Research progress on the relationship between white matter hyperintensity and cognitive impairment

White matter hyperintensity （WMH） is one of the imaging markers of cerebral small vessel disease （CSVD）. Recent studies have found certain relationship between WMH and cognitive impairment. In this article，the mechanism of WMH formation，the relationship between WMH and cognitive impairment，the mechanism of cognitive dysfunction caused by WMH were reviewed，aiming to deepen the understanding of the relationship between WMH and cognitive impairment

Monitoring human growth and development: a continuum from the womb to the classroom

A comprehensive set of fully integrated anthropometric measures is needed to evaluate human growth from conception to infancy so that consistent judgments can be made about the appropriateness of fetal and infant growth. At present, there are 2 barriers to this strategy. First, descriptive reference charts, which are derived from local, unselected samples with inadequate methods and poor characterization of their putatively healthy populations, commonly are used rather than prescriptive standards. The use of prescriptive standards is justified by the extensive biologic, genetic, and epidemiologic evidence that skeletal growth is similar from conception to childhood across geographic populations, when health, nutrition, environmental, and health care needs are met. Second, clinicians currently screen fetuses, newborn infants, and infants at all levels of care with a wide range of charts and cutoff points, often with limited appreciation of the underlying population or quality of the study that generated the charts. Adding to the confusion, infants are evaluated after birth with a single prescriptive tool: the World Health Organization Child Growth Standards, which were derived from healthy, breastfed newborn infants, infants, and young children from populations that have been exposed to few growth-restricting factors. The International Fetal and Newborn Growth Consortium for the 21st Century Project addressed these issues by providing international standards for gestational age estimation, first-trimester fetal size, fetal growth, newborn size for gestational age, and postnatal growth of preterm infants, all of which complement the World Health Organization Child Growth Standards conceptually, methodologically, and analytically. Hence, growth and development can now, for the first time, be monitored globally across the vital first 1000 days and all the way to 5 years of age. It is clear that an integrative approach to monitoring growth and development from pregnancy to school age is desirable, scientifically supported, and likely to improve care, referral patterns, and reporting systems. Such integration can be achieved only through the use of international growth standards, especially in increasingly diverse, mixed ancestry populations. Resistance to new scientific developments has been hugely problematic in medicine; however, we are confident that the obstetric and neonatal communities will join their pediatric colleagues worldwide in the adoption of this integrative strategy

The satisfactory growth and development at 2 years of age of the INTERGROWTH-21st Fetal Growth Standards cohort support its appropriateness for constructing international standards.

BACKGROUND: The World Health Organization recommends that human growth should be monitored with the use of international standards. However, in obstetric practice, we continue to monitor fetal growth using numerous local charts or equations that are based on different populations for each body structure. Consistent with World Health Organization recommendations, the INTERGROWTH-21st Project has produced the first set of international standards to date pregnancies; to monitor fetal growth, estimated fetal weight, Doppler measures, and brain structures; to measure uterine growth, maternal nutrition, newborn infant size, and body composition; and to assess the postnatal growth of preterm babies. All these standards are based on the same healthy pregnancy cohort. Recognizing the importance of demonstrating that, postnatally, this cohort still adhered to the World Health Organization prescriptive approach, we followed their growth and development to the key milestone of 2 years of age. OBJECTIVE: The purpose of this study was to determine whether the babies in the INTERGROWTH-21st Project maintained optimal growth and development in childhood. STUDY DESIGN: In the Infant Follow-up Study of the INTERGROWTH-21st Project, we evaluated postnatal growth, nutrition, morbidity, and motor development up to 2 years of age in the children who contributed data to the construction of the international fetal growth, newborn infant size and body composition at birth, and preterm postnatal growth standards. Clinical care, feeding practices, anthropometric measures, and assessment of morbidity were standardized across study sites and documented at 1 and 2 years of age. Weight, length, and head circumference age- and sex-specific z-scores and percentiles and motor development milestones were estimated with the use of the World Health Organization Child Growth Standards and World Health Organization milestone distributions, respectively. For the preterm infants, corrected age was used. Variance components analysis was used to estimate the percentage variability among individuals within a study site compared with that among study sites. RESULTS: There were 3711 eligible singleton live births; 3042 children (82%) were evaluated at 2 years of age. There were no substantive differences between the included group and the lost-to-follow up group. Infant mortality rate was 3 per 1000; neonatal mortality rate was 1.6 per 1000. At the 2-year visit, the children included in the INTERGROWTH-21st Fetal Growth Standards were at the 49th percentile for length, 50th percentile for head circumference, and 58th percentile for weight of the World Health Organization Child Growth Standards. Similar results were seen for the preterm subgroup that was included in the INTERGROWTH-21st Preterm Postnatal Growth Standards. The cohort overlapped between the 3rd and 97th percentiles of the World Health Organization motor development milestones. We estimated that the variance among study sites explains only 5.5% of the total variability in the length of the children between birth and 2 years of age, although the variance among individuals within a study site explains 42.9% (ie, 8 times the amount explained by the variation among sites). An increase of 8.9 cm in adult height over mean parental height is estimated to occur in the cohort from low-middle income countries, provided that children continue to have adequate health, environmental, and nutritional conditions. CONCLUSION: The cohort enrolled in the INTERGROWTH-21st standards remained healthy with adequate growth and motor development up to 2 years of age, which supports its appropriateness for the construction of international fetal and preterm postnatal growth standards

User Characteristic Aware Participant Selection for Mobile Crowdsensing

Mobile crowdsensing (MCS) is a promising sensing paradigm that leverages diverse embedded sensors in massive mobile devices. One of its main challenges is to effectively select participants to perform multiple sensing tasks, so that sufficient and reliable data is collected to implement various MCS services. Participant selection should consider the limited budget, the different tasks locations, and deadlines. This selection becomes even more challenging when the MCS tries to efficiently accomplish tasks under different heat regions and collect high-credibility data. In this paper, we propose a user characteristics aware participant selection (UCPS) mechanism to improve the credibility of task data in the sparse user region acquired by the platform and to reduce the task failure rate. First, we estimate the regional heat according to the number of active users, average residence time of users and history of regional sensing tasks, and then we divide urban space into high-heat and low-heat regions. Second, the user state information and sensing task records are combined to calculate the willingness, reputation and activity of users. Finally, the above four factors are comprehensively considered to reasonably select the task participants for different heat regions. We also propose task queuing strategies and community assistance strategies to ensure task allocation rates and task completion rates. The evaluation results show that our mechanism can significantly improve the overall data quality and complete sensing tasks of low-heat regions in a timely and reliable manner

Scalable privacy-preserving big data aggregation mechanism

As the massive sensor data generated by large-scale Wireless Sensor Networks (WSNs) recently become an indispensable part of ‘Big Data’, the collection, storage, transmission and analysis of the big sensor data attract considerable attention from researchers. Targeting the privacy requirements of large-scale WSNs and focusing on the energy-efficient collection of big sensor data, a Scalable Privacy-preserving Big Data Aggregation (Sca-PBDA) method is proposed in this paper. Firstly, according to the pre-established gradient topology structure, sensor nodes in the network are divided into clusters. Secondly, sensor data is modified by each node according to the privacy-preserving configuration message received from the sink. Subsequently, intra- and inter-cluster data aggregation is employed during the big sensor data reporting phase to reduce energy consumption. Lastly, aggregated results are recovered by the sink to complete the privacy-preserving big data aggregation. Simulation results validate the efficacy and scalability of Sca-PBDA and show that the big sensor data generated by large-scale WSNs is efficiently aggregated to reduce network resource consumption and the sensor data privacy is effectively protected to meet the ever-growing application requirements

Service Demand Discovery Mechanism for Mobile Social Networks

In the last few years, the service demand for wireless data over mobile networks has continually been soaring at a rapid pace. Thereinto, in Mobile Social Networks (MSNs), users can discover adjacent users for establishing temporary local connection and thus sharing already downloaded contents with each other to offload the service demand. Due to the partitioned topology, intermittent connection and social feature in such a network, the service demand discovery is challenging. In particular, the service demand discovery is exploited to identify the best relay user through the service registration, service selection and service activation. In order to maximize the utilization of limited network resources, a hybrid service demand discovery architecture, such as a Virtual Dictionary User (VDU) is proposed in this paper. Based on the historical data of movement, users can discover their relationships with others. Subsequently, according to the users activity, VDU is selected to facilitate the service registration procedure. Further, the service information outside of a home community can be obtained through the Global Active User (GAU) to support the service selection. To provide the Quality of Service (QoS), the Service Providing User (SPU) is chosen among multiple candidates. Numerical results show that, when compared with other classical service algorithms, the proposed scheme can improve the successful service demand discovery ratio by 25% under reduced overheads

Social Relation Aware Hybrid Service Discovery Mechanism for Intermittently Connected Wireless Networks

In intermittently connected wireless network, service discovery is utilized to identify the best relay to process packets for the service registration, selection and activation. Since packets are transmitted by intermittently connected nodes, the service discovery is challenging due to the partitioned topology, long delays, and dynamic social feature. To maximize the utilization of limited network resources, in this paper, a hybrid service discovery architecture including Virtual Dictionary Node (VDN) is proposed. According to the historical data of movement, all nodes can discover their relationships with others. Subsequently, according to the node activity, VDN is chosen to facilitate the service registration procedure. Further, the service information outside of a home community can be obtained through Global Active Node (GAN) to support the service selection. To improve the utilization of network resources and provide quality services, a Service Providing Node (SPN) is determined among multiple candidates. Simulation results show that, when compared with other classical service algorithms, the proposed scheme can improve the successful service discovery ratio by 25 % with reduced overheads