Development and evaluation of intraoperative ultrasound segmentation with negative image frames and multiple observer labels

When developing deep neural networks for segmenting intraoperative ultrasound images, several practical issues are encountered frequently, such as the presence of ultrasound frames that do not contain regions of interest and the high variance in ground-truth labels. In this study, we evaluate the utility of a pre-screening classification network prior to the segmentation network. Experimental results demonstrate that such a classifier, minimising frame classification errors, was able to directly impact the number of false positive and false negative frames. Importantly, the segmentation accuracy on the classifier-selected frames, that would be segmented, remains comparable to or better than those from standalone segmentation networks. Interestingly, the efficacy of the pre-screening classifier was affected by the sampling methods for training labels from multiple observers, a seemingly independent problem. We show experimentally that a previously proposed approach, combining random sampling and consensus labels, may need to be adapted to perform well in our application. Furthermore, this work aims to share practical experience in developing a machine learning application that assists highly variable interventional imaging for prostate cancer patients, to present robust and reproducible open-source implementations, and to report a set of comprehensive results and analysis comparing these practical, yet important, options in a real-world clinical application

Filling the agronomic data gap through a minimum data collection approach

Context: Agronomic data such as applied inputs, management practices, and crop yields are needed for assessing productivity, nutrient balances, resource use efficiency, as well as other aspects of environmental and economic performance of cropping systems. In many instances, however, these data are only available at a coarse level of aggregation or simply do not exist. Objectives: Here we developed an approach that identifies sites for agronomic data collection for a given crop and country, seeking a balance between minimizing data collection efforts and proper representation of the main crop producing areas. Methods: The developed approach followed a stratified sampling method based on a spatial framework that delineates major climate zones and crop area distribution maps, which guides selection of sampling areas (SA) until half of the national harvested area is covered. We provided proof of concept about the robustness of the approach using three rich databases including data on fertilizer application rates for maize, wheat, and soybean in Argentina, soybean in the USA, and maize in Kenya, which were collected via local experts (Argentina) and field surveys (USA and Kenya). For validation purposes, fertilizer rates per crop and nutrient derived at (sub-) national level following our approach were compared against those derived using all data collected from the whole country. Results: Application of the approach in Argentina, USA, and Kenya resulted in selection of 12, 28, and 10 SAs, respectively. For each SA, three experts or 20 fields were sufficient to give a robust estimate of average fertilizer rates applied by farmers. Average rates at national level derived from our approach compared well with those derived using the whole database ( ± 10 kg N, ± 2 kg P, ± 1 kg S, and ± 5 kg K per ha) requiring less than one third of the observations. Conclusions: The developed minimum crop data collection approach can fill the agronomic data gaps in a costeffective way for major crop systems both in large- and small-scale systems. Significance: The proposed approach is generic enough to be applied to any crop-country combination to guide collection of key agricultural data at national and subnational levels with modest investment especially for countries that do not currently collect data

HIV-1 persistence in CD4+ T cells with stem cell-like properties

Cellular HIV-1 reservoirs that persist despite antiretroviral treatment are incompletely defined. We show that during suppressive antiretroviral therapy, CD4+ T memory stem cells (TSCM) harbor high per-cell levels of HIV-1 DNA, and make increasing contributions to the total viral CD4+ T cell reservoir over time. Moreover, phylogenetic studies suggested long-term persistence of viral quasispecies in CD4+ TSCM cells. Thus, HIV-1 may exploit stem cell characteristics of cellular immune memory to promote long-term viral persistence

Potent Cell-Intrinsic Immune Responses in Dendritic Cells Facilitate HIV-1-Specific T Cell Immunity in HIV-1 Elite Controllers

The majority of HIV-1 elite controllers (EC) restrict HIV-1 replication through highly functional HIV-1-specific T cell responses, but mechanisms supporting the evolution of effective HIV-1-specific T cell immunity in these patients remain undefined. Cytosolic immune recognition of HIV-1 in conventional dendritic cells (cDC) can facilitate priming and expansion of HIV-1-specific T cells; however, HIV-1 seems to be able to avoid intracellular immune recognition in cDCs in most infected individuals. Here, we show that exposure of cDCs from EC to HIV-1 leads to a rapid and sustained production of type I interferons and upregulation of several interferon-stimulated effector genes. Emergence of these cell-intrinsic immune responses was associated with a reduced induction of SAMHD1 and LEDGF/p75, and an accumulation of viral reverse transcripts, but inhibited by pharmacological blockade of viral reverse transcription or siRNA-mediated silencing of the cytosolic DNA sensor cGAS. Importantly, improved cell-intrinsic immune recognition of HIV-1 in cDCs from elite controllers translated into stronger abilities to stimulate and expand HIV-1-specific CD8 T cell responses. These data suggest an important role of cell-intrinsic type I interferon secretion in dendritic cells for the induction of effective HIV-1-specific CD8 T cells, and may be helpful for eliciting functional T cell immunity against HIV-1 for preventative or therapeutic clinical purposes

NLRC4 -mediated activation of CD1c+ dendritic cells contributes to perpetuation of synovitis in rheumatoid arthritis.

The individual contribution of specific myeloid subsets such as CD1c+ conventional dendritic cells (cDC) to perpetuation of Rheumatoid Arthritis (RA) pathology remains unclear. In addition, the specific innate sensors driving pathogenic activation of CD1c+ cDCs in RA patients and their functional implications have not been characterized. Here, we assessed phenotypical, transcriptional and functional characteristics of CD1c+ and CD141+ cDCs and monocytes from the blood and synovial fluid of RA patients. Increased levels of CCR2 and the IgG receptor CD64 on circulating CD1c+ cDC associated with the presence of this DC subset in the synovial membrane in RA patients. Moreover, synovial CD1c+ cDCs are characterized by increased expression of proinflammatory cytokines and high abilities to induce pathogenic IFNγ+IL-17+ CD4+ T cells in vitro. Finally, we identified the crosstalk between Fcγ Receptors and NLRC4 as a new potential molecular mechanism mediating pathogenic activation, CD64 upregulation and functional specialization of CD1c+ cDCs in response to dsDNA-IgG in RA patients.E.M.G. was supported by Comunidad de Madrid Talento Program (2017-T1/BMD5396), Ramón y Cajal Program (RYC2018-024374-I), the MINECO RETOS program (RTI2018-097485-A-I00), La Caixa Foundation (HR20-00218), CIBERINF (CB21/13/00107) and the TV3 Marató (REDINCOV). C.D.A. was supported by Comunidad de Madrid Talento Program (2017-T1/BMD-5396). M.C.M was supported by the NIH (R21AI140930). HR17-00016 grant from “La Caixa Banking Foundation to F.S.M also supported the study. D.C-F. is supported by the Fellowship “la Caixa” Foundation LCF/BQ/DR19/11740010. A.T.M. was supported by a PhD fellowship from the Autonomous Region of Madrid (PEJD-2019-PRE/BMD-16851) and the RD21/0002/0027 grant. R.L. and G.H.B. were supported by PI18/00261 AND PI20/00349 grants from Ministerio de Ciencia e Innovación and Instituto de Salud Carlos III, respectively. O.P. was supported by the TV3 Marató (REDINCOV) and I.T. was funded by grant for the promotion of research studies master-UAM 2021. S.C. was supported by PI21/01474 grant from the Instituto de Salud Carlos III and co-funded by The European Regional Development Fund (ERDF). I.G.A was supported by RD21/0002/0027 and PI21/00526 grants from the Spanish MINECO and Instituto de Salud Carlos III and co-funded by The European Regional Development Fund (ERDF) “A way to make Europe.S

Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq

Systematic measurement biases make normalization an essential step in single-cell RNA sequencing (scRNA-seq) analysis. There may be multiple competing considerations behind the assessment of normalization performance, of which some may be study specific. We have developed "scone"- a flexible framework for assessing performance based on a comprehensive panel of data-driven metrics. Through graphical summaries and quantitative reports, scone summarizes trade-offs and ranks large numbers of normalization methods by panel performance. The method is implemented in the open-source Bioconductor R software package scone. We show that top-performing normalization methods lead to better agreement with independent validation data for a collection of scRNA-seq datasets. scone can be downloaded at http://bioconductor.org/packages/scone/

MICa/b-dependent activation of natural killer cells by CD64+ inflammatory type 2 dendritic cells contributes to autoimmunity.

Primary Sjögren's syndrome (pSS) is an inflammatory autoimmune disorder largely mediated by type I and II interferon (IFN). The potential contribution of innate immune cells, such as natural killer (NK) cells and dendritic cells (DC), to the pSS pathology remains understudied. Here, we identified an enriched CD16+ CD56hi NK cell subset associated with higher cytotoxic function, as well as elevated proportions of inflammatory CD64+ conventional dendritic cell (cDC2) subtype that expresses increased levels of MICa/b, the ligand for the activating receptor NKG2D, in pSS individuals. Circulating cDC2 from pSS patients efficiently induced activation of cytotoxic NK cells ex vivo and were found in proximity to CD56+ NK cells in salivary glands (SG) from pSS patients. Interestingly, transcriptional activation of IFN signatures associated with the RIG-I/DDX60 pathway, IFN I receptor, and its target genes regulate the expression of NKG2D ligands on cDC2 from pSS patients. Finally, increased proportions of CD64hi RAE-1+ cDC2 and NKG2D+ CD11b+ CD27+ NK cells were present in vivo in the SG after poly I:C injection. Our study provides novel insight into the contribution and interplay of NK and cDC2 in pSS pathology and identifies new potential therapy targets.S