This study identifies mechanisms mediating responses to immune checkpoint inhibitors using mouse models of triple-negative breast cancer. By creating new mammary tumor models, we find that tumor mutation burden and specific immune cells are associated with response. Further, we developed a rich resource of single-cell RNA-seq and bulk mRNA-seq data of immunotherapy-treated and non-treated tumors from sensitive and resistant murine models. Using this, we uncover that immune checkpoint therapy induces T follicular helper cell activation of B cells to facilitate the anti-tumor response in these models. We also show that B cell activation of T cells and the generation of antibody are key to immunotherapy response and propose a new biomarker for immune checkpoint therapy. In total, this work presents resources of new preclinical models of breast cancer with large mRNA-seq and single-cell RNA-seq datasets annotated for sensitivity to therapy and uncovers new components of response to immune checkpoint inhibitors.

The use of conductive polymer composites (CPCs) as strain sensors has been widely investigated and various resistivity-strain sensitivities are desirable for different applications. In this study, the use of mixed carbon fillers and functionalized carbon nanotubes was demonstrated to be vital for preparing thermoplastic polyurethane (TPU)-based strain sensors with tunable sensitivity. To understand the strain sensing behavior, we carried out scanning electron microscopy (SEM), Raman spectroscopy, wide-angle X-ray diffraction (WAXD), mechanical test, and rheology-electrical measurement. Hybrid fillers of multi-walled carbon nanotubes (MWNTs) and carbon black (CB) could reduce the entanglement in conductive network structure, thus increase the resistivity-strain sensitivity. Furthermore, incorporation of additional functionalized MWNTs in the CPCs could enhance the interfacial interaction between nanofillers and TPU, leading to further increase in sensitivity. Through such a simple method, strain sensors could be efficiently fabricated with large strain-sensing capability (strain as large as 200%) and a wide range of strain sensitivity (gauge factor ranging from 5 to 140238). Finally, the exponential revolution of resistive response to strain was fitted with a model based on tunneling theory by Simmons. It was observed that the change in tunneling distance and the number of conductive pathways could be accelerated significantly by adjusting conductive network structure and interfacial interaction. This study provides a guideline for the preparation of high-performance CPC strain sensors with a large range of resistivity-strain sensitivity.

Miscanthus is a perennial wild grass that is of global importance for paper production, roofing, horticultural plantings, and an emerging highly productive temperate biomass crop. We report a chromosome-scale assembly of the paleotetraploid M. sinensis genome, providing a resource for Miscanthus that links its chromosomes to the related diploid Sorghum and complex polyploid sugarcanes. The asymmetric distribution of transposons across the two homoeologous subgenomes proves Miscanthus paleo-allotetraploidy and identifies several balanced reciprocal homoeologous exchanges. Analysis of M. sinensis and M. sacchariflorus populations demonstrates extensive interspecific admixture and hybridization, and documents the origin of the highly productive triploid bioenergy crop M. × giganteus. Transcriptional profiling of leaves, stem, and rhizomes over growing seasons provides insight into rhizome development and nutrient recycling, processes critical for sustainable biomass accumulation in a perennial temperate grass. The Miscanthus genome expands the power of comparative genomics to understand traits of importance to Andropogoneae grasses.

Stretchable conductors, which can keep their excellent electrical conductivity while highly stretched, have been investigated extensively due to their wide range of applications in flexible and stretchable electronics, wearable displays, etc.; however, their preparation is often complicated and expensive. Herein, an efficient method to prepare high performance stretchable conductors through morphological control of conductive networks formed with carbon nanotubes (CNTs) in an elastomer matrix is reported. It is observed that an interface-mediated method could be used to align randomly oriented filler during stretching and to induce buckling of CNTs during relaxation. Further morphological studies indicate the possible formation of a wavy CNT structure induced by cyclic pre-straining. Subsequent thermal annealing is observed to collapse the oriented network and improve the local contacts between conductive networks. Through such a simple procedure, a conductivity of nearly 1000 S m(-1) and a stretchability of 200% can be achieved for composites containing 20 wt% CNTs. CNTs are observed to buckle over a large area in polymer bulk, and the combination of pre-straining and thermal annealing modifies the conductive network in the elastomer matrix. As a general method, this could be used for easy fabrication of high-performance stretchable conductors for arbitrary-shaped objects on a large scale.

Improving biomass yield is a major goal of Miscanthus breeding. We conducted a study on one interspecific Miscanthus sinensis 9 Miscanthus sacchariflorus F 1 population and two intraspecific M. sinensis F 1 populations, each of which shared a common parent. A field trial was established at Urbana, IL during spring 2011, and phenotypic data were collected in 2012 and 2013 for fourteen yield traits. Six high-density parental genetic maps, as well as a consensus genetic map integrating M. sinensis and M. sacchariflorus, were developed via the pseudotestcross strategy for noninbred parents with ≥1214 single-nucleotide polymorphism markers generated from restriction site-associated DNA sequencing. We confirmed for the first time a whole-genome duplication in M. sacchariflorus relative to Sorghum bicolor, similar to that observed previously for M. sinensis. Four quantitative trait locus (QTL) analysis methods for detecting marker-trait associations were compared: (1) individual parental map composite interval mapping analysis, (2) individual parental map stepwise analysis, (3) consensus map single-population stepwise analysis and (4) consensus map joint-population stepwise analysis. These four methods detected 288, 264, 133 and 109 total QTLs, which resolved into 157, 136, 106 and 86 meta-QTLs based on QTL congruency, respectively, including a set of 59 meta-QTLs common to all four analysis methods. Composite interval mapping and stepwise analysis co-identified 118 meta-QTLs across six parental maps, suggesting high reliability of stepwise regression in QTL detection. Joint-population stepwise analysis yielded the highest resolution of QTLs compared to the other three methods across all meta-QTLs. Strong, frequently advantageous transgressive segregation in the three populations indicated a promising future for breeding new higher-yielding cultivars of Miscanthus.

Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), COVID-19 is a virus-induced inflammatory disease of the airways and lungs that leads to severe multi-organ damage and death. Here we show that cellular lipid synthesis is required for SARS-CoV-2 replication and offers an opportunity for pharmacological intervention. Screening a short-hairpin RNA sublibrary that targets metabolic genes, we identified genes that either inhibit or promote SARS-CoV-2 viral infection, including two key candidate genes, ACACA and FASN , which operate in the same lipid synthesis pathway. We further screened and identified several potent inhibitors of fatty acid synthase (encoded by FASN ), including the US Food and Drug Administration-approved anti-obesity drug orlistat, and found that it inhibits in vitro replication of SARS-CoV-2 variants, including more contagious new variants, such as Delta. In a mouse model of SARS-CoV-2 infection (K18-hACE2 transgenic mice), injections of orlistat resulted in lower SARS-CoV-2 viral levels in the lung, reduced lung pathology and increased mouse survival. Our findings identify fatty acid synthase inhibitors as drug candidates for the prevention and treatment of COVID-19 by inhibiting SARS-CoV-2 replication. Clinical trials are needed to evaluate the efficacy of repurposing fatty acid synthase inhibitors for severe COVID-19 in humans.

Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine particulate matter (PM2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM2.5 increased by 0.17 K, 0.04, and 1.02 μg/m3 in the period of 2001–2016, respectively. During the past 16 years, LST showed an increasing trend in most areas, with two peaks of 1.58 K and 1.85 K at 72°N and 48°S, respectively. Marked warming also appeared in the Arctic. On the contrary, remarkable decrease in LST occurred in Antarctic. In most parts of the world, LST was affected by the variation in vegetation cover and air pollutant, which can be detected by the satellite. In the Northern Hemisphere, positive relations between SINDVI and LST were found; however, in the Southern Hemisphere, negative correlations were detected. The impact of PM2.5 on LST was more complex. On the whole, LST increased with a small increase in PM2.5 concentrations but decreased with a marked increase in PM2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature.

Sample preparation is a crucial step for the reliable and accurate analysis of both small molecule and biopolymers which often involves processes such as isolation, pre‐concentration, removal of interferences (purification), and pre‐processing (e.g., enzymatic digestion) of targets from a complex matrix. Gold nanoparticle (GNP)‐assisted sample preparation and pre‐concentration has been extensively applied in many analytical procedures in recent years due to the favorable and unique properties of GNPs such as size‐controlled synthesis, large surface‐to‐volume ratio, surface inertness, straightforward surface modification, easy separation requiring minimal manipulation of samples. This review article primarily focuses on applications of GNPs in sample preparation, in particular for bioaffinity capture and biocatalysis. In addition, their most common synthesis, surface modification and characterization methods are briefly summarized. Proper surface modification for GNPs designed in accordance to their target application directly influence their functionalities, e.g., extraction efficiencies, and catalytic efficiencies. Characterization of GNPs after synthesis and modification is worthwhile for monitoring and controlling the fabrication process to ensure proper quality and functionality. Parameters such as morphology, colloidal stability, and physical/chemical properties can be assessed by methods such as surface plasmon resonance, dynamic light scattering, ζ‐potential determinations, transmission electron microscopy, Taylor dispersion analysis, and resonant mass measurement, among others. The accurate determination of the surface coverage appears to be also mandatory for the quality control of functionality of the nanoparticles. Some promising applications of (functionalized) GNPs for bioanalysis and sample preparation are described herein.