News
AI sperm checker could ‘enhance’ IVF success, research suggests
A new AI technology could assess the quality of live sperm in seconds, removing the need for invasive procedures that compromise sperm viability in IVF treatments.
Current clinical practices to evaluate sperm morphology require human analysis and chemical staining of the sperm cells which can cause damage.
However, a new method, from Monash University’s Department of Mechanical and Aerospace Engineering in collaboration with Monash IVF, works on live, unstained sperm, preserving their viability.
The study, published in Advanced Intelligent Systems, found the AI model could analyse sperm imaging with over 93 per cent accuracy in just a few seconds. By choosing the highest quality sperm without affecting its viability, the technology could pave the way for standardised sperm selection through automation in IVF clinical settings.
Lead researcher Dr Reza Nosrati said the speed and precision meant doctors could make better-informed decisions faster than ever before.
“The consistency and reliability of our AI model provide unprecedented accuracy in live sperm morphology classification,” Nosrati explained.
“By providing a clear and precise analysis of sperm quality, it offers promising opportunities for enhancing clinical sperm selection practices and reducing day-to-day variability in clinics.
“With this tool, we hope to improve the outcomes of fertility treatments and offer new hope to couples struggling to conceive.”
Ms Sahar Shahali, lead-author of the work and the PhD candidate, said the technology’s adaptability made it a versatile tool for clinics worldwide.
“The technology has been tested and proven to work effectively with images of various resolutions. This means it can be easily integrated into different clinical environments, providing reliable results regardless of the equipment used.”
Professor Deirdre Zander-Fox, Monash IVF chief scientific officer, said the technology had great potential to make the sperm selection process faster and improve outcomes.
“Sometimes in IVF, embryologists need to inject a single sperm directly into an egg to increase the chances of fertilisation.
“While they are experts at finding the best sperm for this process – sperm that’s the right shape and size and moves around freely – it can sometimes take hours to sift through a sample to find the best sperm for injection,” Zander-Fox said.
“We believe AI can make the process much faster and give patients improved outcomes, while still allowing our highly trained embryologists to have oversight of the process.”
She added: “Following on from this research, Monash IVF hopes to create an AI algorithm that could be used to power a sperm selection device to guide our embryologist on which sperm to choose at the time of microinjection to help improve IVF outcomes.”
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Diagnosis
Lung cancer drug shows breast cancer potential
Ovarian cancer cells quickly activate survival responses after PARP inhibitor treatment, and a lung cancer drug could help block this, research suggests.
PARP inhibitors are a common treatment for ovarian cancer, particularly in tumours with faulty DNA repair. They stop cancer cells fixing DNA damage, which leads to cell death, but many tumours later stop responding.
Researchers identified a way cancer cells may survive PARP inhibitor treatment from the outset, pointing to a potential way to block that response. A Mayo Clinic team found ovarian cancer cells rapidly switch on a pro-survival programme after exposure to PARP inhibitors. A key driver is FRA1, a transcription factor (a protein that turns genes on and off) that helps cancer cells adapt and avoid death.
The team then tested whether brigatinib, a drug approved for certain lung cancers, could block this response and boost the effect of PARP inhibitors. Brigatinib was chosen because it inhibits multiple signalling pathways involved in cancer cell survival.
In laboratory studies, combining brigatinib with a PARP inhibitor was more effective than either treatment alone. Notably, the effect was seen in cancer cells but not normal cells, suggesting a more targeted approach.
Brigatinib also appeared to act in an unexpected way. Rather than working through the usual DNA repair routes, it shut down two signalling molecules, FAK and EPHA2, that aggressive ovarian cancer cells rely on. FAK and EPHA2 are proteins that relay survival signals inside cells. Blocking both at once weakened the cells’ ability to adapt and resist treatment, making them more vulnerable to PARP inhibitors.
Tumours with higher levels of FAK and EPHA2 responded better to the drug combination. Other data link high levels of these molecules to more aggressive disease, pointing to potential benefit in harder-to-treat cases.
Arun Kanakkanthara, an oncology investigator at Mayo Clinic and a senior author of the study, said: “This work shows that drug resistance does not always emerge slowly over time; cancer cells can activate survival programmes very early after treatment begins.”
John Weroha, a medical oncologist at Mayo Clinic and a senior author of the study, said: “From a clinical perspective, resistance remains one of the biggest challenges in treating ovarian cancer. By combining mechanistic insights from Dr Kanakkanthara’s laboratory with my clinical experience, this preclinical work supports the strategy of targeting resistance early, before it has a chance to take hold. This strategy could improve patient outcomes.”
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