Albert Cardona @albertcardona@qoto.org

Sometimes all it takes is to pay attention and let the beauty and extraordinary resilience of little critters wash into you.

Lasioglossum (possibly) #nativebee unwittingly pollinating brambles. Watch the bee now, imagine the blackberries.

https://www.inaturalist.org/observations/50874601

#iNaturalist #insects #photography

@PLOSBiology And notice the call out to the #iNaturalist project "Bees concentrating nectar" and its associated paper by Zach Portman, John Ascher & Daniel Cariveau in 2021, titled "Nectar concentrating behavior by bees (Hymenoptera: Anthophila)" https://link.springer.com/article/10.1007/s13592-021-00895-1

Zach Portman and John Ascher are #entomology experts specialised in #bees who have identified hundreds of #insects among my #iNaturalist observations. Thanks so much!

An example of a #nativebee concentrating nectar: Nomioides minutissimus, a ~3 to 4 mm long solitary bee observed on a beach in Catalonia. https://www.inaturalist.org/observations/120366203

Speaking of #celegans ... now the wireless #connectome!

"The neuropeptidergic connectome of C. elegans" by Lidia Ripoll et al. 2022, a collaboration between Isabel Beets', Petra Vertes' and Bill Schafer's labs https://www.biorxiv.org/content/10.1101/2022.10.30.514396v2

"This connectome is characterized by a high connection density, extended signaling cascades, autocrine foci, and a decentralized topology, with a large, highly interconnected core containing three constituent communities sharing similar patterns of input connectivity. Intriguingly, several of the most important nodes in this connectome are little-studied neurons that are specialized for peptidergic neuromodulation."

Here is a carrot wasp, Gasteruption sp., seen this past July 2022 in Cambridge, UK. The adults drink nectar from flowers of the carrot family–hence the name–and contribute to pollinating them.

Its larval progeny develops as an unwelcomed boarder–a #parasite, really, even a predator–in the nest cells of native bees and wasp larvae, consuming the food intended for the host, and likely have started #hibernation by now. Will only pupate into next Spring.
#wasplove #entomology #iNaturalist
https://www.inaturalist.org/observations/125443949

Playing god with #beetles: "An explanation for unexpected population crashes in a constant environment" by Johnson et al. 2022 https://onlinelibrary.wiley.com/doi/full/10.1111/ele.14110

"Most of the time, populations can be described as fluctuating randomly around a weakly-stable equilibrium. However, some populations experience unexpected population crashes... ecological #blackswan events. These crashes, however rare, have outsized consequences for conservation and management"

"we use mechanistic models and flour #beetle microcosm experiments to derive a novel mechanism of population crashes... can occur when stochasticity occasionally ‘pushes’ population density into a regime where overcrowding is severe."

Curiously: "Obviously, only females can oviposit. Less obviously, females are far more voracious egg cannibals than males—using industrial die to perform an egg mark-recapture experiment, Sonleitner (1961) found that #Tribolium castaneum females ate 19 times as many eggs as males."

#ecology

https://www.inaturalist.org/projects/out-of-season-bees

... which includes this observation of an Andrena cineraria mining #nativebee from the Cambridge Botanic gardens https://www.inaturalist.org/observations/138977895

#outofseasonbees #iNaturalist #entomology

That's a lot of bees and wasps for November.

Yes, some of these, like the cellophane bees (Colletes), have a late flight season, and the garden bumblebees (Bombus terrestis) seem indestructible and adapted to human-altered environments, but the mining bees (Andrena) and sweat bees (Lasioglossum) ought to have been long gone for this season, rather than easy to spot on a leisure walk across the Cambridge Botanic Garden, UK.

#nativebee #wasplove #entomology #climatechange https://www.inaturalist.org/lifelists/albertcardona?view=tree&details_view=observations&taxon_id=47201

Have you visited the #FlyWire website yet? Both for helping proofread and analyze the whole #Drosophila brain #connectome, or simply to admire the beautiful renderings of neuronal arbors: https://join.flywire.ai

(See also the #VirtualFlyBrain for #ontology-driven navigation of the fly brain, and access to images of genetic driver lines, and more: https://v2.virtualflybrain.org/org.geppetto.frontend/geppetto?id=VFB_00101567&i=VFB_00101567 )

Wish I had time or resources to create such a beautiful landing page for the larval central nervous system. The #connectome of the whole larval brain is coming soon. For now, see the #vEM images and some ~3,000 published neurons in this #CATMAID server: https://l1em.catmaid.virtualflybrain.org/?pid=1&zp=108250&yp=82961.59999999999&xp=54210.799999999996&tool=tracingtool&sid0=1&s0=2.4999999999999996&help=true&layout=h(XY,%20%7B%20type:%20%22neuron-search%22,%20id:%20%22neuron-search-1%22,%20options:%20%7B%22annotation-name%22:%20%22papers%22%7D%7D,%200.6)

#connectomics

Torymus sp. chalcid wasp today at the Cambridge Botanic Garden, UK. Despite the large ovipositor, this tiny metallic green parasitoid wasp does not present any danger to its untimely perch, AKA my finger.
http://www.inaturalist.org/observations/141319131
#iNaturalist #wasplove #entomology

Aphid eater hoverfly, Eupeodes sp., looking stunning on a rosemary flower just yesterday, November 4th. Pembroke college, Cambridge, UK.

As in most flies, the eyes seem bigger than the head itself, and often touch each other dorsally. Large eyes alongside tiny antennae is a great distinguishing feature to tell flies apart from wasps. Often, as is the case here, flies present a color pattern similar to that of a wasp: Batesian mimicry which offers protection against predation.

Amusingly, a cook passed by to collect a bunch for “formal hall”, that is, dinner.
#entomology #inaturalist #iphonephotography
http://www.inaturalist.org/observations/141144819

"Post-embryonic remodeling of the C. elegans motor circuit" by Ben Mulcahy et al. 2022 (Mei Zhen's lab https://zhenlab.com/)

... in which the authors show, using #vEM and #connectomics, that while the nematode #celegans nervous system grows from ~200 neurons in the hatchling to ~300 in the adult, the addition of new neurons doesn't disrupt existing motor function, but new circuits are formed that endow the animal with new behaviors such as bending.

Interestingly, in the course of larval maturation one neuron type inverts its polarity: what was the dendrite becomes the axon, and viceversa. And this is accomplished not with retraction and regrowth of the arbor, but rather, by flipping the synapses in situ.

URL: https://doi.org/10.1016/j.cub.2022.09.065

#readingpapers #science #neuroscience #development

Bumblebees, on the other hand, won’t hesitate to rob nectar—a robbery because, by not entering a flower the expected way, they won’t contribute to pollination.

Being big and bulky and strong has disdvantages, but also advantages: bumblebees can bite plants, leaves in particular, to induce flowering. Quite the superpower! https://www.nationalgeographic.com/animals/article/bumblebees-bite-plants-flower-early
#bees #insects #inaturalist #entomology
http://www.inaturalist.org/observations/138859501

Honeybees don’t seem to mind which flowers they harvest nectar and pollen from. All goes.
#bees #entomology #insects #inaturalist
http://www.inaturalist.org/observations/140710590
http://www.inaturalist.org/observations/139904648

On theoretical neural circuits for counting, and their biological implementation in the #Drosophila brain:

"Our second model uses anti-Hebbian plasticity and only tracks frequencies within four count categories (“1-2-3-many”) ... we show that an implementation of the “1-2-3-many” count sketch exists in the insect mushroom body."

From: "A neural theory for counting memories" by Dasgupta et al. 2022 https://www.nature.com/articles/s41467-022-33577-2

HT @andrew_c_lin

Meanwhile, cellophane bees (genus Colletes) keep going strong here in Cambridge, UK, despite having arrived at what ought to be the end of their flight season. Will find out next weekend whether they are still around.
#iNaturalist #bee #nativebee #entomology https://www.inaturalist.org/observations/140696242

For an introduction to #FijiSc from the comfort of #python (or rather, #jython 2.7), see my online tutorial, walking you through image processing concepts with working code that you can copy-paste into the Script Editor, which has code autocompletion to facilitate class and method discovery across the many libraries: https://syn.mrc-lmb.cam.ac.uk/acardona/fiji-tutorial/

Now onto #FijiSc: Fiji is a recursive acronym meaning "Fiji is just ImageJ" https://fji.sc (and the paper https://www.nature.com/articles/nmeth.2019 ) –and #ImageJ is a #java open source software for image processing https://imagej.nih.gov/ij/index.html written by Wayne Rasband from the #NIH Research Branch.

An analogy: think of ImageJ as the kernel and Fiji as the rest of the operating system.

#FijiSc brings to #ImageJ:
(1) a package manager to install and update plugins, and that crucially enables reproducible science by exporting the whole set of plugins and libraries as an executable;
(2) a Script Editor https://imagej.net/scripting/script-editor supporting many languages (#python, #groovy #ruby #scala #clojure and more), all with access to a huge collection of #JVM libraries;
(3) huge amount of libraries such as #ImgLib2, #JFreeChart for plotting, for GUIs, etc.

There are many, many plugins. A tiny sample:

Machine learning-based image segmentation:
- #LabKit https://imagej.net/plugins/labkit/
- #WEKA Trainable Segmentation https://imagej.net/plugins/tws/index

3D/4D/ND Visualization:
- 3D/4D Viewer #3DViewer https://imagej.net/plugins/3d-viewer/index with ray-tracing, orthoslices, volume rendering, and more
- #BigDataViewer #BDV https://imagej.net/plugins/bdv/index for interactively navigate N-dimensional image volumes larger than RAM

Image registration and serial section alignment:
- #BigStitcher for registering 3D/4D tiled datasets, with multiview deconvolution and more https://imagej.net/plugins/bigstitcher/index
- #TrakEM2 for montaging in 2D and alinging in 3D collections of serial sections, typically from #vEM (volume electron microscopy) https://syn.mrc-lmb.cam.ac.uk/acardona/INI-2008-2011/trakem2.html
- #mpicbg libraries for extracting #SIFT and #MOPS features, then finding feature correspondences and estimating rigid and elastic transformation models https://www.nature.com/articles/nmeth.2072

Summarizing #FijiSc is impossible. See the online forum where questions find answers by the hand of the broader community of users and developers https://forum.image.sc/

The web-based open source software #CATMAID was devised as "google maps but for volumes". Documentation at https://catmaid.org and source code at https://github.com/catmaid/CATMAID/

Modern #CATMAID enables hundreds of #neuroscience researchers world wide to collaboratively map neuronal circuits in large datasets, e.g., 100 TB or larger, limited only by bandwidth and server-side storage. The goal: to map and analyse a whole brain #connectome.

Running client-side on #javascript and server-side on #django #python #postgresql, it's a pleasure to use–if I may say so–and easy to hack on to extend its functionality with further widgets.

The first minimally viable product was produced in 2007 by Stephan Saalfeld (what we now refer to, dearly, as "Ice Age CATMAID), who demonstrated to us all that the web, and javascript, where the way to go for distributed, collaborative annotation of large datasets accessed piece-wise. See the original paper: https://academic.oup.com/bioinformatics/article-abstract/25/15/1984/210794

See also public instances at the #VirtulaFlyBrain http://virtualflybrain.org/ particularly under "tools - CATMAID - hosted EM data such as this #Drosophila first instar larval volume of its complete nervous system https://l1em.catmaid.virtualflybrain.org/?pid=1&zp=108250&yp=82961.59999999999&xp=54210.799999999996&tool=tracingtool&sid0=1&s0=2.4999999999999996&help=true&layout=h(XY,%20%7B%20type:%20%22neuron-search%22,%20id:%20%22neuron-search-1%22,%20options:%20%7B%22annotation-name%22:%20%22papers%22%7D%7D,%200.6)

To fill in my profile tags, a thread:

#TrakEM2 is open source software mostly for #connectomics (but found uses well beyond), and provides the means for both manual and automatic montaging and aligning overlapping 2D image tiles (with #SIFT features and rigid or elastic transformation models), and then reconstructing with mostly manual means–by painting with a digital brush–the volumes of structures of interest, as well as trace the branched arbors of e.g., neurons and annotate their synapses, therefore mapping a #connectome from #vEM (volume electron microscopy).

#TrakEM2 paper at https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0038011

Git repository at https://github.com/trakem2/

For 3D visualization, #TrakEM2 uses the 3D Viewer https://imagej.net/plugins/3d-viewer/

As software, #TrakEM2 runs as a plugin of #FijiSc https://fiji.sc/ and in fact motivated the creation of the #FijiSc software in the first place, to manage its many dependencies and therefore facilitate distribution to the broader #neuroscience community.

#TrakEM2 was founded in 2005, when terabyte-sized datasets were rare and considered large. The largest dataset that I've successfully managed with #TrakEM2 was about 16 TB. For larger datasets, see #CATMAID below.