Publisher Health

Researchers have discovered a previously unknown mechanism by which bacteria share their genetic material through virus parasites. The insights could help scientists to better understand how bacteria rapidly adapt and evolve, and how they become more virulent and resistant to antibiotics.
n a study published today in Cell, one of the most prominent peer-reviewed scientific journals in the field of Biochemistry & Molecular Biology, scientists from the National University of Singapore (NUS) and Imperial College London have discovered a new way by which bacteria transmit their genes, enabling them to evolve much faster than previously understood. Led by Assistant Professor John Chen from the Department of Microbiology and Immunology and the Infectious Diseases Translational Research Programme at the NUS Yong Loo Lin School of Medicine (NUS Medicine), the insights could help scientists to better understand how pathogenic bacteria evolve and become increasingly virulent and resistant to antibiotics.
The ability to share genetic material is the major driver of microbial evolution because it can transform a benign bacterium into a deadly pathogen in an instant. Phages, the viruses of bacteria, can act as conduits that allow genes to transfer from one bacterium to another by a process known as genetic transduction. Currently, there are three known mechanisms of transduction: generalised, specialised, and lateral. Lateral transduction was also discovered by the same groups of researchers in 2018, and it is at least one thousand times more efficient than the next most powerful mechanism, generalised transduction.
The new process is termed lateral cotransduction, and the architects behind this new frequency and speed in bacterial evolution are the Staphylococcus aureus pathogenicity islands (SaPIs), which are selfish DNA elements that exploit and parasitise phages and are commonly found integrated into the chromosomes of S. aureus isolates. S. aureus is a type of bacteria that can cause Staph infections in humans and animals. While it primarily manifests as skin infections, it can become life-threatening if it spreads to the bloodstream and infects organs, bones, or joints.
Professor José R. Penadés from the Department of Infectious Diseases, and Director for the Centre for Bacterial Resistance Biology at Imperial College London, said, “This breakthrough sheds light on a novel pathway through which bacteria evolve. Given the alarming surge of antibiotic-resistant superbugs, comprehending the mechanisms driving bacterial evolution becomes increasingly critical.”
This newly discovered process, lateral cotransduction, rivals lateral transduction in terms of efficiency but surpasses the latter in versatility and complexity. While lateral transduction is only known to occur when dormant phages within bacterial genomes become reactivated and initiate reproduction in the lytic cycle, lateral cotransduction can occur during the reactivation process and the infection of new bacterial cells.
Additionally, unlike phages that sacrifice their genes to transmit bacterial host DNA, SaPIs can transfer themselves completely intact with bacterial DNA through lateral cotransduction. This remarkable capability enables them to perpetually repeat the process, making them significantly more potent and efficient in transmitting bacterial genes.

Osaka Metropolitan University. “Tropical plant native to China reveals antiobesity potential: Scientists discover that Mallotus furetianus, native to Hainan Island, China, has antiobesity effects.” ScienceDaily. ScienceDaily, 4 August 2023. .
Osaka Metropolitan University. (2023, August 4). Tropical plant native to China reveals antiobesity potential: Scientists discover that Mallotus furetianus, native to Hainan Island, China, has antiobesity effects. ScienceDaily. Retrieved August 4, 2023 from www.sciencedaily.com/releases/2023/08/230804123740.htm
Osaka Metropolitan University. “Tropical plant native to China reveals antiobesity potential: Scientists discover that Mallotus furetianus, native to Hainan Island, China, has antiobesity effects.” ScienceDaily. www.sciencedaily.com/releases/2023/08/230804123740.htm (accessed August 4, 2023).

AI tools that quickly and accurately create detailed narrative reports of a patient’s CT scan or X-ray can greatly ease the workload of busy radiologists.
Instead of merely identifying the presence or absence of abnormalities on an image, these AI reports convey complex diagnostic information, detailed descriptions, nuanced findings, and appropriate degrees of uncertainty. In short, they mirror how human radiologists describe what they see on a scan.
Several AI models capable of generating detailed narrative reports have begun to appear on the scene. With them have come automated scoring systems that periodically assess these tools to help inform their development and augment their performance.
So how well do the current systems gauge an AI model’s radiology performance?
The answer is good but not great, according to a new study by researchers at Harvard Medical School published Aug. 3 in the journal Patterns.
Ensuring that scoring systems are reliable is critical for AI tools to continue to improve and for clinicians to trust them, the researchers said, but the metrics tested in the study failed to reliably identify clinical errors in the AI reports, some of them significant. The finding, the researchers said, highlights an urgent need for improvement and the importance of designing high-fidelity scoring systems that faithfully and accurately monitor tool performance.
The team tested various scoring metrics on AI-generated narrative reports. The researchers also asked six human radiologists to read the AI-generated reports.

A study from Ann & Robert H. Lurie Children’s Hospital of Chicago has shown that prenatal diagnosis, or diagnosis before a baby is born, is associated with earlier surgery for babies with congenital heart defects, the most common birth defects affecting nearly 1% of all live births. The association was demonstrated for critical defects (when heart surgery is required before the infant leaves the hospital) and certain types of noncritical defects, which constitute about 75% of all congenital heart defects.
The benefits of prenatal diagnosis of congenital heart defects for babies has been debated. With the knowledge that earlier heart surgery is often better for a child’s development, investigators at Lurie Children’s have found that prenatally diagnosed babies born with critical heart disease had surgery on average one week sooner than those with postnatal diagnosis. Surgery for babies with prenatally diagnosed noncritical cardiac defects occurred anywhere from two to 12 months sooner. Results were published in the journal Circulation: Cardiovascular Quality and Outcomes.
“Our study quantifies the tremendous importance of prenatal diagnosis for infants with congenital heart disease,” said lead author Joyce Woo, MD, MS, cardiologist at Lurie Children’s and Assistant Professor of Pediatrics and Medical Social Sciences at Northwestern University Feinberg School of Medicine. “For infants with critical disease especially, getting surgery a week earlier can make a big difference in the development of the brain and other organs. Earlier surgery for certain types of noncritical congenital heart disease can also prevent poor outcomes, such as heart failure. Our findings emphasize that prenatal diagnosis is crucial to optimize surgical timing and the long-term health of the baby. Prenatal diagnosis needs to be equitably accessible to all pregnant people.”
Dr. Woo and colleagues analyzed a cohort of 1,131 patients with congenital heart defects, aged 0-9 years, who received their initial cardiac surgery at Lurie Children’s between 2015 and 2021. Nearly half of these patients had prenatal diagnosis. After accounting for demographics, comorbidities and surgical complexity, the average age at surgery was significantly younger in infants with prenatally versus postnatally diagnosed critical and noncritical congenital heart disease. Infants with one of the most common types of noncritical disease, called atrial septal defects, had surgery about a year sooner.
“Our study shows that the best care for kids starts with prenatal diagnosis. More research is needed to identify and overcome the barriers to prenatal diagnosis,” said Dr. Woo. “These can include social barriers such as distance to care, lack of childcare, or inability to take time off from work. We need a better understanding of these factors in order to provide the highest quality care to babies born with cardiac defects, and their families.”
Research at Ann & Robert H. Lurie Children’s Hospital of Chicago is conducted through Stanley Manne Children’s Research Institute. The Manne Research Institute is focused on improving child health, transforming pediatric medicine and ensuring healthier futures through the relentless pursuit of knowledge. Lurie Children’s is a nonprofit organization committed to providing access to exceptional care for every child. It is ranked as one of the nation’s top children’s hospitals by U.S. News & World Report. Lurie Children’s is the pediatric training ground for Northwestern University Feinberg School of Medicine.

Hospital-acquired infections are often hard to treat because the corresponding pathogens become increasingly resistant against antibiotics. The bacterium Acinetobacter baumannii is a growing threat, and there is great pressure to devise novel therapeutic approaches to combat it. Bioinformaticians from Goethe University Frankfurt and Research Unit FOR2251 of the German Research Foundation have now detected an unexpectedly wide diversity of certain cell appendages in A. baumannii that are associated with pathogenicity. This could lead to treatment strategies that are specifically tailored to a particular pathogen.
Each year, over 670,000 people in Europe fall ill because of antibiotic-resistant pathogens, and 33,000 die from the infections. Especially feared are pathogens with resistances against multiple, or even all, known antibiotics. One of these is the bacterium Acinetobacter baumannii, feared today above all as the “hospital superbug”: According to estimates, up to five percent of all hospital-acquired and one tenth of all bacterial infections resulting in death can be attributed to this pathogen alone. This puts A. baumannii right at the top of a list of pathogens for which — according to the World Health Organization (WHO) — there is an urgent need to develop new therapies.
Understanding which characteristics make A. baumannii a pathogen is one of the prerequisites for this. To this end, bioinformaticians led by Professor Ingo Ebersberger of Goethe University Frankfurt and the LOEWE Center for Translational Biodiversity Genomics (LOEWE-TBG) are comparing the genomes and the proteins encoded therein across a wide range of different Acinetobacter strains. Conclusions about which genes contribute to pathogenicity can be drawn above all from the differences between dangerous and harmless strains.
Due to a lack of suitable methods, corresponding studies have so far concentrated on whether a gene is present in a bacterial strain or not. However, this neglects the fact that bacteria can acquire new characteristics by modifying existing genes and thus also the proteins encoded by them. That is why Ebersberger’s team has developed a bioinformatics method to track the modification of proteins along an evolutionary lineage and has now applied this method for the first time to Acinetobacter in collaboration with microbiologists from the Institute for Molecular Biosciences and the Institute of Medical Microbiology and Infection Control at Goethe University Frankfurt.
In the process, the researchers concentrated on hair-like cell appendages, known as type IVa (T4A) pili, which are prevalent in bacteria and that they use to interact with their environment. The fact that they are present in harmless bacteria on the one hand and have even been identified as a key factor for the virulence of some pathogens on the other suggests that the T4A pili have repeatedly acquired new characteristics associated with pathogenicity during evolution.
The research team could show that the protein ComC, which sits on the tip of the T4A pili and is essential for their function, shows conspicuous changes within the group of pathogenic Acinetobacter strains. Even different strains of A. baumannii have different variants of this protein. This leads bioinformatician Ebersberger to compare the T4A pili to a multifunctional garden tool, where the handle is always the same, but the attachments are interchangeable. “In this way, drastic functional modifications can be achieved over short evolutionary time spans,” Ebersberger is convinced. “We assume that bacterial strains that differ in terms of their T4A pili also interact differently with their environment. This might determine, for example, in which corner of the human body the pathogen settles.”
The aim is to use this knowledge of the unexpectedly high diversity within the pathogen to improve the treatment of A. baumannii infections, as Ebersberger explains: “Building on our results, it might be possible to develop personalized therapies that are tailored to a specific strain of the pathogen.” However, the study by Ebersberger and his colleagues also reveals something else: Previous studies on the comparative genomics of A. baumannii have presumably only unveiled the tip of the iceberg. “Our approach has gone a long way towards resolving the search for possible components that characterize pathogens,” says Ebersberger.

How people feel about their sleep has a greater impact on their well-being than what sleep-tracking technology says about their sleep quality, research led by the University of Warwick has found.
Across a two-week period, over 100 participants aged 18-22 years were asked to keep a daily sleep diary about the previous night’s sleep, including what time they went to bed, time they got ready to fall asleep, the amount of time it took them to fall asleep, what time they woke up, what time they got out of bed, and how satisfied they were with their sleep in general.
Five times throughout the following day, participants were asked to rate their positive and negative emotions and how satisfied they were with their life. Participants also wore an actigraph on their wrist which measures a person’s movement, for the duration of the study, to estimate their sleep patterns and rest cycles.
Researchers compared the actigraphy data with the participants’ perceptions of their sleep and how they felt throughout the following day. They wanted to find out how fluctuations from people’s usual sleep patterns and quality are related to their mood and life satisfaction the next day.
Lead author Dr Anita Lenneis, from the University of Warwick’s Department of Psychology, said: “Our results found that how young people evaluated their own sleep was consistently linked with how they felt about their well-being and life satisfaction.
“For example, when participants reported that they slept better than they normally did, they experienced more positive emotions and had a higher sense of life satisfaction the following day. However, the actigraphy-derived measure of sleep quality which is called sleep efficiency was not associated with next day’s well-being at all.
“This suggests there is a difference between actigraphy-measured sleep efficiency and people’s own perception of their sleep quality in how they link to people’s evaluations of their well-being.”
Professor Anu Realo, from the Department of Psychology at the University of Warwick added: “Our findings are consistent with our previous research that identified people’s self-reported health, and not their actual health conditions, as the main factor associated with their subjective well-being and especially with life satisfaction.

The projected cost of caring for millions of individuals who have Alzheimer’s disease (AD) worldwide will exceed a $1 trillion in a few years. In addition to the enormous health burden, patients and their caregivers experience financial, physical and psychological strain. A theory regarding repeated drug failure in AD is that patients undergoing experimental therapies are selected too late in the disease process. Therefore, it is important to identify patients at a high risk of progression to AD in early stages of the disease.
To help identify persons who could benefit from early interventions, researchers from Boston University have developed a deep learning framework that can stratify individuals with mild cognitive impairment (MCI) based on their risk of advancing to AD.
“Quantifying the risk of progression to Alzheimer’s disease (AD) could help identify persons who could benefit from early interventions,” says corresponding author Vijaya B. Kolachalama, PhD, FAHA, associate professor of medicine at Boston University Chobanian & Avedisian School of Medicine.
The team studied data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and National Alzheimer’s Coordinating Center (NACC), separating individuals with mild cognitive impairment (MCI) into groups based on their brain fluid amyloid-? levels. They studied gray matter volume patterns within these groups to identify risk groups, validating their findings with expert assessments. They developed models that combined neural networks with survival analysis to predict the progress from MCI to Alzheimer’s disease. They then linked their model predictions with biological evidence, confirming Alzheimer’s diagnoses with post-mortem data.
“By utilizing advances in interpretable machine learning, we demonstrated that brain regions relevant to AD such as the medial temporal lobe are among the most important regions for predicting progression risk, thereby assuring that our findings are consistent with established medical knowledge,” added Kolachalama.
According to the researchers, these findings represent innovation at the intersection of neurology and computer science, while underscoring model conformity with biological evidence using routinely collected information such as structural MRI to quantify risk of progression from MCI to AD.
“We utilized survival-based deep neural networks in conjunction with minimally processed structural MRI, a widely available, non-invasive technique. Further, by employing state-of-the-art deep learning methods in conjunction with SHapley Additive exPlanations (SHAP), a method based on cooperative game theory and used to increase transparency and interpretability of machine learning models, we were able to identify regions particularly important for predicting increased progression risk.”
These findings appear online in the journal iScience.
Funding for this study was supported by grants from the Karen Toffler Charitable Trust, the American Heart Association (20SFRN35460031), and the National Institutes of Health (RF1-AG062109, R01-HL159620, R21-CA253498, R43-DK134273, RF1-AG072654, U19-AG068753 and P30-AG013846). We acknowledge grant support from Boston University, CTSI 1UL1TR001430, for our REDCap Survey.

In temperate climates, like North America and Europe, flu season starts in the fall, peaks in the winter and ends in the spring. While public health officials have generally assumed that influenza is also seasonal in tropical climates, new research led by Penn State has found little evidence of a repeatable pattern in influenza cases in Vietnam. The findings suggest that influenza is likely unpredictable throughout the tropics, posing substantial challenges for prevention and management of cases for the one-third of the global population living in tropical areas.
“The World Health Organization estimates that seasonal influenza kills up to 650,000 people worldwide each year due to respiratory disease, alone; this does not include the number of people who die from cardiovascular disease caused by influenza,” said Joseph Servadio, an NIH postdoctoral scholar at Penn State. “Without the ability to identify a regular interval at which epidemics occur in tropical areas, preparations such as timing an annual vaccine campaign or preparing healthcare settings for higher caseloads are not possible.”
The researchers collected weekly counts of patients with influenza from fifteen hospitals over ten years across Vietnam to identify any consistency in the timing of influenza epidemics. Next, they developed a mathematical model incorporating the peak timings of transmission and the repeatability of these peak timings. They compared these parameters across four temperate locations — including Netherlands, Denmark, and two regions of the United States — and northern, central and southern Vietnam.
After accounting for different subtypes of influenza, the team found little evidence of a repeatable pattern throughout Vietnam. The research published July 19th in PLOS Computational Biology.
“The lengths of time between epidemics were highly irregular in Vietnam, varying widely,” said Maciej Boni, a professor of biology at Penn State. “In contrast, we found strong evidence of annual seasonality in the temperate locations, which suggests that our statistical estimation procedure performed as expected.”
Servadio noted that the four temperate locations consistently showed peak transmission during winter months.
“Possible explanations for this winter peak could include seasonal changes in behavior, such as the notable change in indoor versus outdoor gatherings in cold winter months, as well as different conditions for virus transmission, such as having cold, dry air in temperate winters,” he said.
In Vietnam, however, peak transmission occurred throughout the year.
“In contrast to temperate regions, where vaccination and health communication efforts can be strategically focused on autumn, the optimal timing for prioritizing vaccines in Vietnam to achieve maximum protection remains uncertain,” stated Dr. Pham Quang Thai, vice head of the Communicable Disease Control and Prevention Department at Vietnam’s National Institutes for Hygiene and Epidemiology. “While Vietnam has a vaccine policy targeting specific at-risk groups, influenza vaccination is not yet widespread. The findings of this study underscore the challenges in implementing a comprehensive national vaccination strategy.”

Researchers from the National Institute for Physiological Sciences (NIPS) identify an important brain circuit for determining the value of your own reward in relation to others’ rewards.
Although you might never have consciously considered it, it’s very likely that when you receive a reward, part of the value that you place on it depends on what other people have received as similar rewards. In a recent study published in Nature Communications, Japanese researchers have identified an important brain circuit for this specific process. Although researchers have identified the brain regions that are important for deciding the value of a reward in relation to those of others (a process the authors termed ‘socially subjective reward valuation’), the connections between these regions have never been tested experimentally. The research team from the National Institute for Physiological Sciences (NIPS) decided to create a temporary disconnect between the medial prefrontal cortex, which is part of the social brain network, and the lateral hypothalamus, which is involved in social reward valuation. “We used a relatively new technique that is commonly known as DREADD, or ‘designer receptor exclusively activated by designer drug’, in macaque monkeys,” says senior author of the study Masaki Isoda. “This method allowed us to temporarily block most of the connections from the brain’s medial prefrontal cortex to the lateral hypothalamus.”
To test the effects of functionally disconnecting two regions of the monkeys’ brains responsible for socially subjective reward valuation, the researchers used an existing experimental setup. Two monkeys were sat together and shown pictures on a screen. After seeing each picture, only one of the monkeys (or sometimes neither of the monkeys) received water as a reward. By varying the probability of reward for each monkey over a series of tests, the researchers were able to see what happened when the monkeys expected a reward for themselves (they made many licking motions with their tongues) versus a reward for the other monkey (they made fewer licking motions).
“Using this test, we were able to see the effects of disconnecting the medial prefrontal cortex from the lateral hypothalamus on the monkeys’ expectations of rewards,” says Isoda. “We were excited to see that, with this disconnect, the monkeys were much less susceptible to the prospect of others receiving rewards, but that their own expectations of a reward did not change, suggesting that this pathway is a key circuit in socially subjective reward valuation only.”
Together with recent research suggesting that the medial prefrontal cortex/lateral hypothalamus circuit is crucial for social rank information in mice, these results indicate that this circuit underlies many important social behaviors. A better understanding of this pathway will aid in the clinical diagnosis and treatment of injuries or alterations to the medial prefrontal cortex and lateral hypothalamus.

Korean researchers have unveiled a novel signaling pathway that fosters aging-related chronic metabolic disorders.
A research team led by Professor Jong Kyoung Kim from the Department of Life Sciences at POSTECH along with Professor Seung-Hoi Koo from the Division of Life Sciences at Korea University and principal researcher Geum-Sook Hwang from Korea Basic Science Institute (KBSI) announced the discovery of a new mechanism where BCAA metabolic pathway becomes impaired due to aging, resulting in dysfunctions of adipose cells and chronic metabolic disorders. The research findings were published in Nature Aging (IF=16.6) on July 24.
Adipocytes play a crucial role in controlling energy metabolic homeostasis. These cells along with preadipocyte cells and various immune cells comprising adipose tissues undergo cellular senescence. The release of the senescence associated secretory phenotype (SASP) from these cells accelerates aging and diminishes the functions of adipose tissues. Consequently, fat accumulation occurs in liver and muscle cells, leading to the onset of metabolic disorders and ultimately reducing health span.
In their earlier research published in Nature Communications, the research team led by Professor Seung-Hoi Koo uncovered that over-activation of CRTC2 induces insulin resistance, fatty liver, and obesity. However, until now, no research findings explored the impact of CRTC2 in adipocytes on aging and its related disorders.
This recent research marks the first confirmation that an increase in adipose CRTC2 due to aging accelerates cellular senescence, leading to a loss of adipocyte functions and aging-related chronic metabolic disorders. CRTC2 reduces the expression of PPAR gamma in adipocytes and impairs catabolism of branched-chain amino acid (BCAA). Consequently, the mechanistic target of rapamycin complex (mTORC1) becomes activated, as revealed by the composite analysis of metabolome-transcriptome. Increased mTORC1 activation triggers cellular senescence and controls mitochondrial hemostasis, thereby accelerating aging.
The analysis of single-cell transcriptome data showed that aged mice’s adipocytes had increased SASP, particularly IL-1beta and TNF-alpha. This leads to adipose tissue remodeling by inhibiting preadipocyte cell differentiation potency and immunocyte regulations. Notably, mice with CRTC2 removed from their adipocytes displayed limited activation of BCAA-mTORC1 axis, ultimately inhibiting the development of chronic metabolic disorders associated with aging. This suggests that aging can be mitigated by controlling CRTC2 or BCAA catabolism.
On the significance of the study, Professor Seung-Hoi Koo explained, “This study employed the latest convergent omics technology to unveil, for the first time, that an increase of CRTC2 in adipocytes due to aging leads to impaired BCAA catabolism, which is the primary cause of cell aging and metabolic disorders. Consequently, selective inhibition of CRTC2 or activation of PPAR gamma in adipocytes may hold the potential to inhibit aging and extend health span.”
The study was conducted with the support from the Korea Mouse Phenotyping Center Project and the Mid-Career Researcher Project of the National Research Foundation of Korea under the Ministry of Science and ICT, and the Project for Advanced Equipment-based Multi-omics Big Data Convergence Platform Establishment of the National Research Council of Science and Technology and the Project for Establishment of Bio-research Resources Usage Foundation.