tbuckley/cabot-search huggingface dataset:
Into the multiverse: advances in single-cell multiomic profiling
Authors: Silvia Ogbeide, Francesca Giannese, Laura Mincarelli, Iain C. Macaulay
Journal: Trends in Genetics (2022)

Single-cell transcriptomic approaches have revolutionised the study of complex biological systems, with the routine measurement of gene expression in thousands of cells enabling construction of whole-organism cell atlases. However, the transcriptome is just one layer amongst many that coordinate to define cell type and state and, ultimately, function. In parallel with the widespread uptake of single-cell RNA-seq (scRNA-seq), there has been a rapid emergence of methods that enable multiomic profiling of individual cells, enabling parallel measurement of intercellular heterogeneity in the genome, epigenome, transcriptome, and proteomes. Linking measurements from each of these layers has the potential to reveal regulatory and functional mechanisms underlying cell behaviour in healthy development and disease.
Second Heart Field–Derived Cells Contribute to Angiotensin II–Mediated Ascending Aortopathies
Authors: Hisashi Sawada, Yuriko Katsumata, Hideyuki Higashi, Chen Zhang, Yanming Li, Stephanie Morgan, Lang H. Lee, Sasha A. Singh, Jeff Z. Chen, Michael K. Franklin, Jessica J. Moorleghen, Deborah A. Howatt, Debra L. Rateri, Ying H. Shen, Scott A. LeMaire, Masanori Aikawa, Mark W. Majesky, Hong S. Lu, Alan Daugherty
Journal: Circulation (2022)

Background: The ascending aorta is a common location for aneurysm and dissection. This aortic region is populated by a mosaic of medial and adventitial cells that are embryonically derived from either the second heart field (SHF) or the cardiac neural crest. SHF-derived cells populate areas that coincide with the spatial specificity of thoracic aortopathies. The purpose of this study was to determine whether and how SHF-derived cells contribute to ascending aortopathies. Methods: Ascending aortic pathologies were examined in patients with sporadic thoracic aortopathies and angiotensin II (AngII)–infused mice. Ascending aortas without overt pathology from AngII-infused mice were subjected to mass spectrometry–assisted proteomics and molecular features of SHF-derived cells were determined by single-cell transcriptomic analyses. Genetic deletion of either Lrp1 (low-density lipoprotein receptor–related protein 1) or Tgfbr2 (transforming growth factor–β receptor type 2) in SHF-derived cells was conducted to examine the effect of SHF-derived cells on vascular integrity. Results: Pathologies in human ascending aortic aneurysmal tissues were predominant in outer medial layers and adventitia. This gradient was mimicked in mouse aortas after AngII infusion that was coincident with the distribution of SHF-derived cells. Proteomics indicated that brief AngII infusion before overt pathology occurred evoked downregulation of smooth muscle cell proteins and differential expression of extracellular matrix proteins, including several LRP1 ligands. LRP1 deletion in SHF-derived cells augmented AngII-induced ascending aortic aneurysm and rupture. Single-cell transcriptomic analysis revealed that brief AngII infusion decreased Lrp1 and Tgfbr2 mRNA abundance in SHF-derived cells and induced a unique fibroblast population with low abundance of Tgfbr2 mRNA. SHF-specific Tgfbr2 deletion led to embryonic lethality at E12.5 with dilatation of the outflow tract and retroperitoneal hemorrhage. Integration of proteomic and single-cell transcriptomics results identified PAI1 (plasminogen activator inhibitor 1) as the most increased protein in SHF-derived smooth muscle cells and fibroblasts during AngII infusion. Immunostaining revealed a transmural gradient of PAI1 in both ascending aortas of AngII-infused mice and human ascending aneurysmal aortas that mimicked the gradient of medial and adventitial pathologies. Conclusions: SHF-derived cells exert a critical role in maintaining vascular integrity through LRP1 and transforming growth factor–β signaling associated with increases of aortic PAI1.
The Nuclear Proteins TP73 and CUL4A Confer Resistance to Cytarabine by Induction of Translesion DNA Synthesis via Mono-ubiquitination of PCNA
Authors: Miriam Rehberger, Jonas A. Schäfer, Anna-Maria Krampitz, Anne Catherine Bretz, Lukas Jost, Torsten Haferlach, Thorsten Stiewe, Andreas Neubauer
Journal: HemaSphere (2022)

Resistance to cytarabine is a key problem in the treatment of acute myeloid leukemia (AML). To understand the molecular biology of resistance to cytarabine, a viability-based chemosensitizer screen was utilized. We screened synthetic lethal targets using 437 different small interfering RNAs (siRNAs) directed against factors involved in DNA repair mechanisms and cytarabine as the chemical compound. Three hits were identified: CUL4A , TP73 , and RFC2 . We show here that the ubiquitin ligase CULLIN 4A (CUL4A) and the tumor-suppressive transcription factor p73 contribute to drug resistance by modulating DNA damage response. P73 confers resistance to cytarabine therapy by transactivation of REV3L , encoding the catalytic subunit of translesion DNA polymerase ζ, and CUL4A probably by influencing proliferating cell nuclear antigen (PCNA) and the polymerase switch towards error-prone translesion DNA polymerases. Abrogation of the polymerase ζ by siRNA causes identical effects as siRNAs against CUL4A or TP73 and resensitizes cells towards cytarabine therapy in vitro. As CUL4A needs to be activated by neddylation to facilitate the degradation of several proteins including PCNA, we propose a novel explanation for the synergism between cytarabine and the neddylation inhibitor pevonedistat by inhibition of translesion synthesis. In keeping with this, in AML patients treated with cytarabine, we found high expression of CUL4A and TP73 to be associated with poor prognosis.
Harnessing Big Data to Advance Treatment and Understanding of Pulmonary Hypertension
Authors: Christopher J. Rhodes, Andrew J. Sweatt, Bradley A. Maron
Journal: Circulation Research (2022)

Pulmonary hypertension is a complex disease with multiple causes, corresponding to phenotypic heterogeneity and variable therapeutic responses. Advancing understanding of pulmonary hypertension pathogenesis is likely to hinge on integrated methods that leverage data from health records, imaging, novel molecular -omics profiling, and other modalities. In this review, we summarize key data sets generated thus far in the field and describe analytical methods that hold promise for deciphering the molecular mechanisms that underpin pulmonary vascular remodeling, including machine learning, network medicine, and functional genetics. We also detail how genetic and subphenotyping approaches enable earlier diagnosis, refined prognostication, and optimized treatment prediction. We propose strategies that identify functionally important molecular pathways, bolstered by findings across multi-omics platforms, which are well-positioned to individualize drug therapy selection and advance precision medicine in this highly morbid disease.
Antibody evasion of SARS-CoV-2 Omicron BA.1, BA.1.1, BA.2, and BA.3 sub-lineages
Authors: Jingwen Ai, Xun Wang, Xinyi He, Xiaoyu Zhao, Yi Zhang, Yuchao Jiang, Minghui Li, Yuchen Cui, Yanjia Chen, Rui Qiao, Lin Li, Lulu Yang, Yi Li, Zixin Hu, Wenhong Zhang, Pengfei Wang
Journal: Cell Host & Microbe (2022)
Step Therapy’s Balancing Act — Protecting Patients while Addressing High Drug Prices
Authors: Rachel E. Sachs, Michael Anne Kyle
Journal: New England Journal of Medicine (2022)

Interview with Prof. Rachel Sachs on the balance between safeguarding access to high-quality care and constraining drug spending. (07:21)Download The debate regarding step therapy reflects a tension between two important policy goals: safeguarding patients' access to high-quality care and constraining spending on prescription drugs, including by limiting the overuse of costly medications with uncertain efficacy.
Distinct Patterns of Clonal Evolution Drive Myelodysplastic Syndrome Progression to Secondary Acute Myeloid Leukemia
Authors: Tiffany Guess, Chad R. Potts, Pawan Bhat, Justin A. Cartailler, Austin Brooks, Clinton Holt, Ashwini Yenamandra, Ferrin C. Wheeler, Michael R. Savona, Jean-Philippe Cartailler, P. Brent Ferrell
Journal: Blood Cancer Discovery (2022)

Abstract Clonal evolution in myelodysplastic syndrome (MDS) can result in clinical progression and secondary acute myeloid leukemia (sAML). To dissect changes in clonal architecture associated with this progression, we performed single-cell genotyping of paired MDS and sAML samples from 18 patients. Analysis of single-cell genotypes revealed patient-specific clonal evolution and enabled the assessment of single-cell mutational cooccurrence. We discovered that changes in clonal architecture proceed via distinct patterns, classified as static or dynamic, with dynamic clonal architectures having a more proliferative phenotype by blast count fold change. Proteogenomic analysis of a subset of patients confirmed that pathogenic mutations were primarily confined to primitive and mature myeloid cells, though we also identify rare but present mutations in lymphocyte subsets. Single-cell transcriptomic analysis of paired sample sets further identified gene sets and signaling pathways involved in two cases of progression. Together, these data define serial changes in the MDS clonal landscape with clinical and therapeutic implications. Significance: Precise clonal trajectories in MDS progression are made possible by single-cell genomic sequencing. Here we use this technology to uncover the patterns of clonal architecture and clonal evolution that drive the transformation to secondary AML. We further define the phenotypic and transcriptional changes of disease progression at the single-cell level. See related article by Menssen et al., p. 330 (31). See related commentary by Romine and van Galen, p. 270. This article is highlighted in the In This Issue feature, p. 265
MERLIN: Phase 3a, Multicenter, Randomized, Double-Masked Trial of Brolucizumab in Participants with Neovascular Age-Related Macular Degeneration and Persistent Retinal Fluid
Authors: Arshad M. Khanani, David M. Brown, Glenn J. Jaffe, Charles C. Wykoff, Eser Adiguzel, Randall Wong, Xiangyi Meng, Jeffrey S. Heier
Journal: Ophthalmology (2022)
A deep graph neural network architecture for modelling spatio-temporal dynamics in resting-state functional MRI data
Authors: Tiago Azevedo, Alexander Campbell, Rafael Romero-Garcia, Luca Passamonti, Richard A.I. Bethlehem, Pietro Liò, Nicola Toschi
Journal: Medical Image Analysis (2022)

Resting-state functional magnetic resonance imaging (rs-fMRI) has been successfully employed to understand the organisation of the human brain. Typically, the brain is parcellated into regions of interest (ROIs) and modelled as a graph where each ROI represents a node and association measures between ROI-specific blood-oxygen-level-dependent (BOLD) time series are edges. Recently, graph neural networks (GNNs) have seen a surge in popularity due to their success in modelling unstructured relational data. The latest developments with GNNs, however, have not yet been fully exploited for the analysis of rs-fMRI data, particularly with regards to its spatio-temporal dynamics. In this paper, we present a novel deep neural network architecture which combines both GNNs and temporal convolutional networks (TCNs) in order to learn from both the spatial and temporal components of rs-fMRI data in an end-to-end fashion. In particular, this corresponds to intra-feature learning (i.e., learning temporal dynamics with TCNs) as well as inter-feature learning (i.e., leveraging interactions between ROI-wise dynamics with GNNs). We evaluate our model with an ablation study using 35,159 samples from the UK Biobank rs-fMRI database, as well as in the smaller Human Connectome Project (HCP) dataset, both in a unimodal and in a multimodal fashion. We also demonstrate that out architecture contains explainability-related features which easily map to realistic neurobiological insights. We suggest that this model could lay the groundwork for future deep learning architectures focused on leveraging the inherently and inextricably spatio-temporal nature of rs-fMRI data.
Genetic Landscape of the ACE2 Coronavirus Receptor
Authors: Zhijian Yang, Erin Macdonald-Dunlop, Jiantao Chen, Ranran Zhai, Ting Li, Anne Richmond, Lucija Klarić, Nicola Pirastu, Zheng Ning, Chenqing Zheng, Yipeng Wang, Tingting Huang, Yazhou He, Huiming Guo, Kejun Ying, Stefan Gustafsson, Bram Prins, Anna Ramisch, Emmanouil T. Dermitzakis, Grace Png, Niclas Eriksson, Jeffrey Haessler, Xiaowei Hu, Daniela Zanetti, Thibaud Boutin, Shih-Jen Hwang, Eleanor Wheeler, Maik Pietzner, Laura M. Raffield, Anette Kalnapenkis, James E. Peters, Ana Viñuela, Arthur Gilly, Sölve Elmståhl, George Dedoussis, John R. Petrie, Ozren Polašek, Lasse Folkersen, Yan Chen, Chen Yao, Urmo Võsa, Erola Pairo-Castineira, Sara Clohisey, Andrew D. Bretherick, Konrad Rawlik, Tõnu Esko, Stefan Enroth, Åsa Johansson, Ulf Gyllensten, Claudia Langenberg, Daniel Levy, Caroline Hayward, Themistocles L. Assimes, Charles Kooperberg, Ani W. Manichaikul, Agneta Siegbahn, Lars Wallentin, Lars Lind, Eleftheria Zeggini, Jochen M. Schwenk, Adam S. Butterworth, Karl Michaëlsson, Yudi Pawitan, Peter K. Joshi, J. Kenneth Baillie, Anders Mälarstig, Alexander P. Reiner, James F. Wilson, Xia Shen
Journal: Circulation (2022)

SARS-CoV-2, the causal agent of COVID-19, enters human cells using the ACE2 (angiotensin-converting enzyme 2) protein as a receptor. ACE2 is thus key to the infection and treatment of the coronavirus. ACE2 is highly expressed in the heart and respiratory and gastrointestinal tracts, playing important regulatory roles in the cardiovascular and other biological systems. However, the genetic basis of the ACE2 protein levels is not well understood.
Text Messages to Improve Medication Adherence and Secondary Prevention After Acute Coronary Syndrome: The TEXTMEDS Randomized Clinical Trial
Authors: Clara K. Chow, Harry Klimis, Aravinda Thiagalingam, Julie Redfern, Graham S. Hillis, David Brieger, John Atherton, Ravinay Bhindi, Derek P. Chew, Nicholas Collins, Michael Andrew Fitzpatrick, Craig Juergens, Nadarajah Kangaharan, Andrew Maiorana, Michele McGrady, Rohan Poulter, Pratap Shetty, Jonathon Waites, Christian Hamilton Craig, Peter Thompson, Sandrine Stepien, Amy Von Huben, Anthony Rodgers
Journal: Circulation (2022)

Background: TEXTMEDS (Text Messages to Improve Medication Adherence and Secondary Prevention After Acute Coronary Syndrome) examined the effects of text message–delivered cardiac education and support on medication adherence after an acute coronary syndrome. Methods: TEXTMEDS was a single-blind, multicenter, randomized controlled trial of patients after acute coronary syndrome. The control group received usual care (secondary prevention as determined by the treating clinician); the intervention group also received multiple motivational and supportive weekly text messages on medications and healthy lifestyle with the opportunity for 2-way communication (text or telephone). The primary end point of self-reported medication adherence was the percentage of patients who were adherent, defined as &gt;80% adherence to each of up to 5 indicated cardioprotective medications, at both 6 and 12 months. Results: A total of 1424 patients (mean age, 58 years [SD, 11]; 79% male) were randomized from 18 Australian public teaching hospitals. There was no significant difference in the primary end point of self-reported medication adherence between the intervention and control groups (relative risk, 0.93 [95% CI, 0.84–1.03]; P =0.15). There was no difference between intervention and control groups at 12 months in adherence to individual medications (aspirin, 96% vs 96%; β-blocker, 84% vs 84%; angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, 77% vs 80%; statin, 95% vs 95%; second antiplatelet, 84% vs 84% [all P &gt;0.05]), systolic blood pressure (130 vs 129 mm Hg; P =0.26), low-density lipoprotein cholesterol (2.0 vs 1.9 mmol/L; P =0.34), smoking ( P =0.59), or exercising regularly (71% vs 68%; P =0.52). There were small differences in lifestyle risk factors in favor of intervention on body mass index &lt;25 kg/m 2 (21% vs 18%; P =0.01), eating ≥5 servings per day of vegetables (9% vs 5%; P =0.03), and eating ≥2 servings per day of fruit (44% vs 39%; P =0.01). Conclusions: A text message–based program had no effect on medical adherence but small effects on lifestyle risk factors. Registration: URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=364448 ; Unique identifier: ANZCTR ACTRN12613000793718.
Comparison of tenecteplase with alteplase for the early treatment of ischaemic stroke in the Melbourne Mobile Stroke Unit (TASTE-A): a phase 2, randomised, open-label trial
Authors: Andrew Bivard, Henry Zhao, Leonid Churilov, Bruce C V Campbell, Skye Coote, Nawaf Yassi, Bernard Yan, Michael Valente, Angelos Sharobeam, Anna H Balabanski, Angela Dos Santos, Jo Lyn Ng, Vignan Yogendrakumar, Felix Ng, Francesca Langenberg, Damien Easton, Alex Warwick, Elizabeth Mackey, Amy MacDonald, Gagan Sharma, Michael Stephenson, Karen Smith, David Anderson, Philip Choi, Vincent Thijs, Henry Ma, Geoffrey C Cloud, Tissa Wijeratne, Liudmyla Olenko, Dominic Italiano, Stephen M Davis, Geoffrey A Donnan, Mark W Parsons
Journal: The Lancet Neurology (2022)
Ivosidenib Boosts OS with Azacitidine in AML
Journal: Cancer Discovery (2022)

A recent phase III study shows that the combination of azacitidine with the IDH1 inhibitor ivosidenib is more effective than azacitidine alone in patients with acute myeloid leukemia who aren't eligible for intensive chemotherapy. The drug duo tripled overall survival and increased complete remission and event-free survival rates.
Self-rule to multi-adapt: Generalized multi-source feature learning using unsupervised domain adaptation for colorectal cancer tissue detection
Authors: Christian Abbet, Linda Studer, Andreas Fischer, Heather Dawson, Inti Zlobec, Behzad Bozorgtabar, Jean-Philippe Thiran
Journal: Medical Image Analysis (2022)

Supervised learning is constrained by the availability of labeled data, which are especially expensive to acquire in the field of digital pathology. Making use of open-source data for pre-training or using domain adaptation can be a way to overcome this issue. However, pre-trained networks often fail to generalize to new test domains that are not distributed identically due to tissue stainings, types, and textures variations. Additionally, current domain adaptation methods mainly rely on fully-labeled source datasets. In this work, we propose Self-Rule to Multi-Adapt (SRMA), which takes advantage of self-supervised learning to perform domain adaptation, and removes the necessity of fully-labeled source datasets. SRMA can effectively transfer the discriminative knowledge obtained from a few labeled source domain's data to a new target domain without requiring additional tissue annotations. Our method harnesses both domains' structures by capturing visual similarity with intra-domain and cross-domain self-supervision. Moreover, we present a generalized formulation of our approach that allows the framework to learn from multiple source domains. We show that our proposed method outperforms baselines for domain adaptation of colorectal tissue type classification in single and multi-source settings, and further validate our approach on an in-house clinical cohort. The code and trained models are available open-source: https://github.com/christianabbet/SRA.
<scp>Interleukin‐17RA</scp> blockade by brodalumab decreases inflammatory pathways in hidradenitis suppurativa skin and serum
Authors: Christina H. Scheel, Nessr Abu Rached, Thilo Gambichler
Journal: British Journal of Dermatology (2022)

Linked Article: Navrazhina et al. Br J Dermatol 2022; 187:223–233.
Interleukin-6 blockade abrogates immunotherapy toxicity and promotes tumor immunity
Authors: Yared Hailemichael, Daniel H. Johnson, Noha Abdel-Wahab, Wai Chin Foo, Salah-Eddine Bentebibel, May Daher, Cara Haymaker, Khalida Wani, Chantal Saberian, Dai Ogata, Sang T. Kim, Roza Nurieva, Alexander J. Lazar, Hamzah Abu-Sbeih, Faisal Fa'ak, Antony Mathew, Yinghong Wang, Adewunmi Falohun, Van Trinh, Chrystia Zobniw, Christine Spillson, Jared K. Burks, Muhammad Awiwi, Khaled Elsayes, Luisa Solis Soto, Brenda D. Melendez, Michael A. Davies, Jennifer Wargo, Jonathan Curry, Cassian Yee, Gregory Lizee, Shalini Singh, Padmanee Sharma, James P. Allison, Patrick Hwu, Suhendan Ekmekcioglu, Adi Diab
Journal: Cancer Cell (2022)
Author Correction: The brain structure and genetic mechanisms underlying the nonlinear association between sleep duration, cognition and mental health
Authors: Yuzhu Li, Barbara J. Sahakian, Jujiao Kang, Christelle Langley, Wei Zhang, Chao Xie, Shitong Xiang, Jintai Yu, Wei Cheng, Jianfeng Feng
Journal: Nature Aging (2022)
Bi-order multimodal integration of single-cell data
Authors: Jinzhuang Dou, Shaoheng Liang, Vakul Mohanty, Qi Miao, Yuefan Huang, Qingnan Liang, Xuesen Cheng, Sangbae Kim, Jongsu Choi, Yumei Li, Li Li, May Daher, Rafet Basar, Katayoun Rezvani, Rui Chen, Ken Chen
Journal: Genome biology (2022)

Integration of single-cell multiomics profiles generated by different single-cell technologies from the same biological sample is still challenging. Previous approaches based on shared features have only provided approximate solutions. Here, we present a novel mathematical solution named bi-order canonical correlation analysis (bi-CCA), which extends the widely used CCA approach to iteratively align the rows and the columns between data matrices. Bi-CCA is generally applicable to combinations of any two single-cell modalities. Validations using co-assayed ground truth data and application to a CAR-NK study and a fetal muscle atlas demonstrate its capability in generating accurate multimodal co-embeddings and discovering cellular identity.
Immunosuppression impaired the immunogenicity of inactivated SARS-CoV-2 vaccine in non-dialysis kidney disease patients
Authors: Yue-Miao Zhang, Xing-Zi Liu, Miao-Miao Lin, Jin-Can Zan, Yi-Tong Hu, Xiang-Qiu Wang, Wen-Qi Wu, Tai-Cheng Zhou, Ji-Cheng Lv, Hong Zhang, Li Yang, Zi-Jie Zhang
Journal: Journal of Infection (2022)
Superior immunogenicity and effectiveness of the third compared to the second BNT162b2 vaccine dose
Authors: Yaniv Lustig, Tal Gonen, Lilac Meltzer, Mayan Gilboa, Victoria Indenbaum, Carmit Cohen, Sharon Amit, Hanaa Jaber, Ram Doolman, Keren Asraf, Carmit Rubin, Ronen Fluss, Ella Mendelson, Laurence Freedman, Gili Regev-Yochay, Yitshak Kreiss
Journal: Nature Immunology (2022)
Hypoxia induces adrenomedullin from lung epithelia, stimulating ILC2 inflammation and immunity
Authors: Jihye Han, Qingqing Wan, Goo-Young Seo, Kenneth Kim, Sarah el Baghdady, Jee H. Lee, Mitchell Kronenberg, Yun-Cai Liu
Journal: The Journal of Experimental Medicine (2022)

Hypoxia contributes to airway inflammation and remodeling in several lung diseases; however, exactly how hypoxic pulmonary epithelium regulates allergic inflammation remains to be fully characterized. Here, we report that conditional deletion of the E3 ubiquitin ligase VHL in lung epithelial cells resulted in exacerbated type 2 responses accompanied by selective increase of group 2 innate lymphoid cells (ILC2s) at steady state and following inflammation or helminth infection. Ablation of expression of the hypoxia-inducible factor 2α (HIF2α) significantly reversed VHL-mediated ILC2 activation. VHL deficiency in lung epithelial cells caused increased expression of the peptide hormone adrenomedullin (ADM), and our data suggest that HIF2α controls Adm expression. ADM directly promoted ILC2 activation both in vitro and in vivo. Our findings indicate that the hypoxic response mediated by the VHL–HIF2α axis is critical for control of pulmonary type 2 responses by increasing ADM expression in lung epithelia, causing ILC2 activation.