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An ultramassive white dwarf half Earth’s size may hold a rare oxygen-neon core

Astronomers have found evidence that one of the most massive white dwarfs known has an oxygen-neon core instead of the more common carbon-oxygen core. The finding is important because the composition of a white dwarf’s core determines how it will evolve. A paper outlining this discovery was published in The Astrophysical Journal.

Typically, white dwarfs have a mass of 0.5–0.7 times the sun’s mass. Such objects have a core made up mainly of carbon and oxygen (C/O core). When they have stellar companions, these dense objects can accumulate matter from them and eventually produce a Type Ia supernova. Ultramassive white dwarfs, with masses above roughly 1.05–1.1 times the sun’s mass, tell a different story that is not yet fully understood.

These more massive white dwarfs are thought to form from “ancestor” or progenitor stars in the range of about 8–10 times the sun’s mass. In these heavier progenitors, the core reaches higher temperatures and densities, allowing carbon to ignite and fuse further into oxygen and neon (O/Ne core). This does not happen in the cores of lower-mass stars, which stop fusing once they have built up carbon and oxygen, lacking the required core temperatures.

Scientists Find Two New Ways To Break Down “Forever Chemicals” in Water

An HZDR research team has developed methods for breaking down “forever chemicals.”

The carbon-fluorine bonds inside PFAS are among the strongest in chemistry, allowing these industrial pollutants to persist in water for years. Researchers at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) are testing two ways to break those bonds: hydrodynamic cavitation and cold atmospheric plasma combined with gas dispersion.

Analyses by experts at the Helmholtz Centre for Environmental Research (UFZ) confirmed that both processes degraded per-and polyfluoroalkyl substances (PFAS) and released fluoride. If developed into practical industrial systems, the methods could help limit the amount of these highly persistent chemicals entering rivers, lakes and oceans.

HypoxiaInduced Epas1Myl9/12 Axis Shapes the Pathology of Pulmonary Hypertension

BACKGROUND: Pulmonary hypertension (PH) is a progressive cardiopulmonary disorder characterized by vascular remodeling, abnormal vasoconstriction of small lung arteries, and right heart failure. Hypoxia causes vascular damage, leading to vessel stenosis or occlusion by aberrant endothelial cells, hypertrophy of the tunica media, and thrombus formation. But the precise molecular mechanisms underlying the pathology of PH have been uncertain. METHODS: To investigate the pathogenic role of Myl (myosin light chain) 9/12 in PH, we utilized the Sugen/hypoxia mouse model, generated by administration of the VEGF (vascular endothelial growth factor) receptor inhibitor SU5416 under hypoxic conditions (10% O2). Lung tissues of patients with PH and human lung microvascular endothelial cells were used to examine their endothelial changes.

Comparative Cardiovascular Outcomes of Tirzepatide and Glucagon‐Like Peptide‐1 Receptor Agonists in Patients With Type 2 Diabetes and Atherosclerotic Cardiovascular Disease

BackgroundTo evaluate the association between tirzepatide use and 1‐year risk of major adverse cardiovascular events in patients with type 2 diabetes and atherosclerotic cardiovascular disease, compared with GLP‐1 (glucagon‐like peptide‐1) receptor agonists.

SingleCell Studies Advance Understanding of the Genetic and Molecular Basis of Atherosclerosis

Foundational models pretrained on millions of single cells (Geneformer, scGPT, and scBERT) now provide transferable embeddings that can help improve and automate cellular annotation, integration, cross-species mapping, and zero-shot predictions.49–51 While there has been considerable contribution to pretraining with immune and tumor data sets, other cell type–specific data for vascular resident parenchymal cells remain sparse, and the applications in atherosclerosis are still emerging. Therefore, overreliance on early foundational models may lead to mislabeling atherosclerosis-specific subtypes and rare cell states, and this area is still being actively investigated with improved consensus in cell types, such as vascular cells (SMC), forthcoming. While promising, we anticipate that these tools will improve with further fine-tuning and robust vascular tissue validation, and interpreted with pathway and genetics-based constraints. Currently, with more modest-sized vascular disease single-cell data sets available, probabilistic variational autoencoder–based methods, such as scVI, MultiVI, and GLUE,44,45,52 offer a good tradeoff between robustness, interpretability, and analytical efficiency. Another exciting area of research is expanding through the development and application of in silico perturbations. While TF perturbation using tools such as CellOracle has provided a first step, improved regulatory network predictions have long been pursued but are still in early stages of implementation.53,54

Deep learning approaches to study TF-DNA interactions are now being utilized to advance our understanding of the DNA regulatory grammar.55 Beyond simple chromatin syntax predictions, deep learning models can provide functional insights, affinity predictions for TF cooperativity, link allelic variation, and chromatin accessibility to cellular epigenetic and transcriptional functions (see below).56 Implementation of a deep learning approach has dramatically extended the capability of scATAC-seq to identify at single basepair resolution the TF motifs that are functional in a cell-specific context to modulate chromatin accessibility, TF binding, and gene expression (Figure 2). Furthermore, allelic variants that are identified with this method are highly enriched among those associated with the complex human traits and diseases that are being investigated. ChromBPNet is a fully convolutional neural network that uncovers the genomic grammar at dynamic enhancers in loci of interest.

Optimized magnetic pulses could cut memory switching energy by several orders of magnitude

Information and communication technologies (ICTs) driven by artificial intelligence (AI) are generating data at an unprecedented rate. Every internet search, AI-generated image, recommendation, scientific simulation and large language model creates and processes enormous amounts of information that must be stored, transferred and analyzed. As AI continues to expand across every sector of society, global demand for data storage and computing is rising dramatically.

This rapid growth comes at a significant cost: energy consumption. Data centers already consume vast amounts of electricity, and demand is expected to increase sharply over the coming decades. Without major technological advances, ICTs could account for a substantial fraction of global electricity use and carbon emissions, making energy-efficient computing one of the defining scientific challenges of our time.

Quantum Heat Waves Spotted at Room Temperature for the First Time

The discovery could improve thermal management in electronics and support advances in quantum and next-generation computing technologies.

Heat usually spreads outward through a solid, making it difficult to control once it begins moving. Until now, a wavelike form of heat transport called phonon focusing had been observed only at extremely low, or cryogenic, temperatures, sharply limiting its study and possible applications.

Researchers at the UCLA Samueli School of Engineering have now shown that phonons, quantum vibrations that carry heat through a material, can travel along concentrated, ray-like paths at room temperature. Rather than dispersing evenly in every direction, the heat followed routes determined by the underlying crystal structure, suggesting a new way to direct thermal energy in future electronics and quantum technologies.

Similar Response Dynamics Represent Opposite Behaviors and Rewards in the Frontal Cortex

The frontal cortex (FC) has been implicated in many of the cognitive and executive control functions required for goal-directed behavior (Komura et al., 2001; Bruni et al., 2015; Duan et al., 2021; Friedman and Robbins, 2021), including decision-making (Coley et al., 2021; Liu et al., 2021), response inhibition (Schiller et al., 2014; Li et al., 2020), working memory (O’Reilly and Frank, 2006; Miller et al., 2018; Wilhelm et al., 2023), attentional control (Zikopoulos and Barbas, 2007; Gregorlou et al., 2014), and adaptive modulation of sensory filters (Banerjee et al., 2020). In the auditory system, cortical neurons can rapidly adapt their receptive field tuning and spectrotemporal selectivity reflecting changing stimulus context and task conditions (Fritz et al., 2003, 2005, 2007; David et al., 2012; Yin et al., 2014; Elgueda et al., 2019). This task-related receptive field plasticity may be shaped by changing functional connectivity between FC and auditory cortex (Fritz et al., 2010; Sheikhattar et al., 2018; Yin et al., 2020). This adaptive capacity is critical since context can transform the behavioral meaning of incoming stimuli and even cause the same sound to mean two opposite things in different circumstances.

In this study, we explored the role of the FC in this adaptive decision-making process by employing the same sounds to signify diametrically opposite meanings depending on task context and reward valence. In one behavioral paradigm, upon hearing a Target sound, animals initiated licking to obtain a water reward (positive reward; P-paradigm). In the other paradigm, animals learned to stop licking for water when presented with the same Target stimulus in order to avoid a mild shock (negative reward; N-paradigm). In an earlier study (David et al., 2012), we found that such different task reward structures and stimulus-action contingencies induced two strikingly distinct forms of receptive field plasticity in primary auditory cortex (A1). In light of the strong top-down projections from the FC to auditory cortex (AC) influencing dynamic sensory filters (Caras and Sanes, 2017; Bimbard et al., 2018; Schneider et al., 2018; Winkowski et al., 2018; Mittelstadt and Kanold, 2023; Macedo-Lima et al., 2024), we wondered whether the differential receptive plasticity was driven by distinct FC representations of the two opposite behavioral paradigms.

Therefore, we trained two groups of ferrets on two opposite auditory categorical Go-NoGo paradigms, requiring each group to discriminate noncompact sound categories (Yin et al., 2016, 2020). Task stimuli varied along two acoustic feature dimensions: spectral frequency (TN-task) or temporal modulation rate (amplitude-modulated white noise, AM-task). As indicated above, in the P-paradigm group, ferrets learned to lick for water reward when Target stimuli were presented and refrained from licking to Reference stimuli. In contrast, the group that learned the N-paradigm performed the opposite behavior and refrained from licking for water when Target stimuli were presented but could lick freely to Reference sounds (Fig. 1 A).

Google’s Westinghouse Bet

In the article “Google’s Westinghouse Bet” published on Asimov’s Addendum, Tim O’Reilly presents an alternate thesis regarding the organizational shifts, talent departures, and strategic shakeups at Google DeepMind.

While industry reports (such as a analysis by SemiAnalysis) interpreted the DeepMind restructuring as evidence that Google is falling behind in the “frontier model race” against rivals like OpenAI and Anthropic, O’Reilly argues that Google is not losing the race—it is choosing to run a different one.


SemiAnalysis thinks the DeepMind shakeup means Google is losing the AI race. It might be that Google is choosing to run a different race.

Lost Primal Eye Paradigm scientific review and update August 2026

A growing body of research across paleoneurology, evolutionary biology, and chronobiology now supports the core mechanisms of Steve Nichols’s Lost Primal Eye paradigm aka Median Vision Theory (MVT). This is a regular scientific review and update posted for The Posthuman University Journal on academia.edu August 2026 Palaeoneurology and Therapsid Evolution Benoit et al. (2016) (Acta Palaeontologica Polonica): Examined over 800 therapsid fossil skulls, documenting the convergent, gradual reduction and complete loss of the parietal foramen across Permo-Triassic eutheriodonts. The study directly links the degeneration of the physical pineal eye to the evolution of mammalian endothermy, nocturnal adaptation, and the transfer of photoreception to paired lateral eyes.

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