Researchers at the University of Gothenburg have made light-powered gears on a micrometer scale. This paves the way for the smallest on-chip motors in history, which can fit inside a strand of hair.

Gears are everywhere - from clocks and cars to robots and wind turbines. For more than 30 years, researchers have been trying to create even smaller gears in order to construct micro-engines. But progress stalled at 0.1 millimeters, as it was not possible to build the drive trains needed to make them move any smaller.

Researchers from Gothenburg University, among others, have now broken through this barrier by ditching traditional mechanical drive trains and instead using laser light to set the gears in motion directly.

Gears powered by light

In their new study, the researchers shows that microscopic machines can be driven by optical metamaterials - small, patterned structures that can capture and control light on a nanoscale. Using traditional lithography, gears with an optical metamaterial are manufactured with silicon directly on a microchip, with the gear having a diameter of a few tens of micrometers. By shining a laser on the metamaterial, the researchers can make the gear wheel spin. The intensity of the laser light controls the speed, and it is also possible to change the direction of the gear wheel by changing the polarization of the light.

The researchers are thus close to creating micromotors.

A new way of thinking

"We have built a gear train in which a light-driven gear sets the entire chain in motion. The gears can also convert rotation into linear motion, perform periodic movements and control microscopic mirrors to deflect light," says the study's first author, Gan Wang, a researcher in soft matter physics at the University of Gothenburg.

The ability to integrate such machines directly onto a chip and drive them with light opens up entirely new possibilities. Since laser light does not require any fixed contact with the machine and is easy to control, the micromotor can be scaled up to complex microsystems.

"This is a fundamentally new way of thinking about mechanics on a microscale. By replacing bulky couplings with light, we can finally overcome the size barrier," says Gan Wang.

Cell size

With these advances, researchers are beginning to imagine micro- and nanomachines that can control light, manipulate small particles or be integrated into future lab-on-a-chip systems. A gear wheel can be as small as 16-20 micrometers, and there are human cells of that size. Medicine is a field that is within reach, believes Gan Wang.

"We can use the new micromotors as pumps inside the human body, for example to regulate various flows. I am also looking at how they function as valves that open and close."

Read more …Scientists build micromotors smaller than a human hair

Colorectal cancer is the second leading cause of cancer death worldwide. If detected early, it can be efficiently treated, but the cost and discomfort of colonoscopies -- the main diagnostic method currently in use -- often result in delayed diagnosis. Using machine learning algorithms, a team from the University of Geneva (UNIGE) identified for the first time all human gut bacteria to a level of detail that makes it possible to understand the physiological importance of the different microbial subgroups. This inventory was then used to detect the presence of colorectal cancer according to the bacteria present in simple stool samples, a non-invasive and low-cost screening tool. The potential applications are vast, ranging from the diagnosis of other cancers to a better understanding of the links between gut microbiota and health. These findings are published in Cell Host & Microbe.

Colorectal cancer is often diagnosed at an advanced stage when treatment options are limited. This underscores the need for simpler, less invasive diagnostic tools, particularly in the face of a still unexplained rise in cases among young adults. While it has long been known that gut microbiota plays a role in the development of colorectal cancer, translating these findings into clinical practice has proven challenging. This is because different strains of the same bacterial species can have opposite effects, with some promoting the disease and others having no effect.

"Instead of relying on the analysis of the various species composing the microbiota, which does not capture all meaningful differences, or of bacterial strains, which vary greatly from one individual to another, we focused on an intermediate level of the microbiota, the subspecies," explains Mirko Trajkovski, full professor in the Department of Cell Physiology and Metabolism and in the Diabetes Centre at the UNIGE Faculty of Medicine, who led this research. "The subspecies resolution is specific and can capture the differences in how bacteria function and contribute to diseases including cancer, while remaining general enough to detect these changes among different groups of individuals, populations, or countries."

With the help of machine learning

The first step was to analyse huge amounts of data. "As a bioinformatician, the challenge was to come up with an innovative approach for mass data analysis," recalls Matija Trickovic, PhD student in the laboratory of Mirko Trajkovski and first author of this study. "We successfully developed the first comprehensive catalogue of human gut microbiota subspecies, together with a precise and efficient method to use it both for research and in the clinic."

By combining this catalogue with existing clinical data, the scientists developed a model that can predict the presence of colorectal cancer solely based on the bacteria present in stool samples. "Although we were confident in our strategy, the results were striking," enthuses Matija Trickovic. "Our method detected 90% of cancer cases, a result very close to the 94% detection rate achieved by colonoscopies and better than all current non-invasive detection methods."

By integrating more clinical data, this model could become even more precise and match the accuracy of colonoscopy. It could become a routine screening tool and facilitate the early detection of colorectal cancer, which would then be confirmed by colonoscopy but only in a selected group of patients.

A new world of applications

A first clinical trial is being set up in collaboration with the Geneva University Hospitals (HUG) to determine more precisely the cancer stages and the lesions that can be detected. However, the applications go beyond colorectal cancer. By studying the differences between subspecies from the same bacterial species, researchers can now identify the mechanisms of action by which the gut microbiota influences human health. "The same method could soon be used to develop non-invasive diagnostic tools for a wide range of diseases, all based on a single microbiota analysis," concludes Mirko Trajkovski.

Read more …Goodbye colonoscopy? Simple stool test detects 90% of colorectal cancers

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