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Comment by Dr. Krishna Kumari Challa on January 31, 2025 at 1:24pm

How tackling sepsis can save millions of lives—and prevent future pandemic deaths

Sepsis is an underestimated killer. Nearly a quarter of patients treated for sepsis in hospital will die, but because so many different illnesses can predispose patients to experiencing it, it's overlooked as a direct cause of death. Yet approximately 20% of deaths worldwide are caused by sepsis, and currently we have no treatments that tackle it directly.

Now researchers writing in Frontiers in Science explain how systems immunology can help us understand and treat sepsis—and how this could cut the death toll of future pandemics, no matter what disease causes them.

One of the reasons it's so hard to understand and treat sepsis is that it is multifaceted. Sepsis arises when the immune system fails to control an infection and malfunctions, causing multi-organ failure. Many different infections can cause sepsis, and its symptoms and progression vary between patients and over time in the same patient. Its early symptoms are similar to those of many other illnesses, which makes it difficult to diagnose quickly and initiate timely treatment, contributing to high mortality.

Systems immunology offers a potential solution to this diagnosis problem by using mathematical and computational modeling to study the immune system in the context of all the body's other systems. It does this by using different types of clustering analysis to identify patterns in large volumes of omics data, ranging from transcriptomic data (what genes show altered expression) to proteomic and metabolomic data—data that tell us about the body's reaction to its physical circumstances, in this case sepsis, in incredibly fine-grained detail.

These patterns help us work out the patterns and basis for the immune dysregulation that drives sepsis, come up with new hypotheses that we can research and use to develop new treatments, and identify diagnostic markers that we can use to catch sepsis early.

For instance, using these clustering analyses, scientists have identified changes to gene expression that act as early warnings for sepsis. They've also been able to identify five different subtypes of sepsis which are caused by different kinds of immune dysregulation and have different prognoses. In the future, we could build on these advances to diagnose different subtypes of sepsis earlier and treat them with the right drugs when we do.

However, systems immunology analysis is not yet in widespread use, because it is expensive and demands significant volumes of data—so we don't yet know how these diagnostics could translate into clinical results. The researchers call urgently for targeted funding and greater data availability.

"In sepsis we lack the depth of information required to enable more effective systems immunology and machine learning approaches.

Part 1

Comment by Dr. Krishna Kumari Challa on January 31, 2025 at 1:19pm

Essentially, explainable AI approximates the flexibility of expert clinical judgment while avoiding its pitfalls. The researchers' model is also especially well-suited to judging risk for rare pregnancy scenarios, accurately estimating outcomes for people with unique combinations of risk factors. This kind of tool could ultimately help personalize care by guiding informed decisions for people whose situations are one-of-a-kind.
AI models can essentially estimate a risk that is specific to a given person's context and they can do it transparently and reproducibly, which is what human brains can't do.

 AI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios, BMC Pregnancy and Childbirth (2025). DOI: 10.1186/s12884-024-07095-6

Part 2

Comment by Dr. Krishna Kumari Challa on January 31, 2025 at 1:17pm

AI-based pregnancy analysis discovers previously unknown warning signs for stillbirth and newborn complications

A new AI-based analysis of almost 10,000 pregnancies has discovered previously unidentified combinations of risk factors linked to serious negative pregnancy outcomes, including stillbirth.

The study also found that there may be up to a tenfold difference in risk for infants who are currently treated identically under clinical guidelines.

The researchers started with an existing dataset of 9,558 pregnancies, which included information on social and physical characteristics ranging from pregnant people's level of social support to their blood pressure, medical history, and fetal weight, as well as the outcome of each pregnancy. By using AI to look for patterns in the data, they identified new combinations of maternal and fetal characteristics that were linked to unhealthy pregnancy outcomes such as stillbirth.

Usually, female fetuses are at slightly lower risk for complications than male fetuses—a small but well-established effect. But the research team found that if a pregnant person has pre-existing diabetes, female fetuses are at higher risk than males.

This previously undetected pattern shows that the AI model can help researchers learn new things about pregnancy health.

The researchers were especially interested in developing better risk estimates for fetuses in the bottom 10% for weight, but not the bottom 3%. These babies are small enough to be concerning, but large enough that they are usually perfectly healthy. Figuring out the best course of action in these cases is challenging: Will a pregnancy need intensive monitoring and potentially early delivery, or can the pregnancy proceed largely as normal? Current clinical guidelines advise intensive medical monitoring for all such pregnancies, which can represent a significant emotional and financial burden.

But the researchers found that within this fetal weight class, the risk of an unhealthy pregnancy outcome varied widely, from no riskier than an average pregnancy to nearly ten times the average risk. The risk was based on a combination of factors such as fetal sex, presence or absence of pre-existing diabetes, and presence or absence of a fetal anomaly such as a heart defect.

For humans or AI models, estimating pregnancy risks involves taking a very large number of variables into account, from maternal health to ultrasound data. Experienced clinicians can weigh all these variables to make individualized care decisions, but even the best doctors probably wouldn't be able to quantify exactly how they arrived at their final decision. Human factors like bias, mood, or sleep deprivation almost inevitably creep into the mix and can subtly skew judgment calls away from ideal care.

To help address this problem, the researchers used a type of model called "explainable AI," which provides the user with the estimated risk for a given set of pregnancy factors and also includes information on which variables contributed to that risk estimation, and how much.

Part 1

Comment by Dr. Krishna Kumari Challa on January 27, 2025 at 9:13am

New water purification technology helps turn seawater into drinking water without using tons of chemicals

Water desalination plants could replace expensive chemicals with new carbon cloth electrodes that remove boron from seawater, an important step of turning seawater into safe drinking water.

A study describing the new technology has been published in Nature Water.

Boron is a natural component of seawater that becomes a toxic contaminant in drinking water when it sneaks through conventional filters for removing salts. Seawater's boron levels are around twice as high as the World Health Organization's most lenient limits for safe drinking water, and five to 12 times higher than the tolerance of many agricultural plants.

 Most reverse osmosis membranes don't remove very much boron, so desalination plants typically have to do some post treatment to get rid of the boron, which can be expensive. So researchers developed a new technology that's fairly scalable and can remove boron in an energy-efficient way compared to some of the conventional technologies.

In seawater, boron exists as electrically neutral boric acid, so it passes through reverse osmosis membranes that typically remove salt by repelling electrically charged atoms and molecules called ions. To get around this problem, desalination plants normally add a base to their treated water, which causes boric acid to become negatively charged. Another stage of reverse osmosis removes the newly charged boron, and the base is neutralized afterward by adding acid. Those extra treatment steps can be costly.

The new device now developed  reduces the chemical and energy demands of seawater desalination, significantly enhancing environmental sustainability and cutting costs by up to 15 percent, or around 20 cents per cubic meter of treated water.

The new electrodes remove boron by trapping it inside pores studded with oxygen-containing structures. These structures specifically bind with boron while letting other ions in seawater pass through, maximizing the amount of boron they can capture.

But the boron-catching structures still need the boron to have a negative charge. Instead of adding a base, the charge is created by splitting water between two electrodes, creating positive hydrogen ions and negative hydroxide ions. The hydroxide attaches to boron, giving it a negative charge that makes it stick to the capture sites inside the pores in the positive electrode. Capturing boron with the electrodes also enables treatment plants to avoid spending more energy on another stage of reverse osmosis. Afterward, the hydrogen and hydroxide ions recombine to yield neutral, boron-free water.

 Weiyi Pan et al, A highly selective and energy efficient approach to boron removal overcomes the Achilles heel of seawater desalination, Nature Water (2025). DOI: 10.1038/s44221-024-00362-y

Comment by Dr. Krishna Kumari Challa on January 26, 2025 at 12:26pm

Why hibernating animals don't dream

Because hibernation isn’t the same as sleep. 

Sleep is a more physiologically ‘active’ state. Hibernation, in contrast, requires animals (like this hedgehog, above) to substantially reduce all activities to conserve energy.

Hibernating animals reduce their breathing rate, lower their body temperature and decrease their metabolic rate to around five per cent of their usual levels. There’s simply not enough brain activity while an animal is hibernating to enable dreaming.
There is one exception, however: the fat-tailed lemur. As the only primate to hibernate, scientists have observed them having periods of rapid eye movement (REM) sleep.

Comment by Dr. Krishna Kumari Challa on January 25, 2025 at 11:54am

Scientists trace deadly cell-to-cell message chain that spreads in sepsis

Dying cells prick their neighbours with a lethal message. This may worsen sepsis, researchers  report in the Jan. 23 issue of Cell. Their findings could lead to a new understanding of this dangerous illness.

Sepsis is one of the most frequent causes of death worldwide, according to the World Health Organization (WHO), killing 11 million people each year. It's characterized by runaway inflammation, usually sparked by an infection. It can lead to shock, multiple organ failure, and death if treatment is not rapid enough or effective.

But recent research has shown that it isn't actually the infection that causes the spiraling inflammation: it's the cells caught up in it. Even if those cells aren't infected, they act as if they are, and die. As they die, they send out messages to other cells. Those messages somehow cause the recipient cells to die.

If scientists understood what caused this deadly message chain, they might be able to stop it. And that could help heal sepsis.

The deadly message mystery may now be solved. It appears that the "messages" are a byproduct of the cells trying to stay alive.

The process starts with cells that really are infected. To prevent the infection from spreading, those cells destroy themselves by sending a protein called gasdermin-D to their surface. Several gasdermin-D proteins will link together to create a round pore on the cell, like a hole punched in a balloon. The cell's contents leak out, the cell collapses, and dies.

But the collapse isn't inevitable. Sometimes cells can act quickly and eject the section of their surface membrane with the gasdermin-D pore. The cell then zips the membrane closed and survives. The ejected membrane forms a little bubble, called a vesicle , that just happens to carry the deadly gasdermin-D pore. The vesicle floats around, and when it encounters a cell nearby, that deadly gasdermin-D pore punches into the healthy nearby cell's membrane and causes that cell to spill and die.

When a dying cell releases these vesicles, they can transplant these pores to a neighboring cell's surface, which leads to the neighboring cell's death. 

 In other words, the deadly messages are a side effect of cells just trying to save themselves. A group of dying cells can release enough gasdermin-D vesicles to kill a considerable number of nearby cells. That spreading message of death fuels the spiraling inflammation of sepsis.

Researchers are now looking for a way to tamp down the deadly gasdermin-D vesicles. If successful, it could lead to a treatment for inflammatory diseases like sepsis. 

 Skylar S. Wright et al, Transplantation of gasdermin pores by extracellular vesicles propagates pyroptosis to bystander cells, Cell (2024). DOI: 10.1016/j.cell.2024.11.018

Comment by Dr. Krishna Kumari Challa on January 25, 2025 at 11:45am

The researchers also found that five astronauts had a choroidal thickness greater than 400 micrometers, which was not correlated with age, gender or previous space experience.

Weightlessness alters the distribution of blood in the body, increasing blood flow to the head and slowing venous circulation in the eye. This is probably what causes the expansion of the choroid, the vascular layer that nourishes the retina.
According to the researchers, the expansion of the choroid during weightlessness could stretch the collagen in the sclera, the white outer layer of the eye, causing long-lasting changes in the eye's mechanical properties.

They also think that blood pulsations under microgravity can create a water-hammer effect in which sudden changes in blood-flow-pressure cause a mechanical shock to the eye, leading to significant tissue remodeling.
According to the researchers, these ocular changes are generally not cause for concern when the space mission lasts six to 12 months. Although 80% of the astronauts they studied developed at least one symptom, their eyes returned to normal once back on Earth.

In most cases, wearing corrective eyeglasses was sufficient to correct the symptoms developed aboard the ISS.

However, the research community and international space agencies are cautious about the consequences of longer missions, such as a flight to Mars. The eye-health effects of prolonged exposure to microgravity remain unknown, and no preventive or palliative measures now exist.

Marissé Masís Solano et al, Ocular Biomechanical Responses to Long-Duration Spaceflight, IEEE Open Journal of Engineering in Medicine and Biology (2024). DOI: 10.1109/OJEMB.2024.3453049

Part 2

Comment by Dr. Krishna Kumari Challa on January 25, 2025 at 11:42am

Astronauts' eyes weaken during long space missions, raising concerns for Mars travel

The low levels of gravity (microgravity) in space cause significant changes in astronauts' eyes and vision after six to 12 months aboard the International Space Station (ISS), according to a study published in the IEEE Open Journal of Engineering in Medicine and Biology.

Researchers found that at least 70% of astronauts on the ISS have been affected by spaceflight-associated neuro-ocular syndrome, or SANS.

They analyzed data collected by the Canadian team at NASA on 13 astronauts who spent between 157 and 186 days on the ISS.

The subjects had an average age of 48 and came from the U.S., European, Japanese and Canadian space agencies; 31% were women; eight were on their first mission.

The researchers compared three ocular parameters before and after the astronauts' space missions: ocular rigidity, intraocular pressure, and ocular pulse amplitude.
They measured ocular rigidity using optical coherence tomography with a customized video module to improve the quality of images of the choroid. The other two parameters, intraocular pressure and ocular pulse amplitude, were measured using tonometry.

The study found significant changes in the biomechanical properties of the astronauts' eyes: a 33% decrease in ocular rigidity, an 11% decrease in intraocular pressure, and a 25% reduction in ocular pulse amplitude.

These changes were accompanied by symptoms including reduced eye size, altered focal field and, in some cases, optic nerve edema and retinal folds.

Part 1

Comment by Dr. Krishna Kumari Challa on January 25, 2025 at 11:39am

Research reveals how specific types of liver immune cells are required to deal with injury

Our livers contain many different types of immune cells. New research  now reveals that a specific activation state of one of these cell types is required for tissue repair following injury. This suggests these cells may be useful as new therapeutic targets for various liver conditions. The work appears in the journal Immunity.

Macrophages are specialized immune cells located in every tissue of the body, where they play crucial roles in maintaining tissue homeostasis, responding to injury, and facilitating tissue repair. In the healthy liver, most macrophages are classified as Kupffer cells (KCs). However, upon liver injury, as seen, for example, in obesity, another subset of macrophages called lipid-associated macrophages (LAMs) is recruited.

This work shows that the LAM phenotype is critical for liver repair. Moreover, this research revealed that the KCs are not static post-injury, as previously thought, and instead adapt to the new microenvironment also taking on a LAM-like phenotype, allowing them to also participate in the repair.

Federico F. De Ponti et al, Spatially restricted and ontogenically distinct hepatic macrophages are required for tissue repair, Immunity (2025). DOI: 10.1016/j.immuni.2025.01.002

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Comment by Dr. Krishna Kumari Challa on January 25, 2025 at 11:30am

Immune checkpoint inhibitors have revolutionized cancer treatment. But not everyone responds well to these drugs. This study found that patients whose tumors had more mitochondrial mutations were less likely to benefit from checkpoint inhibitors, likely because the mitochondrial hack already compromised their T-cells.

Researchers blocked extracellular vesicle release from cancer cells using a compound called GW4869, which inhibits the production of small extracellular vesicle-like exosomes. Applying this inhibitor in their models showed a significant reduction in mitochondrial transfer from cancer cells to T-cells. This intervention helped prevent the T-cells from taking up damaged mitochondria, reducing their dysfunction.

As a result, T-cells showed improved energy production, reduced markers of exhaustion, and a better ability to perform their immune functions. The blocking strategy restored the effectiveness of immune checkpoint inhibitors, particularly in tumors with high levels of mitochondrial transfer. These findings suggest that targeting extracellular vesicles could be a promising strategy to counteract cancer's immune-evasion tactic.
Typically, science works in small, iterative steps toward discovery, with each new element of knowledge putting a piece of the larger puzzle into place. This discovery helps explain why some treatments are ineffective and discovers the mechanism behind their ineffectiveness. Remarkably, it also found a potential solution, representing a significant leap for future research to build from.

Hideki Ikeda et al, Immune evasion through mitochondrial transfer in the tumour microenvironment, Nature (2025). DOI: 10.1038/s41586-024-08439-0

Jonathan R. Brestoff, Mitochondrial swap from cancer to immune cells thwarts anti-tumour defences, Nature (2025). DOI: 10.1038/d41586-025-00077-4

Part 2

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