Establishing propositional truth-value in counterfactual and real-world contexts during sentence comprehension: Differential sensitivity of the left and right inferior frontal gyri

What makes a proposition true or false has traditionally played an essential role in philosophical and linguistic theories of meaning. A comprehensive neurobiological theory of language must ultimately be able to explain the combined contributions of real-world truth-value and discourse context to sentence meaning. This fMRI study investigated the neural circuits that are sensitive to the propositional truth-value of sentences about counterfactual worlds, aiming to reveal differential hemispheric sensitivity of the inferior prefrontal gyri to counterfactual truth-value and real-world truth-value. Participants read true or false counterfactual conditional sentences (“If N.A.S.A. had not developed its Apollo Project, the first country to land on the moon would be Russia/America”) and real-world sentences (“Because N.A.S.A. developed its Apollo Project, the first country to land on the moon has been America/Russia”) that were matched on contextual constraint and truth-value. ROI analyses showed that whereas the left BA 47 showed similar activity increases to counterfactual false sentences and to real-world false sentences (compared to true sentences), the right BA 47 showed a larger increase for counterfactual false sentences. Moreover, whole-brain analyses revealed a distributed neural circuit for dealing with propositional truth-value. These results constitute the first evidence for hemispheric differences in processing counterfactual truth-value and real-world truth-value, and point toward additional right hemisphere involvement in counterfactual comprehension

Performance indexes for the three peak detection algorithms applied for mean spectra in the simulated datasets.

<p><b>(A)</b> F1 score. <b>(B)</b> Sensitivity. <b>(C)</b> FDR. <b>(D)</b> No of detected peaks. Colors: MS-GMM—red, CWT—blue, CROM—green.</p

Aurum dataset—distributions of absolute relative errors in estimating positions of peaks, represented by histograms, for MS-GMM (red) and CWT (blue) algorithms.

<p>Aurum dataset—distributions of absolute relative errors in estimating positions of peaks, represented by histograms, for MS-GMM (red) and CWT (blue) algorithms.</p

Short fragment of MS including one ground truth Aurum peak m/z = 1690.766 Da from the spectrum T10761_Well A24_18836 and its GMM.

<p><b>(A)</b> MS fragment, <b>(B)</b> GMM decomposition, <b>(C)</b> GMM components. We additionally mark, by vertical lines m/z positions, black: true Aurum peak 1690.766, red: m/z estimate by using MS-GMM, blue: m/z estimate by using CWT algorithm.</p

Fragment of one virtual MS dataset (with 200 peaks, m/z range 2900–3300 Da).

<p>Comparison of MS-GMM and CWT. MS signal (black), GMM model components (red), peaks detected by CWT algorithm (blue asterisks). Positions of true peaks in the spectral signal are marked by circles symbols and detection status is depicted by colors: peak detected only by MS-GMM method (red), peak detected only by CWT method (blue), peak detected by both MS-GMM and CWT (black), peak not detected by any of algorithms (empty circle).</p

An Optimized Method of Metabolite Extraction from Formalin-Fixed Paraffin-Embedded Tissue for GC/MS Analysis

<div><p>Formalin-fixed paraffin-embedded (FFPE) tissue specimens constitute a highly valuable source of clinical material for retrospective molecular studies. However, metabolomic assessment of such archival material remains still in its infancy. Hence, there is an urgent need for efficient methods enabling extraction and profiling of metabolites present in FFPE tissue specimens. Here we demonstrate the methodology for isolation of primary metabolites from archival tissues; either fresh-frozen, formalin-fixed or formalin-fixed and paraffin-embedded specimens of mouse kidney were analysed and compared in this work. We used gas chromatography followed by mass spectrometry (GC/MS approach) to identify about 80 metabolites (including amino acids, saccharides, carboxylic acids, fatty acids) present in such archive material. Importantly, about 75% of identified compounds were detected in all three types of specimens. Moreover, we observed that fixation with formalin itself (and their duration) did not affect markedly the presence of particular metabolites in tissue-extracted material, yet fixation for 24h could be recommended as a practical standard. Paraffin embedding influenced efficiency of extraction, which resulted in reduced quantities of several compounds. Nevertheless, we proved applicability of FFPE specimens for non-targeted GS/MS-based profiling of tissue metabolome, which is of great importance for feasibility of metabolomics studies using retrospective clinical material.</p></div

Venn diagram showing numbers of identified compounds detected in extracts from fresh-frozen, formalin-fixed and FFPE specimens of mouse kidney (samples were fixed with formalin for 24h).

<p>Venn diagram showing numbers of identified compounds detected in extracts from fresh-frozen, formalin-fixed and FFPE specimens of mouse kidney (samples were fixed with formalin for 24h).</p

Contribution of different classes of metabolites detected in extracts from fresh-frozen, formalin-fixed or FFPE specimens of mouse kidney (samples were fixed with formalin for 24h).

<p>Contribution of different classes of metabolites detected in extracts from fresh-frozen, formalin-fixed or FFPE specimens of mouse kidney (samples were fixed with formalin for 24h).</p

Metabolites detected by GC/MS in different preparations of mouse kidney–comparison between different types of tissue preparations.

<p>Shown are differences (fold-changes) in relative abundances of each metabolite between FFPE or formalin-fixed (FF) tissue specimens and fresh-frozen (FrFr) reference tissue, followed by statistical significance of the difference (p-value estimated by the t-test). Tissue specimens were fixed with formalin for 24h. Metabolites not detected (n.d.) in FFPE, FF or FrFr specimens are marked with ^{a, b} and ^c, respectively.</p><p>Metabolites detected by GC/MS in different preparations of mouse kidney–comparison between different types of tissue preparations.</p

The general workflow of metabolite extraction from formalin-fixed paraffin-embedded tissue blocks for GC/MS analysis.

<p>The general workflow of metabolite extraction from formalin-fixed paraffin-embedded tissue blocks for GC/MS analysis.</p