Fast genetic mapping of complex traits in C. elegans using millions of individuals in bulk.

Genetic studies of complex traits in animals have been hindered by the need to generate, maintain, and phenotype large panels of recombinant lines. We developed a new method, C. elegans eXtreme Quantitative Trait Locus (ceX-QTL) mapping, that overcomes this obstacle via bulk selection on millions of unique recombinant individuals. We use ceX-QTL to map a drug resistance locus with high resolution. We also map differences in gene expression in live worms and discovered that mutations in the co-chaperone sti-1 upregulate the transcription of HSP-90. Lastly, we use ceX-QTL to map loci that influence fitness genome-wide confirming previously reported causal variants and uncovering new fitness loci. ceX-QTL is fast, powerful and cost-effective, and will accelerate the study of complex traits in animals

Navigating Cultural Chasms: Exploring and Unlocking the Cultural POV of Text-To-Image Models

Text-To-Image (TTI) models, such as DALL-E and StableDiffusion, have demonstrated remarkable prompt-based image generation capabilities. Multilingual encoders may have a substantial impact on the cultural agency of these models, as language is a conduit of culture. In this study, we explore the cultural perception embedded in TTI models by characterizing culture across three hierarchical tiers: cultural dimensions, cultural domains, and cultural concepts. Based on this ontology, we derive prompt templates to unlock the cultural knowledge in TTI models, and propose a comprehensive suite of evaluation techniques, including intrinsic evaluations using the CLIP space, extrinsic evaluations with a Visual-Question-Answer (VQA) model and human assessments, to evaluate the cultural content of TTI-generated images. To bolster our research, we introduce the CulText2I dataset, derived from four diverse TTI models and spanning ten languages. Our experiments provide insights regarding Do, What, Which and How research questions about the nature of cultural encoding in TTI models, paving the way for cross-cultural applications of these models

Text2Model: Model Induction for Zero-shot Generalization Using Task Descriptions

We study the problem of generating a training-free task-dependent visual classifier from text descriptions without visual samples. This \textit{Text-to-Model} (T2M) problem is closely related to zero-shot learning, but unlike previous work, a T2M model infers a model tailored to a task, taking into account all classes in the task. We analyze the symmetries of T2M, and characterize the equivariance and invariance properties of corresponding models. In light of these properties, we design an architecture based on hypernetworks that given a set of new class descriptions predicts the weights for an object recognition model which classifies images from those zero-shot classes. We demonstrate the benefits of our approach compared to zero-shot learning from text descriptions in image and point-cloud classification using various types of text descriptions: From single words to rich text descriptions

Example-based Hypernetworks for Out-of-Distribution Generalization

As Natural Language Processing (NLP) algorithms continually achieve new milestones, out-of-distribution generalization remains a significant challenge. This paper addresses the issue of multi-source adaptation for unfamiliar domains: We leverage labeled data from multiple source domains to generalize to unknown target domains at training. Our innovative framework employs example-based Hypernetwork adaptation: a T5 encoder-decoder initially generates a unique signature from an input example, embedding it within the source domains' semantic space. This signature is subsequently utilized by a Hypernetwork to generate the task classifier's weights. We evaluated our method across two tasks - sentiment classification and natural language inference - in 29 adaptation scenarios, where it outpaced established algorithms. In an advanced version, the signature also enriches the input example's representation. We also compare our finetuned architecture to few-shot GPT-3, demonstrating its effectiveness in essential use cases. To our knowledge, this marks the first application of Hypernetworks to the adaptation for unknown domains.Comment: First two authors contributed equally to this work. Our code and data are available at: https://github.com/TomerVolk/Hyper-PAD

Energy allocation trade-offs as a function of age in fungiid corals

To compete effectively, living organisms must adjust the allocation of available energy resources for growth, survival, maintenance, and reproduction throughout their life histories. Energy demands and allocations change throughout the life history of an organism, and understanding their energy allocation strategies requires determination of the relative age of individuals. As most scleractinian corals are colonial, the relationship between age and mass/size is complicated by colony fragmentation, partial mortality, and asexual reproduction. To overcome these limitations, solitary mushroom corals, Herpolitha limax from Okinawa, Japan and Fungia fungites from Okinawa and the Great Barrier Reef (GBR), Australia, were used to investigate how energy allocation between these fundamental processes varies as a function of age. Measurements of the relative growth, biochemical profiles, fecundity of individuals of different sizes, and the settlement success of their progeny have revealed physiological trade-offs between growth and reproduction, with increasing body mass ultimately leading to senescence. The importance of energy allocation for reproduction led us to examine the reproductive strategies and sex allocation in the two studied species. In the present study, the smallest individuals of both species studied were found to invest most of their energy in relative growth, showing higher lipid and carbohydrate content than the later stages. In medium-sized corals, this pattern was overturned in favour of reproduction, manifesting in terms of both the highest fecundity and settlement success of the resulting brooded larvae. Finally, a phase of apparent senescence was observed in the largest individuals, characterized by a decrease in most of the parameters measured. In addition, complex reproductive plasticity has been revealed in F. fungites in the GBR, with individual females releasing eggs, embryos, planulae, or a combination of these. These data provide the most direct estimates currently available for physiological, age-related trade-offs during the life history of a coral. The unusual reproductive characteristics of the GBR F. fungites indicate previously unknown layers of complexity in the reproductive biology of corals and have implications for their adaptive potential across a wide geographical scale

Labeled EGFRTK irreversible inhibitor (ML03). In vitro and in vivo properties, potential as PET biomarker for cancer and feasibility as anticancer drug

Radiosynthesis of ML03 (N- {4 Key words: carbon-11; cancer; biodistribution; PET; EGFr Growth factors mediate their pleiotropic actions by binding to and activating receptor tyrosine kinases. Epidermal growth factor receptor (EGFr, erb-B1) belongs to a family of proteins involved in the proliferation of normal and malignant cells. 1,2 The binding of activating ligands such as EGF, TGF ␣, AR, BTC or HB-EGF to the EGFr results in activation of the cytosolic kinase domain. Overexpression of EGFr is the hallmark of many human tumors such as breast cancer, glioma, laryngeal cancer, squamous cell carcinoma of the head and neck and prostate cancer. In our previous work, 15 we synthesized, labeled and evaluated 4-(fluoroanilino)quinazoline derivatives as EGFrTK PET biomarkers. These molecules bind reversibly to the ATP binding site of the receptor and inhibit the autophosphorylation of the EGFrTK. Competition with intracellular ATP results in their fast dissociation from the EGFr kinase site, however, making these compounds ineffective as PET reporter probes. We therefore concluded that irreversible EGFr tyrosine kinase inhibitors labeled with carbon-11 might be more effective as PET markers for tumors overexpressing EGFr. A group of compounds (6-acrylamido-4-anilinoquinazolines) that bind irreversibly to the EGFr have been described recently. 16 -20 The ligand binds covalently to the cys-773, which is proximal to the ATP binding site