Culture

As COVID-19 spread across the world, so did conspiracy theories and false information about the virus. This proliferation of misinformation--labeled an "infodemic" by the World Health Organization (WHO)--makes it difficult to identify trustworthy sources and can threaten public health by undermining confidence in science, governments, and public health recommendations.

The consequences of misinformation can be tragic: hundreds died and thousands were poisoned in Iran after consuming toxic methanol alcohol, falsely believing it could cure COVID-19.

In a new article in the Journal of Public Health Policy, legal scholars at NYU School of Global Public Health and the global health organization Vital Strategies identify five approaches countries have taken to address misinformation about COVID-19. Their tactics ranged from helpful practices like creating media campaigns sharing accurate information to harmful practices like suppressing whistleblowers and factual information, or disseminating disinformation (the intentional spread of false information) on their own. Several approaches criminalized expression, eliciting human rights concerns, given that international law protects freedom of expression.

"Governments can best address COVID-19 misinformation by disseminating factual information, protecting expression, ensuring strong protections for whistleblowers, and supporting an independent media environment," said study author Jennifer Pomeranz, assistant professor of public health policy and management at NYU School of Global Public Health.

"On top of the human rights concerns, overzealous prosecution of expression undercuts public health efforts by sowing mistrust between communities and their government," said study author Aaron Schwid, Director of Public Health Law at Vital Strategies.

To identify the range of methods governments used to address COVID-19 misinformation, the researchers conducted a content analysis of international media coverage. Using keywords including "misinformation," "disinformation," and "fake news," they analyzed hundreds of articles from February through May 2020.

The observed government actions, whether helpful or harmful, fell into five general categories:

Disseminating and increasing access to accurate information. In Taiwan, for example, the government held daily press conferences, distributed newsletters, developed media campaigns, promoted the Taiwan FactCheck Center (which rapidly verifies or debunks online information), and created "mask maps" to show where masks were available. Officials in South Africa and Nigeria worked with the popular social media platform WhatsApp to provide users with information on the virus and how to avoid infection.

Addressing commercial fraud so consumers are not led to purchase ineffective or unsafe products related to COVID-19. In the U.S., federal agencies issued warning letters to companies selling fake products, and state attorneys general brought actions against companies for violating state consumer protection acts. In the European Union, Europol seized 4.4 million units of fake pharmaceuticals and took down 2,500 links to fraudulent COVID-19 websites, marketplaces, and advertisements.

Restricting access to accurate information by refusing to release information, or preventing communication by journalists, health officials, and whistleblowers. This started in the early days of the pandemic, for example, when Chinese doctor Li Wenliang tried to warn fellow medical professionals about a novel virus and was silenced by authorities in Wuhan, and continued throughout 2020 in other countries.

Spreading misinformation or disinformation. In Madagascar, the president broadcast his support for an unproven herbal tea to cure COVID-19. President Trump was also a source of false information, suggesting that injecting disinfectant may kill the virus. "Disinformation spread by government officials is especially problematic because people generally expect governments to provide factual information," the authors write.

Criminalizing expression through prosecuting citizens and journalists under new and existing laws. For instance, Iraq's media regulator fined Reuters and suspended its license for reporting COVID-19 statistics in violation of its media broadcasting rules. In addition, emergency powers enacted in Botswana criminalized disseminating COVID-19 information that did not come from the WHO or the country's director of health services. "The criminalization of speech over the pandemic was not necessary or legitimate and undermined the right to free expression," the authors write.

The researchers stress that, in the face of a pandemic, governments should broadly protect expression and ensure a free and diverse media environment, as accurate reporting by journalists is one of the most powerful tools to reduce misinformation and disinformation. In contrast, censoring or penalizing expression can drive ideas underground, complicating efforts to correct or refute false information.

"Censorship--just like misinformation--undermines public health; both create a state of uncertainty, which motivates people to seek out information from less transparent sources," said Pomeranz.

"The solution to misinformation is for governments to embrace the freedom of expression and encourage more speech--not less--and increase their own dissemination of factual information," Schwid said.

The COVID-19 pandemic is straining health systems across the country, especially intensive care units. New research from the U.S. Department of Veterans Affairs, Regenstrief Institute and Indiana University School of Medicine shows that people treated in the ICU for COVID-19 are twice as likely to die when the ICU capacity is strained by the number of COVID-19 patients.

"These results demonstrate that patients with COVID-19 are more likely to die if they are admitted to an ICU during times with peak COVID-19 caseload," said Dawn Bravata, M.D., first author of the study. "We know that strain on hospital capacity has been associated with increased mortality under normal circumstances. This study provides evidence that the same is true during the current pandemic." Dr. Bravata is a core investigator in the VA Health Services Research and Development Center for Health Information and Communication, a Regenstrief research scientist and an IU School of Medicine professor.

The research team looked at the health outcomes of 8,516 COVID-19 patients who were admitted to 88 VA hospitals across the country from March through August 2020. The team measured the strain on the hospitals' critical care capacity by comparing the number of critically ill COVID-19 patients to the typical ICU bed count and the ICU caseload for each patient's stay in the hospital.

After analyzing the data, they found patients who were admitted during peak times of COVID-19 ICU demand were up to two times more likely to die than those admitted under less strained periods.

"Hospital and health leaders may want to consider tracking COVID-19 ICU demand as they coordinate COVID-19 admissions to improve patient outcomes and potentially save lives," said Dr. Bravata.

Chronic stress could be the prevailing condition of our time. In the short term, our jaws or stomachs may clench; in the long term, stress can lead to metabolic disease and speed up diseases of aging, as well as leading to more serious psychological disorders. The physical manifestations of stress originate in the brain, and they move along a so-called "stress axis" that ends in the adrenal glands. These glands then produce the hormone cortisol. When the stress axis is continually activated, changes occur in the cells and organs along the way, and the continual production of cortisol then substantially contribute the symptoms of chronic stress.

The stress response axis starts with the hypothalamus in the brain, moves through the pituitary right next to the brain and then on to the adrenal glands near the kidneys. Scientists at the Weizmann Institute of Science in Israel and the Max Planck Institute of Psychiatry in Germany used new technology to view the entire stress axis as it has never before been seen. Their findings, which were published in Science Advances may be relevant to a number of stress-related diseases from anxiety and depression to metabolic syndrome and diabetes.

The new study, led by postdoctoral fellow Dr. Juan Pablo Lopez in the joint neurobiology lab of Prof. Alon Chen in the Weizmann Institute of Science and the Max Planck Institute of Psychiatry, made use of a relatively new technique that allows researchers to identify differences across all cell types in a tissue. This method is something like identifying the individual fruits in a bowl of fruit salad - rather than the standard methods of turning that fruit salad into a "smoothie" and then trying to identify the average characteristics of all the fruits together. But in this case, the task was much more complex than separating the apples from oranges: Pablo Lopez and the team mapped the entire length of the stress axis, checking the activities of numerous single cells all along the route. And they conducted this analysis on two sets of mice - one unstressed and one exposed to chronic stress.

All in all, the team mapped 21,723 cells along the three points in that axis, and they compared their findings from the two sets of mice. They noted that as the stress message moved from one organ to the next, the gene expression in the cells and the tissues themselves underwent greater changes. The team found 66 genes that were altered between normal and stressed mice in the hypothalamus, 692 in the pituitaries and a whopping 922 in the adrenals. The adrenals are glands that can change their size visibly under chronic stress exposure, and it was here that the researchers noted the most significant alterations among the various cells.

The unprecedented resolution of the technique enabled the researchers to identify, for the first time, a subpopulation of adrenal cells that may play a crucial role in the stress response and adaptation. These were endocrine cells sitting in the outer layer, or adrenal cortex. Among other things, the team identified a gene, known as Abcb1b, and found it to be overexpressed in these cells under stress situations. This gene encodes a pump in the cell membrane that expels substances from the cell, and the scientists think it plays a role in the release of cortisol. "If extra stress hormones are created, the cell needs extra release valves to let those hormones go," says Pablo Lopez.

Are the findings in mice relevant to humans? In collaboration with researchers in university-based hospitals in the UK, Germany, Switzerland and the US, the scientists obtained adrenal glands that had been removed from patients to relieve the symptoms of Cushing's disease. Though the disease is the result of a growth on the pituitary, the result can be identical to chronic stress - weight gain and metabolic syndrome, high blood pressure and depression or irritability - so in some cases it is treated by removing the adrenal glands, thereby reducing the patients' stress hormone load. Indeed, the cells in these patients' adrenals presented a similar picture to those of the mice in the chronic stress group.

The gene they had identified, Abcb1, was known to the researchers from previous studies into the genetics of depression. It had been found that this gene is polymorphic - it has several variants - and that at least one version is tied to a higher risk for depression. The group analyzed the expression of this variant in blood tests taken from a group of subjects who suffer from depression and who were subjected to temporary stress. They found that certain variants do, indeed, affect the ways the adrenal glands deal with stress signals coming down the axis.

Chronic stress, of course, can ultimately affect every part of the body and open the door to numerous health issues. The new study, because it looks at the entire axis, on the one hand, and has mapped it down to the gene expression pattern of its individual cells, on the other, should provide a wealth of new information and insight into the mechanisms behind the stress axis. "Most research in this field has focused on chronic stress patterns in the brain," says Prof. Chen. "In addition to presenting a possible new target for treating the diseases that arise from chronic stress, the findings of this study will open new directions for future research."

Scientists say stable seafood consumption amongst the world's poorer coastal communities is linked to how local habitat characteristics influence fishing at different times of the year.

In the coastal communities of low-income countries, the seafood people catch themselves is often a main food source. In a new study, scientists focused on an often-overlooked type of fishing called gleaning: collecting molluscs, crabs, octopus and reef fish by hand close to shore.

"We surveyed 131 households in eight coastal communities on a small island off Timor-Leste," said study lead author Ruby Grantham from the ARC Centre of Excellence for Coral Reef Studies.

Grantham said even though gleaning is important for food security in rough weather--when other types of fishing often aren't possible--some households don't do it.

"It's not just a case of people fishing when they need to. Weather and coastal conditions make fishing activities, including gleaning, dangerous, unsuccessful or even impossible in some places at certain times of the year," Grantham said.

She said the findings illustrate the ways people interact with, and benefit from, coastal ecosystems. And how this varies between communities and seasons.

The study found the ability of households to glean in rough weather was influenced by the total area and type of shallow habitat close to the community.

"This highlights why we need context-specific understanding of dynamic coastal livelihoods and small-scale fisheries in particular," Grantham said.

"Even amongst these eight communities on the same small island we found distinct differences in how and when gleaning contributes to household fishing activities and as a source of subsistence seafood."

Co-author Dr David Mills, Research Leader for the WorldFish Country Program in Timor-Leste, said the research is important for the future management of coastal fisheries.

"In Timor-Leste, low-income households have few opportunities to access the high-quality nutrition available from seafood," Dr Mills said.

"We know that gleaning fisheries are really important for food security at particular times of the year," he said.

"And this detailed research will help us develop management approaches that keep fisheries sustainable while also ensuring seafood remains available to those who need it the most, when they need it the most."

Climate change is altering the world and its environments rapidly. People depend on their interactions with nature for many aspects of wellbeing. Understanding these interactions is critical for diagnosing vulnerabilities and building resilience, especially amongst coastal communities who depend directly on healthy oceans for food.

"The success of coastal livelihood strategies depends on a range of influences that are now, at best, poorly-understood," Grantham said.

"We wanted to explore how people interact with and benefit from coastal environments through time."

Grantham said a better understanding of the existing relationships between people and nature, as well as how these influence interactions between societies and local ecosystems, is crucial to legitimate environmental policy and management to ensure sustainable futures.

"We need to further consider the factors influencing how feasible and how desirable social-ecological interactions, like fishing, are across different seasons," she said.

"These insights of the fine scale dynamics in how people interact with coastal ecosystems through activities such as gleaning can help strengthen our understanding in research, decision-making and management in coastal areas exposed to environmental change."

(Boston)--There have been great advances in treating melanoma over the past five years, however, even with these treatments many patients quickly develop drug resistance and die from their disease. A new study from Boston University School of Medicine (BUSM) has discovered that a drug (YK-4-279) that was previously created to target one specific type of protein has much broader use against a family of proteins that act to promote melanoma.

"We find that this drug inhibited melanoma from becoming more aggressive in human cells and in experimental models. We also found a specific pathway that this drug acts through to be anti-cancer: inhibiting proteins that drive genes that promote cancer cell growth and metastasis," explained corresponding author Deborah Lang, PhD, associate professor of dermatology at BUSM.

Melanoma is an aggressive cancer type, with a high propensity for invasion and metastasis
early in the disease process. There are several factors that actively drive melanoma
progression including MET, a tyrosine kinase receptor overexpressed in melanoma and
implicated in tumor growth, invasion and drug resistance.

Researchers utilized human cells in culture to determine if there were impactful changes on pro-cancer behavior in these cells with or without the drug YK-4-279 and found a significant reduction in growth and movement of the cancer cells when using it. In addition, experimental models treated with the drug had significantly delayed or no progression to aggressive disease.

According to the researchers these findings create the opportunity for YK-4-279 to be an option for melanoma treatments, either singularly or in combination with other available therapeutics. "We find that this molecule disrupts the interaction of two factors known to regulate melanocytes and promote melanoma through gene regulation. This work may impact other systems where these factors play a role, such as in the nervous system and in pigmentary disorders."

There is a considerable gap in our current understanding of gift-giving because much of what has been studied has focused on gift-giving as an affair between just two consumers--a single giver and a recipient. Little is known about the impact other gifts have on the recipient of the gifts, even though some of the most common occasions for giving a gift, such as birthdays, the winter holidays, Mothers' and Fathers' Day, graduations, bridal showers, baby showers, bachelor and bachelorette parties, going away parties, and retirement parties, all typically involve a recipient receiving gifts from several different givers.

Researchers from Carnegie Mellon's Tepper School of Business and West Virginia University's John Chambers College of Business and Economics set out to understand gift giving dynamics in these settings and how a giver's and a recipient's evaluation of the giver's gift is influenced by the other gifts the recipient receives.

Across 12 studies examining the behavior of giving and receiving gifts in a multi-giver gift giving setting, the researchers demonstrated that recipients are consistently focused on the thoughtfulness of a gift. Gift givers, however, incorrectly assume recipients' focus is on relative gift value.

"We found that, often times, gift givers believe the recipient's focus is on relative gift value. For example, if I gave one bottle of cheap wine as a gift, but another person gave a bottle of expensive wine, I would incorrectly assume that the recipient would appreciate the gesture of giving the expensive bottle more than mine," said Jeff Galak, associate professor of marketing at the Tepper School of Business who co-authored the paper. "As a result of this misconception, when givers know beforehand others will be giving gifts, they are more likely to spend additional money upgrading their gifts or even to skip the gift-giving occasion altogether."

Christopher Olivola, associate professor of marketing at the Tepper School who co-authored the paper, added, "The next time you find yourself fixating on how your gift might compare to other gifts, consider instead how you would feel if you were in the recipient's shoes. If you are like most consumers, the gift giving gesture is what would really matter to you, and chances are the recipient feels the same."

Oncotarget recently published "Simvastatin is a potential candidate drug in ovarian clear cell carcinomas" which reported that based on previous studies, the authors assessed the anti-proliferative effect of simvastatin, a Rho GTPase interfering drug, in three OCCC cell lines: JHOC-5, OVMANA and TOV-21G, and one high-grade serous ovarian cancer cell line, Caov3. The authors used the Rho GTPase interfering drug CID-1067700 as a control.

All OCCC cell lines were more sensitive to single-agent simvastatin than the HGSOC cells, while all cell lines were less sensitive to CID-1067700 than to simvastatin.

Most treatments inhibited migration, while only simvastatin and CID-1067700 also disrupted actin organization in the OCCC cell lines.

Treatments with simvastatin consistently reduced c-Myc protein expression in all OCCC cell lines and displayed evidence of causing both caspase-mediated apoptotic cell death and autophagic response in a cell line dependent manner.

Conclusively, simvastatin efficiently controlled OCCC proliferation and migration, thus showing potential as a candidate drug for the treatment of OCCC.

"Simvastatin efficiently controlled OCCC proliferation and migration, thus showing potential as a candidate drug for the treatment of OCCC."

Dr. Ingrid Hedenfalk from The Lund University said, "Ovarian clear cell carcinoma (OCCC) is a subtype of epithelial ovarian cancer (EOC) accounting for 5–10% of cases diagnosed in Europe and America, while the incidence in Asia is reported to be higher (10–20%)."

The Oncotarget authors recently reported Rho GTPases and their associated pathways to be differentially expressed between OCCC compared to the other major EOC subtypes.

Rho GTPases have been studied as targets for cancer treatment in various settings due to their role in regulating key cellular functions including the maintenance of cytoskeletal integrity, cell migration and proliferation, but also in metastasis and progressive disease in many cancer types.

However, targeting Rho GTPases directly is challenging due to their high binding affinity for GTP/GDP, and indirect strategies such as targeting the localization of Rho GTPases to the cell membrane are promising alternatives.

CID-1067700 is a pan-GTPase inhibitor that inhibits binding of GTP/GDP and downstream binding of Rho GTPases to their targets and is used as a comparator for Rho GTPase interference as a druggable target in OCCC.

Based on the deregulated expression of both Rho GTPases and cytoskeletal pathways in primary human OCCC tumors in our previous work, they investigated the potential of simvastatin, a lipophilic statin, as a targeted treatment in OCCC cell lines with CID-1067700 as a comparator in the present study.

The Hedenfalk Research Team concluded in their Oncotarget Research Paper that while HGSOC has been studied intensively, OCCC remains a rare subtype with poor prognosis, but this study, although investigative, demonstrates a potential for simvastatin treatment in OCCC.

Simvastatin could act through Rho GTPase interference as simvastatin affects the cytoskeletal integrity of OCCC cells at levels which can be achieved in plasma.

However, the mechanism is different from Rho GTPase inhibition by CID-1067700.

Furthermore, caution should be given, as this data suggest that a combination with standard chemotherapy may elicit an antagonistic response.

Whether this is of clinical relevance for patients receiving statin treatment remains unclear and needs to be investigated further, but simvastatin holds promise as a potential drug candidate in OCCC and warrants further investigation in the clinical setting.

Sign up for free Altmetric alerts about this article

DOI - https://doi.org/10.18632/oncotarget.27747

Full text - https://www.oncotarget.com/article/27747/text/

Correspondence to - Ingrid Hedenfalk - Ingrid.Hedenfalk@med.lu.se

Keywords -
AKT isoform,
CSCs,
ABCG2,
drug resistance,
TNBCs

About Oncotarget

Oncotarget is a biweekly, peer-reviewed, open access biomedical journal covering research on all aspects of oncology.

To learn more about Oncotarget, please visit https://www.oncotarget.com or connect with:

SoundCloud - https://soundcloud.com/oncotarget
Facebook - https://www.facebook.com/Oncotarget/
Twitter - https://twitter.com/oncotarget
LinkedIn - https://www.linkedin.com/company/oncotarget
Pinterest - https://www.pinterest.com/oncotarget/
Reddit - https://www.reddit.com/user/Oncotarget/

Oncotarget is published by Impact Journals, LLC please visit http://www.ImpactJournals.com or connect with @ImpactJrnls

Journal

Oncotarget

DOI

10.18632/oncotarget.27747

COLUMBUS, Ohio - A new deep-learning model that can predict how human genes and medicines will interact has identified at least 10 compounds that may hold promise as treatments for COVID-19.

All but two of the drugs are still considered investigational and are being tested for effectiveness against hepatitis C, fungal disease, cancer and heart disease. The list also includes the approved drugs cyclosporine, an immunosuppressant that prevents transplant organ rejection, and anidulafungin, an antifungal agent.

The discovery was made by computer scientists, meaning much more work needs to be done before any of these medications would be confirmed as safe and effective treatments for people infected with SARS-CoV-2. But by using artificial intelligence to arrive at these options, the scientists have saved pharmaceutical and clinical researchers the time and money it would take to search for potential COVID-19 drugs on a piecemeal basis.

"When no one has any information on a new disease, this model shows how artificial intelligence can help solve the problem of how to consider a potential treatment," said senior author Ping Zhang, assistant professor of computer science and engineering and biomedical informatics at The Ohio State University.

The researchers noted in the paper that a few of the repurposing candidates the model generated have already been studied for their potential use in COVID-19 patients.

"Great minds think alike - some lead compounds identified by machine intelligence coincide with later discoveries by human intelligence," Zhang said.

The research is published today (Feb. 1) in Nature Machine Intelligence.

Zhang and colleagues had completed the model's design in May 2020, just as the first papers detailing how COVID-19 patients' genes responded to the virus were published. The new information provided an important test for the computer model, which the researchers call "DeepCE" - pronounced "Deep Sea."

To make predictions about how genes and medicines will interact and yield drug repurposing candidates, DeepCE relies on two primary sources of publicly available data: L1000, a National Institutes of Health-funded repository of human cell-line data showing how gene expression changes in response to drugs, and DrugBank, which contains information on the chemical structures and other details on about 11,000 approved and investigational drugs.

L1000 displays side-by-side cell-line comparisons of standard gene expression activity with gene expression changes produced by interactions with specific drugs. The cell lines represent diseases, such as melanoma, and organs, like kidneys and lungs. It is an ongoing project, with data being added as experiments in animals or humans supplement the gene expression profiles produced in cell-line experiments.

The Ohio State researchers trained the DeepCE model by running all of the L1000 data through an algorithm against specific chemical compounds and their dosages. To fill in data gaps, the model converts chemical compound descriptions into figures, allowing for automatic consideration of their separate components' effects on genes. And for genes not represented in L1000, the team used a deep learning approach called an "attention mechanism" to increase the model's "learned" sample of gene-chemical compound interactions, which improves the framework's performance.

"This way, the output demonstrates multitask learning - we can predict gene expression values for new chemicals not from one cell to one cell, but automatically predict the role of a drug on different cell lines and different genes," said Zhang, who leads the Artificial Intelligence in Medicine Lab and is a core faculty member in the Translational Data Analytics Institute at Ohio State. "We can use the computer to simulate drug-induced gene expression. This provides real value."

"The story should stop here - this is where we were during spring break. But then COVID-19 arrived, and we hoped our research could help, so we did a special case study for COVID-19 drug repurposing."

The team applied DeepCE's gene expression prediction matrix - focusing on data from lung and airway cell lines and the entire DrugBank catalog of compounds - to the genetic information provided from the early COVID-19 papers and additional government data. The COVID-19 data demonstrated how human gene expression had responded to being infected with SARS-CoV-2, creating a "disease signature."

"Based on the known gene expression changes that have occurred and been identified with known drugs, we apply that to the gene expression in question - in this case, compounds that are being studied but are not yet experimented in L1000. We put such predicted 'drug signatures' against the COVID-19 patient profiles on a population level," Zhang said.

"Once you can identify both signatures, the job is easy. Wherever we find the disease and a drug show opposite gene expression profiles, suggesting the drug would reverse the effects of the disease, you have found a drug that may treat the disease."

This model complements a drug-repurposing model Zhang described in a recent paper that simulates clinical trials using observational clinical data.

"I want to put together a research agenda using all the different data resources for drug repurposing and drug-disease associations from multiple perspectives and connect with researchers who can collaborate with us to find new drugs for diseases - including unknown diseases," Zhang said.

Over the past century, a wide variety of models have emerged to explain the complex behaviours which unfold within atomic nuclei at low energies. However, these theories bring up deep philosophical questions regarding their scientific value. Indeed, traditional epistemological tools have been rather elaborated to account for a unified and stabilised theory rather than to apprehend a plurality of models. Ideally, a theory is meant to be reductionist, unifying and fundamentalist. In view of the intrinsic limited precision of their prediction and of the difficulty in assessing a priori their range of applicability, as well as of their specific and disconnected character, traditional nuclear models are necessarily deficient when analysed by means of standard epistemological interpretative frameworks.

The theoretical construct brought by so-called effective field theories allows a better articulation of the tension between the natural reductionist force at play in physical sciences and the need to account for phenomena emerging at various energy/spatial scales in complex systems such as the atomic nucleus. Because of the various scales involved, a tower or tree-like hierarchies of inter-related effective field theories is inherently necessary and thus needs to be formulated and articulated. This is mandatory to develop a coherent, efficient and salient description of the zoology of nuclear phenomena.

This special issue, published in EPJ A, presents a coherent collection of work by theoretical experts from around the world regarding the use of effective field theories. Several unanswered questions are addressed and clarified, leading to detailed assessments of the philosophical foundations of effective field theories. The collected studies show how these ideas become relevant in low-energy nuclear systems, as well as in biological and gravitational systems - which have comparable levels of underlying complexity. The outcomes of this research pave the way for new advances in the wider-field of low-energy nuclear physics.

Theoretical physicists of the PRISMA+ Cluster of Excellence at Johannes Gutenberg University Mainz are working on a theory that goes beyond the Standard Model of particle physics and can answer questions where the Standard Model has to pass - for example, with respect to the hierarchies of the masses of elementary particles or the existence of dark matter. The central element of the theory is an extra dimension in spacetime. Until now, scientists have faced the problem that the predictions of their theory could not be tested experimentally. They have now overcome this problem in a publication in the current issue of the European Physical Journal C.

Already in the 1920s, in an attempt to unify the forces of gravity and electromagnetism, Theodor Kaluza and Oskar Klein speculated about the existence of an extra dimension beyond the familiar three space dimensions and time - which in physics are combined into 4-dimensional spacetime. If it exists, such a new dimension would have to be incredible tiny and unnoticeable to the human eye. In the late 1990s this idea has seen a remarkable renaissance, when it was realized that the existence of a fifth dimension could resolve some of the profound open questions of particle physics. In particular, Yuval Grossman of Stanford University and Matthias Neubert, then a professor at Cornell University, showed in a highly cited publication that the embedding of the Standard Model of particle physics in a 5-dimensional spacetime could explain the so far mysterious patterns seen in the masses of elementary particles.

Another 20 years later, the group of Matthias Neubert - since 2006 on the faculty of Johannes Gutenberg University in Mainz (Germany) and spokesperson of the PRISMA+ Cluster of Excellence - made another unexpected discovery: they found that the 5-dimensional field equations predicted the existence of a new, heavy particle with similar properties as the famous Higgs boson but a much heavier mass - so heavy, in fact, that it cannot be produced even at the highest-energy particle collider in the world: the Large Hadron Collider (LHC) at the European Center for Nuclear Research CERN near Geneva (Switzerland). "It was a nightmare", recalls Javier Castellano Ruiz, a PhD student involved in the research, "we were excited by the idea that our theory predicts a new particle, but it appeared to be impossible to confirm this prediction in any foreseeable experiment."

The detour through the fifth dimension

In a recent paper published in the European Physical Journal C, the researchers found a spectacular resolution to this dilemma. They discovered that their proposed particle would necessarily mediate a new force between the known elementary particles (our visible universe) and the mysterious dark matter (the dark sector). Even the abundance of dark matter in the cosmos, as observed in astrophysical experiments, can be explained by their theory. This offers exciting new ways to search for the constituents of the dark matter - literally via a detour through the extra dimension - and obtain clues about the physics at a very early stage in the history of our universe, when the dark matter was produced. "After years of searching for possible confirmations of our theoretical predictions, we are now confident that the mechanism we have discovered would make the dark matter accessible to forthcoming experiments, because the properties of the new interaction between ordinary matter and dark matter - which is mediated by our proposed particle - can be calculated accurately within our theory" says Matthias Neubert, head of the research team. "In the end - so our hope - the new particle may be discovered first through its interactions with the dark sector." This example nicely illustrates the fruitful interplay between experimental and theoretical basic science - a hallmark of the PRISMA+ Cluster of Excellence.

Decoy protein intercepts spike of coronavirus

Virus prevented from infecting human cells

Protein may be new way to treat and prevent COVID-19

CHICAGO --- Northwestern Medicine scientists have developed a new protein that acts as a trickster to neutralize the COVID-19 infection in a human kidney organoid, a miniature organ made from stem cells in the lab.

The protein is a variant of ACE2 (angiotensin converting enzyme-2), the receptor the coronavirus uses to enter and infect human cells. The modified protein intercepts the S spike of the coronavirus and fools it into binding to it rather than the real ACE2 receptor in cell membranes.

"The idea was to administer our protein to intercept the coronavirus before it gets to the natural receptor in the cell membranes," said lead study author Dr. Daniel Batlle, a professor of medicine at Northwestern University Feinberg School of Medicine and a Northwestern Medicine physician. "To make it more efficacious, we modified the ACE2 protein to extend its duration of action from hours to days. That feature will be critical for patient use."

The study was published Feb. 1 in the Journal of the American Society of Nephrology.

The findings are proof of concept that the ACE2 protein will be effective in preventing and treating COVID-19 infection in humans, said Batlle, also the Earle, del Greco, Levin Professor of Nephrology and Hypertension at Feinberg.

"While widespread vaccination is the best way to combat the COVID-19 pandemic, there will always be a need for therapies for prevention and treatment of people who were not vaccinated or for whom the vaccine was not fully effective," Batlle said.

The protein was tested in the human kidney organoid because rodents are resistant to infection by the coronavirus causing COVID-19.

Batlle's lab has studied ACE2 for many years as part of a potential treatment for kidney disease. Batlle and study co-author Dr. Jan Wysocki, research assistant professor of medicine at Feinberg,
have bioengineered novel ACE2 variants licensed to Northwestern University which they believe can be adapted for COVID-19 therapy by intercepting the coronavirus and preventing it from attaching to the natural ACE2 receptor in the membrane of the cell.

The next steps involve the planning of safety studies needed before Investigational New Drug approval for future studies in patients with COVID-19.

Social media is increasingly used to spread fake news. The same problem can be found on the capital market - criminals spread fake news about companies in order to manipulate share prices. Researchers at the Universities of Göttingen and Frankfurt and the Jožef Stefan Institute in Ljubljana have developed an approach that can recognise such fake news, even when the news contents are repeatedly adapted. The results of the study were published in the Journal of the Association for Information Systems.

In order to detect false information - often fictitious data that presents a company in a positive light - the scientists used machine learning methods and created classification models that can be applied to identify suspicious messages based on their content and certain linguistic characteristics. "Here we look at other aspects of the text that makes up the message, such as the comprehensibility of the language and the mood that the text conveys," says Professor Jan Muntermann from the University of Göttingen.

The approach is already known in principle from its use by spam filters, for example. However, the key problem with the current methods is that to avoid being recognised, fraudsters continuously adapt the content and avoid certain words that are used to identify the fake news. This is where the researchers' new approach comes in: to identify fake news despite such strategies to evade detection, they combine models recently developed by the researchers in such a way that high detection rates and robustness come together. So even if "suspicious" words disappear from the text, the fake news is still recognised by its linguistic features. "This puts scammers into a dilemma. They can only avoid detection if they change the mood of the text so that it is negative, for instance," explains Dr Michael Siering. "But then they would miss their target of inducing investors to buy certain stocks."

The new approach can be used, for example, in market surveillance to temporarily suspend the trading of affected stocks. In addition, it offers investors valuable information to avoid falling for such fraud schemes. It is also possible that it could be used for criminal prosecutions in the future.

The adoption of recommended changes in concussion management led to a reduction in the length of symptoms among 11- to 18-year-old athletes with first-time, sports-related concussions, according to new research in the Journal of Osteopathic Medicine. These outcomes support the widespread adoption of the updated concussion guidelines.

Researchers conducted a retrospective review of the medical records of athletes who sustained a concussion between 2016 and 2018 and were treated by a physician who used the revised approach to concussion management. They then compared the data with a previously published data set from athletes who sustained a concussion between 2011 and 2013 and whose physicians followed older guidelines for concussion management. A total of 110 male and 72 female athletes met the study's eligibility criteria.

The recommended changes in care include advocating for early activity, recognizing pre-existing conditions, and educating athletes about concussion recovery. Following implementation of the guidelines at the clinic, athletes of both genders experienced a significantly shorter median duration of concussion symptoms. Male athletes reported a duration of symptoms that dropped from 11 days to 5 days, while female athletes' symptom duration dropped from 28 to 7 days.

Active rest

"The most significant change in care involved a shift from strict rest or cocoon therapy to a return to low-intensity physical or cognitive activity after 24 to 48 hours," said the study's lead researcher, John Neidecker, DO, a sports concussion specialist in Raleigh, North Carolina. "Our results show active rest dramatically improved recovery times among young athletes with first-time concussions."

Active rest involves light movement that has no risk of head trauma. Patients should gradually increase their level of physical and mental activity under the guidance of a physician.

Pre-existing conditions

When comparing the 2011-2013 and 2016-2018 data sets, researchers found a higher incidence of pre-existing problems for patients in the newer data set, which suggests that better identification of these conditions led to improved patient outcomes.

"If diagnosis of a pre-existing condition has never been given, patients cannot be expected to report one during our concussion assessment," said Dr. Neidecker. "This is especially true in the adolescent age group, as some may have a condition that they are not aware of yet. This makes screening for preexisting conditions more complex, yet even more essential for this age group."

For example, motion sickness from car rides or intolerance to 3D movies could indicate a pre-existing vision disorder that was previously undiagnosed. Asking parents about preinjury personality and demeanor may uncover pre-existing anxiety, which can also impact recovery.

"This more individualized, osteopathic approach in screening the athletes' past medical history helped us identify health issues that may have been overlooked in the past," said Dr. Neidecker. "By focusing on the diagnosis and treatment of pre-existing health conditions, we can more effectively tailor treatment."

Catastrophizing the injury

In the 2011-2013 data set, concussion knowledge was significantly less, and physician counseling often had a much more cautious or, at times, ominous tone, according to Dr. Neidecker. Following the revised guidelines, physicians in the clinic adopted a more optimistic outlook when speaking with patients. This adjustment in communication may have contributed to patients reporting fewer concussion symptoms at an earlier date.

"Simply put, making clinic visits more positive and less anxiety-provoking supports patient recovery," said Dr. Neidecker. "Whereas catastrophizing an event, particularly with an adolescent population, may exacerbate symptoms."

Early patient counseling and education about concussions and the typical course of symptom resolution may mitigate unnecessary worry. This counseling may be even more critical to patients with pre-existing anxiety.

NEW YORK, NY (Feb. 1, 2021)--Errors in the way chromosomes are packed into antibody-producing B cells appear to play a role in the development of B cell-related blood cancers, according to a new study by researchers at Columbia University Vagelos College of Physicians and Surgeons.

The findings could lead to new biomarkers for predicting the onset of these cancers and to a new class of cancer therapies that prevent or correct harmful changes in genome architecture.

The study was published online Feb. 1 in the journal Nature Genetics.

Antibodies are made by immune cells called B cells through a series of carefully controlled chromosome rearrangements and "good" mutations that allow the cell to make a wide array of different antibodies. "Although these changes are essential for generating the vast diversity of antibodies, there is a risk that 'bad' mutations will occur and lead to B cell-derived cancers," says study leader Uttiya Basu, PhD, professor of microbiology & immunology at Columbia University Vagelos College of Physicians and Surgeons.

Basu's new study shows that a protein called DIS3 is critical in maintaining genomic architecture and preventing uncontrolled chromosome rearrangements that have the potential to cause cancer.

These new studies with mice reveal that B cells become destabilized, have more detrimental chromosomal rearrangements, and are less capable of generating specific antibodies when DIS3 is missing.

DIS3 stabilizes chromosomes by preventing the buildup of noncoding RNAs (RNAs that do not code for proteins), the study also reveals.

"The massive accumulation of these RNAs perturbs the way the genome is packed in the nucleus and leaves the genome vulnerable to DNA translocations," Basu says.

Because DIS3 mutations are common in people with multiple myeloma--a type of blood cancer that stems from B cells--the study may explain why these mutations contribute to the disease.

"It's possible that multiple myeloma treatment could require therapeutic interventions that prevent RNA accumulation and its effect on genome architecture," says Basu.

Future studies will focus on how genome architectural changes could be used to predict the onset of various B cell malignancies, which sometimes start out as relatively benign conditions.

The study also brings to light the role of genomic architecture maintenance for the prevention of cancer and the role of noncoding RNA in the normal production of antibodies.

Winter survival of honey bee colonies is strongly influenced by summer temperatures and precipitation in the prior year, according to Penn State researchers, who said their findings suggest that honey bees have a "goldilocks" preferred range of summer conditions outside of which their probability of surviving the winter falls.

The results of this study, which used several years of survey data provided by the Pennsylvania State Beekeeper's Association and its members, enabled the development of a tool for forecasting honey bee winter survival to support beekeepers' management decisions, the researchers said.

Honey bees contribute more than $20 billion in pollination services to agriculture in the United States and generate another $300 million annually in honey production for U.S. beekeepers, noted the study's lead author, Martina Calovi, postdoctoral researcher in the Earth and Environmental Systems Institute in the College of Earth and Mineral Sciences.

"However, winter colony mortality greatly reduces the economic and ecosystem contributions of honey bees, which suffered estimated overwintering mortality rates of more than 53% from 2016 to 2019 in the United States," Calovi said. "Although winter mortality is known to vary regionally, the landscape and weather factors underlying this variation are poorly understood."

Honey bee colonies are not dormant during the winter, Calovi pointed out. The bees remain active and maintain the hive temperature between 75 and 93 degrees Fahrenheit by forming a thermoregulating cluster, in which they organize into a tight ball and vibrate their flight muscles to generate heat, allowing the colony to survive when outside temperatures fall below 50 F. This enables them to survive long periods of cold temperatures.

"During the winter, the colony stops foraging for nectar and pollen and relies on its existing food stores, collected during the plant growing season," she said. "Rearing of new bees also ceases, and the colony depends on the survival of a long-lived cohort of bees that is produced in the autumn."

As a result, any factors that limit the colony's ability to store adequate amounts of food during the summer and fall, that undermine effective thermoregulation during the winter, or that reduce the life span of overwintering bees can contribute to colony mortality, said co-author Christina Grozinger, Publius Vergilius Maro Professor of Entomology in the College of Agricultural Sciences.

Among these factors, she said, are weather conditions that influence the availability of forage, the bees' ability to thermoregulate in the winter, and the amount of time before bees are able to initiate brood rearing in the spring. Other dynamics include beekeeper management practices that affect parasite and pathogen loads -- particularly control of Varroa mites that transmit viruses -- and forage quality and pesticide exposure due to the surrounding land use.

"We need to consider all of these factors when modeling and predicting honey bee winter survival," Grozinger said, "and that requires large data sets that span multiple types of habitats, microclimates and years."

To collect beekeeper management and winter survival data, the researchers collaborated with the Pennsylvania State Beekeepers Association, which conducts an annual winter-loss survey of beekeepers across the state. The association provided data from this survey covering three winters and containing information about 1,429 honey bee colonies within 257 apiaries.

For each reported apiary location, the researchers compiled data on weather and topographic variables that determine temperature and moisture conditions, as well as landscape variables that influence the availability of floral resources and insecticide exposure risk. The team included agronomic measures such as consecutive dry days and growing degree days, which is a measure of heat accumulation used to estimate growth and development of plants and insects during the growing season.

These diverse and complex datasets were integrated and analyzed using Random Forest, a machine learning algorithm that merges the output of multiple variables to reach a single result.

As the research team reported recently in Scientific Reports, a critical factor influencing winter survival was management of Varroa mites. Beekeepers that did manage Varroa mite levels, however, still experienced high losses (25-60% mortality).

For these beekeepers, the four most important variables in predicting winter colony survival were growing degree days, maximum temperature of the warmest quarter, precipitation during the warmest quarter and precipitation during the wettest quarter. Of these, the strongest predictor was growing degree days in the prior summer, which researchers said may relate to floral resource availability.

"The importance of weather conditions in predicting winter bee survival is quite clear from our analysis," said co-author Sarah Goslee, ecologist with the Pasture Systems and Watershed Management Research Unit of the U.S. Department of Agriculture's Agricultural Research Service.

"Our nuanced analysis of 36 weather and other environmental variables found adverse effects of both too-cool and too-hot summers," she said. "This model can be used to predict the probability of overwintering success, both for the current year and in projected future climate change scenarios."

The model was used to develop a real-time tool to predict honey bee survival probability as a function of growing degree days, said Grozinger, who is director of Penn State's Center for Pollinator Research. The tool, "BeeWinterWise," has been incorporated into Beescape, a decision support system spearheaded by the center that is used by beekeepers and technical advisors.

"We believe this is the first study on honey bee overwintering survival that combines weather, topography and land-use factors," said Calovi. "Our results demonstrate both the predictive power of weather variables on honey bee overwintering survival, and the value of addressing this type of question with machine learning methods."