Saccharomyces cerevisiae multifunctional protein RAP1 binds to a conserved sequence in the Polyoma virus enhancer and is responsible for its transcriptional activity in yeast cells

AbstractThe Polyoma virus enhancer (A + B domain) activates transcription in Saccharomyces cerevisiae when joined to appropriate yeast promoter elements. We demonstrate by DNase I footprints and inhibition of binding by specific antibody, that the yeast protein RAP1 binds to the B-domain of the Polyoma enhancer and, at least in some promoter contexts, is responsible for transcriptional activity of the enhancer B-domain in yeast. Close matches to a consensus RAP1-binding site are also present in other viral enhancers

Understanding novel metaphors. A milestone in the developmental trajectory of children with agenesis of the corpus callosum?

This study explores novel metaphor comprehension in a 7.2-year-old child (conventionally called RJ) with complete and isolated agenesis of the corpus callosum (ACC). RJ’s cognitive level was adequate for his age as well as most of his linguistic competencies. The child’s performance was compared to typically developing (TD) controls on a test assessing novel metaphor comprehension for preschoolers. RJ’s performance showed a delay of about three years in relation to the expected level for his age, and also a significant gap compared to the TDs. The results highlighted the possibility to detect weaknesses in understanding novel metaphors in children with ACC, in spite of their apparently adequate linguistic capabilities. An early detection of a weakness in this area can pave the way to neurolinguistic treatment in order to enhance the understanding of nonliteral meaning, which, in the developmental trajectory, will be increasingly involved in everyday life communication. Future research should explore more in-depth a capability that intrinsically requires high interconnectivity, such as novel metaphor comprehension, in a brain in development where the major tract connecting the two hemispheres is missing

Revealing the coral habitat effect on benthopelagic fauna diversity in the Santa Maria di Leuca cold-water coral province using different devices and Bayesian hierarchical modelling

Data from two experimental longline surveys and two video inspections carried out in Santa Maria di Leuca cold-water coral province (Mediterranean Sea) during spring-autumn 2010 were used in order to compare the benthopelagic abundance and diversity between coral and non-coral habitats and between different devices. The sampling was carried out in two types of habitat: a coral habitat with carbonate mounds and a non-coral habitat characterized by intermound sea floor. A Bayesian hierarchical modelling approach to accommodate factors influencing community assemblages was used considering the number of species, the Shannon-Wiener diversity index and the two most abundant species represented by the European conger (Conger conger) and blackbelly rosefish (Helicolenus dactylopterus). A relevant effect of the habitat factor was observed for both the number of species and the diversity index, showing a higher species number and diversity index in the coral habitat than in the non-coral habitat. Concerning the relevance of fixed effects from the model on the probability of observing non-zero (positive) abundances, the devices considered, longline and baited lander, did not show different influence for either C. conger or H. dactylopterus. In the case of positive abundance, a relevant device effect was only observed for H. dactylopterus, showing higher abundances for longline than for baited lander. A habitat effect was detected, with positive abundances for both species in the coral habitat. This study proves that structurally complex habitats generated by cold-water corals influence the distribution and diversity of the benthopelagic fauna, and that the use of different devices can provide complementary useful results. Increased knowledge about the role of cold-water corals in the associated benthopelagic fauna could lead to better conservation of one of the most important hot spots of biodiversity in the Mediterranean Sea

Association between Mediterranean lifestyle and perception of well-being and distress in a sample population of university Italian students

We investigated the extent to which adherence to the Mediterranean diet (MD) in combination with Mediterranean lifestyle factors influenced students’ perceptions of subjective well-being (SWB) and distress. 939 undergraduates completed a survey to assess sociodemographic and lifestyle characteristics, including adherence to the MD, depression, anxiety, stress, and SWB. Data were analysed with correlation, logistic, and multiple linear regression models. Higher adherence to MD correlated with better SWB. Fruit, red meat, sweet and caffeinated beverages contributed significantly. However, it was the combination of adherence to MD with other factors, including quality of social relationships, income, smoking, sleep, and physical activity that better predicted SWB. Our results confirm the positive influence of MD on SWB. However, they also suggest the need to consider perceptions of well-being by a more holistic approach that considers physical and social factors simultaneously to improve the development of more effective educational and motivational programmes.info:eu-repo/semantics/publishedVersio

A Regulatory Mechanism Involving TBP-1/Tat-Binding Protein 1 and Akt/PKB in the Control of Cell Proliferation

TBP-1 /Tat-Binding Protein 1 (also named Rpt-5, S6a or PSMC3) is a multifunctional protein, originally identified as a regulator of HIV-1-Tat mediated transcription. It is an AAA-ATPase component of the 19S regulative subunit of the proteasome and, as other members of this protein family, fulfils different cellular functions including proteolysis and transcriptional regulation. We and others reported that over expression of TBP-1 diminishes cell proliferation in different cellular contexts with mechanisms yet to be defined. Accordingly, we demonstrated that TBP-1 binds to and stabilizes the p14ARF oncosuppressor increasing its anti-oncogenic functions. However, TBP-1 restrains cell proliferation also in the absence of ARF, raising the question of what are the molecular pathways involved. Herein we demonstrate that stable knock-down of TBP-1 in human immortalized fibroblasts increases cell proliferation, migration and resistance to apoptosis induced by serum deprivation. We observe that TBP-1 silencing causes activation of the Akt/PKB kinase and that in turn TBP-1, itself, is a downstream target of Akt/PKB. Moreover, MDM2, a known Akt target, plays a major role in this regulation. Altogether, our data suggest the existence of a negative feedback loop involving Akt/PKB that might act as a sensor to modulate TBP-1 levels in proliferating cells

HER2 expression as a potential marker for response to therapy targeted to the EGFR

Since human epidermal growth factor receptor 2 (HER2) is known to participate with the epidermal growth factor receptor (EGFR) in mitogenic signalling, we hypothesised that HER2 overexpression might indicate responsiveness to EGFR targeted therapies. MCF7 breast cancer cells transfected with the HER2 gene were subcloned to establish a set of genetically related cell lines expressing graded levels of HER2 by immunoblot analysis. The subcloned cell lines and parental MCF7 cells were characterised by their growth characteristics, and cell by cell patterns of EGFR, HER2 and HER3 expression as well as levels of phosphorylated mitogen-activated protein kinase (MAPK) and AKT by laser scanning cytometry (LSC). Growth inhibition assays were used to characterise response to EGFR targeted therapy, and to determine the relationship between therapeutic response and levels of tyrosine kinase expression. The levels of growth inhibition of AG1478 and of the AG1478-trastuzumab combinations were correlated with levels of HER2 expression among the different cell lines. Among EGFR, HER2 and HER3, HER2 overexpression was the best single predictive marker, but combinations of two markers provided additional predictive information

SELFIES and the future of molecular string representations

Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include the prediction of properties, the discovery of new reaction pathways, or the design of new molecules. The machine needs to read and write fluently in a chemical language for each of these tasks. Strings are a common tool to represent molecular graphs, and the most popular molecular string representation, SMILES, has powered cheminformatics since the late 1980s. However, in the context of AI and ML in chemistry, SMILES has several shortcomings -- most pertinently, most combinations of symbols lead to invalid results with no valid chemical interpretation. To overcome this issue, a new language for molecules was introduced in 2020 that guarantees 100\% robustness: SELFIES (SELF-referencIng Embedded Strings). SELFIES has since simplified and enabled numerous new applications in chemistry. In this manuscript, we look to the future and discuss molecular string representations, along with their respective opportunities and challenges. We propose 16 concrete Future Projects for robust molecular representations. These involve the extension toward new chemical domains, exciting questions at the interface of AI and robust languages and interpretability for both humans and machines. We hope that these proposals will inspire several follow-up works exploiting the full potential of molecular string representations for the future of AI in chemistry and materials science.Comment: 34 pages, 15 figures, comments and suggestions for additional references are welcome

SELFIES and the future of molecular string representations

Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include the prediction of properties, the discovery of new reaction pathways, or the design of new molecules. The machine needs to read and write fluently in a chemical language for each of these tasks. Strings are a common tool to represent molecular graphs, and the most popular molecular string representation, SMILES, has powered cheminformatics since the late 1980s. However, in the context of AI and ML in chemistry, SMILES has several shortcomings -- most pertinently, most combinations of symbols lead to invalid results with no valid chemical interpretation. To overcome this issue, a new language for molecules was introduced in 2020 that guarantees 100\% robustness: SELFIES (SELF-referencIng Embedded Strings). SELFIES has since simplified and enabled numerous new applications in chemistry. In this manuscript, we look to the future and discuss molecular string representations, along with their respective opportunities and challenges. We propose 16 concrete Future Projects for robust molecular representations. These involve the extension toward new chemical domains, exciting questions at the interface of AI and robust languages and interpretability for both humans and machines. We hope that these proposals will inspire several follow-up works exploiting the full potential of molecular string representations for the future of AI in chemistry and materials science