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Although the last 30years have witnessed the mapping of the wiring diagrams of the gene regulatory networks that dictate cell fate and animal body plans, specific understanding building on such network diagrams that shows how DNA regulatory regions control gene expression lags far behind. These networks have yet to yield the predictive power necessary to, for example, calculate how the concentration dynamics of input transcription factors and DNA regulatory sequence prescribes output patterns of gene expression that, in turn, determine body plans themselves. Here, we argue that reaching a predictive understanding of developmental decision-making calls for an interplay between theory and experiment aimed at revealing how the regulation of the processes of the central dogma dictate network connections and how network topology guides cells toward their ultimate developmental fate. To make this possible, it is crucial to break free from the snapshot-based understanding of embryonic development facilitated by fixed-tissue approaches and embrace new technologies that capture the dynamics of developmental decision-making at the single cell level, in living embryos. © 2020 Elsevier Inc. All rights reserved.This article contains the ASTMH Membership Directory for 2020.BACKGROUND Complications of preterm birth cause more than 1 million deaths each year, mostly within the first day after birth (47%) and before full post-natal stabilisation. Kangaroo mother care (KMC), provided as continuous skin-to-skin contact for 18 h per day to fully stabilised neonates ≤ 2000 g, reduces mortality by 36-51% at discharge or term-corrected age compared with incubator care. The mortality effect of starting continuous KMC before stabilisation is a priority evidence gap, which we aim to investigate in the eKMC trial, with a secondary aim of understanding mechanisms, particularly for infection prevention. METHODS We will conduct a single-site, non-blinded, individually randomised, controlled trial comparing two parallel groups to either early (within 24 h of admission) continuous KMC or standard care on incubator or radiant heater with KMC when clinically stable at > 24 h of admission. Eligible neonates (n = 392) are hospitalised singletons or twins less then  2000 g and 1-24 h old at screeninre-stabilised preterm population. Our findings will contribute to the global evidence base in addition to providing insights into the infection prevention mechanisms and safety of using this established intervention for the most vulnerable neonatal population. TRIAL REGISTRATION ClinicalTrials.gov NCT03555981. Submitted 8 May 2018 and registered 14 June 2018. Prospectively registered.BACKGROUND The aim of this study was to evaluate the value of combining pelvic lymph node and tumor characteristics on positron emission tomography-intravoxel incoherent motion magnetic resonance (PET-IVIM MR) imaging for predicting lymph node metastasis in patients with cervical cancer, especially in those with negative lymph nodes on PET. METHODS The medical records of 95 patients with cervical cancer who underwent surgical resection with pelvic lymph node dissection were evaluated. The patients were divided into negative and positive groups according to postoperative pathologic lymph node diagnosis, and comparisons of the PET and IVIM-derived parameters between the two groups were performed. Univariate and multivariate analyses were performed to construct a predictive model of lymph node metastasis. RESULTS For all patients, tumor SUVmax, TLG, Dmin, PET and MRI for lymph node diagnosis showed significant differences between patients with and without confirmed lymph node metastasis. Univariate and multivariate logistic analysis showed that the combination of tumor TLG, Dmin and PET for lymph node diagnosis had the strongest predictive value (AUC 0.913, p  less then  0.001). For patients with PET-negative lymph nodes, SUVmax, SUVmean, MTV, TLG, and Dmin showed significant between-group differences, and univariate and multivariate logistic analysis showed that TLG had the strongest predictive value. CONCLUSIONS The combination of tumorTLG, Dmin and PET for lymph node diagnosis is a powerful prognostic factor for all patients. TLG has the best predictive performance in patients with PET negative lymph nodes.BACKGROUND Lung adenocarcinoma (LUAD) is the most frequent subtype of lung cancer. Methyl-β-cyclodextrin solubility dmso The prognostic signature could be reliable to stratify LUAD patients according to risk, which helps the management of the systematic treatments. In this study, a systematic and reliable immune signature was performed to estimate the prognostic stratification in LUAD. METHODS The profiles of immune-related genes for patients with LUAD were used as one TCGA training set n = 494, other validation set 1 n = 226 and validation set 2 n = 398. Univariate Cox survival analysis was used to identify the candidate immune-related genes from each cohort. Then, the immune signature was developed and validated in the training and validation sets. RESULTS In this study, functional analysis showed that immune-related genes involved in immune regulation and MAPK signaling pathway. A prognostic signature based on 10 immune-related genes was established in the training set and patients were divided into high-risk and low-risk groups. Our 10 immune-related gene signature was significantly related to worse survival, especially during early-stage tumors. Further stratification analyses revealed that this 10 immune-related gene signature was still an effective tool for predicting prognosis in smoking or nonsmoking patients, patients with KRAS mutation or KRAS wild-type, and patients with EGFR mutation or EGFR wild-type. Our signature was negatively correlated with B cell, CD4+ T cell, CD8+ T cell, neutrophil, dendritic cell (DC), and macrophage immune infiltration, and immune checkpoint molecules PD-1 and CTLA-4 (P  less then  0.05). CONCLUSIONS These findings suggested that our signature was a promising biomarker for prognosis prediction and can facilitate the management of immunotherapy in LUAD.