Craterellus Cornucopioides (trumpet Of The Dead) And Hygrocybe Conica (witch's Hat), Competing For Most

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

Botox is made with botulinum toxin,, ok.

clostridium botulinum is anaerobic bacteria. form spores that release neurotoxin. cause paralysis

can be evident in honey. home canned foods. no oxygen

biblical angels but their true form looks like the patterns in 90s arcade carpets

source

BRAINLESS BOX JELLIES CAN LEARN BY EXPERIENCE

Mangrove box jellyfish (Tripedalia cystophora) is a small species of box jellyfish, native to the Caribbean Sea and the Central Indo-Pacific, presenting a simple nervous system. But despite tiny, researchers have demonstrated present the ability to learn by association. Although has no central brain, and being the size of the finger-tip, this box jelly can be trained to associate the sensation of bumping into something with a visual cue, and to use the information to avoid future collisions.

In the wild, the Mangrove box jellyfish forage for tiny crustaceans between the roots of mangroves. To mimic this environment, researchers placed the box jellies in cylindrical tanks that had either black and white or grey and white vertical stripes on the walls. To the jellyfish, the dark stripes looked like mangrove roots in either clear or murky water. In the ‘murky water’ tanks, the jellyfish bumped into the wall because their visual system couldn’t detect the grey stripes very clearly. But after a few minutes, they learnt to adjust their behaviour, pulsing rapidly to swim away from the wall when they got too close, this state learning is based on the combination of visual and mechanical stimuli in simple animals with no brain.

The learning process, in difference with vertebrate animals, doesnt occurs in a central neuronal organs, but instead in a small organs named rhopalial nervous system, which act as learning center, in which the jelly combines visual and mechanical stimuli during operant conditioning.

Main image: An adult specimen of the box jellyfish T. cystophora., showing where is located one of the four sensory structures named rhopalia, which includes two lens eyes. Each rhopalium also contains a visual information processing center.

Reference (Open Access): Bielecki et al., 2023. Associative learning in the box jellyfish Tripedalia cystophora. Current Biology.

A new species of African legless skink, genus Acontias Cuvier, 1816 “1817” (Squamata: Scincidae) from Serra da Neve inselberg, south-western Angola

Mariana P. Marquesa, Diogo Parrinha, Arthur Tiutenko, et al.

ABSTRACT

During a recent survey of the Serra da Neve inselberg in south-western Angola, a population of legless skinks of the genus Acontias was found. Only three species of this genus have been recorded for the country so far – A. occidentalis, A. kgalagadi and A. jappi. Using an integrative approach and combining molecular and morphological data we found that the Serra da Neve population represents a new species, closely related to species such as A. percivali and some members of the A. occidentalis species complex. In this paper, we describe this population as a new species, Acontias mukwando sp. nov. and provide brief comments on its conservation and biogeography.

Read the paper here:

Full article: A new species of African legless skink, genus Acontias Cuvier, 1816 “1817” (Squamata: Scincidae) from Serra da Neve inselberg, south-western Angola (tandfonline.com)

(via Agar Art — A Cultural Triumph: See A Microbiology Masterpiece In A Petri Dish : NPR)

yep, it’s cultured & arranged bacteria!

Pseudomonas aeruginosa is one of the most pleasant bacteria to identify from a microbiologist's perspective. In turn, from the veterinarian's point of view - one of the worst to treat.

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