Genome Sequencing of SHH Medulloblastoma Predicts Genotype-Related Response to Smoothened Inhibition

SummarySmoothened (SMO) inhibitors recently entered clinical trials for sonic-hedgehog-driven medulloblastoma (SHH-MB). Clinical response is highly variable. To understand the mechanism(s) of primary resistance and identify pathways cooperating with aberrant SHH signaling, we sequenced and profiled a large cohort of SHH-MBs (n = 133). SHH pathway mutations involved PTCH1 (across all age groups), SUFU (infants, including germline), and SMO (adults). Children >3 years old harbored an excess of downstream MYCN and GLI2 amplifications and frequent TP53 mutations, often in the germline, all of which were rare in infants and adults. Functional assays in different SHH-MB xenograft models demonstrated that SHH-MBs harboring a PTCH1 mutation were responsive to SMO inhibition, whereas tumors harboring an SUFU mutation or MYCN amplification were primarily resistant

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Comparison of 6-month outcomes of sepsis versus non-sepsis critically ill patients receiving mechanical ventilation

Abstract Background Data on long-term outcomes after sepsis-associated critical illness have mostly come from small cohort studies, with no information about the incidence of new disability. We investigated whether sepsis-associated critical illness was independently associated with new disability at 6 months after ICU admission compared with other types of critical illness. Methods We conducted a secondary analysis of a multicenter, prospective cohort study in six metropolitan intensive care units in Australia. Adult patients were eligible if they had been admitted to the ICU and received more than 24 h of mechanical ventilation. There was no intervention. Results The primary outcome was new disability measured with the WHO Disability Assessment Schedule 2.0 (WHODAS) 12 level score compared between baseline and 6 months. Between enrollment and follow-up at 6 months, 222/888 (25%) patients died, 100 (35.5%) with sepsis and 122 (20.1%) without sepsis (P < 0.001). Among survivors, there was no difference for the incidence of new disability at 6 months with or without sepsis, 42/106 (39.6%) and 106/300 (35.3%) (RD, 0.00 (− 10.29 to 10.40), P = 0.995), respectively. In addition, there was no difference in the severity of disability, health-related quality of life, anxiety and depression, post-traumatic stress, return to work, financial distress or cognitive function. Conclusions Compared to mechanically ventilated patients of similar acuity and length of stay without sepsis, patients with sepsis admitted to ICU have an increased risk of death, but survivors have a similar risk of new disability at 6 months. Trial registration NCT03226912, registered July 24, 2017.http://deepblue.lib.umich.edu/bitstream/2027.42/173930/1/13054_2022_Article_4041.pd

The impact of COVID-19 critical illness on new disability, functional outcomes and return to work at 6 months: A prospective cohort study

Background: There are few reports of new functional impairment following critical illness from COVID-19. We aimed to describe the incidence of death or new disability, functional impairment and changes in health-related quality of life of patients after COVID-19 critical illness at 6 months. Methods: In a nationally representative, multicenter, prospective cohort study of COVID-19 critical illness, we determined the prevalence of death or new disability at 6 months, the primary outcome. We measured mortality, new disability and return to work with changes in the World Health Organization Disability Assessment Schedule 2.0 12L (WHODAS) and health status with the EQ5D-5LTM. Results: Of 274 eligible patients, 212 were enrolled from 30 hospitals. The median age was 61 (51–70) years, and 124 (58.5%) patients were male. At 6 months, 43/160 (26.9%) patients died and 42/108 (38.9%) responding survivors reported new disability. Compared to pre-illness, the WHODAS percentage score worsened (mean difference (MD), 10.40% [95% CI 7.06–13.77]; pp Conclusions: At six months after COVID-19 critical illness, death and new disability was substantial. Over a third of survivors had new disability, which was widespread across all areas of functioning

Comparison of 6-month outcomes of survivors of COVID-19 versus non–COVID-19 critical illness

Rationale: The outcomes of survivors of critical illness due to coronavirus disease (COVID-19) compared with non–COVID-19 are yet to be established. Objectives: We aimed to investigate new disability at 6 months in mechanically ventilated patients admitted to Australian ICUs with COVID-19 compared with non–COVID-19. Methods: We included critically ill patients with COVID-19 and non–COVID-19 from two prospective observational studies. Patients were eligible if they were adult (age ⩾ 18 yr) and received ⩾24 hours of mechanical ventilation. In addition, patients with COVID-19 were eligible with a positive laboratory PCR test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Measurements and Main Results: Demographic, intervention, and hospital outcome data were obtained from electronic medical records. Survivors were contacted by telephone for functional outcomes with trained outcome assessors using the World Health Organization Disability Assessment Schedule 2.0. Between March 6, 2020, and April 21, 2021, 120 critically ill patients with COVID-19, and between August 2017 and January 2019, 199 critically ill patients without COVID-19, fulfilled the inclusion criteria. Patients with COVID-19 were older (median [interquartile range], 62 [55–71] vs. 58 [44–69] yr; P = 0.019) with a lower Acute Physiology and Chronic Health Evaluation II score (17 [13–20] vs. 19 [15–23]; P = 0.011). Although duration of ventilation was longer in patients with COVID-19 than in those without COVID-19 (12 [5–19] vs. 4.8 [2.3–8.8] d; P \u3c 0.001), 180-day mortality was similar between the groups (39/120 [32.5%] vs. 70/199 [35.2%]; P = 0.715). The incidence of death or new disability at 180 days was similar (58/93 [62.4%] vs. 99/150 [66/0%]; P = 0.583). Conclusions: At 6 months, there was no difference in new disability for patients requiring mechanical ventilation for acute respiratory failure due to COVID-19 compared with non–COVID-19

Enhancer hijacking activates GFI1 family oncogenes in medulloblastoma

Medulloblastoma is a highly malignant paediatric brain tumour currently treated with a combination of surgery, radiation and chemotherapy, posing a considerable burden of toxicity to the developing child. Genomics has illuminated the extensive intertumoral heterogeneity of medulloblastoma, identifying four distinct molecular subgroups. Group 3 and group 4 subgroup medulloblastomas account for most paediatric cases; yet, oncogenic drivers for these subtypes remain largely unidentified. Here we describe a series of prevalent, highly disparate genomic structural variants, restricted to groups 3 and 4, resulting in specific and mutually exclusive activation of the growth factor independent 1 family proto-oncogenes, GFI1 and GFI1B. Somatic structural variants juxtapose GFI1 or GFI1B coding sequences proximal to active enhancer elements, including super-enhancers, instigating oncogenic activity. Our results, supported by evidence from mouse models, identify GFI1 and GFI1B as prominent medulloblastoma oncogenes and implicate 'enhancer hijacking' as an efficient mechanism driving oncogene activation in a childhood cancer

A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task

Background: Recent studies have demonstrated the use of convolutional neural networks (CNNs) to classify images of melanoma with accuracies comparable to those achieved by board-certified dermatologists. However, the performance of a CNN exclusively trained with dermoscopic images in a clinical image classification task in direct competition with a large number of dermatologists has not been measured to date. This study compares the performance of a convolutional neuronal network trained with dermoscopic images exclusively for identifying melanoma in clinical photographs with the manual grading of the same images by dermatologists. Methods: We compared automatic digital melanoma classification with the performance of 145 dermatologists of 12 German university hospitals. We used methods from enhanced deep learning to train a CNN with 12,378 open-source dermoscopic images. We used 100 clinical images to compare the performance of the CNN to that of the dermatologists. Dermatologists were compared with the deep neural network in terms of sensitivity, specificity and receiver operating characteristics. Findings: The mean sensitivity and specificity achieved by the dermatologists with clinical images was 89.4% (range: 55.0%-100%) and 64.4% (range: 22.5%-92.5%). At the same sensitivity, the CNN exhibited a mean specificity of 68.2% (range 47.5%-86.25%). Among the dermatologists, the attendings showed the highest mean sensitivity of 92.8% at a mean specificity of 57.7%. With the same high sensitivity of 92.8%, the CNN had a mean specificity of 61.1%. Interpretation: For the first time, dermatologist-level image classification was achieved on a clinical image classification task without training on clinical images. The CNN had a smaller variance of results indicating a higher robustness of computer vision compared with human assessment for dermatologic image classification tasks. (C) 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)