Sharp Rise in Cosmic Ray Irradiation of Organisms on Earth Caused by a Nearby SN Shockwave Passage.

The work considers the modelling of nearby supernova (SN) effects on Earth's biosphere via cosmic rays (CRs) accelerated by shockwaves. The rise of the radiation background on Earth resulted from the external irradiation by CR high-energy particles and internal radiation in organisms by the decay of cosmogenic 14C is evaluated. We have taken into account that the CR flux near Earth goes up steeply when the shockwave crosses the Solar System, while in previous works the CR transport was considered as purely diffusive. Our simulations demonstrate a high rise of the external ionization of the environments at Earth's surface by atmospheric cascade particles that penetrate the first 70-100 m of water depth. Also, the cosmogenic 14C decay is able to irradiate the entire biosphere and deep ocean organisms. We analyzed the probable increase in mutation rate and estimated the distance between Earth and an SN, where the lethal effects of irradiation are possible. Our simulations demonstrate that for SN energy of around 1051 erg the lethal distance could be ∼18 pc.

Diffuse neutrino background from past core collapse supernovae.

Core collapse supernovae are among the most powerful explosions in the Universe, which emit thermal neutrinos that carry away most of the gravitational binding energy released. These neutrinos produce a diffuse supernova neutrino background (DSNB), which is one of the largest energy budgets among all radiation backgrounds. Detecting the DSNB is an important goal of modern high-energy astrophysics and particle physics, which provides valuable insights into core collapse modeling, neutrino physics, and cosmic supernova rate history. In this review, the key ingredients of DSNB calculation and what can be learned from future detections, including black hole formation and non-standard neutrino interactions are discussed. Moreover, an overview of the latest updates in neutrino experiments, which could lead to the detection of the DSNB in the next decade, is provided. With the promise of this breakthrough discovery on the horizon, the study of DSNB has great potential to further our understanding of the Universe.

Circumstellar material ejected violently by a massive star immediately before its death.

Type II supernovae represent the most common stellar explosions in the Universe, for which the final stage evolution of their hydrogen-rich massive progenitors towards core-collapse explosion are elusive. The recent explosion of SN 2023ixf in a very nearby galaxy, Messier 101, provides a rare opportunity to explore this longstanding issue. With the timely high-cadence flash spectra taken within 1-5 days after the explosion, we can put stringent constraints on the properties of the surrounding circumstellar material around this supernova. Based on the rapid fading of the narrow emission lines and luminosity/profile of Hα emission at very early times, we estimate that the progenitor of SN 2023ixf lost material at a mass-loss rate M≈6×10-4M⊙a-1 over the last 2-3 years before explosion. This close-by material, moving at a velocity vw≈55kms-1, accumulates a compact CSM shell at the radius smaller than 7×1014 cm from the progenitor. Given the high mass-loss rate and relatively large wind velocity presented here, together with the pre-explosion observations made about two decades ago, the progenitor of SN 2023ixf could be a short-lived yellow hypergiant that evolved from a red supergiant shortly before the explosion.

Golgi polarity shift instructs dendritic refinement in the neonatal cortex by mediating NMDA receptor signaling.

Dendritic refinement is a critical component of activity-dependent neuronal circuit maturation, through which individual neurons establish specific connectivity with their target axons. Here, we demonstrate that the developmental shift of Golgi polarity is a key process in dendritic refinement. During neonatal development, the Golgi apparatus in layer 4 spiny stellate (SS) neurons in the mouse barrel cortex lose their original apical positioning and acquire laterally polarized distributions. This lateral Golgi polarity, which is oriented toward the barrel center, peaks on postnatal days 5-7 (P5-P7) and disappears by P15, which aligns with the developmental time course of SS neuron dendritic refinement. Genetic ablation of N-methyl-D-aspartate (NMDA) receptors, key players in dendritic refinement, disturbs the lateral Golgi polarity. Golgi polarity manipulation disrupts the asymmetric dendritic projection pattern and the primary-whisker-specific response of SS neurons. Our results elucidate activity-dependent Golgi dynamics and their critical role in developmental neuronal circuit refinement.

Photodegradable by Yellow-Orange Light degFusionRed Optogenetic Module with Autocatalytically Formed Chromophore.

Optogenetic systems driven by yellow-orange light are required for the simultaneous regulation of several cellular processes. We have engineered the red fluorescent protein FusionRed into a 26 kDa monomeric optogenetic module, called degFusionRed. Unlike other fluorescent protein-based optogenetic domains, which exhibit light-induced self-inactivation by generating reactive oxygen species, degFusionRed undergoes proteasomal degradation upon illumination with 567 nm light. Similarly to the parent protein, degFusionRed has minimal absorbance at 450 nm and above 650 nm, making it spectrally compatible with blue and near-infrared-light-controlled optogenetic tools. The autocatalytically formed chromophore provides degFusionRed with an additional advantage over most optogenetic tools that require the binding of the exogenous chromophores, the amount of which varies in different cells. The degFusionRed efficiently performed in the engineered light-controlled transcription factor and in the targeted photodegradation of the protein of interest, demonstrating its versatility as the optogenetic module of choice for spectral multiplexed interrogation of various cellular processes.

A persistent influence of supernovae on biodiversity over the Phanerozoic.

It is an open question what has constrained macroevolutionary changes in marine animal diversity on the time scale of the Phanerozoic. Here, we will show that supernovae appear to have significantly influenced the biodiversity of life. After normalizing diversity curves of major animal marine genera by the changes in the area of shallow marine margins, a close correlation between supernovae frequency and biodiversity is obtained. The interpretation is that supernovae influence Earth's climate, which controls the ocean and atmospheric circulation of nutrients. With this, supernovae influence ocean bioproductivity and are speculated to affect genera-level diversity. The implication is a surprisingly influential role of stellar processes on evolution.

Development of Allogeneic Stem Cell-Based Platform for Delivery and Potentiation of Oncolytic Virotherapy.

We describe the repurposing and optimization of the TK-positive (thymidine kinase) vaccinia virus strain ACAM1000/ACAM2000™ as an oncolytic virus. This virus strain has been widely used as a smallpox vaccine and was also used safely in our recent clinical trial in patients with advanced solid tumors and Acute Myeloid Leukemia (AML). The vaccinia virus was amplified in CV1 cells and named CAL1. CAL1 induced remarkable oncolysis in various human and mouse cancer cells and preferentially amplified in cancer cells, supporting the use of this strain as an oncolytic virus. However, the therapeutic potential of CAL1, as demonstrated with other oncolytic viruses, is severely restricted by the patients' immune system. Thus, to develop a clinically relevant oncolytic virotherapy agent, we generated a new off-the-shelf therapeutic called Supernova1 (SNV1) by loading CAL1 virus into allogeneic adipose-derived mesenchymal stem cells (AD-MSC). Culturing the CAL1-infected stem cells allows the expression of virally encoded proteins and viral amplification prior to cryopreservation. We found that the CAL1 virus loaded into AD-MSC was resistant to humoral inactivation. Importantly, the virus-loaded stem cells (SNV1) released larger number of infectious viral particles and virally encoded proteins, leading to augmented therapeutic efficacy in vitro and in animal tumor models.

Pushing the Limits of Nucleic Acid Function.

For many decades it was thought that information storage and information transfer were the main functions of nucleic acids. However, artificial evolution experiments have shown that the functional potential of DNA and RNA is much greater. Here I provide an overview of this technique and highlight recent advances which have increased its potency. I also describe how artificial evolution has been used to identify nucleic acids with extreme functions. These include deoxyribozymes that generate unusual products such as light, tiny motifs made up of fewer than ten nucleotides, ribozymes that catalyze complex reactions such as RNA polymerization, information-rich sequences that encode overlapping ribozymes, motifs that catalyze reactions at rates too fast to be followed by manual pipetting, and functional nucleic acids which are active in extreme conditions. Such motifs highlight the limits of our knowledge and provide clues about as of yet undiscovered functions of DNA and RNA.

Detailed Imaging of Mitochondrial Transport and Precise Manipulation of Mitochondrial Function with Genetically Encoded Photosensitizers in Adult Drosophila Neurons.

Precise distribution of mitochondria is essential for maintaining neuronal homeostasis. Although detailed mechanisms governing the transport of mitochondria have emerged, it is still poorly understood how the regulation of transport is coordinated in space and time within the physiological context of an organism. How alteration in mitochondrial functionality may trigger changes in organellar dynamics also remains unclear in this context. Therefore, the use of genetically encoded tools to perturb mitochondrial functionality in real time would be desirable. Here we describe methods to interfere with mitochondrial function with high spatiotemporal precision with the use of photosensitizers in vivo in the intact wing nerve of adult Drosophila. We also provide details on how to visualize the transport of mitochondria and to improve the quality of the imaging to attain super-resolution in this tissue.

Optimizing the Chemiluminescence of a Light-Producing Deoxyribozyme.

Supernova is a chemiluminescent deoxyribozyme recently discovered in our group. It transfers the phosphate group from the 1,2-dioxetane substrate CDP-Star to its 5' hydroxyl group, which triggers a decomposition reaction and the production of light. Here we investigated the effects of reaction conditions on the ability of Supernova to generate a chemiluminescent signal (using a plate reader assay) and to phosphorylate itself (using a ligation assay). Our experiments indicate that multiple zinc ions are required for catalytic function, suggesting links between Supernova and protein enzymes that catalyze similar reactions. They also show how factors such as pH, potassium concentration, CDP-Star concentration, and DNA concentration affect the reaction. By combining information from different experiments, the rate enhancement of light production was increased by more than 1000-fold. These results should be useful for applications in which Supernova is used as a sensor.

De Novo Assembly of Linked Reads Using Supernova 2.0.

The recent emergence of "third-generation" sequencing platforms which address shortcomings of standard short reads has allowed the resolution of complex genomic regions during genome assembly. However, sequencing costs for third-generation platforms continue to be high. Novel approaches that leverage the low cost of short-read sequencing while capturing long-range information have been developed. In this chapter, we focus on one such approach, the 10x Genomics' Chromium system. We demonstrate the assembly of the B73 maize reference genome using the Supernova assembler. We also offer suggestions on how one might improve the resulting assembly through analysis of assembly metrics.

Inflammation as A Precursor of Atherothrombosis, Diabetes and Early Vascular Aging.

Vascular disease was for a long time considered a disease of the old age, but it is becoming increasingly clear that a cumulus of factors can cause early vascular aging (EVA). Inflammation plays a key role in vascular stiffening and also in other pathologies that induce vascular damage. There is a known and confirmed connection between inflammation and atherosclerosis. However, it has taken a long time to prove the beneficial effects of anti-inflammatory drugs on cardiovascular events. Diabetes can be both a product of inflammation and a cofactor implicated in the progression of vascular disease. When diabetes and inflammation are accompanied by obesity, this ominous trifecta leads to an increased incidence of atherothrombotic events. Research into earlier stages of vascular disease, and documentation of vulnerability to premature vascular disease, might be the key to success in preventing clinical events. Modulation of inflammation, combined with strict control of classical cardiovascular risk factors, seems to be the winning recipe. Identification of population subsets with a successful vascular aging (supernormal vascular aging-SUPERNOVA) pattern could also bring forth novel therapeutic interventions.

Bioinformation and Neutrino Communication.

Communications among civilizations may include self-descriptive bioinformation because pathogen dynamics exist in their astrobiology and astrovirology, which could become pathogenic upon actual contact. This information is of mutual benefit, if reciprocated. However, in contrast, the strategic counter-scenario of self-hidden civilizations is also discussed. Civilizations, including extra-terrestrial civilizations have been divided and stratified into three levels, using a wide non-linear logarithmic scale. The levels are based on their energy expenditures: level 1 is at 4x10^19 erg/sec; level 2 is at 4x10^33 erg/sec; and level 3 is at 4x10^44 erg/sec. Terrestrial civilization is currently below the entry level I. Particularly advanced civilizations, which are above the highest level, may engineer interstellar travel and could move their planets across interstellar distances. Communication among civilizations has always been of keen interest. In terms of ability to communicate among advanced civilizations, neutrinos may be used for galactic and inter-galactic communication, in addition to or instead of using electromagnetic radiation. Thus, at this juncture, deliberation and debate are essential to proceed with development of civilization and communication.

Recent advancements in CRISPR-Cas toolbox for imaging applications.

The imaging of chromatin, genomic loci, RNAs, and proteins is very important to study their localization, interaction, and coordinated regulation. Recently, several clustered regularly interspaced short palindromic repeats (CRISPR) based imaging methods have been established. The refurbished tool kits utilizing deactivated Cas9 (dCas9) and dCas13 have been established to develop applications of CRISPR-Cas technology beyond genome editing. Here, we review recent advancements in CRISPR-based methods that enable efficient imaging and visualization of chromatin, genomic loci, RNAs, and proteins. RNA aptamers, Pumilio, SuperNova tagging system, molecular beacons, halotag, bimolecular fluorescence complementation, RNA-guided endonuclease in situ labeling, and oligonucleotide-based imaging methods utilizing fluorescent proteins, organic dyes, or quantum dots have been developed to achieve improved fluorescence and signal-to-noise ratio for the imaging of chromatin or genomic loci. RNA-guided RNA targeting CRISPR systems (CRISPR/dCas13) and gene knock-in strategies based on CRISPR/Cas9 mediated site-specific cleavage and DNA repair mechanisms have been employed for efficient RNA and protein imaging, respectively. A few CRISPR-Cas-based methods to investigate the coordinated regulation of DNA-protein, DNA-RNA, or RNA-protein interactions for understanding chromatin dynamics, transcription, and protein function are also available. Overall, the CRISPR-based methods offer a significant improvement in elucidating chromatin organization and dynamics, RNA visualization, and protein imaging. The current and future advancements in CRISPR-based imaging techniques can revolutionize genome biology research for various applications.

Revealing a peculiar supernova remnant G106.3+2.7 as a petaelectronvolt proton accelerator with X-ray observations.

Supernova remnants (SNRs) have long been considered as one of the most promising sources of Galactic cosmic rays. In the SNR paradigm, petaelectronvolt (PeV) proton acceleration may only be feasible at the early evolution stage, lasting a few hundred years, when the SNR shock speed is high. While evidence supporting the acceleration of PeV protons in young SNRs has yet to be discovered, X-ray synchrotron emission is an important indicator of fast shock. Here, we report the first discovery of X-ray synchrotron emission from the possibly middle-aged SNR G106.3+2.7, implying that this SNR is still an energetic particle accelerator despite its age. This discovery, along with the ambient environmental information, multiwavelength observation, and theoretical arguments, supports SNR G106.3+2.7 as a likely powerful proton PeV accelerator.

Supernovae Detection with Fully Convolutional One-Stage Framework.

A series of sky surveys were launched in search of supernovae and generated a tremendous amount of data, which pushed astronomy into a new era of big data. However, it can be a disastrous burden to manually identify and report supernovae, because such data have huge quantity and sparse positives. While the traditional machine learning methods can be used to deal with such data, deep learning methods such as Convolutional Neural Networks demonstrate more powerful adaptability in this area. However, most data in the existing works are either simulated or without generality. How do the state-of-the-art object detection algorithms work on real supernova data is largely unknown, which greatly hinders the development of this field. Furthermore, the existing works of supernovae classification usually assume the input images are properly cropped with a single candidate located in the center, which is not true for our dataset. Besides, the performance of existing detection algorithms can still be improved for the supernovae detection task. To address these problems, we collected and organized all the known objectives of the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) and the Popular Supernova Project (PSP), resulting in two datasets, and then compared several detection algorithms on them. After that, the selected Fully Convolutional One-Stage (FCOS) method is used as the baseline and further improved with data augmentation, attention mechanism, and small object detection technique. Extensive experiments demonstrate the great performance enhancement of our detection algorithm with the new datasets.

Electron capture in stars.

Electron capture on nuclei plays an essential role in the dynamics of several astrophysical objects, including core-collapse and thermonuclear supernovae, the crust of accreting neutron stars in binary systems and the final core evolution of intermediate-mass stars. In these astrophysical objects, the capture occurs at finite temperatures and densities, at which the electrons form a degenerate relativistic electron gas. The capture rates can be derived from perturbation theory, where allowed nuclear transitions [Gamow-Teller (GT) transitions] dominate, except at the higher temperatures achieved in core-collapse supernovae, where forbidden transitions also contribute significantly to the capture rates. There has been decisive progress in recent years in measuring GT strength distributions using novel experimental techniques based on charge-exchange reactions. These measurements not only provide data for the GT distributions of ground states for many relevant nuclei, but also serve as valuable constraints for nuclear models which are needed to derive the capture rates for the many nuclei for which no data yet exist. In particular, models are needed to evaluate stellar capture rates at finite temperatures, where capture can also occur on nuclei in thermally excited states. There has also been significant progress in recent years in the modeling of stellar capture rates. This has been made possible by advances in nuclear many-body models as well as in computer soft- and hardware. Specifically, to derive reliable capture rates for core-collapse supernovae, a dedicated strategy has been developed based on a hierarchy of nuclear models specifically adapted to the abundant nuclei and astrophysical conditions present under various collapse conditions. In particular, for the challenging conditions where the electron chemical potential and the nuclearQvalues are of the same order, large-scale shell-model diagonalization calculations have proved to be an appropriate tool to derive stellar capture rates, often validated by experimental data. Such situations are relevant in the early stage of the core collapse of massive stars, for the nucleosynthesis of thermonuclear supernovae, and for the final evolution of the cores of intermediate-mass stars involving nuclei in the mass rangeA∼ 20-65. This manuscript reviews the experimental and theoretical progress recently achieved in deriving stellar electron capture rates. It also discusses the impact these improved rates have on our understanding of the various astrophysical objects.

Gravitational-Wave Burst Signals Denoising Based on the Adaptive Modification of the Intersection of Confidence Intervals Rule.

Gravitational-wave data (discovered first in 2015 by the Advanced LIGO interferometers and awarded by the Nobel Prize in 2017) are characterized by non-Gaussian and non-stationary noise. The ever-increasing amount of acquired data requires the development of efficient denoising algorithms that will enable the detection of gravitational-wave events embedded in low signal-to-noise-ratio (SNR) environments. In this paper, an algorithm based on the local polynomial approximation (LPA) combined with the relative intersection of confidence intervals (RICI) rule for the filter support selection is proposed to denoise the gravitational-wave burst signals from core collapse supernovae. The LPA-RICI denoising method's performance is tested on three different burst signals, numerically generated and injected into the real-life noise data collected by the Advanced LIGO detector. The analysis of the experimental results obtained by several case studies (conducted at different signal source distances corresponding to the different SNR values) indicates that the LPA-RICI method efficiently removes the noise and simultaneously preserves the morphology of the gravitational-wave burst signals. The technique offers reliable denoising performance even at the very low SNR values. Moreover, the analysis shows that the LPA-RICI method outperforms the approach combining LPA and the original intersection of confidence intervals (ICI) rule, total-variation (TV) based method, the method based on the neighboring thresholding in the short-time Fourier transform (STFT) domain, and three wavelet-based denoising techniques by increasing the improvement in the SNR by up to 118.94% and the peak SNR by up to 138.52%, as well as by reducing the root mean squared error by up to 64.59%, the mean absolute error by up to 55.60%, and the maximum absolute error by up to 84.79%.

Proper motion, spectra, and timing of PSR J1813-1749 using Chandra and NICER.

PSR J1813-1749 is one of the most energetic rotation-powered pulsars known, producing a pulsar wind nebula (PWN) and gamma-ray and TeV emission, but whose spin period is only measurable in X-ray. We present analysis of two Chandra datasets that are separated by more than ten years and recent NICER data. The long baseline of the Chandra data allows us to derive a pulsar proper motion µ R.A. = - ( 0 . ″ 067 ± 0 . ″ 010 ) yr-1 and µ decl. = - ( 0 . ″ 014 ± 0 . ″ 007 ) yr-1 and velocity v ⊥ ≈ 900-1600 km s-1 (assuming a distance d = 3 - 5 kpc), although we cannot exclude a contribution to the change in measured pulsar position due to a change in brightness structure of the PWN very near the pulsar. We model the PWN and pulsar spectra using an absorbed power law and obtain best-fit absorption N H = (13.1 ± 0.9) × 1022 cm-2, photon index Γ = 1.5 ± 0.1, and 0.3-10 keV luminosity L X ≈ 5.4 × 1034 erg s-1(d/ 5 kpc)2 for the PWN and Γ = 1.2 ± 0.1 and L X « 9.3 × 1033 erg s-1(d/ 5 kpc)2 for PSR J1813-1749. These values do not change between the 2006 and 2016 observations. We use NICER observations from 2019 to obtain a timing model of PSR J1813-1749, with spin frequency ν = 22.35 Hz and spin frequency time derivative v . = ( - 6.428 ± 0.003 ) × 10 - 11 Hz s-1. We also fit ν measurements from 2009-2012 and our 2019 value and find a long-term spin-down rate v . = ( - 6.3445 ± 0.0004 ) × 10 - 11 Hz s-1. We speculate that the difference in spin-down rates is due to glitch activity or emission mode switching.

Genetically Encoded Red Photosensitizers with Enhanced Phototoxicity.

Genetically encoded photosensitizers are increasingly used as optogenetic tools to control cell fate or trigger intracellular processes. A monomeric red fluorescent protein called SuperNova has been recently developed, however, it demonstrates suboptimal characteristics in most phototoxicity-based applications. Here, we applied directed evolution to this protein and identified SuperNova2, a protein with S10R substitution that results in enhanced brightness, chromophore maturation and phototoxicity in bacterial and mammalian cell cultures.