Advanced Glycation End Products Upregulate CD40 in Human Retinal Endothelial and Müller Cells: Relevance to Diabetic Retinopathy.

CD40 induces pro-inflammatory responses in endothelial and Müller cells and is required for the development of diabetic retinopathy (DR). CD40 is upregulated in these cells in patients with DR. CD40 upregulation is a central feature of CD40-driven inflammatory disorders. What drives CD40 upregulation in the diabetic retina remains unknown. We examined the role of advanced glycation end products (AGEs) in CD40 upregulation in endothelial cells and Müller cells. Human endothelial cells and Müller cells were incubated with unmodified or methylglyoxal (MGO)-modified fibronectin. CD40 expression was assessed by flow cytometry. The expression of ICAM-1 and CCL2 was examined by flow cytometry or ELISA after stimulation with CD154 (CD40 ligand). The expression of carboxymethyl lysine (CML), fibronectin, and laminin as well as CD40 in endothelial and Müller cells from patients with DR was examined by confocal microscopy. Fibronectin modified by MGO upregulated CD40 in endothelial and Müller cells. CD40 upregulation was functionally relevant. MGO-modified fibronectin enhanced CD154-driven upregulation of ICAM-1 and CCL2 in endothelial and Müller cells. Increased CD40 expression in endothelial and Müller cells from patients with DR was associated with increased CML expression in fibronectin and laminin. These findings identify AGEs as inducers of CD40 upregulation in endothelial and Müller cells and enhancers of CD40-dependent pro-inflammatory responses. CD40 upregulation in these cells is associated with higher CML expression in fibronectin and laminin in patients with DR. This study revealed that CD40 and AGEs, two important drivers of DR, are interconnected.

Acute venous thromboembolism in patients with brain cancer: clinical course.

Background: Patients with brain cancer have been excluded or were underrepresented in studies on the treatment of venous thromboembolism (VTE), mainly due to the fear of intracranial hemorrhage (ICH). Objectives: The aim of this study was to provide data on the risk of ICH, recurrent VTE, and major bleeding in patients with active brain cancer. Methods: This was a multicenter, international cohort study at participating sites of the Registro Informatizado Enfermedad Tromboembólica Registry. Patients included in this study were classified as having known active brain cancer, active nonbrain cancer, or without active cancer. ICH at 3 months was the primary study outcome. Results: Overall, 98,377 patients with VTE were included: 616 with active brain cancer, 16,807 with active nonbrain cancer, and 80,954 without active cancer. At 3 months follow-up, ICH occurred in 2.8%, 0.3%, and 0.2% of the patients, respectively, and was fatal in 1.3%, 0.2%, and 0.1%, respectively. Both rates of major bleeding (3.7% vs 3.2% vs 1.5%, respectively) and recurrent VTE (3.9% vs 3.4% vs 1.1%, respectively) were higher in patients with brain or nonbrain cancer than in patients without cancer. Glioblastomas were associated with a numerically higher risk of ICH, fatal ICH, and recurrent VTE than other brain tumors. Conclusion: In patients with VTE, active brain cancer was associated with a higher risk of ICH or fatal ICH than nonbrain or no active cancer. Further studies are needed to assess the value of different treatment approaches in patients with brain cancer and VTE.

ReinforSec: An Automatic Generator of Synthetic Malware Samples and Denial-of-Service Attacks through Reinforcement Learning.

In recent years, cybersecurity has been strengthened through the adoption of processes, mechanisms and rapid sources of indicators of compromise in critical areas. Among the most latent challenges are the detection, classification and eradication of malware and Denial of Service Cyber-Attacks (DoS). The literature has presented different ways to obtain and evaluate malware- and DoS-cyber-attack-related instances, either from a technical point of view or by offering ready-to-use datasets. However, acquiring fresh, up-to-date samples requires an arduous process of exploration, sandbox configuration and mass storage, which may ultimately result in an unbalanced or under-represented set. Synthetic sample generation has shown that the cost associated with setting up controlled environments and time spent on sample evaluation can be reduced. Nevertheless, the process is performed when the observations already belong to a characterized set, totally detached from a real environment. In order to solve the aforementioned, this work proposes a methodology for the generation of synthetic samples of malicious Portable Executable binaries and DoS cyber-attacks. The task is performed via a Reinforcement Learning engine, which learns from a baseline of different malware families and DoS cyber-attack network properties, resulting in new, mutated and highly functional samples. Experimental results demonstrate the high adaptability of the outputs as new input datasets for different Machine Learning algorithms.

Climatic niche breadths of the Atlantic Forest snakes do not increase with increasing latitude.

The climatic niche is a central concept for understanding species distribution, with current and past climate interpreted as strong drivers of present and historical-geographical ranges. Our aim is to understand whether Atlantic Forest snakes follow the general geographical pattern of increasing species climatic niche breadths with increasing latitude. We also tested if there is a tradeoff between temperature and precipitation niche breadths of species in order to understand if species with larger breadths of one niche dimension have stronger dispersal constraints by the other due to narrower niche breadths. Niche breadths were calculated by the subtraction of maximal and minimal values of temperature and precipitation across species ranges. We implemented Phylogenetic Generalized Least Squares to measure the relationship between temperature and precipitation niche breadths and latitude. We also tested phylogenetic signals by Lambda statistics to analyze the degree of phylogenetic niche conservatism to both niche dimensions. Temperature niche breadths were not related to latitude. Precipitation niche breadths decreased with increasing latitude and presented a high phylogenetic signal, that is, significant phylogenetic niche conservatism. We rejected the tradeoff hypotheses of temperature and precipitation niche breadths. Our results also indicate that precipitation should be an important ecological constraint affecting the geographical distribution of snake lineages across the South American Atlantic Forest. We then provide a general view of how phylogenetic niche conservatism could impact the patterns of latitudinal variation of climatic niches across this biodiversity hotspot.

Disruption of retinal inflammation and the development of diabetic retinopathy in mice by a CD40-derived peptide or mutation of CD40 in Müller cells.

AIMS/HYPOTHESIS: CD40 expressed in Müller cells is a central driver of diabetic retinopathy. CD40 causes phospholipase Cγ1 (PLCγ1)-dependent ATP release in Müller cells followed by purinergic receptor (P2X7)-dependent production of proinflammatory cytokines in myeloid cells. In the diabetic retina, CD40 and P2X7 upregulate a broad range of inflammatory molecules that promote development of diabetic retinopathy. The molecular event downstream of CD40 that activates the PLCγ1-ATP-P2X7-proinflammatory cytokine cascade and promotes development of diabetic retinopathy is unknown. We hypothesise that disruption of the CD40-driven molecular events that trigger this cascade prevents/treats diabetic retinopathy in mice. METHODS: B6 and transgenic mice with Müller cell-restricted expression of wild-type (WT) CD40 or CD40 with mutations in TNF receptor-associated factor (TRAF) binding sites were made diabetic using streptozotocin. Leucostasis was assessed using FITC-conjugated concanavalin A. Histopathology was examined in the retinal vasculature. Expression of inflammatory molecules and phospho-Tyr783 PLCγ1 (p-PLCγ1) were assessed using real-time PCR, immunoblot and/or immunohistochemistry. Release of ATP and cytokines were measured by ATP bioluminescence and ELISA, respectively. RESULTS: Human Müller cells with CD40 ΔT2,3 (lacks TRAF2,3 binding sites) were unable to phosphorylate PLCγ1 and release ATP in response to CD40 ligation, and could not induce TNF-α/IL-1ß secretion in bystander myeloid cells. CD40-TRAF signalling acted via Src to induce PLCγ1 phosphorylation. Diabetic mice in which WT CD40 in Müller cells was replaced by CD40 ΔT2,3 failed to exhibit phosphorylation of PLCγ1 in these cells and upregulate P2X7 and TNF-α in microglia/macrophages. P2x7 (also known as P2rx7), Tnf-α (also known as Tnf), Il-1ß (also known as Il1b), Nos2, Icam-1 (also known as Icam1) and Ccl2 mRNA were not increased in these mice and the mice did not develop retinal leucostasis and capillary degeneration. Diabetic B6 mice treated intravitreally with a cell-permeable peptide that disrupts CD40-TRAF2,3 signalling did not exhibit either upregulation of P2X7 and inflammatory molecules in the retina or leucostasis. CONCLUSIONS/INTERPRETATION: CD40-TRAF2,3 signalling activated the CD40-PLCγ1-ATP-P2X7-proinflammatory cytokine pathway. Src functioned as a link between CD40-TRAF2,3 and PLCγ1. Replacing WT CD40 with CD40 ΔT2,3 impaired activation of PLCγ1 in Müller cells, upregulation of P2X7 in microglia/macrophages, upregulation of a broad range of inflammatory molecules in the diabetic retina and the development of diabetic retinopathy. Administration of a peptide that disrupts CD40-TRAF2,3 signalling reduced retinal expression of inflammatory molecules and reduced leucostasis in diabetic mice, supporting the therapeutic potential of pharmacological inhibition of CD40-TRAF2,3 in diabetic retinopathy.

FASSVid: Fast and Accurate Semantic Segmentation for Video Sequences.

Most of the methods for real-time semantic segmentation do not take into account temporal information when working with video sequences. This is counter-intuitive in real-world scenarios where the main application of such methods is, precisely, being able to process frame sequences as quickly and accurately as possible. In this paper, we address this problem by exploiting the temporal information provided by previous frames of the video stream. Our method leverages a previous input frame as well as the previous output of the network to enhance the prediction accuracy of the current input frame. We develop a module that obtains feature maps rich in change information. Additionally, we incorporate the previous output of the network into all the decoder stages as a way of increasing the attention given to relevant features. Finally, to properly train and evaluate our methods, we introduce CityscapesVid, a dataset specifically designed to benchmark semantic video segmentation networks. Our proposed network, entitled FASSVid improves the mIoU accuracy performance over a standard non-sequential baseline model. Moreover, FASSVid obtains state-of-the-art inference speed and competitive mIoU results compared to other state-of-the-art lightweight networks, with significantly lower number of computations. Specifically, we obtain 71% of mIoU in our CityscapesVid dataset, running at 114.9 FPS on a single NVIDIA GTX 1080Ti and 31 FPS on the NVIDIA Jetson Nano embedded board with images of size 1024×2048 and 512×1024, respectively.

Global structural stability and the role of cooperation in mutualistic systems.

Dynamical systems on graphs allow to describe multiple phenomena from different areas of Science. In particular, many complex systems in Ecology are studied by this approach. In this paper we analize the mathematical framework for the study of the structural stability of each stationary point, feasible or not, introducing a generalization for this concept, defined as Global Structural Stability. This approach would fit with the proper mathematical concept of structural stability, in which we find a full description of the complex dynamics on the phase space due to nonlinear dynamics. This fact can be analyzed as an informational field grounded in a global attractor whose structure can be completely characterized. These attractors are stable under perturbation and suppose the minimal structurally stable sets. We also study in detail, mathematically and computationally, the zones characterizing different levels of biodiversity in bipartite graphs describing mutualistic antagonistic systems of population dynamics. In particular, we investigate the dependence of the region of maximal biodiversity of a system on its connectivity matrix. On the other hand, as the network topology does not completely determine the robustness of the dynamics of a complex network, we study the correlation between structural stability and several graph measures. A systematic study on synthetic and biological graphs is presented, including 10 mutualistic networks of plants and seed-dispersal and 1000 random synthetic networks. We compare the role of centrality measures and modularity, concluding the importance of just cooperation strength among nodes when describing areas of maximal biodiversity. Indeed, we show that cooperation parameters are the central role for biodiversity while other measures act as secondary supporting functions.

Climatic niche breadths of the Atlantic Forest snakes do not increase with increasing latitude

The climatic niche is a central concept for understanding species distribution, with current and past climate interpreted as strong drivers of present and historical-geographical ranges. Our aim is to understand whether Atlantic Forest snakes follow the general geographical pattern of increasing species climatic niche breadths with increasing latitude. We also tested if there is a tradeoff between temperature and precipitation niche breadths of species in order to understand if species with larger breadths of one niche dimension have stronger dispersal constraints by the other due to narrower niche breadths. Niche breadths were calculated by the subtraction of maximal and minimal values of temperature and precipitation across species ranges. We implemented Phylogenetic Generalized Least Squares to measure the relationship between temperature and precipitation niche breadths and latitude. We also tested phylogenetic signals by Lambda statistics to analyze the degree of phylogenetic niche conservatism to both niche dimensions. Temperature niche breadths were not related to latitude. Precipitation niche breadths decreased with increasing latitude and presented a high phylogenetic signal, that is, significant phylogenetic niche conservatism. We rejected the tradeoff hypotheses of temperature and precipitation niche breadths. Our results also indicate that precipitation should be an important ecological constraint affecting the geographical distribution of snake lineages across the South American Atlantic Forest. We then provide a general view of how phylogenetic niche conservatism could impact the patterns of latitudinal variation of climatic niches across this biodiversity hotspot.

CD40 Expressed in Endothelial Cells Promotes Upregulation of ICAM-1 But Not Pro-Inflammatory Cytokines, NOS2 and P2X7 in the Diabetic Retina.

Purpose: CD40 is an upstream inducer of inflammation in the diabetic retina. CD40 is upregulated in retinal endothelial cells in diabetes. The purpose of this study was to determine whether expression of CD40 in endothelial cells is sufficient to promote inflammatory responses in the retina of diabetic mice. Methods: Transgenic mice with CD40 expression restricted to endothelial cells (Trg-CD40 EC), transgenic control mice (Trg-Ctr), B6, and CD40-/- mice were made diabetic using streptozotocin. Leukostasis was assessed using FITC-conjugated ConA. Pro-inflammatory molecule expression was examined by real-time PCR, immunohistochemistry, ELISA, or flow cytometry. Release of ATP was assessed by ATP bioluminescence. Results: Diabetic B6 and Trg-CD40 EC mice exhibited increased retinal mRNA levels of ICAM-1, higher ICAM-1 expression in endothelial cells, and increased leukostasis. These responses were not detected in diabetic mice that lacked CD40 (CD40-/- and Trg-Ctr). Diabetic B6 but not Trg-CD40 EC mice upregulated TNF-α, IL-1ß, and NOS2 mRNA levels. CD40 stimulation in retinal endothelial cells upregulated ICAM-1 but not TNF-α, IL-1ß, or NOS2. CD40 ligation did not trigger ATP release by retinal endothelial cells or pro-inflammatory cytokine production in bystander myeloid cells. In contrast to diabetic B6 mice, diabetic Trg-CD40 EC mice did not upregulate P2X7 mRNA levels in the retina. Conclusions: Endothelial cell CD40 promotes ICAM-1 upregulation and leukostasis. In contrast, endothelial cell CD40 does not lead to pro-inflammatory cytokine and NOS2 upregulation likely because it does not activate purinergic-mediated pro-inflammatory molecule expression by myeloid cells or induce expression of these pro-inflammatory molecules in endothelial cells.

A Dense Neural Network Approach for Detecting Clone ID Attacks on the RPL Protocol of the IoT.

At present, new data sharing technologies, such as those used in the Internet of Things (IoT) paradigm, are being extensively adopted. For this reason, intelligent security controls have become imperative. According to good practices and security information standards, particularly those regarding security in depth, several defensive layers are required to protect information assets. Within the context of IoT cyber-attacks, it is fundamental to continuously adapt new detection mechanisms for growing IoT threats, specifically for those becoming more sophisticated within mesh networks, such as identity theft and cloning. Therefore, current applications, such as Intrusion Detection Systems (IDS), Intrusion Prevention Systems (IPS), and Security Information and Event Management Systems (SIEM), are becoming inadequate for accurately handling novel security incidents, due to their signature-based detection procedures using the matching and flagging of anomalous patterns. This project focuses on a seldom-investigated identity attack-the Clone ID attack-directed at the Routing Protocol for Low Power and Lossy Networks (RPL), the underlying technology for most IoT devices. Hence, a robust Artificial Intelligence-based protection framework is proposed, in order to tackle major identity impersonation attacks, which classical applications are prone to misidentifying. On this basis, unsupervised pre-training techniques are employed to select key characteristics from RPL network samples. Then, a Dense Neural Network (DNN) is trained to maximize deep feature engineering, with the aim of improving classification results to protect against malicious counterfeiting attempts.

A cell-penetrating CD40-TRAF2,3 blocking peptide diminishes inflammation and neuronal loss after ischemia/reperfusion.

While the administration of anti-CD154 mAbs in mice validated the CD40-CD154 pathway as a target against inflammatory disorders, this approach caused thromboembolism in humans (unrelated to CD40 inhibition) and is expected to predispose to opportunistic infections. There is a need for alternative approaches to inhibit CD40 that avoid these complications. CD40 signals through TRAF2,3 and TRAF6-binding sites. Given that CD40-TRAF6 is the pathway that stimulates responses key for cell-mediated immunity against opportunistic pathogens, we examined the effects of pharmacologic inhibition of CD40-TRAF2,3 signaling. We used a model of ischemia/reperfusion (I/R)-induced retinopathy, a CD40-driven inflammatory disorder. Intravitreal administration of a cell-penetrating CD40-TRAF2,3 blocking peptide impaired ICAM-1 upregulation in retinal endothelial cells and CXCL1 upregulation in endothelial and Müller cells. The peptide reduced leukocyte infiltration, upregulation of NOS2/COX-2/TNF-α/IL-1ß, and ameliorated neuronal loss, effects that mimic those observed after I/R in Cd40-/- mice. While a cell-penetrating CD40-TRAF6 blocking peptide also diminished I/R-induced inflammation, this peptide (but not the CD40-TRAF2,3 blocking peptide) impaired control of the opportunistic pathogen Toxoplasma gondii in the retina. Thus, inhibition of the CD40-TRAF2,3 pathway is a novel and potent approach to reduce CD40-induced inflammation, while likely diminishing the risk of opportunistic infections that would otherwise accompany CD40 inhibition.

Predicting the risk for major bleeding in elderly patients with venous thromboembolism using the Charlson index. Findings from the RIETE.

Old patients receiving anticoagulant therapy for venous thromboembolism (VTE) are at an increased risk for bleeding. We used data from the RIETE registry to assess the prognostic ability of the Comorbidity Charlson Index (CCI) to predict the risk for major bleeding in patients aged > 75 years receiving anticoagulation for VTE beyond the third month. We calculated the area under the receiver-operating characteristic curve (AUC), the category-based net reclassification index (NRI) and the net benefit (NB). We included 4303 patients with a median follow-up of 706 days (interquartile range [IQR] 462-1101). Of these, 147 (3%) developed major bleeding (27 died of bleeding). The AUC was 0.569 (95% CI 0.524-0.614). Patients with CCI ≤ 4 points were at a lower risk for adverse outcomes than those with CCI > 10 (major bleeding 0.81 (95% CI 0.53-1.19) vs. 2.21 (95% CI 1.18-3.79) per 100 patient-years; p < 0.05; all-cause death 1.9 (95% CI 1.45-2.44) vs. 15.67 (95% CI 12.63-19.22) per 100 patient-years; p < 0.05). A cut-off point of 4 points (CCI4) had a sensitivity of 82% (95% CI 75-89) and a specificity of 30% (95% CI 29-31) to predict major bleeding beyond the third month. CCI4 reclassification improved the NB of the RIETE bleeding score to predict bleeding beyond the third month (CCI4 NB 1.78% vs. RIETE NB 0.44%). Although the AUC of the CCI to predict major bleeding was modest, it could become an additional help to select patients aged > 75 years that obtain more benefit of extended anticoagulation, due to a lower risk for bleeding and better survival.

Clinical Characteristics and Outcomes of Women Presenting with Venous Thromboembolism during Pregnancy and Postpartum Period: Findings from the RIETE Registry.

Although venous thromboembolism (VTE) is a leading cause of maternal mortality, there is a paucity of real-world clinical data on clinical presentation and management of VTE during pregnancy and postpartum period. Using data from the international RIETE (Registro Informatizado Enfermedad Trombo Embólica) registry, pregnant and postpartum women with VTE were identified. Baseline characteristics, risk factors, therapies, and outcomes were compared. From March 2001 to July 2019, 596 pregnant and 523 postpartum women had symptomatic, objectively confirmed VTE. Pregnant or postpartum women were less likely to have another risk factor for VTE (i.e., immobility, cancer, recent travel) than nonpregnant women aged < 50 years. The prevalence of thrombophilia was higher among pregnant and postpartum women compared with nonpregnant women (53.2% vs. 46%). Pulmonary embolism (PE) was less commonly diagnosed in pregnant versus postpartum women (27% vs. 42%). Pregnant women with PE were commonly treated with low molecular weight heparin (73% vs. 29%), and received more inferior vena cava filters (6.0% vs. 4.2%) compared with postpartum women. By 90 days, one pregnant and one postpartum woman died after PE, and one died after a deep venous thrombosis. The incidence of recurrent VTE was low. In this largest cohort of pregnant and postpartum women with confirmed VTE, we found that pregnant and postpartum women with VTE were unlikely to present with other risk factors for VTE. Adverse outcomes in our study were uncommon.

A network approach to analyze neuronal lineage and layer innervation in the Drosophila optic lobes.

The optic lobes of the fruit fly Drosophila melanogaster form a highly wired neural network composed of roughly 130.000 neurons of more than 80 different types. How neuronal diversity arises from very few cell progenitors is a central question in developmental neurobiology. We use the optic lobe of the fruit fly as a paradigm to understand how neuroblasts, the neural stem cells, generate multiple neuron types. Although the development of the fly brain has been the subject of extensive research, very little is known about the lineage relationships of the cell types forming the adult optic lobes. Here we perform a large-scale lineage bioinformatics analysis using the graph theory. We generated a large collection of cell clones that genetically label the progeny of neuroblasts and built a database to draw graphs showing the lineage relationships between cell types. By establishing biological criteria that measures the strength of the neuronal relationships and applying community detection tools we have identified eight clusters of neurons. Each cluster contains different cell types that we pose are the product of eight distinct classes of neuroblasts. Three of these clusters match the available lineage data, supporting the predictive value of the analysis. Finally, we show that the neuronal progeny of a neuroblast do not have preferential innervation patterns, but instead become part of different layers and neuropils. Here we establish a new methodology that helps understanding the logic of Drosophila brain development and can be applied to the more complex vertebrate brains.

Toxoplasma gondii induces prolonged host epidermal growth factor receptor signalling to prevent parasite elimination by autophagy: Perspectives for in vivo control of the parasite.

Toxoplasma gondii causes retinitis and encephalitis. Avoiding targeting by autophagosomes is key for its survival because T. gondii cannot withstand lysosomal degradation. During invasion of host cells, T. gondii triggers epidermal growth factor receptor (EGFR) signalling enabling the parasite to avoid initial autophagic targeting. However, autophagy is a constitutive process indicating that the parasite may also use a strategy operative beyond invasion to maintain blockade of autophagic targeting. Finding that such a strategy exists would be important because it could lead to inhibition of host cell signalling as a novel approach to kill the parasite in previously infected cells and treat toxoplasmosis. We report that T. gondii induced prolonged EGFR autophosphorylation. This effect was mediated by PKCα/PKCß âž” Src because T. gondii caused prolonged activation of these molecules and their knockdown or incubation with inhibitors of PKCα/PKCß or Src after host cell invasion impaired sustained EGFR autophosphorylation. Addition of EGFR tyrosine kinase inhibitor (TKI) to previously infected cells led to parasite entrapment by LC3 and LAMP-1 and pathogen killing dependent on the autophagy proteins ULK1 and Beclin 1 as well as lysosomal enzymes. Administration of gefitinib (EGFR TKI) to mice with ocular and cerebral toxoplasmosis resulted in disease control that was dependent on Beclin 1. Thus, T. gondii promotes its survival through sustained EGFR signalling driven by PKCα/ß âž” Src, and inhibition of EGFR controls pre-established toxoplasmosis.

Vehicle Counting in Video Sequences: An Incremental Subspace Learning Approach.

The counting of vehicles plays an important role in measuring the behavior patterns of traffic flow in cities, as streets and avenues can get crowded easily. To address this problem, some Intelligent Transport Systems (ITSs) have been implemented in order to count vehicles with already established video surveillance infrastructure. With this in mind, in this paper, we present an on-line learning methodology for counting vehicles in video sequences based on Incremental Principal Component Analysis (Incremental PCA). This incremental learning method allows us to identify the maximum variability (i.e., motion detection) between a previous block of frames and the actual one by using only the first projected eigenvector. Once the projected image is obtained, we apply dynamic thresholding to perform image binarization. Then, a series of post-processing steps are applied to enhance the binary image containing the objects in motion. Finally, we count the number of vehicles by implementing a virtual detection line in each of the road lanes. These lines determine the instants where the vehicles pass completely through them. Results show that our proposed methodology is able to count vehicles with 96.6% accuracy at 26 frames per second on average-dealing with both camera jitter and sudden illumination changes caused by the environment and the camera auto exposure.

CD40 in Endothelial Cells Restricts Neural Tissue Invasion by Toxoplasma gondii.

Little is known about whether pathogen invasion of neural tissue is affected by immune-based mechanisms in endothelial cells. We examined the effects of endothelial cell CD40 on Toxoplasma gondii invasion of the retina and brain, organs seeded hematogenously. T. gondii circulates in the bloodstream within infected leukocytes (including monocytes and dendritic cells) and as extracellular tachyzoites. After T. gondii infection, mice that expressed CD40 restricted to endothelial cells exhibited diminished parasite loads and histopathology in the retina and brain. These mice also had lower parasite loads in the retina and brain after intravenous (i.v.) injection of infected monocytes or dendritic cells. The protective effect of endothelial cell CD40 was not explained by changes in cellular or humoral immunity, reduced transmigration of leukocytes into neural tissue, or reduced invasion by extracellular parasites. Circulating T. gondii-infected leukocytes (dendritic cells used as a model) led to infection of neural endothelial cells. The number of foci of infection in these cells were reduced if endothelial cells expressed CD40. Infected dendritic cells and macrophages expressed membrane-associated inducible Hsp70. Infected leukocytes triggered Hsp70-dependent autophagy in CD40+ endothelial cells and anti-T. gondii activity dependent on ULK1 and beclin 1. Reduced parasite load in the retina and brain not only required CD40 expression in endothelial cells but was also dependent on beclin 1 and the expression of inducible Hsp70 in dendritic cells. These studies suggest that during endothelial cell-leukocyte interaction, CD40 restricts T. gondii invasion of neural tissue through a mechanism that appears mediated by endothelial cell anti-parasitic activity stimulated by Hsp70.

Area and distance from mainland affect in different ways richness and phylogenetic diversity of snakes in Atlantic Forest coastal islands.

AIM: The Theory of Island Biogeography posits that ecological and evolutionary processes regulate species richness of isolated areas. We assessed the influences of an island area and distance from the mainland on species richness, phylogenetic diversity, and phylogenetic composition of snakes on coastal islands. LOCATION: Coastal islands of the megadiverse Atlantic Forest in southeastern Brazil. METHODS: We compiled the species composition of 17 coastal islands in southeastern Brazil. Species richness and phylogenetic diversity were calculated for each island. Phylogenetic composition was measured using principal coordinates of phylogenetic structure. We then employed generalized linear models to test the influence of area and distance from the mainland on the diversity metrics. RESULTS: We found a prominent influence of area on species richness, whereas phylogenetic diversity was more affected by distance from the mainland. Snake clades were distinctly associated with area and distance. The Boidae family was associated with nearer and larger islands, whereas Elapidae was broadly distributed. Distance from the mainland was associated with the distribution of Dipsadidae, whereas Colubridae was influenced by both the area and distance. The Viperidae family attained higher values of phylogenetic diversity in smaller and more remote islands. MAIN CONCLUSIONS: This island system conserved a considerable piece of snake richness from southeastern Brazil, including island endemic species. Area and distance from the mainland were important drivers of snake diversity in the Atlantic Forest coastal islands. However, these predictors affected the different components of diversity in different ways. Phylogenetic composition analysis enables us to understand how basal nodes contributed to high levels of phylogenetic diversity on smaller and farther islands regardless of the decrease in species richness.

Using Twitter Data to Monitor Natural Disaster Social Dynamics: A Recurrent Neural Network Approach with Word Embeddings and Kernel Density Estimation.

In recent years, Online Social Networks (OSNs) have received a great deal of attention for their potential use in the spatial and temporal modeling of events owing to the information that can be extracted from these platforms. Within this context, one of the most latent applications is the monitoring of natural disasters. Vital information posted by OSN users can contribute to relief efforts during and after a catastrophe. Although it is possible to retrieve data from OSNs using embedded geographic information provided by GPS systems, this feature is disabled by default in most cases. An alternative solution is to geoparse specific locations using language models based on Named Entity Recognition (NER) techniques. In this work, a sensor that uses Twitter is proposed to monitor natural disasters. The approach is intended to sense data by detecting toponyms (named places written within the text) in tweets with event-related information, e.g., a collapsed building on a specific avenue or the location at which a person was last seen. The proposed approach is carried out by transforming tokenized tweets into word embeddings: a rich linguistic and contextual vector representation of textual corpora. Pre-labeled word embeddings are employed to train a Recurrent Neural Network variant, known as a Bidirectional Long Short-Term Memory (biLSTM) network, that is capable of dealing with sequential data by analyzing information in both directions of a word (past and future entries). Moreover, a Conditional Random Field (CRF) output layer, which aims to maximize the transition from one NER tag to another, is used to increase the classification accuracy. The resulting labeled words are joined to coherently form a toponym, which is geocoded and scored by a Kernel Density Estimation function. At the end of the process, the scored data are presented graphically to depict areas in which the majority of tweets reporting topics related to a natural disaster are concentrated. A case study on Mexico's 2017 Earthquake is presented, and the data extracted during and after the event are reported.

Epidermal growth factor receptor promotes cerebral and retinal invasion by Toxoplasma gondii.

Little is known about strategies used by pathogens to facilitate CNS invasion. Toxoplasma gondii reaches the CNS by circulating in blood within leukocytes or as extracellular tachyzoites. T. gondii induces EGFR signaling in vitro during invasion of mammalian cells. We examined the effects of endothelial cell EGFR on CNS invasion. Transgenic mice whose endothelial cells expressed a dominant negative (DN) EGFR (inhibits EGFR signaling) exhibited diminished parasite load and histopathology in the brain and retina after T. gondii infection. I.V. administration of infected leukocytes or extracellular tachyzoites led to reduced parasite loads in mice with DN EGFR. This was not explained by enhanced immunity or reduced leukocyte recruitment. Endothelial cell infection is key for CNS invasion. Parasite foci in brain endothelial cells were reduced by DN EGFR. DN EGFR in these cells led to recruitment of the autophagy protein LC3 around T. gondii and spontaneous parasite killing dependent on the autophagy protein ULK1 and lysosomal enzymes. The autophagy inhibitor 3-MA prevented DN EGFR mice from exhibiting reduced CNS invasion. Altogether, EGFR is a novel regulator of T. gondii invasion of neural tissue, enhancing invasion likely by promoting survival of the parasite within endothelial cells.