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A new model construction based on the knowledge graph for mining elite polyphenotype genes in crops.Frontiers in Plant Science 2024Identifying polyphenotype genes that simultaneously regulate important agronomic traits (e.g., plant height, yield, and disease resistance) is critical for developing...
Identifying polyphenotype genes that simultaneously regulate important agronomic traits (e.g., plant height, yield, and disease resistance) is critical for developing novel high-quality crop varieties. Predicting the associations between genes and traits requires the organization and analysis of multi-dimensional scientific data. The existing methods for establishing the relationships between genomic data and phenotypic data can only elucidate the associations between genes and individual traits. However, there are relatively few methods for detecting elite polyphenotype genes. In this study, a knowledge graph for traits regulating-genes was constructed by collecting data from the PubMed database and eight other databases related to the staple food crops rice, maize, and wheat as well as the model plant . On the basis of the knowledge graph, a model for predicting traits regulating-genes was constructed by combining the data attributes of the gene nodes and the topological relationship attributes of the gene nodes. Additionally, a scoring method for predicting the genes regulating specific traits was developed to screen for elite polyphenotype genes. A total of 125,591 nodes and 547,224 semantic relationships were included in the knowledge graph. The accuracy of the knowledge graph-based model for predicting traits regulating-genes was 0.89, the precision rate was 0.91, the recall rate was 0.96, and the F1 value was 0.94. Moreover, 4,447 polyphenotype genes for 31 trait combinations were identified, among which the rice polyphenotype gene and the polyphenotype gene were verified via a literature search. Furthermore, the wheat gene was revealed as a potential polyphenotype gene that will need to be further characterized. Meanwhile, the result of venn diagram analysis between the polyphenotype gene datasets (consists of genes that are predicted by our model) and the transcriptome gene datasets (consists of genes that were differential expression in response to disease, drought or salt) showed approximately 70% and 54% polyphenotype genes were identified in the transcriptome datasets of Arabidopsis and rice, respectively. The application of the model driven by knowledge graph for predicting traits regulating-genes represents a novel method for detecting elite polyphenotype genes.
PubMed: 38571713
DOI: 10.3389/fpls.2024.1361716 -
Neuropsychologia Apr 2024Neural circuits related to language exhibit a remarkable ability to reorganize and adapt in response to visual deprivation. Particularly, early and late blindness induce...
Neural circuits related to language exhibit a remarkable ability to reorganize and adapt in response to visual deprivation. Particularly, early and late blindness induce distinct neuroplastic changes in the visual cortex, repurposing it for language and semantic processing. Interestingly, these functional changes provoke a unique cognitive advantage - enhanced verbal working memory, particularly in early blindness. Yet, the underlying neuromechanisms and the impact on language and memory-related circuits remain not fully understood. Here, we applied a brain-constrained neural network mimicking the structural and functional features of the frontotemporal-occipital cortices, to model conceptual acquisition in early and late blindness. The results revealed differential expansion of conceptual-related neural circuits into deprived visual areas depending on the timing of visual loss, which is most prominent in early blindness. This neural recruitment is fundamentally governed by the biological principles of neural circuit expansion and the absence of uncorrelated sensory input. Critically, the degree of these changes is constrained by the availability of neural matter previously allocated to visual experiences, as in the case of late blindness. Moreover, we shed light on the implication of visual deprivation on the neural underpinnings of verbal working memory, revealing longer reverberatory neural activity in 'blind models' as compared to the sighted ones. These findings provide a better understanding of the interplay between visual deprivations, neuroplasticity, language processing and verbal working memory.
Topics: Humans; Memory, Short-Term; Language; Blindness; Brain; Occipital Lobe
PubMed: 38331022
DOI: 10.1016/j.neuropsychologia.2024.108816 -
Journal of Neurology Mar 2024Increasing evidence implicates endo-lysosomal dysfunction in frontotemporal dementia (FTD). 18 proteins were quantified using a mass spectrometry assay panel in the...
Increasing evidence implicates endo-lysosomal dysfunction in frontotemporal dementia (FTD). 18 proteins were quantified using a mass spectrometry assay panel in the cerebrospinal fluid of 36 people with the language variant of FTD, primary progressive aphasia (PPA) (including 13 with non-fluent variant (nfvPPA), 11 with semantic variant (svPPA), and 12 with logopenic variant (lvPPA)) and 19 healthy controls. The concentrations of the cathepsins (B, D, F, L1, and Z) as well as AP-2 complex subunit beta, ganglioside GM2 activator, beta-hexosaminidase subunit beta, tissue alpha L-fucosidase, and ubiquitin were decreased in nfvPPA compared with controls. In contrast, the concentrations of amyloid beta A4 protein, cathepsin Z, and dipeptidyl peptidase 2 were decreased in svPPA compared with controls. No proteins were abnormal in lvPPA. These results indicate a differential alteration of lysosomal proteins in the PPA variants, suggesting those with non-Alzheimer's pathologies are more likely to show abnormal lysosomal function.
Topics: Humans; Aphasia, Primary Progressive; Amyloid beta-Peptides; Frontotemporal Dementia; Language; Lysosomes
PubMed: 37917233
DOI: 10.1007/s00415-023-12063-9 -
Frontiers in Neuroscience 2024Alzheimer's disease (AD) and Lewy body disease (LBD), the two most common causes of neurodegenerative dementia with similar clinical manifestations, both show impaired...
BACKGROUND
Alzheimer's disease (AD) and Lewy body disease (LBD), the two most common causes of neurodegenerative dementia with similar clinical manifestations, both show impaired visual attention and altered eye movements. However, prior studies have used structured tasks or restricted stimuli, limiting the insights into how eye movements alter and differ between AD and LBD in daily life.
OBJECTIVE
We aimed to comprehensively characterize eye movements of AD and LBD patients on naturalistic complex scenes with broad categories of objects, which would provide a context closer to real-world free viewing, and to identify disease-specific patterns of altered eye movements.
METHODS
We collected spontaneous viewing behaviors to 200 naturalistic complex scenes from patients with AD or LBD at the prodromal or dementia stage, as well as matched control participants. We then investigated eye movement patterns using a computational visual attention model with high-level image features of object properties and semantic information.
RESULTS
Compared with matched controls, we identified two disease-specific altered patterns of eye movements: diminished visual exploration, which differentially correlates with cognitive impairment in AD and with motor impairment in LBD; and reduced gaze allocation to objects, attributed to a weaker attention bias toward high-level image features in AD and attributed to a greater image-center bias in LBD.
CONCLUSION
Our findings may help differentiate AD and LBD patients and comprehend their real-world visual behaviors to mitigate the widespread impact of impaired visual attention on daily activities.
PubMed: 38646608
DOI: 10.3389/fnins.2024.1333894 -
Cerebral Cortex (New York, N.Y. : 1991) Sep 2023We investigated the neurocognitive mechanisms underlying the processing of combinatorial unstated meaning. Sentences like "Charles jumped for 5 minutes." engender an...
We investigated the neurocognitive mechanisms underlying the processing of combinatorial unstated meaning. Sentences like "Charles jumped for 5 minutes." engender an iterative meaning that is not explicitly stated but enriched by comprehenders beyond simple composition. Comprehending unstated meaning involves meaning contextualization-integrative meaning search in sentential-discourse context. Meanwhile, people differ in how they process information with varying context sensitivity. We hypothesized that unstated meaning processing would vary with individual socio-cognitive propensity indexed by the Autism-Spectrum Quotient (AQ), accompanied by differential cortical engagements. Using functional magnetic resonance imaging, we examined the processing of sentences with unstated iterative meaning in typically-developed individuals and found an engagement of the fronto-parietal network, including the left pars triangularis (L.PT), right intraparietal (R.IPS), and parieto-occipital sulcus (R.POS). We suggest that the L.PT subserves a contextual meaning search, while the R.IPS/POS supports enriching unstated iteration in consideration of event durations and interval lengths. Moreover, the activation level of these regions negatively correlated with AQ. Higher AQ ties to lower L.PT activation, likely reflecting weaker context sensitivity, along with lower IPS activation, likely reflecting weaker computation of events' numerical-temporal specifications. These suggest that the L.PT and R.IPS/POS support the processing of combinatorial unstated meaning, with the activation level modulated by individual cognitive styles.
Topics: Humans; Brain; Thinking; Language; Cerebral Cortex; Magnetic Resonance Imaging; Cognition; Semantics; Brain Mapping
PubMed: 37557907
DOI: 10.1093/cercor/bhad261 -
Journal of Health, Population, and... Feb 2024The health of city residents is at risk due to the high rate of urbanization and the extensive use of electronics. In the context of urbanization, individuals have...
The health of city residents is at risk due to the high rate of urbanization and the extensive use of electronics. In the context of urbanization, individuals have become increasingly disconnected from nature, resulting in elevated stress levels among adults. The goal of this study was to investigate the physical and psychological benefits of spending time in nature. The benefits of touching real grass and artificial turf (the control activity) outdoors with the palm of the hand for five minutes were measured. Blood pressure and electroencephalography (EEG) as well as State-trait Anxiety Inventory (STAI) scores, and the semantic differential scale (SDM) were used to investigate psychophysiological responses. Touching real grass was associated with significant changes in brainwave rhythms and a reduction in both systolic and diastolic blood pressure compared to touching artificial turf. In addition, SDM scores revealed that touching real grass increased relaxation, comfort, and a sense of naturalness while decreasing anxiety levels. Compared to the control group, the experimental group had higher mean scores in both meditation and attentiveness. Our findings indicate that contact with real grass may reduce physiological and psychological stress in adults.
Topics: Adult; Female; Humans; Blood Pressure; China; Poaceae; East Asian People; Touch; Stress, Psychological; Anxiety
PubMed: 38310320
DOI: 10.1186/s41043-024-00514-6 -
Technology and Health Care : Official... 2024Early diagnosis of knee osteoarthritis is an important area of research in the field of clinical medicine. Due to the complexity in the MRI imaging sequences and the...
BACKGROUND
Early diagnosis of knee osteoarthritis is an important area of research in the field of clinical medicine. Due to the complexity in the MRI imaging sequences and the diverse structure of cartilage, there are many challenges in the segmentation of knee bone and cartilage. Relevant studies have conducted semantic fusion processing through splicing or summing forms, which results in reduced resolution and the accumulation of redundant information.
OBJECTIVE
This study was envisaged to construct an MRI image segmentation model to improve the diagnostic efficiency and accuracy of different grade knee osteoarthritis by adopting the Dual Attention and Multi-scale Feature Fusion Segmentation network (DA-MFFSnet).
METHODS
The feature information of different scales was fused through the Multi-scale Attention Downsample module to extract more accurate feature information, and the Global Attention Upsample module weighted lower-level feature information to reduce the loss of key information.
RESULTS
The collected MRI knee images were screened and labeled, and the study results showed that the segmentation effect of DA-MFFSNet model was closer to that of the manually labeled images. The mean intersection over union, the dice similarity coefficient and the volumetric overlap error was 92.74%, 91.08% and 7.44%, respectively, and the accuracy of the differential diagnosis of knee osteoarthritis was 84.42%.
CONCLUSIONS
The model exhibited better stability and classification effect. Our results indicated that the Dual Attention and Multi-scale Feature Fusion Segmentation model can improve the segmentation effect of MRI knee images in mild and medium knee osteoarthritis, thereby offering an important clinical value and improving the accuracy of the clinical diagnosis.
Topics: Humans; Magnetic Resonance Imaging; Osteoarthritis, Knee; Knee Joint; Image Processing, Computer-Assisted; Algorithms; Image Interpretation, Computer-Assisted
PubMed: 38759056
DOI: 10.3233/THC-248024 -
Behavioural Brain Research Feb 2024Limited research has been conducted on humor among the Taiwanese indigenous (IND) population. This study attempted to identify the differential neural correlates of...
Limited research has been conducted on humor among the Taiwanese indigenous (IND) population. This study attempted to identify the differential neural correlates of humor comprehension and appreciation between IND and Han Chinese (HAN) populations. Each participant was presented with jokes and non-jokes. IND participants when encountered with jokes displayed a greater activation of the mesolimbic dopaminergic reward system, including the amygdala, midbrain, and nucleus accumbens than HAN participants. This suggests a more pleasurable response and appreciation of humor. The IND group also displayed greater activation in the right temporoparietal junction (rTPJ) than HAN, suggesting that the IND group may experience a greater sense of novelty and be more involved in social understanding, thus exhibiting greater humor appreciation. In terms of humor comprehension, both IND and HAN showed greater activation in the superior temporal gyrus (STG) and dorsal anterior cingulate cortex (dACC). IND exhibited greater activation in the anterior STG (aSTG), while HAN showed greater activation in the posterior STG (pSTG). This suggests that the IND tends to integrate emotional messages, whereas the HAN focuses on comprehending semantic cognitive information. Interestingly, HAN did not show any greater activation than IND in terms of appreciation of humor. These group disparities have substantial implications for advancing our knowledge of the neural mechanisms underlying humor comprehension and appreciation.
Topics: Humans; Brain; Brain Mapping; Comprehension; East Asian People; Magnetic Resonance Imaging; Mesencephalon; Wit and Humor as Topic
PubMed: 37813282
DOI: 10.1016/j.bbr.2023.114702 -
BMC Medical Imaging Apr 2024Accurate preoperative identification of ovarian tumour subtypes is imperative for patients as it enables physicians to custom-tailor precise and individualized...
BACKGROUND
Accurate preoperative identification of ovarian tumour subtypes is imperative for patients as it enables physicians to custom-tailor precise and individualized management strategies. So, we have developed an ultrasound (US)-based multiclass prediction algorithm for differentiating between benign, borderline, and malignant ovarian tumours.
METHODS
We randomised data from 849 patients with ovarian tumours into training and testing sets in a ratio of 8:2. The regions of interest on the US images were segmented and handcrafted radiomics features were extracted and screened. We applied the one-versus-rest method in multiclass classification. We inputted the best features into machine learning (ML) models and constructed a radiomic signature (Rad_Sig). US images of the maximum trimmed ovarian tumour sections were inputted into a pre-trained convolutional neural network (CNN) model. After internal enhancement and complex algorithms, each sample's predicted probability, known as the deep transfer learning signature (DTL_Sig), was generated. Clinical baseline data were analysed. Statistically significant clinical parameters and US semantic features in the training set were used to construct clinical signatures (Clinic_Sig). The prediction results of Rad_Sig, DTL_Sig, and Clinic_Sig for each sample were fused as new feature sets, to build the combined model, namely, the deep learning radiomic signature (DLR_Sig). We used the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) to estimate the performance of the multiclass classification model.
RESULTS
The training set included 440 benign, 44 borderline, and 196 malignant ovarian tumours. The testing set included 109 benign, 11 borderline, and 49 malignant ovarian tumours. DLR_Sig three-class prediction model had the best overall and class-specific classification performance, with micro- and macro-average AUC of 0.90 and 0.84, respectively, on the testing set. Categories of identification AUC were 0.84, 0.85, and 0.83 for benign, borderline, and malignant ovarian tumours, respectively. In the confusion matrix, the classifier models of Clinic_Sig and Rad_Sig could not recognise borderline ovarian tumours. However, the proportions of borderline and malignant ovarian tumours identified by DLR_Sig were the highest at 54.55% and 63.27%, respectively.
CONCLUSIONS
The three-class prediction model of US-based DLR_Sig can discriminate between benign, borderline, and malignant ovarian tumours. Therefore, it may guide clinicians in determining the differential management of patients with ovarian tumours.
Topics: Humans; Female; Deep Learning; Radiomics; Ovarian Neoplasms; Ultrasonography; Algorithms; Retrospective Studies
PubMed: 38622546
DOI: 10.1186/s12880-024-01251-2 -
The Western Journal of Emergency... Mar 2024Despite the importance of peer review to publications, there is no generally accepted approach for editorial evaluation of a peer review's value to a journal editor's...
INTRODUCTION
Despite the importance of peer review to publications, there is no generally accepted approach for editorial evaluation of a peer review's value to a journal editor's decision-making. The graduate medical education editors of the Special Issue in Educational Research & Practice (Special Issue) developed and studied the holistic editor's scoring rubric (HESR) with the objective of assessing the quality of a review and an emphasis on the degree to which it informs a holistic appreciation for the submission under consideration.
METHODS
Using peer-review guidelines from several journals, the Special Issue's editors formulated the rubric as descriptions of peer reviews of varying degree of quality from the ideal to the unacceptable. Once a review was assessed by each editor using the rubric, the score was submitted to a third party for blinding purposes. We compared the performance of the new rubric to a previously used semantic differential scale instrument. Kane's validity framework guided the evaluation of the new scoring rubric around three basic assumptions: improved distribution of scores; relative consistency rather than absolute inter-rater reliability across editors; and statistical evidence that editors valued peer reviews that contributed most to their decision-making.
RESULTS
Ninety peer reviews were the subject of this study, all were assessed by two editors. Compared to the highly skewed distribution of the prior rating scale, the distribution of the new scoring rubric was bell shaped and demonstrated full use of the rubric scale. Absolute agreement between editors was low to moderate, while relative consistency between editor's rubric ratings was high. Finally, we showed that recommendations of higher rated peer reviews were more likely to concur with the editor's formal decision.
CONCLUSION
Early evidence regarding the HESR supports the use of this instrument in determining the quality of peer reviews as well as its relative importance in informing editorial decision-making.
Topics: Humans; Pilot Projects; Reproducibility of Results; Peer Review; Education, Medical, Graduate; Emergency Medicine
PubMed: 38596927
DOI: 10.5811/westjem.18432