News | Page 2 | The Biomedical Scientist Magazine of the IBMS

Tech news: January 2022

This month's top tech news stories

Fighting blood diseases with artificial intelligence

A team from Helmholtz Munich has developed the largest open access database on microscopic images of bone marrow cells to date. It consists of more than 170,000 single-cell images from over 900 patients with various blood diseases.

Under the microscope: AB569 AD Bactericidal Agent

This month: AB569 Bactericidal Agent

Detecting tumour cell death after novel therapy

Recently, a promising therapeutic virus that selectively kills cancer cells while sparing normal tissue has sparked hope for treating aggressive brain tumours.

30 minute UTI test

Every year, over 100 million people are diagnosed with UTIs, with the infections responsible for more than 22% of the UK’s antibiotic prescriptions.

Interactive COVID-19 risk tool

Based on estimates provided by 26 international experts, the graphic shows the different pathways that may be taken by the virus that causes COVID-19 when it transfers between two people.

An optoacoustic endoscopic probe

Optoacoustic imaging is a promising diagnostic technique that could find applications in a range of screening tasks.

Diagnosing children’s cancer in the pandemic

The research, which was presented at the National Cancer Research Institute Festival, also shows that children who were diagnosed with cancer during the first wave of the pandemic were mo

Microbiology & Virology

Under the microscope: Fomitopsis officinalis

What is Fomitopsis officinalis?

Immunology

New approach for ovarian cancer treatment?

In new research, scientists reveal how certain cells drive immunotherapy resistance in a mouse model of ovarian cancer and show that targeting a signalling pathway in these cells improved

Molecular Pathology & Genomics

Emergency department risk calculator

In a collaborative project between University Hospitals of North Midlands (UHNM) NHS Trust and Staffordshire University, experts have developed a prediction model to identify patients mos