After mpox outbreak, Africa is under the threat of yet another virus outbreak, this is the Marburg virus outbreak in Rwanda. So far, six people have died from the outbreak, confirmed the health minister. Most victims were the healthcare workers in the hospital's intensive care unit. As per reports, 20 cases have been identified since the outbreak was confirmed on Friday.

What Is Marbug Virus?

With the fatality rate of 8% it is the same virus family as Ebola. The main carrier is from fruit bats which spreads to humans then through the contact of bodily fluids of infected individuals, it spreads to others.

Common Signs And Symptoms

The common signs and symptoms of the Marburg virus include fever, pain, diarrhoea, vomiting and in the case of extreme blood loss, death too can happen.

So far, there is no specific treatment or vaccine for the virus. However, treatments like drugs and immune therapy are being developed as per the World Health Organisation (WHO).

Call Of Action

Rwanda says that it has intensified its contact tracing, surveillance and testing to contain the spread. It has also tracked about 300 people who had come into contact with individuals affected by the Marburg virus.

The health minister has urged people to stay vigilant and avoid any physical contact and to wash their hands with clean water, soap or sanitiser and report any suspected case.

As of now, most of the cases have spread to the capital in Kigali. In light of this, the US Embassy in the city has advised its employees to work remotely for the next week.

This is the first time Rwanda has confirmed for Marburg cases, before this, in 2023, Tanzania confirmed the outbreak, whereas three people had died of this in Uganda in 2017.

History Of Marburg

As per WHO, this virus kills half of the people it infects. In the previous outbreaks, it has killed between 24% to 88% of the patients.

The virus was first detected in 1976 after 31 people were infected, out of which 7 died in simultaneous outbreak in Marburg and Frankfurt in Germany, and Belgrade in Serbia.

The source was traced to African green monkeys who were imported from Uganda. However, other animals too are linked to the virus spread, including bats.

In the past, the virus outbreaks have happened in countries like Equatorial Guinea, Ghana, the Democratic Republic of the Congo, Kenya, South Africa, Uganda, and Zimbabwe. In 2005, this virus killed 300 people in Angola.

However, for the rest of the world, only two people have died from the virus in the rest of the world, with one of them being in Europe, and the other in the US. These both have been on expeditions to caves in Uganda.

Alcohol-attributable cancer deaths in the US doubled between 1990 and 2023, according to a study published in The Lancet Regional Health – Americas.

Using more than three decades of Global Burden of Disease data, researchers found that annual alcohol-attributable cancer deaths rose from 11,361 in 1990 to 23,126 in 2023.

Men and adults aged 55 and older experienced the greatest burden, but increases were seen across most cancer types, age groups and regions.

Among older men, liver cancer accounted for the highest alcohol-attributable mortality rates, followed by esophageal and colorectal cancers. Among women, breast cancer represented the leading source of alcohol-attributable cancer mortality.

Colorectal Cancer Leads In Younger Men

The study also identified concerning patterns among younger adults. For men aged 20 to 54, colorectal cancer was the leading alcohol-attributable cause of cancer death. Among women in the same age group, breast cancer ranked first, followed by colorectal cancer.

“Notably, among adults aged 20 to 54, colorectal cancer was the leading cause of alcohol-attributable cancer mortality in men and the second leading cause in women, surpassing liver cancer in both groups,” Jani said.

Alcohol And Cancer Risk

While it is commonly known that alcohol damages the liver, the new study highlights that its impact extends beyond liver cancer, with growing burdens from colorectal, breast, esophageal, pancreatic and other cancers.

Alcohol has long been recognized as a Group 1 carcinogen by the International Agency for Research on Cancer, in the same category as tobacco smoke and asbestos. Scientific evidence links alcohol consumption to cancers of the breast, liver, esophagus, colorectum and several head and neck sites.

“The most surprising finding was the breadth of alcohol’s potential impact across cancer types,” said Chinmay Jani, chief fellow in hematology and oncology at Sylvester Comprehensive Cancer Center, part of the University of Miami Miller School of Medicine.

“Although its relationship with liver cancer is widely recognized, its contribution to cancers such as colorectal, esophageal, breast, pancreatic and prostate cancer is less well understood by the public.”

Alcohol As A Modifiable Risk Factor

Gilberto Lopes, chief of the Division of Medical Oncology at Sylvester, said the findings reinforce the importance of giving people clear information about lifestyle factors that influence cancer risk.

“What this study makes clear is that alcohol-related cancer risk is not limited to one disease or one group of people,” Lopes said. “As physicians and cancer researchers, we have an opportunity to help patients understand that alcohol is a modifiable risk factor and that even small, informed changes can be part of a broader strategy to reduce cancer risk in our community.”

Despite increasing scientific evidence, public awareness of the alcohol-cancer connection remains relatively low compared with awareness of other risk factors such as tobacco use.

“The most important takeaway is greater awareness that alcohol may affect cancer risk beyond the liver,” Jani said.

“These findings highlight alcohol as a potentially modifiable risk factor, and while the lowest safe dose is not yet known, this study suggests that reducing consumption to the lowest amount feasible for each individual may help lessen its impact on cancer risk and overall health.”

While GLP-1 drugs such as Ozempic, Wegovy and Zepbound are helping with weight loss and diabetes management, men already at risk of androgenetic alopecia may face a 7% higher risk of hair loss with higher GLP-1 activity, according to a new study.

Hair thinning has been reported by both men and women using GLP-1 drugs, with researchers largely attributing the shedding to rapid weight loss associated with the medications.

However, researchers at NYU Langone Health have now identified a potential genetic link between GLP-1 activity and androgenetic alopecia, an inherited form of hair loss affecting the top and front of the scalp.

"Our study provides the first genetic link between GLP-1 use and an increased risk of male-pattern hair loss from androgenetic alopecia, an association long suspected but until now not shown scientifically," said Lynn Petukhova, assistant professor in the Department of Dermatology and the Department of Population Health at NYU Grossman School of Medicine.

What Did The Study Find?

Researchers used large, publicly available genetic databases, including:

• eQTLGen: 31,684 mostly white men and women.
• Complex Traits Genetics group: 205,327 mostly white men

The researchers compared GLP1R-related genetic data with markers associated with androgenetic alopecia. They found that genetic variants linked to naturally higher levels of GLP-1 receptor proteins were more common in men with androgenetic alopecia.

The team also adjusted the analysis for hypertension, which may affect blood flow to the scalp and hair follicle growth; and accounted for insulin resistance and lower testosterone levels.

After these adjustments, the 7% higher risk remained.

Published online in the Journal of Investigative Dermatology, the findings suggest that GLP-1 activity and male-pattern hair loss may share a biological link.

Could Screening Help Prevent Hair Loss?

The findings could eventually help identify people who may be more vulnerable to hair loss before they are prescribed GLP-1 medications.

"Our findings suggest that, if future experiments prove successful, some men, and possibly women too, could be screened and benchmarked for their risk of hair loss before being prescribed GLP-1 medications," Petukhova said.

The researchers also suggested that some GLP-1 users could potentially receive combination treatments to prevent hair loss, such as minoxidil or another drug.

However, more research is needed to understand how GLP-1 activity may affect hair follicle growth. Petukhova also plans to investigate whether the genetic link seen in men applies to women.

Hair shedding has been reported among GLP-1 users and has been linked by researchers to rapid weight loss.

In many cases, hair growth resumes several months after weight stabilizes.

The new findings add a potential genetic explanation to these reports, but further research is needed to establish the underlying biological mechanism.

What Is Androgenetic alopecia?

Androgenetic alopecia is a common form of hair loss that becomes more likely with age. It can begin as early as the teenage years and affects both men and women, with hair loss in women most commonly observed after menopause.

Surveys suggest that 12% of Americans have used GLP-1 drugs specifically for weight loss, including one-fifth of women aged 50 to 64. Since Ozempic was approved by the US Food and Drug Administration in 2020, prescriptions for the medication have more than tripled.

Researchers from the Indian Institute of Technology Madras (IIT Madras) and Christian Medical College (CMC), Vellore, have developed three artificial intelligence (AI)-based tools designed to help detect and assess kidney diseases earlier.

The technologies could help doctors identify kidney conditions more quickly, analyse medical images more consistently and assess the extent of kidney tumours in greater detail.

What Did The Researchers Develop?

The team developed three complementary technologies:

A machine learning model that uses clinical and laboratory information to predict a person's risk of chronic kidney disease (CKD).

Together, the tools have been designed to support clinicians in detecting kidney disease and assessing its severity.

How Can The AI Tools Help?

Kidney diseases can remain asymptomatic during their early stages and may go undetected until significant damage has occurred.

The researchers say their AI-based tools could assist physicians by providing rapid and consistent analysis, potentially supporting earlier diagnosis and more informed treatment decisions.

“The team aimed to develop intelligent systems that would help clinicians make quicker and more informed decisions. We used machine learning along with clinical knowledge to develop tools that would assist in the earlier detection of kidney diseases and give more detailed information specific to the patient,” said Prof. G.L. Samuel, Department of Mechanical Engineering, IIT Madras, in a statement.

AI System Trained On More Than 12,000 CT Images

The CT image classifier was trained using more than 12,000 images and can distinguish between healthy kidneys, cysts, stones and tumours.

The researchers also developed a 3D imaging framework using open-source software to measure tumour burden.

According to the team, the approach offers an inexpensive and repeatable way to assess the extent of a tumour, which could provide additional information for treatment planning.

The CKD prediction model was implemented as a user-friendly prototype interface with the aim of facilitating future clinical translation. The team also worked on improving the model's accuracy and interpretability for doctors.

“Early detection is of paramount importance when dealing with kidney diseases; these AI tools can help detect at-risk patients early and plan their treatment more effectively. The patient-specific imaging framework is of significant promise as it goes beyond the standard measurements to give a more comprehensive picture of the extent of the disease,” said Jennifer Delighta, Research Scholar, IIT Madras.

Towards A Kidney Digital Twin

The research could also contribute to the development of a kidney Digital Twin — a technology that combines AI-assisted image analysis with patient-specific 3D anatomical models.

Such virtual models could eventually help researchers and clinicians monitor disease progression, forecast changes and support more personalized treatment planning.

However, the technologies are still being developed. The researchers plan to test the models using additional patient datasets to validate their performance and establish partnerships with healthcare institutions for potential real-world deployment.

The team is also exploring the long-term integration of these AI technologies with minimally invasive wearable sensing systems and Digital Twin platforms for personalised kidney health monitoring.