Human-AI Co-Creation Approach to Find Forever Chemicals Replacements

Generative models are a powerful tool in AI for material discovery. We are designing a software framework that supports a human-AI co-creation process to accelerate finding replacements for the ``forever chemicals''-- chemicals that enable our modern lives, but are harmful to the environment and the human health. Our approach combines AI capabilities with the domain-specific tacit knowledge of subject matter experts to accelerate the material discovery. Our co-creation process starts with the interaction between the subject matter experts and a generative model that can generate new molecule designs. In this position paper, we discuss our hypothesis that these subject matter experts can benefit from a more iterative interaction with the generative model, asking for smaller samples and ``guiding'' the exploration of the discovery space with their knowledge.Comment: 5 pages, Generative AI and HCI (GenAICHI) Workshop at CHI 23 (ACM CHI Conference on Human Factors in Computing Systems

On the general one-dimensional XY Model: positive and zero temperature, selection and non-selection

We consider $(M,d)$ a connected and compact manifold and we denote by $\mathcal{B}_i$ the Bernoulli space $M^{\Z}$ of sequences represented by $$x=(... x_{-3},x_{-2},x_{-1},x_0,x_1,x_2,x_3,...),$$ where $x_i$ belongs to the space (alphabet) $M$. The case where $M=\mathbb{S}^1$, the unit circle, is of particular interest here. The analogous problem in the one-dimensional lattice $\mathbb{N}$ is also considered. %In this case we consider the potential $A: {\cal B}=M^\mathbb{N} \to \mathbb{R}.$ Let A: \mathcal{B}_i \rar \R be an {\it observable} or {\it potential} defined in the Bernoulli space $\mathcal{B}_i$. The potential $A$ describes an interaction between sites in the one-dimensional lattice $M^\mathbb{Z}$. Given a temperature $T$, we analyze the main properties of the Gibbs state $\hat{\mu}_{\frac{1}{T} A}$ which is a certain probability measure over ${\cal B}_i$. We denote this setting "the general XY model". In order to do our analysis we consider the Ruelle operator associated to $\frac{1}{T} A$, and, we get in this procedure the main eigenfunction $\psi_{\frac{1}{T} A}$. Later, we analyze selection problems when temperature goes to zero: a) existence, or not, of the limit (on the uniform convergence) $$V:=\lim_{T\to 0} T\, \log(\psi_{\frac{1}{T} A}),\,\,\,\,\text{a question about selection of subaction},$$ and, b) existence, or not, of the limit (on the weak$^*$ sense) $$\tilde{\mu}:=\lim_{T\to 0} \hat{\mu}_{\frac{1}{T}\, A},\,\,\,\,\text{a question about selection of measure}.$$ The existence of subactions and other properties of Ergodic Optimization are also considered

Duffy Negative Antigen Is No Longer a Barrier to Plasmodium vivax – Molecular Evidences from the African West Coast (Angola and Equatorial Guinea)

Recent reports of Plasmodium vivax infections, the most widely distributed species of human malaria, show that this parasite is evolving and adapting, becoming not only more aggressive but also more frequent in countries where it was not present in the past, becoming, therefore, a major source of concern. Thus, it is extremely important to perform new studies of its distribution in West and Central Africa, where there are few reports of its presence, due to the high prevalence of Duffy-negative individuals. The aim of this study was to investigate the presence of P. vivax in Angola and in Equatorial Guinea, using blood samples and mosquitoes. The results showed that P. vivax seems to be able to invade erythrocytes using receptors other than Duffy, and this new capacity is not exclusive to one strain of P. vivax, since we have found samples infected with two different strains: VK247 and classic. Additionally we demonstrated that the parasite has a greater distribution than previously thought, calling for a reevaluation of its worldwide distribution

Biocomposite films based on κ-carrageenan/locust bean gum blends and clays : physical and antimicrobial properties

The aims of this work were to evaluate the physical and antimicrobial properties of biodegradable films composed of mixtures of κ-carrageenan (κ-car) and locust bean gum (LBG) when organically modified clay Cloisite 30B (C30B) was dispersed in the biopolymer matrix. Film-forming solutions were prepared by adding C30B (ranging from 0 to 16 wt.%) into the κ-car/LBG solution (40/60 wt.%) with 0.3 % (w/v) of glycerol. Barrier properties (water vapour permeability, P vapour; CO2 and O2 permeabilities), mechanical properties (tensile strength, TS, and elongation-at-break, EB) and thermal stability of the resulting films were determined and related with the incorporation of C30B. Also, X-ray diffraction (XRD) was done in order to investigate the effect of C30B in film structure. Antimicrobial effects of these films against Listeria monocytogenes, Escherichia coli and Salmonella enterica were also evaluated. The increase of clay concentration causes a decrease of P vapour (from 5.34 × 10−11 to 3.19 × 10−11 g (m s Pa)−1) and an increase of the CO2 permeability (from 2.26 × 10−14 to 2.91 × 10−14 g (m s Pa)−1) and did not changed significantly the O2 permeability for films with 0 and 16 wt.% C30B, respectively. Films with 16 wt.% clay exhibited the highest values of TS (33.82 MPa) and EB (29.82 %). XRD patterns of the films indicated that a degree of exfoliation is attained depending on clay concentration. κ-car/LBG–C30B films exhibited an inhibitory effect only against L. monocytogenes. κ-car/LBG–C30B composite films are a promising alternative to synthetic films in order to improve the shelf life and safety of food products.J. T. Martins, A. I. Bourbon, A. C. Pinheiro and M. A. Cerqueira gratefully acknowledge the Fundacao para a Ciencia e Tecnologia (FCT, Portugal) for their fellowships (SFRH/BD/32566/2006, SFRH/BD/73178/2010, SFRH/BD/48120/2008 and SFRH/BPD/72753/2010, respectively), and B. W. S. Souza acknowledges the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES, Brazil)

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives