Kochi, Kerala: A 44-year-old woman from Karunagappally in Kollam has undergone surgery to remove three glass fragments that had remained lodged near her spine for 12 years, after imaging finally identified the source of pain that doctors had previously been unable to explain.

Manu S B had lived with chronic back pain since 2014, when she fell onto a glass-topped table while eight months pregnant and attending a family wedding. Glass shattered on impact and pierced her back. She was treated at a hospital at the time, but not all the fragments could be located, and some remained embedded in the tissue near her spine.

Over the following twelve years, Manu consulted multiple hospitals without a diagnosis. Her husband, Rajeeve, said the unexplained pain affected her sleep, her ability to raise her arms, and eventually her work as a Taluk Supply Officer in Karunagappally. Family members said the prolonged, undiagnosed pain also took a psychological toll, with some around her suggesting the problem was not physical.

A recent consultation led doctors to suspect a tumour-like lesion and recommend an MRI. Rajeeve then approached Dr Krishnakumar R, Director of the Institute of Spine and Scoliosis Surgery at VPS Lakeshore Hospital, under whom he had previously undergone surgery. A subsequent 3D CT scan identified the retained glass fragments, including one triangular piece measuring roughly 3 cm.

Surgeons removed the three fragments from the mid-back region of Manu’s spine last week, in a procedure led by Dr Krishnakumar with support from the hospital’s radiology and anaesthesiology teams. She is currently recovering at VPS Lakeshore Hospital.

“Pain that continues for years after an injury needs careful evaluation,” Dr Krishnakumar said. “In this case, imaging helped us identify the retained glass fragments and understand the reason for her longstanding symptoms.”

Rajeeve said much of the earlier medical attention over the years had focused on Manu’s neck rather than the back, which he believes contributed to the delay in diagnosis.

India recorded an estimated 15.6 lakh new cancer cases and 8.74 lakh cancer deaths in 2024, according to estimates based on data from 43 cancer registries. Cancer is now the second leading cause of death globally after cardiovascular diseases, with the World Health Organization estimating 20.6 million new cases and nearly 10 million deaths worldwide in 2024. Against this growing burden, cancer stem cells are emerging as a critical target in understanding why tumours return and resist treatment.

The growing cancer burden has made early detection, effective treatment and preventing recurrence critical challenges. While advances in surgery, chemotherapy, radiation, targeted therapies and immunotherapy have improved treatment options, cancer can still return after an apparently successful treatment. One reason may lie in a small population of cancer stem cells that can remain hidden inside a tumour.

These are known as cancer stem cells. Although they make up only a small fraction of a tumour, researchers believe they can play an important role in tumour recurrence, metastasis and treatment resistance. Their rarity and ability to change their identity have also made them difficult to detect. This is where a new Indian research effort could offer a different way of looking at cancer.

Researchers from the S. N. Bose National Centre for Basic Sciences, an autonomous institute under the Department of Science and Technology, in collaboration with Ashoka University, have developed an artificial intelligence framework that can identify hidden cancer stem-like cell populations from tumour gene-expression data.

Called ACSCeND, or AI-based Cancer Stem Cells Profiler and Neoplasm Deconvoluter, the framework could help researchers examine cancer biology at a level that conventional tumour analysis may miss.

Cancer Stem Cells: Understanding Single Stemness Score

Cancer is not a uniform mass of identical cells. Different cells within the same tumour can behave differently, with some populations potentially more capable of surviving treatment and driving tumour growth.

Conventional computational approaches often assign a tumour a single “stemness” score. ACSCeND instead identifies three distinct developmental states of cancer stem-like cells: pluripotent-like, multipotent-like and unipotent-like.

The distinction could give researchers a more detailed picture of the biological composition of a tumour.

The framework combines information learned from high-resolution single-cell sequencing with deep learning to analyse conventional bulk tumour RNA sequencing. This is significant because single-cell experiments are not available for every tumour sample, while large collections of conventional RNA sequencing data already exist.

In effect, the researchers are using AI to extract information about hidden cell populations from data that may otherwise appear less detailed.

Tested Across More Than 25,000 Tumours

The researchers validated ACSCeND against existing computational methods and tested it across independent datasets and sequencing platforms. They then applied the framework to more than 25,000 tumour samples from major international cancer databases, including TCGA and PRECOG.

The analysis revealed a significant association between the presence of highly potent, pluripotent-like cancer stem cells and poorer outcomes. Tumours enriched with these cancer stem cells were associated with poorer patient survival, a greater likelihood of recurrence and reduced response to modern immunotherapies.

The framework also identified molecular programmes that may help these cells survive, adapt and evade the immune system. Such findings could provide researchers with potential targets for future drug development and help identify patients who may be more likely to relapse.

Why This Could Matter for Precision Medicine

The significance of the research lies not in AI replacing cancer doctors or predicting an individual patient’s future, but in its ability to reveal biological patterns that are difficult to detect using conventional analysis.

If researchers can better identify the cell populations that are associated with recurrence and treatment resistance, they may gain a clearer understanding of why some tumours return after apparently successful treatment. That knowledge could eventually contribute to therapies designed to target not only the bulk of a tumour but also the populations of cells that help it survive.

The approach could also be valuable because it works with conventional bulk RNA sequencing data. Instead of requiring every tumour sample to undergo expensive and highly detailed single-cell analysis, researchers may be able to investigate hidden cancer stem-like populations across much larger collections of existing samples.

For India, where an estimated 15.6 lakh people were diagnosed with cancer in 2024, such computational approaches could strengthen cancer research and the country’s move towards more data-driven precision medicine.

But the findings need to be viewed in context. ACSCeND is currently a research framework, not a clinical diagnostic tool that can determine whether an individual patient’s cancer will return. The study establishes associations between cancer stem cells states and outcomes; translating those findings into clinical decisions will require further research and validation.

The potential turning point, therefore, is not that AI has solved cancer recurrence. It is that researchers now have another way to look for the cancer stem cells that may be helping tumours survive treatment.

In the long battle against cancer, understanding what remains after treatment may be just as important as understanding what the treatment destroys.

Kerala’s flood emergency is creating another public-health challenge alongside displacement, injuries and infrastructure damage. As people wade through floodwater, clean homes, move through stagnant water or gather in relief shelters, they face exposure to infectious diseases ranging from leptospirosis and dengue to diarrhoeal and respiratory infections.

The risks are emerging as Kerala already carries a substantial communicable-disease burden.

Kerala is India’s Leptospirosis Hotspot

India recorded 8,121 confirmed leptospirosis cases between January and June 2026, according to data tabled in the Rajya Sabha by the Union Ministry of Health and Family Welfare. More than half, 4,340 cases, or 53.4% — came from Kerala, Tamil Nadu, Karnataka, Andhra Pradesh and Telangana.

Kerala recorded the highest number at 1,726 cases, followed by Tamil Nadu with 1,473 and Karnataka with 624. Assam reported 786 cases and Maharashtra 780.

The figures place Kerala at the top of the national list even before the current flood emergency. That is significant because leptospirosis is strongly associated with exposure to contaminated water and soil — conditions that become more common during floods and the recovery period.

Floods Create Multiple Disease Pathways

Flooding does not produce one uniform disease pattern. Different infections emerge through different pathways and at different times. A 2026 systematic review in BMC Infectious Diseases, covering 71 studies published between 2014 and 2024, found consistent links between flooding and waterborne infections including leptospirosis, cholera, bacillary dysentery and hepatitis A/E. It also identified increased risks of vector-borne diseases such as dengue and malaria. Disease emergence varied from days to weeks depending on the pathogen and flood conditions.

The evidence is particularly strong for diarrhoeal disease. A meta-analysis of 42 studies found that floods were associated with a 40% higher risk of infectious diarrhoea, with the risk of bacterial diarrhoea increasing by 82%. For Kerala, this matters because diarrhoea was already one of the state’s most frequently reported communicable diseases.

During the first eight days of July 2026, government hospitals reported 19,428 diarrhoeal cases, alongside 84,658 fever cases. The same period recorded 834 dengue cases, 661 influenza cases, 113 leptospirosis cases, 197 jaundice cases, 56 malaria cases and 34 Shigella cases. Thirty people died from communicable diseases during those eight days.

Kerala’s Floods Offer a Warning

Kerala’s own experience shows why disease surveillance must continue after the rain stops. A study comparing leptospirosis in Kerala during 2017, 2018 and 2019 found higher case numbers in the flood years, with the strongest increase following the severe 2018 floods. Importantly, cases were highest during the post-flood period, indicating a time lag between flooding and disease emergence.

2018 floods identified 61 leptospirosis hotspots, compared with 34 in 2017 and 21 in 2019. Several hotspots overlapped with high flood-risk areas, while others were in places with limited access to hospitals. The finding points to a larger preparedness opportunity: flood-risk mapping could be combined with disease-risk mapping to identify communities that need early warnings and preventive interventions.

Why Leptospirosis is a Particular Concern

Leptospirosis is caused by Leptospira bacteria and is commonly transmitted through contact with water or soil contaminated by infected animal urine, particularly from rodents. Floods increase this exposure as people walk through contaminated water, clean flooded homes or handle mud and debris. The risk can continue after water recedes, when residents return to clean houses and remove waste.

Kerala has developed specific responses for this risk. The state’s health system uses doxycycline prophylaxis for selected high-risk exposures and has previously established dedicated “Doxy Corners” during disaster responses. It has also expanded early diagnosis: RT-PCR testing for leptospirosis is available through nine government laboratories, according to the Health Department.

The challenge is ensuring these measures reach exposed populations quickly enough.

Dengue and Diarrhoeal Diseases May Follow Different Timelines

Dengue presents a different risk. Heavy rainfall can initially wash away mosquito breeding sites, but as floodwater recedes, stagnant pools can remain in containers, drains and construction sites. These can become breeding sites for Aedes mosquitoes.

Kerala had already recorded 834 dengue cases in the first eight days of July, so vector surveillance will remain important as the flood situation evolves. Diarrhoeal diseases can emerge through another pathway. Flooding can damage sanitation infrastructure, contaminate water and disrupt food hygiene. Kerala’s 19,428 diarrhoeal cases in eight days provide a reminder that this risk exists independently of leptospirosis.

The state’s existing disease burden also includes Shigella. By June 23, Kerala had reported 241 Shigella infections, with outbreaks identified in Kozhikode, Wayanad, Thrissur and Alappuzha.

Influenza Adds Another Layer

Respiratory infections are less directly connected to floodwater but can become harder to control when people are displaced. Relief camps bring people from different households into shared spaces. Crowding and inadequate ventilation can increase opportunities for respiratory transmission.

Kerala recorded 661 influenza cases during the first eight days of July. The concern is about vulnerability. Children, older adults and people with underlying illnesses may be at greater risk when respiratory infections spread in crowded shelters and routine healthcare is disrupted.

The Health Emergency May Peak After the Flood

The most important lesson from Kerala’s previous floods is that the health emergency does not necessarily end when the water recedes. The immediate risks include injuries, drowning and direct exposure to contaminated water. Later, people face contaminated mud and waste while cleaning homes, stagnant water that can support mosquito breeding, disrupted sanitation and increased contact in temporary shelters.

Research shows that different infections can emerge over different time lags. For leptospirosis, Kerala’s experience suggests that the post-flood period can be particularly important. That makes the weeks after flooding a crucial test of public-health preparedness.

Kerala already has daily disease surveillance, district-level monitoring, leptospirosis testing and preventive protocols. The next step is to connect these systems more closely with flood-risk information so that authorities can identify potential disease clusters before hospitals begin seeing a large increase in patients.