Search Results (87)

Achieving the precise targeting of lentiviral vectors (LVs) to specific cell populations is crucial for effective gene therapy, particularly in cancer treatment where the modulation of the tumor microenvironment can enhance anti-tumor immunity. Programmed cell death protein 1 (PD-1) is overexpressed on activated tumor-infiltrating T lymphocytes, including regulatory T cells that suppress immune responses via FOXP3 expression. We developed PD1-targeted LVs by incorporating the anti-PD1 nanobody nb102c3 into receptor-blinded measles virus H and VSV-G_mut glycoproteins. We assessed the retargeting potential of nb102c3 and evaluated transduction efficiency in activated T lymphocytes. FOXP3 expression was suppressed using shRNA delivered by these LVs. Our results demonstrate that PD1-targeted LVs exerted pronounced tropism towards PD1⁺ cells, enabling the selective transduction of activated T lymphocytes while sparing naive T cells. The suppression of FOXP3 in Tregs reduced their suppressive activity. PD1-targeted glycoprotein H provided greater specificity, whereas the VSV-G_mut, together with the anti-PD1 pseudoreceptor, achieved higher viral titers but was less selective. Our study demonstrates that PD1-targeted LVs may offer a novel strategy to modulate immune responses within the tumor microenvironment with the potential for developing new therapeutic strategies aimed at enhancing anti-tumor immunity. Full article

Background: As spontaneous renal artery dissection (SRAD) is a rare cause of abdominal pain, bilateral dissection is an extremely rare event. Only approximately two hundred cases of SRAD have been reported in the literature. The diagnosis is often delayed due to the rarity of the disease and non-specific clinical presentations such as flank pain, hypertension, fever, nausea, vomiting, and hematuria, which can be often misdiagnosed as a genito-urinary infection or gastrointestinal or bowel disease. Before 1980, the diagnosis of SRAD was mostly confirmed via autopsy or, rarely, via angiography. At present, the diagnosis is made using advanced imaging approaches, including computed tomography angiography (CTA) and magnetic resonance angiography (MRA), with a higher number of incidentally diagnosed SRADs. Methods: we performed laboratory tests and radiological examinations (computed abdominal tomography and multiplanar reconstruction) that revealed multiple infarctions and ischemic areas with hypoperfusion in the upper middle third of the left kidney and in a large part of middle and lower areas of the right kidney; the left renal artery exhibited increased intimal thickening and arteritis. Results: The multiplanar reconstruction revealed bilateral renal artery dissection and multiple arterial infarctions disseminated throughout both kidneys. After a clinical follow-up and hypertension retargeting, the patient was discharged with dual antiplatelet therapy and ACE inhibitor drugs. No lipid-lowering therapy was needed. Conclusions: Spontaneous renal artery dissection (SRAD) is a rare clinical event that typically presents with acute low-back or flank pain, hypertension, fever, hematuria, and acute renal failure. The condition could be misdiagnosed or receive a delayed diagnosis due to its relative rarity and non-specific presentation. The gold standard is enhanced computed tomography (CT) scans, and if the diagnosis is positive, vascular multiplanar reconstruction is generally suggested, as it can display lesions more clearly. Over 300 cases have been reported since the first characterization of SRAD; however, to date, a consensus has not been reached on the most appropriate treatment. Conservative therapy, open surgery, and intravascular intervention have been reported as treatments for SRAD. Full article

Image retargeting is a common computer graphics task which involves manipulating the size or aspect ratio of an image. This task often presents a challenge to the artist or user, because manipulating the size of an image necessitates some degree of data loss as pixels need to be removed to accommodate a different image size. We present an image retargeting framework which implements a confidence map generated by a segmentation model for content-aware resizing, allowing users to specify which subjects in an image to preserve using natural language prompts much like the role of an art director conversing with their artist. Using computer vision models to detect object positions also provides additional control over the composition of the retargeted image at various points in the image-processing pipeline. This object-based approach to energy map augmentation is incredibly flexible, because only minor adjustments to the processing of the energy maps can provide a significant degree of control over where seams—paths of pixels through the image—are removed, and how seam removal is prioritized in different sections of the image. It also provides additional control with techniques for object and background separation and recomposition. This research explores how several different types of deep-learning models can be integrated into this pipeline in order to easily make these decisions, and provide different retargeting results on the same image based on user input and compositional considerations. Because this is a framework based on existing machine-learning models, this approach will benefit from advancements in the rapidly developing fields of computer vision and large language models and can be extended for further natural language directorial controls over images. Full article

Retroviruses integrate into the genomes of infected host cells to form proviruses, a genetic platform for stable viral gene expression. Epigenetic silencing can, however, hamper proviral transcriptional activity. As gammaretroviruses (γRVs) preferentially integrate into active promoter and enhancer sites, the high transcriptional activity of γRVs can be attributed to this integration preference. In addition, long terminal repeats (LTRs) of some γRVs were shown to act as potent promoters by themselves. Here, we investigate the capacity of different γRV LTRs to drive stable expression within a non-preferred epigenomic environment in the context of diverse retroviral vectors. We demonstrate that different γRV LTRs are either rapidly silenced or remain active for long periods of time with a predominantly active proviral population under normal and retargeted integration. As an alternative to the established γRV systems, the feline leukemia virus and koala retrovirus LTRs are able to drive stable, albeit intensity-diverse, transgene expression. Overall, we show that despite the occurrence of rapid silencing events, most γRV LTRs can drive stable expression outside of their preferred chromatin landscape after retrovirus integrations. Full article

The potential of the immune system to eradicate leukemic cells has been consistently demonstrated by the Graft vs. Leukemia effect occurring after allo-HSCT and in the context of donor leukocyte infusions. Various immunotherapeutic approaches, ranging from the use of antibodies, antibody–drug conjugates, bispecific T-cell engagers, chimeric antigen receptor (CAR) T-cells, and therapeutic infusions of NK cells, are thus currently being tested with promising, yet conflicting, results. This review will concentrate on various types of immunotherapies in preclinical and clinical development, from the point of view of a clinical hematologist. The most promising therapies for clinical translation are the use of bispecific T-cell engagers and CAR-T cells aimed at lineage-restricted antigens, where overall responses (ORR) ranging from 20 to 40% can be achieved in a small series of heavily pretreated patients affected by refractory or relapsing leukemia. Toxicity consists mainly in the occurrence of cytokine-release syndrome, which is mostly manageable with step-up dosing, the early use of cytokine-blocking agents and corticosteroids, and myelosuppression. Various cytokine-enhanced natural killer products are also being tested, mainly as allogeneic off-the-shelf therapies, with a good tolerability profile and promising results (ORR: 20–37.5% in small trials). The in vivo activation of T lymphocytes and NK cells via the inhibition of their immune checkpoints also yielded interesting, yet limited, results (ORR: 33–59%) but with an increased risk of severe Graft vs. Host disease in transplanted patients. Therefore, there are still several hurdles to overcome before the widespread clinical use of these novel compounds. Full article

Manual facial rigging is time-consuming. Traditional automatic rigging methods lack either 3D datasets or explainable semantic parameters, which makes it difficult to retarget a certain 3D expression to a new face. To address the problem, we automatically generate a large 3D dataset containing semantic parameters, joint positions, and vertex positions from a limited number of spatiotemporal meshes. We establish an expression generator based on a multilayer perceptron with vertex constraints from the semantic parameters to the joint positions and establish an expression recognizer based on a generative adversarial structure from the joint positions to the semantic parameters. To enhance the accuracy of key facial area recognition, we add local vertex constraints for the eyes and lips, which are determined by the 3D masks computed by the proposed projection-searching algorithm. We testthe generation and recognition effects on a limited number of publicly available Metahuman meshes and self-collected meshes. Compared with existing methods, our generator has the shortest generation time of 14.78 ms and the smallest vertex relative mean square error of 1.57 × 10⁻³, while our recognizer has the highest accuracy of 92.92%. The ablation experiment verifies that the local constraints can improve the recognition accuracy by 3.02%. Compared with other 3D mask selection methods, the recognition accuracy is improved by 1.03%. In addition, our method shows robust results for meshes of different levels of detail, and the rig has more dimensions of semantic space. The source code will be made available if this paper is accepted for publication. Full article

Recent advancements in high dynamic range (HDR) display technology have significantly enhanced the contrast ratios and peak brightness of modern displays. In the coming years, it is expected that HDR televisions capable of delivering significantly higher brightness and, therefore, contrast levels than today’s models will become increasingly accessible and affordable to consumers. While HDR technology has gained prominence over the past few years, low dynamic range (LDR) content is still consumed due to a substantial volume of historical multimedia content being recorded and preserved in LDR. Although the amount of HDR content will continue to increase as HDR becomes more prevalent, a large portion of multimedia content currently remains in LDR. In addition, it is worth noting that although the HDR standard supports multimedia content with luminance levels up to 10,000 cd/m² (a standard measure of brightness), most HDR content is typically limited to a maximum brightness of around 1000 cd/m². This limitation aligns with the current capabilities of consumer HDR TVs but is a factor approximately five times brighter than current LDR TVs. To accurately present LDR content on a HDR display, it is processed through a dynamic range expansion process known as inverse tone mapping (iTM). This LDR to HDR conversion faces many challenges, including the inducement of noise artifacts, false contours, loss of details, desaturated colors, and temporal inconsistencies. This paper introduces complete inverse tone mapping, artifact suppression, and a highlight enhancement pipeline for video sequences designed to address these challenges. Our LDR-to-HDR technique is capable of adapting to the peak brightness of different displays, creating HDR video sequences with a peak luminance of up to 6000 cd/m². Furthermore, this paper presents the results of comprehensive objective and subjective experiments to evaluate the effectiveness of the proposed pipeline, focusing on two primary aspects: real-time operation capability and the quality of the HDR video output. Our findings indicate that our pipeline enables real-time processing of Full HD (FHD) video (1920 × 1080 pixels), even on hardware that has not been optimized for this task. Furthermore, we found that when applied to existing HDR content, typically capped at a brightness of 1000 cd/m², our pipeline notably enhances its perceived quality when displayed on a screen that can reach higher peak luminances. Full article

The role of the interaction with cell-surface glycosaminoglycans (GAGs) during in vivo HSV infection is currently unknown. The rationale of the current investigation was to improve the anticancer efficacy of systemically administered retargeted oHSVs (ReHVs) by decreasing their binding to GAGs, including those of endothelial cells, blood cells, and off-tumor tissues. As a proof-of-principle approach, we deleted seven amino acids critical for interacting with GAGs from the glycoprotein C (gC) of R-337 ReHV. The modification in the resulting R-399 recombinant prolonged the half-life in the blood of systemically administered R-399 and enhanced its biodistribution to tumor-positive lungs and to the tumor-negative liver. Ultimately, it greatly increased the R-399 efficacy against metastatic-like lung tumors upon IV administration but not against subcutaneous tumors upon IT administration. These results provide evidence that the increased efficacy seen upon R-399 systemic administration correlated with the slower clearance from the circulation. To our knowledge, this is the first in vivo evidence that the partial impairment of the gC interaction with GAGs resulted in a prolonged half-life of circulating ReHV, an increase in the amount of ReHV taken up by tissues and tumors, and, ultimately, an enhanced anticancer efficacy of systemically administered ReHV. Full article

The small GTPase Ras plays an important role in connecting external and internal signalling cues to cell fate in eukaryotic cells. As such, the loss of RAS regulation, localisation, or expression level can drive changes in cell behaviour and fate. Post-translational modifications and expression levels are crucial to ensure Ras localisation, regulation, function, and cell fate, exemplified by RAS mutations and gene duplications that are common in many cancers. Here, we reveal that excessive production of yeast Ras2, in which the phosphorylation-regulated serine at position 225 is replaced with alanine or glutamate, leads to its mislocalisation and constitutive activation. Rather than inducing cell death, as has been widely reported to be a consequence of constitutive Ras2 signalling in yeast, the overexpression of RAS2^S225A or RAS2^S225E alleles leads to slow growth, a loss of respiration, reduced stress response, and a state of quiescence. These effects are mediated via cAMP/PKA signalling and transcriptional changes, suggesting that quiescence is promoted by an uncoupling of cell-cycle regulation from metabolic homeostasis. The quiescent cell fate induced by the overexpression of RAS2^S225A or RAS2^S225E could be rescued by the deletion of CUP9, a suppressor of the dipeptide transporter Ptr2, or the addition of peptone, implying that a loss of metabolic control, or a failure to pass a metabolic checkpoint, is central to this altered cell fate. Our data suggest that the combination of an increased RAS2 copy number and a dominant active mutation that leads to its mislocalisation can result in growth arrest and add weight to the possibility that approaches to retarget RAS signalling could be employed to develop new therapies. Full article

We investigated the anticancer efficacy, blood clearance, and tissue biodistribution of systemically administered retargeted oncolytic herpes simplex viruses (ReHVs) in HSV-naïve and HSV-preimmunized (HSV-IMM) mice. Efficacy was tested against lung tumors formed upon intravenous administration of cancer cells, a model of metastatic disease, and against subcutaneous distant tumors. In naïve mice, HER2- and hPSMA-retargeted viruses, both armed with mIL-12, were highly effective, even when administered to mice with well-developed tumors. Efficacy was higher for combination regimens with immune checkpoint inhibitors. A significant amount of infectious virus persisted in the blood for at least 1 h. Viral genomes, or fragments thereof, persisted in the blood and tissues for days. Remarkably, the only sites of viral replication were the lungs of tumor-positive mice and the subcutaneous tumors. No replication was detected in other tissues, strengthening the evidence of the high cancer specificity of ReHVs, a property that renders ReHVs suitable for systemic administration. In HSV-IMM mice, ReHVs administered at late times failed to exert anticancer efficacy, and the circulating virus was rapidly inactivated. Serum stability and in vivo whole blood stability assays highlighted neutralizing antibodies as the main factor in virus inactivation. Efforts to deplete mice of the neutralizing antibodies are ongoing. Full article

The effects SARS-CoV-2 inflicts on human physiology, especially in patients who developed COVID-19, can range from flu-like symptoms to death, and although many lives have been lost during the pandemic, others have faced the resolution of aggressive neoplasms that once proclaimed a poor prognosis following traditional treatments. The purpose of this review was to analyze several fortunate case reports and their associated biomolecular pathways to further explore new avenues that might provide oncological treatments in the future of medicine. We included papers that discussed cases in which patients affected by COVID-19 suffered beneficial changes in their cancer status. Multiple mechanisms which elicited a reactivation of the host’s immune system included cross-reactivity with viral antigens and downregulation of neoplastic cells. We were able to identify important cases presenting the resolution/remission of different aggressive neoplasms, for which most of the time, standard-of-care treatments offered little to no prospect towards a cure. The intricacy of the defense mechanisms humans have adopted against cancer cells through the millennia are still not well understood, but SARS-CoV-2 has demonstrated that the same ruinous cytokine storm which has taken so many lives can paradoxically be the answer we have been looking for to recalibrate the immunological system to retarget and vanquish malignancies. Full article

Analog IC design is characterized by non-systematic re-design iterations, often requiring partial or complete layout re-design. The layout task usually starts with device placement, where the several performance figures and constraints to be met escalate its complexity immensely, and, due to the inherent tradeoffs, an “optimal” floorplan solution does not usually exist. Deep learning models are now establishing for the automation of the placement task of analog integrated circuit layout design, promising to bypass the limitations of existing approaches based on: time-consuming optimization processes with several constraints; or placement retargeting from legacy designs/templates, which rely heavily on legacy layout data. However, as the complexity of analog design cases tackled by these methodologies increases, a broader set of topological constraints must be supported to cover the different layout styles and circuit classes. Here, model-independent differentiable encodings for regularity, boundary, proximity, and symmetry island constraints are formulated for the first time in the literature, and an unsupervised loss function is used for the artificial neural network model to learn how to generate placements that follow them. The use of a deep learning model makes push-button speed placement generation possible, additionally, as only sizing data are required for its training, it discards the need to acquire legacy layouts containing insights into this vast set of, often neglected, constraints. The model is ultimately used to produce floorplans from scratch at push-button speed for real state-of-the-art analog structures, including technology nodes not used for training. A case-study comparison with a floorplan design made by a human-expert presents improvements in the fulfillment of every constraint, reaching an overall improvement of around 70%, demonstrating the approach’s value in placement design. Full article

The electroencephalogram (EEG) can objectively reflect the emotional state of human beings, and has attracted much attention in the academic circles in recent years. However, due to its weak, non-stationary, and low signal-to-noise properties, it is inclined to cause noise in the collected EEG data. In addition, EEG features extracted from different frequency bands and channels usually exhibit different levels of emotional expression abilities in emotion recognition tasks. In this paper, we fully consider the characteristics of EEG and propose a new model RSRRW (retargeted semi-supervised regression with robust weights). The advantages of the new model can be listed as follows. (1) The probability weight is added to each sample so that it could help effectively search noisy samples in the dataset, and lower the effect of them at the same time. (2) The distance between samples from different categories is much wider than before by extending the $ϵ$-dragging method to a semi-supervised paradigm. (3) Automatically discover the EEG emotional activation mode by adaptively measuring the contribution of sample features through feature weights. In the three cross-session emotion recognition tasks, the average accuracy of the RSRRW model is 81.51%, which can be seen in the experimental results on the SEED-IV dataset. In addition, with the support of the Friedman test and Nemenyi test, the classification of RSRRW model is much more accurate than that of other models. Full article

Player pose estimation is particularly important for sports because it provides more accurate monitoring of athlete movements and performance, recognition of player actions, analysis of techniques, and evaluation of action execution accuracy. All of these tasks are extremely demanding and challenging in sports that involve rapid movements of athletes with inconsistent speed and position changes, at varying distances from the camera with frequent occlusions, especially in team sports when there are more players on the field. A prerequisite for recognizing the player’s actions on the video footage and comparing their poses during the execution of an action is the detection of the player’s pose in each element of an action or technique. First, a 2D pose of the player is determined in each video frame, and converted into a 3D pose, then using the tracking method all the player poses are grouped into a sequence to construct a series of elements of a particular action. Considering that action recognition and comparison depend significantly on the accuracy of the methods used to estimate and track player pose in real-world conditions, the paper provides an overview and analysis of the methods that can be used for player pose estimation and tracking using a monocular camera, along with evaluation metrics on the example of handball scenarios. We have evaluated the applicability and robustness of 12 selected 2-stage deep learning methods for 3D pose estimation on a public and a custom dataset of handball jump shots for which they have not been trained and where never-before-seen poses may occur. Furthermore, this paper proposes methods for retargeting and smoothing the 3D sequence of poses that have experimentally shown a performance improvement for all tested models. Additionally, we evaluated the applicability and robustness of five state-of-the-art tracking methods on a public and a custom dataset of a handball training recorded with a monocular camera. The paper ends with a discussion apostrophizing the shortcomings of the pose estimation and tracking methods, reflected in the problems of locating key skeletal points and generating poses that do not follow possible human structures, which consequently reduces the overall accuracy of action recognition. Full article

Selective gene delivery to a cell type of interest utilizing targeted lentiviral vectors (LVs) is an efficient and safe strategy for cell and gene therapy applications, including chimeric antigen receptor (CAR)-T cell therapy. LVs pseudotyped with measles virus envelope proteins (MV-LVs) have been retargeted by ablating binding to natural receptors while fusing to a single-chain antibody specific for the antigen of choice. However, the broad application of MV-LVs is hampered by the laborious LV engineering required for every new target. Here, we report the first versatile targeting system for MV-LVs that solely requires mixing with biotinylated adapter molecules to enable selective gene transfer. The analysis of the selectivity in mixed cell populations revealed transduction efficiencies below the detection limit in the absence of an adapter and up to 5000-fold on-to-off-target ratios. Flexibility was confirmed by transducing cell lines and primary cells applying seven different adapter specificities in total. Furthermore, adapter mixtures were applied to generate CAR-T cells with varying CD4/CD8-ratios in a single transduction step. In summary, a selective and flexible targeting system was established that may serve to improve the safety and efficacy of cellular therapies. Compatibility with a wide range of readily available biotinylated molecules provides an ideal technology for a variety of applications. Full article