The advent of quantum computers promises to revolutionize computing by solving complex problems exponentially more rapidly than classical computers. However, today’s quantum computers face challenges such as maintaining stability and transporting quantum information.
Phonons, which are quantized vibrations in periodic lattices, offer new ways to improve these systems by enhancing qubit interactions and providing more reliable information conversion. Phonons also facilitate better communication within quantum computers, allowing the interconnection of them in a network.
Nanophononic materials, which are artificial nanostructures with specific phononic properties, will be essential for next-generation quantum networking and communication devices. However, designing phononic crystals with desired vibration characteristics at the nano-and micro-scales remains challenging.
A team of scientists from the University of Sharjah say they have invented a biosensor capable of detecting the gene mutations responsible for the loss of hearing.
Advances in Care Podcast — Episode 24In today’s world, genetic testing has become increasingly accessible for more people, creating an increased opportunity…
This prospective, multimodal neuroimaging study systematically assessed both intracerebellar pathology and cerebrocerebellar connectivity alterations in a genetically stratified cohort of amyotrophic lateral sclerosis:
This single-center longitudinal cohort study has followed known carriers of PRNP pathogenic variants at risk for prion disease, individuals with a close relative who died of genetic prion disease but who have not undergone predictive genetic testing, and controls. All participants were asymptomatic at first visit and returned roughly annually. We determined PRNP genotypes, measured NfL and GFAP in plasma, and RT-QuIC, total PrP, NfL, T-tau, and beta-synuclein in CSF.
This study uncoversthe pivotal role of the enzyme METTL4 in promoting tumor metastasis through the mediation of nuclear N6-methyldeoxyadenosine (6mA) in mammalian cells. By utilizing cellular models, the study demonstrates how hypoxia induces METTL4 to mediate 6mA modifications. This process, in turn, activates genes essential for tumor metastasis, including the involvement of specific long noncoding RNA and a novel HIF-1α co-activator, ZMIZ1. These findings not only shed light on the epigenetic mechanisms driving tumor progression but also establish METTL4 as a prognostic marker for cancer and a potential target for therapeutic intervention. The promise of this discovery lies in its potential to inspire new strategies for combating hypoxia-induced tumor progression, opening avenues for further research and development in cancer treatment.
DNA N6-methyldeoxyadenosine (6mA) has been recognized in various organisms for its role in gene regulation. However, its function in mammalian cells, particularly in the context of cancer, has remained elusive. Previous studies have shown that 6mA modifications can influence gene expression and are present in several species, indicating a potential regulatory role in tumorigenesis. This research addresses a critical gap in understanding the nuclear role of 6mA and its enzymatic mediator METTL4, in mammalian tumor cells, particularly under hypoxia (a common condition in tumor microenvironments that promotes metastasis). The study posits that METTL4-mediated 6mA deposition is a key epigenetic modification that activates metastasis-inducing genes. This finding offers a new perspective on the mechanisms of tumor progression and identifying novel targets for therapeutic intervention.
According to recent World Health Organization statistics, cancer remains a leading cause of death globally, with metastatic cancers posing significant treatment challenges. This study’s revelations underscore the urgent need for novel therapeutic strategies to address the complex mechanisms of cancer metastasis. By linking the research findings to SDG 3, which aims to ensure healthy lives and promote well-being for all, the study highlights the potential for significant advancements in cancer treatment. Ultimately, the study paves the way for improved health outcomes and underscores the importance of continued investment in research and development to combat the global cancer burden.
Building a conscious robot is a grand scientific and technological challenge. Debates about the possibility of conscious robots and the related positive outcomes and hazards for human beings are today no more confined to philosophical circles. Robot consciousness is a research field aimed to a unified view of approaches as cognitive robotics, epigenetic and affective robotics, situated and embodied robotics, developmental robotics, anticipatory systems, biomimetic robotics. Scholars agree that a conscious robot would completely change the current views on technology: it would not be an “intelligent companion” but a complete novel kind of artifact. Notably, many neuroscientists involved in the study of consciousness do not exclude this possibility. Moreover, facing the problem of consciousness in robots may be a major move on the study of consciousness in humans and animals.
Aussie scientists have developed a new gene-editing technique that could be a major breakthrough. It could allow scientists to make accurate and more significant changes to DNA.
A team led by NCI researchers has developed an artificial intelligence (AI) tool that uses data from individual cells inside tumors to predict whether a person’s cancer will respond to a specific drug. Learn more about how these findings hold promise for optimally matching cancer drugs to patients:
Precision oncology, in which doctors choose cancer treatment options based on the underlying molecular or genetic signature of individual tumors, has come a long way. The Food and Drug Administration has approved a growing number of tests that look for specific genetic changes that drive cancer growth to match patients to targeted treatments. The NCI-MATCH trial, supported by the National Cancer Institute, in which participants with advanced or rare cancer had their tumors sequenced in search of genetic changes that matched them to a treatment, has also suggested benefits for guiding treatment through genetic sequencing. But there remains a need to better predict treatment responses for people with cancer.
A promising approach is to analyze a tumor’s RNA in addition to its DNA. The idea is to not only better understand underlying genetic changes, but also learn how those changes impact gene activity as measured by RNA sequencing data. A recent study introduces an artificial intelligence (AI)-driven tool, dubbed PERCEPTION (PERsonalized single-Cell Expression-based Planning for Treatments In ONcology), developed by an NIH-led team to do just this.1 This proof-of-concept study, published in Nature Cancer, shows that it’s possible to fine-tune predictions of a patient’s treatment responses from bulk RNA data by zeroing in on what’s happening inside single cells.
One of the challenges in relying on bulk data from tumor samples is they typically include mixtures of like cells known as clones. Because different clones may respond differently to specific drugs, averaging what’s happening in cells across a particular patient’s tumor may not provide a clear picture of how that cancer will respond to a drug. Being able to capture gene activity patterns all the way down to the single-cell level might be a better way to target clones with specific alterations and therefore see better drug responses, but so far, single-cell gene expression data haven’t been widely available.
This may be about as wildly entertaining, disruptive and philosophically profound as legitimate scientific research gets. Michael Levin’s work in cellular intelligence, bioelectrical communication and embodied minds “is going to overturn everything.”
