Thoracic aortic aneurysms (TAAs) stem from diverse mechanical and mechanobiological disruptions to the aortic wall that can also increase the risk of dissection or rupture. There is increasing evidence that dysfunctions along the aortic mechanotransduction axis, including reduced integrity of elastic fibers and loss of cell-matrix connections, are particularly capable of causing thoracic aortopathy. Because different insults can produce distinct mechanical vulnerabilities, there is a pressing need to identify interacting factors that drive progression. In this work, we employ a finite element framework to generate synthetic TAAs arising from hundreds of heterogeneous insults that span a range of compromised elastic fiber integrity and cellular mechanosensing. From these simulations, we construct localized dilatation and distensibility maps throughout the aortic domain to serve as training data for neural network models to predict the initiating combined insult. Several candidate architectures (Deep Operator Networks, UNets, and Laplace Neural Operators) and input data formats are compared to establish a standard for handling future subject-specific information. We further quantify the predictive capability when networks are trained on geometric (dilatation) information alone, which mimics current clinical guidelines, versus training on both geometric and mechanical (distensibility) information. We show that prediction errors based on dilatation data are significantly higher than those based on dilatation and distensibility across all networks considered, highlighting the benefit of obtaining local distensibility measures in TAA assessment. Additionally, we identify UNet as the best-performing architecture across all training data formats.

An AI tool has been used to review public responses to a government consultation for the first time and is now set to be rolled out more widely in an effort to save money and staff time. The tool, named "Consult", was first used by the Scottish government when it was seeking perspectives on the regulation of non-surgical cosmetic procedures such as lip filler. The UK government said the tool analysed responses and was able to produce results identical to human officials, and will now be used to review responses from other consultations, while also being developed further. While reviewing more than 2,000 responses, Consult identified key themes, which were then checked and refined by experts in the Scottish government. The government built Consult to be among its new package of AI tools, nicknamed "Humphrey", which they claim will "speed up work in Whitehall and cut back on consulting spending".

One night in 1966, a twenty-three-year-old graduate student named Nicholas Humphrey was working in a darkened psychology lab at the University of Cambridge. An anesthetized monkey sat before him; glowing targets moved across a screen in front of the animal, and Humphrey, using an electrode, recorded the activity of nerve cells in its superior colliculus, an ancient brain area involved in visual processing. The superior colliculus predates the more advanced visual cortex, which enables conscious sight in mammals. Although the monkey was not awake, the cells in its superior colliculus were firing anyway, their activation registering as a series of crackles issuing from a loudspeaker. Humphrey seemed to be listening to the brain cells "seeing."

In many of these cases, mutationrelated changes in vascular composition and biomechanical properties play key roles in both disease initiation and progression. Consequently, considerable attention continues to be devoted to comparing histomechanical properties of vessels from affected humans and animal models against those of age-and sex-matched healthy controls. Such information can provide insight into these diseases and their overall consequences on the cardiovascular system. Mouse models have emerged as particularly important in the study of genetically triggered vascular diseases for multiple reasons, including the now routine genetic manipulations in mice as well as their short gestational period, the availability of antibodies for biological assays, and the feasibility of miniaturized instrumentation for both in vivo and ex vivo assessments. Among others, we developed custom computer-controlled devices for biomechanically phenotyping murine arteries [1, 2] and identified protocols that ensure robust parameter estimations [3, 4, 5]. Findings have revealed, for example, graduated decreases in elastic energy storage capacity in cases of increasingly severe elastopathies and progressive increases in circumferential material stiffness in enlarging thoracic aortic aneurysms [6, 7]. Although microstructurally motivated, existing constitutive relations based on continuum biomechanics are phenomenological [8]. These models cannot directly relate the mechanical behavior with either the genotype or the precise microstructure of the arterial walls. They similarly cannot delineate or predict contributions of the myriad proteins, glycoproteins, and glycosaminoglycans that constitute the arterial wall in health and disease, and cannot characterize the genotype that determines the constituents of the wall and associated biomechanical properties.

Here's an easy way to improve your fur-riendship with your cat. A team of psychologists has found a way to communicate positive emotions with cats using eye movement. The researchers from the Portsmouth and Sussex universities in the U.K. found that narrowing eyes at a cat in a movement they described as a "slow blink," followed by a prolonged eye narrowing or closure is like smiling for cats. The results of their two experiments with slow blinking at cats were published in the journal Scientific Reports this week. Their study found that pet cats were more likely to slow blink back at their owners if the owners slow blinked at them first, and they were even more likely to approach a researcher they'd just met if the person slow blinked before offering an open hand than if the researcher kept a neutral facial expression.

If your digital marketing team struggles with attribution, you're not alone. Nielsen reports that only one out of every four marketers can confidently attribute revenue to their digital efforts. But does that surprise you? Probably not -- attribution is a pressing issue and can be a serious challenge for marketing and sales teams. Activating cross-channel campaigns through different platforms leads to siloed data in various, disconnected systems.

Four billion years ago, Earth was a lifeless place. Nothing struggled, thought, or wanted. Seawater leached chemicals from rocks; near thermal vents, those chemicals jostled and combined. Some hit upon the trick of making copies of themselves that, in turn, made more copies. The replicating chains were caught in oily bubbles, which protected them and made replication easier; eventually, they began to venture out into the open sea. A new level of order had been achieved on Earth. The tree of life grew, its branches stretching toward complexity. Organisms developed systems, subsystems, and sub-subsystems, layered in ever-deepening regression. They used these systems to anticipate their future and to change it. When they looked within, some found that they had selves--constellations of memories, ideas, and purposes that emerged from the systems inside. They experienced being alive and had thoughts about that experience. They developed language and used it to know themselves; they began to ask how they had been made. This, to a first approximation, is the secular story of our creation. It has no single author; it's been written collaboratively by scientists over the past few centuries. If, however, it could be said to belong to any single person, that person might be Daniel Dennett, a seventy-four-year-old philosopher who teaches at Tufts. In the course of forty years, and more than a dozen books, Dennett has endeavored to explain how a soulless world could have given rise to a soulful one. His special focus is the creation of the human mind.