Biomarker Identification for Gender Specificity of Alzheimer's Disease Based on the Glial Transcriptome Profiles.

Many sex-specific biomarkers have been recently revealed in Alzheimer's disease (AD); however, cerebral glial cells were rarely reported. This study analyzed 220,095 single-nuclei transcriptomes from the frontal cortex of thirty-three AD individuals in the GEO database. Sex-specific Differentially Expressed Genes (DEGs) were identified in glial cells, including 243 in astrocytes, 1,154 in microglia, and 572 in oligodendrocytes. Gene Ontology (GO) functional annotation analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses revealed functional concentration in synaptic, neural, and hormone-related pathways. Protein-protein interaction network (PPI) identified MT3, CALM2, DLG2, KCND2, PAKACB, CAMK2D, and NLGN4Y in astrocytes, TREM2, FOS, APOE, APP, and NLGN4Y in microglia, and GRIN2A, ITPR2, GNAS, and NLGN4Y in oligodendrocytes as key genes. NLGN4Y was the only gene shared by the three glia and was identified as the biomarker for the gender specificity of AD. Gene-transcription factor (TF)-miRNA coregulatory network identified key regulators for NLGN4Y and its target TCMs. Ecklonia kurome Okam (Kunbu) and Herba Ephedrae (Mahuang) were identified, and the effects of the active ingredients on AD were displayed. Finally, enrichment analysis of Kunbu and Mahuang suggested that they might act as therapeutic candidates for gender specificity of AD.

Automatic diagnosis of pediatric supracondylar humerus fractures using radiomics-based machine learning.

The aim of this study was to construct a classification model for the automatic diagnosis of pediatric supracondylar humerus fractures using radiomics-based machine learning. We retrospectively collected elbow joint Radiographs of children aged 3 to 14 years and manually delineated regions of interest (ROI) using ITK-SNAP. Radiomics features were extracted using pyradiomics, a python-based feature extraction tool. T-tests and the least absolute shrinkage and selection operator (LASSO) algorithm were used to further select the most valuable radiomics features. A logistic regression (LR) model was trained, with an 8:2 split into training and testing sets, and 5-fold cross-validation was performed on the training set. The diagnostic performance of the model was evaluated using receiver operating characteristic curves (ROC) on the testing set. A total of 411 fracture samples and 190 normal samples were included. 1561 features were extracted from each ROI. After dimensionality reduction screening, 40 and 94 features with the most diagnostic value were selected for further classification modeling in anteroposterior and lateral elbow radiographs. The area under the curve (AUC) of anteroposterior and lateral elbow radiographs is 0.65 and 0.72. Radiomics can extract and select the most valuable features from a large number of image features. Supervised machine-learning models built using these features can be used for the diagnosis of pediatric supracondylar humerus fractures.

Single-cell profiling reveals the metastasis-associated immune signature of hepatocellular carcinoma.

AIM: Metastasis is the leading cause of mortality in hepatocellular carcinoma (HCC). The metastasis-associated immune signature in HCC is worth exploring. METHODS: Bioinformatic analysis was conducted based on the single-cell transcriptome data derived from HCC patients in different stages. Cellular composition, pseudotime state transition, and cell-cell interaction were further analyzed and verified. RESULTS: Generally, HCC with metastasis exhibited suppressive immune microenvironment, while HCC without metastasis exhibited active immune microenvironment. Concretely, effector regulatory T cells (eTregs) were found to be enriched in HCC with metastasis. PHLDA1 was identified as one of exhaustion-specific genes and verified to be associated with worse prognosis in HCC patients. Moreover, A novel cluster of CCR7+ dendritic cells (DCs) was identified with high expression of maturation and migration marker genes. Pseudotime analysis showed that inhibition of differentiation occurred in CCR7+ DCs rather than cDC1 in HCC with metastasis. Furthermore, interaction analysis showed that the reduction of CCR7+ DCs lead to impaired CCR7/CCL19 interaction in HCC with metastasis. CONCLUSIONS: HCC with metastasis exhibited upregulation of exhaustion-specific genes of eTregs and inhibition of CCL signal of a novel DC cluster, which added new dimensions to the immune landscape and provided new immune therapeutic targets in advanced HCC.

Discovery of Potential Drug Targeting Key Genes in Alzheimer's Disease: Insights from Transcriptome Analysis and Molecular Docking.

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder that presents a significant global health challenge. To explore drugs targeting key genes in AD, R software was used to analyze the data of single nuclei transcriptome from human cerebral frontal cortex in AD, and the differentially expressed genes (DEGs) were screened. Then the gene ontology (GO) analysis, Kyoto gene and genome encyclopedia (KEGG) pathway enrichment and protein-protein interaction (PPI) network were analyzed. The hub genes were calculated by Cytoscape software. Molecular docking and molecular dynamics simulation were used to evaluate and visualize the binding between candidate drugs and key genes. A total of 564 DEGs were screened, and the hub genes were ISG15, STAT1, MX1, IFIT3, IFIT2, RSAD2, IFIT1, IFI44, IFI44L and DDX58. Enrichment terms mainly included response to virus, IFN-γ signaling pathway and virus infection. Diclofenac had good binding effect with IFI44 and IFI44L. Potential drugs may act on key gene targets and then regulate biological pathways such as virus response and IFN-γ-mediated signal pathway, so as to achieve anti-virus, improve immune balance and reduce inflammatory response, and thus play a role in anti-AD.

Identifying predictors of glioma evolution from longitudinal sequencing.

Clonal evolution drives cancer progression and therapeutic resistance. Recent studies have revealed divergent longitudinal trajectories in gliomas, but early molecular features steering posttreatment cancer evolution remain unclear. Here, we collected sequencing and clinical data of initial-recurrent tumor pairs from 544 adult diffuse gliomas and performed multivariate analysis to identify early molecular predictors of tumor evolution in three diffuse glioma subtypes. We found that CDKN2A deletion at initial diagnosis preceded tumor necrosis and microvascular proliferation that occur at later stages of IDH-mutant glioma. Ki67 expression at diagnosis was positively correlated with acquiring hypermutation at recurrence in the IDH-wild-type glioma. In all glioma subtypes, MYC gain or MYC-target activation at diagnosis was associated with treatment-induced hypermutation at recurrence. To predict glioma evolution, we constructed CELLO2 (Cancer EvoLution for LOngitudinal data version 2), a machine learning model integrating features at diagnosis to forecast hypermutation and progression after treatment. CELLO2 successfully stratified patients into subgroups with distinct prognoses and identified a high-risk patient group featured by MYC gain with worse post-progression survival, from the low-grade IDH-mutant-noncodel subtype. We then performed chronic temozolomide-induction experiments in glioma cell lines and isogenic patient-derived gliomaspheres and demonstrated that MYC drives temozolomide resistance by promoting hypermutation. Mechanistically, we demonstrated that, by binding to open chromatin and transcriptionally active genomic regions, c-MYC increases the vulnerability of key mismatch repair genes to treatment-induced mutagenesis, thus triggering hypermutation. This study reveals early predictors of cancer evolution under therapy and provides a resource for precision oncology targeting cancer dynamics in diffuse gliomas.

Internet addiction, loneliness, and academic burnout among Chinese college students: a mediation model.

Background: The dynamics of education and student life have changed since the COVID-19 pandemic. Our society, especially the education system, has become largely dependent on the Internet. This paradigm shifts largely took place in the last few decades. As such, there are various ways in which we cannot comprehend the impact that the Internet can have on student psychology, and how multiple other factors could influence that. Internet addiction and its relationship with academic burnout, along with the impact of loneliness, are all essential factors that must be discussed candidly in the post-COVID-19 era. Hence, the objective of this study was, therefore, to explore the relationship between Internet addiction, loneliness, and academic burnout among Chinese college students as well as the mediating role of loneliness. Methods: We conducted a cross-sectional questionnaire survey at a Chinese university from October to November 2022. In total, 810 valid respondents were selected via random cluster sampling using the well-established Internet Addiction, Loneliness, and Academic Burnout Scale. The primary approach of mediation analysis and structural equation modeling testing examined the relationships among the three components. Results: Internet addiction could be responsible for academic burnout among college students. Loneliness partially mediates the relationship between Internet addiction and academic burnout. In a mediated way, different types of loneliness contribute to different types of academic burnout. Conclusion: Psychological interventions for loneliness, especially emotional loneliness prevention, are the critical aspects of the problem of Internet addiction accompanied with academic burnout. The causal relationship between Internet addiction and academic burnout, possibly of a two-way nature, needs to be further explored in the next future.

Albumin pre-opsonized membrane-active iPep nanomedicine potentiates chemo to immunotherapy of cancer.

Chemotherapy-conjugated immunotherapy in clinical oncology conceptually resembles the combined effects of cytoreduction and immunostimulation in membrane targeted cell killings mediated by pore-forming proteins or host defense peptides. Of the similar concept, targeting cancer cell membrane using membrane active peptides is a hopeful therapeutic modality but had long been hindered from in vivo application. Here we report an enabling strategy of pre-opsonizing a membrane penetrating Ir-complexed octa-arginine peptide (iPep) with serum albumin via intrinsic amphipathicity-driven bimodal interactions into nanoparticles (NP). We found that NP triggered stress-mediated 4T1 cell oncosis which induced potent immunological activation, surpassing several well-known immunogenic medicines. Vested with albumin-enhanced in vivo tumor targeting specificity and pharmacokinetic properties, NP showed combined chemo to immunotherapies of s. c. tumors in mice, with decreased percentages of MDSC, Treg, M2-like macrophage and improved infiltration of CTLs in tumor site, caused complete regression of 4T1 and CT26 tumors, outperforming clinical medicines. In a challenging orthotopic breast cancer model, boost i. v. injections of NP acted as in situ tumor vaccine that drastically enhanced 4T1-specific cellular and humoral immunities to reverse disease progression. Thus, with combined effects of direct cytoreduction, immune activation and tumor vaccine, iPep-NP presents the promise and potential of a new modality of cancer medicine.

Successful anesthesia management with inhalation anesthesia in Rosai-Dorfman disease: a case report.

Rosai-Dorfman disease (RDD) is a rare, benign, non-Langerhans cell histiocytic proliferative disease. RDD with central nervous system involvement is extremely rare. Surgical excision is generally regarded as the appropriate treatment of choice for this disease, especially when the lesion causes neurological compression. RDD can be accompanied by systemic symptoms, such as malaise, fever, weight change, leukocytosis, anemia, and hormonal disturbance, which may be challenging during general management. Little is known regarding peri-anesthesia management of this rare disease. We report a case of a patient in his 20s who had recurrent RDD and had general anesthesia with perioperative management. He was obese and hepatic insufficiency. This case report adds to the literature regarding the perioperative anesthetic management of RDD with central nervous system involvement.

Characterization of tumor-associated reactive astrocytes in gliomas by single-cell and bulk tumor sequencing.

Objective: Astrocytes constitute approximately 30% of cells in gliomas and play important roles in synapse construction and survival. Recently, JAK/STAT pathway activation associated with a new type of astrocyte was reported. However, the implications of these tumor-associated reactive astrocytes (TARAs) in glioma are not known. Methods: We comprehensively assessed TARAs in gliomas, both in single cells and at the bulk tumor level, by analyzing five independent datasets. First, we analyzed two single-cell RNA sequencing datasets of 35,563 cells from 23 patients to estimate the infiltration level of TARAs in gliomas. Second, we collected clinical information and genomic and transcriptomic data of 1,379 diffuse astrocytoma and glioblastoma samples from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas datasets to evaluate the genomic, transcriptomic and clinical characteristics of TARA infiltration. Third, we downloaded expression profiles of recurrent glioblastoma samples from patients receiving PD-1 inhibitors to analyze the predictive value of TARAs for immune checkpoint inhibition. Results: Single-cell RNA sequencing data showed TARAs were abundant in the glioma micro-environment (15.7% in the CGGA dataset and 9.1% in the Gene Expression Omnibus GSE141383 dataset, respectively). Bulk tumor sequencing data showed that the extent of TARA infiltration was highly associated with major clinical and molecular features of astrocytic gliomas. Patients with more TARA infiltration were more likely to have MUC16, FLG, and PICK3A mutations, chromosome 9p21.3, 10q23.3, and 13q14.2 deletions and 7p11.2 amplification. Gene Ontology analysis revealed that the high level of astrocyte infiltration was characterized by immune and oncogenic pathways, such as the inflammatory response, positive regulation of the JAK-STAT cascade, positive regulation of NIK/NF-kappa B signaling and the tumor necrosis factor biosynthetic process. Patients with greater TARA infiltration showed inferior prognosis. Meanwhile, the extent of reactive astrocyte infiltration exhibited a predictive value for recurrent glioblastoma patients undergoing anti-PD-1 immune therapy. Conclusion: TARA infiltration might promote glioma tumor progression and can be used as a diagnostic, predictive and prognostic marker in gliomas. Prevention of TARA infiltration might be a new therapeutic strategy for glioma.

Ronidazole Is a Superior Prodrug to Metronidazole for Nitroreductase-Mediated Hepatocytes Ablation in Zebrafish Larvae.

The liver plays a very important role in physiological processes of the human body. Liver regeneration has developed into an important area of study in liver disease. The Mtz (metronidazole)/NTR (nitroreductase)-mediated cell ablation system has been widely used to study the processes and mechanisms of liver injury and regeneration. However, high concentrations and toxic side effects of Mtz severely limit the application of the Mtz/NTR system. Therefore, screening new analogs to replace Mtz has become an important means to optimize the NTR ablation system. In this study, we screened five Mtz analogs including furazolidone, ronidazole, ornidazole, nitromide, and tinidazole. We compared their toxicity on the transgenic fish line Tg(fabp10a: mCherry-NTR) and their specific ablation ability on liver cells. The results showed that Ronidazole at a lower concentration (2 mM) had the same ability to ablate liver cells comparable with that of Mtz (10 mM), almost without toxic side effects on juvenile fish. Further study found that zebrafish hepatocyte injury caused by the Ronidazole/NTR system achieved the same liver regenerative effect as the Mtz/NTR system. The above results show that Ronidazole can replace Mtz with NTR to achieve superior damage and ablation effects in zebrafish liver.

Vaping Flavors and Flavor Representation: A Test of Youth Risk Perceptions, Novelty Perceptions, and Susceptibility.

INTRODUCTION: Whether novelty-flavored vaping devices should be available in the marketplace has been a hotly contested debate. From one perspective, the variety of different flavors, such as fruit and mint, may help adult cigarette smokers who are seeking to switch to reduced-harm nicotine products. However, these flavors are also wildly popular among youth, creating concerns about new nicotine product use among minors. AIMS AND METHODS: This experiment (n = 176) tests whether vaping flavors (tobacco vs fruit) and flavor representations on packages (flavor color, flavor image) influence how middle school youth perceive vaping products. RESULTS: While results show no difference in risk perceptions based on condition, novelty perceptions (eg, how fun, interesting) and susceptibility to vaping are highest among those who view the fruit-flavored vaping product with flavor color and flavor image. Those who viewed this condition reported higher novelty perceptions and susceptibility than those who viewed the fruit-flavored vaping product with no flavor color and no flavor image. Additionally, they reported higher novelty perceptions than those who viewed the tobacco-flavored vaping product with flavor color and flavor image. A post-hoc analysis in supplemental data shows that youth who report lower risk perceptions and higher susceptibility have higher behavioral intentions to vape in the next year. CONCLUSION: Findings suggest that restricting flavor representation on packaging might reduce how fun and interesting youth perceive these products to be and how susceptible they are to using them.

A High-Sensitivity Dual-Axis Accelerometer with Two FP Cavities Assembled on Single Optical Fiber.

In this paper, a dual-axis Fabry-Pérot (FP) accelerometer assembled on single optical fiber is proposed. The sensor is equipped with a special beam-splitting prism to split the light into two perpendicular directions (the X- and Y-axes); the prism surface coated with semi-permeable film and the reflective sheet on the corresponding Be-Cu vibration-sensitive spring form two sets of FP cavities of different sizes. When the Be-Cu spring with a proof mass (PM) is subjected to the vibration signal, the cavity length of the corresponding FP cavity is changed and the interference signal returns to the collimator through the original path of the prism. After bandpass filtering and demodulation, the two cavity lengths are obtained, and the acceleration measurement in dual-axis directions is completed. The resonant frequency of the proposed dual-axis fiber optic accelerometer is around 280 Hz. The results of the spectral measurements show 3.93 µm/g (g = 9.8 m/s2: gravity constant) and 4.19 µm/g for the applied acceleration along the X- and Y-axes, respectively, and the cross-axis sensitivity is below 5.1%. Within the angle range of 180°, the maximum error of measured acceleration is less than 3.77%. The proposed fiber optic dual-axis FP accelerometer has high sensitivity and strong immunity to electromagnetic interference. The size of the sensor mainly depends on the size of the prism, which is easy to reduce and mass produce. Moreover, this FP construction method has high flexibility and development potential.

Nrf2 transcriptional upregulation of IDH2 to tune mitochondrial dynamics and rescue angiogenic function of diabetic EPCs.

Endothelial progenitor cells (EPCs) are reduced in number and impaired in function in diabetic patients. Whether and how Nrf2 regulates the function of diabetic EPCs remains unclear. In this study, we found that the expression of Nrf2 and its downstream genes were decreased in EPCs from both diabetic patients and db/db mice. Survival ability and angiogenic function of EPCs from diabetic patients and db/db mice also were impaired. Gain- and loss-of-function studies, respectively, showed that knockdown of Nrf2 increased apoptosis and impaired tube formation in EPCs from healthy donors and wild-type mice, while Nrf2 overexpression decreased apoptosis and rescued tube formation in EPCs from diabetic patients and db/db mice. Additionally, proangiogenic function of Nrf2-manipulated mouse EPCs was validated in db/db mice with hind limb ischemia. Mechanistic studies demonstrated that diabetes induced mitochondrial fragmentation and dysfunction of EPCs by dysregulating the abundance of proteins controlling mitochondrial dynamics; upregulating Nrf2 expression attenuated diabetes-induced mitochondrial fragmentation and dysfunction and rectified the abundance of proteins controlling mitochondrial dynamics. Further RNA-sequencing analysis demonstrated that Nrf2 specifically upregulated the transcription of isocitrate dehydrogenase 2 (IDH2), a key enzyme regulating tricarboxylic acid cycle and mitochondrial function. Overexpression of IDH2 rectified Nrf2 knockdown- or diabetes-induced mitochondrial fragmentation and EPC dysfunction. In a therapeutic approach, supplementation of an Nrf2 activator sulforaphane enhanced angiogenesis and blood perfusion recovery in db/db mice with hind limb ischemia. Collectively, these findings indicate that Nrf2 is a potential therapeutic target for improving diabetic EPC function. Thus, elevating Nrf2 expression enhances EPC resistance to diabetes-induced oxidative damage and improves therapeutic efficacy of EPCs in treating diabetic limb ischemia likely via transcriptional upregulating IDH2 expression and improving mitochondrial function of diabetic EPCs.

Pretreatment of Ultra-Weak Fiber Bragg Grating Hydrophone Array Based on Cubic Spline Interpolation Using Intensity Compensation.

The demodulation algorithm based on 3 × 3 coupler in a fiber-optic hydrophone array has gained extensive attention in recent years. The traditional method uses a circulator to construct the normal path-match interferometry; however, the problem of increasing the asymmetry of the three-way signal to be demodulated is easily overlooked. To provide a solution, we report a pretreatment method for hydrophone array based on 3 × 3 coupler demodulation. We use cubic spline interpolation to perform nonlinear fitting to the reflected pulse train and calculate the peak-to-peak values of the single pulse to determine the light intensity compensation coefficient of the interference signal, so as to demodulate the corrected three-way interference signal. For experimental verification, ultra-weak fiber Bragg gratings (uwFBGs) with reflectivity of -50 dB are applied to construct a hydrophone array with 800 sensors, and a vibratory liquid column method is set up to generate a low-frequency hydroacoustic signal. Compared to the traditional demodulation algorithm based on a 3 × 3 coupler, the pretreatment method can improve the consistency of interference signals. The Lissajous figures show that cubic spline interpolation can improve the accuracy of monopulse peak seeking results by about 1 dB, and intensity compensation can further lead to a much lower noise density level for the interference pulse amplitude-specifically, more than 7 dB at 5~50 Hz-and the signal-to-noise ratio is improved by approximately 10 dB at 10 Hz. The distinct advantages of the proposed pretreatment method make it an excellent candidate for a hydrophone array system based on path-match interferometry.

Long Short-Term Memory Neural Network with Transfer Learning and Ensemble Learning for Remaining Useful Life Prediction.

Prediction of remaining useful life (RUL) is greatly significant for improving the safety and reliability of manufacturing equipment. However, in real industry, it is difficult for RUL prediction models trained on a small sample of faults to obtain satisfactory accuracy. To overcome this drawback, this paper presents a long short-term memory (LSTM) neural network with transfer learning and ensemble learning and combines it with an unsupervised health indicator (HI) construction method for remaining-useful-life prediction. This study consists of the following parts: (1) utilizing the characteristics of deep belief networks and self-organizing map networks to translate raw sensor data to a synthetic HI that can effectively reflect system health; and (2) introducing transfer learning and ensemble learning to provide the required degradation mechanism for the RUL prediction model based on LSTM to improve the performance of the model. The performance of the proposed method is verified by two bearing datasets collected from experimental data, and the results show that the proposed method obtains better performance than comparable methods.

Empagliflozin Ameliorates Diabetic Cardiomyopathy via Attenuating Oxidative Stress and Improving Mitochondrial Function.

Diabetic cardiomyopathy (DCM) is considered to be a critical contributor to the development of heart failure. Empagliflozin (EMPA), a sodium-glucose cotransporter 2 inhibitor, has been shown to prevent cardiovascular events and reduce the incidence of heart failure in randomized clinical trials. However, the mechanism of how EMPA prevents DCM is poorly understood. To study the potential mechanisms involved in the therapeutic effects of EMPA, we assessed the protective effects of EMPA on myocardial injury in type 2 diabetic db/db mice and H9C2 cardiomyocytes. 9-10-week-old male db/db mice were treated with EMPA (10 mg/kg) via oral gavage daily for 20 weeks. Afterward, cardiac function of treated mice was evaluated by echocardiography, and pathological changes in heart tissues were determined by histopathological examination and western blot assay. EMPA markedly reduced blood glucose levels, improved insulin tolerance, and enhanced insulin sensitivity of db/db mice. In addition, EMPA significantly prevented cardiac dysfunction, inhibited cardiac hypertrophy and fibrosis, and reduced glycogen deposition in heart tissues. Furthermore, EMPA improved diabetes-induced oxidative stress and mitochondrial dysfunction in both heart tissues of db/db mice and palmitate exposed H9C2 cells. EMPA significantly increased the expression of nuclear factor erythroid 2-related factor 2 (Nrf2) and its downstream genetic targets in cardiac tissue of type 2 diabetic db/db mice and H9C2 cells. EMPA also downregulated the expression of mitochondrial fission-related proteins and upregulated the expression of mitochondrial fusion-related proteins. Collectively, these findings indicate that EMPA may prevent DCM via attenuating oxidative stress and improving mitochondrial function in heart tissue.

High-Resolution Optical Fiber Temperature Sensor Based on Draw Tower Grating Array.

Ocean temperature monitoring is of great significance to marine fishing, aquaculture, and marine operations. Traditional electric sensors lack the potential to multiplex several sensors, and may suffer from electromagnetic interference. Meanwhile, fiber Bragg grating-based sensors have the advantages of high sensitivity, possibility for large-scale multiplexing, and immunity to electromagnetic interference. In this paper, we propose a Fabry-Pérot (FP) interferometer based on the draw tower grating array and combine it with the phase measurement method for demonstration and testing. In the sensor system, two adjacent fiber Bragg gratings (FBGs) are used as mirrors and an optical fiber connects them, forming a sensor unit. The signal was detected through the compensation of the optical path difference via two-arm path differences in an unbalanced interferometer. The sensor is calibrated in the range of 36.00-36.50 °C, and back to 36.00 °C, in steps of 0.10 °C. A thermocouple (DW1222) is used as a reference. Experimental testing demonstrates that under the thermal loop, the temperature and phase can be approximated as a linear relationship, the Pearson square correlation coefficient is 0.9996, and the temperature sensitivity is -9846 rad/°C. To prove that our experimental device can achieve a higher temperature resolution, we measured the background noise of the system. The experimental results indicate that the order of magnitude of our system temperature resolution can reach 10-5 °C. Thus, we believe that the sensor system is promising for the application of ocean temperature detection, and owing to the ultraweak reflection characteristics of the FBG, this method provides the possibility for large-scale multiplexing of the system.

Polo-like kinases as potential targets and PLK2 as a novel biomarker for the prognosis of human glioblastoma.

The most prevalent malignant central nervous system (CNS) cancer is glioblastoma multiforme (GBM). PLKs (polo-like kinases) are a kind of serine-threonine kinase that modulate DNA replication, mitosis, and stress responses. PLKs in GBM need to be better studied and examined in terms of their expression, function, along with prognostic significance. Using an existing publicly available data set, we evaluated the expression level and prognostic relevance of PLKs in GBM patients at the molecular level. The biological processes along with cascades of the screened gene were predicted using the functional enrichment of Gene Set Enrichment Analysis, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes pathways. The data illustrated that PLK1/3/4 contents were greater in GBM tissues than in non-tumorous tissues, but PLK2/5 expression levels were lower. PLK2 expression was also linked to patient outcome in GBM. Our findings imply that PLKs might be useful molecular indicators as well as prospective treatment targets for GBM. A PLK2 inhibitor has been studied for the first time in a glioma cell in this work. In glioma cells, ON1231320 has anticancer effects. Finally, a summary of PLK inhibitors is presented, along with projections for future progress.

Comprehensive analysis of the LncRNAs, MiRNAs, and MRNAs acting within the competing endogenous RNA network of LGG.

Messenger RNA (mRNA) and long noncoding RNA (lncRNA) targets interact via competitive microRNA (miRNA) binding. However, the roles of cancer-specific lncRNAs in the competing endogenous RNA (ceRNA) networks of low-grade glioma (LGG) remain unclear. This study obtained RNA sequencing data for normal solid tissue and LGG primary tumour tissue from The Cancer Genome Atlas database. We used a computational method to analyse the relationships among the mRNAs, lncRNAs, and miRNAs in these samples. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to predict the biological processes (BPs) and pathways associated with these genes. Kaplan-Meier survival analysis was used to evaluate the association between the expression levels of specific mRNAs, lncRNAs, and miRNAs and overall survival. Finally, we created a ceRNA network describing the relationships among these mRNAs, lncRNAs, and miRNAs using Cytoscape 3.5.1. A total of 2555 differentially expressed (DE) mRNAs, 218 DElncRNAs, and 192 DEmiRNAs were identified using R. In addition, GO and KEGG pathway analysis of the mRNAs and lncRNAs in the ceRNA network identified 10 BPs, 10 cell components, 10 molecular functions, and 48 KEGG pathways as selectively enriched. A total of 55 lncRNAs, 50 miRNAs, and 10 mRNAs from this network were shown to be closely associated with overall survival in LGG. Finally, 59 miRNAs, 235 mRNAs, and 17 lncRNAs were used to develop a ceRNA network comprising 313 nodes and 1046 edges. This study helps expand our understanding of ceRNA networks and serves to clarify the underlying pathogenesis mechanism of LGG.

Minimum spanning tree based graph neural network for emotion classification using EEG.

Emotion classification based on neurophysiology signals has been a challenging issue in the literature. Recent neuroscience findings suggest that brain network structure underlying the different emotions provides a window in understanding human affection. In this paper, we propose a novel method to capture the distinct minimum spanning tree (MST) topology underpinning the different emotions. Specifically, we propose a hierarchical aggregation-based graph neural network to investigate the MST structure in emotion recognition. Extensive experiments on the public available DEAP dataset demonstrate the superior performance of the model in emotion classification as compared to existing methods. In addition, the results show that the theta, lower beta and gamma frequency band network information are more sensitive to emotions, suggesting a multi-frequency interaction in emotion processing.