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1. Multi-Task Learning for Post-transplant Cause of Death Analysis: A Case Study on Liver Transplant

   Ding, Sirui Ding; Tan, Qiaoyu; Chang, Chia-yuan; Zou, Na; Zhang, Kai; Hoot, Nathan R.; Jiang, Xiaoqian; Hu, Xia (January 2024, AMIA Annual Symposium proceedings)
2. The Houston Methodist lung transplant risk model – a validated tool for pre-transplant risk assessment

   https://doi.org/10.1016/j.athoracsur.2019.03.108  

   Chan EY, Nguyen DT (October 2019, The annals of thoracic surgery)

   BACKGROUND: Lung transplantation is the gold standard for a carefully selected patient population with end-stage lung disease. We sought to create a unique risk stratification model using only preoperative recipient data to predict one-year postoperative mortality during our pre-transplant assessment. METHODS: Data of lung transplant recipients at Houston Methodist Hospital (HMH) from 1/2009 to 12/2014 were extracted from the United Network for Organ Sharing (UNOS) database. Patients were randomly divided into development and validation cohorts. Cox proportional-hazards models were conducted. Variables associated with 1-year mortality post-transplant were assigned weights based on the beta coefficients, and risk scores were derived. Patients were stratified into low-, medium- and high-risk categories. Our model was validated using the validation dataset and data from other US transplant centers in the UNOS database RESULTS: We randomized 633 lung recipients from HMH into the development (n=317 patients) and validation cohort (n=316). One-year survival after transplant was significantly different among risk groups: 95% (low-risk), 84% (medium-risk), and 72% (high-risk) (p<0.001) with a C-statistic of 0.74. Patient survival in the validation cohort was also significantly different among risk groups (85%, 77% and 65%, respectively, p<0.001). Validation of the model with the UNOS dataset included 9,920 patients and found 1-year survival to be 91%, 86% and 82%, respectively (p < 0.001). CONCLUSIONS: Using only recipient data collected at the time of pre-listing evaluation, our simple scoring system has good discrimination power and can be a practical tool in the assessment and selection of potential lung transplant recipients. 

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3. Integrating Surgeon Expertise and AI: The Transplant Surgeon Fuzzy Associative Memory Model for Enhanced Kidney Transplant Decision-Making

   https://doi.org/10.1016/j.ajt.2025.07.824  

   Dzieran, R; Dagli, C; Randall, H; Marley, R; Canfield, C; Lentine, K; Schnitzler, M (August 2025, American Journal of Transplantation)

   (TSFAM) model, an adaptive human-AI teaming framework designed to enhance hard-to-place kidney acceptance decision-making by integrating transplant surgeons’ individualized expertise with advanced AI analytics (Figure 1). Methods: TSFAM is an innovative solution for complex issues in kidney transplant decision-making support. It employs fuzzy associative memory to capture and codify unique decision-making rules of transplant surgeons. Using the Deceased Donor Organ Assessment (DDOA) and Final Acceptance AI models designed to evaluate hard-to-place kidneys, TSFAM integrates fuzzy logic with deep learning techniques to manage inherent uncertainties in donor organ assessments. Surgeon-specifi c ontologies and membership functions are extracted through interviews. Similar to how a pain scale is used for understanding patients, an ontology ambiguity scale is used to develop surgeon rules (Figure 2). Fuzzy logic captures ambiguity and enables the model to adapt to evolving clinical, environmental, and policy conditions. The structured incorporation of human expertise ensures decision support remains closely aligned with local clinical practices and global best evidence. Results: This novel framework incorporates human expertise into AI decisionmaking tools to support donor organ acceptance in transplantation. Integrating surgeon-defi ned criteria into a robust decision-support tool enhances accuracy and transparency of organ allocation decision-making support. TSFAM bridges the gap between data-driven models and nuanced judgment required in complex clinical scenarios, fostering trust and promoting responsible AI adoption. Conclusions: TSFAM fuses deep learning analytics with subtleties of human expertise for a promising pathway to improve decision-making support in transplant surgery. The framework enhances clinical assessment and sets a precedent for future systems prioritizing human-AI collaboration. Prospective studies will focus on clinical implementation with dynamic interfaces for a more patient-centered, evidencebased model in organ transplantation. The intent is for this approach to be adaptable to individual case scenarios and the diverse needs of key transplant team members 

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4. Turf Transplant NDVI, 2024 - ongoing.

   https://doi.org/10.6073/pasta/6fc427492b2c8dc0b992cbc5f5ec92d6  

   Smith, Jane G; LTER, Niwot Ridge (February 2025, Environmental Data Initiative)

   The Turf Transplant Experiment was set up in the summer of 2024. Paired experimental sites were established in two tundra community types - dry meadow and moist meadow - with one site of each community type pair in a lower elevation/warmer area and one site in a higher elevation/cooler area. Subplot turfs (25 cm^2) were transplanted (1) between sites of the same community type at different elevations/temperatures, (2) between plots within the same site or (3) left in place as non-transplant controls. This data package contains NDVI measurements. 

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5. Growth chamber reciprocal transplant dataset

   https://doi.org/10.5061/dryad.4mw6m90kb  

   Garrison, Ava (October 2024, Dryad)

   Phenotypic plasticity can alter traits that are crucial to population\n establishment in a new environment, before adaptation can occur. How often\n phenotypic plasticity enables subsequent adaptive evolution is unknown,\n and examples of the phenomenon are limited. We investigated the hypothesis\n of plasticity-mediated persistence as a means of colonization of\n agricultural fields in one of the world’s worst weeds, Raphanus\n raphanistrum ssp. raphanistrum. Using non-weedy native populations of the\n same species and subspecies as a comparison, we tested for\n plasticity-mediated persistence in a growth chamber reciprocal transplant\n experiment. We identified traits with genetic differentiation between the\n weedy and native ecotypes as well as phenotypic plasticity between growth\n chamber environments. We found that most traits were both plastic and\n differentiated between ecotypes, with the majority plastic and\n differentiated in the same direction. This suggests that phenotypic\n plasticity may have enabled radish populations to colonize and then adapt\n to novel agricultural environments."],"TechnicalInfo":["# Growth Chamber Reciprocal Transplant Dataset\n [https://doi.org/10.5061/dryad.4mw6m90kb](https://doi.org/10.5061/dryad.4mw6m90kb) This dataset contains the phenotypic data collected from plants grown in the growth chamber reciprocal transplant experiment, as well as the conditions in the growth chambers. ## Description of the data and file structure The dataset contains three sheets: "Chamber Conditions", "Main Data", and "Leaf Data" (although much of the information in "Leaf Data" has been incorporated into "Main data") ### Chamber Conditions This sheet contains the temperature and day length set points for each chamber each week. All temperature and day length information from the two weather stations used (LGER and KBTL) were collected from [www.wunderground.com](http://www.wunderground.com). Variables: * Granada, Spain (LGER) - the dates from which we collected temperature and day length information from the Grenada, Spain weather station (LGER) to simulate in the Winter Annual chamber * HighTempGrenada - the Winter Annual chamber's daytime set points, based on the average maximum temperature in Grenada on a given day * LowTempGrenada - the Winter Annual chamber's nighttime set points, based on the average minimum temperature in Grenada on a given day * DayLengthGrenada - the length of time the Winter Annual chamber was in its day cycle (lights on and typically higher temps), based on length of visible light in Grenada * DayStartGrenada - programed start of day time in the Winter Annual growth chamber * DayEndGrenada - programmed end of day time in the Winter Annual growth chamber * Date Set - the real-life date on which we changed the chamber conditions. * Augusta, MI (KBTL) - the dates from which we collected temperature and day length information from the Augusta, MI, USA weather station (KBTL) to simulate in the Spring Annual chamber * HighTempAugusta - the Spring Annual chamber's daytime set points, based on the average maximum temperature in Augusta on a given day * LowTempAugusta - the Spring Annual chamber's nighttime set points, based on the average minimum temperature in Augusta on a given day * DayLengthAugusta - the length of time the Spring Annual chamber was in its day cycle (lights on and typically higher temps), based on length of visible light in Augusta * DayStartAugusta - programed start of day time in the Spring Annual growth chamber * DayEndAugusta - programmed end of day time in the Spring Annual growth chamber ### Main Data This sheet contains all of the data used in our analyses, as well as descriptors for plants and growth chambers. Variables: * Chamber # - the number designation of the four growth chambers used in this study * Environment - the growing conditions in a given growth chamber, with "Winter Annual" corresponding to the "Grenada, Spain (LGER)" columns in Chamber Conditions, and "Spring Annual" corresponding to "Augusta, MI (KBTL)" * Ecotype - variety of* R. raphanistrum*, either weedy or native * Population - the six source populations used in this study identified by their location codes, with the final two letters denoting country or state (FR=France, ES=Spain, NY=New York, NC=North Carolina) and the first two letters denoting a specific location in those areas (available in Table 1 of the manuscript) * Matriline -  a line number is listed when discrete matrilines are known from field collections, but not for seeds collected in bulk (in which case the cell will be blank) * Flat - plants were arranged into four flats in each chamber, and the flats within a chamber were each assigned a number (1-4) * Position - the position of each plant within a flat was also tracked and pots were assigned a position number (1-35) * Pot# - Number assigned to each plant to give it a unique identifier -- for plants with individual matrilines tracked, pot # only went up to 2, while plants with unknown matrilines had pot numbers up to 40 to ensure individuals could be tracked * Plant Date - the date seeds were sown into each pot * Germ[1-5] - the date that each one of 5 seeds planted emerged as a germinant -- blank cells indicate that a germinant did not emerge * Plant Kept - the emergence date of the single plant that remained in the pot after excess germinants were thinned; missing values mean no germinants emerged or did not survive past the seedling stage * Days to Emergence - calculated as the day of emergence minus the planting date; missing values mean no germinants emerged or did not survive past the seedling stage * Rosette Photo Date - the date on which overhead and side photos of plants were taken, also the day the plants first showed signs of bolting (buds visible); missing values mean the plant did not survive to bolting * \\# Rosette Leaves - the number of leaves in the basal rosette, counted on the day of bolting; missing values mean the plant did not survive to bolting * Rosette Height - the vertical height of the tallest free-standing basal rosette leaf, measured from the height of the soil (cm); missing values mean the plant did not survive to bolting * 1st flower date - the date on which the first flower on a plant opened; missing values mean the plant did not survive to flowering * Days to First Flower - calculated as 1st flower date minus emergence date; missing values mean the plant did not survive to flowering * 1st Flower Height - measured on the first flower date, it is the vertical distance from the soil to the point at which the first open flower's pedicel connects to the main stalk (cm); missing values mean the plant did not survive to flowering * Ovule # - collected from typically the third flower to open, it is the number of ovules in one flower of a given plant; missing values mean the plant did not survive to flowering or ovules were not clearly visible * Notes - any additional information on a plant that we tracked * Blossom Photo Date - the date on which we took top and side photographs of at least the third flower to open, taken at the same time that ovule number was counted; missing values mean the plant did not survive to flowering  * PetalLength - measured using a top-view photo in Image J, the distance from the tip of the petal to where it meets the floral tube in the center of the floral display (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * PetalWidth - measured using a top-view photo in Image J, the distance from the widest part of the petal, perpendicular to the line measured for petal length (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * Tube - measured using a side-view photo in Image J, the length of the most clearly visible petal from where it meets the pedicel to the apex of its curve outward (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * LAnther - measured using a side-view photo in Image J, the length of the anther of the long stamen from where it meets its filament to its tip (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * LFilament - measured using a side-view photo in Image J, the length of the frontmost (closest to the camera) long filament from where it meets the pedicel to where it meets its anther (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * SAnther - measured using a side-view photo in Image J, the length of the anther of the short stamen from where it meets its filament to its tip (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * SFilament - measured using a side-view photo in Image J, the length of the frontmost (closest to the camera) short filament from where it meets the pedicel to where it meets its anther (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * Pistil - measured using a side-view photo in Image J, the length of the pistil made by drawing a line down the center of the pistil from the top of the stigma to where it meets the pedicel (mm); missing values mean the plant did not survive to flowering or the view in the photo was obscured so the measurement could not be taken * AntherExsertion - calculated as long filament length minus the tube length (mm); missing values mean the plant did not survive to flowering or that either one of the values needed for the measurement was missing * AntherSeparation - calculated as long filament length minus the short filament length (mm); missing values mean the plant did not survive to flowering or one or that either one of the values needed for the measurement was missing * FlowerSize - the geometric mean of all floral traits (excluding anther exsertion and anther separation; mm); missing values mean the plant did not survive to flowering or one or more flower trait was missing * LeafWidth - measured using either a top-view or side-view photo in Image J, the distance between each edge of the leaf measured at its widest point, with the line being perpendicular to the central leaf vein on the largest fully visible leaf (more information in the Leaf Data sheet; cm); missing values mean the plant did not survive to bolting or a picture was not taken * LeafLength -  measured using either a top-view or side-view photo in Image J using the segmented line tool, follow the central vein of the largest visible leaf from the center of the rosette to the tip of the leaf (more information in the Leaf Data sheet; cm); missing values mean the plant did not survive to bolting or a picture was not taken ### Leaf Data This sheet includes some additional information about Leaf Length and Leaf Width measurements. Side image was only used when leaf was not flat or clearly visible in the top image. Variables: * Top Photo Image - image ID of the top view photo of the plant being measured * Ecotype - the ecotype of the plant (more information in Main Data) * Population - the population that the plant belongs to (more information in Main Data) * Plant Label - the label visible in the image -- includes population, matriline (when available), and pot # * Leaf Width (cm) - measured using the top-view photo in Image J, the distance between each edge of the leaf measured at its widest point, with the line being perpendicular to the central leaf vein on the largest fully visible leaf; missing values mean that a picture was not taken or the leaf was obscured in the top view photo * Leaf Length 1 (cm) - measured using the top-view photo in Image J using the segmented line tool, follow the central vein of the largest visible leaf from the center of the rosette to the tip of the leaf; missing values mean that a picture was not taken or the leaf was obscured in the top view photo * Side Photo Image - Image ID of the side view photo of the plant being measured; side image was only used when leaf was not flat or clearly visible in the top image, so missing values indicate that the length and width of the leaf could be reliably measured using the top view photo * Leaf Length 2 (cm) - measured using the side-view photo in Image J using the segmented line tool, follow the central vein of the largest visible leaf from the center of the rosette to the tip of the leaf; missing values mean that a picture was not taken or that the length of the leaf could be reliably measured using the top view photo * Leaf Width 2 (cm) - measured using the side-view photo in Image J, the distance between each edge of the leaf measured at its widest point, with the line being perpendicular to the central leaf vein on the largest fully visible leaf; missing values mean that a picture was not taken or that the width of the leaf could be reliably measured using the top view photo * Notes - any additional information about the the measurement of a particular plants' leaf length or width"]} 

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