Factors influencing degradation kinetics of mRNAs and half-lives of microRNAs, circRNAs, lncRNAs in blood in vitro using quantitative PCR

RNAs are rapidly degraded in samples and during collection, processing and testing. In this study, we used the same method to explore the half-lives of different RNAs and the influencing factors, and compared the degradation kinetics and characteristics of different RNAs in whole blood and experimental samples. Fresh anticoagulant blood samples were incubated at room temperature for different durations, RNAs were extracted, and genes, including internal references, were amplified by real-time quantitative PCR. A linear half-life model was established according to cycle threshold (Ct) values. The effects of experimental operations on RNA degradation before and after RNA extraction were explored. Quantitative analysis of mRNA degradation in samples and during experimental processes were explored using an orthogonal experimental design. The storage duration of blood samples at room temperature had the greatest influence on RNA degradation. The half-lives of messenger RNAs (mRNAs) was 16.4 h. The half-lives of circular RNAs (circRNAs), long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) were 24.56 ± 5.2 h, 17.46 ± 3.0 h and 16.42 ± 4.2 h, respectively. RNA degradation occurred mainly in blood samples. The half-life of mRNAs was the shortest among the four kinds of RNAs. Quantitative experiments related to mRNAs should be completed within 2 h. The half-lives of circRNAs and lncRNAs were longer than those of the former two.

https://www.nature.com/articles/s41598-022-11339-w

Has anyone observed if penicilin can kill bacteria on a slide under a microscope?

Facebook just announced LLaMA, a collection of large language models ranging from 7B to 65B parameters, competitive with the state-of-the-art and available to the research community. Checkout Zuckerbergs Post.

By training longer, LLaMA obtains GPT3 175B level performance with a 13B model (It performs like GPT-3 with <10% of the parameters)

LLaMA-65B is competitive with Chinchilla 70B and PaLM 540B. They trained LLaMA using only publicly available data, while most existing models, rely on data which is either not publicly available or undocumented.

Checkout Paper and GitHub repo

Looking for list of tools and resources for microRNA research?

Visit https://www.scientificreporters.com/tool/research/mirna.html

You can also query AI Model if your query is not resolved.

/ask What is gene knockout?

/ask Composition of RPMI Media?

/ask Which is the rarest blood group in the world?

The research published uses Huc extracted from Mycobacterium smegmatis which can survive in nutrient deficient condition. Chris Greening earlier published about the survival of M. smegmatis by enhanced co-metabolism of atmospheric H2. Almost nine year later he successfully isolated the Huc enzyme responsible for atmospheric hydrogen gas molecule.

bi0.in/s71?q=tg

NVIDIA today announced an expanded set of generative AI cloud services for customizing AI foundation models to accelerate the creation of new proteins and therapeutics, as well as research in the fields of genomics, chemistry, biology and molecular dynamics.

Part of NVIDIA AI Foundations, the new BioNeMo™ Cloud service offering — for both AI model training and inference — accelerates the most time-consuming and costly stages of drug discovery. It enables researchers to fine-tune generative AI applications on their own proprietary data, and to run AI model inference directly in a web browser or through new cloud application programming interfaces (APIs) that easily integrate into existing applications.

Are you a Ph.D student / Researcher? Here are some AI tools that you can use at various stages of your research:

☑️Research Planning
GanttPRO A research planning tool to create a timeline, tasks, follow progress and deadlines.
https://ganttpro.com/

☑️Finding & Synthesizing Literature
Semantic Scholar:
Get access to 200 million research papers, discover links between topics, get recommendations based on recent searches and generate summaries.
https://lnkd.in/dKkGMeXw

Scholarcy
AI powered article summarizer which identifies key info like participants, data analysis, main findings and limitations.
https://lnkd.in/d-n_yEHn

Paper Digest
Creates 3-minute summaries of research papers by extracting key ideas and sentences.
https://lnkd.in/d7TsH96f

Content Mine
Enables you to find, download, analyze, and extract knowledge from academic papers.
https://lnkd.in/dQ73C2Af

Elink.io
Enables you to save the content from around the web: articles, videos, cloud files, social media posts and share them with peers.
https://elink.io/

Elicit
Another AI tool which helps you find relevant papers without perfect keyword match, summarize takeaways from the paper specific to your question, and extract key information from the papers.
https://elicit.org/

Scite
Allows researcher to see how publication has been cited by providing the context of citation and discover supporting and contrasting evidence for each paper.
https://scite.ai/

SciSpace Copilot
A multi-lingual AI tool, is helps you comprehend the paper (and the math and tables in it), seek answers to your queries, turn lengthy texts and sections into easy to consume summaries.
https://typeset.io/

☑️Data Analysis
Excel Formula Bot
Converts your text instructions into spreadsheet formula.
https://lnkd.in/dRFKeC25!

☑️Academic Writing
Trinka
A grammar checker and language correction AI tool for academic and technical writing; finds errors unique to academic writing that other grammar checker tools may miss.
https://www.trinka.ai/

Lex
A text editor which helps you neatly store and format documents with simple prompts including references, headers and bulleted list.
https://lex.page/

Scrivener
A tool for long writing projects. It helps you fight page fright and writer's block by letting you write text in any order and find its place in the thesis later. Helpful in keeping your notes organized.
https://lnkd.in/dtXgAQnT

☑️Citations/ Bibliography/ Referencing
Endnote
Researchers waste nearly 2,00,000 hours/year formatting citation! This tool simplifies formatting bibliographies, finding impact of references and full texts.
https://endnote.com/

Mendeley
Creates references, citations, and bibliographies in multiple journal styles.
https://www.mendeley.com/

P.S These tools do not aim to write your thesis or paper but enable you to optimize your time and resources as you do your research.

The list isn't exhaustive. Feel free to add.
#phd #artificialintelligence #research

Photoshop is finished. 🏌

Imagine being able to perfect any picture exactly how you want it.

Now it's as simple as drag and drop with this AI:

Researchers from Max Planck Institute for Informatics, MIT and Google have developed DragGAN.

It lets you 'drag' any part of a picture to exactly where you want it.

DragGAN has 2 main parts:
• Motion supervision — this guides the point you're moving towards the target position
• Point tracking — this uses special features to keep an eye on the point you're moving

This means it can make really realistic changes, even for difficult tasks like creating hidden parts of images or changing shapes while keeping them looking natural.

Where Photoshop often requires intricate skill and knowledge, DragGAN makes complex edits as simple as drag and drop.

While DragGAN excels at precise image deformation, I still feel Photoshop's comprehensive tools for graphic design hold value.

Code: https://github.com/XingangPan/DragGAN
Paper: https://huggingface.co/papers/2305.10973

Noise is a secret destroyer of productivity

It is secret because it impacts cognition, not effort, so we don’t notice, but a 10db noise increase (from a dishwasher to a vacuum) lowers productivity by 5%.

Cancer Therapy Snapshot (Cell, 2023)

DALL·E 3 is here and it looks amazing!

Some thoughts:

From the announcement: "DALL·E 3 delivers significant improvements over DALL·E 2 when generating text within an image and in human details like hands. DALL·E 3 creates engaging images by default—no hacks or prompt engineering required."

Very curious to see to what extent we will rely on prompt engineering for this version. That has been one of the pain points for image generation systems, making them hard to use or get good results with.

OpenAI claims we won't need as much prompt engineering and that DALL·E 3 adheres better to prompt instructions and details.

Also, incredibly excited about the availability of DALL·E 3 in ChatGPT Plus and how this could improve the entire process of prompting and discovering interesting prompts to generate compelling and unique images. openai.com/dall-e-3

If you think that AI was born in 2022 👐🏾