bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tumor cell intrinsic and extrinsic features predicts prognosis in estrogen receptor positive breast cancer
Authors: Yao Kevin , Schaafsma Evelien , Zhang Baoyi , Cheng Chao 
Published: October 2021

AbstractAlthough estrogen-receptor-positive (ER+) breast cancer is generally associated with favorable prognosis, clinical outcome varies substantially among patients. Genomic assays have been developed and applied to predict patient prognosis for personalized treatment. We hypothesize that the recurrence risk of ER+ breast cancer patients is determined by both genomic mutations intrinsic to tumor cells and extrinsic immunological features in the tumor microenvironment. Based on the Cancer Genome Atlas (TCGA) breast cancer data, we identified the 72 most common genomic aberrations (including gene mutations and indels) in ER+ breast cancer and defined sample-specific scores that systematically characterized the deregulated pathways intrinsic to tumor cells. To further consider tumor cell extrinsic features, we calculated immune infiltration scores for six major immune cell types. Many individual intrinsic features are predictive of patient prognosis in ER+ breast cancer, and some of them achieved comparable accuracy with the Oncotype DX assay. In addition, statistical learning models that integrated these features predicts the recurrence risk of patients with significantly better performance than the Oncotype DX assay. As a proof-of-concept, our study indicates the great potential of genomic and immunological features in prognostic prediction for improving breast cancer precision medicine. The framework introduced in this work can be readily applied to other cancers.Author SummaryMany genomic biomarker tests such as Oncotype DX have been developed for breast cancer and have helped guide clinical decisions. We have developed gene signatures to integrate cancer genomic and transcriptomic data to characterize the downstream effect of driver genomic events. These signatures recapitulate the de-regulated pathways underlying the corresponding driver genomic events and are more correlated with clinical phenotypes such as recurrence free survival than mutation status alone. We apply this framework to ER+ breast cancer and define gene signatures for a total of 72 most commonly observed genomic events including gene mutations, amplifications and deletions. We find that many of these gene signatures are predictive of patient prognosis in ER+ breast cancer, and some of them achieved comparable accuracy with the Oncotype DX assay. We combine these tumor-intrinsic signatures with infiltration signatures for major immune cell types (tumor-extrinsic features) to construct integrative models for prognosis prediction. The models predicts the recurrence risk of patients with significantly better performance than the Oncotype DX assay.
Predicting Knee Adduction Moment Response to Gait Retraining with Minimal Clinical Data
Authors: Rokhmanova Nataliya , Kuchenbecker Katherine J. , Shull Peter B. , Ferber Reed , Halilaj Eni 
Published: October 2021

AbstractKnee osteoarthritis is a progressive disease mediated by high joint loads. Foot progression angle modifications that reduce the knee adduction moment (KAM), a surrogate of knee loading, have demonstrated efficacy in alleviating pain and improving function. Although changes to the foot progression angle are overall beneficial, KAM reductions are not consistent across patients. Moreover, customized interventions are time-consuming and require instrumentation not commonly available in the clinic. We present a model that uses minimal clinical data to predict the extent of first peak KAM reduction after toe-in gait retraining. For such a model to generalize, the training data must be large and variable. Given the lack of large public datasets that contain different gaits for the same patient, we generated this dataset synthetically. Insights learned from ground-truth datasets with both baseline and toe-in gait trials (N=12) enabled the creation of a large (N=138) synthetic dataset for training the predictive model. On a test set of data collected by a separate research group (N=15), the first peak KAM reduction was predicted with a mean absolute error of 0.134% body weight * height (%BW*HT). This error is smaller than the test set’s subject average standard deviation of the first peak during baseline walking (0.306 %BW*HT). This work demonstrates the feasibility of training predictive models with synthetic data and may provide clinicians with a streamlined pathway to identify a patient-specific gait retraining outcome without requiring gait lab instrumentation.Author SummaryGait retraining as a conservative intervention for knee osteoarthritis shows great promise in extending pain-free mobility and preserving joint health. Although customizing a treatment plan for each patient may help to ensure a therapeutic response, this procedure cannot yet be performed outside of the gait laboratory, preventing research advances from becoming a part of clinical practice. Our work aims to predict the extent to which a patient with knee osteoarthritis will benefit from a non-invasive gait retraining therapy using measures that can be easily collected in the clinic. To overcome a lack of normative databases for gait retraining, we generated data synthetically based on limited ground-truth examples, and provided experimental evidence for the model’s ability to generalize to new subjects by evaluating on data collected by a separate research group. Our results can contribute to a future in which predicting the therapeutic benefit of a potential treatment can determine a custom treatment path for any patient.
The European Prevention of Alzheimer’s Dementia (EPAD) MRI Dataset and Processing Workflow
Authors: Lorenzini Luigi , Ingala Silvia , Wink Alle Meije , Kuijer Joost PA , Wottschel Viktor , Dijsselhof Mathijs , Sudre Carole H , Haller Sven , Molinuevo José Luis , Gispert Juan Domingo , Cash David M , Thomas David L , Vos Sjoerd B , Prados Ferran , Petr Jan , Wolz Robin , Palombit Alessandro , Schwarz Adam J , Gael Chételat , Payoux Pierre , Di Perri Carol , Wardlaw Joanna , Frisoni Giovanni B , Foley Christopher , Fox Nick C , Ritchie Craig , Pernet Cyril , Waldman Adam , Barkhof Frederik , Mutsaerts Henk JMM ,   for the EPAD consortium
Published: October 2021

AbstractThe European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer’s Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences.Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI preprocessing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features — i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia.The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features — Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER), and Image Quality Rate (IQR) — were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses.
Plasticity in female timing may explain current shifts in breeding phenology of a North American songbird
Authors: Kimmitt Abigail A. , Becker Daniel J. , Diller Sara N. , Gerlach Nicole M. , Rosvall Kimberly A. , Ketterson Ellen D. 
Published: October 2021

AbstractClimate change has driven changes in breeding phenology. Identifying the magnitude of phenological shifts and whether selection in response to climate change drives these shifts is key for determining species’ reproductive success and persistence in a changing world.We investigated reproductive timing in a primarily sedentary population of the dark-eyed junco (Junco hyemalis) over 32 years. We predicted that juncos would breed earlier in warmer springs in response to selection favouring earlier breeding.To test this prediction, we compared the annual median date for reproductive onset (i.e., egg one date) to monthly spring temperatures and examined evidence for selection favouring earlier breeding and for plasticity in timing.Egg one dates occurred earlier over time, with the timing of breeding advancing up to 24 days over the 32-year period. Breeding timing also strongly covaried with maximum April temperature. We found significant overall selection favouring earlier breeding (i.e., higher relative fitness with earlier egg one dates) that became stronger over time, but strength of selection was not predicted by temperature. Lastly, individual females exhibited plastic responses to temperature across years.Our findings provide further evidence that phenotypic plasticity plays a crucial role in driving phenological shifts in response to climate change. For multi-brooded bird populations, a warming climate might extend the breeding season and provide more opportunities to re-nest rather than drive earlier breeding in response to potential phenological mismatches. However, as plasticity will likely be insufficient for long-term survival in the face of climate change, further research in understanding the mechanisms of female reproductive timing will be essential for forecasting the effects of climate change on population persistence.
The evolutionary trajectory of drosophilid walking
Authors: York Ryan A. , Brezovec Luke , Coughlan Jenn , Herbst Steven , Krieger Avery , Lee Su-Yee , Pratt Brandon , Smart Ashley , Song Eugene , Suvorov Anton , Matute Daniel R. , Tuthill John C. , Clandinin Thomas R. 
Published: October 2021

SummaryNeural circuits must both execute the behavioral repertoire of individuals and account for behavioral variation across species. Understanding how this variation emerges over evolutionary time requires large-scale phylogenetic comparisons of behavioral repertoires. Here, we describe the evolution of walking in fruit flies by capturing high-resolution, unconstrained movement from 13 species and 15 strains of drosophilids. We find that walking can be captured in a universal behavior space, the structure of which is evolutionarily conserved. However, the occurrence of, and transitions between, specific movements have evolved rapidly, resulting in repeated convergent evolution in the temporal structure of locomotion. Moreover, a meta-analysis demonstrates that many behaviors evolve more rapidly than other traits. Thus, the architecture and physiology of locomotor circuits can both execute precise individual movements in one species and simultaneously support rapid evolutionary changes in the temporal ordering of these modular elements across clades.
Genomics Characterization of an engineered Corynebacterium glutamicum in Bioreactor Cultivation under Ionic Liquid Stress
Authors: Banerjee Deepanwita , Eng Thomas , Sasaki Yusuke , Srinivasan Aparajitha , Oka Asun , Herbert Robin A. , Trinh Jessica , Singan Vasanth R. , Sun Ning , Putnam Dan , Scown Corinne D. , Simmons Blake , Mukhopadhyay Aindrila 
Published: October 2021

AbstractCorynebacterium glutamicum is an ideal microbial chassis for the production of valuable bioproducts including amino acids and next-generation biofuels. Here we resequence engineered isopentenol (IP) producing C. glutamicum BRC-JBEI 1.1.2 strain and assess differential transcriptional profiles using RNA sequencing under industrially relevant conditions including scale transition and compare the presence vs. absence of an ionic liquid, cholinium lysinate ([Ch][Lys]). Analysis of the scale transition from shake flask to bioreactor with transcriptomics identified a distinct pattern of metabolic and regulatory responses needed for growth in this industrial format. These differential changes in gene expression corroborate altered accumulation of organic acids and bioproducts, including succinate, acetate, and acetoin that occur when cells are grown in the presence of 50mM [Ch][Lys] in the stirred-tank reactor. This new genome assembly and differential expression analysis of cells grown in a stirred tank bioreactor clarify the cell response of a C. glutamicum strain engineered to produce IP.
Distance estimation from monocular cues in an ethological visuomotor task
Authors: Parker Philip R. L. , Abe Elliott T. T. , Beatie Natalie T. , Leonard Emmalyn S. P. , Martins Dylan M. , Sharp Shelby L. , Wyrick David G. , Mazzucato Luca , Niell Cristopher M. 
Published: October 2021

ABSTRACTIn natural contexts, sensory processing and motor output are closely coupled, which is reflected in the fact that many brain areas contain both sensory and movement signals. However, standard reductionist paradigms decouple sensory decisions from their natural motor consequences, and head-fixation prevents the natural sensory consequences of self-motion. In particular, movement through the environment provides a number of depth cues beyond stereo vision that are poorly understood. To study the integration of visual processing and motor output in a naturalistic task, we investigated distance estimation in freely moving mice. We found that mice use vision to accurately jump across a variable gap, thus directly coupling a visual computation to its corresponding ethological motor output. Monocular eyelid suture did not affect gap jumping success, thus mice can use cues that do not depend on binocular disparity and stereo vision. Under monocular conditions, mice altered their head positioning and performed more vertical head movements, consistent with a shift from using stereopsis to other monocular cues, such as motion or position parallax. Finally, optogenetic suppression of primary visual cortex impaired task performance under both binocular and monocular conditions when optical fiber placement was localized to binocular or monocular zone V1, respectively. Together, these results show that mice can use monocular cues, relying on visual cortex, to accurately judge distance. Furthermore, this behavioral paradigm provides a foundation for studying how neural circuits convert sensory information into ethological motor output.
KRAB Zinc Finger protein Znf684 interacts with Nxf1 to regulate mRNA export
Authors: Nitoiu Alexandra , Nabeel-Shah Syed , Farhangmehr Shaghayegh , Pu Shuye , Braunschweig Ulrich , Blencowe Benjamin J. , Greenblatt Jack F. 
Published: October 2021

AbstractCys2His2 (C2H2) type zinc finger (ZnF) proteins constitute a large class of proteins that are generally considered to be DNA-binding transcription factors. Using affinity purification followed by mass spectrometry, as well as reciprocal co-immunoprecipitation experiments, we determined that the C2H2-ZnF protein Znf684 interacts physically with several proteins involved in mRNA export, including Nxf1 and Alyref. We utilized individual nucleotide resolution cross-linking immunoprecipitation followed by high throughput sequencing (iCLIP-seq) experiments to show that Znf684 binds directly to specific mRNAs in vivo and has an RNA-binding profile similar to those of Nxf1 and Alyref, suggesting a role in mRNA export regulation. Immunofluorescence microscopy (IF) experiments revealed that Znf684 localizes to both the nucleus and cytoplasm. Using cellular fractionation experiments, we demonstrate that overexpression of Znf684 negatively impacts the export of SMAD3 and other target mRNAs. Taken together, our results suggest that Znf684 regulates the export of a subset of transcripts through physical interactions with Nxf1 and specific target mRNAs.
Biophysical characterization of the oligomeric states of recombinant Immunoglobulins type-M and their C1q binding kinetics by Biolayer Interferometry
Authors: Chouquet Anne , Pinto Andrea J. , Hennicke Julia , Ling Wai Li , Bally Isabelle , Schwaigerlehner Linda , Thielens Nicole M. , Kunert Renate , Reiser Jean-Baptiste 
Published: October 2021

AbstractThe Immunoglobulins type-M (IgMs) are one of the first antibody classes mobilized during immune responses against pathogens and tumor cells. Binding to specific target antigens enables the interaction with the C1 complex which strongly activates the classical complement pathway. This biological function is the basis for the huge therapeutic potential of IgMs but due to their high oligomeric complexity,in vitroproduction, biochemical and biophysical characterizations are challenging. In the present study, we present recombinant production of two IgM models (IgM617 and IgM012) in pentameric and hexameric states and the evaluation of their polymer distribution using different biophysical methods (AUC, SEC-MALLS, Mass Photometry and Transmission Electron Microscopy). Each IgM oligomer has individual specific expression pattern and yield with different protein quality likely due to intrinsic IgM properties and patterning. Nevertheless, the purified recombinant IgMs retain their ability to activate complement in a C1q dependent manner. And more importantly, a new method to evaluate their functional quality attribute by characterizing the kinetics of C1q binding to recombinant IgM has been developed using BioLayer Interferometry (BLI). We show that recombinant IgMs possess similar C1q binding properties as IgMs purified from human plasma.
Durability of immune responses to the BNT162b2 mRNA vaccine
Authors: Suthar Mehul S. , Arunachalam Prabhu S. , Hu Mengyun , Reis Noah , Trisal Meera , Raeber Olivia , Chinthrajah Sharon , Davis-Gardner Meredith E. , Manning Kelly , Mudvari Prakriti , Boritz Eli , Godbole Sucheta , Henry Amy R. , Douek Daniel C. , Halfmann Peter , Kawaoka Yoshihiro , Zarnitsyna Veronika I. , Nadeau Kari , Pulendran Bali 
Published: October 2021

AbstractThe development of the highly efficacious mRNA vaccines in less than a year since the emergence of SARS-CoV-2 represents a landmark in vaccinology. However, reports of waning vaccine efficacy, coupled with the emergence of variants of concern that are resistant to antibody neutralization, have raised concerns about the potential lack of durability of immunity to vaccination. We recently reported findings from a comprehensive analysis of innate and adaptive immune responses in 56 healthy volunteers who received two doses of the BNT162b2 vaccination. Here, we analyzed antibody responses to the homologous Wu strain as well as several variants of concern, including the emerging Mu (B.1.621) variant, and T cell responses in a subset of these volunteers at six months (day 210 post-primary vaccination) after the second dose. Our data demonstrate a substantial waning of antibody responses and T cell immunity to SARS-CoV-2 and its variants, at 6 months following the second immunization with the BNT162b2 vaccine. Notably, a significant proportion of vaccinees have neutralizing titers below the detection limit, and suggest a 3rd booster immunization might be warranted to enhance the antibody titers and T cell responses.
In Vivo Generation of Bone Marrow from Embryonic Stem Cells in Interspecies Chimeras
Authors: Wen Bingqiang , Wang Guolun , Li Enhong , Kolesnichenko Olena A. , Tu Zhaowei , Divanovic Senad , Kalin Tanya V. , Kalinichenko Vladimir V. 
Published: October 2021

SUMMARYGeneration of bone marrow (BM) from embryonic stem cells (ESCs) or induced pluripotent stem cells (iPSCs) promises to accelerate the development of future cell therapies for life-threatening disorders. However, such approach is limited by technical challenges to produce a mixture of functional BM progenitor cells able to replace all hematopoietic cell lineages. Herein, we used blastocyst complementation to simultaneously produce all BM hematopoietic cell lineages from mouse ESCs in a rat. Based on FACS analysis and single-cell RNA sequencing, mouse ESCs differentiated into hematopoietic progenitor cells and multiple hematopoietic cell types that were indistinguishable from normal mouse BM cells based on gene expression signatures and cell surface markers. Transplantation of ESC-derived BM cells from mouse-rat chimeras rescued lethally-irradiated syngeneic mice and resulted in long-term contribution of donor cells to hematopoietic cell lineages. Altogether, a fully functional bone marrow was generated from mouse ESCs using rat embryos as “bioreactors”.KEY POINTS- We used blastocyst complementation to simultaneously produce all bone marrow hematopoietic cell lineages from mouse ESCs in a rat.- ESC-derived cells from mouse-rat chimeras were fully functional and exhibited normal gene expression signatures and cell surface markers.
Bayesian machine learning analysis of single-molecule fluorescence colocalization images
Authors: Ordabayev Yerdos A. , Friedman Larry J. , Gelles Jeff , Theobald Douglas L. 
Published: October 2021

AbstractMulti-wavelength single-molecule fluorescence colocalization (CoSMoS) methods allow elucidation of complex biochemical reaction mechanisms. However, analysis of CoSMoS data is intrinsically challenging because of low image signal-to-noise ratios, non-specific surface binding of the fluorescent molecules, and analysis methods that require subjective inputs to achieve accurate results. Here, we use Bayesian probabilistic programming to implement Tapqir, an unsupervised machine learning method that incorporates a holistic, physics-based causal model of CoSMoS data. This method accounts for uncertainties in image analysis due to photon and camera noise, optical non-uniformities, non-specific binding, and spot detection. Rather than merely producing a binary “spot/no spot” classification of unspecified reliability, Tapqir objectively assigns spot classification probabilities that allow accurate downstream analysis of molecular dynamics, thermodynamics, and kinetics. We both quantitatively validate Tapqir performance against simulated CoSMoS image data with known properties and also demonstrate that it implements fully objective, automated analysis of experiment-derived data sets with a wide range of signal, noise, and non-specific binding characteristics.