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#microbial — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #microbial, aggregated by home.social.

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  1. Coupled Hydrological And Public Health Risks From Urban Flooding - Integrated Remote Sensing, Machine Learning, And Hydrodynamic–Ecological Modelling
    --
    doi.org/10.1016/j.jhydrol.2026 <-- shared paper
    --
    youtu.be/VHzYLvSYR7k?si=5oGGPe <-- recent overview video created about the research
    --
    doi.org/10.1016/j.wroa.2025.10 <-- share (earlier) paper
    --
    H/T @RAHUL DEOPA | Research Scholar (IIT Roorkee)
    “… [U]rban floods are not merely hydraulic events; they also transport sewage, pathogens, and other contaminants across streets and communities, leading to significant public health risks…
    How do we quantify microbial contamination in near real time during a flood event, when emergency conditions make field sampling unsafe, sparse, or even impossible?...
    [The authors] explored whether Earth observation data, combined with machine learning, could bridge this critical monitoring gap. By combining Landsat-derived water surface temperature, machine learning, a coupled MIKE+ Flood–ECO Lab hydrodynamic–ecological model, and Quantitative Microbial Risk Assessment (QMRA), [they] estimated microbial concentrations (𝘌. 𝘤𝘰𝘭𝘪), simulated their fate and transport during floods, and quantified the associated human health risks.
    The takeaway: predicting flood risk isn't just about where the water goes; it's about what it's carrying and who it puts in harm's way. Earth observation and machine learning can help close that gap when it matters most, during the emergency, not weeks after…”
    #publichealth #risk #hazard #watersecurity #Floodrisk #Humanhealthrisk #Urbanflooding #Hydrodynamicmodelling #waterquality #model #modeling #SupportVectorRegression #flood #flooding #urban #city #sewage #pathogens #contaminant #disease #streets #community #quantification #remotesensing #GIS #spatial #mapping #earthobservation #spatialanalysis #water #hydrology #climatechange #extremeweather #spatiotemporal #AI #machineleraning #fateandtransport #hydrodynamic #microbial #rainfall #drainage #streamflow #topography #hydrogeomorphology #Delhi #India #floodplain

  2. Coupled Hydrological And Public Health Risks From Urban Flooding - Integrated Remote Sensing, Machine Learning, And Hydrodynamic–Ecological Modelling
    --
    doi.org/10.1016/j.jhydrol.2026 <-- shared paper
    --
    youtu.be/VHzYLvSYR7k?si=5oGGPe <-- recent overview video created about the research
    --
    doi.org/10.1016/j.wroa.2025.10 <-- share (earlier) paper
    --
    H/T @RAHUL DEOPA | Research Scholar (IIT Roorkee)
    “… [U]rban floods are not merely hydraulic events; they also transport sewage, pathogens, and other contaminants across streets and communities, leading to significant public health risks…
    How do we quantify microbial contamination in near real time during a flood event, when emergency conditions make field sampling unsafe, sparse, or even impossible?...
    [The authors] explored whether Earth observation data, combined with machine learning, could bridge this critical monitoring gap. By combining Landsat-derived water surface temperature, machine learning, a coupled MIKE+ Flood–ECO Lab hydrodynamic–ecological model, and Quantitative Microbial Risk Assessment (QMRA), [they] estimated microbial concentrations (𝘌. 𝘤𝘰𝘭𝘪), simulated their fate and transport during floods, and quantified the associated human health risks.
    The takeaway: predicting flood risk isn't just about where the water goes; it's about what it's carrying and who it puts in harm's way. Earth observation and machine learning can help close that gap when it matters most, during the emergency, not weeks after…”
    #publichealth #risk #hazard #watersecurity #Floodrisk #Humanhealthrisk #Urbanflooding #Hydrodynamicmodelling #waterquality #model #modeling #SupportVectorRegression #flood #flooding #urban #city #sewage #pathogens #contaminant #disease #streets #community #quantification #remotesensing #GIS #spatial #mapping #earthobservation #spatialanalysis #water #hydrology #climatechange #extremeweather #spatiotemporal #AI #machineleraning #fateandtransport #hydrodynamic #microbial #rainfall #drainage #streamflow #topography #hydrogeomorphology #Delhi #India #floodplain

  3. Coupled Hydrological And Public Health Risks From Urban Flooding - Integrated Remote Sensing, Machine Learning, And Hydrodynamic–Ecological Modelling
    --
    doi.org/10.1016/j.jhydrol.2026 <-- shared paper
    --
    youtu.be/VHzYLvSYR7k?si=5oGGPe <-- recent overview video created about the research
    --
    doi.org/10.1016/j.wroa.2025.10 <-- share (earlier) paper
    --
    H/T @RAHUL DEOPA | Research Scholar (IIT Roorkee)
    “… [U]rban floods are not merely hydraulic events; they also transport sewage, pathogens, and other contaminants across streets and communities, leading to significant public health risks…
    How do we quantify microbial contamination in near real time during a flood event, when emergency conditions make field sampling unsafe, sparse, or even impossible?...
    [The authors] explored whether Earth observation data, combined with machine learning, could bridge this critical monitoring gap. By combining Landsat-derived water surface temperature, machine learning, a coupled MIKE+ Flood–ECO Lab hydrodynamic–ecological model, and Quantitative Microbial Risk Assessment (QMRA), [they] estimated microbial concentrations (𝘌. 𝘤𝘰𝘭𝘪), simulated their fate and transport during floods, and quantified the associated human health risks.
    The takeaway: predicting flood risk isn't just about where the water goes; it's about what it's carrying and who it puts in harm's way. Earth observation and machine learning can help close that gap when it matters most, during the emergency, not weeks after…”
    #publichealth #risk #hazard #watersecurity #Floodrisk #Humanhealthrisk #Urbanflooding #Hydrodynamicmodelling #waterquality #model #modeling #SupportVectorRegression #flood #flooding #urban #city #sewage #pathogens #contaminant #disease #streets #community #quantification #remotesensing #GIS #spatial #mapping #earthobservation #spatialanalysis #water #hydrology #climatechange #extremeweather #spatiotemporal #AI #machineleraning #fateandtransport #hydrodynamic #microbial #rainfall #drainage #streamflow #topography #hydrogeomorphology #Delhi #India #floodplain

  4. Coupled Hydrological And Public Health Risks From Urban Flooding - Integrated Remote Sensing, Machine Learning, And Hydrodynamic–Ecological Modelling
    --
    doi.org/10.1016/j.jhydrol.2026 <-- shared paper
    --
    youtu.be/VHzYLvSYR7k?si=5oGGPe <-- recent overview video created about the research
    --
    doi.org/10.1016/j.wroa.2025.10 <-- share (earlier) paper
    --
    H/T @RAHUL DEOPA | Research Scholar (IIT Roorkee)
    “… [U]rban floods are not merely hydraulic events; they also transport sewage, pathogens, and other contaminants across streets and communities, leading to significant public health risks…
    How do we quantify microbial contamination in near real time during a flood event, when emergency conditions make field sampling unsafe, sparse, or even impossible?...
    [The authors] explored whether Earth observation data, combined with machine learning, could bridge this critical monitoring gap. By combining Landsat-derived water surface temperature, machine learning, a coupled MIKE+ Flood–ECO Lab hydrodynamic–ecological model, and Quantitative Microbial Risk Assessment (QMRA), [they] estimated microbial concentrations (𝘌. 𝘤𝘰𝘭𝘪), simulated their fate and transport during floods, and quantified the associated human health risks.
    The takeaway: predicting flood risk isn't just about where the water goes; it's about what it's carrying and who it puts in harm's way. Earth observation and machine learning can help close that gap when it matters most, during the emergency, not weeks after…”
    #publichealth #risk #hazard #watersecurity #Floodrisk #Humanhealthrisk #Urbanflooding #Hydrodynamicmodelling #waterquality #model #modeling #SupportVectorRegression #flood #flooding #urban #city #sewage #pathogens #contaminant #disease #streets #community #quantification #remotesensing #GIS #spatial #mapping #earthobservation #spatialanalysis #water #hydrology #climatechange #extremeweather #spatiotemporal #AI #machineleraning #fateandtransport #hydrodynamic #microbial #rainfall #drainage #streamflow #topography #hydrogeomorphology #Delhi #India #floodplain

  5. Coupled Hydrological And Public Health Risks From Urban Flooding - Integrated Remote Sensing, Machine Learning, And Hydrodynamic–Ecological Modelling
    --
    doi.org/10.1016/j.jhydrol.2026 <-- shared paper
    --
    youtu.be/VHzYLvSYR7k?si=5oGGPe <-- recent overview video created about the research
    --
    doi.org/10.1016/j.wroa.2025.10 <-- share (earlier) paper
    --
    H/T @RAHUL DEOPA | Research Scholar (IIT Roorkee)
    “… [U]rban floods are not merely hydraulic events; they also transport sewage, pathogens, and other contaminants across streets and communities, leading to significant public health risks…
    How do we quantify microbial contamination in near real time during a flood event, when emergency conditions make field sampling unsafe, sparse, or even impossible?...
    [The authors] explored whether Earth observation data, combined with machine learning, could bridge this critical monitoring gap. By combining Landsat-derived water surface temperature, machine learning, a coupled MIKE+ Flood–ECO Lab hydrodynamic–ecological model, and Quantitative Microbial Risk Assessment (QMRA), [they] estimated microbial concentrations (𝘌. 𝘤𝘰𝘭𝘪), simulated their fate and transport during floods, and quantified the associated human health risks.
    The takeaway: predicting flood risk isn't just about where the water goes; it's about what it's carrying and who it puts in harm's way. Earth observation and machine learning can help close that gap when it matters most, during the emergency, not weeks after…”

  6. Is #microbial #ecology fair? This study uses an ecological 'Game of Growth' to explore how fair ecological dynamics is as a distribution rule of biomass, revealing the degree of meritocracy found in the state of nature @PLOSBiology plos.io/4xMqQjl

  7. Is #microbial #ecology fair? This study uses an ecological 'Game of Growth' to explore how fair ecological dynamics is as a distribution rule of biomass, revealing the degree of meritocracy found in the state of nature @PLOSBiology plos.io/4xMqQjl

  8. Is #microbial #ecology fair? This study uses an ecological 'Game of Growth' to explore how fair ecological dynamics is as a distribution rule of biomass, revealing the degree of meritocracy found in the state of nature @PLOSBiology plos.io/4xMqQjl

  9. Is #microbial #ecology fair? This study uses an ecological 'Game of Growth' to explore how fair ecological dynamics is as a distribution rule of biomass, revealing the degree of meritocracy found in the state of nature @PLOSBiology plos.io/4xMqQjl

  10. Is #microbial #ecology fair? This study uses an ecological 'Game of Growth' to explore how fair ecological dynamics is as a distribution rule of biomass, revealing the degree of meritocracy found in the state of nature @PLOSBiology plos.io/4xMqQjl

  11. “The gap between the rate of #humanevolution and the rate of #microbial #evolution, Eren said, is like ‘the difference between a drifting tectonic plate and an F-16 fighter jet’.” www.newyorker.com/magazine/202...

    Our Warming Planet Is a Petri ...

  12. “The gap between the rate of #humanevolution and the rate of #microbial #evolution, Eren said, is like ‘the difference between a drifting tectonic plate and an F-16 fighter jet’.” www.newyorker.com/magazine/202...

    Our Warming Planet Is a Petri ...

  13. “The gap between the rate of #humanevolution and the rate of #microbial #evolution, Eren said, is like ‘the difference between a drifting tectonic plate and an F-16 fighter jet’.” www.newyorker.com/magazine/202...

    Our Warming Planet Is a Petri ...

  14. “The gap between the rate of #humanevolution and the rate of #microbial #evolution, Eren said, is like ‘the difference between a drifting tectonic plate and an F-16 fighter jet’.” www.newyorker.com/magazine/202...

    Our Warming Planet Is a Petri ...

  15. “The gap between the rate of #humanevolution and the rate of #microbial #evolution, Eren said, is like ‘the difference between a drifting tectonic plate and an F-16 fighter jet’.” www.newyorker.com/magazine/202...

    Our Warming Planet Is a Petri ...

  16. The #microbial #diversity of #dynamic #ecosystems can today be assessed using more efficient methods. M. F. Peña-Valencia et al. (2026) identified potential #polyethyleneterephthalate (#PET)-degrading #enzymes from #mangrove #soil using #AI, #3D #structuralanalysis and #metagenomics. Some of these enzymes could be assigned to the bacterial genus #Microbulbifer.

    © #StefanFWirth

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    Ref
    doi.org/10.1038/s41467-026-715

    #Illustrations
    ©S.F.Wirth, AI assisted

  17. The #microbial #diversity of #dynamic #ecosystems can today be assessed using more efficient methods. M. F. Peña-Valencia et al. (2026) identified potential #polyethyleneterephthalate (#PET)-degrading #enzymes from #mangrove #soil using #AI, #3D #structuralanalysis and #metagenomics. Some of these enzymes could be assigned to the bacterial genus #Microbulbifer.

    © #StefanFWirth

    Please support me
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    Ref
    doi.org/10.1038/s41467-026-715

    #Illustrations
    ©S.F.Wirth, AI assisted

  18. The #microbial #diversity of #dynamic #ecosystems can today be assessed using more efficient methods. M. F. Peña-Valencia et al. (2026) identified potential #polyethyleneterephthalate (#PET)-degrading #enzymes from #mangrove #soil using #AI, #3D #structuralanalysis and #metagenomics. Some of these enzymes could be assigned to the bacterial genus #Microbulbifer.

    © #StefanFWirth

    Please support me
    ko-fi.com/sfwirth

    Ref
    doi.org/10.1038/s41467-026-715

    #Illustrations
    ©S.F.Wirth, AI assisted

  19. The #microbial #diversity of #dynamic #ecosystems can today be assessed using more efficient methods. M. F. Peña-Valencia et al. (2026) identified potential #polyethyleneterephthalate (#PET)-degrading #enzymes from #mangrove #soil using #AI, #3D #structuralanalysis and #metagenomics. Some of these enzymes could be assigned to the bacterial genus #Microbulbifer.

    © #StefanFWirth

    Please support me
    ko-fi.com/sfwirth

    Ref
    doi.org/10.1038/s41467-026-715

    #Illustrations
    ©S.F.Wirth, AI assisted

  20. The #microbial #diversity of #dynamic #ecosystems can today be assessed using more efficient methods. M. F. Peña-Valencia et al. (2026) identified potential #polyethyleneterephthalate (#PET)-degrading #enzymes from #mangrove #soil using #AI, #3D #structuralanalysis and #metagenomics. Some of these enzymes could be assigned to the bacterial genus #Microbulbifer.

    © #StefanFWirth

    Please support me
    ko-fi.com/sfwirth

    Ref
    doi.org/10.1038/s41467-026-715

    #Illustrations
    ©S.F.Wirth, AI assisted

  21. New publication: High-Dose #Biochar Hinders Micro/#Nanoplastic-Induced #Soil Positive Priming by Reducing #Substrate Quality and #Microbial Activity.
    doi.org/10.1021/acs.est.5c11467

  22. New publication: High-Dose #Biochar Hinders Micro/#Nanoplastic-Induced #Soil Positive Priming by Reducing #Substrate Quality and #Microbial Activity.
    doi.org/10.1021/acs.est.5c11467

  23. New publication: High-Dose #Biochar Hinders Micro/#Nanoplastic-Induced #Soil Positive Priming by Reducing #Substrate Quality and #Microbial Activity.
    doi.org/10.1021/acs.est.5c11467

  24. New publication: High-Dose #Biochar Hinders Micro/#Nanoplastic-Induced #Soil Positive Priming by Reducing #Substrate Quality and #Microbial Activity.
    doi.org/10.1021/acs.est.5c11467

  25. New publication: Unveiling the dominant role of #soilpH in shaping #nitrogen cycling #microbial #gene abundances: Insights from 65-years of chemical #fertilizer selection in an acidic #grassland #meadow.
    doi.org/10.1016/j.agee.2026.11

  26. New publication: Unveiling the dominant role of #soilpH in shaping #nitrogen cycling #microbial #gene abundances: Insights from 65-years of chemical #fertilizer selection in an acidic #grassland #meadow.
    doi.org/10.1016/j.agee.2026.11

  27. New publication: Unveiling the dominant role of #soilpH in shaping #nitrogen cycling #microbial #gene abundances: Insights from 65-years of chemical #fertilizer selection in an acidic #grassland #meadow.
    doi.org/10.1016/j.agee.2026.11

  28. New publication: Unveiling the dominant role of #soilpH in shaping #nitrogen cycling #microbial #gene abundances: Insights from 65-years of chemical #fertilizer selection in an acidic #grassland #meadow.
    doi.org/10.1016/j.agee.2026.11

  29. New publication: Unveiling the dominant role of #soilpH in shaping #nitrogen cycling #microbial #gene abundances: Insights from 65-years of chemical #fertilizer selection in an acidic #grassland #meadow.
    doi.org/10.1016/j.agee.2026.11

  30. In biology/geology "#marinesnow" refers to the #organicdebris of organisms from higher #waterlevels. The #carboncycle thus transfers #CO2 to the #seabed, thus binding the #greenhousegas.
    B. Borer et al. (2026) found that #microbial components of this "snow" induce #calciumcarbonate #dissolution in higher waters, reducing their #settlingvelocity and requiring consideration in future #climatemodels.
    ©#StefanFWirth

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  31. In biology/geology "#marinesnow" refers to the #organicdebris of organisms from higher #waterlevels. The #carboncycle thus transfers #CO2 to the #seabed, thus binding the #greenhousegas.
    B. Borer et al. (2026) found that #microbial components of this "snow" induce #calciumcarbonate #dissolution in higher waters, reducing their #settlingvelocity and requiring consideration in future #climatemodels.
    ©#StefanFWirth

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  32. In biology/geology "#marinesnow" refers to the #organicdebris of organisms from higher #waterlevels. The #carboncycle thus transfers #CO2 to the #seabed, thus binding the #greenhousegas.
    B. Borer et al. (2026) found that #microbial components of this "snow" induce #calciumcarbonate #dissolution in higher waters, reducing their #settlingvelocity and requiring consideration in future #climatemodels.
    ©#StefanFWirth

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  33. In biology/geology "#marinesnow" refers to the #organicdebris of organisms from higher #waterlevels. The #carboncycle thus transfers #CO2 to the #seabed, thus binding the #greenhousegas.
    B. Borer et al. (2026) found that #microbial components of this "snow" induce #calciumcarbonate #dissolution in higher waters, reducing their #settlingvelocity and requiring consideration in future #climatemodels.
    ©#StefanFWirth

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  34. In biology/geology "#marinesnow" refers to the #organicdebris of organisms from higher #waterlevels. The #carboncycle thus transfers #CO2 to the #seabed, thus binding the #greenhousegas.
    B. Borer et al. (2026) found that #microbial components of this "snow" induce #calciumcarbonate #dissolution in higher waters, reducing their #settlingvelocity and requiring consideration in future #climatemodels.
    ©#StefanFWirth

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  35. #Newswire: Melt&Marble, the Swedish biotech company specializing in microbial fermentation-derived fats, has achieved self-affirmed GRAS (Generally Recognised as Safe) status for its MeltyMarble fat ingredient, clearing a path for commercialization in the United States.

    #microbial #fat #fermentation #meat #dairy #ingredients #biotech #foodtech #regulatory #marketaccess #confectionery #innovation #sustainability #startups #sweden #pressrelease

    proteinreport.org/newswire/mel

  36. #Newswire: Melt&Marble, the Swedish biotech company specializing in microbial fermentation-derived fats, has achieved self-affirmed GRAS (Generally Recognised as Safe) status for its MeltyMarble fat ingredient, clearing a path for commercialization in the United States.

    #microbial #fat #fermentation #meat #dairy #ingredients #biotech #foodtech #regulatory #marketaccess #confectionery #innovation #sustainability #startups #sweden #pressrelease

    proteinreport.org/newswire/mel

  37. #Newswire: Melt&Marble, the Swedish biotech company specializing in microbial fermentation-derived fats, has achieved self-affirmed GRAS (Generally Recognised as Safe) status for its MeltyMarble fat ingredient, clearing a path for commercialization in the United States.

    #microbial #fat #fermentation #meat #dairy #ingredients #biotech #foodtech #regulatory #marketaccess #confectionery #innovation #sustainability #startups #sweden #pressrelease

    proteinreport.org/newswire/mel

  38. #Newswire: Melt&Marble, the Swedish biotech company specializing in microbial fermentation-derived fats, has achieved self-affirmed GRAS (Generally Recognised as Safe) status for its MeltyMarble fat ingredient, clearing a path for commercialization in the United States.

    #microbial #fat #fermentation #meat #dairy #ingredients #biotech #foodtech #regulatory #marketaccess #confectionery #innovation #sustainability #startups #sweden #pressrelease

    proteinreport.org/newswire/mel

  39. #Newswire: Melt&Marble, the Swedish biotech company specializing in microbial fermentation-derived fats, has achieved self-affirmed GRAS (Generally Recognised as Safe) status for its MeltyMarble fat ingredient, clearing a path for commercialization in the United States.

    #microbial #fat #fermentation #meat #dairy #ingredients #biotech #foodtech #regulatory #marketaccess #confectionery #innovation #sustainability #startups #sweden #pressrelease

    proteinreport.org/newswire/mel

  40. Nitrosopumilus maritimus is a highly adaptable species of #marine #archaea that accounts for approximately 30% of the marine #microbial #plankton population and plays a vital role in regulating the ocean's biological and chemical balance amid climate change.
    #Microbiology #MarineBiology #Environmental #GlobalChangeBiology #OceanBiogeochemistry #ClimateChange #sflorg
    sflorg.com/2026/03/mcb03092601

  41. Nitrosopumilus maritimus is a highly adaptable species of #marine #archaea that accounts for approximately 30% of the marine #microbial #plankton population and plays a vital role in regulating the ocean's biological and chemical balance amid climate change.
    #Microbiology #MarineBiology #Environmental #GlobalChangeBiology #OceanBiogeochemistry #ClimateChange #sflorg
    sflorg.com/2026/03/mcb03092601

  42. Nitrosopumilus maritimus is a highly adaptable species of #marine #archaea that accounts for approximately 30% of the marine #microbial #plankton population and plays a vital role in regulating the ocean's biological and chemical balance amid climate change.
    #Microbiology #MarineBiology #Environmental #GlobalChangeBiology #OceanBiogeochemistry #ClimateChange #sflorg
    sflorg.com/2026/03/mcb03092601

  43. Nitrosopumilus maritimus is a highly adaptable species of #marine #archaea that accounts for approximately 30% of the marine #microbial #plankton population and plays a vital role in regulating the ocean's biological and chemical balance amid climate change.
    #Microbiology #MarineBiology #Environmental #GlobalChangeBiology #OceanBiogeochemistry #ClimateChange #sflorg
    sflorg.com/2026/03/mcb03092601

  44. Nitrosopumilus maritimus is a highly adaptable species of #marine #archaea that accounts for approximately 30% of the marine #microbial #plankton population and plays a vital role in regulating the ocean's biological and chemical balance amid climate change.
    #Microbiology #MarineBiology #Environmental #GlobalChangeBiology #OceanBiogeochemistry #ClimateChange #sflorg
    sflorg.com/2026/03/mcb03092601

  45. #Microbial nutrients dictate the success or failure of #antibiotics in structured bacterial communities, creating an observable death front where metabolically active surface cells perish while nutrient-starved interior cells survive.
    #Bioengineering #ChemicalEngineering #Biophysics #sflorg
    sflorg.com/2026/02/beng0224260

  46. #Microbial nutrients dictate the success or failure of #antibiotics in structured bacterial communities, creating an observable death front where metabolically active surface cells perish while nutrient-starved interior cells survive.
    #Bioengineering #ChemicalEngineering #Biophysics #sflorg
    sflorg.com/2026/02/beng0224260

  47. #Microbial nutrients dictate the success or failure of #antibiotics in structured bacterial communities, creating an observable death front where metabolically active surface cells perish while nutrient-starved interior cells survive.
    #Bioengineering #ChemicalEngineering #Biophysics #sflorg
    sflorg.com/2026/02/beng0224260

  48. #Microbial nutrients dictate the success or failure of #antibiotics in structured bacterial communities, creating an observable death front where metabolically active surface cells perish while nutrient-starved interior cells survive.
    #Bioengineering #ChemicalEngineering #Biophysics #sflorg
    sflorg.com/2026/02/beng0224260

  49. #Microbial nutrients dictate the success or failure of #antibiotics in structured bacterial communities, creating an observable death front where metabolically active surface cells perish while nutrient-starved interior cells survive.
    #Bioengineering #ChemicalEngineering #Biophysics #sflorg
    sflorg.com/2026/02/beng0224260

  50. #Newswire: MicroHarvest, the German biotechnology company producing protein ingredients through biomass fermentation using regional agri-food side streams, today announced that it has selected Industriepark Leuna (Saxony-Anhalt) as the location for its future production plant.

    #microbial #ingredients #protein #biotech #foodtech #innovation #sustainability #investing #germany #bioeconomy #SaxonyAnhalt #pressrelease

    proteinreport.org/newswire/mic