This is the first lesson that will eventually lead to Grover’s Algorithm and Rotation (Phase) Estimation. We talk about the task of distinguishing between two qubit states, with \.
Over the recent decades, comprehensive genome-wide association studies (GWAS) have indicated the potential influence of genetic factors on one’s alcohol consumption volume and identified over 100 related variants6,7. However, a predominant proportion of the identified variants are localized within noncoding regions, and their effect sizes tend to be small, making interpretation and identification of the causal gene challenging8. In addition, previous GWAS mainly utilized imputed genotype data, which only cover limited regions of the genome, and thus may have missed many potential genes. Furthermore, GWAS studies focused mainly on common variants, and few studies have investigated rare variants associated with alcohol consumption, which yield greater potential to interpret biological function and elucidate mechanisms9. Although there are studies that have attempted to leverage exome chip data to identify rare variants contributing to alcohol consumption, the sample size was small and limited regions of the whole exome were examined10.
The introduction of whole exome sequencing (WES) provides a great chance to overcome the limitations of previous genetic studies on alcohol consumption with a substantially larger amount of rare and ultra-rare protein-coding variants11,12,13. Collapsing of loss-of-function (LOF) variants helps estimate the effect direction of associated genes13,14. When combined with large-scale population cohorts with multi-modal phenotypic data, WES would greatly facilitate our understanding of the genetic underpinnings of alcohol consumption as well as its implication on physical and mental health6. However, to our knowledge, there have been few large-scale WES studies on alcohol consumption, let alone elucidating the potential implications of the identified genes10,15. Meanwhile, as indicated by a previous genome-wide association study, significant genetic associations existed between alcohol consumption and several body health phenotypes7. The application of phenome-wide analysis for alcohol-related genes can help extend and deepen our current comprehension of the association between alcohol consumption and human health.
Hence, aiming to refine the genetic architecture of alcohol consumption, we conduct an exome-wide association study (ExWAS) for alcohol consumption among 304,119 individuals from the UK Biobank (UKB). We also examine the rare-variant associations with genes reported by previous GWAS6,7,16,17. Finally, we provide biological insights into the identified genes via bioinformatics analyses and phenome-wide association analysis (PheWAS).
Gallium nitride (GaN)-based light-emitting diodes (LEDs) have transformed the lighting industry by replacing conventional lighting technologies with superior energy efficiency, longer operating life and greater environmental sustainability.
In recent years, considerable attention has been paid to the trend toward miniaturization of LEDs, driven by display devices, augmented reality, virtual reality, and other emerging technologies. Due to the lack of cost-effective native substrates, the presence of high threading dislocation density in heteroepitaxial films grown on sapphire substrate is a major limiting factor for device performance.
In addition, Fresnel reflections at the interface between epitaxy and substrate caused by abrupt changes in the refractive indices of the material reduce the light energy utilization.
This Perspective explores the potential of organic electrochemical neurons, which are based on organic electrochemical transistors, in the development of adaptable and biointegrable neuromorphic event-based sensing applications.
Eexxeccellent.
Human brains outperform computers in many forms of processing and are far more energy efficient. What if we could harness their power in a new form of biological computing?
In multicellular organisms, many biological pathways exhibit a curious structure, involving sets of protein variants that bind or interact with one another in a many-to-many fashion. What functions do these seemingly complicated architectures provide? And can similar architectures be useful in synthetic biology? Here, Dr. Elowitz discusses recent work in his lab that shows how many-to-many circuits can function as versatile computational devices, explore the roles these computations play in natural biological contexts, and show how many-to-many architectures can be used to design synthetic multicellular behaviors.
About Michael Elowitz.
Michael Elowitz is a Howard Hughes Medical Institute Investigator and Roscoe Gilkey Dickinson Professor of Biology and Biological Engineering at Caltech. Dr. Elowitz’s laboratory has introduced synthetic biology approaches to build and understand genetic circuits in living cells and tissues. As a graduate student with Stanislas Leibler, Elowitz developed the Repressilator, an artificial genetic clock that generates gene expression oscillations in individual E. coli cells. Since then, his lab has continued to design and build synthetic genetic circuits, bringing a “build to understand” approach to bacteria, yeast, and mammalian cells. He and his group have shown that gene expression is intrinsically stochastic, or ‘noisy’, and revealed how noise functions to enable probabilistic differentiation, time-based regulation, and other functions. Currently, Elowitz’s lab is bringing synthetic approaches to understand and program multicellular functions including multistability, cell-cell communication, epigenetic memory, and cell fate control, and to provide foundations for using biological circuits as therapeutic devices. His lab also co-develops systems such as “MEMOIR” that allows cells to record their own lineage histories and tools for RNA export, and precise gene expression. Elowitz received his PhD in Physics from Princeton University and did postdoctoral research at Rockefeller University. Honors include the HFSP Nakasone Award, MacArthur Fellowship, Presidential Early Career Award, Allen Distinguished Investigator Award, the American Academy of Arts and Sciences, and election to the National Academy of Sciences.
Explore the leading quantum computing companies that are shaping the future of technology. Learn what projects are worth your attention.
Fab 29.1 and Fab 29.2 will span roughly 81,000 square meters, with a combined length of 530 meters and a width of 153 meters. Including roof structures for air conditioning and heating, the buildings will reach a height of 36.7 meters, with several underground floors as well. The cross-section plans show multiple above-ground floors with heights ranging from 5.7 to 6.5 meters.
Initially, construction of Intel’s Fab 29 was scheduled to begin in the first half of 2023, but delays in subsidy approvals pushed the start to the summer of 2024. Recently it turned out that construction of Intel’s Fab 29 modules 1 and 2 near Magdeburg, Germany, has been delayed to May 2025 due to the pending approval of EU subsidies and the requirement to relocate black soil for reuse at another site.
Intel’s Fab 29 modules 1 and 2 were initially scheduled to start operations in late 2027 and make chips on Intel’s 14A (1.4nm) and 10A (1nm) production nodes. Typically, Intel launches new client PC products in the second half of the year and ramps up production in the first half. The fabs were intended to produce client PC products set for release in the second half of 2028. Although production could begin if the fabs were ready by mid-2028, the timeline would be tight. However, some of the latest reports indicate a different schedule, estimating four to five years for construction, with production now expected to start between 2029 and 2030.
The power of quantum computing drives a desperate need for quantum encryption. This megatrend is creating a multi-billion-dollar security market.
