Biology subjects

Ackerman, J.

Publications and source records attributed to Ackerman, J..

7 recordsLinked to original sources

bioRxiv2026

Correcting and georeferencing natural history occurrence records with calibrated uncertainty

1. Occurrence records underpin biodiversity analyses, but their coordinates are often erroneous or missing. Misplaced coordinates distort environmental predictors and range estimates used in conservation assessment. Existing tools flag suspect records or georeference locality text, but rarely correct coordinates, provide calibrated uncertainty, or quantify downstream consequences. 2. We present GeoMend, a deterministic, rule-based method that flags and corrects suspect coordinates and georeferences records lacking coordinates from locality text, assigning each a precision tier or uncertainty radius. It uses no machine learning or artificial intelligence. We evaluate it against expert coordinates for 16,913 records and 736 species on Hispaniola, compare georeferencers using 5,000 localities from 72 countries, and measure changes in environmental predictors and the extent of occurrence. 3. On held-out Hispaniola records, GeoMend flags 92% of coordinates more than 5 km from expert truth, versus 27% for CoordinateCleaner. Among the accepted corrections with paired coordinates, the median error falls from 2.19 to 0.82 km, and 68% of the complete held-out pairs improve. On records placed by both GeoMend and GEOLocate that also have original coordinates, the median error is 0.67 km for GeoMend versus 10.69 km for GEOLocate. For records lacking coordinates, evaluated uncertainty radii contain expert truth about 92% of the time in well-supported gazetteer classes. Correction reduces the mean standardized environmental distance from expert truth by 38% and moves the extent of occurrence toward expert truth by a median of 8% (mean of 79%). Corrections and newly georeferenced records give 17 Hispaniola species their first range estimate. 4. On the global benchmark, GeoMend is more accurate than GPT-4o for two-thirds of the records placed by all four comparators, with median errors of 4.4 and 10.8 km, respectively. Applied to Global Biodiversity Information Facility (GBIF) records lacking coordinates, it places records from 82,180 previously unmapped species across 233 countries, ranging from precise locality interpretations to administrative centroids. Automated placement makes the global backlog more approachable, while explicit tiers distinguish uses supported by precise and coarse coordinates. Further georeferencing requires regional expertise to combine automated placement with local knowledge.

ecology↗

bioRxiv2023

Development of a Nanoparticle-Based Tendon-Targeting Drug Delivery System to Pharmacologically Modulate Tendon Healing

Tendon regeneration following acute injury is marred by a fibrotic healing response that prevents complete functional recovery. Despite the high frequency of tendon injuries and the poor outcomes, including functional deficits and elevated risk of re-injury, there are currently no pharmacological therapies in clinical use to enhance the healing process. Several promising pharmacotherapies have been identified; however, systemic treatments lack tendon specificity, resulting in poor tendon biodistribution and perhaps explaining the largely limited beneficial effects of these treatments on the tendon healing process. To address this major unmet need, we leveraged our existing spatial transcriptomics dataset of the tendon healing process to identify an area of the healing tendon that is enriched for expression of Acp5. Acp5 encodes tartrate-resistant acid phosphatase (TRAP), and we demonstrate robust TRAP activity in the healing tendon. This unexpected finding allowed us to refine and apply our existing TRAP binding peptide (TBP) functionalized nanoparticle (NP) drug delivery system (DDS) to facilitate improved delivery of systemic treatments to the healing tendon. To demonstrate the translational potential of this drug delivery system, we delivered the S100a4 inhibitor, Niclosamide to the healing tendon. We have previously shown that genetic knockdown of S100a4 enhances tendon healing. While systemic delivery of Niclosamide did not affect the healing process, relative to controls, TBP-NP delivery of Niclosamide enhanced both functional and mechanical outcome measures. Collectively, these data identify a novel tendon-targeting drug delivery system and demonstrate the translational potential of this approach to enhance the tendon healing process.

bioengineering↗

bioRxiv2023

The Origin And Speciation Of Orchids

Orchids constitute one of the most spectacular radiations of flowering plants. However, their geographical origin, historical spread across the globe, and hotspots of speciation remain uncertain due to the lack of a broad phylogenomic framework. We present a new Orchidaceae phylogeny based on high-throughput and Sanger sequencing datasets, covering all five subfamilies, 17/22 tribes, 40/49 subtribes, 285/736 genera, and [~]7% (1,921) of the currently 29,524 accepted species. We then use it to infer geographic range evolution, diversity, and speciation patterns by adding curated geographical distribution data through the World Checklist of Vascular Plants. Orchids most recent common ancestor is traced back to the Late Cretaceous in Laurasia. The modern Southeast Asian range of subfamily Apostasioideae is interpreted as relictual, matching the history of numerous clades that went extinct at higher latitudes following the global climate cooled during the Oligocene. Despite their ancient origins, modern orchid species diversity mainly originated over the last 5 Ma, with the fastest speciation rates found in south-eastern Central America. Our results substantially alter our understanding of the geographic origin of orchids, previously proposed as Australian, and further pinpoint the role of Central American as a region of recent and explosive speciation.

evolutionary biology↗

bioRxiv2023

An In-Silico Testbed for Fast and Accurate MR Labeling of Orthopaedic Implants

AO_SCPLOWBSTRACTC_SCPLOWOne limitation on the ability to monitor health in older adults using Magnetic Resonance (MR) imaging is the presence of implants, where the prevalence of implantable devices (orthopedic, cardiac, neuromodulation) increases in the population, as does the pervasiveness of conditions requiring MRI studies for diagnosis (musculoskeletal diseases, infections, or cancer). The present study describes a novel multiphysics implant modeling testbed using the following approaches with two examples: - an in-silico human model based on the widely available Visible Human Project (VHP) cryo-section dataset; - a finite element method (FEM) modeling software workbench from Ansys (Electronics Desktop/Mechanical) to model MR radio frequency (RF) coils and the temperature rise modeling in heterogeneous media. The in-silico VHP Female model (250 parts with an additional 40 components specifically characterizing embedded implants and resultant surrounding tissues) corresponds to a 60-year-old female with a body mass index (BMI) of 36. The testbed includes the FEM-compatible in-silico human model, an implant embedding procedure, a generic parameterizable MRI RF birdcage two-port coil model, a workflow for computing heat sources on the implant surface and in adjacent tissues, and a thermal FEM solver directly linked to the MR coil simulator to determine implant heating based on an MR imaging study protocol. The primary target is MR labeling of large orthopaedic implants. The testbed has very recently been approved by the US Food and Drug Administration (FDA) as a medical device development tool (MDDT) for 1.5 T orthopaedic implant examinations.

biophysics↗

bioRxiv2023

JUMP Cell Painting dataset: morphological impact of 136,000 chemical and genetic perturbations

Image-based profiling has emerged as a powerful technology for various steps in basic biological and pharmaceutical discovery, but the community has lacked a large, public reference set of data from chemical and genetic perturbations. Here we present data generated by the Joint Undertaking for Morphological Profiling (JUMP)-Cell Painting Consortium, a collaboration between 10 pharmaceutical companies, six supporting technology companies, and two non-profit partners. When completed, the dataset will contain images and profiles from the Cell Painting assay for over 116,750 unique compounds, over-expression of 12,602 genes, and knockout of 7,975 genes using CRISPR-Cas9, all in human osteosarcoma cells (U2OS). The dataset is estimated to be 115 TB in size and capturing 1.6 billion cells and their single-cell profiles. File quality control and upload is underway and will be completed over the coming months at the Cell Painting Gallery: https://registry.opendata.aws/cellpainting-gallery. A portal to visualize a subset of the data is available at https://phenaid.ardigen.com/jumpcpexplorer/.

bioinformatics↗

bioRxiv2019

Cell non-autonomous functions of S100a4 drive fibrotic tendon healing

Identification of pro-regenerative approaches to improve tendon healing is of critical importance given the diminished quality of life and physical function that accompanies the typical fibrotic response to tendon injury. S100a4 modulates fibrosis through tissue-type dependent mechanisms, and the role of S100a4 in fibrotic, scar-mediated tendon healing has not been established. In the present study we tested the hypothesis that inhibition of S100a4 improves tendon function following acute injury and surgical repair. We demonstrate cell non-autonomous functions of S100a4 as S100a4 haploinsufficiency promotes regenerative tendon healing, including decreased scar formation and improved mechanical properties. Moreover, inhibition of S100a4 via antagonism of its putative receptor, the Receptor for Advanced Glycation Endproducts (RAGE), also decreases scar formation. Mechanistically, knock-down of S100a4 decreases myofibroblast and macrophage content at the site of injury, with both cell populations being key drivers of fibrotic progression. In contrast, S100a4+ cell depletion displays time-dependent effects on scar formation, and consistent impairments in restoration of mechanical properties, indicating a critical role for these cells in re-establishing tendon strength after injury. Finally, we demonstrate, that S100a4-lineage cells become -SMA+ myofibroblasts, via loss of S100a4 expression. Using a combination of genetic mouse models, small molecule inhibitors and in vitro studies we have defined S100a4 as a novel, promising therapeutic candidate to improve tendon function after acute injury.

cell biology↗

bioRxiv2018

Non-invasive ultrasound quantification of Scar Tissue Volume predicts functional changes during tendon healing

Tendon injuries are very common and disrupt the transmission of forces from muscle to bone, leading to impaired function and quality of life. Successful restoration of tendon function after injury is a challenging clinical problem due to the pathological, scar-mediated manner in which tendons heal. Currently, there are no standard treatments to modulate scar tissue formation and improve tendon healing. A major limitation to the identification of therapeutic candidates has been the reliance on terminal end-point metrics of healing in pre-clinical studies, which require a large number of animals and result in destruction of the tissue. To address this limitation, we have identified quantification of Scar Tissue Volume (STV) from ultrasound imaging as a longitudinal, non-invasive metric of tendon healing. STV was strongly correlated with established endpoint metrics of gliding function including Gliding Resistance (GR) and Metatarsophalangeal (MTP) Flexion Angle. However, no associations were observed between STV and tensile mechanical properties. To define the sensitivity of STV to identify differences between functionally discrete tendon healing phenotypes, we utilized S100a4 haploinsufficient mice (S100a4GFP/+), which heal with improved gliding function relative to wildtype (WT) littermates. A significant decrease in STV was observed in S100a4GFP/+repairs, relative to WT at day 14. Taken together, these data suggest US quantification of STV as a means to facilitate the rapid screening of biological and pharmacological interventions to improve tendon healing, and identify promising therapeutic targets, in an efficient, cost-effective manner.

bioengineering↗