Oestrogen helps protect premenopausal women from hypertension by relaxing and widening blood vessels, according to new research examining why women develop high blood pressure less often before menopause.

High blood pressure, also known as hypertension, affects more than a billion people worldwide and is a leading cause of heart disease and stroke.

Premenopausal women are less likely to develop the condition than men or postmenopausal women, but the biological reason has been unclear.

Researchers used a mathematical model of the cardiovascular and kidney systems to analyse how oestrogen influences blood pressure.

The analysis found that oestrogen’s strongest protective effect comes from vasodilation, the process by which blood vessels relax and widen, helping blood flow more easily and lowering pressure in the arteries.

Anita Layton, Canada 150 Research Chair Laureate in Mathematical Biology and Medicine and professor of applied mathematics, said: “Oestrogen is often thought of only in terms of reproductive health, but it plays a much broader role in how the body functions.

“It affects how blood vessels respond, how the kidneys regulate fluids and how different systems communicate with one another.

“What we found is that its impact on blood vessels is especially important for regulating blood pressure.”

The findings may also have implications for treating women after menopause, when oestrogen levels naturally decline.

The model predicted that angiotensin receptor blockers, a common class of blood pressure drugs, could be more effective than another widely used treatment group known as angiotensin converting enzyme inhibitors in treating women with hypertension, even after oestrogen levels decline after menopause.

Layton said her team has spent years developing a mathematical model of women’s kidneys and the cardiovascular system, designed to explore how different biological mechanisms affect blood pressure.

The model allows researchers to test individual effects separately and examine how each influences the body.

“We can turn on one effect, then another, and see exactly how each one affects the body,” Layton said.

She added: “For too long, women’s health, especially older women’s health, has been overlooked by medicine.

“Understanding how age and sex affect the body and, therefore, treatment, is an equity issue.”

Digital symptom checkers could reduce endometriosis diagnosis delays by more than four years and save over US$5,000 per patient, according to a modelling study.

Endometriosis is a condition where tissue similar to the womb lining grows outside the uterus, often causing pelvic pain and other symptoms.

In the US it takes about seven years on average to diagnose.

Researchers used a Markov decision process model, a mathematical method used to estimate outcomes across different scenarios over time, to compare a digital symptom checker with standard care over 40 years.

The analysis suggested that using the tool alongside usual care could reduce diagnostic delay by about 4.36 years, shifting the average time to diagnosis from roughly seven years to around three years.

The research was carried out by scientists from Flo Health, which funded the study, working with the London School of Hygiene and Tropical Medicine and York Health Economic Consortium.

Anna Klepchukova, chief medical officer at Flo Health, said: “Endometriosis can deeply disrupt women’s lives, yet many spend years searching for answers within a system that hasn’t always been designed to connect the patterns they experience over time.

“This research explores how digital tools may help women better recognise their symptoms and bring clearer insights into conversations with their health care providers.

“While these tools aren’t diagnostic, they support earlier awareness and more informed decisions, ultimately changing the trajectory of their care and their lives.”

Economic modelling estimated savings of US$5,196.22 per person over the 40-year period, mainly from reduced medical costs and lower productivity losses.

From a clinical perspective, the model estimated a gain of 0.049 quality-adjusted life years per person. Quality-adjusted life years, or QALYs, are a measure used in health economics to assess both the length and quality of life produced by a healthcare intervention.

These clinical improvements were described as modest, equating to nearly three additional weeks of healthy life per patient, while the economic impact was more substantial.

Researchers said the greatest benefit would occur when the symptom checker maintains sensitivity and specificity of at least 0.7, user compliance exceeds 45 per cent, and the evaluation period is at least 10 years.

The tools are intended as educational resources rather than diagnostic devices and are designed to prompt earlier referral for clinical assessment.

The study authors said the modelling approach could provide a framework for assessing digital health tools beyond simple accuracy measures and may help guide future research into other under-recognised women’s health conditions.

An electronic nose using machine learning can detect early signs of ovarian cancer in blood samples with 97 per cent accuracy, according to researchers.

The device uses 32 sensors that react to volatile substances released from blood plasma.

Different cancers emit different substances, meaning each effectively has a distinct chemical pattern.

Rather than searching for a single biomarker, the system analyses a wide range of signals using machine-learning models trained to identify ovarian cancer.

The models are trained on known samples from a biobank, a collection of biological specimens used for research.

The approach was developed by researchers in Sweden.

Donatella Puglisi, associate professor at Linköping University, said: “We’re trying to mimic the mammalian sense of smell artificially.

“We’ve now developed an algorithm that can distinguish ovarian cancer from endometrial cancer and healthy control groups, using data from an electronic nose.

“More and more people are being diagnosed with cancer, especially young adults, and this is alarming.

“If screening were more accessible, both in terms of cost and location, it would be possible to improve early diagnosis.

“Our approach could facilitate the adoption of new screening protocols and the development of new diagnostic methods, improving survival rates, quality of life, and overall clinical outcomes.”

Electronic nose technology has existed for around 60 years.

The sensors used in the prototype are relatively simple models already available on the market, but recent advances in artificial intelligence and machine learning have enabled the technology to be used in new ways.

Current blood-based cancer screening typically involves searching for biomarkers specific to the suspected cancer.

However, researchers say these tests are often slow and lack accuracy.

Jens Eriksson, associate professor at Linköping University and chief technology officer at VOC Diagnostics AB, the company developing the electronic nose, said: “Unlike in breast cancer, there is currently no reliable ovarian cancer screening method.

“These tests are often based on a single biomarker and lack the precision required to detect the disease at an early stage.

“Our method is therefore far ahead not only in terms of accuracy but also in the ability to identify early disease.

“It’s a simple test that takes 10 minutes and gives a clear result. Our method can test many people at a low cost and is much more accurate than what’s on the market today.

“This study is a pilot, but we hope it will be used as part of cancer screening within three years. Right now, we’ve focused on detecting cancer, but the applications are endless.

Ovarian cancer often causes vague symptoms similar to those of more common conditions, meaning it is frequently diagnosed at a late stage when survival outcomes are poor.

In 2022, about 325,000 new cases and more than 200,000 deaths were reported globally, with estimates suggesting these figures will rise sharply by 2050.