2,061 research outputs found
ChIP-Seq and In Vivo Transcriptome Analyses of the Aspergillus fumigatus SREBP SrbA Reveals a New Regulator of the Fungal Hypoxia Response and Virulence
The Aspergillus fumigatus sterol regulatory element binding protein (SREBP) SrbA belongs to the basic Helix-Loop-Helix (bHLH) family of transcription factors and is crucial for antifungal drug resistance and virulence. The latter phenotype is especially striking, as loss of SrbA results in complete loss of virulence in murine models of invasive pulmonary aspergillosis (IPA). How fungal SREBPs mediate fungal virulence is unknown, though it has been suggested that lack of growth in hypoxic conditions accounts for the attenuated virulence. To further understand the role of SrbA in fungal infection site pathobiology, chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) was used to identify genes under direct SrbA transcriptional regulation in hypoxia. These results confirmed the direct regulation of ergosterol biosynthesis and iron uptake by SrbA in hypoxia and revealed new roles for SrbA in nitrate assimilation and heme biosynthesis. Moreover, functional characterization of an SrbA target gene with sequence similarity to SrbA identified a new transcriptional regulator of the fungal hypoxia response and virulence, SrbB. SrbB co-regulates genes involved in heme biosynthesis and demethylation of C4-sterols with SrbA in hypoxic conditions. However, SrbB also has regulatory functions independent of SrbA including regulation of carbohydrate metabolism. Loss of SrbB markedly attenuates A. fumigatus virulence, and loss of both SREBPs further reduces in vivo fungal growth. These data suggest that both A. fumigatus SREBPs are critical for hypoxia adaptation and virulence and reveal new insights into SREBPs\u27 complex role in infection site adaptation and fungal virulence
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Covalent targeting of the vacuolar H+-ATPase activates autophagy via mTORC1 inhibition.
Autophagy is a lysosomal degradation pathway that eliminates aggregated proteins and damaged organelles to maintain cellular homeostasis. A major route for activating autophagy involves inhibition of the mTORC1 kinase, but current mTORC1-targeting compounds do not allow complete and selective mTORC1 blockade. Here, we have coupled screening of a covalent ligand library with activity-based protein profiling to discover EN6, a small-molecule in vivo activator of autophagy that covalently targets cysteine 277 in the ATP6V1A subunit of the lysosomal v-ATPase, which activates mTORC1 via the Rag guanosine triphosphatases. EN6-mediated ATP6V1A modification decouples the v-ATPase from the Rags, leading to inhibition of mTORC1 signaling, increased lysosomal acidification and activation of autophagy. Consistently, EN6 clears TDP-43 aggregates, a causative agent in frontotemporal dementia, in a lysosome-dependent manner. Our results provide insight into how the v-ATPase regulates mTORC1, and reveal a unique approach for enhancing cellular clearance based on covalent inhibition of lysosomal mTORC1 signaling
Analysis of margin classification systems for assessing the risk of local recurrence after soft tissue sarcoma resection
Purpose:
To compare the ability of margin classification systems to determine local recurrence (LR) risk after soft tissue sarcoma (STS) resection.
Methods:
Two thousand two hundred seventeen patients with nonmetastatic extremity and truncal STS treated with surgical resection and multidisciplinary consideration of perioperative radiotherapy were retrospectively reviewed. Margins were coded by residual tumor (R) classification (in which microscopic tumor at inked margin defines R1), the R+1mm classification (in which microscopic tumor within 1 mm of ink defines R1), and the Toronto Margin Context Classification (TMCC; in which positive margins are separated into planned close but positive at critical structures, positive after whoops re-excision, and inadvertent positive margins). Multivariate competing risk regression models were created.
Results:
By R classification, LR rates at 10-year follow-up were 8%, 21%, and 44% in R0, R1, and R2, respectively. R+1mm classification resulted in increased R1 margins (726 v 278, P < .001), but led to decreased LR for R1 margins without changing R0 LR; for R0, the 10-year LR rate was 8% (range, 7% to 10%); for R1, the 10-year LR rate was 12% (10% to 15%) . The TMCC also showed various LR rates among its tiers (P < .001). LR rates for positive margins on critical structures were not different from R0 at 10 years (11% v 8%, P = .18), whereas inadvertent positive margins had high LR (5-year, 28% [95% CI, 19% to 37%]; 10-year, 35% [95% CI, 25% to 46%]; P < .001).
Conclusion:
The R classification identified three distinct risk levels for LR in STS. An R+1mm classification reduced LR differences between R1 and R0, suggesting that a negative but < 1-mm margin may be adequate with multidisciplinary treatment. The TMCC provides additional stratification of positive margins that may aid in surgical planning and patient education
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Digital Orthopaedics: A Glimpse Into the Future in the Midst of a Pandemic.
BackgroundThe response to COVID-19 catalyzed the adoption and integration of digital health tools into the health care delivery model for musculoskeletal patients. The change, suspension, or relaxation of Medicare and federal guidelines enabled the rapid implementation of these technologies. The expansion of payment models for virtual care facilitated its rapid adoption. The authors aim to provide several examples of digital health solutions utilized to manage orthopedic patients during the pandemic and discuss what features of these technologies are likely to continue to provide value to patients and clinicians following its resolution.ConclusionThe widespread adoption of new technologies enabling providers to care for patients remotely has the potential to permanently change the expectations of all stakeholders about the way care is provided in orthopedics. The new era of Digital Orthopaedics will see a gradual and nondisruptive integration of technologies that support the patient's journey through the successful management of their musculoskeletal disease
The transcriptome landscape of 3D-cultured placental trophoblasts reveals activation of TLR2 and TLR3/7 in response to low Trypanosoma cruzi parasite exposure
Vertical transmission of Trypanosoma cruzi (T. cruzi) become a globalized health problem accounting for 22% of new cases of Chagas disease (CD). Congenital infection is now considered the main route of CD spread in non-endemic countries where no routine disease testing of pregnant women is implemented. The main mechanisms that lead to fetal infection by T. cruzi remain poorly understood. Mother-to-child transmission may occur when bloodstream trypomastigotes interact with the syncytiotrophoblasts (SYNs) that cover the placenta chorionic villi. These highly specialized cells function as a physical barrier and modulate immune responses against pathogen infections. To model the human placenta environment, we have previously used a three-dimensional (3D) cell culture system of SYNs that exhibits differentiation characteristics comparable to placental trophoblasts. Further, we have shown that 3D-grown SYNs are highly resistant to T. cruzi infection. In this work, we used RNA sequencing and whole transcriptome analysis to explore the immunological signatures that drive SYNs’ infection control. We found that the largest category of differentially expressed genes (DEGs) are associated with inflammation and innate immunity functions. Quantitative RT-PCR evaluation of selected DEGs, together with detection of cytokines and chemokines in SYNs culture supernatants, confirmed the transcriptome data. Several genes implicated in the Toll-like receptors signaling pathways were upregulated in 3D-grown SYNs. In fact, TLR2 blockade and TLR3/7 knockdown stimulated T. cruzi growth, suggesting that these molecules play a significant role in the host cell response to infection. Ingenuity Pathway Analysis of DEGs predicted the activation of canonical pathways such as S100 protein family, pathogen induced cytokine storm, wound healing, HIF1α signaling and phagosome formation after T. cruzi exposure. Our findings indicate that SYNs resist infection by eliciting a constitutive pro-inflammatory response and modulating multiple defense mechanisms that interfere with the parasite’s intracellular life cycle, contributing to parasite killing and infection control
Effects of Ellipticity and Shear on Gravitational Lens Statistics
We study the effects of ellipticity in lens galaxies and external tidal shear
from neighboring objects on the statistics of strong gravitational lenses. For
isothermal lens galaxies normalized so that the Einstein radius is independent
of ellipticity and shear, ellipticity {\it reduces} the lensing cross section
slightly, and shear leaves it unchanged. Ellipticity and shear can
significantly enhance the magnification bias, but only if the luminosity
function of background sources is steep. Realistic distributions of ellipticity
and shear {\it lower} the total optical depth by a few percent for most source
luminosity functions, and increase the optical depth only for steep luminosity
functions. The boost in the optical depth is noticeable (>5%) only for surveys
limited to the brightest quasars (L/L_* > 10). Ellipticity and shear broaden
the distribution of lens image separations but do not affect the mean.
Ellipticity and shear naturally increase the abundance of quadruple lenses
relative to double lenses, especially for steep source luminosity functions,
but the effect is not enough (by itself) to explain the observed
quadruple-to-double ratio. With such small changes to the optical depth and
image separation distribution, ellipticity and shear have a small effect on
cosmological constraints from lens statistics: neglecting the two leads to
biases of just Delta Omega_M = 0.00 \pm 0.01 and Delta Omega_Lambda = -0.02 \pm
0.01 (where the errorbars represent statistical uncertainties in our
calculations).Comment: Optical depth normalization discussed. Matches the published versio
Improved Imputation of Common and Uncommon Single Nucleotide Polymorphisms (SNPs) with a New Reference Set
Statistical imputation of genotype data is an important technique for analysis of genome-wide association studies (GWAS). We have built a reference dataset to improve imputation accuracy for studies of individuals of primarily European descent using genotype data from the Hap1, Omni1, and Omni2.5 human SNP arrays (Illumina). Our dataset contains 2.5-3.1 million variants for 930 European, 157 Asian, and 162 African/African-American individuals. Imputation accuracy of European data from Hap660 or OmniExpress array content, measured by the proportion of variants imputed with R^2^>0.8, improved by 34%, 23% and 12% for variants with MAF of 3%, 5% and 10%, respectively, compared to imputation using publicly available data from 1,000 Genomes and International HapMap projects. The improved accuracy with the use of the new dataset could increase the power for GWAS by as much as 8% relative to genotyping all variants. This reference dataset is available to the scientific community through the NCBI dbGaP portal. Future versions will include additional genotype data as well as non-European populations
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