Arylsilanes and siloxanes as optoelectronic materials for organic light-emitting diodes (OLEDs)

Organic light emitting diodes (OLEDs) are currently receiving much attention for applications in new generation full-colour flat-panel and flexible displays and as sources for low energy solid-state lighting. Arylsilanes and siloxanes have been extensively studied as components of OLEDs, mainly focusing on optimizing the physical and electronic properties of the light-emitting layer and other functional layers within the OLED architecture. Arylsilanes and siloxanes display the advantages of good solubility in common organic solvents and excellent resistance to thermal, chemical and irradiation degradations. In this review, we summarize the recent advances in the utilization of arylsilanes and siloxanes as fluorophore emitters, hosts for phosphor emitters, hole and exciton blocking materials, and as electron and hole transporting materials. Finally, perspectives and challenges related to arylsilanes and siloxanes for OLED applications are proposed based on the reported progress and our own opinions

Brain Tumor Classification Using a Combination of Variational Autoencoders and Generative Adversarial Networks

Brain tumors are a pernicious cancer with one of the lowest five-year survival rates. Neurologists often use magnetic resonance imaging (MRI) to diagnose the type of brain tumor. Automated computer-assisted tools can help them speed up the diagnosis process and reduce the burden on the health care systems. Recent advances in deep learning for medical imaging have shown remarkable results, especially in the automatic and instant diagnosis of various cancers. However, we need a large amount of data (images) to train the deep learning models in order to obtain good results. Large public datasets are rare in medicine. This paper proposes a framework based on unsupervised deep generative neural networks to solve this limitation. We combine two generative models in the proposed framework: variational autoencoders (VAEs) and generative adversarial networks (GANs). We swap the encoder–decoder network after initially training it on the training set of available MR images. The output of this swapped network is a noise vector that has information of the image manifold, and the cascaded generative adversarial network samples the input from this informative noise vector instead of random Gaussian noise. The proposed method helps the GAN to avoid mode collapse and generate realistic-looking brain tumor magnetic resonance images. These artificially generated images could solve the limitation of small medical datasets up to a reasonable extent and help the deep learning models perform acceptably. We used the ResNet50 as a classifier, and the artificially generated brain tumor images are used to augment the real and available images during the classifier training. We compared the classification results with several existing studies and state-of-the-art machine learning models. Our proposed methodology noticeably achieved better results. By using brain tumor images generated artificially by our proposed method, the classification average accuracy improved from 72.63% to 96.25%. For the most severe class of brain tumor, glioma, we achieved 0.769, 0.837, 0.833, and 0.80 values for recall, specificity, precision, and F1-score, respectively. The proposed generative model framework could be used to generate medical images in any domain, including PET (positron emission tomography) and MRI scans of various parts of the body, and the results show that it could be a useful clinical tool for medical experts

Molecular Dynamic Simulation to Explore the Molecular Basis of Btk-PH Domain Interaction with Ins(1,3,4,5)P4

Bruton’s tyrosine kinase contains a pleckstrin homology domain, and it specifically binds inositol 1,3,4,5-tetrakisphosphate (Ins(1,3,4,5)P4), which is involved in the maturation of B cells. In this paper, we studied 12 systems including the wild type and 11 mutants, K12R, S14F, K19E, R28C/H, E41K, L11P, F25S, Y40N, and K12R-R28C/H, to investigate any change in the ligand binding site of each mutant. Molecular dynamics simulations combined with the method of molecular mechanics/Poisson-Boltzmann solvent-accessible surface area have been applied to the twelve systems, and reasonable mutant structures and their binding free energies have been obtained as criteria in the final classification. As a result, five structures, K12R, K19E, R28C/H, and E41K mutants, were classified as “functional mutations,” whereas L11P, S14F, F25S, and Y40N were grouped into “folding mutations.” This rigorous study of the binding affinity of each of the mutants and their classification provides some new insights into the biological function of the Btk-PH domain and related mutation-causing diseases

A versatile hybrid polyphenylsilane host for highly efficient solution-processed blue and deep blue electrophosphorescence

A universal hybrid polymeric host (PCzSiPh) for blue and deep blue phosphors has been designed and synthesized by incorporating electron-donating carbazole as pendants on a polytetraphenylsilane main chain. The polymer PCzSiPh (4) has a wide bandgap and high triplet energy (ET) because of the tetrahedral geometry of the silicon atom in the tetraphenylsilane backbone. The distinct physical properties of good solubility, combined with high thermal and morphological stability give amorphous and homogenous PCzSiPh films by solution processing. As a result, using PCzSiPh as host with the guest iridium complex TMP-FIrpic gives blue phosphorescent organic light-emitting diodes (PhOLEDs) with overall performance which far exceeds that of a control device with poly(vinylcarbazole) (PVK) host. Notably, FIrpic-based devices exhibit a maximum external quantum efficiency (EQE) of 14.3% (29.3 cd A−1, 10.4 lm W−1) which are comparable to state-of-the-art literature data using polymer hosts for a blue dopant emitter. Moreover, the versatility of PCzSiPh extends to deep blue PhOLEDs using FIr6 and FCNIrpic as dopants, with high efficiencies of 11.3 cd A−1 and 8.6 cd A−1, respectively

Recent Advances in Flame Retardant and Mechanical Properties of Polylactic Acid: A Review.

The large-scale application of ecofriendly polymeric materials has become a key focus of scientific research with the trend toward sustainable development. Mechanical properties and fire safety are two critical considerations of biopolymers for large-scale applications. Polylactic acid (PLA) is a flammable, melt-drop carrying, and strong but brittle polymer. Hence, it is essential to achieve both flame retardancy and mechanical enhancement to improve safety and broaden its application. This study reviews the recent research on the flame retardant functionalization and mechanical reinforcement of PLA. It classifies PLA according to the type of the flame retardant strategy employed, such as surface-modified fibers, modified nano/micro fillers, small-molecule and macromolecular flame retardants, flame retardants with fibers or polymers, and chain extension or crosslinking with other flame retardants. The functionalization strategies and main parameters of the modified PLA systems are summarized and analyzed. This study summarizes the latest advances in the fields of flame retardancy and mechanical reinforcement of PLA.pre-print3656 K

Risk assessment of malaria in land border regions of China in the context of malaria elimination

BACKGROUND:Cross-border malaria transmission poses a challenge for countries to achieve and maintain malaria elimination. Because of a dramatic increase of cross-border population movement between China and 14 neighbouring countries, the malaria epidemic risk in China's land border regions needs to be understood.METHODS: In this study, individual case-based epidemiological data on malaria in the 136 counties of China with international land borders, from 2011 to 2014, were extracted from the National Infectious Disease Information System. The Plasmodium species, seasonality, spatiotemporal distribution and changing features of imported and indigenous cases were analysed using descriptive spatial and temporal methods.RESULTS:A total of 1948 malaria cases were reported, with 1406 (72.2%) imported cases and 542 (27.8%) indigenous cases. Plasmodium vivax is the predominant species, with 1536 malaria cases occurrence (78.9%), following by Plasmodium falciparum (361 cases, 18.5%), and the others (51 cases, 2.6%). The magnitude and geographic distribution of malaria in land border counties shrunk sharply during the elimination period. Imported malaria cases were with a peak of 546 cases in 2011, decreasing yearly in the following years. The number of counties with imported cases decreased from 28 counties in 2011 to 26 counties in 2014. Indigenous malaria cases presented a markedly decreasing trend, with 319 indigenous cases in 2011 reducing to only 33 indigenous cases in 2014. The number of counties with indigenous cases reduced from 26 counties in 2011 to 10 counties in 2014. However, several bordering counties of Yunnan province adjacent to Myanmar reported indigenous malaria cases in the four consecutive years from 2011 to 2014.CONCLUSIONS:The scale and extent of malaria occurrence in the international land border counties of China decreased dramatically during the elimination period. However, several high-risk counties, especially along the China-Myanmar border, still face a persistent risk of malaria introduction and transmission. The study emphasizes the importance and urgency of cross-border cooperation between neighbouring countries to jointly face malaria threats to elimination goals

a practical tool to implement hospital-based syndromic surveillance: SCM

Background: syndromic surveillance has been widely used for the early warning of infectious disease outbreaks, especially in mass gatherings, but the collection of electronic data on symptoms in hospitals is one of the fundamental challenges that must be overcome during operating a syndromic surveillance system. The objective of our study is to describe and evaluate the implementation of a symptom-clicking-module (SCM) as a part of the enhanced hospital-based syndromic surveillance during the 41st World Exposition in Shanghai, China, 2010.Methods: the SCM, including 25 targeted symptoms, was embedded in the sentinels’ Hospital Information Systems (HIS). The clinicians used SCM to record these information of all the visiting patients, and data were collated and transmitted automatically in daily batches. The symptoms were categorized into seven targeted syndromes using pre-defined criteria, and statistical algorithms were applied to detect temporal aberrations in the data series.Results: SCM was deployed successfully in each sentinel hospital and was operated during the 184-day surveillance period. A total of 1,730,797 patient encounters were recorded by SCM, and 6.1 % (105,352 visits) met the criteria of the seven targeted syndromes. Acute respiratory and gastrointestinal syndromes were reported most frequently, accounted for 92.1 % of reports in all syndromes, and the aggregated time-series presented an obvious day-of-week variation over the study period. In total, 191 aberration signals were triggered, and none of them were identified as outbreaks after verification and field investigation.Conclusions: SCM has acted as a practical tool for recording symptoms in the hospital-based enhanced syndromic surveillance system during the 41st World Exposition in Shanghai, in the context of without a preexisting electronic tool to collect syndromic data in the HIS of the sentinel hospitals

Plasmodium falciparum malaria importation from Africa to China and its mortality: an analysis of driving factors

Plasmodium falciparum malaria importation from Africa to China is rising with increasing Chinese overseas investment and international travel. Identifying networks and drivers of this phenomenon as well as the contributors to high case-fatality rate is a growing public health concern to enable efficient response. From 2011–2015, 8653?P. falciparum cases leading to 98 deaths (11.3 per 1000 cases) were imported from 41 sub-Saharan countries into China, with most cases (91.3%) occurring in labour-related Chinese travellers. Four strongly connected groupings of origin African countries with destination Chinese provinces were identified, and the number of imported cases was significantly associated with the volume of air passengers to China (P?=?0.006), parasite prevalence in Africa (P?<?0.001), and the amount of official development assistance from China (P?<?0.001) with investment in resource extraction having the strongest relationship with parasite importation. Risk factors for deaths from imported cases were related to the capacity of malaria diagnosis and diverse socioeconomic factors. The spatial heterogeneity uncovered, principal drivers explored, and risk factors for mortality found in the rising rates of P. falciparum malaria importation to China can serve to refine malaria elimination strategies and the management of cases, and high risk groups and regions should be targeted