Entropy measures to study and model long term simultaneous evolution of children in Doose and Lennox-Gastaut syndromes

Stress Response Analysis via Dynamic Entropy in EEG: Caregivers in View

According to the World Health Organization (WHO), stress can be defined as any type of alteration that causes physical, emotional, or psychological tension. A very important concept that is sometimes confused with stress is anxiety. The difference between stress and anxiety is that stress usually has an existing cause. Once that activator has passed, stress typically eases. In this respect, according to the American Psychiatric Association, anxiety is a normal response to stress and can even be advantageous in some circumstances. By contrast, anxiety disorders differ from temporary feelings of anxiousness or nervousness with more intense feelings of fear or anxiety. The Diagnostic and Statistical Manual (DSM-5) explicitly describes anxiety as exorbitant concern and fearful expectations, occurring on most days for at least 6 months, about a series of events. Stress can be measured by some standardized questionnaires; however, these resources are characterized by some major disadvantages, the main one being the time consumed to interpret them; i.e., qualitative information must be transformed to quantitative data. Conversely, a physiological recourse has the advantage that it provides quantitative spatiotemporal information directly from brain areas and it processes data faster than qualitative supplies. A typical option for this is an electroencephalographic record (EEG). We propose, as a novelty, the application of time series (TS) entropies developed by us to inspect collections of EEGs obtained during stress situations. We investigated this database related to 23 persons, with 1920 samples (15 s) captured in 14 channels for 12 stressful events. Our parameters reflected that out of 12 events, event 2 (Family/financial instability/maltreatment) and 10 (Fear of disease and missing an important event) created more tension than the others. In addition, the most active lobes reflected by the EEG channels were frontal and temporal. The former is in charge of performing higher functions, self-control, self monitoring, and the latter is in charge of auditory processing, but also emotional handling. Thus, events E2 and E10 triggering frontal and temporal channels revealed the actual state of participants under stressful situations. The coefficient of variation revealed that E7 (Fear of getting cheated/losing someone) and E11 (Fear of suffering a serious illness) were the events with more changes among participants. In the same sense, AF4, FC5, and F7 (mainly frontal lobe channels) were the most irregular on average for all participants. In summary, by means of dynamic entropy analysis, the goal is to process the EEG dataset in order to elucidate which event and brain regions are key for all participants. The latter will allow us to easily determine which was the most stressful and on which brain zone. This study can be applied to other caregivers datasets. All this is a novelty.

MicroRNA-802 promotes the progression of osteosarcoma through targeting p27 and activating PI3K/AKT pathway

PURPOSE

Increasing evidences suggest dysfunctions of microRNAs (miRNAs) are playing important part in tumors. Therefore, the role of miR-802 in osteosarcoma (OS) was exploited. The object was to evaluate the effect of miR-802 and verify its influence on p27 Kip1 (p27) in OS.

METHODS

RT-qPCR experiment was used to detect miR-802 and p27 expression in OS tissues and cells. We explored the function of miR-802 through Transwell assays. The phosphoinositide 3-kinase (PI3K)/AKT serine/threonine kinase pathway and epithelial-mesenchymal transition (EMT) was detected by Western blot assays. Luciferase assay was used to testify the target of miR-802.

RESULTS

MiR-802 expression was elevated in OS, which was related to poor clinical outcome in OS patients. MiR-802 overexpression promoted OS migration, invasion and EMT. Further, p27 is a direct target of miR-802. P27 elevation counteracted the promotion effect of OS on EMT, migration and invasion induced by miR-802. In addition, miR-802 overexpression inactivated PI3K/AKT pathway via targeting p27 in OS.

CONCLUSION

MiR-802 promoted the progress of EMT, migration and invasion in OS via targeting p27. This newly identified miR-802/p27/PI3K/AKT axis may represent potential targets for OS.

Measuring the effects of sleep on epileptogenicity with multifrequency entropy

OBJECTIVE

We demonstrate that multifrequency entropy gives insight into the relationship between epileptogenicity and sleep, and forms the basis for an improved measure of medical assessment of sleep impairment in epilepsy patients.

METHODS

Multifrequency entropy was computed from electroencephalography measurements taken from 31 children with Benign Epilepsy with Centrotemporal Spikes and 31 non-epileptic controls while awake and during sleep. Values were compared in the epileptic zone and away from the epileptic zone in various sleep stages.

RESULTS

We find that (I) in lower frequencies, multifrequency entropy decreases during non-rapid eye movement sleep stages when compared with wakefulness in a general population of pediatric patients, (II) patients with Benign Epilepsy with Centrotemporal Spikes had lower multifrequency entropy across stages of sleep and wakefulness, and (III) the epileptic regions of the brain exhibit lower multifrequency entropy patterns than the rest of the brain in epilepsy patients.

CONCLUSIONS

Our results show that multifrequency entropy decreases during sleep, particularly sleep stage 2, confirming, in a pediatric population, an association between sleep, lower multifrequency entropy, and increased likelihood of seizure.

SIGNIFICANCE

We observed a correlation between lowered multifrequency entropy and increased epileptogenicity that lays preliminary groundwork for the detection of a digital biomarker for epileptogenicity.

Are the new mobile wireless EEG headsets reliable for the evaluation of musical pleasure?

Since the beginning of the 20th century, electroencephalography (EEG) has been used in a wide variety of applications, both for medical needs and for the study of various cerebral processes. With the rapid development of the technique, more and more precise and advanced tools have emerged for research purposes. However, the main constraints of these devices have often been the high price and, for some devices the low transportability and the long set-up time. Nevertheless, a broad range of wireless EEG devices have emerged on the market without these constraints, but with a lower signal quality. The development of EEG recording on multiple participants simultaneously, and new technological solutions provides further possibilities to understand the cerebral emotional dynamics of a group. A great number of studies have compared and tested many mobile devices, but have provided contradictory results. It is therefore important to test the reliability of specific wireless devices in a specific research context before developing a large-scale study. The aim of this study was to assess the reliability of two wireless devices (g.tech Nautilus SAHARA electrodes and Emotiv™ Epoc +) for the detection of musical emotions, in comparison with a gold standard EEG device. Sixteen participants reported feeling emotional pleasure (from low pleasure up to musical chills) when listening to their favorite chill-inducing musical excerpts. In terms of emotion detection, our results show statistically significant concordance between Epoc + and the gold standard device in the left prefrontal and left temporal areas in the alpha frequency band. We validated the use of the Emotiv™ Epoc + for research into musical emotion. We did not find any significant concordance between g.tech and the gold standard. This suggests that Emotiv Epoc is more appropriate for musical emotion investigations in natural settings.

Impairment of Cardiac Autonomic Nerve Function in Pre-school Children With Intractable Epilepsy

Objective: Intractable epilepsy and uncontrolled seizures could affect cardiac function and the autonomic nerve system with a negative impact on children's growth. The aim of this study was to investigate the variability and complexity of cardiac autonomic function in pre-school children with pediatric intractable epilepsy (PIE). Methods: Twenty four-hour Holter electrocardiograms (ECGs) from 93 patients and 46 healthy control subjects aged 3-6 years were analyzed by the methods of traditional heart rate variability (HRV), multiscale entropy (MSE), and Kurths-Wessel symbolization entropy (KWSE). Receiver operating characteristic (ROC) curve analysis was used to estimate the overall discrimination ability. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) models were also analyzed. Results: Pre-school children with PIE had significantly lower HRV measurements than healthy controls in time (Mean_RR, SDRR, RMSSD, pNN50) and frequency (VLF, LF, HF, LF/HF, TP) domains. For the MSE analysis, area 1_5 in awake state was lower, and areas 6_15 and 6_20 in sleep state were higher in PIE with a significant statistical difference. KWSE in the PIE group was also inferior to that in healthy controls. In ROC curve analysis, pNN50 had the greatest discriminatory power for PIE. Based on both NRI and IDI models, the combination of MSE indices (wake: area1_5 and sleep: area6_20) and KWSE (m = 2, τ = 1, α = 0.16) with traditional HRV measures had greater discriminatory power than any of the single HRV measures. Significance: Impaired HRV and complexity were found in pre-school children with PIE. HRV, MSE, and KWSE could discriminate patients with PIE from subjects with normal cardiac complexity. These findings suggested that the MSE and KWSE methods may be helpful for assessing and understanding heart rate dynamics in younger children with epilepsy.

MicroRNA-466 inhibits osteosarcoma cell proliferation and induces apoptosis by targeting CCND1

Emerging pieces of evidence indicate that microRNA-466 (miR-466) serves as a tumor suppressor in several human tumors, including colorectal cancer and prostate cancer. However, whether miR-466 is involved in osteosarcoma (OS) progression remains largely unknown. The present study demonstrated that miR-466 was significantly downregulated in OS tissues and cell lines. Furthermore, it was revealed that the expression of miR-466 was negatively correlated with OS severity. Moreover, low miR-466 expression in patients with OS predicted poor prognosis. Through functional experiments, miR-466 overexpression significantly inhibited the proliferation and cell cycle of OS cells while inducing cellular apoptosis. In terms of mechanism, it was revealed that CCND1 was a target of miR-466 in OS cells. miR-466 overexpression suppressed CCND1 expression in OS cells. A reverse association was observed between the expression levels of miR-466 and CCND1 in OS tissues. Furthermore, CCND1 restoration in OS cells significantly rescued the effects of miR-466 on cellular proliferation and apoptosis. Overall, the results of the present study demonstrated that miR-466 suppressed OS progression by targeting CCND1, suggesting that miR-466 may be a promising biomarker and therapeutic target for OS prognosis and treatment.

Chronic vagus nerve stimulation reverses heart rhythm complexity in patients with drug-resistant epilepsy: An assessment with multiscale entropy analysis

OBJECTIVE

Vagus nerve stimulation (VNS) is an adjunctive treatment in drug-resistant epilepsy. The alterations in heart rate dynamics through VNS are not well understood. This study aimed to determine changes in heart rhythm complexity in association with VNS and to relate the findings to the outcome of VNS treatment in patients with drug-resistant epilepsy.

METHODS

We prospectively analyzed 32 patients with drug-resistant epilepsy, who underwent VNS implantation, and 32 age- and sex-matched healthy control subjects. The interictal heartbeat intervals were analyzed using the heart rhythm complexity with multiscale entropy (MSE) and traditional heart rate variability (HRV) analyses based on ambulatory 24-hour electrocardiograms (ECGs).

RESULTS

Patients had significantly decreased complexity indices (Slope 5, Area 1-5, Area 6-15, Area 6-20) on MSE analysis and decreased HRV measurements (standard deviation of the heartbeat interval (SDNN), square root of the mean of sum of squares of the differences between adjacent RR intervals (RMSSD), pNN50, very low frequency (VLF), low frequency (LF), high frequency (HF), total power (TP)) in time and frequency domain analyses. After one year of VNS treatment in patients with drug-resistant epilepsy, there was a trend in an elevated MSE profile with significant higher values between the scales 1 and 9. Vagus nerve stimulation induces a more significant increase of MSE in VNS responders than those in the nonresponders. The conventional HRV measurements did not change.

CONCLUSION

Our results suggest that heart rhythm complexity is impaired in patients with drug-resistant epilepsy, and this is at least partially reversed by VNS treatment. Furthermore, VNS-induced effects on heart rate complexity may be associated with the therapeutic response to VNS in patients with drug-resistant epilepsy.

Downregulation of miR‑135a predicts poor prognosis in acute myeloid leukemia and regulates leukemia progression via modulating HOXA10 expression

MicroRNA‑135a (miR‑135a) has been shown to exert important roles in various human cancer types, such as glioblastoma, thyroid carcinoma and renal carcinoma. However, the function of miR‑135a in acute myeloid leukemia (AML) remains largely unknown. In the present study, it was demonstrated that miR‑135a expression was significantly downregulated in AML cells compared with normal control cells. Furthermore, the downregulation of miR‑135a in patients with AML predicted poor prognosis. Through functional experiments, overexpression of miR‑135a was demonstrated to significantly inhibit the proliferation and cell cycle of AML cells, while it promoted cellular apoptosis. miR‑135a directly targeted HOXA10 in AML cells. miR‑135a overexpression significantly suppressed the mRNA and protein levels of HOXA10 in AML cells. Moreover, there was an inverse association between miR‑135a expression and HOXA10 level in AML samples. Additionally, by ectopic expression of HOXA10, restoration of HOXA10 significantly abolished the effects of miR‑135a overexpression on AML cell proliferation, cell cycle and apoptosis. In conclusion, the present study demonstrated that miR‑135a serves as a tumor suppressor in AML by targeting HOXA10, and miR‑135a may be a promising prognostic biomarker for AML patients.

miR-223-5p Suppresses Tumor Growth and Metastasis in Non-Small Cell Lung Cancer by Targeting E2F8

miR-223-5p has been demonstrated to regulate the development and progression of various cancers, such as hepatocellular carcinoma, breast cancer, and gastric carcinoma. However, the role of miR-223-5p in non-small cell lung cancer (NSCLC) requires further investigation. In this study, we found that the expression of miR-223-5p was significantly downregulated in NSCLC tissues and cell lines. Moreover, the expression level of miR-223-5p is negatively correlated with the malignance of NSCLC. We found that overexpression of miR-223-5p remarkably suppressed the proliferation of NSCLC cells in vitro and in vivo. miR-223-5p overexpression also led to reduced migration and invasion in NSCLC cells. Mechanistically, we found that E2F8, a key transcription factor involved in many kinds of biological processes, was a direct target gene of miR-223-5p. Overexpression of miR-223-5p significantly decreased the mRNA and protein levels of E2F8 in NSCLC cells. We also showed that restoration of E2F8 rescued the proliferation, migration, and invasion of miR-223-5p-overexpressing NSCLC cells. Taken together, our findings demonstrated that miR-223-5p suppressed NSCLC progression through targeting E2F8.

Preoperative Heart Rate Variability as Predictors of Vagus Nerve Stimulation Outcome in Patients with Drug-resistant Epilepsy

Vagus nerve stimulation (VNS) is an adjunctive treatment for drug-resistant epilepsy (DRE). However, it is still difficult to predict which patients will respond to VNS treatment and to what extent. We aim to explore the relationship between preoperative heart rate variability (HRV) and VNS outcome. 50 healthy control subjects and 63 DRE patients who had received VNS implants and had at least one year of follow up were included. The preoperative HRV were analyzed by traditional linear methods and heart rhythm complexity analyses with multiscale entropy (MSE). DRE patients had significantly lower complexity indices (CI) as well as traditional linear HRV measurements than healthy controls. We also found that non-responders₀ had significantly lower preoperative CI including Area 1-5, Area 6-15 and Area 6-20 than those in the responders₀ while those of the non-responders₅₀ had significantly lower RMSSD, pNN50, VLF, LF, HF, TP and LF/HF than the responders₅₀. In receiver operating characteristic (ROC) curve analysis, Area 6-20 and RMSSD had the greatest discriminatory power for the responders₀ and non-responders₀, responders₅₀ and non-responders₅₀, respectively. Our results suggest that preoperative assessment of HRV by linear and MSE analysis can help in predicting VNS outcomes in patients with DRE.

Impairment of heart rhythm complexity in patients with drug-resistant epilepsy: An assessment with multiscale entropy analysis

OBJECTIVE

Epilepsy and seizures can have dramatic effects on the cardiac function. The aim of this study was to investigate the heart rhythm complexity in patients with drug-resistant epilepsy (DRE).

METHODS

Ambulatory 24-h electrocardiograms (ECG) from 70 DRE patients and 50 healthy control subjects were analyzed using conventional heart rate variability (HRV) and multiscale entropy (MSE) methods The variation of complexity indices (CI), which was calculated from MSE profile, was determined.

RESULTS

DRE patients had significantly lower time domain (Mean RR, SDNN, RMSSD, pNN50) and frequency domain (VLF, LF, HF, TP) HRV measurements than healthy controls. Of the MSE analysis, MSE profile, CI including Slope 5, Area 1-5, Area 6-15 and Area 6-20 were significantly lower than those in the healthy control group. In receiver operating characteristic (ROC) curve analysis, VLF had the greatest discriminatory power for the two groups. In both net reclassification improvement (NRI) model and integrated discrimination improvement (IDI) models, CI derived from MSE profiles significantly improved the discriminatory power of Mean RR, SDNN, RMSSD, pNN50, VLF, LF, HF and TP.

SIGNIFICANCE

The heart rate complexity is impaired for DRE patients. CI are useful to discriminate DRE patients from subjects with normal cardiac complexity. These findings indicate that MSE method may serve as a complementary approach for characterizing and understanding abnormal heart rate dynamics in epilepsy. Furthermore, the CI may potentially be used as a biomarker in monitoring epilepsy.

Dynamic complexity measures and entropy paths for modelling and comparison of evolution of patients with drug resistant epileptic encephalopathy syndromes (DREES)

Epileptic encephalopathies (EE) is a term coined by the International League Against Epilepsy (ILAE) to refer to a group of epilepsies in which the ictal and interictal abnormalities may contribute to progressive cerebral dysfunction. Among them, two affect mainly children and are very difficult to deal with, Doose and Lennox-Gastaut syndromes, (DS and LGS, respectively). So far (Zavala-Yoe et al., J Integr Neurosci 15(2):205-223, 2015a and works of ours there), quantitative analysis of single case studies of EE have been performed. All of them are manifestations of drug resistant epileptic encephalopathies (DREES) and as known, such disorders require a lot of EEG studies through all patient's life. As a consequence, dozens of EEG records are stored by parents and neurologists as time goes by. However, taking into account all this massive information, our research questions (keeping colloquial wording by parents) arise: a) Which zone of the brain has been the most affected so far? b) On which year was the child better? c) How bad is our child with respect to others? We must reflect that despite clinical assessment of the EEG has undergone standardization by establishment of guidelines such as the recently published guidelines of the American Clinical Neurophysiology Society (Tsuchida et al., J Clin Neurophysiol 4(33):301-302, 2016), qualitative EEG will never be as objective as quantitative EEG, since it depends largely on the education and experience of the conducting neurophysiologist (Grant et al., Epilepsy Behav 2014(32):102-107, 2014, Rating, Z Epileptologie, Springer Med 27(2):139-142, 2014). We already answered quantitatively the above mentioned questions in the references of ours given above where we provided entropy curves and an entropy index which encompasses the complexity of bunches of EEG making possible to deal with massive data and to make objective comparisons among some patients simultaneously. However, we have refined that index here and we also offer another two measures which are spatial and dynamic. Moreover, from those indices we also provide what we call a temporal dynamic complexity path which shows in a standard 10-20 system head diagram the evolution of the lowest complexity per brain zone with respect to the EEG period. These results make it possible to compare quantitatively/graphically the progress of several patients at the same time, answering the questions posed above. The results obtained showed that we can associate low spatio-temporal entropy indices to multiple seizures events in several patients at the same time as well as tracking seizure progress in space and time with our entropy path, coinciding with neurophysiologists observations.