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Comment by Dr. Krishna Kumari Challa on November 28, 2024 at 8:54am

Brains grew faster as humans evolved

Modern humans, Neanderthals, and other recent relatives on our human family tree evolved bigger brains much more rapidly than earlier species, a new study of human brain evolution has found.

Scientists found that brain size increased gradually within each ancient human species rather than through sudden leaps between species. The research, published November 26 in the Proceedings of the National Academy of Sciences, overturns long-standing ideas about human brain evolution.

The team assembled the largest-ever dataset of ancient human fossils spanning 7 million years and used advanced computational and statistical methods to account for gaps in the fossil record. These innovative approaches provided the most comprehensive view yet of how brain size evolved over time.

This study completely changes our understanding of how human brains evolved. It was previously thought that brain size jumps dramatically between species, like new upgrades between the latest computer models. This study instead shows a steady, incremental 'software update' happening within each species over millions of years.

The research challenges old ideas that some species, like Neanderthals, were unchanging and unable to adapt and instead highlights gradual and continuous change as the driving force behind brain size evolution.

Big evolutionary changes don't always need dramatic events. They can happen through small, gradual improvements over time, much like how we learn and adapt today, say the researchers.

The researchers also uncovered a striking pattern: While larger-bodied species generally had bigger brains, the variation observed within an individual species did not consistently correlate with body size. Brain size evolution across long evolutionary timescales extending millions of years is therefore shaped by different factors to those observed within individual species—highlighting the complexity of evolutionary pressures on brain size.

The conclusion:  Our hallmark large brains arose primarily from gradual changes within individual species.

Thomas A. Püschel et al, Hominin brain size increase has emerged from within-species encephalization, Proceedings of the National Academy of Sciences (2024). DOI: 10.1073/pnas.2409542121

Comment by Dr. Krishna Kumari Challa on November 28, 2024 at 8:26am

Comment by Dr. Krishna Kumari Challa on November 28, 2024 at 8:22am

The sound of traffic increases stress and anxiety, research shows

Manmade sounds such as vehicle traffic can mask the positive impact of nature soundscapes on people's stress and anxiety, according to a study published November 27, 2024, in the open-access journal PLOS ONE 

Existing research shows that natural sounds, like birdsong, can lower blood pressure, heart, and respiratory rates, as well as self-reported stress and anxiety. Conversely, anthropogenic soundscapes, like traffic or aircraft noise, are hypothesized to have negative effects on human health and well-being in a variety of ways.

The study found that listening to a natural soundscape reduced self-reported stress and anxiety levels, and also enhanced mood recovery after a stressor. However, the benefits of improved mood associated with the natural soundscape was limited when traffic sounds were included.

The natural soundscape alone was associated with the lowest levels of stress and anxiety, with the highest levels reported after the soundscape that included 40 miles per hour traffic.

The authors conclude that reducing traffic speed in urban areas might influence human health and well-being not only through its safety impacts, but also through its effect on natural soundscapes.

The study shows that listening to natural soundscapes can reduce stress and anxiety, and that anthropogenic sounds such as traffic noise can mask potential positive impacts. Reducing traffic speeds in cities is therefore an important step towards more people experiencing the positive effects of nature on their health and well-being.

Natural soundscapes enhance mood recovery amid anthropogenic noise pollution, PLOS ONE (2024). DOI: 10.1371/journal.pone.0311487

Comment by Dr. Krishna Kumari Challa on November 28, 2024 at 8:09am

The researchers proposed a mathematical definition of cell death. It's based on the way cellular states, including metabolism, can be controlled by modulating the activities of enzymes. They define dead states as those states from which cells cannot return to an apparent "living" state, regardless of the modulation of any biochemical processes.
This led them to develop a computational method for quantifying the life-death boundary, which they call "stoichiometric rays." The method was developed by focusing on enzymatic reactions and the second law of thermodynamics, which states that systems naturally move from ordered to disordered states.

Researchers could use these methods to better understand, control, and possibly even reverse, cellular death in controlled lab experiments.
The conclusion : We naively believe that death is irreversible, but it is not so trivial and does not have to be the case. Should death come more under our control, human beings, our understanding of life, and society will change completely. In this sense, to understand death is crucial in terms of science and also in terms of social implications. This is one step towards that goal.

Yusuke Himeoka et al, A theoretical basis for cell deaths. Physical Review Research (2024). On arXiv. DOI: 10.48550/arxiv.2403.02169

Part 2

Comment by Dr. Krishna Kumari Challa on November 28, 2024 at 8:05am

A mathematical definition of cell death?

Cellular death is a fundamental concept in the biological sciences. Given its significance, its definition depends on the context in which it takes place, and lacks a general mathematical definition.

Researchers now propose a new mathematical definition of death based on whether a potentially dead cell can return to a predefined "representative state of living," which are the states of being that we can confidently call "alive." The researchers' work could be useful for biological researchers and future medical research.

The paper is published in Physical Review Research.

While it's not something we like to think about, death comes for us all eventually, whether you're an animal, a plant, or even a cell. And even though we can all differentiate between what is alive and dead, it might be surprising to know that death at a cellular level lacks a widely recognized mathematical definition.

Given that cell death plays such an important role in various biological processes and can have important health implications, it's of critical importance to understand what we really mean by cellular death, especially in research.

The scientific goal is to understand the inherent difference between life and nonlife, mathematically; why the transition from nonlife to life is so difficult, while the other way around is so easy. 

The  aim in this project was to develop a mathematical definition and computational method to quantify the life-death boundary. Researchers were able to do this by exploiting an important feature of biological reaction systems, specifically enzymatic reactions within cells.

Part 1

Comment by Dr. Krishna Kumari Challa on November 27, 2024 at 11:42am

Long COVID brain fog linked to lung function

In patients with long COVID, lower pulmonary gas exchange may be associated with impaired cognitive function, according to a study presented at the annual meeting of the Radiological Society of North America (RSNA).

People with long COVID may exhibit a wide variety of symptoms, including difficulty concentrating ("brain fog"), change in sense of smell or taste, fatigue, joint or muscle pain, dyspnea (shortness of breath), digestive symptoms, and more. These symptoms may persist for weeks, months, or even years after COVID-19 infection.

In pulmonary gas exchange, oxygen moves from the lungs to the bloodstream, while carbon dioxide moves from the bloodstream to the lungs.

If these findings can be generalized to the long COVID population, the study suggests that there may be a causative relationship between cognitive dysfunction and lung dysfunction, suggesting a potential treatment strategy using methods that target improved gas exchange, say the researchers.

Source: https://www.rsna.org/annual-meeting

Comment by Dr. Krishna Kumari Challa on November 27, 2024 at 11:36am

This work also tells us how important it is to move away from a 'one-size-fits-all' approach to managing type 2 diabetes, and we hope that this will allow us to find ways to offer more precise treatments that treat the condition more effectively and reduces the development of diabetes complications.

Genes & Health will contribute to future efforts to ensure that precision medicine approaches are developed and bring real benefits to south Asian communities living with, and at risk of, type 2 diabetes.

Genetic basis of early onset and progression of type 2 diabetes in south Asians, Nature Medicine (2024). DOI: 10.1038/s41591-024-03317-8. www.nature.com/articles/s41591-024-03317-8 

Part 2

Comment by Dr. Krishna Kumari Challa on November 27, 2024 at 11:34am

Why are South Asians more diabetic prone?

A genetic predisposition to having lower insulin production and less healthy fat distribution are major causes of early-onset type 2 diabetes in  South Asian people, according to new research. These genetic factors also lead to quicker development of health complications, earlier need for insulin treatment, and a weaker response to some medications.

The findings, published in Nature Medicine, reinforce the need to understand how genetic variation across different population groups can influence the onset of diseases, treatment responses, and disease progression.

Key discoveries from the study include:

• Genetic signatures in South Asians: The younger age of onset in South Asians is strongly linked to genetic signatures that lead to both lower insulin production and unfavorable patterns of body fat distribution and obesity. The most significant genetic signature influencing whether a South Asian person develops type 2 diabetes, and at a young age, is a reduced ability of pancreatic beta cells to produce insulin. This genetic signature also increases the risk of gestational diabetes and the progression of gestational diabetes to type 2 diabetes after pregnancy.

• • Treatment responses: The genetic signatures identified in the study provide vital clues about how different people may respond to type 2 diabetes treatments. For example, individuals with high genetic risk for low insulin production were less likely to respond to common medications such as sodium-glucose co-transporter 2 inhibitors and were more likely to require insulin therapy.

  • High genetic-risk group identified: The study identified a subset of people with extreme genetic signatures for both low insulin production and unfavorable fat distribution. These individuals were found to develop type 2 diabetes an average of eight years earlier and at lower body mass index. Over time, these individuals were more likely to need insulin treatment and were at higher risk for diabetes complications such as eye and kidney disease.

Part 1

Comment by Dr. Krishna Kumari Challa on November 27, 2024 at 11:19am

To validate their findings further, the researchers used computer simulations to create different virtual tumors, some with surface growth and others with volume growth. The researchers compared the patterns of mutations from the simulations to the patterns found in the real tumor data.

They found that mutation patterns in the real tumors matched the patterns from the volume growth simulations but not the surface growth simulations.

One of the limitations of the study is that it focused on liver cancer, so the findings might not apply universally to all types of cancer. Another limitation is that the study mainly provides insights into the early stages of tumor growth, which might not fully capture the behavior of larger or metastatic types of cancer.

Arman Angaji et al, High-density sampling reveals volume growth in human tumours, eLife (2024). DOI: 10.7554/eLife.95338.2

Part 2

Comment by Dr. Krishna Kumari Challa on November 27, 2024 at 11:18am

Spatial genomics approach shows cancers grow uniformly, challenging the idea of 'two-speed' entities

Researchers have discovered that cancer grows uniformly throughout its mass, rather than at the outer edges. The work, published in the journal eLife, challenges decades-old assumptions about how the disease grows and spreads.

The researchers challenge the old idea  that a tumour is a 'two-speed' entity with rapidly dividing cells on the surface and slower activity in the core. For the last 50 years, researchers have hypothesized that tumors grow faster at their outer edges. Cancer cells on the surface are thought to have natural advantages compared to cells deep within. For example, peripheral cells have better access to nutrients and oxygen from surrounding healthy tissues. They can also get rid of their waste more easily. As a tumor grows, its center gets further and further away from the blood vessels in the area where it is growing. The cells in a tumor's core get less and less oxygen and nutrients. The cells are also under more mechanical pressure, with compression limiting their ability to divide.

Instead, this work shows they are uniformly growing masses, where every region is equally active and has the potential to harbour aggressive mutations.

These  findings have implications for tumor evolution. The constant churn of cells dying and being replaced by new ones throughout the tumour volume gives cancer many opportunities for evolutionary innovations, such as escaping from immune surveillance.

The researchers made the discovery thanks to spatial genomics, a technique used to study the genetic information of cells in their exact locations within a tissue.

The team obtained data from previous studies where hundreds of small samples were taken from different parts of liver tumors, both in two- and three-dimensional space. This provided a detailed map of the mutations throughout the tumor.
They looked at the mutations in each of the samples, and developed a method to measure the direction and spread of these mutations, allowing them to calculate the angles between the positions of parent cells and their mutated offspring.

In the surface growth model, these angles would point outwards. Instead, the researchers found the angles were spread evenly in all directions, showing uniform growth throughout the tumor.

The study also looked at how mutations were spread within the tumor. If cancer cells grew mostly at the edges, mutations would be more clustered. They found that mutations were spread out, suggesting that cells were dividing all over the tumor.
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