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The same types of cells can assume diverse states with varying functionalities. Effective cell therapy can be achieved by specifically driving a desirable cell state, which requires the elucidation of key transcription factors (TFs). Here, we integrated epigenomic and transcriptomic data at the systems level to identify TFs that define different CD8+T cell states in an unbiased manner. These TF profiles can be used for cell state programming that aims to maximize the therapeutic potential of T cells. For example, T cells can be programmed to avoid a terminal exhaustion state (TexTerm), a dysfunctional T cell state that is often found in tumors or chronic infections. However, TexTermexhibits high similarity with the beneficial tissue-resident memory T states (TRM) in terms of their locations and transcription profiles. Our bioinformatic analysis predictedZscan20, a novel TF, to be uniquely active in TexTerm. Consistently,Zscan20knock-out thwarted the differentiation of TexTermin vivo, but not that of TRM. Furthermore, perturbation ofZscan20programs T cells into an effector-like state that confers superior tumor and virus control and synergizes with immune checkpoint therapy. We also identifiedJdp2andNfil3as powerful TexTermdrivers. In short, our multiomics-based approach discovered novel TFs that enhance anti-tumor immunity, and enable highly effective cell state programming.One sentence summaryMultiomics atlas enables the systematic identification of cell-state specifying transcription factors for therapeutic cell state programming.

Catabolic responses of lean and fat energy stores are a component of the host response to infection. Cachexia is an extreme catabolic state characterized by unintentional weight loss and muscle loss, that can include fat loss. Whether cachexia plays any role in host defense or is a maladaptive consequence of host-pathogen interactions remains unknown. Traditionally studies have focused on understanding how inflammatory mediators and cells of the innate immune system contribute to the pathogenesis of cachexia and the depletion of energy stores. The cells of the adaptive immune system that regulate infection-induced cachexia remain elusive. In the present study, we examined the role of the adaptive immune response in cachexia pathogenesis using a murine model of the chronic parasitic infectionTrypanosoma brucei, the causative agent of sleeping sickness. We found that the cachectic response occurs in two phases with the first stage occurring early in the infection and involved a loss of body fat mass associated with anorexia, and the second stage occurring later in the infection and involved a sustained loss of fat mass that was accompanied by lean mass wasting. CD4+ T cells were necessary for the development of the sickness-induced anorexic response during stage 1 of the infection, which led to adipose triglyceride lipase dependent lipolysis in adipocytes and the resulting fat wasting. Adipose tissue wasting had no impact on host resistance defenses or survival of infection, both of which were antibody-mediated and independent ofCD4+ T cell responses. Our work reveals a new mechanism for infection induced cachexia involving CD4+ T cell regulation of host feeding behavior and an unexpected decoupling of adaptive immune mediated resistance from the cachectic response during infection.

Reconstructing the Hamiltonian of a quantum system is an essential task for characterizing and certifying quantum processors and simulators. Existing techniques either rely on projective measurements of the system before and after coherent time evolution and do not explicitly reconstruct the full time-dependent Hamiltonian or interrupt evolution for tomography. Here, we experimentally demonstrate that an a priori unknown, time-dependent Hamiltonian can be reconstructed from continuous weak measurements concurrent with coherent time evolution in a system of two superconducting transmons coupled by a flux-tunable coupler. In contrast to previous work, our technique does not require interruptions, which would distort the recovered Hamiltonian. We introduce an algorithm which recovers the Hamiltonian and density matrix from an incomplete set of continuous measurements and demonstrate that it reliably extracts amplitudes of a variety of single qubit and entangling two qubit Hamiltonians. We further demonstrate how this technique reveals deviations from a theoretical control Hamiltonian which would otherwise be missed by conventional techniques. Our work opens up novel applications for continuous weak measurements, such as studying non-idealities in gates, certifying analog quantum simulators, and performing quantum metrology., Main text: 12 pages, 4 figures. Appendix: 10 pages, 4 figures

In the tumor microenvironment, immune cells and tumor cells interact in a process called cancer immunoediting, giving rise to changes in gene expression, metabolism, mutational burden, and cellularity in the tumor. This SnapShot compares endogenous versus therapy-induced cancer immunoediting and outlines the molecular and cellular characteristics of interactions that result in complete tumor regression versus tumor escape and progression. To view this SnapShot, open or download the PDF.

In this investigation, a facile and cost-effective method was developed for fabricating the tungsten selenide/carbon nanotube (WSe2/CNT) hybrid photocatalysts by an aqueous hydrothermal method. The structural, optical, and photocatalytic activities of the prepared photocatalysts were investigated through various characterization techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectra analysis, UV-Vis spectra analysis, and photoluminescence spectra analysis. The photocatalytic activity of the catalysts was tested toward methyl orange (MO) under visible light irradiation. The WSe2/CNT hybrid photocatalysts show outstanding efficiency (95%), high rate constant (0.341 min−1), and high stability. Moreover, the WSe2/CNT composite exhibits enhanced photoconversion efficiency (8.23%) under solar light. The possible photovoltaic mechanism was also proposed and discussed.

SummaryThe limited efficacy of immunotherapies against glioblastoma illustrates the urgent need to better understand the interactions between the central nervous system and the immune system. Here, we showed that a protective response to αCTLA-4 therapy depended on a mutualistic relationship between microglia and CD4+ T cells. Suppression of gliomas by CD4+ T cells did not require tumor-intrinsic MHC-II expression, but rather was dependent on the selective expression of MHC-II and antigen presentation by local microglia that in turn, sustained CD4+ T cell tumoricidal effector functions. CD4+ T cell secretion of IFNγ made the glioma cells vulnerable to enhanced tumor surveillance and phagocytosis by microglia via the AXL/MER tyrosine kinase receptors that were necessary for tumor suppression. This work illustrates a novel partnership between CD4+ T cells and microglia that unleashes the tumoricidal properties of microglia that can be harnessed to improve immunotherapies for glioblastoma.

In this work, holey g-C3N4 nanosheet wrapped Ag3PO4 composite was prepared by facile hydrothermal method. The structural, morphological, optical and elemental composition of the samples were analyzed by X-ray diffraction, Scanning electron microscope, Transmission electron microscope, Raman, UV–Vis diffuse reflectance spectra, Photoluminescence, N2 adsorption–desorption and X-ray photoelectron spectra, respectively. Systematic investigation indicated that phosphorus was effectively doped into the g-C3N4 framework, which increases the BET surface area, expands the visible light response region, and elevates the separation efficiency of electron–hole pairs. Sandwich type DSSC was fabricated and studied the studied the J–V characteristics. The results suggest that the optimal composite electrode (APG-50) with Ag3PO4/g-C3N4 ratio of 3:1 showed high photo-conversion efficiency (9.71%) than compared with bare g-C3N4 (1.89%) and Ag3PO4 (2.52%) electrodes, respectively. Besides, the EIS comes about illustrate that the APG-50 test appears tall electron exchange proficiency and lifetime. The progressed instrument of the proposed materials was moreover examined in detail.

Summary Metabolic reprogramming is a hallmark of T cell activation and function. As our understanding of T cell metabolism increases, so does our appreciation of its inherent complexity. The metabolic heterogeneity of T cells that reside in different locations, such as lymphoid and non-lymphoid tissues, presents a challenge to developing therapies that exploit metabolic vulnerabilities. The roots of metabolic heterogeneity are only beginning to be understood. Here, we propose four factors that contribute to the adaptation of T cells to their dynamic tissue environment: (1) functional status of T cells, (2) local factors unique to the tissue niche, (3) type of inflammation, and (4) time spent in a specific tissue. We review emerging concepts about tissue-specific metabolic reprogramming in T cells with particular attention to explain how such metabolic properties are used as an adaptation mechanism. Adaptation of immune cells to the local microenvironment is critical for their persistence and function. Here, Varanasi et al. review the role and types of metabolic adaptation acquired by T cells in tissues and how these adaptations might differ between tissue type, disease state, and functionality of a T cell.

4-methyl N-(4-chlorobenzylidene)aniline (4CBT) single crystal with dimension of 10 × 7 × 2 mm3 has been grown by the slow evaporation solution growth method. 4CBT crystal belonging to the monoclinic crystal system with space group of P21/c was studied by single-crystal X-ray diffraction. Fourier transform infrared analysis shows the existence of functional groups in 4CBT crystal. The existence of different protons position is confirmed using 1HNMR analysis. The optical nature of 4CBT is illustrated with help of cut-off wavelength and the transparency of the titled compound. The thermal stability of the grown crystal was analysed by thermogravimetric technique. Dielectric studies were also studied with respect to temperature and frequency. The energy values of highest occupied molecular orbital and lowest unoccupied molecular orbital have been measured by frontier molecular analysis. Third-order nonlinear optical properties of 4-methyl N-(4-chlorobenzylidene) aniline crystal were measured by Z-scan technique and the measured values of the nonlinear index of refraction and absorption coefficient shows the suitability of grown crystal for photonic applications.

We have fabricated the PANI/SnO2 and PANI/SnO2/rGO ternary composites by facile one-step hydrothermal approach followed by polymerization method. The hybrid nanocomposites were scientifically investigated for their structural, morphological and elemental composition through XRD, TEM, EDAX, FTIR and EPR analysis. The tetragonal rutile phase with nanospherical morphology sizes in the range of 25–35 nm was investigated by XRD and TEM results. The N2 adsorption–desorption measurement showed that ternary PANI/SnO2/rGO composite showed huge specific surface area (114.51 m2/g) and pore size (17–21 nm), which is higher than the bare SnO2 (surface area = 83.51 m2/g; pore size = 33–37 nm). The chemiresistive-type gas sensor was fabricated and the designed sensors were investigated by their sensing responses towards different gases (ethanol, methanol, carbon monoxide, oxygen, H2S and NH3). The results exposed that the ternary PANI/SnO2/rGO showed high sensing response (56%), fast response (35 s) and recovery time (40 s) towards H2S gas than other gases. The improved gas-sensing mechanism was also proposed.

We present SSOD, the first end-to-end analysis-by synthesis framework with controllable GANs for the task of self-supervised object detection. We use collections of real world images without bounding box annotations to learn to synthesize and detect objects. We leverage controllable GANs to synthesize images with pre-defined object properties and use them to train object detectors. We propose a tight end-to-end coupling of the synthesis and detection networks to optimally train our system. Finally, we also propose a method to optimally adapt SSOD to an intended target data without requiring labels for it. For the task of car detection, on the challenging KITTI and Cityscapes datasets, we show that SSOD outperforms the prior state-of-the-art purely image-based self-supervised object detection method Wetectron. Even without requiring any 3D CAD assets, it also surpasses the state-of-the-art rendering based method Meta-Sim2. Our work advances the field of self-supervised object detection by introducing a successful new paradigm of using controllable GAN-based image synthesis for it and by significantly improving the baseline accuracy of the task. We open-source our code at https://github.com/NVlabs/SSOD.

Light chain–associated amyloidosis is characterized by the extracellular deposition of amyloid fibrils in abdominothoracic organs, skin, soft tissue, and peripheral nerves. Phagocytic cells of the innate immune system appear to be ineffective at clearing the material; however, human light chain amyloid extract, injected subcutaneously into mice, is rapidly cleared in a process that requires neutrophil activity. To better elucidate the phagocytosis of light chain fibrils, a potential method of cell-mediated dissolution, amyloid-like fibrils were labeled with the pH-sensitive dye pHrodo red and a near infrared fluorophore. After injecting this material subcutaneously in mice, optical imaging was used to quantitatively monitor phagocytosis and dissolution of fibrils concurrently. Histologic evaluation of the residual fibril masses revealed the presence of CD68(+), F4/80(+), ionized calcium binding adaptor molecule 1(−) macrophages containing Congo red–stained fibrils as well as neutrophil-associated proteins with no evidence of intact neutrophils. These data suggest an early infiltration of neutrophils, followed by extensive phagocytosis of the light chain fibrils by macrophages, leading to dissolution of the mass. Optical imaging of this novel murine model, coupled with histologic evaluation, can be used to study the cellular mechanisms underlying dissolution of synthetic amyloid-like fibrils and human amyloid extracts. In addition, it may serve as a test bed to evaluate investigational opsonizing agents that might serve as therapeutic agents for light chain–associated amyloidosis.

A common metabolic alteration in the tumor microenvironment (TME) is lipid accumulation, a feature associated with immune dysfunction. Here we examined how CD8(+) tumor infiltrating lymphocytes (TILs) respond to lipids within the TME. We found elevated concentrations of several classes of lipids in the TME and accumulation of these in CD8(+) TILs. Lipid accumulation was associated with increased expression of CD36, a scavenger receptor for oxidized lipids, on CD8(+) TILs, which also correlated with progressive T cell dysfunction. Cd36(−/−) T cells retained effector functions in the TME, as compared to WT counterparts. Mechanistically, CD36 promoted uptake of oxidized low-density lipoproteins (OxLDL) into T cells and this induced lipid peroxidation and downstream activation of p38 kinase. Inhibition of p38 restored effector T cell functions in vitro, and resolution of lipid peroxidation by over-expression of glutathione peroxidase 4 restored functionalities in CD8(+) TILs in vivo. Thus, an oxidized lipid-CD36 axis promotes intratumoral CD8 T cell dysfunction and serves as a therapeutic avenue for immunotherapies.

Hepatocellular carcinoma (HCC) is an emerging health crisis due to rapidly increasing incidence rates and an overall 5-year survival rate of 18%. Consequently, there is an urgent need for new therapies and better preventive strategies. Aging and obesity are two of the biggest risk factors for HCC, and with ever-increasing aging and obese populations, uncovering how aging and obesity drive the increased risk for HCC has become imperative. Aging and obesity are well known to be characterized by immune dysregulation leading to persistent inflammation, and a dysregulated immune microenvironment is also a common theme shared by multiple hallmarks of HCC. In this study, we aim to assess the immune microenvironment of aged and obese mouse livers by performing spatial phenotyping of distinct immune signatures which can potentially predispose hepatocytes to HCC. To address this, we used Akoya’s ultra-high multiplexed CODEX (CO-Detection by indEXing) imaging system to interrogate 31 different biomarkers in liver samples at the single cell level. Specifically, we compared the liver immune microenvironment of mice within 2 different treatment groups (old mice on a high fat diet (HFD) and young mice on a normal diet (ND)) to the immune landscape of liver tumor tissue. Our goal is to identify distinct immune phenotypes present in both, liver tumor tissues and livers of HFD mice, compared to ND livers - to better understand how immune dysregulation can predispose an aged and obese liver to HCC. Citation Format: Adarsh Rajesh, Aaron Havas, Siva Karthik Varanasi, Katrina Evans, Bassem B. Cheikh, Clemens Duerrschmid, Najiba Mammadova, Peter Adams, Susan Kaech. a [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2531.

Discovery of electrode materials with superior light harvesting performance with high conductivity nature have become more and more urgent for the field of photovoltaics and portable electronic devices. Here in, synthesis of Fe2(MoO4)3/reduced graphene oxide (RGO) nanocomposite was prepared by simple hydrothermal approach and used as high efficient dye sensitized solar cells (DSSCs). The decoration of RGO into the Fe2(MoO4)3 was proved by various physic-chemical studies such as XRD, SEM, TEM, Raman, UV, PL and BET analysis. Due to the synergic effect between the Fe2(MoO4)3 and RGO the light absorption property is significantly improved as well the high surface area (112.5 m2/g) and pore size (38.7 nm) was achieved than compared with bare Fe2(MoO4)3 (88.5 m2/g and 17.8 nm). The Fe2(MoO4)3/RGO hybrid photoanode establish to display an outstanding catalytic activity toward the reduction of triiodide to iodide in a dye-sensitized solar cell (DSSC) and can provide a solar cell efficiency of 9.65%, which is superior to a Pt-based DSSC (6.17%). The better electro-catalytic ability of Fe2(MoO4)3/RGO electrode is obtained by a synergistic effect that resulted in the high specific surface area and intrinsic reactivity of the photocathode materials.

Neural rendering techniques promise efficient photorealistic image synthesis while providing rich control over scene parameters by learning the physical image formation process. While several supervised methods have been proposed for this task, acquiring a dataset of images with accurately aligned 3D models is very difficult. The main contribution of this work is to lift this restriction by training a neural rendering algorithm from unpaired data. We propose an autoencoder for joint generation of realistic images from synthetic 3D models while simultaneously decomposing real images into their intrinsic shape and appearance properties. In contrast to a traditional graphics pipeline, our approach does not require to specify all scene properties, such as material parameters and lighting by hand. Instead, we learn photo-realistic deferred rendering from a small set of 3D models and a larger set of unaligned real images, both of which are easy to acquire in practice. Simultaneously, we obtain accurate intrinsic decompositions of real images while not requiring paired ground truth. Our experiments confirm that a joint treatment of rendering and decomposition is indeed beneficial and that our approach outperforms state-of-the-art image-to-image translation baselines both qualitatively and quantitatively.

SummaryT cell metabolic fitness plays a pivotal role in anti-tumor immunity and metabolic deregulation causes T cell dysfunction (i.e., ‘exhaustion’) in cancer. We identify that the scavenger receptor CD36 limits anti-tumor CD8+T cell effector functions through lipid peroxidation. In murine tumors, oxidized phospholipids (OxPLs) were highly abundant and CD8+TILs increased uptake and accumulation of lipids and lipid peroxidation. Functionally ‘exhausted’ CD8+TILs substantially increased CD36 expression and CD36-deficient CD8+TILs had more robust anti-tumor activity and cytokine production than wild-type cells. We further show that CD36 promotes uptake of oxidized low-density lipoproteins (OxLDL) and induces lipid peroxidation in CD8+TILs, and OxLDL inhibits CD8+T cell functions in a CD36-dependent manner. Moreover, glutathione peroxidase 4 (GPX4) over-expression lowers lipid peroxidation and restores functionalities in CD8+TILs. These results define a key role for an oxidized lipid-CD36 axis in promoting intratumoral CD8+T cell dysfunction.

Background:The aims and objectives of this study are to study the influence of Estrogen receptor ER, Progesterone receptor PR of patients having infiltrating ductal carcinoma of breast recieving Neoadjuvant chemotherapy, To study the influence of ER and PR receptors in patients receiving neoadjuvant chemotherapy & correlate complete pathological response. Methods . Type of study: Prospective clinical study. present study was carried out in the department of general surgery Vinayaka Missions medical college and hospital karaikal from July 2016 – December 2017.. HPE (Histopathological examination) and ER PR status was done. Patients diagnosed with locally advanced breast cancer underwent simple randomization into 2 treatment groupsGroup 1: AC (Adriamycin 60mg/m2, Cyclophosphamide 600mg/m2) once every 3 weeks for 4 cyclesGroup2: Docetaxel 75 mg/m2 for 4 cycles every 3 weekly (11).Clinical examination was performed after every two cycles and completing all the chemotherapy, study group patients were subjected to Modified radical mastectomy which was then followed by evaluation of pathological response. Conclusion: In this study 30 patients ER PR status was done. According to ER PR status Neoadjuvant chemotherapy regimen given. NCT response was assessed with clinical / imaging study. There was reduction in tumor size and change in lymph node status in both the groups with p value of .44. As our study size is small we cannot predict the actual outcome of the two study groups. We need larger sample size to predict the actual outcome.Results: The statistical analysis was performed by STATA 11.2. Descriptive statistics of frequency and percentage were performed all the study variables. Chi square test were used to measure the association between the CP response with ER status. P

Glioblastoma multiforme (GBM) is the deadliest form of brain cancer, for which there is currently no effective treatment. Despite success of immunotherapies such as checkpoint inhibitors (CPI) in treating some cancers, less than 8% of GBM patients responded to anti-PD-1 therapy. Thus, we need to understand what mechanisms underlie tumor resistance to immunotherapies. In our GBM mouse model, we have found that anti-CTLA-4 treatment greatly improved survival and suppressed tumor growth, but surprisingly, its efficacy was lost in mice that were depleted of CD4+ but not CD8+ T cells, suggesting that CD4+ T cells are critical for protection against GBM. This matches clinical data showing decreased populations of CD4+ T cells in patients with adverse clinical outcomes such as high-grade GBM. Our preliminary results from flow cytometry and single-cell RNA sequencing (sc-RNAseq) also suggested enhanced cytokine production (IFNγ, TNFα, IL-2) in CD4+ T cells after anti-CTLA-4 treatment. Similarly, we found that microglia, the local sentinels of the central nervous system, also play a significant role in tumor control, as indicated by faster GBM growth and reduced number of tumor-infiltrating CD4+ T cells when mice are depleted of microglia by a CSF1R inhibitor (PLX3397). Additionally, microglia in GBM may serve as potential antigen-presenting cells, as shown by their high MHC class II (MHC-II) expression. Therefore, we postulate that microglia are necessary to sustain anti-tumor immunity by CD4+ T cells. Importantly, through a more detailed exploration of how CD4+ T cells and microglia interact to impact tumor control, our study will provide new insights for developing therapeutic strategies against “difficult-to-treat” cancers such as GBM.

This report deals with the possible mechanism by which IL-18 can contribute to the control and resolution of inflammatory lesions in the cornea caused by herpes simplex virus infection. Our results demonstrate that the expression of the IL-18R by both regulatory T cells (Treg) and effector T cells was a pivotal event that influenced lesion pathogenesis. The engagement of IL-18R on Treg with its cytokine ligand resulted in Amphiregulin expression a molecule associated with tissue repair. In support of this scheme of events, lesion severity became more severe in animals unable to express the IL-18R because of gene knockout and was reduced in severity when IL-18 was overexpressed in the cornea. These changes in lesion severity correlated with the frequency and number of both Treg and Teff that expressed Amphiregulin. Additional experiments indicated that IL-12 and IL-18 acted synergistically to enhance Amphiregulin expression in Treg, an event partly dependent on P38 MAPK activity. Finally, sub-conjunctival administration of Amphiregulin resulted in resolution of both developing and developed lesions. Thus, overall our results imply that IL-18 may participate in controlling the severity of SK and contribute to tissue repair by converting both Treg and effector T cells into those that produce Amphiregulin.

The outcome of virus infections depends on multiple factors. This review deals with the role of host metabolism as one such factor. We describe how different cells in the immune system employ differential metabolic pathways and how this relates to the outcome of virus infections. We also discuss how nutritional and metabolic diseases can influence the nature of viral pathogenesis as well as how targeted therapies against metabolic processes can impact on the outcome of virus infections. The case is also made for metabolic profiling as a potential tool to predict the outcome of a virus infection and to guide therapies that enhance host resistance.

Thermal management in the supersonic combustion chambers subjected to high heat fluxes is vital for maintaining their integrity. At high temperatures ordinary materials cannot sustain the high heat loads. On the other hand, the prevailing high temperature gradients, necessitates the provision for expansion to avoid build of thermal stresses for the integration. Hence, thermal management needs a holistic approach encompassing the areas of material selection, heat transfer and structural integration. The current state of art research is focused on achieving this by active cooling through endothermic fuel, which is used as a coolant due to the advantages such as reduced weight and improved heat sink capacities. Particularly the space applications pose serious limitations on the weight. 1D thermo-structural hand calculations can be easy point to start with to arrive at the optimized shape of the single actively cooled channel. But the underlying assumptions and owing to the 1D nature of the such calculations, pose limitation towards understanding the behavior of the active panel as a whole and achieving the practical integration strategy. Therefore, there is need to perform 3D CFD and FEA thermo-structural analysis of the active panel structure. This paper extends upon the approach of 1D analytical material selection methodology through weight optimization followed by rigorous CFD and FEA analysis to understand and device ways for structural integration for long duration flight of about 600 seconds.

This report deals with physiological changes and their implication following ocular infection with HSV. This infection usually results in a blinding inflammatory reaction in the cornea, orchestrated mainly by proinflammatory CD4 T cells and constrained in severity by regulatory T cells. In the present report, we make the unexpected finding that blood glucose levels change significantly during the course of infection. Whereas levels remained normal during the early phase of infection when the virus was actively replicating in the cornea, they increased around 2-fold during the time when inflammatory responses to the virus was occurring. We could show that glucose levels influenced the extent of induction of the inflammatory T cell subset in vitro that mainly drives lesions, but not regulatory T cells. Additionally, if glucose utilization was limited in vivo as a consequence of therapy in the inflammatory phase with the drug 2-deoxy-glucose (2DG), lesions were diminished compared with untreated infected controls. In addition, lesions in 2DG-treated animals contained less proinflammatory effectors. Glucose metabolism also influenced the acute phase of infection when the replicating virus was present in the eye. Thus, therapy with 2DG to limit glucose utilization caused mice to become susceptible to the lethal effects of HSV infection, with the virus spreading to the brain causing encephalitis. Taken together, our results indicate that glucose metabolism changed during the course of HSV infection and that modulating glucose levels can influence the outcome of infection, being detrimental or beneficial according to the stage of viral pathogenesis.

Neural rendering techniques promise efficient photo-realistic image synthesis while at the same time providing rich control over scene parameters by learning the physical image formation process. While several supervised methods have been proposed for this task, acquiring a dataset of images with accurately aligned 3D models is very difficult. The main contribution of this work is to lift this restriction by training a neural rendering algorithm from unpaired data. More specifically, we propose an autoencoder for joint generation of realistic images from synthetic 3D models while simultaneously decomposing real images into their intrinsic shape and appearance properties. In contrast to a traditional graphics pipeline, our approach does not require to specify all scene properties, such as material parameters and lighting by hand. Instead, we learn photo-realistic deferred rendering from a small set of 3D models and a larger set of unaligned real images, both of which are easy to acquire in practice. Simultaneously, we obtain accurate intrinsic decompositions of real images while not requiring paired ground truth. Our experiments confirm that a joint treatment of rendering and decomposition is indeed beneficial and that our approach outperforms state-of-the-art image-to-image translation baselines both qualitatively and quantitatively.

Training deep neural networks to estimate the viewpoint of objects requires large labeled training datasets. However, manually labeling viewpoints is notoriously hard, error-prone, and time-consuming. On the other hand, it is relatively easy to mine many unlabelled images of an object category from the internet, e.g., of cars or faces. We seek to answer the research question of whether such unlabeled collections of in-the-wild images can be successfully utilized to train viewpoint estimation networks for general object categories purely via self-supervision. Self-supervision here refers to the fact that the only true supervisory signal that the network has is the input image itself. We propose a novel learning framework which incorporates an analysis-by-synthesis paradigm to reconstruct images in a viewpoint aware manner with a generative network, along with symmetry and adversarial constraints to successfully supervise our viewpoint estimation network. We show that our approach performs competitively to fully-supervised approaches for several object categories like human faces, cars, buses, and trains. Our work opens up further research in self-supervised viewpoint learning and serves as a robust baseline for it. We open-source our code at https://github.com/NVlabs/SSV., Comment: Accepted at CVPR 20

Our knowledge of T cell metabolism relies primarily on studies performed in vitro that may not fully recapitulate physiological conditions in vivo. In this issue of Immunity, Ma et al. find that the in vivo environment dictates the metabolic phenotype of effector CD8+ T cells—particularly their glucose utilization.

Autonomous explorative robots frequently encounter scenarios where multiple future trajectories can be pursued. Often these are cases with multiple paths around an obstacle or trajectory options towards various frontiers. Humans in such situations can inherently perceive and reason about the surrounding environment to identify several possibilities of either manoeuvring around the obstacles or moving towards various frontiers. In this work, we propose a 2 stage Convolutional Neural Network architecture which mimics such an ability to map the perceived surroundings to multiple trajectories that a robot can choose to traverse. The first stage is a Trajectory Proposal Network which suggests diverse regions in the environment which can be occupied in the future. The second stage is a Trajectory Sampling network which provides a finegrained trajectory over the regions proposed by Trajectory Proposal Network. We evaluate our framework in diverse and complicated real life settings. For the outdoor case, we use the KITTI dataset and our own outdoor driving dataset. In the indoor setting, we use an autonomous drone to navigate various scenarios and also a ground robot which can explore the environment using the trajectories proposed by our framework. Our experiments suggest that the framework is able to develop a semantic understanding of the obstacles, open regions and identify diverse trajectories that a robot can traverse. Our comparisons portray the performance gain of the proposed architecture over a diverse set of methods against which it is compared.

Summary A common metabolic alteration in the tumor microenvironment (TME) is lipid accumulation, a feature associated with immune dysfunction. Here, we examined how CD8+ tumor infiltrating lymphocytes (TILs) respond to lipids within the TME. We found elevated concentrations of several classes of lipids in the TME and accumulation of these in CD8+ TILs. Lipid accumulation was associated with increased expression of CD36, a scavenger receptor for oxidized lipids, on CD8+ TILs, which also correlated with progressive T cell dysfunction. Cd36−/− T cells retained effector functions in the TME, as compared to WT counterparts. Mechanistically, CD36 promoted uptake of oxidized low-density lipoproteins (OxLDL) into T cells, and this induced lipid peroxidation and downstream activation of p38 kinase. Inhibition of p38 restored effector T cell functions in vitro, and resolution of lipid peroxidation by overexpression of glutathione peroxidase 4 restored functionalities in CD8+ TILs in vivo. Thus, an oxidized lipid-CD36 axis promotes intratumoral CD8+ T cell dysfunction and serves as a therapeutic avenue for immunotherapies.

This study presents a rational-designed structure and facile strategy to fabricate tungsten selenide/carbon nanotube (WSe2/CNT) hybrid photoanodes as promising anodes for DSSC applications. The fundamental physic-chemical properties proved that the uniform, pure and tubular WSe2/CNT hybrid nanoparticles were produced and WSe2 nanoparticles were anchored the CNT surface successfully. The WSe2/CNT hybrid nanostructure exhibits higher surface area (107.8 m2/g) and pore size (45.3 nm) than compared with pure WSe2 (86.2 m2/g and 19.8 nm). WSe2/CNT composite exhibits enhanced photo-conversion efficiency (8.85%), electro-catalytic activity and high electron life time (87 ns). The improved PCE of the WSe2/CNT composite is due to the CNTs can reduce electron-hole pair recombination and efficiently inhibit the aggregation of WSe2 for fully exposing the active edges. Those outstanding electrochemical performances of WSe2/CNT hybrid can be assigned to its unique nanoarchitecture: the CNT with high conductivity work as the skeleton of WSe2/CNT anode facilitating the electron transfer; the CNT can effectively prevent WSe2 from the aggregation and promote the in-situ growth of WSe2 on CNT. Moreover, the hybrid structure, which can allow for efficient ionic diffusion and easy electrolyte infiltration.

The task of generating natural images from 3D scenes has been a long standing goal in computer graphics. On the other hand, recent developments in deep neural networks allow for trainable models that can produce natural-looking images with little or no knowledge about the scene structure. While the generated images often consist of realistic looking local patterns, the overall structure of the generated images is often inconsistent. In this work we propose a trainable, geometry-aware image generation method that leverages various types of scene information, including geometry and segmentation, to create realistic looking natural images that match the desired scene structure. Our geometrically-consistent image synthesis method is a deep neural network, called Geometry to Image Synthesis (GIS) framework, which retains the advantages of a trainable method, e.g., differentiability and adaptiveness, but, at the same time, makes a step towards the generalizability, control and quality output of modern graphics rendering engines. We utilize the GIS framework to insert vehicles in outdoor driving scenes, as well as to generate novel views of objects from the Linemod dataset. We qualitatively show that our network is able to generalize beyond the training set to novel scene geometries, object shapes and segmentations. Furthermore, we quantitatively show that the GIS framework can be used to synthesize large amounts of training data which proves beneficial for training instance segmentation models.

We address the task of 6D pose estimation of known rigid objects from single input images in scenarios where the objects are partly occluded. Recent RGB-D-based methods are robust to moderate degrees of occlusion. For RGB inputs, no previous method works well for partly occluded objects. Our main contribution is to present the first deep learning-based system that estimates accurate poses for partly occluded objects from RGB-D and RGB input. We achieve this with a new instance-aware pipeline that decomposes 6D object pose estimation into a sequence of simpler steps, where each step removes specific aspects of the problem. The first step localizes all known objects in the image using an instance segmentation network, and hence eliminates surrounding clutter and occluders. The second step densely maps pixels to 3D object surface positions, so called object coordinates, using an encoder-decoder network, and hence eliminates object appearance. The third, and final, step predicts the 6D pose using geometric optimization. We demonstrate that we significantly outperform the state-of-the-art for pose estimation of partly occluded objects for both RGB and RGB-D input.

The task of generating natural images from 3D scenes has been a long standing goal in computer graphics. On the other hand, recent developments in deep neural networks allow for trainable models that can produce natural-looking images with little or no knowledge about the scene structure. While the generated images often consist of realistic looking local patterns, the overall structure of the generated images is often inconsistent. In this work we propose a trainable, geometry-aware image generation method that leverages various types of scene information, including geometry and segmentation, to create realistic looking natural images that match the desired scene structure. Our geometrically-consistent image synthesis method is a deep neural network, called Geometry to Image Synthesis (GIS) framework, which retains the advantages of a trainable method, e.g., differentiability and adaptiveness, but, at the same time, makes a step towards the generalizability, control and quality output of modern graphics rendering engines. We utilize the GIS framework to insert vehicles in outdoor driving scenes, as well as to generate novel views of objects from the Linemod dataset. We qualitatively show that our network is able to generalize beyond the training set to novel scene geometries, object shapes and segmentations. Furthermore, we quantitatively show that the GIS framework can be used to synthesize large amounts of training data which proves beneficial for training instance segmentation models.

Context: Gonadotropin-releasing hormone (GnRH) antagonists in fixed or flexible regimens are used for prevention of premature luteinizing hormone (LH) surge, however, data comparing these regimens in stimulated intrauterine insemination (IUI) cycles are lacking. Aims: The aim of this study is to evaluate the effectiveness of GnRH antagonists in fixed and flexible regimens on the rate of premature luteinization (PL) and ovulation rate in sequential clomiphene-gonadotropin controlled ovulation–IUI cycles. Settings and Design: This study was conducted at tertiary care center; this was randomized controlled study. Materials and Methods: A total of 45 infertile women randomized into three groups of 15 each received clomiphene citrate + human menopausal gonadotrophin. GnRH antagonist was added according to fixed (n = 15) and flexible (n = 15) protocol. No antagonist in control group (n = 15). PL was defined as LH level ≥10 mIU/ml and progesterone level ≥1.0 ng/ml. Statistical Analysis: Mean values compared using the Student's t-test or one-way analysis of variance. Categorical variables distribution tested using either Pearson's Chi-square or Fisher's exact test as appropriate. Results: Of a total of 45 women, 58% (n = 26) presented with primary and 42% (n = 19) secondary infertility with mean age of 30.8 ± 3.43 years and BMI 26.57 ± 3.22 kg/m2. Fixed regimen (3.7%) showed most reduction in PL compared to flexible (15.38%, P = 0.33) or control (36.67%, P = 0.004). On human chorionic gonadotropin day, mean LH (P = 0.002) and progesterone (P = 0.079) levels in fixed, flexible, and control groups were as follows: 5.04 ± 5.47 mIU/ml, 3.95 ± 4.16 mIU/ml, 9.57 ± 7.91 mIU/ml, and 0.409 ± 0.320 ng/ml, 0.579 ± 0.727 ng/ml, and 1.033 ± 1.022 ng/ml, respectively. Ovulation (P = 0.813) and pregnancy rates (P = 0.99) were 88.9%, 84.6%, and 90% and 22.2%, 19.23%, and 10% in fixed, flexible, and control groups, respectively. Conclusions: Addition of antagonist in any regimen appears to lower PL rates and improve pregnancy rates in controlled ovarian stimulation and IUI cycles.

Herpes simplex 1 infection of the eye can cause blindness with lesions in the corneal stroma largely attributable to inflammatory events that include components of both adaptive and innate immunity. Several innate immune responses are triggered by herpes simplex 1, but it is unclear how such innate events relate to the subsequent development of stromal keratitis. In this study, we compared the outcome of herpes simplex 1 ocular infection in mice unable to express NLRP3 because of gene knockout (NLRP3−/−) to that of wild-type mice. The NLRP3−/− mice developed more-severe and earlier stromal keratitis lesions and had higher angiogenesis scores than did infected wild-type animals. In addition, NLRP3−/− mice generated an increased early immune response with heightened chemokines and cytokines, including interleukin-1β and interleukin-18, and elevated recruitment of neutrophils. Increased numbers of CD4+ T cells were seen at later stages of the disease in NLRP3−/− animals. Reduction in neutrophils prevented early onset of the disease in NLRP3−/− animals and lowered levels of bioactive interleukin-1β but did not lower bioactive interleukin-18. In conclusion, our results indicate that NLRP3 has a regulatory and beneficial role in herpetic stromal keratitis pathogenesis.

Ocular infection with herpes simplex virus 1 can result in a chronic immunoinflammatory stromal keratitis (SK) lesion that is a significant cause of human blindness. A key to controlling SK lesion severity is to identify cellular and molecular events responsible for tissue damage and to manipulate them therapeutically. Potential targets for therapy are miRNAs, but these are minimally explored especially in responses to infection. Here, we demonstrated that Mir155 expression was up-regulated after ocular herpes simplex virus 1 infection, with the increased Mir155 expression occurring mainly in macrophages and CD4 + T cells and to a lesser extent in neutrophils. In vivo studies indicated that Mir155 knockout mice were more resistant to herpes SK with marked suppression of T helper cells type 1 and 17 responses both in the ocular lesions and the lymphoid organs. The reduced SK lesion severity was reflected by increased phosphatidylinositol-3,4,5-trisphosphate 5-phosphatase 1 and interferon-γ receptor α-chain levels in activated CD4 + T cells in the lymph nodes. Finally, in vivo silencing of miR-155 by the provision of antagomir-155 nanoparticles to herpes simplex virus 1–infected mice led to diminished SK lesions and corneal vascularization. In conclusion, our results indicate that miR-155 contributes to the pathogenesis of SK and represents a promising target to control SK severity.

Ocular infection with herpes simplex virus (HSV) can result in a chronic immune inflammatory lesion that is a significant cause of human blindness. A key to controlling stromal keratitis (SK) lesion severity is to identify cellular and molecular events responsible for tissue damage and to counteract them. One potentially useful approach to achieve such therapy is Retinoic Acid (RA). Here we show that RA therapy reduces the severity of SK by having inhibitory effects on the T effector subtypes responsible for orchestrating SK. RA also served to stabilize the function of regulatory T cell (Treg) which counteract inflammatory cell activity. The Treg stabilizing effect was demonstrated by in vitro studies where RA was shown to retain Foxp3 expression when exposed to proinflammatory conditions such as IL-12 and IL-6+TGF-β. in vivo studies revealed that RA exerted its stabilizing effects by downregulating IL-6R expression on Treg after HSV-1 infection and this helped to control the progression of SK. Since the therapy was effective when used both early and after the initiation of lesions, it may represent a valuable means of therapy when used alone or along with additional therapies.

The smartphone industry has gained a large user base since the digital revolution. Due to this, even the Telecommunication operators have had a surge in customers. This has led to call tariffs being decided by the operators and frequently users end up paying for more than what they have used. This research paper explores the option of local call routing using femtocells instead of routing the call through a switching center that belongs to a licensed operator. It has been statistically verified that using VoIP based systems based on the Session Initiation Protocol is very efficient in cutting down costs. Gartner predicts that SIP trunking services can slash enterprise telecommunications expenses by up to 50 percent. It is estimated that VoIP systems can reduce initial startup costs to new businesses by up to 90 percent. The Session Initiation Protocol is the ideal candidate for efficient implementation of VoIP-based systems. The general idea being portrayed here is that the traffic generated in a network does not leave the network and terminates in a host within the same network. This ensures that the overhead to reach an operator is minimized. A call manager, specific to VoIP packets, may be developed to address hosts and efficiently route video and audio traffic in between them. Textual data can also be exchanged. This proves very useful during disaster relief as it is possible to set up such systems with relative ease.

Ocular infection with HSV causes a chronic T cell–mediated inflammatory lesion in the cornea. Lesion severity is affected by the balance of different CD4 T cell subsets, with greater severity occurring when the activity of regulatory T cells (Tregs) is compromised. In this study, fate-mapping mice were used to assess the stability of Treg function in ocular lesions. We show that cells that were once Foxp3+ functional Tregs may lose Foxp3 and become Th1 cells that could contribute to lesion expression. The instability primarily occurred with IL-2Rlo Tregs and was shown, in part, to be the consequence of exposure to IL-12. Lastly, in vitro–generated induced Tregs (iTregs) were shown to be highly plastic and capable of inducing stromal keratitis when adoptively transferred into Rag1−/− mice, with 95% of iTregs converting into ex-Tregs in the cornea. This plasticity of iTregs could be prevented when they were generated in the presence of vitamin C and retinoic acid. Importantly, adoptive transfer of these stabilized iTregs to HSV-1–infected mice prevented the development of stromal keratitis lesions more effectively than did control iTregs. Our results demonstrate that CD25lo Treg and iTreg instability occurs during a viral immunoinflammatory lesion and that its control may help to avoid lesion chronicity.

Summary Immunotherapy has revolutionized cancer treatment, yet most patients do not respond. Here, we investigated mechanisms of response by profiling the proteome of clinical samples from advanced stage melanoma patients undergoing either tumor infiltrating lymphocyte (TIL)-based or anti- programmed death 1 (PD1) immunotherapy. Using high-resolution mass spectrometry, we quantified over 10,300 proteins in total and ∼4,500 proteins across most samples in each dataset. Statistical analyses revealed higher oxidative phosphorylation and lipid metabolism in responders than in non-responders in both treatments. To elucidate the effects of the metabolic state on the immune response, we examined melanoma cells upon metabolic perturbations or CRISPR-Cas9 knockouts. These experiments indicated lipid metabolism as a regulatory mechanism that increases melanoma immunogenicity by elevating antigen presentation, thereby increasing sensitivity to T cell mediated killing both in vitro and in vivo. Altogether, our proteomic analyses revealed association between the melanoma metabolic state and the response to immunotherapy, which can be the basis for future improvement of therapeutic response.

We address the task of 6D pose estimation of known rigid objects from single input images in scenarios where the objects are partly occluded. Recent RGB-D-based methods are robust to moderate degrees of occlusion. For RGB inputs, no previous method works well for partly occluded objects. Our main contribution is to present the first deep learning-based system that estimates accurate poses for partly occluded objects from RGB-D and RGB input. We achieve this with a new instance-aware pipeline that decomposes 6D object pose estimation into a sequence of simpler steps, where each step removes specific aspects of the problem. The first step localizes all known objects in the image using an instance segmentation network, and hence eliminates surrounding clutter and occluders. The second step densely maps pixels to 3D object surface positions, so called object coordinates, using an encoder-decoder network, and hence eliminates object appearance. The third, and final, step predicts the 6D pose using geometric optimization. We demonstrate that we significantly outperform the state-of-the-art for pose estimation of partly occluded objects for both RGB and RGB-D input.