Biology subjects

Madsen, M.

Publications and source records attributed to Madsen, M..

5 recordsLinked to original sources

bioRxiv2026

Validation of an AI-Powered Automated Colony Analysis Platform Across Eight ISO Microbiological Methods: A Multi-Pathogen, Multi-Matrix Performance Study

Manual colony counting remains the rate-limiting, operator-dependent step in culture-based food microbiology quality control (QC). Automated colony analysis using machine learning (ML) offers the potential to standardise, accelerate, and improve the traceability of this process. However, systematic multi-method validation data for AI-based platforms against recognised international standards remain scarce. We conducted a prospective, multi-study validation of the Reshape Smart Incubator which is an automated imaging and ML-based colony analysis system, across eight ISO microbiological reference methods. In total, 887 plates were analysed, spanning qualitative (presence/absence) detection of Listeria spp. (ISO 11290-1) and Salmonella spp. (ISO 6579), and quantitative enumeration of total viable count (ISO 4833), Bacillus cereus (ISO 7932), Enterobacteriaceae (ISO 21528), coagulase-positive Staphylococci (ISO 6888), yeasts and moulds (ISO 21527), and lactic acid bacteria (ISO 15214). Automated results were benchmarked against the consensus of three or more trained technicians. The platform achieved 100% agreement with manual assessment for all both qualitative detection methods (ISO 11290-1, ISO 6579) with zero false positives and zero false negatives. For quantitative enumeration, agreement ranged from 92.97% (ISO 15214, n=122, using ISO-aligned {+/-}10%/>30 CFU thresholds) to 98.46% (ISO 21528, n=130). Where discrepancies occurred, they largely coincided with plates showing high inter-technician variability. Precision testing demonstrated a coefficient of variation of 5.88% and a mean standard deviation of 0.44 CFU for low-count plates. This study presents a comprehensive multi-ISO validation of an AI-based colony analysis system to date. The AI models demonstrated performance comparable to or exceeding that of trained human technicians across a broad range of microbiological targets, agar types, and colony morphologies, thereby supporting their use as a validated and traceable alternative to manual plate reading in accredited food microbiology quality control laboratories.

microbiology↗

bioRxiv2025

LRP2 expression in melanoma is associated with a transitory cell state, increased T cell infiltration, and is upregulated by IFNγ signaling

Low density lipoprotein receptor-related protein 2 (LRP2) is a 600 kilodalton multi-ligand endocytic membrane receptor expressed in several cell types during fetal development, including neuroepithelial cells, and in select absorptive epithelial cells in the adult. In epithelial cancers, LRP2 expression is associated with a differentiated tumor cell state and better prognosis. In previous work, we found that while LRP2 is not expressed in benign naevi, it is frequently acquired in melanoma. However, the molecular drivers of LRP2 expression in melanoma and characteristics of LRP2-expressing melanoma have yet to be described. Here, we show that LRP2 expression is related to a transitory melanoma cell state defined by co-expression of melanocyte lineage and neural crest transcriptional programs. Further, we reveal that melanoma LRP2 expression is increased in T cell-inflamed tumors, and is directly upregulated through interferon-gamma signaling. Correlation of melanoma LRP2 expression with clinicopathological variables demonstrates that LRP2 expression is associated with low Breslow thickness and low clinical stage in primary melanomas. Taken together, the present study describes the characteristics of LRP2-expressing melanoma and reveals interferon gamma signaling as a novel strong positive regulator of LRP2 expression in melanoma. SignificanceMelanoma cells often acquire LRP2 expression but the drivers of LRP2 expression in this setting and characteristics of LRP2-expressing melanoma remain unclear. Here, we show that LRP2 expression is related to a transitory melanoma differentiation cell state. Further, LRP2 expression in melanoma correlates with a T cell-inflamed tumor microenvironment and LRP2 expression in melanoma cells can be directly increased by interferon-gamma. In addition, LRP2 expression is associated with less advanced histopathological characteristics of melanoma. These findings encourage future studies on LRP2 in settings with increased interferon signaling, in particular in melanoma metastases following immunotherapy.

cancer biology↗

bioRxiv2024

The Swiss Army Knife of Alginate Manipulation - A Gut Bacterium Alginate Lyase with Diverse Catalytic Activities

The alginate-degrading enzyme BoPL38 of the human gut bacterium Bacteroides ovatus CP926 degrades the three polysaccharide structures found in alginate, a major constituent of brown macroalgae with numerous industrial applications. However, the detailed mechanisms of alginate-degrading enzymes remain unclear. Crystal structures of BoPL38 complexes with alginate oligosaccharides, now shed light on the enzymes catalytic machinery. QM/MM simulations reveal distinct conformational and reaction pathways, highlighting different transition states for mannuronate and guluronate conversion. C5 proton abstraction at subsite +1 by Y298 and H243 facilitates syn- and anti-{beta}-elimination reactions, respectively. Substrate recognition relies on R292 distorting the sugar at subsite +1 into a preactivated conformation, while stabilizing the active site tunnel through a salt bridge. Furthermore, NMR spectroscopy found that BoPL38 also catalyze mannuronate to guluronate epimerization in addition to its lyase function, thereby paving the way for future enzymatic alginate modification.

biochemistry↗

bioRxiv2020

Look where you go: characterizing eye movements toward optic flow

When we move through our environment, objects in the visual scene create optic flow patterns on the retina. Even though optic flow is ubiquitous in everyday life, it is not well understood how our eyes naturally respond to it. In small groups of human and non-human primates, optic flow triggers intuitive, uninstructed eye movements to the patterns focus of expansion (Knoll, Pillow & Huk, 2018). Here we investigate whether such intuitive oculomotor responses to optic flow are generalizable to a larger group of human observers, and how eye movements are affected by motion signal strength and task instructions. Observers (n = 43) viewed expanding or contracting optic flow constructed by a cloud of moving dots radiating from or converging toward a focus of expansion that could randomly shift. Results show that 84% of observers tracked the focus of expansion with their eyes without being explicitly instructed to track. Intuitive tracking was tuned to motion signal strength: saccades landed closer to the focus of expansion and smooth tracking was more accurate when dot contrast, motion coherence, and translational speed were high. Under explicit tracking instruction, the eyes aligned with the focus of expansion more closely than without instruction. Our results highlight the sensitivity of intuitive eye movements as indicators of visual motion processing in dynamic contexts.

neuroscience↗

bioRxiv2017

Novel Pedigree Analysis Implicates DNA Repair And Chromatin Remodeling In Multiple Myeloma Risk

The high-risk pedigree (HRP) design is an established strategy to discover rare, highly-penetrant, Mendelian-like causal variants. Its success, however, in complex traits has been modest, largely due to challenges of genetic heterogeneity and complex inheritance models. We describe a HRP strategy that addresses intra-familial heterogeneity, and identifies inherited segments important for mapping regulatory risk. We apply this new Shared Genomic Segment (SGS) method in 11 extended, Utah, multiple myeloma (MM) HRPs, and subsequent exome sequencing in SGS regions of interest in 1063 MM / MGUS (monoclonal gammopathy of undetermined significance - a precursor to MM) cases and 964 controls from a jointly-called collaborative resource, including cases from the initial 11 HRPs. One genome-wide significant 1.8 Mb shared segment was found at 6q16. Exome sequencing in this region revealed predicted deleterious variants in USP45 (p.Gln691*, p.Gln621Glu), a gene known to influence DNA repair through endonuclease regulation. Additionally, a 1.2 Mb segment at 1p36.11 is inherited in two Utah HRPs, with coding variants identified in ARID1A (p.Ser90Gly, p.Met890Val), a key gene in the SWI/SNF chromatin remodeling complex. Our results provide compelling statistical and genetic evidence for segregating risk variants for MM. In addition, we demonstrate a novel strategy to use large HRPs for risk-variant discovery more generally in complex traits.\n\nAUTHOR SUMMARYAlthough family-based studies demonstrate inherited variants play a role in many common and complex diseases, finding the genes responsible remains a challenge. High-risk pedigrees, or families with more disease than expected by chance, have been helpful in the discovery of variants responsible for less complex diseases, but have not reached their potential in complex diseases. Here, we describe a method to utilize high-risk pedigrees to discover risk-genes in complex diseases. Our method is appropriate for complex diseases because it allows for genetic-heterogeneity, or multiple causes of disease, within a pedigree. This method allows us to identify shared segments that likely harbor disease-causing variants in a family. We apply our method in Multiple Myeloma, a heritable and complex cancer of plasma cells. We identified two genes USP45 and ARID1A that fall within shared segments with compelling statistical evidence. Exome sequencing of these genes revealed likely-damaging variants inherited in Myeloma high-risk families, suggesting these genes likely play a role in development of Myeloma. Our Myeloma findings demonstrate our high-risk pedigree method can identify genetic regions of interest in large high-risk pedigrees that are also relevant to smaller nuclear families and overall disease risk. In sum, we offer a strategy, applicable across phenotypes, to revitalize high-risk pedigrees in the discovery of the genetic basis of common and complex disease.

genetics↗