Biology subjects

Schiffman, J.

Publications and source records attributed to Schiffman, J..

5 recordsLinked to original sources

bioRxiv2025

Longitudinal Trajectories of Cognition and Neural Metrics as Predictors of Persistent Distressing Psychotic-Like Experiences Across Middle Childhood and Early Adolescence

ObjectivesPsychotic-like experiences (PLEs) may arise from genetic and environmental risk leading to worsening cognitive and neural metrics over time, which in turn lead to worsening PLEs. Persistence and distress are factors that distinguish more clinically significant PLEs. Analyses used three waves of unique longitudinal Adolescent Brain Cognitive Development Study data (ages 9-13) to test whether changes in cognition and structural neural metrics attenuate associations between genetic and environmental risk with persistent distressing PLEs. MethodsMultigroup univariate latent growth models examined three waves of cognitive metrics and global structural neural metrics separately for three PLE groups: persistent distressing PLEs (n=356), transient distressing PLEs (n=408), and low-level PLEs (n=7901). Models then examined whether changes in cognitive and structural neural metrics over time attenuated associations between genetic liability (i.e., schizophrenia polygenic risk scores/family history) or environmental risk scores (e.g., poverty) and PLE groups. ResultsPersistent distressing PLEs showed greater decreases (i.e., more negative slopes) of cognition and neural metrics over time compared to those in low-level PLE groups. Associations between environmental risk and persistent distressing PLEs were attenuated when accounting for lowered scores over time on cognitive (e.g., picture vocabulary) and to a lesser extent neural (e.g., cortical thickness, volume) metrics. ConclusionsAnalyses provide novel evidence for extant theories that worsening cognition and global structural metrics may partially account for associations between environmental risk with persistent distressing PLEs.

neuroscience↗

bioRxiv2023

Germline mutation rate predicts cancer mortality across 37 vertebrate species

The explanation for why some species are more susceptible to cancer than others remains an area of intense investigation. Cancer evolves in part through the accumulation of mutations and, therefore, we hypothesized that germline mutation rates would be associated with cancer prevalence and mortality across species. We collected previously published data on germline mutation rate and cancer mortality data for 37 vertebrate species. Germline mutation rate was positively correlated with cancer mortality (P = 0.008). Why animals with increased germline mutation rates die more from cancer remains an open question, however they may benefit from close monitoring for tumors due to hereditary cancer predisposition syndromes. Early diagnoses of cancer in these species may increase their chances of treatment and overall survival.

cancer biology↗

bioRxiv2023

Cancer Prevalence Across Vertebrates

Cancer is pervasive across multicellular species, but what explains differences in cancer prevalence across species? Using 16,049 necropsy records for 292 species spanning three clades (amphibians, sauropsids and mammals) we found that neoplasia and malignancy prevalence increases with adult weight (contrary to Petos Paradox) and somatic mutation rate, but decreases with gestation time. Evolution of cancer susceptibility appears to have undergone sudden shifts followed by stabilizing selection. Outliers for neoplasia prevalence include the common porpoise (<1.3%), the Rodrigues fruit bat (<1.6%) the black-footed penguin (<0.4%), ferrets (63%) and opossums (35%). Discovering why some species have particularly high or low levels of cancer may lead to a better understanding of cancer syndromes and novel strategies for the management and prevention of cancer. Statement of SignificanceEvolution has discovered mechanisms for suppressing cancer in a wide variety of species. By analyzing veterinary necropsy records we can identify species with exceptionally high or low cancer prevalence. Discovering the mechanisms of cancer susceptibility and resistance may help improve cancer prevention and explain cancer syndromes.

cancer biology↗

bioRxiv2018

Dynamics of the p53 response to ionizing and ultraviolet radiation

The tumor suppressor protein p53 compiles information about cellular stressors to make decisions on whether the cell should survive or undergo apoptosis. However, the p53 response depends on the source of damage, displaying a digital oscillatory response after ionizing radiation (IR) damage and a proportional non-oscillatory response following UV damage. We propose a mathematical model that qualitatively replicates this observed behavior. The difference in p53 dynamics in the model results from two mechanisms: IR damage is fully detected minutes after exposure while UV damage is detected over several hours; and the p53-controlled transcriptional response is dominated by inactive p53 following UV damage. In particular, we hypothesize that an unidentified positive feedback loop controlled by inactive p53 is required to maintain the qualitative high p53 response to UV damage. This work proposes an explanation for two distinct responses of p53 to DNA damage and how each response can lead to cell cycle arrest or apoptosis.\n\nAuthor summaryWe propose a mathematical model hypothesizing how the tumor suppressor protein p53 produces two contrasting dynamical responses in response to different types of DNA damage. In particular, we predict the existence of a positive feedback loop controlled by the inactive form of p53, which allows the cell to respond to slowly detected damage. The existence of differing dynamic responses by p53 has implications for our understanding of tumor development and possibly p53-related therapeutic strategies.

cancer biology↗

bioRxiv2018

Cross-Platform Mechanical Characterization of Lung Tissue

Published data on the mechanical strength and elasticity of lung tissue is widely variable, primarily due to differences in how testing was conducted across individual studies. This makes it extremely difficult to find a benchmark modulus of lung tissue when designing synthetic extracellular matrices (ECMs). To address this issue, we tested tissues from various areas of the lung using multiple characterization techniques, including micro-indentation, small amplitude oscillatory shear (SAOS), uniaxial tension, and cavitation rheology. We report the sample preparation required and data obtainable across these unique but complimentary methods to quantify the modulus of lung tissue. We highlight cavitation rheology as a new method, which can measure the modulus of intact tissue with precise spatial control, and reports a modulus on the length scale of typical tissue heterogeneities. Shear rheology, uniaxial, and indentation testing require heavy sample manipulation and destruction; however, cavitation rheology can be performed in situ across nearly all areas of the lung with minimal preparation. The Youngs modulus of bulk lung tissue using microindentation (1.9{+/-}0.5 kPa), SAOS (3.2{+/-}0.6 kPa), uniaxial testing (3.4{+/-}0.4 kPa), and cavitation rheology (6.1{+/-}1.6 kPa) were within the same order of magnitude, with higher values consistently reported from cavitation, likely due to our ability to keep the tissue intact. Although cavitation rheology does not capture the non-linear strains revealed by uniaxial testing and SAOS, it provides an opportunity to measure mechanical characteristics of lung tissue on a microscale level on intact tissues. Overall, our study demonstrates that each technique has independent benefits, and each technique revealed unique mechanical features of lung tissue that can contribute to a deeper understanding of lung tissue mechanics.

bioengineering↗