Resting state electroencephalographic brain activity in neonates can predict age and is indicative of neurodevelopmental outcome.

OBJECTIVE: Electroencephalography (EEG) can be used to estimate neonates' biological brain age. Discrepancies between postmenstrual age and brain age, termed the brain age gap, can potentially quantify maturational deviation. Existing brain age EEG models are not well suited to clinical cot-side use for estimating neonates' brain age gap due to their dependency on relatively large data and pre-processing requirements. METHODS: We trained a deep learning model on resting state EEG data from preterm neonates with normal neurodevelopmental Bayley Scale of Infant and Toddler Development (BSID) outcomes, using substantially reduced data requirements. We subsequently tested this model in two independent datasets from two clinical sites. RESULTS: In both test datasets, using only 20 min of resting-state EEG activity from a single channel, the model generated accurate age predictions: mean absolute error = 1.03 weeks (p-value = 0.0001) and 0.98 weeks (p-value = 0.0001). In one test dataset, where 9-month follow-up BSID outcomes were available, the average neonatal brain age gap in the severe abnormal outcome group was significantly larger than that of the normal outcome group: difference in mean brain age gap = 0.50 weeks (p-value = 0.04). CONCLUSIONS: These findings demonstrate that the deep learning model generalises to independent datasets from two clinical sites, and that the model's brain age gap magnitudes differ between neonates with normal and severe abnormal follow-up neurodevelopmental outcomes. SIGNIFICANCE: The magnitude of neonates' brain age gap, estimated using only 20 min of resting state EEG data from a single channel, can encode information of clinical neurodevelopmental value.

Ecological assessment of Iran's terrestrial biomes for wildlife conservation.

Man-made activities pose the greatest threats to wildlife in Iran's terrestrial biomes, causing significant habitat damage and fragmentation in recent years. To fully understand these threats, the present study was conducted to identify and map the Iran's terrestrial biomes using the IDRISI TerrSet 18.31 Software, the Terrestrial Biomes Ecosystem Service Modeler on the InVEST toolkit (TBESMI), and comprehensive data sources including maps of roads, protected areas, terrestrial biomes, and country-wide land cover maps of 2017. The results showed that the largest terrestrial biome in Iran is deserts and xeric shrublands (DXS), while flooded grasslands and savannas (FGS) is the smallest biome. Roads, along with urban and agricultural developments are among the biggest threats and most destructive stressors in Iran's terrestrial biomes. The results also revealed that there was a growth in destruction of habitats located in the temperate broadleaf and mixed forest (TBMF), temperate coniferous forest (TCF), and FGS, alongside a decrease in the DXS biome. Furthermore, we detected an increase in habitat landscape quality in the DXS, FGS and montane grasslands and shrub lands (MGS), and a decrease in the temperate grasslands, savannas and shrublands (TGSS) and TBMF biomes. Finally, the cumulative risk of habitat degradation increased in the FGS, TCF, TGSS, and TBMF biomes, whereas it decreased in the DXS biome. The FGS biome with the highest consequence cumulative score, and the MGS biome with the highest cumulative risk exposure score were found to be at the highest risk from man-made activities. Stressors associated with agriculture and urbanization had the highest cumulative exposure scores in the MGS, while roads had the highest exposure scores in the TBMF and DXS biomes. Our study underscores the critical importance of conserving Iran's terrestrial biomes and wildlife, especially in high-risk biomes like FGS and MGS, given the substantial threats posed by human activities.

Associations between RORγt and T-bet Expressions, clinicopathological indices and survival rate in oral Squamous cell carcinoma patients.

BACKGROUND: Oral cancers are the sixth most common cancers around the world. According to the pivotal role of immune cells in the pathogenesis of oral squamous cell carcinoma (OSCC), as the frequent form of malignant epithelial neoplasm in the oral cavity, we investigated the association between the expression of RORγt and T-bet genes as two transcription factors, clinicopathologic indices, and survival rate. METHODS AND MATERIALS: Forty-two OSCC paraffin embded-blocks tissue samples and their surgical healthy margins (as a control group) were collected. Demographic information like age and gender, and medical history including tumor stage/grade, and following-up time were registered. The RORγt and T-bet expression were assessed by qPCR. The overall survival (OS) and disease free survival (DFS) were analyzed by SPSS V.23 software. RESULTS: The expression of RORγt and T-bet genes in OSCC patients were significantly higher than in surgical healthy margins (P < 0.001). Both expression demonstrated a significant difference between surgical healthy margins and tumor tissues related to gender and clinicopathological indices including stage and grade (P < 0.05). The expression of both genes in stage I patients was significant compared to stage IV (P < 0.05). The relation between expressions, OS, and DFS with clinical stage and histological grade of tumors was not statistically significant (P > 0.05). CONCLUSION: Overexpression of RORγt and T-bet in OSCC patients with higher grade and stage in compare to surgical healthy margin highlighted their critical role in OSCC pathogenesis including oral epithelial cell differentiation, tumorigenesis process, and malignant transformation. Moreover, both mentioned genes can apply as prognostic biomarkers in OSCC patients. We suggest surgical healthy margin be considered as valuable biological area.

Association between Tissue Expression of Toll-Like Receptor and Some Clinicopathological Indices in Oral Squamous Cell Carcinoma.

Background: The oral squamous cell carcinoma (OSCC) composes about 90% of all head and neck cancers. The toll-like receptor (TLR)+ immune cells have potential of invasion and malignancy transformation. The aim of this study was assessment of possible associations between clinicopathological indices and TLR2 and TLR9 gene expression in OSCC. Methods: Forty-two OSCC samples with related healthy margins including 25 early and 17 advanced stages were gathered. The samples were classified histologically from grade I to II. The expression of TLR2 and TLR2 was evaluated by Real-time PCR. The patient's disease-free survival (DFS) and overall survival (OS) were analyzed using SPSS V.23 software. Results: The expression of TLR2 and TLR9 genes in tumor tissues (especially in grade I and II) were higher than healthy surgical margin tissue (p< 0.001). TLR9 expression in grade II was statistically significant than grade I in tumor tissue (p< 0.001). TLR9 expression in advanced stage was statistically significant in compare to early stage (p= 0.012). In advanced stage both overall survival (p= 0.029) and disease-free survival (p= 0.012) were statistically lower than early stage. The follow-up time to recurrence in advanced stage was statistically lower than early stage (p= 0.007). Conclusion: Overexpression of TLRs 2, 9 play role in the pathogenesis and tumor development of OSCC and can be applied as biomarker in prognostic approaches.

Transient left ventricular dysfunction following chimeric antigen receptor T-cell-mediated encephalopathy: A form of stress cardiomyopathy.

Chimeric antigen receptor (CAR) T-cell therapy represents a new strategy in treating lymphoid malignancies, such as relapsed-refractory diffuse large B-cell lymphoma (DLBCL). Several toxicities including cytokine release syndrome (CRS), neurotoxicity, and cardiovascular toxicity have been linked to CAR T-cell therapy. Transient impairment in left ventricular systolic function is described after CAR-T, however, the mechanism remains poorly understood. This paper reports the clinical presentation and outcome of two patients with relapsed-refractory DLBCL who experienced encephalopathy and CRS following CAR T-cell therapy and developed transient left ventricular dysfunction consistent with stress cardiomyopathy.

Health risk assessment of total chromium in the qanat as historical drinking water supplying system.

This study investigated the health risk assessment of total chromium (CrT) in qanats of South Khorasan, Eastern Iran. For this, concentration of CrT in a total of 83 qanats were measured in summer 2020. Samples were initially tested in the field for temperature, pH, dissolved oxygen (DO), electrical conductivity (EC), and total dissolved solids (TDS). In the lab, collected samples were filtered and fixed with nitric acid (HNO3) for the detection of CrT using inductively coupled plasma mass spectrometry (ICP-MS). Hazard quotient (HQ) and carcinogenic risk assessments were considered to evaluate the risks of CrT to inhabitants. Results showed that concentration of CrT ranged from 1.79 to 1017.05 µg L-1, and a total of 25 stations illuminated CrT concentrations above the WHO standards (50 µg L-1). HQ demonstrated HQ < 1 for 90.37% of studied samples with negligible hazard, whereas 9.63% of stations illuminated HQ ≥ 1 meaning the presence of non-carcinogenic risk for water consumers. Carcinogenic risk (CR) exhibited CR > 1.00E-04 in 81.93% of qanats while 18.07% of stations had 1.00E-06 < CR < 1.00E-04 meaning no acceptable and acceptable CR for the studied qanats, respectively. Zoning map displayed that qanats in the south of South Khorasan possessed the highest HQ, but north regions showed the lowest ones. Together, CrT in qanats of South Khorasan is above the WHO limit, which results in a high risk of carcinogenicity for residents, and in turn, more efforts should be made to provide hygienic groundwater for consumers.

What Is the Effect of Pre-Emptive Oral Montelukast on Postoperative Pain Following Bimaxillary Orthognathic Surgery? A Triple-Blind Randomized Clinical Trial.

PURPOSE: The aim of this study was to assess the effect of preoperative administration of oral montelukast on the amount of postoperative pain following bimaxillary orthognathic surgery. METHODS AND MATERIALS: All healthy skeletal class III deformity candidates for bimaxillary orthognathic surgery were included in this triple-blind randomized clinical trial. The subjects were randomly divided into placebo and montelukast groups. One hour before the surgery, a 10 mL of apple juice was given to each and every patient; however, a 10 mg tablet of montelukast was dissolved in the juice for the intervention group. All operations were performed by the same surgical team, under the same general anesthesia protocols. The outcome variable was the amount of postoperative pain (1-, 3-, 6-, 12-, 18-, and 24-hour intervals) which was measured during the first 24 hours using a Visual Analog Scale. For statistical analysis, the significance level was set at 0.05 using SPSS 23. RESULTS: A total of 60 consecutive patients, comprising 31 females (51.7%) and 29 males (48.3%) with an average age of 25.2 ± 2.2 were recruited. The average surgical duration was 193 ± 28.0 minutes. In general, pain intensity exhibited an increasing trend from the first hour postoperatively, reaching its peak in the 12th hour and decreasing thereafter. Nevertheless, the average amount of pain was significantly higher in the placebo group compared with the montelukast group, in all the studied time intervals (P < .05). The number of patients who required postoperative opioid analgesics was significantly higher in the placebo group compared to the montelukast group (P = .024). Moreover, the duration of surgery had a direct and significant effect on the postoperative pain intensity (P < .001). CONCLUSIONS: It might be concluded that preoperative administration of montelukast is effective in reducing postoperative pain following bimaxillary orthognathic surgery. Further studies are necessary for more relevancy.

A Deep Shared Multi-Scale Inception Network Enables Accurate Neonatal Quiet Sleep Detection With Limited EEG Channels.

In this paper, we introduce a new variation of the Convolutional Neural Network Inception block, called Sinc, for sleep stage classification in premature newborn babies using electroencephalogram (EEG). In practice, there are many medical centres where only a limited number of EEG channels are recorded. Existing automated algorithms mainly use multi-channel EEGs which perform poorly when fewer numbers of channels are available. The proposed Sinc utilizes multi-scale analysis to place emphasis on the temporal EEG information to be less dependent on the number of EEG channels. In Sinc, we increase the receptive fields through Inception while by additionally sharing the filters that have similar receptive fields, overfitting is controlled and the number of trainable parameters dramatically reduced. To train and test this model, 96 longitudinal EEG recordings from 26 premature infants are used. The Sinc-based model significantly outperforms state-of-the-art neonatal quiet sleep detection algorithms, with mean Kappa 0.77 ± 0.01 (with 8-channel EEG) and 0.75 ± 0.01 (with a single bipolar channel EEG). This is the first study using Inception-based networks for EEG analysis that utilizes filter sharing to improve efficiency and trainability. The suggested network can successfully detect quiet sleep stages with even a single EEG channel making it more practical especially in the hospital setting where cerebral function monitoring is predominantly used.

Recombinant activated factor VII in a patient with intracranial hemorrhage and severe thrombocytopenia.

Hemorrhage in patients with hematologic malignancies is often difficult to manage as many of these patients also have coagulopathy and thrombocytopenia of varying severity. Recombinant factor VIIa is a FDA-approved agent for management of bleeding in hemophilia patients with inhibitors. Use of recombinant FVIIa has also been used as a last resort in various clinical settings such as trauma, alveolar hemorrhage, gastrointestinal bleeding, and intracranial hemorrhage for control of bleeding with variable outcomes. This paper presents a case of recombinant FVIIa administration in a patient with multiple myeloma and profound transfusion refractory thrombocytopenia suffering from traumatic subdural hematoma.

The Effect of Reducing the Fasting Time on Postoperative Pain in Orthopaedic Patients: A Randomized Controlled Trial.

BACKGROUND: Patients undergoing orthopedics surgery experience the most severe postoperative pain. The fasting time is a factor that affects this complication. The aim of this study was to investigate the impact of fasting time reduction by using oral carbohydrate on postoperative pain and analgesic consumption in orthopedic patients. MATERIALS AND METHODS: This randomized control trial was conducted between November 2017 and December 2018. Sixty-four patients were randomly assigned into the intervention (which consumed 200 mL of the 12.50% carbohydrate, 2 h before the surgery) and the control group (which was fasted from midnight). Postoperative pain was measured by visual analog scale; the amount of the consumed analgesics was also recorded. The data were analyzed by using Chi-square and t-test. RESULTS: The mean (SD) of the pain scores in the control group immediately and 2, 4, 6, 12 and 24 h after consciousness were 7.19 (2.64), 6.69 (2.17), 6.31 (2.05), 6.16 (2.08), 6.06 (2.24), and 5.38 (1.86), respectively. These scores for the intervention group were 7.44 (1.48), 6.31 (1.25), 5.72 (1.17), 5.59 (1.43), 5.25 (1.13), and 4.97 (1.57). The mean of the pain scores between two groups was not different (p > 0.05). The amount of the consumed morphine (t 61= -2.10, p = 0.039), pethidine (t 62= -2.25, p = 0.028), and diclofenac (t 62= -2.51, p = 0.015) were significantly different between the two groups. CONCLUSIONS: The pain intensity in the patients with shortened fasting time was lower, but it was not statistically significant. Moreover, reducing fasting time by using carbohydrate significantly reduced the use of analgesics.

EEG-based detection of the locus of auditory attention with convolutional neural networks.

In a multi-speaker scenario, the human auditory system is able to attend to one particular speaker of interest and ignore the others. It has been demonstrated that it is possible to use electroencephalography (EEG) signals to infer to which speaker someone is attending by relating the neural activity to the speech signals. However, classifying auditory attention within a short time interval remains the main challenge. We present a convolutional neural network-based approach to extract the locus of auditory attention (left/right) without knowledge of the speech envelopes. Our results show that it is possible to decode the locus of attention within 1-2 s, with a median accuracy of around 81%. These results are promising for neuro-steered noise suppression in hearing aids, in particular in scenarios where per-speaker envelopes are unavailable.

Targeting the Hedgehog Pathway Using Itraconazole to Prevent Progression of Barrett's Esophagus to Invasive Esophageal Adenocarcinoma.

OBJECTIVE: The aim of the study was to investigate whether inhibition of Sonic Hedgehog (SHH) pathway would prevent progression of Barrett's Esophagus (BE) to esophageal adenocarcinoma. BACKGROUND: The hedgehog signaling pathway is a leading candidate as a molecular mediator of BE and esophageal adenocarcinoma (EAC). Repurposed use of existing off-patent, safe and tolerable drugs that can inhibit hedgehog, such as itraconazole, could prevent progression of BE to EAC. METHODS: The efficacy of itraconazole was investigated using a surgical rat reflux model of Barrett's Metaplasia (BM). Weekly intraperitoneal injections of saline (control group) or itraconazole (treatment group; 200 mg/kg) were started at 24 weeks postsurgery. Esophageal tissue was harvested at 40 weeks. The role of the Hh pathway was also evaluated clinically. Esophageal tissue was harvested after 40 weeks for pathological examination and evaluation of the SHH pathway by immunohistochemistry. RESULTS: BM was present in control animals 29 of 31 (93%) versus itraconazole 22 of 24 (91%). EAC was significantly lower in itraconazole 2 of 24 (8%) versus control 10 of 31 (32%), respectively (P = 0.033). Esophageal SHH levels were lower in itraconazole vs control (P = 0.12). In esophageal tissue from humans with recurrent or persistent dysplastic BE within 24 months of ablative treatment, strong SHH and Indian Hedgehog expression occurred in distal BE versus proximal squamous epithelium, odds ratio = 6.1 (95% confidence interval: 1.6, 23.4) and odds ratio = 6.4 (95% confidence interval: 1.2, 32.8), respectively. CONCLUSION: Itraconazole significantly decreases EAC development and SHH expression in a preclinical animal model of BM. In humans, BE tissue expresses higher SHH, Indian Hedgehog, and bone morphogenic protein levels than normal squamous esophageal epithelium.

Clinicobacteriological evaluation of leprosy patients with 1-5 skin lesions.

Background: Mycobacterium leprae is a noncultivable mycobacteria, and diagnosis of the disease is based on its clinical and histopathological characteristics and finding the bacteria in skin scrapings and in biopsies taken from the patients. The aim of this study was to shed light on the clinical classification (based on the number of skin lesions) used extensively in the field where patients classified as paucibacillary (PB) were positive on skin smears and histopathology leading to treatment failure and drug resistance. Methods: In this study, we enrolled untreated 62 leprosy patients with 1-5 skin lesions and did a detailed bacterio-histopathological analysis by slit-skin smears (SSSs) and histopathology. Results: Of 62 patients analyzed, 15 patients came out to be multibacillary (MB) and 47 were PB by SSS and histopathology. Conclusion: The findings of the present study showed that the WHO classification of leprosy based on the number of lesions seems to be inappropriate as it considers a number of MB lesions as PB only, thus misleading the treatment strategies. Hence, it is essential that a comprehensive clinicobacteriological assessment of leprosy cases should be done to ensure the appropriate bacillary status and guiding the appropriate treatment strategy.

Prevalence of Postoperative Nausea and Vomiting and Pain in Patients Undergoing Elective Orthopaedic Surgery in Iran.

PURPOSE: The purpose of this study is to determine the prevalence of postoperative nausea, vomiting, and pain and the severity of postoperative pain in adult patients undergoing elective orthopaedic surgery in Iran. DESIGN: A descriptive, cross-sectional study design was used. METHODS: One hundred twenty-eight patients undergoing elective orthopaedic surgery participated in the study. Demographic and surgical characteristics, severity of pain, frequency of postoperative nausea and vomiting, amount of analgesics and antiemetics administered were measured. FINDINGS: The mean time of surgery was 123.67 min. Of all patients, 59.3% experienced nausea and 39% had postoperative vomiting; 98.4% of participants experienced pain. The mean pain intensity in the first 24 hours after surgery was 6.3 based on the Visual Analogue Scale. CONCLUSION: High prevalence rates of postoperative nausea (59.3%) and vomiting (39%) were recorded. Among 98.4% of participants, pain intensity was rated as moderate during the first 24 hours after consciousness.

A convolutional neural network outperforming state-of-the-art sleep staging algorithms for both preterm and term infants.

OBJECTIVE: To classify sleep states using electroencephalogram (EEG) that reliably works over a wide range of preterm ages, as well as term age. APPROACH: A convolutional neural network is developed to perform 2- and 4-class sleep classification in neonates. The network takes as input an 8-channel 30 s EEG segment and outputs the sleep state probabilities. Apart from simple downsampling of the input and smoothing of the output, the suggested network is an end-to-end algorithm that avoids the need for hand-crafted feature selection or complex pre/post processing steps. To train and test this method, 113 EEG recordings from 42 infants are used. MAIN RESULTS: For quiet sleep detection (the 2-class problem), mean kappa between the network estimate and the ground truth annotated by EEG human experts is 0.76. The sensitivity and specificity are 90% and 88%, respectively. For 4-class classification, mean kappa is 0.64. The averaged sensitivity and specificity (1 versus all) respectively equal 72% and 91%. The results outperform current state-of-the-art methods for which kappa ranges from 0.66 to 0.70 in preterm and from 0.51 to 0.61 in term infants, based on training and testing using the same database. SIGNIFICANCE: The proposed method has the highest reported accuracy for EEG sleep state classification for both preterm and term age neonates.

The insulin-like growth factor binding protein-3 and its death receptor in pancreatic ductal adenocarcinoma poor prognosis.

Insulin-like growth factor binding protein-3 (IGFBP-3) and its newly discovered death receptor (IGFBP-3R) have been reported to involve in a wide variety of cancers. However, their role in pancreatic ductal adenocarcinoma (PDAC) has not been elucidated yet. Here, 478 pancreatic cancers were screened for primary PDAC tumors. The samples were evaluated using quantitative reverse-transcriptase polymerase chain reaction, western blotting, and immunohistochemistry staining. The results indicated that relative IGFBP-3 mRNA expression and its protein level were reduced stage dependently in the PDAC tumors (p < .001 and p < .05, respectively). The subcellular distribution of IGFBP-3 was mainly nuclear only in Stage 0 + 1 (about 150% compared to adjacent normal tissues [p < .05]). The value for IGFBP-3R messenger RNA (mRNA) and protein were also reduced in tumors in compared to adjacent normal pancreatic tissues (p < .05). The Kaplan-Meier analysis also showed that mRNA expression of IGFBP-3 and IGFBP-3R was positively associated with survival, (p = .001). In addition, there is a strong association between low expression of IGFBP-3 and tumor size (p = .032), the lymphatic invasion (p = .001), the TNM (tumor, node, metastasis) staging (p = .001), tumor differentiation (p = .001), and PNI status (p = .021). Down-regulation of IGFBP-3R was also correlated with the tumor size (p = .01), the lymphatic invasion (p = .012) TNM staging (p = .001), tumor differentiation (p = .021) and PNI status (p = .038). In conclusion, IGFBP-3 and its receptor were down-regulated and their expression was associated with poor prognosis of PDAC.

Over-expression of low-density lipoprotein receptor-related Protein-1 is associated with poor prognosis and invasion in pancreatic ductal adenocarcinoma.

BACKGROUND: Low-density lipoprotein receptor-Related Protein-1 (LRP-1) has been reported to involve in tumor development. However, its role in pancreatic cancer has not been elucidated. The present study was designed to evaluate the expression of LRP-1 in Pancreatic Ductal Adenocarcinoma Cancer (PDAC) as well as its association with prognosis. METHODS: Here, 478 pancreatic cancers were screened for suitable primary PDAC tumors. The samples were analyzed using qRT-PCR, western blotting, and Immunohistochemistry (IHC) staining as well as LRP-1 expression in association with clinicopathological features. RESULTS: The relative LRP-1 mRNA expression was up-regulated in 82.3% (42/51) of the PDAC tumors and its expression (3.72 ±â€¯1.25) was significantly higher than that in pancreatic normal margins (1.0 ±â€¯0.23, P < 0.05). This up-regulation was stage dependent (P < 0.05). A similar pattern of LRP-1 protein expression was discovered (P < 0.05). The high expression of LRP-1 in the PDAC tissues was strongly correlated with the low survival time (P = 0.001), TNM classification (P = 0.001), low differentiations status (P = 0.001), lymphatic invasion (P = 0.01) and Perineural Invasion (PNI) status (P = 0.001). CONCLUSIONS: Our finding for the first time revealed that LRP-1 expression inversely associated with poor prognosis and PNI in PDAC tumor.

Automated EEG background analysis to identify neonates with hypoxic-ischemic encephalopathy treated with hypothermia at risk for adverse outcome: A pilot study.

BACKGROUND: To improve the objective assessment of continuous video-EEG (cEEG) monitoring of neonatal brain function, the aim was to relate automated derived amplitude and duration parameters of the suppressed periods in the EEG background (dynamic Interburst Interval= dIBIs) after neonatal hypoxic-ischemic encephalopathy (HIE) to favourable or adverse neurodevelopmental outcome. METHODS: Nineteen neonates (gestational age 36-41 weeks) with HIE underwent therapeutic hypothermia and had cEEG-monitoring. EEGs were retrospectively analyzed with a previously developed algorithm to detect the dynamic Interburst Intervals. Median duration and amplitude of the dIBIs were calculated at 1 h-intervals. Sensitivity and specificity of automated EEG background grading for favorable and adverse outcomes were assessed at 6 h-intervals. RESULTS: Dynamic IBI values reached the best prognostic value between 18 and 24 h (AUC of 0.93). EEGs with dIBI amplitude ≥15 µV and duration <10 s had a specificity of 100% at 6-12 h for favorable outcome but decreased subsequently to 67% at 25-42 h. Suppressed EEGs with dIBI amplitude <15 µV and duration >10 s were specific for adverse outcome (89-100%) at 18-24 h (n = 10). Extremely low voltage and invariant EEG patterns were indicative of adverse outcome at all time points. CONCLUSIONS: Automated analysis of the suppressed periods in EEG of neonates with HIE undergoing TH provides objective and early prognostic information. This objective tool can be used in a multimodal strategy for outcome assessment. Implementation of this method can facilitate clinical practice, improve risk stratification and aid therapeutic decision-making. A multicenter trial with a quantifiable outcome measure is warranted to confirm the predictive value of this method in a more heterogeneous dataset.

Neonatal Seizure Detection Using Deep Convolutional Neural Networks.

Identifying a core set of features is one of the most important steps in the development of an automated seizure detector. In most of the published studies describing features and seizure classifiers, the features were hand-engineered, which may not be optimal. The main goal of the present paper is using deep convolutional neural networks (CNNs) and random forest to automatically optimize feature selection and classification. The input of the proposed classifier is raw multi-channel EEG and the output is the class label: seizure/nonseizure. By training this network, the required features are optimized, while fitting a nonlinear classifier on the features. After training the network with EEG recordings of 26 neonates, five end layers performing the classification were replaced with a random forest classifier in order to improve the performance. This resulted in a false alarm rate of 0.9 per hour and seizure detection rate of 77% using a test set of EEG recordings of 22 neonates that also included dubious seizures. The newly proposed CNN classifier outperformed three data-driven feature-based approaches and performed similar to a previously developed heuristic method.

Impact of Physical Activity on the Incidence of Vascular Diseases in Adults with Type 2 Diabetes Mellitus.

BACKGROUND: Diabetes mellitus (DM) is a common metabolic disease worldwide and has many complications. Vascular events are the major complication of DM, which have an important effect on mortality and disability. Physical activity (PA) enhances the vascular function by several pathways. The aim of this study was to evaluate the relationship between PA and vascular diseases in patients with DM. MATERIALS AND METHODS: This study was performed as a case-control study extracted from a prospective epidemiological research study in Iran. Patients with type 2 DM for more than six months as a case group were compared to sex- and age-matched healthy control subjects. The metabolic equivalent of task score was used to evaluate the level of PA and blood glucose, lipid profile, body mass index, overweight, dyslipidemia, glomerular filtration rate, myocardial infarction, unstable angina, and stroke. RESULTS: Overall, 1242 patients with DM were extracted, and 2484 non-DM subjects were investigated. In the case group, 355 (28.6%) and 887 (71.4%) subjects were men and women, respectively, and 710 (28.6%) men and 1774 (71.4%) women were in the control group. The mean metabolic equivalent of task score was 30 and 40.97 in the DM and non-DM groups, respectively (P˂0.001). The frequency of myocardial infarction, stroke, and cardiac ischemia was 44 (3.5%), 37 (3%), and 267 (21.5%) in the DM group, and 54 (2.2%), 43 (1.7%), and 389 (15.7%) in the non-DM group, respectively. CONCLUSION: The incidence of vascular events associated with PA level in patients with DM and adherence to regular PA reduced vascular events and DM complications.