Hot on the heals of the post on how to downsize microscopy movie files, let’s look at ways to shrink the size of a PDF file. There’s several ways to tackle this – suggestions came from this thread on Mastodon. Scenario: you have created a preprint/manuscript/proposal in PDF format.

What’s the best way to make a movie file from microscopy data? Maybe you need to generate a movie for the supplementary info for a paper, or insert one into your electronic lab notebook, or to show in a talk. The problem is that the requirements for each of those is different. This situation is compounded by the fact that there are so many options to make movie files and not much guidance on what is the best method.

This is a rather niche post, but the method can likely be adapted for other use cases. In the lab we have many different cell lines stored in liquid nitrogen. The arrangement is: the vials are in specific positions in a box (10 x 10) there are 13 boxes to a cane we have 5 canes Ideally, to retrieve the correct vial from the cell store requires a map.

Answering the question of what fraction of a journal’s papers were previously available as a preprint is quite difficult to do. The tricky part is matching preprints (from a number of different servers) with the published output from a journal.

I am having some fun running AlphaPulldown on a computing cluster. A requirement is to have input sequences in FASTA format. I found that I needed to get ~600 sequences. I had a list of the relevant Uniprot IDs. Surely getting the sequences for these proteins should be straightforward? Solution The Uniprot IDs can be converted – using the ID Mapping Tool on the Uniprot website – into any number of other IDs.

Bands have been known to declare “No Synths!” on their albums. This statement was a badge of pride indicating that the artists hadn’t used any modern trickery in their recordings. Today, the growing use of artificial intelligence (AI) and large language models (LLMs) in science has created a similar scenario. Advocates argue that these tools improve every aspect of science, including the publication process.

We have a new paper out describing how vesicles move inside cells. The paper in a nutshell In science-speak We analysed how small vesicles are transported in cells. In contrast to large vesicles and organelles, which move using motors inside cells, our analysis revealed that passive diffusion is the main mode of small vesicle transport. In normal language Inside cells, molecules are moved in tiny transport packets called vesicles.

Here is a summary of the info I gleaned from asking for recommendations for the best human cell line. These were my criteria: For context, we currently use a number of human cell lines in the lab: HeLa, RPE1, HCT116, SKOV3; as well as many others in the past: HEK293, DLD-1, U2OS. I consider HeLa to be the almost perfect cell line.

I recently did a webinar for ASCB called “From Microscope To Figure”. For posterity, I am re-posting the webinar here with some additional info.

When preparing images for publication, it is good practice to check how accessible they are for colour blind people. Using a simple bit of code, it is possible to check an image – or a whole figure – in ImageJ for accessibility. For example, Figure 1 from our recent paper. Originally looked like this: Using the script we can see how it appears to people with different types of colour blindness.