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  1. DATE: July 28, 2026 at 06:00PM
    SOURCE: PSYPOST.ORG

    ** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
    -------------------------------------------------

    TITLE: Elevated body mass index might lead to lower cortical thickness, study finds

    URL: psypost.org/elevated-body-mass

    A Mendelian randomization study found that elevated body mass index might be a cause of lower cortical thickness. This was particularly prominent in the precentral and fusiform gyrus regions of the brain. The paper was published in Molecular Psychiatry.

    Obesity is a chronic condition characterized by an excessive accumulation of body fat that can impair health and well-being. It is commonly assessed using body mass index, or BMI, which is calculated by dividing a person’s weight in kilograms by the square of their height in meters. A BMI between 25 and 30 suggests a person is overweight, while a BMI of 30 or more indicates obesity. Although BMI is useful for population-level screening, it is a rough measure that does not directly evaluate body fat or show how fat is distributed throughout the body.

    Obesity develops through an interaction of genetic, biological, psychological, social, and environmental factors. In modern environments, high-calorie foods tend to be readily available while opportunities for everyday physical activity tend to be reduced. Studies provide evidence that diets based on foods rich in both easily digestible sugars and fats contribute heavily to weight gain. This is exactly the composition of many popular modern foods.

    Obesity increases the risk of many adverse health conditions, such as type 2 diabetes, cardiovascular disease, sleep apnea, joint problems, and some cancers. It can also affect mental health and expose people to stigma and discrimination, which may reduce their quality of life.

    Study author Jodie N. Painter and her colleagues note that previous research links obesity to certain structural changes in the brain. Until now, it was unknown whether these changes preceded obesity or were the consequences of weight gain. Fat tissue secretes proteins called pro-inflammatory cytokines that cause low-grade inflammation in individuals with obesity. The researchers suspected this inflammation could potentially lead to the observed adverse changes in the brain.

    The authors conducted a study using Mendelian randomization to see whether an elevated body mass index causes changes in the brain. The brain changes were measured as reduced cortical thickness, which refers to the depth of the brain’s outer layer of gray matter. Mendelian randomization is a research approach that uses naturally inherited genetic differences as proxies for environmental exposures. This helps scientists test whether an observed association is likely to reflect a direct cause-and-effect relationship.

    This analysis was based on genome-wide association studies, which scan the entire genetic codes of large populations to find variations linked to specific traits. The genetic data for body mass index came from large international research consortiums that pool health information from hundreds of thousands of people. Specifically, the researchers used combined genetic data from up to 681,275 individuals of European ancestry. Data for the additional risk factors were drawn from other previously published genetic scans.

    These additional factors included estimates of visceral fat, which is fat stored deep inside the belly around internal organs. The researchers also looked at fasting blood sugar, triglycerides, and high-density lipoprotein, a type of cholesterol that helps clear other cholesterols from the bloodstream. Finally, they included blood pressure and C-reactive protein, a substance that indicates the level of inflammation in the body.

    Neuroimaging outcome data came from another massive international scientific collaborative group that studies the brain. This group provided genetic studies of global and regional cortical thickness in up to 23,183 individuals. The results showed that a higher body mass index was associated with lower average global cortical thickness. This association was particularly prominent in the precentral and fusiform gyrus regions of the brain.

    The precentral gyrus controls voluntary movement, while the fusiform gyrus supports high-level visual recognition, especially of faces and words. More visceral fat and higher levels of the inflammatory blood marker C-reactive protein were also associated with lower cortical thickness. These associations tended to be stronger in areas where lower cortical thickness was already linked to a higher body mass index. In contrast, the researchers found very few associations between cortical thickness and blood pressure or metabolic blood markers.

    The study authors concluded that their findings provide evidence for a causal effect of body mass index on lower cortical thickness. They recommend future research to explore how this effect on brain structure might increase the risk for neuropsychiatric conditions.

    The study contributes to the scientific understanding of the structural brain changes induced by obesity. However, the scientists primarily investigated whether an elevated body mass index causes brain changes, rather than the reverse. A Mendelian randomization study like this can strengthen causal inferences but cannot provide definitive proof, as the research design depends on a number of assumptions.

    The paper, “Deciphering the causal influence of BMI and related metabolic, inflammatory, and cardiovascular factors on brain structure: a Mendelian Randomization Study,” was authored by Jodie N. Painter, Alexander Refisch, Moritz Rau, Martin Walter, Scott Mackey, Jennifer Laurent, Paul M. Thompson, Katrina L. Grasby, Tomas Hajek, Sarah E. Medland, and Nils Opel.

    URL: psypost.org/elevated-body-mass

    -------------------------------------------------

    Private, vetted email list for mental health professionals: clinicians-exchange.org

    Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

    -------------------------------------------------

    #psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #BMI #ObesityBrainLink #CorticalThickness #MendelianRandomization #BrainStructure #PrecentralGyrus #FusiformGyrus #Inflammation #NeuropsychiatricRisk #BiomedicalResearch

  2. DATE: July 28, 2026 at 06:00PM
    SOURCE: PSYPOST.ORG

    ** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
    -------------------------------------------------

    TITLE: Elevated body mass index might lead to lower cortical thickness, study finds

    URL: psypost.org/elevated-body-mass

    A Mendelian randomization study found that elevated body mass index might be a cause of lower cortical thickness. This was particularly prominent in the precentral and fusiform gyrus regions of the brain. The paper was published in Molecular Psychiatry.

    Obesity is a chronic condition characterized by an excessive accumulation of body fat that can impair health and well-being. It is commonly assessed using body mass index, or BMI, which is calculated by dividing a person’s weight in kilograms by the square of their height in meters. A BMI between 25 and 30 suggests a person is overweight, while a BMI of 30 or more indicates obesity. Although BMI is useful for population-level screening, it is a rough measure that does not directly evaluate body fat or show how fat is distributed throughout the body.

    Obesity develops through an interaction of genetic, biological, psychological, social, and environmental factors. In modern environments, high-calorie foods tend to be readily available while opportunities for everyday physical activity tend to be reduced. Studies provide evidence that diets based on foods rich in both easily digestible sugars and fats contribute heavily to weight gain. This is exactly the composition of many popular modern foods.

    Obesity increases the risk of many adverse health conditions, such as type 2 diabetes, cardiovascular disease, sleep apnea, joint problems, and some cancers. It can also affect mental health and expose people to stigma and discrimination, which may reduce their quality of life.

    Study author Jodie N. Painter and her colleagues note that previous research links obesity to certain structural changes in the brain. Until now, it was unknown whether these changes preceded obesity or were the consequences of weight gain. Fat tissue secretes proteins called pro-inflammatory cytokines that cause low-grade inflammation in individuals with obesity. The researchers suspected this inflammation could potentially lead to the observed adverse changes in the brain.

    The authors conducted a study using Mendelian randomization to see whether an elevated body mass index causes changes in the brain. The brain changes were measured as reduced cortical thickness, which refers to the depth of the brain’s outer layer of gray matter. Mendelian randomization is a research approach that uses naturally inherited genetic differences as proxies for environmental exposures. This helps scientists test whether an observed association is likely to reflect a direct cause-and-effect relationship.

    This analysis was based on genome-wide association studies, which scan the entire genetic codes of large populations to find variations linked to specific traits. The genetic data for body mass index came from large international research consortiums that pool health information from hundreds of thousands of people. Specifically, the researchers used combined genetic data from up to 681,275 individuals of European ancestry. Data for the additional risk factors were drawn from other previously published genetic scans.

    These additional factors included estimates of visceral fat, which is fat stored deep inside the belly around internal organs. The researchers also looked at fasting blood sugar, triglycerides, and high-density lipoprotein, a type of cholesterol that helps clear other cholesterols from the bloodstream. Finally, they included blood pressure and C-reactive protein, a substance that indicates the level of inflammation in the body.

    Neuroimaging outcome data came from another massive international scientific collaborative group that studies the brain. This group provided genetic studies of global and regional cortical thickness in up to 23,183 individuals. The results showed that a higher body mass index was associated with lower average global cortical thickness. This association was particularly prominent in the precentral and fusiform gyrus regions of the brain.

    The precentral gyrus controls voluntary movement, while the fusiform gyrus supports high-level visual recognition, especially of faces and words. More visceral fat and higher levels of the inflammatory blood marker C-reactive protein were also associated with lower cortical thickness. These associations tended to be stronger in areas where lower cortical thickness was already linked to a higher body mass index. In contrast, the researchers found very few associations between cortical thickness and blood pressure or metabolic blood markers.

    The study authors concluded that their findings provide evidence for a causal effect of body mass index on lower cortical thickness. They recommend future research to explore how this effect on brain structure might increase the risk for neuropsychiatric conditions.

    The study contributes to the scientific understanding of the structural brain changes induced by obesity. However, the scientists primarily investigated whether an elevated body mass index causes brain changes, rather than the reverse. A Mendelian randomization study like this can strengthen causal inferences but cannot provide definitive proof, as the research design depends on a number of assumptions.

    The paper, “Deciphering the causal influence of BMI and related metabolic, inflammatory, and cardiovascular factors on brain structure: a Mendelian Randomization Study,” was authored by Jodie N. Painter, Alexander Refisch, Moritz Rau, Martin Walter, Scott Mackey, Jennifer Laurent, Paul M. Thompson, Katrina L. Grasby, Tomas Hajek, Sarah E. Medland, and Nils Opel.

    URL: psypost.org/elevated-body-mass

    -------------------------------------------------

    Private, vetted email list for mental health professionals: clinicians-exchange.org

    Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot

    -------------------------------------------------

    #psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #BMI #ObesityBrainLink #CorticalThickness #MendelianRandomization #BrainStructure #PrecentralGyrus #FusiformGyrus #Inflammation #NeuropsychiatricRisk #BiomedicalResearch

  3. 🧬 Ever found the perfect cell line for your project, only to discover...

    • it has 5 different names in the literature
    • another lab says it was misidentified
    • a database lists a different tissue origin

    So… which information do you trust?

    This is exactly why researchers use Cellosaurus
    👉Visit us at: lnkd.in/eKQzET_K

    By bringing together curated information on thousands of cell lines; including synonyms, origins, disease associations, references, and authentication data, Cellosaurus helps scientists quickly answer questions that would otherwise take hours of searching across papers and databases.

    Because researchers shouldn’t have to solve a detective case before starting an experiment.

    What’s the most confusing cell line naming issue you’ve encountered?

    Part of the SIB Swiss Institute of Bioinformatics biodata resource portfolio, Cellosaurus is recognized as an ELIXIR Core Data Resource and Global Biodata Coalition Global Core Biodata Resource + International Rare Diseases Research Consortium (IRDiRC) Recognized Resource
    More about SIB resources: expasy.org/

    #cellines #Cellosaurus #cellbiology #researchtools #LifeSciences #BiomedicalResearch #bioinformatics

  4. 🧬 Ever found the perfect cell line for your project, only to discover...

    • it has 5 different names in the literature
    • another lab says it was misidentified
    • a database lists a different tissue origin

    So… which information do you trust?

    This is exactly why researchers use Cellosaurus
    👉Visit us at: lnkd.in/eKQzET_K

    By bringing together curated information on thousands of cell lines; including synonyms, origins, disease associations, references, and authentication data, Cellosaurus helps scientists quickly answer questions that would otherwise take hours of searching across papers and databases.

    Because researchers shouldn’t have to solve a detective case before starting an experiment.

    What’s the most confusing cell line naming issue you’ve encountered?

    Part of the SIB Swiss Institute of Bioinformatics biodata resource portfolio, Cellosaurus is recognized as an ELIXIR Core Data Resource and Global Biodata Coalition Global Core Biodata Resource + International Rare Diseases Research Consortium (IRDiRC) Recognized Resource
    More about SIB resources: expasy.org/

    #cellines #Cellosaurus #cellbiology #researchtools #LifeSciences #BiomedicalResearch #bioinformatics

  5. RESEARCH INITIATIVES EARN ACCLAIM AMIDST GLOBAL HIGHER EDUCATION SHIFTS

    Universities win awards for new wound models. This shows research is important for medical use and helps universities get noticed.

    #WoundCare, #BiomedicalResearch, #UniversityAwards, #MedicalInnovation, #HigherEducation

    newsletter.tf/university-wound

  6. 🧠 What if missing data is not a flaw, but one of the most informative parts of a complex system?

    🔗 Informative Missingness in Nominal Data: A Graph-Theoretic Approach to Revealing Hidden Structure. Computational and Structural Biotechnology Journal (CSBJ). DOI: doi.org/10.34133/csbj.0099

    📚 CSBJ - A Science Partner Journal: spj.science.org/journal/csbj

    #DataScience #BigData #GraphTheory #ComputationalBiology #NetworkScience #Bioinformatics #SystemsBiology #BiomedicalResearch #MissingData

  7. 🧠 What if missing data is not a flaw, but one of the most informative parts of a complex system?

    🔗 Informative Missingness in Nominal Data: A Graph-Theoretic Approach to Revealing Hidden Structure. Computational and Structural Biotechnology Journal (CSBJ). DOI: doi.org/10.34133/csbj.0099

    📚 CSBJ - A Science Partner Journal: spj.science.org/journal/csbj

    #DataScience #BigData #GraphTheory #ComputationalBiology #NetworkScience #Bioinformatics #SystemsBiology #BiomedicalResearch #MissingData

  8. The Persistent Echo of Henrietta Lacks: Immortal Cells, Human Cost

    Henrietta Lacks's cells, taken without consent in 1951, fueled medical research but her family was not recognized for decades. Learn about the ethical issues.

    #HenriettaLacks, #HeLaCells, #MedicalEthics, #InformedConsent, #BiomedicalResearch

    newsletter.tf/henrietta-lacks-

  9. I'm excited that @SciPyConf is coming to #minneapolis July 13-19 on the UMN campus. Check out the schedule at scipy2026.scipy.org/schedule

    There are online tickets for those that aren't here (but why not come here) with special pricing for students and academics. In particular the Biology and Medical Sciences talks are Wed the 15th. #biomedicalResearch #python

  10. I'm excited that @SciPyConf is coming to #minneapolis July 13-19 on the UMN campus. Check out the schedule at scipy2026.scipy.org/schedule

    There are online tickets for those that aren't here (but why not come here) with special pricing for students and academics. In particular the Biology and Medical Sciences talks are Wed the 15th. #biomedicalResearch #python

  11. HHS Unveils AI Plan to Accelerate Biomedical Research

    Imagine a future where life-changing breakthroughs aren't held back by slow and familiar research methods - the Advanced Research Projects Agency for Health is making this a reality with a bold new AI plan. By harnessing the power of artificial intelligence, they aim to turbocharge biomedical research and deliver results up to ten…

    osintsights.com/hhs-unveils-ai

    #BiomedicalResearch #ArtificialIntelligence #Arpah #Healthcare #EmergingTechnologies

  12. 6/
    • Biomedical Research: The discussion contrasts observational curiosity, such as the AMNH cat sex experiments or Harry Harlow’s monkey studies, with research intended for lifesaving cures.

    • The Three R's: It highlights progress in the scientific community through Replacement (e.g., synthetic skin), Reduction (computer models), and Refinement (pain management).

    youtu.be/6lOfoKbLPDg

    #AnimalRights #Ethics #Philosophy #FactoryFarming #AnimalWelfare #BiomedicalResearch #DavidDeGrazia

  13. 6/
    • Biomedical Research: The discussion contrasts observational curiosity, such as the AMNH cat sex experiments or Harry Harlow’s monkey studies, with research intended for lifesaving cures.

    • The Three R's: It highlights progress in the scientific community through Replacement (e.g., synthetic skin), Reduction (computer models), and Refinement (pain management).

    youtu.be/6lOfoKbLPDg

    #AnimalRights #Ethics #Philosophy #FactoryFarming #AnimalWelfare #BiomedicalResearch #DavidDeGrazia

  14. 4/
    Philosophical Frameworks

    The podcast defines three tiers of moral consideration:

    1. Moral Status: Recognizing a being’s welfare for its own sake.
    2. Equal Consideration: Granting equal moral weight to comparable interests, such as the avoidance of pain.
    3. Utility-Trumping Rights: Protecting vital interests, like life or liberty, regardless of societal benefit

    youtu.be/6lOfoKbLPDg

    #AnimalRights #Ethics #Philosophy #FactoryFarming #AnimalWelfare #BiomedicalResearch

  15. 4/
    Philosophical Frameworks

    The podcast defines three tiers of moral consideration:

    1. Moral Status: Recognizing a being’s welfare for its own sake.
    2. Equal Consideration: Granting equal moral weight to comparable interests, such as the avoidance of pain.
    3. Utility-Trumping Rights: Protecting vital interests, like life or liberty, regardless of societal benefit

    youtu.be/6lOfoKbLPDg

    #AnimalRights #Ethics #Philosophy #FactoryFarming #AnimalWelfare #BiomedicalResearch

  16. 3/
    • Eastern Traditions: In contrast, the podcast highlights Jainism, Buddhism, and Hinduism, which emphasize interconnectedness and non-injury to all living things through principles like ahimsa.

    • Scientific Shifts: The narrative covers how Charles Darwin's theory of evolution and Jeremy Bentham's focus on suffering dismantled rigid mechanical hierarchies.

    youtu.be/6lOfoKbLPDg

    #AnimalRights #Ethics #Philosophy #FactoryFarming #AnimalWelfare #BiomedicalResearch #DavidDeGrazia

  17. 3/
    • Eastern Traditions: In contrast, the podcast highlights Jainism, Buddhism, and Hinduism, which emphasize interconnectedness and non-injury to all living things through principles like ahimsa.

    • Scientific Shifts: The narrative covers how Charles Darwin's theory of evolution and Jeremy Bentham's focus on suffering dismantled rigid mechanical hierarchies.

    youtu.be/6lOfoKbLPDg

    #AnimalRights #Ethics #Philosophy #FactoryFarming #AnimalWelfare #BiomedicalResearch #DavidDeGrazia

  18. 2/
    Historical and Global Perspectives

    • Western Hierarchy: The episode traces the origins of human supremacy to Aristotle, who argued that because animals lack reason, their biological purpose is to serve humans.

    • Mechanical Views: It discusses René Descartes' 17th-century view of animals as "organic machines" without consciousness or the ability to feel pain.

    youtu.be/6lOfoKbLPDg

    #AnimalRights #Ethics #Philosophy #FactoryFarming #AnimalWelfare #BiomedicalResearch #podcast

  19. 2/
    Historical and Global Perspectives

    • Western Hierarchy: The episode traces the origins of human supremacy to Aristotle, who argued that because animals lack reason, their biological purpose is to serve humans.

    • Mechanical Views: It discusses René Descartes' 17th-century view of animals as "organic machines" without consciousness or the ability to feel pain.

    youtu.be/6lOfoKbLPDg

    #AnimalRights #Ethics #Philosophy #FactoryFarming #AnimalWelfare #BiomedicalResearch #podcast

  20. Are Animals Machines or Moral Equals ?

    This podcast episode provides a detailed exploration of the ethical and philosophical frameworks surrounding animal rights and human utility. Using David de Grazia’s Animal Rights: A Very Short Introduction as a primary resource, the discussion aims to provide listeners with a philosophical toolkit to navigate complex debates on animal welfare.

    youtu.be/6lOfoKbLPDg

    #AnimalRights #Ethics #Philosophy #FactoryFarming #AnimalWelfare #BiomedicalResearch

  21. Are Animals Machines or Moral Equals ?

    This podcast episode provides a detailed exploration of the ethical and philosophical frameworks surrounding animal rights and human utility. Using David de Grazia’s Animal Rights: A Very Short Introduction as a primary resource, the discussion aims to provide listeners with a philosophical toolkit to navigate complex debates on animal welfare.

    youtu.be/6lOfoKbLPDg

    #AnimalRights #Ethics #Philosophy #FactoryFarming #AnimalWelfare #BiomedicalResearch

  22. Here's the third (and last!) entry in a series of blog posts on the #cdisc Dataset-JSON standard. This entry goes over the REST API component and potential issues with it.

    Pushing for the future of #clinicaltrial #data (and related to the #pharmaverse and #rstats folks in #biomedicalresearch) and better workflows for running those trials.

    brianrepko.github.io/blog/post

  23. Here's the third (and last!) entry in a series of blog posts on the #cdisc Dataset-JSON standard. This entry goes over the REST API component and potential issues with it.

    Pushing for the future of #clinicaltrial #data (and related to the #pharmaverse and #rstats folks in #biomedicalresearch) and better workflows for running those trials.

    brianrepko.github.io/blog/post

  24. A study in Nature shows that M101—an oxygen carrier from the marine worm *Arenicola marina*—significantly reduces inflammation and tissue destruction caused by *P. gingivalis*. A promising step for periodontal therapy! 🧫🌊🦷

    Read more: nature.com/articles/s41598-020
    #Periodontitis #Inflammation #BiomedicalResearch #ScienceNews

  25. A study in Nature shows that M101—an oxygen carrier from the marine worm *Arenicola marina*—significantly reduces inflammation and tissue destruction caused by *P. gingivalis*. A promising step for periodontal therapy! 🧫🌊🦷

    Read more: nature.com/articles/s41598-020
    #Periodontitis #Inflammation #BiomedicalResearch #ScienceNews

  26. Here's the second entry in a series of blog posts on the #cdisc Dataset-JSON standard. This entry goes over potential issues with the specification.

    Pushing for the future of #clinicaltrial #data (and related to the #pharmaverse and #rstats folks in #biomedicalresearch).

    Here's to moving past 1989 file formats in ... 2026 - in SAS, R, or Python!

    brianrepko.github.io/blog/post

  27. Here's the second entry in a series of blog posts on the #cdisc Dataset-JSON standard. This entry goes over potential issues with the specification.

    Pushing for the future of #clinicaltrial #data (and related to the #pharmaverse and #rstats folks in #biomedicalresearch).

    Here's to moving past 1989 file formats in ... 2026 - in SAS, R, or Python!

    brianrepko.github.io/blog/post

  28. Scientists have grown a tiny human "blood factory" that actually works—an advanced 3D bone marrow model made entirely from human cells! This breakthrough promises to reduce animal testing and could revolutionize blood cancer research and personalized treatments. 🩸🦴🔬 #BiomedicalResearch #Innovation sciencedaily.com/releases/2025
    #newz

  29. Scientists have grown a tiny human "blood factory" that actually works—an advanced 3D bone marrow model made entirely from human cells! This breakthrough promises to reduce animal testing and could revolutionize blood cancer research and personalized treatments. 🩸🦴🔬 #BiomedicalResearch #Innovation sciencedaily.com/releases/2025
    #newz

  30. 🔍 Can AI transform how we discover biological datasets?

    🔗 Public Omics Explorer (POE): Enabling integrative semantic search across GEO omics datasets based on PubMed publications. Computational and Structural Biotechnology Journal, DOI: doi.org/10.1016/j.csbj.2025.11

    📚 CSBJ: csbj.org/

    #Bioinformatics #Genomics #SemanticSearch #ArtificialIntelligence #BiomedicalResearch #FAIRData #OpenScience #ComputationalBiology #DataDiscovery #MachineLearning

  31. 🔍 Can AI transform how we discover biological datasets?

    🔗 Public Omics Explorer (POE): Enabling integrative semantic search across GEO omics datasets based on PubMed publications. Computational and Structural Biotechnology Journal, DOI: doi.org/10.1016/j.csbj.2025.11

    📚 CSBJ: csbj.org/

    #Bioinformatics #Genomics #SemanticSearch #ArtificialIntelligence #BiomedicalResearch #FAIRData #OpenScience #ComputationalBiology #DataDiscovery #MachineLearning

  32. This lower bound differed across disciplines, countries, journals, reaching 40% for some #subcorpora. We show that #LLMs have had an unprecedented impact on #scientificwriting in #biomedicalresearch, surpassing the effect of major world events such as the COVID pandemic

  33. Yet, many scientists use them for their scholarly writing. But how widespread is such #LLM usage in the #academicliterature? To answer this question for the field of #biomedicalresearch, we present an #unbiased, large-scale approach: We study vocabulary changes in more than 15 million biomedical

  34. #Abstract
    Large language models #LLMs like #ChatGPT can generate & revise text with human-level performance. These models come with clear limitations can produce inaccurate information & reinforce existing biases. Yet, many scientists use them for their scholarly writing. But how widespread is such LLM usage in the academic literature? To answer this question for the field of #biomedicalresearch, we present an #unbiased, large-scale approach: We study vocabulary changes in more than 15 million

  35. 🔬🧠 Researchers from our school have developed a ‘self-driving’ microscope that can predict the onset of misfolded protein aggregation, a hallmark of neurodegenerative disease, as well as analyze the biomechanical properties of these aggregates.

    #NeurodegenerativeDisease #BiomedicalResearch #MedicalInnovation

    Read more: go.epfl.ch/eST-en

  36. 🔬🧠 Researchers from our school have developed a ‘self-driving’ microscope that can predict the onset of misfolded protein aggregation, a hallmark of neurodegenerative disease, as well as analyze the biomechanical properties of these aggregates.

    #NeurodegenerativeDisease #BiomedicalResearch #MedicalInnovation

    Read more: go.epfl.ch/eST-en

  37. 🔎 How can AI-powered tools help scientists uncover hidden connections in disease research?

    🔗 Darling (v2.0): Mining disease-related databases for the detection of biomedical entity associations. Computational and Structural Biotechnology Journal, DOI: doi.org/10.1016/j.csbj.2025.06

    📚 CSBJ: csbj.org/

    #AIinScience #BiomedicalTextMining #Genomics #PrecisionMedicine #Bioinformatics #OpenScience #BiomedicalResearch #BiomedicalAI #LiteratureMining #SystemsBiology #Omics #KnowledgeDiscovery

  38. 🔎 How can AI-powered tools help scientists uncover hidden connections in disease research?

    🔗 Darling (v2.0): Mining disease-related databases for the detection of biomedical entity associations. Computational and Structural Biotechnology Journal, DOI: doi.org/10.1016/j.csbj.2025.06

    📚 CSBJ: csbj.org/

    #AIinScience #BiomedicalTextMining #Genomics #PrecisionMedicine #Bioinformatics #OpenScience #BiomedicalResearch #BiomedicalAI #LiteratureMining #SystemsBiology #Omics #KnowledgeDiscovery

  39. 🧬 Can we track nanoparticles in cells without fluorescent labels or destructive prep?

    🔗 The application of label-free Raman microscopy to monitor particle-cell interactions in in-vitro experiments. Computational and Structural Biotechnology Journal, DOI: doi.org/10.1016/j.csbj.2025.06

    📚 CSBJ Quantum Biology and Biophotonics: csbj.org/qbio

    #RamanMicroscopy #Nanotoxicology #CellBiology #LabelFreeImaging #Nanoparticles #BiomedicalResearch #TiO2 #LabelFree #Nanomedicine #ChemicalImaging

  40. Don’t miss it!

    Final reminder: Prof. Markus List's seminar on data leakage in biomedical ML is today! Many thanks to @Francesca_Finotello, @uniinnsbruck, and the Molecular Biology Department for this opportunity.

    🕔 17:00 (CEST)
    📍 Campus Technik, Hörsaal D

    #BiomedicalResearch #MachineLearning

  41. Don’t miss it!

    Final reminder: Prof. Markus List's seminar on data leakage in biomedical ML is today! Many thanks to @Francesca_Finotello, @uniinnsbruck, and the Molecular Biology Department for this opportunity.

    🕔 17:00 (CEST)
    📍 Campus Technik, Hörsaal D

    #BiomedicalResearch #MachineLearning

  42. 🧬 Happening today! Join us for a GHGA lecture by Prof. Rami Abou Jamra (University of Leipzig):
    "Genome sequencing for rare disease diagnostics: uncovering hidden causal variants"
    Learn how genome sequencing is advancing the diagnosis of rare diseases beyond exome analysis.

    📅 May 21, 2025 | 🕒 4PM
    🔗 Register here: dkfz-de.zoom.us/meeting/regist

    Part of the Advances in Data-Driven Biomedicine series.
    #Genomics #RareDiseases #GHGA #BiomedicalResearch #GenomeSequencing

  43. 🔬 🧫 Organoids are a promising breakthrough that scientists have been exploring over the past 15 years. These three-dimensional tissue cultures grown from human stem cells stand to revolutionize some aspects of biomedical research, but they won’t do away entirely with the need for animal testing.

    #Organoids #BiomedicalResearch #StemCellResearch

    Read more: go.epfl.ch/61U-en

  44. 🔬 Biomedical AI Insights! 🔬

    Join Prof. Markus List as he reveals how data leakage impacts ML in biomedical research & how to avoid false results! Special laudations to @Francesca_Finotello for enabling this seminar!

    uibk.ac.at/en/disc/events/semi
    #BiomedicalResearch #MachineLearning