working-all-the-time

[working-all-the-time]

Rainbow Dessert 🌈

(Recipe 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)

[working-all-the-time]

[working-all-the-time]

[working-all-the-time]

Hacked Instacart to find the forbidden flavors

[working-all-the-time]

I love her sm tbh.

[working-all-the-time]

[working-all-the-time]

hogwarts, where we arbitrarily divide you based on vague character traits, then encourage rivalry and wonder why all these kids turn out with deep-seated hatred of each other

[working-all-the-time]

“The implications from this study are tremendous,” said Judy Van de Water, a professor of rheumatology, allergy and clinical immunology at UC Davis and the lead author of the study. “It’s the first time that machine learning has been used to identify with 100% accuracy MAR ASD-specific patterns as potential biomarkers of ASD risk.”

Autoantibodies are immune proteins that attack a person’s own tissues. Previously, Van de Water  found that a pregnant mother’s autoantibodies can react with her growing fetus’ brain and alter its development.

Machine learning identifies patterns indicating likelihood and severity of autism

The research team obtained plasma samples from mothers enrolled in the CHARGE study. They analyzed the samples from 450 mothers of children with autism and 342 mothers of typically developing children, also from CHARGE, to detect reactivity to eight different proteins that are abundant in fetal brain. They then used a machine learning algorithm to determine which autoantibody patterns were specifically associated with a diagnosis of ASD.

The researchers created and validated a test to identify ASD-specific maternal autoantibody patterns of reactivity against eight proteins highly expressed in the developing brain.

“The big deal about this particular study is that we created a new, very translatable test for future clinical use,” said Van de Water.  This simple maternal blood test uses an ELISA (Enzyme-Linked-ImmunoSorbent Assay) platform, which is very quick and accurate.  

The machine learning program crunched roughly 10,000 patterns and identified three top patterns associated with MAR ASD: CRMP1+GDA, CRMP1+CRMP2 and NSE+STIP1.

“For example, if the mother has autoantibodies to CRIMP1 and GDA (the most common pattern), her odds of having a child with autism is 31 times greater than the general population, based on this current dataset. That’s huge,” said Van de Water. “There’s very little out there that is going to give you that type of risk assessment.”

Read More

[working-all-the-time]

fucking cowards

[working-all-the-time]

[working-all-the-time]

to whatever teenager needs to hear this:

statistically your generation is having less underage sex & drinking less & doing fewer drugs & generally making better choices than your parents’ generation

the shit you see on tv is just a bunch of middle-aged tv producers (who should know better) sexualizing you & projecting onto your age group. 

do your best not to internalize it as normal (it’s not!), and absolutely call them on their bullshit. 

[working-all-the-time]

[working-all-the-time]

🥵🥵That doink doink doink hit different 😂

[working-all-the-time]

Top ten worst anime tiddies

just off the top of my head

[working-all-the-time]

[working-all-the-time]

[working-all-the-time]