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To explore the connection between chloroplast and coffee resistance factors, designated as S H 1 to S H 9, whole genomic DNA of 42 coffee genotypes was sequenced, and entire chloroplast genomes were de novo assembled. The chloroplast phylogenetic haplotype network clustered individuals per species instead of S H factors. However, for the first time, it allowed the molecular validation of Coffea arabica as the maternal parent of the spontaneous hybrid "Híbrido de Timor". Individual reads were also aligned on the C. arabica reference genome to relate S H factors with chloroplast metabolism, and an in-silico analysis of selected nuclear-encoded chloroplast proteins (132 proteins) was performed. The nuclear-encoded thioredoxin-like membrane protein HCF164 enabled the discrimination of individuals with and without the S H 9 factor, due to specific DNA variants linked to chromosome 7c (from C. canephora-derived sub-genome). The absence of both the thioredoxin domain and redox-active disulphide center in the HCF164 protein, observed in S H 9 individuals, raises the possibility of potential implications on redox regulation. For the first time, the identification of specific DNA variants of chloroplast proteins allows discriminating individuals according to the S H profile. This study introduces an unexplored strategy for identifying protein/genes associated with S H factors and candidate targets of H. vastatrix effectors, thereby creating new perspectives for coffee breeding programs., (© 2023. Springer Nature Limited.)

Effective human-robot collaboration requires the appropriate allocation of indivisible tasks between humans and robots. A task allocation method that appropriately makes use of the unique capabilities of each agent (either a human or a robot) can improve team performance. This paper presents a novel task allocation method for heterogeneous human-robot teams based on artificial trust from a robot that can learn agent capabilities over time and allocate both existing and novel tasks. Tasks are allocated to the agent that maximizes the expected total reward. The expected total reward incorporates trust in the agent to successfully execute the task as well as the task reward and cost associated with using that agent for that task. Trust in an agent is computed from an artificial trust model, where trust is assessed along a capability dimension by comparing the belief in agent capabilities with the task requirements. An agent's capabilities are represented by a belief distribution and learned using stochastic task outcomes. Our task allocation method was simulated for a human-robot dyad. The team total reward of our artificial trust-based task allocation method outperforms other methods both when the human's capabilities are initially unknown and when the human's capabilities belief distribution has converged to the human's actual capabilities. Our task allocation method enables human-robot teams to maximize their joint performance., (© 2022. The Author(s).)

A growing body of evidence suggests a key role of tumor microenvironment, especially for bone marrow mesenchymal stem cells (MSC), in the maintenance and progression of multiple myeloma (MM), through direct and indirect interactions with tumor plasma cells. Thus, this study aimed to investigate the gene expression and functional alterations of MSC from MM patients (MM-MSC) in comparison with their normal counterparts from normal donors (ND-MSC). Gene expression analysis (Affymetrix) was performed in MM-MSC and ND-MSC after in vitro expansion. To validate these findings, some genes were selected to be evaluated by quantitative real time PCR (RT-qPCR), and also functional in vitro analyses were performed. We demonstrated that MM-MSC have a distinct gene expression profile than ND-MSC, with 485 differentially expressed genes (DEG) - 280 upregulated and 205 downregulated. Bioinformatics analyses revealed that the main enriched functions among downregulated DEG were related to cell cycle progression, immune response activation and bone metabolism. Four genes were validated by qPCR - ZNF521 and SEMA3A, which are involved in bone metabolism, and HLA-DRA and CHIRL1, which are implicated in the activation of immune response. Taken together, our results suggest that MM-MSC have constitutive abnormalities that remain present even in the absence of tumors cells. The alterations found in cell cycle progression, immune system activation, and osteoblastogenesis suggest, respectively, that MM-MSC are permanently dependent of tumor cells, might contribute to immune evasion and play an essential role in bone lesions frequently found in MM patients.

The human genome encodes two active Vaccinia-related protein kinases (VRK), VRK1 and VRK2. These proteins have been implicated in a number of cellular processes and linked to a variety of tumors. However, understanding the cellular role of VRKs and establishing their potential use as targets for therapeutic intervention has been limited by the lack of tool compounds that can specifically modulate the activity of these kinases in cells. Here we identified BI-D1870, a dihydropteridine inhibitor of RSK kinases, as a promising starting point for the development of chemical probes targeting the active VRKs. We solved co-crystal structures of both VRK1 and VRK2 bound to BI-D1870 and of VRK1 bound to two broad-spectrum inhibitors. These structures revealed that both VRKs can adopt a P-loop folded conformation, which is stabilized by different mechanisms on each protein. Based on these structures, we suggest modifications to the dihydropteridine scaffold that can be explored to produce potent and specific inhibitors towards VRK1 and VRK2.

Basic leucine zipper (bZIP) transcription factors control important developmental and physiological processes in plants. In Arabidopsis thaliana, the three gene F-bZIP subfamily has been associated with zinc deficiency and salt stress response. Benefiting from the present abundance of plant genomic data, we performed an evolutionary and structural characterization of plant F-bZIPs. We observed divergence during seed plant evolution, into two groups and inferred different selective pressures for each. Group 1 contains AtbZIP19 and AtbZIP23 and appears more conserved, whereas Group 2, containing AtbZIP24, is more prone to gene loss and expansion events. Transcriptomic and experimental data reinforced AtbZIP19/23 as pivotal regulators of the zinc deficiency response, mostly via the activation of genes from the ZIP metal transporter family, and revealed that they are the main regulatory switch of AtZIP4. A survey of AtZIP4 orthologs promoters across different plant taxa revealed an enrichment of the Zinc Deficiency Response Element (ZDRE) to which both AtbZIP19/23 bind. Overall, our results indicate that while the AtbZIP24 function in the regulation of the salt stress response may be the result of neo-functionalization, the AtbZIP19/23 function in the regulation of the zinc deficiency response may be conserved in land plants (Embryophytes).

The mechanisms triggering renal inflammation in chronic kidney disease (CKD) are unclear. We performed a detailed analysis of the time course of innate and adaptive immunity activation in the 5/6 renal ablation (Nx) model. Munich-Wistar rats undergoing Nx were studied 15, 60 and 120 days after ablation. Hypertension, albuminuria, creatinine retention, interstitial expansion and infiltration by macrophages and T-lymphocytes were already evident 15 days after Nx. PCR-array was used to screen for altered gene expression, whereas gene and protein expressions of TLR4, CASP1, IL-1β and NLRP3 were individually assessed. Tlr4, Tlr5, Lbp, Nlrp3, Casp1, Irf7 and Il1b were already upregulated 15 days after Nx, while activation of Tlr2, Tlr7, Tlr9, Nod2, Tnf and Il6 was seen after 60 days post-ablation. The number of genes related to innate or adaptive immunity grew steadily with time. These observations indicate that parallel activation of innate and adaptive immunity antecedes glomerular injury and involves a growing number of intricate signaling pathways, helping to explain the difficulty in detaining renal injury in Nx as CKD advances, and, stressing the need for early treatment. Additionally, these findings may contribute to the search of therapeutic targets specific for advanced phases of CKD.

Biological networks display high robustness against random failures but are vulnerable to targeted attacks on central nodes. Thus, network topology analysis represents a powerful tool for investigating network susceptibility against targeted node removal. Here, we built protein interaction networks associated with chemoresistance to temozolomide, an alkylating agent used in glioma therapy, and analyzed their modular structure and robustness against intentional attack. These networks showed functional modules related to DNA repair, immunity, apoptosis, cell stress, proliferation and migration. Subsequently, network vulnerability was assessed by means of centrality-based attacks based on the removal of node fractions in descending orders of degree, betweenness, or the product of degree and betweenness. This analysis revealed that removing nodes with high degree and high betweenness was more effective in altering networks' robustness parameters, suggesting that their corresponding proteins may be particularly relevant to target temozolomide resistance. In silico data was used for validation and confirmed that central nodes are more relevant for altering proliferation rates in temozolomide-resistant glioma cell lines and for predicting survival in glioma patients. Altogether, these results demonstrate how the analysis of network vulnerability to topological attack facilitates target prioritization for overcoming cancer chemoresistance.