Intrapartum fetal surveillance: a physiological approach

Continuous utero-placental circulation, and patent umbilical blood vessels ensure an uninterrupted transfer of oxygen and nutrients to the fetus as well as clearance of metabolic waste products. The onset of labour characterized by progressive and strong uterine contractions poses a threat to fetal oxygenation as a result of collapsing the spiral arterioles traversing the myometrium to supply the placental bed, and repetitive compression of the blood vessels within the umbilical cord. Human fetuses are equipped with compensatory mechanisms to cope with transient interruptions of blood supply during labour. The ability to compensate may be blunted in cases of poor fetal reserves, increased metabolic demand (macrosomia or maternal fever), and due to non-hypoxic pathways (e.g. chorioamniontis or fetal hypovolumia-hypotension syndrome). Intrapartum fetal surveillance involves prompt recognition of the features that signal the onset of fetal decompensation on the cardiotocograph (CTG) to ensure a timely intervention to avoid hypoxic-ischaemic encephalopathy (HIE) or perinatal deaths. This article summarises a ‘physiological approach’ to the interpretation of the CTG which, in places, conflicts with other current UK guidance.     

Analysis of Progression Patterns and Failure Sites of Patients With Metastatic Lung Adenocarcinoma With EGFR Mutations Receiving First-line Treatment of Tyrosine Kinase Inhibitors

BackgroundReliable prediction of progression patterns and failure sites for patients with stage IV lung adenocarcinoma is valuable for physicians to deliver personalized tyrosine kinase inhibitor (TKI) treatment.Patients and MethodsWe retrospectively enrolled 266 patients who had stage IV lung adenocarcinoma and received first-line TKI treatment from 2013 to 2017 in Shanghai Chest Hospital. The clinical characteristics at initial diagnosis, progression patterns, and failure sites were analyzed with the attempt to identify some predictive factors for progression patterns and failure sites.ResultsAmong all patients, 62.4% developed systemic progression, and 37.6% developed oligoprogression. Both cohorts had a median progression-free survival (PFS) of 9 months. The percentage of patients who developed original and distant failure was 39.1% and 60.9%, respectively. Patients with oligometastasis at initial diagnosis were more prone to develop oligoprogression (odds ratio [OR], 4.370; 95% confidence interval [CI], 1.881-10.151; P = .001), whereas pulmonary metastasis was negatively correlated with oligoprogression (OR, 0.567; 95% CI, 0.330-0.974; P = .04). Both oligometastasis diagnosis (OR, 2.959; 95% CI, 1.347-6.500; P = .007) and the maximum diameter of the primary lung lesion (threshold 3.25 cm: OR, 3.646; 95% CI, 2.041-6.515; P = .0001) were strong predictive factors for original failures. Osseous metastasis at initial diagnosis might be an indication for distant failure (OR, 0.536; 95% CI, 0.316-0.909; P = .021).ConclusionOver one-half of patients with stage IV lung adenocarcinoma receiving first-line TKI treatment developed systemic progression and distant failure. Metastasis patterns at initial diagnosis was the most important predictive factor for progression patterns and failure sites. The maximum diameter of the primary lung lesion and evidence of osseous metastasis were also found to be significant indicative factors for failure sites.     

Facial expression recognition in Alzheimer’s disease: A systematic review

Introduction: It is well established that behavioral variant frontotemporal dementia can impair social and emotional function. However, there is no consensus regarding how Alzheimer’s disease can affect facial expression recognition. We aim to systematically review all the literature addressing this issue over the last 10 years.

Method: We conducted a search based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The search for literature was undertaken on 19 September 2017, using Pubmed, SciELO, BIREME, and Thomson Reuters Web of Science electronic databases. The key terms for the search were: Alzheimer’s disease, dementia, and facial expression recognition.

Results: We screened 173 articles, and 22 of them were selected. The most common methodology involved showing participants photographs of people expressing the six basic emotions—fear, anger, sadness, disgust, surprise, and happiness. Results were ambiguous. Among people with mild Alzheimer’s disease, happiness was easier to recognize than the other five basic emotions, with sadness and anger the most difficult to recognize. In addition, the intensity level of the emotions presented seems to be important, and facial expression recognition is related to specific cognitive capacities, including executive function and visuoperceptual abilities. Impairment in facial expression recognition does not appear to be a consistent neuropsychological finding in Alzheimer’s disease.

Conclusions: The lack of standardized assessment instruments and the heterogeneity of the methods and samples used across studies hamper comparisons. Future researches should investigate facial expression recognition through more ecological and standardized methods.     

Transforming brain signals related to value evaluation and self‐control into behavioral choices

The processes involved in value evaluation and self‐control are critical when making behavioral choices. However, the evidence linking these two types of processes to behavioral choices in intertemporal decision‐making remains elusive. As the ventromedial prefrontal cortex (vmPFC), striatum, and dorsolateral prefrontal cortex (dlPFC) have been associated with these two processes, we focused on these three regions. We employed functional magnetic resonance imaging during a delayed discounting task (DDT) using a relatively large sample size, three independent samples. We evaluated how much information about a specific choice could be decoded from local patterns in each brain area using multivoxel pattern analysis (MVPA). To investigate the relationship between the dlPFC and vmPFC/striatum regions, we performed a psychophysiological interaction (PPI) analysis. In Experiment I, we found that the vmPFC and dlPFC, but not the striatum, could determine choices in healthy participants. Furthermore, we found that the dlPFC showed significant functional connectivity with the vmPFC, but not the striatum, when making decisions. These results could be replicated in Experiment II with an independent sample of healthy participants. In Experiment III, the choice‐decoding accuracy in the vmPFC and dlPFC was lower in patients with addiction (smokers and participants with Internet gaming disorder) than in healthy participants, and decoding accuracy in the dlPFC was related to impulsivity in addicts. Taken together, our findings may provide neural evidence supporting the hypothesis that value evaluation and self‐control processes both guide the intertemporal choices, and might provide potential neural targets for the diagnosis and treatment of impulsivity‐related brain disorders.     

Changes to foot pressure pattern in post-stroke individuals who have started to walk independently during the convalescent phase

BackgroundAbnormal foot contact patterns following stroke affect functional gait; however, objective analysis targeting independent walking is lacking.Research questionHow do walking abilities and foot pressure patterns differ between post-stroke individuals who achieved independent walking and healthy controls? Secondarily, how do the abilities and patterns in post-stroke individuals change before and after achieving independent walking? Can these changes become criteria for permitting independent walking?MethodsTwenty-eight individuals with hemiplegia and 32 controls were enrolled. Motor dysfunction score (MDScore), walking speed (WSpeed), and foot pressure patterns were measured when they were first able to walk without orthosis or physical assistance (1st assessment) and when they achieved independent walking around discharge (2nd assessment). Foot pressure patterns were measured using insole-type foot pressure-measuring system. Ratios of partial foot pressure to body weight (%PFP), ratios of anteroposterior length of center of pressure (COP; %Long), and backward moving distance of COP to the foot length (%Backward) were calculated. Parameters during the 2nd assessment were compared with those of controls and those during the 1st assessment. During the 2nd assessment, relationships among the parameters, MDScore, and WSpeed were analyzed.ResultsDuring the 2nd assessment, no difference was observed in both %Long and %Backward between the non-paretic limbs and the controls. While the %Backward was higher, the %PFP of toes and %Long were lower in the paretic limb than in the controls. Although the %Backward was lower, both %PFP of toes and %Long of the paretic limb were higher in the 2nd assessment than in the 1st assessment. During the 2nd assessment, both %Long and % Backward values of the paretic limb moderately correlated with MDScore and WSpeed.SignificanceAfter improvement of foot pressure in toes, both an increase in anteroposterior length and a decrease in backward moving of COP path were objective signs permitting independent walking.     

应用 σ度量对深圳市龙华区三家综合医院临床生化检验结果互认的评价研究

目的　探讨 σ度量在深圳市龙华区三家综合医院临床生化检验结果互认中的应用价值。方法　收集三家医院 2019年广东省临检中心常规化学，特殊蛋白前两次的室间质评（ EQA）样本，经混匀并分割成比对样本送至各评价实验室进行检测；以卫生部临检中心（ NCCL)标准和生物学变异导出的允许总误差（ TEa%）为质量规范，通过加权法计算出各项目 2019年 1～ 6月期间室内质控在控数据的不精密度，以 2018年参加卫生部室间质评（ EQA）数据作为偏倚（ bias%）来源，计算三家医院 29个检验项目的 σ度量值并进行性能评价，利用质量目标指数（ QGI)提出改善方法；将评价项目的 σ度量值与直接比对试验进行比较，通过统计分析确定 σ截断值（ cut-off）。结果　①三家医院 29个生化项目的性能并不一致，将项目中、高值的 σ值进行配对 t检验，其 t值分别为 2.28，3.01和 0.74，按 α =0.05水准判断得出医院 A与 B，医院 A与 C间的性能差异有统计学意义，医院 B与 C间的性能差异无统计学意义，医院 A项目性能要优于 B，C医院。评估的 87个项目中有 53项 σ平均值 <6，根据 QGI判断，3个项目需优先改善准确度，10个项目需同步改善准确度和精密度，另 40个项目需优先改善精密度。②对医院间项目比对通过率进行配对 χ2检验，其 χ2分别为 5.33，6.25和 2.5，按α=0.05水准判断， B与 A医院比对通过率低于 C与 A医院、 C与 B医院，差异有统计学意义； C与 A医院比对通过率跟 C与 B医院差异无统计学意义。③将 σ度量值与直接比对试验进行比较，经配对 χ2检验，当 σ cut-off值取≥ 2σ， ≥ 3σ，≥ 4σ，≥ 5σ和≥ 6σ时，其 χ2分别为 7.20，0.00，9.09，15.06和 16.06，按 χ20.05，1=3.84，α=0.05水准判断，当σcut-off值取≥ 3σ时，两种比对方法的差异无统计学意义。结论　σ度量值可以单独用于评价医院间生化检验结果的互认，在判断项目是否具有可比性时，可考虑将 σ cut-off值设为≥ 3σ。     

Machine-learning models for activity class prediction: A comparative study of feature selection and classification algorithms

PurposeMachine-learning (ML) approaches have been repeatedly coupled with raw accelerometry to classify physical activity classes, but the features required to optimize their predictive performance are still unknown. Our aim was to identify appropriate combination of feature subsets and prediction algorithms for activity class prediction from hip-based raw acceleration data.MethodsThe hip-based raw acceleration data collected from 27 participants was split into training (70 %) and validation (30 %) subsets. A total of 206 time- (TD) and frequencydomain (FD) features were extracted from 6-second non-overlapping windows of the signal. Feature selection was done using seven filter-based, two wrapper-based, and one embedded algorithm, and classification was performed with artificial neural network (ANN), support vector machine (SVM), and random forest (RF). For every combination between the feature selection method and the classifiers, the most appropriate feature subsets were found and used for model training within the training set. These models were then validated with the left-out validation set.ResultsThe appropriate number of features for the ANN, SVM, and RF ranged from 20 to 45. Overall, the accuracy of all the three classifiers was higher when trained with feature subsets generated using filter-based methods compared with when they were trained with wrapper-based methods (range: 78.1 %–88 % vs. 66 %–83.5 %). TD features that reflect how signals vary around the mean, how they differ with one another, and how much and how often they change were more frequently selected via the feature selection methods.ConclusionsA subset of TD features from raw accelerometry could be sufficient for ML-based activity classification if properly selected from different axes.     

Episodic memory: Neuronal codes for what,where, and when

Episodic memory is defined as the ability to recall events in a spatiotemporal context. Formation of such memories is critically dependent on the hippocampal formation and its inputs from the entorhinal cortex. To be able to support the formation of episodic memories, entorhinal cortex and hippocampal formation should contain a neuronal code that follows several requirements. First, the code should include information about position of the agent (“where”), sequence of events (“when”), and the content of the experience itself (“what”). Second, the code should arise instantly thereby being able to support memory formation of one‐shot experiences. For successful encoding and to avoid interference between memories during recall, variations in location, time, or in content of experience should result in unique ensemble activity. Finally, the code should capture several different resolutions of experience so that the necessary details relevant for future memory‐based predictions will be stored. We review how neuronal codes in entorhinal cortex and hippocampus follow these requirements and argue that during formation of episodic memories entorhinal cortex provides hippocampus with instant information about ongoing experience. Such information originates from (a) spatially modulated neurons in medial entorhinal cortex, including grid cells, which provide a stable and universal positional metric of the environment; (b) a continuously varying signal in lateral entorhinal cortex providing a code for the temporal progression of events; and (c) entorhinal neurons coding the content of experiences exemplified by object‐coding and odor‐selective neurons. During formation of episodic memories, information from these systems are thought to be encoded as unique sequential ensemble activity in hippocampus, thereby encoding associations between the content of an event and its spatial and temporal contexts. Upon exposure to parts of the encoded stimuli, activity in these ensembles can be reinstated, leading to reactivation of the encoded activity pattern and memory recollection.     

Neurofeedback and neuroplasticity of visual self-processing in depressed and healthy adolescents: A preliminary study

Adolescence is a neuroplastic period for self-processing and emotion regulation transformations, that if derailed, are linked to persistent depression. Neural mechanisms of adolescent self-processing and emotion regulation ought to be targeted via new treatments, given moderate effectiveness of current interventions. Thus, we implemented a novel neurofeedback protocol in adolescents to test the engagement of circuits sub-serving self-processing and emotion regulation.MethodsDepressed (n = 34) and healthy (n = 19) adolescents underwent neurofeedback training using a novel task. They saw their happy face as a cue to recall positive memories and increased displayed amygdala and hippocampus activity. The control condition was counting-backwards while viewing another happy face. A self vs. other face recognition task was administered before and after neurofeedback training.ResultsAdolescents showed higher frontotemporal activity during neurofeedback and higher amygdala and hippocampus and hippocampi activity in time series and region of interest analyses respectively. Before neurofeedback there was higher saliency network engagement for self-face recognition, but that network engagement was lower after neurofeedback. Depressed youth exhibited higher fusiform, inferior parietal lobule and cuneus activity during neurofeedback, but controls appeared to increase amygdala and hippocampus activity faster compared to depressed adolescents.ConclusionsNeurofeedback recruited frontotemporal cortices that support social cognition and emotion regulation. Amygdala and hippocampus engagement via neurofeedback appears to change limbic-frontotemporal networks during self-face recognition. A placebo group or condition and contrasting amygdala and hippocampus, hippocampi or right amygdala versus frontal loci of neurofeedback, e.g. dorsal anterior cingulate cortex, with longer duration of neurofeedback training will elucidate dosage and loci of neurofeedback in adolescents.