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Following the sentence reading task, children completed a reading-aloud task where they were exposed to the novel orthographic forms for a second time. The findings are discussed in the context of theories of reading acquisition.Visual working memory (VWM) resources are limited, placing constraints on how much visual information can be simultaneously retained. During visually guided activity, stored information can quickly become outdated, so updating mechanisms are needed to ensure the contents of memory remain relevant to current task goals. In particular, successful deallocation of resources from items that become obsolete is likely to be critical for maintaining the precision of those representations still in memory. The experiments in this study involved presenting two memory arrays of coloured disks in sequence. The appearance of the second array was a cue to replace, rehearse, or add a new colour to the colours in memory. We predicted that successful resource reallocation should result in comparable recall precision when an item was replaced or rehearsed, owing to the removal of pre-replacement features. In contrast, a failure to update WM should lead to comparable precision with a condition in which a new colour was added to memory. We identified a very small proportion (∼5%) of trials in which participants incorrectly reported a feature from the first array in place of its replacement in the second, which we interpreted as a failure to incorporate the information from the second display into memory. Once these trials were discounted, precision estimates were consistent with complete redistribution of resources in the case of updating a single item. We conclude that working memory can be efficiently updated when previous information becomes obsolete, but that this is a demanding active process that occasionally fails.Inhibition of return (IOR) refers to the slower response to targets presented at previously attended locations, and such repetition-induced inhibition has been found to be differentially associated with personality traits. Although it has been well documented how personality traits affect spatial IOR, a mechanism associated with the attentional orienting network, there is not yet a consensus as to the relationship between personality traits and nonspatial repetition inhibition, a mechanism associated with the attentional executive network. The present study herein examined how the Big Five personality traits relate to cross-modal nonspatial repetition inhibition. Participants completed the NEO-PI-R and performed a cross-modal nonspatial repetition inhibition task built on the prime-neutral cue-target paradigm, in which the relationships of the identities and modalities between the prime and the target were manipulated. The results showed a significant nonspatial inhibitory effect and the effect was larger under the visual-auditory condition than under the auditory-visual condition. More importantly, neuroticism was associated with decreased cross-modal nonspatial inhibitory effect, presumably due to impaired attentional control. However, such a result was only found in the visual-auditory condition. We propose that retrieving previous prime representations under the visual-auditory condition requires a large consumption of cognitive resources, making inhibitory control more difficult for individuals with high neuroticism. These findings provide new insight into the influence of personality traits on attentional performance requiring nonspatial inhibitory control and enrich the relationship between neuroticism and repetition-induced inhibition.Despite the promise of combination cancer therapy, it remains challenging to develop targeted strategies that are nontoxic to normal cells. Here we report a combination therapeutic strategy based on engineered DNAzyme molecular machines that can promote cancer apoptosis via dynamic inter- and intracellular regulation. To achieve external regulation of T-cell/cancer cell interactions, we designed a DNAzyme-based molecular machine with an aptamer and an i-motif, as the MUC-1-selective aptamer allows the specific recognition of cancer cells. The i-motif is folded under the tumor acidic microenvironment, shortening the intercellular distance. As a result, T-cells are released by metal ion activated DNAzyme cleavage. To achieve internal regulation of mitochondria, we delivered another DNAzyme-based molecular machine with mitochondria-targeted peptides into cancer cells to induce mitochondria aggregation. Our strategy achieved an enhanced killing effect in zinc deficient cancer cells.

The differential diagnosis of intrahepatic cholangiocarcinomas (iCCAs) from metastatic adenocarcinomas from organs adjacent to the liver (gallbladder, pancreas, and stomach) is difficult due to histopathological similarity and a lack of specific markers. This study aimed to develop a method to differentiate iCCA and adenocarcinomas originated from extrahepatic organs adjacent to the liver.

We retrospectively enrolled surgically resected iCCA (n = 181) and adenocarcinomas from extrahepatic organs (n = 30, n = 28, and n = 38 from gallbladder, pancreas, and stomach, respectively) between 2007 and 2013. The albumin mRNA in situ hybridization (ISH) and immunohistochemistry (IHC) of filamin-A and cytokeratin 19 (CK19) were performed using tissue microarray. Using logistic regression analysis of three markers, iCCA-score was developed, and its diagnostic performance was evaluated.

The iCCAs were more frequently positive for albumin ISH (23.2% vs. 0%), filamin-A IHC (47.5% vs. 12.5%) and CK19 (68.5% vs. 40.6%) better diagnostic performance than albumin ISH alone.Theory of mind (ToM) deficits in people with schizophrenia have been reported and associated with impaired social interactions. Thus, ToM deficits may negatively impact social functioning and warrant consideration in treatment development. However, extant ToM measures may place excessive cognitive demands on people with schizophrenia. Therefore, the study aimed to develop a comprehensible Assessment of ToM for people with Schizophrenia (AToMS) and evaluate its psychometric properties. The AToMs was developed in 5 stages, including item formation, expert review, content validity evaluation, animation production, and cognitive interviews of 25 people with schizophrenia. The psychometric properties of the 16-item AToMS (including reliability and validity) were then tested on 59 people with schizophrenia. The newly developed animated AToMS assesses 8 ToM concepts in the cognitive and affective dimensions while placing minimal neurocognitive demands on people with schizophrenia. The AToMS presented satisfactory psychometric properties, with adequate content validity (content validity index = 0.91); mostly moderate item difficulty (item difficulty index = 0.339-0.966); good discrimination (coefficients = 0.379-0.786), internal consistency (Cronbach's α = 0.850), and reliability (intraclass correlation coefficient = 0.901 for test-retest, 0.997 for inter-rater); and satisfactory convergent and divergent validity. The AToMS is reliable and valid for evaluating ToM characteristics in people with schizophrenia. Future studies are warranted to examine the AToMS in other populations (e.g., people with affective disorders) to cross-validate and extend its utility and psychometric evidence.Efficacious treatments are available for major depressive disorder (MDD), but treatment dropout is common and decreases their effectiveness. However, knowledge about prevalence of treatment dropout and its risk factors in routine care is limited. Luzindole supplier The objective of this study was to determine the prevalence of and risk factors for dropout in a large outpatient sample. In this retrospective cohort analysis, routinely collected data from 2235 outpatients with MDD who had a diagnostic work-up between 2014 and 2016 were examined. Dropout was defined as treatment termination without achieving remission before the fourth session within six months after its start. Total and item scores on the Dutch Measure for Quantification of Treatment Resistance in Depression (DM-TRD) at baseline, and demographic variables were analyzed for their association with dropout using logistic regression and elastic net analyses. Data of 987 subjects who started routine outpatient depression treatment were included in the analyses of which 143 (14.5%) dropped out. Higher DM-TRD-scores were predictive for lower dropout odds [OR = 0.78, 95% CI = (0.70-0.86), p  less then  0.001]. The elastic net analysis revealed several clinical variables predictive for dropout. Higher SES, higher depression severity, comorbid personality pathology and a comorbid anxiety disorder were significantly associated with less dropout in the sample. In this observational study, treatment dropout was relatively low. The DM-TRD, an easy-to-use clinical instrument, revealed several variables associated with less dropout. When applied in daily practice and combined with demographical information, this instrument may help to reduce dropout and increase treatment effectiveness.Radiology reports contain a diverse and rich set of clinical abnormalities documented by radiologists during their interpretation of the images. Comprehensive semantic representations of radiological findings would enable a wide range of secondary use applications to support diagnosis, triage, outcomes prediction, and clinical research. In this paper, we present a new corpus of radiology reports annotated with clinical findings. Our annotation schema captures detailed representations of pathologic findings that are observable on imaging ("lesions") and other types of clinical problems ("medical problems"). The schema used an event-based representation to capture fine-grained details, including assertion, anatomy, characteristics, size, and count. Our gold standard corpus contained a total of 500 annotated computed tomography (CT) reports. We extracted triggers and argument entities using two state-of-the-art deep learning architectures, including BERT. We then predicted the linkages between trigger and argument entities (referred to as argument roles) using a BERT-based relation extraction model. We achieved the best extraction performance using a BERT model pre-trained on 3 million radiology reports from our institution 90.9-93.4% F1 for finding triggers and 72.0-85.6% F1 for argument roles. To assess model generalizability, we used an external validation set randomly sampled from the MIMIC Chest X-ray (MIMIC-CXR) database. The extraction performance on this validation set was 95.6% for finding triggers and 79.1-89.7% for argument roles, demonstrating that the model generalized well to the cross-institutional data with a different imaging modality. We extracted the finding events from all the radiology reports in the MIMIC-CXR database and provided the extractions to the research community.Medical image analysis for perfect diagnosis of disease has become a very challenging task. Due to improper diagnosis, required medical treatment may be skipped. Proper diagnosis is needed as suspected lesions could be missed by the physician's eye. Hence, this problem can be settled up by better means with the investigation of similar case studies present in the healthcare database. In this context, this paper substantiates an assistive system that would help dermatologists for accurate identification of 23 different kinds of melanoma. For this, 2300 dermoscopic images were used to train the skin-melanoma similar image search system. The proposed system uses feature extraction by assigning dynamic weights to the low-level features based on the individual characteristics of the searched images. Optimal weights are obtained by the newly proposed optimized pair-wise comparison (OPWC) approach. The uniqueness of the proposed approach is that it provides the dynamic weights to the features of the searched image instead of applying static weights.