Biology subjects

Foster, J.

Publications and source records attributed to Foster, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Subtyping active-site inhibitor binding mode to Abl kinase using super-resolution nanopore tweezers.

Accurate determination of kinase inhibitor binding modes could provide essential information for understanding resistance mechanisms and accelerating drug discovery. While conventional structural methods such as X-ray crystallography, cryo-EM and NMR provide high-resolution information but are low-throughput and capture largely static snapshots of dynamic protein-ligand interactions Here, we introduce a single-molecule nanopore tweezer platform that functionally subtypes ATP-competitive Abl kinase inhibitors by resolving distinct ionic current signatures of Abl-inhibitor complexes. This approach distinguishes Type I, Type IIA, and Type IIB inhibitors without structural determination. We further show how clinically relevant Abl variants (T315I and E255V) reshape inhibitor engagement and binding modes. By combining baseline probability features with wavelet-based time-frequency descriptors, ensemble machine-learning models achieved 97.5% classification accuracy across seven kinase inhibitor binding modes at sub-angstrom resolution and enabled deconvolution of mixed-inhibitor samples at nanomolar concentrations. These results establish nanopore tweezers as a label-free, super-resolution platform for profiling kinase conformational states and inhibitor binding modes, complementing structural approaches and supporting precision oncology.

biophysics↗

bioRxiv2026

Seven mutations unlock strict synthetic methylotrophy in engineered Pseudomonas putida

Methanol is a reduced, soluble one-carbon (C1) feedstock for sustainable bioproduction, but converting this potential into robust microbial growth remains difficult. Several synthetic C1 assimilation routes depend on autocatalytic cycles, whose operation requires coordinated control of redox balance, toxic intermediates, substrate regeneration, and host regulation. Here, we implemented the serine-threonine cycle (STC) in the soil bacterium Pseudomonas putida and used growth-coupled selection with adaptive laboratory evolution (ALE) to transition from mixotrophic C1 incorporation to strict methylotrophy. The evolved strain grew with methanol as the sole carbon and energy source under atmospheric CO2 with a doubling time of ca. 40 h. Whole-genome sequencing, reverse genetics, biosensors, isotope labelling, and comparative RNA sequencing showed that evolution repeatedly targeted native pyrroloquinoline quinone (PQQ)-dependent methanol oxidation, membrane-bound transhydrogenase activity, glycine regeneration, STC enzyme balance, and global regulatory nodes. Additional ALE under glycine-methanol co-feeding increased growth rates and exposed further targets for improving cycle flux. These results establish P. putida as a chassis for strict synthetic methylotrophy and define actionable engineering routes toward C1 biomanufacturing. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=63 SRC="FIGDIR/small/739708v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1642d2dorg.highwire.dtl.DTLVardef@1d203d1org.highwire.dtl.DTLVardef@f8a5d7org.highwire.dtl.DTLVardef@4fe272_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2026

From eye anatomy to navigation: a biologically accurate model of bees polarisation vision

Skylight polarisation patterns provide a critical navigational cue for many insects. Bees perceive these patterns through specialised ommatidia in the dorsal rim area of their compound eyes, enabling them to estimate the suns direction and navigate between food sources and the hive. Although polarisation-based navigation has been extensively studied behaviourally, computational models that link DRA anatomy with navigational performance are lacking. Here, we simulate polarisation vision in honeybees (Apis mellifera) and bumblebees (Bombus terrestris) using real sky polarisation images to capture biologically relevant skylight properties. Our biologically grounded simulation incorporates species-specific DRA anatomy, including ommatidial optical axis directions, photoreceptor receptive fields, and microvillar orientations. We evaluate navigational accuracy and consistency across sun elevations under two distinct, potentially complementary navigational models: the matched filter, which requires scanning across body orientations to identify the solar axis, and the vector-sum model, which generates instantaneous sun azimuth estimates from a single body orientation, making it independent of active scanning. Matched filter errors in estimating solar axis are below 5{degrees} across most sun elevations and in both species. Absolute errors in the vector-sum model are lower for honeybees than bumblebees (median [~]10{degrees} and [~]30{degrees}, respectively), reflecting differences in DRA anatomy, particularly viewing direction and microvillar arrangement. Both models allow stable course control across most sun elevations in both species, yet the matched filter, being limited to solar axis alignment, only enables positive or negative phototaxis. Overall, this work provides a mechanistic and comparative framework based on realistic DRA anatomy to study polarisation-based navigation, generating testable predictions for insect navigation under natural sky conditions. Author SummaryMany insects, including bees, navigate with the help of skylight polarisation patterns which hold information about the suns position even when it is not visible. Bees detect these patterns through the dorsal rim area (DRA) of their complex eyes. How differences in DRA anatomy between bee species translate into differences in navigational ability has remained unclear. Here, we built a biologically realistic simulation of polarisation vision in honeybees and bumblebees. We used real sky images to examine what polarisation information is available to each species. We then tested two models of sun position estimation based on the polarisation pattern: one that requires the bee to actively scan the sky, and one that generates an instantaneous estimate from a single body orientation. In both species, both models show that accurate sun position estimation and stable navigation are possible using just polarisation information under a wide range of sun elevations. Differences in navigational performance between honeybees and bumblebees arise because the two DRAs look at different parts of the sky. Our results provide a robust framework for understanding how DRA anatomy shapes polarisation-based navigation in bees.

neuroscience↗

bioRxiv2025

Systemic and local regulation of root growth by vascular trehalose 6-phosphate is correlated with re-allocation of primary metabolites between shoots and roots

Trehalose 6-phoshpate (Tre6P) is a key signalling molecule that reflects carbon status and integrates it with developmental decision making. Tre6P has been demonstrated to regulate various developmental processes, including vegetative growth, shoot branching, flowering, and root branching. Here, we investigate how vasculature-derived Tre6P influences root system architecture by expressing heterologous Tre6P synthase (TPS) or Tre6P phosphatase (TPP) specifically in the plant vasculature. Plants with elevated vascular-derived Tre6P levels had smaller root systems, reduced sucrose levels, and lower root metabolite levels, whereas vascular TPP overexpression had the opposite effect. Using reciprocal grafting experiments, we identified shoot-derived vascular Tre6P to be the main driver of these systemic responses. In lines with increased Tre6P in the shoot vasculature, the shoot-to-root metabolite ratios were consistently increased, indicating that Tre6P modulates metabolite allocation and utilization to balance carbon partitioning between shoot and root growth. Our data further suggest that vascular Tre6P contributed to optimizing the carbon-to-nitrogen ratio to support growth and fitness. Besides this systemic function, this study shows that root-derived Tre6P also plays a critical local role in modulating root development. Collectively, our results demonstrate that Tre6P in the vasculature functions both systemically and locally to coordinate metabolic status with root growth and architecture.

plant biology↗

bioRxiv2025

Regioselective biosynthesis of oligoamides as precursors for sequence-controlled co-polyamides

Polyamides are important natural and synthetic polymers, best exemplified by proteins and nylons respectively. Proteins demonstrate that novel polymers with emergent properties can be generated by combining diverse monomers in precisely defined sequences. However, commercial polyamides represent only a small fraction of the potential diversity in polyamide sequences, due to the synthetic challenges of sequence-controlled polymerization. Amide synthetases have been shown to synthesize a broad array of nylon-relevant diads, but the generation of novel sequenced copolyamides requires enzymes capable of acting with longer and more diverse substrates. In this study, we demonstrated that NRPS-independent siderophore (NIS) synthetases, represented by DesD, can ligate oligomeric substrates. A simultaneous enzyme cascade using DesD enabled the synthesis of an oligotriad directly from unprotected substrates. Moreover, the regioselectivity of DesD allowed the selective synthesis of a sequenced amide tetrad, the precursor to a novel sequenced-defined polyamide with properties superior to nylon 66. This study establishes a direct biocatalytic route for the facile synthesis of sequenced oligoamides from unprotected bifunctional substrates, opening new possibilities to synthesize sequenced copolyamides.

biochemistry↗

bioRxiv2025

Molecular Insights into the Production of Extracellular Vesicles by Plants

Extracellular vesicles (EVs) produced by Arabidopsis are highly heterogeneous in protein content. Specific EV subpopulations have been proposed to participate in plant immunity, particularly during plant-fungal interaction. To understand the origins of plant EV heterogeneity, we used a proximity labeling approach to identify proteins and pathways involved in the secretion of distinct EV subpopulations. Proximity labeling, co-immunoprecipitation, and fluorescence microscopy in Nicotiana benthamiana all indicated a general role in EV secretion for EXO70 proteins (a subunit of the exocyst complex) and the immune-related protein RPM1-INTERACTING PROTEIN 4 (RIN4), while the ER-localized VAMP-ASSOCIATED PROTEIN 27(VAP27) was specifically associated with the EV marker protein TETRAPSANIN8 (TET8). Despite being secreted in separate EV populations, we found that TET8 and PENETRATION 1 (PEN1) co-localized in multivesicular body-like subcellular structures. Based on these results, we tested Arabidopsis mutants and identified several proteins involved in EV secretion, including members of the exo70 family, rin4, rabA2a, scd1 (a GTP-exchange factor for RabE GTPases), and vap27. We also uncovered a possible connection between trichomes and EVs, as the trichomeless mutant glabrous1 secreted approximately half the number of EVs as wild type. Furthermore, PEN1 MVB-like structures were prevalent in guard cells, suggesting that guard cells may contribute to secretion of PEN1+ EVs on the leaf surface. Lastly, we found that exo70 family mutants are more susceptible to infection with the fungal pathogen Colletotrichum higginsianum, underlining the importance of secretion for plant immunity. Together, our results unravel some of the complex mechanisms that give rise to EV subpopulations in plants.

plant biology↗

bioRxiv2025

Application of post glycosylation modifying enzymes for mass spectrometry imaging of modified N-glycans in situ.

Glycans are essential components of cells and are involved in innumerable biological processes. Their structural diversity and complexity present unique analytical challenges. Glycans are comprised of various types of monosaccharides that are linked together at different positions and with varied stereochemistry. In addition, glycans are frequently decorated with a diverse set of chemical modifications, termed post-glycosylation modifications (PGMs). Characterization of PGMs is essential for a thorough understanding of glycans, however, the technical challenges and low throughput of current methodologies have limited our understanding of these modifications. Here we demonstrate a novel approach for rapid visualization of specific PGMs present in tissue N-glycans by applying PGM-targeting enzymes to mass spectrometry imaging (MSI). The method enables in situ investigation of glycans with PGMs en masse, identifying the sugar residue and position modified, as well as visualizing the spatial distribution of each modified N-glycan in tissues. As the repertoire of PGM-targeting enzymes expands, we anticipate this approach will enable a better understanding of PGM distribution within a dynamic N-glycome. This may yield both new biological insights and the potential for identification of novel disease biomarkers.

molecular biology↗

bioRxiv2024

Bumblebees flexibly adjust learning and decision strategies to sensory information content in a foraging task

When making decisions, humans and animals often rely on multiple sensory cues simultaneously. These provide complementary sources of information, which can help overcome ambiguity and noise, and increase the accuracy of decisions. While most studies have focused on the benefits of multimodal and within-mode integration for learning and decision making, their costs have received less attention. Processing, learning and memorizing multiple inputs requires more neural resources than for single cues, and might also require more time. In this study, we tested whether insects trade off the costs and benefits of learning multiple cues in a foraging task, using the buff-tailed bumblebee Bombus terrestris. To maximize comparability between cues, we presented combinations of visual-only features, as found on natural flowers: colours of varying discriminability, paired with shapes or patterns. We found that the bees relied exclusively on colours when these were easy to discriminate, and did not learn pattern or shape features presented simultaneously. With harder to discriminate colours, the bees learned both colour and shape or pattern features. Our results demonstrate that bumblebees flexibly adjust their learning strategies when presented with visual features of varying discriminability, to balance the costs and benefits of multi-cue learning. Our analysis of the learning rates of the bees with multi- and single attribute stimuli suggests that blocking could serve as a mechanism to implement this strategy switch. These results shed light on trade-offs in learning and decision making with multiple cues, and can directly be compared to studies in other insects, animals and humans. Significance StatementWhen making decisions, animals often rely on multiple sensory cues simultaneously. These complementary sources of information can increase decision accuracy. Unlike the benefits of cue integration, their costs have received less attention. In this study, we tested whether insects trade off the costs and benefits of learning multiple cues in a foraging task. We trained buff-tailed bumblebees, Bombus terrestris, to feature combinations of natural flowers. Bees flexibly switched from linear integration to winner-takes-all decision strategies depending on the sensory information available, thereby balancing accuracy and time investment in the task. We find that this switch can be explained by the cognitive phenomenon of blocking; providing the ground for future investigations into the underlying neural mechanisms of flexible decision strategies.

animal behavior and cognition↗

bioRxiv2024

Identification and characterization of substrate- and product-selective nylon hydrolases

Enzymes have evolved to rapidly and selectively hydrolyze diverse natural and anthropogenic polymers, but only a limited group of related enzymes have been shown to hydrolyze synthetic polyamides. In this work, we synthesized and characterized a panel of 95 diverse enzymes from the N-terminal nucleophile hydrolase superfamily with 30-50% pairwise amino acid identity. We found that nearly 40% of the enzymes had substantial nylon hydrolase activity, in many cases comparable to that of the best-characterized nylon hydrolase, NylC. There was no relationship between phylogeny and activity, nor any evidence of prior selection for nylon hydrolase activity. Several newly-identified hydrolases showed significant substrate selectivity, generating up to 20-fold higher product titers with Nylon 6,6 versus Nylon 6. Finally, we determined the crystal structure and oligomerization state of a Nylon 6,6-selective hydrolase to elucidate structural factors that could affect activity and selectivity. These new enzymes provide insights into the widespread potential for nylon hydrolase evolution and opportunities for analysis and engineering of improved hydrolases. SignificanceNylons are common industrial polyamides with few recycling options. As an alternative to mechanical or chemical recycling, enzymes may provide a selective and energy-efficient route to deconstruct nylons from mixed waste. Several nylon hydrolases have been identified, most notably NylC, but these enzymes are all closely related and demonstrated similar activity and substrate range. In this work, we investigated a diverse set of enzymes and showed that nylon hydrolase activity is common, providing new insights into the evolution of microbial nylon hydrolysis. Unlike NylC, several enzymes demonstrated unprecedented substrate selectivity, preferentially hydrolyzing Nylon 6,6 compared to Nylon 6. These enzymes can be used to understand substrate selectivity in nylon hydrolysis and to engineer enzymes for nylon recycling from mixed waste.

biochemistry↗

bioRxiv2024

A novel toolbox of GATEWAY-compatible vectors for rapid functional gene analysis in soybean composite plants

The generation of transgenic plants is essential for plant biology research to investigate plant physiology, pathogen interactions and gene function. However, producing stable transgenic plants for plants such as soybean is a laborious and time-consuming process, which can impede research progress. Composite plants consisting of wild-type shoots and transgenic roots are an alternative method for generating transgenic plant tissues that can facilitate functional analysis of genes-of-interest involved in root development or root-microbe interactions. In this report, we introduce a novel set of GATEWAY-compatible vectors that enable a wide range of molecular biology uses in roots of soybean composite plants. These vectors incorporate in-frame epitope fusions of green fluorescent protein, 3x-HA, or miniTurbo-ID, which can be easily fused to a gene-of-interest using the GATEWAY cloning system. Moreover, these vectors allow for the identification of transgenic roots using either mCherry fluorescence or the RUBY marker. We demonstrate the functionality of these vectors by expressing subcellular markers in soybean, providing evidence of their effectiveness in generating protein fusions in composite soybean plants. Furthermore, we show how these vectors can be used for gene function analysis by expressing the bacterial effector, AvrPphB in composite roots, enabling the identification of soybean targets via immunoprecipitation followed by mass spectrometry. Additionally, we demonstrate the successful expression of stable miniTurbo-ID fusion proteins in composite roots. Overall, this new set of vectors is a powerful tool that can be used to assess subcellular localization and perform gene function analyses in soybean roots without the need to generate stable transgenic plants. Key MessageWe developed a set of GATEWAY vectors to accelerate gene function analysis in soybean composite plants to rapidly screen transgenic roots and investigate subcellular localization, protein-protein interactions, and root-pathogen interactions.

plant biology↗

bioRxiv2024

Dlk1 is a novel adrenocortical stem/progenitor cell marker that predicts malignancy in adrenocortical carcinoma

Disruption of processes involved in tissue development and homeostatic self-renewal is increasingly implicated in cancer initiation, progression, and recurrence. The adrenal cortex is a dynamic tissue that undergoes life-long turnover. Here, using genetic fate mapping and murine adrenocortical carcinoma (ACC) models, we have identified a population of adrenocortical stem cells that express delta-like non-canonical Notch ligand 1 (DLK1). These cells are active during development, near dormant postnatally but are re-expressed in ACC. In a study of over 200 human ACC samples, we have shown DLK1 expression is ubiquitous and is an independent prognostic marker of recurrence-free survival. Paradoxically, despite its progenitor role, spatial transcriptomic analysis has identified DLK1 expressing cell populations to have increased steroidogenic potential in human ACC, a finding also observed in four human and one murine ACC cell lines. Finally, the cleavable DLK1 ectodomain is measurable in patients serum and can discriminate between ACC and other adrenal pathologies with high sensitivity and specificity to aid in diagnosis and follow-up of ACC patients. These data demonstrate a prognostic role for DLK1 in ACC, detail its hierarchical expression in homeostasis and oncogenic transformation and propose a role for its use as a biomarker in this malignancy. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/609117v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@12aba74org.highwire.dtl.DTLVardef@374daaorg.highwire.dtl.DTLVardef@cbdc37org.highwire.dtl.DTLVardef@1e6aeac_HPS_FORMAT_FIGEXP M_FIG C_FIG Statement of significanceThis study presents DLK1 as a novel biomarker in ACC with opportunities for use in the diagnosis, prognosis and longitudinal follow up of patients. DLK1, a marker of adrenocortical stem cells, is re-expressed in ACC, is measurable in patients serum and is associated with increased malignancy.

cancer biology↗

bioRxiv2024

The Soybean Cyst Nematode Effector Cysteine Protease 1 (CPR1) Targets a Mitochondrial Soybean Branched-Chain Amino Acid Aminotransferase (GmBCAT1) for Degradation

The soybean cyst nematode (SCN; Heterodera glycines) facilitates infection by secreting a repertoire of effector proteins into host cells to establish a permanent feeding site composed of a syncytium of root cells. Among the diverse proteins secreted by the nematode, we were specifically interested in identifying proteases to pursue our goal of engineering decoy substrates that elicit an immune response when cleaved by an SCN protease. We identified a cysteine protease that we named Cysteine Protease 1 (CPR1), which was predicted to be a secreted effector based on transcriptomic data obtained from SCN esophageal gland cells, presence of a signal peptide, and lack of transmembrane domains. CPR1 is conserved in all isolates of SCN sequenced to date, suggesting it is critical for virulence. Transient expression of CPR1 in Nicotiana benthamiana leaves suppressed cell death induced by a constitutively active nucleotide binding leucine-rich repeat protein, RPS5, indicating that CPR1 inhibits effector-triggered immunity. CPR1 localizes in part to the mitochondria when expressed in planta. Proximity-based labeling in transgenic soybean roots, co-immunoprecipitation, and cleavage assays identified a branched-chain amino acid aminotransferase from soybean (GmBCAT1) as a substrate of CPR1. Silencing of the CPR1 transcript in the nematode reduced penetration frequency in soybean roots while the expression of CPR1 in soybean roots enhanced susceptibility. Our data demonstrates that CPR1 is a conserved effector protease with a direct target in soybean roots, highlighting it as a promising candidate for decoy engineering.

plant biology↗

bioRxiv2022

Overlapping Neural Representations for Dynamic Visual Imagery and Stationary Storage in Spatial Working Memory

Representations in working memory need to be flexibly transformed to adapt to our dynamic environment and variable task demands. Recent work has demonstrated that activity in the alpha frequency band enables precise decoding of visual information during both perception and sustained storage in working memory. Extant work, however, has focused exclusively on the representation of static visual images. Here we used EEG recordings to examine whether alpha-band activity supports the dynamic transformation of representations in spatial working memory using an imagery task that required the active shifting of a stored position to a new position. In line with recent findings, a common format of alpha-band activity precisely tracked both the initial position stored in working memory as well as the transformed position, with the latter emerging approximately 800-1200 ms following an auditory cue to "rotate" to a new position. Moreover, the time course of this transformation of alpha activity predicted between-subject differences in manual reaction time to indicate the new position (Experiment 1), as well as within-subject variations in saccade latency in a speeded version of the task (Experiment 2). Finally, cross-training analyses revealed robust generalization of alpha-band reconstruction of working memory contents before and after mental transformation. These findings demonstrate that alpha activity tracks dynamic transformations of representations in spatial working memory, and that the format of this activity is preserved across the initial and transformed memory representations. These findings highlight a new approach for measuring voluntary shifts in online memory representations and show common representational formats during dynamic mental imagery and the maintenance of static representations in working memory.

neuroscience↗

bioRxiv2022

Flower patterns improve foraging efficiency in bumblebees independent of nectary guidance

Colourful patterns on flowers are thought to benefit both pollinators and the plants they visit, by increasing the plants pollination success via an improved foraging efficiency of its pollinators. This increased efficiency is thought to result from a guidance effect of the flower patterns, correspondingly termed nectar guides, which indicate the position of the nectary to visiting pollinators. While it is well established that flower patterns play an important role in flower choice, the mechanisms underlying their function for flower-visiting insects remain poorly understood. In this study, we quantified the contributions of patterns to all phases of flower interaction in the buff-tailed bumblebee (Bombus terrestris). We analysed their flight paths, as well as landing positions and walking tracks on artificial flowers with different pattern types. We reveal that flower patterns improved the overall foraging efficiency of the bees by up to 30%, by guiding their approach flight, landing positions, and departure decisions. Surprisingly, these effects were not related to nectary guidance. Since we conducted the experiments with experienced foragers, which represent the majority of insect pollinators active in nature, the newly described nectary-independent guidance effects of flower patterns are of fundamental importance to plant-pollinator interactions under natural conditions.

ecology↗

bioRxiv2022

Host genetics maps to behaviour and brain structure in mice

Gene-environment interactions in the postnatal period have a long-term impact on neurodevelopment. To effectively model neurodevelopment in the mouse, we incorporated several validated behavioural tests to develop a behavioural pipeline that measures translationally relevant milestones of development in mice. The behavioral phenotype of 1060 wild type and genetically-modified mice was examined in parallel with structural brain imaging. The influence of genetics, sex, and early life stress on behaviour and neuroanatomy was determined using traditional statistical and machine learning methods. The results demonstrated that neuroanatomical diversity was primarily associated with genotype whereas behavioural phenotypic diversity was observed to be more susceptible to gene-environment interactions.

neuroscience↗

bioRxiv2022

Primary cilia regulate Meibomian glands development and dimensions without impairing the lipid composition of the meibum

PurposePrimary cilia regulate the development of various ectoderm-derived tissues, including the corneal epithelium, skin, hair follicle and sebaceous glands. We aimed to investigate their role in meibomian gland (MG) development. MethodsPrimary cilium ablation in MGs was achieved by crossing a floxed Ift88 mouse (Ift88fl/fl) with a mouse expressing the Cre recombinase under the keratin 14 (K14) promoter, to generate K14-Cre;Ift88fl/fl mice. MG morphology was evaluated by histology and immunostaining, as well as lipid staining and 2-photon microscopy on whole mount tarsal plates. MG lipid profiles were assessed by chromatography. ResultsWe showed that most of MG cells are ciliated during early stages of MG development and that MG ciliated rate decreases throughout morphogenesis. In morphologically mature glands, only the MG central duct and ductules are ciliated, and meibocytes lose their cilia as they differentiate and become filled with lipids. Primary cilium ablation induces enlargement of MGs, dilation of the MG central duct, and an increased production of lipids, without dramatically changing the lipid profiles. In addition, primary cilia regulate MG elongation and the spatial distribution of proliferating and dying cells within MGs, without changing the total cell proliferation and death rates. ConclusionsThese findings indicate that primary cilia are not necessary for normal MG development. However, they promote MG enlargement and lipid production, suggesting that primary cilia could be an interesting target for treatments of ocular surface diseases involving MGs, like dry eye disease.

developmental biology↗

bioRxiv2021

Why can we detect lianas from space?

Lianas, woody vines acting as structural parasites of trees, have profound effects on the composition and structure of tropical forests, impacting tree growth, mortality, and forest succession. Remote sensing offers a powerful tool for quantifying the scale of liana infestation, provided the availability of robust detection methods. We analyze the consistency and global specificity of spectral signals from liana-infested tree crowns and forest stands, examining the underlying mechanisms. We compiled a database, including leaf reflectance spectra from 5424 leaves, fine-scale airborne reflectance data from 999 liana-infested canopies, and coarse-scale satellite reflectance data covering hectares of liana-infested forest stands. To unravel the mechanisms of the liana spectral signal, we applied mechanistic radiative transfer models across scales, corroborated by field data on liana leaf chemistry and canopy structure. We find a consistent liana spectral signature at canopy and stand scales across sites. This signature mainly arises at the canopy level due to direct effects of leaf angles, resulting in a larger apparent leaf area, and indirect effects from increased light scattering in the NIR and SWIR regions, linked to lianas less costly leaf construction compared to trees. The existence of a consistent global spectral signal for lianas suggests that large-scale quantification of liana infestation is feasible. However, because the traits identified are not exclusive to lianas, accurate large-scale detection requires rigorously validated remote sensing methods. Our models highlight challenges in automated detection, such as potential misidentification due to leaf phenology, tree life-history, topography, and climate, especially where the scale of liana infestation is less than a single remote sensing pixel. The observed cross-site patterns also prompt ecological questions about lianas adaptive similarities across environments, indicating possible convergent evolution due to shared constraints on leaf biochemical and structural traits. Open data statementOf the 17 datasets used, 10 are published and publicly accessible, with links provided in this submission (Appendix S1: Section S1). Upon acceptance, remaining seven datasets will be provided via Smithsonians Dspace. The open-source model code is available as R-package ccrtm (https://cran.r-project.org/web/packages/ccrtm/index.html) and on github (https://github.com/MarcoDVisser/ccrtm). Code will be archived in Zenodo should the manuscript be accepted for publication

plant biology↗

bioRxiv2021

The impact of heat on human physical work capacity; Part III: the impact of solar radiation varies with air temperature, humidity, and clothing coverage.

It is well-known that heat impacts human labour/physical work capacity (PWC), but systematic evaluations of solar radiation (SOLAR) effects and the interaction with air temperature and humidity levels and clothing are lacking, as most lab-studies are conducted in semi-nude subjects without radiation or only in a single climatic condition. Due to the high relevance of SOLAR in various occupations, this study quantified how SOLAR interacts with clothing and other primary environmental factors (air temperature/humidity) of importance to determine PWC in the heat. The data allowed the development of a SOLAR correction factor for predicting PWC in major outdoor industries. Fourteen young adult males (7 wearing a standardised work coverall (0.9 Clo), 7 with shorts and trainers (0.3 Clo) walked for 1-hour at a fixed heart rate of 130 b{middle dot}min-1, in seven combinations of air temperature (25 to 45{degrees}C) and relative humidity (20 or 80%), with and without SOLAR (800 W/m2 from solar lamps). Cumulative energy expenditure in the heat, relative to the work achieved in a cool reference condition, was used to determine PWC%. Skin temperature was the primary determinant of PWC in the heat. In dry climates with exposed skin (0.3 Clo), SOLAR caused PWC to decrease exponentially with rising air temperature, whereas work coveralls (0.9 Clo) negated this effect. In humid conditions, the SOLAR-induced reduction in PWC was consistent and linear across all levels of air temperature, and clothing conditions. WBGT and UTCI based prediction equations of PWC represented SOLAR correctly. For heat indices not intrinsically accounting for SOLAR, correction factors are provided enabling forecasting of heat effects on work productivity.

physiology↗