Automatic Localization of Seizure Onset Zone Based on Multi-Epileptogenic Biomarkers Analysis of Single-Contact from Interictal SEEG.

Successful surgery on drug-resistant epilepsy patients (DRE) needs precise localization of the seizure onset zone (SOZ). Previous studies analyzing this issue still face limitations, such as inadequate analysis of features, low sensitivity and limited generality. Our study proposed an innovative and effective SOZ localization method based on multiple epileptogenic biomarkers (spike and HFOs), and analysis of single-contact (MEBM-SC) to address the above problems. We extracted contacts epileptic features from signal distributions and signal energy based on machine learning and end-to-end deep learning. Among them, a normalized pathological ripple rate was designed to reduce the disturbance of physiological ripple and enhance the performance of SOZ localization. Then, a feature selection algorithm based on Shapley value and hypothetical testing (ShapHT+) was used to limit interference from irrelevant features. Moreover, an attention mechanism and a focal loss algorithm were used on the classifier to learn significant features and overcome the unbalance of SOZ/nSOZ contacts. Finally, we provided an SOZ prediction and visualization on magnetic resonance imaging (MRI). Ten patients with DRE were selected to verify our method. The experiment performed cross-validation and revealed that MEBM-SC obtains higher sensitivity. Additionally, the spike has better sensitivity while HFOs have better specificity, and the combination of these biomarkers can achieve the best performance. The study confirmed that MEBM-SC can increase the sensitivity and accuracy of SOZ localization and help clinicians to perform a precise and reliable preoperative evaluation based on interictal SEEG.

[Clinical application of adaptive minute ventilation + IntelliCycle ventilation mode in patients with mild-to-moderate acute respiratory distress syndrome].

OBJECTIVE: To verify the clinical safety and efficacy of new intelligent ventilation mode adaptive minute ventilation (AMV)+IntelliCycle ventilation in patients with mild-to-moderate acute respiratory distress syndrome (ARDS). METHODS: The patients with mild-to-moderate ARDS, admitted to intensive care unit (ICU) of the First Affiliated Hospital of Jinzhou Medical University from February 2018 to February 2019, were enrolled in the study. The patients were divided into synchronous intermittent mandatory ventilation+pressure support ventilation (SIMV+PSV) group and AMV+IntelliCycle group according to the random number table method. All patients were given mechanical ventilation, anti-infection, analgesia and sedation, nutritional support and symptomatic treatment of primary disease after admission. SV800 ventilator was used for mechanical ventilation. In the AMV+IntelliCycle group, after setting the minute ventilation volume (VE), inhaled oxygen concentration (FiO2) and positive end expiratory pressure (PEEP), the ventilator was turned on the full-automatic mode, and the preset value of VE percentage was 120%. In the SIMV+PSV group, the ventilator parameters were set as follows: the ventilation frequency was 12-20 times/min, the inspiratory expiratory ratio was 1:1-2, the peak inspiratory pressure (PIP) limit level was 35-45 cmH2O (1 cmH2O = 0.098 kPa), and the setting of FiO2 and PEEP was as the same as that of AMV+IntelliCycle group, the triggering flow was set to 2 L/min. All of the clinical parameters between the two groups were compared. The main outcomes were duration of mechanical ventilation, ventilator alarm times, manual operation times, and the mechanical power; the secondary outcomes were respiratory rate (RR), VE, tidal volume (VT), PIP, mouth occlusion pressure (P0.1), static compliance (Cst), work of breathing (WOB), and time constant at 0, 6, 12, 24, 48, 72, and 120 hours; and the blood gas analysis parameters of patients before and after ventilation were recorded. RESULTS: A total of 92 patients with mild-to-moderate ARDS were admitted during the study period, excluding those who quit the study due to death, abandonment of treatment, accidental extubation of tracheal intubation and so on. Eighty patients were finally enrolled in the analysis, with 40 patients in SIMV+PSV group and AMV+IntelliCycle group respectively. (1) Results of main outcomes: compared with the SIMV+PSV mode, AMV+IntelliCycle ventilation mode could shorten the duration of mechanical ventilation (hours: 106.35±55.03 vs. 136.50±73.78), reduce ventilator alarm times (times: 10.35±5.87 vs. 13.93±6.87) and the manual operations times (times: 4.25±2.01 vs. 6.83±3.75), and decrease the mechanical power (J/min: 12.88±4.67 vs. 16.35±5.04, all P < 0.05). But the arterial partial pressure of carbon dioxide (PaCO2) of AMV+IntelliCycle group was significantly higher than that of SIMV+PSV group [mmHg (1 mmHg = 0.133 kPa): 41.58±6.81 vs. 38.45±5.77, P < 0.05]. (2) Results of secondary outcomes: the RR of both groups was improved significantly with the prolongation of ventilation time which showed a time effect (F = 4.131, P = 0.005). Moreover, compared with SIMV+PSV mode, AMV+IntelliCycle mode could maintain a better level of RR, with intervention effect (F = 5.008, P = 0.031), but no interaction effect was found (F = 2.489, P = 0.055). There was no significant difference in VE, PIP, P0.1 or Cst between the two groups, without intervention effect (F values were 3.343, 2.047, 0.496, 1.456, respectively, all P > 0.05), but they were significantly improved with the prolongation of ventilation time in both groups, with time effect (F values were 2.923, 12.870, 23.120, 7.851, respectively, all P < 0.05), but no interaction effect was found (F values were 1.571, 1.291, 0.300, 0.354, respectively, all P > 0.05). The VT, WOB or time constant in both groups showed no significant changes with the prolongation of ventilation time, and no significant difference was found between the two groups, there was neither time effect (F values were 0.613, 1.049, 2.087, respectively, all P > 0.05) nor intervention effect (F values were 1.459, 0.514, 0.923, respectively, all P > 0.05). CONCLUSIONS: AMV+IntelliCycle ventilation mode can shorten the ventilation time of patients with mild-to-moderate ARDS, reduce mechanical power, and reduce the workload of medical care, but PaCO2 in the patients with AMV+IntelliCycle mode is higher than that in the patients with SIMV+PSV mode.

Silencing of PHLPP1 promotes neuronal apoptosis and inhibits functional recovery after spinal cord injury in mice.

AIM: Spinal cord injury (SCI) causes increased apoptosis of neurons, leading to irreversible dysfunction of the spinal cord. In this study, we investigated the effects of the progression of SCI and potential regulation of apoptosis after the Pleckstrin homology (PH) domain and leucine rich repeat protein phosphatase 1 (PHLPP1) gene was silenced. MAIN METHODS: Spinal cord injection, and neuronal transfection with a recombinant adenovirus vector encoding small interfering RNA (siRNA) against PHLPP1 (AdsiPHLPP1) successfully silenced PHLPP1. These created in vivo and in vitro PHLPP1-silenced models, respectively, resulting in stable expression of the transgene in neurons. KEY FINDINGS: The results showed that silencing of PHLPP1 evidently reduced levels of the nuclear factor erythroid 2-related factor 2 (Nrf2) after SCI. Western blot analysis revealed that the mice injected with AdsiPHLPP1 showed increased the expression of pro-apoptotic factors (Bax and cleaved-caspase 3), and reduced levels of neurotrophic (BDNF) and anti-apoptotic (Bcl-2) factors, both in vivo and in vitro. The motor function of AdsiPHLPP1-injected mice was restored more slowly than that of wild type (WT) mice. In addition, the number of motor neurons surviving in the anterior horn of the spinal cord was also reduced after SCI. SIGNIFICANCE: Our results confirm that silencing of PHLPP1 promotes neuronal apoptosis and inhibits functional recovery after injury in vivo and in vitro. Consequently, PHLPP1 represents a potential therapeutic target gene for the clinical treatment of SCI.