Fungal Ecology

Background: Human activities such as mining generally lead to increased heavy metal concentrations in the environment. While traditional remediation techniques are often costly, the use of fungi as bioremediators, known as mycoremediation, is increasingly gaining attention as a sustainable approach for removal of heavy metals. Here, we evaluated heavy metal levels inside the Kiirunavaara iron ore mine in Northern Sweden and analysed fungal responses to various metal concentrations by comparing growth and metal uptake in mine-derived isolates and closely related control isolates. Results: Sediments inside the mine were enriched in heavy metals compared to those from the outlet of the mine to natural lakes. Six Fusarium isolates were recovered from contaminated mining environments: five isolates from inside the mine were identified as Fusarium oxysporum, and one isolate from the outlet was identified as Fusarium tricinctum. Isolates from the mine and outlet showed overall higher survival and biomass production in presence of copper, iron, and zinc across a range of concentrations (up to 1000 mg/L) compared to control isolates. At the same time, these isolates often exhibited reduced relative metal uptake. As a result, mycoremediation potential, assessed as total uptake in the grown mycelium, was isolate-dependent. Conclusions: Based on these results, we conclude that Fusarium isolates from the Kiirunavaara mine show increased growth in media enriched with heavy metals compared to closely related control isolates. We additionally show that mycoremediation potential is not necessarily associated with environmental origin. Instead, mycoremediation potential should be evaluated on a case-by-case basis for each isolate and based on specific needs for mycoremediation.

Microbial succession can be used to estimate the postmortem interval (PMI); however, the impact of spatial variability within the cadaver decomposition island (CDI) is not well understood. This study examined spatial variation in necrobiome communities where soil samples were collected over time and across spatial locations from the CDIs of two human body donors. Microbial communities were characterized using 16S rRNA sequencing and statistical modelling of variation and PMI were conducted. Necrobiome community metrics showed no significant differences across anatomical sampling sites within the CDI at a single timepoint. Temporal modelling identified 11 taxa with significant relationships to PMI in one donor, with spatial sampling having a minimal impact on the PMI relationships. Non-linear approaches also identified taxa with likely PMI signals in the second donor. These findings demonstrate that opportunistic sampling can capture robust linear and non-linear PMI signals in later decomposition stages.

Alternaria fungi produce various structurally diverse mycotoxins, several of which exhibit immunomodulatory properties. Among these, alternariol monomethyl ether (AME), alternariol (AOH), alterperylenol (ALTP), altertoxin I (ATX-I), and altersetin (AST) have been reported to suppress lipopolysaccharide (LPS)-induced inflammatory responses. However, the precise molecular mechanisms underlying these effects remain unclear. The present study aimed to elucidate how these selected Alternaria mycotoxins (0.1-50 M) target the NF-{kappa}B signaling pathway in THP-1 monocytes. Key components of the NF-{kappa}B cascade were analyzed by immunofluorescence microscopy, Western blotting and qRT-PCR. Nuclear translocation of NF-{kappa}B p65 and its phosphorylated form (p- NF-{kappa}B p65) was assessed by Western blot, while cytokine responses were determined at transcript (qRT-PCR) and protein (ELISA) levels. Moreover, in silico docking analyses were performed to investigate potential interactions of the toxins with IKK{beta}, and receptor-mediated crosstalk was studied using the glucocorticoid receptor (GR) antagonist RU486. Co-treatment with RU486 attenuated the immunosuppressive effects of 1 and 5 M AOH, indicating partial involvement of GR-dependent mechanisms. AME, AOH, ALTP, ATX-I, and AST increased total I{kappa}B levels while reducing its phosphorylated form. Additionally, AST and ALTP decreased the protein levels of Toll-like receptor 4 (TLR4), the I{kappa}B kinase (IKK) complex, NF-{kappa}B p65, and p- NF-{kappa}B p65. While AOH (5 M) and AST (25 M) reduced nuclear translocation of p65 and p-p65, ALTP (2 M) enhanced nuclear localization despite decreasing cytokine expression. Together, these findings suggest toxin-specific interference at multiple regulatory levels of NF-{kappa}B signaling and provide novel mechanistic insight into the immunomodulatory effects of Alternaria mycotoxins.

Tropical dry evergreen forests (TDEFs) are a unique and highly threatened forest type of the dry tropics. Their restoration could be strengthened if native species demonstrate carbon sequestration comparable to widely used non-native trees. We assessed biodiversity and carbon sequestration in a restored TDEF in India, developed over 50 years from a largely barren landscape. The site now supports high woody-plant diversity, with 91 native species across 34 families. Aboveground biomass (AGB) averaged 66.91 +/- 41.2 Mg/ha comparable to seasonally dry tropical forests globally. Although native species were planted more recently and are shorter than non-natives, they contributed 23.86 +/- 23.4 Mg/ha to AGB and show potential for future increases in basal area. Given their comparable wood densities and capacity to attain similar heights, native species are predicted to sequester carbon at levels similar to non-natives in the long term. AGB was unrelated to species diversity. Overall, native TDEF species can achieve carbon storage while maintaining ecological integrity.

Global climate change has increased the frequency and intensity of drought events, making it urgent to understand how native species respond to water deficit (WD). In biodiverse environments such as tropical forests, simple methods are needed to study multiple species simultaneously. This can help predict how natural environments will respond to climate change and guide the strategic selection of drought-resistant species for reforestation. This study aimed to: (1) adapt an existing simple and inexpensive method to apply a controlled WD on tree seedlings from tropical species commonly produced in nurseries for restoration projects, suitable for greenhouse experiments; and (2) evaluate the effectiveness of this method in generating ecophysiological responses to WD that allow the estimation of species' drought resistance. Ten native tree species from the Semideciduous Seasonal Forest (SSF), a phytophysiognomy of the Atlantic Forest, were selected. An existing method was adapted to implement capillary irrigation, in which the bases of the seedling tubes were placed in floral foam blocks positioned inside 15 L plastic containers filled with water. A gradual and severe WD was applied to five seedlings of each species by removing all water from the containers, leaving only the water retained in the saturated floral foam available for plant uptake. The remaining seedlings were maintained well-watered (containers full and foam saturated) as the control group. Stomatal conductance (gs) was measured daily for all seedlings until they reached 50% or less of their initial gs (igs); at this point, stem water potential ({Psi}w) was measured. Both gs and {Psi}w differed significantly among treatments and species (p < 0.01). Ficus guaranitica and Heliocarpus popayanensis were the only species that did not show significant {Psi}w differences between treatments, indicating higher drought resistance. In contrast, Campomanesia xanthocarpa and Eugenia uniflora had the lowest {Psi}w values under WD, suggesting lower drought resistance. The remaining species were distributed along a gradient of responses to WD. Additionally, no correlation was found between {Psi}w and gs at 50% igs in the WD group (rho = 0.16, p = 0.26). The method proved effective in inducing controlled WD and generating measurable ecophysiological responses, offering a useful tool for screening native species for drought resistance.

Premise: Rapid and accurate plant species identification is a critical challenge exacerbated by the taxonomic impediment. Although portable near-infrared (Micro NIR) spectroscopy represents a promising solution, the current absence of standardized protocols and a fundamental understanding of how critical acquisition and analysis parameters influence accuracy remain significant barriers. This study focused on the systematic optimization and validation of a comprehensive workflow designed to maximize the reliability of plant identification using this technology. To ensure methodological robustness across diverse foliar matrices, four vascular plant species were strategically selected as a representative test set to encompass morphological extremes, including significant variations in leaf thickness, pubescence, and surface texture. Methods: Using a portable spectrometer on herbarium specimens (exsiccate) of four vascular plant species, we systematically tested five spectral backgrounds, seven pre-processing methods, and four classification models. Subsequently, we optimized the number of spectral readings and evaluated the influence of the leaf scanning surface (adaxial vs. abaxial) on model accuracy. Results: The highest-performing combination was a Shiny Aluminum background, Second Derivative pre-processing, and a Random Forest model, which achieved a mean cross-validated accuracy of 99%. An average of just three spectral readings from the adaxial (upper) leaf face was sufficient to saturate model performance, proving statistically superior to other approaches (p < 0.001). Discussion: This study establishes a validated, high-accuracy protocol for plant species identification from herbarium specimens using portable NIR, offering a powerful tool for biodiversity studies. Direct applicability to fresh plants in the field requires future validation to account for the spectral influence of moisture variability.

Melanins are biological macromolecule with immense functionality synthesised by a wide spectrum of living organism. It is mainly synthesised by the oxidative polymerization of indolic and phenolic compounds through several enzymatic process. It has wide spread application in agriculture, cosmetic and therapeutic industry due to its various properties including antioxidation ability, UV protection efficiency and anticancer activity. Because of this wide range of application in different sectors, large scale production and commercialization attains enormous consideration. The present study deals with the effect of 12 different process parameters on melanin production viz., production media, incubation time, inoculum concentration, pH, temperature, agitation, carbon source, phosphate and magnesium source, CuSO4.5H2O, sodium chloride and L-tyrosine on melanin production by Pseudomonas stutzeri strain BTCZ 109 obtained from Arabian sea sediments was evaluated. After optimizing the important process parameters, the bacteria showed about ~4.65 fold increase in melanin production compared to unoptimized cultural conditions. The melanin optimized through this method was found to be nano sized. The Nano sized DOPA melanin in treating Skin cancer cell line SK ML28 which showed a dose-dependent activity with an IC50 value of 164 g/mL. All these results highlight the therapeutic efficiency of DOPA melanin Nano particle as promising bioactive molecule.

Microbial fuel cells (MFCs) technology offers sustainable electricity production. Current research largely focuses on few select model organisms, therefore the true prevalence of exoelectrogenesis amongst bacteria remaining largely unknown. We present a broad-scale survey of monomicrobial electricity production among environmental bacterial isolates inoculated in MFCs, using model organism Shewanella oneidensis MR-1 as a benchmark. Of the assessed taxa, 11-22% displayed exoelectrogenic activity, exceeding current predictions and identifying a further three novel exoelectrogenic species. Phylogenetic analysis based on the 16S sequences enabled the evolutionary relationship between isolates to be visualised, revealing that exoelectrogenesis is non-randomly distributed and phylogenetically conserved. Polarisation studies were implemented, revealing that numerous electron transfer mechanism were being utilised to perform exoelectrogenesis. The results of this study imply that bacterial electricity production is more widespread amongst culturable bacteria than previously estimated, with implications for bioprospecting novel exoelectrogens and predicting electrogenic activity in diverse microbial communities.

In order to feed a growing global population without silencing nature, conceiving agricultural management strategies reconciling yield and conservation goals is key. Using numerical simulations of a metacommunity model, we explore the possibilities for compromise offered by spatial management strategies of farmed areas. Each strategy is characterized by its farming intensity, the proportion of farmed lands and their spatial aggregation. We show that achieving equitable yield-biodiversity compromise is difficult. While conciliatory strategies offering top yield and biodiversity are typically not possible, accepting slightly lower yields (ie, "Pretty Good Yield strategies") allows to recover substantial biodiversity. Such reconciliation possibilities are limited for species with small dispersal. Yield increases mainly through farmland expansion, whereas farming intensity strongly influences biodiversity, increasing it at low intensity before decreasing with further intensification. Finally, we demonstrate that reconciliation is easier if agricultural production relies on biodiversity through ecosystem services.

The coast redwood (Sequoia sempervirens) is a long-lived, hexaploid conifer of high ecological, cultural, and economic value whose range has been greatly reduced by historical logging. Effective restoration and conservation depend on understanding patterns of genetic differentiation across the redwood range to delineate populations for management prioritization. Yet, past range-wide studies provided only a partial picture of population structure in coast redwood as they relied on a limited set of genetic markers or limited sampling, as sequencing was done on the same range-wide provenance collection. Here, we analyze 334,029 SNPs from a new range-wide set of 224 individuals using a dosage-based approach that accounts for polyploidy. Principal coordinates and neighbor-joining analyses reveal clear latitudinal genetic differentiation, with a distinct break south of San Francisco Bay. Outlier SNP analysis indicates new candidate loci involved in salinity tolerance, climate stress response, and nutrient uptake, suggesting potential local adaptation. These results point to the central role of geography in shaping genetic variation in coast redwood and give scientific basis for designing new conservation strategies and future experiments, including assisted migration, provenance trials, and restoration planning aimed at preserving the species into the future.

While emerging diseases pose a global threat to amphibians, the dynamics of understudied vector-borne blood pathogens remain poorly understood. Pathogen occurrence is driven by a combination of environmental, ecological, and phylogenetic factors, yet how these drivers shape blood pathogen communities in tropical amphibians is largely unknown. In this study, we used molecular screening and phylogenetic linear models (PGLMMs) to evaluate how climate and ecomorphology influence the incidence of three blood pathogen groups (Trypanosomatidae, Hepatozoon, and Rickettsia) in wild anurans from a protected area in the Brazilian Atlantic Forest. Among 93 individuals sampled, over 93% were infected with at least one pathogen. Trypanosomatidae was the most common (76.3%), followed by Rickettsia (69.9%) and Hepatozoon (16.1%). Pathogen responses to temperature were contrasting: Hepatozoon occurrence increased in warmer periods, while Trypanosomatidae declined. Furthermore, rheophilic species showed a lower probability of Rickettsia infection, providing the first evidence that microhabitat use influences blood pathogen dynamics in amphibians. Our findings demonstrate that hemoparasites prevalence is driven by a multifaceted interplay of variables, highlighting that conservation strategies must account for these pathogen-specific responses to habitat use and environmental change, even within protected areas.

Extrahepatic delivery of lipid nanoparticles (LNPs) to non-phagocytic cells is a major challenge, with the leading strategy involving surface functionalization with target-specific monoclonal antibody (mAb) ligands. We investigate the stability of mAb-conjugated LNPs using two anchoring systems: the commonly used DSPE-PEG2kDa-maleimide and a block copolymer, PCL5kDa-b-PEG2kDa -maleimide, with the hypothesis that conjugation to a 150,000 Da antibody could overwhelm the relatively small ~600 Da aliphatic anchor on the PEG-lipid in vivo. Shedding of the mAB would compromise targeting. Conjugation integrity following IV injection was assessed by tagging LNPs and mAbs with metal ion tracers that could be quantified by ICP-MS. Results show that DSPE-PEG-mAb rapidly (within 1h) dissociates from LNPs in blood, leading to accelerated LNP clearance. In contrast, mAbs conjugated using PCL-b-PEG remained stably associated with the LNP over the 24h circulation and clearance of the construct. Results are connected to a thermodynamic model that reproduces experimental findings for PEG-anchor(-mAb) shedding in vitro and in vivo. This study identifies anchoring strength as a critical, unconsidered parameter for in vivo performance when conjugating mAbs to LNPs for extrahepatic delivery.

Blockade by sedimentary particles, such as mineral crystals, is a continuous risk the kidney tubule faces. To prevent that, kidney resident macrophages form transepithelial protrusions and remove intratubular sedimentary particles, a behavior particularly prevailing in the medulla over the cortex. However, the molecular mechanisms underlying this characteristic behavior of medulla macrophages are incompletely understood. In this study, we identified that the medulla had higher mechanical stiffness than the cortex in steady state, which was further elevated when kidney stone formed. Increased tissue rigidity was sensed by medulla macrophages via mechanoreceptor Piezo1, which promoted macrophage protrusion formation and their ability to clean the tubules. Loss of Piezo1 expression in kidney macrophages predisposed mice to intratubular accumulation of mineral crystal in steady state and accelerated kidney stone formation during oxalate intake challenge. Signaling via Piezo1 mobilized molecules involved in cell adhesion and protrusion assembly, including Talin2 and focal adhesion kinase (FAK). Finally, we developed a first-of-its-kind cell-based therapy for the treatment of experimental nephrolithiasis by exploiting macrophage Piezo1 activity, and this strategy shows great promise for future translational research.

Single-nucleus transcriptomic atlases offer an unprecedented opportunity to connect cellular molecular states with Alzheimer's disease (AD) neuropathology, but whether these profiles encode reproducible, predictive information about pathological burden remains unclear. We present the SEA-AD DREAM Challenge, an open, international, model-to-data competition built on the Seattle Alzheimer's Disease Brain Cell Atlas to predict Alzheimer's disease neuropathological severity from single-nucleus RNA-sequencing data. Participants developed containerized models to predict categorical neuropathological staging, including overall Alzheimer's disease neuropathologic change, Braak stage, Thal phase, and CERAD score, as well as quantitative amyloid-{beta} and phospho-tau burden measured by 6E10 and AT8 immunohistochemistry. Across 17 eligible teams from 15 countries, the crowdsourcing framework enabled systematic comparison of diverse computational approaches and surfaced a broad landscape of modeling strategies and candidate predictive features. Top-performing methods achieved near-perfect prediction of categorical staging, with the best submission reaching a quadratic weighted kappa of 1.0 for the Overall AD Neuropathological Change score (ADNC), and competitive prediction of quantitative pathological burden in held-out data, with a best concordance correlation coefficient of 0.48. Post hoc perturbation analyses revealed that top categorical-stage predictions relied heavily on donor-level metadata-driven signals rather than transcriptomic features, whereas quantitative pathology prediction was more robust and supported by transcriptomic and cell-type-associated features with potential biological relevance to AD progression. The challenge also introduced the first AI Agent Track in a DREAM Challenge, providing an early benchmark for autonomous and human-guided agentic model development in single-cell neuroscience. This work demonstrates that single-nucleus transcriptomes encode substantial information about Alzheimer's disease pathology, establishes a reproducible benchmark for molecular neuropathology prediction, and highlights critical principles for designing privacy-preserving, leakage-aware community challenges using deeply phenotyped human brain data.

Temporal niche partitioning is a strategy for reducing interspecies competition and strengthening reproductive isolation. It relies on animals confining their daily activity to distinct diurnal, crepuscular, or nocturnal windows. However, a hardwired temporal niche is only advantageous under stable, predictable ecological regimes; surviving dynamic environments demands behavioral flexibility. Yet, it remains unclear how animals override rigid biological constraints to rapidly exploit transiently available fitness-critical time windows. To address this, we leveraged the twilight-active, species-rich Drosophila genus and monitored their daily activity under naturalistic conditions. Here, we show that intense sociosexual interactions rapidly drive a species-specific reformatting of their canonical crepuscular niche. The dominant sensory modality used for sexual communication predicts niche shift direction: reliance on chemosensation for courtship redirects behavioral activity into the night, while visual reliance shifts it into the day. This temporal plasticity bypasses the circadian clock, instead operating via a conserved dopaminergic pathway. Dopamine operates a dual-output brain circuit that simultaneously inhibits sleep and sustains sexual motivation. Our results reveal how mating imperatives decouple behavioral timing from circadian command, enabling conditional colonization of otherwise restricted temporal windows. Ultimately, by driving the divergence of previously overlapping niches, sociosexually induced temporal plasticity provides a powerful mechanism for sympatric coexistence in crowded environments.

Spectral bleed-through remains a persistent practical problem in multichannel fluorescence microscopy. Signal from one fluorophore can be recorded in the detection channel of another, thereby biasing intensity measurements, inflating apparent colocalization, and complicating the interpretation of dynamic microscopy data. Although many correction strategies exist, routine workflows often remain fragmented across ad hoc scripts, manually tuned graphical procedures, or method-specific blind-unmixing implementations with limited provenance. Here we present spectral-unmixing, an open-source Python package for reproducible linear spectral unmixing in multidimensional microscopy stacks. The package unifies directed two-channel correction with multiple alpha-estimation strategies, optional bidirectional two-channel correction through explicit inversion of a 2 x 2 mixing model, and PICASSO-family blind unmixing for multichannel data. Microscopy inputs are normalized at the API boundary to canonical TZCY X stacks, allowing the same unmixing code to be applied across file formats without manual axis handling. Machine-readable sidecar reports preserve the effective processing configuration and estimated coefficients for every output, so that workflows can be audited and reproduced. Synthetic and real-data-derived benchmarks show that the implemented workflows accurately estimate and correct bleed-through when their model assumptions are satisfied. In fixed-alpha two-channel simulations, the mean-ratio and linear-fit estimators recovered {approx} 0.283 for a ground-truth value of 0.28 and reduced target-channel normalized root mean squared error from approximately 0.029 to 0.003. In time-varying simulations, per-time-point estimation tracked coefficient drift substantially better than reference-time-point estimation. Bidirectional inversion recovered reciprocally mixed channels accurately when coefficients were known or well estimated. PICASSO-family benchmarks further showed a practical trade-off between reducing residual inter-channel dependence and preserving fluorophore identity, with MATLAB-style workflows behaving more conservatively and source-sink formulations providing stronger dependence suppression when meaningful directional priors are available. Together, these elements make spectral-unmixing a practical, transparent, and extensible platform for reproducible spectral unmixing of fluorescence microscopy data in neuroscience and other quantitative bioimage-analysis settings.

We showed before that the endogenous peptide Nociceptin blocks the premature differentiation of oligodendrocytes (OLGs), preventing untimely precocious myelination in the developing brain. Consistent with this early function, Nociceptin brain expression is developmentally regulated, sharply decreasing with the initiation and progression of myelination. However, we now found that at difference with controls and relapsing-remitting multiple sclerosis (RRMS), Nociceptin levels are highly elevated in cerebrospinal fluid from patients with the most severe progressive MS (PMS) forms. This questioned whether Nociceptin early developmental effects could be latter recapitulated, interfering with remyelination in PMS. This possibility was tested by inducing experimental autoimmune encephalomyelitis in older mice, at an age equivalent to that with increased risk of RRMS transition into PMS. Older animals develop persistently highly debilitating clinical symptoms, and display both brain and spinal cord demyelination. Importantly, these mice exhibit elevated brain Nociceptin levels, and their treatment with an antagonist of the Nociceptin receptor (NOR) elicits a regression of clinical scoring that is accompanied by higher ratios of OLGs/OLG progenitor cells, increased myelination, and reduction of reactive astrocytes. These findings suggest that Nociceptin may be a crucial player in the age-related progression of MS; interfering with OLG maturation and remyelination, and perhaps further exacerbating neurological dysfunction by targeting astrocyte populations. The upregulation of Nociceptin secretion by human astrocytes in response to proinflammatory cytokines, also points to this peptide as a mediator of microglia-astrocyte interactions supporting MS progression with aging. NOR may offer a novel pharmacological target for ameliorating the devastating effects of MS progression.

The spatial arrangement of immune cells in the tumor microenvironment (TME) varies widely, from dispersed to clustered and tumor excluded to infiltrating. Multiplexed spatial profiling is an effective means of characterizing tumor-infiltrating lymphocytes (TILs) and immune complexes such as tertiary lymphoid structures (TLS) in the TME. However, few approaches have been described for objectively parametrizing patterns of immune organization and assessing their association with biological or clinical variables. This makes it difficult to evaluate whether a set of tumors is relatively immunologically cold or hot. Here we describe an intuitive set of statistical tools (available in the R package, tlsR) for characterizing lymphocyte patterns in the TME of solid cancers. We apply tlsR to primary prostate cancer (PCa), which is often described as immunologically cold. Using a cohort of 29 radical prostatectomy specimens stratified into low Gleason-grade (LGG; n=15) and high Gleason-grades (HGG; n =14) we show that HGG PCa is significantly more infiltrated than LGG PCa with lymphocytes organized into B cell or T cell enriched immune clusters (BICs and TICs). A subset of these ICs have the B and T cell zonation and follicular dendritic cells characteristic of a bona fide TLS. HGGs are also enriched with ICs containing precursor exhausted T cells (Tpex) and proliferating B cells and their tumor compartments harbor granzyme-B+ cytotoxic T cells in contact with cancer cells. Thus, far from being cold, a subset of HGG PCa has features associated with active immune surveillance, a finding with implications for emerging PCa immunotherapies.

Social media users often feel that time vanishes while scrolling, but real feeds confound novelty, rewards, social signals, and self-paced control, leaving the driver of this distortion unclear. We tested whether self-paced visual exploration is sufficient to compress subjective time by comparing active scrolling with passive, yoked viewing and a static baseline. Twenty-three adults viewed sequences of natural images under three within-subject conditions: Scrolling (self-paced mouse clicks), Watching (a passive, yoked replay of their own scrolling sequence), and a Baseline (a static image). Participants estimated the elapsed duration of each block. Subjective duration was most compressed under Scrolling (48% of elapsed time), followed by Watching (51%) and Baseline (65%). Two sources separated these effects. Adding back the empty inter-image fixations brought the image-rich conditions to within seconds of the Baseline, showing that observers barely counted the blank gaps; the Scrolling--Watching difference, by contrast, was independent of these shared gaps, isolating self-paced control as a second source of compression. Electrophysiology linked that control to anticipatory neural states and the timing of early visual responses, with no amplified encoding of individual images. The results favor an attention-weighted account of timing, on which subjective duration tracks how much attention reaches the clock, a resource that a self-paced stream and its uncounted gaps both draw away.

Medical foundation models compress biomedical data into embeddings that support diverse downstream clinical tasks. However, successful model deployment is hampered by performance degradation on external data. It is recognized that embeddings capture acquisition signatures, such as hardware and technical differences, in addition to biology. Effective harmonization must remove the acquisition signature while preserving biological signals, a trade-off that current methods fail to balance adequately. Input-level normalization fails to eliminate acquisition signatures from embeddings, whereas embedding-level methods adjust features in an untargeted manner. We present FEATMAP, a harmonization approach that models acquisition signatures as geometric distortions between manifolds of similarly arranged embeddings. Using paired data that isolate the effect of acquisition signatures, FEATMAP fits a single global affine transformation per foundation model to correct acquisition signatures directly in the embedding space. This targeted, reusable correction aims to preserve biological and demographic variation while harmonizing across acquisition signatures. Across scanner and foundation-model harmonization in digital pathology and field-strength harmonization in brain MRI, FEATMAP improves cross-condition embedding similarity, reduces performance gaps without retraining, and suggests potential for the alignment of disparate embedding spaces.