A bilingual speech neuroprosthesis driven by cortical articulatory representations shared between languages

Bilingual Speech Neuroprosthesis Driven by Cortical Speech Representations Background In the development of neuroprostheses, research on decoding language from brain activity has primarily focused on decoding a single language. Thus, the extent to which bilingual speech production relies on unique or shared cortical activity between different langu...

Imaging Bioluminescence by Detecting Localized Haemodynamic Contrast from Photosensitized Vasculature

Imaging Bioluminescence by Detecting Localized Haemodynamic Contrast from Photosensitized Vasculature

Academic News Report: New MRI Technology Achieves Biological Fluorescence Imaging by Detecting Local Hemodynamics of Photosensitive Blood Vessels Academic Background Introduction Bioluminescent probes are widely used for monitoring biomedical processes and cellular targets in living animals. However, the absorption and scattering of visible light b...

Accelerating Diabetic Wound Healing by ROS-Scavenging Lipid Nanoparticle–mRNA Formulation

Accelerating Diabetic Wound Healing by ROS-Scavenging Lipid Nanoparticle–mRNA Formulation

Utilization of Lipid Nanoparticles-mRNA Formulations to Eliminate ROS and Accelerate Diabetic Wound Healing Diabetic wounds are common complications in patients with hyperglycemia, characterized by high incidence and recurrence rates, causing substantial global economic losses. Existing treatments, including wound offloading and growth factor thera...

Information-Based TMS to Mid-Lateral Prefrontal Cortex Disrupts Action Goals During Emotional Processing

Abstract In recent years, researchers have gradually recognized that contextual awareness and goal-directed responses to emotional events are crucial for adaptive functioning. Behavioral and emotional regulation models posit that the lateral prefrontal cortex (lpfc) maintains goal-related representations, thereby facilitating cognitive control. How...

Low-Intensity Ultrasound Ameliorates Brain Organoid Integration and Rescues Microcephaly Deficits

Low-intensity Ultrasound Promotes Brain Organoid Integration and Improves Microcephaly Defects Background of the Study Brain organoids are generated through the differentiation of pluripotent stem cells (PSCs) and exhibit impressive cellular diversity, capable of mimicking functional networks similar to the human brain. These organoid methods hold ...

Self-Supervised Deep Learning-Based Denoising for Diffusion Tensor MRI

Self-Supervised Deep Learning-Based Denoising for Diffusion Tensor MRI

Background Introduction Diffusion Tensor Magnetic Resonance Imaging (DTI) is a widely used neuroimaging technique for imaging the microstructure of brain tissues and white matter tracts. However, noise in Diffusion-Weighted Images (DWI) can reduce the accuracy of microstructural parameters derived from DTI data and also necessitate longer acquisiti...

Scalp nerve block alleviates headaches associated with sonication during transcranial magnetic resonance–guided focused ultrasound

In this academic paper, the authors attempt to address the common headache complication during magnetic resonance-guided focused ultrasound (mrgFUS) treatment. Headache is a common complication, and in severe cases, it may even cause patients to be unable to tolerate ultrasound radiation and terminate the treatment. There is currently no establishe...

A 5' UTR Language Model for Decoding Untranslated Regions of mRNA and Function Predictions

A 5' UTR Language Model for Decoding Untranslated Regions of mRNA and Function Predictions

The 5’ untranslated region (5’UTR) is a regulatory region at the start of messenger RNA (mRNA) molecules, playing a crucial role in regulating the translation process and affecting protein expression levels. Language models have demonstrated effectiveness in decoding protein and genomic sequence functions. In this study, the authors introduce a lan...

Hyperbolic secant representation of the logistic function: Application to probabilistic multiple instance learning for CT intracranial hemorrhage detection

There has long been a problem of “weak supervision” in the field of artificial intelligence, where only part of the labels are observable in the training data, while the remaining labels are unknown. Multiple Instance Learning (MIL) is a paradigm to address this issue. In MIL, the training data is divided into multiple “bags”, each containing multi...