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  1. Article ; Online: Testicular Traction Technique in an Adolescent With Torsion.

    Scheier, Eric / Levy, Efrat Shapira

    Pediatric emergency care

    2023  Volume 39, Issue 11, Page(s) e75–e76

    MeSH term(s) Male ; Humans ; Adolescent ; Traction ; Testis ; Spermatic Cord Torsion/diagnosis ; Spermatic Cord Torsion/surgery ; Retrospective Studies
    Language English
    Publishing date 2023-07-29
    Publishing country United States
    Document type Journal Article
    ZDB-ID 632588-9
    ISSN 1535-1815 ; 0749-5161
    ISSN (online) 1535-1815
    ISSN 0749-5161
    DOI 10.1097/PEC.0000000000003024
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2083: Show issues Location:
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  2. Article: Exosomes in the Diseased Brain: First Insights from

    Levy, Efrat

    Frontiers in neuroscience

    2017  Volume 11, Page(s) 142

    Abstract: Extracellular vesicles (EVs) are nanoscale size vesicles secreted by cells and are important mediators of intercellular communication and genetic exchange. Exosomes, EVs generated in endosomal multivesicular bodies, have been the focus of numerous ... ...

    Abstract Extracellular vesicles (EVs) are nanoscale size vesicles secreted by cells and are important mediators of intercellular communication and genetic exchange. Exosomes, EVs generated in endosomal multivesicular bodies, have been the focus of numerous publications as they have emerged as clinically valuable markers of disease states. Exosomes have been mostly studied from conditioned culture media and body fluids, with the difficulty of isolating exosomes from tissues having delayed their study
    Language English
    Publishing date 2017-03-23
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2411902-7
    ISSN 1662-453X ; 1662-4548
    ISSN (online) 1662-453X
    ISSN 1662-4548
    DOI 10.3389/fnins.2017.00142
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Book ; Online: ZeroSCROLLS

    Shaham, Uri / Ivgi, Maor / Efrat, Avia / Berant, Jonathan / Levy, Omer

    A Zero-Shot Benchmark for Long Text Understanding

    2023  

    Abstract: We introduce ZeroSCROLLS, a zero-shot benchmark for natural language understanding over long texts, which contains only test and small validation sets, without training data. We adapt six tasks from the SCROLLS benchmark, and add four new datasets, ... ...

    Abstract We introduce ZeroSCROLLS, a zero-shot benchmark for natural language understanding over long texts, which contains only test and small validation sets, without training data. We adapt six tasks from the SCROLLS benchmark, and add four new datasets, including two novel information fusing tasks, such as aggregating the percentage of positive reviews. Using ZeroSCROLLS, we conduct a comprehensive evaluation of both open-source and closed large language models, finding that Claude outperforms ChatGPT, and that GPT-4 achieves the highest average score. However, there is still room for improvement on multiple open challenges in ZeroSCROLLS, such as aggregation tasks, where models struggle to pass the naive baseline. As the state of the art is a moving target, we invite researchers to evaluate their ideas on the live ZeroSCROLLS leaderboard.

    Comment: Findings of EMNLP 2023
    Keywords Computer Science - Computation and Language ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning ; Statistics - Machine Learning
    Subject code 006
    Publishing date 2023-05-23
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Book ; Online: LMentry

    Efrat, Avia / Honovich, Or / Levy, Omer

    A Language Model Benchmark of Elementary Language Tasks

    2022  

    Abstract: As the performance of large language models rapidly improves, benchmarks are getting larger and more complex as well. We present LMentry, a benchmark that avoids this "arms race" by focusing on a compact set of tasks that are trivial to humans, e.g. ... ...

    Abstract As the performance of large language models rapidly improves, benchmarks are getting larger and more complex as well. We present LMentry, a benchmark that avoids this "arms race" by focusing on a compact set of tasks that are trivial to humans, e.g. writing a sentence containing a specific word, identifying which words in a list belong to a specific category, or choosing which of two words is longer. LMentry is specifically designed to provide quick and interpretable insights into the capabilities and robustness of large language models. Our experiments reveal a wide variety of failure cases that, while immediately obvious to humans, pose a considerable challenge for large language models, including OpenAI's latest 175B-parameter instruction-tuned model, TextDavinci002. LMentry complements contemporary evaluation approaches of large language models, providing a quick, automatic, and easy-to-run "unit test", without resorting to large benchmark suites of complex tasks.

    Comment: minor results updates
    Keywords Computer Science - Computation and Language ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning
    Publishing date 2022-11-03
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Book ; Online: The Turking Test

    Efrat, Avia / Levy, Omer

    Can Language Models Understand Instructions?

    2020  

    Abstract: Supervised machine learning provides the learner with a set of input-output examples of the target task. Humans, however, can also learn to perform new tasks from instructions in natural language. Can machines learn to understand instructions as well? We ...

    Abstract Supervised machine learning provides the learner with a set of input-output examples of the target task. Humans, however, can also learn to perform new tasks from instructions in natural language. Can machines learn to understand instructions as well? We present the Turking Test, which examines a model's ability to follow natural language instructions of varying complexity. These range from simple tasks, like retrieving the nth word of a sentence, to ones that require creativity, such as generating examples for SNLI and SQuAD in place of human intelligence workers ("turkers"). Despite our lenient evaluation methodology, we observe that a large pretrained language model performs poorly across all tasks. Analyzing the model's error patterns reveals that the model tends to ignore explicit instructions and often generates outputs that cannot be construed as an attempt to solve the task. While it is not yet clear whether instruction understanding can be captured by traditional language models, the sheer expressivity of instruction understanding makes it an appealing alternative to the rising few-shot inference paradigm.
    Keywords Computer Science - Computation and Language ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning
    Subject code 401
    Publishing date 2020-10-22
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article: Exosome Production Is Key to Neuronal Endosomal Pathway Integrity in Neurodegenerative Diseases.

    Mathews, Paul M / Levy, Efrat

    Frontiers in neuroscience

    2019  Volume 13, Page(s) 1347

    Abstract: Dysfunction of the endosomal-lysosomal system is a prominent pathogenic factor in Alzheimer's disease (AD) and other neurodevelopmental and neurodegenerative disorders. We and others have extensively characterized the neuronal endosomal pathway pathology ...

    Abstract Dysfunction of the endosomal-lysosomal system is a prominent pathogenic factor in Alzheimer's disease (AD) and other neurodevelopmental and neurodegenerative disorders. We and others have extensively characterized the neuronal endosomal pathway pathology that results from either triplication of the amyloid-β precursor protein (APP) gene in Down syndrome (DS) or from expression of the apolipoprotein E ε4 allele (APOE4), the greatest genetic risk factor for late-onset AD. More recently brain exosomes, extracellular vesicles that are generated within and released from endosomal compartments, have been shown to be altered in DS and by APOE4 expression. In this review, we discuss the emerging data arguing for an interdependence between exosome production and endosomal pathway integrity in the brain.
    Language English
    Publishing date 2019-12-12
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2411902-7
    ISSN 1662-453X ; 1662-4548
    ISSN (online) 1662-453X
    ISSN 1662-4548
    DOI 10.3389/fnins.2019.01347
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  7. Book ; Online: Cryptonite

    Efrat, Avia / Shaham, Uri / Kilman, Dan / Levy, Omer

    A Cryptic Crossword Benchmark for Extreme Ambiguity in Language

    2021  

    Abstract: Current NLP datasets targeting ambiguity can be solved by a native speaker with relative ease. We present Cryptonite, a large-scale dataset based on cryptic crosswords, which is both linguistically complex and naturally sourced. Each example in ... ...

    Abstract Current NLP datasets targeting ambiguity can be solved by a native speaker with relative ease. We present Cryptonite, a large-scale dataset based on cryptic crosswords, which is both linguistically complex and naturally sourced. Each example in Cryptonite is a cryptic clue, a short phrase or sentence with a misleading surface reading, whose solving requires disambiguating semantic, syntactic, and phonetic wordplays, as well as world knowledge. Cryptic clues pose a challenge even for experienced solvers, though top-tier experts can solve them with almost 100% accuracy. Cryptonite is a challenging task for current models; fine-tuning T5-Large on 470k cryptic clues achieves only 7.6% accuracy, on par with the accuracy of a rule-based clue solver (8.6%).

    Comment: EMNLP 2021
    Keywords Computer Science - Computation and Language ; Computer Science - Artificial Intelligence ; Computer Science - Machine Learning ; Statistics - Machine Learning
    Publishing date 2021-03-01
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Book ; Online: How Optimal is Greedy Decoding for Extractive Question Answering?

    Castel, Or / Ram, Ori / Efrat, Avia / Levy, Omer

    2021  

    Abstract: Fine-tuned language models use greedy decoding to answer reading comprehension questions with relative success. However, this approach does not ensure that the answer is a span in the given passage, nor does it guarantee that it is the most probable one. ...

    Abstract Fine-tuned language models use greedy decoding to answer reading comprehension questions with relative success. However, this approach does not ensure that the answer is a span in the given passage, nor does it guarantee that it is the most probable one. Does greedy decoding actually perform worse than an algorithm that does adhere to these properties? To study the performance and optimality of greedy decoding, we present exact-extract, a decoding algorithm that efficiently finds the most probable answer span in the context. We compare the performance of T5 with both decoding algorithms on zero-shot and few-shot extractive question answering. When no training examples are available, exact-extract significantly outperforms greedy decoding. However, greedy decoding quickly converges towards the performance of exact-extract with the introduction of a few training examples, becoming more extractive and increasingly likelier to generate the most probable span as the training set grows. We also show that self-supervised training can bias the model towards extractive behavior, increasing performance in the zero-shot setting without resorting to annotated examples. Overall, our results suggest that pretrained language models are so good at adapting to extractive question answering, that it is often enough to fine-tune on a small training set for the greedy algorithm to emulate the optimal decoding strategy.

    Comment: 12 pages, 3 figures
    Keywords Computer Science - Computation and Language
    Subject code 006
    Publishing date 2021-08-12
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Mmp2 Deficiency Leads to Defective Parturition and High Dystocia Rates in Mice.

    Kalev-Altman, Rotem / Becker, Gal / Levy, Tamar / Penn, Svetlana / Shpigel, Nahum Y / Monsonego-Ornan, Efrat / Sela-Donenfeld, Dalit

    International journal of molecular sciences

    2023  Volume 24, Issue 23

    Abstract: Parturition is the final and essential step for mammalian reproduction. While the uterus is quiescent during pregnancy, fundamental changes arise in the myometrial contractility, inducing fetal expulsion. Extracellular matrix (ECM) remodeling is ... ...

    Abstract Parturition is the final and essential step for mammalian reproduction. While the uterus is quiescent during pregnancy, fundamental changes arise in the myometrial contractility, inducing fetal expulsion. Extracellular matrix (ECM) remodeling is fundamental for these events. The gelatinases subgroup of matrix metalloproteinases (MMPs), MMP2 and MMP9, participate in uterine ECM remodeling throughout pregnancy and parturition. However, their loss-of-function effect is unknown. Here, we determined the result of eliminating
    MeSH term(s) Animals ; Female ; Mice ; Pregnancy ; Dystocia/genetics ; Dystocia/pathology ; Mammals ; Matrix Metalloproteinase 2/genetics ; Matrix Metalloproteinase 9/genetics ; Myometrium/pathology ; Parturition/genetics
    Chemical Substances Matrix Metalloproteinase 2 (EC 3.4.24.24) ; Matrix Metalloproteinase 9 (EC 3.4.24.35) ; Mmp2 protein, mouse (EC 3.4.24.24)
    Language English
    Publishing date 2023-11-27
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2019364-6
    ISSN 1422-0067 ; 1422-0067 ; 1661-6596
    ISSN (online) 1422-0067
    ISSN 1422-0067 ; 1661-6596
    DOI 10.3390/ijms242316822
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  10. Article ; Online: Mortality prediction using a modified R

    Levy, David / Gur, Efrat / Topaz, Guy / Naser, Rawand / Kitay-Cohen, Yona / Benchetrit, Sydney / Sarel, Erez / Cohen-Hagai, Keren / Wand, Ori

    Internal and emergency medicine

    2022  Volume 17, Issue 6, Page(s) 1711–1717

    Abstract: ... The ... ...

    Abstract The CHA
    MeSH term(s) Adult ; Aged ; Aged, 80 and over ; Atrial Fibrillation/epidemiology ; COVID-19/complications ; Comorbidity ; Female ; Hospitalization ; Humans ; Male ; Middle Aged ; Prognosis ; Retrospective Studies ; Risk Assessment ; Risk Factors
    Language English
    Publishing date 2022-06-25
    Publishing country Italy
    Document type Journal Article
    ZDB-ID 2454173-4
    ISSN 1970-9366 ; 1828-0447
    ISSN (online) 1970-9366
    ISSN 1828-0447
    DOI 10.1007/s11739-022-02993-z
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