Recent advances in human respiratory epithelium models for drug discovery

The respiratory epithelium is intimately associated with the pathophysiologies of highly infectious viral contagions and chronic illnesses such as chronic obstructive pulmonary disorder, presently the third leading cause of death worldwide with a projected economic burden of £1.7 trillion by 2030. Preclinical studies of respiratory physiology have almost exclusively utilised non-humanised animal models, alongside reductionistic cell line-based models, and primary epithelial cell models cultured at an air-liquid interface (ALI). Despite their utility, these model systems have been limited by their poor correlation to the human condition. This has undermined the ability to identify novel therapeutics, evidenced by a 15% chance of success for medicinal respiratory compounds entering clinical trials in 2018. Consequently, preclinical studies require new translational efficacy models to address the problem of respiratory drug attrition. This review describes the utility of the current in vivo (rodent), ex vivo (isolated perfused lungs and precision cut lung slices), two-dimensional in vitro cell-line (A549, BEAS-2B, Calu-3) and three-dimensional in vitro ALI (gold-standard and co-culture) and organoid respiratory epithelium models. The limitations to the application of these model systems in drug discovery research are discussed, in addition to perspectives of the future innovations required to facilitate the next generation of human-relevant respiratory models

The effects of solvent treated PEDOT:PSS buffer layer in organic solar cells

Various treatments on the PEDOT:PSS films were carried out to investigate it’s influence on the conductivity, morphology, transmittance and the corresponding impact of the performance of the organic photovoltaic devices based on the PCPDTBT:PCBM and P3HT:PCBM blends. These processing including doping PEDOT:PSS with DMF and ME solvents and exposing these films to the vapor of DMF and ME solvents, separately. A considerable enhancement of the conductivity and transmittance of PEDOT:PSS was observed after doping solvent into the PEDOT;PSS solution followed by solvent treatment through exposing these films to solvents environment. The best organic PV doped devices based on either PCPDTBT:PCBM or based on P3HT:PCBM with power conversion efficiency were 2.93% compared to 1.87% for the pristine PV devices or 2.79% compared to 1.77% for the pristine devices, respectively. The conductivity improvement was highly influenced by solvent treatment

An Alternative Choice in Heighting

Comparison of orthometric heights obtained from the combination of GPS/Levelling survey method with that obtained from Lidar, Srtm, and Astergdem data is an area of research which is of great interest to Geomaticians. This area of research makes possible the discovery of other suitable methods of determining orthometric height which can be selected for use depending on the region, extent and nature of the terrain where the project is to be executed.The X, Y, Z coordinates and the geoidal heights for all the existing controls within university of Lagos were determined using the GPS/ Levelling survey method, the required orthometric height (H) was then obtained as the differences between ellipsoidal and geoidal heights. Extracting orthometric heights for the X and Y coordinates of observed control points overlaid on each of Lidar, Srtm and Astergdem required the use of spatial analysis tool in an arc map environment. From the profile plot (Figure 3.5) of all the orthometric heights, the heights relationship was easy established. From the descriptive statistics test (Table 3.4), the one way ANOVAs test at 1% and 5% level of significance (Table 3.8), the number of points in other methods whose orthometric height is closed to that of Levelling/GPS method (Table 3.7) and correlation test on the various orthometric heights obtained (Table 3.5) it is obvious that all the applied methods operates at different spatial resolutions, of all the four methods, GPS/Levelling method was the most reliable and most accurate method followed by lidar method, then by astergdem method and Srtm has the least. In a nutshell, Orthometric heights generated by method of Lidar are very close to that generated by GPS/Levelling method at several stations, thus method of Lidar was considered as the most suitable alternative to GPS/Levelling method, whenever the use of later method cannot be easily accomplished.

Harmonization of brain PET images in multi-center PET studies using Hoffman phantom scan

Background: Image harmonization has been proposed to minimize heterogeneity in brain PET scans acquired in multi-center studies. However, standard validated methods and software tools are lacking. Here, we assessed the performance of a framework for the harmonization of brain PET scans in a multi-center European clinical trial. / Method: Hoffman 3D brain phantoms were acquired in 28 PET systems and reconstructed using site-specific settings. Full Width at Half Maximum (FWHM) of the Effective Image Resolution (EIR) and harmonization kernels were estimated for each scan. The target EIR was selected as the coarsest EIR in the imaging network. Using “Hoffman 3D brain Analysis tool,” indicators of image quality were calculated before and after the harmonization: The Coefficient of Variance (COV%), Gray Matter Recovery Coefficient (GMRC), Contrast, Cold-Spot RC, and left-to-right GMRC ratio. A COV% ≤ 15% and Contrast ≥ 2.2 were set as acceptance criteria. The procedure was repeated to achieve a 6-mm target EIR in a subset of scans. The method’s robustness against typical dose-calibrator-based errors was assessed. / Results: The EIR across systems ranged from 3.3 to 8.1 mm, and an EIR of 8 mm was selected as the target resolution. After harmonization, all scans met acceptable image quality criteria, while only 13 (39.4%) did before. The harmonization procedure resulted in lower inter-system variability indicators: Mean ± SD COV% (from 16.97 ± 6.03 to 7.86 ± 1.47%), GMRC Inter-Quartile Range (0.040–0.012), and Contrast SD (0.14–0.05). Similar results were obtained with a 6-mm FWHM target EIR. Errors of ± 10% in the DRO activity resulted in differences below 1 mm in the estimated EIR. / Conclusion: Harmonizing the EIR of brain PET scans significantly reduced image quality variability while minimally affecting quantitative accuracy. This method can be used prospectively for harmonizing scans to target sharper resolutions and is robust against dose-calibrator errors. Comparable image quality is attainable in brain PET multi-center studies while maintaining quantitative accuracy

PET imaging of putative microglial activation in individuals at ultra-high risk for psychosis, recently diagnosed and chronically ill with schizophrenia

We examined putative microglial activation as a function of illness course in schizophrenia. Microglial activity was quantified using [11C](R)-(1-[2-chrorophynyl]-N-methyl-N-[1-methylpropyl]-3 isoquinoline carboxamide (11C-(R)-PK11195) positron emission tomography (PET) in: (i) 10 individuals at ultra-high risk (UHR) of psychosis; (ii) 18 patients recently diagnosed with schizophrenia; (iii) 15 patients chronically ill with schizophrenia; and, (iv) 27 age-matched healthy controls. Regional-binding potential (BPND) was calculated using the simplified reference-tissue model with four alternative reference inputs. The UHR, recent-onset and chronic patient groups were compared to age-matched healthy control groups to examine between-group BPND differences in 6 regions: dorsal frontal, orbital frontal, anterior cingulate, medial temporal, thalamus and insula. Correlation analysis tested for BPND associations with gray matter volume, peripheral cytokines and clinical variables. The null hypothesis of equality in BPND between patients (UHR, recent-onset and chronic) and respective healthy control groups (younger and older) was not rejected for any group comparison or region. Across all subjects, BPND was positively correlated to age in the thalamus (r=0.43, P=0.008, false discovery rate). No correlations with regional gray matter, peripheral cytokine levels or clinical symptoms were detected. We therefore found no evidence of microglial activation in groups of individuals at high risk, recently diagnosed or chronically ill with schizophrenia. While the possibility of 11C-(R)-PK11195-binding differences in certain patient subgroups remains, the patient cohorts in our study, who also displayed normal peripheral cytokine profiles, do not substantiate the assumption of microglial activation in schizophrenia as a regular and defining feature, as measured by 11C-(R)-PK11195 BPND.M A Di Biase, A Zalesky, G O'keefe, L Laskaris, B T Baune, C S Weickert, J Olver, P D McGorry, G P Amminger, B Nelson, A M Scott, I Hickie, R Banati, F Turkheimer, M Yaqub, I P Everall, C Pantelis and V Crople

What Determines Cognitive Functioning in the Oldest-Old? The EMIF-AD 90+ Study

OBJECTIVES: Determinants of cognitive functioning in individuals aged 90 years and older, the oldest-old, remain poorly understood. We aimed to establish the association of risk factors, white matter hyperintensities (WMH), hippocampal atrophy and amyloid aggregation with cognition in the oldest-old. METHODS: We included 84 individuals without cognitive impairment and 38 individuals with cognitive impairment from the EMIF-AD 90+ Study (mean age 92.4 years) and tested cross-sectional associations between risk factors (cognitive activity, physical parameters, nutritional status, inflammatory markers and cardiovascular risk factors), brain pathology biomarkers (WMH and hippocampal volume on MRI, and amyloid binding measured with PET) and cognition. Additionally, we tested whether the brain pathology biomarkers were independently associated with cognition. When applicable, we tested whether the effect of risk factors on cognition was mediated by brain pathology. RESULTS: Lower values for handgrip strength, Short Physical Performance Battery (SPPB), nutritional status, HbA1c and hippocampal volume, and higher values for WMH volume and amyloid binding were associated with worse cognition. Higher past cognitive activity and lower BMI were associated with increased amyloid binding, lower muscle mass with more WMH, and lower SPPB scores with more WMH and hippocampal atrophy. The brain pathology markers were independently associated with cognition. The association of SPPB with cognition was partially mediated by hippocampal volume. DISCUSSION: In the oldest-old, physical parameters, nutritional status, HbA1c, WMH, hippocampal atrophy and amyloid binding are associated with cognitive impairment. Physical performance may affect cognition through hippocampal atrophy. This study highlights the importance to consider multiple factors when assessing cognition in the oldest-old

Improving Fetal Head Contour Detection by Object Localisation with Deep Learning

Ultrasound-based fetal head biometrics measurement is a key indicator in monitoring the conditions of fetuses. Since manual measurement of relevant anatomical structures of fetal head is time-consuming and subject to inter-observer variability, there has been strong interest in finding automated, robust, accurate and reliable method. In this paper, we propose a deep learning-based method to segment fetal head from ultrasound images. The proposed method formulates the detection of fetal head boundary as a combined object localisation and segmentation problem based on deep learning model. Incorporating an object localisation in a framework developed for segmentation purpose aims to improve the segmentation accuracy achieved by fully convolutional network. Finally, ellipse is fitted on the contour of the segmented fetal head using least-squares ellipse fitting method. The proposed model is trained on 999 2-dimensional ultrasound images and tested on 335 images achieving Dice coefficient of$$97.73 \pm 1.32$$. The experimental results demonstrate that the proposed deep learning method is promising in automatic fetal head detection and segmentation