Rapid access to accurate equation-of-state (EOS) data is crucial in the warm-dense matter (WDM) regime, as it is employed in various applications, such as providing input for hydrodynamic codes to model inertial confinement fusion processes. In this study, we develop neural network models for predicting the EOS based on first-principles data. The first model utilises basic physical properties, while the second model incorporates more sophisticated physical information, using output from average-atom (AA) calculations as features. AA models are often noted for providing a reasonable balance of accuracy and speed; however, our comparison of AA models and higher-fidelity calculations shows that more accurate models are required in the WDM regime. Both the neural network models we propose, particularly the physics-enhanced one, demonstrate significant potential as accurate and efficient methods for computing EOS data in WDM.
Publisher's Version arXiv version
Intestinal inflammation is mediated by a subset of cells populating the intestine, such as enteric glial cells (EGC) and macrophages. Different studies indicate that phytocannabinoids could play a possible role in the treatment of inflammatory bowel disease (IBD) by relieving the symptoms involved in the disease. Phytocannabinoids act through the endocannabinoid system, which is distributed throughout the mammalian body in the cells of the immune system and in the intestinal cells. Our in vitro study analyzed the putative anti-inflammatory effect of nine selected pure cannabinoids in J774A1 macrophage cells and EGCs triggered to undergo inflammation with lipopolysaccharide (LPS). The anti-inflammatory effect of several phytocannabinoids was measured by their ability to reduce TNFα transcription and translation in J774A1 macrophages and to diminish S100B and GFAP secretion and transcription in EGCs. Our results demonstrate that THC at the lower concentrations tested exerted the most effective anti-inflammatory effect in both J774A1 macrophages and EGCs compared to the other phytocannabinoids tested herein. We then performed RNA-seq analysis of EGCs exposed to LPS in the presence or absence of THC or THC-COOH. Transcriptomic analysis of these EGCs revealed 23 differentially expressed genes (DEG) compared to the treatment with only LPS. Pretreatment with THC resulted in 26 DEG, and pretreatment with THC-COOH resulted in 25 DEG. To evaluate which biological pathways were affected by the different phytocannabinoid treatments, we used the Ingenuity platform. We show that THC treatment affects the mTOR and RAR signaling pathway, while THC-COOH mainly affects the IL6 signaling pathway.
Botvinik-Nezer Rotem, Petre, Bogdan , Ceko, Marta , Lindquist, Martin A, Friedman, Naomi P, ו Wager, Tor D. 2023.
“Placebo Treatment Affects Brain Systems Related To Affective And Cognitive Processes, But Not Nociceptive Pain”. Biorxiv. Cold Spring Harbor Laboratory, Pp. 2023-09. .
Publisher's Version תקציר Rohit Srivastava, Horwitz, Margalit , Hershko-Moshe, Anat , Bronstein, Shirly , Ben-Dov, Iddo Z, ו Melloul, Danielle . 2023.
“Posttranscriptional Regulation Of The Prostaglandin E Receptor Spliced-Isoform Ep3-Γ And Its Implication In Pancreatic Β-Cell Failure”. Faseb J., 37, Pp. e22958.
In Type 2 diabetes (T2D), elevated lipid levels have been suggested to contribute to insulin resistance and β-cell dysfunction. We previously reported that the expression of the PGE2 receptor EP3 is elevated in islets of T2D individuals and is preferentially stimulated by palmitate, leading to β-cell failure. The mouse EP3 receptor generates three isoforms by alternative splicing which differ in their C-terminal domain and are referred to as mEP3α, mEP3β, and mEP3γ. We bring evidence that the expression of the mEP3γ isoform is elevated in islets of diabetic db/db mice and is selectively upregulated by palmitate. Specific knockdown of the mEP3γ isoform restores the expression of β-cell-specific genes and rescues MIN6 cells from palmitate-induced dysfunction and apoptosis. This study indicates that palmitate stimulates the expression of the mEP3γ by a posttranscriptional mechanism, compared to the other spliced isoforms, and that the de novo synthesized ceramide plays an important role in FFA-induced mEP3γ expression in β-cells. Moreover, induced levels of mEP3γ mRNA by palmitate or ceramide depend on p38 MAPK activation. Our findings suggest that mEP3γ gene expression is regulated at the posttranscriptional level and defines the EP3 signaling axis as an important pathway mediating β-cell-impaired function and demise.
Rohit Srivastava, Horwitz, Margalit , Hershko-Moshe, Anat , Bronstein, Shirly , Ben-Dov, Iddo Z, ו Melloul, Danielle . 2023.
“Posttranscriptional Regulation Of The Prostaglandin E Receptor Spliced-Isoform Ep3-Γ And Its Implication In Pancreatic Β-Cell Failure”. Faseb J, 37, 6, Pp. e22958. doi:10.1096/fj.202201984R.
In Type 2 diabetes (T2D), elevated lipid levels have been suggested to contribute to insulin resistance and β-cell dysfunction. We previously reported that the expression of the PGE2 receptor EP3 is elevated in islets of T2D individuals and is preferentially stimulated by palmitate, leading to β-cell failure. The mouse EP3 receptor generates three isoforms by alternative splicing which differ in their C-terminal domain and are referred to as mEP3α, mEP3β, and mEP3γ. We bring evidence that the expression of the mEP3γ isoform is elevated in islets of diabetic db/db mice and is selectively upregulated by palmitate. Specific knockdown of the mEP3γ isoform restores the expression of β-cell-specific genes and rescues MIN6 cells from palmitate-induced dysfunction and apoptosis. This study indicates that palmitate stimulates the expression of the mEP3γ by a posttranscriptional mechanism, compared to the other spliced isoforms, and that the de novo synthesized ceramide plays an important role in FFA-induced mEP3γ expression in β-cells. Moreover, induced levels of mEP3γ mRNA by palmitate or ceramide depend on p38 MAPK activation. Our findings suggest that mEP3γ gene expression is regulated at the posttranscriptional level and defines the EP3 signaling axis as an important pathway mediating β-cell-impaired function and demise.
Children living in households where severe intimate partner violence (IPV) exists sometimes move with their mothers to shelters for battered women. Although there is an increased interest in research exploring children's exposure to IPV, little is known about children's subjective experiences during their stay in shelters. The present study examines children's views of their disconnection from their social and familial networks during their stay in a shelter. Using qualitative methods, 32 children, ages 7–12 years, who resided in a shelter were interviewed. Thematic analysis was implemented to develop codes and themes. The following five themes emerged from the data analysis: (a) absence of grandparents, (b) worry about older siblings, (c) disconnection from the neighbourhood, (d) missing their house and (e) disconnection from previous school and classmates. Findings suggest that children's disconnection from previous formal and informal networks significantly affected their well-being. The findings are discussed and interpreted in light of selected key concepts of Bronfenbrenner's bioecological model. The limitations of this study are discussed, along with implications for future research, as well as highlights for future intervention.
BACKGROUND: The study of gene essentiality, which measures the importance of a gene for cell division and survival, is used for the identification of cancer drug targets and understanding of tissue-specific manifestation of genetic conditions. In this work, we analyze essentiality and gene expression data from over 900 cancer lines from the DepMap project to create predictive models of gene essentiality. METHODS: We developed machine learning algorithms to identify those genes whose essentiality levels are explained by the expression of a small set of "modifier genes". To identify these gene sets, we developed an ensemble of statistical tests capturing linear and non-linear dependencies. We trained several regression models predicting the essentiality of each target gene, and used an automated model selection procedure to identify the optimal model and hyperparameters. Overall, we examined linear models, gradient boosted trees, Gaussian process regression models, and deep learning networks. RESULTS: We identified nearly 3000 genes for which we accurately predict essentiality using gene expression data of a small set of modifier genes. We show that both in the number of genes we successfully make predictions for, as well as in the prediction accuracy, our model outperforms current state-of-the-art works. CONCLUSIONS: Our modeling framework avoids overfitting by identifying the small set of modifier genes, which are of clinical and genetic importance, and ignores the expression of noisy and irrelevant genes. Doing so improves the accuracy of essentiality prediction in various conditions and provides interpretable models. Overall, we present an accurate computational approach, as well as interpretable modeling of essentiality in a wide range of cellular conditions, thus contributing to a better understanding of the molecular mechanisms that govern tissue-specific effects of genetic disease and cancer.
Effective proteome homeostasis is key to cellular and organismal survival, and cells therefore contain efficient quality control systems to monitor and remove potentially toxic misfolded proteins. Such general protein quality control to a large extent relies on the efficient and robust delivery of misfolded or unfolded proteins to the ubiquitin-proteasome system. This is achieved via recognition of so-called degradation motifs—degrons—that are assumed to become exposed as a result of protein misfolding. Despite their importance, the nature and sequence properties of quality-control degrons remain elusive. Here, we have used data from a yeast-based screen of 23,600 17-residue peptides to build a predictor of quality-control degrons. The resulting model, QCDPred (Quality Control Degron Prediction), achieves good accuracy using only the sequence composition of the peptides as input. Our analysis reveals that strong degrons are enriched in hydrophobic amino acids and depleted in negatively charged amino acids, in line with the expectation that they are buried in natively folded proteins. We applied QCDPred to the entire yeast proteome, enabling us to analyse more widely the potential effects of degrons. As an example, we show a correlation between cellular abundance and degron potential in disordered regions of proteins. Together with recent results on membrane proteins, our work suggest that the recognition of exposed hydrophobic residues is a key and generic mechanism for proteome homeostasis.
Carmel Hutchings ו Sela-Donenfeld, Dalit . 2023.
“Primer On Fgf3”. Differentiation. doi:10.1016/j.diff.2023.09.003.
תקציר Though initially discovered as a proto-oncogene in virally induced mouse mammary tumors, FGF3 is primarily active in prenatal stages, where it is found at various sites at specific times. FGF3 is crucial during development, as its roles include tail formation, inner ear development and hindbrain induction and patterning. FGF3 expression and function are highly conserved in vertebrates, while it also interacts with other FGFs in various developmental processes. Intriguingly, while it is classified as a classical paracrine signaling factor, murine FGF3 was uniquely found to also act in an intracrine manner, depending on alternative translation initiation sites. Corresponding with its conserved role in inner ear morphogenesis, mutations in FGF3 in humans are associated with LAMM syndrome, a disorder that include hearing loss and inner ear malformations. While recent studies indicate of some FGF3 presence in post-natal stages, emerging evidences of its upregulation in various human tumors and cariogenic processes in mouse models, highlights the importance of its close regulation in adult tissues. Altogether, the broad and dynamic expression pattern and regulation of FGF3 in embryonic and adult tissues together with its link to congenital malformations and cancer, calls for further discoveries of its diverse roles in health and disease.
We examined the effect of explicit norm nudge requests for compliance in a field study on workplace dishonesty and three controlled experiments on reciprocity. The requests were presented either with affirmation (e.g., “please pay” and “please remember to pay”) or negation (e.g., “please, do not forget to pay”) and solicited by either one person or three people who were also the beneficiaries of compliance. We also explored how these requests affected first time and repeated behaviors. We found no effect of the number of people soliciting the requests. However, we did find that for first-time behaviors, any request increased compliance compared with no request, and those worded with affirmation were more effective than those worded with negation. We replicated this pattern in repeated behaviors—both at the group and at the individual level—but only when the initial compliance, before the request, was low. Importantly, no increase emerged when individuals did not receive requests, showing that requests only, and not regression to the mean, explained the effect.
We propose and initiate the study of privacy elasticity—the responsiveness of economic variables to small changes in the level of privacy given to participants in an economic system. Individuals rarely experience either full privacy or a complete lack of privacy; we propose to use differential privacy—a computer-science theory increasingly adopted by industry and government—as a standardized means of quantifying continuous privacy changes. The resulting privacy measure implies a privacy-elasticity notion that is portable and comparable across contexts. We demonstrate the feasibility of this approach by estimating the privacy elasticity of public-good contributions in a lab experiment.
