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Comparison of multiple gene expression platforms for measuring a bladder cancer hypoxia signature
Get PDFTumour hypoxia status provides prognostic informa‑tion and predicts response to hypoxia‑modifying treatments. Aprevious study by our group derived a 24‑gene signature to assess hypoxia in bladder cancer. The objectives of the present study were to compare platforms for generating signature scores, identify cut‑off values for prospective studies, assess intra‑tumour heterogeneity and confirm hypoxia relevance. Briefly, RNA was extracted from prospectively collected diag‑nostic biopsies of muscle invasive bladder cancer (51 patients), and gene expression was measured using customised Taqman Low Density Array (TLDA) cards, NanoString and Clariom S arrays. Cross‑platform transferability of the gene signature was assessed using regression and concordance analysis. The cut‑off values were the cohort median expression values. Intra‑ and inter‑tumour variability were determined in a retrospective patient cohort (n=51) with multiple blocks (2‑18) from the same tumour. To demonstrate relevance, bladder cancer cell lines were exposed to hypoxia (0.1% oxygen, 24 h), and extracted RNA was run on custom TLDA cards. Hypoxia scores (HS) values showed good agreement between platforms: Clariom S vs. TLDA (r=0.72, P<0.0001; concor‑dance 73%); Clariom S vs. NanoString (r=0.84, P<0.0001; 78%); TLDA vs. NanoString (r=0.80, P<0.0001; 78%). Cut‑off values were 0.047 (TLDA), 7.328 (NanoString) and 6.667 (Clariom S). Intra‑tumour heterogeneity in gene expression and HS (coefficient of variation 3.9%) was less than inter‑tumour (7.9%) variability. HS values were higher in bladder cancer cells exposed to hypoxia compared with normoxia (P<0.02). In conclusion, the present study revealed that application of the 24‑gene bladder cancer hypoxia signature was platform agnostic, cut‑off values determined prospectively can be used in a clinical trial, intra‑tumour heterogeneity was low and the signature was sensitive to changes in oxygen levels in vitro
Nanovibration detection based on a microsphere
Get PDFWe propose a novel, to the best of our knowledge, sensor for nanovibration detection based on a microsphere. The sensor consists of a stretched single-mode fiber and a 2 µm microsphere. The light from the optical fiber passes through the microsphere, forming a photonic nanojet (PNJ) phenomenon at the front of the microsphere. The evanes- cent field in the PNJ enhances the light reflected from the measured object to the single-mode fiber-microsphere probe (SMFMP). Results showed that the system can detect arbi- trary nanovibration waveforms in real time with an SMFMP detection resolution of 1 nm. The voltage signal received and the vibration amplitude showed a good linear relationship within the range of 0–100 nm, with a sensitivity of 0.7 mV/nm and a linearity of more than 99%. The sensor is expected to have potential applications in the field of cell nanovibration detection
Using the Software DeepWings© to Classify Honey Bees across Europe through Wing Geometric Morphometrics
Get PDFDeepWings© is a software that uses machine learning to automatically classify honey bee subspecies by wing geometric morphometrics. Here, we tested the five subspecies classifier (A. m. carnica, Apis mellifera caucasia, A. m. iberiensis, Apis mellifera ligustica, and A. m. mellifera) of DeepWings© on 14,816 wing images with variable quality and acquired by different beekeepers and researchers. These images represented 2601 colonies from the native ranges of the M-lineage A. m. iberiensis and A. m. mellifera, and the C-lineage A. m. carnica. In the A. m. iberiensis range, 92.6% of the colonies matched this subspecies, with a high median probability (0.919). In the Azores, where the Iberian subspecies was historically introduced, a lower proportion (85.7%) and probability (0.842) were observed. In the A. m mellifera range, only 41.1 % of the colonies matched this subspecies, which is compatible with a history of C-derived introgression. Yet, these colonies were classified with the highest probability (0.994) of the three subspecies. In the A. m. carnica range, 88.3% of the colonies matched this subspecies, with a probability of 0.984. The association between wing and molecular markers, assessed for 1214 colonies from the M-lineage range, was highly significant but not strong (r = 0.31, p < 0.0001). The agreement between the markers was influenced by C-derived introgression, with the best results obtained for colonies with high genetic integrity. This study indicates the good performance of DeepWings© on a realistic wing image dataset
Real-time experimental demonstration of a computationally efficient hybrid OFDM DFMA PON
Get PDFThis paper presents the first real-time experimental demonstration of a hybrid OFDM DFMA PON. The presented PON is validated for two channels (I or Q) occupying two subwavelength bands. The hybrid OFDM DFMA PON eliminates the need for a dedicated matching filter at the receiver for each individual channel, by employing a single FFT operation to recover all channels, thereby achieving lower computational complexity. The hybrid OFDM DFMA PON used in conjunction with a joint sideband processing technique, when compared to a DFMA PON under the exact same operating conditions, is shown to offer increased performance, including a lower received optical power of up to 1.2 dB for the adopted FEC limit at a given bit rate. The experimentally demonstrated PON is also proven to be significantly more tolerant to the symbol timing offset effect at the OLT receiver. Furthermore, compared to the DFMA PON’s OLT receiver, the implemented FFT-based receiver is shown to operate at a drastically reduced logic clock rate and with significantly lower DSP complexity. The hybrid OFDM DFMA PON is thus shown to have numerous advantages over the DFMA PON
Development of an organic photovoltaic energy harvesting system for wireless sensor networks; application to autonomous building information management systems and optimisation of OPV module sizes for future applications
Get PDFThe emergence of internet of things (IoT) has motivated research into developing Organic Photovoltaic (OPV) devices that can efficiently convert indoor light into electricity. In this work, the performance and operation of an OPV-powered Wireless Sensor network (WSN) for Building Information management system is provided through a case study. Results are shown for the operation of the WSN and how data can be acquired to build machine learning algorithms that can forecast the indoor conditions of a building, when the system is linked to an external weather station. Remarkably, our data indicates only minor degradation of the OPV when tested under indoor conditions over a 21-month period; at a luminance level of 1000 Lux, only a −10% relative drop in performance was measured. Finally, the field data is used to optimise the size of the OPV and battery for future indoor applications which possess different energy loads. Based on the energy efficiency model, the loss of power supply probability (LPSP) of the indoor applications system is calculated for different size combinations of PV, battery sizes and load energies. This model provides a method to calculate the required OPV output power to ensure remote operation of other IoT electronics
Development of a LoRaWAN IoT Node with Ion-Selective Electrode Soil Nitrate Sensors for Precision Agriculture
Get PDFCrop productivity is highly dependent on the availability of soluble nitrogen (N), e.g. nitrate, in soil. When N levels are low, fertilisers are applied to replenish the soil’s reserves. Typically the timing of these applications is based on paper-based guidance and sensor-based measurements of canopy greenness, which provides an indirect measure of soil N status. However this approach often means that N fertiliser is applied inappropriately or too late, resulting in excess N being lost to the environment, or too little N to meet crop demand. To promote greater N use efficiency and improve agricultural sustainability, we developed an Internet of Things (IoT) approach for the real-time measurement of soil nitrate levels using ion-selective membrane sensors in combination with digital soil moisture probes. The node incorporates state-of-the-art IoT connectivity using a LoRaWAN transceiver. The sensing platform can transfer real-time data via a cloud-connected gateway for processing and storage. In summary, we present a validated soil sensor system for real-time monitoring of soil nitrate concentrations, which can support fertiliser management decisions, improve N use efficiency and reduce N losses to the environment
Species Traits and Geomorphic Setting as Drivers of Global Soil Carbon Stocks in Seagrass Meadows
Get PDFAbstract Our knowledge of the factors that can influence the stock of organic carbon (OC) that is stored in the soil of seagrass meadows is evolving, and several causal effects have been used to explain the variation of stocks observed at local to national scales. To gain a global-scale appreciation of the drivers that cause variation in soil OC stocks, we compiled data on published species-specific traits and OC stocks from monospecific and mixed meadows at multiple geomorphological settings. Species identity was recognized as an influential driver of soil OC stocks, despite their large intraspecific variation. The most important seagrass species traits associated with OC stocks were the number of leaves per seagrass shoot, belowground biomass, leaf lifespan, aboveground biomass, leaf lignin, leaf breaking force and leaf OC plus the coastal geomorphology of the area, particularly for lagoon environments. A revised estimate of the global average soil OC stock to 20 cm depth of 15.4 Mg C ha−1 is lower than previously reported. The largest stocks were still recorded in Mediterranean seagrass meadows. Our results specifically identify Posidonia oceanica from the Mediterranean and, more generally, large and persistent species as key in providing climate regulation services, and as priority species for conservation for this specific ecosystem service
Inquiry into Benefits in Wales: options for a better delivery
Get PDFWritten for Senedd Cymru Welsh Parliamen
Cost-effective models for delivering behaviour analysis teaching in UK schools and local authorities
Get PDFEducation programmes based on behaviour analysis are often used to teach children with learning disabilities. A common application of behaviour analysis is Early Intensive Behaviour Intervention (EIBI), which is evidence-based, but most children in the UK do not have access to this approach. EIBI is usually implemented for 30 to 40 hours per week, over two years. High levels of supervision from behaviour analysts are essential to ensure EIBI's effectiveness. A recent cost-effectiveness study concluded that EIBI was not cost-effective: while the children make progress relative to treatment as usual, the outcomes did not justify the cost of the intervention. Other low-cost models of delivery need to be considered. School-based models used in the UK may provide cost-effective and sustainable ways to use applied behaviour analysis in schools. They could be used in other local authorities to increase access to an education that includes behaviour analysis
Mohave rattlesnake (Crotalus scutulatus) identification revisited
Get PDFCrotalus scutulatus (Mohave rattlesnake) is a clinically significant pit viper broadly distributed across much of the arid southwestern United States and mainland Mexico. Identification of C scutulatus is a concern among emergency medical service and emergency department personnel owing to its reputation for severe envenomations and difficulty in visually differentiating between C scutulatus and other species, primarily Crotalus atrox (western diamond-backed rattlesnake). We contrast distinctive characteristics of C scutulatus, C atrox, and 3 other sympatric species: Crotalus molossus, Crotalus ornatus, and Crotalus viridis (western and eastern black-tailed rattlesnakes and prairie rattlesnake, respectively). Greenish coloration eliminates C atrox but does not confirm C scutulatus. Obvious coarse and fine speckling of the dorsal pattern and a pale postocular stripe intersecting the mouth characterize C atrox. Dorsal speckling is insignificant or absent in the other species, whereas the pale postocular stripe passes above the mouth in C scutulatus and C viridis and is absent in C molossus and C ornatus. Tails boldly ringed with alternating black and white or contrasting shades of gray are shared by C atrox and C scutulatus, respectively, but a lack of boldly ringed tails characterizes the other species. The proximal rattle segment is yellow and black, or entirely yellow, in C scutulatus but black in the others. The most reliable visual identifications are based on evaluations of multiple traits, all of which are variable to some extent. Traits such as tail ring width and the size and number of crown scales have frequently been over-emphasized in the past