Dynamic mechanism of epileptic seizures induced by excitatory pyramidal neuronal population

The pyramidal neuronal population (PY) in the cerebral cortex is closely related to epilepsy, while the excitability of PY is directly affected by the excitatory interneurons (EIN), the inhibitory interneurons (IN), and the thalamic relay nucleus (TC). Based on this, we use the thalamocortical neural field model to explore the dynamic mechanism of system transition by taking the synaptic connection strengths of the above three nuclei on PY as the main factor affecting seizures. The results show that the excitatory effects of EIN on PY induce transitions from 1-spike and wave discharges (SWDs) to 2-spike and wave discharges (2-SWDs), the inhibitory effects of IN on PY induce transitions from saturated state to tonic oscillation state, and the excitatory effects of TC on PY induce transitions from clonic oscillation state to saturated state. According to the single-parameter bifurcation analysis, it is found that Hopf and fold limit cycle bifurcations are the key factors leading to the state transition. In addition, the state analysis of the three pathways is carried out in pairs. The results show that the system produces more types of epileptic seizures with the combined action of EIN and TC on PY. According to the two-parameter bifurcation curve, we obtain the stable parameter areas of tonic-clonic oscillations, SWDs, 2-SWDs and saturated discharges, and clearly find the reasonable transition path between tonic-clonic seizures and absence seizures. This may provide some theoretical guidance for the transmission and evolution of seizures

Estructura de la comunidad bacteriana en sedimentos de manglares en relación a variables medioambientales mediante análisis de fragmentos del gen 16S rRNA y electroforesis en geles desnaturalizantes

Bacterial community structure and the relationship between environmental variables and microbial communities in the surface sediments of tropical mangrove ecosystems were investigated in Sanya, Hainan Island, China. Profiles of bacterial communities were generated using culture-independent PCR-denaturing gradient gel electrophoresis (DGGE), and the results were interpreted with multivariate statistical analysis. Findings suggested that microbial communities varied with sample collection sites and seasons. The samples collected from the same sample sites at the same time had more similar microbial communities except samples SH3 and AB5, which also had unique sediment quality. Canonical correspondence analysis (CCA) revealed that the organic carbon concentration of the sediments accounted for a significant amount of the variability in the bacterial community composition. Phylogenetic analysis was used to identify the major groups of the predominant bacterial phylotypes. 16S rRNA gene-V3 fragments from 17 individual DGGE bands were sequenced and the corresponding bacteria were found in mangrove sediments for the first time based on BLAST results. Predominant bacterial phylotypes clustered with various taxonomic groups, including Proteobacteria, Bacteroidetes, Gemmatimonadetes, Actinobacteria and Firmicutes.La estructura de la comunidad bacteriana y la relación entre variables ambientales y las comunidades microbianas de la superficie de sedimentos de los ecosistemas tropicales de manglares fueron investigados en Sanya, Hainan Island, China. Los perfiles de las comunidades bacterianas fueron obtenidos utilizando electroforesis de gradiente de gel desnaturalizante (DGE), cultivo-independiente, y los resultados fueron interpretados con un análisis estadístico multivariante. Los resultados sugerían que las comunidades microbianas variaban con los lugares de muestreo y las estaciones. Las muestras recogidas en el mismo lugar de muestreo y al mismo tiempo tenían comunidades microbianas similares, excepto las muestras SH3 y AB5, que tenían diferente calidad de sedimentos. El análisis de correspondencia (CCA) mostró que la concentración de carbono orgánico en sedimentos explicaba una parte importante de la variabilidad en la composición de la comunidad bacteriana. Los análisis filogenéticos fueron usados para identificar los grupos más importantes de filotipos predominantes de bacterias. Se secuenciaron fragmentos 16 rRNA gene-V3 de 17 bandas individuales de DGE y las bacterias correspondientes fueron encontradas por primera vez en sedimentos de manglares en base a resultados de BLAST. Los filotipos de bacterias predominantes se agrupaban con varios grupos taxonómicos que incluyen Proteobacteria, Bacteroidetes, Gemmatimonadetes, Actinobacteria y Firmicutes

Modeling Studies of Gravity Wave Dynamics in Highly Structured Environments: Reflection, Trapping, Instability, Momentum Transport, Secondary Gravity Waves, and Induced Flow Responses

A compressible numerical model is applied for three-dimensional (3-D) gravity wave (GW) packets undergoing momentum deposition, self-acceleration (SA), breaking, and secondary GW (SGW) generation in the presence of highly-structured environments enabling thermal and/or Doppler ducts, such as a mesospheric inversion layer (MIL), tidal wind (TW), or combination of MIL and TW. Simulations reveal that ducts can strongly modulate GW dynamics. Responses modeled here include reflection, trapping, suppressed transmission, strong local instabilities, reduced SGW generations, higher altitude SGW responses, and induced large-scale flows. Instabilities that arise in ducts experience strong dissipation after they emerge, while trapped smaller-amplitude and smaller-scale GWs can survive in ducts to much later times. Additionally, GW breaking and its associated dynamics enhance the local wind along the GW propagation direction in the ducts, and yield layering in the wind field. However, these dynamics do not yield significant heat transport in the ducts. The failure of GW breaking to induce stratified layers in the temperature field suggests that such heat transport might not be as strong as previously assumed or inferred from observations and theoretical assessments. The present numerical simulations confirm previous finding that MIL generation may not be caused by the breaking of a transient high-frequency GW packet alone

Classification of knee osteoarthritis based on quantum-to-classical transfer learning

Quantum machine learning takes advantage of features such as quantum computing superposition and entanglement to enable better performance of machine learning models. In this paper, we first propose an improved hybrid quantum convolutional neural network (HQCNN) model. The HQCNN model was used to pre-train brain tumor dataset (MRI) images. Next, the quantum classical transfer learning (QCTL) approach is used to fine-tune and extract features based on pre-trained weights. A hybrid quantum convolutional network structure was used to test the osteoarthritis of the knee dataset (OAI) and to quantitatively evaluate standard metrics to verify the robustness of the classifier. The final experimental results show that the QCTL method can effectively classify knee osteoarthritis with a classification accuracy of 98.36%. The quantum-to-classical transfer learning method improves classification accuracy by 1.08%. How to use different coding techniques in HQCNN models applied to medical image analysis is also a future research direction

Thermo-Responsive Molecularly Imprinted Hydrogels for Selective Adsorption and Controlled Release of Phenol From Aqueous Solution

In this study, thermo-responsive molecularly imprinted hydrogels (T-MIHs) were developed as an effective potential adsorbent for selectively adsorption phenol from wastewater. During the process, N-isopropyl acrylamide (NIPAm) was used as thermal responsive monomer. The obtained materials were characterized in detail by fourier transform infrared (FT-IR) spectrometer, scanning electron microscope (SEM), and thermo gravimetric analysis (TGA). A series of static adsorption studies were performed to investigate the kinetics, specific adsorption equilibrium, and selective recognition ability of phenol. Reversible adsorption and release of phenol were realized by changing temperatures. Three type of phenols, namely 3-chlorophenols (3-CP), 2,4-dichlorophenol (2,4-DCP), and 2,4,6-trichlorophenol (2,4,6-TCP) were selected as model analytes to evaluate the selective recognition performance of T-MIHs. The T-MIHs have good selectivity, temperature response, and reusability, making them ideal in applying in the controlled separation and release of phenol pollutants

Analysis of single-cell RNAseq identifies transitional states of T cells associated with hepatocellular carcinoma

BACKGROUND: Exhausted T cells and regulatory T cells (Tregs) comprise diverse subsets of tumor immunosuppressive microenvironment that play key roles in tumor progress. Understanding subset diversity in T cells is a critical question for developing cancer immunotherapy. METHODS: A total of 235 specimens from surgical resections of hepatocellular carcinoma (HCC) patients were examined for infiltration of exhausted T cell (Tex) in tumor and adjacent tissue. We conducted deep single-cell targeted immune profiling on CD3 RESULTS: We observed transitional differentiation of exhausted CD8 CONCLUSIONS: T cell exhaustion is a progressive process, and the gene-expression profiling displayed T cell exhaustion and anergy are different. Accordingly, it is possible that functional exhaustion is caused by the combination effects of passive defects and overactivation in stress response. The results help to understand the dynamic framework of T cells function in cancer which is important for designing rational cancer immunotherapies

Overexpressed transferrin receptor implied poor prognosis and relapse in gastrointestinal stromal tumors

Ferroptosis, as a novel-induced programmed cell death, plays critical roles in the pathogenesis of cancers. However, the promising biomarkers of ferroptosis in gastrointestinal stromal tumor (GIST) remain to be elucidated. Herein, the expression of ferroptosis-related genes was analyzed in GIST. Among the 64 ferroptosis-related genes, transferrin receptor (TFRC) expression presented a remarkable upregulation in high-risk patients through Gene Expression Omnibus (GEO) dataset analysis, as well as its significant change after imatinib was treated. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of TFRC-relevant genes revealed that TFRC expression was closely associated with cell growth pathways and metabolism-related pathways. Furthermore, patients at high risk of recurrence were more likely to exhibit high TFRC expression by immunohistochemistry. Additionally, high TFRC expression indicated an undesirable state of patient relapse, which could serve as a powerful significant independent predictor of recurrence-free survival (RFS). In summary, we systematically summarize the expression characteristics and clinical relevance of TFRC and show that TFRC can be used as a prognostic factor, which can be considered a potential therapeutic target in GIST