Low-Power Upconversion in Poly(Mannitol-Sebacate) Networks with Tethered Diphenylanthracene and Palladium Porphyrin

[EN] Efforts to fabricate low-power up converting solid-state systems have rapidly increased in the past decade because of their possible application in several fields such as bio-imaging, drug delivery, solar harvesting or displays. The synthesis of upconverting cross-linked polyester rubbers with covalently tethered chromophores is presented here. Cross-linked films were prepared by reacting a poly(mannitol- sebacate) pre-polymer with 9,10-bis(4-hydroxymethylphenyl) anthracene (DPA-(CH2OH)2) and palladium mesoporphyrin IX. These chromophores served as emitters and sensitizers, respectively, and through a cascade of photophysical events, resulted in an anti-Stokes shifted emission. Indeed, blue emission (*440 nm) of these solid materials was detected upon excitation at 543 nm with a green laser and the power dependence of integrated unconverted intensity versus excitation was examined. The new materials display upconversion at power densities as low as 32 mW/cm2, and do not display phase de-mixing, which has been identified as an obstacle in rubbery blends comprising untethered chromophores.The authors are thankful for the financial support of the Swiss National Science Foundation (200021_13540/1 and 200020_152968), Spanish Ministry of Economy and Competitiveness (Project MAT2010/21494-C03) and the Adolphe Merkle Foundation. The authors thank Prof. Christoph Weder for his help and support.Lee, S.; Sonseca, A.; Vadrucci, R.; Giménez Torres, E.; Foster, E.; Simon, YC. (2014). Low-Power Upconversion in Poly(Mannitol-Sebacate) Networks with Tethered Diphenylanthracene and Palladium Porphyrin. Journal of Inorganic and Organometallic Polymers. 24(5):898-903. https://doi.org/10.1007/s10904-014-0063-7S898903245C. A. Parker, C. G. Hatchard. P. Chem. Soc. London, 386–387 (1962)Y.C. Simon, C. Weder, J. Mater. Chem. 22, 20817–20830 (2012)J.Z. Zhao, S.M. Ji, H.M. 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Aryl hydrocarbon receptor deficiency causes the development of chronic obstructive pulmonary disease through the integration of multiple pathogenic mechanisms

Emphysema, a component of chronic obstructive pulmonary disease (COPD), is characterized by irreversible alveolar destruction that results in a progressive decline in lung function. This alveolar destruction is caused by cigarette smoke, the most important risk factor for COPD. Only 15%-20% of smokers develop COPD, suggesting that unknown factors contribute to disease pathogenesis. We postulate that the aryl hydrocarbon receptor (AHR), a receptor/transcription factor highly expressed in the lungs, may be a new susceptibility factor whose expression protects against COPD. Here, we report that Ahr-deficient mice chronically exposed to cigarette smoke develop airspace enlargement concomitant with a decline in lung function. Chronic cigarette smoke exposure also increased cleaved caspase-3, lowered SOD2 expression, and altered MMP9 and TIMP-1 levels in Ahr-deficient mice. We also show that people with COPD have reduced expression of pulmonary and systemic AHR, with systemic AHR mRNA levels positively correlating with lung function. Systemic AHR was also lower in never-smokers with COPD. Thus, AHR expression protects against the development of COPD by controlling interrelated mechanisms involved in the pathogenesis of this disease. This study identifies the AHR as a new, central player in the homeostatic maintenance of lung health, providing a foundation for the AHR as a novel therapeutic target and/or predictive biomarker in chronic lung disease

An investig-ation into the epidemiology of chikungunya virus across neglected regions of Indonesia

Funder: US-CDCBackground: Chikungunya virus (CHIKV) is an important emerging and re-emerging public health problem worldwide. In Indonesia, where the virus is endemic, epidemiological information from outside of the main islands of Java and Bali is limited. Methodology/Principal Findings: Four hundred and seventy nine acutely febrile patients presenting between September 2017–2019 were recruited from three city hospitals situated in Ambon, Maluku; Banjarmasin, Kalimantan; and Batam, Batam Island as part of a multi-site observational study. CHIKV RNA was detected in a single serum sample while a separate sample was IgM positive. IgG seroprevalence was also low across all three sites, ranging from 1.4–3.2%. The single RT-PCR positive sample from this study and 24 archived samples collected during other recent outbreaks throughout Indonesia were subjected to complete coding region sequencing to assess the genetic diversity of Indonesian strains. Phylogenetic analysis revealed all to be of a single clade, which was distinct from CHIKV strains recently reported from neighbouring regions including the Philippines and the Pacific Islands. Conclusions/Significance: Chikungunya virus strains from recent outbreaks across Indonesia all belong to a single clade. However, low-level seroprevalence and molecular detection of CHIKV across the three study sites appears to contrast with the generally high seroprevalences that have been reported for non-outbreak settings in Java and Bali, and may account for the relative lack of CHIKV epidemiological data from other regions of Indonesia

An investig-ation into the epidemiology of chikungunya virus across neglected regions of Indonesia

Funder: US-CDCBackground: Chikungunya virus (CHIKV) is an important emerging and re-emerging public health problem worldwide. In Indonesia, where the virus is endemic, epidemiological information from outside of the main islands of Java and Bali is limited. Methodology/Principal Findings: Four hundred and seventy nine acutely febrile patients presenting between September 2017–2019 were recruited from three city hospitals situated in Ambon, Maluku; Banjarmasin, Kalimantan; and Batam, Batam Island as part of a multi-site observational study. CHIKV RNA was detected in a single serum sample while a separate sample was IgM positive. IgG seroprevalence was also low across all three sites, ranging from 1.4–3.2%. The single RT-PCR positive sample from this study and 24 archived samples collected during other recent outbreaks throughout Indonesia were subjected to complete coding region sequencing to assess the genetic diversity of Indonesian strains. Phylogenetic analysis revealed all to be of a single clade, which was distinct from CHIKV strains recently reported from neighbouring regions including the Philippines and the Pacific Islands. Conclusions/Significance: Chikungunya virus strains from recent outbreaks across Indonesia all belong to a single clade. However, low-level seroprevalence and molecular detection of CHIKV across the three study sites appears to contrast with the generally high seroprevalences that have been reported for non-outbreak settings in Java and Bali, and may account for the relative lack of CHIKV epidemiological data from other regions of Indonesia

Assessment of a multiplex PCR and Nanopore-based method for dengue virus sequencing in Indonesia

Abstract: Background: Dengue virus (DENV) infects hundreds of thousands of people annually in Indonesia. However, DENV sequence data from the country are limited, as samples from outbreaks must be shipped across long-distances to suitably equipped laboratories to be sequenced. This approach is time-consuming, expensive, and frequently results in failure due to low viral load or degradation of the RNA genome. Methods: We evaluated a method designed to address this challenge, using the ‘Primal Scheme’ multiplex PCR tiling approach to rapidly generate short, overlapping amplicons covering the complete DENV coding-region, and sequencing the amplicons on the portable Nanopore MinION device. The resulting sequence data was assessed in terms of genome coverage, consensus sequence accuracy and by phylogenetic analysis. Results: The multiplex approach proved capable of producing near complete coding-region coverage from all samples tested (x¯ = 99.96%, n = 18), 61% of which could not be fully amplified using the current, long-amplicon PCR, approach. Nanopore-generated consensus sequences were found to be between 99.17–99.92% identical to those produced by high-coverage Illumina sequencing. Consensus accuracy could be improved by masking regions below 20X coverage depth (99.69–99.92%). However, coding-region coverage was reduced at this depth (x¯ = 93.48%). Nanopore and Illumina consensus sequences generated from the same samples formed monophyletic clades on phylogenetic analysis, and Indonesian consensus sequences accurately clustered by geographical origin. Conclusion: The multiplex, short-amplicon approach proved superior for amplifying DENV genomes from clinical samples, particularly when the virus was present at low concentrations. The accuracy of Nanopore-generated consensus sequences from these amplicons was sufficient for identifying the geographic origin of the samples, demonstrating that the approach can be a useful tool for identifying and monitoring DENV clades circulating in low-resource settings across Indonesia. However, the inaccuracies in Nanopore-generated consensus sequences mean that the approach may not be appropriate for higher resolution transmission studies, particularly when more accurate sequencing technologies are available

Distinct Dengue Disease Epidemiology, Clinical, and Diagnosis Features in Western, Central, and Eastern Regions of Indonesia, 2017–2019

The people of Indonesia have been afflicted by dengue, a mosquito-borne viral disease, for over 5 decades. The country is the world's largest archipelago with diverse geographic, climatic, and demographic conditions that may impact the dynamics of disease transmissions. A dengue epidemiology study was launched by us to compare and understand the dynamics of dengue and other arboviral diseases in three cities representing western, central, and eastern Indonesia, namely, Batam, Banjarmasin, and Ambon, respectively. A total of 732 febrile patients were recruited with dengue-like illness during September 2017–2019 and an analysis of their demographic, clinical, and virological features was performed. The seasonal patterns of dengue-like illness were found to be different in the three regions. Among all patients, 271 (37.0%) were virologically confirmed dengue, while 152 (20.8%) patients were diagnosed with probable dengue, giving a total number of 423 (57.8%) dengue patients. Patients' age and clinical manifestations also differed between cities. Mostly, mild dengue fever was observed in Batam, while more severe cases were prominent in Ambon. While all dengue virus (DENV) serotypes were detected, distinct serotypes dominated in different locations: DENV-1 in Batam and Ambon, and DENV-3 in Banjarmasin. We also assessed the diagnostic features in the study sites, which revealed different patterns of diagnostic agreements, particularly in Ambon. To detect the possibility of infection with other arboviruses, further testing on 461 DENV RT-PCR-negative samples was performed using pan-flavivirus and -alphavirus RT-PCRs; however, only one chikungunya infection was detected in Ambon. A diverse dengue epidemiology in western, central, and eastern Indonesia was observed, which is likely to be influenced by local geographic, climatic, and demographic conditions, as well as differences in the quality of healthcare providers and facilities. Our study adds a new understanding on dengue epidemiology in Indonesia

Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.This research has been supported by the Integrated Research Program for Advancing Climate Models (TOUGOU) of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (grant nos. JPMXD0717935457 and JPMXD0717935561), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (grant no. 274762653), the Helmholtz Climate Initiative REKLIM (Regional Climate Change) and European Union's Horizon 2020 Research & Innovation program (grant nos. 727862 and 800154), the Research Council of Norway (EVA (grant no. 229771) and INES (grant no. 270061)), the US National Science Foundation (NSF) (grant no. 1852977), the National Natural Science Foundation of China (grant nos. 41931183 and 41976026), NOAA's Science Collaboration Program and administered by UCAR's Cooperative Programs for the Advancement of Earth System Science (CPAESS) (grant nos. NA16NWS4620043 and NA18NWS4620043B), and NOAA (grant no. NA18OAR4320123).Peer ReviewedPostprint (published version

Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

We present a new framework for global ocean- sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean-sea-ice models (JRA55-do).We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean-ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean-sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80% of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP- 2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP- 2. For example, the sea surface temperatures of the OMIP- 2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating processlevel responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean-sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework

Distinct Dengue Disease Epidemiology, Clinical, and Diagnosis Features in Western, Central, and Eastern Regions of Indonesia, 2017–2019

The people of Indonesia have been afflicted by dengue, a mosquito-borne viral disease, for over 5 decades. The country is the world's largest archipelago with diverse geographic, climatic, and demographic conditions that may impact the dynamics of disease transmissions. A dengue epidemiology study was launched by us to compare and understand the dynamics of dengue and other arboviral diseases in three cities representing western, central, and eastern Indonesia, namely, Batam, Banjarmasin, and Ambon, respectively. A total of 732 febrile patients were recruited with dengue-like illness during September 2017–2019 and an analysis of their demographic, clinical, and virological features was performed. The seasonal patterns of dengue-like illness were found to be different in the three regions. Among all patients, 271 (37.0%) were virologically confirmed dengue, while 152 (20.8%) patients were diagnosed with probable dengue, giving a total number of 423 (57.8%) dengue patients. Patients' age and clinical manifestations also differed between cities. Mostly, mild dengue fever was observed in Batam, while more severe cases were prominent in Ambon. While all dengue virus (DENV) serotypes were detected, distinct serotypes dominated in different locations: DENV-1 in Batam and Ambon, and DENV-3 in Banjarmasin. We also assessed the diagnostic features in the study sites, which revealed different patterns of diagnostic agreements, particularly in Ambon. To detect the possibility of infection with other arboviruses, further testing on 461 DENV RT-PCR-negative samples was performed using pan-flavivirus and -alphavirus RT-PCRs; however, only one chikungunya infection was detected in Ambon. A diverse dengue epidemiology in western, central, and eastern Indonesia was observed, which is likely to be influenced by local geographic, climatic, and demographic conditions, as well as differences in the quality of healthcare providers and facilities. Our study adds a new understanding on dengue epidemiology in Indonesia

Genome-Wide Association Study of Susceptibility to Idiopathic Pulmonary Fibrosis

Rationale: Idiopathic pulmonary fibrosis (IPF) is a complex lung disease characterised by scarring of the lung that is believed to result from an atypical response to injury of the epithelium. Genome-wide association studies have reported signals of association implicating multiple pathways including host defence, telomere maintenance, signalling and cell-cell adhesion. Objectives: To improve our understanding of factors that increase IPF susceptibility by identifying previously unreported genetic associations. Methods and measurements: We conducted genome-wide analyses across three independent studies and meta-analysed these results to generate the largest genome-wide association study of IPF to date (2,668 IPF cases and 8,591 controls). We performed replication in two independent studies (1,456 IPF cases and 11,874 controls) and functional analyses (including statistical fine-mapping, investigations into gene expression and testing for enrichment of IPF susceptibility signals in regulatory regions) to determine putatively causal genes. Polygenic risk scores were used to assess the collective effect of variants not reported as associated with IPF. Main results: We identified and replicated three new genome-wide significant (P<5×10−8) signals of association with IPF susceptibility (associated with altered gene expression of KIF15, MAD1L1 and DEPTOR) and confirmed associations at 11 previously reported loci. Polygenic risk score analyses showed that the combined effect of many thousands of as-yet unreported IPF susceptibility variants contribute to IPF susceptibility. Conclusions: The observation that decreased DEPTOR expression associates with increased susceptibility to IPF, supports recent studies demonstrating the importance of mTOR signalling in lung fibrosis. New signals of association implicating KIF15 and MAD1L1 suggest a possible role of mitotic spindle-assembly genes in IPF susceptibility