48 research outputs found

    CovidCTNet: an open-source deep learning approach to diagnose covid-19 using small cohort of CT images

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    Coronavirus disease 2019 (Covid-19) is highly contagious with limited treatment options. Early and accurate diagnosis of Covid-19 is crucial in reducing the spread of the disease and its accompanied mortality. Currently, detection by reverse transcriptase-polymerase chain reaction (RT-PCR) is the gold standard of outpatient and inpatient detection of Covid-19. RT-PCR is a rapid method; however, its accuracy in detection is only ~70�75. Another approved strategy is computed tomography (CT) imaging. CT imaging has a much higher sensitivity of ~80�98, but similar accuracy of 70. To enhance the accuracy of CT imaging detection, we developed an open-source framework, CovidCTNet, composed of a set of deep learning algorithms that accurately differentiates Covid-19 from community-acquired pneumonia (CAP) and other lung diseases. CovidCTNet increases the accuracy of CT imaging detection to 95 compared to radiologists (70). CovidCTNet is designed to work with heterogeneous and small sample sizes independent of the CT imaging hardware. To facilitate the detection of Covid-19 globally and assist radiologists and physicians in the screening process, we are releasing all algorithms and model parameter details as open-source. Open-source sharing of CovidCTNet enables developers to rapidly improve and optimize services while preserving user privacy and data ownership. © 2021, The Author(s)

    Enhancing cancer immunotherapy using antiangiogenics: opportunities and challenges.

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    Immunotherapy has emerged as a major therapeutic modality in oncology. Currently, however, the majority of patients with cancer do not derive benefit from these treatments. Vascular abnormalities are a hallmark of most solid tumours and facilitate immune evasion. These abnormalities stem from elevated levels of proangiogenic factors, such as VEGF and angiopoietin 2 (ANG2); judicious use of drugs targeting these molecules can improve therapeutic responsiveness, partially owing to normalization of the abnormal tumour vasculature that can, in turn, increase the infiltration of immune effector cells into tumours and convert the intrinsically immunosuppressive tumour microenvironment (TME) to an immunosupportive one. Immunotherapy relies on the accumulation and activity of immune effector cells within the TME, and immune responses and vascular normalization seem to be reciprocally regulated. Thus, combining antiangiogenic therapies and immunotherapies might increase the effectiveness of immunotherapy and diminish the risk of immune-related adverse effects. In this Perspective, we outline the roles of VEGF and ANG2 in tumour immune evasion and progression, and discuss the evidence indicating that antiangiogenic agents can normalize the TME. We also suggest ways that antiangiogenic agents can be combined with immune-checkpoint inhibitors to potentially improve patient outcomes, and highlight avenues of future research

    Bioinspired hydrogels build a bridge from bench to bedside

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    During million years, Nature has created a �wealthy repertoire of novel features.� These features are frequently used in the fabric of artificial materials, referred to as �biomaterials.� Hydrogels are among the most attractive biomaterials because they are highly amenable to accept nature-derived properties/functionalities. The inclusion of these features in biomaterials serves as promising tools for today's most urged clinical needs, among others. In this review, we explore the major applications of different bioinspired hydrogels. We focused on rationale design, multi-faceted biomimetics strategies, and their potentials utility in the clinic. For the clinical application, we focused on four major clinical areas of i) regenerative medicine, ii) tissue engineering, iii) cancer therapy, and iv) bioinspired devices/actuators/robots. We discussed how incorporating nature-inspired properties into hydrogels� design can introduce novel solutions to the many unresolved and persistent problems in biomedicine. Finally, given the complexity of bioinspired hydrogels, we propose that a collective effort among the material scientists, artificial intelligence experts, clinicians, and life sciences is required to pave the path for the entrance of bioinspired hydrogel into personalized medicine and from bench to bedside. © 202

    Cancer cells induce metastasis-supporting neutrophil extracellular DNA traps

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    Neutrophils, the most abundant type of leukocytes in blood, can form neutrophil extracellular traps (NETs). These are pathogen-trapping structures generated by expulsion of the neutrophil's DNA with associated proteolytic enzymes. NETs produced by infection can promote cancer metastasis. We show that metastatic breast cancer cells can induce neutrophils to form metastasis-supporting NETs in the absence of infection. Using intravital imaging, we observed NET-like structures around metastatic 4T1 cancer cells that had reached the lungs of mice. We also found NETs in clinical samples of triple-negative human breast cancer. The formation of NETs stimulated the invasion and migration of breast cancer cells in vitro. Inhibiting NET formation or digesting NETs with deoxyribonuclease I (DNase I) blocked these processes. Treatment with NET-digesting, DNase I-coated nanoparticles markedly reduced lung metastases in mice. Our data suggest that induction of NETs by cancer cells is a previously unidentified metastasis-promoting tumor-host interaction and a potential therapeutic target
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