Restriction spectrum imaging (RSI) decomposes the diffusion-weighted MRI signal into separate components of known apparent diffusion coefficients (ADCs). The number of diffusion components and optimal ADCs for RSI are organ-specific and determined empirically. The purpose of this work was to determine the RSI model for breast tissues. Methods:The diffusion-weighted MRI signal was described using a linear combination of multiple exponential components. A set of ADC values was estimated to fit voxels in cancer and control ROIs. Later, the signal contributions of each diffusion component were estimated using these fixed ADC values. Relative-fitting residuals and Bayesian information criterion were assessed. Contrast-to-noise ratio between cancer and fibroglandular tissue in RSI-derived signal contribution maps was compared to DCE imaging.Results: A total of 74 women with breast cancer were scanned at 3.0 Tesla MRI.The fitting residuals of conventional ADC and Bayesian information criterion suggest that a 3-component model improves the characterization of the diffusion signal over a biexponential model. Estimated ADCs of triexponential model were

Hepatitis C virus (HCV) prevalence is high among people experiencing homelessness, but barriers to scaling up HCV testing and treatment persist. We aimed to implement onsite HCV testing and education and evaluate the effectiveness of low‐barrier linkage to HCV therapy among individuals accessing homeless shelters. HCV rapid testing was performed at four large shelters in San Francisco (SF) and Minneapolis (MN). Sociodemographic status, HCV risk, barriers to testing, and interest in therapy were captured. Participants received information about HCV. Those testing positive underwent formal HCV education and onsite therapy. Multivariable modeling assessed predictors of receipt of HCV therapy and sustained virologic response (SVR). A total of 766 clients were tested. Median age was 53.7 years, 68.2% were male participants, 46.3% were Black, 27.5% were White, 13.2% were Hispanic, and 57.7% had high school education or less; 162 (21.1%) were HCV antibody positive, 107 (66.0%) had detectable HCV RNA (82.1% with active drug use, 53.8% history of psychiatric illness), 66 (61.7%) received HCV therapy, and 81.8% achieved SVR. On multivariate analysis, shelter location (MN vs. SF, odds ratio [OR], 0.3; P = 0.01) and having a health care provider (OR, 4.1; P = 0.02) were associated with receipt of therapy. On intention to treat analysis, the only predictor of SVR when adjusted for age, sex, and race was HCV medication adherence (OR, 14.5; P = 0.01). Conclusion: Leveraging existing homeless shelter infrastructure was successful in enhancing HCV testing and treatment uptake. Despite high rates of active substance use, psychiatric illness, and suboptimal adherence, over 80% achieved HCV cure. This highlights the critical importance of integrated models in HCV elimination efforts in people experiencing homelessness that can be applied to other shelter settings.

When previous research is cited incorrectly, misinformation can infiltrate scientific discourse and undermine scholarly knowledge. One of the more damaging citation issues involves incorrectly citing article content (called quotation errors); therefore, investigating quotation accuracy is an important research endeavor. One field where quotation accuracy is needed is in the learning sciences given its impact on pedagogy. An integral article in pedagogical discussions surrounding how to teach at the college level is the meta-analysis on active learning by Freeman et al. The Freeman et al. meta-analysis compared active learning to traditional lecture in terms of its effects on student learning and has been important in national initiatives on STEM (science, technology, engineering, and mathematics) reform. Given its influence coupled with the impact quotation errors could have in scientific discourse, we used citation context analysis to analyze whether assertions in the citing text that related to the efficacy of lecture and active learning were supported by what was explicitly stated in the cited meta-analysis. Assertions were analyzed undersupported, unsupported, or irrelevant for purposes of study categories. The most prevalent supported category related to active learning being more effective than lecture; the most prevalent unsupported category related to the effectiveness of specific activities/approaches other than the general approach of active learning. Overall, the percentage of supported assertions was 47.67%, and the percentage of unsupported assertions was 26.01%. Furthermore, the percentage of articles containing at least one unsupported assertion was 34.77%. Proactive measures are needed to reduce the incidence of quotation errors to ensure robust scientific integrity.