Chemical Synaptic Transmission Research Articles

Integrated meta-analysis, data mining, and animal experiments to investigate the efficacy and potential pharmacological mechanism of a TCM tonic prescription, Jianpi Tongmai formula, in depression

BackgroundDepression is a common psychiatric disorder and has become a growing public health issue. Traditional Chinese medicine (TCM) tonic prescriptions have been clinically proven to be an effective treatment for depression. PurposeThis study aimed to identify the core prescription to improve depression among the numerous TCM tonic prescriptions. Methods and resultsFirst, we used meta-analysis to clarify the efficacy and safety of tonic prescriptions in depression among 37 studies and identified 16 effective tonic prescriptions. Second, we conducted data mining to analyze the tonic prescriptions and identified important nourishing herbs. Third, based on the data mining results, we constructed a Delphi experiment to investigate the effects of these important nourishing herbs in depression. Combining the results of Delphi expert questionnaires and weight analysis, a core TCM tonic prescription, Jianpi Tongmai formula (JPTMF) for the treatment of depression, was constructed and was composed of invigorating Spleen qi herbs. Fourth, we verified that JPTMF can improve chronic unpredictable mild stress (CUMS) induced depression-like behaviors in mice. Fifth, we predicted that the mechanism of JPTMF in the treatment of depression was mainly associated with chemical synaptic transmission and neuroinflammation through network pharmacology and determined preliminary confirmation through animal experiments. ConclusionThis study was undertaken to evaluate the efficacy of TCM tonic prescriptions on depression and construct a core TCM tonic prescription, JPTMF, through a progressive analysis. Network pharmacology and animal experiments verified the reliability of JPTMF. The proposal of JPTMF is of innovative significance, and may provide far-reaching implications for improving depression by using nourishing herbs. Furthermore, the integrated methods applied in this study provide an innovative paradigm for the standardization and scientific basis of TCM research.

Identification of a costimulatory molecule-based signature to predict prognostic risk of pancreatic adenocarcinoma

We aimed to investigate the prognostic value of costimulatory molecules in PAAD by generating a CMS. Gene expression data and clinical factors of PAAD patients were obtained from TCGA. The signature was constructed using the survival package progressive Cox risk proportional regression model. Analyses of CMS-related genes, pathways, immune cell infiltration, and somatic mutations were conducted. A five-gene-based CMS was developed, and the risk score for CMS could be an independent risk factor for PAAD patients. Patients were divided into high- and low-risk groups based on the median Y of the CMS model. Differential analysis revealed 341 DEGs between the groups, and KEGG analysis demonstrated that these positively related genes in the high-risk group were mainly involved in chemical synaptic transmission pathway modulation and trans-synaptic signaling pathway regulation. Immune cell infiltration analysis revealed that the high-risk patients had higher proportions of M1 macrophages and T+ CD4 cells, but a lower proportion of M2 macrophages than that of the low-risk group. Mutational analysis revealed that the high-risk group showed a higher proportion of somatic mutations compared with that of the low-risk group. A CMS was developed, and the risk score could be an independent risk factor for PAAD patients.

Visualizing Presynaptic Active Zones and Synaptic Vesicles.

The presynaptic active zone (AZ) of chemical synapses is a highly dynamic compartment where synaptic vesicle fusion and neurotransmitter release take place. During evolution the AZ was optimized for speed, accuracy, and reliability of chemical synaptic transmission in combination with miniaturization and plasticity. Single-molecule localization microscopy (SMLM) offers nanometer spatial resolution as well as information about copy number, localization, and orientation of proteins of interest in AZs. This type of imaging allows quantifications of activity dependent AZ reorganizations, e.g., in the context of presynaptic homeostatic potentiation. In combination with high-pressure freezing and optogenetic or electrical stimulation AZs can be imaged with millisecond temporal resolution during synaptic activity. Therefore SMLM allows the determination of key parameters in the complex spatial environment of AZs, necessary for next generation simulations of chemical synapses with realistic protein arrangements.

Effect of Prenatal Opioid Exposure on the Human Placental Methylome.

Prenatal exposure to addictive drugs can lead to placental epigenetic modifications, but a methylome-wide evaluation of placental DNA methylation changes after prenatal opioid exposure has not yet been performed. Placental tissue samples were collected at delivery from 19 opioid-exposed and 20 unexposed control full-term pregnancies. Placental DNA methylomes were profiled using the Illumina Infinium HumanMethylationEPIC BeadChip. Differentially methylated CpG sites associated with opioid exposure were identified with a linear model using the ‘limma’ R package. To identify differentially methylated regions (DMRs) spanning multiple CpG sites, the ‘DMRcate’ R package was used. The functions of genes mapped by differentially methylated CpG sites and DMRs were further annotated using Enrichr. Differentially methylated CpGs (n = 684, unadjusted p < 0.005 and |∆β| ≥ 0.05) were mapped to 258 genes (including PLD1, MGAM, and ALCS2). Differentially methylated regions (n = 199) were located in 174 genes (including KCNMA1). Enrichment analysis of the top differentially methylated CpG sites and regions indicated disrupted epigenetic regulation of genes involved in synaptic structure, chemical synaptic transmission, and nervous system development. Our findings imply that placental epigenetic changes due to prenatal opioid exposure could result in placental dysfunction, leading to abnormal fetal brain development and the symptoms of opioid withdrawal in neonates.

Common and distinguishing genetic factors for substance use behavior and disorder: an integrated analysis of genomic and transcriptomic studies from both human and animal studies.

Genomic and transcriptomic findings greatly broaden the biological knowledge regarding substance use. However, systematic convergence and comparison evidence of genome-wide findings is lacking for substance use. Here, we combined all the genome-wide findings from both substance use behavior and disorder (SUBD) and identified common and distinguishing genetic factors for different SUBDs. Systemic literature search for genome-wide association (GWAS) and RNA-seq studies of alcohol/nicotine/drug use behavior (partially meets or not reported diagnostic criteria) and alcohol use behavior and disorder (AUBD), nicotine use behavior and disorder (NUBD) and drug use behavior and disorder (DUBD) was performed using PubMed and the GWAS catalog. Drug use was focused upon cannabis, opioid, cocaine and methamphetamine use. GWAS studies required case-control or case/cohort samples. RNA-seq studies were based on brain tissues. The genes which contained significant single nucleotide polymorphism (P ≤ 1 × 10-6 ) in GWAS and reported as significant in RNA-seq studies were extracted. Pathway enrichment was performed by using Metascape. Gene interaction networks were identified by using the Protein Interaction Network Analysis database. Total SUBD-related 2910 genes were extracted from 75 GWAS studies (2 773 889 participants) and 17 RNA-seq studies. By overlapping the genes and pathways of AUBD, NUBD and DUBD, four shared genes (CACNB2, GRIN2B, PLXDC2 and PKNOX2), four shared pathways [two Gene Ontology (GO) terms of 'modulation of chemical synaptic transmission', 'regulation of trans-synaptic signaling', two Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of 'dopaminergic synapse', 'cocaine addiction'] were identified (significantly higher than random, P< 1×10-5 ). The top shared KEGG pathways (Benjamini-Hochberg-corrected P-value <0.05) in the pairwise comparison of AUBD versus DUBD, NUBD versus DUBD, AUBD versus NUBD were 'Epstein-Barr virus infection', 'protein processing in endoplasmic reticulum' and 'neuroactive ligand-receptor interaction', respectively. We also identified substance-specific genetic factors: i.e. ADH1B and ALDH2 were unique for AUBD, while CHRNA3 and CHRNA4 were unique for NUBD. This systematic review identifies the shared and unique genes and pathways for alcohol, nicotine and drug use behaviors and disorders at the genome-wide level and highlights critical biological processes for the common and distinguishing vulnerability of substance use behaviors and disorders.

Identification of an autophagy-related gene signature for predicting prognosis and immune activity in pancreatic adenocarcinoma

Adenocarcinoma of the pancreas (PAAD) is a cancerous growth that deteriorates rapidly and has a poor prognosis. Researchers are investigating autophagy in PAAD to identify a new biomarker and treatment target. An autophagy-related gene (ARG) model for overall survival (OS) was constructed using multivariate Cox regression analyses. A cohort of the Cancer Genome Atlas (TCGA)-PAAD was used as the training group as a basis for model construction. This prediction model was validated with several external datasets. To evaluate model performance, the analysis with receiver operating characteristic curves (ROC) was performed. The Human Protein Atlas (HPA) and Cancer Cell Line Encyclopedia (CCLE) were investigated to validate the effects of ARGs expression on cancer cells. Comparing the levels of immune infiltration between high-risk and low-risk groups was finished through the use of CIBERSORT. The differentially expressed genes (DEGs) between the low-/high-risk groups were analyzed further via Gene Ontology biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, which were used to identify potential small-molecule compounds in Connectivity Map (CMap), followed by half-maximal inhibitory concentration (IC50) examination with PANC-1 cells. The risk score was finally calculated as follows: BAK1 × 0.34 + ITGA3 × 0.38 + BAG3 × 0.35 + APOL1 × 0.26–RAB24 × 0.67519. ITGA3 and RAB24 both emerged as independent prognostic factors in multivariate Cox regression. Each PAAD cohort had a significantly shorter OS in the high-risk group than in the low-risk group. The high-risk group exhibited infiltration of several immune cell types, including naive B cells (p = 0.003), plasma cells (p = 0.044), and CD8 T cells (nearly significant, p = 0.080). Higher infiltration levels of NK cells (p = 0.025), resting macrophages (p = 0.020), and mast cells (p = 0.007) were found in the high-risk group than the low-risk group. The in vitro and in vivo expression of signature ARGs was consistent in the CCLE and HPA databases. The top 3 enriched Gene Ontology biological processes (GO-BPs) were signal release, regulation of transsynaptic signaling, and modulation of chemical synaptic transmission, and the top 3 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were MAPK, cAMP, and cell adhesion molecules. Four potential small-molecule compounds (piperacetazine, vinburnine, withaferin A and hecogenin) that target ARGs were also identified. Taking the results together, our research shows that the ARG signature may serve as a useful prognostic indicator and reveal potential therapeutic targets in patients with PAAD.

A Network Pharmacology Based Research on the Mechanism of Donepezil in Treating Alzheimer's Disease.

ObjectiveIn order to explore and further understand the efficacy of donepezil (DNP) in the treatment of Alzheimer's disease (AD), this research was conducted based on network pharmacology and molecular docking.MethodCompounds of DNP and its effective targets were collected using the TCMSP Chinese medicine system pharmacology database. Disease targets were screened and selected utilizing GeneCards, TTD, DrugBank, CTD, and other online databases. Then, Venn diagrams were generated to identify the intersections. A diseases-drug-active ingredient-key target protein interaction (PPI) network was constructed using the STING database. GO and KEGG enrichment analyses were conducted to predict the function and mechanism of DNP, which were visualized by graphs and bubble charts. After the screening, the top five interacting targets in the PPI network and the compound containing the most active target were selected for molecular docking.ResultsThe study received 110 potential targeting genes and 155 signaling pathways. A strong association between DNP and modulation of chemical synaptic transmission and the regulation of trans-synaptic signaling is noted. Signaling pathways related to the proliferation, differentiation, and survival of cells are also found positively relative. The results revealed that the mechanism of its therapeutic effect is multi-component, multi-target, and multi-pathway, laying a foundation for the follow-up in-depth study of the mechanism of DNP in the treatment of AD.ConclusionThis research provides a superior prediction that AD could be treated using DNP which targets the key proteins and essential pathways associated with the recovery of AD.

Genome-Wide Expression Profiling by RNA-Sequencing in Spinal Cord Dorsal Horn of a Rat Chronic Postsurgical Pain Model to Explore Potential Mechanisms Involved in Chronic Pain.

BackgroundChronic postsurgical pain (CPSP) is common among patients receiving major surgeries. CPSP produces suffering in patients, both physically and mentally. However, the mechanisms underlying CPSP remain elusive. Here, a genome-wide expression profiling of ipsilateral spinal cord dorsal horn (SCDH) was performed to identify potential genes related with CPSP.MethodsA rat skin/muscle incision and retraction (SMIR) model was established to induce CPSP. Immunostaining was used to study glial cell and neuron activation in ipsilateral SCDH of SMIR model rats. RNA sequencing (RNA-Seq), combined with bioinformatics analysis, was undertaken to explore gene expression profiles. qPCR was applied to validate the expression of some representative genes.ResultsThe SMIR model rats developed persistent mechanical allodynia in ipsilateral hindpaw for up to 14 days. Ipsilateral SCDH of SMIR rats showed remarkable glial cell and neuron activation. A number of differentially expressed genes (DEGs) were identified in ipsilateral SCDH of SMIR rats by RNA-Seq. qPCR confirmed expression of some representative DEGs. Bioinformatics indicated that chemical synaptic transmission, sensory perception of pain and neuroactive ligand-receptor interaction were predominant functions. We compared our dataset with human pain-related genes and found that several genes exclusively participate in pain modulation and mechanisms.ConclusionOur study provided novel understandings of the molecular mechanisms possibly contributing to CPSP. These findings may offer new targets for future treatment of CPSP.

Analysis of the Mechanism of RAD18 in Glioma

Introduction: This study aimed to evaluate the regulatory mechanism of RAD18 in glioma development. Methods: RAD18 expression was compared in glioma tumors and normal samples. Furthermore, we investigated the association between gene transcription and clinical factors in glioma samples, followed by functional enrichment analysis, screening for key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, immune infiltration analysis of high and low RAD18 expression groups, and correlation analysis of quantified KEGG signaling pathways and immune cell types. Results: The expression of RAD18 was upregulated in gliomas. Moreover, RAD18 expression was significantly correlated with age, tumor grade, and histological subtype. Notably, patients with gliomas with high RAD18 expression levels had worse overall survival. Functional enrichment analysis showed that RAD18 was significantly related to biological processes, such as cell division, chemical synaptic transmission, and mitotic nuclear division, and KEGG pathways such as cell cycle, oxidative phosphorylation, and extracellular matrix (ECM)-receptor interaction. The infiltration of five immune cells (plasma B cells, naive B cells, resting CD4+ memory T cells, monocytes, and M1 macrophages) was significantly different between the high and low RAD18 expression groups, and this difference was significantly related to key KEGG pathways, such as neuroactive ligand-receptor interaction and ECM-receptor interaction. Conclusion: RAD18 may serve as a target for glioma treatment and as a key regulator of glioma development.

Promoter Hypomethylation of TGFBR3 as a Risk Factor of Alzheimer's Disease: An Integrated Epigenomic-Transcriptomic Analysis.

Alzheimer’s disease (AD) is characterized by the abnormal deposition of amyloid-β (Aβ) plaques and tau tangles in the brain and accompanied with cognitive impairment. However, the fundamental cause of this disease remains elusive. To elucidate the molecular processes related to AD, we carried out an integrated analysis utilizing gene expression microarrays (GSE36980 and GSE5281) and DNA methylation microarray (GSE66351) in temporal cortex of AD patients from the Gene Expression Omnibus (GEO) database. We totally discovered 409 aberrantly methylated and differentially expressed genes. These dysregulated genes were significantly enriched in biological processes including cell part morphogenesis, chemical synaptic transmission and regulation of Aβ formation. Through convergent functional genomic (CFG) analysis, expression cross-validation and clinicopathological correlation analysis, higher TGFBR3 level was observed in AD and positively correlated with Aβ accumulation. Meanwhile, the promoter methylation level of TGFBR3 was reduced in AD and negatively associated with Aβ level and advanced Braak stage. Mechanically, TGFBR3 might promote Aβ production by enhancing β- and γ-secretase activities. Further investigation revealed that TGFBR3 may exert its functions via Synaptic vesicle cycle, Calcium signaling pathway and MAPK signal pathway by regulating hub genes GNB1, GNG3, CDC5L, DYNC1H1 and FBXW7. Overall, our findings highlighted TGFBR3 as an AD risk gene and might be used as a diagnostic biomarker and therapeutic target for AD treatment.

Microarray analysis of lipopolysaccharide-induced endotoxemia in the cochlea

Lipopolysaccharide (LPS)-induced endotoxemia alters intracochlear homeostasis and potentiates aminoglycoside-induced ototoxicity. However, the pathological mechanisms in the cochlea following systemic LPS-induced inflammation are unclear. In this study, three groups of mice received intraperitoneal injections [group A, saline control (n = 10); group B, 1 mg/kg LPS (n = 10); group C, 10 mg/kg LPS (n = 10)]. After 24 h, gene expression in cochlea samples was analyzed using DNA microarrays covering 28,853 genes in a duplicate manner. A total of 505 differentially expressed genes (DEGs) (≥2.0-fold change; p < 0.05) were identified. Interferon- and chemotaxis-related genes, including gbp2, gbp5, cxcl10, and Rnf125, were dose-dependently upregulated by LPS-induced endotoxemia. These results were verified by RT-qPCR. Upregulated DEGs were associated with inflammation, positive regulation of immune responses, and regulation of cell adhesion, while downregulated ones were associated with chemical synaptic transmission and the synaptic vesicle cycle. Protein-protein interaction included four functional clusters associated with interleukin-4, −10, and −13 and G protein-coupled receptor (GPCR) ligand binding; activation of matrix metalloproteinases and collagen degradation; recruitment of amyloid A proteins; and neutrophil degranulation. The findings of this study provide an additional basis on changes in the expression of genes in the cochlea in response to LPS-induced endotoxemia.

Regulation of Hippocampal Gamma Oscillations by Modulation of Intrinsic Neuronal Excitability.

Ion channels activated around the subthreshold membrane potential determine the likelihood of neuronal firing in response to synaptic inputs, a process described as intrinsic neuronal excitability. Long-term plasticity of chemical synaptic transmission is traditionally considered the main cellular mechanism of information storage in the brain; however, voltage- and calcium-activated channels modulating the inputs or outputs of neurons are also subjects of plastic changes and play a major role in learning and memory formation. Gamma oscillations are associated with numerous higher cognitive functions such as learning and memory, but our knowledge of their dependence on intrinsic plasticity is by far limited. Here we investigated the roles of potassium and calcium channels activated at near subthreshold membrane potentials in cholinergically induced persistent gamma oscillations measured in the CA3 area of rat hippocampal slices. Among potassium channels, which are responsible for the afterhyperpolarization in CA3 pyramidal cells, we found that blockers of SK (KCa2) and KV7.2/7.3 (KCNQ2/3), but not the BK (KCa1.1) and IK (KCa3.1) channels, increased the power of gamma oscillations. On the contrary, activators of these channels had an attenuating effect without affecting the frequency. Pharmacological blockade of the low voltage-activated T-type calcium channels (CaV3.1–3.3) reduced gamma power and increased the oscillation peak frequency. Enhancement of these channels also inhibited the peak power without altering the frequency of the oscillations. The presented data suggest that voltage- and calcium-activated ion channels involved in intrinsic excitability strongly regulate the power of hippocampal gamma oscillations. Targeting these channels could represent a valuable pharmacological strategy against cognitive impairment.

Identification of key pathways and genes in vestibular schwannoma using bioinformatics analysis.

The aim of the present study is to identify novel promising marks and targets of diagnosis, therapy and prognosis for patients with vestibular schwannoma at the molecular level. The gene expression profiles of GSE54934, GSE39645 and GSE56597 datasets were obtained respectively from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified by comparing between gene expression profiles of the vestibular schwannoma tissues and normal tissues. Subsequently, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein-protein interaction (PPI) network analysis were performed. The function and pathway enrichment analysis were performed for DEGs with DAVID. Reverse transcription-quantitative PCR were conducted to confirm the expression of BCL2, AGT, IL6 and ITGA2 in human Schwann cells and vestibular schwannoma cells. A total of 4,025, 1,1291 and 1,513 DEGs were identified from GSE54934, GSE56597 and GSE39645 datasets, respectively. GO and KEGG analysis showed that the mutual upregulated genes were mainly enriched in cell division, mitotic nuclear division, and transition of mitotic cell cycle, whilst mutual downregulated genes were enriched in chemical synaptic transmission, neurotransmitter transport, and synaptic vesicle membrane. Subsequently, 20 genes, including BCL2, AGT, IL6 and ITGA2 were selected as hub genes with high degrees after PPI network analysis. The significant differential expression of those genes were detected among vestibular schwannoma tissues compared with normal nerve tissues. In conclusion, BCL2, AGT, IL6 and ITGA2 are significantly higher expressed in vestibular schwannoma tissues compared with human Schwann tissues. The DEGs identified in the present study provide novel targets for the diagnosis and treatment of vestibular schwannoma.

MAGI-MS: multiple seed-centric module discovery.

Complex disorders manifest by the interaction of multiple genetic and environmental factors. Through the construction of genetic modules that consist of highly coexpressed genes, it is possible to identify genes that participate in common biological pathways relevant to specific phenotypes. We have previously developed tools MAGI and MAGI-S for genetic module discovery by incorporating coexpression and protein interaction networks. Here, we introduce an extension to MAGI-S, denoted as Merging Affected Genes into Integrated Networks-Multiple Seeds (MAGI-MS), which permits the user to further specify a disease pathway of interest by selecting multiple seed genes likely to function in the same molecular mechanism. By providing MAGI-MS with seed genes involved in processes underlying certain classes of neurodevelopmental disorders, such as epilepsy, we demonstrate that MAGI-MS can reveal modules enriched in genes relevant to chemical synaptic transmission, glutamatergic synapse and other functions associated with the provided seed genes. MAGI-MS is free and available at https://github.com/jchow32/MAGI-MS. Supplementary data are available at Bioinformatics Advances online.

Expression and regulatory network of long noncoding RNA in rats after spinal cord hemisection injury.

Long noncoding RNAs (lncRNAs) participate in a variety of biological processes and diseases. However, the expression and function of lncRNAs after spinal cord injury has not been extensively analyzed. In this study of right side hemisection of the spinal cord at T10, we detected the expression of lncRNAs in the proximal tissue of T10 lamina at different time points and found 445 lncRNAs and 6522 mRNA were differentially expressed. We divided the differentially expressed lncRNAs into 26 expression trends and analyzed Profile 25 and Profile 2, the two expression trends with the most significant difference. Our results showed that the expression of 68 lncRNAs in Profile 25 rose first and remained high 3 days post-injury. There were 387 mRNAs co-expressed with the 68 lncRNAs in Profile 25. The co-expression network showed that the co-expressed genes were mainly enriched in cell division, inflammatory response, FcγR-mediated cell phagocytosis signaling pathway, cell cycle and apoptosis. The expression of 56 lncRNAs in Profile2 first declined and remained low after 3 days post-injury. There were 387 mRNAs co-expressed with the 56 lncRNAs in Profile 2. The co-expression network showed that the co-expressed genes were mainly enriched in the chemical synaptic transmission process and in the signaling pathway of neuroactive ligand-receptor interaction. The results provided the expression and regulatory network of the main lncRNAs after spinal cord injury and clarified their co-expressed gene enriched biological processes and signaling pathways. These findings provide a new direction for the clinical treatment of spinal cord injury.

Neuromodulation of Chemical Synaptic Transmission Driven by THz Photons.

Postsynaptic currents of chemical synapse are modulated by multitudinous neurotransmitters, such as acetylcholine, dopamine, glutamate, and γ-aminobutyric acid, many of which have been used in the treatment of neurological diseases. Here, based on molecular dynamics simulations and quantum chemical calculation, we propose that 30- to 45-THz photons can resonate with a variety of typical neurotransmitter molecules and make them absorb photon energy to activate the transition to high energy state, which is expected to be a new method of neural regulation. Furthermore, we verified the calculated results through experiments that THz irradiation could substantively change neuronal signal emission and enhance the frequency, amplitude, and dynamic properties of excitatory postsynaptic current and inhibitory postsynaptic current. In addition, we demonstrated the potential of neural information regulation by THz photons through 2-photon imaging in vivo. These findings are expected to improve the understanding of the physical mechanism of biological phenomena and facilitate the application of terahertz technology in neural regulation and the development of new functional materials.

Identification of an Autophagy-Related Pair Signature for Predicting Prognoses and Immune Activity in Pancreatic Adenocarcinoma.

BackgroundPancreatic adenocarcinoma (PAAD) spreads quickly and has a poor prognosis. Autophagy research on PAAD could reveal new biomarkers and targets for diagnosis and treatment.MethodsAutophagy-related genes were translated into autophagy-related gene pairs, and univariate Cox regression was performed to obtain overall survival (OS)-related IRGPs (P<0.001). LASSO Cox regression analyses were performed to construct an autophagy-related gene pair (ARGP) model for predicting OS. The Cancer Genome Atlas (TCGA)-PAAD cohort was set as the training group for model construction. The model predictive value was validated in multiple external datasets. Receiver operating characteristic (ROC) curves were used to evaluate model performance. Tumor microenvironments and immune infiltration were compared between low- and high-risk groups with ESTIMATE and CIBERSORT. Differentially expressed genes (DEGs) between the groups were further analyzed by Gene Ontology biological process (GO-BP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and used to identify potential small-molecule compounds in L1000FWD.ResultsRisk scores were calculated as follows: ATG4B|CHMP4C×(-0.31) + CHMP2B|MAP1LC3B×(0.30) + CHMP6|RIPK2 ×(-0.33) + LRSAM1|TRIM5×(-0.26) + MAP1LC3A|PAFAH1B2×(-0.15) + MAP1LC3A|TRIM21×(-0.08) + MET|MFN2×(0.38) + MET|MTDH×(0.47) + RASIP1|TRIM5×(-0.23) + RB1CC1|TPCN1×(0.22). OS was significantly shorter in the high-risk group than the low-risk group in each PAAD cohort. The ESTIMATE analysis showed no difference in stromal scores but a significant difference in immune scores (p=0.0045) and ESTIMATE scores (p=0.014) between the groups. CIBERSORT analysis showed higher naive B cell, Treg cell, CD8 T cell, and plasma cell levels in the low-risk group and higher M1 and M2 macrophage levels in the high-risk group. In addition, the results showed that naive B cells (r=-0.32, p<0.001), Treg cells (r=-0.31, p<0.001), CD8 T cells (r=-0.24, p=0.0092), and plasma cells (r=-0.2, p<0.026) were statistically correlated with the ARGP risk score. The top 3 enriched GO-BPs were signal release, regulation of transsynaptic signaling, and modulation of chemical synaptic transmission, and the top 3 enriched KEGG pathways were the insulin secretion, dopaminergic synapse, and NF-kappa B signaling pathways. Several potential small-molecule compounds targeting ARGs were also identified.ConclusionOur results demonstrate that the ARGP-based model may be a promising prognostic indicator for identifying drug targets in patients with PAAD.

Animated pedagogical agents enhance learning outcomes and brain activity during learning

AbstractBackgroundWith the rapid popularization of e‐learning, how to improve online learning has aroused widespread concern. A human‐like pedagogical agent (PA) that displays eye gaze and gestures, is often added to online multimedia lessons to increase social connection and improve learning in e‐learning environments. However, there has been a debate about how PAs affect learning processes and learning outcomes.ObjectivesSocial agency theory holds that learners can build a social connection with PAs, which affects learning processes and outcomes. This study seeks to reveal how PAs influence learning by exploring the influence of PAs on learning outcomes and brain activity during learning.MethodsCollege students viewed a multimedia lesson on the process of chemical synaptic transmission either with or without an embodied PA on the left side of the screen that pointed to the graphic as she lectured. During learning students' brain cortical activity was measured by a functional near‐infrared spectroscopy (fNIRS) system, and after learning students completed learning outcomes post‐tests.Results and ConclusionsConsistent with social agency theory, students learning with a PA performed better on learning outcome tests and showed greater brain activity in the social areas of the brain during learning based on fNIRS measures.ImplicationsBy using fNIRS technology, this study provides preliminary new support for the idea that learners engage in social processing during online learning with an embodied PA that leads to improved learning outcomes.

Identification of key genes and pathways involved in Alzheimer’s disease through bioinformatic analysis

AbstractBackgroundAlthough there has been an intensive research on the molecular mechanisms of AD, there’re still unexplored pathways due to the heterogeneity of the disease mechanisms and variations in experimental approaches. Therefore, bioinformatics to would be helpful in deciphering the key gene expression patterns in existing datasets, which will eventually serve as biomarkers for AD.MethodIn this study, we aimed to identify the key genes and miRNAs involved in AD via bioinformatic analyses. We selected the GEO dataset GSE48350, which contains the microarray data collected from entorhinal cortex (EC), hippocampus (H), postcentral gyrus (PCG) and superior frontal gyrus (SFG) of the 80 AD and 173 healthy brains. We first identified the differentially expressed genes (DEGs) using the GEO2R web tool. Then, functional enrichment analysis (FEA) was performed by using DAVID. Protein‐protein interaction (PPI) networks were drawn by using STRINGdb and the hub proteins were detected by using the Cytohubba module in the Cytoscape program. miRNA detection was performed by using the miRDB web tool.ResultWe identified 12, 49, 69, 7, and 26 downregulated and 16, 51, 245, 10, and 44 upregulated genes as in all parts of the brain, EC, H, PCG and SFG regions, respectively. PPI analysis revealed the top three hub proteins as: GFAP, CXCR4, FOS in the EC; SNAP25, GRIN1, SLC32A1 in H; GFAP, SST, CXCR4 in FG regions and GFAP, SLC32A1, SST in the whole brain. According to FEA, the identified genes are involved in chemical synaptic transmission, neurotransmitter release, extracellular matrix organization, and inflammatory response. Upon analysis of the miRNA target database, we identified seven miRNAs targeting these genes. The most exciting miRNA turns out to be hsa‐miR548 family, since it targets CXCR4, FOS and GFAP.ConclusionThe identified DEGs may serve as biomarkers and drug targets for AD. Therefore, additional experiments on expressions of these genes in the plasma or cerebrospinal fluid samples of the patients should be performed. Also, miR‐548 family should be explored as a candidate drug target.

An age stratified analysis of the biomarkers in patients with colorectal cancer

Colorectal cancer (CRC), a common malignant tumor of the digestive tract, has a high incidence and mortality rate. Several recent studies have found that aging is associated with the increasing risk of cancer. Nevertheless, the expression status and function of age-related genes in CRC is still not well understood. In the study, we comprehensively analyzed the gene expression data of CRC patients from The Cancer Genome Atlas (TCGA) database. Age-related differential expression genes (age-related DEGs) in tumor tissues compared with normal tissues of CRC were further identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of age-related DEGs were performed by clusterProfiler of R. Afterwards, we used the STRING database to map the protein–protein interaction network of DEGs. We constructed prognostic model through univariate and multivariate COX regression analyses, and further evaluated their predictive power. The prognostic gene signature-related functional pathways were explored by gene set enrichment analysis (GSEA). The weighted gene co-expression network analysis (WGCNA) was used to identify key module associated with two prognostic gene signatures. Finally, we used the Metascape to perform functional enrichment analysis of genes in the key module. A total of 279 age-related DEGs were identified from the TCGA database. GO and KEGG enrichment analysis showed that the age-related DEGs were enriched in the Modulation of chemical synaptic transmission and Neuroactive ligand–receptor interaction. Moreover, we established a novel age-related gene signature (DLX2 and PCOLCE2) for overall survival in CRC, which was further predicted in both the training and validation sets. The results of GSEA demonstrated that numerous disease-related pathways were enriched in the high-risk group. We identified 43 genes related to the DLX2 and PCOLCE2 by the WGCNA co-expression network. We also found that these 43 genes were enriched in the cancer-related pathways. To sum up, the study identified an age-related gene signature for predicting the prognosis of CRC patients, which is conducive to the identification of novel prognostic molecular markers.