Genome-Wide Identification of Calmodulin-Binding Protein 60 Gene Family and the Function of GhCBP60B in Cotton Growth and Development and Abiotic Stress Response.

The calmodulin-binding protein 60 (CBP60) family is a gene family unique to plants, and its members play a crucial role in plant defense responses to pathogens and growth and development. Considering that cotton is the primary source of natural cotton textile fiber, the functional study of its CBP60 gene family members is critical. In this research, we successfully identified 162 CBP60 members from the genomes of 21 species. Of these, 72 members were found in four cotton species, divided into four clades. To understand the function of GhCBP60B in cotton in depth, we conducted a detailed analysis of its sequence, structure, cis-acting elements, and expression patterns. Research results show that GhCBP60B is located in the nucleus and plays a crucial role in cotton growth and development and response to salt and drought stress. After using VIGS (virus-induced gene silencing) technology to conduct gene silencing experiments, we found that the plants silenced by GhCBP60B showed dwarf plants and shortened stem nodes, and the expression of related immune genes also changed. In further abiotic stress treatment experiments, we found that GhCBP60B-silenced plants were more sensitive to drought and salt stress, and their POD (peroxidase) activity was also significantly reduced. These results imply the vital role of GhCBP60B in cotton, especially in regulating plant responses to drought and salt stress. This study systematically analyzed CBP60 gene family members through bioinformatics methods and explored in depth the biological function of GhCBP60B in cotton. These research results lay a solid foundation for the future use of the GhCBP60B gene to improve cotton plant type and its drought and salt resistance.

Hydraulic constraints determine the distribution of heteromorphic leaves along plant vertical height.

As an interesting and important trait of some drought-tolerant species, heteromorphic leaves are distributed differentially along plant vertical heights. However, the underpinning mechanism for the formation of heteromorphic leaves remains unclear. We hypothesize that heteromorphic leaves are caused by the hydraulic constraints possibly due to the compensation of the changes in functional traits in response to water transport capacity or the reduction of ineffective water loss. In this study, differences in water transport capacity, morphological traits, anatomical structures, and cellular water relations among three typical types of heteromorphic leaves (i.e., lanceolate, ovate, and broad-ovate) of Populus euphratica Oliv. (a dominant species of desert riparian forest in Central and West Asia) and their relationships were analyzed in order to explore the forming mechanism of heteromorphic leaves. The results showed that the lanceolate, ovate, and broad-ovate leaves were growing in the lower, intermediate, and higher positions from the ground, respectively. Morphological traits, anatomical structures, cellular water relations, and water transport capacity significantly varied among the three types of heteromorphic leaves (P< 0.01). Drought stress in broad-ovate leaves was significantly higher than that in ovate and lanceolate leaves (P< 0.01). Water transport capacity has significant correlations with morphological traits, anatomical structures, and cellular water relations (R 2 ≥ 0.30; P< 0.01). Our results indicated that heteromorphic leaves were used as an important adaptive strategy for P. euphratica to alleviate the increase of hydraulic constraints along vertical heights.

A multi-sample particle swarm optimization algorithm based on electric field force.

Aiming at the premature convergence problem of particle swarm optimization algorithm, a multi-sample particle swarm optimization (MSPSO) algorithm based on electric field force is proposed. Firstly, we introduce the concept of the electric field into the particle swarm optimization algorithm. The particles are affected by the electric field force, which makes the particles exhibit diverse behaviors. Secondly, MSPSO constructs multiple samples through two new strategies to guide particle learning. An electric field force-based comprehensive learning strategy (EFCLS) is proposed to build attractive samples and repulsive samples, thus improving search efficiency. To further enhance the convergence accuracy of the algorithm, a segment-based weighted learning strategy (SWLS) is employed to construct a global learning sample so that the particles learn more comprehensive information. In addition, the parameters of the model are adjusted adaptively to adapt to the population status in different periods. We have verified the effectiveness of these newly proposed strategies through experiments. Sixteen benchmark functions and eight well-known particle swarm optimization algorithm variants are employed to prove the superiority of MSPSO. The comparison results show that MSPSO has better performance in terms of accuracy, especially for high-dimensional spaces, while maintaining a faster convergence rate. Besides, a real-world problem also verified that MSPSO has practical application value.

Linear Integration of Sensory Evidence over Space and Time Underlies Face Categorization.

Visual object recognition relies on elaborate sensory processes that transform retinal inputs to object representations, but it also requires decision-making processes that read out object representations and function over prolonged time scales. The computational properties of these decision-making processes remain underexplored for object recognition. Here, we study these computations by developing a stochastic multifeature face categorization task. Using quantitative models and tight control of spatiotemporal visual information, we demonstrate that human subjects (five males, eight females) categorize faces through an integration process that first linearly adds the evidence conferred by task-relevant features over space to create aggregated momentary evidence and then linearly integrates it over time with minimum information loss. Discrimination of stimuli along different category boundaries (e.g., identity or expression of a face) is implemented by adjusting feature weights of spatial integration. This linear but flexible integration process over space and time bridges past studies on simple perceptual decisions to complex object recognition behavior.SIGNIFICANCE STATEMENT Although simple perceptual decision-making such as discrimination of random dot motion has been successfully explained as accumulation of sensory evidence, we lack rigorous experimental paradigms to study the mechanisms underlying complex perceptual decision-making such as discrimination of naturalistic faces. We develop a stochastic multifeature face categorization task as a systematic approach to quantify the properties and potential limitations of the decision-making processes during object recognition. We show that human face categorization could be modeled as a linear integration of sensory evidence over space and time. Our framework to study object recognition as a spatiotemporal integration process is broadly applicable to other object categories and bridges past studies of object recognition and perceptual decision-making.

Development and Validation of a Deep Learning Algorithm for Mortality Prediction in Selecting Patients With Dementia for Earlier Palliative Care Interventions.

Importance: Early palliative care interventions drive high-value care but currently are underused. Health care professionals face challenges in identifying patients who may benefit from palliative care. Objective: To develop a deep learning algorithm using longitudinal electronic health records to predict mortality risk as a proxy indicator for identifying patients with dementia who may benefit from palliative care. Design, Setting, and Participants: In this retrospective cohort study, 6-month, 1-year, and 2-year mortality prediction models with recurrent neural networks used patient demographic information and topics generated from clinical notes within Partners HealthCare System, an integrated health care delivery system in Boston, Massachusetts. This study included 26 921 adult patients with dementia who visited the health care system from January 1, 2011, through December 31, 2017. The models were trained using a data set of 24 229 patients and validated using another data set of 2692 patients. Data were analyzed from September 18, 2018, to May 15, 2019. Main Outcomes and Measures: The area under the receiver operating characteristic curve (AUC) for 6-month and 1- and 2-year mortality prediction models and the factors contributing to the predictions. Results: The study cohort included 26 921 patients (16 263 women [60.4%]; mean [SD] age, 74.6 [13.5] years). For the 24 229 patients in the training data set, mean (SD) age was 74.8 (13.2) years and 14 632 (60.4%) were women. For the 2692 patients in the validation data set, mean (SD) age was 75.0 (12.6) years and 1631 (60.6%) were women. The 6-month model reached an AUC of 0.978 (95% CI, 0.977-0.978); the 1-year model, 0.956 (95% CI, 0.955-0.956); and the 2-year model, 0.943 (95% CI, 0.942-0.944). The top-ranked latent topics associated with 6-month and 1- and 2-year mortality in patients with dementia include palliative and end-of-life care, cognitive function, delirium, testing of cholesterol levels, cancer, pain, use of health care services, arthritis, nutritional status, skin care, family meeting, shock, respiratory failure, and swallowing function. Conclusions and Relevance: A deep learning algorithm based on patient demographic information and longitudinal clinical notes appeared to show promising results in predicting mortality among patients with dementia in different time frames. Further research is necessary to determine the feasibility of applying this algorithm in clinical settings for identifying unmet palliative care needs earlier.

Comparison of ß-Amyloid Plaque Labeling Methods: Antibody Staining, Gallyas Silver Staining, and Thioflavin-S Staining.

Objective To evaluate senile plaque formation and compare the sensitivity of three different ß-amyloid (Aß) labeling methods (antibody staining, Gallyas silver staining, and thioflavin-S staining) to detect Aß deposition.Methods APPswe/PSEN1dE9 transgenic mice (APP/PS1) of different ages were used to examine spatiotemporal changes in Aß plaque deposition. Antibody staining, Gallyas silver staining, and thioflavin-S staining were used to detect Aß plaque deposition in the same brain region of adjacent slices from model mice, and the results were compared.Results With aging, Aß plaques first appeared in the cortex and then the deposition increased throughout the whole brain. Significantly greater plaque deposition was detected by 6E10 antibody than that analyzed with Gallyas silver staining or thioflavin-S staining (P<0.05). Plaque deposition did not show significant difference between the APP/PS1 mice brains assayed with Gallyas silver staining and ones with thioflavin-S staining (P=0.0033).Conclusions The APP/PS1 mouse model of Alzheimer's disease could mimick the progress of Aß plaques occurred in patients with Alzheimer's disease. Antibody detection of Aß deposition may be more sensitive than chemical staining methods.

MAPK8 mediates resistance to temozolomide and apoptosis of glioblastoma cells through MAPK signaling pathway.

OBJECTIVE: In this study, we aimed to evaluate the expression and functions of MAPK8 in temozolomide (TMZ) -resistant glioblastoma cells as well as to explore the mechanism of TMZ resistance in glioblastoma cells. METHODS: Gene Expression Omnibus (GEO) database was used for identifying the differentially expressed genes (DEGs) in TMZ resistant samples. The functional partner genes of TMZ were screened out by Gene-drug interaction network (STITCH) and the glioblastoma-related genes were selected by gene search engine with evidence sentences (Digsee). The interactions among identified DEGs and glioblastoma-related genes were detected by Search Tool for the Retrieval of Interacting Genes (STRING). The dysregulated pathways were identified by Gene set enrichment analysis (GSEA). qRT-PCR was performed to detect the expression level of MAPK8 in glioblastoma cells. Western blot was used to detect the expressions of MAPK8 and MAPK signaling pathway-related proteins. MTT assay was utilized to measure the cell viability of TMZ sensitive and resistant cells. Colony formation assay was performed to detect the clone ability and flow cytometry (FCM) assay was applied to identify the apoptosis rate of TMZ resistant glioblastoma cells. RESULTS: MAPK8 was one of the DEGs and was up-regulated in TMZ resistant glioblastoma cells. The MAPK signaling pathway was activated in TMZ resistant glioblastoma cells under the condition of over-expression of MAPK8. The inhibition of MAPK8 restrained the colony formation, inducing apoptosis of TMZ resistant glioblastoma cells and suppressed the MAPK signaling pathway. CONCLUSION: MAPK8 promoted the resistance to TMZ, accelerated cell proliferation and inhibited the apoptosis of glioblastoma cells via activating MAPK signaling pathway.

Psychophysical reverse correlation reflects both sensory and decision-making processes.

Goal-directed behavior depends on both sensory mechanisms that gather information from the outside world and decision-making mechanisms that select appropriate behavior based on that sensory information. Psychophysical reverse correlation is commonly used to quantify how fluctuations of sensory stimuli influence behavior and is generally believed to uncover the spatiotemporal weighting functions of sensory processes. Here we show that reverse correlations also reflect decision-making processes and can deviate significantly from the true sensory filters. Specifically, changes of decision bound and mechanisms of evidence integration systematically alter psychophysical reverse correlations. Similarly, trial-to-trial variability of sensory and motor delays and decision times causes systematic distortions in psychophysical kernels that should not be attributed to sensory mechanisms. We show that ignoring details of the decision-making process results in misinterpretation of reverse correlations, but proper use of these details turns reverse correlation into a powerful method for studying both sensory and decision-making mechanisms.

Sensory and decision-making processes underlying perceptual adaptation.

Perceptual systems adapt to their inputs. As a result, prolonged exposure to particular stimuli alters judgments about subsequent stimuli. This phenomenon is commonly assumed to be sensory in origin. Changes in the decision-making process, however, may also be a component of adaptation. Here, we quantify sensory and decision-making contributions to adaptation in a facial expression paradigm. As expected, exposure to happy or sad expressions shifts the psychometric function toward the adaptor. More surprisingly, response times show both an overall decline and an asymmetry, with faster responses opposite the adapting category, implicating a substantial change in the decision-making process. Specifically, we infer that sensory changes from adaptation are accompanied by changes in how much sensory information is accumulated for the two choices. We speculate that adaptation influences implicit expectations about the stimuli one will encounter, causing modifications in the decision-making process as part of a normative response to a change in context.

Inflammatory caspase-related pyroptosis: mechanism, regulation and therapeutic potential for inflammatory bowel disease.

As an essential part of programmed cell death, pyroptosis is an inflammatory response that is elicited upon infection by intracellular pathogens. Metabolic diseases, atherosclerosis and vital organ damage occur if pyroptosis is over-activated. Macrophages are the main cells that induce pyroptosis with the help of intracellular pattern-recognition receptors stimulated by danger signals and pathogenic microorganisms in the cytosol of host cells. Activated inflammatory caspases induce pyroptosis and produce pro-inflammatory cytokines, such as interleukin-1ß and interleukin-18. Inflammatory programmed cell death is classified as canonical or non-canonical based on inflammatory caspases, which includes caspase-1 (in human and mouse) and caspase-11 (in mouse) or caspase-4 and -5 (in humans). Activated inflammatory caspases cleave the pore-forming effector protein, gasdermin-D, inducing osmotic pressure deregulation of internal fluids and subsequently rupturing the cell membranes. Inflammatory caspases could be attractive therapeutic targets for inflammatory bowel disease (IBD) in which pyroptosis may play an important role. This article reviews the current understanding of the mechanism of pyroptosis, focusing on the regulation of inflammatory caspases and therapeutic strategies for IBD.

GlycoDeNovo - an Efficient Algorithm for Accurate de novo Glycan Topology Reconstruction from Tandem Mass Spectra.

A major challenge in glycomics is the characterization of complex glycan structures that are essential for understanding their diverse roles in many biological processes. We present a novel efficient computational approach, named GlycoDeNovo, for accurate elucidation of the glycan topologies from their tandem mass spectra. Given a spectrum, GlycoDeNovo first builds an interpretation-graph specifying how to interpret each peak using preceding interpreted peaks. It then reconstructs the topologies of peaks that contribute to interpreting the precursor ion. We theoretically prove that GlycoDeNovo is highly efficient. A major innovative feature added to GlycoDeNovo is a data-driven IonClassifier which can be used to effectively rank candidate topologies. IonClassifier is automatically learned from experimental spectra of known glycans to distinguish B- and C-type ions from all other ion types. Our results showed that GlycoDeNovo is robust and accurate for topology reconstruction of glycans from their tandem mass spectra. Graphical Abstract ᅟ.

Expressions of CCAAT/enhancer-binding Protein Homologous Protein and Calnexin in the Hippocampus of a Mouse Model of Mesial Temporal Lobe Epilepsy.

Objective To explore the temporal and spatial distribution of CCAAT/enhancer-binding protein homologous protein (CHOP) and calnexin (CNX) in the dentate gyrus of mesial temporal lobe epilepsy (mTLE) mouse model. Methods We used kainic acid (KA) to induce acute phase (12 h and 24 h) mTLE mouse models and performed Western blotting and immunofluorescence to detect the different expressions and distribution pattern of CHOP and CNX in CA3 of the hippocampus. Results Compared with the controls,the expressions of CHOP(F=1.136,P=0.4069) and CNX (F=2.378,P=0.2087) did not increase in CA3 of hippocampus 12 h following KA injection in the acute phase of mTLE mouse models,whereas the expressions in CA1 and CA3 of hippocampus 24 h after injection were significantly higher (F=8.510,P=0.0362;F=6.968,P=0.0497,respectively). As shown by immunofluorescence analysis,CHOP was expressed mainly in CA3 of hippocampus 12 h after KA injection,and increased in CA1 and CA3 24 h after KA administration. Compared with the controls,the expressions of CHOP(F=24.480,P=0.0057) and CNX (F=7.149,P=0.0478) were significantly higher 24 h after KA injection.Conclusions The expression of CHOP increases along with the progression of seizures,indicating the increased level of endoplasmic reticulum stress. An increasing number of CNX,which serves as molecular chaperone,may be needed to facilitate the unfolded protein to complete the folding process.

How the Human Brain Represents Perceived Dangerousness or "Predacity" of Animals.

UNLABELLED: Common or folk knowledge about animals is dominated by three dimensions: (1) level of cognitive complexity or "animacy;" (2) dangerousness or "predacity;" and (3) size. We investigated the neural basis of the perceived dangerousness or aggressiveness of animals, which we refer to more generally as "perception of threat." Using functional magnetic resonance imaging (fMRI), we analyzed neural activity evoked by viewing images of animal categories that spanned the dissociable semantic dimensions of threat and taxonomic class. The results reveal a distributed network for perception of threat extending along the right superior temporal sulcus. We compared neural representational spaces with target representational spaces based on behavioral judgments and a computational model of early vision and found a processing pathway in which perceived threat emerges as a dominant dimension: whereas visual features predominate in early visual cortex and taxonomy in lateral occipital and ventral temporal cortices, these dimensions fall away progressively from posterior to anterior temporal cortices, leaving threat as the dominant explanatory variable. Our results suggest that the perception of threat in the human brain is associated with neural structures that underlie perception and cognition of social actions and intentions, suggesting a broader role for these regions than has been thought previously, one that includes the perception of potential threat from agents independent of their biological class. SIGNIFICANCE STATEMENT: For centuries, philosophers have wondered how the human mind organizes the world into meaningful categories and concepts. Today this question is at the core of cognitive science, but our focus has shifted to understanding how knowledge manifests in dynamic activity of neural systems in the human brain. This study advances the young field of empirical neuroepistemology by characterizing the neural systems engaged by an important dimension in our cognitive representation of the animal kingdom ontological subdomain: how the brain represents the perceived threat, dangerousness, or "predacity" of animals. Our findings reveal how activity for domain-specific knowledge of animals overlaps the social perception networks of the brain, suggesting domain-general mechanisms underlying the representation of conspecifics and other animals.

Parcellation of Human Amygdala Subfields Using Orientation Distribution Function and Spectral K-means Clustering.

Amygdala plays an important role in fear and emotional learning, which are critical for human survival. Despite the functional relevance and unique circuitry of each human amygdaloid subnuclei, there has yet to be an efficient imaging method for identifying these regions in vivo. A data-driven approach without prior knowledge provides advantages of efficient and objective assessments. The present study uses high angular and high spatial resolution diffusion magnetic resonance imaging to generate orientation distribution function, which bears distinctive microstructural features. The features were extracted using spherical harmonic decomposition to assess microstructural similarity within amygdala subfields are identified via similarity matrices using spectral k-mean clustering. The approach was tested on 32 healthy volunteers and three distinct amygdala subfields were identified including medial, posterior-superior lateral, and anterior-inferior lateral.

[Advance in research on chemical constituents from Notopterygii Rhizoma et Radix].

This paper summarized the recent 30 years research progress of the chemical constituents from Notopterygii Rhizoma et Radix. The chemical constituents from Notopterygii Rhizoma et Radix mainly consist of coumarins, polyene-polyacetylenes, sesquiterpenes, phenolic acids, while steroids and flavonoids were less reported. All constituents were confirmed and corrected through SciFinder. We also checked the Chinese name and English name and listed the CAS number of each compound. It can provide some guidelines for the research, development and utilization of Notopterygii Rhizoma et Radix in the future. Whether there is columbianin in the Notopterygii Rhizoma et Radix need to be further researched.

Establishment of a chronic restraint stress model of depression with C57BL/6J mice.

OBJECTIVE: To establish a chronic restraint stress (CRS) model of depression,using C57BL/6J mice. METHODS: Totally 20 C57BL/6J mice were screened by weight,sucrose preference,and the results of open-field test. Then,they were equally randomized into two groups:normal control (NC) group and CRS group. Mice in the CRS group were under restraint 4 hours a day and their behavioral changes were evaluated after 21 days. RESULTS: The immobility time was significantly longer in CRS mice [(131.70 ± 21.65) s] compared with controls [(68.88 ± 8.43) s] (P=0.0304). CRS mice showed a significant decrease in sucrose preference during the time 0-24 h [(66.21 ±3.24)% vs.(79.46 ± 3.85)%, P=0.0196] and 0-48 h [(73.25 ± 1.50)% vs.(80.20 ± 2.26)%, P=0.0248] compared with controls. CONCLUSION: The C57BL/6J mice CRS models of depression were successfully established.

The animacy continuum in the human ventral vision pathway.

Major theories for explaining the organization of semantic memory in the human brain are premised on the often-observed dichotomous dissociation between living and nonliving objects. Evidence from neuroimaging has been interpreted to suggest that this distinction is reflected in the functional topography of the ventral vision pathway as lateral-to-medial activation gradients. Recently, we observed that similar activation gradients also reflect differences among living stimuli consistent with the semantic dimension of graded animacy. Here, we address whether the salient dichotomous distinction between living and nonliving objects is actually reflected in observable measured brain activity or whether previous observations of a dichotomous dissociation were the illusory result of stimulus sampling biases. Using fMRI, we measured neural responses while participants viewed 10 animal species with high to low animacy and two inanimate categories. Representational similarity analysis of the activity in ventral vision cortex revealed a main axis of variation with high-animacy species maximally different from artifacts and with the least animate species closest to artifacts. Although the associated functional topography mirrored activation gradients observed for animate-inanimate contrasts, we found no evidence for a dichotomous dissociation. We conclude that a central organizing principle of human object vision corresponds to the graded psychological property of animacy with no clear distinction between living and nonliving stimuli. The lack of evidence for a dichotomous dissociation in the measured brain activity challenges theories based on this premise.

[Expression of growth-associated protein 43 in the hippocampus of mesial temporal lobe epilepsy mouse model].

OBJECTIVE: To explore the temporal and spatial distribution of growth-associated protein 43(GAP-43)and phosphorylated growth-associated protein 43(p-GAP-43)in the dentate gyrus of mesial temporal lobe epilepsy(MTLE)mouse model. METHODS: MTLE mouse model was established by using the kainic acid(KA)induction. Immunohistochemistry and Western blotting were applied to detect the expressions of GAP-43 and p-GAP-43 in different stages of epileptogenesis. RESULTS: Both in the epileptic and control mice, high GAP-43 expression level was detected in the dentate gyrus, hilus, and inner molecular layer of hippocampus. Decreased p-GAP-43 expression was detected 5 days, 2 weeks, and 5 weeks after KA-induced seizures. CONCLUSION: The decreased p-GAP-43 expression in the duration of seizure may play an important role in the synaptic reorganization of the sclerotic hippocampus.

Mapping the spatio-temporal pattern of the mammalian target of rapamycin (mTOR) activation in temporal lobe epilepsy.

Growing evidence from rodent models of temporal lobe epilepsy (TLE) indicates that dysregulation of the mammalian target of rapamycin (mTOR) pathway is involved in seizures and epileptogenesis. However, the role of the mTOR pathway in the epileptogenic process remains poorly understood. Here, we used an animal model of TLE and sclerotic hippocampus from patients with refractory TLE to determine whether cell-type specific activation of mTOR signaling occurs during each stage of epileptogenesis. In the TLE mouse model, we found that hyperactivation of the mTOR pathway is present in distinct hippocampal subfields at three different stages after kainate-induced seizures, and occurs in neurons of the granular and pyramidal cell layers, in reactive astrocytes, and in dispersed granule cells, respectively. In agreement with the findings in TLE mice, upregulated mTOR was observed in the sclerotic hippocampus of TLE patients. All sclerotic hippocampus (n = 13) exhibited widespread reactive astrocytes with overactivated mTOR, some of which invaded the dispersed granular layer. Moreover, two sclerotic hippocampus exhibited mTOR activation in some of the granule cells, which was accompanied by cell body hypertrophy. Taken together, our results indicate that mTOR activation is most prominent in reactive astrocytes in both an animal model of TLE and the sclerotic hippocampus from patients with drug resistant TLE.

Spatio-temporal expression study of phosphorylated 70-kDa ribosomal S6 kinase (p70S6k) in mesial temporal lobe epilepsy.

OBJECTIVE: To determine the spatio-temporal expression of p70S6k activation in hippocampus in mesial temporal lobe epilepsy. METHODS: Temporal lobe epilepsy model was established by stereotaxically unilateral and intrahippocampal injection of kainite acid (KA) in adult male C57BL/6 mice. Latent and chronic epileptogenesis were represented by mice 5 days after KA injection (n = 5) and mice 5 weeks after KA injection (n = 8), respectively. Control mice (n = 5) were injected with saline. Immunohistochemical assays were performed on brain sections of the mice. RESULTS: Hippocampus both ipsilateral and contralateral to the KA injection displayed significantly up-regulated pS6 immunoreactivity in dispersed granule cells in 5-day and 5-week model mice. CONCLUSION: The activation of p70S6k is mainly located in the dentate gyrus in KA-induced mouse model of temporal lobe epilepsy, indicating that the activation may be related with the disperse degree and hypertrophy of granule cells.