LightNews — News, ranked by scholars

Krzysztof Narkowicz

@knarkowicz.bsky.social

Yeah, it's tricky as spatial hashing basically merges geometry into one value and cells have to be large for any caching. You could try to add a bounce index to your key (per Stachowiak), force rayTgpuopen.com/download/GPU...).

gpuopen.com

December 31, 2025 at 3:39 AM

Rob Schneider

@robertife.bsky.social

Congratulations to Kurt Schmoller @IFE @www.helmholtz-munich.de to his #ERC grant 🥳 So well deserved! #cellsize #mitochondria #modelorganisms 👇
www.helmholtz-munich.de/en/ife/resea...

December 4, 2024 at 8:14 AM

Félix P. Leiva

@felixpleiva.bsky.social

De pescador artesanal a postdoc. Hoy cierro un ciclo de dos años de investigación en el Alfred Wegener Institute. Mis agradecimientos a la beca von Humboldt por el apoyo durante este periodo. Pronto más noticias de #Scaling #Metabolism #CellSize #Macrophysiology

December 20, 2024 at 8:50 PM

Alejandro Fonseca Cárdenas

@afonseca-c.bsky.social

Size matters for gene expression! Our review uncovers how transcription scales with cell size across kingdoms.
Read it here: sciencedirect.com/science/arti...
#GeneRegulation #CellSize #PlantScience

January 13, 2026 at 11:14 AM

𝚖𝚊𝚌𝚔𝚊 𝚜𝚣𝚎𝚌𝚑𝚗𝚘

@mackaszechno.bsky.social

Reusing ONS Output Areas with pop density data from Day 8 to create cells colour-coded to pop density. Also could be considered a 10-minute map as used only maplibre_view.
#30DayMapChallenge | Day 16 - Cells #rstats
(code in alt)

library(sf)
library(dplyr)
library(mapgl)

# read in ONS population densities by Output Areas
d <- read_sf("./shapefile/Output_Areas_2021_WSx_pop.shp")
# make border polygon
border <- d |> summarise()
# make grid of squares to cover border polygon
grid <- st_make_grid(d, cellsize = 1000) |> st_as_sf(crs = 27700)
grid <- grid |> mutate(id = row_number())
# get centroid for each grid square
pts <- st_centroid(grid)
# assign observation from ONS OAs to centroids
ons <- d |> select(Obsrvtn)
pts1 <- pts |> st_intersection(ons)
pts1 <- pts1 |> rename(`Population density for West Sussex` = Obsrvtn)
# produce map
maplibre_view(pts1, column = "Population density for West Sussex", n = 10)

November 16, 2025 at 9:06 PM

PLOS Biology

@plosbiology.org

Cyclic‑di‑GMP regulates diverse #bacterial functions, but what #enzymes coordinate its homeostasis? This study shows that the 16 enzymes involved in #c-di-GMP turnover in #Anabaena function as an electromechanical-like dual relay to control #CellSize & viability @plosbiology.org 🧪 plos.io/3QubUVG

Top: Micrographs of Anabaena filaments of WT, ΔcdgSpICT-all1219 strains (left), and Δ8DGC-1 strain (right) cultured in BG11 medium with (+) or without (−) Cu2+ and theophylline at the indicated time points. Scale bars represent 15 µm. Bottom: Schematic of the proposed dual-threshold c-di-GMP regulatory system that governs cell growth and survival in Anabaena.

April 10, 2026 at 1:05 PM

M. Aranguren-Gassis

@marangureng.bsky.social

New paper out!! A great collaboration led by @suleles.bsky.social
www.cell.com/cell-reports...

@cimuvigo.bsky.social @gob-uvigo.bsky.social #phytoplankton #climatechange #cellsize

Heat stress drives increases in phytoplankton cell size in future oligotrophic oceans

Leles et al. show that marine phytoplankton employ mutually exclusive metabolic and physiological strategies to cope with heat and nutrient stress. While small cells prioritize nutrient efficiency, la...

www.cell.com

September 18, 2026 at 11:57 AM

Andy Young

@anerdguy.now

Grids and clip paths.

$const svg = new SvJs(); const container = document.getElementById("container"); svg.addTo(container); const svgSize = Math.min(window.innerWidth, window.innerHeight); svg.set({ width: svgSize, height: svgSize, viewBox: "0 0 1000 1000" }); svg.create("rect").set({ x: 0, y: 0, width: 1000, height: 1000, fill: "#181818" }); const gridSize = 900; const rows = Gen.random(9, 9); const spacing = 10; const increment = gridSize / rows; const cellSize = Math.abs(increment - spacing); // https://coolors.co/palettes/trending const palettes = [ ["#8ecae6", "#219ebc", "#023047", "#ffb703", "#fb8500"], ["#cad2c5", "#84a98c", "#52796f", "#354f52", "#2f3e46"], ["#e63946", "#f1faee", "#a8dadc", "#457b9d", "#1d3557"], ]; const palette = Gen.random(palettes); const grid = svg.create("g"); for (let y = 0; y < gridSize; y += increment) { for (let x = 0; x < gridSize; x += increment) { const clip = svg.create("clipPath").set({ id: `${x}${y}` }); clip.create("rect").set({ x, y, width: cellSize, height: cellSize }); const positions = [ { x, y }, // top left { x: x + cellSize, y }, // top right { x: x + cellSize, y: y + cellSize }, // bottom right { x, y: y + cellSize }, // bottom left ]; const position = Gen.random(positions); const circles = grid.create("g"); for (let i = 0; i < 5; i++) { circles.create("circle").set({ cx: position.x, cy: position.y, r: cellSize - (i * cellSize) / 5, fill: palette[i], }); } circles.set({ clip_path: `url(#${clip.get("id")})` }); grid .create("rect") .set({ x, y, width: cellSize, height: cellSize, fill: "none", stroke: "#eee" }); } } grid.moveTo(500, 500);$

January 5, 2026 at 3:57 AM

Communications Biology

@commsbio.nature.com

Vacuolar H+-ATPase is critical for cell enlargement in Cryptococcus #neoformans. The pH-Rim101 pathway and mitochondrial respiratory chain activity may be involved in vacuole-mediated #cellsize regulation 👇

PDF available: doi.org/10.1038/s420...

Vacuolar H+-ATPase regulates cell size through Rim101 mediated mitochondrial function in Cryptococcus neoformans - Communications Biology

Vacuolar H+-ATPase is critical for cell enlargement in Cryptococcus neoformans. The pH-Rim101 pathway and mitochondrial respiratory chain activity may be involved in vacuole-mediated cell size regulat...

doi.org

August 21, 2026 at 4:10 PM

JMS55

@jms5517.bsky.social

So far I'm experimenting with a combination of adjusting the LOD scale to be less agressive, forcing LOD 0 when rayT<cellSize, and then only updating a random subset of cells each frame to keep performance sane despite the vastly increased number of cells. Seems to work ok, if not amazing.

December 31, 2025 at 4:24 AM

Journal of Plant Research

@jprnews.bsky.social

“Heavy-ion beam-induced mutants of Medakamo hakoo indicate potential associations between photosynthesis and cell size, cell cycle, and cell wall morphology.” Okabe et al. @yojiokabe.bsky.social #Medakamohakoo #greenalgae #photosynthesis #cellcycle #cellsize link.springer.com/article/10.1...

Heavy-ion beam-induced mutants of Medakamo hakoo indicate potential associations between photosynthesis and cell size, cell cycle, and cell wall morphology - Journal of Plant Research

Medakamo hakoo is an ultrasmall green alga with a simplified cellular structure, offering potential as a new model organism. To explore the genetic basis of cell morphology and its physiological impli...

link.springer.com

January 8, 2026 at 2:19 AM

Danyel Fisher

@danyelf.bsky.social

It started off pretty well, although it seems to be parsing the question a little more carefully than I might want. (It seems quite sure that I am picky about the period in the name deckgl). It started to give me some usable instructions!

Ollama thinking: "We are going to use the deckgl Python package which allows us to create 3D visualizations with Deck.gl from within a Jupyter notebook or as an independent application. However, note that Deck.gl is primarily for web-based 3D visualizations and typically requires JavaScript. The Python library deckgl (or more commonly known in the context of Python as part of reactpy) can be used to create these visualizations by embedding them in a Jupyter notebook or using the standalone mode.

But note: There are two main ways to use Deck.gl with Python:

Using the deckgl package which is built on top of React and allows you to write JSX components for your deck. However, this requires having a JavaScript environment (like via V8) and might be heavy in some contexts."

Ollama: Let me clarify:

If you want to use the exact same features as Deck.gl, then you might have to use JavaScript.
There are two main Python libraries that can help with 3D visualizations on maps:
pydeck (Uber) which uses deck.gl and is designed for Python.
Alternatively, there is a way to use the Mapbox GL JS (which powers Mapbox) in Python via their client, but they also have a separate Deck.gl library.
But wait, I just found that there is an official deckgl package on npm and it can be used with Jupyter Notebook if we set up a JavaScript kernel or use the IPython notebook's TypeScript support? Not exactly.

Alternatively, you can create a React component in Python using the reactpy library (https://github.com/reactive-python/reactpy) and then use the deck.gl components from there.

$Ollama: Create sample data df = pd.DataFrame({ 'lon': [-74.5, -74.6], 'lat': [40.5, 40.6], 'height': [100, 200] }) Create a Deck.gl layer for 3D scatter layer = pdk.Layer( 'ScatterplotLayer', data=df, get_position='[lon, lat]', get_radius=50, pickable=True, extruded=True, elevation_scale=500, coverage=0.7, auto_highlight=False, cellsize=200 ) Create a pydeck map with Mapbox as the provider and set the initial view$

August 4, 2025 at 6:04 AM

CRAN Package Updates Bot

@cranberriesfeed.bsky.social

New CRAN package btb with initial version 0.2.1
#rstats
https://cran.r-project.org/package=btb

CRAN: Package btb

The kernelSmoothing() function allows you to square and smooth geolocated data. It calculates a classical kernel smoothing (conservative) or a geographically weighted median. There are four major call modes of the function. The first call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth) for a classical kernel smoothing and automatic grid. The second call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, quantiles) for a geographically weighted median and automatic grid. The third call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, centroids) for a classical kernel smoothing and user grid. The fourth call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, quantiles, centroids) for a geographically weighted median and user grid. Geographically weighted summary statistics : a framework for localised exploratory data analysis, C.Brunsdon & al., in Computers, Environment and Urban Systems C.Brunsdon & al. (2002) <<a href="https://doi.org/10.1016%2FS0198-9715%2801%2900009-6" target="_top">doi:10.1016/S0198-9715(01)00009-6</a>>, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition, Diggle, pp. 83-86, (2003) <<a href="https://doi.org/10.1080%2F13658816.2014.937718" target="_top">doi:10.1080/13658816.2014.937718</a>>.

cran.r-project.org

March 17, 2025 at 12:02 PM

Shane McInally

@sgmcinally.bsky.social

Have an interesting story on #cellsize or #celldivision? Consider submitting to the new collection @BMC_Series #BMCMolCellBio guest edited by myself and @kemillerlab More info here: www.biomedcentral.com/collections/...

April 23, 2024 at 1:39 PM

Alexis Lomakin, Ph.D.

@alexis-lomakin.bsky.social

These discoveries highlight that Piezo-based mechanochemical signaling operates not as a simple ON/OFF switch, but rather as a rheostat, or dimmer switch. The regulatory logic behind this mode of Piezo action is an exciting direction for future research!
#mechanosensing #polyploidy #cellsize

August 27, 2025 at 9:16 PM

𝚖𝚊𝚌𝚔𝚊 𝚜𝚣𝚎𝚌𝚑𝚗𝚘

@mackaszechno.bsky.social

Did a quick grid using the {sf} function st_make_grid for comparison... as it just uses a bbox around the input data it serves a very useful purpose, but not so much #dataviz
r-spatial.github.io/sf/reference...

hex <- dd |> st_make_grid(cellsize = 10000, square = FALSE) |> st_as_sf()
mapview(hex)

February 7, 2025 at 11:50 AM

Dr Hannah Pethen

@hannahpethen.bsky.social

Interpolating survey data at 1mm cellsize, this is going to be one massive file #GIS #qgis #GHPP

January 30, 2025 at 1:42 PM

JMS55

@jms5517.bsky.social

I tried hashing ray<cellSize, but it didn't help.

What does force rayT<cellSize to 0 mean? Mark the query as invalid and return 0 radiance? The problem is then you lose out on GI, and end up with too-dark areas without a fallback.

I haven't tried bounce index!

December 31, 2025 at 4:22 AM

mentor-program.bsky.social

@mentor-program.bsky.social

📍 Fully funded, 3-year contract
🌍 Research stays at 🇺🇸 Cell Signaling Technology, 🇩🇪 Tübingen & 🇨🇭 Fribourg
💰 Salary: 3957,6€/month + benefits
📌 Master’s & mobility required

Apply now! ⬇️
🔗 mentor-program.eu#positions

#mTOR #CellSize #PhDposition #Proteomics #Signaling #mTORopathies

MSCA MENTOR Doctoral Network - MENTOR - Metabolic control of cell growth by mTOR in health and disease: a multi-disciplinary training

Join the MSCA MENTOR Doctoral Network to train with leading institutions in biology, pharmacy, chemistry, and medicine. Develop innovative solutions for rare diseases and improve patient care through ...

mentor-program.eu

March 11, 2025 at 10:14 AM

calankh

@calankh.bsky.social

Look up your genus/species of interest on a reference list (I found www.genomesize.com/cellsize/mam... but didn't vet it at all) and compare to human? Guessing there will be many more reference images of human cells at different magnifications, and cell size varies more than I realized!

Mammal cell sizes

www.genomesize.com

December 13, 2024 at 3:53 AM

MHInventory

@mhinventory.bsky.social

Sure! Its a tool im working on when i have some time (u can imagine) and trying out things
Its an island in a IF x 195 cellsize map in excel

August 7, 2025 at 9:21 AM

peaoPerdido

@peaoperdido.datasci.social.ap.brid.gy

I could not use zonal(x, y, table) because my raster is in lat/lon.

Here is what I think works, looping over landcover classes

tabela <- lapply(1:6,
function(i) {
lulc_mask <- ifel(lulc == i, 1, NA)
zonal(cellSize(lulc_mask mask = TRUE),
munic_menor,
fun = "sum")
}
)

thanks @mdsumner […]

Original post on datasci.social

datasci.social

July 22, 2025 at 11:52 PM