Motor Development in Context

The study of motor development has traditionally focused on the timing and sequence of the acquisition of motor skills, such as sitting, crawling, or walking, over the first years of life. Because motor skills are directly observable, motor development serves as a useful exemplar for general principles of development. Current frameworks emphasize motor development in and as a context, such as how change in motor skill interacts with simultaneous change in other developmental domains, how the acquisition of new motor skills creates new opportunities for learning, and how the context in which motor development occurs shapes the course of development. For example, the onset of new motor skills changes the allocation of attentional resources, the quality of infants’ sleep, and available perceptual information. Reciprocally, contexts such as culturally specific parenting practices and individual differences in everyday experiences impact the timing and trajectory of new motor skills.

Directional scale elasticity considering the management preference of decision-makers

Most data envelopment analysis (DEA) studies on scale elasticity (SE) and returns to scale (RTS) of efficient units arise from the traditional definitions of them in economics, which is based on measuring radial changes in outputs caused by the simultaneous change in all inputs. In actual multiple inputs/outputs activities, the goals of expanding inputs are not only to obtain increases in outputs, but also to expect the proportions of such increases consistent with the management preference of decision-makers. However, the management preference is usually not radial changes in outputs. With the latter goal into consideration, this paper proposes the directional SE and RTS in a general formula for multi-output activities, and offers a DEA-based model for the formula of directional SE at any point on the DEA frontier, which is straightforward and requires no simplifying assumptions. Finally, the empirical part employs the data of 16 basic research institutions in Chinese Academy of Sciences (CAS) to illustrate the superiority of the proposed theories and methods.

One-year old infants control bottom-up saliencies to purposely sustain attention

Salient stimuli attract gaze [1,2]. Mature perceivers internally suppress salient distractors to purposefully sustain attention on a visual target. Infants’ abilities to purposefully sustain gaze on an object, often measured in the context of play, is also assumed to require the internal suppression of distractors and is considered an early marker and risk point in the development of the internal regulatory processes mediated by the pre-frontal cortex [3,4]. Here we show that sustained attention by one-year-old infants includes a behavior-driven increase in the external salience of the target. Using head-mounted eye trackers, we measured infants’ gaze during object play and the momentary visual size of objects in the infant’s field of view. Visual size is well-known to robustly attract gaze [1]. We found that when infants directed gaze to an object, there was a simultaneous change in the the spatial relation of the head to the attended object increasing the target’s visual size relative to distractors. The onset, duration, and offset of the increased salience was time-locked with the onset, duration and offset of infant gaze to the object. The findings challenge characterizations of infant attention as a competition between bottom-up and top-down control and implicate instead a collaboration in which top-down goals drive infant’s externally-directed behaviors that suppress the salience of distractors at input. The top-down control of attention through externally directed behavior may serve as the training ground –and risk factor – in the development of internal control.

Features of genes copy number in normal, primary tumor, and lymph nodes metastases cells in patients with cervical cancer.

e17503 Background: Early stages of cervical cancer (CC) can be treated with surgery or radiation therapy, metastatic CC is incurable, and therefore new diagnostic approaches based on highly effective molecular markers are required. As such markers, the Copy Number Variation (CNV) is of great interest. Purpose of the study: to analyze the peculiarities of genes CNV in normal cells, primary tumor and lymph nodes tumor metastases cells in patients with CC. Methods: Tissue sections from FFPE-blocks of 300 patients with CC were used for the study. Primary tumor, tumor metastatic and normal cells were isolated using non-contact laser microdissection (Palm MicroBeam, Carl Zeiss). DNA was extracted from the cells using the phenol-chloroform method. Determination of 14 genes CNV (LAMP3, PRKAA1, TORC2, FOXO3, HDAC5, MEF2C, MLXIPL, EP300, HNF4A, TP53, SREBF1, SREBF2, PPARGC1A, and CCND1) was performed by Real-Time qPCR method. Statistical analysis was performed using the Mann-Whitney test; Bonferroni's correction was applied to correct multiple comparisons. Results: An increase in the CNV of LAMP3 and TORC2 genes by 2.5 and 3.2 times (p < 0.05), respectively, and a decrease in the CNV of TP53 and FOXO3 genes by 2.3 and 2.0 times (p < 0.05), respectively, were found in the primary tumor cells relative to normal cells. The effect of the simultaneous change in the CNV of LAMP3, TORC2, TP53 and FOXO3 genes was observed in 60% of the sample, and LAMP3 and TP53 genes - in 80%. In cells of lymph nodes tumor metastases an increase in the CNV of CCND1 and TORC2 genes by 2.0 and 3.5 times (p < 0.05), respectively, was found, as well as a decrease in the CNV of PPARGC1A gene by 2.1 times (p < 0.05) relative to normal cells. A simultaneous change in the CNV of CCND1, TORC2, and PPARGC1A was observed in 70% of the sample, and CNV of CCND1 and TORC2 genes - in 85%. Primary tumor and metastases cells differed in the CNV of CCND1 (2.5 times higher in metastatic cells), LAMP3 (3.0 times lower in metastatic cells) and FOXO3 genes (2.0 times higher in metastatic cells). Conclusions: Thus, the primary tumor and lymph nodes metastases cells differ in the level of genes CNV from normal cervix cells. Accordingly, the CNV of LAMP3, TORC2, TP53 and FOXO3 genes may have the potential for diagnosing a primary cervical tumor, and the CNV of CCND1, TORC2 and PPARGC1A genes for diagnosing its metastases to regional lymph nodes.

E-wave asymmetry elucidates diastolic ventricular stiffness-relaxation coupling: model-based prediction with in vivo validation

Although diastolic stiffness and relaxation are considered independent chamber properties, the cardio-hemic inertial oscillation that generates E-waves obeys Newton’s law. E-waves vary with heart rate requiring simultaneous change in stiffness and relaxation. By retrospective analysis of human heart-rate varying transmitral Doppler-data, we show that diastolic stiffness and relaxation are coupled and that the coupling manifests through E-wave asymmetry, quantified through a parametrized diastolic filling model-derived dimensionless parameter, which only depends on deceleration time and acceleration time, readily obtainable via standard echocardiography.

The Multidimensional Algorithm of Cumulative Sums for Detecting Changes in Time Series Characteristics

The article presents a cumulative sum algorithm intended to detect a sudden step-like change in the probabilistic characteristics of a monitored time series when such a change (“disorder”) is associated with a simultaneous change in both the location characteristics and the dispersion characteristics of the corresponding distribution functions. In the general case of a multidimensional time series, the disorder is associated with a jump in the values of the mathematical expectation vector (the vector of means) and covariance matrix entries. To solve this problem, it is proposed to use a preliminary linear transformation of the time series values, as a result of which the covariance matrix is transformed to the unity form before disordering and to the diagonal form after disordering. The change in the vector of means is analyzed, and the main relations describing the considered detection algorithm are derived. It is noted that by using the above-mentioned linear transformation it is possible to simplify the obtaining of the reference data necessary for synthesizing the monitoring algorithm with the predetermined properties. As an example, a particular case of a one-dimensional time series and a disorder in the form of a simultaneous change in the mean and variance is considered. For this case, reference data obtained by applying the simulation method are given, using which it is possible to find the monitoring algorithm triggering threshold and estimate the average delay time of detecting the specified disorder from the given interval between false alarms. This study is a logical continuation and further development of the approach to construction of multidimensional algorithms for detecting disorders [1].

Analytic methods for estimating the health effects of social policies in the presence of simultaneous change in multiple policies: A review

A growing body of empirical research seeks to quantify the causal effects of social policies on health by exploiting variation in the timing of policy changes across places. However, multiple social policies are often adopted simultaneously or in close succession in the same locations, creating clustering which must be handled analytically for valid inferences. Although this is a substantial methodological challenge for studies aiming to isolate social policy effects, yet systematic assessments of available analytic solutions and tradeoffs among approaches are lacking. We designated eight analytic solutions prior researchers have adopted, including efforts to disentangle individual policy effects and efforts to estimate the joint effects of clustered policies. We leveraged an existing systematic review of social policies and health to evaluate how often policy clustering is identified as a threat to validity and how often each analytic solution is applied in practice. Of the 55 studies, only 17 (31%) reported checking for any clustered policies, and 36 (67%) used at least one approach that helps address clustered policies. The most common approaches were adjusting for clustered policies, defining the outcome on subpopulations likely to be affected by the policy of interest but not other clustered policies, and selecting a less-correlated measure of policy exposure were the most common approaches. Systematically assessing policy clustering and applying analytic solutions when necessary would strengthen future studies on the health effects of social policies. Adequate reporting on these analytic decisions would facilitate evaluating validity and interpreting study findings.

The revolution will be hard to evaluate: How simultaneous change in multiple policies affects policy-based health research

Extensive empirical health research leverages variation in the timing and location of policy changes as quasi-experiments. Multiple social policies may be adopted simultaneously in the same locations, creating clustering which must be addressed analytically for valid inferences. The pervasiveness and consequences of policy clustering have received limited attention. We analyzed a systematic sample of 13 social policy databases covering diverse domains including poverty, paid family leave, and tobacco. We quantified policy clustering in each database as the fraction of variation in each policy measure across jurisdictions and times that could be explained by co-variation with other policies (R2). We used simulations to estimate the ratio of the variance of effect estimates under the observed policy clustering to variance if policies were independent. Policy clustering ranged from very high for state-level cannabis policies to low for country-level sexual minority rights policies. For 65% of policies, greater than 90% of the place-time variation was explained by other policies. Policy clustering increased the variance of effect estimates by a median of 57-fold. Policy clustering poses a major methodological challenge to rigorously evaluating health effects of individual social policies. Tools to enhance validity and precision for evaluating clustered policies are needed.