Deficiency of Parkinson's disease-related gene Fbxo7 is associated with impaired mitochondrial metabolism by PARP activation

The Parkinson's disease (PD)-related protein F-box only protein 7 (Fbxo7) is the substrate-recognition component of the Skp1-Cullin-F-box protein E3 ubiquitin ligase complex. We have recently shown that PD-associated mutations in Fbxo7 disrupt mitochondrial autophagy (mitophagy), suggesting a role for Fbxo7 in modulating mitochondrial homeostasis. Here we report that Fbxo7 deficiency is associated with reduced cellular NAD(+) levels, which results in increased mitochondrial NADH redox index and impaired activity of complex I in the electron transport chain. Under these conditions of compromised respiration, mitochondrial membrane potential and ATP contents are reduced, and cytosolic reactive oxygen species (ROS) production is increased. ROS activates poly (ADP-ribose) polymerase (PARP) activity in Fbxo7-deficient cells. PARP inhibitor restores cellular NAD(+) content and redox index and ATP pool, suggesting that PARP overactivation is cause of decreased complex I-driven respiration. These findings bring new insight into the mechanism of Fbxo7 deficiency, emphasising the importance of mitochondrial dysfunction in PD

Identifying the Machine Learning Family from Black-Box Models

[EN] We address the novel question of determining which kind of machine learning model is behind the predictions when we interact with a black-box model. This may allow us to identify families of techniques whose models exhibit similar vulnerabilities and strengths. In our method, we first consider how an adversary can systematically query a given black-box model (oracle) to label an artificially-generated dataset. This labelled dataset is then used for training different surrogate models (each one trying to imitate the oracle¿s behaviour). The method has two different approaches. First, we assume that the family of the surrogate model that achieves the maximum Kappa metric against the oracle labels corresponds to the family of the oracle model. The other approach, based on machine learning, consists in learning a meta-model that is able to predict the model family of a new black-box model. We compare these two approaches experimentally, giving us insight about how explanatory and predictable our concept of family is.This material is based upon work supported by the Air Force Office of Scientific Research under award number FA9550-17-1-0287, the EU (FEDER), and the Spanish MINECO under grant TIN 2015-69175-C4-1-R, the Generalitat Valenciana PROMETEOII/2015/013. F. Martinez-Plumed was also supported by INCIBE under grant INCIBEI-2015-27345 (Ayudas para la excelencia de los equipos de investigacion avanzada en ciberseguridad). J. H-Orallo also received a Salvador de Madariaga grant (PRX17/00467) from the Spanish MECD for a research stay at the CFI, Cambridge, and a BEST grant (BEST/2017/045) from the GVA for another research stay at the CFI.Fabra-Boluda, R.; Ferri Ramírez, C.; Hernández-Orallo, J.; Martínez-Plumed, F.; Ramírez Quintana, MJ. (2018). Identifying the Machine Learning Family from Black-Box Models. Lecture Notes in Computer Science. 11160:55-65. https://doi.org/10.1007/978-3-030-00374-6_6S556511160Angluin, D.: Queries and concept learning. Mach. Learn. 2(4), 319–342 (1988)Benedek, G.M., Itai, A.: Learnability with respect to fixed distributions. Theor. Comput. Sci. 86(2), 377–389 (1991)Biggio, B., et al.: Security Evaluation of support vector machines in adversarial environments. In: Ma, Y., Guo, G. (eds.) Support Vector Machines Applications, pp. 105–153. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-02300-7_4Blanco-Vega, R., Hernández-Orallo, J., Ramírez-Quintana, M.J.: Analysing the trade-off between comprehensibility and accuracy in mimetic models. In: Suzuki, E., Arikawa, S. (eds.) DS 2004. LNCS (LNAI), vol. 3245, pp. 338–346. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-30214-8_29Dalvi, N., Domingos, P., Sanghai, S., Verma, D., et al.: Adversarial classification. In: Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 99–108. ACM (2004)Dheeru, D., Karra Taniskidou, E.: UCI machine learning repository (2017). http://archive.ics.uci.edu/mlDomingos, P.: Knowledge discovery via multiple models. Intell. Data Anal. 2(3), 187–202 (1998)Duin, R.P.W., Loog, M., Pȩkalska, E., Tax, D.M.J.: Feature-based dissimilarity space classification. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds.) ICPR 2010. LNCS, vol. 6388, pp. 46–55. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-17711-8_5Fernández-Delgado, M., Cernadas, E., Barro, S., Amorim, D.: Do we need hundreds of classifiers to solve real world classification problems. J. Mach. Learn. Res. 15(1), 3133–3181 (2014)Ferri, C., Hernández-Orallo, J., Modroiu, R.: An experimental comparison of performance measures for classification. Pattern Recognit. 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The Light Stop Scenario from Gauge Mediation

In this paper we embed the light stop scenario, a MSSM framework which explains the baryon asymmetry of the universe through a strong first order electroweak phase transition, in a top-down approach. The required low energy spectrum consists in the light SM-like Higgs, the right-handed stop, the gauginos and the Higgsinos while the remaining scalars are heavy. This spectrum is naturally driven by renormalization group evolution starting from a heavy scalar spectrum at high energies. The latter is obtained through a supersymmetry-breaking mix of gauge mediation, which provides the scalars masses by new gauge interactions, and gravity mediation, which generates gaugino and Higgsino masses. This supersymmetry breaking also explains the \mu\ and B_\mu\ parameters necessary for electroweak breaking and predicts small tri-linear mixing terms A_t in agreement with electroweak baryogenesis requirements. The minimal embedding predicts a Higgs mass around its experimental lower bound and by a small extension higher masses m_H\lesssim 127 GeV can be accommodated.Comment: 20 pages, 3 figures; v2: changes in the conventions; v3: more details on the Higgs mass prediction, version published in JHE

Auxin-regulated reversible inhibition of TMK1 signaling by MAKR2 modulates the dynamics of root gravitropism

Plants are able to orient their growth according to gravity, which ultimately controls both shoot and root architecture.1 Gravitropism is a dynamic process whereby gravistimulation induces the asymmetric distribution of the plant hormone auxin, leading to asymmetric growth, organ bending, and subsequent reset of auxin distribution back to the original pre-gravistimulation situation.1, 2, 3 Differential auxin accumulation during the gravitropic response depends on the activity of polarly localized PIN-FORMED (PIN) auxin-efflux carriers.1, 2, 3, 4 In particular, the timing of this dynamic response is regulated by PIN2,5,6 but the underlying molecular mechanisms are poorly understood. Here, we show that MEMBRANE ASSOCIATED KINASE REGULATOR2 (MAKR2) controls the pace of the root gravitropic response. We found that MAKR2 is required for the PIN2 asymmetry during gravitropism by acting as a negative regulator of the cell-surface signaling mediated by the receptor-like kinase TRANSMEMBRANE KINASE1 (TMK1).2,7, 8, 9, 10 Furthermore, we show that the MAKR2 inhibitory effect on TMK1 signaling is antagonized by auxin itself, which triggers rapid MAKR2 membrane dissociation in a TMK1-dependent manner. Our findings suggest that the timing of the root gravitropic response is orchestrated by the reversible inhibition of the TMK1 signaling pathway at the cell surface

Risk of miscarriage after chorionic villus sampling.

OBJECTIVE: To estimate the risk of miscarriage associated to chorionic villus sampling (CVS). METHODS: This was a retrospective cohort study performed in eight fetal-medicine units in Spain, Belgium and Bulgaria. Two populations were included: first, all singleton pregnancies attending to their first-trimester assessment in Murcia, Spain, and second, all singleton pregnancies having a CVS following first-trimester assessment at any of the participating centers. We used propensity score matching analysis to estimate the association between CVS and miscarriage. We compared risks of miscarriage of CVS and non-CVS groups after propensity score matching (1:1 ratio). This procedure creates two comparable groups balancing the maternal and pregnancy characteristics that lead to CVS, in a similar way in which randomization operates in a randomized clinical trial. RESULTS: The study population consisted of 22,250 participants in the non-CVS group and 3,613 in the CVS group. The incidence of miscarriage in the CVS group was 2.1% (77/3,613), which was significantly higher than the 0.9% (207/22,250) in the non-CVS group (p <0.001). The propensity score algorithm matched 2,122 CVS cases with 2,122 non-CVS cases including 40 (1.9%) and 55 (2.6%) miscarriages in the CVS and non-CVS groups, respectively (OR 0.72 [95% CI 0.48 to 1.10]; p = 0.146). However, we found a significant interaction between the CVS risk of miscarriage and the risk of aneuploidies, suggesting a different effect of the CVS for different baseline characteristics in such a way that, when the risk of aneuploidies is low, the risk after CVS increases (OR 2.87 [95% CI 1.13 to 7.30]) but when the risk is high, the risk after CVS is paradoxically reduced (OR 0.47 [95% CI 0.28 to 0.76]), presumably due to prenatal diagnosis and termination of major aneuploidies that would have otherwise resulted in spontaneous miscarriage. CONCLUSIONS: The risk of miscarriage in women having a CVS is about 1% higher than in women without CVS, although this excess risk is not entirely due to the invasive procedure but to some extent the demographic and pregnancy characteristics of the patient undergoing CVS. After accounting for these risk factors and confining the analysis to low-risk pregnancies, CVS seems to increase the risk of miscarriage about three times above the patient's background-risk. Although this is a substantial increase in relative terms, in pregnancies without risk factors, the risk of miscarriage after CVS will still remain low and similar to or slightly higher than that of the general population. For example, if her risk of aneuploidy is 1 in a 1,000 (0.1%), her risk of miscarriage after CVS will increase to 0.3% (0.2% higher)

Generation and characterization of two immortalized human osteoblastic cell lines useful for epigenetic studies

Different model systems using osteoblastic cell lines have been developed to help understand the process of bone formation. Here, we report the establishment of two human osteoblastic cell lines obtained from primary cultures upon transduction of immortalizing genes. The resulting cell lines had no major differences to their parental lines in their gene expression profiles. Similar to primary osteoblastic cells, osteocalcin transcription increased following 1,25-dihydroxyvitamin D3 treatment and the immortalized cells formed a mineralized matrix, as detected by Alizarin Red staining. Moreover, these human cell lines responded by upregulating ALPL gene expression after treatment with the demethylating agent 5-aza-2 Œ-deoxycytidine (AzadC), as shown before for primary osteoblasts. We further demonstrate that these cell lines can differentiate in vivo, using a hydroxyapatite/tricalcium phosphate composite as a scaffold, to produce bone matrix. More importantly, we show that these cells respond to demethylating treatment, as shown by the increase in SOST mRNA levels, the gene encoding sclerostin, upon treatment of the recipient mice with AzadC. This also confirms, in vivo, the role of DNA methylation in the regulation of SOST expression previously shown in vitro. Altogether our results show that these immortalized cell lines constitute a particularly useful model system to obtain further insight into bone homeostasis, and particularly into the epigenetic mechanisms regulating sclerostin production

The Goal Programming as a Tool for Measuring the Sustainability of Agricultural Production Chains of Rice

Agricultural activity is characterized by an intensive use of capital and a considerable dependence on external financing. Access to credit is often limited by the scarcity of resources and lack of guarantees, seriously affecting the productivity and economic performance of agricultural exploitations. The objective of this paper is to assess the sustainability of agricultural production chain of rice in Latin America using multi-criteria analysis tools to facilitate decision-making through a benchmarking process to contribute to their economic sustainability. The implementation of the model in an exploitation typy depending on financing sources (conservative, intermediate, and innovative) has revealed the conflict between the goals, being the intermediate exploitation, which gets the best results. The conclusions show that the flexibilization of financing options positively affects the economic performance

&amp;lt;i&amp;gt;In Vitro&amp;lt;/i&amp;gt; Activity of Squaramides and Acyclic Polyamine Derivatives against Trophozoites and Cysts of &amp;lt;i&amp;gt;Acanthamoeba castellanii&amp;lt;/i&amp;gt;

Pathogenic strains of Acanthamoeba cause keratitis (AK), granulomatous amoebic encephalitis (GAE), amoebic pneumonitis (AP), and skin infection in human and animals. The treatment of an Acanthamoeba infection is invariably very difficult and not always effective, and compounds that are amebicidic or amebistatic are frequently toxic and/or irritating for humans. Squaramides and polyamine derivatives have been demonstrated to have antitumor and antiprotozoal activity. The aim of this study was to investigate the activity of 5 squaramides and 5 acyclic polyamines against trophozoites and cysts of A. castellanii Neff. Amoebicidal activity against the trophozoites and cytotoxicity against Vero cells were evaluated with a colorimetric assay, using Alamar Blue®, and chlorhexidine digluconate was assayed as the reference drug. The squaramides 3 and 5 and the acyclic polyamine 6 appeared to be the most active against the trophozoites and their cytotoxicity was low, showing selectivity indexes of 28.3, 26, and 25.7, respectively, similar to the control drug, chlorhexidine digluconate (27.6). But only the squaramide 3 showed complete cysticidal activity at the concentrations of 100 and 200 µM, as the chlorhexidine digluconate. Further studies of the mechanism of action and in vivo assays are needed, but squaramide 3 could be used for developing novel therapeutic approaches against Acanthamoeba infections

The MDM2-p53 pathway is involved in preconditioning-induced neuronal tolerance to ischemia.

Brain preconditioning (PC) refers to a state of transient tolerance against a lethal insult that can be evoked by a prior mild event. It is thought that PC may induce different pathways responsible for neuroprotection, which may involve the attenuation of cell damage pathways, including the apoptotic cell death. In this context, p53 is a stress sensor that accumulates during brain ischemia leading to neuronal death. The murine double minute 2 gene (MDM2), a p53-specific E3 ubiquitin ligase, is the main cellular antagonist of p53, mediating its degradation by the proteasome. Here, we study the role of MDM2-p53 pathway on PC-induced neuroprotection both in cultured neurons (in vitro) and rat brain (in vivo). Our results show that PC increased neuronal MDM2 protein levels, which prevented ischemiainduced p53 stabilization and neuronal death. Indeed, PC attenuated ischemia-induced activation of the p53/PUMA/caspase-3 signaling pathway. Pharmacological inhibition of MDM2-p53 interaction in neurons abrogated PC-induced neuroprotection against ischemia. Finally, the relevance of the MDM2-p53 pathway was confirmed in rat brain using a PC model in vivo. These findings demonstrate the key role of the MDM2-p53 pathway in PC-induced neuroprotection against a subsequent ischemic insult and poses MDM2 as an essential target in ischemic tolerance