Wednesday, March 12, 2025

Good parenting helps, but has limits under major deprivation

Washington University in St. Louis

Good parenting can make all the difference as newborns learn to communicate and process information, and an increasing amount of early-childhood development research has shown that parent training is a worthy investment to improve childhood outcomes.

However, there may be a limit to how much skilled parenting can improve a newborn’s language and cognition skills, especially in situations where the family is facing significant deprivation.

Researchers at Washington University in St. Louis wanted to see how “prenatal social disadvantage,” a newborn’s brain volumes and parenting factor into cognitive and language abilities. Prenatal social disadvantage refers to not having the resources to meet a family’s basic needs. To do this, they recruited from obstetric clinics in St. Louis to find pregnant people from a broad variety of backgrounds.

They followed up with approximately 200 new mothers and their newborns at ages 1 and 2 to conduct parenting observations along with language and cognition assessments. What they found was that prenatal social disadvantage is associated with lower cognition and language scores and that supportive parenting behaviors could improve those indicators — but only up to a point.

The research, published in the Journal of Pediatrics, can help inform how to improve the effectiveness of prenatal and early childhood interventions.

Researcher Deanna Barch describes “social disadvantage” as a spectrum of how much a family’s financial needs are being met. Barch is vice dean of research and a professor of psychological and brain sciences in Arts & Sciences and the Gregory B. Couch Professor of Psychiatry at the School of Medicine.

If someone has basic needs covered such as stable access to housing, food and insurance, “then parenting can make a difference,” Barch said. “But if basic needs are not met, that’s probably what is constraining cognition, and parenting doesn’t have the opportunity to have the positive influence.”

Supportive parenting may not be able overcome the “hit” that deprivation causes to a newborn’s brain development. The research can be helpful in developing social programs that invest in prenatal care and parent training.

First author Shelby Leverett, a PhD student in neuroscience at WashU Medicine, explained they were initially surprised by the results because much of the scientific literature shows that parenting skills can be an effective intervention target, but the majority of those findings may be based on a narrower, more advantaged, sampling of the “social disadvantage” spectrum.

“It’s really important that we aim to support families so we can eliminate disadvantage and kids have a chance to develop optimally,” Leverett said.

Leverett SD, Grady RG, Tooley UA, Lean RE, Tillman R, Wilson J, Ruscitti M, Triplett RL, Alexopoulos D, Gerstein ED, Smyser TA, Warner B, Luby JL, Smyser CD, Rogers CE, Barch DM. Associations between Parenting and Cognitive and Language Abilities at 2 Years of Age Depend on Prenatal Exposure to Disadvantage. J Pediatr. Epub 2024 Sep 2 DOI: 10.1016/j.jpeds.2024.114289.

This study was funded by R01MH113883, K01MH122735, T32NS121881, and T32MH100019 from the NIH, the March of Dimes Foundation, grant MI-II-2018-725 from the Children’s Discovery Institute, grant P50 HD103525 from the Washington University Intellectual and Developmental Disability Research Center, and National Alliance for Research on Schizophrenia & Depression Young Investigator Grant 28521 from the Brain and Behavior Research Foundation, and grant KL2 TR00234.

Wiley announces latest release of its Wiley Identifier of Natural Products

Wiley

HOBOKEN, NY — Wiley, one of the world’s largest publishers and a global leader in research and learning, today announced the 2025 release of its Wiley Identifier of Natural Products (AntiBase Library + ChemWindow).

With the addition of 9,500 compounds, the latest release of the renowned AntiBase library provides access to more than 105,000 compounds. This growing natural products database is a powerful screening tool to aid in the discovery of novel compounds having antimicrobial, antitumor, or other desired effects. Additional applications include food, cosmetics, agriculture, pesticides, and other sectors where natural products are prevalent.

Graeme Whitley, director of data science solutions at Wiley, commented, “The addition of further compounds, structures, and spectra to this resource continues to aid in the discovery of compounds with significant therapeutic potential.”

AntiBase includes compounds from multiple biological sources including algae, animals, bacteria, dinoflagellate, fungi, lichens, plants, and others. It also includes valuable metadata such as chemical properties, biological activity data, and links to related references such as literature DOIs, Human Metabolome Database (HMDB), ZINC, KEGG, ChEMBL. Many of the records also provide access to computed spectra, if available, as well as peak data for multiple techniques including IR, HRMS, MS, UV, HNMR.

The Wiley Identifier of Natural Products package also includes Wiley’s ChemWindow software, which features sophisticated chemistry tools to search and mine the database, along with sophisticated databasing tools to manage, incorporate and leverage internal research data into your data searches.

Learn more at: https://sciencesolutions.wiley.com/solutions/technique/screening/wiley-identifier-of-natural-products/

About Wiley

Wiley (NYSE: WLY) is one of the world’s largest publishers and a trusted leader in research and learning. Our industry-leading content, services, platforms, and knowledge networks are tailored to meet the evolving needs of our customers and partners, including researchers, students, instructors, professionals, institutions, and corporations. We empower knowledge-seekers to transform today’s biggest obstacles into tomorrow’s brightest opportunities. For more than two centuries, Wiley has been delivering on its timeless mission to unlock human potential. Visit us at Wiley.com. Follow us on Facebook, X (Twitter), LinkedIn and Instagram.

Media Contacts:
Wiley / newsroom@wiley.com

Self-optimizing catalysts facilitate water-splitting for the green production of hydrogen

Researchers present cost-effective and efficient water-splitting catalysts to be used in the eco-friendly production of hydrogen / Catalyst performance surprisingly increases over time

Johannes Gutenberg Universitaet Mainz

research team — image:
The Gao Lab team: (front row, fltr) Jennifer Christina Schmidt, Dandan Gao, Bahareh Feizimohazzab ; (back row, fltr) David Leander Troglauer, Christean Nickel, Guillermo Gustavo Corea, Shikang Han
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Credit: photo/©: Regine Jung-Pothmann

Hydrogen is a much-debated option in terms of CO₂-neutral energy production. Electrolyzer units that split water into its constituent oxygen and storable hydrogen are supplied with electricity from renewable resources, mainly generated by wind and solar energy. However, catalysts are necessary to facilitate this process. To date, noble metal oxides such as ruthenium dioxide and iridium dioxide are being used as benchmark catalysts. These metals, however, are expensive, rare, and unstable in both acidic and alkaline environments.

Dr. Dandan Gao, a junior group leader at Johannes Gutenberg University Mainz (JGU) and holder of a Walter Benjamin Fellowship sponsored by the German Research Foundation, and her team have managed to devise an alternative form of catalyst using cobalt and tungsten, elements that are readily available at low cost. "What's so unique about our catalyst is that it actually enhances its performance over time, while conventional catalysts either maintain their performance at a consistent rate or even lose some of their performance because they are insufficiently durable," stated Dr. Dandan Gao. "After the process of optimization, activity is even higher than that of benchmark catalysts." The results of Gao and her team have recently been published in the international edition of the journal Angewandte Chemie.

What causes the self-optimization process?

The researchers undertook experimental and theoretical investigations to find an explanation for the extraordinary self-optimization of their catalyst. They were able to determine that the chemical nature of the catalyzing cobalt-tungsten oxide changes during the process of water-splitting. While the cobalt is initially largely present in the form of Co²⁺, it is increasingly converted to Co³⁺. At the same time, the proportion of the original tungsten W⁵⁺ ion to the W⁶⁺ ion shifts in favor of the latter. "There are two reactions during the splitting of water. The hydrogen evolution reaction (HER), which produces hydrogen gas, and the oxygen evolution reaction (OER), which produces oxygen gas. The OER represents the bottleneck for the whole reaction," explained Gao. "That's why we are so committed to developing a catalyst that can promote the OER half reaction."

While the OER is initially induced by the tungsten active site, this process is transferred with time to the cobalt active site. Moreover, the electrochemically active surface area of the catalyst also increases over the course of time. The research team also observed alterations to the hydrophilicity of the surface. Its affinity for water increases progressively, which is particularly beneficial in the context of electrochemical water-splitting. "In general, we recorded notably reduced overpotentials and increased current densities accompanied by a substantial increase in OER kinetics," concluded Gao. All this is positive news for the hydrogen production of the future.

Funding by the Walter Benjamin Program of the German Research Foundation

Dandan Gao has been sponsored through the Walter Benjamin Program of the German Research Foundation (DFG) since June 2023. This program enables early career researchers to pursue their own research project at an institution of their choice. The host research institution – Johannes Gutenberg University Mainz in this case – provides support for the project in question.

The work outlined in Angewandte Chemie also received support from the Carl Zeiss Foundation, the Alexander von Humboldt Foundation, and JGU's Top-level Research Area SusInnoScience –Sustainable Chemistry as the Key to Innovation in Resource-efficient Science in the Anthropocene.

lab

Dr. Dandan Gao and her co-workers (left) Christean Nickel and David Leander Troglauer (right) in the lab at Mainz University

Credit

photo/©: Jennifer Christina Schmidt

Journal

Angewandte Chemie

DOI

10.1002/anie.202424074

Article Title

Self-optimizing Cobalt Tungsten Oxide Electrocatalysts toward Enhanced Oxygen Evolution in Alkaline Media

‘Fishial’ recognition: Neural network identifies coral reef sounds

Faster identification of fish sounds from acoustic recordings can improve research, conservation efforts

American Institute of Physics

image:
CUREE, an autonomous underwater robot, is used by the researchers to collect acoustic data for analysis.
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Credit: Austin Greene, Woods Hole Oceanographic Institution

WASHINGTON, March 11, 2025 – Coral reefs are some of the world’s most diverse ecosystems. Despite making up less than 1% of the world’s oceans, one quarter of all marine species spend some portion of their life on a reef. With so much life in one spot, researchers can struggle to gain a clear understanding of which species are present and in what numbers.

In JASA, published on behalf of the Acoustical Society of America by AIP Publishing, researchers from Woods Hole Oceanographic Institution combined acoustic monitoring with a neural network to identify fish activity on coral reefs by sound.

For years, researchers have used passive acoustic monitoring to track coral reef activity. Typically, an acoustic recorder would be deployed underwater, where it would spend months recording audio from a reef. Existing signal processing tools can be used to analyze large batches of acoustic data at a time, but they cannot be used to find specific sounds — to do that, scientists usually need to go through all that data by hand.

“But for the people that are doing that, it's awful work, to be quite honest,” said author Seth McCammon. “It's incredibly tedious work. It's miserable.”

Equally as important, this type of manual analysis is too slow for practical use. With many of the world’s coral reefs under threat from climate change and human activity, being able to rapidly identify and track changes in reef populations is crucial for conservation efforts.

“It takes years to analyze data to that level with humans,” said McCammon. “The analysis of the data in this way is not useful at scale.”

As an alternative, the researchers trained a neural network to sort through the deluge of acoustic data automatically, analyzing audio recordings in real time. Their algorithm can match the accuracy of human experts in deciphering acoustical trends on a reef, but it can do so more than 25 times faster, and it could change the way ocean monitoring and research is conducted.

“Now that we no longer need to have a human in the loop, what other sorts of devices — moving beyond just recorders — could we use?” said McCammon. “Some work that my co-author Aran Mooney is doing involves integrating this type of neural network onto a floating mooring that's broadcasting real-time updates of fish call counts. We are also working on putting our neural network onto our autonomous underwater vehicle, CUREE, so that it can listen for fish and map out hot spots of biological activity.”

This technology also has the potential to solve a long-standing problem in marine acoustic studies: matching each unique sound to a fish.

“For the vast majority of species, we haven't gotten to the point yet where we can say with certainty that a call came from a particular species of fish,” said McCammon. “That's, at least in my mind, the holy grail we're looking for. By being able to do fish call detection in real time, we can start to build devices that are able to automatically hear a call and then see what fish are nearby.”

Eventually, McCammon hopes that this neural network will provide researchers with the ability to monitor fish populations in real time, identify species in trouble, and respond to disasters. This technology will help conservationists gain a clearer picture of the health of coral reefs, in an era where reefs need all the help they can get.

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The article “Rapid detection of fish calls within diverse coral reef soundscapes using a convolutional neural network” is authored by Seth McCammon, Nathan Formel, Sierra Jarriel, and T. Aran Mooney. It will appear in The Journal of the Acoustical Society of America on March 11, 2025 (DOI: 10.1121/10.0035829). After that date, it can be accessed at https://doi.org/10.1121/10.0035829.

ABOUT THE JOURNAL

The Journal of the Acoustical Society of America (JASA) is published on behalf of the Acoustical Society of America. Since 1929, the journal has been the leading source of theoretical and experimental research results in the broad interdisciplinary subject of sound. JASA serves physical scientists, life scientists, engineers, psychologists, physiologists, architects, musicians, and speech communication specialists. See https://pubs.aip.org/asa/jasa.

ABOUT ACOUSTICAL SOCIETY OF AMERICA

The Acoustical Society of America (ASA) is the premier international scientific society in acoustics devoted to the science and technology of sound. Its 7,000 members worldwide represent a broad spectrum of the study of acoustics. ASA publications include The Journal of the Acoustical Society of America (the world's leading journal on acoustics), JASA Express Letters, Proceedings of Meetings on Acoustics, Acoustics Today magazine, books, and standards on acoustics. The society also holds two major scientific meetings each year. See https://acousticalsociety.org/.

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Journal

The Journal of the Acoustical Society of America

DOI

10.1121/10.0035829

Article Title

Rapid detection of fish calls within diverse coral reef soundscapes using a convolutional neural network

Article Publication Date

11-Mar-2025

Patients’ affinity for AI messages drops if they know the technology was used

A survey of patients showed a slight preference for AI messages over messages written by their clinician, but overall satisfaction was high for both communications

Duke University Medical Center

DURHAM, N.C. – In a Duke Health-led survey, patients who were shown messages written either by artificial intelligence (AI) or human clinicians indicated a preference for responses drafted by AI over a human. That preference was diminished, though not erased, when told AI was involved.

The study, publishing March 11 in JAMA Network Open, showed high overall satisfaction with communications written both by AI and humans, despite their preference for AI. This suggests that letting patients know AI was used does not greatly reduce confidence in the message.

“Every health system is grappling with this issue of whether we disclose the use of AI and how,” said senior author Anand Chowdhury, M.D., assistant professor in the Department of Medicine at Duke University School of Medicine. “There is a desire to be transparent, and a desire to have satisfied patients. If we disclose AI, what do we lose? That is what our study intended to measure.”

Chowdhury and colleagues sent a series of surveys to members of the Duke University Health System patient advisory committee. This is a group of Duke Health patients and community members who help inform how Duke Health communicates with and cares for patients. More than 1,400 people responded to at least one of the surveys.

The surveys focused on three clinical topics, including routine medication refill request (a low seriousness topic), medication side effect question (moderate seriousness), and potential cancer on imaging (high seriousness).

Human responses were provided by a multidisciplinary team of physicians who were asked to write a realistic response to each survey scenario based on how they typically draft responses to patients. The generative AI responses were written using ChatGPT and were reviewed for accuracy by the study physicians who made minimal changes to the responses.

For each survey, participants were asked to review a vignette that presented one of the clinical topics. Each vignette included a response from either AI or human clinicians, along with either a disclosure or no disclosure telling them who the author was. They were then asked to rate their overall satisfaction with the response, usefulness of the information, and how cared for they felt during the interaction.

Comparing authors, patients preferred AI-drafted messages by an average difference of 0.30 points on 5-point scale for satisfaction. The AI communications tended to be longer, included more details, and likely seemed more empathetic than human-drafted messages.

“Our study shows us that patients have a slight preference for messages written by AI, even though they are slightly less satisfied when the disclosure informs them that AI was involved,” said first author Joanna S. Cavalier, M.D., assistant professor in the Department of Medicine at Duke University School of Medicine.

When they looked at the difference in satisfaction when participants were told AI was involved, disclosing AI led to lower satisfaction, though not by much: 0.1 points on the 5-point scale. Regardless of the actual author, patients were overall more satisfied with messages when they were not told AI was involved in drafting the response.

“These findings are particularly important in the context of research showing that patients have higher satisfaction when they can connect electronically with their clinicians,” Chowdhury said.

“At the same time, clinicians express burnout when their in-basket is full, making the use of automated tools highly attractive to ease that burden,” Chowdhury said. “Ultimately these findings give us confidence to use technologies like this to potentially help our clinicians reduce burnout, while still doing the right thing and telling our patients when we use AI.”

In addition to Chowdhury and Cavalier, study authors include Benjamin A. Goldstein, Vardit Ravitsky, Jean-Christophe Bélisle-Pipon, Armando Bedoya, Jennifer Maddocks, Sam Klotman, Matt Roman, Jessica Sperling, Chun Xu, and Eric G Poon.

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Journal

JAMA Network Open

Ethics in patient preferences for AI–drafted responses to electronic messages

JAMA Network Open

About The Study:

In this survey study, participants expressed a mild preference for messages written by artificial intelligence (AI) but had a slightly decreased satisfaction when told AI was involved. Patient experience must be considered along with ethical implementation of AI. Although AI disclosure may slightly reduce satisfaction, disclosure should be maintained to uphold patient autonomy and empowerment.

Corresponding Author: To contact the corresponding author, Anand Chowdhury, MD, MMCi, email anand.chowdhury@duke.edu.

To access the embargoed study: Visit our For The Media website at this link https://media.jamanetwork.com/

(doi:10.1001/jamanetworkopen.2025.0449)

Editor’s Note: Please see the article for additional information, including other authors, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support.

# # #

Embed this link to provide your readers free access to the full-text article This link will be live at the embargo time https://jamanetwork.com/journals/jamanetworkopen/fullarticle/10.1001/jamanetworkopen.2025.0449?guestAccessKey=c0957767-f5eb-4d6d-88a4-15c747418b57&utm_source=for_the_media&utm_medium=referral&utm_campaign=ftm_links&utm_content=tfl&utm_term=031125

About JAMA Network Open: JAMA Network Open is an online-only open access general medical journal from the JAMA Network. On weekdays, the journal publishes peer-reviewed clinical research and commentary in more than 40 medical and health subject areas. Every article is free online from the day of publication.

Journal

JAMA Network Open

LA REVUE GAUCHE - Left Comment

Wednesday, March 12, 2025

Good parenting helps, but has limits under major deprivation

Wiley announces latest release of its Wiley Identifier of Natural Products

Self-optimizing catalysts facilitate water-splitting for the green production of hydrogen

Credit

Journal

DOI

Article Title

‘Fishial’ recognition: Neural network identifies coral reef sounds

Journal

DOI

Article Title

Article Publication Date

Patients’ affinity for AI messages drops if they know the technology was used

Journal

Ethics in patient preferences for AI–drafted responses to electronic messages

Journal

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