From urban biosolids to biochar and nanobiochar: A scoping review of environmental applications and circular resource recovery - Sheila Abreu Mourão; Alexandre Santos Pimenta; José Cola Zanuncio; Fernanda Helfer; Ivan Gratchev; Ruby Naomi Michael (Journal of Environmental Management, 2026)

Prenatal and early postnatal lead exposure and later adulthood BMI: The Saint Louis baby tooth – Later life health study - Joyce J.Y. Lin; Ruby Hickman; Michael Leung; Justin Farmer; Ian W. Tang; Kaleigh McAlaine; Tracy Punshon; Brian P. Jackson; Felicitas B. Bidlack; Joseph J. Mangano; Marc G. Weisskopf (Environmental Research, 2026)

Shifts in subsurface oxygen transport and consumption patterns in a restored coastal flood plain over five years - Emilio Grande; Ruby N. Ghosh; Charles McIntire; Michael J. Freeman; Peter Regier; Nicholas D. Ward (Limnology and Oceanography, 2026)
Groundwater dissolved oxygen (DO) variability in coastal systems remains poorly understood despite its importance for biogeochemical cycling and ecosystem modeling. This study investigates temporal variability in groundwater DO and its hydro‐climatic drivers across timescales (hourly to seasonal) in a coastal floodplain at Beaver Creek, Washington, USA, a site transitioning from a freshwater forest to brackish tidal wetland following restoration of tidal influence. Using 5 years of high‐frequency (5‐min) hydro‐meteorological and continuous groundwater DO data, we applied wavelet and information theory analyses to disentangle the role of different drivers (e.g., groundwater levels, temperature, precipitation, among others) on DO dynamics. Monitoring was initiated 5 years after the site was restored but prior to subsurface conditions reaching a new steady state. We found that DO pulses related to tidal flooding events were most frequent during earlier water years, dominated by hourly, daily and multiday variability. In later years both the frequency and magnitude of these DO pulses decreased, resulting in more prolonged subsurface anoxia. These shifts in DO patterns reflect gradually changing subsurface biogeochemical conditions as the system continues to fully transition from lowland forest to brackish wetland 10 years after restoration. This study highlights the critical role of timescale‐specific analyses in understanding wetland biogeochemistry by identifying dominant drivers of DO variability and linking them to ecosystem transitions. Our scale‐aware approach offers a framework for evaluating ecosystem responses to climate change, sea‐level rise, and restoration efforts in tidal wetlands.

Worldwide assessment of green roofs retention using general linear models and multivariate adaptive regression splines - Inês Meireles; Verônica Brandão; Vitor Sousa; Ruby N. Michael; Ana Cláudia Dias (Sustainable Cities and Society, 2026)

Continuous reproduction facilitates the invasion success of the black mussel Mytella strigata in a tropical estuary - Robert Keith A. Sienes; Ma. Shirley M. Golez; Hessed T. Cabanilla; Michael H. Flores; Marienel A. Laguit; Paz Geneveve Q. Gacus; Junaisah Nissi L. Degoma; Delyn M. Bucay; Ruby C. Gonzales; Kaent Immanuel N. Uba (Regional Studies in Marine Science, 2026)

Abiotic factors influencing the health of mature Araucaria heterophylla (Norfolk Island Pine trees) in urban coastal parks - Anna Petrova; Chris Pratt; Ruby Naomi Michael (Environmental Management, 2026)
Tree decline can significantly impact both the aesthetic value and ecological function of urban forests. Understanding the abiotic factors influencing tree health is essential for developing effective management strategies. This study investigated the decline of heritage Araucaria heterophylla (Norfolk Island Pine) in urban areas of the Gold Coast, Queensland, Australia, with a focus on identifying underlying abiotic causes. General assessment was conducted along a 5-km coastal strip (including 946 trees); climate conditions on the Gold Coast and Norfolk Island were compared; and 38 selected trees of varying health status were examined in detail. This included soil physicochemical and nutrient analysis, as well as foliar nutrient profiling. Results showed that 15.8% of the 946 initially assessed trees exhibited symptoms of decline, such as dieback, browning of foliage tips, extensive defoliation and shortened foliage length. Mean temperatures on the Gold Coast were consistently higher than those in the species’ native range and the current decline followed a period of elevated temperatures and reduced rainfall. Declining trees ( n = 32) from the subset population were found to be growing in compacted soils, with significantly elevated foliar sodium and lower foliar carbon levels compared to healthy trees ( n = 6), indicating possible disruption of nutrient regulation. Half of the trees in the advanced stage of decline were located less than 5 m away from carparks (50%), which was higher when compared with Moderate Decline (18.7%) and very healthy Benchmarking trees (0%). Most trees in the advanced decline category were not mulched and had turfgrass as the primary groundcover (62.5%), whereas trees in moderate decline were more commonly associated with turfgrass combined with fallen branchlets (43.75%). In addition, all Benchmarking trees were located in sandy soils, whereas declining trees were more commonly associated with loam soils, which are more susceptible to compaction. Key abiotic stressors identified were extreme weather and proximity to urban infrastructure. Management recommendations include improving root zone conditions by providing irrigation during dry periods, mulching, implementing routine health monitoring to support early intervention and, for new planting, increasing distances from hard infrastructure.

Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

Pseudocapillaria tomentosa infections in laboratory larval and Adult Zebrafish (Danio rerio): Development and advances in an in vivo anthelmintic drug discovery model - Connor Leong; Ruby Scanlon; Aisling Kyne; Thomas J. Sharpton; Michael L. Kent (Veterinary Parasitology, 2026)

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

Environmental monitoring of carbofuran pesticides in wastewater, soil, and food samples using a Co9S8@N, S-doped carbon nanocomposite-engineered voltammetric sensor - Janagaraj Gandhiraj; Kavitha Balasubramanian; Michael Ruby Raj; Saradh Prasad; Khalid Eidah Alzahrani; Murugan Velmurugan; Chelladurai Karuppiah; Subramanian Chidambaravinayagam; Sayee Kannan Ramaraj (Environmental Geochemistry and Health, 2026)

The Toxicology Investigators Consortium 2024 Annual Report - Kim Aldy; Shao Li; Mari Costantini; Alyssa Falise; Rachel Culbreth; Paul M. Wax; Jeffery Brent; Michael Abesamis; Faiz Ahmed; Salman Ahsan; Peter Akpunonu; Adam Algren; et al. (Journal of Medical Toxicology, 2026)

Benchmarking CO₂ storage simulations: Results from the 11th Society of Petroleum Engineers Comparative Solution Project - Jan M. Nordbotten; Martin A. Fernø; Bernd Flemisch; Anthony R. Kovscek; Knut-Andreas Lie; Jakub W. Both; Olav Møyner; Tor Harald Sandve; Etienne Ahusborde; Sebastian Bauer; Zhangxing Chen; Holger Class; et al. (International Journal of Greenhouse Gas Control, 2025)

Exploratory Analysis of Clearance Rates and Feeding Constraints in the Invasive Black Mussel Mytella strigata (Hanley, 1843) Across Salinity and Seston Gradients - Kaent Immanuel N. Uba; Robert Keith A. Sienes; Michael H. Flores; Hessed T. Cabanilla; Gaireen D. Gaid; Junaisah Nissi L. Degoma; Delyn M. Bucay; Ruby C. Gonzales (Estuaries and Coasts, 2025)

Integrated assessment of biological activated carbon filters with UV/peracetic acid pretreatment for the mitigation of organic micropollutants and toxicity - Sana Ajaz; Mikaela Radke; Ashraf Aly Hassan; Prasad Kaparaju; Ruby N. Michael; Frederic D.L. Leusch (Journal of Water Process Engineering, 2025)

Direct Seeding achieves rehabilitation objectives for an operational sand mine in Southeast Queensland: A case study - Christopher D. Johnson; Matthew Thomson; Michael Vermeulen; Mark Waud; James McBroom; Ruby N. Michael (Ecological Engineering, 2025)

Heterostructure La0.5Sr0.5Fe0.4Mn0.6O3/TiC/porous graphene oxide for efficient trace-level detection of methiocarb pesticide in environmental samples - Francis Packiaraj Don Disouza; Shen-Ming Chen; Michael Ruby Raj; So-Qian Ching; Matar Alsalwi; Prabhakarn Arunachalam; Chelladurai Karuppiah (Process Safety and Environmental Protection, 2025)

Long-term glyphosate application and its effects on soil total nitrogen and microbial composition two years after application stopped in biochar-amended soil - Negar Omidvar; Zhihong Xu; Steven M. Ogbourne; Rebecca Ford; Prabhakaran Thanjavur Sambasivam; Trong D. Tran; Babak Salehin; Ruby N. Michael; Fang Wang; Iman Tahmasbian; Rachele S. Wilson; Shahla Hosseini Bai (Applied Soil Ecology, 2025)

Development and Preliminary Evaluation of a Food Literacy Measure for Use With Young People in Canada - Tracey Borland; Michael D.T. Fung; Emily Taylor; Michael Chaiton; Robert Schwartz; Heather Thomas; Elsie Azevedo Perry; H. Ruby Samra; Lucy Valleau; Sharon I. Kirkpatrick (Journal of the Academy of Nutrition and Dietetics, 2025)

The Cost of Antivenom: A Cost Minimization Study using the North American Snakebite Registry - Benjamin Herzel; Neev Batavia; Paul Gavaza; Tammy Phan; Emmelyn Samones; Anne-Michelle Ruha; Jakub Furmaga; Christopher Hoyte; Brian J. Wolk; Peter Akpunonu; Adam Algren; Alexandra Amaducci; et al. (Journal of Medical Toxicology, 2025)
Envenomation is a global health issue, with over 9,000 encounters managed in the United States yearly. The introduction of immunoglobulin fragment antivenom has reduced the risk of hypersensitivity. This study compares treatment costs of crotaline envenomation using the Fab and F(ab’) 2 antivenoms as reported to the North American Snakebite Registry (NASBR), a nationwide surveillance tool. Methods This was a retrospective analysis of NASBR data between 2018 and 2020. The following data points were assessed: patient demographics (age, gender, race), snake species, type of antivenom used, and treatment costs. Unit costs were estimated based on United States Centers for Medicare and Medicaid Services data. Average (mean) per patient costs from the payer perspective were calculated by multiplying resources by the unit costs. Sensitivity analyses were performed regarding cost variance and snake species. All costs reported in this study are in U.S. dollars. Results The average total cost of treatment was $31,343 per person, with medications contributing 72% of the total. Average total cost among patients who received Fab treatments was $33,347 per person compared to $19,747 among patients who received F(ab’) 2 . Antivenom costs accounted for 75% of the total cost in the Fab group and 42% in the F(ab’) 2 group. F(ab’) 2 required more vials than Fab (median 18 versus 10). Non-antivenom costs such as hospitalizations were higher in the F(ab’) 2 group. Using average sale prices increased average total cost to $52,572; Fab remained more expensive. Conclusion Antivenom is the primary cost driver in snakebite treatment in North America. Treatment with F(ab’) 2 resulted in lower overall costs, driven by lower cost of antivenom. F(ab’) 2 did not significantly lower overall resource use except for blood product administration.

Correction to: Rapid root development in clay subsoils enhances the early growth of native grassland species - Katherine Horsfall; Nicholas S. G. Williams; Ruby N. Michael; Stephen J. Livesley (Plant and Soil, 2025)

Rapid root development in clay subsoils enhances the early growth of native grassland species - Katherine Horsfall; Nicholas S. G. Williams; Ruby N. Michael; Stephen J. Livesley (Plant and Soil, 2025)

What Kills Mature Street and Park Trees in Cities? Systematic Quantitative Review of Published Case Studies - Anna Petrova; Ruby Naomi Michael; Chris Pratt (Environmental Management, 2025)
Street and park trees often endure harsher conditions, including increased temperatures and drier soil and air, than those found in urban or natural forests. These conditions can lead to shorter lifespans and a greater vulnerability to dieback. This literature review aimed to identify confirmed causes of street and park tree dieback in urban areas from around the world. Peer-reviewed case studies related to urban tree decline were scanned for the words “urban”, “city”, “cities”, “tree*”, “decline”, “dieback”, “mortality”, and “survival”. From an initial pool of 1281 papers on Web of Science and 1489 on Scopus, 65 original peer-reviewed research papers were selected for detailed analysis. Out of all species reported to decline, 46 were native, while non-natives were represented by 35 species. The most commonly affected trees were Platanus, Fraxinus, Acer, and Ficus . Most studies were conducted in Mediterranean, humid subtropical, and humid continental climates, with the greatest representation from the United States, followed by Australia, Brazil, Iran, Italy, and Russia. Many authors focused on either biotic or abiotic causes of dieback; some explored both, and some also discussed underlying environmental and urban stresses as potential predisposing factors. The majority (81% of the papers) concluded that a decline was caused by either an arthropod or a microorganism. Overall, it was suggested that changing management strategies to improve water availability and soil health might help with tree resilience. Additionally, regular monitoring and research, along with improving tree species selection and implementing biological and chemical control methods, can help prevent or slow down tree decline. Increasing awareness and adopting preventative approaches could help to extend the lifespan of street and park trees in urban environments and mitigate some of the biological threats, especially considering the challenges we may be facing due to the changing climate.

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Systemic toxicity after rattlesnake envenomation in patients using angiotensin converting enzyme inhibitors: A North American Snakebite Registry study - A.M. Ruha; M.B. Spyres; R. Culbreth; B. Wolk; C. Hoyte; S. Campleman; Peter Akpunonu; Adam Algren; Alexandra Amaducci; Sukhshant Atti; Connie Aubin; Kevin Baumgartner; et al. (Toxicon, 2025)

Exploring soil pedogenesis through frequency-dependent magnetic susceptibility in varied lithological environments - Abdessalam Ouallali; Naima Bouhsane; Saidati Bouhlassa; Velibor Spalevic; Shuraik Kader; Ruby Michael; Paul Sestras (Euro-Mediterranean Journal for Environmental Integration, 2025)
The use of percent frequency-dependent magnetic susceptibility (χfd%) is well-established for detecting superparamagnetic (SP) components in fine-grained soils and sediments. This study employs χfd% as a direct indicator of pedogenetic processes in soils from the Moroccan Rif region. Three soil transects (T1, T2, and T3), each comprising four soil cores with depths reaching 100 to 120 cm, were sampled from distinct lithological formations within an area subject to moderate to intense erosion. A total of 272 soil samples were collected and analyzed using MS2 Bartington Instruments, providing values to calculate χfd% and identify ultrafine ferrimagnetic minerals (SP, < 0.03 μm). In Quaternary fluvial terraces (T1) soils, approximately 60% of the samples indicate a mixture of SP, multidomain (MD), and Single Stable Domain (SSD) magnetic grains, while 30% contained coarser MD grains. Only 10% of the samples exhibit predominantly superparamagnetic (SP) grains. Soils on marly substrates (T2) showed 90% of samples with a combination of SP, MD, and SSD, and just 10% had SP grains. In contrast, soils from Villafranchian sandy deposits displayed χfd% values exceeding 10% in over 50% of samples, indicating that almost all iron components consist of SP grains. Physico-chemical analyses of the soils in profiles T1, T2, and T3 reveal distinct characteristics, including variations in clay content, organic matter, nutrient levels, and proportions of free and total iron. These results are important for understanding soil evolution and pedogenesis, with profiles T1 and T3 showing advanced development marked by high mineral iron, clay, and organic matter content. In contrast, profile T2 reflects a weak stage, influencing nutrient availability and contributing to overall soil dynamics in the respective profiles. The results of this study suggest that magnetic susceptibilities in these samples primarily originate from pedogenetic sources, revealing significantly advanced pedogenesis compared to T1 and T2 soils. The findings of this study align with previous research on soil erosion and degradation in the region, demonstrating that soils developed on terraces and marly substrates are more degraded and less stable than those on sandy substrates. This study underscores the utility of magnetic susceptibility as a rapid and effective indicator for initial soil assessment and gauging the degree of pedogenesis.

Classic Theory of Aerosol Filtration for Application to Urban Green Infrastructure - Nathalie Tomson; Ruby N. Michael; Igor E. Agranovski (Water, Air, & Soil Pollution, 2025)
The use of green infrastructure (GI) in urban environments has been widely investigated for its associated ecosystem services including air pollution mitigation. Plants are well-known for their ability of purifying air through photosynthesis and microbial activities occurring in the rhizosphere, however the simple filtration of particulate matter in air by plants is still not well understood. This study aimed to investigate the potential to adapt classic filtration theory for application in GI design. Two native Australian plants used as filter media were involved in laboratory experiments to remove aerosol particles ranging in size from 0.3 to > 10 µm. A comparison of aerosol removal efficiencies obtained from the laboratory experiments and predicted through classic filtration theory showed good correlation for the smaller (needle-like) leaf system. In contrast, the correlation obtained for a plant with larger elliptical leaves was not as good, showing a larger difference between the results. Such outcomes led to the conclusion that smaller and spatially homogeneous plant systems have more predictable aerosol filtration characteristics, which can be reasonably calculated using filtration theory. This finding provides practical insight into GI design, allowing quantitative predictions of local air pollution reductions using green barriers. Graphical Abstract

Implications of scale up flexible plastic packaging recycling in the United States - Michael Severson; Tessa Lee; Yuan-Yuan Lee; Sameer Kulkarni; Ruby Nguyen (Waste Management, 2025)

Benefits and burdens: perceiving the impact of non-indigenous black mussel (Mytella strigata) on ecosystem services and human well-being in Panguil Bay, Philippines - Kaent Immanuel N. Uba; Robert Keith A. Sienes; Hessed T. Cabanilla; Paz Geneveve Q. Gacus; Michael H. Flores; Ruby C. Gonzales; Junaisah Nissi L. Degoma; Delyn M. Bucay (Biological Invasions, 2025)

Environmental assessment of green wall: A comparison between Australia and Italy - Milad Reyhani; Enrica Santolini; Ruby N. Michael; Alberto Barbaresi; Patrizia Tassinari; Daniele Torreggiani (Science of The Total Environment, 2024)

In-field carbon dioxide removal via weathering of crushed basalt applied to acidic tropical agricultural soil - Fredrick J. Holden; Kalu Davies; Michael I. Bird; Ruby Hume; Hannah Green; David J. Beerling; Paul N. Nelson (Science of The Total Environment, 2024)

Corrigendum to “Recycled waste substrates: A systematic review” [Sci. Total Environ. 953 (2024) (25 November 2024) 176029] - Shuraik Kader; Ivan Gratchev; Ruby N. Michael (Science of The Total Environment, 2024)

Population dynamics of the black mussel Mytella strigata (Hanley, 1843) across environmental gradients in Panguil Bay, Philippines: Implications for management - Kaent Immanuel N. Uba; Robert Keith A. Sienes; Hessed T. Cabanilla; Paz Geneveve Q. Gacus; Michael H. Flores; Ruby C. Gonzales; Junaisah Nissi L. Degoma; Delyn M. Bucay (Regional Studies in Marine Science, 2024)

Recycled waste substrates: A systematic review - Shuraik Kader; Ivan Gratchev; Ruby N. Michael (Science of The Total Environment, 2024)

A mathematical model of melatonin synthesis and interactions with the circadian clock - Janet Best; Ruby Kim; Michael Reed; H. Frederik Nijhout (Mathematical Biosciences, 2024)

The Toxicology Investigators Consortium 2023 Annual Report - Adrienne Hughes; Alexandra Amaducci; Sharan L. Campleman; Shao Li; Mari Costantini; Meghan B. Spyres; Hannah Spungen; Jessica Kent; Alyssa Falise; Rachel Culbreth; Paul M. Wax; Jeffery Brent; et al. (Journal of Medical Toxicology, 2024)

Impacts of aluminum-cerium alloy deployment on different cerium commodities - Michael H. Severson; Ruby T. Nguyen; Adam Sibal; Haeyeon Kim (Resources, Conservation and Recycling, 2024)

Mathematical vs. machine learning models for particle size distribution in fragile soils of North-Western Himalayas - Owais Bashir; Shabir Ahmad Bangroo; Shahid Shuja Shafai; Tajamul Islam Shah; Shuraik Kader; Lizny Jaufer; Nicola Senesi; Alban Kuriqi; Negar Omidvar; Soora Naresh Kumar; Ayyanadar Arunachalam; Ruby Michael; et al. (Journal of Soils and Sediments, 2024)
Purpose Particle size distribution (PSD) assessment, which affects all physical, chemical, biological, mineralogical, and geological properties of soil, is crucial for maintaining soil sustainability. It plays a vital role in ensuring appropriate land use, fertilizer management, crop selection, and conservation practices, especially in fragile soils such as those of the North-Western Himalayas. Materials and methods In this study, the performance of eleven mathematical and three Machine Learning (ML) models used in the past was compared to investigate PSD modeling of different soils from the North-Western Himalayan region, considering that an appropriate model must fit all PSD data. Results and discussion Our study focuses on the significance of evaluating the goodness of fit in particle size distribution modeling using the coefficient of determination (R 2 adj = 0.79 to 0.45), the Akaike information criterion (AIC = 67 to 184), and the root mean square error (RMSE = 0.01 to 0.09). The Fredlund, Weibull, and Rosin Rammler models exhibited the best fit for all samples, while the performance of the Gompertz, S-Curve, and Van Genutchen models was poor. Of the three ML models tested, the Random Forest model performed the best (R 2 = 0.99), and the SVM model was the lowest (R 2 = 0.95). Thus, the PSD of the soil can be best predicted by ML approaches, especially by the Random Forest model. Conclusion The Fredlund model exhibited the best fit among mathematical models while random forest performed best among the machine learning models. As the number of parameters in the model increased better was the accuracy.

Applications and advancements of nanoparticle-based drug delivery in alleviating lung cancer and chronic obstructive pulmonary disease - Gabriele De Rubis; Keshav Raj Paudel; Leander Corrie; Samir Mehndiratta; Vyoma K. Patel; Popat S. Kumbhar; Arehalli Sidramappa Manjappa; John Disouza; Vandana Patravale; Gaurav Gupta; Bikash Manandhar; Rashi Rajput; et al. (Naunyn-Schmiedeberg's Archives of Pharmacology, 2024)

Removal of organic micropollutants in biologically active filters: A systematic quantitative review of key influencing factors - Sana Ajaz; Ashraf Aly Hassan; Ruby N. Michael; Frederic D.L. Leusch (Journal of Environmental Management, 2024)

Insulin-like peptides and ovary ecdysteroidogenic hormone differentially stimulate physiological processes regulating egg formation in the mosquito Aedes aegypti - Kangkang Chen; Xiaoyi Dou; Jai Hoon Eum; Ruby E. Harrison; Mark R. Brown; Michael R. Strand (Insect Biochemistry and Molecular Biology, 2023)

The Toxicology Investigators Consortium 2022 Annual Report - Alexandra M. Amaducci; Sharan L. Campleman; Shao Li; Dana L. Karshenas; Meghan B. Spyres; Lynn A. Farrugia; A. Min Kang; Rachel E. Culbreth; Paul M. Wax; Jeffrey Brent; Kim Aldy; Jennifer Acciani; et al. (Journal of Medical Toxicology, 2023)

Seasonal drivers of dissolved oxygen across a tidal creek–marsh interface revealed by machine learning - Peter J. Regier; Nicholas D. Ward; Allison N. Myers‐Pigg; Jay Grate; Michael J. Freeman; Ruby N. Ghosh (Limnology and Oceanography, 2023)
Dissolved oxygen (DO) is a key biogeochemical control in coastal systems, and its concentration and drivers vary markedly through time and space. This makes it difficult to accurately represent coastal DO and associated biogeochemical processes in models, limiting our ability to predict how these systems will respond to global change. We obtained high‐frequency (5‐min) in situ measurements of DO collected at three locations across the interface of a tidal creek and coastal marsh in the Pacific Northwest, USA. Random Forest machine learning models quantified the importance of three categories of environmental drivers (Aquatic, Climatic, and Terrestrial) of DO variability across the creek–marsh interface. We selected two 4‐month datasets representing Summer and Winter seasonal periods to test two hypotheses on the dominant drivers of DO at the coastal interface. We found that the Terrestrial driver—characterized by long periods of anaerobic conditions and episodic pulses in DO after floods—was most important during the Winter, whereas the Aquatic driver—characterized by variability over tidal, diel, and lunar cycles—was most important during the Summer. We explored how future climate change scenarios could alter the drivers of DO variability using a cumulative sums driver–response framework. Our results suggest that under climate change, Aquatic and Climatic drivers may increase in importance during the Summer, potentially linked to changing metabolic regimes and sea level, with Terrestrial driver importance potentially increasing during the Winter. Our approach highlights useful methods for understanding the spatiotemporal complexity of oxygen across coastal interfaces and quantifying the relative importance of distinct environmental drivers.

Effects of herbicides and mulch on the soil carbon, nitrogen, and microbial composition of two revegetated riparian zones over 3 years - Negar Omidvar; Steven M. Ogbourne; Zhihong Xu; Joanne Burton; Rebecca Ford; Babak Salehin; Iman Tahmasbian; Ruby Michael; Rachele Wilson; Shahla Hosseini Bai (Journal of Soils and Sediments, 2023)
Purpose Revegetation of riparian zones is important to improve their soil nitrogen (N) dynamics and to preserve their microbial compositions. However, the success of revegetation projects currently depends on weed control to reduce non-target vegetation competing over nutrients and to ensure the target plant species growth and survival. Different weed control methods affect soil microbial composition and N cycling. However, the long-term effects of herbicides on soil nitrogen (N) pools and microbial community composition remain uncertain even after cessation of the herbicide application. Materials and methods This study compared the impacts of different herbicides (Roundup ® , BioWeed™, Slasher ® , and acetic acid) with mulch on soil N dynamics and microbial community structure 3 years after vegetation establishment (herbicides applied repeatedly in the first 2 years after which no herbicides were applied in the third final year). Results and discussion Soil microbial biomass carbon (MBC) was significantly higher in mulch compared with Roundup ® , BioWeed™, Slasher ® , and acetic acid at month 26 at the Kandanga site and month 10 at the Pinbarren site. Soil MBC remained significantly higher in mulch compared with Roundup ® and BioWeed™, 12 months after the cessation of herbicide application at the Pinbarren site. Soil MBC in the Roundup ® and BioWeed™ groups was also lower than the acceptable threshold (160 mg kg −1 ) at month 34 at the Pinbarren site. Soil NO 3 − -N was significantly higher in the mulch than the Roundup ® at months 22 and 34 after revegetation at the Pinbarren site which could be partly explained by the decreased abundance of the denitrifying bacteria ( Candidatus solibacter and C. koribacter ). Additionally, both soil bacterial and fungal communities at the Pinbarren site and only fungal community at the Kandanga site were different in the mulch group compared with all other herbicides. The differences persisted 12 months after the cessation of herbicide application at the Pinbarren site. Conclusion Our study suggested that the application of mulch to assist with riparian revegetation would be beneficial for soil microbial functionality. The use of herbicides may have long-lasting effects on soil microbial biomass and diversity and therefore herbicides should be used with caution as part of an integrated land management plan.

Economic and environmental feasibility of recycling flexible plastic packaging from single stream collection - Yingqian Lin; Michael H. Severson; Ruby T. Nguyen; Anne Johnson; Christopher King; Beth Coddington; Hongqiang Hu; Brennan Madden (Resources, Conservation and Recycling, 2023)

An integrated supply chain analysis for cobalt and rare earth elements under global electrification and constrained resources - Michael H. Severson; Ruby T. Nguyen; John Ormerod; Sophie Williams (Resources, Conservation and Recycling, 2023)

Mathematical insights into the role of dopamine signaling in circadian entrainment - Ruby Kim; H. Frederik Nijhout; Michael C. Reed (Mathematical Biosciences, 2023)

The Toxicology Investigators Consortium Case Registry—the 2021 Annual Report - Jennifer S. Love; Dana L. Karshenas; Meghan B. Spyres; Lynn A. Farrugia; A. Min Kang; HoanVu Nguyen; Sharan L. Campleman; Shao Li; Paul M. Wax; Jeffery Brent; Kim Aldy; Michael Abesamis; et al. (Journal of Medical Toxicology, 2022)

North American extreme precipitation events and related large-scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends - Mathew Barlow; William J. Gutowski; John R. Gyakum; Richard W. Katz; Young-Kwon Lim; Russ S. Schumacher; Michael F. Wehner; Laurie Agel; Michael Bosilovich; Allison Collow; Alexander Gershunov; Richard Grotjahn; et al. (Climate Dynamics, 2019)
This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.

Copy number variation arising from gene conversion on the human Y chromosome - Wentao Shi; Andrea Massaia; Sandra Louzada; Ruby Banerjee; Pille Hallast; Yuan Chen; Anders Bergström; Yong Gu; Steven Leonard; Michael A. Quail; Qasim Ayub; Fengtang Yang; et al. (Human Genetics, 2018)

North American extreme temperature events and related large scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends - Richard Grotjahn; Robert Black; Ruby Leung; Michael F. Wehner; Mathew Barlow; Mike Bosilovich; Alexander Gershunov; William J. Gutowski; John R. Gyakum; Richard W. Katz; Yun-Young Lee; Young-Kwon Lim; et al. (Climate Dynamics, 2016)

BioEarth: Envisioning and developing a new regional earth system model to inform natural and agricultural resource management - Jennifer C. Adam; Jennie C. Stephens; Serena H. Chung; Michael P. Brady; R. David Evans; Chad E. Kruger; Brian K. Lamb; Mingliang Liu; Claudio O. Stöckle; Joseph K. Vaughan; Kirti Rajagopalan; John A. Harrison; et al. (Climatic Change, 2015)

Investigating the nexus of climate, energy, water, and land at decision-relevant scales: the Platform for Regional Integrated Modeling and Analysis (PRIMA) - Ian Kraucunas; Leon Clarke; James Dirks; John Hathaway; Mohamad Hejazi; Kathy Hibbard; Maoyi Huang; Chunlian Jin; Michael Kintner-Meyer; Kerstin Kleese van Dam; Ruby Leung; Hong-Yi Li; et al. (Climatic Change, 2015)

Natural transformation of Vibrio fischeri requires tfoX and tfoY - Amber Pollack‐Berti; Michael S. Wollenberg; Edward G. Ruby (Environmental Microbiology, 2010)
Summary Recent evidence has indicated that natural genetic transformation occurs in Vibrio cholerae, and that it requires both induction by chitin oligosaccharides, like chitohexaose, and expression of a putative regulatory gene designated tfoX . Using sequence and phylogenetic analyses we have found two tfoX paralogues in all sequenced genomes of the genus Vibrio . Like V. cholerae , when grown in chitohexaose, cells of V. fischeri are able to take up and incorporate exogenous DNA. Chitohexaose‐independent transformation by V. fischeri was observed when tfoX was present in multicopy. The second tfoX paralogue, designated tfoY, is also required for efficient transformation in V. fischeri , but is not functionally identical to tfoX . Natural transformation of V. fischeri facilitates rapid transfer of mutations across strains, and provides a highly useful tool for experimental genetic manipulation in this species. The presence of chitin‐induced competence in several vibrios highlights the potential for a conserved mechanism of genetic exchange across this family of environmentally important marine bacteria.

Symbiosis research, technology, and education: Proceedings of the 6th International Symbiosis Society Congress held in Madison Wisconsin, USA, August 2009 - Heidi Goodrich-Blair; Jean-Michel Ané; James D. Bever; Seth R. Bordenstein; Monika Bright; John M. Chaston; Keith Clay; Cameron R. Currie; Angela E. Douglas; Nicole Gerardo; Maria J. Harrison; Ruth E. Ley; et al. (Symbiosis, 2010)

Poster abstracts - J. Ferrie; M. Shipley; F. Cappuccio; E. Brunner; M. Miller; M. Kumari; M. Marmot; A. Coenen; J. L. Castillo; F. Araya; G. Bustamante; L. Montecino; et al. (Sleep and Biological Rhythms, 2007)

Contributory presentations/posters - N. Manoj; V. R. Srinivas; A. Surolia; M. Vijayan; K. Suguna; R. Ravishankar; K. Suguna; A. Surolia; M. Vijayan; R. Schwarzenbacher; K. Zeth; Diederichs; et al. (Journal of Biosciences, 1999)