Mikrobiotch - 🔬🧪🧫🧬

Chlorociboria cup fungi and Hemitrichia decipiens slime mold by Alison Pollack

Microglossum viride

a super macro

hi i hate being perceived on the internet 99% of the time but you should take this quiz i made about the immune system

Broad's Scientist Introduce a Machine Learning Model to Identify Genetic Factors for Cardiovascular Diseases

A machine learning model has been introduced by Broad's Scientists to identify genetic factors associated with cardiovascular diseases.

Using the heart as an investigational model, scientists at the Broad Institute of MIT and Harvard have designed an autoencoder-based machine-learning pipeline that can effectively predict a patient’s heart condition based on image data from ECGs and MRIs. The approach could also be used to detect markers related to cardiovascular diseases.

Nearly all areas of medical science have utilized artificial intelligence (AI) over the years. It has been effectively diagnosing diseases and predicting their transmission and prognosis. AI has been used to design therapeutic approaches effectively and has been helpful in the field of drug design. The use of AI in studying cardiovascular diseases has come a long way, especially machine learning-based systems. AI-based algorithms can be trained to predict cardiovascular disease outcomes using available diagnostic imaging technology.

Currently, the field of cardiology uses a variety of imaging technologies, such as ultrasound imaging, magnetic resonance imaging (MRI), computed tomography (CT), etc. The Electrocardiogram (ECG) is a widely used test to monitor the heart’s rhythm. These technologies generate a lot of data that can be utilized to analyze the condition of a person’s heart. The availability of several diagnostic modalities has raised the need for standardized tools for analyzing imaging data effectively. A multi-modal framework built on machine learning techniques has been suggested by researchers from The Broad Institute of MIT and Harvard. The proposed system can help doctors to understand the cardiovascular state of a person using data from MRIs and ECGs. In practice, clinicians can use data generated from the machine learning program to diagnose a patient appropriately.

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"Wherever you are on your journey to the microcosmos, the odds are high that you'll run into a diatom. They're both abundant and easy to spot because of the shells they encase themselves in. The results are beautiful, exacting geometries that create a living kaleidoscope in the microcosmos. Even if you lived your entire life without ever seeing a diatom, without ever hearing the word "diatom", you would still be living a life that's shaped by them... all the way down to the oxygen you breathe, thanks in no small part to their outsized contribution to the world's photosynthesis."

Journey to the Microcosmos- How Diatoms Build Their Beautiful Shells

Images Originally Captured by Jam's Germs

Astrionella 630x, Bacillaria paxillifer 200x, Diatom 630x, Diatom 630x, Diatom frustule 630x, Diatoms 630x

pixie’s parasol (Mycena interrupta), one of my favourites!

I’ve done it! I’ve designed such an incredibly cursed molecule that MolView doesn’t even assign it a systematic IUPAC name. Behold:

The image doesn’t even show up right in the post editor lol. This thing would have such unbelievably ridiculous angle strain that if a molecule of it was ever assembled, it would almost certainly degrade instantly. Possibly violently.

FOTD #074 : slimy green waxcap! (gliophorus/hygrocybe graminicolor)

the slimy green waxcap is an agaric fungus from the family hygrophoraceae. it is found in australia & aotearoa :-) not much else is known about this mushroom.

the big question : can i bite it?? the edibility is unknown.

g./h. graminicolor description :

"the light green cap & stem of this small agaric are covered with a thick, slimy, glutinous coating. a waxy, grey-green, glutinous thread runs along the edges of white waxy gills. the convex cap becomes centrally depressed & ages to brown."

[images : source & source] [fungus description : source]

"GREEN BABY !! i couldn't find an exact measurement, but she's *small*. i love this mushroom so so so much<3"

Willkommlangea reticulata

by Alison Pollack