Metaphor processing: Referring and predicating

The general consensus emerging from decades of empirical investigation of metaphor processing is that, when appropriately contextualised, metaphorically used language is no more demanding of processing effort than literally used language. However, there is a small number of studies which contradict this position, notably Noveck, Bianco, and Castry (2001): they maintain that relevance-based pragmatic theory predicts increased cognitive costs incurred in deriving the extra effects that metaphors typically yield, and they provide experimental results that support this prediction. In our study, we first surveyed and assessed the tasks and stimulus materials of many experiments on metaphor processing from the 1970's to the present day. The most telling result was an apparent disparity between the processing of metaphorical language used predicatively versus referentially. We then ran two self-paced reading experiments to test our hypothesis that when used as a predicate, metaphorical language is no more costly than literal language, but when used referentially, it does incur extra costs, even given a preceding biasing context. In the first experiment, all metaphorical referring expressions were in subject position so occurred early in the sentence; in the second experiment, we controlled for any effect of sentence position by placing metaphorical referring expressions in object position, thus later in the sentence, similar to the predicate metaphors. In both cases, metaphorical referring incurred significantly greater costs relative to literal equivalents than did metaphorical predication, with no effect of sentence position. We end with a brief analysis of why the referential use of metaphor is special and effort-demanding.

The role of language in building abstract, generalized conceptual representations of one- and two-place predicates: A comparison between adults and infants

Theories of relations between language and conceptual development benefit from empirical evidence for concepts available in infancy, but such evidence is comparatively scarce. Here, we examine early representations of specific concepts, namely, sets of dynamic events corresponding either to predicates involving two variables with a reversible, asymmetric relation between them (such as the set of all events that correspond to a linguistic phrase like "a dog is pushing a car,") or to comparatively simpler, one-variable predicates (such as the set of events corresponding to a phrase like "a dog is jumping."). We develop a non-linguistic, anticipatory eye-tracking task that can be administered to both infants and adults, and we use this task to gather evidence for the formation and use of such one-and two-place-predicate classes (which we refer to as event sortals) in 12-24-mo-old infants, and in adults with and without concurrent verbal prose shadowing. Using visually similar stimuli for both the simpler (one-place) and the more complex (reversible, asymmetric, two-place) concepts, we find that infants only show evidence for forming and generalizing one-place event sortals, and, while adults succeed with both kinds in the absence of verbal shadowing, shadowing hampers their ability to form and use the asymmetric two-place event sortals. In a subsequent experiment with adults, we find that if the shadowing material is grammatically impoverished, adults now succeed in forming and using both one- and two-place event sortals. We discuss implications of these results for theories of concept acquisition, and the role of language in this process.

Easily generated hematological biomarkers and prediction of placental abruption

OBJECTIVE

Placental abruption (PA) is associated with adverse maternal and neonatal outcomes. Increasing evidence has shown an association between abruption and inflammation as well as utilization of hematological biomarkers to predict the later. We aimed to evaluate the feasibility of using neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ration (PLR) taken early in pregnancy in predicting later occurrence of PA.

STUDY DESIGN

A nested case control study, which compared parturient with PA (cases) to parturient without PA (controls). Parturient were matched by hospitalization date and maternal age. Demographic, clinical, and obstetrical characteristics were retrieved. Hematological indices derived from complete blood count taken during the first trimester of pregnancy, specifically NLR and PLR were retrieved and compared between the groups. Mann-Whitney and T-test were performed for not normally and normally distributed continuous variables respectively, categorical variables were analyzed using Chi-Square or Fisher Exact test as appropriate.

RESULTS

The study comprised of 232 patients. Of these, 131 had suffered from PA and 131 without PA. Parturient who had PA has significantly higher rates of hypertensive disorders of pregnancy, mean neutrophil, lymphocyte and platelet count did not differ between the groups. A comparison of NLR and PLR between the study groups yielded no significant differences.

CONCLUSION

NLR and PLR taken early in the course of pregnancy were not found associated with PA. Given the potentially severe consequences of PA, the biological plausibility and the readiness of these hematological markers, further investigation of this method with larger, prospective studies are needed.

Isfahan and Covid-19: Deep spatiotemporal representation

The coronavirus COVID-19 is affecting 213 countries and territories around the world. Iran was one of the first affected countries by this virus. Isfahan, as the third most populated province of Iran, experienced a noticeable epidemic. The prediction of epidemic size, peak value, and peak time can help policymakers in correct decisions. In this study, deep learning is selected as a powerful tool for forecasting this epidemic in Isfahan. A combination of effective Social Determinant of Health (SDH) and the occurrences of COVID-19 data are used as spatiotemporal input by using time-series information from different locations. Different models are utilized, and the best performance is found to be for a tailored type of long short-term memory (LSTM). This new method incorporates the mutual effect of all classes (confirmed/ death / recovered) in the prediction process. The future trajectory of the outbreak in Isfahan is forecasted with the proposed model. The paper demonstrates the positive effect of adding SDHs in pandemic prediction. Furthermore, the effectiveness of different SDHs is discussed, and the most effective terms are introduced. The method expresses high ability in both short- and long- term forecasting of the outbreak. The model proves that in predicting one class (like the number of confirmed cases), the effect of other accompanying numbers (like death and recovered cases) cannot be ignored. In conclusion, the superiorities of this model (particularity the long term predication ability) turn it into a reliable tool for helping the health decision-makers.

Nuclear shape, architecture and orientation features from H&E images are able to predict recurrence in node-negative gastric adenocarcinoma

BACKGROUND

Identifying intestinal node-negative gastric adenocarcinoma (INGA) patients with high risk of recurrence could help perceive benefit of adjuvant therapy for INGA patients following surgical resection. This study evaluated whether the computer-extracted image features of nuclear shapes, texture, orientation, and tumor architecture on digital images of hematoxylin and eosin stained tissue, could help to predict recurrence in INGA patients.

METHODS

A tissue microarrays cohort of 160 retrospectively INGA cases were digitally scanned, and randomly selected as training cohort (D1 = 60), validation cohort (D2 = 100 and D3 = 100, D2 and D3 are different tumor TMA spots from the same patient), accompanied with immunohistochemistry data cohort (D3' = 100, a duplicate cohort of D3) and negative controls data cohort (D5 = 100, normal adjacent tissues). After nuclear segmentation by watershed-based method, 189 local nuclear features were captured on each TMA core and the top 5 features were selected by Wilcoxon rank sum test within D1. A morphometric-based image classifier (NGAHIC) was composed across the discriminative features and predicted the recurrence in INGA on D2. The intra-tumor heterogeneity was assessed on D3. Manual nuclear atypia grading was conducted on D1 and D2 by two pathologists. The expression of HER2 and Ki67 were detected by immunohistochemistry on D3 and D3', respectively. The association between manual grading and INGA outcome was analysis.

RESULTS

Independent validation results showed the NGAHIC achieved an AUC of 0.76 for recurrence prediction. NGAHIC-positive patients had poorer overall survival (P = 0.017) by univariate survival analysis. Multivariate survival analysis, controlling for T-stage, histology stage, invasion depth, demonstrated NGAHIC-positive was a reproducible prognostic factor for poorer disease-specific survival (HR = 17.24, 95% CI 3.93-75.60, P < 0.001). In contrast, human grading was only prognostic for one reader on D2. Moreover, significant correlations were observed between NGAHIC-positive patients and positivity of HER2 and Ki67 labeling index.

CONCLUSIONS

The NGAHIC could provide precision oncology, personalized cancer management.

Once More about Boesch's Ontological Predication in Focus

In this article I address some more aspects regarding Boesch's ontological predication aiming to clarify mistaken comprehensions as appeared in Perez-Campos" (2017) detailed work on my former paper about this issue (Simão 2016b). With this purpose, the following three aspects will be approached: the philosophical roots of my former proposal; the place of Boesch's symbolic action theory in that proposal and the relevance of this discussion for the relationship between ontology and psychology.

Prediction of terrestrial gamma dose rate based on geological formations and soil types in the Johor State, Malaysia

This study aims to predict and estimate unmeasured terrestrial gamma dose rate (TGDR) using statistical analysis methods to derive a model from the actual measurement based on geological formation and soil type. The measurements of TGDR were conducted in the state of Johor with a total of 3873 measured points which covered all geological formations, soil types and districts. The measurements were taken 1 m above the soil surface using NaI [Ti] detector. The measured gamma dose rates ranged from 9 nGy h(-1) to 1237 nGy h(-1) with a mean value of 151 nGy h(-1). The data have been normalized to fit a normal distribution. Tests of significance were conducted among all geological formations and soil types, using the unbalanced one way ANOVA. The results indicated strong significant differences due to the different geological formations and soil types present in Johor State. Pearson Correlation was used to measure the relations between gamma dose rate based on geological formation and soil type (D(G,S)) with the gamma dose rate based on geological formation (D(G)) or soil type (D(s)). A very good correlation was found between D(G,S) and D(G) or D(G,S) and D(s). A total of 118 pairs of geological formations and soil types were used to derive the statistical contribution of geological formations and soil types to gamma dose rates. The contribution of the gamma dose rate from geological formation and soil type were found to be 0.594 and 0.399, respectively. The null hypotheses were accepted for 83% of examined data, therefore, the model could be used to predict gamma dose rates based on geological formation and soil type information.

Survival prediction for advanced cancer patients in the real world: A comparison of the Palliative Prognostic Score, Delirium-Palliative Prognostic Score, Palliative Prognostic Index and modified Prognosis in Palliative Care Study predictor model

PURPOSE

The aim of this study was to investigate the feasibility and accuracy of the Palliative Prognostic Score (PaP score), Delirium-Palliative Prognostic Score (D-PaP score), Palliative Prognostic Index (PPI) and modified Prognosis in Palliative Care Study predictor model (PiPS model).

PATIENTS AND METHODS

This multicentre prospective cohort study involved 58 palliative care services, including 19 hospital palliative care teams, 16 palliative care units and 23 home palliative care services, in Japan from September 2012 to April 2014. Analyses were performed involving four patient groups: those treated by palliative care teams, those in palliative care units, those at home and those receiving chemotherapy.

RESULTS

We recruited 2426 participants, and 2361 patients were finally analysed. Risk groups based on these instruments successfully identified patients with different survival profiles in all groups. The feasibility of PPI and modified PiPS-A was more than 90% in all groups, followed by PaP and D-PaP scores; modified PiPS-B had the lowest feasibility. The accuracy of prognostic scores was ⩾69% in all groups and the difference was within 13%, while c-statistics were significantly lower with the PPI than PaP and D-PaP scores.

CONCLUSION

The PaP score, D-PaP score, PPI and modified PiPS model provided distinct survival groups for patients in the three palliative care settings and those receiving chemotherapy. The PPI seems to be suitable for routine clinical use for situations where rough estimates of prognosis are sufficient and/or patients do not want invasive procedure. If clinicians can address more items, the modified PiPS-A would be a non-invasive alternative. In cases where blood samples are available or those requiring more accurate prediction, the PaP and D-PaP scores and modified PiPS-B would be more appropriate.

Consideration of tumor size improves the accuracy of TNM predictions in patients with gastric cancer after curative gastrectomy

OBJECTIVE

To investigate whether addition of tumor size improves the prognostic accuracy of the UICC 7th TNM staging system in gastric cancer patients who underwent radical surgery (R0 resection).

METHODS

The clinical and pathological data and postoperative 5-year survival rate of 507 patients with gastric cancer who underwent radical surgery (R0 resection) in our department from January 2004 to June 2006 were evaluated retrospectively. The prognostic accuracy of conventional UICC 7th TNM staging was compared with that of UICC 7th TNM staging plus tumor size. The ability of tumor size to improve the 95% confidence interval (CI) of postoperative 5-year survival rate in gastric cancer patients was assessed.

RESULTS

Of the 507 patients, 470 (92.7%) were followed up. The five-year survival rate of these patients was 50.4%. The survival rates of patients with pT1, pT2, pT3, and pT4 stage tumors were 89.3%, 72.4%, 36.9%, and 23.7%, respectively (P < 0.05), and the survival rates of patients with pN0, pN1, pN2, and pN3 stage tumors were 75.2%, 68.8%, 46.7%, and 21.3% (P < 0.05). Depth of invasion, lymph node metastasis stage, metastatic lymph node ratio (MLR), lymphatic invasion and tumor size were independent predictors of patient prognosis. The accuracy of UICC 7th TNM staging in predicting 5-year survival was 75.4% and the accuracy of tumor size plus the UICC 7th TNM staging was 77.9% (P < 0.05). This combination improved the 95% CI of postoperative 5-year survival rate in gastric cancer patients.

CONCLUSION

Tumor size can improve the accuracy of UICC 7th TNM staging in predicting survival in gastric cancer patients following radical surgery (R0 resection). Tumor size is likely to be another important indicator in future UICC-TNM staging systems for gastric cancer patients.