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An investigative study into the suitability of the Bradford assay for rapid protein determination in whey
Get PDFThe gold-standard method to calculate protein content is to determine nitrogen levels, through Kjeldahl or Dumas, and subsequently convert this to protein using a conversion factor. However, this is slow, expensive and requires specialist equipment. This has led to the widespread use of colorimetric assays, principally the Bradford assay, as a rapid protein determination method. Limited research exists quantifying the accuracy of these methods for whey protein, using bovine serum albumin (BSA) as a quantifiable standard. To this end, standardised solutions were made of whey protein and BSA and protein content confirmed using Dumas. When tested with Bradford reagent, it was shown that standard solutions of whey protein were significantly less reactive than equivalent concentrations of BSA: thus, the use of BSA substantially underestimated the amount of protein present within a whey protein sample. This highlights that different proteins vary in their affinity for the reagent, indicating the need for researchers to create a sample-specific standard curve. Bradford data was shown to vary significantly from the reported protein concentration for a range of commercial whey proteins. Dumas was accurate only within a limited range, with higher margins of error being seen than commonly reported. The authors suggest against the use of BSA standard curves in the determination of protein within whey due to the varying protein-reagent affinities and recommend the use of any colorimetric assays with caution for heterogenous mixtures. It is hoped that highlighting these limitations will assist the development of more accurate protein determination methodologies, improving scientific quality.</p
PyamilySeq:Exposing the fragility of conventional gene (re)clustering and prokaryotic pangenomic inference methods
Get PDFPangenomics has become a central framework for exploring microbial diversity and evolution, enabling researchers to distinguish genes that define shared biological function from those that drive adaptation. However, this relies on clustering genes by sequence similarity, a process that is far less deterministic than often assumed. This study introduces PyamilySeq, a transparent and flexible toolkit designed to diagnose and quantify hidden biases within gene clustering and pangenome inference methodologies. Using PyamilySeq, we can see how clustering thresholds (often hard-coded and poorly documented) and paralog handling can substantially alter gene family composition. Surprisingly, even parameters unrelated to clustering, such as decimal precision (0.8 versus 0.80), output selection, and even CPU and memory allocation, can alter gene family assignments, challenging the assumption that identical clustering thresholds yield consistent results. Furthermore, tools often fail to report biologically meaningful or representative sequences for gene families, undermining downstream analyses. These findings reveal systematic fragilities in gene clustering and pangenome construction and highlight that pangenomics is not merely a data-driven task but a methodological one, where transparency, reproducibility, and interpretability are as critical as biological insight. This work calls for a re-evaluation of how pangenomes are constructed and compared, and advocates for methodologies that make their assumptions explicit and their results verifiable.</p
A systems reset for sustainable development
Get PDFAlthough sustainable development is an agreed vision for all countries, it lacks theoretical grounding. The contemporary market-based economy maximizes flows of material from nature through the economy to society, amplifying trends away from sustainability. We provide an alternative conceptualization of sustainable development, based not only on the flow of contributions from nature to economic actors, but equally of subsequent benefits to society, the effects of indirect drivers from society on economic actors, and direct drivers of economies on nature. This facilitates understanding of the dynamics and limits of the system, impacts on nature, the values influencing current trends away from sustainability, and of potential responses. This more holistic conceptualization enables actors to align their actions, supporting collective action towards sustainability across all scales. It thereby opens up space for inclusive co-habitation of the planet by people with diverse worldviews, enhanced achievement of the Sustainable Development Goals and more holistic framing for a post-2030 agenda for sustainability
Evaluating the Quantitative Accuracy and Application of DNA Metabarcoding for Dietary Reconstruction in Ruminants
Get PDFDNA metabarcoding offers a powerful, non-invasive tool to identify dietary composition with high taxonomic resolution, yet its quantitative accuracy and bias remain a well-recognised limitation across taxa and sample types. This universal challenge is particularly evident in herbivores, where plant material introduces additional amplification constraints. This study evaluates the accuracy of DNA metabarcoding in reconstructing the diets of sheep under controlled feeding trials involving high and low digestibility forage, using two widely used plant DNA barcodes (ITS2 and trnL). A secondary trial tested the detectability and proportional representation of a target species, Medicago sativa, when added to the diet in varying amounts (1%, 5%, 10%). ITS2 provided greater species-level resolution, while trnL showed broader taxonomic coverage but reduced precision. Both markers distinguished diet treatments effectively; however, faecal DNA showed proportional discrepancies from vegetation input, particularly under low-digestibility conditions. M. sativa was reliably detected even at 1% inclusion but was consistently overrepresented in sequence reads. Our findings highlight the strengths and limitations of DNA metabarcoding for herbivore diet studies and underscore the importance of marker choice and the effects of differential digestion biases. These findings demonstrate the need for multi-marker approaches and calibration controls in dietary studies, especially when quantitative interpretation is required. Despite limitations in quantitative accuracy, faecal DNA metabarcoding provides valuable insights into herbivore diet composition and preferences, with future refinements expected to improve its resolution and reliability for ecological monitoring and grazing management.</p
A systems reset for sustainable development
No full textAlthough sustainable development is an agreed vision for all countries, it lacks theoretical grounding. The contemporary market-based economy maximizes flows of material from nature through the economy to society, amplifying trends away from sustainability. We provide an alternative conceptualization of sustainable development, based not only on the flow of contributions from nature to economic actors, but equally of subsequent benefits to society, the effects of indirect drivers from society on economic actors, and direct drivers of economies on nature. This facilitates understanding of the dynamics and limits of the system, impacts on nature, the values influencing current trends away from sustainability, and of potential responses. This more holistic conceptualization enables actors to align their actions, supporting collective action towards sustainability across all scales. It thereby opens up space for inclusive co-habitation of the planet by people with diverse worldviews, enhanced achievement of the Sustainable Development Goals and more holistic framing for a post-2030 agenda for sustainability
Nations as refrains:Wales and the Festival of Britain 1951
Get PDFOver the past two decades, cultural geographers have been paying increasing attention to the performative, habitual, affective and atmospheric qualities of nations, nationalist movements and national identities. In this paper I utilise the concept of the refrain (ritournelle) from the writings of Gilles Deleuze and Fèlix Guattari to trace the very different rhythmic refrains and movements which may or may not gain a certain consistency in the world and affect bodies of different kinds. Refrains may be material, embodied and/or vibrational perturbations which attain a certain rhythm and consistency, and I examine how they are central to the processes of individuation and collective individuation by which nations, national subjects and national identities become crystallised and unfold. In the latter part of the paper I draw upon archival research on the Festival of Britain 1951 to argue that it can usefully be approached through the refrain. In contrast to accounts which present the Festival as a largely London affair which positioned Welsh, Scottish and Irish narratives as reflective of the regional diversity of Britain, I reveal the different responses of Welsh individuals and organisations to the idea of a Festival of Britain. I trace the importance of the Welsh language in setting a different tone or refrain for national events, and I examine how a range of material infrastructures, one-off staged events, and celebrations functioned as refrains of Welshness and/or Britishness. The paper outlines the reactions of Welsh nationalists and republicans for whom British refrains were seen as negative affective forces that would continue to subordinate Wales under a nation-state ruled from England (and specifically London)
Self-supervised multimodal change detection based on difference contrast learning for remote sensing imagery
No full textMost existing change detection (CD) methods target homogeneous images. However, in real-world scenarios like disaster management, where CD is urgent and pre-changed and post-changed images are typical of different modalities, significant challenges arise for multimodal change detection (MCD). One challenge is that bi-temporal image pairs, sourced from distinct sensors, may cause an image domain gap. Another issue surfaces when multimodal bi-temporal image pairs require collaborative input from domain experts who are specialised among different image fields for pixel-level annotation, resulting in scarce annotated samples. To address these challenges, this paper proposes a novel self-supervised difference contrast learning framework (Self-DCF). This framework facilitates networks training without labelled samples by automatically exploiting the feature information inherent in bi-temporal imagery to supervise each other mutually. Additionally, a Unified Mapping Unit reduces the domain gap between different modal images. The efficiency and robustness of Self-DCF are validated on five popular datasets, outperforming state-of-the-art algorithms.</p