Epstein-Barr Virus (EBV) is now recognized as an essential causal agent in the development of Multiple Sclerosis (MS). MS is a chronic autoimmune disease resulting in demyelination and neurodegeneration in the central nervous system (CNS). EBV is a ubiquitous human γ-herpesvirus that establishes long-term latent infection in a small subpopulation of memory B-lymphocytes. While EBV and B-lymphocytes are known to be drivers of MS autoimmune disease, it remains enigmatic how a small population of EBV-infected cells trigger and drive MS pathogenesis in some individuals. In this review, we discuss the known biology of EBV and its role in MS and other disease, including cancers, where EBV is an essential driving factor in disease progression. We review some of the conditions and cofactors that increase the risk of EBV infection leading to MS and the potential of pharmacological, biologic and vaccine approaches to more selectively target EBV to treat MS.
Keywords: EBNA1; Episome; Latency; Multiple Sclerosis; Therapeutics.
Copyright © 2026. Published by Elsevier B.V.
There is a habit of mind so embedded in Western intellectual history that we barely notice it anymore: when we want to understand the brain, we reach for the most sophisticated machine available and say, in effect, the brain is something like that. This is not merely a rhetorical convenience. It is a cognitive strategy — perhaps the only one available to us — for peering into an organ that cannot be fully observed from the inside, from the outside, or from anywhere in between. The machine metaphor is the mind’s mirror, and like all mirrors, it tells us something true and something distorted at the same time.
From the article
Economists Ozkan and Aakash Kalyani, along with research associate Nicholas Sullivan, scanned roughly 490,000 earnings call transcripts from 5,198 publicly traded U.S. firms between 2000 and 2025, using an AI model to tag sentences about productivity and AI. The share of productivity commentary tied to AI rose from near zero before ChatGPT’s late-2022 debut to roughly 15% of all productivity discussions by the end of 2025.
Approximately 95% of AI-related productivity sentences describe gains executives expect in the future, not gains already realized, a share that has held steady since 2023. When executives do describe AI’s effect, they’re almost uniformly bullish: 95% describe productivity as rising, compared with 75% for non-AI commentary.
Researchers say this is exactly what history predicts.
Ozkan said he wasn’t surprised by the future-tense findings, since aggregate data already showed no meaningful bump in productivity once capital investment was accounted for. He invoked economist Robert Solow’s famous quip that “you can see the computer age everywhere but in the productivity statistics,” drawing a direct line to electrification; it took “several decades,” Ozkan said, to reorganize factories, retrain workers, and change workflows before its productivity payoff showed up in the data.
Stanford economist Erik Brynjolfsson called this the “productivity paradox” in a 1993 paper for MIT, and lately has taken to describing the current situation as the modern sequel.”
Fertilization is often imagined as a frantic race, with millions of sperm competing for a single prize. But new research by a team of evolutionary biologists from Syracuse University, the University of Siena in Italy and the University of Szeged in Hungary reveals a more surprising reality, where success can depend less on competition and more on cooperation.
The group focused its study on organisms called arthropods, a large and diverse part of the animal kingdom that includes spiders, crabs, insects and centipedes. The scientists explored instances throughout evolutionary history where arthropod sperm worked together in coordinated groups, forming structures to improve their chances of reaching and fertilizing an egg. This process, known as sperm conjugation, is reshaping what researchers thought they understood about reproduction and evolution.
