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Researchers have discovered new connections between the gut and brain that hold promise for more targeted treatments for depression and anxiety, and could help prevent digestive issues in children by limiting the transmission of antidepressants during pregnancy.

The study, published in the journal Gastroenterology, shows that increasing serotonin in the gut epithelium—the thin layer of cells lining the small and large intestines—improves symptoms of anxiety and depression in animal studies. The researchers also found that, in humans, antidepressant use during increases the risk of babies developing constipation in the first year of life.

“Our findings suggest that there may be an advantage to targeting antidepressants selectively to the gut epithelium, as systemic treatment may not be necessary for eliciting the drugs’ benefits but may be contributing to digestive issues in children exposed during pregnancy,” said Kara Margolis, director of the NYU Pain Research Center and associate professor of molecular pathobiology at NYU College of Dentistry, who co-led the study with Mark Ansorge, associate professor of clinical neurobiology at Columbia University.

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NASA’s James Webb Space Telescope (JWST) has for the first time captured an image of what our galaxy likely looked like just as it was forming — and it’s got space scientists feeling very Christmassy.

“I just love the sparkle galaxy with its Christmas lights shining as it was when the Universe was just 600 million years old,” Prof Catherine Heymans, Scotland’s Astronomer Royal, told BBC News.

The image shows ten balls of stars of different colours, appearing like Christmas tree baubles hanging in the cosmos.

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HighlyCitedPapers.

📝 — Schulze, et al.

The present work reviews the strategies and technical approaches used to overcome the multilayered problems associated with large bone defect healing in long bones, with emphasis on research rooted in scaffold-guided tissue regeneration.

Full text is available 👇

Continue reading “Scaffold Guided Bone Regeneration for the Treatment of Large Segmental Defects in Long Bones” | >

HighlyCitedPapers.

📝 The Many Faces of Immune Activation in HIV-1 Infection: A Multifactorial Interconnection — Mazzuti, et al.

Full text is available 👇

Ovarian cancer (OC) is the leading cause of death from gynecological malignancies. Despite great advances in treatment strategies, therapeutic resistance and the gap between preclinical data and actual clinical efficacy justify the necessity of developing novel models for investigating OC. Organoids represent revolutionary three-dimensional cell culture models, deriving from stem cells and reflecting the primary tissue’s biology and pathology. The aim of the current review is to study the current status of mouse-and patient-derived organoids, as well as their potential to model carcinogenesis and perform drug screenings for OC.

Continue reading “Patient-Derived Organoids: The Beginning of a New Era in Ovarian Cancer Disease Modeling and Drug Sensitivity Testing” | >

Dyson spheres and rings have always held a special fascination for me. The concept is simple: build a great big structure either as a sphere or ring to harness the energy from a star. Dyson rings are far more simple and feasible to construct and in a recent paper a team of scientists explore how we might detect them by analyzing the light from distant stars. The team suggests they might be able to detect Dyson rings around pulsars using their new technique.

Like their spherical cousins, Dyson rings remain for now, a popular idea in yet they are starting to appear more and more in scientific debates. The concept of the ring is similar to the sphere, a megastructure designed to encircle a star, harnessing its energy on a gargantuan scale.

It might consist of a series of satellites or even habitats in a with solar collectors and unlike the spheres, require far less resources to build. The concept of the sphere was first proposed by physicist and mathematician Freeman Dyson in 1960. Such structures might be detectable and reveal the existence of intelligent civilizations.

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As our devices multiply and data demands grow, traditional wireless systems are hitting their limits. To meet these challenges, we have turned to an innovative solution. At the University of Melbourne and Monash University, we have developed a dual-carrier Modular Optical Phased Array (MOPA) communication system. At the core of our innovation is a groundbreaking concept: a modular phased array.

This design is inspired by the quantum superposition principle, applying its logic to enhance technical performance and efficiency. This cutting-edge technology is designed to make indoor wireless networks faster, more reliable and more secure, while addressing the limitations of traditional systems. Our research is published in the IEEE Open Journal of the Communications Society.

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Land cover classification (LCC) of heterogeneous mining areas is important for understanding the influence of mining activities on regional geo-environments. Hyperspectral remote sensing images (HSI) provide spectral information and influence LCC. Convolutional neural networks (CNNs) improve the performance of hyperspectral image classification with their powerful feature learning ability. However, if pixel-wise spectra are used as inputs to CNNs, they are ineffective in solving spatial relationships. To address the issue of insufficient spatial information in CNNs, capsule networks adopt a vector to represent position transformation information. Herein, we combine a clustering-based band selection method and residual and capsule networks to create a deep model named ResCapsNet. We tested the robustness of ResCapsNet using Gaofen-5 Imagery. The images covered two heterogeneous study areas in Wuhan City and Xinjiang Province, with spatially weakly dependent and spatially basically independent datasets, respectively. Compared with other methods, the model achieved the best performances, with averaged overall accuracies of 98.45 and 82.80% for Wuhan study area, and 92.82 and 70.88% for Xinjiang study area. Four transfer learning methods were investigated for cross-training and prediction of those two areas and achieved good results. In summary, the proposed model can effectively improve the classification accuracy of HSI in heterogeneous environments.

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