Abnormal static and dynamic functional network connectivity of the whole-brain in children with generalized tonic-clonic seizures

IntroductionGeneralized tonic-clonic seizures (GTCS) are a subtype of generalized seizures exhibiting bursts of bilaterally synchronous generalized spike-wave discharges. Numerous neuroimaging studies have reported aberrant functional activity and topological organization of brain network in epilepsy patients with GTCS, but most studies have focused on adults. However, the effect of GTCS on the spatial and temporal properties of brain function in children remains unclear. The present study aimed to explore whole-brain static (sFC) and dynamic functional connectivity (dFC) in children with GTCS.MethodsTwenty-three children with GTCS and 32 matched healthy controls (HCs) were recruited for the present study. Resting-state functional magnetic resonance imaging (MRI) data were collected for each subject. The group independent component analysis method was used to obtain independent components (ICs). Then, sFC and dFC methods were applied and the differences in functional connectivity (FC) were compared between the children with GTCS and the HCs. Additionally, we investigated the correlations between the dFC indicators and epilepsy duration.ResultsCompared to HCs, GTCS patients exhibited a significant decrease in sFC strengths among most networks. The K-means clustering method was implemented for dFC analysis, and the optimal number of clusters was estimated: two discrete connectivity configurations, State 1 (strong connection) and State 2 (weak connection). The decreased dFC mainly occurred in State 1, especially the dFC between the visual network (VIS) and somatomotor network (SMN); but the increased dFC mainly occurred in State 2 among most networks in GTCS children. In addition, GTCS children showed significantly shorter mean dwell time and lower fractional windows in stronger connected State 1, while GTCS children showed significantly longer mean dwell time in weaker connected State 2. In addition, the dFC properties, including mean dwell time and fractional windows, were significantly correlated with epilepsy duration.ConclusionOur results indicated that GTCS epilepsy not only alters the connectivity strength but also changes the temporal properties of connectivity in networks in the whole brain. These findings also emphasized the differences in sFC and dFC in children with GTCS. Combining sFC and dFC methods may provide more comprehensive understanding of the abnormal changes in brain architecture in children with GTCS

Atypical neurological manifestations in anti-IgLON5 disease: a case report

Anti-IgLON5 disease is a recently discovered autoimmune encephalopathy with sleep disorder as a hallmark in the majority of reported cases. Additional neurological manifestations include bulbar dysfunction, gait problems, movement disorders, oculomotor abnormalities, and hyperexcitability of the nervous system. At present, an increasing number of publications have dealt with the course and possible treatment options for anti-IgLON5 disease, and its clinical spectrum has expanded wider and more heterogeneous. Here, we report a case of a 66-year-old female with cognitive impairment accompanied by slow reaction, impaired memory, and decreased orientation. A positive cerebral MRI change and serum and cerebrospinal fluid (CSF) antibodies against IgLON5 were found during the diagnostic course. Subsequently the patient received immunotherapy and was generally in good health with no new symptoms during follow-up. Early testing for IgLON5 antibodies should be considered in patients with atypical neurological symptoms such as cognitive impairment, slow reaction, or decreased orientation. In clinical practice, immunotherapy should be considered in all cases of anti-IgLON5 encephalopathies

Changes and Trend Disparities in Life Expectancy and Health-Adjusted Life Expectancy Attributed to Disability and Mortality From 1990 to 2019 in China

ObjectiveThis study aims to investigate sex, age, and cause-specific contributions to changes and trend disparities in life expectancy (LE) and health-adjusted life expectancy (HALE) attributed to disability and mortality from 1990 to 2019 in China, which provides insight into policy-making, health systems planning, and resource allocation.MethodsContributions of disability and mortality to changes and trend disparities in LE and HALE were estimated with standard abridged life table, Sullivan's method, and decomposition method, using retrospective demographic analysis based on mortality and years lived with disability (YLD) rates extracted from Global Burden of Disease Study 2019 (GBD 2019).ResultsFrom 1990 to 2019, LE and HALE increased by 10.49 and 8.71 years for both sexes, mainly due to noncommunicable diseases (NCDs) (5.83 years, 55.58% for LE and 6.28 years, 72.10% for HALE). However, HIV/AIDS and sexually transmitted infections had negative effects on changes in LE (−0.03 years, −0.29%) and HALE (−0.05 years, −0.57%). Lung cancer and ischemic heart disease caused the biggest reduction in LE (−0.14 years, −1.33%) and HALE (−0.42 years, −4.82%). Also, cardiovascular diseases (−0.08 years, −0.92%), neurological disorders (−0.08 years, −0.92%), diabetes and kidney diseases (−0.06 years, −0.69%), and transport injuries (−0.06 years, −0.69%) had main negative disability effects in HALE. Moreover, life expectancy lived with disability (LED) increased by 1.78 years, mainly attributed to respiratory infections and tuberculosis (1.04 years, 58.43%) and maternal and neonatal disorders (0.78 years, 43.82%).ConclusionThe LE and HALE in China have grown rapidly over the past few decades, mainly attributed to NCDs. It is necessary to further reduce the negative mortality effect of HIV/AIDS, lung cancer, colon and rectum cancer, pancreatic cancer, and ischemic heart disease and the negative disability effect of stroke, diabetes mellitus, and road injuries. In addition, the signs of disparities in mortality and disability of different sexes and ages call for targeted and precise interventions for key groups such as males and the elderly. According to the decomposition results, we may better determine the key objects of health policies that take into account substantial cause-specific variations to facilitate the realization of “healthy China 2030” plan

A seven-gene signature predicts overall survival of patients with colorectal cancer

Colorectal cancer (CRC) is a major cause of global cancer mortality. Gene expression profiles can help predict prognosis of patients with CRC. In most of previous studies, disease recurrence was analyzed as the survival endpoint. Thus we aim to build a robust gene signature for prediction of overall survival (OS) in patients with CRC. Fresh frozen CRC tissues from 64 patients were analyzed using Affymetrix HG-U133plus 2.0 gene arrays. By performing univariate survival analysis, 6487 genes were found to be associated with the OS in our cohort. KEGG analysis revealed that these genes were mainly involved in pathways such as endocytosis, axon guidance, spliceosome, Wnt signalling and ubiquitin mediated proteolysis. A seven-gene signature was further selected by a robust likelihood-based survival modelling approach. The prognostic model of seven-gene signature (NHLRC3, ZDHHC21, PRR14L, CCBL1, PTPRB, PNPO, and PPIP5K2) was constructed and weighted by regression coefficient, which divided patients into high- and low-risk groups. The OS for patients in high-risk group was significantly poorer compared with patients in low-risk group. Moreover, all seven genes were found to be differentially expressed in CRC tissues as compared with adjacent normal tissues, indicating their potential role in CRC initiation and progression. This seven-gene signature was further validated as an independent prognostic marker for OS prediction in patients with CRC in other two independent cohorts. In short, we developed a robust seven-gene signature that can predict the OS for CRC patients, providing new insights into identification of CRC patients with high risk of mortality

Observation of short-lived local polar states induced by applied tip biases in BaTiO3-based relaxor ferroelectric ceramics

Using piezoresponse force microscopy imaging and spectroscopy methods, surface polar states induced by applied tip biases in the ergodic/paraelectric phase of a BaTiO3-based relaxor ferroelectric ceramic have been observed. The induced polar state appears to be short-lived (typical lifetime only a few seconds) and dependent on the voltages applied and their duration. The observed piezoresponse hysteresis and relaxation behavior is primarily interpreted with respect to the picture of the polar nano-region dynamics, as proposed for lead-based relaxors. Spatially resolved piezoresponse relaxation mapping reveals the presence of sub-micron correlated features, presumably due to A-site chemical inhomogeneity as supported by site-correlated elemental mapping microanalysis.Q.L., Y.L., and R.L.W., acknowledge the support of the Australian Research Council (ARC) in the form of ARC Discovery Grants. Y.L. also acknowledges support from the ARC Future Fellowships Program

2-(2-Fur­yl)-1H-imidazo[4,5-f][1,10]phenanthroline-3,7-diium dichloride monohydrate

The organic cation of the title salt, C17H12N4O2+·2Cl−·H2O, is nearly planar, the dihedral angle between two pyridine rings being 2.53 (16)° and that between the pyridinum and furan rings being 4.17 (19)°. Mol­ecules are linked via N—H⋯O, N—H⋯Cl and O—H⋯Cl hydrogen bonds, forming a three-dimensional framework and π–π stacking inter­actions help to stabilize the crystal structure [the imidazole–pyridine and imidazole–benzene centroid–centroid distances are 3.501 (3) and 3.674 (3) Å; respectively]

ChatGraph: Chat with Your Graphs

Graph analysis is fundamental in real-world applications. Traditional approaches rely on SPARQL-like languages or clicking-and-dragging interfaces to interact with graph data. However, these methods either require users to possess high programming skills or support only a limited range of graph analysis functionalities. To address the limitations, we propose a large language model (LLM)-based framework called ChatGraph. With ChatGraph, users can interact with graphs through natural language, making it easier to use and more flexible than traditional approaches. The core of ChatGraph lies in generating chains of graph analysis APIs based on the understanding of the texts and graphs inputted in the user prompts. To achieve this, ChatGraph consists of three main modules: an API retrieval module that searches for relevant APIs, a graph-aware LLM module that enables the LLM to comprehend graphs, and an API chain-oriented finetuning module that guides the LLM in generating API chains