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The objective of the current review was to synthesize the literature on intersectionality relative to disparities across the cancer care continuum. A model to support future intersectional cancer research was proposed.Web-based discovery services and discipline-specific databases were queried for both peer-reviewed and gray literature. Study screening and data extraction were facilitated through the Covidence software platform.Among 497 screened studies, 28 met study inclusion criteria. Most articles were peer-reviewed empirical studies (n = 22) that focused on pre-diagnosis/screening (n = 19) and included marginalized racial/ethnic (n = 22) identities. Pre-cancer diagnosis, sexual orientation and race influenced women's screening and vaccine behaviors. Sexual minority women, particularly individuals of color, were less likely to engage in cancer prevention behaviors prior to diagnosis. Race and socioeconomic status (SES) were important factors in patient care/survivorship with worse outcomes among non-white women of low SES. Emergent themes in qualitative results emphasized the importance of patient intersectional identities, as well as feelings of marginalization, fears of discrimination, and general discomfort with providers as barriers to seeking cancer care.Patients with intersectional identities often experience barriers to cancer care that adversely impact screening, diagnosis, treatment, as well as survivorship. The use of an "intersectional lens" as a future clinical and research framework will facilitate a more multidimensional and holistic approach to the care of cancer patients.

Accurately predicting post-critical heat flux (CHF) heat transfer is an important but challenging task in water-cooled reactor design and safety analysis. Although numerous heat transfer correlations have been developed to predict post-CHF heat transfer, these correlations are only applicable to relatively narrow ranges of flow conditions due to the complex physical nature of the post-CHF heat transfer regimes. In this paper, a large quantity of experimental data is collected and summarized from the literature for steady-state subcooled and low-quality film boiling regimes with water as the working fluid in vertical tubular test sections. A low-quality water film boiling (LWFB) database is consolidated with a total of 22,813 experimental data points, which cover a wide flow range of the system pressure from 0.1 to 9.0 MPa, mass flux from 25 to 2750 kg/m2 s, and inlet subcooling from 1 to 70 °C. Two machine learning (ML) models, based on random forest (RF) and gradient boosted decision tree (GBDT), are trained and validated to predict wall temperatures in post-CHF flow regimes. The trained ML models demonstrate significantly improved accuracies compared to conventional empirical correlations. To further evaluate the performance of these two ML models from a statistical perspective, three criteria are investigated and three metrics are calculated to quantitatively assess the accuracy of these two ML models. For the full LWFB database, the root-mean-square errors between the measured and predicted wall temperatures by the GBDT and RF models are 5.7% and 6.2%, respectively, confirming the accuracy of the two ML models.

The purpose of this study was to examine whether certain types of leaders were associated with the degree to which local health departments (LHDs) generate and use evidence to inform their service offering.Pooled, cross-sectional analysis using 4 waves (2010, 2013, 2016, and 2019) of the National Profiles of Local Health Departments sponsored by the National Association of County and City Health Officials (NACCHO). Univariate analysis was used to assess the extent to which LHDs were generating and using evidence to improve the health of their local communities and whether this changed over time. Multinomial logistic regression models were used to examine the relationships between LHD leader attributes and the extent to which LHDs were generating and using evidence.Between 1496 and 2087 (varied by survey round) LHDs from throughout the United States.Two outcome variables pertaining to the generation of evidence: (1) how recently an LHD completed a community health assessment and (2) how recently an LHD completed a community health improvement plan. A third outcome variable reflected how extensively an LHD used the Community Guide, a compendium of evidence-based findings.In 2010, 25.1% and 41.4% of all LHDs had not completed a community health assessment or a community health improvement plan, respectively; by 2019, those figures declined significantly to 14.6% and 24.7%. Similarly, in 2010, 61.7% of all LHDs were not using the Community Guide; by 2019, that percentage declined significantly to 42.5%. Multivariable analysis revealed that leader experience was a more robust correlate of evidence generation and use by LHDs than leader education.While LHDs' generation and use of evidence have grown over the past decade, there is room for improvement. Local health department leader attributes-education and experience-highlight targeted opportunities to fill gaps in the use of evidence-based public health practices.

Background Biomechanical muscle stiffness has been linked to musculoskeletal disorders. Assessing changes in muscle stiffness following DN may help elucidate a physiologic mechanism of DN. This study characterizes the effects of dry needling (DN) to the infraspinatus, erector spinae, and gastrocnemius muscles on biomechanical muscle stiffness. Method 60 healthy participants were randomized into infraspinatus, erector spinae, or gastrocnemius groups. One session of DN was applied to the muscle in standardized location. Stiffness was assessed using a MyotonPRO at baseline, immediately post DN, and 24 h later. The presence of a localized twitch response (LTR) during DN was used to subgroup participants. Results A statistically significant decrease in stiffness was observed in the gastrocnemius, the LTR gastrocnemius, and the LTR erector spinae group immediately following DN treatment. However, stiffness increased after 24 h. No significant change was found in the infraspinatus group. Conclusions DN may cause an immediate, yet transitory change in local muscle stiffness. It is unknown whether these effects are present in a symptomatic population or related to improvements in clinical outcomes. Future studies are necessary to determine if a decrease in biomechanical stiffness is related to improvement in symptomatic individuals.

[Image: see text] The selectivity of histone deacetylase inhibitors (HDACis) is greatly impacted by the zinc binding groups. In an effort to search for novel zinc binding groups, we applied a parallel medicinal chemistry (PMC) strategy to quickly synthesize substituted benzamide libraries. We discovered a series containing 2-substituted benzamides as the zinc binding group which afforded highly selective and potent HDAC3 inhibitors, exemplified by compound 16 with a 2-methylthiobenzamide. Compound 16 inhibited HDAC3 with an IC(50) of 30 nM and with unprecedented selectivity of >300-fold over all other HDAC isoforms. Interestingly, a subtle change of the 2-methylthio to a 2-hydroxy benzamide in 20 retains HDAC3 potency but loses all selectivity over HDAC 1 and 2. This significant difference in selectivity was rationalized by X-ray crystal structures of HDACis 16 and 20 bound to HDAC2, revealing different binding modes to the catalytic zinc ion. This series of HDAC3 selective inhibitors served as tool compounds for investigating the minimal set of HDAC isoforms that must be inhibited for the HIV latency activation in a Jurkat 2C4 cell model and potentially as leads for selective HDAC3 inhibitors for other indications.

Data augmentation (DA) turns seemingly intractable computational problems into simple ones by augmenting latent missing data. In addition to computational simplicity, it is now well-established that DA equipped with a deterministic transformation can improve the convergence speed of iterative algorithms such as an EM algorithm or Gibbs sampler. In this article, we outline a framework for the transformation-based DA, which we call data transforming augmentation (DTA), allowing augmented data to be a deterministic function of latent and observed data, and unknown parameters. Under this framework, we investigate a novel DTA scheme that turns heteroscedastic models into homoscedastic ones to take advantage of simpler computations typically available in homoscedastic cases. Applying this DTA scheme to fitting linear mixed models, we demonstrate simpler computations and faster convergence rates of resulting iterative algorithms, compared with those under a non-transformation-based DA scheme. We also fit a Beta-Binomial model using the proposed DTA scheme, which enables sampling approximate marginal posterior distributions that are available only under homoscedasticity. An R package, Rdta, is publicly available at CRAN.

361 Background: TRK-950 is a first-in-class humanized antibody raised against CAPRIN-1 which we have identified as a novel and universal target for cancer therapies. TRK-950 strongly and specifically binds to various cancer cells and shows anti-tumor effects via engagement of immune cells. A series of pre-clinical studies demonstrates its potency and safety. In the phase I study of TRK-950 monotherapy (NCT02990481), it appears safe and well tolerated. No DLT was observed and MTD was not reached at doses of 3-30mg/kg IV weekly. Here, we report on select cohort of the ongoing, multicenter phase Ib study of TRK-950 combined with standard of care (SOC) regimens in patients (pts) with gastric cancer including GEJ cancer (NCT03872947). Methods: Patients with gastric or gastro-esophageal junction (GEJ) cancer and measurable disease were enrolled in phase Ib study, and received paclitaxel on D1, 8, 15 and ramucirumab on D1, 15 of 28-day cycles. In addition TRK-950 was given 10 mg/kg IV weekly. DLT was evaluated during the first cycle. Response was assessed every 2 cycles up to Cycle 6 and every 3 cycles thereafter. Primary endpoint was safety and tolerability. Secondary endpoints included overall response rate (ORR), disease control rate (DCR) per REClST v1.1. Tumor CAPRIN-1 expression was retrospectively assessed by IHC. Results: Nine patients were enrolled, median age 58 yrs; Karnofsky performance status 80 (11%), 90 (67%), 100 (22%); 89% male, 11% female; median number of prior treatments 2 [1, 4]. TRK-950 in combination with ramucirumab and paclitaxel was well tolerated with no DLTs. Most common all-grade treatment-related AEs (TRAEs) were fatigue (67%), vomiting (33%), anemia (22%), nausea (22%), diarrhea (22%), neutrophil count decreased (22%) and decreased appetite (22%). Most common grade ≥ 3 TRAE in ≥ 20% of pts were anemia (22%) and neutrophil count decreased (22%). In 9 response-evaluable pts, ORR was 55.6% and DCR was 100%. Four patients had a screening CAPRIN-1 score of 3+, and all achieved partial response. Conclusions: TRK-950 binds to a newly described target, CAPRIN-1, and has an acceptable safety and tolerability profile when combined with ramucirumab and paclitaxel in gastric cancer including GEJ cancer. Preliminary clinical activity is demonstrated in pre-treated patients with encouraging response rates, particularly enriched by the expression of CAPRIN-1. Further antitumor activity is being confirmed by limiting patients to only 1 prior treatment regimen with an eye towards a randomized trial. Clinical trial information: NCT03872947 .