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Ribosomal proteins are major substrates of starvation-induced endosomal microautophagy in Drosophila.

Maintenance of cellular homeostasis requires tight coordination between protein synthesis and degradation, particularly at old age and under conditions of stress including starvation. Autophagy contributes to sustain this balance by degrading cytoplasmic proteins and organelles. It thus is essential to prevent the accumulation of damaged proteins and organelles and to recycle nutrients. Of the three forms of autophagy, macroautophagy, chaperone mediated autophagy, and (endosomal) microautophagy (e-MI), the latter remains the least well understood. During e-MI, cytosolic substrate proteins are captured into late endosomes via ESCRT-dependent multivesicular body formation and then degraded in late endosomes or lysosomes. e-MI is thought to contribute to protein quality control under basal conditions and under stress. Importantly, very little is known about the endogenous substrates of e-MI in flies and thus about its physiological role. Performing integrative multi-omic analyses in Drosophila larval fat body that has functions similar to mammalian liver and adipose tissue, we identified 153 high-confidence endogenous e-MI substrates with the degradation of ribosomal proteins by e-MI being the most strongly affected functional category. Generally, we found that starvation caused the depletion of proteins involved in translation, aminoacyl-tRNA synthesis, and ribosomal biogenesis, without affecting their level of transcripts. Importantly, we observe a striking specificity between e-MI and macroautophagy, as the two pathways largely target distinct protein sets including different subsets of ribosomal proteins. Our metabolomic analysis further shows that genetic inhibition of e-MI reverses the reduced levels of amino acid caused by starvation. Together, our findings reveal ribosome turnover as a central physiological function of Drosophila e-MI and establish e-MI as a pathway driving metabolic adaptation during starvation.

cell biology

Tumor γδ T-cell abundance is associated with favorable cancer treatment outcomes

Purpose: Clinical response to immune checkpoint blockade (ICB) remains variable. We asked whether immune-cell populations in the tumor microenvironment (TME) are associated with benefit across treatments and tumor types. Experimental Design: We analyzed pretreatment bulk tumor RNA-seq from ICB cohorts and TCGA. Gene-level effects associated with ICB response or TCGA survival were projected onto Human Primary Cell Atlas profiles of 157 cell types. Cox and mixed-effects models accounted for cancer type, cohort, and therapy, as appropriate. After {gamma}{delta} T cells emerged as a leading population, we adjusted their associations for eight CD8 estimators and evaluated them using TRUST4-based TRG/TRD reconstruction and single-cell RNA-seq. Results: {gamma}{delta} T-cell programs were among the signatures consistently associated with ICB response and favorable TCGA survival. Across ICB cohorts, {gamma}{delta} T-cell abundance was associated with response (n=1,356; OR, 1.38; 95% CI, 1.23-1.56) and overall survival (n=1,074; HR, 0.82; 95% CI, 0.76-0.88), with associations persisting after CD8 adjustment. ICB-response-associated cell-type profiles were strongly concordant with chemotherapy response (r=0.92) and moderately concordant with radiation response (r=0.58); targeted and hormone therapy analyses were underpowered. TRUST4 reconstruction and single-cell RNA-seq provided orthogonal support for the {gamma}{delta} signal. Conclusions: Pretreatment {gamma}{delta} T-cell abundance was associated with favorable ICB outcomes and survival across cancers, while related cell-type programs extended to selected non-immunotherapy response settings. Although associative and context dependent, these findings support prospective evaluation of {gamma}{delta} T-cell abundance as a candidate tumor-immune biomarker.

immunology

The DYNAM-O Toolbox: Characterizing Individualized Neural Signatures in Sleep EEG

Conventional sleep electroencephalography (EEG) measures often rely on predefined bands, thresholds, and averages that incompletely capture transient oscillatory dynamics across an entire night. Here, we introduce the Dynamic Oscillation (DYNAM-O) Toolbox, an open-source, cross-platform (MATLAB, Python, and Rust) software package for data-driven characterization of individualized neural dynamics in sleep EEG. DYNAM-O identifies transient oscillations as time-frequency peaks on multitaper spectrograms using a novel multi-resolution procedure, computes intrinsic and sleep-state-dependent extrinsic features for each event, and represents the overnight distributions of tens of thousands of TF-peaks as feature histograms spanning oscillation frequency, slow oscillation power, and slow oscillation phase. This distributional representation preserves continuous brain-state variation that could be obscured by averaging within conventional sleep stages. The toolbox further provides Gaussian and spline basis-based dimensionality reduction, visualization, and whole-histogram statistical testing tools to support both exploratory and hypothesis-driven analyses. To demonstrate its use for group-level inference, we analyzed overnight C3-channel EEG from 133 adults (71 females, 72 males; ages 20-35 years) in the Cleveland Family Study. Whole-histogram and parameterized-mode analyses reproduced the established higher center frequency of fast-spindle activity in females and additionally revealed greater low-alpha transient oscillatory activity in females, a pattern outside the conventional sleep spindle range. By completing the analysis cycle from TF-peak extraction to statistical inference, DYNAM-O provides an accessible and interpretable framework for studying individualized sleep physiology and identifying subtle, reproducible electrophysiological patterns.

bioinformatics

Aberrant neuronal cell cycle re-entry induces late-onset Alzheimer's disease relevant neuropathological and gene expression changes

Aberrant neuronal cell cycle re-entry (NCCR) is an alternative pathogenic mechanism in Alzheimer disease (AD) that has gained substantial support in the literature. The pathogenic role of ectopic NCCR is supported by our past work demonstrating that SV40T-mediated NCCR in adult mice can induce numerous pathologies associated with AD. Since NCCR is chronically induced for an extended period in the mouse model which gives rise to numerous pathologies including neuroinflammation, many of these neuropathological changes could simultaneously participate in driving disease progression. We hypothesized that the NCCR is a primary pathogenic driver and that halting this disease process at a later age could be sufficient for preventing the progression of AD-related pathologies. Here we show that modulation of NCCR at a later age prevents the progression of AD pathologies, including Abeta; and tau pathologies. Furthermore, functional genomics analysis demonstrates the late-onset AD (LOAD)-relevance of NCCR. Our findings suggest that our NCCR mouse model could help identify novel therapeutic targets that could aid in preventing AD progression.

neuroscience

Physiological and anatomical leaf acclimation of understory trees subjected to a through-fall precipitation exclusion in a temperate rain forest in southern South America.

Water input is a key component of the ecosystems. Water defines the functionality, composition, and structure of biomes; therefore, any change in its availability would have an impact on ecosystem features. Moreover, a change in the water balance of an ecosystem affects its persistence as well as biochemical cycles, such as the carbon and nitrogen. Forests are ecosystems structured using high amounts of water. Thus, trees, the oldest living plants, are the prime species in these ecosystems and are the main managers of this abiotic element. Trees uptake water from the soil, store it in their biomass, and exchange it with the environment through leaf stomata. They also intercepted rainfall and fog with their canopies. All of this water is also transmitted to the entire biological diversity that inhabits these ecosystems. Any change in water input affects the web described above. The ability of trees to modify their anatomy or processes, that is, to acclimate to novel climates, is of great advantage in maintaining the characteristics of ecosystems. In this study, we took advantage of a precipitation exclusion experiment to reveal the acclimation of shade-tolerant understory trees, which will be the main component of a cold temperate rainforest in the future. We evaluated different anatomical and physiological leaf traits involved in the use of water by these species. We hypothesized that, as observed in similar experiments, species would adopt more conservative water-use strategies by adjusting their functional traits accordingly. Contrary to our hypotheses, we found that understory tree species inhabiting this temperate ecosystem will not become more conservative when using water. In minimal, but significant differences, most of the studied species displayed traits, in the precipitation exclusion treatment, that were demonstrated to be water spender, rather than conservative. We attributed these contrasting changes to root metabolism alleviation due to the flooded soils of Chiloe inhabited by these forests.

ecology

Ex vivo human tumor slices more accurately predict patient responses to an oncolytic virus than in vivo mouse models

Immunotherapies, including oncolytic viruses (OV), are promising therapies that can enhance anti-tumor immune responses. However, preclinical success of immunotherapies in mouse models has not always translated to clinical benefit in cancer patients. This study compared preclinical efficacy and mechanism of action for ASP9801, a vaccinia virus expressing IL-7 and IL-12, using mouse models of colorectal cancer (CRC) in vivo and in human organotypic tumor slice models ex vivo. The murine surrogate for ASP9801 significantly reduced tumor volumes in treated and abscopal tumors in two different CRC models in vivo (MC38 and RO100). Treatment efficacy was accentuated when combined with anti-PD1 treatment, and single-cell RNA sequencing analysis revealed depletion of tumor cells and increased T cell infiltration and activation in both treated and abscopal tumors. However, human tissue analysis ex vivo (E-slices) using PDX models and patient samples showed that ASP9801 is not effective in CRC, consistent with clinical trial results. On the other hand, ASP9801 was highly effective in GBM, indicating indication-specific efficacy of ASP9801, and how E-slice assays can be used to identify treatment-sensitive indications. This study demonstrates the superiority of E-slices over mouse models for predicting clinical response and its utility in planning clinical trials.

cancer biology

Synergistic targeting of EP300/CBP and EYA co-activators collapses the rhabdomyosarcoma core regulatory circuit

Rhabdomyosarcoma (RMS) is a multi-subtype, high-risk pediatric sarcoma with a low mutational burden. The mutations found in RMS often alter genes involved in transcriptional control. Approaches to target dysregulated RMS transcription have remained elusive. Here, we develop a novel approach to target RMS transcription comprising simultaneous targeting of two distinctly acting transcriptional co-activators. We discover a common identity-controlling pan-RMS core regulatory circuit (CRC) composed of oncogenic and lineage-specific myogenic master transcription factors (mTFs). Using a super-enhancer-based reporter screen, we identify the EP300/CBP inhibitor A485 as a potent inhibitor of the pan-RMS CRC, though with efficacy-limiting toxicities. To enhance efficacy, we identify the mTF-binding co-activator EYA2 as a co-factor of this pan-RMS CRC and exploit a new second-generation EYA1/2 inhibitor, LG1-34, to disrupt its function. Combined co-activator inhibition inactivates the CRC and synergistically reduces RMS growth. This strategy dually targets CRC-associated co-activators to cooperatively suppress the RMS transcriptome and enforce cell death.

cancer biology

ENPP3 expressed by HER2-positive breast cancer cells is associated with good prognosis by restraining epithelial-to-mesenchymal phenotype

Background Ectonucleotide pyrophosphatase/phosphodiesterase 3 (ENPP3/CD203c) is largely studied as a marker of mast cells and basophils. By depleting extracellular ATP, it prevents excessive activation of mast cells and basophils, hence reducing inflammation and allergic reactions. Recent findings have also shown that Enpp3 can deplete cGAMP, another molecule involved in STING activation and IFN-mediated pro-inflammation. Little is still known regarding the role of Enpp3 in non-immune cells although a few reports have described its expression in healthy tissues and tumors. Methods In silico analysis were performed to investigate the expression levels and the prognostic value of Enpp3 in breast cancer, together with ovarian, prostate and colon carcinoma. ENPP3 expression was evaluated in formalin-fixed, paraffin-embedded tumor samples of breast cancer patients by immunohistochemistry, and in mouse mammary cancer cell lines by western blots. Cells were treated with EGFR ligands to stimulate the EGFR/HER2 axis. A mouse-derived mammary cancer cell line was engineered by CRISPR/Cas9 to introduce a GFP sequence under the control of the Enpp3 promoter. GFP-positive and -negative cells were sorted and analyzed by gene expression profiling to identify genes and pathways associated with Enpp3 expression. Finally, wild type and Enpp3 knockout cells were injected in the fat pad of Wsh mice, which do not have mast cells, to evaluate the growth of the tumors which were further analyzed by immunohistochemistry. Results We provide evidence that HER2-positive cells express higher levels of ENPP3 in samples of breast cancer patients. Moreover, in vitro models confirmed that HER2 expression and EGFR stimulation result in up-regulation of Enpp3. We identified pathways that can concur to Enpp3 expression and showed that in vivo the absence of Enpp3 promotes tumor growth and development of tumors with a marked epithelial-to-mesenchymal phenotype. Finally, in a small cohort of HER2-positive breast cancer patients, we found that ENPP3 expression correlates with increased relapse-free survival. Conclusions Despite its potential immunosuppressive role, our findings support the notion that ENPP3 expression is promoted by HER2 in breast cancer, and that it is endowed with a positive prognostic value.

cancer biology

Scaling recipes for single-cell RNA sequencing foundation models: when do scaling laws hold?

Deep learning models exhibit empirical scaling laws whereby performance changes predictably with model size, dataset size, and training compute. Although these relationships are well established in domains such as language and image modelling, their applicability to biological data remains unclear. Here, we investigate scaling behaviour in foundation models trained on large collec tions of single-cell transcriptomes. We show that pre-training loss decreases systematically with model capacity and training compute, exhibiting a power law dependence on model size. The strength and regularity of these trends differ between model formulations. We identify and quantify empirical relationships linking the optimal learning rate and depth-to-width ratio to model size and depth or compute. These results demonstrate that scaling principles extend to transcriptomic modelling. More broadly, they provide a quantitative framework for estimating the expected returns from additional resources and selecting suit able hyperparameters and architectures, thereby supporting the development of increasingly capable foundation models for omics data.

bioinformatics

GDF15 contributes to inflammasome-associated excessive mechanoresponses of hyperlipidemic PdL fibroblasts

Orthodontic tooth movement relies on a tightly regulated pro-inflammatory and pro resorptive mechanoresponse of local periodontal ligament fibroblasts (PdLFs). Dysregulation is linked to complications such as root resorption and tooth loss. Hyperlipidemic conditions promote excessive PdL mechanoresponses, with growth differentiation factor 15 (GDF15) acting as potential regulator. This study examined the contribution of the inflammasome/pyroptosis pathway as underlying mechanism for dysregulated mechanoresponses. Human PdLFs were treated with palmitic acid (PA) or oleic acid (OA) for six days before 24 hours of compressive loading. PA increased CASP1, CASP4, and CASP3 activity, secretion of IL-1{beta}, IL-18, and HMGB1, and LDH release. Pharmacological blockade and siRNA-mediated knockdown of inflammasome- and pyroptosis-related targets revealed that NLRP3, CASP1, CASP4, and GSDMD partially contributed to monocyte and osteoclast overactivation. Silencing PA-increased GDF15, partially normalized the phenotype, at least in part by inflammasome/pyroptosis regulation. GDF15 acted through extracellular, and a nuclear signaling route, each accounting partially to this phenotype. Together, GDF15 partially regulates the PA-induced, pyroptosis-associated overactivated mechanoresponse alongside pyroptosis-independent mechanisms suggesting it as an interesting target for potential clinical interventions.

cell biology

Three new species of Thelymitra (Diurideae, Orchidaceae) endemic to Aotearoa New Zealand.

Three new species of sun orchid (Thelymitra) endemic to Aotearoa New Zealand are here described. These are T. palustris, T. scabrifolia and T. semaphora. The morphological distinctiveness of these three species has been acknowledged for decades; however, their taxonomic status has remained unresolved. Evidence from existing karyological data, recently generated DNA sequence data (LFY and ycf1) and morphological studies from historical and fresh collections are used here to support their formal description. Both, T. palustris and T. semaphora are restricted to wet habitats north of Auckland (North Island). Thelymitra scabrifolia inhabits mostly scrub, and it has a similar northern North Island distribution, but is has been found also in Manawat[a]whi / Three Kings Islands and historically in Otago (South Island). All three species are polyploids and are of conservation concern.

plant biology

Topological Closure Drives Structural Stabilization and Fast Cooperative Dynamics in Crowded Circular Polysomes

In linear polysomes, excluded-volume interactions among ribosomes can induce dimensional reduction of mRNA. Yet linear architectures allow steric stress to relax at open ends-- limiting how strongly crowding can remodel the mRNA's structure and dynamics. Using coarse-grained molecular-dynamics simulations, we compare circular and linear polysomes over a range of ribosome densities. Circular closure selects a predominantly quasi-planar global conformational ensemble, as indicated by a shape dimensionality dshape {approx} 2 over a range of ribosome densities. Crucially, circular topology and ribosome crowding act cooperatively to suppress structural fluctuations. While closure alone or linear crowding reduces relative global size fluctuations ({Delta}Rg/Rg) only to {approx} 0.16, their combined effect drives this fluctuation down to {approx} 0.07. Within this stabilized architecture, increasing ribosome density drives a distinct in-plane reorganization: the ring becomes more isotropic, global size fluctuations are strongly suppressed, and the scaling exponent increases toward {nu} [~=] 0.74 - 0.77, consistent with two-dimensional self-avoiding walk-like value over the accessible finite-size window, 1000 [≤] N [≤] 4969. Closure shortens the radius-of-gyration decorrelation time of circular polysomes by 40-fold relative to matched linear systems, reflecting the topological elimination of free ends. Within this closureselected ensemble, ribosome crowding further reduces the decorrelation time by up to 20% at the highest density. A fluctuation-informed crossover model links the density dependence of the global scaling exponent to inter-ribosomal subchain statistics. These results distinguish the geometric role of circular closure from the density-dependent steric response that it enables, revealing a confined yet dynamically responsive conformational regime for circular polysomes.

biophysics

A configuration-resolved benchmark of differential abundance analysis methods for human gut 16S rRNA microbiome data

Tools for differential abundance testing of 16S rRNA data are conventionally treated as discrete methods, and benchmarks have accordingly sought to determine which tool performs best. However, each tool offers an array of configurations based on different normalisation, transformation, reference choice, and sensitivity filtering methods, and the specific impact of these configurations on performance has rarely been systematically investigated. We benchmarked five widely used tools (MaAsLin 2, MaAsLin 3, edgeR, ALDEx2, and ANCOM-BC2) across 18 configurations, using simulated communities and human gut profiles with implanted signals, at two taxonomic resolutions and across several design factors. Configuration accounted for as much performance variation as the choice of tool itself, with the ranking of two tools depending on which of their settings are compared. Individual parameters behaved as switches between opposite error regimes rather than as graded adjustments, and the settings carrying this weight are identifiable in advance. These behaviours were reproducible across data sources and resolutions. Our results define a configuration-aware framework for matching a tool and its settings to the cohort, study design, and feature resolution, establishing that a differential abundance result is interpretable only if the configuration used for the analysis is reported.

microbiology

From Bile Acids to a Gas-Producing Microbiome Phenotype: A Novel Mechanism of Host-Microbiome Communication

Background Microbiome-derived metabolites regulate host physiology, yet bacterial gaseous metabolites remain largely overlooked. Traditionally regarded as fermentation end-products, bacterial gases may act as biologically active mediators of host-microbiome communication. We hypothesized that bile acids regulate bacterial gaseous metabolism and influence host epithelial responses. Methods A high gas-producing clinical Escherichia coli isolate from a patient with moderately severe acute pancreatitis was cultured with selected primary and secondary bile acids. Gas production was assessed by pressure measurements, GC-TCD and GC-MS. Biological activity was evaluated by indirect exposure of Caco-2 and PANC-1 epithelial cells, followed by apoptosis/necrosis assays and whole-transcriptome RNA sequencing. Results Bile acids markedly reshaped bacterial gaseous metabolism. Cholic acid and deoxycholic acid promoted intense gas production, whereas chenodeoxycholic acid almost completely abolished it. Despite minimal apoptosis and necrosis, bacterial gaseous metabolites induced extensive transcriptional remodeling. Caco-2 cells showed stronger responses than PANC-1 cells, particularly to deoxycholic acid-derived gases, involving inflammatory signaling, extracellular matrix remodeling, epithelial plasticity, stress responses, and cancer-associated genes including PTGS2, MMP1, PLAUR, NR4A2, and SERPINE1. PANC-1 cells exhibited a more restricted response involving oxidative stress, proteostasis, and autophagy-associated pathways. Conclusions Our findings indicate that bacterial gases are a previously underrecognized class of microbiome-derived signaling molecules capable of modulating host gene expression independently of direct bacterial contact. We identify a gas-producing microbiome phenotype regulated by bile acid composition, linking microbial metabolism with epithelial signaling. These findings expand the concept of host-microbiome communication and provide a framework for investigating bacterial gaseous metabolites in intestinal and pancreatic diseases.

microbiology

The emerging medium-scale: Prioritising fisheries management for elasmobranch conservation.

Fishing pressure has substantially increased over time and elasmobranchs are among the most vulnerable marine taxa impacted. 'Small-scale' and 'large-scale' are terms frequently used to describe fisheries, yet definitions used across the globe are inconsistent. The global impact of small-scale fisheries on elasmobranch decline is increasingly evident. However, ambiguous vessel-capacity classifications undermine effective conservation management. Technological advancements have led to the emergence of medium-capacity vessels that sit between small and large-scale classifications, creating regulatory gaps that increase bycatch impacts on vulnerable elasmobranchs. Beyond vessel size, the gear specificities and practices also affect interaction with species caught incidentally, and can alter bycatch risk for vulnerable elasmobranchs. Manta and devil rays (collectively, mobulids) represent a pelagic ray group that includes species listed as Critically Endangered with high risk of extinction, largely due to bycatch threats. To prioritise fisheries management for conservation, we assess the contribution of fishing gear specifications and practices to mobulid bycatch as a case study in their largest fishery globally. We use a Huber-robust extension to a Hurdle negative binomial model to assess the impact of fishery characteristics and operational specificities on mobulid bycatch risk. We find that within the Food and Agriculture Organization (FAO) of the United Nations' broad international fleet classification of small-scale vessels based on overall length ([≤]24 m), the 'medium-capacity vessels' in India are twice as likely to catch mobulids than small-scale vessels. Further, increased fishing intensity, measured in five-day increments, doubles mobulid bycatch risk. Our results indicate the emergence of a distinct medium-capacity fishery class in rapidly developing blue-economy nations, shaped by rising technological capacity and exemptions from large-scale management measures. We propose a comprehensive re-conceptualisation of small-scale fisheries to ensure that advanced medium-capacity vessels are subject to management measures commensurate with their bycatch impact. Our recommended re-conceptualisation is complementary to FAO's SSF characterisation matrix and would promote fishery-level sustainability and enable bycatch risk mitigation for elasmobranchs, including manta and devil rays. Further, for congruence between elasmobranch demography and regulations, we recommend that fisheries management measures distinguish vessel capacities for elasmobranch bycatch risk and apply biologically relevant regulations to the associated fisheries scale.

ecology

Joint ancestry inference reveals the landscape of archaic introgression in admixed populations

Studying the evolutionary history of archaic segments in recently admixed individuals requires inferring both continental and archaic ancestry in admixed genomes. Here, we present TRACTINATOR, the first deep-learning method for simultaneous inference of continental and archaic ancestry in admixed human genomes. The model combines SNP sequences, population allele-frequency information, and S* statistics to improve both inference tasks. By learning relationships between haplotypes and population allele frequencies, TRACTINATOR can generalize across genomic regions and even across different genomic datasets. We train our model using both real and synthetic data, and show that augmenting with synthetic data improves accuracy for both continental and archaic ancestry inference. Finally, we apply TRACTINATOR to admixed Latin American populations from the 1,000 Genomes Project, revealing how archaic ancestry is distributed within chromosomal segments of African, European and Indigenous American ancestry in Latin American individuals. For candidates of adaptive introgression, we also infer whether the archaic haplotype was introduced via European or Indigenous American ancestors.

bioinformatics

miR-34/449 miRNAs regulate choroid plexus ciliogenesis to control cerebrospinal fluid production

A developmental increase in cerebrospinal fluid (CSF) production during development is essential for neuronal growth and ventricular expansion. A key regulator of CSF production is the specialized sensory multicilia of the choroid plexus (ChP), which mediate non-canonical Sonic hedgehog (Shh) signaling to suppress water channel and ion transporter expression, thereby limiting CSF production. ChP multicilia progressively shortens during development, attenuating Shh signaling and promoting CSF production. Here, we identify miR-34/449 miRNAs as essential regulators of ChP multiciliogenesis. Whereas mutations in canonical ciliogenesis genes elevate CSF production and contribute to hydrocephaly, deletion of miR-34/449 reduces CSF volume and causes microcephaly. Loss of miR-34/449 miRNAs causes excessive basal body amplification, defective basal body docking, and failure of developmental multiciliary shortening. Consequently, miR-34/449-deficient ChP cilia remain abnormally long and fail to attenuate Shh signaling, resulting in sustained repression of water channel and ion transporter expression and reduced CSF production. Mechanistically, miR-34/449 miRNAs directly target Gmnc, a master transcriptional regulator of multiciliogenesis, to restrain basal body amplification and promote basal body docking. Together, our findings identify miR-34/449 miRNAs as critical regulators of ChP multiciliogenesis and establish the developmental remodeling of ChP multicilia as a mechanism to couple Shh signaling dynamics to developmental control of CSF production.

developmental biology

AWET -- Arthropod Weight Estimation Tool

Arthropods drive essential ecosystem processes such as pollination, decomposition, and nutrient cycling and are widely used as indicators of ecosystem condition and function. Among various arthropod-derived metrics, body weight is a key variable in functional ecology and frequently assessed as dry body weight. However, drying arthropod specimens limits the samples future potential for research, as it prevents further processing such as trait measurements or species identification. Here, we present AWET (Arthropod Weight Estimation Tool), an open-source application for automated estimation of individual fresh body weight and extraction of morphometric measurements from standardized images of pre-sorted arthropod samples. AWET combines automated image analysis with taxon-specific allometric regression models to estimate fresh body weight while simultaneously quantifying body length, width, area, and specimen abundance. The software operates with standard imaging equipment, requires no machine-learning-based classification or segmentation, and allows users to define taxonomic groupings according to their objectives. By preserving specimens for downstream analyses while processing large numbers of individuals within milliseconds, AWET provides an efficient, non-destructive, and cost-effective workflow for high-throughput arthropod phenotyping. The software is a practical and expandable tool for biodiversity monitoring projects investigating changes in arthropod biomass, abundance and individual morphometric measures.

ecology