Cerebrospinal fluid penetration of the colony-stimulating factor-1 receptor (CSF-1R) inhibitor,pexidartinib

Pexidartinib (PLX3397) is a colony-stimulating factor-1 receptor (CSF-1R) inhibitor under clinical evaluation for potential CNS tumor treatment. This study aims to evaluate plasma pharmacokinetic parameters and estimate CNS penetrance of pexidartinib in a non-human primate (NHP) cerebrospinal fluid (CSF) reservoir model. Five male rhesus macaques, each with a previously implanted subcutaneous CSF ventricular reservoir and central venous lines, were used. NHPs received a single dose of 40 mg/kg pexidartinib (human equivalent dose of 800 mg/m2), administered orally as 200 mg tablets. Serial paired samples of blood and CSF were collected at 0–8, 24, 48, and 72 h. Pexidartinib concentrations were assayed by Integrated Analytical Solutions, Inc. (Berkeley, CA, USA) using HPLC/MS/MS. Pharmacokinetic (PK) analysis was performed using noncompartmental methods. Samples from four NHPs were evaluable. Average (± SD) plasma PK parameters were as follows: Cmax = 16.50 (± 6.67) μg/mL; Tmax = 5.00 (± 2.58) h; AUClast = 250.25 (± 103.76) h*μg/mL; CL = 0.18 (± 0.10) L/h/kg. In CSF, pexidartinib was either quantifiable (n = 2), with Cmax values of 16.1 and 10.1 ng/mL achieved 2–4 h after plasma Tmax, or undetected at all time points (n = 2, LLOQCSF = 5 ng/mL). Pexidartinib was well-tolerated in NHPs, with no Grade 3 or Grade 4 toxicities. The CSF penetration of pexidartinib after single-dose oral administration to NHPs was limited.     

Mechanisms of vascular dysfunction in the interleukin-10–deficient murine model of preeclampsia indicate nitric oxide dysregulation

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Artificial Neural Networks as a Way to Predict Future Kidney Cancer Incidence in the United States

IntroductionThe incidence of kidney cancer is increasing; it could be counteracted with new ways to predict and detect it. We aimed to implement an artificial neural network in order to predict new cases of renal-cell carcinoma (RCC) in the population using population rate, obesity, smoking incidence, uncontrolled hypertension, and life expectancy data in the United States.Patients and MethodsStatistics were collected on US population numbers, life expectancy, obesity, smoking, and hypertension. We used MATLAB R2018 (MathWorks) software to implement an artificial neural network. Data were repeatedly and randomly divided into training (70%) and validation (30%) subsets.ResultsThe number of new RCC cases will grow from 44,400 (2020) to 55,400 (2050), an increase of +24.7%. Our data show that preventing hypertension would have the greatest impact on reduction of the incidence, estimated at ?775 and ?575 cases per year in 2020 and in 2030, respectively. The prevention of obesity and smoking would have a more limited impact, estimated at ?64 and ?180 cases per year in 2020 and in 2030, respectively, for obesity, and ?173 and ?21 cases per year in 2020 and in 2030, respectively, for smoking.ConclusionsOur predictions underline the need for accurate studies on RCC-related risk factors to reduce the incidence.     

SEOM clinical guideline thyroid cancer (2019)

Clinical and Translational Oncology - Thyroid carcinoma is the most frequent endocrine malignancy and accounts for around 3% of global cancer incidence. Different histologies and clinical scenarios...     

Neuroanatomy of dyslexia: An allometric approach

Despite evidence for a difference in total brain volume between dyslexic and good readers, no previous neuroimaging study examined differences in allometric scaling (i.e. differences in the relationship between regional and total brain volumes) between dyslexic and good readers. The present study aims to fill this gap by testing differences in allometric scaling and regional brain volume differences in dyslexic and good readers. Object‐based morphometry analysis was used to determine grey and white matter volumes of the four lobes, the cerebellum and limbic structures in 130 dyslexic and 106 good readers aged 8–14 years. Data were collected across three countries (France, Poland and Germany). Three methodological approaches were used as follows: principal component analysis (PCA), linear regression and multiple‐group confirmatory factor analysis (MGCFA). Difference in total brain volume between good and dyslexic readers was Cohen's d = 0.39. We found no difference in allometric scaling, nor in regional brain volume between dyslexic and good readers. Results of our three methodological approaches (PCA, linear regression and MGCFA) were consistent. This study provides evidence for total brain volume differences between dyslexic and control children, but no evidence for differences in the volumes of the four lobes, the cerebellum or limbic structures, once allometry is taken into account. It also finds no evidence for a difference in allometric relationships between the groups. We highlight the methodological interest of the MGCFA approach to investigate such research issues.     

An online app platform enhances collaborative medical student group learning and classroom management

Purpose: The authors presented their results in effectively using a free and widely-accessible online app platform to manage and teach a first-year pathology course at Mayo Medical School.

Methods used: The authors utilized the Google “Blogger”, “Forms”, “Flubaroo”, “Sheets”, “Docs”, and “Slides” apps to effectively build a collaborative classroom teaching and management system. Students were surveyed on the use of the app platform in the classroom, and 44 (94%) students responded.

Results: Thirty-two (73%) of the students reported that “Blogger” was an effective place for online discussion of pathology topics and questions. 43 (98%) of the students reported that the “Forms/Flubaroo” grade-reporting system was helpful. 40 (91%) of the students used the remote, collaborative features of “Slides” to create team-based learning presentations, and 39 (89%) of the students found those collaborative features helpful. “Docs” helped teaching assistants to collaboratively create study guides or grading rubrics. Overall, 41 (93%) of the students found that the app platform was helpful in establishing a collaborative, online classroom environment.

Conclusions: The online app platform allowed faculty to build an efficient and effective classroom teaching and management system. The ease of accessibility and opportunity for collaboration allowed for collaborative learning, grading, and teaching.