Phosphoproteomic Landscape of AML Cells Treated with the ATP-Competitive CK2 Inhibitor CX-4945

Casein kinase 2 (CK2) regulates a plethora of proteins with pivotal roles in solid and hematological neoplasia. Particularly, in acute myeloid leukemia (AML) CK2 has been pointed as an attractive therapeutic target and prognostic marker. Here, we explored the impact of CK2 inhibition over the phosphoproteome of two cell lines representing major AML subtypes. Quantitative phosphoproteomic analysis was conducted to evaluate changes in phosphorylation levels after incubation with the ATP-competitive CK2 inhibitor CX-4945. Functional enrichment, network analysis, and database mining were performed to identify biological processes, signaling pathways, and CK2 substrates that are responsive to CX-4945. A total of 273 and 1310 phosphopeptides were found differentially modulated in HL-60 and OCI-AML3 cells, respectively. Despite regulated phosphopeptides belong to proteins involved in multiple biological processes and signaling pathways, most of these perturbations can be explain by direct CK2 inhibition rather than off-target effects. Furthermore, CK2 substrates regulated by CX-4945 are mainly related to mRNA processing, translation, DNA repair, and cell cycle. Overall, we evidenced that CK2 inhibitor CX-4945 impinge on mediators of signaling pathways and biological processes essential for primary AML cells survival and chemosensitivity, reinforcing the rationale behind the pharmacologic blockade of protein kinase CK2 for AML targeted therapy

Metal dealing at the origin of the Chordata phylum: The metallothionein system and metal overload response in Amphioxus.

Non-vertebrate chordates, specifically amphioxus, are considered of the utmost interest for gaining insight into the evolutionary trends, i.e. differentiation and specialization, of gene/protein systems. In this work, MTs (metallothioneins), the most important metal binding proteins, are characterized for the first time in the cephalochordate subphylum at both gene and protein level, together with the main features defining the amphioxus response to cadmium and copper overload. Two MT genes (BfMT1 and BfMT2) have been identified in a contiguous region of the genome, as well as several ARE (antioxidant response element) and MRE (metal response element) located upstream the transcribed region. Their corresponding cDNAs exhibit identical sequence in the two lancelet species (B. floridae and B. lanceolatum), BfMT2 cDNA resulting from an alternative splicing event. BfMT1 is a polyvalent metal binding peptide that coordinates any of the studied metal ions (Zn, Cd or Cu) rendering complexes stable enough to last in physiological environments, which is fully concordant with the constitutive expression of its gene, and therefore, with a metal homeostasis housekeeping role. On the contrary, BfMT2 exhibits a clear ability to coordinate Cd(II) ions, while it is absolutely unable to fold into stable Cu (I) complexes, even as mixed species. This identifies it as an essential detoxification agent, which is consequently only induced in emergency situations. The cephalochordate MTs are not directly related to vertebrate MTs, neither by gene structure, protein similarity nor metal-binding behavior of the encoded peptides. The closest relative is the echinoderm MT, which confirm proposed phylogenetic relationships between these two groups. The current findings support the existence in most organisms of two types of MTs as for their metal binding preferences, devoted to different biological functions: multivalent MTs for housekeeping roles, and specialized MTs that evolve either as Cd-thioneins or Cu-thioneins, according to the ecophysiological needs of each kind of organisms

Performance analysis of ML-based MTC traffic pattern predictors

Abstract Prolonging the lifetime of massive machine-type communication (MTC) networks is key to realizing a sustainable digitized society. Great energy savings can be achieved by accurately predicting MTC traffic followed by properly designed resource allocation mechanisms. However, selecting the proper MTC traffic predictor is not straightforward and depends on accuracy/complexity trade-offs and the specific MTC applications and network characteristics. Remarkably, the related state-of-the-art literature still lacks such debates. Herein, we assess the performance of several machine learning (ML) methods to predict Poisson and quasi-periodic MTC traffic in terms of accuracy and computational cost. Results show that the temporal convolutional network (TCN) outperforms the long-short term memory (LSTM), the gated recurrent units (GRU), and the recurrent neural network (RNN), in that order. For Poisson traffic, the accuracy gap between the predictors is larger than under quasi-periodic traffic. Finally, we show that running a TCN predictor is around three times more costly than other methods, while the training/inference time is the greatest/least

Energy-efficient wake-up signalling for machine-type devices based on traffic-aware long-short term memory prediction

Abstract Reducing energy consumption is a pressing issue in low-power machine-type communication (MTC) networks. In this regard, the Wake-up Signal (WuS) technology, which aims to minimize the energy consumed by the radio interface of the machine-type devices (MTDs), stands as a promising solution. However, state-of-the-art WuS mechanisms use static operational parameters, so they cannot efficiently adapt to the system dynamics. To overcome this, we design a simple but efficient neural network to predict MTC traffic patterns and configure WuS accordingly. Our proposed forecasting WuS (FWuS) leverages an accurate long-short term memory (LSTM)-based traffic prediction that allows extending the sleep time of MTDs by avoiding frequent page monitoring occasions in idle state. Simulation results show the effectiveness of our approach. The traffic prediction errors are shown to be below 4%, being false alarm and miss-detection probabilities respectively below 8.8% and 1.3%. In terms of energy consumption reduction, FWuS can outperform the best benchmark mechanism in up to 32%. Finally, we certify the ability of FWuS to dynamically adapt to traffic density changes, promoting low-power MTC scalability

Possibilidades terapêuticas e risco toxicológico de Jatropha gossypiifolia L.: uma revisão narrativa Therapeutic possibilities and toxicological risk of Jatropha gossypiifolia L.: a narrative review

A espécie Jatropha gossypiifolia L. (Euphorbiaceae), popularmente conhecida como pião-roxo, entre tantos outros nomes, é um bom exemplo do tênue limiar que separa o efeito terapêutico do tóxico. Apesar de ser classicamente conhecida como planta tóxica possui usos na medicina popular. Alguns desses efeitos têm sido comprovados em estudos experimentais, como os de antimicrobiano, antineoplásico, cicatrizante e hipotensor, sendo possivelmente explicados pela presença de substâncias como alcalóides, terpenóides, flavonóides, lignanas e taninos. Esta revisão aborda aspectos importantes, com ênfase na toxicidade crônica dessa espécie, de modo a servir de fonte de informação aos interessados em avaliar a relação risco/benefício do uso terapêutico de Jatropha gossypiifolia L.<br>The species Jatropha gossypiifolia L. (Euphorbiaceae), popularly known as bellyache bush, among several other names, is an important example of the tenuous threshold that separates the therapeutic from the toxic effect. Although traditionally known as a toxic plant, it has been used in folk medicine. Some of its effects have been proved by experimental studies as antimicrobial, antineoplastic, healing and hypotensive, likely explained by the presence of substances such as alkaloids, terpenoids, flavonoids, lignans and tannins. This review deals with important aspects, focusing on the chronic toxicity of this species, in order to serve as an information source for those interested in evaluating the risk-benefit ratio of the therapeutic use of Jatropha gossypiifolia L