Tzu-Shiang Lin

Clinical utility of array comparative genomic hybridisation for prenatal diagnosis: a cohort study of 3171 pregnancies

Sir, We read with great interest your recent publication by Lee et al. on the use of array comparative genomic hybridisation (CGH) for prenatal diagnosis: a cohort study of 3171 pregnancies. Such a large cohort is an important contribution to the existing literature. It is important then to compare and contrast the results of Lee’s study with those of other recently published cohorts. The abstract states that when array CGH is performed for a fetus with a congenital anomaly apparent on prenatal ultrasound, the test was effective in identifying submicroscopic genomic imbalances (i.e. that are unidentifiable by conventional G-band karyotyping) in 33 of 194 (17%) cases. However, on reviewing data within table 2 (and later on in the abstract) this rate is recorded as 16/194 (8.2%). We attempted to extract data on submicroscopic copy number changes from table 2, but there appeared to have been formatting errors (e.g. in the row ‘pathogenic karyotyping reports’ the columns appear to be shifted a space to the right). It is unclear within the table how the calculated total of pathogenic karyotype and array CGH reports are constructed. We assume that pathogenic karyotype reports would be made up of those with numerical abnormality plus those with large chromosomal deletions and duplications, whereas pathogenic array reports would be made up of the former plus microscopic chromosomal deletions and duplications, plus variants of unknown significance. This, however, is not made clear. It is not certain whether there may have been instances where the array CGH test failed to identify a chromosomal anomaly detected by conventional karyotyping, and indeed whether both types of karyotype testing were performed for all fetuses included in the study. The authors state within the discussion that ‘when array CGH was performed alone no significantly pathological results were missed’, but without a reference test how could one be sure? Two array CGH platforms were used within this study: a 1-Mb bacterial artificial chromosome (BAC) and a 60-kb oligonucleotide array. It appears that there was a switch to the higher resolution 60-kb array towards the end of the cohort study. However, table 3 is not transparent to which array was used to detect which abnormal result. When extrapolating using the coordinates of the oligonucleotide probes in comparison with those of BAC probes aligned to the reference genome in ensembl, and in BlueGnome’s bluefuse multi database software, we predict that only one of the abnormal results detected by the higher resolution 60-kb array within Lee et al.’s cohort would have been missed by the 1-Mb BAC. This point should be commented on, as the lower resolution BAC would be predicted to produce less variants of unknown significance (VOUS), an important point to consider when using this technology on prenatal samples. The authors did not however state which array contributed to the five VOUS recorded. Finally, the authors conclude that there is a 0.52% baseline risk of submicroscopic genomic imbalance, even in women with an uneventful prenatal ultrasound examination. The authors conclude that prenatal array CGH is a recommended additional test in pregnant women undergoing invasive testing, but do not comment on the additional VOUS results that such testing could reveal, and the problems of interpretation and counselling of these variants in the prenatal setting. Before we can think about using this technology, even as an adjunct to conventional karyotypic testing, this issue must be addressed and the additional costs to overall pregnancy health care must be considered. j

A QoS-guaranteed coverage precedence routing algorithm for wireless sensor networks.

For mission-critical applications of wireless sensor networks (WSNs) involving extensive battlefield surveillance, medical healthcare, etc., it is crucial to have low-power, new protocols, methodologies and structures for transferring data and information in a network with full sensing coverage capability for an extended working period. The upmost mission is to ensure that the network is fully functional providing reliable transmission of the sensed data without the risk of data loss. WSNs have been applied to various types of mission-critical applications. Coverage preservation is one of the most essential functions to guarantee quality of service (QoS) in WSNs. However, a tradeoff exists between sensing coverage and network lifetime due to the limited energy supplies of sensor nodes. In this study, we propose a routing protocol to accommodate both energy-balance and coverage-preservation for sensor nodes in WSNs. The energy consumption for radio transmissions and the residual energy over the network are taken into account when the proposed protocol determines an energy-efficient route for a packet. The simulation results demonstrate that the proposed protocol is able to increase the duration of the on-duty network and provide up to 98.3% and 85.7% of extra service time with 100% sensing coverage ratio comparing with LEACH and the LEACH-Coverage-U protocols, respectively.

High-Precision RSSI-based Indoor Localization Using a Transmission Power Adjustment Strategy for Wireless Sensor Networks

Indoor localization is an important issue in wireless sensor network (WSN) studies. Sensed data may become meaningless, if the locations of sensors are not known. Traditional localization techniques do not meet the requirements of low-cost and energy-conservation while performing localization tasks. Recently, the received signal strength indicator (RSSI)-based range measurement technology is widely used in sensor networks due to its easy implementation. In typical indoor environments, RSSI is affected by dense multipath fading effects because people are moving around, or because furniture and equipment block transmission signals. Therefore, the overall accuracy of RSSI-based localization schemes remains low. In this paper, a new localization scheme which is based on a transmission power adjustment strategy is proposed. Firstly, power decay curves are created in a real indoor environment to accurately estimate the distances between an unknown node and anchor nodes. Secondly, the unknown node selects three nearest anchor nodes by using the minimum transmission power to limit the estimated location to a triangle area. And then, the centroid of the triangle is calculated and serves as the initial estimated point. Finally, based on the estimated distances of corresponding power curves determined by RSSI scores using different transmission power levels, the final estimated location falls in one of the three equally divided areas of the triangle. The experimental results demonstrate that the proposed method can provide a low-cost solution for indoor localization with high precision.

CoCMA: Energy-Efficient Coverage Control in Cluster-Based Wireless Sensor Networks Using a Memetic Algorithm

Deployment of wireless sensor networks (WSNs) has drawn much attention in recent years. Given the limited energy for sensor nodes, it is critical to implement WSNs with energy efficiency designs. Sensing coverage in networks, on the other hand, may degrade gradually over time after WSNs are activated. For mission-critical applications, therefore, energy-efficient coverage control should be taken into consideration to support the quality of service (QoS) of WSNs. Usually, coverage-controlling strategies present some challenging problems: (1) resolving the conflicts while determining which nodes should be turned off to conserve energy; (2) designing an optimal wake-up scheme that avoids awakening more nodes than necessary. In this paper, we implement an energy-efficient coverage control in cluster-based WSNs using a Memetic Algorithm (MA)-based approach, entitled CoCMA, to resolve the challenging problems. The CoCMA contains two optimization strategies: a MA-based schedule for sensor nodes and a wake-up scheme, which are responsible to prolong the network lifetime while maintaining coverage preservation. The MA-based schedule is applied to a given WSN to avoid unnecessary energy consumption caused by the redundant nodes. During the network operation, the wake-up scheme awakens sleeping sensor nodes to recover coverage hole caused by dead nodes. The performance evaluation of the proposed CoCMA was conducted on a cluster-based WSN (CWSN) under either a random or a uniform deployment of sensor nodes. Simulation results show that the performance yielded by the combination of MA and wake-up scheme is better than that in some existing approaches. Furthermore, CoCMA is able to activate fewer sensor nodes to monitor the required sensing area.

Application of a web-based remote agro-ecological monitoring system for observing spatial distribution and dynamics of Bactrocera dorsalis in fruit orchards

Improving fruit farm profitability through integrated pest management (IPM) programs is always an important issue to modern agriculture systems. In order to enhance IPM programs against Bactrocera dorsalis, an automatic infield monitoring system is required to efficiently capture long-term and up-to-the-minute environmental fluctuations in a fruit farm. In this study, a remote agro-ecological monitoring system built upon wireless sensor networks has been developed to provide precision agriculture (PA) services with large-scale, long-distance, long-term, scalable, and real-time infield data collection capabilities. Historical data with spatial information is available through a web-based decision support program built upon a database. Pest population forecast results are also provided so that farmers and government officials would be able to accurately respond to infield variations. Compared with the previous version of the system, various useful functions have been added into the system, and its accuracy has been improved when measuring different parameters in the field. The system could provide a valuable framework for farmers and pest control officials to analyze the relations between population dynamics of the fruit fly and meteorological events. Based on the analysis, a better insect pest risk assessment and accurate decision-making strategy can be made as an aid to PA against B. dorsalis.

Resolution of high uterine artery pulsatility index and notching following sildenafil citrate treatment in a growth‐restricted pregnancy

Fetal growth restriction (FGR) and pre-eclampsia remain the major causes of neonatal and maternal morbidity and mortality1. These two conditions have been shown to result from abnormal trophoblast invasion, which compromises uteroplacental circulation2. Uterine artery Doppler ultrasonography and a variety of proteins and hormones have been studied as potential early biomarkers of FGR or pre-eclampsia3. However, after identifying high-risk patients, management strategies are limited to increasing frequency of surveillance. Recent studies have demonstrated that sildenafil citrate significantly enhances vasodilation of myometrial small arteries and is also associated with fetal weight gain4–6, which offers a potential therapeutic possibility for FGR. We report here a case demonstrating improvement of uterine artery Doppler ultrasonography following sildenafil citrate treatment in a 26-week pregnancy with FGR.

Collaborative Localization in Wireless Sensor Networks via Pattern Recognition in Radio Irregularity Using Omnidirectional Antennas

In recent years, various received signal strength (RSS)-based localization estimation approaches for wireless sensor networks (WSNs) have been proposed. RSS-based localization is regarded as a low-cost solution for many location-aware applications in WSNs. In previous studies, the radiation patterns of all sensor nodes are assumed to be spherical, which is an oversimplification of the radio propagation model in practical applications. In this study, we present an RSS-based cooperative localization method that estimates unknown coordinates of sensor nodes in a network. Arrangement of two external low-cost omnidirectional dipole antennas is developed by using the distance-power gradient model. A modified robust regression is also proposed to determine the relative azimuth and distance between a sensor node and a fixed reference node. In addition, a cooperative localization scheme that incorporates estimations from multiple fixed reference nodes is presented to improve the accuracy of the localization. The proposed method is tested via computer-based analysis and field test. Experimental results demonstrate that the proposed low-cost method is a useful solution for localizing sensor nodes in unknown or changing environments.

Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

A self sustainable air quality monitoring system using WSN

In recent years, urban air quality monitoring is increasingly important. To monitor air quality in urban areas, wireless sensor networks (WSNs) might be a great tool, because they can automatically collect air-quality data. WSNs are able to provide data with spatiotemporal continuity, so researchers can analyze the data in detail. This paper proposes a self-sustainable air quality monitoring system based on the WSN technology to collect air quality parameters in an urban area. The proposed system uses carbon monoxide (CO) and particulate matter (PM) sensors to monitor CO and PM, and the readings from the two sensors are viewed as air quality indices. The proposed system combines a solar cell and a lead-acid battery as its power supply devices, so the system has the long-tern monitoring capability.

A GSM-based Field Monitoring System for Spodoptera litura (Fabricius)*

The hot and humid weather of Taiwan causes a wide spread of pests and a great loss to Taiwans agriculture. In particular, Spodoptera litura (Fabricius) causes huge agricultural disasters in past years. To gather important information related to the outbreak of S. litura, we develop an ecological monitoring system which combines GSM transmission technologies with mechatronics. The proposed system also equips with an MSP430 low-power microcontroller, a solar power supply system, and a trapping tube. All information collected by the system is stored in a specially designed database. The system is then deployed at an outdoor environment to verify its reliability. The test results show that the system is capable of providing effective monitoring information for pest management.