Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of High Temperature and Drought Stress on the Expression of Gene Encoding Enzymes and the Activity of Key Enzymes Involved in Starch Biosynthesis in Wheat Grains

High temperature (HT) and drought stress (DS) play negative roles in wheat growth, and are two most important factors that limit grain yield. Starch, the main component of the wheat [][endosperm, accounts for 65–75% of grain weight, and is significantly influenced by environmental factors. To understand the effects of post-anthesis HT and DS on starch biosynthesis, we performed a pot experiment using wheat cultivar “Zhengmai 366” under field conditions combined with a climate-controlled greenhouse to simulate HT. There were two temperature regimes (optimum day/night temperatures of 25/15°C and high day/night temperatures of 32/22°C from 10 days after anthesis to maturity) accompanied by two water treatments (optimum of ∼75% relative soil water content, and a DS of ∼50% relative soil water content). Optimum temperature with optimum water treatment was the control (CK). We evaluated the expression patterns of 23 genes encoding six classes of enzymes involved in starch biosynthesis in wheat grains using real-time qPCR. HT, DS, and HT+DS treatments altered gene expression profiles. Compared to the CK, expression of 22 of the 23 genes was down regulated by HT, and only one gene (ISA2) was up-regulated by HT. Actually ISA2 was the only gene up-regulated by all three stress treatments. The expression of 17 genes was up-regulated, while six genes, including granule-bound starch synthase (GBSSI), AGPS2, BEIII, PHOL, ISA1, and AGPL2, were down-regulated by DS. Eleven genes were down-regulated and 12 were up-regulated by HT+DS. The activity of ADP-Glc pyrophosphorylase, starch synthases, GBSS, SS, and starch branching enzymes in the stress treatments (HT, DS, and HT+DS) often appeared to peak values in advance and declined significantly to be lower than that in the CK. The genes that coordinated participation in the enzymes formation can serve as an indicator of the enzymes activity potentially involved in starch biosynthesis. HT, DS, and HT+DS altered the timing of starch biosynthesis and also influenced the accumulation of amylose, amylopectin, total starch, and sucrose. Under HT, DS, and HT+DS, the key enzymes activity and their genes expression associated with the conversion of sucrose to starch, was reduced, which was the leading cause of the reductions in starch content. Our study provide further evidence about the effects of stress on starch biosynthesis in wheat, as well as a physiological understanding of the impact of post-anthesis heat and DS on starch accumulation and wheat grain yield.
Deep Learning-Based Phenotyping System With Glocal Description of Plant Anomalies and Symptoms

Recent advances in Deep Neural Networks have allowed the development of efficient and automated diagnosis systems for plant anomalies recognition. Although existing methods have shown promising results, they present several limitations to provide an appropriate characterization of the problem, especially in real-field scenarios. To address this limitation, we propose an approach that besides being able to efficiently detect and localize plant anomalies, allows to generate more detailed information about their symptoms and interactions with the scene, by combining visual object recognition and language generation. It uses an image as input and generates a diagnosis result that shows the location of anomalies and sentences describing the symptoms as output. Our framework is divided into two main parts: First, a detector obtains a set of region features that contain the anomalies using a Region-based Deep Neural Network. Second, a language generator takes the features of the detector as input and generates descriptive sentences with details of the symptoms using Long-Short Term Memory (LSTM). Our loss metric allows the system to be trained end-to-end from the object detector to the language generator. Finally, the system outputs a set of bounding boxes along with the sentences that describe their symptoms using glocal criteria into two different ways: a set of specific descriptions of the anomalies detected in the plant and an abstract description that provides general information about the scene. We demonstrate the efficiency of our approach in the challenging tomato diseases and pests recognition task. We further show that our approach achieves a mean Average Precision (mAP) of 92.5% in our newly created Tomato Plant Anomalies Description Dataset. Our objective evaluation allows users to understand the relationships between pathologies and their evolution throughout their stage of infection, location in the plant, symptoms, etc. Our work introduces a cost-efficient tool that provides farmers with a technology that facilitates proper handling of crops.
Resolving School Staffing Problems in Greece: A Strategic Management Approach

Schooling constitutes one of the most fundamental means to social wellbeing, cultural advancement and economic growth in a nation. In order for school units to be effective in this role, it is imperative for their teaching staff to be well-trained, skilled and eager to perform their duties. In Greece, staffing in primary and secondary public education is performed at a central level by the Ministry of Education, whose utmost priority is to safeguard transparency in the selection process rather than select those candidates who would be most capable of improving the operation of the country’s public schools (in terms of its pedagogical, teaching and administrative functions). Since early January 2019, the Greek Ministry of Education has reviewed existing school staffing practices, sparking reactions among the education community and professional teachers’ unions as well as fueling discussions in society. The aim of this study is to critically deliberate upon school staffing practices in Greece by perusing pertinent literature and legislation. In particular, in the light of strategic management, it shall investigate whether school staffing in Greek schools is consistent with current and future education requirements concerning teaching staff with adequate knowledge and skills, as well as proper attitudes and behaviours. The present study also aims at identifying the degree to which this system provides newly appointed teaching staff with professional support so as to ensure a smooth and productive incorporation into the school unit.
LAMA4-Regulating miR-4274 and Its Host Gene SORCS2 Play a Role in IGFBP6-Dependent Effects on Phenotype of Basal-Like Breast Cancer

Specificity of RNAi to selected target is challenged by off-target effects, both canonical and non-canonical. Notably, more than half of all human microRNAs are co-expressed with hosting them proteincoding genes. Here we dissect regulatory subnetwork centered on IGFBP6 gene, which is associated with low proliferative state and high migratory activity of basal-like breast cancer. We inhibited expression of IGFBP6 gene in a model cell line for basal-like breast carcinoma MDA-MB-231, then traced secondary and tertiary effects of this knockdown to LAMA4, a laminin encoding gene that contributes to the phenotype of triple-negative breast cancer. LAMA4-regulating miRNA miR-4274 and its host gene SORCS2 were highlighted as intermediate regulators of the expression levels of LAMA4, which correlated in a basal-like breast carcinoma sample subset of TCGA to the levels of SORCS2 negatively. Overall, our study points that the secondary and tertiary layers of regulatory interactions are certainly underappreciated. As these types of molecular event may significantly contribute to the formation of the cell phenotypes after RNA interference based knockdowns, further studies of multilayered molecular networks affected by RNAi are warranted.
Children With Reading Difficulty Rely on Unimodal Neural Processing for Phonemic Awareness

Phonological awareness skills in children with reading difficulty (RD) may reflect impaired automatic integration of orthographic and phonological representations. However, little is known about the underlying neural mechanisms involved in phonological awareness for children with RD. Eighteen children with RD, ages 9–13, participated in a functional magnetic resonance imaging (fMRI) study designed to assess the relationship of two constructs of phonological awareness, phoneme synthesis, and phoneme analysis, with crossmodal rhyme judgment. Participants completed a rhyme judgment task presented in two modality conditions; unimodal auditory only and crossmodal audiovisual. Measures of phonological awareness were correlated with unimodal, but not crossmodal, lexical processing. Moreover, these relationships were found only in unisensory brain regions, and not in multisensory brain areas. The results of this study suggest that children with RD rely on unimodal representations and unisensory brain areas, and provide insight into the role of phonemic awareness in mapping between auditory and visual modalities during literacy acquisition.
Diabetes, a Contemporary Risk for Parkinson’s Disease: Epidemiological and Cellular Evidences

Diabetes mellitus (DM), a group of diseases characterized by defective glucose metabolism, is the most widespread metabolic disorder affecting over 400 million adults worldwide. This pathological condition has been implicated in the pathogenesis of a number of central encephalopathies and peripheral neuropathies. In further support of this notion, recent epidemiological evidence suggests a link between DM and Parkinson’s disease (PD), with hyperglycemia emerging as one of the culprits in neurodegeneration involving the nigrostriatal pathway, the neuroanatomical substrate of the motor symptoms affecting parkinsonian patients. Indeed, dopaminergic neurons located in the mesencephalic substantia nigra appear to be particularly vulnerable to oxidative stress and degeneration, likely because of their intrinsic susceptibility to mitochondrial dysfunction, which may represent a direct consequence of hyperglycemia and hyperglycemia-induced oxidative stress. Other pathological pathways induced by increased intracellular glucose levels, including the polyol and the hexosamine pathway as well as the formation of advanced glycation end-products, may all play a pivotal role in mediating the detrimental effects of hyperglycemia on nigral dopaminergic neurons. In this review article, we will examine the epidemiological as well as the molecular and cellular clues supporting the potential susceptibility of nigrostriatal dopaminergic neurons to hyperglycemia.
Mediating Effect of Sleep Quality on the Relationship Between Problematic Mobile Phone Use and Depressive Symptoms in College Students

Background and Aim: Problematic mobile phone use (PMPU) and depression are great public health concerns among adolescents. The aim of this study was to determine the association between PMPU and symptoms of depression, as well as the mediating role of sleep quality. Methods: A total of 4,624 college students participated in this study. The Self-rating Questionnaire for Adolescent Problematic Mobile Phone Use (SQAPMPU), Pittsburgh Sleep Quality Index (PSQI), and Patient Health Questionnaire-9 (PHQ-9) were administered to assess PMPU, sleep quality, and symptoms of depression. Mediation analysis was conducted using PROCESS macro in the SPSS software. Results: Of the participants, 27.5% were classified as PMPU, 44.9% exhibited symptoms of depression, and 15.6% reported sleep problems. Compared with those without PMPU, those with PMPU exhibited higher rates of sleep problems and depressive symptoms. The mediation analysis further revealed partial mediation effects of sleep quality on the association between PMPU and depression. Conclusions: This study demonstrated that PMPU was associated with mental health in college students, and sleep quality played a mediating role in this relationship. Our findings highlight the critical role of early intervention for depression with a focus on those with PMPU and, more specifically, on those with sleep problems.
Short Carbon Fiber Reinforced Polymers: Utilizing Lignin to Engineer Potentially Sustainable Resource-Based Biocomposites

Carbon fiber reinforced composites have exceptional potential to play a key role in the materials world of our future. However, their success undoubtedly depends on the extent they can contribute to advance a global sustainability objective. Utilizing polymers in these composites that can be potentially derived from biomasses would be certainly vital for next-generation manufacturing practices. Nevertheless, deep understanding and tailoring fiber-matrix interactions are crucial issues in order to design carbon fiber reinforced sustainable resource-based biocomposites. In this study, cellulose derivatives (cellulose propionate and cellulose acetate butyrate) are utilized as model polymer matrices that can be potentially fabricated from biomasses, and the mechanical properties of the prepared short carbon fiber reinforced composites are engineered by means of a functional biobased lignin coating on the fiber surface. Furthermore, polyamide 6 based composites are also prepared, the monomer of this polymer could be obtained using C6 sugars derived from lignocellulosic biomasses in the future (through 5-hydroxymethylfurfural). Lignin was successfully immobilized on the carbon fiber surface via an industrially scalable benign epoxidation reaction. The surface modification had a beneficial impact on the mechanical properties of cellulose propionate and polyamide 6 composites. Furthermore, our results also revealed that cellulose-based matrices are highly sensitive to the presence of rigid fiber segments that restrict polymer chain movements and facilitate stress development. It follows that the physicochemical properties of the cellulosic matrices (molecular weight, crystallinity), associated with polymer chain mobility, might need to be carefully considered when designing these composites. At the same time, polyamide 6 showed excellent ability to accommodate short carbon fibers without leading to a largely brittle material, in this case, a maximum tensile strength of ~136 MPa was obtained at 20 wt% fiber loading. These results were further contrasted with that of a petroleum-based polypropylene matrix exhibiting inferior mechanical properties. Our study clearly indicates that carbon fiber reinforced polymers derived and designed using biomass-derived resources can be promising green materials for a sustainable future.
Graph2Seq: Fusion Embedding Learning for Knowledge Graph Completion

Knowledge Graph (KG) usually contains billions of facts about the real world, where a fact is represented as a triplet in the form of (head entity, relation, tail entity). KG is a complex network and consists of numerous nodes (entities) and edges (relations). Given that most KGs are noisy and far from being complete, KG analysis and completion methods are becoming more and more important. Knowledge graph embedding (KGE) aims to embed entities and relations in a low dimensional and continuous vector space, which is proven to be a quite efficient and effective method in knowledge graph completion tasks. KGE models devise various kinds of score functions to evaluate each fact in KG, which assign high points for true facts and low points for invalid ones. In a KG of the real world, some nodes may have hundreds of links with other nodes. There is a wealth of information around an entity, and the surrounding information (i.e., the sub-graph structure information) of one entity can make a significant contribution to predicting new facts. However, many previous works including, translational approaches such as Trans(E, H, R, and D), factorization approaches such as DistMult, ComplEx, and other deep learning approaches such as NTN, ConvE, concentrate on rating each fact in an isolated and separated way and lack a specially designed mechanism to learn the sub-graph structure information of the entity in KG. To conquer this challenge, we leverage the information fusion mechanism (Graph2Seq) used in graph neural network which is specially designed for graph-structured data, to learn fusion embeddings for entities in KG. And a novel fusion embedding learning KGE model (referred as G2SKGE) which aims to learn the sub-graph structure information of the entity in KG is proposed. With empirical experiments on four benchmark datasets, our proposed model achieves promising results and outperforms the state-of-the-art models.
Association of GPx1 P198L and CAT C-262T Genetic Variations With Polycystic Ovary Syndrome in Chinese Women

Background: Oxidative stress plays an important role in the pathogenesis of polycystic ovary syndrome (PCOS). Glutathione peroxidase 1 (GPx1) and catalase (CAT) are the major intracellular antioxidant enzymes that can detoxify hydrogen peroxide into water, preventing cellular injury from reactive oxygen species. The aim of the present study was to investigate the association of GPx1 P198L (Pro198Leu, C559T, rs1050450) and CAT C-262T (rs1001179) genetic polymorphisms with the risk of PCOS and evaluate the effects of the genotypes on clinical, hormonal, metabolic and oxidative stress parameters in Chinese women. Methods: This is a case-control study of 654 patients with PCOS and 535 controls. The GPx1 P198L, CAT C-262T, and superoxide dismutase 2 (SOD2) A16V genotypes were determined by polymerase chain reaction amplification and restriction analysis. Clinical, hormonal, metabolic and oxidative stress parameters were also analyzed. Results: The frequencies of the PL + LL genotype (14.1 vs. 8.4%) and L allele (7.3 vs. 4.4%) of GPx1 P198L polymorphism were significantly higher in patients with PCOS than in control subjects. Genotype (PL + LL) remained a significant predictor for PCOS in prognostic models including age, body mass index (BMI), insulin resistance index, total cholesterol, triglycerides, high-density lipoprotein-cholesterol, and low-density lipoprotein-cholesterol as covariates (OR = 2.105, 95%CI: 1.330–3.331, P = 0.001). Patients carrying the L allele had relatively high average ovarian volume, waist circumference, and malondialdehyde levels (P < 0.07) compared with patients with the PP genotype. We also demonstrated that the subjects with both GPx1 L and SOD2 A alleles further increase the risk of PCOS compared with the individuals carrying the PP/VV genotype after adjusting for age and BMI (OR = 5.774, 95%CI: 2.243–14.863, P < 0.001). However, no significant differences were observed in the frequencies of the CAT C-262T genotypes and alleles between PCOS and control groups. Conclusions: The GPx1 P198L, but not CAT C-262T, genetic polymorphism is associated with the risk of PCOS in Chinese women.
Binary Theorizing Does Not Account for Action Control

Everyday thinking and scientific theorizing about human action control are equally driven by the apparently obvious contrast between will and habit or, in their more modern disguise: intentional and automatic processes, and model-based and model-free action planning. And yet, no comprehensive category system to systematically tell truly willed from merely habitual actions is available. As I argue, this is because the contrast is ill-conceived, because almost every single action is both willed and habitual, intentional and automatic, and model-based and model-free, simply because will and habit (and their successors) do not refer to alternative modes or pathways of action control but rather to different phases of action planning. I further discuss three basic misconceptions about action control that binary theorizing relies on: the assumption that intentional processes compete with automatic processes (rather than the former setting the stage for the latter), the assumption that action control is targeting processes (rather than representations of action outcomes), and the assumption that people follow only one goal at a time (rather than multiple goals). I conclude that (at least the present style of) binary theorizing fails to account for action control and should thus be replaced by a more integrative view.
Bone Mineral Density Loss in People With Epilepsy Taking Valproate as a Monotherapy: A Systematic Review and Meta-Analysis

Objective: Data on changes in bone mineral density (BMD) from valproate (VPA) therapy are ambiguous and conflicting. Thus, the aim of this study was to systematically review the existing data and carry out a meta-analysis to investigate the effect of VPA as a monotherapy on BMD in people with epilepsy (PWE). Methods: We systematically searched PubMed, EMBASE, and MEDLINE for eligible studies. We calculated the standardized mean difference (SMD) with 95% confidence interval (CI) to investigate the statistical power of the association between VPA treatment and BMD. Results: Nineteen studies were included in this systematic review and meta-analysis. We found that BMD was lower in the VPA group than in the control group (SMD: −0.44; 95% CI: −0.65 to −0.22). A significant association was found in adult patients (SMD: −0.57; 95% CI: −0.88 to −0.26; I2 = 69.8%) and pediatric patients (SMD: −0.32; 95% CI: −0.60 to −0.03; I2 = 67.8%) by subgroup analysis. This study indicated that BMD was significantly lower in patients treated for more than 36 months than in controls (SMD: −0.52; 95% CI: −0.76 to −0.27; I2 = 61.8%). However, a significant difference was not found between patients who were treated for less than 36 months and controls (SMD: −0.36; 95% CI: −0.72 to 0.01; I2 = 74.8%). Conclusion and significance: The present study provided evidence that VPA treatment was significantly associated with BMD loss in PWE. Thus, for patients at a high risk of osteoporosis and fracture, especially for patients who need long-term treatment, VPA may not be a good choice.
Acute Moderate-Intensity Exercise Generally Enhances Attentional Resources Related to Perceptual Processing

The present study aimed to investigate whether acute moderate-intensity exercise led to a selective effect on executive function tasks or general effect on cognitive tasks that involve executive function and basic information processing in young adults. Besides, we also aimed to examine acute exercise’s effect on multiple ERP components (e.g., P2, N2, P3b, and N450) to expand previous research. Seventy-two young adults were randomly assigned to the exercise or control groups. The Stroop task was administrated before and after treatments (exercise or reading), and the P2, N2, P3b, and N450 components of the Event-Related Potential (ERP) waveform were recorded and analyzed. Larger P2 amplitudes on both congruent and incongruent tasks were observed following acute exercise. Acute exercise did not influence accuracy or response time, and no effects on N2, P3b, and N450 components were found. These findings suggest that acute moderate-intensity exercise may have a generally beneficial effect on mobilization of attentional resources related to perceptual processing and exercise-related physiological arousal.