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Comment by Dr. Krishna Kumari Challa on January 31, 2025 at 2:01pm

The team then studied the impacts of the structural variation on the human cell lines. Using genomic sequencing, the team was able to take 'snapshots' of the human cells and their 'shuffled' genomes over the course of a few weeks, watching which cells survived and which died.

As expected, they found that when structural variation deleted essential genes, this was heavily selected against and the cells died. However, they found that groups of cells with large-scale deletions in the genomes that avoided essential genes survived.

The team also conducted RNA sequencing of the human cell lines, which measures gene activity, known as gene expression. This revealed that large-scale deletions of the genetic code, especially in non-coding regions, did not seem to impact the gene expression of the rest of the cell.

The researchers suggest that human genomes are extremely tolerant of structural variation, including variants that change the position of hundreds of genes, as long as essential genes are not deleted.

In another study related to this  another research  team used a different approach, adding recombinase sites to transposons—mobile genetic elements—that randomly integrated in the genomes of human cell lines and mouse embryonic stem cells.

Using their method, they demonstrated that the effects of the induced structural variants can be read out using single-cell RNA sequencing. This advance paves the way for large screens of structural variant impact, potentially improving the classification of structural variants found in human genomes as benign or clinically significant.

Both studies came to similar conclusions that human genomes are surprisingly tolerant to some substantial structural changes, although the full extent of this tolerance remains to be explored in future studies enabled by these technologies.

Jonas Koeppel et al, Randomizing the human genome by engineering recombination between repeat elements, Science (2025). DOI: 10.1126/science.ado3979. www.science.org/doi/10.1126/science.ado3979

Science (2025). DOI: 10.1126.science.ado5978

part2

Comment by Dr. Krishna Kumari Challa on January 31, 2025 at 2:00pm

Complex engineering of human cell lines reveals genome's unexpected resilience to structural changes

The most complex engineering of human cell lines ever has been achieved by scientists, revealing that our genomes are more resilient to significant structural changes than was previously thought.

Researchers used CRISPR prime editing to create multiple versions of human genomes in cell lines, each with different structural changes. Using genome sequencing, they were able to analyze the genetic effects of these structural variations on cell survival .

The research, published in Science, shows that as long as essential genes remain intact, our genomes can tolerate significant structural changes, including large deletions of the genetic code. The work opens the door to studying and predicting the role of structural variation in disease.

Structural variation is a change in the structure of an organism's genome, such as deletions, duplications and inversions of the genetic sequence. These structural changes to the genome can be significant, sometimes affecting hundreds to many thousands of nucleotides—the basic building blocks of DNA and RNA.

Structural variants are associated with developmental diseases and cancer. However, our ability to study the effects of structural variation in the genomes of mammals, and the role they play in disease, has been difficult due to the inability to engineer these genetic changes.

To overcome this challenge,  researchers  set out to develop new approaches for creating and studying structural variation.

In a new study, the team used a combination of CRISPR prime editing and human cell lines—groups of human cells in a dish—to generate thousands of structural variants in human genomes within a single experiment.

To do this, researchers used prime editing to insert a recognition sequence into the genomes of the human cell lines to target with recombinase—an enzyme that enabled the team to 'shuffle' the genome.

By inserting these recombinase handles into repetitive sequences, which are hundreds and thousands of identical sequences in the genome, with a single prime editor they were able to integrate up to almost 1,700 recombinase recognition sites into each cell line.

This resulted in more than 100 random large-scale genetic structural changes per cell. This is the first time that it's been possible to 'shuffle' a mammalian genome, especially at this scale.

part1

Comment by Dr. Krishna Kumari Challa on January 31, 2025 at 1:40pm

Your fridge still uses tech from the 50s, but scientists have an update

Researchers report on Jan. 30 in the journal Joule that a more efficient and environmentally friendly form of refrigeration might be on the horizon. The new technology is based on thermogalvanic cells that produce a cooling effect by way of a reversible electrochemical reaction.

Thermogalvanic refrigeration is cheaper and more environmentally friendly than other cooling methods because it requires a far lower energy input, and its scalability means that it could be used for various applications—from wearable cooling devices to industrial-grade scenarios.

Thermogalvanic cells use the heat produced by reversible electrochemical reactions to create electrical power. In theory, reversing this process—applying an external electrical current to drive electrochemical reactions—enables cooling power to be generated.

Previous studies have shown that thermogalvanic cells have a limited potential to produce cooling power, but  this new work was able to dramatically increase this potential by optimizing the chemicals used in the technology.

By tweaking the solutes and solvents used in the electrolyte solution, the researchers were able to improve the hydrogalvanic cell's cooling power. They used a hydrated iron salt containing perchlorate, which helped the iron ions dissolve and dissociate more freely compared to other previously tested iron-containing salts such as ferricyanide.
By dissolving the iron salts in a solvent containing nitriles rather than pure water, the researchers were able to improve the hydrogalvanic cell's cooling power by 70%.

The optimized system was able to cool the surrounding electrolyte by 1.42 K, which is a big improvement compared to the 0.1 K cooling capacity reported by previously published thermogalvanic systems.

Looking ahead, the team plans to continue optimizing their system's design and is also investigating potential commercial applications.

Solvation entropy engineering of thermogalvanic electrolytes for efficient electrochemical refrigeration, Joule (2025). DOI: 10.1016/j.joule.2025.101822. www.cell.com/joule/fulltext/S2542-4351(25)00003-0

Comment by Dr. Krishna Kumari Challa on January 31, 2025 at 1:35pm

Mast cells are culprits in a range of inflammatory skin conditions and allergic reactions, but they're also important for protecting against bacteria and other pathogens. As such, the researchers wondered if scratching-induced activation of mast cells could affect the skin microbiome.
The researchers showed that scratching reduced the amount of Staphylococcus aureus, the most common bacteria involved in skin infections, on the skin.
The finding that scratching improves defense against Staphylococcus aureus suggests that it could be beneficial in some contexts. But the damage that scratching does to the skin probably outweighs this benefit when itching is chronic.

Andrew W. Liu et al, Scratching promotes allergic inflammation and host defense via neurogenic mast cell activation, Science (2025). DOI: 10.1126/science.adn9390. www.science.org/doi/10.1126/science.adn9390

Part 2

Comment by Dr. Krishna Kumari Challa on January 31, 2025 at 1:33pm

Why you shouldn't scratch an itchy rash

New research published in the journal Science uncovers how scratching aggravates inflammation and swelling in a mouse model of a type of eczema called allergic contact dermatitis.

Scratching is often pleasurable, which suggests that, in order to have evolved, this behaviour must provide some kind of benefit. This new study helps resolve this paradox by providing evidence that scratching also provides defense against bacterial skin infections.

Allergic contact dermatitis is an allergic reaction to allergens or skin irritants—including poison ivy and certain metals such as nickel—leading to an itchy, swollen rash. Succumbing to the often-irresistible urge to scratch triggers further inflammation that worsens symptoms and slows healing.

To figure out what drives this vicious cycle,  researchers used itch-inducing allergens to induce eczema-like symptoms on the ears of normal mice and those that don't get itchy because they lack an itch-sensing neuron.

When normal mice were allowed to scratch, their ears became swollen and filled with inflammatory immune cells called neutrophils. In contrast, inflammation and swelling were much milder in normal mice that couldn't scratch because they wore tiny Elizabethan collars, similar to a cone that a dog might sport after a visit to the vet, and in animals that lacked the itch-sensing neuron. This experiment confirmed that scratching further aggravates the skin.

Next, the researchers showed that scratching causes pain-sensing neurons to release a compound called substance P. In turn, substance P activates mast cells, which are key coordinators of inflammation that drive itchiness and inflammation via recruitment of neutrophils.

In contact dermatitis, mast cells are directly activated by allergens, which drives minor inflammation and itchiness.

In response to scratching, the release of substance P activates mast cells through a second pathway, so the reason that scratching triggers more inflammation in the skin is because mast cells have been synergistically activated through two pathways.

Part 1

Comment by Dr. Krishna Kumari Challa on January 31, 2025 at 1:26pm

Successfully treating sepsis would be a multipurpose life-saver, preventing mortality regardless of the illness that triggered it. Viral sepsis is a major cause of deaths triggered by severe COVID-19, while many deaths in historical pandemics like the 1919 influenza pandemic and the bubonic plague are thought to have resulted from sepsis.

If we can tackle sepsis, we might be able to protect ourselves against the worst consequences and the highest death tolls in future pandemics, no matter what kind of infection causes them. Since immune dysregulation linked to sepsis can linger, causing symptoms similar to post-viral syndromes like long COVID-19, learning to treat this could also benefit some chronic illness patients.

But to make this happen, the researchers caution, more funding and larger studies will be needed.
The omics methods that underlie systems immunology are relatively expensive on a per patient basis. It will require a concerted drive from stakeholders to generate the data needed for further insights. We need to invest in larger omics studies of patients, develop new animal and organoid models that reflect sepsis heterogeneity, and invest in early diagnostics for sepsis and treatments that correct or supplement defective immunity in sepsis patients.

Deciphering sepsis: transforming diagnosis and treatment through systems immunology, Frontiers in Science (2025). DOI: 10.3389/fsci.2024.1469417

Part 2

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

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