MRPL13 is a metastatic and prognostic marker of breast cancer: A silico analysis accompanied with experimental validation.

BACKGROUND: Although progress has been made in accurate diagnosis and targeted treatments, breast cancer (BC) patients with metastasis still present a grim prognosis. With the continuous emergence and development of new personalized and precision medicine targeting specific tumor biomarkers, there is an urgent need to find new metastatic and prognostic biomarkers for BC patients. METHODS: We were dedicated to identifying genes linked to metastasis and prognosis in breast cancer through a combination of in silico analysis and experimental validation. RESULTS: A total of 25 overlap differentially expressed genes were identified. Ten hub genes (namely MRPL13, CTR9, TCEB1, RPLP0, TIMM8B, METTL1, GOLT1B, PLK2, PARL and MANBA) were identified and confirmed. MRPL13, TCEB1 and GOLT1B were shown to be associated with the worse overall survival (OS) and were optionally chosen for further verification by western blot. Only MRPL13 was found associated with cell invasion, and the expression of MRPL13 in metastatic BC was significantly higher than in primary BC. CONCLUSION: We proposed MRPL13 could be a potential novel biomarker for the metastasis and prognosis of breast cancer.

Exploring physiological stress response evoked by passive translational acceleration in healthy adults: a pilot study utilizing electrodermal activity and heart rate variability measurements.

Passive translational acceleration (PTA) has been demonstrated to induce the stress response and regulation of autonomic balance in healthy individuals. Electrodermal activity (EDA) and heart rate variability (HRV) measurements are reliable indicators of the autonomic nervous system (ANS) and can be used to assess stress levels. The objective of this study was to investigate the potential of combining EDA and HRV measurements in assessing the physiological stress response induced by PTA. Fourteen healthy subjects were randomly assigned to two groups of equal size. The experimental group underwent five trials of elevator rides, while the control group received a sham treatment. EDA and HRV indices were obtained via ultra-short-term analysis and compared between the two groups to track changes in the ANS. In addition, the complexity of the EDA time series was compared between the 4 s before and the 2-6 s after the onset of PTA to assess changes in the subjects' stress levels in the experimental group. The results revealed a significant increase in the skin conductance response (SCR) frequency and a decrease in the root mean square of successive differences (RMSSD) and high frequency (HF) components of HRV. In terms of stress assessment, the results showed an increase in the complexity of the EDA time series 2-6 s after the onset of PTA. These results indicate an elevation in sympathetic tone when healthy subjects were exposed to a translational transport scenario. Furthermore, evidence was provided for the ability of EDA complexity to differentiate stress states in individual trials of translational acceleration.

Influence of avalanche transistor switching mode on waveform characteristics of solid-state pulse source.

The design of the Marx circuit based on avalanche transistors (ATs) is one of the effective techniques for developing solid-state pulse sources to generate nanosecond pulses. However, the influence of the avalanche transistor as a switching device on the output pulse characteristics is still unclear. In this study, investigating the switching mechanism of the AT with a mixed-mode simulation of the semiconductor device has been accomplished. An experiment has checked the simulation model's transient switching characteristics. The switching mechanisms of ATs in the Marx circuit were divided into base triggering mode (BTM) and voltage ramp mode (VRM). This paper proposes a modified circuit for adjusting the output pulse parameters of solid-state pulse sources. The results show that to satisfy the simulation accuracy, the width parameter of the AT model in the BTM must be 100 µm, much less than the actual physical size. Because of the higher electric field when the initial impact ionization occurs, the AT operates at a higher switching speed in the VRM than in the BTM. In addition, since the carriers of initial impact ionization locate at the p-n0 interface or the n0-n+ interface, the AT switching process will oscillate in the VRM. All ATs in the modified Marx circuit switch to operate in the BTM. The leading edge of the output pulse increases from 275 to 1125 ps, and the pulse trailing oscillation has disappeared. The research results provide an important technical means for optimizing the output waveform of solid-state pulse sources.

Ku70 affects the frequency of chromosome translocation in human lymphocytes after radiation and T-cell acute lymphoblastic leukemia.

BACKGROUND: As one of the most common chromosomal causes, chromosome translocation leads to T-cell acute lymphoblastic leukemia (T-ALL). Ku70 is one of the key factors of error-prone DNA repair and it may end in translocation. So far, the direct correlation between Ku70 and translocation has not been assessed. This study aimed to investigate the association between Ku70 and translocation in human lymphocytes after radiation and T-ALL. METHODS: Peripheral blood lymphocytes (PBLs) from volunteers and human lymphocyte cell line AHH-1 were irradiated with X-rays to form the chromosome translocations. Phytohemagglutinin (PHA) was used to stimulate lymphocytes. The frequency of translocation was detected by fluorescence in situ hybridization (FISH). Meanwhile, the expression of Ku70 was detected by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blot. Furthermore, Ku70 interference, overexpression and chemical inhibition were used in AHH-1 cell lines to confirm the correlation. Finally, the expression of Ku70 in T-ALL samples with or without translocation was detected. RESULTS: The expression of Ku70 and frequencies of translocation were both significantly increased in PBLs after being irradiated by X-rays, and a positive correlation between the expression (both mRNA and protein level) of Ku70 and the frequency of translocation was detected (r = 0.4877, P = 0.004; r = 0.3038, P = 0.0358 respectively). Moreover, Ku70 interference decreased the frequency of translocations, while the frequency of translocations was not significantly affected after Ku70 overexpression. The expression of Ku70 and frequencies of translocation were both significantly increased in cells after irradiation, combined with chemical inhibition (P < 0.01). The protein level and mRNA level of Ku70 in T-ALL with translocation were obviously higher than T-ALL with normal karyotype (P = 0.009, P = 0.049 respectively). CONCLUSIONS: Ku70 is closely associated with the frequency of chromosome translocation in human lymphocytes after radiation and T-ALL. Ku70 might be a radiation damage biomarker and a potential tumor therapy target.

Polymorphisms Within DNA Double-Strand Breaks Repair-Related Genes Contribute to Structural Chromosome Abnormality in Recurrent Pregnancy Loss.

Background: Structural chromosome abnormality (SCA) is an important cause of human diseases, including recurrent pregnancy loss (RPL). DNA double-strand breaks (DSBs) repair-related genes play critical roles in SCA. The present study aims to investigate the potential contribution of DSBs repair-related gene polymorphisms to SCA. Methods: Fifty-four affected RPL individuals with SCA, 88 affected RPL individuals without SCA, and 84 controls were analyzed. Targeted whole-exome sequencing (WES) was used for screening single nucleotide polymorphisms in six DSBs repair-related genes (EP300, XRCC6, LIG4, XRCC4, PRKDC, and DCLRE1C), and validation was performed by Sanger sequencing. Finally, we detected the frequency of radiation-induced chromosome translocations in no SCA samples with significant polymorphisms by fluorescence in situ hybridization (FISH). Results: A total of 35 polymorphisms have been identified and confirmed. Frequencies of EP300 rs20551, XRCC6 rs132788, and LIG4 rs1805388 were significantly different between SCA RPL and no SCA RPL (p = 0.030, 0.031, and 0.040 respectively). Frequencies of those three gene polymorphisms between SCA RPL and controls also were significantly different (p = 0.017, 0.028, and 0.029 respectively). Moreover, the frequency of the G allele at rs20551 locus, the T allele at rs132788 locus and the A allele at rs1805388 locus was significantly higher in SCA RPL than no SCA RPL (OR = 3.227, p = 0.005; OR = 1.978, p = 0.008 and OR = 1.769, p = 0.036 respectively) and controls (OR = 7.130, p = 0.000; OR = 2.157, p = 0.004; OR = 2.397, p = 0.003 respectively). Additionally, the frequency of radiation-induced translocation in no SCA samples with rs20551, rs132788 or rs1805388 was significantly higher compared with the wild type samples (p = 0.015, 0.012, and 0.007 respectively). Conclusion: Our results suggest that rs20551, rs132788, and rs1805388 might be associated with the risk of SCA. Larger scales of genetic variations studies and functional experiments are necessary to further confirm these findings.

Comprehensive analysis and identification of key genes and signaling pathways in the occurrence and metastasis of cutaneous melanoma.

BACKGROUND: Melanoma is a malignant tumor of melanocytes, and the incidence has increased faster than any other cancer over the past half century. Most primary melanoma can be cured by local excision, but metastatic melanoma has a poor prognosis. Cutaneous melanoma (CM) is prone to metastasis, so the research on the mechanism of melanoma occurrence and metastasis will be beneficial to diagnose early, improve treatment, and prolong life survival. In this study, we compared the gene expression of normal skin (N), primary cutaneous melanoma (PM) and metastatic cutaneous melanoma (MM) in the Gene Expression Omnibus (GEO) database. Then we identified the key genes and molecular pathways that may be involved in the development and metastasis of cutaneous melanoma, thus to discover potential markers or therapeutic targets. METHODS: Three gene expression profiles (GSE7553, GSE15605 and GSE46517) were downloaded from the GEO database, which contained 225 tissue samples. R software identified the differentially expressed genes (DEGs) between pairs of N, PM and MM samples in the three sets of data. Subsequently, we analyzed the gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of the DEGs, and constructed a protein-protein interaction (PPI) network. MCODE was used to seek the most important modules in PPI network, and then the GO function and KEGG pathway of them were analyzed. Finally, the hub genes were calculated by the cytoHubba in Cytoscape software. The Cancer Genome Atlas (TCGA) data were analyzed using UALCAN and GEPIA to validate the hub genes and analyze the prognosis of patients. RESULTS: A total of 134, 317 and 147 DEGs were identified between N, PM and MM in pair. GO functions and KEGG pathways analysis results showed that the upregulated DEGs mainly concentrated in cell division, spindle microtubule, protein kinase activity and the pathway of transcriptional misregulation in cancer. The downregulated DEGs occurred in epidermis development, extracellular exosome, structural molecule activity, metabolic pathways and p53 signaling pathway. The PPI network obtained the most important module, whose GO function and KEGG pathway were enriched in oxidoreductase activity, cell division, cell exosomes, protein binding, structural molecule activity, and metabolic pathways. 14, 18 and 18 DEGs were identified respectively as the hub genes between N, PM and MM, and TCGA data confirmed the expression differences of hub genes. In addition, the overall survival curve of hub genes showed that the differences in these genes may lead to a significant decrease in overall survival of melanoma patients. CONCLUSIONS: In this study, several hub genes were found from normal skin, primary melanoma and metastatic melanoma samples. These hub genes may play an important role in the production, invasion, recurrence or death of CM, and may provide new ideas and potential targets for its diagnosis or treatment.

Association of hMSH5 C85T polymorphism with radiation sensitivity of testicular cell lines GC-1, GC-2, TM3, and TM4.

BACKGROUND: The hMSH5 C85T polymorphism, which encodes hMSH5 P29S, is associated with individual differences in spermatogenic abnormalities caused by ionizing radiation (IR), but the molecular mechanisms remain unclear. OBJECTIVES: This manuscript aims to explore the role of hMSH5 C85T polymorphism in IR-induced individual differences in spermatogenic abnormalities. MATERIAL AND METHODS: We transfected pcDNA-hMSH5P29S vector into mouse spermatogonia GC-1, mouse spermatocytes GC-2, mouse testicular mesenchymal cells TM3, and mouse testicular support cells TM4. After radiation, we evaluated cell survival with colony formation assay, apoptosis with TUNEL assay and caspase-3 activity assay, DNA damage with comet assay and an in vivo NHEJ activity assay. RESULTS: Results showed that only spermatocytes GC-2 transfected with pcDNA-hMSH5P29S vector had significant differences in IR-induced cell survival and apoptosis when compared to that transfected with pcDNA empty vector and pcDNA-wild-hMSH5 vector, while there was no statistical difference in GC-1, TM3, and TM4. In addition, comet assay showed that the DNA damage of GC-2 transfected with pcDNA-hMSH5P29S vector increased significantly compared to that transfected with pcDNA empty vector and pcDNA-wild-hMSH5 vector after IR. And in vivo NHEJ activity assay showed that the NHEJ activity of GC-2 transfected with pcDNA-hMSH5P29S vector was statistically higher than that transfected with pcDNA empty vector and pcDNA-wild-hMSH5 vector. CONCLUSION: Our study indicates that the hMSH5 C85T polymorphism leads to an abnormal increase in apoptosis and lessen the control on error-prone NHEJ of spermatocyte GC-2, thereby altering the difference of radiation sensitivity of spermatogenesis.

Identification of key genes and multiple molecular pathways of metastatic process in prostate cancer.

BACKGROUND: Cancer metastasis is well known as the most adverse outcome and the major cause of mortality in cancer patients, including prostate cancer (PCa). There are no credible predictors, to this day, that can reflect the metastatic ability of localized PCa. In the present study, we firstly identified the differentially expressed genes (DEGs) and molecular pathways involved in the metastaic process of PCa by comparing gene expressions of metastaic PCa with localized PCa directly, with the purpose of identifying potential markers or therapeutic targets. METHODS: The gene expression profiles (GSE6919 and GSE32269) were downloaded from the Gene Expression Omnibus database, which contained 141 tissue samples, including 87 primary localized PCa samples and 54 metastaic PCa samples. After data processing, DEGs were identified by R language using the Student's t-test adjusted via the Beniamini-Hochberg method. Subsequently, the gene ontology functional and pathway enrichment analyses of DEGs were performed and the protein-protein interaction network was constructed. Hub genes were identified using the plug-in cytoHubba in Cytoscape software by MCC and degree. Furthermore, validation and prognostic significance analysis of the hub genes were performed by UALCAN and gene expression profiling interactive analysis (GEPIA). RESULTS: A total of 90 DEGs were identified between localized and metastaic PCa, which consisted of 47 upregulated and 43 downregulated genes. The enriched functions and pathways of the DEGs include catabolic process, cell cycle, response to steroid hormone, extracellular matrix (ECM)-receptor interaction and vascular smooth muscle contraction. A total of 10 genes were identified as hub genes and biological process analysis of hub genes showed that cell cycle phase, cell division, and mitotic cell cycle process were mainly enriched. The expression of hub genes were confirmed in metastaic PCa when compared with localized PCa tissues by The Cancer Genome Atlas database. Moreover, the disease-free survival analysis of hub genes revealed that these genes may play an important role in invasion, progression or recurrence. Therefore, these hub genes might be the key genes contributed to tumor progression or metastasis in PCa and provide candidate therapeutic targets for PCa. CONCLUSIONS: The present study identified some DEGs between localized and metastaic PCa tissue samples. These key genes might be potential therapeutic targets and biomarkers for the metastaic process of PCa.

Study of the time-domain electromagnetic pulse standard field generation setup and its application.

In this paper, a time-domain electromagnetic pulse standard field generation setup was designed and manufactured for transient electromagnetic pulse sensor calibration. The calibration setup is based on the mono-cone structure. It can produce a calculated electromagnetic pulse field with the electric field intensity from 100 V/m to 600 V/m. The quantity of the electric field intensity is traced to the national primary standard of the pulse parameter, the S parameter, and the length quantity. The standard uncertainty of the produced electric field is 2.4%. The waveform and field distribution of the standard field were verified by experiment. Based on this facility, the calibration methods and uncertainty evaluation methods for two types of electromagnetic pulse sensors (TEM horn and D-dot sensor) were proposed. Finally, we obtained the calibration results of the sensors. The standard uncertainties of the calibration are 3.6% for the TEM horn and 3.0% for the D-dot sensor.

A neural network model for the orbitofrontal cortex and task space acquisition during reinforcement learning.

Reinforcement learning has been widely used in explaining animal behavior. In reinforcement learning, the agent learns the value of the states in the task, collectively constituting the task state space, and uses the knowledge to choose actions and acquire desired outcomes. It has been proposed that the orbitofrontal cortex (OFC) encodes the task state space during reinforcement learning. However, it is not well understood how the OFC acquires and stores task state information. Here, we propose a neural network model based on reservoir computing. Reservoir networks exhibit heterogeneous and dynamic activity patterns that are suitable to encode task states. The information can be extracted by a linear readout trained with reinforcement learning. We demonstrate how the network acquires and stores task structures. The network exhibits reinforcement learning behavior and its aspects resemble experimental findings of the OFC. Our study provides a theoretical explanation of how the OFC may contribute to reinforcement learning and a new approach to understanding the neural mechanism underlying reinforcement learning.

Efficient reinforcement learning of a reservoir network model of parametric working memory achieved with a cluster population winner-take-all readout mechanism.

The brain often has to make decisions based on information stored in working memory, but the neural circuitry underlying working memory is not fully understood. Many theoretical efforts have been focused on modeling the persistent delay period activity in the prefrontal areas that is believed to represent working memory. Recent experiments reveal that the delay period activity in the prefrontal cortex is neither static nor homogeneous as previously assumed. Models based on reservoir networks have been proposed to model such a dynamical activity pattern. The connections between neurons within a reservoir are random and do not require explicit tuning. Information storage does not depend on the stable states of the network. However, it is not clear how the encoded information can be retrieved for decision making with a biologically realistic algorithm. We therefore built a reservoir-based neural network to model the neuronal responses of the prefrontal cortex in a somatosensory delayed discrimination task. We first illustrate that the neurons in the reservoir exhibit a heterogeneous and dynamical delay period activity observed in previous experiments. Then we show that a cluster population circuit decodes the information from the reservoir with a winner-take-all mechanism and contributes to the decision making. Finally, we show that the model achieves a good performance rapidly by shaping only the readout with reinforcement learning. Our model reproduces important features of previous behavior and neurophysiology data. We illustrate for the first time how task-specific information stored in a reservoir network can be retrieved with a biologically plausible reinforcement learning training scheme.

Water quality monitoring using abnormal tail-beat frequency of crucian carp.

Fish are rapidly becoming favored as convenient sentinels for behavioral assays of toxic chemical exposure. Tail-beat frequency (TBF) of fish is highly correlated with swimming speed, which has been used to detect toxicants. Here we examined the effect on TBF of exposure to two chemicals, and evaluated the ability of this novel behavioral parameter to accurately monitor water quality. To further refine our approach, the Wall-hitting rate (WHR) was used to characterize behavioral avoidance after exposure. Overall, exposure to test chemicals at different levels induced significant increase in both behavioral parameters of the red crucian carp during 1-h exposure periods. Furthermore, the TBF achieved better performance as an indicator when it was calculated in cases where the fish hit the tank wall. Collectively, this study demonstrates the capacity of the TBF of fish to assess water quality in a reliable manner.