Researchers at the University of Electronic Science and Technology of China have developed a novel quantum algorithm that extends Grover's quadratic speedup to continuous search problems, including optimization and spectral analysis over infinite-dimensional spaces. The team rigorously proved the algorithm's optimality by establishing a matching lower bound on query complexity. They also proposed a general framework for constructing the required quantum oracle, enhancing adaptability to diverse applications.

The ability to analyze gene expression at the single-cell level — known as single-cell RNA sequencing (scRNA-seq) — has transformed life sciences, driving discoveries across immunology, oncology, and developmental biology. Over 40,000 studies have leveraged this technique to map the complex diversity of cells within tissues and organisms.

Yet beneath this explosive growth lies a persistent problem: clustering instability. When researchers attempt to group cells by expression patterns to identify cell types or disease states, they often face inconsistent results — even when analyzing the same dataset repeatedly.

Inaccurate clustering can lead to misclassifying normal cells as cancerous or missing rare but critical cell types — jeopardizing interpretation and therapeutic decisions. This “reliability crisis” forces scientists to rerun analyses or rely on computationally expensive pipelines to extract trustworthy insights.

Now, a research team led by Professor KIM Jae Kyoung of the Korea Advanced Institute of Science and Technology (KAIST) and the Institute for Basic Science (IBS) has developed a solution: a mathematical framework named scICE (single-cell Inconsistency Clustering Estimator).

Researchers from The University of Osaka have developed a method to visualize and reconstruct individual urban plants in different seasons using AI and street view images. The novel Seasonal Species-Specific Plant View Index allows urban designers to enhance the ecological sustainability and the well-being of city dwellers by incorporating diverse plant configurations, colors, and seasonality into current and future urban green spaces.

In August 2024, the World Health Organization declared a second “Public Health Emergency of International Concern” for mpox. The current outbreak in Africa is driven mainly by the clade I variant, with multiple countries reporting their first-ever mpox cases of this more severe strain. Nagoya University researchers and their collaborators have found that measuring the amount of virus in the blood when skin lesions first appear can help predict whether patients will experience mild or severe progression of the disease. The study analyzes viral loads during early infection to predict how sick patients will get, potentially improving treatment strategies for future outbreaks. 

Harvard scientists have described a particular movement observed mostly in young, teenaged anacondas, called an S-start. A mathematical model shows that young anacondas, as opposed to babies and adults, exist in a “goldilocks zone” of relative weight and strength to allow them to execute the movement.