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Telephone hotlines that allow primary care doctors to immediately consult with a child psychiatrist about urgent patient problems appears to increase the number of children who receive aid, offering one strategy to help more children receive mental health services, according to a new study from the nonprofit RAND Corporation.

Examining the growth of such services from 2009 to 2015, researchers found that parents of children who lived in states with child psychiatric telephone access programs were significantly more likely to say their children received mental health services than parents of children in states without such programs.

The study is the first to examine the influence of child psychiatric telephone access programs on a national level. The findings are published online by the Journal of the American Academy of Child & Adolescent Psychiatry.

"These findings suggest that telephone access programs may be one strategy to improve the proportion of children who receive help for their mental health needs," said Dr. Bradley D. Stein, the study's lead author and a physician scientist at RAND, a nonprofit research organization.

Studies estimate that half of the children in the U.S. with mental health problems do not receive needed treatment, often because there are too few child mental health specialists to provide the services needed.

In response, many states have established child psychiatric telephone consultant programs in the hope that access to psychiatric specialists will encourage more primary care physicians to provide mental health services to their patients.

Most of the programs are modeled after the first such effort that was created in Massachusetts in 2004. Since then a majority of states have established such programs, although some states have partial programs that serve only select counties.

RAND researchers used information from the National Survey of Children's Health to examine how mental health treatment patterns have changed since the establishment of child psychiatric telephone consultant programs. The information included details about more than 245,000 children ages 5 to 17 who took part in surveys done in 2003, 2007, 2011 and 2016.

Because states adopted child psychiatric telephone access programs in different years, examining treatment trends over time allowed researchers to account for the influence of other efforts to improve access to child mental health services.

Researchers found that nationally the percentage of children receiving mental health treatment rose from 8.4% in 2003 to 9.5% in 2007, 11.1% in 2011 and 11.4% in 2016.

By 2016, the percentage of children receiving mental health services in states with statewide child psychiatric telephone access programs was 12.3 percent, in contrast to states where there were partial programs (10.9%) or no such programs (9.5%).

Even after considering factors such as family income that could influence access to treatment, children from states with statewide child psychiatry telephone access programs were significantly more likely to receive mental health services than children residing in states without such programs.

Researchers say the study suggests that recent federal investment to substantially expand child psychiatric telephone consultation programs could bolster the number of children who receive needed mental health services.

"These programs likely complement other efforts such as telepsychiatry programs for children and families who have no nearby provider, and student loan forgiveness programs intended to increase the number of child-focused mental health providers," Stein said. "Helping families to find mental health care for their children is likely to require the full range of efforts."

HOUSTON -- (July 15, 2019) -- There's no known way to prove a three-dimensional "quantum spin liquid" exists, so Rice University physicists and their collaborators did the next best thing: They showed their single crystals of cerium zirconium pyrochlore had the right stuff to qualify as the first possible 3D version of the long-sought state of matter.

Despite the name, a quantum spin liquid is a solid material in which the weird property of quantum mechanics -- entanglement -- ensures a liquidlike magnetic state.

In a paper this week in Nature Physics, researchers offered a host of experimental evidence -- including crucial neutron-scattering experiments at Oak Ridge National Laboratory (ORNL) and muon spin relaxation experiments at Switzerland's Paul Scherrer Institute (PSI) -- to support their case that cerium zirconium pyrochlore, in its single-crystal form, is the first material that qualifies as a 3D quantum spin liquid.

"A quantum spin liquid is something that scientists define based on what you don't see," said Rice's Pengcheng Dai, corresponding author of the study and a member of Rice's Center for Quantum Materials (RCQM). "You don't see long-range order in the arrangement of spins. You don't see disorder. And various other things. It's not this. It's not that. There's no conclusive positive identification."

The research team's samples are believed to be the first of their kind: Pyrochlores because of their 2-to-2-to-7 ratio of cerium, zirconium and oxygen, and single crystals because the atoms inside them are arranged in a continuous, unbroken lattice.

"We've done every experiment that we could think of on this compound," Dai said. "(Study co-author) Emilia Morosan's group at Rice did heat capacity work to show that the material undergoes no phase transition down to 50 millikelvin. We did very careful crystallography to show there is no disorder in the crystal. We did muon spin relaxation experiments that demonstrated an absence of long-range magnetic order down to 20 millikelvin, and we did diffraction experiments that showed the sample has no oxygen vacancy or other known defects. Finally, we did inelastic neutron scattering that showed the presence of a spin-excitation continuum -- which may be a quantum spin liquid hallmark -- down to 35 millikelvin."

Dai, a professor of physics and astronomy, credited the success of the study to his colleagues, notably co-lead authors Bin Gao and Tong Chen and co-author David Tam. Gao, a Rice postdoctoral research associate, created the single-crystal samples in a laser floating zone furnace at the lab of Rutgers University co-author Sang-Wook Cheong. Tong, a Rice Ph.D. student, helped Bin perform experiments at ORNL that produced a spin excitation continuum indicative of the presence of spin entanglement that produces short-range order, and Tam, also a Rice Ph.D. student, led muon spin rotation experiments at PSI.

Despite the team's effort, Dai said it is impossible to definitively say cerium-zirconium 227 is a spin liquid, partly because physicists haven't yet agreed on what experimental proof is necessary to make the declaration, and partly because the definition of a quantum spin liquid is a state that exists at absolute zero temperature, an ideal beyond the reach of any experiment.

Quantum spin liquids are believed to occur in solid materials that are composed of magnetic atoms in particular crystalline arrangements. The inherent property of electrons that leads to magnetism is spin, and electron spins can only point up or down. In most materials, spins are shuffled at random like a deck of cards, but magnetic materials are different. In the magnets on refrigerators and inside MRI machines, spins sense their neighbors and arrange themselves collectively in one direction. Physicists call this "long-range ferromagnetic order," and another important example of long-range magnetic order is antiferromagnetism, where spins collectively arrange in a repeating, up-down, up-down pattern.

"In a solid with a periodic arrangement of spins, if you know what a spin is doing over here, you can know what a spin is doing many, many repetitions away because of long-range order," said Rice theoretical physicist and study co-author Andriy Nevidomskyy, an associate professor of physics and astronomy and RCQM member.
"In a liquid, on the other hand, there is no long-range order. If you look at two molecules of water a millimeter apart, for example, there is no correlation whatsoever. Nevertheless, due to their hydrogen-hydrogen bonds, they can still have an ordered arrangement at very short distances with nearby molecules, which would be an example of short-range order."

In 1973, Nobel laureate physicist Philip Anderson proposed the idea of quantum spin liquids based upon the realization that that geometric arrangement of atoms in some crystals could make it impossible for entangled spins to collectively orient themselves in stable arrangements.

As noted science writer Philip Ball aptly described in 2017, "Imagine an antiferromagnet -- in which adjacent spins prefer to be oppositely oriented -- on a triangular lattice. Each spin has two nearest neighbors in a triangle, but the antiparallel alignment cannot be satisfied for all of the trio. One possibility is that the spin lattice freezes into a disordered 'glassy' state, but Anderson showed that quantum mechanics allows the possibility of fluctuating spins even at absolute zero (temperature). This state is called a quantum spin liquid, and Anderson later suggested that it might be connected to high-temperature superconductivity."

The possibility that quantum spin liquids might explain high-temperature superconductivity spurred widespread interest among condensed matter physicists since the 1980s, and Nevidomskyy said interest further increased when it was "suggested that some examples of so-called topological quantum spin liquids may be amenable to building qubits" for quantum computing.

"But I believe part of the curiosity about quantum spin liquids is that it has resurfaced in many incarnations and theoretical proposals," he said. "And although we have theoretical models where we know, for a fact, that the result will be a spin liquid, finding an actual physical material that would fulfill those properties has, so far, proven very difficult. There is no consensus in the field, up to now, that any material -- 2D or 3D -- is a quantum spin liquid."

NEW YORK, July 15, 2019 -- The disability burden for people with multiple sclerosis (MS) can vary significantly depending on whether they have a relapsing/remitting form of the disease, where they experience periods of clinical remission, or a progressive form, where they have continued neurological deterioration without clinical remission. Effective therapies exist for managing relapsing/remitting MS, but treatment for progressive MS has proved more challenging. Now, a new paper published in the journal Brain from researchers at the Advanced Science Research Center (ASRC) at The Graduate Center, CUNY and Friedman Brain Institute at the Icahn School of Medicine at Mount Sinai has identified potential mechanisms that may inform the development of therapies that effectively manage progressive MS.

Previous research had suggested that dysfunction of neuronal mitochondria -- the energy-producing subcellular organelles -- occurs in the brains of MS patients with progressive clinical disability. However, the molecular mechanisms underlying this process remained elusive.

"Because the brain is bathed by the cerebrospinal fluid (CSF), we asked whether treating cultured neurons with the CSF from MS patients with a relapsing/remitting or a progressive disease course would possibly elicit different effects on neuronal mitochondrial function," said the study's primary investigator Patrizia Casaccia, Einstein Professor of Biology at The Graduate Center and founding director of the Neuroscience Initiative at the ASRC. "We detected dramatic differences in the shape of the neuronal mitochondria and their ability to produce energy. Only exposure to the CSF from progressive MS patients caused neuronal mitochondria to fuse and elongate while rendering them unable to produce energy. We therefore searched for potential mechanisms of CSF-induced neurodegeneration with the intent to define therapeutic strategies."

Methodology

CSF samples were acquired from 15 patients with relapsing/remitting MS and 29 with progressive MS. These samples were extensively characterized, both functionally and metabolically. Video recordings of live, cultured rat neurons that were exposed to the CSF revealed important differences. Researchers detected a characteristic elongation of mitochondria exposed to CSF samples from progressive MS patients. This characteristic response was not present in mitochondria exposed to CSF from patients with a relapsing/remitting MS. Biochemical characterization of mitochondrial activity further revealed that elongated mitochondria were less functional and therefore less capable of producing energy, which eventually resulted in neuronal demise.

The research team delved deeper to determine what was present in the CSF of progressive MS patients that could be causing these mitochondrial changes and, possibly, an increased energy demand. Previous research has indicated that mitochondria elongate in an effort to generate more energy for cells when there is enhanced energetic demand or a decrease in available glucose. The researchers' lipid profiling of the CSF samples revealed that CSF from progressive MS patients had increased levels of ceramides.

"When we exposed cultured neurons to ceramides, we elicited the same changes caused by exposure to CSF from progressive MS patients, and we further discovered that ceramides induced neuronal damage by acting on two cellular mechanisms," said Maureen Wentling, a research associate in the Casaccia lab and the study's first author. "On one end, ceramides impaired the ability of neurons to make energy by directly damaging the mitochondria. On the other end, they also forced neurons to more rapidly uptake glucose in an attempt to provide energy for the cell."

The researchers were able to prevent the neurotoxic effect of CSF on cultured neurons by supplementing glucose. Supplementation isn't a sustainable approach in the diseased brain, however, so a different approach will ultimately be needed for developing therapies that improve mitochondrial function in patients with progressive MS.

CORVALLIS, Ore. - Oregon State University researchers have developed a new computer model for calculating the water content of snowpacks, providing an important tool for water resource managers and avalanche forecasters as well as scientists.

"In many places around the world, snow is a critical component of the hydrological cycle," said OSU civil engineering professor David Hill. "Directly measuring snow-water equivalent is difficult and expensive and can't be done everywhere. But information about snow depth is much easier to get, so our model, which more accurately estimates snow-water equivalent from snow depth than earlier models, is a big step forward."

The findings, published in The Cryosphere, are related to a NASA-funded snow depth project co-led by Hill and also involving Oregon State Ph.D. student Ryan Crumley.

The project is called Community Snow Observations and is part of NASA's Citizen Science for Earth Systems program. Snowshoers, backcountry skiers and snow-machine users are gathering data to use in computer modeling of snow-water equivalent, or SWE.

The Community Snow Observations research team kicked off in February 2017. Led by Hill, Gabe Wolken of the University of Alaska Fairbanks and Anthony Arendt of the University of Washington, the project originally focused on Alaskan snowpacks. Researchers then started recruiting citizen scientists in the Pacific Northwest. Currently, the project has more than 2,000 participants.

The University of Alaska Fairbanks has spearheaded the public involvement aspect of the project, while the University of Washington's chief role is managing the data. Hill and Crumley are responsible for the modeling.

In addition to snow depth information collected and uploaded by recreationists using avalanche probes, vast amounts of data are also available thanks to LIDAR, a remote sensing method that uses a pulsed laser to map the Earth's topography.

The new model developed by the Community Snow Observations team and collaborators at the University of New Hampshire calculates snow-water equivalent by factoring in snow depth, time of year, 30-year averages (normals) of winter precipitation, and seasonal differences between warm and cold temperatures.

"Using those climate normals rather than daily weather data allows our model to provide SWE estimates for areas far from any weather station," Hill said.

Researchers validated the model against a database of snow pillow measurements - a snow pillow measures snow-water equivalents via the pressure exerted by the snow atop it - as well as a pair of large independent data sets, one from western North America, the other from the northeastern United States.

"We also compared the model against three other models of varying degrees of complexity built in a variety of geographic regions," Hill said. "The results show our model performed better than all of them against the validation data sets. It's an effective, easy-to-use means of estimation very useful for vast areas lacking weather instrumentation - areas for which snow depth data are readily available and daily weather data aren't."

FAYETTEVILLE, Ark. - Climate change is amplifying the intensity and likelihood of heatwaves during severe droughts in the southern plains and southwest United States, according to a new study by a University of Arkansas researcher.

Linyin Cheng, assistant professor of geosciences, used data from the National Center for Atmospheric Research's Community Earth System Model to study summer droughts that occurred both before and after the Industrial Revolution. Cheng and colleagues from the National Oceanic and Atmospheric Administration and universities in China and Colorado ran simulations to assess how, and by how much, human-induced climate change affects summer heatwaves in the contiguous United States. The study was published in the Journal of Climate.

The researchers found that in places with low moisture in the soil, such as the southern plains and southwest, higher temperatures brought about by climate change led to an increased "coupling" of land and atmosphere, which further increased the severity of heatwaves. In places with more moisture in the soil, such as the northeast, they found no appreciable coupling and therefore no contribution to heatwave intensification.

"Our analysis of climate simulation finds that summertime drought-heatwave relationships change significantly over the southern and southwest U.S. due to man-made climate change since the late 19th century," said Cheng. "By contrast, the drought-heatwave relationship over northern U.S regions undergoes little change in the warmed climate."

The findings raise the idea of a self-reinforcing climate loop: as a region's climate becomes more arid due to climate change, droughts become hotter, further reducing soil moisture.

"Overall, these results indicate that strengthened land-atmosphere feedback is a significant physical driver for increasing occurrences of drought-related extreme heatwaves, particularly over the semi-arid and arid regions of the United States," the report states.

A new reusable device created by the Johns Hopkins University can help women with breast cancer in lower income countries by using carbon dioxide, a widely available and affordable gas, to power a cancer tissue-freezing probe instead of industry-standard argon.

A study detailing the tool's success in animals was published this month in PLOS One.

"Innovation in cancer care doesn't always mean you have to create an entirely new treatment, sometimes it means radically innovating on proven therapies such that they're redesigned to be accessible to the majority of the world's population," says Bailey Surtees, a recent Johns Hopkins University biomedical engineering graduate and the study's first author.

"This project is a remarkable example of success from the Biomedical Engineering Design Program," says Nicholas Durr, an Assistant Professor of Biomedical Engineering at Johns Hopkins and the study's senior author. "This team of undergraduates has been so successful because they created a practical solution for the problem after really understanding the constraints that needed to be met to be impactful."

The largest cause of cancer-related mortality for women across the globe, breast cancer disproportionately affects women in lower-income countries due to lack of treatment. While the survival rate for women in the United States is greater than 90%, they are significantly lower at 64%, 46% and 12% in Saudi Arabia, Uganda and The Gambia, respectively.

"Instead of saying 'She has breast cancer," the locals we met while conducting focus groups for our research said 'She has death,' because breast cancer is often considered an automatic death sentence in these communities," adds Surtees.

In lower-income countries, the main barriers to treating breast cancer are inadequate treatment options--with surgery, chemotherapy and radiation being impractical or too expensive--and long travel times to regional hospitals where efficient treatment is available. Even if a woman is able to travel to a hospital for treatment, she may not be seen and recovery times will keep her out of work for an additional few weeks.

Killing cancerous tissue with cold, or cryoablation, is preferable to surgically removing tumors in these countries because it eliminates the need for a sterile operating room and anesthesia, thus making it possible to local clinics to perform the procedure. It's also minimally invasive, thereby reducing complications such as pain, bleeding and extended recovery time.

Current cryoablation technologies, however, are too expensive, with a single treatment costing upwards of $10,000, and are dependent on argon gas, which typically isn't available in lower-income countries, to form the tissue-killing ice crystals.

With these barriers in mind, the student-led research team, named Kubanda (which means "cold" in Zulu), wanted to create a tissue-freezing tool that uses carbon dioxide, which is already widely available in most rural areas thanks to the popularity of carbonated drinks.

The research team tested their tool in three experiments to ensure it could remain cold enough in conditions similar to the human breast and successfully kill tumor tissue.

In the first experiment, the team used the tool on jars of ultrasound gel, which thermodynamically mimics human breast tissue, to determine whether it could successfully reach standard freezing temperatures killing tissue and form consistent iceballs. In all trials, the device formed large enough iceballs and reached temperatures below -40 degrees Celsius, which meets standard freezing temperatures for tissue death for similar devices in the United States.

For the second experiment, the team treated 9 rats with 10 mammary tumors. Afterwards, they looked at the tissue under a microscope and confirmed that the tool successfully killed 85% or more tissue for all tumors.

Finally, the team tested the tool's ability to reach temperatures cold enough for tissue destruction in the normal liver of a pig, which has a temperature similar to a human breast. The device was successfully able to stay cold enough during the entire experiment to kill the target tissue.

"When we started the project, experts in the area told us it was impossible to ablate meaningful tissue volumes with carbon dioxide. This mindset may have come from both the momentum of the field and also from not thinking about the importance of driving down the cost of this treatment," says Durr.

While the results are promising, the device still requires additional experiments before it's ready for commercial use. Mainly, the research team's next steps are to ensure it can consistently kill cancer tissue under the same heat conditions as human breast tissue.

In the near future, the team hopes to continue testing their device for human use, and expand its use to pets.

Adults with HIV are more likely to continue life-saving treatments if their primary health care providers show respect, unconditional empathy without judgement and demonstrate an ability to partner with patients in decision making to address their goals, a Rutgers study finds.

The systematic review appears in the Joanna Briggs Institute Database of Systematic Reviews and Implementation Reports.

The findings showed that the complexity of the illness, treatment regimen and overall healthcare system frequently overwhelms the patient and fear of stigma often prevents them from beginning or continuing treatment. The researchers found that patients need help in understanding their illness and care needs using understandable language to translate complex information, letting patients know what to expect and reinforcing that HIV is now a treatable, yet complex, chronic illness.

"Today, HIV is considered a chronic, treatable condition. However, this study found that many patients continue to view it as a death sentence," said lead author Andrea Norberg, executive director of the François-Xavier Bagnoud Center at Rutgers School of Nursing, which provides care for people with HIV, infectious diseases and immunologic disorders. "We know that people who are knowledgeable about HIV, who are engaged in care and taking antiretroviral therapy medications remain relatively healthy. Our challenge is to reach those people diagnosed with HIV and who are not retained or engaged in ongoing care. In the United States, this is approximately 49 percent of the 1.1 million people diagnosed."

The researchers included 41 studies published between 1997 to 2017. The sample populations included adults with HIV and their healthcare providers. All adults with HIV were between the ages of 18 and 65, represented diverse races and ethnicities, sexual orientations and gender identities. Healthcare providers included physicians, nurse practitioners, physician assistants, pharmacists, social workers and others. The included studies had 1,597 participants.

They found that many patients experience stigma and a lack of compassion that is often grounded in primary care providers' ignorance about HIV and transmission risks. The resulting poor communication between providers and patients results in many patients' failure to seek or remain in care and adhere to antiretroviral therapy medications.

Patients reported feeling "grilled" by providers who often assumed they were not taking medications. Norberg suggested providers would be more successful in getting information from patients by allowing them to be honest, inquiring about their health goals and telling them how other patients have managed treatment.

Conversely, the researchers found that patients were more inclined to adhere to HIV treatment when their primary care providers showed empathy, true listening, trust, consideration of the whole person and involvement in decision making. However, many patients reported that healthcare providers viewed care only as "prescribing antiretroviral therapy medicine."

"Providers should use common language, not medical jargon, to educate patients about HIV, medications and how they can live a healthy life," Norberg said. "They should thoroughly teach them about the disease, the medications and side effects, and the meaning of the tests."

The researchers noted that providers who help patients navigate the health system, offer one-stop location of services and provide connections to psychological support, health insurance, medicine, transportation and other services, can help their patients stay engaged in care.

Primary healthcare providers can enroll in professional education to improve their knowledge about HIV, use of motivational interviewing skills and seek opportunities for experiential learning, observation and hands-on practice working directly with patients with HIV, Norberg said.

Immune checkpoint blockade (ICB) therapy using the antibody that combats the programmed cell death ligand 1 (PD-L1) shows great potential and is causing a revolution in clinical cancer management. Unfortunately, only a subset of treated patients responds to current ICB therapies, likely due to the immunological tolerance of tumors. Therefore, developing a practical strategy to combat this immunological tolerance and amplify ICB therapies has become a priority.

To meet this challenge, scientists from the Shanghai Institute of Materia Medica (SIMM) of the Chinese Academy of Sciences have developed a tumor enzymatic microenvironment-activatable antibody nanoparticle for robust cancer immunotherapy. This research was published online in Science Immunology.

In this study, Prof. YU Haijun, Prof. LI Yaping and their colleagues engineered the antibody nanoparticles by integrating anti-PD-L1 antibody (αPDL1) and indocyanine green (ICG) into one single nanoplatform. ICG is a clinically approved fluorophore for fluorescence imaging in live surgery and photosensitizer for photodynamic therapy (PDT). The antibody nanoparticles remain inert in blood circulation and protect αPDL1 from binding with normal tissues. Once accumulated at the tumor site through the enhanced permeability and retention (EPR) effect, the antibody nanoparticles become activated to release αPDL1 for tumor-specific PD-L1 blockading.

Moreover, the scientists revealed that the antibody nanoparticles triggered the release of tumor antigens and promoted intratumoral infiltration of cytotoxic T lymphocytes (CTLs) through the ICG-based PDT effect. "This is crucial for cancer immunotherapy since CTLs have been well-identified as the killer of tumor cells," explained Prof. YU, co-corresponding author of the study.

Finally, they showed that the antibody nanoparticles not only boost antitumor immunity with great efficiency, but also elicit long-term immune memory effects in BALB/c mice, thus leading to remarkable tumor regression.

In particular, the antibody nanoparticle-mediated combination of ICB and PDT therapy effectively suppressed tumor growth and metastasis to the lung and lymph nodes when using a 4T1 tumor-bearing BALB/C mouse model, which resulted in survival for >70% of the mice for more than 65 days, compared to complete mouse death in 42 days for the free αPDL1 group.

"We provided a robust antibody nanoplatform for priming the antitumor immunity and inhibiting the immune checkpoint, which could be readily adapted to other immune checkpoint inhibitors for enhanced ICB therapies. Given the simplicity of the nanostructures, our study has the potential of being translated into future generations of cancer immunotherapy," Prof. YU said.

HERSHEY, Pa. -- Preventing a protein from doing its job may keep a certain type of ovarian cancer cell from growing and dividing uncontrollably in the lab, according to a new study from Penn State College of Medicine.

In a study with cell cultures, the researchers identified the protein as a potential therapeutic target for high-grade serous ovarian cancer cells. Approximately 70% of patients with this type of ovarian cancer relapse with chemo-resistant disease, increasing the need for new approaches to treatment.

Katherine Aird, assistant professor of cellular and molecular physiology, and other researchers in her lab have identified a potential method to put high-grade serous ovarian cancer cells in a "sleep state," called senescence.

"One of the biggest problems of cancer cells is they can grow forever without stimulus," Aird said. "By inducing senescence, the cells can no longer divide and grow."

Cells break down and build up the chemicals needed for supporting life through various cycles and pathways in a process known as metabolism.

"A hallmark of cancer cells is that their metabolic processes are often different from normal, healthy cells," said Erika Dahl, a doctoral student at the College of Medicine and lead author on the paper. In the study, Dahl set out to evaluate the metabolic differences between normal fallopian tube cells and the cancerous cells.

The metabolites in each line of cells was quantified using spectrometry. After comparing differences in their metabolic processes, the lab found that the cancerous cells prefer to use sugars in the citric acid cycle, instead of making lactate, the more common route.

"Many therapies target glycolysis, but that may not be the best approach," Dahl said. She noted often when targeting glycolysis, there could be toxic damage to normal, healthy tissue.

Further investigation revealed that inhibiting, or stopping the activity, of a specific protein -- isocitrate dehydrogenase 1 -- in the citric acid cycle led to a halt in cell division. Aird said that while mutated forms of this protein are common in other cancers, she and her team identified that the wildtype, or normal, form was present in high-grade serous cancer cells.

"The Food and Drug Administration has already approved a drug that targets the mutant form of the protein," Aird said. "One of the drugs that target the mutant form can also target the wildtype form. One of our long-term goals is to try and repurpose this already-approved drug as a treatment for this form of ovarian cancer."

The research team found that inhibiting the wildtype form of the protein may be an effective strategy for future therapies for all stages of high-grade serous ovarian cancer. When these cells spread to other parts of the body, they adopt a form that is different from the original cancer cells. The inhibitor proved effective at arresting the cell cycle in both forms.

"It is important that therapies are effective at later stages, as this is when ovarian cancer patients are typically diagnosed," Dahl said.

Available data showed that the chances for progression-free survival decreased when the protein is highly expressed.

In the future, the lab will further investigate metabolic differences between normal and high-grade serous ovarian cancer cells. Researchers also will look to see if combining the inhibitor with other therapies is effective.

Singapore, 7 July 2019 - Functional regions within the brain become less distinct and inter-connected in the elderly over time, especially in those networks related to attention span and cognition. The finding, published by researchers at Duke-NUS Medical School in The Journal of Neuroscience, adds to current understanding of longitudinal decline in brain network integrity associated with ageing.

"We currently live in a rapidly ageing society," said the study's corresponding author, Associate Professor Juan Helen Zhou, a neuroscientist from the faculty of Duke-NUS' Neuroscience and Behavioural Disorders programme. "Compared to cross-sectional studies, it is vital to understand brain changes over time that underlie both healthy and pathologic ageing, in order to inform efforts to slow down cognitive ageing."

The human brain contains functionally segregated neuronal networks with dense internal connections and sparse inter-connectivity. Ageing is thought to be associated with reduced functional specialisation and segregation of these brain networks.

Joint senior authors Assoc Prof Zhou and Prof Michael Chee, Director of Duke-NUS' Centre for Cognitive Neuroscience, led the research team, collecting data from neuropsychological assessments and functional magnetic resonance imaging (fMRI) brain scans from a cohort of 57 healthy young adults and 72 healthy elderly Singaporeans. Each elderly participant was scanned two to three times during a period of up to four years. The neuropsychological assessments tested participants' ability to process information quickly, focus their attention, remember verbal and visuo-spatial information, and plan and execute tasks. The fMRI scans measured how brain regions are functionally connected based on low-frequency blood oxygenation level fluctuations over time. Participants were asked to relax with their eyes open and remain still as these were performed.

Dr Joanna Chong, first author of the paper and a PhD graduate from Assoc Prof Zhou's lab at Duke-NUS, developed approaches to convert the fMRI images into graphic representations that depict the inter- and intra-network connectedness of each individual's brain. She then compared differences in brain functional networks between the young and elderly participants, and in the elderly over time.

The team tracked changes in brain functional networks that affected specific cognitive abilities, such as goal-oriented thought and action, and choosing where to focus attention. As one ages, these networks associated with cognition are less efficient in information transfer, more vulnerable to disturbance, and less distinctive.

"Overall, our research advances understanding of brain network changes over time, underlying cognitive decline in healthy ageing," said Assoc Prof Zhou. "This can facilitate future work to identify elderly individuals at risk of ageing-related disorders or to identify strategies that can preserve cognitive function."

Commenting on the study, Prof Patrick Casey, Senior Vice Dean for Research at Duke-NUS, stated, "Ageing is a significant risk factor for a variety of chronic diseases in people, including neurodegenerative and cerebrovascular diseases. Governments worldwide are concerned about the public health implications of increasingly ageing populations. Basic research such as this plays a vital role in informing efforts to help us stay healthy longer as we live longer lives."

The researchers aim to next examine how various factors, such as genetic and cardiovascular risks, might influence ageing-related changes in brain networks. By studying a larger group of healthy young, middle-aged and older adults, they hope to develop better ways to predict cognitive decline.

Seeking to improve upon existing checkpoint inhibitor therapies, scientists have developed a common checkpoint inhibitor (anti-PD-L1) in a nanoparticle formulation, which were activated specifically at tumor sites in mouse models of cancer. Their approach intends to prevent the immune system from becoming tolerant of tumors - which occurs in 30% of all cancer patients - and could help avoid the toxic off-target effects observed during the use of standard antibody checkpoint inhibitors. As well, the antibodies used to target immune system-suppressing proteins like PD-1 and PD-L1 can fail to reach deep-seated or metastatic tumors, further hindering their efficacy. Seeking a method to overcome these hurdles, Dangge Wang and colleagues developed highly tumor-specific nanoparticles carrying PD-L1-targeting antibodies and a photosensitizer, a light-activated molecule that produces tumor-killing reactive oxygen species after encountering matrix metalloproteinase protein 2 (MMP-2), a protein abundant in tumors. In mouse models, the dual administration of PD-L1-carrying nanoparticles in conjunction with local near-infrared radiation (that activates the photosensitizer) promoted the infiltration of cancer cell-killing T cells into the tumor site and further sensitized the tumors to PD-L1 checkpoint blockade. This combination also helped the nanoparticles effectively suppress tumor growth and metastasis to the lung and lymph nodes, resulting in approximately 80% mouse survival over 70 days, compared to complete mouse death in 45 days in the group treated with only PD-L1 antibodies. With further improvement, the platform used here could be readily adapted to other immune checkpoint inhibitors for improved checkpoint blockade immunotherapy, the authors say.

What The Study Did: Called a systematic review and meta-analysis, this study combined the results of 26 studies to examine the cognitive and motor development of infants and children exposed to opioids prenatally.

Many burn victims suffer acute kidney injury (AKI), but early recognition of AKI remains challenging. Now an Artificial Intelligence / Machine Learning (AI/ML) model developed at UC Davis Health and reported in a new study can predict acute kidney injury quicker and more accurately than ever.

"The ability to predict AKI in burn patients using AI is a potential breakthrough for burn centers," said Tina Palmieri, professor and director of the Firefighters Burn Institute Regional Burn Center at UC Davis Medical Center. "If we can tell that a patient might have kidney injury, we can institute measures to prevent it."

What is acute kidney injury?

Acute kidney injury (AKI) is sudden kidney failure or damage causing a build-up of waste in blood and a fluid imbalance in the body. AKI usually happens within the first week of serious burn due to inadequate resuscitation, especially during the critical first 24?hours. Developing in around 30% of cases, AKI is a common complication after severe burn, with a mortality rate reaching 80%.

Diagnosing acute kidney injury

Physicians typically rely on traditional biomarkers such as serum/plasma creatinine and urine output for diagnosis. However, urine output and creatinine measures are considered poor biomarkers of AKI.

"UC Davis was the first to identify the role a novel biomarker, known as neutrophil gelatinase associated lipocalin (NGAL), plays in early prediction of AKI in severely burned patients," said Nam Tran, associate clinical professor at Department of Pathology and Laboratory Medicine at UC Davis.

Despite its strong predictive power, NGAL was not available in the United States and its interpretation required more experienced clinicians and laboratory experts. This challenge prompted the development of an artificial intelligence machine learning model to make it easier to interpret results for the NGAL test.

Machine learning enhances acute kidney injury recognition

Sometimes the assumption in the AI/ML world is that the more complicated algorithms such as deep neural network are better than more traditional algorithms in building ML models. This assumption is not always true.

"We built a powerful ML model through our k-Nearest Neighbor approach that is able to accurately predict AKI in our patient population in a much shorter period," said Hooman Rashidi, professor in the Department of Pathology and Laboratory Medicine at UC Davis Health. "Based on admission data, the model can shorten the time to diagnosis by as much as two days."

The models were trained and tested with clinical laboratory data for 50 adult burn patients that had NGAL, urine output, creatinine and NT-proBNP measured within the first 24 hours of admission. Half of patients in the dataset developed AKI within the first week following admission. The models containing NGAL, creatinine, urine output and NT-proBNP achieved 90-100% accuracy for identifying AKI. The models containing only NT-proBNP and creatinine achieved 80-90% accuracy.

The average time from admission to diagnosis with traditional biomarkers was 42.7 hours. The average time using the ML algorithm was just 18.8 hours. The ML model beat the traditional method by nearly a full day - critical time to prevent and treat AKI.

"For our study, AI/ML has shown the potential clinical utility for predicting burn-related AKI when using just a few routine laboratory results," Tran added.

Applications and implications of the new model

This model has applications to be used in the field, including for military casualties. Because troops might be sent to hospitals that lack the facilities to manage kidney injury, the AI/ML method could identify patients with AKI more quickly so they can be diverted faster to advanced medical facilities. This optimizes limited resources in the battlefield and accelerates the transport of patients to where they need to go. The same process applies in the civilian world.

"We envision such machine learning platforms to be incorporated in a variety of settings outside of AKI which could ultimately enhance various aspects of patient care within the clinical medicine arena," Rashidi added.

Two proteins that activate the fastest molecule in our nerve cells identified by researchers at University of Warwick

Mechanism is responsible for transport through our nervous system

Faults in cargo transporters can lead to hereditary spastic paraplegia (HSP) and other neurodegenerative disorders

Could lead to therapeutic treatment for people with HSP and neurological disorders

Scientists at the University of Warwick have discovered a new process that sets the fastest molecular motor on its marathon-like runs through our neurons.

The findings, now published in Nature Communications, paves the way towards new treatments for certain neurological disorders.

The research focuses on KIF1C: a tiny protein-based molecular motor that moves along microscopic tubular tracks (called microtubules) within neurons. The motor converts chemical energy into mechanical energy used to transport various cargoes along microtubule tracks, which is necessary for maintaining proper neurological function.

Neurons are cells that form the basis of our nervous system, conducting the vital function of transferring signals between the brain, the spinal cord and the rest of the body. They consist of a soma, dendrites, and an axon, a long projection from the cell that transports signals to other neurons.

Molecular motors need to be inactive and park until their cargo is loaded onto them. Neurons are an unusually long (up to 3 feet) type of nerve cell, and because of this marathon distance, these tiny molecular motors need to keep going until their cargo is delivered at the end.

Insufficient cargo transport is a crucial cause for some debilitating neurological disorders. Faulty KIF1C molecular motors cause hereditary spastic paraplegia, which affects an estimated 135,000 people worldwide. Other studies have also found links between defective molecular motors and neurological disorders such as Alzheimer's disease and dementia.

The research shows how, when not loaded with cargo, KIF1C prevents itself from attaching to microtubule tracks by folding on to itself. The scientists also identified two proteins: PTNPN21 and Hook3, which can attach to the KIF1C molecular motor. These proteins unfold KIF1C, activating it and allowing the motor to attach and run along the microtubule tracks - like firing the starting pistol for the marathon race.

The newly identified activators of KIF1C may stimulate cargo transport within the defective nerve cells of patients with hereditary spastic paraplegia, a possibility the team is currently exploring.

Commenting on the future impact of this research, Dr Anne Straube from Warwick Medical School said: "If we understand how motors are shut off and on, we may be able to design cellular transport machines with altered properties. These could potentially be transferred into patients with defect cellular transport to compensate for the defects. Alternatively they can be used for nanotechnology to build new materials by exploiting their ability to concentrate enzymes or chemical reagents. We are also studying the properties of the motors with patient mutations to understand why they function less well.

"We still know very little about how motors are regulated. There are 45 kinesins expressed in human cells, but we only have an idea how the motors are activated for less than a handful of them. KIF1C is the fastest motor in neurons and the motor that is the most versatile - it delivers cargoes efficiently to all processes in a neuron, not just the axon."

Gaku Kudo of Hokkaido University and Elisabeth J. Cooper of the Arctic University of Norway have demonstrated that early snowmelt results in the spring ephemeral Corydalis ambigua flowering ahead of the emergence of its pollinator, the bumblebee.

Global warming has affected the phenology of diverse organisms, such as the timing of plant flowering and leafing, animal hibernation and migration. This is particularly so in cold ecosystems, increasing the risk of disturbing mutual relationships between living organisms. It could also affect the relationship between plants and insects that carry pollen, but few studies have been conducted and the subject remains largely unknown.

The researchers examined Corydailis ambigua growing in cold-temperature forests in Hokkaido in northern Japan, and bumblebees, which collect nectar from the flowers. Usually the bloom of the flowers and emergence of the bumblebees are in sync.

They monitored the plant and insect for 19 years in a natural forest of Hokkaido, recording the timing of snowmelt, flowering and emergence of bumblebees as well as the seed-set rate. In this way, they were able to observe how the snowmelt timing and ambient temperatures affect the local phenology.

Long-term monitoring revealed that snowmelt timing dictates when Corydailis ambigua flowers. The earlier the snowmelt, the earlier the flowering. The researchers also found that bumblebees, which hibernate underground during winter, become active when soil temperatures reach 6 C. When the snowmelt is early, flowering tends to occur before the bees emerge, creating a mismatch. The wider the mismatch, the lower the seed-set rate due to insufficient pollination.

A snow-removal experiment also showed similar trends backing up the finding that the phenological mismatch affects the seed production of spring ephemerals.

"Our study suggests the early arrival of spring increases the risk of disruption to the mutualism between plants and pollinators," says Gaku Kudo. "Studying how this phenological mismatch will affect the reproduction and survival of plants and insects could give us clues to the larger question ­­­­of how global warming is affecting the overall ecosystem."