The mishandling of robot raises ethical concerns about how we treat lifelike machines.
A livestream showing an influencer mishandling a $70K Unitree G1 humanoid robot sparks debate on ethics and human behavior towards machines.
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RNA sequencing has emerged as a powerful tool for detecting various types of cancers and gaining a deeper understanding of tumor biology.
However, many samples used in these analyses are derived from tumor tissues preserved as formalin-fixed paraffin-embedded (FFPE) blocks. While FFPE blocks are excellent for histological examination, they pose significant challenges for molecular analysis due to the potential degradation or crosslinking of genetic material.
This application note describes the use of targeted custom RNA panels to overcome these challenges by enabling the robust and sensitive detection of gene expression profiles from FFPE non-small cell lung cancer samples.
Very interesting paper by Lindley et al. showing that two mRNAs can be spliced together with extremely high efficiency using an optimized ribozyme system, allowing expression of large genes after dual-AAV delivery for treatment of muscular dystrophies. #genetherapy #biotech #synbio
Ribozymes are small catalytic RNA sequences capable of nucleotide-specific self-cleavage found widespread in nature. Ribozyme cleavage generates distinct 2′, 3′-phosphate and 5′-hydroxyl termini that resemble substrates for recently characterized RNA repair pathways in cells. We report that ribozyme cleavage of two separate mRNAs activated their scarless trans-ligation and translation into full-length protein in eukaryotic cells, a process that we named StitchR (for Stitch RNA). Optimization of StitchR activity in mammalian cells resulted in a ~900-fold increase in protein expression that approached levels observed for genes expressed from single vectors. We demonstrate that StitchR can be harnessed for effective dual adeno-associated virus gene therapies to correct muscular dystrophies by restoring large functional muscle proteins to endogenous levels in vivo.
Simultaneous measurements of the optical force and power exerted by a collimated laser beam on a 50-nm-thick silicon nitride lightsail membrane suspended by compliant micromechanical springs quantify the radiation pressure, enabling further multiphysics studies of radiation pressure forces on macroscopic objects.
Latest data shows which counties have been hardest hit by bird flu outbreaks among poultry flocks as the human case count climbs.
This may be a global pandemic it is even suspected to hit the USA.
Dengue is sometimes known as “breakbone fever” – a description that resonated with Braga. “I consider myself to have a high pain tolerance, but the pain was so intense.”
She needed hospital treatment, after deteriorating to the point that she was vomiting and could no longer eat or drink. “Even after being hospitalised for five days, I only gradually started getting better. The fatigue, in particular, didn’t leave me for about 15 days,” she says.
The World Health Organization estimates that 4 billion people are at risk of dengue and related viruses, rising to 5 billion by 2050. The rapid spread over recent years is “an alarming trend”, says WHO director general Dr Tedros Adhanom Ghebreyesus.
Their method scrambles laser beams into chaotic patterns, making decryption impossible without a trained neural network. This innovation could revolutionize cryptography.
Holograms for Next-Level Encryption
As the demand for digital security grows, researchers have developed a new optical system that uses holograms to encode information, creating a level of encryption that traditional methods cannot penetrate. This advance could pave the way for more secure communication channels, helping to protect sensitive data.
Dr James Cooke, PhD trained is a neuroscientist, speaker, and writer. He holds three degrees from Oxford University (a PhD and Masters in Neuroscience & a BA in Experimental Psychology). He has conducted scientific research for over a decade at institutions such as Oxford University, University of California, Berkeley, University College London, Trinity College Dublin, and Riken Brain Sciences Institute in Tokyo. James is the author of The Dawn of Mind: How Matter Became Conscious and Alive (2024), which synthesizes science and spiritual insight to offer a radical solution to the Hard Problem of Consciousness. He is the founder of the \.
TISR or video SR (VSR) neural network models are designed to leverage temporal neighbor frames to assist the SR of the current frame and are, therefore, expected to achieve better performance than SISR models19 (Supplementary Note 1). Although TISR models have been widely explored in natural image SR to improve video definition, whether such models can be applied to super-resolve biological images (that is, enhancing both sampling rate and optical resolution) has been poorly investigated. Here, we used the total internal reflection fluorescence (TIRF) SIM, grazing incidence (GI) SIM and nonlinear SIM20 modes of our home-built Multi-SIM system to acquire an extensive TISR dataset of five different biological structures: clathrin-coated pits (CCPs), lysosomes, outer mitochondrial membranes (Mitos), microtubules (MTs) and F-actin filaments (Extended Data Fig. 1). For each type of specimen, we generally acquired over 50 sets of raw SIM images with 20 consecutive time points at 2–4 levels of excitation light intensity (Methods). Each set of raw SIM images was averaged out to a diffraction-limited wide-field (WF) image sequence and was used as the network input, while the raw SIM images acquired at the highest excitation level were reconstructed into SR-SIM images as the ground truth (GT) used in network training. In particular, the image acquisition configuration was modified into a special running order where each illumination pattern is applied 2–4 times at escalating excitation light intensity before changing to the next phase or orientation, so as to minimize the motion-induced difference between WF inputs and SR-SIM targets.
To effectively use the temporal continuity of time-lapse data, SOTA TISR neural networks consist of mainly two important components21,22: temporal information propagation and neighbor feature alignment. We selected two popular types of propagation approaches, sliding window (Fig. 1a) and recurrent network (Fig. 1b), and three representative neighbor feature alignment mechanisms, explicit warping using OF15 (Fig. 1c) and implicit alignment by nonlocal attention23,24 (NA; Fig. 1d) or deformable convolution21,25,26 (DC; Fig. 1e), resulting in six combinations in total. For fair comparison, we custom-designed a general TISR network architecture composed of a feature extraction module, a propagation and alignment module and a reconstruction module (Extended Data Fig. 2) and kept the architecture of the feature extraction module and reconstruction module unchanged while only modifying the propagation and alignment module during evaluation (Methods). We then examined the six models on five different data types: linear SIM data of MTs, lysosomes and Mito, three of the most common biological structures in live-cell experiments, nonlinear SIM data of F-actin, which is of the highest structural complexity and upscaling factor in BioTISR, and simulated data of tubular structure with infallible GT references (Supplementary Note 2). As is shown in Fig. 1f, Extended Data Fig. 3 and Supplementary Fig. 2, all models denoised and sharpened the input noisy WF image evidently, among which the model constructed with a recurrent scheme and DC alignment resolved the finest details compared to the GT-SIM image (indicated by white arrows in Fig. 1f). Furthermore, we calculated time-lapse correlation matrices (Fig. 1g) and image fidelity metrics (Fig. 1h–j) (that is, peak SNR (PSNR) and structural similarity (SSIM)) for the output SR images to quantitatively evaluate the temporal consistency and reconstruction fidelity, respectively. According to the evaluation, we found that recurrent network-based propagation (RNP) outperformed sliding window-based propagation (SWP) in both temporal consistency and image fidelity with fewer trainable parameters (Methods) and propagation mechanisms had little effect on the temporal consistency of the reconstructed SR time-lapse data, while the DC-based alignment generally surpassed the other two mechanisms with a similar number of parameters for all types of datasets (Supplementary Fig. 3).
The risk of a stroke may be increased by a common bacteria found in the mouth and gut, suggests a new study.
Higher levels of Streptococcus anginosus were found in the gut of recent stroke survivors in Japan.
Stroke patients with a significant amount of the bacteria in their gut were more likely to die or have another major cardiovascular event within two years than stroke patients without Streptococcus anginosus in the gut.