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Dr. Steven Gazal, an assistant professor of population and public health sciences at the Keck School of Medicine of USC, is on a mission to answer a perplexing question: Why, despite millions of years of evolution, do humans still suffer from diseases?

As part of an international research team, Gazal has made a groundbreaking discovery. They’ve become the first to accurately pinpoint specific base pairs in the human genome that have remained unaltered throughout millions of years of mammalian evolution. These base pairs play a significant role in human disease. Their findings were published in a special Zoonomia edition of the journal Science.

Gazal and his team analyzed the genomes of 240 mammals, including humans, zooming in with unprecedented resolution to compare DNA.

Out of all common refrains in the world of computing, the phrase “if only software would catch up with hardware” would probably rank pretty high. And yet, software does sometimes catch up with hardware. In fact, it seems that this time, software can go as far as unlocking quantum computations for classical computers. That’s according to researchers with the RIKEN Center for Quantum Computing, Japan, who have published work on an algorithm that significantly accelerates a specific quantum computing workload. More significantly, the workload itself — called time evolution operators — has applications in condensed matter physics and quantum chemistry, two fields that can unlock new worlds within our own.

Normally, an improved algorithm wouldn’t be completely out of the ordinary; updates are everywhere, after all. Every app update, software update, or firmware upgrade is essentially bringing revised code that either solves problems or improves performance (hopefully). And improved algorithms are nice, as anyone with a graphics card from either AMD or NVIDIA can attest. But let’s face it: We’re used to being disappointed with performance updates.

One fish, swimming alone, encountering a robotic fish impersonator will be wary and tend to avoid the robot, but a group of real fish are more likely to accept the robot as one of their own, and sometimes even abandon other real fish to follow the robot.

Those are the findings of engineers from Peking University and China Agricultural University who created a realistic koi fish robot, and placed one or two in a tank with real fish to see how they would respond.

We’re currently working with companies that develop software and tools that make surgery smarter and safer while they empower surgeons and providers to improve patient outcomes, enhance operational efficiency and increase profitability with data-driven surgery using AI, automation and operating room analytics. This is where analytic components such as data lakes and warehouses are already making a difference in healthcare. We’ve seen them capable of powering millions of facts and patient records at a time. Tied to expertise, these tools allow data-informed decisions for measurable improvements in clinical, financial and operational aspects.

For instance, we’ve helped design and develop surgical applications to improve operating room efficiency, tele-surgery, data lake construction and surgical analytics. Clients come back with feedback on our skills and technical experience, feeling supported by the flexibility and technical boost we give their teams.

Collaboration between technology outsourcing companies and healthcare providers can result in considerable optimization, including improved patient care and maximized processes. Tech providers can strive for the perfect collaborative balance with the above key conversations while boosting robust ecosystems, shared platforms and data.

Research published in Nature Communications today, has shown that techniques initially developed for astronomy and ecology can be used to study the microenvironment of solid tumors.

Led by Peter Mac’s 2020 Lea Medal winner Dr. Anna Trigos and Yuzhou Feng, the study looked at patient tumor samples from prostate, colon and breast cancers and identified novel cancer subtypes, new patterns associated with , and was able to predict which patients were likely to develop metastasis first.

These exciting results have generated significant interest from medical oncologists, pathologists and immunologists.