Verb Variability and Morphosyntactic Priming With Typically Developing 2- and 3-Year-Olds

Purpose

This study was specifically designed to examine how verb variability and verb overlap in a morphosyntactic priming task affect typically developing children's use and generalization of auxiliary IS.

Method

Forty typically developing 2- to 3-year-old native English-speaking children with inconsistent auxiliary IS production were primed with 24 present progressive auxiliary IS sentences. Half of the children heard auxiliary IS primes with 24 unique verbs (high variability). The other half heard auxiliary IS primes with only 6 verbs, repeated 4 times each (low variability). In addition, half of the children heard prime–target pairs with overlapping verbs (lexical boost), whereas the other half heard prime–target pairs with nonoverlapping verbs (no lexical boost). To assess use and generalization of the targeted structure to untrained verbs, all children described probe items at baseline and 5 min and 24 hr after the priming task.

Results

Children in the high variability group demonstrated strong priming effects during the task and increased auxiliary IS production compared with baseline performance 5 min and 24 hr after the priming task, suggesting learning and generalization of the primed structure. Children in the low variability group showed no significant increases in auxiliary IS production and fell significantly below the high variability group in the 24-hr posttest. Verb overlap did not boost priming effects during the priming task or in posttest probes.

Conclusions

Typically developing children do indeed make use of lexical variability in their linguistic input to help them extract and generalize abstract grammatical rules. They can do this quite quickly, with relatively stable, robust learning occurring after a single optimally variable input session. With reduced variability, learning does not occur.

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Structural Relationship Between Cognitive Processing and Syntactic Sentence Comprehension in Children With and Without Developmental Language Disorder

Purpose

We assessed the potential direct and indirect (mediated) influences of 4 cognitive mechanisms we believe are theoretically relevant to canonical and noncanonical sentence comprehension of school-age children with and without developmental language disorder (DLD).

Method

One hundred seventeen children with DLD and 117 propensity-matched typically developing (TD) children participated. Comprehension was indexed by children identifying the agent in implausible sentences. Children completed cognitive tasks indexing the latent predictors of fluid reasoning (FLD-R), controlled attention (CATT), complex working memory (cWM), and long-term memory language knowledge (LTM-LK).

Results

Structural equation modeling revealed that the best model fit was an indirect model in which cWM mediated the relationship among FLD-R, CATT, LTM-LK, and sentence comprehension. For TD children, comprehension of both sentence types was indirectly influenced by FLD-R (pattern recognition) and LTM-LK (linguistic chunking). For children with DLD, canonical sentence comprehension was indirectly influenced by LTM-LK and CATT, and noncanonical comprehension was indirectly influenced just by CATT.

Conclusions

cWM mediates sentence comprehension in children with DLD and TD children. For TD children, comprehension occurs automatically through pattern recognition and linguistic chunking. For children with DLD, comprehension is cognitively effortful. Whereas canonical comprehension occurs through chunking, noncanonical comprehension develops on a word-by-word basis.

Supplemental Material

https://doi.org/10.23641/asha.7178939

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Minimally Detectable Change and Minimal Clinically Important Difference of a Decline in Sentence Intelligibility and Speaking Rate for Individuals With Amyotrophic Lateral Sclerosis

Purpose

The purpose of this study was to determine the minimally detectable change (MDC) and minimal clinically important difference (MCID) of a decline in speech sentence intelligibility and speaking rate for individuals with amyotrophic lateral sclerosis (ALS). We also examined how the MDC and MCID vary across severities of dysarthria.

Method

One-hundred forty-seven patients with ALS and 49 healthy control subjects were selected from a larger, longitudinal study of bulbar decline in ALS, resulting in a total of 650 observations. Intelligibility and speaking rate in words per minute (WPM) were calculated using the Sentence Intelligibility Test (Yorkston, Beukelman, & Hakel, 2007), and the ALS Functional Rating Scale–Revised (Cedarbaum et al., 1999) was administered to capture patient perception of motor impairment. The MDC at the 95% confidence level was estimated using the following formula: MDC₉₅ = 1.96 × √2 × SEM. For estimation of the MCID, receiver operating characteristic curves were generated, and area under the curve and optimal thresholds to maximize sensitivity and specificity were calculated.

Results

The MDC for sentence intelligibility was 12.07%, and the MCID was 1.43%. The MDC for speaking rate was 36.57 WPM, and the MCID was 8.80 WPM. Both MDC and MCID estimates varied with severity of dysarthria.

Conclusions

The findings suggest that declines greater than 12% sentence intelligibility and 37 WPM are required to be outside measurement error and that these estimates vary widely across dysarthria severities. The MDC and MCID metrics used in this study to detect real and clinically relevant change should be estimated for other measures of speech outcomes in intervention research.

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Treating Speech Movement Hypokinesia in Parkinson's Disease: Does Movement Size Matter?

Purpose

This study evaluates the effects of a novel speech therapy program that uses a verbal cue and gamified augmented visual feedback regarding tongue movements to address articulatory hypokinesia during speech in individuals with Parkinson's disease (PD).

Method

Five participants with PD participated in an ABA single-subject design study. The treatment aimed to increase tongue movement size using a combination of a verbal cue and augmented visual feedback and was conducted in 10 45-min sessions over 5 weeks. The presence of visual feedback was manipulated during treatment. Articulatory working space of the tongue was the primary outcome measure and was examined during treatment and in cued and uncued sentences pre- and posttreatment. Changes in speech intelligibility in response to a verbal cue pre- and posttreatment were also examined.

Results

During treatment, 4/5 participants showed a beneficial effect of visual feedback on tongue articulatory working space. At the end of the treatment, they used larger tongue movements when cued, relative to their pretreatment performance. None of the participants, however, generalized the effect to the uncued sentences. Speech intelligibility of cued sentences was judged as superior posttreatment only in a single participant.

Conclusions

This study demonstrated that using an augmented visual feedback approach is beneficial, beyond a verbal cue alone, in addressing articulatory hypokinesia in individuals with PD. An optimal degree of articulatory expansion might, however, be required to elicit a speech intelligibility benefit.

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Alpha 1 antitrypsin distribution in an allergic asthmatic population sensitized to house dust mites

Severe alpha1 antitrypsin deficiency has been clearly associated with pulmonary emphysema, but its relationship with bronchial asthma remains controversial. Some deficient alpha 1 antitrypsin (AAT) genotypes s...

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Papel de la PET/TC con 18F-FDG en el diagnóstico del cáncer de ovario

Publication date: Available online 1 November 2018

Source: Revista Española de Medicina Nuclear e Imagen Molecular

Author(s): D. Rubello, M.C. Marzola, P.M. Colletti

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A novel technique for measurement of orthodontic mini-implant stability using the Osstell ISQ device.

Related Articles

A novel technique for measurement of orthodontic mini-implant stability using the Osstell ISQ device.

Angle Orthod. 2018 Nov 01;:

Authors: Hosein YK, Dixon SJ, Rizkalla AS, Tassi A

Abstract
OBJECTIVES:: To develop and validate a method for application of the Osstell ISQ device in the assessment of mini-implant stability.
MATERIALS AND METHODS:: An adaptor was developed for attachment of Osstell's SmartPeg onto a variety of orthodontic mini-implants. For validation of the adaptor, Benefit mini-implants were inserted into bone blocks that mimicked different stability conditions. The Osstell device was used to assess mini-implant stability with the adaptor (test measurement) and conventional SmartPeg attachment (gold-standard measurement). Implant stability quotient (ISQ) values were assessed for agreement, repeatability, and reproducibility.
RESULTS:: Strong positive correlations were found between ISQ values obtained using the novel adaptor and the conventional attachment. Repeatability and reproducibility of ISQ values with the adaptor were similar to those obtained with the conventional attachment.
CONCLUSIONS:: A method was developed and validated to assess the stability of orthodontic mini-implants using the Osstell system. The novel mini-implant adaptor provided repeatable and reproducible measurements of mini-implant stability, which agreed with those obtained using a conventional SmartPeg attachment. This adaptor permits noninvasive stability assessment of various designs of mini-implants, most of which are incompatible with the conventional SmartPeg attachment.

PMID: 30382751 [PubMed - as supplied by publisher]

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Clinical metric for differentiating intracranial hemangiopericytomas from meningiomas using diffusion weighted MRI

Publication date: Available online 1 November 2018

Source: Clinical Imaging

Author(s): Alexander M. El-Ali, Vikas Agarwal, Andrew Thomas, Ronald L. Hamilton, Christopher G. Filippi

Abstract

Purpose

Intracranial Hemangiopericytomas (IHP) are dural based tumors that frequently recur/metastasize. Unfortunately, their imaging appearance overlaps significantly with more benign meningiomas. We evaluated the use of diffusion weighted imaging (DWI) to differentiate IHP from meningioma.

Methods

We compared MRI of IHP tumors (WHO Grades II/III) (n = 20) to meningioma (n = 48, WHO Grade I/II).

Findings

ADC values differed between IHP (1.05 × 10–3 mm2/s) and meningiomas (0.89 × 10–3 mm2/s) (p = 0.05). Normalized ADC ratios (nADC), differed between IHP and meningiomas (1.30 vs 1.07, p = 0.03).

Conclusion

Importantly, a nADC cutoff of >1.3 was specific (96%) but not sensitive (35%) for identifying IHP.

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High Molecular Weight Hyaluronic Acid Regulates P. gingivalis–induced Inflammation and Migration in Human Gingival Fibroblasts via MAPK and NF-κB Signaling Pathway

Publication date: Available online 1 November 2018

Source: Archives of Oral Biology

Author(s): Minshan Chen, Lin Li, Zhenshi Wang, Ping Li, Feng Feng, Xi Zheng

Abstract

Chronic periodontitis is associated with Porphyromonas gingivalis (P. gingivalis) infection. Hyaluronic Acid (HA), a critical component of the extracellular matrix, exhibits anti-inflammatory and wound-healing properties. This study aimed to investigate the effect of various molecular weights of HA (30, 300 and 1300 kDa) on P. gingivalis-induced inflammatory and wound-healing responses in human gingival fibroblasts (HGFs). Cell cytotoxicity and proliferation were assessed by Lactate dehydrogenase and MTT assays, respectively. An enzyme linked immunosorbent assay was used to detect the levels of interleukin (IL) -1β, IL-6, IL-8, IL-4 and IL-10. Cell migration was evaluated with a scratch wound healing assay. The expression of nuclear factor kappa B (NF-кB), IкBα, p38 and extracellular signal-regulated kinase (ERK) were analyzed with Western blotting. The results showed that P. gingivalis (1.6 × 10⁶ CFU/mL) and HA (1, 2, 5 and 10 mg/mL) exhibited no toxicity to the HGFs. The 1300 kDa HA inhibited P. gingivalis-induced IL-1β, IL-6, IL-8, IL-4 and IL-10 production in a dose-dependent manner, while the 30 and 300 kDa HA did not have an effect. Meanwhile, cell migration was significantly promoted by the 30 and 1300 kDa HA. Furthermore, the 1300 kDa HA inhibited NF-κB expression, IκBα degradation and P. gingivalis-induced ERK and P38 activation. Therefore, our study suggests that high molecular weight HA may have beneficial effects on periodontal inflammation and oral wounds.

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MMP-3 and MMP-8 in Rat Mandibular Condylar Cartilage Associated with Dietary Loading, Estrogen Level, and Aging

Publication date: Available online 1 November 2018

Source: Archives of Oral Biology

Author(s): Jia Yu, Eerika Mursu, Matleena Typpo, Sakari Laaksonen, Hanna-Marja Voipio, Paula Pesonen, Aune Raustia, Pertti Pirttiniemi

Abstract

Objectives

The structure of the mandibular condylar cartilage (MCC) is regulated by dynamic and multifactorial processes. The aim of this study was to examine the effects of altered dietary loading, estrogen level, and aging on the structure of the condylar cartilage and the expressions of matrix metalloproteinase (MMP) -3 and MMP-8 of rat MCC.

Methods

In this study, Crl:CD (SD) female rats were randomly divided into 3 groups according to dietary hardness: hard diet (diet board), normal diet (pellet), and soft diet (powder). In each group, the rats were further divided into 2 subgroups by ovariectomy at the age of 7 weeks. The rats were sacrificed at 5- and 14-month-old. Histomorphometric analysis of the MCC thickness was performed after toluidine blue staining. Immunochemical staining was done for MMP-3 and MMP-8. A linear mixed model was used to assess the effects of dietary loading, estrogen level, and aging. Results: Increased dietary loading was the main factor to increase the MMP-3 expression and the anterior and central thickness of the MCC. Lack of estrogen was the main factor associated with decreased MMP-8. Aging was associated with the thickness changes of the whole condylar cartilage and the reduced expression of MMP-8.

Conclusion

The condylar cartilage structure and metabolism of the female rats are sensitive to dietary loading changes, estrogen level as well as aging. The proper balance of these factors seems to be essential for the maintenance of the condylar cartilage.

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Determination of IgE and IgG reactivity to more than 170 allergen molecules in paper-dried blood spots

Publication date: Available online 1 November 2018

Source: Journal of Allergy and Clinical Immunology

Author(s): Victoria Garib, Eva Rigler, Felix Gastager, Raffaela Campana, Yulia Dorofeeva, Pia Gattinger, Yury Zhernov, Musa Khaitov, Rudolf Valenta

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Reply

Publication date: Available online 1 November 2018

Source: Journal of Allergy and Clinical Immunology

Author(s): Ana Olivera, Dean D. Metcalfe

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Effect of IL-33 on de novo synthesized mediators from human mast cells

Publication date: Available online 1 November 2018

Source: Journal of Allergy and Clinical Immunology

Author(s): Theoharis C. Theoharides, Susan E. Leeman

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A Two-Stage Cepstral Analysis Procedure for the Classification of Rough Voices

Publication date: Available online 1 November 2018

Source: Journal of Voice

Author(s): Shaheen N. Awan, Jordan A. Awan

Summary

Objectives. The objective of this study was to investigate the ability of a two-stage method of cepstral peak identification to effectively discriminate rough vs breathy vs typical voice in sustained vowel productions. It was hypothesized that a dual-stage search for cepstral peak prominences (CPP's) above and below specified quefrency/F₀ cutoffs would result in a CPP difference that would be characteristic of the rough, diplophonic voice type.

Methodology. Central one-second portions of sustained vowel /a/ productions were obtained from 90 subjects (rough, breathy, and normophonic voices). All voice samples were analyzed using a a two-stage cepstral analysis process in which a CPPHigh−Low difference value was obtained by identifying cepstral peaks above and below a lower limit for expected F₀ (150 Hz for females and 90 Hz for males), called CPP_High and CPP_Low respectively.

Results. The CPPHigh−Low difference value was observed to be a highly significant predictor, with negative values for this parameter characteristic of a dominant subharmonic in the voice signal and the perception of diplophonic, rough voice. Correct classification of rough vs nonrough voice samples was 82.2% (sensitivity 0.80 and specificity 0.833). In the consideration of three group classification (breathy vs. normophonic vs. rough), models incorporating two predictors (the CPP obtained from a single search through a 60 to 300 Hz frequency range (CPP_Default) and the CPPHigh−Low difference value) correctly classified 78.88% of the voice samples.

Conclusions. Rough, diplophonic voices were consistently observed to have a subharmonic peak that was greater in amplitude than the cepstral peak obtained within the region of the expected F₀, resulting in a negative value for the CPPHigh−Low difference. The two-stage cepstral analysis process described herein is visually intuitive from the graphical display of a cepstrum and is a simple extended calculation derived from cepstral analysis procedures that have been recommended as essential in the acoustic description of vocal quality.

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Automatic Brain Labeling via Multi-Atlas Guided Fully Convolutional Networks

Publication date: Available online 1 November 2018

Source: Medical Image Analysis

Author(s): Longwei Fang, Lichi Zhang, Dong Nie, Xiaohuan Cao, Islem Rekik, Seong-Whan Lee, Huiguang He, Dinggang Shen

Abstract

Multi-atlas-based methods are commonly used for MR brain image labeling, which alleviates the burdening and time-consuming task of manual labeling in neuroimaging analysis studies. Traditionally, multi-atlas-based methods first register multiple atlases to the target image, and then propagate the labels from the labeled atlases to the unlabeled target image. However, the registration step involves non-rigid alignment, which is often time-consuming and might lack high accuracy. Alternatively, patch-based methods have shown promise in relaxing the demand for accurate registration, but they often require the use of hand-crafted features. Recently, deep learning techniques have demonstrated their effectiveness in image labeling, by automatically learning comprehensive appearance features from training images. In this paper, we propose a multi-atlas guided fully convolutional network (MA-FCN) for automatic image labeling, which aims at further improving the labeling performance with the aid of prior knowledge from the training atlases. Specifically, we train our MA-FCN model in a patch-based manner, where the input data consists of not only a training image patch but also a set of its neighboring (i.e., most similar) affine-aligned atlas patches. The guidance information from neighboring atlas patches can help boost the discriminative ability of the learned FCN. Experimental results on different datasets demonstrate the effectiveness of our proposed method, by significantly outperforming the conventional FCN and several state-of-the-art MR brain labeling methods.

Graphical abstract

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Oral ulceration with bone sequestration: retrospective study of 8 cases and literature review

Oral Diseases, Volume 0, Issue ja, -Not available-.


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Blocking antibodies induced by peanut oral and sublingual immunotherapy suppress basophil activation and are associated with sustained unresponsiveness

Clinical &Experimental Allergy, Volume 0, Issue ja, -Not available-.


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