#long non-coding RNAs

[science-sculpt]

RNA: The Dynamic Molecule Driving Life's Diversity

DNA, the blueprint of life, often steals the spotlight when it comes to genetics. But lurking in its shadow is another crucial molecule, RNA (Ribonucleic Acid), playing a pivotal role in the symphony of life. More than just a passive messenger, RNA boasts a vibrant history and holds exciting potential for the future. Let's embark on a journey to unveil the world of RNA, exploring its captivating story and why it deserves your attention.

The story of RNA's discovery began in 1860 when Friedrich Miescher isolated a mysterious "nuclein" from white blood cells. However, it wasn't until the 1950s that James Watson and Francis Crick, alongside Rosalind Franklin (whose contributions were initially overlooked), unraveled the structure of DNA, relegating RNA to a supporting role as a mere messenger molecule. But the plot thickened in the 1960s when researchers like Howard Temin and David Baltimore stumbled upon reverse transcriptase, an enzyme that could convert RNA into DNA, challenging the long-held "central dogma" of DNA being the sole source of genetic information. This discovery opened the door to a whole new understanding of RNA's diverse capabilities.

The Many Faces of RNA

But RNA isn't just a protein puppet master. There are different types of RNA, each with unique jobs:

Messenger RNA (mRNA): Delivers the protein-making message. Transfer RNA (tRNA): Brings the amino acids, the building blocks of proteins, to the party. Ribosomal RNA (rRNA): The foreman of the ribosome factory, making sure everything runs smoothly. Non-coding RNA (ncRNA): A diverse bunch with various roles, from regulating genes to fighting viruses.

The true game-changer came in the early 2000s. Scientists stumbled upon a vast class of non-coding RNAs that don't code for proteins but have diverse and crucial functions. microRNAs (miRNAs), for example, regulate gene expression by silencing specific genes, while long non-coding RNAs (lncRNAs) control various cellular processes like development and disease. This discovery shattered the dogma that only protein-coding genes mattered, highlighting the crucial roles played by non-coding RNAs.

This newfound understanding of RNA's potential has ignited a revolution in medicine. Researchers are exploring RNA-based therapies for various diseases, from cancer and neurodegenerative disorders to viral infections. mRNA vaccines, like the ones used against COVID-19, harness the power of messenger RNA to deliver genetic instructions directly to cells, triggering immune responses. The future holds even more promise, with scientists exploring techniques like CRISPR-Cas9 to edit RNA and potentially treat genetic diseases.

New discoveries are constantly rewriting our understanding of this versatile molecule. Its adaptability and diverse roles make it a powerful tool for exploring the very essence of life, from evolution and development to disease and therapy. So, the next time you hear about genes, remember that RNA, the often-overlooked player, is just as crucial in shaping the tapestry of life. It's a story of constant evolution, unexpected discoveries, and immense potential, making RNA a molecule brimming with fascination and promise for the future.

[rnomics]

Genes, Vol. 15, Pages 1: #RNA Polymerases IV and V Are Involved in Olive Fruit Development

Transcription is carried out in most eukaryotes by three multimeric complexes (#RNA polymerases I, II and III). However, plants contain two additional #RNA polymerases (IV and V), which have evolved from #RNA polymerase II. #RNA polymerases II, IV and V contain both common and specific subunits that may specialise some of their functions. In this study, we conducted a search for the genes that putatively code for the specific subunits of #RNA polymerases IV and V, as well as those corresponding to #RNA polymerase II in olive trees. Based on the homology with the genes of Arabidopsis thaliana, we identified 13 genes that putatively code for the specific subunits of polymerases IV and V, and 16 genes that code for the corresponding specific subunits of polymerase II in olives. The transcriptomic analysis by #RNA-Seq revealed that the expression of the #RNA polymerases IV and V genes was induced during the initial stages of fruit development. Given that #RNA polymerases IV and V are involved in the transcription of long non-coding #RNAs, we investigated their expression and observed relevant changes in the expression of this type of #RNAs. Particularly, the expression of the intergenic and intronic long non-coding #RNAs tended to increase in the early steps of fruit development, suggesting their potential role in this process. The positive correlation between the expression of #RNA polymerases IV and V subunits and the expression of non-coding #RNAs supports the hypothesis that #RNA polymerases IV and V may play a role in fruit development through the synthesis of this type of #RNAs. https://www.mdpi.com/2073-4425/15/1/1?utm_source=dlvr.it&utm_medium=tumblr

[incirrata]

interesting! it's not clear from the pull quote, but these vaccines are "RNA-based" in a very different way than the mRNA vaccines we've been using for COVID-19.

mRNA vaccines introduce mRNA sequences that code for a viral protein, causing the body's cells to produce these proteins which then trigger an immune response, most importantly activating B and T immune cells and antibodies, some of which will stick around and be able to specifically recognize that viral protein in the future and attack viruses with that protein. one problem with these vaccines is that, if those viral proteins mutate too much, this protection will be weakened or disappear.

the vaccines discussed in this article, on the other hand, are live viruses altered to get rid of their ability to suppress the body's antiviral RNA interference (RNAi). this is a totally different mechanism of the immune system—and unfortunately my one immunology class only quickly touched on it, so I don't know how it works in great detail. basically, the body's cells recognize that there's viral RNA and produce their own little bits of RNA ("small interfering RNA," or siRNA) that match up with that viral RNA. these are then used in a system that recognizes viral RNA when it enters a cell and stops it from being translated into proteins. I think it's a recent discovery that these antiviral siRNAs continue to circulate in the bloodstream after an infection is cleared. this means that when the mice in this study were vaccinated with viruses altered to be particularly susceptible to RNAi, (1) these viruses didn't harm them because RNAi was able to clear the infection, and (2) the siRNAs that continued to circulate protected them from subsequent infections for at least 90 days.

my (non-expert) takeaways: this is really exciting as a plausible new mechanism for long-lasting immune protection which could also work for people deficient in the B cell/T cell/antibody aspects of the immune system, and in infants! as the article says, it's also more likely to work for different strains of a virus because pieces of siRNA will be produced which match (as far as I can tell) all/most of the viral RNA genome, including sections which aren't likely to mutate. a caveat: this is a proof of concept in mice and with a virus which doesn't actually infect humans. the article notes that humans produce siRNA in reponse to influenza, so it seems likely that this strategy could work against the flu. I don't know the current state of research on RNA interference in humans, so I'm curious whether we know, for example, how long siRNA remains circulating or how effective an RNA interference response is against flu.

the "universal vaccine" statement is a little misleading: a different vaccine would have to be produced for a different virus (but using the same strategy), and I don't think this could work at all against DNA viruses (e.g. chickenpox, herpes, HPV). but definitely a cool approach that I hope works out!

Scientists at UC Riverside have demonstrated a new, RNA-based vaccine strategy that is effective against any strain of a virus and can be used safely even by babies or the immunocompromised.  Every year, researchers try to predict the four influenza strains that are most likely to be prevalent during the upcoming flu season. And every year, people line up to get their updated vaccine, hoping the researchers formulated the shot correctly. The same is true of COVID vaccines, which have been reformulated to target sub-variants of the most prevalent strains circulating in the U.S. This new strategy would eliminate the need to create all these different shots, because it targets a part of the viral genome that is common to all strains of a virus. The vaccine, how it works, and a demonstration of its efficacy in mice is described in a paper published today in the Proceedings of the National Academy of Sciences.  “What I want to emphasize about this vaccine strategy is that it is broad,” said UCR virologist and paper author Rong Hai. “It is broadly applicable to any number of viruses, broadly effective against any variant of a virus, and safe for a broad spectrum of people. This could be the universal vaccine that we have been looking for.”

Continue Reading.

[jhnneelam]

Epigenetics Diagnostics Market Analysis & Industry Growth Analysis 2025 to 2037

The global Epigenetics Diagnostics Market is experiencing rapid growth, driven by increased awareness of personalized medicine and the role of epigenetic alterations in complex diseases. The market is projected to expand significantly, rising from a value of USD 2.9 billion in 2024 to USD 15.8 billion by 2037, reflecting a Compound Annual Growth Rate (CAGR) of 19.9%. This growth trajectory underscores the transformative potential of epigenetic tools in diagnostics, offering non-invasive, early-detection solutions for diseases that were previously difficult to identify at an early stage.

Epigenetics Diagnostics Industry Demand

The Epigenetics Diagnostics Market focuses on tools and technologies designed to detect inheritable alterations in gene activity that occur without altering the underlying DNA sequence. These epigenetic changes are largely driven by processes like DNA methylation, histone modification, and the regulation of gene expression through non-coding RNAs.

Key Demand Drivers:

Cost-Effectiveness: Epigenetic tests often allow for early diagnosis, which can reduce the need for expensive treatments down the line, improving patient outcomes while cutting healthcare costs.

Ease of Use and Minimally Invasive Techniques: Many epigenetic diagnostics can be conducted using blood, saliva, or other non-invasive samples, making them attractive for routine screening.

Long Shelf Life of Reagents and Kits: Modern epigenetic diagnostic kits are designed with extended stability, reducing waste and simplifying logistics in research and clinical settings.

Growing interest in precision medicine, increased funding for biomarker research, and advancements in next-generation sequencing (NGS) technologies are all accelerating the adoption of epigenetic diagnostics in both clinical and research settings.

Epigenetics Diagnostics Market: Growth Drivers & Key Restraint

Growth Drivers –

Rising Prevalence of Chronic Diseases The increasing global burden of cancer, cardiovascular disorders, and neurological diseases is driving demand for diagnostic methods that can detect and monitor disease progression at a molecular level.

Technological Advancements in Epigenetic Platforms Innovations in high-throughput sequencing, single-cell epigenomics, and AI-assisted diagnostic algorithms are making epigenetic testing faster, more accurate, and scalable for clinical use.

Expansion of Outsourcing and CRO Collaborations Pharmaceutical and biotech firms are increasingly partnering with Contract Research Organizations (CROs) to conduct large-scale epigenetic studies, reducing internal development costs and accelerating timelines.

Restraint –

High Cost of Diagnostic Equipment and Skilled Personnel

Despite long-term cost benefits, the initial investment required for setting up epigenetic testing facilities—along with a need for trained molecular biologists and bioinformaticians

Epigenetics Diagnostics Market: Segment Analysis

Segment Analysis by Product Type (Enzymes, Instruments and Consumables, Reagents, Software, Services):

Enzymes: Critical for modifying DNA or histones in diagnostic assays; demand is rising with the development of targeted diagnostic platforms.

Instruments and Consumables: Includes sequencing systems, PCR machines, and related consumables; instrumental in clinical and high-throughput research settings.

Reagents: Reagents for methylation analysis, chromatin accessibility, and histone modification are widely used in diagnostics and research.

Software: Bioinformatics tools that help analyze large epigenetic datasets; increasingly integrated with AI for disease classification and prediction.

Services: Outsourced diagnostic services, such as methylation profiling and biomarker discovery, are gaining popularity among companies without in-house capabilities.

Request Report Sample@ https://www.kennethresearch.com/sample-request-10352538

Segment Analysis by Application (Oncology Applications, Metabolic Diseases, Developmental Biology, Immunology, Cardiovascular Diseases, Neurodegenerative Disorders):

Oncology Applications: A dominant segment, as epigenetic alterations are hallmarks of many cancers. Diagnostic tests help in early detection, treatment stratification, and monitoring.

Metabolic Diseases: Epigenetic diagnostics aid in understanding the underlying gene-environment interactions in conditions like diabetes and obesity.

Developmental Biology: Used for studying congenital anomalies and inherited disorders through epigenetic screening.

Immunology: Helps decipher immune system dysfunctions and autoimmune conditions by assessing epigenetic markers.

Cardiovascular Diseases: Epigenetic biomarkers are being studied for their predictive potential in atherosclerosis and heart failure.

Neurodegenerative Disorders: Alzheimer’s, Parkinson’s, and other cognitive diseases show distinct epigenetic signatures, opening new diagnostic avenues.

Segment Analysis by End‑User (Academic and Research Institutes, Pharmaceutical Companies, Biotechnology Companies, Contract Research Organizations (CROs), Hospitals and Clinics):

Academic and Research Institutes: Drive innovation through basic research and clinical studies involving epigenetic biomarkers.

Pharmaceutical Companies: Use epigenetic diagnostics for patient stratification, clinical trial optimization, and companion diagnostics.

Biotechnology Companies: Focus on product development, kit manufacturing, and commercializing epigenetic technologies.

Contract Research Organizations (CROs): Serve a critical function in the outsourcing of diagnostic innovation, offering expertise in biomarker analysis, clinical validation, and adherence to regulatory standards.

Hospitals and Clinics: Are progressively adopting epigenetic diagnostics as part of standard medical evaluations, aiding in early disease detection and personalized treatment strategies.

Epigenetics Diagnostics Market: Regional Insights

North America:

North America, led by the United States, dominates the epigenetics diagnostics market due to high healthcare spending, extensive R&D activities, and early adoption of precision medicine technologies. Strong government support for cancer research, coupled with a robust presence of key market players and academic centers, contributes to market maturity and consistent innovation.

Europe:

Europe holds a strong position driven by significant investments in genomics research and national healthcare programs supporting early disease detection. Countries like Germany, the UK, and France are particularly active in integrating epigenetic diagnostics into oncology and rare disease programs. Regulatory harmonization and public-private partnerships further enhance market expansion.

Asia-Pacific (APAC):

APAC is emerging as a fast-growing region, fueled by expanding biotechnology infrastructure, rising healthcare awareness, and government-backed genomics initiatives in countries like China, Japan, South Korea, and India. Cost-sensitive innovations and increasing CRO presence are making epigenetic diagnostics more accessible and scalable in this region.

Access our detailed report link:https://www.kennethresearch.com/report-details/epigenetics-diagnostics-market/10352538

Top Players in the Epigenetics Diagnostics Market

Illumina, Inc.,Thermo Fisher Scientific,QIAGEN N.V.,F. Hoffmann-La Roche Ltd,Merck KGaA,Eisai Co., Ltd.,Takara Bio Inc.,Bioneer Corporation,Cell Signaling Technology,Zymo Research Corporation,Bio-Rad Laboratories,Agilent Technologies,PerkinElmer, Inc.,Novogene Co., Ltd.,BGI Genomics,Syngene International,GeneCare Research Institute,Australian Genome Research Facility,Pacific Biosciences,Epigentek Group Inc.

[thelovebudllc]

Serum hsa_circ_101555 as a promising biomarker for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents the most prevalent malignancy in Egypt and globally. However, non-invasive diagnostic/prognostic biomarkers for early detection of HCC are still lacking. Circular RNAs (circRNAs) are one of the promising biomarkers. They are considered stable, long-stranded non-coding RNAs in a sealed circular form held together by covalent bonds. circRNAs have been…

[medchemexpressinhibitor-blog]

Nobel Prizes 2024：Three major awards announced

The Nobel Prize in Physiology or Medicine 2024

Discovery of micrornas and their role in post-transcriptional gene regulation

Figure 1. The Nobel Prize in Physiology or Medicine 2024[1].

For a long time, it was believed that genetic information is transcribed from DNA to mRNA, which is then translated into proteins. However, the findings of Victor Ambros and Gary Ruvkun demonstrate that RNA, in addition to encoding proteins, also includes non-coding RNA (ncRNA) that plays a regulatory role in gene function.

Discovery of miRNA

Figure 2. Discovery of miRNA[3].

Although this discovery was groundbreaking and revealed a new mechanism of gene regulation, it did not garner much attention in the scientific community at the time.

Figure 3. Ruvkun cloned let-7, a second gene encoding a microRNA[3].

The discovery of the let-7 gene sparked great interest among researchers, motivating scientists worldwide to conduct related studies. Over the following years, hundreds of different miRNAs were identified. Due to the rapid discovery and functional elucidation of miRNAs, scientists from the Sanger Institute established the microRNA Registry in 2002, which was later renamed miRBase. The creation of this database provided a standardized and convenient resource for miRNA research, enabling researchers to easily access comprehensive information about known miRNAs, including their sequences, origins, and functions.

miRNA: Synthesis and Application

In addition to identifying new miRNAs, researchers have elucidated the mechanisms by which miRNAs are generated and bind to mRNA, leading to the inhibition of protein synthesis or the degradation of mRNA. This will not be elaborated on here.

Interestingly, due to the low complementarity of miRNAs, they often do not perfectly match their target genes, allowing them to regulate the expression of multiple target genes simultaneously. Increasing evidence suggests that miRNA dysregulation is associated with various human diseases, including cancer, diabetes, and cardiovascular diseases. For example, the loss of let-7 plays a pathogenic role in several cancers. During the process of muscle cell fibrosis, miR-21 is significantly upregulated, leading to cardiac hypertrophy[5][6][7].

Currently, efforts are underway to develop oligonucleotide drugs targeting miRNAs. Examples include RGLS4326 (which inhibits the function of miR-17) for the treatment of autosomal dominant polycystic kidney disease (ADPKD), Miravirsen (which inhibits the function of miR-122) for HCV treatment, and Cobomarsen (which inhibits the function of miR-155) for the treatment of B-cell lymphoma.

miRNA Related Products

MedChemExpress (MCE) has independently designed and developed a series of tools for studying miRNA functions based on the mature miRNA sequences of humans, mice, and rats from the miRBase database. These tools include miRNA mimics, miRNA inhibitors, miRNA agomirs, and miRNA antagomirs. Currently, these miRNA-related products are available at a 35% discount promotion. We welcome all customers to inquire about our custom services related to miRNA.

The Nobel Prize in Physiology or Medicine 2024

For promoting the fundamental discovery and invention of machine learning using artificial neural networks

Figure 4. The Nobel Prize in Physiology or Medicine 2024[8].

The awardees utilized tools from physics to develop various methods that laid the groundwork for today’s powerful machine learning. John Hopfield created a structure capable of storing and reconstructing information. Geoffrey Hinton invented a method that can independently discover data properties, which is crucial for the large artificial neural networks currently in use.

Figure 5. The Nobel Prize in Physiology or Medicine 2024[9].

In recent years, this technology has also begun to be used to compute and predict the properties of molecules and materials, such as calculating the molecular structure of proteins that determine their function or identifying which new materials may have the best characteristics for more efficient solar cells.

Machine Learning

As early as 1950, the Turing Test was proposed, igniting a heated discussion about whether machines can “think.”

Machine learning differs from traditional software in its operation. Traditional software works by receiving data, processing it according to clear instructions, and producing results. In contrast, in machine learning, computers learn through examples, enabling them to solve problems.

Yes, computers cannot think, but machines can now mimic functions such as memory and learning. This year’s Nobel Prize winners contributed to making this possible, laying the groundwork for today’s powerful machine learning. They utilized fundamental concepts and methods from physics to develop techniques for processing information using network structures, specifically through artificial neural networks.

The advancements we are witnessing today have been made possible by the acquisition of vast amounts of data available for training networks and a significant increase in computational power.

AI and Drug Development

Today’s artificial neural networks are often very large and consist of multiple layers. These are known as deep neural networks, and their training method is referred to as deep learning.

Deep learning is a branch of artificial intelligence (AI) that utilizes neural networks for learning. This technology has made significant advances in the field of biomedicine.

Research has shown that deep learning techniques have advantages in optimizing chemical synthesis pathways, predicting the pharmacokinetic properties of drugs, forecasting drug targets, and generating novel molecules.

Currently, researchers have developed a range of application strategies based on deep learning for disease diagnosis, protein design, and medical image recognition. The pharmaceutical industry is also beginning to recognize the value of deep learning technology, hoping to leverage it to accelerate drug development and reduce costs.

MCE One-Stop Drug Screening Platform

MCE’s one-stop drug screening platform focuses on the drug discovery phase and utilizes generative artificial intelligence technology to create an ultra-large compound library called MegaUni, which combines novelty, drug-like properties, diversity, and synthetic feasibility. This library is suitable for AI drug screening and large-scale virtual screening.

The MegaUni library contains a vast number of previously unreported novel structural molecules, providing limitless possibilities for scientific innovation. Additionally, AI algorithms are applied to the construction of various types of Mini compound libraries, helping clients more efficiently obtain compound libraries that meet their specific needs.

Furthermore, the drug screening platform includes both computer-based virtual screening and physical drug screening. In the realm of virtual screening, it combines AI active learning with molecular docking to support larger-scale virtual screenings.

The Nobel Prize in Chemistry 2024

Figure 6. The Nobel Prize in Chemistry 2024[10].

David Baker has created entirely new types of proteins, successfully accomplishing feats that were previously thought to be nearly impossible. Demis Hassabis and John M. Jumper developed an artificial intelligence model to tackle a problem that has persisted for 50 years: predicting the complex structures of proteins. These two distinct discoveries are closely linked and hold tremendous potential.

“Computational Protein Design”

The field of protein design began in the late 1990s, with researchers designing custom proteins with new functions. In many cases, researchers adjusted existing proteins so that they could break down harmful substances or serve as tools in chemical manufacturing.

Figure 7. Top7 — the first protein that was entirely different to all known existing proteins[11].

“Protein Structure Prediction”

Proteins are typically composed of 20 different amino acids, which can be combined in countless ways. Using the information stored in DNA as a template, amino acids are linked together in our cells to form long chains. These chains of amino acids twist and fold into unique (and sometimes one-of-a-kind) three-dimensional structures. This structure imparts functionality to the proteins.

Since the 1970s, researchers have been trying to predict protein structures based on amino acid sequences, but this has proven to be very challenging.

Figure 8. AlphaFold2 computes a 3D structure model of the protein[12].

Statistics show that about two-thirds of the structures predicted by AlphaFold 2 achieved a prediction accuracy that matches the measurement precision of structural biology experiments.

Since this breakthrough, more than 2 million users from 190 countries have utilized AlphaFold 2.

Additionally, AlphaFold 3, a new revolutionary artificial intelligence (AI) model, has been developed through significant advancements in the architecture and training process of AlphaFold 2. It adapts to more general chemical structures and improves the efficiency of learning from data. It predicts the structures of a wider range of biomolecules with unprecedented accuracy, including complexes involving ligands, ions, nucleic acids, and modified residues.

Compared to existing prediction methods, AlphaFold 3 shows at least a 50% improvement in the accuracy of predicting protein interactions with other biomolecules, with prediction accuracy even doubling for certain important categories of interactions.

Without proteins, life cannot exist. The ability to predict protein structures and design our own proteins has a profound impact on humanity.

References

[1] The Nobel Prize in Physiology or Medicine 2024. NobelPrize.org. Nobel Prize Outreach AB 2024. Wed. 9 Oct 2024. [2] Lee RC, et al. Cell. 1993;75(5):843–854. [3] Press release. NobelPrize.org. Nobel Prize Outreach AB 2024. Wed. 9 Oct 2024. [4] Rupaimoole R,et al. Nat Rev Drug Discov. 2017;16(3):203–222. [5] Liu H, et al. Mol Cancer. 2018;17(1):64. [6] Pasquinelli AE, et al.Nature. 2000;408(6808):86–89. [7] Wang P, et al.Theranostics. 2021;11(18):8771–8796. [8] The Nobel Prize in Physics 2024. NobelPrize.org. Nobel Prize Outreach AB 2024. Wed. 9 Oct 2024. [9] Press release. NobelPrize.org. Nobel Prize Outreach AB 2024. Thu. 10 Oct 2024. [10] The Nobel Prize in Chemistry 2024. NobelPrize.org. Nobel Prize Outreach AB 2024. Wed. 9 Oct 2024. [11] Popular information. NobelPrize.org. Nobel Prize Outreach AB 2024. Thu. 10 Oct 2024 . [12] Jumper J, et al. Nature. 2021 Aug;596(7873):583–589 .

[snigepippi]

This sounds a bit too anti-medication to me.

But I agree that there is way too little study of the psychobiological variations in the human brain.

However it is damn hard to design ethical experiments on human brains.

Currently there is a lot of interest in epigenetic changes (when some genes are permanently turned off or on) in the brain, regarding disorders. Because a lot of disorders have been correlated to specific gene clusters, but not everyone with these gene clusters get severe disorders, and the severity varies a lot. So the suggestions are that how genes are regulated affect the brain. And epigenetic changes can be triggered by nurture and events in life, and it would be awesome if we could prevent bad cases, by knowing what to do and what not to do. Not to mention working more on changing the epigenetic regulations.

But how can you learn which genes are turned off or on? Sadly we need actual brain samples. Because the non-brain cells will likely have tuned all these genes off. Why would blood cells from a blood sample have brain regulation genes turned ontoff? They are unnecessary for blood cells, so the genes are all turned off and packed tightly. We need brain tissue, preferably from many places in the brain. And that is considered very unethical to take from mostly healthy brains. We don't even do it on dead people, without their consent.

What is mostly done in studying the psychobiology, is doing in vitro testing, making mice or rats who express the same disorders, and even give them the genes we suspect have an effect. And of course asking people to donate brains after death. But even if rodents are the closest family to primates and dead brains do keep some of the epigenetic changes. It is not optimal.

Also to understand what triggers epigenetic changes, we really need to start with the maternal grandmother of the study subject, as the epigenetic changes in her ovaries affect at least the next two generations. On humans that is very long studies. (Even if we were very unethical it would take around 40 years to get a teen brain to study.) And extra unethical if we want to expose the families to suspected triggers. We do it on mice, but while genomes of mice are close to us, there are also some major differences. For instance humans have more non-coding DNA (junk-DNA) than most other species. Non-coding DNA make a lot of regulatory RNA that aren't recognisable genes, and RNA is fickle and fiddly to work with.

Same with the biochemistry. We cannot really tell much about the exact biochemistry in a human living brain. Because we need to take a look on the exact cells, to really know what's going on.

The reason why we use the effect of medication to make conclusions, is that it indirectly tells something about the biochemistry of the brain. We know how this drug tend to affect other cells, and then extrapolate what it might do to brain biochemistry, without having to take a brain sample.

We can still do more than we are doing now.

But as always the minorities, the poor and the powerless are more often ignored by medical science. And unfortunately disorders and poverty often go together. And when you have bad mental health, it's hard to find the time and energy to fight for better treatment.

if you look into the history of biopsychiatric research you will often find a tension between the search for new drugs and the search for a biological cause of specific disorders. often, as soon as a medicine is found that performs slightly better than placebo in one clinical trial, its workings are then retroactively explained by a “new insight” into the workings of the disorder (see the dopamine theory of schizophrenia, or the lithium theory of bipolar disorder). describing the disorder as resulting of a specific imbalance in brain chemistry helps legitimize the existence of the diagnosis; describing the drug as correcting that imbalance helps sell it. discussing lithium, johanna moncrief says: “without it the treatment for mania and schizophrenia would appear indistinguishable (as they more or less are), the justification for diagnosis would be undermined and the whole disease-centred conception of modern psychiatric drug treatment would start to look fragile.”

both of those processes often develop in parallel to each other in a process that is famous for poor methodology and unreplicable results. often the same drug is presented in various new ways (“we know it works, we just didn���t know why until now!”, rinse and repeat) - or sold for a different diagnosis (while still asserting its disease-specific action) to keep the sales up, by funding new studies so that anyone pointing out this pattern can be dismissed as ignoring scientific progress.

[nursingwriter]

Role of HIT in Healthcare Planning Healthcare information technology (HIT) is one of the greatest disruptive forces that will affect vision and planning over the next decade. However, regardless of the technology that is developed, it must be supported and executed by hospital leadership to be successful. Currently, research is underway for the use of artificial intelligence, supercomputing, and clinical support systems in the healthcare environment. This research will explore how these technologies are likely to change healthcare in the future, and the role of readership in making the integration of these technologies a success. Overview Currently, information technology is an integral part of the healthcare system. HIT refers to a variety of technologies that collect, transmit, store, and display patient data electronically (Hemmat, Ayatollahi, Maleki, and Safhafi, 2017). This makes it easy to send, review, and update patient information quickly and easily. The current list of technologies includes remote and mobile health technology, cloud-based services, medical devices, telemonitoring tools, sensor technologies, and electronic health records (EHR’s) (Hemmat, Ayatollahi, Maleki, and Safhafi, 2017). The use of technology in many different types of healthcare settings is already in daily practice. However, in the future, the use and types of technologies used in the healthcare setting are expected to expand exponentially. Countries continue to make extensive investment in the area of technology development for the healthcare industry (Hemmat, Ayatollahi, Maleki, and Safhafi, 2017). This suggests that there is considerable interest in the development of technology in the healthcare industry in the near and long-term future. Now, it is time to examine some of the different types of technology that can be expected to be seen in the future. Artificial Intelligence Artificial intelligence (AI) is technology that is designed to mimic human cognitive functions. One of the areas that it offers improvement in the healthcare setting is the ability to assist in analytics that can be applied to both structured and unstructured data (Jiang, Jiang, Zhi, Dong, Hao, & Ma, et al., 2017). In the future, it is expected to be able to help doctors make better clinical decisions, with many of the advances in this area in the field of radiology (Jiang, Jiang, Zhi, Dong, Hao, & Ma, et al., 2017). The fascinating feature of AI is that it can be trained through data to perform clinical activities including diagnosis and treatment assignment for patients (Jiang, Jiang, Zhi, Dong, Hao, & Ma, et al., 2017). Technology is being developed that can learn similar groups of subjects and the associations between features, such as race and demographic information, to increase the likelihood of the desired outcome. One of the areas where AI is being developed to be used in future is in the field of cancer diagnosis. In a recent study, this technology was used to analyze abnormal genetic expression in non-coding RNA to diagnose gastric cancer in a sample population (Li, Liang, Yao, Sui, Shen, & Zhang, 2016). It also been applied to detect diabetic retinopathy through retinal fundus photographs with a sensitivity of over 90% (Gulsham, Peng, & Coram, 2016). These are only a few examples of the uses of this technology that are currently under study and development. However, an examination of the literature indicates that there is a significant amount of interest in the use of AI for diagnostic and treatment analysis. This technology is designed to assist physicians, and give them another tool, but it will not replace human intervention in the process. It is another set of eyes and gives the physician a level of information that they did not have access to in the past. Supercomputing Supercomputing is another form of information technology that is set to revolutionize the ability to solve data intensive problems in the healthcare industry. This technology uses an array of computer systems working in parallel at their maximum performance to do data intensive calculations. In many cases, this type of data analysis would take months or years to complete by humans, and in some it may not even be possible without the use of these arrays of computers. Cray supercomputer systems have teamed up with Microsoft using Microsoft Azure data centers (O’Dowd, 2017). This will allow users in the healthcare industry to run heavy workloads and support artificial intelligence in this environment. In addition, this technology can now be deployed in the cloud. This allows the ability to process real-time analytics and provide powerful solutions to the healthcare industry (O’Dowd, 2017). Supercomputers have been around since 1964, but their power and ability to process big data has increased exponentially with the power of the computers hooked into the array (Engel, 2019). Now, computers can perform 1 trillion operations every second (Engel, 2019). One of the most prominent areas where super computers are being employed is in the area of genetics and DNA. Plans are under development to be able to use supercomputers to detect tiny genetic differences that can help adjust medications and save lives (Engel, 2019). One of the challenges of developing super computers that can be used in a real-time clinical setting is cost. Supercomputer systems cost hundreds of millions of dollars. This is one of the key barriers to implementing them in the average healthcare setting. For this reason, they are typically only found in research setting at the present time (Engel, 2019). However, as computer technology continues to grow, these systems may become more accessible to healthcare providers in the future. Many researchers are now beginning to develop the potential for combining artificial intelligence and supercomputing in a way that opens possibilities that were never achievable in the past. This is some of the technology that is behind the sequencing of the human genome and that will be at the forefront of genetic research in the future. Never before has humanity have the ability to analyze such large numbers of data quickly and efficiently. This opens up many new possibilities and probabilities that have not been considered in the past. Clinical Support Systems Perhaps one of the most exciting areas in the development of HIT for the healthcare community is research into clinical support systems that will assist in helping to make clinical decisions for patients. One of the key areas where this technology is being developed is to promote patient safety. It is expected that in the future clinical support systems will be the cornerstone of improved efficiency, effectiveness of healthcare, quality, and safety (HealthIT.gov, 2018). The clinical support system allows the information to be filtered and presented at an appropriate time in the clinical workflow (HealthIT.gov, 2018). Currently, a wide number of tools are being developed for use in many different clinical settings. There is a significant interest in the development of the systems at the present time. The capabilities of clinical support systems include alerts and reminders to care providers and patients (HealthIT.gov, 2018). It includes clinical guidelines, and a condition-specific treatment sequence. It can provide instant patient data reports and summaries, documentation templates, and diagnostic support. Can also provide relevant reference information and a number of other tools (HealthIT.gov, 2018). The systems that are currently in use and being further developed have functions in place for reasoning and inferences. This allows them to combine both data collection and knowledge in a way that is relevant and useful to the current patient situation (HealthIT.gov, 2018). Clinical support systems are currently a requirement for healthcare facilities that accept Medicare and Medicaid (Centers for Medicare & Medicaid Services, 2014). There are also quite a few systems of one the market from major manufacturers. This area is highly lucrative for both suppliers and healthcare providers. By now, most healthcare staff are familiar with using clinical support systems as a part of their daily routine. The purpose of the clinical support system is to provide not only information, but information that is relevant to the patient and provide interventions that will be most likely to be effective (Centers for Medicare & Medicaid Services, 2014). Their use in pharmacies, hospitals, and many individual practices. One of the advantages of the clinical support system is that records are portable and allow the electronic transmission of records that are compliant with HIPAA (Centers for Medicare & Medicaid Services, 2014). Currently, there are well-established guidelines that affect the operation of these systems. However, they are likely to become even more advanced and capable of doing more things in the future. Role of Leadership This research provided an overview of some of the exciting advances in technology that are currently under development, and currently in use in healthcare systems. These systems promise to provide the ability to analyze data faster and analyze larger quantities of data to achieve more precise and valid research results. Computers can now do things in terms of data analysis that humans are no longer capable of when it comes to time and ability. There is no doubt that HIT will provide promising outcomes in the future. However, this technology is only as good as the ability to apply it in a real-world settings. It is up to healthcare leaders to keep up-to-date with the latest advances in technology and to support their application in the clinical setting. There is no doubt that having the latest technology in a healthcare setting gives it a decided competitive advantage. Having the latest technology is an excellent branding and advertising point. Leaders must understand the importance of having the latest technology to improve their operational costs, staff efficiency, and reduce their rates of errors. It is responsibility of leadership to keep up with the advances in HIT and to find ways to implement these new technologies and their healthcare setting as quickly as possible. Of course, funding is always an issue when it comes to new technology, but the advantages in the ability to process through a higher number of patients and provide them with better care justifies the cost of this new technology. In the healthcare industry, staff members and lower managers look to the attitudes and support of upper leadership in terms of whether to support the adoption of the latest advances in technology. Sometimes these new technologies can be intimidating because they are unfamiliar. However, it is up to the leaders to make certain that staff is trained and becomes familiar with the operation of the new technology and that they have a supportive attitude towards it on adoption. Leadership plays a key role in the adoption and use of new advances in technology in the real world. Keeping up with the newest technology is paramount to the commitment to provide quality healthcare to patients. It is a leader’s responsibility to make sure that their patients have access to the most advanced technology available in order to improve overall outcomes. Technology is the key to leading a healthcare organization to excellence and sustaining a competitive advantage. Leaders must keep this in the forefront of their decision-making guidelines. The bottom line is not about controlling costs, it is about providing excellent patient care and making sure that they have the best equipment and technology available in order to do so. References Centers for Medicare & Medicaid Services. (2014). Clinical decision support: more than just ‘alerts’ tipsheet. eHealthUniversity. Retrieved from https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/ClinicalDecisionSupport_Tipsheet-.pdf Engel, K. (2019), Supercomputers are shaping future of humanity. Retrieved from https://www.whoishostingthis.com/blog/2016/08/12/supercomputers/ Gulshan, V., Peng, L. & Coram, M. (2016). Development and Validation of a Deep Learning Algorithm for detection of Diabetic Retinopathy in retinal fundus photographs. JAMA, 316, 2402–10. Retrieved from: https://jamanetwork.com/journals/jama/fullarticle/2588763 Hemmat, M., Ayatollahi, H., Maleki, M., & Saghafi, F. (2017). Future research and health information technology: a review. Perspectives in Health Information Management, 14(1b), Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5430110/ HeatlhIT.gov (2018). Clinical Decision Support. Retrieved from https://www.healthit.gov/topic/safety/clinical-decision-support Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Hao, L. & Ma, S. et al. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology, 2(4). Retrieved from: https://svn.bmj.com/content/2/4/230 Li, C., Liang, G., Yao, W., Sui, J., Shen, X., & Zhang, Y et al. (2016). Integrated analysis of long non-coding RNA competing interactions reveals the potential role in progression of human gastric Cancer. Int J Oncol 48, 1965–76. Retrieved from https://www.spandidos-publications.com/10.3892/ijo.2016.3407 O’Dowd, E. (2017). Cray Supercomputers, Microsoft Azure Aid Healthcare Analytics. HIT Infrastructure. Retrieved from https://hitinfrastructure.com/news/cray-supercomputers-microsoft-azure-aid-healthcare-analytics Read the full article

[opinionated-opinion]

The Role of Epigenetic Modifications in Gene Regulation: A Critical Review Cellular differentiation, development, and response to various environmental changes all are multistep biological processes that depend fundamentally on gene regulation. Epigenetic modifications allow the cell to respond interactively to environmental changes without altering the DNA sequence and have thus gained increased attention during the last few years. This blog will critically review some of the important epigenetic mechanisms-DNA methylation, histone modifications, and noncoding RNAs-and their involvement in health and disease.

What is Epigenetic? Epigenetics is defined as the study of heritable features concerning the role of gene regulation and not the underlying DNA sequence. These types of modification, usually reversible, have the ability to dynamically alter the expression of a gene by a cell. The epigenetic mechanisms allow cell differentiation in multicellular organisms beginning from the same DNA sequence genome.

Key Mechanisms of Epigenetic Regulation

DNA Methylation

DNA Methylation DNA methylation is one among the well-studied epigenetic mechanisms. It comprises the addition of a methyl group to the cytosine residue in the CpG dinucleotides, usually associated with the silencing of gene expression. Methylation patterns are important in normal development, while abnormal methylation is associated with diseases including cancer. For instance, the hypermethylation of tumor suppressor genes has been related to the inactivation of such genes in many kinds of cancers Esteller 2007.

Histone Modifications

DNA wraps around core histone proteins to form a nucleoprotein called chromatin, and changing the tail domains of the histones affects both the structure of chromatin and gene expression. Acetylation, methylation, phosphorylation, and sumoylation of histones affects the access of DNA to the transcriptional machinery. For example, in general, histone acetylation activates transcription whereas deacetylation causes silencing, Kouzarides 2007.

Non-coding RNAs: ncRNAs Non-coding RNAs, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), also play significant roles in gene regulation. miRNAs can degrade messenger RNA (mRNA) or inhibit translation, thus controlling gene expression post-transcriptionally. lncRNAs, on the other hand, regulate gene expression at various levels, including chromatin modification, transcription, and post-transcriptional processes (Rinn & Chang, 2012).

Critical Review: Epigenetic Changes Are of a Janus Nature Epigenetic modification is an indispensable component in physiological processes but turns out to be a double-edged sword since inappropriate epigenetic change gives rise to diseases like tumorigenesis, neurodegeneration, and autoimmune disease.

Epigenetic Therapies Epigenetic alterations, due to their reversible nature, represent very promising therapeutic targets. Therapeutic drugs like DNA methyltransferase inhibitors (for example, azacitidine) and histone deacetylase inhibitors (for example, vorinostat) are effective in the treatment of some cancers (Jones et al., 2016). However, the main challenges lie in guaranteeing specificity because broad epigenetic reprogramming leads to off-target effects.

Epigenetic and Environmental Influence The epigenome is very sensitive to nutrition, toxicants, and stresses. For example, prenatal exposure to malnutrition results in epigenetic modification, increasing the susceptibility to metabolic diseases later in life (Heijmans et al., 2008). Such sensitivities underline how understanding of epigenetic regulation involves lifestyle factors.

Conclusion:

Epigenetic modifications also play crucial roles in fine-tuning gene expression and the maintenance of cellular homeostasis. While allowing new possibilities of therapeutic intervention, especially in cancer, some problems remain to be investigated concerning specificity and also environmental impact. Further research will thus become necessary regarding the dynamic nature of the epigenome if specific and efficacious treatments are to be developed.

References

Esteller, M. (2007). Epigenetic gene silencing in cancer: The DNA hypermethylome. Human Molecular Genetics, 16(R1), R50–R59.

Heijmans, B. T., Tobi, E. W., Stein, A. D., Putter, H., Blauw, G. J., Susser, E. S., Slagboom, P. E., & Lumey, L. H. (2008). Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proceedings of the National Academy of Sciences, 105(44), 17046-17049.

Jones, P. A., Issa, J. P., & Baylin, S. (2016). Targeting the cancer epigenome for therapy. Nature Reviews Genetics, 17(10), 630–641.

Kouzarides, T. (2007). Chromatin modifications and their function. Cell, 128(4), 693-705.

Rinn, J. L., & Chang, H. Y. (2012). Genome regulation by long noncoding RNAs. Annual Review of Biochemistry, 81, 145-166.

[leedsomics]

Comparative pan-genomics reveals divergent adaptations in clinically-relevant members of the Fusarium solani species complex

The Fusarium solani species complex are a group of dual-kingdom fungal pathogens capable of causing devastating disease on a wide range of host plants and life-threatening infections in humans that are difficult to treat. In this study, we generate highly contiguous genomes for three clinical isolates of Fusarium keratoplasticum and three clinical isolates of Fusarium petroliphilum and compare them with other genomes of the FSSC from plant and animal sources. We find that human pathogenicity is polyphyletic within the FSSC, including in F. keratoplasticum. Pan-genome analysis revealed a high degree of gene presence-absence in the complex, with only 41% of genes (11,079/27,068) found in all samples and the presence of accessory chromosomes encoding isolate- and species-specific genes. We also defined conserved long non-coding RNAs (lncRNAs) between F. keratoplasticum and F. petroliphilum, revealing that they show a similar low degree of presence-absence variation. Secondary metabolite analysis revealed a conserved core set of biosynthetic gene clusters across the FSSC, as well as a unique cluster potentially linked to keratitis. Transcriptomic analysis under stress conditions showed minimal differential gene expression, indicating that both F. keratoplasticum and F. petroliphilum are well adapted to human infection-relevant conditions. This study provides valuable insights into the evolutionary dynamics, genomic architecture, and potential pathogenicity mechanisms of the FSSC, with implications for understanding multi-kingdom virulence, of increasing relevance as climate change potentially increases the number of fungal species that can grow at human temperatures. http://dlvr.it/TDbBH3

[rnomics]

Biomedicines, Vol. 12, Pages 1988: Importance of Studying Non-Coding #RNA in Children and Adolescents with Type 1 Diabetes

Type 1 diabetes (T1D) mellitus is a chronic illness in children and teens, with rising global incidence rates. It stems from an autoimmune attack on pancreatic β cells, leading to insufficient insulin production. Genetic susceptibility and environmental triggers initiate this process. Early detection is possible by identifying multiple autoantibodies, which aids in predicting future T1D development. A new staging system highlights T1D’s onset with islet autoimmunity rather than symptoms. Family members of T1D patients face a significantly increased risk of T1D. Italy recently passed a law mandating national T1D screening for pediatric populations. Measurements of β cell function continue to be essential in assessing efficacy, and different models have been proposed, but more appropriate biomarkers are mandatory for both progression studies before the onset of diabetes and during therapeutic monitoring. Biomarkers like micro#RNAs (#miRNAs), long non-coding #RNAs (l#ncRNAs), and circular #RNAs (circ#RNAs) play key roles in T1D pathogenesis by regulating gene expression. Understanding their roles offers insights into T1D mechanisms and potential therapeutic targets. In this review, we summarized recent progress in the roles of some non-coding #RNAs (#ncRNAs) in the pathogenesis of T1D, with particular attention to #miRNAs, l#ncRNAs, and circ#RNAs. https://www.mdpi.com/2227-9059/12/9/1988?utm_source=dlvr.it&utm_medium=tumblr

[mysticalpeacenut]

Trends in RNA Targeted Drug Development

RNA has emerged as a promising target within the subject of drug discovery, supplying new opportunities for healing intervention in a number sicknesses. Unlike traditional approaches that mainly recognition on proteins, RNA-targeted drug development seeks to govern RNA molecules immediately, influencing gene expression and protein synthesis in ways that have been previously inconceivable. This shift is opening up interesting avenues for the remedy of genetic disorders, cancers, and viral infections, among others.

In this weblog, we're going to explore the ultra-modern developments in RNA-targeted drug development and the way this innovative approach is reworking the landscape of medication.

The Rise of RNA-Targeted Drug Discovery

RNA Targeted Drug Discovery has won widespread momentum in recent years, driven by means of advances in information RNA biology and the improvement of new technologies. Traditional drug discovery has predominantly targeted on proteins as the primary targets for healing intervention. However, RNA offers several unique benefits as a drug target.

Firstly, RNA plays a valuable role inside the waft of genetic statistics, appearing as a crucial intermediary among DNA and proteins. By focused on RNA, researchers can immediately impact gene expression, doubtlessly silencing dangerous genes or correcting genetic defects. This makes RNA-focused treatment options in particular attractive for treating genetic sicknesses wherein traditional protein-targeting procedures may also fall quick.

Moreover, the invention of various RNA sorts, which include long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), has multiplied the scope of RNA-targeted drug discovery. These RNA molecules play important roles in gene law and cell processes, and concentrated on them can provide new therapeutic avenues.

Transforming RNA-Targeted Drug Discovery

The transformation of RNA-targeted drug discovery has been fueled through numerous key traits:

RNA Interference (RNAi): RNAi is a groundbreaking generation that permits for the selective silencing of particular genes. By introducing small interfering RNAs (siRNAs) into cells, researchers can degrade goal RNA molecules, efficiently shutting down the expression of sickness-causing genes. RNAi has already brought about the development of numerous FDA-authorised tablets, demonstrating the potential of RNA-focused healing procedures.

Antisense Oligonucleotides (ASOs): ASOs are short, artificial RNA-like molecules designed to bind to particular RNA sequences. By binding to goal RNA, ASOs can modulate splicing, degrade RNA, or block translation, presenting a versatile technique to RNA-targeted drug development. ASOs have shown promise in treating a number of situations, which includes spinal muscular atrophy and Duchenne muscular dystrophy.

Drugs Targeting RNA Riboswitches: RNA riboswitches are regulatory segments of RNA which can trade their shape in reaction to small molecule binding. These riboswitches manage gene expression by means of influencing RNA transcription, translation, or balance. Drugs focused on RNA riboswitches represent a novel method to modulate gene expression and provide a new frontier in RNA drug improvement.

CRISPR-Cas Systems: Originally advanced as a tool for gene modifying, CRISPR-Cas structures are actually being tailored for RNA targeting. CRISPR-based technology may be used to precisely edit RNA molecules, providing a effective tool for correcting genetic defects or modulating gene expression. This method has the capability to revolutionize RNA-centered drug discovery via enabling unique, on-demand manipulation of RNA.

RNA Vaccines: The fulfillment of mRNA vaccines in combating COVID-19 has underscored the ability of RNA-primarily based cures. MRNA vaccines paintings by using introducing synthetic mRNA into cells, teaching them to provide particular proteins that elicit an immune reaction. This technique may be extended to other diseases, doubtlessly leading to the development of vaccines and therapies for a wide variety of situations.

The Future of RNA-Targeted Drug Development

The destiny of RNA-focused drug improvement is highly promising, with ongoing research aimed at overcoming present challenges and expanding the range of treatable situations. Key regions of focus consist of enhancing the stability and delivery of RNA-primarily based drugs, lowering off-goal consequences, and exploring new RNA targets.

One of the most interesting regions of studies involves RNA riboswitches and different regulatory RNA elements. By designing tablets that especially bind to those RNA structures, researchers can modulate gene expression in a especially managed way. This technique has the potential to liberate new healing techniques for situations that are currently hard to deal with.

Another trend is the exploration of RNA modifications, inclusive of methylation, that may affect RNA characteristic. By focused on these changes, researchers can expand remedies that pleasant-tune RNA pastime, offering a new stage of precision in drug development.

In addition to therapeutic applications, RNA-focused techniques are being explored for diagnostic purposes. RNA biomarkers are being investigated as capability tools for early sickness detection and tracking remedy responses. This should lead to the development of customized medication techniques which can be tailored to an man or woman’s RNA profile.

Conclusion

The rapid improvements in RNA-targeted drug discovery and RNA-targeted drug improvement are reworking the panorama of medication. From RNAi and antisense oligonucleotides to CRISPR-Cas structures and RNA vaccines, the opportunities for therapeutic intervention are increasing at an extraordinary fee. The potential to target RNA at once gives new possibilities for treating a wide variety of diseases, from genetic problems to cancer.

As researchers maintain to explore the ability of RNA-primarily based treatment options, the future of drugs seems more and more promising. The improvements in RNA drug discovery are paving the manner for a brand new generation of precision remedy, in which treatments may be tailored to the precise molecular makeup of every affected person.

For those at the forefront of this interesting area, the possibilities are endless. Whether you’re involved in research, development, or clinical utility, staying knowledgeable approximately the contemporary traits in RNA-centered drug discovery is important for riding innovation and enhancing affected person outcomes.

At Depixus, we are devoted to advancing the sphere of RNA-targeted drug discovery. Our current technologies are designed to aid researchers of their quest to increase the following generation of RNA-based totally healing procedures.

To learn more about how we can help you live in advance in this hastily evolving area, go to us at Depixus.

Reposted Blog Post URL: https://petrickzagblogger.wordpress.com/2024/08/28/rna-targeted-drug-development/

[evoldir]

Fwd: Graduate position: Mainz_Germany.SexDeterminaitonHymenoptera

Begin forwarded message: > From: evoldir@evol.biology.mcmaster.ca > Subject: Graduate position: Mainz_Germany.SexDeterminaitonHymenoptera > Date: 27 June 2024 at 05:59:08 BST > To: rdmpage@gmail.com > > > We invite applicants for a PhD position to study molecular regulation > and evolution of sex determination in hymenopteran insects. The > project is funded for 3 years through the GenEvo RTG and will be > based at the Institute of Molecular Biology in Mainz, Germany. The > project is based on our recent discovery of a long non-coding RNA > that coordinates sex determination in ants and will be conducted > under the supervision of Miya Qiaowei Pan, Hugo Darras, Claudia > Keller-Valsecchi and Ren� Ketting. Details of the project can be found > at: https://ift.tt/mfbACLu > > Only application submitted through the GenEvo recruitment procedure > will be considered. Please feel free to contact Miya Qiaowei Pan > (q.pan@imb-mainz.de) should you have any questions about the project or > the application procedures.  Deadline For application: 15th of July, 2024 > > > > "Pan, Qiaowei"

[thelovebudllc]

Review sheds light on the mechanistic role of long non-coding RNAs in liver disease

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease (NAFLD), is a global health challenge, affecting nearly 30% of adults worldwide. A significant subset of MASLD patients progresses to metabolic dysfunction-associated steatohepatitis (MASH), liver fibrosis, and even hepatocellular carcinoma (HCC), yet no universally approved…