MONAI: An open-source framework for deep learning in healthcare

Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications of AI in healthcare have the potential to improve our ability to detect, diagnose, prognose, and intervene on human disease. For AI models to be used clinically, they need to be made safe, reproducible and robust, and the underlying software framework must be aware of the particularities (e.g. geometry, physiology, physics) of medical data being processed. This work introduces MONAI, a freely available, community-supported, and consortium-led PyTorch-based framework for deep learning in healthcare. MONAI extends PyTorch to support medical data, with a particular focus on imaging, and provide purpose-specific AI model architectures, transformations and utilities that streamline the development and deployment of medical AI models. MONAI follows best practices for software-development, providing an easy-to-use, robust, well-documented, and well-tested software framework. MONAI preserves the simple, additive, and compositional approach of its underlying PyTorch libraries. MONAI is being used by and receiving contributions from research, clinical and industrial teams from around the world, who are pursuing applications spanning nearly every aspect of healthcare.Comment: www.monai.i

Mutational analysis of the C-terminal FATC domain of Saccharomyces cerevisiae Tra1

Tra1 is a component of the Saccharomyces cerevisiae SAGA and NuA4 complexes and a member of the PIKK family, which contain a C-terminal phosphatidylinositol 3-kinase-like (PI3K) domain followed by a 35-residue FATC domain. Single residue changes of L3733A and F3744A, within the FATC domain, resulted in transcriptional changes and phenotypes that were similar but not identical to those caused by mutations in the PI3K domain or deletions of other SAGA or NuA4 components. The distinct nature of the FATC mutations was also apparent from the additive effect of tra1-L3733A with SAGA, NuA4, and tra1 PI3K domain mutations. Tra1-L3733A associates with SAGA and NuA4 components and with the Gal4 activation domain, to the same extent as wild-type Tra1; however, steady-state levels of Tra1-L3733A were reduced. We suggest that decreased stability of Tra1-L3733A accounts for the phenotypes since intragenic suppressors of tra1-L3733A restored Tra1 levels, and reducing wild-type Tra1 led to comparable growth defects. Also supporting a key role for the FATC domain in the structure/function of Tra1, addition of a C-terminal glycine residue resulted in decreased association with Spt7 and Esa1, and loss of cellular viability. These findings demonstrate the regulatory potential of mechanisms targeting the FATC domains of PIKK proteins

The Pseudokinase Domain of Saccharomyces cerevisiae Tra1 Is Required for Nuclear Localization and Incorporation into the SAGA and NuA4 Complexes

Tra1 is an essential component of the SAGA/SLIK and NuA4 complexes in S. cerevisiae, recruiting these co-activator complexes to specific promoters. As a PIKK family member, Tra1 is characterized by a C-terminal phosphoinositide 3-kinase (PI3K) domain. Unlike other PIKK family members (e.g., Tor1, Tor2, Mec1, Tel1), Tra1 has no demonstrable kinase activity. We identified three conserved arginine residues in Tra1 that reside proximal or within the cleft between the N- and C-terminal subdomains of the PI3K domain. To establish a function for Tra1’s PI3K domain and specifically the cleft region, we characterized a tra1 allele where these three arginine residues are mutated to glutamine. The half-life of the Tra1Q3 protein is reduced but its steady state level is maintained at near wild-type levels by a transcriptional feedback mechanism. The tra1Q3 allele results in slow growth under stress and alters the expression of genes also regulated by other components of the SAGA complex. Tra1Q3 is less efficiently transported to the nucleus than the wild-type protein. Likely related to this, Tra1Q3 associates poorly with SAGA/SLIK and NuA4. The ratio of Spt7SLIK to Spt7SAGA increases in the tra1Q3 strain and truncated forms of Spt20 become apparent upon isolation of SAGA/SLIK. Intragenic suppressor mutations of tra1Q3 map to the cleft region further emphasizing its importance. We propose that the PI3K domain of Tra1 is directly or indirectly important for incorporating Tra1 into SAGA and NuA4 and thus the biosynthesis and/or stability of the intact complexes

Costs of caring for children with an intellectual developmental disorder

Background: Caring for a child with intellectual developmental disorder (IDD) is expensive for the medical system, for the family, and for society in general. Whereas the health care costs of IDD have been described, the societal and parental costs of IDD have been less well documented. Objective: Our goal was to estimate the out-of-pocket costs to parents, and the non-health system costs to society, of raising a child with IDD. Methods: We used an online retrospective survey, previously developed by our group, to collect parental and societal costs to families of 80 children who presented with IDD of unknown etiology in British Columbia, Canada. Results: Median annual parental costs of caring for 80 children with IDD was CAD$44,570 (range CAD$2245-$225,777). The largest contributors to parental costs were income loss and caregiving time costs. Median annual societal costs (excluding health system costs) were CAD$27,428 (range CAD$0-$119,188). In school age children, the largest contributor to societal costs was a per child school subsidy. Both parental and societal costs increased with increasing IDD severity. Parental costs were not adequately compensated by government benefits received. Conclusions: Although medical care is universally available through Canadian provincial health systems and social assistance is provided to the families of children with IDD, parents continue to bear a substantial financial burden beyond that associated with raising an unaffected child. (C) 2015 Elsevier Inc. All rights reserve

Supplemental Material for Berg et al.,2018

Supplemental Information contains Table S1 with strain information, Table S2 with oligonucleotide sequences, Figure S1 with sequence of synthetic DNA fragments, Figure S2 with <i>S. cereivisae</i> PIKK alignments, Figure S3 with half life of WT Tra1, Figure S4 with Tra1pr-LacZ data, Figure S5 with synthetic growth interactions between <i>tra1_Q3 </i>and various SAGA and NuA4 deletions, Figure S6 with mapping of mutated residues on Tra1 structure, Figure S7 with fractionation data, Figure S8 with Spt7 localization data, Figure S9 with western blot of Spt7, Figure S10 with coverage map of Spt20 from mass spectrometry data, Figure S11 with tagged Spt20 spot plate and Figure S12 with half life of various <i>tra1</i>_Q3suppressors. Tra1Q3 Spt20 Mass Spectrometry Data file contains peaks identified from mass spectrometry of Spt20 isolated from TAP-Ada2 pull downs of SAGA

Sfp1 links TORC1 and cell growth regulation to the yeast SAGA-complex component Tra1 in response to polyQ proteotoxicity

Chromatin remodeling regulates gene expression in response to the accumulation of misfolded polyQ proteins associated with Huntington\u27s disease (HD). Tra1 is an essential component of both the SAGA/SLIK and NuA4 transcription co‐activator complexes and is linked to multiple cellular processes, including protein trafficking and signaling pathways associated with misfolded protein stress. Cells with compromised Tra1 activity display phenotypes distinct from deletions encoding components of the SAGA and NuA4 complexes, indicating a potentially unique regulatory role of Tra1 in the cellular response to protein misfolding. Here, we employed a yeast model to define how the expression of toxic polyQ expansion proteins affects Tra1 expression and function. Expression of expanded polyQ proteins mimics deletion of SAGA/NuA4 components and results in growth defects under stress conditions. Moreover, deleting genes encoding SAGA and, to a lesser extent, NuA4 components exacerbates polyQ toxicity. Also, cells carrying a mutant Tra1 allele displayed increased sensitivity to polyQ toxicity. Interestingly, expression of polyQ proteins upregulated the expression of TRA1 and other genes encoding SAGA components, revealing a feedback mechanism aimed at maintaining Tra1 and SAGA functional integrity. Moreover, deleting the TORC1 (Target of Rapamycin) effector SFP1 abolished upregulation of TRA1 upon expression of polyQ proteins. While Sfp1 is known to adjust ribosome biogenesis and cell size in response to stress, we identified a new role for Sfp1 in the control of TRA1 expression, linking TORC1 and cell growth regulation to the SAGA acetyltransferase complex during misfolded protein stress