Brain study probes molecular origins of anxiety

CATHARINE PADDOCK | August 19, 2019 | 3 views

Scientists have found that increasing the levels of a molecule in a particular part of the brain can reduce anxious temperament in young monkeys. The finding sheds light on the origins of anxiety disorders and how it might be possible to devise early treatments for those at risk.

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Advancement in Genomics Accelerating its Penetration into Precision Health

Article | April 13, 2020

Genomics is an interdisciplinary field of biology emphasizing the structure, editing, evolution, function, and mapping of genomes. It is creating deeper inroads across the precision health domain with the increasing introduction of advanced technologies such as quantum simulation, next-generation sequencing (NGS), and precise genome manipulation. As precision health focuses on providing the proper intervention to the right patient at the right time, genomics increasingly finds applications in human and pathogen genome sequencing in clinical and research spaces. Rising Hereditary Diseases Burden Paving the Way for Genomics in Precision Health In the last few years, a significant surge in the prevalence of diseases and ailments such as diabetes, obesity, baldness, and others has been witnessed across the globe. A history of family members with chronic diseases, such as cancer, diabetes, high blood pressure, hearing issues, and heart disease, can sometimes continue into the next generation. Hence, the study of genes is extensively being conducted for predicting health risks and early treatment of these diseases. It also finds use in CRISPR-based diagnostics and the preparation of precision medication for the individual. In addition, ongoing advancements in genomics are making it possible to identify different genetic traits that persuade people to more widespread diseases and health problems. The Emergence of Genomics Improves Disease Understanding Genomics refers to the study of the complete genetic makeup of a cell or organism. Increasing scientific research in the area substantially contributes to increasing knowledge about the human genome and assists in improving the ability to understand disease etiology, risk, diagnosis, treatment, and prevention. On account of these improvements, innovative genomic technologies and tools are being developed to enable better precision health not only for the individual but for various regional populations as well. The Way Forward With growing preference for personalized medicine and an increasing need for more accurate pathogen detection and diagnostics, genomics is gaining huge popularity across the precision health domain. Also, increasing research activities for developing novel high-precision therapeutics and rising importance of gene study in the prevention, diagnosis, and management of infectious and genetic diseases will further pave the way for genomics in the forthcoming years.

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Top 10 biotech IPOs in 2019

Article | April 17, 2020

The big question at the start of 2019 was whether the IPO window would stay open for biotech companies, particularly those seeking to pull off ever-larger IPOs at increasingly earlier stages of development. The short answer is yes—kind of. Here’s the long answer: In the words of Renaissance Capital, the IPO market had “a mostly good year.” The total number of deals fell to 159 from 192 the year before, but technology and healthcare companies were standout performers. The latter—which include biotech, medtech and diagnostics companies—led the pack, making up 43% of all IPOs in 2019. By Renaissance’s count, seven companies went public at valuations exceeding $1 billion, up from five the year before

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MEDICAL

Cell Out? Lysate-Based Expression an Option for Personalized Meds

Article | June 22, 2022

Cell-free expression (CFE) is the practice of making a protein without using a living cell. In contrast with cell line-based methods, production is achieved using a fluid containing biological components extracted from a cell, i.e., a lysate. CFE offers potential advantages for biopharma according to Philip Probert, PhD, a senior scientist at the Centre for Process Innovation in the U.K.

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Closing bacterial genomes from the human gut microbiome using long-read sequencing

Article | February 12, 2020

In our lab, we focus on the impact of the gut microbiome on human health and disease. To evaluate this relationship, it’s important to understand the particular functions that different bacteria have. As bacteria are able to exchange, duplicate, and rearrange their genes in ways that directly affect their phenotypes, complete bacterial genomes assembled directly from human samples are essential to understand the strain variation and potential functions of the bacteria we host. Advances in the microbiome space have allowed for the de novo assembly of microbial genomes directly from metagenomes via short-read sequencing, assembly of reads into contigs, and binning of contigs into putative genome drafts. This is advantageous because it allows us to discover microbes without culturing them, directly from human samples and without reference databases. In the past year, there have been a number of tour de force efforts to broadly characterize the human gut microbiota through the creation of such metagenome-assembled genomes (MAGs)[1–4]. These works have produced hundreds of thousands of microbial genomes that vastly increase our understanding of the human gut. However, challenges in the assembly of short reads has limited our ability to correctly assemble repeated genomic elements and place them into genomic context. Thus, existing MAGs are often fragmented and do not include mobile genetic elements, 16S rRNA sequences, and other elements that are repeated or have high identity within and across bacterial genomes.

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Life Sciences Search Group provides specialised national recruitment services for global pharmaceutical, biotechnology and medical device innovators.

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Newly-discovered protein could play key role in fighting obesity

Drug Target Review | November 21, 2019

Scientists at Scripps Research, US have opened the door to critical new understandings about obesity and metabolism with an unexpected finding about a protein that is highly expressed in fat tissue. This discovery, the scientists say, could lead to new approaches for addressing obesity and potentially many other diseases. The signalling protein known as progesterone receptor membrane component 2 (PGRMC2) had previously been detected in the uterus, liver and several areas of the body. But the lab of Enrique Saez, PhD, saw that it was most abundant in fat tissue, particularly in brown fat, which turns food into heat to maintain body temperature. The team built on their discovery, finding that PGRMC2 binds to and releases an essential molecule called heme, which travels within cells to enable crucial life processes such as cellular respiration, cell proliferation, cell death and circadian rhythms. Saez and his team found that PGRMC2 is a ‘chaperone’ of heme, encapsulating the molecule and transporting it from the cell’s mitochondria, where heme is created, to the nucleus, where it helps carry out important functions. Without a protective chaperone, heme would react with and destroy everything in its path.

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AI Algorithm To Speed Up Drug Molecule Design

Technology Networks | November 20, 2019

Artificial Intelligence can be used to predict molecular wave functions and the electronic properties of molecules. This innovative AI method developed by a team of researchers at the University of Warwick, the Technical University of Berlin and the University of Luxembourg, could be used to speed-up the design of drug molecules or new materials. Artificial Intelligence and machine learning algorithms are routinely used to predict our purchasing behaviour and to recognise our faces or handwriting. In scientific research, Artificial Intelligence is establishing itself as a crucial tool for scientific discovery. In Chemistry AI has become instrumental in predicting the outcomes of experiments or simulations of quantum systems. To achieve this, AI needs to be able to systematically incorporate the fundamental laws of physics. An interdisciplinary team of chemists, physicists, and computer scientists led by the University of Warwick, and including the Technical University of Berlin, and the University of Luxembourg have developed a deep machine learning algorithm that can predict the quantum states of molecules, so-called wave functions, which determine all properties of molecules.

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Regeneration mechanism could provide target for liver disease drugs

Drug Target Review | November 06, 2019

A newly-discovered molecular mechanism that allows damaged adult liver cells to regenerate could pave the way for drugs for chronic liver diseases. A molecular mechanism that allows damaged adult liver cells to regenerate has been discovered and could pave the way for drugs to treat conditions such as cirrhosis or other chronic liver diseases where regeneration is impaired. The researchers used mice and liver organoids (‘mini-livers’ generated in the lab from mouse liver cells) to study adult liver regeneration. They discovered that a molecule called TET1 is produced in healthy adult liver cells during the first steps of regeneration, and that this process is mimicked in liver organoids, where it has a role in stimulating organoid growth. “We now understand how adult liver cells respond to the changes caused by tissue injury,” said Dr Luigi Aloia, first author of the paper and postdoctoral researcher at the Gurdon Institute “This paves the way for exciting future work to boost cell regeneration in chronic liver disease, or in other organs where regeneration is minimal such as the brain or pancreas.”

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Newly-discovered protein could play key role in fighting obesity

Drug Target Review | November 21, 2019

Scientists at Scripps Research, US have opened the door to critical new understandings about obesity and metabolism with an unexpected finding about a protein that is highly expressed in fat tissue. This discovery, the scientists say, could lead to new approaches for addressing obesity and potentially many other diseases. The signalling protein known as progesterone receptor membrane component 2 (PGRMC2) had previously been detected in the uterus, liver and several areas of the body. But the lab of Enrique Saez, PhD, saw that it was most abundant in fat tissue, particularly in brown fat, which turns food into heat to maintain body temperature. The team built on their discovery, finding that PGRMC2 binds to and releases an essential molecule called heme, which travels within cells to enable crucial life processes such as cellular respiration, cell proliferation, cell death and circadian rhythms. Saez and his team found that PGRMC2 is a ‘chaperone’ of heme, encapsulating the molecule and transporting it from the cell’s mitochondria, where heme is created, to the nucleus, where it helps carry out important functions. Without a protective chaperone, heme would react with and destroy everything in its path.

Read More

AI Algorithm To Speed Up Drug Molecule Design

Technology Networks | November 20, 2019

Artificial Intelligence can be used to predict molecular wave functions and the electronic properties of molecules. This innovative AI method developed by a team of researchers at the University of Warwick, the Technical University of Berlin and the University of Luxembourg, could be used to speed-up the design of drug molecules or new materials. Artificial Intelligence and machine learning algorithms are routinely used to predict our purchasing behaviour and to recognise our faces or handwriting. In scientific research, Artificial Intelligence is establishing itself as a crucial tool for scientific discovery. In Chemistry AI has become instrumental in predicting the outcomes of experiments or simulations of quantum systems. To achieve this, AI needs to be able to systematically incorporate the fundamental laws of physics. An interdisciplinary team of chemists, physicists, and computer scientists led by the University of Warwick, and including the Technical University of Berlin, and the University of Luxembourg have developed a deep machine learning algorithm that can predict the quantum states of molecules, so-called wave functions, which determine all properties of molecules.

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Regeneration mechanism could provide target for liver disease drugs

Drug Target Review | November 06, 2019

A newly-discovered molecular mechanism that allows damaged adult liver cells to regenerate could pave the way for drugs for chronic liver diseases. A molecular mechanism that allows damaged adult liver cells to regenerate has been discovered and could pave the way for drugs to treat conditions such as cirrhosis or other chronic liver diseases where regeneration is impaired. The researchers used mice and liver organoids (‘mini-livers’ generated in the lab from mouse liver cells) to study adult liver regeneration. They discovered that a molecule called TET1 is produced in healthy adult liver cells during the first steps of regeneration, and that this process is mimicked in liver organoids, where it has a role in stimulating organoid growth. “We now understand how adult liver cells respond to the changes caused by tissue injury,” said Dr Luigi Aloia, first author of the paper and postdoctoral researcher at the Gurdon Institute “This paves the way for exciting future work to boost cell regeneration in chronic liver disease, or in other organs where regeneration is minimal such as the brain or pancreas.”

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