Inside Audit Firms

We develop and test hypotheses about compensation policy and auditor retention in accounting firms. Our analyses use de-identified employment and compensation data to investigate the entire pay distribution within accounting firms. Accounting firms all have low retention rates but exhibit differing pay structures. Big 4 firms give similar raises within each cohort, while non-Big 4 give substantial raises to a few top performers. Auditors often "move up" to Big 4 firms, but relatively few move the other way. Audit fees are consistently related to compensation structure. Overall, our results suggest that compensation policies in professional accounting firms affect auditor behavior

CR Cistrome: a ChIP-Seq database for chromatin regulators and histone modification linkages in human and mouse

Diversified histone modifications (HMs) are essential epigenetic features. They play important roles in fundamental biological processes including transcription, DNA repair and DNA replication. Chromatin regulators (CRs), which are indispensable in epigenetics, can mediate HMs to adjust chromatin structures and functions. With the development of ChIP-Seq technology, there is an opportunity to study CR and HM profiles at the whole-genome scale. However, no specific resource for the integration of CR ChIP-Seq data or CR-HM ChIP-Seq linkage pairs is currently available. Therefore, we constructed the CR Cistrome database, available online at http://compbio.tongji.edu.cn/cr and http://cistrome.org/cr/, to further elucidate CR functions and CR-HM linkages. Within this database, we collected all publicly available ChIP-Seq data on CRs in human and mouse and categorized the data into four cohorts: the reader, writer, eraser and remodeler cohorts, together with curated introductions and ChIP-Seq data analysis results. For the HM readers, writers and erasers, we provided further ChIP-Seq analysis data for the targeted HMs and schematized the relationships between them. We believe CR Cistrome is a valuable resource for the epigenetics community

Computational inference of mRNA stability from histone modification and transcriptome profiles

Histone modifications play important roles in regulating eukaryotic gene expression and have been used to model expression levels. Here, we present a regression model to systematically infer mRNA stability by comparing transcriptome profiles with ChIP-seq of H3K4me3, H3K27me3 and H3K36me3. The results from multiple human and mouse cell lines show that the inferred unstable mRNAs have significantly longer 3′Untranslated Regions (UTRs) and more microRNA binding sites within 3′UTR than the inferred stable mRNAs. Regression residuals derived from RNA-seq, but not from GRO-seq, are highly correlated with the half-lives measured by pulse-labeling experiments, supporting the rationale of our inference. Whereas, the functions enriched in the inferred stable and unstable mRNAs are consistent with those from pulse-labeling experiments, we found the unstable mRNAs have higher cell-type specificity under functional constraint. We conclude that the systematical use of histone modifications can differentiate non-expressed mRNAs from unstable mRNAs, and distinguish stable mRNAs from highly expressed ones. In summary, we represent the first computational model of mRNA stability inference that compares transcriptome and epigenome profiles, and provides an alternative strategy for directing experimental measurements

Med-Flamingo: a Multimodal Medical Few-shot Learner

Medicine, by its nature, is a multifaceted domain that requires the synthesis of information across various modalities. Medical generative vision-language models (VLMs) make a first step in this direction and promise many exciting clinical applications. However, existing models typically have to be fine-tuned on sizeable down-stream datasets, which poses a significant limitation as in many medical applications data is scarce, necessitating models that are capable of learning from few examples in real-time. Here we propose Med-Flamingo, a multimodal few-shot learner adapted to the medical domain. Based on OpenFlamingo-9B, we continue pre-training on paired and interleaved medical image-text data from publications and textbooks. Med-Flamingo unlocks few-shot generative medical visual question answering (VQA) abilities, which we evaluate on several datasets including a novel challenging open-ended VQA dataset of visual USMLE-style problems. Furthermore, we conduct the first human evaluation for generative medical VQA where physicians review the problems and blinded generations in an interactive app. Med-Flamingo improves performance in generative medical VQA by up to 20\% in clinician's rating and firstly enables multimodal medical few-shot adaptations, such as rationale generation. We release our model, code, and evaluation app under https://github.com/snap-stanford/med-flamingo.Comment: Preprin

Patterns and trends among physicians-in-training named in civil legal cases: a retrospective analysis of Canadian Medical Protective Association data from 1993 to 2017

BACKGROUND: Medico-legal data show opportunities to improve safe medical care; little is published on the experience of physicians-in-training with medical malpractice. The purpose of this study was to examine closed civil legal cases involving physicians-in-training over time and provide novel insights on case and physicians characteristics. METHODS: We conducted a retrospective descriptive study of closed civil legal cases at the Canadian Medical Protective Association (CMPA), a mutual medico-legal defence organization for more than 105 000 physicians, representing an estimated 95% of physicians in Canada. Eligible cases involved at least 1 physician-in-training and were closed between 1993 and 2017 (for time trends) or 2008 and 2017 (for descriptive analyses). We analyzed case rates over time using Poisson regression and the annualized change rate. Descriptive analyses addressed case duration, medico-legal outcome and patient harm. We explored physician specialties and practice characteristics in a subset of cases. RESULTS: Over a 25-year period (1993-2017), 4921 physicians-in-training were named in 2951 closed civil legal cases, and case rates decreased significantly (β = -0.04, 95% confidence interval -0.05 to -0.03, where β was the 1-year difference in log case rates). The annualized change rate was -1.1% per year. Between 2008 and 2017, 1901 (4.1%) of 45 967 physicians-in-training were named in 1107 civil legal cases. Cases with physicians-in-training generally involved more severe patient harm than cases without physicians-in-training. In a subgroup with available information (n = 951), surgical specialties were named most often (n = 531, 55.8%). INTERPRETATION: The rate of civil legal cases involving physicians-in-training has diminished over time, but more recent cases featured severe patient harm and death. Efforts to promote patient safety may enhance medical care and reduce the frequency and severity of malpractice issues for physicians-in-training

PHF8 and REST/NRSF co-occupy gene promoters to regulate proximal gene expression

Chromatin regulators play an important role in the development of human diseases. In this study, we focused on Plant Homeo Domain Finger protein 8 (PHF8), a chromatin regulator that has attracted special concern recently. PHF8 is a histone lysine demethylase ubiquitously expressed in nuclei. Mutations of PHF8 are associated with X-linked mental retardation. It usually functions as a transcriptional co-activator by associating with H3K4me3 and RNA polymerase II. We found that PHF8 may associate with another regulator, REST/NRSF, predominately at promoter regions via studying several published PHF8 chromatin immunoprecipitation-sequencing (ChIP-Seq) datasets. Our analysis suggested that PHF8 not only activates but may also repress gene expression

Elucidating the Role of Prelithiation in Si-based Anodes for Interface Stabilization

Prelithiation as a facile and effective method to compensate the lithium inventory loss in the initial cycle has progressed considerably both on anode and cathode sides. However, much less research has been devoted to the prelithiation effect on the interface stabilization for long-term cycling of Si-based anodes. An in-depth quantitative analysis of the interface that forms during the prelithiation of SiOx is presented here and the results are compared with prelithiaton of Si anodes. Local structure probe combined with detailed electrochemical analysis reveals that a characteristic mosaic interface is formed on both prelithiated SiOx and Si anodes. This mosaic interface containing multiple lithium silicates phases, is fundamentally different from the solid electrolyte interface (SEI) formed without prelithiation. The ideal conductivity and mechanical properties of lithium silicates enable improved cycling stability of both prelithiated anodes. With a higher ratio of lithium silicates due to the oxygen participation, prelithiated SiO1.3 anode improves the initial coulombic efficiency to 94% in full cell and delivers good cycling retention (77%) after 200 cycles. The insights provided in this work can be used to further optimize high Si loading (>70% by weight) based anodes in future high energy density batteries

MethylPurify: tumor purity deconvolution and differential methylation detection from single tumor DNA methylomes

We propose a statistical algorithm MethylPurify that uses regions with bisulfite reads showing discordant methylation levels to infer tumor purity from tumor samples alone. MethylPurify can identify differentially methylated regions (DMRs) from individual tumor methylome samples, without genomic variation information or prior knowledge from other datasets. In simulations with mixed bisulfite reads from cancer and normal cell lines, MethylPurify correctly inferred tumor purity and identified over 96% of the DMRs. From patient data, MethylPurify gave satisfactory DMR calls from tumor methylome samples alone, and revealed potential missed DMRs by tumor to normal comparison due to tumor heterogeneity. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0419-x) contains supplementary material, which is available to authorized users

An alternative approach to measuring treatment persistence with antipsychotic agents among patients with schizophrenia in the Veterans Health Administration

Prior studies have demonstrated the importance of treatment persistence with anti-psychotic agents in sustaining control of schizophrenic symptoms. However, the conventional approach in measuring treatment persistence tended to use only the first prescription episode even though some patients received multiple prescriptions (or multiple treatment episodes) of the same medication within one year following the initiation of the index drug. In this study, we used data from the Veterans Health Administration in the United States to assess the extent to which patients received multiple prescriptions. The study found that about a quarter of the patients had two or more treatment episodes and that levels of treatment persistence tended to vary across treatment episodes. Based on these results, we offered an alternative approach in which we calculated treatment persistence with typical and atypical antipsychotic agents separately for patients with one, two, or three treatment episodes. Considering that patients with different number of treatment episodes might differ in disease profiles, this treatment episode-specific approach offered a fair comparison of the levels of treatment persistence across patients with different number of treatment episodes. Future research needs to extend the analyses beyond two antipsychotic classes to individual antipsychotic agents. A more comprehensive assessment using appropriate analytic methods should help physicians make prescription choices that will ultimately improve the care of patients with schizophrenia

The role of Glial cell derived neurotrophic factor in head and neck cancer

Glial cell-derived neurotrophic factor (GDNF) is reported to promote the survival of neurons and salivary gland regeneration after radiation damage. This study investigated the effect of GDNF on cell migration, growth, and response to radiation in preclinical models of head and neck squamous cell carcinoma (HNSCC) and correlated GDNF expression to treatment outcomes in HNSCC patients. Our ultimate goal is to determine whether systemic administration of GDNF at high dose is safe for the management of hyposalivation or xerostomia in HNSCC patients. Three HPV-positive and three HPV-negative cell lines were examined for cell migration, growth, and clonogenic survival in vitro and tumor growth assay in vivo. Immunohistochemical staining of GDNF, its receptors GFRα1 and its co-receptor RET was performed on two independent HNSCC tissue microarrays (TMA) and correlated to treatment outcomes. Results showed that GDNF only enhanced cell migration in two HPV-positive cells at supra-physiologic doses, but not in HPV-negative cells. GDNF did not increase cell survival in the tested cell lines post-irradiation. Likewise, GDNF treatment affected neither tumor growth in vitro nor response to radiation in xenografts in two HPV-positive and two HPV-negative HNSCC models. High stromal expression of GDNF protein was associated with worse overall survival in HPV-negative HNSCC on multivariate analysis in a combined cohort of patients from Stanford University (n = 82) and Washington University (n = 189); however, the association between GDNF gene expression and worse survival was not confirmed in a separate group of HPV-negative HNSCC patients identified from the Cancer Genome Atlas (TCGA) database. Based on these data, we do not believe that GNDF is a safe systemic treatment to prevent or treat xerostomia in HNSCC and a local delivery approach such as intraglandular injection needs to be explored