Machine Learning Algorithm to Predict Acidemia Using Electronic Fetal Monitoring Recording Parameters

Background: Electronic fetal monitoring (EFM) is the universal method for the surveillance of fetal well-being in intrapartum. Our objective was to predict acidemia from fetal heart signal features using machine learning algorithms. Methods: A case–control 1:2 study was carried out compromising 378 infants, born in the Miguel Servet University Hospital, Spain. Neonatal acidemia was defined as pH < 7.10. Using EFM recording logistic regression, random forest and neural networks models were built to predict acidemia. Validation of models was performed by means of discrimination, calibration, and clinical utility. Results: Best performance was attained using a random forest model built with 100 trees. The discrimination ability was good, with an area under the Receiver Operating Characteristic curve (AUC) of 0.865. The calibration showed a slight overestimation of acidemia occurrence for probabilities above 0.4. The clinical utility showed that for 33% cutoff point, missing 5% of acidotic cases, 46% of unnecessary cesarean sections could be prevented. Logistic regression and neural networks showed similar discrimination ability but with worse calibration and clinical utility. Conclusions: The combination of the variables extracted from EFM recording provided a predictive model of acidemia that showed good accuracy and provides a practical tool to prevent unnecessary cesarean sections.     

A New Series of Aryloxyacetic Acids Endowed with Multi-Target Activity towards Peroxisome Proliferator-Activated Receptors (PPARs), Fatty Acid Amide Hydrolase (FAAH), and Acetylcholinesterase (AChE)

A new series of aryloxyacetic acids was prepared and tested as peroxisome proliferator-activated receptors (PPARs) agonists and fatty acid amide hydrolase (FAAH) inhibitors. Some compounds exhibited an interesting dual activity that has been recently proposed as a new potential therapeutic strategy for the treatment of Alzheimer’s disease (AD). AD is a multifactorial pathology, hence multi-target agents are currently one of the main lines of research for the therapy and prevention of this disease. Given that cholinesterases represent one of the most common targets of recent research, we decided to also evaluate the effects of our compounds on the inhibition of these specific enzymes. Interestingly, two of these compounds, (S)-5 and 6, showed moderate activity against acetylcholinesterase (AChE) and even some activity, although at high concentration, against Aβ peptide aggregation, thus demonstrating, in agreement with the preliminary dockings carried out on the different targets, the feasibility of a simultaneous multi-target activity towards PPARs, FAAH, and AChE. As far as we know, these are the first examples of molecules endowed with this pharmacological profile that might represent a promising line of research for the identification of novel candidates for the treatment of AD.     

A review of computational modeling and deep brain stimulation: applications to Parkinson's disease

Biophysical computational models are complementary to experiments and theories, providing powerful tools for the study of neurological diseases. The focus of this review is the dynamic modeling and control strategies of Parkinson's disease (PD). In previous studies, the development of parkinsonian network dynamics modeling has made great progress. Modeling mainly focuses on the cortex-thalamus-basal ganglia (CTBG) circuit and its sub-circuits, which helps to explore the dynamic behavior of the parkinsonian network, such as synchronization. Deep brain stimulation (DBS) is an effective strategy for the treatment of PD. At present, many studies are based on the side effects of the DBS. However, the translation from modeling results to clinical disease mitigation therapy still faces huge challenges. Here, we introduce the progress of DBS improvement. Its specific purpose is to develop novel DBS treatment methods, optimize the treatment effect of DBS for each patient, and focus on the study in closed-loop DBS. Our goal is to review the inspiration and insights gained by combining the system theory with these computational models to analyze neurodynamics and optimize DBS treatment.     

铁过量与人体健康

综述了机体铁储存过多与某些疾病之间的关系,包括:铁过量与肝脏疾病、心血管病、肿瘤、肾损伤、高血压等有关。铁过量主要是由于病理过程和通过各种途径进入人体的铁量增加。过量的铁在失控条件下,引起细胞成分的明显损伤,导致组织炎症和多器官的纤维化。因为铁是自由基反应的催化剂,可引起过氧化作用或细胞膜脂质和细胞内化合物的交联反应,致细胞老化或死亡。     

On the Variability of Heart Rate Variability—Evidence from Prospective Study of Healthy Young College Students

Heart rate variability (HRV) has been widely used as indices for autonomic regulation, including linear analyses, entropy and multi-scale entropy based nonlinear analyses, and however, it is strongly influenced by the conditions under which the signal is being recorded. To investigate the variability of healthy HRV under different settings, we recorded electrocardiograph (ECG) signals from 56 healthy young college students (20 h for each participant) at campus using wearable single-lead ECG device. Accurate R peak to R peak (RR) intervals were extracted by combing the advantages of five commonly used R-peak detection algorithms to eliminate data quality influence. Thorough and detailed linear and nonlinear HRV analyses were performed. Variability of HRV metrics were evaluated from five categories: (1) different states of daily activities; (2) different recording time period in the same day during free-running daily activities; (3) body postures of sitting and lying; (4) lying on the left, right and back; and (5) gender influence. For most of the analyzed HRV metrics, significant differences (p < 0.05) were found among different recording conditions within the five categories except lying on different positions. Results suggested that the standardization of ECG data collection and HRV analysis should be implemented in HRV related studies, especially for entropy and multi-scale entropy based analyses. Furthermore, this preliminary study provides reference values of HRV indices under various recording conditions of healthy young subjects that could be useful information for different applications (e.g., health monitoring and management).     

Ultrasonic stimulation of the brain to enhance the release of dopamine – A potential novel treatment for Parkinson’s disease

Parkinson’s disease (PD) is characterized by the decrease of dopamine (DA) production and release in the substantia nigra and striatum regions of the brain. Transcranial ultrasound has been exploited recently for neuromodulation of the brain in a number of fields. We have stimulated DA release in PC12 cells using low-intensity continuous ultrasound (0.1 W/cm² − 0.3 W/cm², 1 MHz), 12 h after exposure at 0.2 W/cm², 40 s, the amount of DA content eventually increased 78.5% (p = 0.004). After 10-day ultrasonic treatment (0.3 W/cm², 5 min/d), the DA content in the striatum of PD mice model restored to 81.07% of the control (vs 43.42% in the untreated PD mice model). In addition to this the locomotion activity was restored to the normal level after treatment. We suggest that the low intensity ultrasound-induced DA release can be attributed to a combination of neuron regeneration and improved membrane permeability produced by the mechanical force of ultrasound. Our study indicates that the application of transcranial ultrasound applied below FDA limits, could provide a candidate for relatively safe and noninvasive PD therapy through an amplification of DA levels and the stimulation of dopaminergic neuron regeneration without contrast agents.     

载脂蛋白E与阿尔兹海默病的相关研究进展*

载脂蛋白E（Apolipoprotein E,ApoE ）的等位基因ε4是阿尔兹海默病（Alzheimer’s disease,AD）主要的危险遗传因子，它主要与晚发型以及散发型阿尔兹海默病相关。阿尔兹海默病的两个主要病理学特征均被发现与ApoE 有着极为密切的关系。本文介绍了ApoE在阿尔兹海默病中所起的主要作用的研究进展以及目前国内外关于基于ApoE的阿尔兹海默病相关药物研究。     

Human exhaled air analytics: biomarkers of diseases

Over the last few years, breath analysis for the routine monitoring of metabolic disorders has attracted a considerable amount of scientific interest, especially since breath sampling is a non-invasive technique, totally painless and agreeable to patients. The investigation of human breath samples with various analytical methods has shown a correlation between the concentration patterns of volatile organic compounds (VOCs) and the occurrence of certain diseases. It has been demonstrated that modern analytical instruments allow the determination of many compounds found in human breath both in normal and anomalous concentrations. The composition of exhaled breath in patients with, for example, lung cancer, inflammatory lung disease, hepatic or renal dysfunction and diabetes contains valuable information. Furthermore, the detection and quantification of oxidative stress, and its monitoring during surgery based on composition of exhaled breath, have made considerable progress. This paper gives an overview of the analytical techniques used for sample collection, preconcentration and analysis of human breath composition. The diagnostic potential of different disease-marking substances in human breath for a selection of diseases and the clinical applications of breath analysis are discussed.     

心脑血管疾病与微量元素研究进展

心脑血管疾病发病日益增多的原因之一是机体缺乏人体必需微量元素,目前报道硒、锗、锌、钴、铜、锰、铬、钼、钒、镍等与心脑血管疾病有密切关系。用微量元素调控防治心脑血管疾病,目前是国内外研究的新课题,其目的是降低心脑血管疾病的死亡率和发病率,促进人类健康长寿。     

Light‐Induced Chiral Iron Copper Selenide Nanoparticles Prevent β‐Amyloidopathy In Vivo

The accumulation and deposition of β‐amyloid (Aβ) plaques in the brain is considered a potential pathogenic mechanism underlying Alzheimer's disease (AD). Chiral l/d ‐Fe_xCu_ySe nanoparticles (NPs) were fabricated that interfer with the self‐assembly of Aβ42 monomers and trigger the Aβ42 fibrils in dense structures to become looser monomers under 808 nm near‐infrared (NIR) illumination. d ‐Fe_xCu_ySe NPs have a much higher affinity for Aβ42 fibrils than l ‐Fe_xCu_ySe NPs and chiral Cu_2?xSe NPs. The chiral Fe_xCu_ySe NPs also generate more reactive oxygen species (ROS) than chiral Cu_2?xSe NPs under NIR‐light irradiation. In living MN9D cells, d ‐NPs attenuate the adhesion of Aβ42 to membranes and neuron loss after NIR treatment within 10 min without the photothermal effect. In‐vivo experiments showed that d ‐Fe_xCu_ySe NPs provide an efficient protection against neuronal damage induced by the deposition of Aβ42 and alleviate symptoms in a mouse model of AD, leading to the recovery of cognitive competence.