Search Results (1,807)

(1) Background: As a high-biomass cereal crop, maize provides substantial raw materials for food, animal feed, and processing industries. Plant root systems, vital for nutritional support, are directly vulnerable to diverse stressors that result in developmental abnormalities. Anthocyanins function as essential antioxidants, serving not only as natural pigments, but also playing crucial roles in plant stress resistance. As an essential plant hormone, jasmonic acid (JA) mediates plant stress adaptation and developmental processes, and is frequently employed to stimulate anthocyanin production. (2) Methods: Due to scarce reports on JA functions in maize, we specifically examined JA-triggered developmental regulation and anthocyanin biosynthesis using transcriptomic and metabolomic analysis. (3) Results: Phenotypic analyses revealed that exogenous JA application promoted culm development and intensified pigmentation, while enlarging the areas of stems and primary roots. Combined with phenotypic variations, our integrated transcriptomic and metabolomic analyses of root tissues also indicated that significantly altered metabolites specifically clustered within the flavonoid biosynthesis pathway. Moreover, GO and KEGG enrichment analyses of the associated differentially expressed genes confirmed their participation in this synthetic pathway with high confidence. These findings strongly suggest that methyl jasmonate (MeJA) exposure primarily modulates flavonoid biosynthesis, particularly through regulation of F3H and DFR gene expression, thereby enhancing flavonoid/anthocyanin accumulation in roots. Additionally, our correlation analysis of transcription factors revealed that Zm00001d018097 (MYB), Zm00001d029963 (MYB), and Zm00001d000236 (bHLH) likely participate in regulating the expression of structural genes, thereby promoting the upregulation of functional gene expression. (4) Conclusions: These results provide a robust framework for deciphering the MeJA-mediated regulation of anthocyanin biosynthesis in maize radicles, specifically demonstrating that Zm00001d018097 (MYB), Zm00001d029963 (MYB), and Zm00001d000236 (bHLH) coordinately enhance the expression of F3H and DFR. Full article

Reconstruction-based unsupervised detection methods have demonstrated strong generalization capabilities in the field of tablet anomaly detection, but there are still problems such as poor reconstruction effect and inaccurate positioning of abnormal areas. To address these problems, this paper proposes an unsupervised Diffusion-based Tablet Defect Detection (DTDD) method. This method uses an Assisted Reconstruction (AR) network to introduce original image information to assist in the reconstruction of abnormal areas, thereby improving the reconstruction effect of the diffusion model. It also uses a Scale Fusion (SF) network and an improved anomaly measurement method to improve the accuracy of abnormal area positioning. Finally, the effectiveness of the algorithm is verified on the tablet dataset. The experimental results show that the algorithm in this paper is superior to the algorithms in the same field, effectively improving the detection accuracy and abnormal positioning accuracy, and performing well in the tablet defect detection task. Full article

Low-voltage distribution area is the “last kilometer” connecting the distribution network and users, and the traditional distribution system is difficult to digitally manage in the low-voltage area, resulting in untimely and imprecise handling of voltage overruns, short-circuit outages, and other abnormal problems. With the deployment of smart meters, new sensors, smart gateways, and other devices in distribution areas, digital intelligent monitoring and management based on digital twins in LV distribution areas has gradually become the focus of distribution network research. In view of the profound changes that are taking place in the low-voltage distribution area, this paper first summarizes the characteristics and shortcomings of the existing digital twin research in the low-voltage distribution area, then puts forward the ‘6C’ development goals for the digital transformation of the low-voltage distribution area, introduces the practice work of Guangxi Power Grid Corporation around the ‘6C’ development goals in the low-voltage distribution area. Finally, the future research work of the ‘6C’ development goals for the digital transformation of the low-voltage distribution area is promising. Full article

Introduction: Learning disabilities (LD) compromise academic achievement in approximately 5–10% of school-aged children, yet the neurophysiological signatures that could facilitate earlier detection or stratification remain poorly defined. Resting-state electroencephalography (rs-EEG) offers millisecond resolution and is cost-effective, but its findings have never been synthesized systematically across pediatric LD cohorts. Methods: Following a PROSPERO-registered protocol (CRD420251087821) and adhering to PRISMA 2020 guidelines, we searched PubMed, Embase, Web of Science, Scopus, and PsycINFO through 31 March 2025 for peer-reviewed studies that recorded eyes-open or eyes-closed rs-EEG using ≥ 4 scalp electrodes in children (≤18 years) formally diagnosed with LD, and compared the results with typically developing peers or normative databases. Four reviewers independently screened titles and abstracts, extracted data, and assessed the risk of bias using ROBINS-I. Results: Seventeen studies (704 children with LD; 620 controls) met the inclusion criteria. The overall risk of bias was moderate, primarily due to small clinic-based samples and inconsistent control for confounding variables. Three consistent electrophysiological patterns emerged: (i) a 20–60% increase in delta/theta power over mesial-frontal, fronto-central and left peri-Sylvian cortices, resulting in markedly elevated θ/α and θ/β ratios; (ii) blunting or anterior displacement of the posterior alpha rhythm, particularly in language-critical temporo-parietal regions; and (iii) developmentally immature connectivity, characterized by widespread slow-band hypercoherence alongside hypo-connected upper-alpha networks linking left-hemisphere language hubs to posterior sensory areas. These abnormalities were correlated with reading, writing, and IQ scores and, in two longitudinal cohorts, they partially normalized in parallel with academic improvement. Furthermore, a link between reduced posterior/overall alpha and neuroinflammation has been found. Conclusions: Rs-EEG reveals a robust yet heterogeneous electrophysiological profile of pediatric LD, supporting a hybrid model that combines maturational delay with persistent circuit-level atypicalities in some children. While current evidence suggests that rs-EEG features show promise as potential biomarkers for LD detection and subtyping, these findings remain preliminary. Definitive clinical translation will require multi-site, dense-array longitudinal studies employing harmonized pipelines, integration with MRI and genetics, and the inclusion of EEG metrics in intervention trials. Full article

Diastolic heart failure, also referred to as heart failure with preserved ejection fraction (HFpEF), is a complex cardiovascular clinical syndrome that is a growing health burden worldwide. Patients present with high abnormal left ventricular filling pressures but normal ejection fraction that can progress to diastolic heart failure and death. The causes of diastolic dysfunction are varied, and pharmacotherapies are limited to managing the symptoms of the disease. At the level of the myocyte, cytoskeletal disarray and mitochondrial dysfunction are common features associated with diastolic disease. Understanding the mechanisms of abnormal diastolic filling pressures is necessary to identify novel treatments, which remains an area of significant unmet need. In this article, we discuss the mechanisms of maladaptive feedback contributing to increased extracellular stiffness, cytoskeletal disarray, and mitochondrial dysfunction in diastolic heart failure. Since the mechanisms are complex, understanding the contributing factors provides opportunities for the development of novel drug targets. These will be discussed and examined in the context of current therapy. Full article

Polycystic ovary syndrome (PCOS) is an endocrine and metabolic disorder characterized by a clinical and/or biochemical hyperandrogenism. In addition, PCOS is also associated with the presence of ovarian cysts, anovulation, and menstrual abnormalities such as oligomenorrhea or amenorrhea. The aetiology of the syndrome is multifactorial and heterogeneous due to the interaction of genetic, hormonal, metabolic, and environmental factors, as well as the different phenotypes and responses to treatments exhibited by the patients. Considering this complex interaction, it is essential to continue with the research focused on the mechanisms involved in the development and maintenance of the pathology. The alteration in the pulsatile secretion of the gonadotropin-releasing hormone (GnRH) is considered to be one of the main causes that contributes to its onset. In this review, we discuss recent evidence about the role of the rostral periventricular area of the third ventricle (RP3V), the arcuate nucleus (ARC), and the ventromedial nucleus of the hypothalamus (VMH), key hypothalamic regions that regulate GnRH secretion, in the development of PCOS. In addition, we analyse the clinical, metabolic, and endocrine factors that interact in the patients with PCOS, offering a multifactorial perspective to improve our understanding of this disorder. Full article

Background: Left ventricular (LV) non-compaction (NC) is a rare ventricular phenotype characterized by a thin compacted epicardial layer and an extensive non-compacted endocardial layer with prominent LV trabeculations and deep intertrabecular recesses. According to the recent literature, no information is available regarding the abnormalities of the aortic valve annulus (AVA) in LVNC. Therefore, the aim of the present study was to perform a detailed analysis of the AVA by three-dimensional speckle-tracking echocardiography (3DSTE) in LVNC patients and to compare the findings with matched healthy controls. Methods: The present study comprised 21 isolated LVNC patients, from which 9 cases were excluded due to inferior image quality. The remaining group consisted of 12 patients with isolated LVNC (mean age: 54.6 ± 13.6 years, 7 males). Jenni’s echocardiography criteria served as a definition of LVNC. The 12 patients’ results were compared to 38 healthy age- and gender-matched controls (mean age: 48.2 ± 8.0 years, 19 males). Subgroups of patients having a greater end-diastolic versus end-systolic AVA area were also compared. Results: Most of AVA dimensions did not differ significantly between LVNC patients and controls; however, most LVNC patients showed a larger end-diastolic AVA area (9 out of 12, 75%), which was a significantly larger ratio as seen in matched controls (11 out of 38, 29%, p < 0.05). Aortic valve annular plane systolic excursion (AAPSE) proved to be significantly reduced in all LVNC patients (1.12 ± 0.24 cm vs. 0.78 ± 0.28 cm, p < 0.05) and in LVNC subjects with a greater end-diastolic AVA area (1.11 ± 0.21 cm vs. 0.72 ± 0.21 cm, p < 0.05). Basal LV radial (RS) and longitudinal (LS) strains were reduced in healthy adults with a greater end-diastolic AVA area as compared to cases with a greater end-systolic AVA area. In LVNC, not only basal LV-RS and LV-LS, but also LV circumferential strain (CS) proved to be reduced regardless of whether the AVA was greater in end-diastole or in end-systole. Conclusions: In patients with isolated LVNC, the AVA is not dilated; however, the presence of a greater end-diastolic AVA area is observed more frequently than in healthy controls. AAPSE and basal LV-RS, LV-LS and LV-CS values are significantly reduced in LVNC irrespective of whether the end-systolic or end-diastolic AVA area is greater. Full article

Background/Objectives: The aortic valve has a prominent role in regulating blood flow and is of exceptional importance in clinical cardiological practice, as it can be affected by numerous abnormalities, so any clinical study that examines its physiological properties may be of significance. It is known that the dimensions of the aortic valve annulus (AVA) not only change during the cardiac cycle, but also undergo spatial displacement. Considering this, the question arises as to whether the AVA’s dimensions and their spatial displacement, represented by aortic annular plane systolic excursion (AAPSE), are related or not. Therefore, these parameters were simultaneously assessed using three-dimensional speckle-tracking echocardiography (3DSTE) in healthy adults. Methods: The present study’s cohort consisted of 148 healthy adults (mean age: 34.8 ± 12.4 years, 80 men). In all cases, two-dimensional Doppler echocardiography and 3DSTE were performed, the latter being used to assess the aortic valve. Results: In all subjects, end-diastolic and end-systolic AVA dimensions showed no association with an increase in AAPSE. In subjects with a greater end-diastolic AVA area (AVA-A), end-systolic AVA dimensions tended to decrease with increasing AAPSE; this trend reached statistical significance for end-systolic minimum AVA diameter, when comparing participants with AAPSE below versus above the mean. With increasing end-diastolic AVA-A, all other AVA parameters increased accordingly in all subjects and regardless of which AVA-A proved to be greater. In all subjects, and in those with a greater end-systolic AVA-A, the AAPSE proved to be similar regardless of the size of the end-diastolic AVA-A. In cases with a greater end-diastolic AVA-A, only one subject showed a very small end-diastolic AVA-A. With increasing end-systolic AVA-A, all other AVA dimensions were increased in all subjects and in cases with a greater end-diastolic or end-systolic AVA-A. AAPSE showed no significant differences between the subgroups examined, although it tended to be lower in cases with a greater end-diastolic AVA-A and the largest end-systolic AVA-A, and in subjects with a greater end-systolic AVA-A and the smallest end-systolic AVA-A. Moreover, individuals with a greater end-diastolic AVA-A and the smallest end-systolic AVA-A had a tendency for increased AAPSE. No correlations were present between AVA dimensions and AAPSE. Conclusions: 3DSTE-derived AVA dimensions showed no obvious associations with AAPSE in the same healthy adults. Full article

Thirst is usually characterized as an unpleasant sensation provoking drinking of water. The purpose of the present review is to draw attention to the importance of thirst in overall regulation of body fluid homeostasis in health and pathology. Intensity of thirst is determined by signals generated in multiple groups of osmosensitive neurons engaged in dipsogenic and antidipsogenic activities, which are located in the brain cortex, the insula, the amygdala, the median preoptic area, the hypothalamic nuclei and the organum vasculosum laminae terminalis. Water ingestion is also influenced by signals generated in the cardiovascular system, the gastrointestinal system, the pancreas, the liver and the kidney and by changes of body temperature. Regulation of thirst engages the autonomic nervous system and several neuroactive factors synthetized in the brain and the peripheral organs. Among them are components of the renin–angiotensin system, vasopressin, atrial natriuretic peptide, cholecystokinin, ghrelin, gaseous transmitters, cytokines and prostaglandins. Experimental studies provide evidence that elevation of fluid osmolality, which is the most frequent cause of thirst, influences function of the voltage-gated sodium channel and calcium-dependent kinase II subunit alpha. Regulation of thirst may be inappropriate in old age and under some pathological conditions including infections, heart failure, diabetes insipidus, diabetes mellitus, and psychogenic disorders. The molecular background of the abnormal regulation of thirst in the clinical disorders is not yet sufficiently recognized and requires further examination. Full article

Internal conductive defects in composite insulators severely degrade their insulation performance and are considered concealed defects, posing a significant threat to the safe and stable operation of the power grid. Focusing on this issue, this study develops an electro-thermal multi-physical field simulation model and uses finite element analysis to investigate the electric field distribution and temperature rise characteristics. Composite insulator specimens with varying defect lengths were fabricated using the electrical erosion test. Charged tests were then conducted on these defective specimens, as well as on field-decommissioned specimens. The impact of internal conductive defects on the infrared, ultraviolet, and electric field distribution characteristics of composite insulators during operation was analyzed. The results indicate that the surface electric field of composite insulators with internal conductive defects becomes highly concentrated along the defect path, with a significant increase in electric field strength at the defect’s end. The maximum field strength migrates toward the grounded end as the defect length increases. Conductive defects lead to partial discharge and abnormal temperature rise at the defect’s end and the bending points of the composite insulator. The temperature rise predominantly manifests as “bar-form temperature rise,” with temperature rise regions correlating well with discharge areas. Conductive defects accelerate the decay-like degradation process of composite insulators through a positive feedback loop formed by the coupling of electric field distortion, Joule heating, material degradation, and discharge activity. This study identifies the key characteristics of electrical and temperature rise changes in insulators with conductive defects, reveals the deterioration evolution process and degradation mechanisms of insulators, and provides effective criteria for on-site diagnosis of conductive defects. Full article

Background/Objectives: The rapid development of artificial intelligence is transforming the face of medicine. Due to the large number of imaging studies (pre-, intra-, and postoperative) combined with histopathological and molecular findings, its impact may be particularly significant in neurosurgery. We aimed to perform a scoping review of recent applications of deep learning in MRI-based diagnostics of brain tumors relevant to neurosurgical practice. Methods: We conducted a systematic search of scientific articles available in the PubMed database. The search was performed on 22 April 2024, using the following query: ((MRI) AND (brain tumor)) AND (deep learning). We included original studies that applied deep-learning methods to brain tumor diagnostics using MRI, with potential relevance to neuroradiology or neurosurgery. A total of 893 records were retrieved, and after title/abstract screening and full-text assessment by two independent reviewers, 229 studies met the inclusion criteria. The study was not registered and received no external funding. Results: Most included articles were published after 1 January 2022. The studies primarily focused on developing models to differentiate between specific CNS tumors. With improved radiological analysis, deep-learning technologies can support surgical planning through enhanced visualization of cerebral vessels, white matter tracts, and functional brain areas. Over half of the papers (52%) focused on gliomas, particularly their detection, grading, and molecular characterization. Conclusions: Recent advancements in artificial intelligence methods have enabled differentiation between normal and abnormal CNS imaging, identification of various pathological entities, and, in some cases, precise tumor classification and molecular profiling. These tools show promise in supporting both diagnosis and treatment planning in neurosurgery. Full article

Background: Electrocardiograms (EKGs) are essential tools in emergency medicine, often used to evaluate chest pain, dyspnea, and other symptoms suggestive of cardiac dysfunction. Yet, EKGs are not universally administered to all emergency department (ED) patients. Understanding and predicting which patients receive an EKG may offer insights into clinical decision making, resource allocation, and potential disparities in care. This study examines whether integrating structured clinical data with free-text patient narratives can improve prediction of EKG utilization in the ED. Methods: We conducted a retrospective observational study to predict electrocardiogram (EKG) utilization using data from 13,115 adult emergency department (ED) visits in the nationally representative 2021 National Hospital Ambulatory Medical Care Survey–Emergency Department (NHAMCS-ED), leveraging both structured features—demographics, vital signs, comorbidities, arrival mode, and triage acuity, with the most influential selected via Lasso regression—and unstructured patient narratives transformed into numerical embeddings using Clinical-BERT. Four supervised learning models—Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF) and Extreme Gradient Boosting (XGB)—were trained on three inputs (structured data only, text embeddings only, and a late-fusion combined model); hyperparameters were optimized by grid search with 5-fold cross-validation; performance was evaluated via AUROC, accuracy, sensitivity, specificity and precision; and interpretability was assessed using SHAP values and Permutation Feature Importance. Results: EKGs were administered in 30.6% of adult ED visits. Patients who received EKGs were more likely to be older, White, Medicare-insured, and to present with abnormal vital signs or higher triage severity. Across all models, the combined data approach yielded superior predictive performance. The SVM and LR achieved the highest area under the ROC curve (AUC = 0.860 and 0.861) when using both structured and unstructured data, compared to 0.772 with structured data alone and 0.823 and 0.822 with unstructured data alone. Similar improvements were observed in accuracy, sensitivity, and specificity. Conclusions: Integrating structured clinical data with patient narratives significantly enhances the ability to predict EKG utilization in the emergency department. These findings support a personalized medicine framework by demonstrating how multimodal data integration can enable individualized, real-time decision support in the ED. Full article

Background: HIV-associated neurocognitive disorders (HANDs) continue to be a significant concern, despite the advancements in prognosis achieved through Combination Antiretroviral Therapy (cART). Neuropsychological assessment, recommended by international guidelines for HANDs diagnosis, can be resource-intensive. Brief screening tools, like the International HIV Dementia Scale (IHDS) and the Montreal Cognitive Assessment (MoCA), are crucial in facilitating initial evaluations. This study aims to assess the Italian IHDS (IHDS-IT) and evaluate its sensitivity and specificity in detecting cognitive impairment in HIV patients. Methods: This cross-sectional study involved 294 patients aged ≥30 years, evaluated at the Immunology Unit of the University of Cagliari. Cognitive function was assessed using the MoCA and IHDS. Laboratory parameters, such as CD4 nadir, current CD4 count, and HIV-RNA levels, were also collected. Statistical analyses included Spearman’s correlation, Receiver Operating Characteristic analysis, and the Youden J statistic to identify the optimal IHDS-IT cut-off for cognitive impairment detection. Results: The IHDS and MoCA scores showed a moderate positive correlation (Spearman’s rho = 0.411, p < 0.0001). ROC analysis identified an IHDS-IT cut-off of ≤9, yielding an Area Under the Curve (AUC) of 0.76, sensitivity of 71.7%, and specificity of 67.2%. At this threshold, 73.1% of patients with MoCA scores below 23 also presented abnormal IHDS scores, highlighting the complementary utility of both cognitive assessment instruments. Conclusions: The IHDS-IT exhibited fair diagnostic accuracy for intercepting cognitive impairment, with a lower optimal cut-off than previously reported. The observed differences may reflect this study cohort’s demographic and clinical characteristics, including advanced age and long-lasting HIV infection. Further, longitudinal studies are necessary to validate these findings and to confirm the proposed IHDS cut-off over extended periods. Full article

Magnetic parameters of river sediments are commonly used as end-members for source tracing in the coasts and shelves. The eastern continental shelf area of China, with multiple sources of input, is a key region for discussing sediment sources. However, magnetic parameters are influenced by grain size, and the nature of this influence remains unclear. In this study, the Jiulong River was selected as a case to analyze the magnetic parameters and mineral characteristics for both the coarse (>63 μm) and fine-grained (<63 μm) fractions. Results show that the magnetic minerals mainly contain detrital-sourced magnetite and hematite. In the North River, a tributary of the Jiulong River, the content of coarse-grained magnetic minerals increases from upstream to downstream, contrary to fine-grained magnetic minerals, suggesting the influence of hydrodynamic forces. Some samples with abnormally high magnetic susceptibility may result from the combined influence of the parent rock and human activities. In the scatter diagrams of magnetic parameters for provenance tracing, samples of the <63 μm fractions have a more concentrated distribution than that of the >63 μm fractions. Hence, magnetic parameters for the <63 μm fraction are more useful in provenance identification. Full article

Background and Clinical Significance: The term “boomerang sign” refers to a boomerang-shaped area of cytotoxic edema in the splenium of the corpus callosum. It is seen as hyperintense lesions on T2-weighted images, FLAIR and DWI in MRI. No specific pathomechanism leading to these changes in the splenium have been yet found; however, authors have listed a variety of potential causes. Case Presentation: The case presents a 38-year-old male patient after left cerebellopontine angle tumor resection with an abnormal, increased signal intensity within the corpus callosum (boomerang sign) in FLAIR MRI sequence. In the case of our patient, unlike the patients described in the literature, the changes in the commissure persist. Conclusions: These lesions could be caused by several factors such as the development of cerebellar edema and subarachnoid bleeding or hypertonic salt usage while in the intensive care unit. Full article