I have taken a picture of this before... it was one of my best taken from my DSLR + simple star tracker setup.
However, you can see that the detail with the telescope+guided mount is much sharper.
With hydrogen & oxygen filters, I can separate the data cleanly, too.
/2
Incredibly, the photo is taken from my balcony in Vancouver, where there is a tremendous amount of light pollution, AND it was taken pretty much directly pointing at a 3/4 moon. It was not a DARK sky at all.
/3
But, it's an incredible application of physics and science. The photons from the nebula are there, but they are in specific wavelengths of light. I purchased a filter that very narrowly allows those wavelengths through. @antlia_filter
/4
Each five minute photo i take lets through an incredibly faint amount of data. In fact, this is what 1 five minute exposure looks like:
if you look very closely, you can faintly see some stars.
/5
However, there is data there! in the darkest areas of the picture, the camera is receiving photons of light. if we streeeettttttchhhhh the data as far as we can (exaggerated here for effect), there is a signal in the noise!!
/6
By "stacking" (repeating this signal>noise and adding the images together), what happens is that the random noise stays random, but the faint signal stays a signal, so the computer can start working out what is noise and what is signal even better!
/7
When I get this image I have incredible processing tools (Pixinsight, Photoshop), that allow me to remove the colour cast (this is because of the moonlight and the filter itself).
/8
From this point, its just a ton of practice and technique! I separate the colour layers so that i can work on Hydrogen alpha and Oxygen III data separately (with stars removed using machine learning!)
/9
There are many processes I use, but mostly it's bending the curves of light to boost signal while minimizing background (space) noise.
Voila!!! The final image is 6500x4000, more than enough for me to print!
total data: 3.5 hours. As I add more data, it will get better.
To be clear, my first answer is "well we know they are supposed to block serotonin reuptake, but it's not that simple and we don't really know."
But, if you want the best 2026 science...
/1
For a few particularly science-interested patients, I walk them through what we currently have for the 'best evidence' even though we're still not sure.
This is the "best story" I can tell about SSRI's right now.
(nb, this is NOT locked in, this is MY best synthesis)
/2
1) SSRIs BLOCK the Serotonin Transporter
The protein that pulls serotonin back into the neuron after its released is blocked. Serotonin lingers longer in the synapse, the gap where neurons signal each other.
This is very well established, & how SSRIs were designed.
Ask any person who has been even suggested to have BPD; they will uniformly tell you that they have been told to try DBT (Dialectical Behavioural Therapy). Reflexively recommended. "Gold standard."
This is not science-supported.
/1
Quick history: Marsha Linehan developed DBT in the late 1980s, published the foundational manual in 1993. She drew on CBT, Zen Buddhism, and dialectical philosophy. Brilliant clinician, brilliant marketer. Her institute has trained tens of thousands of therapists worldwide.
/2
That marketing machine is the reason DBT is "the BPD treatment." It is not the reason DBT works better than alternatives, because it does not.
The faint superiority signals in older trials evaporate once you adjust for allegiance bias (DBT researchers studying DBT).
/3
The McCullough Foundation's @NicHulscher — who posts garbage medical misinformation — styles himself an "independent epidemiologist."
His entire career has been spent publishing with, and working for, McCullough.
No academic post, no health agency, no clinical role, no pre-Foundation experience. Hired straight out of his 2024 MPH by the senior author on nearly every paper bearing his name.
/2
He publishes almost exclusively with McCullough, overwhelmingly in predatory or fringe journals, and has already been retracted twice — plus an Expression of Concern — in a career that's barely two years old.
/3
Since MAID has been enacted in 2014, approximately 90,000 Canadians have chosen dying by this method rather than painful, drawn out, or medically complicated deaths.
This represents 0.2% of the Canadian population and accounts for approximately 2% of all deaths since 2014.
The amount of time that American & Canadian right wingers spent on MAID is ridiculous. It is certainly a controversial policy, but it boogeymanning about it is bonkers.
It's not the #1 cause of death. Cancer, for example, kills 90k per year, or as many as MAID in 14 years.
/2
The reality of MAID:
1) The Median age of MAID is 79 years old. (the same age as the median age of COVID which right wingers have decided was 'fine' because they were old anyway)
2) 95.6% are track 1 (death imminent)
3) People who receive MAID do not disproportionately come from lower-income or disadvantaged communities.
4) People who receive MAID are less likely (not more likely) to live in remote areas.
5) 75% have received palliative (end of life) care and also choose MAID
6) A very small proportion (0.1%) required, but did not receive, disability support services; of these individuals, 91.4% confirmed that services were accessible to them.
7) Minorities are under-represented (not over-represented) in those receiving MAID.
/3
If we analyze a group of 40-year-old adults with the same diagnostic criteria & screening as we use currently on children, we get virtually identical rates of autism.
"Exploding rates of autism" likely a reflection of our exploding understanding.
A 2025 Canadian study estimated 1.8% autism prevalence in adults, similar to child rates, showing diagnosis consistency across ages despite evolving awareness.
/2
From 2011-2022 US data found increased autism diagnoses in children, alongside rises in young adult diagnoses simultaneously, not lagged. This implies that it is not something new to this generation.
/3