Multi-virus wastewater surveillance shows promise at smaller, site-specific scales

Study suggests onsite monitoring at buildings or complexes could aid efforts against disease spread

PLOS

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In a new study, wastewater surveillance for multiple pathogens at five different sites identified local trends that were not captured in larger surveillance programs, and some sites used the data to inform efforts to prevent disease spread. Jay Bullen of Untap Health in London, U.K., Charlotte Hammer of the University of Cambridge and colleagues present these findings in the open-access journal PLOS Global Public Health.

People with viral infections produce waste containing viral RNA that ends up in wastewater in sewage systems. Measuring viral RNA levels in wastewater at treatment plants can be a cost-effective way to monitor community health. For instance, this method has been useful for monitoring COVID-19 infection trends and tracking polio eradication efforts.

Prior research suggests that wastewater surveillance programs that track multiple diseases at once could be beneficial at the municipal level. However, few studies have assessed their potential value at smaller, site-specific scales.

To fill that gap, Bullen and colleagues monitored daily wastewater concentrations of multiple viruses at five different sites in the U.K.; an office, a charity center for elderly citizens, a museum, a university co-working space, and a care home. The community size of the sites ranged from 50 to 2,000 people, and the researchers measured wastewater levels of the viruses SARS-CoV-2, influenza A and B, RSV A and B, and norovirus GI and GII.

Analysis of trends captured in the wastewater measurements revealed links with site-specific reported events, including staff illness, cleaning practices, and holidays. At the care home, where the community had less contact with the larger regional community, wastewater data captured local events that were not seen in public health data. In larger, more open communities, such as the university space, wastewater data aligned more closely with public health data.

Some sites began using the wastewater data to help inform decisions about disease prevention efforts, such as enhanced cleaning routines and notices in bathrooms about washing hands with soap.

These findings suggest that near-source wastewater monitoring could benefit local communities and perhaps provide earlier warnings of wider trends. Further research is needed to refine understanding of these potential benefits.

The authors add: “Building-level wastewater surveillance enables detection of norovirus, influenza, RSV and COVID-19 in a local population not captured by national surveillance. We see a future with near-source wastewater surveillance scaled across different communities to provide tailored local infection prevention and control measures, reducing outbreaks.” 

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In your coverage please use this URL to provide access to the freely available article in PLOS Mental Health: https://plos.io/3R6Uwn5

Citation: Bullen JC, Mohaghegh M, Tahir F, Hammer C, Sims J, Myers F, et al. (2025) Near-source wastewater surveillance of SARS-CoV-2, norovirus, influenza virus and RSV across five different sites in the UK. PLOS Glob Public Health 5(4): e0004397. https://doi.org/10.1371/journal.pgph.0004397 

Author Countries: United Kingdom

Funding: JCB, MM, FT, JS, FM, LE, ARK, CFT: This work was supported by two grants from Innovate UK (part of UK Research and Innovation, or UKRI): an Innovate UK Smart Grant [grant number 10019802] and an Innovate UK Women in Innovation award [grant number 10050739]. The funder had no involvement in study design, data collection analysis, decision to publish, or preparation of the manuscript.

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Journal

PLOS Global Public Health

DOI

10.1371/journal.pgph.0004397 

Method of Research

Observational study

Subject of Research

People

COI Statement

Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: • JCB, MM, FT, JS, FM, LE, ARK, CFT: These authors have been employed by Untap Health, a commercial company, in which JCB and CFT own equity and CFT is a board member. MM, FT, JS, FM, and CFT are current employees. The company develops automated hardware systems for water quality monitoring, which were neither used nor discussed in the current study. These competing interests will not alter adherence to PLOS Global Public Health policies on sharing data and materials. • None of the authors have served on the editorial board of this journal, or acted as expert witnesses in relevant legal proceedings.

 

MSU research: Eating brown rice increases exposure to arsenic compared to white rice

Michigan State University

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Why this matters:

• Arsenic levels in brown rice were found to be higher for U.S. consumers than in white rice, despite people often looking to brown rice as a healthier alternative.
• There is significant arsenic risk for U.S. children under 5 who consume brown rice, as arsenic is a toxic chemical element that can lead to health problems.
• Arsenic levels in U.S.-grown rice were found to be considerably lower than rice grown outside the country, suggesting there is concern to U.S. consumers who eat rice grown outside the country.

EAST LANSING, Mich. – Whether you buy rice at the grocery store or order a side of it while dining out, do you prefer brown rice or white rice? Or do you exclusively choose brown rice over white rice because you want to eat healthier, as brown rice contains more nutrients and fiber? Well, the answer to this question is not as simple as you might have thought, as it ignores a potential food safety concern.

According to new research from Michigan State University, published in the journal Risk Analysis, brown rice was found to contain higher levels of arsenic content and inorganic arsenic concentration than white rice among American populations.

While there are no major health risks for the general American public, there are potential health concerns for infants and children under age 5, as they consume more food relative to their bodyweights than adults.

“This research is important because it acknowledges the importance of considering food safety along with nutrition when consumers make choices about food,” said senior investigator of the study Felicia Wu, John A. Hannah Distinguished Professor and University Distinguished Professor at MSU’s College of Agriculture and Natural Resources. “While we found that choosing brown rice over white rice would result in higher arsenic exposure on average, the levels should not cause long-term health problems unless someone ate an enormous amount of brown rice every day for years.”

Research background and methodology

Arsenic is a natural component of the earth’s crust, and it is highly toxic. When compared to other cereal grains, rice has significantly higher contents of arsenic. In fact, rice takes up nearly 10 times more arsenic content than other grains.

This is because rice is often grown in continually flooded paddies, and wet soil conditions favor arsenic being taken up from the soil into the plants.

While the nutritional benefits of brown rice are well documented, white rice remains to be consumed more both in the U.S. and throughout the globe.

Therefore, Wu, along with postdoctoral research associate and lead author Christian Scott, both in the Department of Food Science and Human Nutrition, compared the arsenic exposure and associated risks between brown and white rice for U.S. populations.

Specifically, after comparing the nutritional aspects of brown and white rice, Wu and Scott used data courtesy of the “What We Eat in America” database of the U.S. Environmental Protection Agency and Joint Institute for Food Safety and Applied Nutrition to calculate average daily intake mean rice values for both brown and white rice.

The results provided insight into the difference in arsenic levels between brown and white rice as well as more complex data regarding how levels differed by region, highlighting where and what populations may be at increase health risk.

Geographic arsenic differences

The inorganic arsenic concentration of white versus brown rice was considerably different by region. For rice grown in the United States, the researchers found the proportion of the more toxic inorganic arsenic in white rice was 33%, and in brown rice was 48%; whereas in rice grown globally, 53% of total arsenic in white rice was inorganic, 65% of total arsenic in brown rice was inorganic. Organic arsenic, more commonly found in seafood as well as in other foods, is less toxic because it is readily excreted from the body.

There are also some populations who are more vulnerable due to elevated rice consumption or susceptibility to arsenic exposure. Specifically, this includes young children, Asian immigrant populations and populations that face food insecurity.

The values researchers found did indicate a potential harmful risk of arsenic exposure from brown rice for children under age 5 and as young as 6 months.

Interpreting the results

It’s important to not interpret these findings as evidence that brown rice is unhealthy, or that you should now consume only white rice, Wu said. Brown rice does contain important ingredients such as fiber, protein and niacin, which all benefit consumers.

“This exposure assessment is only one side of the equation when examining the potential trade-offs between brown and white rice consumption,” Wu said. “Even if arsenic levels are slightly higher in brown rice than white rice, more research is needed to demonstrate if the potential risks from this exposure are mitigated in part by the potential nutritional benefits provided by the rice bran.”

The researchers suggest completing an empirical analysis of the cost and benefits to societal public health by consuming brown rice compared to white rice. In their manuscript, they document additional key differences between brown and white rice, including prices, overall nutritional benefit and environmental burden.

Potential policy changes

Chronic exposure to arsenic over a lifetime may increase cancer risk. Therefore, this research raises the question about consumer behavior and public health. If more consumers were aware about arsenic concerns, then they may intentionally make different dietary decisions, especially when it comes to rice consumption.

As water is already regulated, the Food and Drug Administration’s Closer to Zero initiative will soon set action levels for arsenic when it comes to food products based on risk assessment to the American population. It is important for all consumers to be aware of arsenic levels in their food and understand that brown rice is a major source.

As Americans try to eat healthily and look to incorporate higher-nutrition content choices in their diets, this study challenges the notion that these choices are simply black and white — or in this case, brown and white.

By Jack Harrison

Read on MSUToday.

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Michigan State University has been advancing the common good with uncommon will for 170 years. One of the world’s leading public research universities, MSU pushes the boundaries of discovery to make a better, safer, healthier world for all while providing life-changing opportunities to a diverse and inclusive academic community through more than 400 programs of study in 17 degree-granting colleges.

For MSU news on the web, go to MSUToday or x.com/MSUnews

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Journal

Risk Analysis

DOI

10.1111/risa.70008 

Article Title

Arsenic content and exposure in brown rice compared to white rice in the United States

Article Publication Date

9-Apr-2025

 

HKU professor Bo Huang and research team uncover universal spatiotemporal scaling laws governing daily population flow in cities

The University of Hong Kong

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Fig. 1 The spatiotemporal scaling laws unveiled at the city-wide scale.

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Credit: The University of Hong Kong

While the daily ebb and flow of people across a city might seem chaotic, new research reveals underlying universal patterns. A study published in the leading international journal Nature Communications by a team led by Chair Professor Bo Huang from the Department of Geography at the University of Hong Kong (HKU) unveils fundamental spatiotemporal scaling laws that govern these population dynamics.

Understanding how people move and distribute themselves within cities is crucial for effective urban planning and management. While technology has provided vast amounts of data on where people go, grasping the temporal rhythms of population density across different locations has remained a challenge. Professor Huang's team tackled this gap by applying complexity science principles to analyse large-scale mobile device data from major cities worldwide.

"We found that seemingly random population movements are governed by organised principles," explains Professor Huang, the corresponding author. "These principles connect the temporal pulse of the city to its physical structure, showing that population dynamics scale predictably with urban density and distance from central hubs." Their findings, detailed in the article "The spatiotemporal scaling laws of urban population dynamics", demonstrate that:

1. Predictable Patterns Emerge: Contrary to appearances, daily population fluctuations are not random. They follow predictable "scaling laws" – mathematical relationships that hold true across different time intervals and geographical scales within a city.
2. City-Wide Consistency: At the scale of the entire city, these fluctuations exhibit consistent spatiotemporal patterns, describable by power-law functions.
3. Local Dynamics and Distance Decay: At specific locations (micro-level), fluctuations also follow scaling laws over time. Crucially, the intensity of these dynamics diminishes with increasing distance from urban centers, similar to how indicators like population density decrease. This decay follows an "allometric model," connecting the vibrancy of population dynamics to the density of urban features, such as points of interest (POIs).
4. Linking Space and Time: The research establishes a novel logarithmic relationship between the spatial decay and the temporal scaling, effectively linking how population dynamics change over time and across urban space.

This study offers significant theoretical advances by extending scaling concepts in urban science firmly into the temporal domain, forging a new link between space and time dynamics, and offering fresh perspectives on how cities self-organise. Practically, the research enables the creation of "space-time spectra" maps (Figs. 1 & 2) that visualise population dynamics across a city. This provides a powerful, activity-based view of the city's functional structure.

"This deeper understanding has direct implications," says Dr Xingye Tan, a postdoctoral researcher and co-first author with Professor Huang. "It can inform more effective urban planning, optimise commercial and transportation strategies, guide infrastructure development, and aid in managing public health challenges, ultimately helping build more livable, resilient, and sustainable cities."

The collaborative research team includes Professor Michael Batty (University College London), Assistant Professor Weiyu Li (Suzhou University of Science and Technology), Associate Professor Qi Wang (Northeastern University, USA), Assistant Professor Yulun Zhou (Department of Urban Planning and Design, HKU), and Professor Peng Gong, Vice-President (Academic Development) and Chair Professor in the Department of Geography at HKU.

The full paper can be accessed at: https://www.nature.com/articles/s41467-025-58286-4.

For media enquiries after office hours, please send a message via Whatsapp to  +852 6347 2221.

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Journal

Nature Communications

DOI

10.1038/s41467-025-58286-4 

Method of Research

Observational study

Subject of Research

Not applicable

Article Title

The spatiotemporal scaling laws of urban population dynamics

MORE THAN TWO SEXES/GENDERS

Warm temperature promotes sex change in ricefield eel, a protogynous hermaphrodite freshwater fish

KeAi Communications Co., Ltd.

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diagram

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Credit: Yue Ou and Yuhua Sun

The ricefield eel (Monopterus albus) is the only protogynous hermaphrodite freshwater fish. While the mechanism underlying the natural sex change in this species has been fascinating scientists for a long time, it remains elusive and mysterious.

In a new study published in Water Biology and Security, a team of researchers in China reported a temperature-induced sex reversal mechanism in ricefield eel.

“We show that warm temperature induces the expression of male sex determination genes in ovarian tissues, and that temperature-induced up-regulation of male genes depends on Trpv4, a cation channel protein that controls calcium flux into a cell,” shares corresponding author Yuhua Sun.

Previous work has revealed that the sex reversing of ricefield eel is accompanied by changes in levels of sex hormones and the expression of sex determination genes. Also, environmental factors, including temperature, light and pH, can influence the onset of the sex reversal.

The state of DNA methylation is correlated to the expression of sex determination genes during sex reversal of ricefield eel, in line with that the DNA methylome is dynamic and can be impacted by environmental factors. It is generally believed that gene-environmental interaction drive the sex reversal.

“The scenario at play here would be that of environmental cues triggering the change of the epigenetic state of genome, which leads to the transcriptional change of sex determination and endocrine genes, eventually resulting in the sex change of ricefield eel,” says Sun. “While this is interesting and reasonable, it is largely descriptive and lack of support by experimental evidences.”

In fact, some outstanding and fundamental questions have not been answered. For instance, which environmental factor is the most important driver? How are environmental cues captured and sensed, and transduced to the sex determination cascades?

“We show that warm temperature induced the expression of male sex determination genes in ovarian tissues, and that temperature-induced up-regulation of male genes depends on a cation channel thermosensor protein called Trpv4,” explains Sun. 

Trpv4 is a transmembrane protein that belongs to the transient receptor potential ion channel family, which can control the calcium flux into a cell in response to temperature cues. The identification and characterization of Trpv4 is important, as it fills the gap between temperature and the sex determination cascades.

“Our findings offer new insights into the mechanism underlying sex reversal of ricefield eel, which is a refreshing cognition,” adds Sun. “This leads to the potential of sex control breeding of this economically important aquaculture fish, as temperatures can be easily and conveniently controlled in an environmentally friendly manner.”

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Contact the author: Yuhua Sun; the Institute of Hydrobiology, Chinese Academy of Sciences; sunyh@ihb.ac.cn

The publisher KeAi was established by Elsevier and China Science Publishing & Media Ltd to unfold quality research globally. In 2013, our focus shifted to open access publishing. We now proudly publish more than 200 world-class, open access, English language journals, spanning all scientific disciplines. Many of these are titles we publish in partnership with prestigious societies and academic institutions, such as the National Natural Science Foundation of China (NSFC).

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Journal

Water Biology and Security

DOI

10.1016/j.watbs.2025.100360 

Method of Research

Experimental study

Subject of Research

Animals

Article Title

A temperature-induced sex reversal mechanism in ricefield eels.

Investing using words

KeAi Communications Co., Ltd.

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a schematic representation of the topic index algorithm

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Credit: Marcel Lee, Alan Spark

A recent article in The Journal of Finance and Data Science introduces an innovative method for constructing investment instruments directly from financial reports — without the need for human intervention.

This novel approach employs dynamic topic modeling (DTM), a variant of Latent Dirichlet Allocation (LDA), to analyze annual and quarterly reports from companies, uncovering hidden risk factors and translating them into tradable indices.

"The beauty of this method lies in its simplicity and transparency; it combines several established algorithms to achieve what previously was not possible,” says co-author Marcel Lee. “By automating the process, we eliminate biases and provide a cost-effective alternative to traditional index construction."

This unsupervised technique automatically selects optimal parameters, discovering implicit risk factors through the semantic analysis of corporate publications, thereby creating a new class of investment instruments — thematic indices.

The study describes the model's capacity to dynamically track economic and industrial trends, illustrating that sectors considered static are in reality constantly evolving. This method captures the fluid nature of industries more accurately than traditional static classifications like GICS or ICB.

"We're observing the industrial landscape through a much sharper and multicoloured lens, enabling investors to tap into nuanced market themes and risk factors previously inaccessible," adds co-author Alan Spark.

In several cases, the research demonstrated that these newly created thematic indices closely mimic established indices, yet are derived without the predefined biases of manual classification systems. “This not only paves the way for a more unbiased benchmarking tool but also reveals industry trends and vocabulary shifts over time, offering a fresh perspective on sectoral dynamics,” says Lee.

One notable challenge acknowledged by the researchers is the approach’s reliance on a ‘bag-of-words’ model, which, while instrumental in parsing large datasets, overlooks the nuanced relationships between words. “Future iterations of this work aim to incorporate more complex models that capture these subtleties, potentially enhancing the predictive power of thematic indices on corporate actions and industry shifts,” shares Spark.

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Journal

The Journal of Finance and Data Science

DOI

10.1016/j.jfds.2025.100149 

Method of Research

Computational simulation/modeling

Subject of Research

Not applicable

Article Title

Unsupervised generation of tradable topic indices through textual analysis