HSD3B1 genotype identifies glucocorticoid responsiveness in severe asthma

Asthma resistance to glucocorticoid treatment is a major health problem with unclear etiology. Glucocorticoids inhibit adrenal androgen production. However, androgens have potential benefits in asthma. HSD3B1 encodes for 3β-hydroxysteroid dehydrogenase-1 (3β-HSD1), which catalyzes peripheral conversion from adrenal dehydroepiandrosterone (DHEA) to potent androgens and has a germline missense-encoding polymorphism. The adrenal restrictive HSD3B1(1245A) allele limits conversion, whereas the adrenal permissive HSD3B1(1245C) allele increases DHEA metabolism to potent androgens. In the Severe Asthma Research Program (SARP) III cohort, we determined the association between DHEA-sulfate and percentage predicted forced expiratory volume in 1 s (FEV1PP). HSD3B1(1245) genotypes were assessed, and association between adrenal restrictive and adrenal permissive alleles and FEV1PP in patients with (GC) and without (noGC) daily oral glucocorticoid treatment was determined (n = 318). Validation was performed in a second cohort (SARP I&II; n = 184). DHEA-sulfate is associated with FEV1PP and is suppressed with GC treatment. GC patients homozygous for the adrenal restrictive genotype have lower FEV1PP compared with noGC patients (54.3% vs. 75.1%; P < 0.001). In patients with the homozygous adrenal permissive genotype, there was no FEV1PP difference in GC vs. noGC patients (73.4% vs. 78.9%; P = 0.39). Results were independently confirmed: FEV1PP for homozygous adrenal restrictive genotype in GC vs. noGC is 49.8 vs. 63.4 (P < 0.001), and for homozygous adrenal permissive genotype, it is 66.7 vs. 67.7 (P = 0.92). The adrenal restrictive HSD3B1(1245) genotype is associated with GC resistance. This effect appears to be driven by GC suppression of 3β-HSD1 substrate. Our results suggest opportunities for prediction of GC resistance and pharmacologic intervention

Climate warming accelerates temporal scaling of grassland soil microbial biodiversity.

Determining the temporal scaling of biodiversity, typically described as species-time relationships (STRs), in the face of global climate change is a central issue in ecology because it is fundamental to biodiversity preservation and ecosystem management. However, whether and how climate change affects microbial STRs remains unclear, mainly due to the scarcity of long-term experimental data. Here, we examine the STRs and phylogenetic-time relationships (PTRs) of soil bacteria and fungi in a long-term multifactorial global change experiment with warming (+3 °C), half precipitation (-50%), double precipitation (+100%) and clipping (annual plant biomass removal). Soil bacteria and fungi all exhibited strong STRs and PTRs across the 12 experimental conditions. Strikingly, warming accelerated the bacterial and fungal STR and PTR exponents (that is, the w values), yielding significantly (P &lt; 0.001) higher temporal scaling rates. While the STRs and PTRs were significantly shifted by altered precipitation, clipping and their combinations, warming played the predominant role. In addition, comparison with the previous literature revealed that soil bacteria and fungi had considerably higher overall temporal scaling rates (w = 0.39-0.64) than those of plants and animals (w = 0.21-0.38). Our results on warming-enhanced temporal scaling of microbial biodiversity suggest that the strategies of soil biodiversity preservation and ecosystem management may need to be adjusted in a warmer world

Radiogenomics-Based Risk Prediction of Glioblastoma Multiforme with Clinical Relevance

Glioblastoma multiforme (GBM)is the most common and aggressive primary brain tumor. Although temozolomide (TMZ)-based radiochemotherapy improves overall GBM patients\u27 survival, it also increases the frequency of false positive post-treatment magnetic resonance imaging (MRI) assessments for tumor progression. Pseudo-progression (PsP) is a treatment-related reaction with an increased contrast-enhancing lesion size at the tumor site or resection margins miming tumor recurrence on MRI. The accurate and reliable prognostication of GBM progression is urgently needed in the clinical management of GBM patients. Clinical data analysis indicates that the patients with PsP had superior overall and progression-free survival rates. In this study, we aimed to develop a prognostic model to evaluate the tumor progression potential of GBM patients following standard therapies. We applied a dictionary learning scheme to obtain imaging features of GBM patients with PsP or true tumor progression (TTP) from the Wake dataset. Based on these radiographic features, we conducted a radiogenomics analysis to identify the significantly associated genes. These significantly associated genes were used as features to construct a 2YS (2-year survival rate) logistic regression model. GBM patients were classified into low- and high-survival risk groups based on the individual 2YS scores derived from this model. We tested our model using an independent The Cancer Genome Atlas Program (TCGA) dataset and found that 2YS scores were significantly associated with the patient\u27s overall survival. We used two cohorts of the TCGA data to train and test our model. Our results show that the 2YS scores-based classification results from the training and testing TCGA datasets were significantly associated with the overall survival of patients. We also analyzed the survival prediction ability of other clinical factors (gender, age, KPS (Karnofsky performance status), normal cell ratio) and found that these factors were unrelated or weakly correlated with patients\u27 survival. Overall, our studies have demonstrated the effectiveness and robustness of the 2YS model in predicting the clinical outcomes of GBM patients after standard therapies

Preferential binding to elk-1 by sle-associated il10 risk allele upregulates il10 expression

Immunoregulatory cytokine interleukin-10 (IL-10) is elevated in sera from patients with systemic lupus erythematosus (SLE) correlating with disease activity. The established association of IL10 with SLE and other autoimmune diseases led us to fine map causal variant(s) and to explore underlying mechanisms. We assessed 19 tag SNPs, covering the IL10 gene cluster including IL19, IL20 and IL24, for association with SLE in 15,533 case and control subjects from four ancestries. The previously reported IL10 variant, rs3024505 located at 1 kb downstream of IL10, exhibited the strongest association signal and was confirmed for association with SLE in European American (EA) (P = 2.7×10−8, OR = 1.30), but not in non-EA ancestries. SNP imputation conducted in EA dataset identified three additional SLE-associated SNPs tagged by rs3024505 (rs3122605, rs3024493 and rs3024495 located at 9.2 kb upstream, intron 3 and 4 of IL10, respectively), and SLE-risk alleles of these SNPs were dose-dependently associated with elevated levels of IL10 mRNA in PBMCs and circulating IL-10 protein in SLE patients and controls. Using nuclear extracts of peripheral blood cells from SLE patients for electrophoretic mobility shift assays, we identified specific binding of transcription factor Elk-1 to oligodeoxynucleotides containing the risk (G) allele of rs3122605, suggesting rs3122605 as the most likely causal variant regulating IL10 expression. Elk-1 is known to be activated by phosphorylation and nuclear localization to induce transcription. Of interest, phosphorylated Elk-1 (p-Elk-1) detected only in nuclear extracts of SLE PBMCs appeared to increase with disease activity. Co-expression levels of p-Elk-1 and IL-10 were elevated in SLE T, B cells and monocytes, associated with increased disease activity in SLE B cells, and were best downregulated by ERK inhibitor. Taken together, our data suggest that preferential binding of activated Elk-1 to the IL10 rs3122605-G allele upregulates IL10 expression and confers increased risk for SLE in European Americans

Comparative transcriptome analyses indicate molecular homology of zebrafish swimbladder and mammalian lung

10.1371/journal.pone.0024019PLoS ONE68

Predictive approaches for 3D ‐printing : Methods and approaches for polymeric materials

By bridging molecular‐level insights with macroscopic performance metrics, computational strategies are poised to transform how we design next‐generation 3D‐printable materials with enhanced precision, functionality, and sustainability. We present a critical overview examining the role of computational methods in advancing the design and application of 3D‐printable polymers. We cover key considerations—including solvation behavior, viscosity, gel point, mechanical properties, and polymer structure—as well as the design of new polymer functionalities. We highlight how a spectrum of physics‐based methods, ranging from quantum chemical to coarse‐grained simulations, can be leveraged to interrogate relevant polymer properties at multiple scales. In particular, we illustrate the growing impact of machine learning in accelerating polymer discovery and optimization. Such methods, whether applied independently or integrated into multi‐scale modeling frameworks, offer powerful tools for pre‐screening and selecting optimal formulations tailored to diverse 3D printing technologies and applications. Although challenges remain to integrate different approaches into workable prediction pipelines, the rate of advance and improvements in methods, data interoperability, and data quality, offer great promise of a ‘concept to print’ pipeline in the future. This article is categorized under: Structure and Mechanism > Computational Materials Science Data Science > Artificial Intelligence/Machine Learning Structure and Mechanism > Molecular Structure

Inter-diffusion of Plasmonic Metals and Phase Change Materials

This work investigates the problematic diffusion of metal atoms into phase change chalcogenides, which can destroy resonances in photonic devices. Interfaces between Ge2Sb2Te5 and metal layers were studied using X-ray reflectivity (XRR) and reflectometry of metal-Ge2Sb2Te5 layered stacks. The diffusion of metal atoms influences the crystallisation temperature and optical properties of phase change materials. When Au, Ag, Al, W structures are directly deposited on Ge2Sb2Te5 inter-diffusion occurs. Indeed, Au forms AuTe2 layers at the interface. Diffusion barrier layers, such as Si3N4 or stable diffusionless plasmonic materials, such as TiN, can prevent the interfacial damage. This work shows that the interfacial diffusion must be considered when designing phase change material tuned photonic devices, and that TiN is the most suitable plasmonic material to interface directly with Ge2Sb2Te5.Comment: 23 pages, 8 figures, articl

Developing colloidal nanoparticles for inkjet printing of devices with optical properties tuneable from the UV to the NIR

Colloidal low-dimensional photo-sensitive nanomaterials have attracted significant interest for optoelectronic device applications where inkjet printing offers a high accuracy and low waste route for their deposition on silicon-based, as well as flexible, devices. However, to achieve photodetection and displays with absorption and emission tuneable across the range from the ultraviolet (UV) to the near infrared (NIR), the availability of printable optically active materials needs to be addressed. In this work we develop printable ink formulations of graphene quantum dots (GQDs), NaYF4:(20%Yb and/or 2%Er doped) upconverting nanoparticles (UCNPs), and PbS quantum dots (QDs) and demonstrate their use in devices such as graphene-based photodetectors and fluorescent displays. The ink formulations, printing strategies and post-deposition techniques were developed and optimised to enable the deposition of photo-sensitive nanomaterial layers in a controllable manner onto flexible polymeric, glass and silicon substrates. The nanomaterials retained their properties post deposition, as we exemplify by photosensitisation of single layer graphene (SLG) photodetector devices, with spectral responsivity tuneable from the UV for GQD/SLG to the NIR for UCNP/SLG and PbS/SLG devices, with photoresponsivity up to R ∼ 103 A W−1. Fluorescent displays were also demonstrated consisting of CsPbBr3 perovskite nanocrystals and UCNPs inkjet printed onto flexible transparent substrates, for selective sensing of UV and NIR light. This work successfully expands the material library of printable optically active materials and demonstrates their potential for printed optoelectronics, including flexible devices

Synthesis of Monodisperse Nanocrystals via Microreaction: Open-to-Air Synthesis with Oleylamine as a Coligand

Microreaction provides a controllable tool to synthesize CdSe nanocrystals (NCs) in an accelerated fashion. However, the surface traps created during the fast growth usually result in low photoluminescence (PL) efficiency for the formed products. Herein, the reproducible synthesis of highly luminescent CdSe NCs directly in open air was reported, with a microreactor as the controllable reaction tool. Spectra investigation elucidated that applying OLA both in Se and Cd stock solutions could advantageously promote the diffusion between the two precursors, resulting in narrow full-width-at-half maximum (FWHM) of PL (26 nm). Meanwhile, the addition of OLA in the source solution was demonstrated helpful to improve the reactivity of Cd monomer. In this case, the focus of size distribution was accomplished during the early reaction stage. Furthermore, if the volume percentage (vol.%) of OLA in the precursors exceeded a threshold of 37.5%, the resulted CdSe NCs demonstrated long-term fixing of size distribution up to 300 s. The observed phenomena facilitated the preparation of a size series of monodisperse CdSe NCs merely by the variation of residence time. With the volume percentage of OLA as 37.5% in the source solution, a 78 nm tuning of PL spectra (from 507 to 585) was obtained through the variation of residence time from 2 s to 160 s, while maintaining narrow FMWH of PL (26–31 nm) and high QY of PL (35–55%)

Radiation-Induced c-Jun Activation Depends on MEK1-ERK1/2 Signaling Pathway in Microglial Cells

Radiation-induced normal brain injury is associated with acute and/or chronic inflammatory responses, and has been a major concern in radiotherapy. Recent studies suggest that microglial activation is a potential contributor to chronic inflammatory responses following irradiation; however, the molecular mechanism underlying the response of microglia to radiation is poorly understood. c-Jun, a component of AP-1 transcription factors, potentially regulates neural cell death and neuroinflammation. We observed a rapid increase in phosphorylation of N-terminal c-Jun (on serine 63 and 73) and MAPK kinases ERK1/2, but not JNKs, in irradiated murine microglial BV2 cells. Radiation-induced c-Jun phosphorylation is dependent on the canonical MEK-ERK signaling pathway and required for both ERK1 and ERK2 function. ERK1/2 directly interact with c-Jun in vitro and in cells; meanwhile, the JNK binding domain on c-Jun is not required for its interaction with ERK kinases. Radiation-induced reactive oxygen species (ROS) potentially contribute to c-Jun phosphorylation through activating the ERK pathway. Radiation stimulates c-Jun transcriptional activity and upregulates c-Jun-regulated proinflammatory genes, such as tumor necrosis factor-α, interleukin-1β, and cyclooxygenase-2. Pharmacologic blockade of the ERK signaling pathway interferes with c-Jun activity and inhibits radiation-stimulated expression of c-Jun target genes. Overall, our study reveals that the MEK-ERK1/2 signaling pathway, but not the JNK pathway, contributes to the c-Jun-dependent microglial inflammatory response following irradiation