Researchers from King Abdullah University of Science and Technology (KAUST) have developed deepBlastoid, the first deep-learning platform specifically designed for the high-throughput, automated classification of human stem cell-derived embryo models (blastoids). By leveraging a ResNet-18 architecture and a novel Confidence Rate metric, the model achieves up to 97% accuracy and processes images 1,000 times faster than human experts. This tool facilitates large-scale drug screening and basic research into early human development by providing a standardized, objective evaluation framework.

Cardiovascular diseases (CVDs) remain a leading cause of global morbidity and mortality, with significant residual risk unexplained by traditional factors. The discovery of novel therapeutic targets or the repurposing of existing drug targets could improve the prevention and treatment for different CVDs. However, previous studies have encountered different analytic challenges, such as failing to cover the whole spectrum of CVDs, not including cardiovascular magnetic resonance imaging (CMR) traits or lack of large-scale replication analysis and multidimensional downstream analysis.

Neurologist Dr. Varun Venkataramani (36) from Heidelberg University Hospital will be awarded the Paul Ehrlich and Ludwig Darmstaedter Early Career Award 2026, the Scientific Council of the Paul Ehrlich Foundation announced today. The prizewinner has fundamentally expanded our understanding of glioblastomas – particularly malignant brain tumors. They arise from glial cells, whose task is to protect and nourish nerve cells. Venkataramani discovered that glioblastomas hijack the nervous system to tap into electrical signals, which they then use to accelerate their deadly growth. A drug to interrupt this electrical activity is already being tested on patients.

A research team led by Professor Xiang David Li from the Department of Chemistry at The University of Hong Kong (HKU), in collaboration with researchers from the Shenzhen Bay Laboratory and Tsinghua University, has made a breakthrough in epigenetic drug discovery. The team has successfully developed a first-in-class chemical inhibitor that precisely and selectively targets the ATAC complex, a critical cellular “switch operator” that activates tumour-promoting genes, opening a novel therapeutic avenue for non-small cell lung cancer (NSCLC). The findings were recently published in the top-tier journal Nature Chemical Biology, and multiple international patent applications have been filed.

Seeing chemistry unfold inside living cells is one of the biggest challenges of modern bioimaging. Raman microscopy offers a powerful way to meet this challenge by reading the unique vibrational “signatures” of molecules. However, cells are extraordinarily complex environments filled with thousands of biomolecules. To make specific molecules stand out, researchers often attach small chemical “probes,” such as alkyne tags, that produce signals in a so-called cell-silent spectral window where native cellular components do not scatter light. This allows Raman microscopes to selectively detect the tagged molecules against an otherwise crowded molecular background. Despite this advantage, the widespread adoption of Raman microscopy in biology has been limited by one fundamental problem: Raman signals are extremely weak. In a new study published in Angewandte Chemie International Edition, TIFR researchers report a molecular design strategy that dramatically amplifies Raman signals, enabling the development of Raman sensors that can detect biomolecules using standard spontaneous Raman microscopes. These new Raman sensors enable sensitive, ratiometric imaging of biological molecules and ions, such as hydrogen peroxide molecules, copper ions, and pH, inside living cells. The work is supported by the Department of Atomic Energy, Government of India, and the Japan Science and Technology Agency, with the research team comprising Prof. Ankona Datta and Sujit Das from the Tata Institute of Fundamental Research, Mumbai, and Heqi Xi, Itsuki Yamamoto, and Prof. Katsumasa Fujita from the University of Osaka, Japan.

An international group of experts has developed new guidelines to help veterinarians better recognize and diagnose canine cognitive dysfunction syndrome (CCDS), commonly known as canine dementia. The condition affects many older dogs and can cause changes in behavior, sleep, learning, and daily routines, yet it is often overlooked despite its significant impact on animal welfare. The guidelines also highlight that research on canine dementia has the potential to contribute to our understanding of human dementia, particularly Alzheimer’s disease.