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IntroductionManagement of refractory shock in the setting of overdose can be challenging. We describe a case of vasodilatory and cardiogenic shock after bupropion and citalopram overdose. Vasopressors and conventional therapies failed to stabilize the patient resulting in placement of venoarterial extracorporeal membrane oxygenation (VA ECMO) for patient rescue and recovery.Case summary: A 23-year-old male presented after intentional bupropion and citalopram overdose. He developed seizures, acute respiratory failure, metabolic acidosis, severe refractory vasodilatory, and cardiogenic shock. The patient received mechanical ventilation, Advanced Cardiac Life Support (ACLS), Intralipid ® therapy, vasopressor support, and VA ECMO. Total duration of ECMO was 72 h. Serum laboratory studies drawn on the day of admission showed serum concentrations of citalopram (3400 ng/mL, reference range 9-200 ng/mL) and bupropion (597 ng/mL, reference range 50-100 ng/mL). The patient was extubated on hospital day 18 and discharged home with referral to outpatient psychiatry, 28 days after intentional overdose.ConclusionsThis case illustrates successful recovery after hydroxocobalamin and VA ECMO in severe vasodilatory and cardiogenic shock following overdose of bupropion and citalopram.

Multiple major health organisations recommend the use of extracorporeal membrane oxygenation (ECMO) support for COVID-19-related acute hypoxaemic respiratory failure. However, initial reports of ECMO use in patients with COVID-19 described very high mortality and there have been no large, international cohort studies of ECMO for COVID-19 reported to date. We used data from the Extracorporeal Life Support Organization (ELSO) Registry to characterise the epidemiology, hospital course, and outcomes of patients aged 16 years or older with confirmed COVID-19 who had ECMO support initiated between Jan 16 and May 1, 2020, at 213 hospitals in 36 countries. The primary outcome was in-hospital death in a time-to-event analysis assessed at 90 days after ECMO initiation. We applied a multivariable Cox model to examine whether patient and hospital factors were associated with in-hospital mortality. Data for 1035 patients with COVID-19 who received ECMO support were included in this study. Of these, 67 (6%) remained hospitalised, 311 (30%) were discharged home or to an acute rehabilitation centre, 101 (10%) were discharged to a long-term acute care centre or unspecified location, 176 (17%) were discharged to another hospital, and 380 (37%) died. The estimated cumulative incidence of in-hospital mortality 90 days after the initiation of ECMO was 37·4% (95% CI 34·4–40·4). Mortality was 39% (380 of 968) in patients with a final disposition of death or hospital discharge. The use of ECMO for circulatory support was independently associated with higher in-hospital mortality (hazard ratio 1·89, 95% CI 1·20–2·97). In the subset of patients with COVID-19 receiving respiratory (venovenous) ECMO and characterised as having acute respiratory distress syndrome, the estimated cumulative incidence of in-hospital mortality 90 days after the initiation of ECMO was 38·0% (95% CI 34·6–41·5). In patients with COVID-19 who received ECMO, both estimated mortality 90 days after ECMO and mortality in those with a final disposition of death or discharge were less than 40%. These data from 213 hospitals worldwide provide a generalisable estimate of ECMO mortality in the setting of COVID-19. None.

Duty hour restrictions for residency training were implemented in the United States to improve residents’ educational experience and quality of life, as well as to improve patient care and safety; however, these restrictions are by no means problem-free. In this paper, we discuss the positive and negative aspects of duty hour restrictions, briefly highlighting research on the impact of reduced duty hours and the experiences of American residents. We also consider whether certain specialties (e.g., Emergency Medicine, Radiology) may be more amenable than others (e.g., Surgery) to duty hour restrictions. We conclude that feedback from residents is a crucial element that must be considered in any future attempts to strike a balance between reducing fatigue and enhancing education.

Management of refractory shock in the setting of overdose can be challenging. We describe a case of vasodilatory and cardiogenic shock after bupropion and citalopram overdose. Vasopressors and conventional therapies failed to stabilize the patient resulting in placement of venoarterial extracorporeal membrane oxygenation (VA ECMO) for patient rescue and recovery. Case summary: A 23-year-old male presented after intentional bupropion and citalopram overdose. He developed seizures, acute respiratory failure, metabolic acidosis, severe refractory vasodilatory, and cardiogenic shock. The patient received mechanical ventilation, Advanced Cardiac Life Support (ACLS), Intralipid ® therapy, vasopressor support, and VA ECMO. Total duration of ECMO was 72 h. Serum laboratory studies drawn on the day of admission showed serum concentrations of citalopram (3400 ng/mL, reference range 9-200 ng/mL) and bupropion (597 ng/mL, reference range 50-100 ng/mL). The patient was extubated on hospital day 18 and discharged home with referral to outpatient psychiatry, 28 days after intentional overdose. This case illustrates successful recovery after hydroxocobalamin and VA ECMO in severe vasodilatory and cardiogenic shock following overdose of bupropion and citalopram.

Induced pluripotent stem cells (iPSCs), and cells derived from them, have become key tools for modeling biological processes, particularly in cell types that are difficult to obtain from living donors. Here we present a map of regulatory variants in iPSC-derived neurons, based on 123 differentiations of iPSCs to a sensory neuronal fate. Gene expression was more variable across cultures than in primary dorsal root ganglion, particularly for genes related to nervous system development. Using single-cell RNA-sequencing, we found that the number of neuronal versus contaminating cells was influenced by iPSC culture conditions before differentiation. Despite high differentiation-induced variability, our allele-specific method detected thousands of quantitative trait loci (QTLs) that influenced gene expression, chromatin accessibility, and RNA splicing. On the basis of these detected QTLs, we estimate that recall-by-genotype studies that use iPSC-derived cells will require cells from at least 20–80 individuals to detect the effects of regulatory variants with moderately large effect sizes. This study identifies regulatory variants in sensory neurons derived from induced pluripotent stem cells. Despite differentiation-induced variability, an allele-specific method allowed detection of loci influencing gene expression, chromatin accessibility and RNA splicing.

The genetic and morphological development of colorectal cancer is a paradigm for tumorigenesis. However, the dynamics of clonal evolution underpinning carcinogenesis remain poorly understood. Here we identify multipotential stem cells within human colorectal adenomas and use methylation patterns of nonexpressed genes to characterize clonal evolution. Numerous individual crypts from six colonic adenomas and a hyperplastic polyp were microdissected and characterized for genetic lesions. Clones deficient in cytochrome c oxidase (CCO ⁻) were identified by histochemical staining followed by mtDNA sequencing. Topographical maps of clone locations were constructed using a combination of these data. Multilineage differentiation within clones was demonstrated by immunofluorescence. Methylation patterns of adenomatous crypts were determined by clonal bisulphite sequencing; methylation pattern diversity was compared with a mathematical model to infer to clonal dynamics. Individual adenomatous crypts were clonal for mtDNA mutations and contained both mucin-secreting and neuroendocrine cells, demonstrating that the crypt contained a multipotent stem cell. The intracrypt methylation pattern was consistent with the crypts containing multiple competing stem cells. Adenomas were epigenetically diverse populations, suggesting that they were relatively mitotically old populations. Intratumor clones typically showed less diversity in methylation pattern than the tumor as a whole. Mathematical modeling suggested that recent clonal sweeps encompassing the whole adenoma had not occurred. Adenomatous crypts within human tumors contain actively dividing stem cells. Adenomas appeared to be relatively mitotically old populations, pocketed with occasional newly generated subclones that were the result of recent rapid clonal expansion. Relative stasis and occasional rapid subclone growth may characterize colorectal tumorigenesis.

During the COVID-19 pandemic, lockdowns provided an opportunity to assess what factors, including changes in an owner’s routine and time spent at home, were associated with changes in dog behaviour. We undertook a longitudinal survey over a period of 8 months during which we asked about people’s work patterns, dog management, and their dogs’ behaviour. Generalized linear models revealed that the pre-existence of signs of potential separation-related problems, and especially vocalisation, self-injury, and chewing to escape confinement, was associated with an increase in a range of separation issues. Dogs showing separation-related signs prior to COVID were also more likely to develop more problems during lockdown. Management changes tended to result in increased physical and social stress, with a range of potential compensatory actions taken by the dog, however these signs of stress did not generally appear to be connected to separation-related issues. Survival analysis was used to investigate the emergence of specific issues over time. This indicated that a change to working from home was related initially to a decreased risk of aggression towards the owner, but over time, those who continued to work from the home were at an increased risk of this problem. No other significant time-related relationships were found.

Background Inference of active regulatory cascades under specific molecular and environmental perturbations is a recurring task in transcriptional data analysis. Commercial tools based on large, manually curated networks of causal relationships offering such functionality have been used in thousands of articles in the biomedical literature. The adoption and extension of such methods in the academic community has been hampered by the lack of freely available, efficient algorithms and an accompanying demonstration of their applicability using current public networks. Results In this article, we propose a new statistical method that will infer likely upstream regulators based on observed patterns of up- and down-regulated transcripts. The method is suitable for use with public interaction networks with a mix of signed and unsigned causal edges. It subsumes and extends two previously published approaches and we provide a novel algorithmic method for efficient statistical inference. Notably, we demonstrate the feasibility of using the approach to generate biological insights given current public networks in the context of controlled in-vitro overexpression experiments, stem-cell differentiation data and animal disease models. We also provide an efficient implementation of our method in the R package QuaternaryProd available to download from Bioconductor. Conclusions In this work, we have closed an important gap in utilizing causal networks to analyze differentially expressed genes. Our proposed Quaternary test statistic incorporates all available evidence on the potential relevance of an upstream regulator. The new approach broadens the use of these types of statistics for highly curated signed networks in which ambiguities arise but also enables the use of networks with unsigned edges. We design and implement a novel computational method that can efficiently estimate p -values for upstream regulators in current biological settings. We demonstrate the ready applicability of the implemented method to analyze differentially expressed genes using the publicly available networks.

Parosteal osteosarcoma, low-grade central osteosarcoma, and fibrous dysplasia share similar histological features that may pose a diagnostic challenge. The detection of GNAS mutations in primary bone tumors has been useful in clinical practice for diagnosing fibrous dysplasia. However, the recent report of GNAS mutations being detected in a significant proportion of parosteal osteosarcoma challenges the specificity of this mutation. As the number of cases reported in this study was small we set out to determine if these results could be reproduced. We studied 97 formalin-fixed paraffin-embedded low-grade osteosarcomas from 90 patients including 62 parosteal osteosarcomas, of which MDM2 amplification was detected in 79%, 11 periosteal osteosarcomas and 24 low-grade central osteosarcoma samples. The mutational status of GNAS was analyzed in codons p.R201, p.Q227, and other less common GNAS alterations by bidirectional Sanger sequencing and/or next generation sequencing using the Life Technologies Ion Torrent platform. GNAS mutations were not detected in any of the low-grade osteosarcomas from which informative DNA was extracted. Our findings therefore support prior observations that GNAS mutations are highly specific for fibrous dysplasia and occur rarely, if ever, in parosteal and other low-grade osteosarcomas.

In many research areas scientists are interested in clustering objects within small datasets while making use of prior knowledge from large reference datasets. We propose a method to apply the machine learning concept of transfer learning to unsupervised clustering problems and show its effectiveness in the field of single-cell RNA sequencing (scRNA-Seq). The goal of scRNA-Seq experiments is often the definition and cataloguing of cell types from the transcriptional output of individual cells. To improve the clustering of small disease- or tissue-specific datasets, for which the identification of rare cell types is often problematic, we propose a transfer learning method to utilize large and well-annotated reference datasets, such as those produced by the Human Cell Atlas. Our approach modifies the dataset of interest while incorporating key information from the larger reference dataset via Non-negative Matrix Factorization (NMF). The modified dataset is subsequently provided to a clustering algorithm. We empirically evaluate the benefits of our approach on simulated scRNA-Seq data as well as on publicly available datasets. Finally, we present results for the analysis of a recently published small dataset and find improved clustering when transferring knowledge from a large reference dataset. Implementations of the method are available at https://github.com/nicococo/scRNA .