Aurelia Butler

Kidney cancer is not always confined to the kidney. In advanced cases, this cancer invades the body’s biggest vein, the inferior vena cava (IVC), which carries blood out of the kidneys back to the heart. Via the IVC, cancer may infiltrate the liver and heart. The Mays Cancer Center at The University of Texas Health Science Center at San Antonio (UT Health San Antonio) is one of the high-volume centers in the U.S. with surgical expertise in treating this serious problem. The Mays Cancer Center is San Antonio’s National Cancer Institute-designated Cancer Center.
In a study featured on the cover of the Journal of Urology (Official Journal of the American Urological Association), researchers from the Mays Cancer Center and Department of Urology at UT Health San Antonio show that robotic IVC thrombectomy (removal of cancer from the inferior vena cava) is not inferior to standard open IVC thrombectomy and is a highly safe and effective alternative approach. The affected kidney is removed along with the tumor during surgery, which is performed at UT Health San Antonio’s clinical partner, University Hospital.
Harshit Garg, MD, urologic oncology fellow in the Department of Urology, is first author of the study, and Dharam Kaushik, MD, urologic oncology fellowship program director, is the senior author. Kaushik is an associate professor and the Stanley and Sandra Rosenberg Endowed Chair in Urologic Research at UT Health San Antonio.
The open surgery requires an incision that begins 2 inches below the ribcage and extends downward on both sides of the ribcage. “It looks like an inverted V,” Kaushik said. Next, organs that surround the IVC, such as the liver, are mobilized, and the IVC is clamped above and below the cancer. In this way, surgeons gain control of the inferior vena cava for cancer resection.
“Open surgery has an excellent success rate, and most cases are performed in this manner,” Kaushik said. “But now, with the robotic approach, we can achieve similar results with smaller incisions. Therefore, we need to study the implications of utilizing this newer approach.”
The study is a systematic review and meta-analysis of data from 28 studies that enrolled 1,375 patients at different medical centers. Of these patients, 439 had robotic IVC thrombectomy and 936 had open surgery. Kaushik and his team collaborated with Memorial Sloan Kettering Cancer Center, New York; Cedars-Sinai Medical Center, Los Angeles; and the University of Washington, Seattle, to perform this study.
“We pulled the data together to make conclusions because, before this, only small studies from single institutions had been conducted to compare the IVC thrombectomy approaches,” Kaushik said.
Findings
The results are encouraging and indicate further study of robotic IVC thrombectomy is warranted. The robotic approach in comparison with open was associated with: Fewer blood transfusions: 18% of robotic patients required transfusions compared to 64% of open patients. Fewer complications: 5% of robotic patients experienced complications such as bleeding compared to 36.7% of open thrombectomy patients.These large, technically challenging surgeries last eight to 10 hours and involve a multidisciplinary team of vascular surgeons, cardiac surgeons, transplant surgeons and urologic oncology surgeons, Kaushik said.
“This study is the largest meta-analysis analyzing the outcomes of robotic versus open IVC thrombectomy,” Kaushik said. “In more than 1,300 patients, we found that overall complications were lower with the robotic approach and the blood transfusion rate was lower with this approach.
“That tells us there is more room for us to grow and refine this robotic procedure and to offer it to patients who are optimal candidates for it,” Kaushik said. “Optimal candidacy for a robotic surgery should be based on a surgeon’s robotic expertise, the extent and burden of the tumor, and the patient’s comorbid conditions. The open surgical approach remains the gold standard for achieving excellent surgical control.” More

What do corncobs and tomato peels have to do with electronics? They both can be used to salvage valuable rare earth elements, like neodymium, from electronic waste. Penn State researchers used micro- and nanoparticles created from the organic materials to capture rare earth elements from aqueous solutions.
Their findings, available online now, will also be published in the November issue of Chemical Engineering Journal.
“Waste products like corncobs, wood pulp, cotton and tomato peels often end up in landfills or in compost,” said corresponding author Amir Sheikhi, assistant professor of chemical engineering. “We wanted to transform these waste products into micro- or nanoscale particles capable of extracting rare earth elements from electronic waste.”
Rare earth metals are used to manufacture strong magnets used in motors for electric and hybrid cars, loudspeakers, headphones, computers, wind turbines, TV screens and more. However, mining these metals proves challenging and environmentally costly, according to Sheikhi, as large land areas are required to mine even small amounts of the metals. Instead, efforts have turned to recycling the metals from electronic waste items like old computers or circuit boards.
The challenge lies in efficiently separating the metals from refuse, Sheikhi said.
“Using the organic materials as a platform, we created highly functional micro- and nanoparticles that can attach to metals like neodymium and separate them from the fluid that surrounds them,” Sheikhi said. “Via electrostatic interactions, the negatively-charged micro- and nano-scale materials bind to positively-charged neodymium ions, separating them.”
To prepare the experiment, Sheikhi’s team ground up tomato peel and corncob and cut wood pulp and cotton paper into small, thin pieces and soaked them in water. Then, they chemically reacted these materials in a controlled fashion to disintegrate them into three distinct fractions of functional materials: microproducts, nanoparticles and solubilized biopolymers. Adding the microproducts or nanoparticles to neodymium solutions triggered the separation process, resulting in the capture of neodymium samples. More

An international research team led by the University of Göttingen has, for the first time, observed the build-up of a physical phenomenon that plays a role in the conversion of sunlight into electrical energy in 2D materials. The scientists succeeded in making quasiparticles — known as dark Moiré interlayer excitons — visible and explaining their formation using quantum mechanics. The researchers show how an experimental technique newly developed in Göttingen, femtosecond photoemission momentum microscopy, provides profound insights at a microscopic level, which will be relevant to the development of future technology. The results were published in Nature.
Atomically thin structures made of two-dimensional semiconductor materials are promising candidates for future components in electronics, optoelectronics and photovoltaics. Interestingly, the properties of these semiconductors can be controlled in an unusual way: like Lego bricks, the atomically thin layers can be stacked on top of each other. However, there is another important trick: while Lego bricks can only be stacked on top — whether directly or twisted at an angle of 90 degrees — the angle of rotation in the structure of the semiconductors can be varied. It is precisely this angle of rotation that is interesting for the production of new types of solar cells.
However, although changing this angle can reveal breakthroughs for new technologies, it also leads to experimental challenges. In fact, typical experimental approaches have only indirect access to the moiré interlayer excitons, therefore, these excitons are commonly termed “dark” excitons. “With the help of femtosecond photoemission momentum microscopy, we actually managed to make these dark excitons visible,” explains Dr. Marcel Reutzel, junior research group leader at the Faculty of Physics at Göttingen University. “This allows us to measure how the excitons are formed at a time scale of a millionth of a millionth of a millisecond. We can describe the dynamics of the formation of these excitons using quantum mechanical theory developed by Professor Ermin Malic’s research group at Marburg.”
“These results not only give us a fundamental insight into the formation of dark Moiré interlayer excitons, but also open up a completely new perspective to enable scientists to study the optoelectronic properties of new and fascinating materials,” says Professor Stefan Mathias, head of the study at Göttingen University’s Faculty of Physics. “This experiment is ground-breaking because, for the first time, we have detected the signature of the Moiré potential imprinted on the exciton, that is, the impact of the combined properties of the two twisted semiconductor layers. In the future, we will study this specific effect further to learn more about the properties of the resulting materials.”
This research was made possible thanks to the German Research Foundation (DFG) who provided Collaborative Research Centre funding for the CRCs “Control of Energy Conversion on Atomic Scales” and “Mathematics of Experiment” in Göttingen, and the CRC “Structure and Dynamics of Internal Interfaces” in Marburg.
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A Rutgers analysis of dozens of artificial intelligence (AI) software programs used in precision, or personalized, medicine to prevent, diagnose and treat disease found that no program exists that can be used for all treatments.
“Precision medicine is one of the most trending subjects in basic and medical science today,” said Zeeshan Ahmed, an assistant professor of medicine at Rutgers Robert Wood Johnson Medical School who led the study, published in Briefings in Bioinformatics. “Major reasons include its potential to provide predictive diagnostics and personalized treatment to variable known and rare disorders. However, until now, there has been very little effort exerted in organizing and understanding the many computing approaches to this field. We want to pave the way for a new data-centric era of discovery in health care.”
Precision medicine, a technology still in its infancy, is an approach to treatment that uses information about an individual’s medical history and genetic profile and relates it to the information of many others to find patterns that can help prevent, diagnose or treat a disease. The AI-based approach rests on a high level of both computing power and machine-learning intelligence because of the enormous scope of medical and genetic information scoured and analyzed for patterns.
The comparative and systematic review, believed by the authors to be one of the first of its kind, identified 32 of the most prevalent precision medicine AI approaches used to study preventive treatments for a range of diseases, including obesity, Alzheimer’s, inflammatory bowel disease, breast cancer and major depressive disorder. The bevy of AI approaches analyzed in the study — the researchers combed through five years of high-quality medical literature — suggest the field is advancing rapidly but is suffering from disorganization, Ahmed said.
In AI, software programs simulate human intelligence processes. In machine learning, a subcategory of AI, programs are designed to “learn” as they process more and more data, becoming ever more accurate at predicting outcomes. The effort rests on algorithms, step-by-step procedures for solving a problem or performing a computation.
Researchers such as Ahmed, who conducts studies on cardiovascular genomics at the Rutgers Institute for Health, Health Care Policy and Aging Research (IFH), are racing to collect and analyze complex biological data while also developing the computational systems that undergird the endeavor.
Because the use of genetics is “arguably the most data-rich and complex component of precision medicine,” Ahmed said, the team focused especially on reviewing and comparing scientific objectives, methodologies, data sources, ethics and gaps in approaches used.
Those interested in precision medicine, he said, can look to the paper for guidance as to which AI programs may be best suited for their research.
To aid the advent of precision medicine, the study concluded that the scientific community needs to embrace several “grand challenges,” from addressing general issues such as improved data standardization and enhanced protection of personal identifying information to more technical issues such as correcting for errors in genomic and clinical data.
“AI has the potential to play a vital role to achieve significant improvements in providing better individualized and population healthcare at lower costs,” Ahmed said. “We need to strive to address possible challenges that continue to slow the advancements of this breakthrough treatment approach.”
Other Rutgers researchers involved in the study included Sreya Vadapalli and Habiba Abdelhalim, research assistants at the IFH, and Saman Zeeshan, a bioinformatics research scientist and former postdoctoral research associate at the Rutgers Cancer Institute of New Jersey.
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Materials provided by Rutgers University. Original written by Kitta MacPherson. Note: Content may be edited for style and length. More

When some materials are cooled to a certain temperature, they lose electric resistance, becoming superconductors.
In this state, an electric charge can course through the material indefinitely, making superconductors a valuable resource for transmitting high volumes of electricity and other applications. Superconductors ferry electricity between Long Island and Manhattan. They’re used in medical imaging devices such as MRI machines, in particle accelerators and in magnets such as those used in maglev trains. Even unexpected materials, such as certain ceramic materials, can become superconductors when cooled sufficiently.
But scientists previously have not understood what occurs in a material to make it a superconductor. Specifically, how high-temperature superconductivity, which occurs in some copper-oxide materials, works hasn’t been previously understood. A 1966 theory examining a different type of superconductors posited that electrons which spin in opposite directions bind together to form what’s called a Cooper pair and allow electric current to pass through the material freely.
A pair of University of Michigan-led studies examined how superconductivity works, and found, in the first paper, that about 50% of superconductivity can be attributed to the 1966 theory — but the reality, examined in the second paper, is a bit more complicated. The studies, led by recent U-M doctoral graduate Xinyang Dong and U-M physicist Emanuel Gull, are published in Nature Physics and the Proceedings of the National Academy of Science.
Electrons floating in a crystal need something to bind them together, Gull said. Once you have two electrons bound together, they build a superconducting state. But what ties these electrons together? Electrons typically repel each other, but the 1966 theory suggested that in a crystal with strong quantum effects, the electron-electron repulsion is being screened, or absorbed, by the crystals.
While the electron repulsion is absorbed by the crystal, an opposite attraction emerges from the spinning properties of the electrons — and causes the electrons to bind in Cooper pairs. This underlies the lack of electronic resistivity. However, the theory doesn’t account for complex quantum effects in these crystals. More