The best AI dictation apps, tested and ranked
AI dictation apps have come a long way in a short time. For years they were slow and inaccurate — unless you spoke with a particular accent and enunciated clearly. Advances in large language models ...
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A transcription coupling model for how enhancers communicate with their target genes
How enhancers communicate with their target genes to influence transcription is an unresolved question of fundamental importance. Current models of the mechanism of enhancer–target gene or enhancer–promoter (E–P) communication are transcription-factor-centric and underappreciate major findings, including that enhancers are themselves transcribed by RNA polymerase II, which correlates with enhancer activity. In this Perspective, we posit that enhancer transcription and its products, enhancer RNAs, are elementary components of enhancer–gene communication. Specifically, we discuss the possibility that transcription at enhancers and at their cognate genes are linked and that this coupling is at the basis of how enhancers communicate with their targets. This model of transcriptional coupling between enhancers and their target genes is supported by growing experimental evidence and represents a synthesis of recent key discoveries. In this Perspective, the authors propose that transcription at enhancers and transcription at their cognate genes are linked, forming the basis of enhancer–gene communication. This model represents a synthesis of recent key discoveries.
Structural insights into nuclear transcription by eukaryotic DNA-dependent RNA polymerases
The eukaryotic transcription apparatus synthesizes a staggering diversity of RNA molecules. The labour of nuclear gene transcription is, therefore, divided among multiple DNA-dependent RNA polymerases. RNA polymerase I (Pol I) transcribes ribosomal RNA, Pol II synthesizes messenger RNAs and various non-coding RNAs (including long non-coding RNAs, microRNAs and small nuclear RNAs) and Pol III produces transfer RNAs and other short RNA molecules. Pol I, Pol II and Pol III are large, multisubunit protein complexes that associate with a multitude of additional factors to synthesize transcripts that largely differ in size, structure and abundance. The three transcription machineries share common characteristics, but differ widely in various aspects, such as numbers of RNA polymerase subunits, regulatory elements and accessory factors, which allows them to specialize in transcribing their specific RNAs. Common to the three RNA polymerases is that the transcription process consists of three major steps: transcription initiation, transcript elongation and transcription termination. In this Review, we outline the common principles and differences between the Pol I, Pol II and Pol III transcription machineries and discuss key structural and functional insights obtained into the three stages of their transcription processes. Nuclear transcription of a wide variety of RNA species is conducted mainly by three RNA polymerases, which are large and dynamic protein complexes. Recent structural studies have provided important insights into the activities at different transcription stages and the commonalities and differences between these transcription machineries.
Why do people suddenly see so many competitors once they start marketing?
I have been asked this question many times: What is the difference between using IdeaGrit(https://ideagrit.foundersailab.com/) and using ChatGPT directly?Every time I answer this question, I feel I can only provide part of the answer. My thoughts are fragmented. So I decided to document them here and clearly show the difference.Several months ago, I joined a WhatsApp channel with around 500 people. When a community becomes big enough, you start noticing interesting patterns.One th
Clinical audiometry with Implant connection
Audiometric assessments for cochlear implant patients are typically performed in a free field environment. This usually involves masking of the non-implanted ear, as well as the use of a dedicated hearing booth or a sound-treated testing room. Room acoustics, reverberation and background noise can all affect the results. This often leads to time-consuming readjustments. AURITEC's Implant Connection eliminates these challenges. Rather than being presented through loudspeakers, the test signal is
Livestream 1 - Nationals 2026
Presented by the Institute for Speech & Debate Schedule (in Central Time): Thursday, June 19: 12:30 PM - Informative Speaking Finals, presented by Truman State University. 2:00 PM - Humorous Interpretation Finals, presented by Advantage Communications. 3:30 PM - Lanny D. and B. J. Naegelin Dramatic Interpretation Finals, presented by Simpson College. 5:00 PM - New First and Second Diamond Recognition, presented by Colorado College. 5:30 PM - Program Oral Interpretation Finals, presented by Quak
Best Colleges Offering B.Tech in AI and Machine Learning in India
Explore the best AI and ML colleges in India, including fees, entrance exams, placements, eligibility criteria, and career opportunities for aspiring engineers.
Machine Learning-Based Model May Predict In-Hospital CAP Mortality
A machine learning (ML)-based model may aid in-hospital community-acquired pneumonia (CAP) mortality prediction, according to study findings published in Respiratory Medicine. Res ...
NASA deploys machine learning for timely flash flood warnings
A new open-source machine learning system cuts flash food forecasting time to just 15 minutes. The tool automates complex satellite data analysis to help meteorologists issue more timely, accurate warnings.
Physics-Informed Machine Learning
This cross-journal Collection between Nature Communications, Nature Computational Science, Communications Physics, Communications AI & Computing, and Scientific Reports brings together the advances in Physics-Informed Machine Learning.
Integrating machine learning into business and management in the age of artificial intelligence
Machine learning, with its capacity to leverage computational techniques for experiential learning, has profoundly influenced various disciplines, including business and management. Despite its contributions to the progress of these fields and the advent of artificial intelligence presenting new challenges, there remains ambiguity regarding the specific areas of significant advancement and those with potential for further development. This study addresses three central questions: (1) How is the intellectual landscape of machine learning in business and management research organized and structured? (2) What are the primary applications of machine learning in business administration? And (3) What strategic considerations should companies adopt to effectively leverage machine learning in their business applications? By means of co-occurrence analysis of over 9399 peer-reviewed documents retrieved from Scopus discussing machine learning in business and management, we identified fifteen clusters within the literature. This classification serves as a starting point for firms looking to integrate ML into their routines across fifteen distinct topics. Although some firms have appropriated ML, the upsurge of artificial intelligence presents new challenges, including the digital divide, infrastructure and acquisition dilemmas, security concerns especially with outsourced services, and cost-effectiveness in algorithm selection and practical applications.
Dark matter cannot be ruled out as cause of gamma ray glow at the Milky Way's center, machine learning shows
An international research collaboration between the University of Vienna and Lawrence Berkeley National Laboratory in the ...
A conversation with Congressman Jay Obernolte on artificial intelligence
For now, GAAIA is imperfect, but it is a step in the right direction in taking a proactive approach to the challenges that AI is beginning to present.
Steven Spielberg reveals the one thing he'd change about his movie A.I Artificial Intelligence today
It wasn't until Jurassic Park pushed the limits of special effects in 1993 that Kubrick reconsidered Artificial Intelligence, ...
Berkshire Hathaway Has Plowed Over $21 Billion Into This Artificial Intelligence (AI) Stock Since Warren Buffett Stepped Down
Berkshire's new CEO, Greg Abel, is already swinging for the fences.
Utah lawmakers discuss artificial intelligence, data center policies
Utah lawmakers met on Wednesday morning to discuss a study on artificial intelligence and data center policies across the ...
Can you trust artificial intelligence to help manage your money?
Many people are turning to AI for financial advice but there are questions over the reliability of its responses ...
3 Top Artificial Intelligence (AI) Stocks to Buy With $1,000 Right Now
There are plenty of artificial intelligence (AI) stocks that look like smart buys right now. Whether they're trading at a ...
This Artificial Intelligence (AI) Stock Is Up 4,800% in the Past Year. Wall Street Says This Will Happen Next.
Sandisk shares have rocketed higher amid an unprecedented memory chip supply shortage.
What is the real test of artificial intelligence: Powerful machines or empowering people? PM Modi weighs in at G7 summit
During the G7 Summit, PM Modi discussed AI's transformative potential, emphasising its role in empowering society. He ...