogy to the porpholactones first synthesized by Crossley et al. ( J. Chem. Soc., Chem. Commun. 1984, 920-922). These expanded porpholactones present a noticeable red shift as well as an increase in the intensity of the Q-bands regarding the parent compounds. The photophysical properties of Sapphyrin have been explored through DFT calculations and vibrationally resolved absorption spectra simulations. Energetic parameters showed favorable electron injection from the chromophore to the TiO2 semiconductor. In addition, aromaticity was analyzed and rationalized using magnetic and delocalization criteria. Results showed qualitatively similar trends between aromaticity descriptors and Q bands giving a great opportunity to the use this property in the rational design of chromophores. Finally, the nonequilibrium Green's function formalism shows the ability of expanded porpholactones in electron transport.

Cellular interactions within the bone marrow microenvironment modulate the properties of subsets of leukemic cells leading to the development of drug-resistant phenotypes. The intercellular transfer of proteins and organelles contributes to this process but the set of transferred proteins and their effects in the receiving cells remain unclear. This study aimed to detect the intercellular protein transfer from mouse bone marrow stromal cells (OP9 cell line) to human T-lymphoblasts (CCRF-CEM cell line) using nanoLC-MS/MS-based shotgun proteomics in a 3D co-culture system. After 24 h of co-culture, 1513 and 67 proteins from human and mouse origin, respectively, were identified in CCRF-CEM cells. The presence of mouse proteins in the human cell line, detected by analyzing the differences in amino acid sequences of orthologous peptides, was interpreted as the result of intercellular transfer. The transferred proteins might have contributed to the observed resistance to vincristine, methotrexate, and hydrogen peroxide in the co-cultured leukemic cells. Our results suggest that shotgun proteomic analyses of co-cultured cells from different species could be a simple option to get a preliminary survey of the proteins exchanged among interacting cells.

Here, we analyze the possibility of predicting local and global current densities in a series of bicyclic hydrocarbons with 4n and 4n + 2 π-electrons from the nucleus-independent chemical shifts (NICS) computations. Our results show that although it is possible to establish the net current flows through C–C bonds, it is impossible to predict all the local and global weak current density flows. Thus, for polycyclic systems, it is essential to analyze magnetically induced current densities in conjunction with NICS measurements, or with induced magnetic fields, to have an adequate representation of the molecules’ magnetic behavior and their relationship with the aromaticity phenomenon.

The Internet of Things (IoT) has developed infrastructures and applications that generate large amounts of data. These data are usually yielded as streams, characterized for being continuous and infinite, and presenting the peculiarity of modifying their behavior over time. Due to the large capacity of storage, data processing, and provisioning of resources, such data are generally processed/analyzed in Cloud Computing environments. Although those environments provide IoT infrastructure with adequate scalability and resource-centric features, the distance between devices and the cloud can impose limitations to achieve low latency in data traffic. In order to maintain scalability, achieve low latency, and reduce data traffic between the IoT devices and the Cloud, the Fog Computing was proposed, providing resource availability at the edge of the network. Although Fog Computing establishes resource availability at the edge of the network, the technologies/techniques currently used for IoT data processing and analysis may not be sufficient to support the continuous and unlimited streams that IoT platforms and applications produce. In addition, data stream applications at Fog must be supported by the computationally limited devices. Therefore, aiming at taking advantage of Fog Computing and resolve the gap of the data stream in IoT environments, this work presents a new platform called FoT-Stream designed to process and analyze, in real-time, data stream from the Internet of Things in Fog. The main advantage of using our approach is the possibility of reducing the amount of data transmitted on the network infrastructure, which allows, as a consequence, to perform an online data modeling, by detecting changes in data behavior, and a reduction of the Internet usage. Our results in a real-world scenario emphasize FoT-Stream considerably reduces the latency and amount of data traffic in IoT environments without affecting the system throughput.