Colleagues, we need to talk about the damage that endless zooming can do. Every day I see new opportunities to join in this or that online discussion or conference, and each invitation is becoming a burden 1/... #AcademicTwitter #AcademicChatter

Super excited to share my very first lead-author paper in @ScienceAdvances

Supported by @HIRN_CC @NIDDKgov @UFBME @UFWertheim @ufdiabetes @UMCoEDean
Lead by @Cherie_Stabler & @ashu83

link: https://t.co/FbqVWQ0n5p

This is a thread 👇

Highlights:
⚪️A Lab-on-a-Chip platform for organoids w/ wide capabilities: long-term culture | controlled & dynamic perifusion | in situ spatio-temporal imaging | serial cell assessment | ease of sample retrieval

⚪️Continuous fluidic flow increased local oxygen supply to islets in hydrogels & reduced cellular hypoxia
⚪️Flow increased cellular viability & reduced apoptosis & cell death

⚪️Human islets in hydrogels were highly functional during the 10 day in situ culture in our chips, while islet function was rapidly lost under static conditions
⚪️Glucolipotoxicity study showed a treatment window as small as 2.5 hours can elevate cell death

What are organoids? – A miniaturized version of an organ that imitate an aspect of human interface. They are commonly developed from stem cells in a lab. Human body also produces organoids naturally particularly within the pancreas.

JUST IN: The U.S. National Climate Assessment is now public.

This is the report that the Trump Administration doesn’t want you to see. Years in the making, released on the day after Thanksgiving. #ClimateFriday

Here are some of the main

This report is mandated by Congress and focused on the impacts of climate change in the U.S.

Basically: This is what our best scientists think will happen to us as a result of the actions our government is (not) taking to address the most important problem in human history.
/2

300 experts in 13 federal agencies volunteered their time to make sure you have this information.

Please share it widely.
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The top finding:

“Climate change is projected to significantly affect human health, the economy, and the environment in the United

To expand on that finding:

“In the absence of more significant global mitigation efforts, climate change is projected to impose substantial damages on the U.S. economy, human health, and the environment. ...”
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1/

Get a cup of coffee.

In this thread, I'll help you understand the basics of Binomial Thinking.

The future is always uncertain. There are many different ways it can unfold -- some more likely than others. Binomial thinking helps us embrace this view.

2/

The S&P 500 index is at ~3768 today.

Suppose we want to predict where it will be 10 years from now.

Historically, we know that this index has returned ~10% per year.

If we simply extrapolate this, we get an estimate of ~9773 for the index 10 years from now:

3/

What we just did is called a "point estimate" -- a prediction about the future that's a single number (9773).

But of course, we know the future is uncertain. It's impossible to predict it so precisely.

So, there's a sense of *false precision* in point estimates like this.

4/

To emphasize the uncertainty inherent in such predictions, a better approach is to predict a *range* of values rather than a single number.

For example, we may say the index will return somewhere in the *range* of 8% to 12% (instead of a fixed 10%) per year.

5/

10 years from now, this implies an index value in the *range* [8135, 11703]:

1/This is a rant I had with someone while texting, and I thought it would make an interesting thread:

2/ Jim, If you come across any information, I still desire to hear any information on the state of our beleaguered union.

Ct values can be used to estimate epidemic dynamics UPDATE! Ct values are expected to change depending on whether the epidemic is growing or declining, and we harness this to estimate the epidemic trajectory. Lots of cool new analyses and methods!

Highlights:
- Cts from symptom-based surveillance change over time, but the effect is weaker
- Methods to infer incidence using single cross-sections of Cts
- Unbiased by changing testing coverage
- Gaussian process (wiggly line) model for incidence tracking using Ct values
2/12

This work is *JOINTLY led* with @LeekShaffer and PI’d by @michaelmina_lab. Thank you also to the ever insightful @mlipsitch and to coauthors @SanjatKanjilal @gabriel_stacey and @nialljlennon. 3/12

Premise: times since infection depend on the epidemic trajectory. Distributions of randomly sampled viral loads proxy times since infection. With calibration, Ct values can estimate growth rate. We focus on qPCR in SARS-CoV-2, but the principle applies to any outbreak. 4/12

Result 1: viral loads are shifted higher (Cts lower) during epidemic growth and lower (Cts higher) during decline when individuals are sampled *based on the onset of symptoms*. We simulated linelist data under symptom-based surveillance and looked at TSI and Cts over time. 5/12