As per the latest data released by Transforming Access to Student Outcomes in Higher Education (TASO) and the Policy Institute at King's College London, the number of UK students reporting mental health difficulties tripled. The estimate reveals that around 300,000 students could now be experiencing mental health struggles. Of the total, 18% of students reported some kind of mental health issue in 2024.

As per the reports, this estimate is triple what was reported in 2017, where it was at 6%. Experts also say that Covid-19 pandemic is "often considered to have contributed to this, it does not explain the ongoing rise in mental health difficulties." Another reason could also be the "changing definition and increasing openness about mental health" which has led to a rise in numbers. The report notes, "This trend pre-dates the Covid-19 pandemic and the cost-of-living crisis. Although these factors play a part in students' deteriorating mental health, they cannot therefore be the only explanation."

How Did The Report Conclude?

The report drew data collected over the latest Student Academic Experience Survey of 93,212 students. From the survey, it was found that there exist significant disparities between demographic groups, with women being twice as likely to report mental health difficulties, about 22% as compared to men, at 11%.

What Did The Results Reveal?

The results revealed that students who identified as LGBTQ experienced the highest rates of mental health challenges. This has actually lessened the hope that conditions for LGBTQ students are improving, which may not have been a positive case.

Of them, 42% are bisexual and lesbian students, whereas last year it was 35% and 32% respectively. The report also noted that mental health difficulties among lesbian women and gay men rose three times the rate of straight people, and among bisexual and asexual people, it was twice as high. For trans students, the number jumped from 25% in 2023 to 40% in 2024.

Is The LGBTQ+ Prone To Mental Health Crisis?

As per the Child Mind Institute, being LGBTQ+ does not cause mental health problems, but because these kids often face factors like rejection, discrimination and violence, they are at a higher risk of challenges including depression, anxiety, and even attempting suicide.

A UTAH Health study quotes Anna Docherty, PhD, LP, assistant professor of psychiatry at Huntsman Mental Health Institute that, "likely with any identity, feeling different - or worse, unaccepted as you are is a significant risk factor of mental health struggle." The data reveals that LGBTQ+ teens are six times more likely to experience symptoms of depression than non-LGBTQ+ identifying teens. They are also more than twice as likely to feel suicidal and more than four times as likely to attempt suicide. In the US alone, 48% of transgender adults report that they have considered suicide in the last year, compared to 4% of the overall population.

What Do These Findings Mean?

TASO's academic lead and professor of public policy at King's College London, Michael Sanders said, "LGBTQ students and women bear the brunt of the rise in declining mental health and urgent action is needed to understand and address these trends."

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.

On September 3, 1928, Scottish scientist Alexander Fleming returned to his laboratory after a holiday. He famously noticed the antibacterial effect of mold contaminating a Staphylococcus culture.

Fleming identified the mold as belonging to the Penicillium genus and found that it produced a substance capable of inhibiting bacterial growth, which he named penicillin.

However, Fleming’s discovery was only the beginning. Penicillin proved difficult to isolate, purify and mass-produce. During World War II, scientists Howard Florey and Ernst Chain built on Fleming’s work to develop large-scale production methods, converting penicillin into a life-saving medicine and ushering in the modern antibiotic era.

How Did Penicillin Resistance Develop?

As penicillin came into widespread medical use in the 1940s, resistance to the drug also emerged.

“Penicillin acts through a beta-lactam ring, which targets the bacteria, but then the organisms started producing an enzyme known as beta-lactamase,” Dr NK Ganguly, former Director General of the Indian Council of Medical Research (ICMR) told HealthandMe.

“This beta-lactamase broke the ring, so various derivative varieties of penicillins were synthesized,” he explained.

But as new penicillin derivatives were developed, bacteria also evolved or acquired mechanisms, including different beta-lactamases, that could break down these drugs.

As a result, penicillin became less effective against many bacteria. However, it remains effective against certain organisms and infections, including:

• Syphilis
• Group A beta-haemolytic Streptococcus
• Streptococcus pneumoniae (pneumococcus)

“Penicillin remains the gold standard for certain infections and indications, including neonatal sepsis, childhood pneumonia, rheumatic heart disease prophylaxis and resurging cases of syphilis,” Dr Ganguly said.

The Growing Threat Of Resistance

The story of penicillin resistance is an early example of a much broader problem the world is grappling with today: antimicrobial resistance (AMR), which threatens the effectiveness of modern healthcare.

Decades after antibiotics transformed medicine, the bacteria these drugs were designed to target have evolved significant resistance. This threat has been further compounded by the misuse and overuse of antibiotics across sectors.

According to the World Health Organization (WHO), approximately 1 in 6 laboratory-confirmed bacterial infections worldwide were resistant to antibiotic treatments in 2023.

Low- and middle-income countries bear the heaviest burden of infectious disease but face severe shortages of specialized antibiotics.

A global study covering 82 countries, led by the Murdoch Children’s Research Institute (MCRI), found that antibiotic resistance increased across every region between 2004 and 2022. As a result, critical treatments for routine childhood infections are becoming increasingly ineffective.

“The discovery of antibiotics is perhaps the most significant, life-changing breakthrough in the history of medicine,” Dr. Rajeev Jayadevan, Ex-President of IMA Cochin and Convener of the Research Cell, Kerala, told HealthandMe.

“However, bacteria possess natural evolutionary mechanisms to resist antibiotics as part of their survival machinery. Unfortunately, overuse in human healthcare, veterinary medicine and agriculture has allowed bacteria to continuously adapt and evade treatment,” he added.

Major Drivers Of Antimicrobial Resistance

Antimicrobial resistance is driven by a combination of clinical, agricultural, industrial and environmental factors:

1. Inappropriate syndromic and empirical prescribing
   • Viral infections
   • Unnecessary STD treatment
2. Self-medication and suboptimal adherence
3. Informal healthcare providers
4. Substandard and falsified medicines
5. Agricultural and veterinary misuse
   • Growth promoters in animal feed
   • Use of human-critical antibiotics in livestock
6. Industrial and environmental contamination
   • Manufacturing effluents
   • Fermentation and industrial waste
   • Effluents and sewage
7. Lack of public awareness

What Can Be Done?

So, are we running out of effective antibiotics? Not entirely, yet "the development of newer antibiotics has not kept pace with bacterial evolution" Dr Rajeev said.

Resistance is also making some infections increasingly difficult to treat. To counter, stronger national policies are needed the unnecessary antibiotic prescribing while ensuring that patients who genuinely need specialized antibiotics can access them.

Improving access will require coordinated action at both local and national levels. This includes:

• Ensuring quality-assured antibiotics are available and affordable in frontline healthcare settings
• Procuring the right antibiotics in adequate quantities
• Strengthening surveillance of antibiotic use
• Setting country-specific prescribing targets based on local disease burden and public health needs.

“Beyond discovering new drugs, the long-term solution lies in regulating antibiotic use globally—because antimicrobial resistance knows no boundaries. A resistant organism originating in one region can rapidly spread worldwide,” Dr Rajeev said.

A new experimental vaccine could offer protection against several forms of Streptococcus pneumoniae, showing promise for a future vaccine that will not have to fight each bacterial strain separately.

The bacterium, commonly called pneumococcus, can live in the nose and throat without causing any symptoms. But when the body's defenses are compromised and weakened, it can target other parts of the body and cause symptoms like pneumonia, meningitis, bloodstream infections and other serious diseases.

About The Study

One of the primary challenges of preventing these infections is that S. pneumoniae exists in more than 100 serotypes, or distinct versions of the bacterium. The current vaccines available to fight them only cover a selection of these types.

A new study published in Science Advances has found a different strategy. Instead of developing the vaccine around the sugar coating that differs between serotypes, researchers targeted proteins that is shared across pneumococcal strains.

Also read: H5N1 Detected In Captive Mink In US For First Time: Should You Be Concerned?

Current Pneumococcal Vaccines Have A Limitation

Existing pneumococcal vaccines work by instructing the immune system to recognise some components of the bacterium's outer shell.

Pneumococcal conjugate vaccines, or PCVs, combine these bacterial sugars with a carrier protein to produce a stronger immune response. Vaccines that target multiple serotypes have helped reduce invasive pneumococcal disease significantly.

But when vaccination reduces the prevalence of the serotypes that is included in a vaccine, other serotypes that are not covered can become more common. This phenomenon is known as serotype replacement.

Some of these replacement strains can also acquire antibiotic-resistance genes, which becomes another challenge.

This is why researchers have been exploring a vaccine that could provide protection across almost all pneumococcal serotypes, rather than having to continuously expand the list of strains covered.

Also read: Fall Vaccines 2026: US Doctors Issue COVID, Flu And RSV Jab Guidance

How Is The New Vaccine Developed?

Researchers opted for a reverse strategy to develop this universal vaccine. Instead of growing the bacterium and looking for useful components, researchers started with its genetic information.

They studied thousands of S. pneumoniae genomes to identify proteins that were conserved across different serotypes. The team looked for proteins that would:

• Be present on or accessible from the bacterial surface
• Be sufficiently different from human proteins
• Be capable of producing a strong immune response

From this analysis, researchers selected three proteins: zinc metalloprotease B (ZmpB), pneumococcal adherence and virulence factor A (PavA), and a YfhO-like protein.

These were combined with two immune-stimulating ingredients, CpG and chitosan, to create the experimental vaccine called ZPY-CpG-Ch.

Also read: 84% Cancer Patients Report Benefit From Ivermectin-Mebendazole: What The Study Found & Why More Trials Are Needed

Effects Of The Vaccine On Mice

Researchers tested the vaccine in both adult and mice to compare its performance with the 13-valent pneumococcal conjugate vaccine, PCV13.

In one experiment, vaccinated mice were exposed to serotype 1, a highly virulent strain of S. pneumoniae. The experimental vaccine produced 80% to 100% survival. The researchers also tested the vaccine against serotypes that are not covered by PCV13.

ZPY-CpG-Ch provided complete protection against serotypes 11A and 33F, while protection against serotype 8 was 50%.

The study found that the vaccine's protective effect was associated largely with a type of immune response that is be important in defense against pneumococcal infection.

The researchers also found that antibodies produced after vaccination could help kill pneumococci in laboratory experiments.

When these antibodies were transferred into unvaccinated mice, they provided protection against a lethal pneumococcal strain.

Despite the promising results, the researchers are not claiming that ZPY-CpG-Ch is ready for people.

The biggest limitation is that the work is still preclinical. The vaccine has been tested in mice but not in human clinical trials. The researchers also challenged the animals with only a small number of pneumococcal serotypes.

If the vaccine eventually proves to be safe and effective in humans, it could lead to wider protection against pneumococcal diseases.