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Thomas Polger “The Puzzling Resilience of Multiple Realization” (#DDLS)

This talk by Professor Thomas Polger (Professor of Philosophy at the Department of Philosophy University of Cincinnati) was given on Thursday 24 March 2022 as part of the Dutch Distinguished Lecture Series in Philosophy and Neuroscience (#DDLS).

Title:
Thomas Polger “The Puzzling Resilience of Multiple Realization” (#DDLS).

Caption.

Abstract.

According to the multiple realization argument, mental states or processes can be realized in diverse and heterogeneous physical systems; and that fact implies that mental states or processes can not be identified with any one particular kind of physical state or process. In particular, mental processes can not be identified with of brain processes. Moreover, the argument provides a general model for the autonomy of the “special” sciences. The multiple realization argument is widely influential. But over the last thirty years it has also faced serious objections. Despite those objections, most philosophers regard that fact of multiple realization and the cogency of the multiple realization argument as obviously correct. Why is that? What is it about the multiple realization argument that makes it so resilient? One reason that the multiple realization argument is deeply intertwined with a view that minds are, in some sense, computational. But I argue that the sense in which minds are computational does not support the conclusion that they are obviously multiply realized. I argue that the sense in which brains compute does not imply that brains implement computational processes that are multiply realizable, and it does not provide a general model for the autonomy of the special sciences.

Computational Theory of Mind

The mind is a lot like a computer — but what if this metaphor was more than just a metaphor? According to the philosopher Andy Clark, human minds aren’t just like computers, human minds are computers! In this video, we’ll get into the consequences of this seemingly radical framework and what it means for cognitive science as a whole.

0:00 — Intro.
1:09 — The conceivability argument.
2:17 — Behaviorism revisited.
5:14 — Identity theory.
7:54 — Functionalism revisited.
8:56 — Computational theory of mind.
12:09 — Formal systems.
13:26 — Games.
15:20 — Language.
17:19 — Wrapping up.
18:55 — Key concepts.

Scientists Are Mapping the Boundaries of What Is Knowable and Unknowable

“I give you God’s view,” said Toby Cubitt, a physicist turned computer scientist at University College London and part of the vanguard of the current charge into the unknowable, and “you still can’t predict what it’s going to do.”

Eva Miranda, a mathematician at the Polytechnic University of Catalonia (UPC) in Spain, calls undecidability a “next-level chaotic thing.”

Undecidability means that certain questions simply cannot be answered. It’s an unfamiliar message for physicists, but it’s one that mathematicians and computer scientists know well. More than a century ago, they rigorously established that there are mathematical questions that can never be answered, true statements that can never be proved. Now physicists are connecting those unknowable mathematical systems with an increasing number of physical ones and thereby beginning to map out the hard boundary of knowability in their field as well.

Computational platform helps unlock A20’s dual role in cancer immunotherapy

There is an urgent need for precision immunotherapy strategies that simultaneously target both tumor cells and immune cells to enhance treatment efficacy. Identifying genes with dual functions in both cancer and immune cells opens new possibilities for overcoming tumor resistance and improving patient survival.

Professor Zeng Zexian’s team from the Center for Quantitative Biology at the Peking University Academy for Advanced Interdisciplinary Studies, in collaboration with the Peking University-Tsinghua University Joint Center for Life Sciences, has developed ICRAFT, an innovative computational platform for identifying cancer targets. Their study has been published in Immunity.

ICRAFT integrates 558 CRISPR screening datasets, 2 million single-cell RNA sequencing datasets, and 943 RNA-Seq datasets from clinical immunotherapy samples.

Mechanistic understanding could enable better fast-charging batteries

Fast-charging lithium-ion batteries are ubiquitous, powering everything from cellphones and laptops to electric vehicles. They’re also notorious for overheating or catching fire.

Now, with an innovative computational model, a University of Wisconsin–Madison has gained new understanding of a phenomenon that causes lithium-ion batteries to fail.

Developed by Weiyu Li, an assistant professor of mechanical engineering at UW–Madison, the model explains lithium plating, in which fast charging triggers metallic lithium to build up on the surface of a battery’s anode, causing the battery to degrade faster or catch fire.

Designer bacteria for cancer therapy

In this study, researchers engineered an attenuated strain, Designer Bacteria 1 (DB1), which efficiently survives and proliferates in tumor tissues while being cleared in normal tissues, achieving a remarkable “tumor-targeting” effect as well as “tumor-clearing” effect.

To understand how DB1 simultaneously achieves these effects, researchers investigated the interactions between the bacteria and tumors. They discovered that DB1’s antitumor efficacy is closely linked to tissue-resident memory (TRM) CD8+ T cells within the tumor, which are reinvigorated and expanded following DB1 therapy. Interleukin-10 (IL-10) plays a crucial role in mediating this effect, with efficacy depending on the high expression of interleukin-10 receptor (IL-10R) on CD8+ TRM cells.

To investigate the molecular mechanisms underlying the high expression of IL-10R on CD8+ TRM cells, researchers conducted a series of computational and quantitative experiments. They found that IL-10 binds to IL-10R on CD8+ TRM cells, activating the STAT3 protein and further promoting IL-10R expression. This established a positive feedback loop, enabling cells to bind more IL-10 and creating a nonlinear hysteretic effect, whereby CD8+ TRM cells “memorize” previous IL-10 stimulation during tumorigenesis. The high expression of IL-10R on CD8+ TRM cells was exploited by a bacteria-induced IL-10 surge, which activated and expanded CD8+ TRM cells to clear tumor cells.

To examine the source of IL-10 within the tumor microenvironment (TME) after bacterial therapy, researchers found that tumor-associated macrophages (TAMs) upregulate IL-10 expression following DB1 stimulation via the Toll-like Receptor 4 (TLR4) signaling pathway. Interestingly, IL-10 reduced the migration speed of tumor-associated neutrophils (TANs), aiding DB1 in evading rapid clearance. These processes depended on high IL-10R expression in tumor-associated immune cells, highlighting the critical role of IL-10R hysteresis.

A research team elucidated the mechanism behind bacterial cancer therapy using a genetically engineered bacterial strain. Their findings were published in Cell.

Exploring the use of antitumor bacteria in cancer therapy dates back to the 1860s. Despite this long history, however, clinical application of bacterial-based cancer therapy has faced significant challenges in terms of safety and efficacy.

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