Enterococcus faecalis is a major opportunistic pathogen that readily forms protective biofilms leading to chronic infections. Biofilms protect bacteria from detergent solutions, antimicrobial agents, ...environmental stress, and effectively make bacteria 10 to 1000-fold more resistant to antibiotic treatment. Extracellular proteins and polysaccharides are primary components of biofilms and play a key role in cell survival, microbial persistence, cellular interaction, and maturation of E. faecalis biofilms. Degradation of biofilm components by mammalian proteases is an effective antibiofilm strategy because proteases are known to degrade bacterial proteins leading to bacterial cell lysis and growth inhibition. Here, we show that human matrix metalloprotease-1 inhibits and disrupts E. faecalis biofilms. MMPs are cell-secreted zinc- and calcium-dependent proteases that degrade and regulate various structural components of the extracellular matrix. Human MMP1 is known to degrade type-1 collagen and can also cleave a wide range of substrates. We found that recombinant human MMP1 significantly inhibited and disrupted biofilms of vancomycin sensitive and vancomycin resistant E. faecalis strains. The mechanism of antibiofilm activity is speculated to be linked with bacterial growth inhibition and degradation of biofilm matrix proteins by MMP1. These findings suggest that human MMP1 can potentially be used as a potent antibiofilm agent against E. faecalis biofilms.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
How words are associated within the linguistic environment conveys semantic content; however, different contexts induce different linguistic patterns. For instance, it is well known that adults speak ...differently to children than to other adults. We present results from a new word association study in which adult participants were instructed to produce either unconstrained or child-oriented responses to each cue, where cues included 672 nouns, verbs, adjectives, and other word forms from the McArthur–Bates Communicative Development Inventory (CDI; Fenson et al.,
2006
). Child-oriented responses consisted of higher frequency words with fewer letters, earlier ages of acquisition, and higher contextual diversity. Furthermore, the correlations among the responses generated for each pair of cues differed between unconstrained (adult-oriented) and child-oriented responses, suggesting that child-oriented associations imply different semantic structure. A comparison of growth models guided by a semantic network structure revealed that child-oriented associations are more predictive of early lexical growth. Additionally, relative to a growth model based on a corpus of naturalistic child-directed speech, the child-oriented associations explain added unique variance to lexical growth. Thus, these new child-oriented word association norms provide novel insight into the semantic context of young children and early lexical development.
The human cortex encodes information in complex networks that can be anatomically dispersed and variable in their microstructure across individuals. Using simulations with neural network models, we ...show that contemporary statistical methods for functional brain imaging-including univariate contrast, searchlight multivariate pattern classification, and whole-brain decoding with L1 or L2 regularization-each have critical and complementary blind spots under these conditions. We then introduce the sparse-overlapping-sets (SOS) LASSO-a whole-brain multivariate approach that exploits structured sparsity to find network-distributed information-and show in simulation that it captures the advantages of other approaches while avoiding their limitations. When applied to fMRI data to find neural responses that discriminate visually presented faces from other visual stimuli, each method yields a different result, but existing approaches all support the canonical view that face perception engages localized areas in posterior occipital and temporal regions. In contrast, SOS LASSO uncovers a network spanning all four lobes of the brain. The result cannot reflect spurious selection of out-of-system areas because decoding accuracy remains exceedingly high even when canonical face and place systems are removed from the dataset. When used to discriminate visual scenes from other stimuli, the same approach reveals a localized signal consistent with other methods-illustrating that SOS LASSO can detect both widely distributed and localized representational structure. Thus, structured sparsity can provide an unbiased method for testing claims of functional localization. For faces and possibly other domains, such decoding may reveal representations more widely distributed than previously suspected.
Brain systems represent information as patterns of activation over neural populations connected in networks that can be widely distributed anatomically, variable across individuals, and intermingled with other networks. We show that four widespread statistical approaches to functional brain imaging have critical blind spots in this scenario and use simulations with neural network models to illustrate why. We then introduce a new approach designed specifically to find radically distributed representations in neural networks. In simulation and in fMRI data collected in the well studied domain of face perception, the new approach discovers extensive signal missed by the other methods-suggesting that prior functional imaging work may have significantly underestimated the degree to which neurocognitive representations are distributed and variable across individuals.
With practice, humans tend to improve their performance on most tasks. But do such improvements then generalize to new tasks? Although early work documented primarily task-specific learning outcomes ...in the domain of perceptual learning 1–3, an emerging body of research has shown that significant learning generalization is possible under some training conditions 4–9. Interestingly, however, research in this vein has focused nearly exclusively on just one possible manifestation of learning generalization, wherein training on one task produces an immediate boost to performance on the new task. For instance, it is this form of generalization that is most frequently referred to when discussing learning “transfer” 10, 11. Essentially no work in this domain has focused on a second possible manifestation of generalization, wherein the knowledge or skills acquired via training, despite not being directly applicable to the new task, nonetheless allow the new task to be learned more efficiently 12–15. Here, in both the visual category learning and visual perceptual learning domains, we demonstrate that sequentially training participants on tasks that share a common high-level task structure can produce faster learning of new tasks, even in cases where there is no immediate benefit to performance on the new tasks. We further show that methods commonly employed in the field may fail to detect or else conflate generalization that manifests as increased learning rate with generalization that manifests as immediate boosts to performance. These results thus lay the foundation for the various routes to learning generalization to be more thoroughly explored
•Training on multiple perceptual tasks produced significant learning generalization•Learning generalization manifested as increased learning rate (“learning to learn”)•Standard methodology would tend to miss or misidentify this type of generalization
The extent to which learning generalizes to new tasks is a key concern in the study of perceptual learning. Kattner, Cochrane, et al. report three experiments demonstrating that training on a series of tasks can induce generalization that manifests only in terms of increases in learning rate (“learning to learn”), not immediate performance.
This paper outlines a multiparametric renal MRI acquisition and analysis protocol to allow non-invasive assessment of hemodynamics (renal artery blood flow and perfusion), oxygenation (BOLD T
), and ...microstructure (diffusion, T
mapping).
We use our multiparametric renal MRI protocol to provide (1) a comprehensive set of MRI parameters renal artery and vein blood flow, perfusion, T
, T
, diffusion (ADC, D, D
, f
), and total kidney volume in a large cohort of healthy participants (127 participants with mean age of 41 ± 19 years) and show the MR field strength (1.5 T vs. 3 T) dependence of T
and T
relaxation times; (2) the repeatability of multiparametric MRI measures in 11 healthy participants; (3) changes in MRI measures in response to hypercapnic and hyperoxic modulations in six healthy participants; and (4) pilot data showing the application of the multiparametric protocol in 11 patients with Chronic Kidney Disease (CKD).
Baseline measures were in-line with literature values, and as expected, T
-values were longer at 3 T compared with 1.5 T, with increased T
corticomedullary differentiation at 3 T. Conversely, T
was longer at 1.5 T. Inter-scan coefficients of variation (CoVs) of T
mapping and ADC were very good at <2.9%. Intra class correlations (ICCs) were high for cortex perfusion (0.801), cortex and medulla T
(0.848 and 0.997 using SE-EPI), and renal artery flow (0.844). In response to hypercapnia, a decrease in cortex T
was observed, whilst no significant effect of hyperoxia on T
was found. In CKD patients, renal artery and vein blood flow, and renal perfusion was lower than for healthy participants. Renal cortex and medulla T
was significantly higher in CKD patients compared to healthy participants, with corticomedullary T
differentiation reduced in CKD patients compared to healthy participants. No significant difference was found in renal T
.
Multiparametric MRI is a powerful technique for the assessment of changes in structure, hemodynamics, and oxygenation in a single scan session. This protocol provides the potential to assess the pathophysiological mechanisms in various etiologies of renal disease, and to assess the efficacy of drug treatments.
Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis, and new therapies are needed. Altered metabolism is a cancer vulnerability, and several metabolic pathways have been shown to promote ...PDAC. However, the changes in cholesterol metabolism and their role during PDAC progression remain largely unknown. Here we used organoid and mouse models to determine the drivers of altered cholesterol metabolism in PDAC and the consequences of its disruption on tumor progression. We identified sterol O-acyltransferase 1 (SOAT1) as a key player in sustaining the mevalonate pathway by converting cholesterol to inert cholesterol esters, thereby preventing the negative feedback elicited by unesterified cholesterol. Genetic targeting of Soat1 impairs cell proliferation in vitro and tumor progression in vivo and reveals a mevalonate pathway dependency in p53 mutant PDAC cells that have undergone p53 loss of heterozygosity (LOH). In contrast, pancreatic organoids lacking p53 mutation and p53 LOH are insensitive to SOAT1 loss, indicating a potential therapeutic window for inhibiting SOAT1 in PDAC.
High-dispersion observations of the Na I D lambdalambda5890, 5896 and K I lambdalambda7665, 7699 interstellar lines, and the diffuse interstellar band at 5780 A in the spectra of 32 Type Ia ...supernovae are used as an independent means of probing dust extinction. We show that the dust extinction of the objects where the diffuse interstellar band at 5780 A is detected is consistent with the visual extinction derived from the supernova colors. This strongly suggests that the dust producing the extinction is predominantly located in the interstellar medium of the host galaxies and not in circumstellar material associated with the progenitor system. One quarter of the supernovae display anomalously large Nai column densities in comparison to the amount of dust extinction derived from their colors. Remarkably, all of the cases of unusually strong Na I D absorption correspond to "Blueshifted" profiles in the classification scheme of Sternberg et al. This coincidence suggests that outflowing circumstellar gas is responsible for at least some of the cases of anomalously large Na i column densities. Two supernovae with unusually strong Nai D absorption showed essentially normal K I column densities for the dust extinction implied by their colors, but this does not appear to be a universal characteristic. Overall, we find the most accurate predictor of individual supernova extinction to be the equivalent width of the diffuse interstellar band at 5780 A, and provide an empirical relation for its use. Finally, we identify ways of producing significant enhancements of the Na abundance of circumstellar material in both the single-degenerate and double-degenerate scenarios for the progenitor system.
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•Assessment of MRI parameters in a single scan session.•Higher liver T1 and reduced liver perfusion with increasing disease severity and clinical outcomes.•Reduced renal cortex T1 ...linked to disease severity and clinical outcomes.
Advancing liver disease results in deleterious changes in a number of critical organs. The ability to measure structure, blood flow and tissue perfusion within multiple organs in a single scan has implications for determining the balance of benefit vs. harm for therapies. Our aim was to establish the feasibility of magnetic resonance imaging (MRI) to assess changes in Compensated Cirrhosis (CC), and relate this to disease severity and future liver-related outcomes (LROs).
A total of 60 patients with CC, 40 healthy volunteers and 7 patients with decompensated cirrhosis were recruited. In a single scan session, MRI measures comprised phase-contrast MRI vessel blood flow, arterial spin labelling tissue perfusion, T1 longitudinal relaxation time, heart rate, cardiac index, and volume assessment of the liver, spleen and kidneys. We explored the association between MRI parameters and disease severity, analysing differences in baseline MRI parameters in the 11 (18%) patients with CC who experienced future LROs.
In the liver, compositional changes were reflected by increased T1 in progressive disease (p <0.001) and an increase in liver volume in CC (p = 0.006), with associated progressive reduction in liver (p <0.001) and splenic (p <0.001) perfusion. A significant reduction in renal cortex T1 and increase in cardiac index and superior mesenteric arterial blood flow was seen with increasing disease severity. Baseline liver T1 (p = 0.01), liver perfusion (p <0.01), and renal cortex T1 (p <0.01) were significantly different in patients with CC who subsequently developed negative LROs.
MRI enables the contemporaneous assessment of organs in liver cirrhosis in a single scan without the requirement for a contrast agent. MRI parameters of liver T1, renal T1, hepatic and splenic perfusion, and superior mesenteric arterial blood flow were related to the risk of LROs.
This study assesses the changes to structure, blood flow and perfusion that occur in the key organs (liver, spleen and kidney) associated with severe liver disease (Compensated Cirrhosis), using magnetic resonance imaging. The magnetic resonance imaging measures which changed with disease severity and were related to negative liver-related clinical outcomes are described.
Research of social neuroscience establishes that regions in the brain's default-mode network (DN) and semantic network (SN) are engaged by socio-cognitive tasks. Research of the human connectome ...shows that DN and SN regions are both situated at the transmodal end of a cortical gradient but differ in their loci along this gradient. Here we integrated these 2 bodies of research, used the psychological continuity of self versus other as a "test-case," and used functional magnetic resonance imaging to investigate whether these 2 networks would encode social concepts differently. We found a robust dissociation between the DN and SN-while both networks contained sufficient information for decoding broad-stroke distinction of social categories, the DN carried more generalizable information for cross-classifying across social distance and emotive valence than did the SN. We also found that the overarching distinction of self versus other was a principal divider of the representational space while social distance was an auxiliary factor (subdivision, nested within the principal dimension), and this representational landscape was more manifested in the DN than in the SN. Taken together, our findings demonstrate how insights from connectome research can benefit social neuroscience and have implications for clarifying the 2 networks' differential contributions to social cognition.
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