Impact of glioma peritumoral edema, tumor size, and tumor location on alternating electric fields (AEF) therapy in realistic 3D rat glioma models: a computational study.

Objective.Alternating electric fields (AEF) therapy is a treatment modality for patients with glioblastoma. Tumor characteristics such as size, location, and extent of peritumoral edema may affect the AEF strength and distribution. We evaluated the sensitivity of the AEFs in a realistic 3D rat glioma model with respect to these properties.Approach.The electric properties of the peritumoral edema were varied based on calculated and literature-reported values. Models with different tumor composition, size, and location were created. The resulting AEFs were evaluated in 3D rat glioma models.Main results.In all cases, a pair of 5 mm diameter electrodes induced an average field strength >1 V cm-1. The simulation results showed that a negative relationship between edema conductivity and field strength was found. As the tumor core size was increased, the average field strength increased while the fraction of the shell achieving >1.5 V cm-1decreased. Increasing peritumoral edema thickness decreased the shell's mean field strength. Compared to rostrally/caudally, shifting the tumor location laterally/medially and ventrally (with respect to the electrodes) caused higher deviation in field strength.Significance.This study identifies tumor properties that are key drivers influencing AEF strength and distribution. The findings might be potential preclinical implications.

Electric field distributions in realistic 3D rat head models during alternating electric field (AEF) therapy: a computational study.

Objective.Application of alternating electrical fields (AEFs) in the kHz range is an established treatment modality for primary and recurrent glioblastoma. Preclinical studies would enable innovations in treatment monitoring and efficacy, which could then be translated to benefit patients. We present a practical translational process converting image-based data into 3D rat head models for AEF simulations and study its sensitivity to parameter choices.Approach.Five rat head models composed of up to 7 different tissue types were created, and relative permittivity and conductivity of individual tissues obtained from the literature were assigned. Finite element analysis was used to model the AEF strength and distribution in the models with different combinations of head tissues, a virtual tumor, and an electrode pair.Main results.The simulations allowed for a sensitivity analysis of the AEF distribution with respect to different tissue combinations and tissue parameter values.Significance.For a single pair of 5 mm diameter electrodes, an average AEF strength inside the tumor exceeded 1.5 V cm-1, expected to be sufficient for a relevant therapeutic outcome. This study illustrates a robust and flexible approach for simulating AEF in different tissue types, suitable for preclinical studies in rodents and translatable to clinical use.

Current status of the preclinical evaluation of alternating electric fields as a form of cancer therapy.

Exposing cancer cells to alternating electric fields of 100-300 kHz frequency and 1-4 V/cm strength has been shown to significantly reduce cancer growth in cell culture and in human patients. This form of anti-cancer therapy is more commonly referred to as tumor treating fields (TTFields), a novel treatment modality that has been approved by the U.S. Food and Drug Administration for use in patients with glioblastoma and malignant pleural mesothelioma. Pivotal trials in other solid organ cancer trials are underway. In regards to overall survival, TTFields alone is comparable to chemotherapy alone in recurrent glioblastoma. However, when combined with adjuvant chemotherapy, TTFields prolong median survival by 4.9 months in newly-diagnosed glioblastoma. TTFields hold promise as a therapeutic approach to numerous solid organ cancers. This review summarizes the current status of TTFields research at the preclinical level, highlighting recent aspects of a relatively complex working hypothesis. In addition, we point out the gaps between limited preclinical in vivo studies and the available clinical data. To date, no customized system for TTFields delivery in rodent models of glioblastoma has been presented. We aim to motivate the expansion of TTFields preclinical research and facilitate the availability of suitable hardware, to ultimately improve outcomes in patients with cancer.

Causal relationships between metabolic-associated fatty liver disease and iron status: Two-sample Mendelian randomization.

BACKGROUND & AIMS: Dysregulated iron homeostasis plays an important role in the hepatic manifestation of metabolic-associated fatty liver disease (MAFLD). We investigated the causal effects of five iron metabolism markers, regular iron supplementation and MAFLD risk. METHODS: Genetic summary statistics were obtained from open genome-wide association study databases. Two-sample bidirectional Mendelian randomization analysis was performed to estimate the causal effect between iron status and MAFLD, including Mendelian randomization inverse-variance weighted, weighted median methods and Mendelian randomization-Egger regression. The Mendelian randomization-PRESSO outlier test, Cochran's Q test and Mendelian randomization-Egger regression were used to assess outliers, heterogeneity and pleiotropy respectively. RESULTS: Mendelian randomization inverse-variance weighted results showed that the genetically predicted per standard deviation increase in liver iron (Data set 2: odds ratio 1.193, 95% confidence interval [CI] 1.074-1.326, p = .001) was associated with an increased MAFLD risk, consistent with the weighted median estimates and Mendelian randomization-Egger regression, although Data set 1 was not significant. Mendelian randomization inverse-variance weighted analysis showed that genetically predicted MAFLD was significantly associated with increased serum ferritin levels in both datasets (Dataset 1: ß = .038, 95% CI = .014 to .062, p = .002; Dataset 2: ß = .081, 95% CI = .025 to .136, p = .004), and a similar result was observed with the weighted median methods for Dataset 2 instead of Mendelian randomization-Egger regression. CONCLUSIONS: This study uncovered genetically predicted causal associations between iron metabolism status and MAFLD. These findings underscore the need for improved guidelines for managing MAFLD risk by emphasizing hepatic iron levels as a risk factor and ferritin levels as a prognostic factor.

High-gain inverters based on WSe2 complementary field-effect transistors.

In this work, the operation of n- and p-type field-effect transistors (FETs) on the same WSe2 flake is realized,and a complementary logic inverter is demonstrated. The p-FET is fabricated by contacting WSe2 with a high work function metal, Pt, which facilities hole injection at the source contact. The n-FET is realized by utilizing selective surface charge transfer doping with potassium to form degenerately doped n+ contacts for electron injection. An ON/OFF current ratio of >10(4) is achieved for both n- and p-FETs with similar ON current densities. A dc voltage gain of >12 is measured for the complementary WSe2 inverter. This work presents an important advance toward realization of complementary logic devices based on layered chalcogenide semiconductors for electronic applications.