Soil is a major source of nitrogen trace gases (NTGs). Microbial denitrification has long been identified as a source of NTGs under reducing conditions, whereas the production of NTGs during ...nitrification is far from being completely understood. This review updates information about the role of abiotic processes in the formation of gaseous N products in soil and brings attention to the potential interplay of microbial and chemical soil processes that tend to be neglected in research on NTG emissions. Several reactions that involve the nitrification intermediates, nitrite (NO₂ ⁻) and hydroxylamine (NH₂OH), are known to produce the NTGs nitric oxide (NO) and nitrous oxide (N₂O). These abiotic reactions are: the self‐decomposition of NO₂ ⁻, reactions of NO₂ ⁻ with reduced metal cations, nitrosation of soil organic matter (SOM) by NO₂ ⁻, the reaction between NO₂ ⁻ and NH₂OH, and the oxidation of NH₂OH by Fe³⁺ or MnO₂. These reactions can occur over a broad range of soil characteristics, but they are disregarded in most current research on NTG studies in favour of biological processes only. Relatively few studies have tried to quantify the contribution of abiotic processes to total NTG emissions, which results in uncertainty in emission models and mitigation strategies. It is difficult to discriminate between biological and abiotic sources because both processes can proceed at the same time in the same soil layer. The potential of stable isotope techniques to disentangle the different processes in soil and to constrain budgets of atmospheric NTGs better are highlighted. Recent advances in stable isotope technologies, such as infrared real‐time laser spectroscopy, provide considerable potential for both natural abundance and tracer studies in this field.
Those building predictive models from transcriptomic data are faced with two conflicting perspectives. The first, based on the inherent high dimensionality of biological systems, supposes that ...complex non-linear models such as neural networks will better match complex biological systems. The second, imagining that complex systems will still be well predicted by simple dividing lines prefers linear models that are easier to interpret. We compare multi-layer neural networks and logistic regression across multiple prediction tasks on GTEx and Recount3 datasets and find evidence in favor of both possibilities. We verified the presence of non-linear signal when predicting tissue and metadata sex labels from expression data by removing the predictive linear signal with Limma, and showed the removal ablated the performance of linear methods but not non-linear ones. However, we also found that the presence of non-linear signal was not necessarily sufficient for neural networks to outperform logistic regression. Our results demonstrate that while multi-layer neural networks may be useful for making predictions from gene expression data, including a linear baseline model is critical because while biological systems are high-dimensional, effective dividing lines for predictive models may not be.
In patients with operable early breast cancer, neoadjuvant systemic treatment (NST) is a standard approach. Indications have expanded from downstaging of locally advanced breast cancer to facilitate ...breast conservation, to in vivo drug-sensitivity testing. The pattern of response to NST is used to tailor systemic and locoregional treatment, that is, to escalate treatment in nonresponders and de-escalate treatment in responders. Here we discuss four questions that guide our current thinking about ‘response-adjusted’ surgery of the breast after NST. (i) What critical diagnostic outcome measures should be used when analyzing diagnostic tools to identify patients with pathologic complete response (pCR) after NST? (ii) How can we assess response with the least morbidity and best accuracy possible? (iii) What oncological consequences may ensue if we rely on a nonsurgical-generated diagnosis of, for example, minimally invasive biopsy proven pCR, knowing that we may miss minimal residual disease in some cases? (iv) How should we design clinical trials on de-escalation of surgical treatment after NST?
•Safe past de-escalation treatments.•Surgery after complete response might be overtreatment.•Biopsies might diagnose response.
Objective
Systemic sclerosis (SSc) is characterized by immune activation, vasculopathy, and unresolving fibrosis in the skin, lungs, and other organs. We performed RNA‐sequencing analysis on skin ...biopsy samples and peripheral blood mononuclear cells (PBMCs) from SSc patients and unaffected controls to better understand the pathogenesis of SSc.
Methods
We analyzed these data 1) to test for case/control differences and 2) to identify genes whose expression levels correlate with SSc severity as measured by local skin score, modified Rodnan skin thickness score (MRSS), forced vital capacity (FVC), or diffusing capacity for carbon monoxide (DLco).
Results
We found that PBMCs from SSc patients showed a strong type I interferon signature. This signal was found to be replicated in the skin, with additional signals for increased extracellular matrix (ECM) genes, classical complement pathway activation, and the presence of B cells. Notably, we observed a marked decrease in the expression of SPAG17, a cilia component, in SSc skin. We identified genes that correlated with the MRSS, DLco, and FVC in SSc PBMCs and skin using weighted gene coexpression network analysis. These genes were largely distinct from the case/control differentially expressed genes. In PBMCs, type I interferon signatures negatively correlated with the DLco. In SSc skin, ECM gene expression positively correlated with the MRSS. Network analysis of SSc skin genes that correlated with clinical features identified the noncoding RNAs SOX9‐AS1 and ROCR, both near the SOX9 locus, as highly connected, “hub‐like” genes in the network.
Conclusion
These results identify noncoding RNAs and SPAG17 as novel factors potentially implicated in the pathogenesis of SSc.
Summary
Background
Hidradenitis suppurativa (HS), also called acne inversa, is a chronic skin disease. The symptoms can be severe, and include intensely painful nodules and abscesses in ...apocrine‐gland rich inverse skin, such as the buttocks, under the arms and in the groin. Autosomal dominant forms of HS exist, but are rare. Some of these kindred have heterozygous loss‐of‐function rare variants in the γ‐secretase complex component nicastrin (NCSTN).
Aim
To investigate the effect of NCSTN haploinsufficiency on human keratinocytes and assess potential mechanisms for lesion development.
Methods
NCSTN was knocked down using a small hairpin RNA construct in both a keratinocyte cell line (HEK001) and an embryonic kidney cell line (HEK293), and differential gene expression was assessed using RNA microarray. Using the HEK293 line, a heterozygous deletion of NCSTN was created with CRISPR/Cas9 genome editing, and nuclear factor kappa B activity was assessed using a luciferase reporter.
Results
Compared with controls, the keratinocyte NCSTN knockdown cell line showed a significantly increased expression of genes related to the type I interferon response pathway. Both HEK001 and HEK293 knockdowns demonstrated evidence of altered growth. There was a small but significant increase in nuclear factor kappa B signalling in response to tumour necrosis factor treatment in HEK293 cells genome‐edited for reduced NCSTN.
Conclusions
Our data suggest a role for increased keratinocyte inflammatory responsiveness in familial HS. Confirming this phenotype and characterizing additional effects in different cell types will require study beyond cell lines, such as in primary cells and tissues.
Abstract
Motivation
Classification by supervised machine learning greatly facilitates the annotation of protein characteristics from their primary sequence. However, the feature generation step in ...this process requires detailed knowledge of attributes used to classify the proteins. Lack of this knowledge risks the selection of irrelevant features, resulting in a faulty model. In this study, we introduce a supervised protein classification method with a novel means of automating the work-intensive feature generation step via a Natural Language Processing (NLP)-dependent model, using a modified combination of n-grams and skip-grams (m-NGSG).
Results
A meta-comparison of cross-validation accuracy with twelve training datasets from nine different published studies demonstrates a consistent increase in accuracy of m-NGSG when compared to contemporary classification and feature generation models. We expect this model to accelerate the classification of proteins from primary sequence data and increase the accessibility of protein characteristic prediction to a broader range of scientists.
Availability and implementation
m-NGSG is freely available at Bitbucket: https://bitbucket.org/sm_islam/mngsg/src. A web server is available at watson.ecs.baylor.edu/ngsg.
Supplementary information
Supplementary data are available at Bioinformatics online.
Background
During the last decade, neoadjuvant chemotherapy (NACT) of early breast cancer (EBC) evolved from a therapy intended to enable operability to a standard treatment option aiming for ...increasing cure rates equivalent to adjuvant chemotherapy (ACT). In parallel, improvements in the quality control of breast cancer care have been established in specialized breast care units.
Patients and methods
This study analyzed chemotherapy usage in patients with EBC treated at the Heidelberg University Breast Unit between January 2003 and December 2014.
Results
Overall, 5703 patients were included in the analysis of whom 2222 (39 %) received chemotherapy, 817 (37 %) as NACT, and 1405 (63 %) as ACT. The chemotherapy usage declined from 48 % in 2003 to 34 % in 2014 of the cohort. Further, the proportion of NACT raised from 42 to 65 % irrespective of tumor subtype. In addition, frequency of pathologic complete response (pCR) defined as no tumor residues in breast and axilla (ypT0 ypN0) at surgery following NACT increased from 12 % in 2003 to 35 % in 2014. The greatest effect was observed in HER2+ breast cancer with an increase in patients achieving pCR from 24 to 68 %.
Conclusions
The results mirror the refined indication for chemotherapy in EBC and its preferred usage as NACT in Germany. The increase in pCR rate over time suggests improvement in outcome accomplished by a multidisciplinary decision-making process and stringent measures for quality control.
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