54 research outputs found

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    The Role of Phosphoglycans in the Susceptibility of Leishmania mexicana to the Temporin Family of Anti-Microbial Peptides

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    Natural product antimicrobial peptides (AMPs) have been proposed as promising agents against the Leishmania species, insect vector borne protozoan parasites causing the neglected tropical disease leishmaniasis. However, recent studies have shown that the mammalian pathogenic amastigote form of L. mexicana, a causative agent of cutaneous leishmaniasis, is resistant to the amphibian-derived temporin family of AMPs when compared to the insect stage promastigote form. The mode of resistance is unknown, however the insect and mammalian stages of Leishmania possess radically different cell surface coats, with amastigotes displaying low (or zero) quantities of lipophosphoglycan (LPG) and proteophosphoglycan (PPG), macromolecules which form thick a glycocalyx in promastigotes. It has been predicted that negatively charged LPG and PPG influence the sensitivity/resistance of promastigote forms to cationic temporins. Using LPG and PPG mutant L. mexicana, and an extended range of temporins, in this study we demonstrated that whilst LPG has little role, PPG is a major factor in promastigote sensitivity to the temporin family of AMPs, possibly due to the conferred anionic charge. Therefore, the lack of PPG seen on the surface of pathogenic amastigote L. mexicana may be implicated in their resistance to these peptides

    Pattern-Guided Data Anonymization and Clustering

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    Abstract. A matrix M over a fixed alphabet is k-anonymous if every row in M has at least k − 1 identical copies in M. Making a matrix k-anonymous by replacing a minimum number of entries with an additional ⋆-symbol (called “suppressing entries”) is known to be NP-hard. This task arises in the context of privacy-preserving publishing. We propose and analyze the computational complexity of an enhanced anonymization model where the user of the k-anonymized data may additionally “guide” the selection of the candidate matrix entries to be suppressed. The basic idea is to express this by means of “pattern vectors ” which are part of the input. This can also be interpreted as a sort of clustering process. It is motivated by the observation that the “value ” of matrix entries may significantly differ, and losing one (by suppression) may be more harmful than losing the other, which again may very much depend on the intended use of the anonymized data. We show that already very basic special cases of our new model lead to NP-hard problems while others allow for (fixed-parameter) tractability results.

    Effects of age and gender on shortening velocity and myosin isoforms in single rat muscle fibres

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    The maximum velocity of unloaded shortening (V0) and the myosin heavy chain (MyHC) and light chain (MyLC) isoform composition were determined in single fibres from soleus and extensor digitorum longus (EDL) muscles of male and female rats 3–6 and 22–24 months old. In the soleus muscle, the β/slow (type I MyHC) isoform predominated in both young and old animals, irrespective of gender. In the EDL, fibres expressing type IIX MyHC or a combination of IIX and IIB (IIXB) MyHC isoforms were predominant in old rats, while type IIB MyHC fibres predominated in young individuals of both genders. The V0 of soleus fibres expressing the type I MyHC isoform decreased (P < 0.001) by 40% with age in spite of an unchanged MyLC composition. In the EDL, the V0 of fibres expressing IIX, IIXB and IIB MyHC isoforms did not change with age or differ between males and females. In conclusion, similar age-related changes in V0 and MyHC composition were observed in single muscle cells from both male and female rats. The present results demonstrate that the relationship between V0 and MyHC isoform composition at the single fibre level is similar in male and female rats, and that similar qualitative changes take place during ageing in both genders. Motor impairment, such as slowing of muscle movement and increasing muscle weakness, is a prominent feature of ageing. Consequently, many elderly people have difficulties in performing activities of daily life, maintaining postural balance and preventing impending falls. This, together with the age-related decrease in bone strength, which has been suggested to be related to muscle weakness (Madsen et al. 1993), increases the risk of bone fractures in the elderly. The problems may be even greater in women than in men, since men are generally stronger than women at any age (Miller et al. 1993), and consequently women are at greater risk of becoming impaired in certain motor tasks with ageing (Rantanen et al. 1996). The mechanisms underlying these impairments are complex, but alterations within the motor neurone and muscle cell play an important role. An understanding of the age-related changes in skeletal muscle becomes increasingly important in the light of the growing population of elderly people. The maximum velocity of unloaded shortening (V0) is one of the most important design parameters of skeletal muscle, since muscles develop their maximum power at approximately one-third of V0 (Rome et al. 1990). Thus, to generate power optimally over a wide range of movements, it is crucial to be able to recruit muscle fibres with a wide range of V0. The V0 of a muscle is proportional to the myosin adenosine triphosphatase (ATPase) activity (Bárány 1967). The activity of myosin ATPase is determined by the myosin heavy chain (MyHC) isoform composition, and there is a close correlation between V0 and this composition at the single fibre level (Reiser et al. 1985, Greaser et al. 1988, Sweeney et al. 1988, Schluter & Fitts 1994). Ageing has been reported to have different effects in muscles of male and female mammals, including man (Beltran Niclos et al. 1995, Cartee 1995, Phillips et al. 1996). Most studies on the effects of age and gender on skeletal muscle have been focused on differences in maximum force (Miller et al. 1993, Phillips et al. 1996a,b; Rantanan et al. 1996) and muscle size (Cartee 1995). However, the effects of age and gender on the shortening velocity have received less scientific attention and the studies published so far have dealt with changes in the velocity of whole muscle movement (e.g. Beltran Niclos et al. 1995). Measurements of skeletal muscle function in vivo are limited by factors that tend to obscure the behaviour of individual muscle fibres, such as (i) intramuscular differences in fibre orientation, (ii) differences in the mechanical leverage provided by the bony anatomy of the joint, (iii) the elasticity of the muscle and its tendons and, during voluntary contractions, (iv) differences in patterns of motor unit recruitment and (v) activation of antagonistic muscles. In addition, the roles of different fibre types in whole muscle contraction are difficult to evaluate. These confounding factors are circumvented in skinned fibre preparations which allow investigation of the function of the myofilament proteins in a cell with an intact filament lattice under near physiological conditions. In this study the effects of age and gender on the contractile speed and expression of myosin isoforms in skinned single fibres were investigated. On the basis of previous observations indicating that male and female rats exhibited similar age-related changes in the composition of myosin isoforms in both fast- and slow-twitch skeletal muscles (Larsson & Yu 1997), it was hypothesized that V0 and its relation to the MyHC composition of single extensor digitorum longus (EDL) and soleus muscle fibres from female rats would follow the same pattern as that of their male counterparts

    Using graph convolutional network to characterize individuals with major depressive disorder across multiple imaging sites

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    BACKGROUND: Establishing objective and quantitative neuroimaging biomarkers at individual level can assist in early and accurate diagnosis of major depressive disorder (MDD). However, most previous studies using machine learning to identify MDD were based on small sample size and did not account for the brain connectome that is associated with the pathophysiology of MDD. Here, we addressed these limitations by applying graph convolutional network (GCN) in a large multi-site MDD dataset. METHODS: Resting-state functional MRI scans of 1586 participants (821 MDD vs. 765 controls) across 16 sites of Rest-meta-MDD consortium were collected. GCN model was trained with individual whole-brain functional network to identify MDD patients from controls, characterize the most salient regions contributing to classification, and explore the relationship between topological characteristics of salient regions and clinical measures. FINDINGS: GCN achieved an accuracy of 81·5% (95%CI: 80·5–82·5%, AUC: 0·865), which was higher than other common machine learning classifiers. The most salient regions contributing to classification were primarily identified within the default mode, fronto-parietal, and cingulo-opercular networks. Nodal topologies of the left inferior parietal lobule and left dorsolateral prefrontal cortex were associated with depressive severity and illness duration, respectively. INTERPRETATION: These findings based on a large, multi-site dataset support the feasibility and effectiveness of GCN in characterizing MDD, and also illustrate the potential utility of GCN for enhancing understanding of the neurobiology of MDD by detecting clinically-relevant disruption in functional network topology. FUNDING: This study was supported by the National Natural Science Foundation of China (Grant Nos. 81621003, 82027808, 81820108018)

    Blocking muscle wasting via deletion of the muscle-specific E3 ligase MuRF1 impedes pancreatic tumor growth.

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    Cancer-induced muscle wasting reduces quality of life, complicates or precludes cancer treatments, and predicts early mortality. Herein, we investigate the requirement of the muscle-specific E3 ubiquitin ligase, MuRF1, for muscle wasting induced by pancreatic cancer. Murine pancreatic cancer (KPC) cells, or saline, were injected into the pancreas of WT and MuRF1 &lt;sup&gt;-/-&lt;/sup&gt; mice, and tissues analyzed throughout tumor progression. KPC tumors induces progressive wasting of skeletal muscle and systemic metabolic reprogramming in WT mice, but not MuRF1 &lt;sup&gt;-/-&lt;/sup&gt; mice. KPC tumors from MuRF1 &lt;sup&gt;-/-&lt;/sup&gt; mice also grow slower, and show an accumulation of metabolites normally depleted by rapidly growing tumors. Mechanistically, MuRF1 is necessary for the KPC-induced increases in cytoskeletal and muscle contractile protein ubiquitination, and the depression of proteins that support protein synthesis. Together, these data demonstrate that MuRF1 is required for KPC-induced skeletal muscle wasting, whose deletion reprograms the systemic and tumor metabolome and delays tumor growth
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