Biotransformation of lactose-free acid whey by Chlorella vulgaris and Tetradesmus obliquus into value-added products - Duygu Ozcelik; Rocio Espinosa; Radhakrishna Shetty; Shyam Suwal; Henriette Lyng Røder; Charlotte Jacobsen; Colin Ray; Brijesh K. Tiwari; Poul Erik Jensen; Mahesha M. Poojary (Bioresource Technology, 2026)

Influence of phosphorus fertiliser use on two New Zealand pasture insect pest communities - Katrin G. Hewitt; Rainer W. Hofmann; Olivier J. Ball; Chanatda Somchit; Colin M. Ferguson; Ray Moss; Racheal H. Bryant; Alison J. Popay (Agriculture, Ecosystems & Environment, 2025)

Network of networks: Time series clustering of AmeriFlux sites - David E Reed; Housen Chu; Brad G. Peter; Jiquan Chen; Michael Abraha; Brian Amiro; Ray G. Anderson; M. Altaf Arain; Paulo Arruda; Greg A. Barron-Gafford; Carl Bernacchi; Daniel P. Beverly; et al. (Agricultural and Forest Meteorology, 2025)

Real-Time detection of sewer water levels and blockages using UHF-RFID sensors - Sundra R. Tatiparthi; Yashika G. De Costa; David Wyllie; Ray Y. Zhong; Shihu Hu; Zhiguo Yuan; Colin N. Whittaker; Wei-Qin Zhuang (Water Research, 2025)

Dosimetric comparison of proton therapy and CyberKnife in stereotactic body radiation therapy for liver cancers - Samuel Shyllon; Scott Penfold; Ray Dalfsen; Elsebe Kirkness; Ben Hug; Pejman Rowshanfarzad; Peter Devlin; Colin Tang; Hien Le; Peter Gorayski; Garry Grogan; Rachel Kearvell; et al. (Physical and Engineering Sciences in Medicine, 2024)
Stereotactic body radiation therapy (SBRT) has been increasingly used for the ablation of liver tumours. CyberKnife and proton beam therapy (PBT) are two advanced treatment technologies suitable to deliver SBRT with high dose conformity and steep dose gradients. However, there is very limited data comparing the dosimetric characteristics of CyberKnife to PBT for liver SBRT. PBT and CyberKnife plans were retrospectively generated using 4DCT datasets of ten patients who were previously treated for hepatocellular carcinoma (HCC, N = 5) and liver metastasis ( N = 5). Dose volume histogram data was assessed and compared against selected criteria; given a dose prescription of 54 Gy in 3 fractions for liver metastases and 45 Gy in 3 fractions for HCC, with previously published consensus-based normal tissue dose constraints. Comparison of evaluation parameters showed a statistically significant difference for target volume coverage and liver, lungs and spinal cord ( p < 0.05) dose, while chest wall and skin did not indicate a significant difference between the two modalities. A number of optimal normal tissue constraints was violated by both the CyberKnife and proton plans for the same patients due to proximity of tumour to chest wall. PBT resulted in greater organ sparing, the extent of which was mainly dependent on tumour location. Tumours located on the liver periphery experienced the largest increase in organ sparing. Organ sparing for CyberKnife was comparable with PBT for small target volumes.

Reconstructing 120 years of climate change impacts on Joshua tree flowering - Jeremy B. Yoder; Ana Karina Andrade; Lesley A. DeFalco; Todd C. Esque; Colin J. Carlson; Daniel F. Shryock; Ray Yeager; Christopher I. Smith (Ecology Letters, 2024)
Quantifying how global change impacts wild populations remains challenging, especially for species poorly represented by systematic datasets. Here, we infer climate change effects on masting by Joshua trees ( Yucca brevifolia and Y. jaegeriana ), keystone perennials of the Mojave Desert, from 15 years of crowdsourced observations. We annotated phenophase in 10,212 geo‐referenced images of Joshua trees on the iNaturalist crowdsourcing platform, and used them to train machine learning models predicting flowering from annual weather records. Hindcasting to 1900 with a trained model successfully recovers flowering events in independent historical records and reveals a slightly rising frequency of conditions supporting flowering since the early 20th Century. This reflects increased variation in annual precipitation, which drives masting events in wet years—but also increasing temperatures and drought stress, which may have net negative impacts on recruitment. Our findings reaffirm the value of crowdsourcing for understanding climate change impacts on biodiversity.

Developing an integrated framework for Marine Cultural Heritage (MCH) and Marine Protected Areas (MPA) across Africa and the Middle East - Colin Breen; Sophie Tews; Julia Nikolaus; Nick Ray; Georgia Holly; Georgia Andreou; Chris McGonigle; Kieran Westley; Lucy Blue (Marine Policy, 2024)

Valorization of dairy side-streams for the cultivation of microalgae for value added food products - Duygu Ozcelik; Shyam Suwal; Colin Ray; Brijesh K. Tiwari; Poul Erik Jensen; Mahesha M. Poojary (Trends in Food Science & Technology, 2024)

SoJel –A 3D printed jellyfish-like robot using soft materials for underwater applications - Pawandeep Singh Matharu; Zhong Wang; John H. Costello; Sean P. Colin; Ray H. Baughman; Yonas T. Tadesse (Ocean Engineering, 2023)

A Meta-Analysis of the Genome-Wide Association Studies on Two Genetically Correlated Phenotypes Suggests Four New Risk Loci for Headaches - Weihua Meng; Parminder S. Reel; Charvi Nangia; Aravind Lathika Rajendrakumar; Harry L. Hebert; Qian Guo; Mark J. Adams; Hua Zheng; Zen Haut Lu; Debashree Ray; Lesley A. Colvin; Colin N. A. Palmer; et al. (Phenomics, 2023)
Headache is one of the commonest complaints that doctors need to address in clinical settings. The genetic mechanisms of different types of headache are not well understood while it has been suggested that self-reported headache and self-reported migraine were genetically correlated. In this study, we performed a meta-analysis of genome-wide association studies (GWAS) on the self-reported headache phenotype from the UK Biobank and the self-reported migraine phenotype from the 23andMe using the Unified Score-based Association Test (metaUSAT) software for genetically correlated phenotypes ( N = 397,385). We identified 38 loci for headaches, of which 34 loci have been reported before and four loci were newly suggested. The LDL receptor related protein 1 ( LRP1 )— Signal Transducer and Activator of Transcription 6 ( STAT6 )— S hort chain D ehydrogenase / R eductase family 9C member 7 ( SDR9C7 ) region in chromosome 12 was the most significantly associated locus with a leading p value of 1.24 × 10 –62 of rs11172113. The One Cut homeobox 2 ( ONECUT2 ) gene locus in chromosome 18 was the strongest signal among the four new loci with a p value of 1.29 × 10 –9 of rs673939. Our study demonstrated that the genetically correlated phenotypes of self-reported headache and self-reported migraine can be meta-analysed together in theory and in practice to boost study power to identify more variants for headaches. This study has paved way for a large GWAS meta-analysis involving cohorts of different while genetically correlated headache phenotypes.

Consensus Head Acceleration Measurement Practices (CHAMP): Laboratory Validation of Wearable Head Kinematic Devices - Lee Gabler; Declan Patton; Mark Begonia; Ray Daniel; Ahmad Rezaei; Colin Huber; Gunter Siegmund; Tyler Rooks; Lyndia Wu (Annals of Biomedical Engineering, 2022)
Wearable devices are increasingly used to measure real-world head impacts and study brain injury mechanisms. These devices must undergo validation testing to ensure they provide reliable and accurate information for head impact sensing, and controlled laboratory testing should be the first step of validation. Past validation studies have applied varying methodologies, and some devices have been deployed for on-field use without validation. This paper presents best practices recommendations for validating wearable head kinematic devices in the laboratory, with the goal of standardizing validation test methods and data reporting. Key considerations, recommended approaches, and specific considerations were developed for four main aspects of laboratory validation, including surrogate selection, test conditions, data collection, and data analysis. Recommendations were generated by a group with expertise in head kinematic sensing and laboratory validation methods and reviewed by a larger group to achieve consensus on best practices. We recommend that these best practices are followed by manufacturers, users, and reviewers to conduct and/or review laboratory validation of wearable devices, which is a minimum initial step prior to on-field validation and deployment. We anticipate that the best practices recommendations will lead to more rigorous validation of wearable head kinematic devices and higher accuracy in head impact data, which can subsequently advance brain injury research and management.

TRY plant trait database – enhanced coverage and open access - Jens Kattge; Gerhard Bönisch; Sandra Díaz; Sandra Lavorel; Iain Colin Prentice; Paul Leadley; Susanne Tautenhahn; Gijsbert D. A. Werner; Tuomas Aakala; Mehdi Abedi; Alicia T. R. Acosta; George C. Adamidis; et al. (Global Change Biology, 2020)
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.