Compared to those who never or rarely added salt, those who always added salt to their food had a 28% increased risk of dying prematurely. In the general population about three in every hundred people aged between 40 and 69 die prematurely. The increased risk from always adding salt to food seen in the current study suggests that one more person in every hundred may die prematurely in this age group.

In addition, the study found a lower life expectancy among people who always added salt compared to those who never, or rarely added salt. At the age of 50, 1.5 years and 2.28 years were knocked off the life expectancy of women and men, respectively, who always added salt to their food compared to those who never, or rarely, did.

The researchers, led by Professor Lu Qi, of Tulane University School of Public Health and Tropical Medicine, New Orleans, USA, say their findings have several public health implications.

“To my knowledge, our study is the first to assess the relation between adding salt to foods and premature death,” he said. “It provides novel evidence to support recommendations to modify eating behaviours for improving health. Even a modest reduction in sodium intake, by adding less or no salt to food at the table, is likely to result in substantial health benefits, especially when it is achieved in the general population.”

Assessing overall sodium intake is notoriously difficult as many foods, particularly pre-prepared and processed foods, have high levels of salt added before they even reach the table. Studies assessing salt intake by means of urine tests often only take one urine test and so do not necessarily reflect usual behaviour. In addition, foods that are high in salt are often accompanied by foods rich in potassium, such as fruit and vegetables, which is good for us [1]. Potassium is known to protect against the risk of heart diseases and metabolic diseases such as diabetes, whereas sodium increases the risk of conditions such as cancer, high blood pressure and stroke.

For these reasons, the researchers chose to look at whether or not people added salt to their foods at the table, independent of any salt added during cooking.

“Adding salt to foods at the table is a common eating behaviour that is directly related to an individual’s long-term preference for salty-tasting foods and habitual salt intake,” said Prof. Qi. “In the Western diet, adding salt at the table accounts for 6-20% of total salt intake and provides a unique way to evaluate the association between habitual sodium intake and the risk of death.”

The researchers analysed data from 501,379 people taking part in the UK Biobank study. When joining the study between 2006 and 2010, the participants were asked, via a touch-screen questionnaire, whether they added salt to their foods (i) never/rarely, (ii) sometimes, (iii) usually, (iv) always, or (v) prefer not to answer. Those who preferred not to answer were not included in the analysis. The researchers adjusted their analyses to take account of factors that could affect outcomes, such as age, sex, race, deprivation, body mass index (BMI), smoking, alcohol intake, physical activity, diet and medical conditions such as diabetes, cancer and heart and blood vessel diseases. They followed the participants for a median (average) of nine years. Premature death was defined as death before the age of 75 years.

As well as finding that always adding salt to foods was linked to a higher risk of premature death from all causes and a reduction in life expectancy, the researchers found that these risks tended to be reduced slightly in people who consumed the highest amounts of fruit and vegetables, although these results were not statistically significant.

“We were not surprised by this finding as fruits and vegetables are major sources of potassium, which has protective effects and is associated with a lower risk of premature death,” said Prof. Qi.

He added: “Because our study is the first to report a relation between adding salt to foods and mortality, further studies are needed to validate the findings before making recommendations.”

In an editorial to accompany the paper [2], Professor Annika Rosengren, a senior researcher and professor of medicine at the Sahlgrenska Academy, University of Gothenburg, Sweden, who was not involved with the research, writes that the net effect of a drastic reduction in salt intake for individuals remains controversial.

“Given the various indications that a very low intake of sodium may not be beneficial, or even harmful, it is important to distinguish between recommendations on an individual basis and actions on a population level,” she writes.

She concludes: “Classic epidemiology argues that a greater net benefit is achieved by the population-wide approach (achieving a small effect in many people) than from targeting high-risk individuals (a large effect but only achieved in a small number of people). The obvious and evidence-based strategy with respect to preventing cardiovascular disease in individuals is early detection and treatment of hypertension, including lifestyle modifications, while salt-reduction strategies at the societal level will lower population mean blood pressure levels, resulting in fewer people developing hypertension, needing treatment, and becoming sick. Not adding extra salt to food is unlikely to be harmful and could contribute to strategies to lower population blood pressure levels.”

A strength of Prof. Qi’s study is the large number of people included. It also has some limitations, which include: the possibility that adding salt to food is an indication of an unhealthy lifestyle and lower socio-economic status, although analyses attempted to adjust for this; there was no information on the quantity of salt added; adding salt may be related to total energy intake and intertwined with intake of other foods; participation in UK Biobank is voluntary and therefore the results are not representative of the general population, so further studies are needed to confirm the findings in other populations.

Prof. Qi and his colleagues will be carrying out further studies on the relation between adding salt to foods and various chronic diseases such as cardiovascular disease and diabetes. They also expect potential clinical trials to test the effects of a reduction in adding salt on health outcomes.

[1] An example of a typically salty food that also contains vegetables are tacos, which are often filled with beans and vegetables.

[2] “Salt — the sweet spot?,” by Annika Rosengren. European Heart Journal. doi:10.1093/eurheartj/ehac336

The study, published July 7, 2022 in PAIN, showed that mindfulness meditation interrupted the communication between brain areas involved in pain sensation and those that produce the sense of self. In the proposed mechanism, pain signals still move from the body to the brain, but the individual does not feel as much ownership over those pain sensations, so their pain and suffering are reduced.

“One of the central tenets of mindfulness is the principle that you are not your experiences,” said senior author Fadel Zeidan, PhD, associate professor of anesthesiology at UC San Diego School of Medicine. “You train yourself to experience thoughts and sensations without attaching your ego or sense of self to them, and we’re now finally seeing how this plays out in the brain during the experience of acute pain.”

On the first day of the study, 40 participants had their brains scanned while painful heat was applied to their leg. After experiencing a series of these heat stimuli, participants had to rate their average pain levels during the experiment.

Participants were then split into two groups. Members of the mindfulness group completed four separate 20-minute mindfulness training sessions. During these visits, they were instructed to focus on their breath and reduce self-referential processing by first acknowledging their thoughts, sensations and emotions but then letting them go without judging or reacting to them. Members of the control group spent their four sessions listening to an audio book.

On the final day of the study, both groups had their brain activity measured again, but participants in the mindfulness group were now instructed to meditate during the painful heat, while the control group rested with their eyes closed.

Researchers found that participants who were actively meditating reported a 32 percent reduction in pain intensity and a 33 percent reduction in pain unpleasantness.

“We were really excited to confirm that you don’t have to be an expert meditator to experience these analgesic effects,” said Zeidan. “This is a really important finding for the millions of people looking for a fast-acting and non-pharmacological treatment for pain.”

When the team analyzed participants’ brain activity during the task, they found that mindfulness-induced pain relief was associated with reduced synchronization between the thalamus (a brain area that relays incoming sensory information to the rest of the brain) and parts of the default mode network (a collection of brain areas most active while a person is mind-wandering or processing their own thoughts and feelings as opposed to the outside world).

One of these default mode regions is the precuneus, a brain area involved in fundamental features of self-awareness, and one of the first regions to go offline when a person loses consciousness. Another is the ventromedial prefrontal cortex, which includes several sub regions that work together to process how you relate to or place value on your experiences. The more these areas were decoupled or deactivated, the more pain relief the participant reported.

“For many people struggling with chronic pain, what often affects their quality of life most is not the pain itself, but the mental suffering and frustration that comes along with it,” said Zeidan. “Their pain becomes a part of who they are as individuals — something they can’t escape — and this exacerbates their suffering.”

By relinquishing the self-referential appraisal of pain, mindfulness meditation may provide a new method for pain treatment. Mindfulness meditation is also free and can be practiced anywhere. Still, Zeidan said he hopes trainings can be made even more accessible and integrated into standard outpatient procedures.

“We feel like we are on the verge of discovering a novel non-opioid-based pain mechanism in which the default mode network plays a critical role in producing analgesia. We are excited to continue exploring the neurobiology of mindfulness and its clinical potential across various disorders.”

Co-authors include: Gabriel Riegner, Valeria Oliva and William Mobley at UC San Diego, as well as Grace Posey at Tulane University and Youngkyoo Jung at University of California Davis.

The double-layered protein nanoparticle vaccine, which is constructed with a stabilized portion of the influenza virus (the hemagglutinin (HA) stalk), induced broadly reactive immune responses and conferred robust and sustained cross-immune protection against influenza B virus strains of both lineages. The findings are published in the journal Biomaterials.

Influenza epidemics pose a major threat to public health, and type B influenza has coincided with several severe flu outbreaks. About one-fourth of clinical infection cases are caused by influenza B viruses each year. Influenza B viruses are sometimes the dominant circulating strains during influenza seasons, such as the 2019-20 U.S. flu season when influenza B caused more than 50 percent of the infections.

Influenza B has two lineages that are genetically distinct and trigger different immune responses. Seasonal flu vaccines are developed with one or both lineages of influenza B viruses, but they’re limited by the ability of circulating strains to escape the immune system or vaccination. These vaccines are often ineffective because the variable portion of the influenza virus (the HA head) evolves. As a result, seasonal influenza vaccines need to be reformulated and updated frequently. To overcome these limitations, a universal influenza vaccine containing conserved parts of the virus and providing substantial broad cross-protection against diverse virus strains is urgently needed.

“In this study, we generated structure-stabilized HA stalk antigens from influenza B and fabricated double-layered protein nanoparticles as universal influenza B vaccine candidates,” said Dr. Baozhong Wang, senior author of the study and Distinguished University Professor in the Institute for Biomedical Sciences at Georgia State University. “We found that layered protein nanoparticles incorporated with structure-stabilized constant antigens have potential as a universal influenza vaccine with improved immune protective potency and breadth.”

The nanoparticle vaccine was tested in cell culture and in mice. Studies in cell culture found the protein nanoparticles were effectively taken up to activate dendritic cells, which are critical for inducing protective immune responses against pathogens. The vaccine was found to be safe, biocompatible, biodegradable and highly immunogenic in animals.

“Our next aim is to combine the influenza A nanoparticles from our previous study with the influenza B nanoparticles we have fabricated and tested here to create a multivalent universal influenza nanoparticle vaccine against both influenza A and B,” Wang said.

Co-authors of the study include Yufeng Song (first author), Wandi Zhu, Ye Wang, Lei Deng, Yao Ma, Chunhong Dong, Gilbert X. Gonzalez, Joo Kim, Lai Wei, Sang-Moo Kang and Bao-Zhong Wang of the Center for Inflammation, Immunity & Infection in the Institute for Biomedical Sciences at Georgia State. Deng is also affiliated with Hunan University in Changsha, China.

The study is funded by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institutes of Health (NIH).

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Scientists studied the behaviour of mute and whooper swans, to see how they used their time and energy.

Watching four key behaviours — aggression, foraging, maintenance (preening, cleaning and oiling feathers) and resting — they found a “trade-off” between aggression and rest, meaning that “increased aggression is achieved at the expense of resting.”

The study, by the University of Exeter and the Wildfowl & Wetlands Trust (WWT), could help managers of nature reserves design habitats that reduce the need for aggression.

“These swans use aggression if there’s competition over foraging areas,” said Dr Paul Rose, from the University of Exeter and WWT.

“Our findings show this this requires a trade-off, and that both species reduce resting time to allow for this aggression.

“This was the strongest trade-off we found, but there was also a trade-off for both species between foraging and resting.

“However, there was no apparent trade-off between some behaviours, such as aggression and foraging, and aggression and maintenance.”

The swans were observed via a live-streaming webcam at WWT Caerlaverock nature reserve in Scotland.

Whooper swans are migratory, and those observed in the study spend their winters at Caerlaverock.

Mute swans live there all year round, and Dr Rose said this means they can be more “flexible” in their behaviour because they don’t share the whooper swans’ urgent need to store fat ahead of migration.

“By providing enough foraging spots for the birds, we can reduce the need for aggression around desirable feeding spots, giving them more time to rest,” Dr Rose said.

“This can help to ensure that migratory species don’t ‘push out’ non-migratory species when they mix in the same wintering locations.

“Our study also demonstrates how remotely collected data can be used to investigate fundamental questions in behavioural research.”

Dr Kevin Wood, of WWT, said: “At WWT we get lots of questions from our visitors about the aggressiveness of swans.

“This new study helps us to understand how swans’ behaviour changes when they engage in their disputes.”

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This was what Dr. Dirk Wulff and Professor Rui Mata, researchers in the Faculty of Psychology at the University of Basel, set out to discover. “There is a lot of academic interest in the phenomenon of risk,” explains Dirk Wulff. “But disciplines such as psychology, sociology and economics define it in different ways.”

According to Wulff, little attention has been paid until now to the fact that the meaning of risk can differ from individual to individual depending on goals and life experience. He feels it is important to understand how different people think about risk in order, for example, to gauge attitudes to new technologies or societal challenges.

Risk links polar ends of the sentiment spectrum

To investigate this, the researchers have developed a new method based on word associations and an algorithmic process that maps the representation of risk for different groups and individuals. The researchers adopted a new approach, employing a snowball word association method. Participants were asked to name five things they associated with the term risk and then, in turn, five things they associated with these associations. Using this method, researchers surveyed a nationally representative sample of 1205 people, with equal representation of men and women and different age ranges.

An algorithm was used to generate a semantic network of risk from the 36,100 associations. It identified the following components: threat, fortune, investment, activity and analysis. The semantic cluster “threat” (danger, accident, loss, etc.) was the component most prominently associated with risk, closely followed by “fortune” (profit, game, adventure). “Up until now, studies have mostly focused on the negative components of risk and ignored the fact that it can also have positive associations,” Wulff comments.

The method is designed to map both individual and group-specific differences in risk perception. The psychologists investigated the differences between men and women and between different age groups. Overall, women and men and people of different ages appeared to share similar thoughts about risk. Nevertheless, there were some differences: a higher proportion of older people than younger people and a higher proportion of women than men associated risk more closely with threat and less with fortune.

Small differences between languages

The researchers also posed the question: Do people from different language regions think about risk in a similar way? To investigate this, they compared the semantic network of risk that emerged from the German survey group with those that resulted in two other languages — Dutch and English. There were some small differences in the frequency of associations. For example, in Dutch the term risk tended to be more closely associated with threat and in English more with fortune and finance. Overall, however, the results indicate that there are some universal correlations in risk representation that transcend language boundaries.

“Our study lays new foundations for examining the question of how people think about risk,” says Wulff. “It could play an important role in helping to provide a better understanding of how different social groups interpret risk, enabling risk communication strategies to be improved to combat social polarization.”

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Researchers have developed a two-step approach using whole exome sequencing to zero in on genes and pathways that predict whether cancer patients will respond to immunotherapy. The study, published in Nature Communications and conducted by researchers at New York University, Weill Cornell Medicine, and the New York Genome Center, illustrates how the use of whole exome sequencing can better predict treatment response than current laboratory tests.

“Can we better predict who will benefit from immunotherapy? Scientists have developed various biomarkers that help anticipate immunotherapy treatment response, but there’s still an unmet need for a robust, clinically practical predictive model,” said Neville Sanjana, assistant professor of biology at NYU, assistant professor of neuroscience and physiology at NYU Grossman School of Medicine, a core faculty member at New York Genome Center, and the study’s co-senior author.

Several biomarkers — including age, tumor type, and the number of mutations found in cancer cells, known as tumor mutational burden — are already known to correlate with responses to immunotherapy. Tumor mutational burden, which is calculated by analyzing a few hundred genes, is the most well-established predictor and is often used to determine a patient’s eligibility for immune checkpoint inhibitors.

If scientists look at a much larger portion of our genes, could that help to better predict which patients will respond to immunotherapy? Whole exome sequencing is a method for sequencing the part of the genome that codes for proteins — around 20,000 genes, or two percent of the genome — to look for mutations that may be involved in disease.

While whole exome sequencing is not widely used in cancer treatment, some recent studies of immunotherapies have started to include sequencing. These studies are small, but together can help illuminate the relationship between genomic factors and how patients respond to immunotherapy.

The researchers combined data from six previous immunotherapy studies of patients with melanoma, lung cancer, bladder cancer, and head and neck cancer. Whole exome sequencing was available for all participants, who were treated with an immune checkpoint inhibitor (either anti-PD-1 or anti-CTLA-4).

But even after combining the six studies, the number of patients — 319 in total — was still relatively small.

“The problem with a small study of only a few hundred people is a mismatch between the number of patients and the vast number of genes sequenced in whole exome sequencing. We’d ideally have a dataset with more patients than genes,” said Zoran Gajic, a graduate student in the Sanjana Lab, and the study’s first author.

To get around this problem, the researchers turned to a model called fishHook which distinguishes mutations that drive cancer from background mutations, or mutations that occur by chance but are not involved in cancer. The model corrects for a range of factors that affect the rates of background mutations — for instance, adjusting for the size of a gene, since larger genes are more likely to have mutations.

Using this model, the researchers employed a two-step approach: first, they looked at the sequencing from all patients to find any genes with a higher mutational burden than they would expect, adjusting for genomic factors like gene size or whether a particular piece of DNA is a known hotspot that tends to accumulate more mutations. This yielded six genes with suspiciously high mutational burdens.

Next, the researchers determined if any of these six genes were enriched in people who responded or did not respond to immunotherapy. Two of the genes — KRAS, a gene often mutated in lung cancer, and BRAF, the most commonly mutated gene in melanoma — were enriched in patients who responded to immunotherapy. In contrast, two other genes — TP53 and BCLAF1 — were enriched in those who did not respond to immunotherapy. BCLAF1 is not well studied, but these findings suggest that patients with BCLAF1 mutations are less likely to respond to immune checkpoint inhibitors.

Using the same two-step approach on collections of genes called pathways, the researchers determined that certain pathways (MAPK signaling, p53 associated, and immunomodulatory) also predicted immune checkpoint inhibitor response.

They then combined the four genes and three pathways with other predictive variables such as age, tumor type, and tumor mutational burden to create a tool they named the Cancer Immunotherapy Response CLassifiEr (CIRCLE). CIRCLE was able to better predict immunotherapy response by approximately 11% than tumor mutational burden alone. CIRCLE was also able to accurately predict cancer survival after immunotherapy.

“These results suggest that the use of broader diagnostics such as whole exome or even whole genome sequencing may significantly improve our ability to predict who will respond to immunotherapy — essentially, showing that more data does help to better predict treatment response,” said Marcin Imieliński, associate professor of computational genomics and associate professor of pathology and laboratory medicine at Weill Cornell Medicine, a core faculty member at the New York Genome Center, and the study’s co-senior author.

To validate their approach, the researchers tested CIRCLE on data from 165 additional cancer patients with whole exome sequencing who underwent treatment with immunotherapy and found that CIRCLE captured predictive information beyond that obtained from tumor mutational burden alone.

Future research will involve testing CIRCLE on larger cohorts of patient data, as the researchers anticipate that the model will improve with data from thousands of patients rather than hundreds. They also hope that with larger cohorts, they can begin to tease out which patients are likely to respond to different immunotherapies, given the growing number of treatments available.

“We envision that this two-step approach and use of whole exome sequencing will pave the way for better prognostic tools for cancer immunotherapy,” said Sanjana.

Additional authors include Aditya Deshpande of NYGC and Weill Cornell Medicine and Mateusz Legut of NYGC and NYU. The research was funded by the National Institutes of Health (U24-CA15020, DP2HG010099, R01CA218668, and GM136573), Sidney Kimmel Foundation, Brain and Behavior Foundation, Burroughs Wellcome Fund, Doris Duke Clinical Foundation, Starr Cancer Consortium, Melanoma Research Alliance, Hope Funds for Cancer Research, and startup funds from NYU, Weill Cornell Medicine, and the New York Genome Center.

Though engineering of biological systems is truly indispensable in biotechnology and synthetic biology, today machine learning has become useful in all fields of biology. However, it is obvious that application and improvement of algorithms, computational procedures made of lists of instructions, is not easily accessible. Not only are they limited by programming skills but often also insufficient experimentally-labeled data. At the intersection of computational and experimental works, there is a need for efficient approaches to bridge the gap between machine learning algorithms and their applications for biological systems.

Now a team at the Max Planck Institute for Terrestrial Microbiology led by Tobias Erb has succeeded in democratizing machine learning. In their recent publication in “Nature Communications,” the team presented together with collaboration partners from the INRAe Institute in Paris, their tool METIS. The application is built in such a versatile and modular architecture that it does not require computational skills and can be applied on different biological systems and with different lab equipment. METIS is short from Machine-learning guided Experimental Trials for Improvement of Systems and also named after the ancient goddess of wisdom and crafts Μῆτις, lit. “wise counsel.”

Less data required

Active learning, also known as optimal experimental design, uses machine learning algorithms to interactively suggest the next set of experiments after being trained on previous results, a valuable approach for wet-lab scientists, especially when working with a limited number of experimentally-labeled data. But one of the main bottlenecks is the experimentally-labeled data generated in the lab that are not always high enough to train machine learning models. “While active learning already reduces the need for experimental data, we went further and examined various machine learning algorithms. Encouragingly, we found a model that is even less dependent on data,” says Amir Pandi, one of the lead authors of the study.

To show the versatility of METIS, the team used it for a variety of applications, including optimization of protein production, genetic constructs, combinatorial engineering of the enzyme activity, and a complex CO₂ fixation metabolic cycle named CETCH. For the CETCH cycle, they explored a combinatorial space of 1025 conditions with only 1,000 experimental conditions and reported the most efficient CO₂ fixation cascade described to date.

Optimizing biological systems

In application, the study provides novel tools to democratize and advance current efforts in biotechnology, synthetic biology, genetic circuit design, and metabolic engineering. “METIS allows researchers to either optimize their already discovered or synthesized biological systems,” says Christoph Diehl, Co-lead author of the study. “But it is also a combinatorial guide for understanding complex interactions and hypothesis-driven optimization. And what is probably the most exciting benefit: it can be a very helpful system for prototyping new-to-nature systems.”

METIS is a modular tool running as Google Colab Python notebooks and can be used via a personal copy of the notebook on a web browser, without installation, registration, or the need for local computational power. The materials provided in this work can guide users to customize METIS for their applications.

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