Molecular subtypes of ALS are associated with differences in patient prognosis.

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease with poorly understood clinical heterogeneity, underscored by significant differences in patient age at onset, symptom progression, therapeutic response, disease duration, and comorbidity presentation. We perform a patient stratification analysis to better understand the variability in ALS pathology, utilizing postmortem frontal and motor cortex transcriptomes derived from 208 patients. Building on the emerging role of transposable element (TE) expression in ALS, we consider locus-specific TEs as distinct molecular features during stratification. Here, we identify three unique molecular subtypes in this ALS cohort, with significant differences in patient survival. These results suggest independent disease mechanisms drive some of the clinical heterogeneity in ALS.

Automated microscope-independent fluorescence-guided micropipette.

Glass micropipette electrodes are commonly used to provide high resolution recordings of neurons. Although it is the gold standard for single cell recordings, it is highly dependent on the skill of the electrophysiologist. Here, we demonstrate a method of guiding micropipette electrodes to neurons by collecting fluorescence at the aperture, using an intra-electrode tapered optical fiber. The use of a tapered fiber for excitation and collection of fluorescence at the micropipette tip couples the feedback mechanism directly to the distance between the target and electrode. In this study, intra-electrode tapered optical fibers provide a targeted robotic approach to labeled neurons that is independent of microscopy.

A Metabolomic Approach for Predicting Diurnal Changes in Cortisol.

Introduction: The dysregulation of cortisol secretion has been associated with a number of mental health and mood disorders. However, diagnostics for mental health and mood disorders are behavioral and lack biological contexts. Objectives: The goal of this work is to identify volatile metabolites capable of predicting changes in total urinary cortisol across the diurnal cycle for long-term stress monitoring in psychological disorders. Methods: We applied comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry to sample the urinary volatile metabolome using an untargeted approach across three time points in a single day for 60 subjects. Results: The finalized multiple regression model includes 14 volatile metabolites and 7 interaction terms. A review of the selected metabolites suggests pyrrole, 6-methyl-5-hepten-2-one and 1-iodo-2-methylundecane may originate from endogenous metabolic mechanisms influenced by glucocorticoid signaling mechanisms. Conclusion: This analysis demonstrated the feasibility of using specific volatile metabolites for the prediction of secreted cortisol across time.

Monitoring changes in the healthy female metabolome across the menstrual cycle using GC × GC-TOFMS.

Urinary metabolomics offers a non-invasive means of obtaining information about the system-wide biological health of a patient. Untargeted metabolomics approaches using one-dimensional gas chromatography (GC) are limited due to the chemical complexity of urine, which poorly detects co-eluting low-abundance analytes. Metabolite detection and identification can be improved by applying comprehensive two-dimensional GC, allowing for the discovery of additional viable biomarkers of disease. In this work, we applied comprehensive two-dimensional GC coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) to the analysis of urine samples collected daily across 28-days from 10 healthy female subjects for a personalized approach to female reproductive health monitoring. Through this analysis, we identified 935 unique volatile metabolites. Two statistical methods, a modified T-statistic and Wilcoxon Rank Sum, were applied to analyze differences in metabolome abundance on ovulation days as compared to non-ovulation days. Four metabolites (2-pentanone, 3-penten-2-one, carbon disulfide, acetone) were identified as statistically significant by the modified T-statistic but not the Rank Sum, after a false-discovery rate of 0.1 was set using a Benjamini-Hochberg correction. Subsequent analyses by boxplot indicated that the putative volatile metabolic biomarkers for fertility are expressed in increased or decreased abundance in urine on the day of ovulation. Individual analysis of metabolome expression across 28-days revealed some subject-specific features, which suggest a potential for long-term, personalized fertility monitoring using metabolomics.

Photoacoustic Flow System for the Detection of Ovarian Circulating Tumor Cells Utilizing Copper Sulfide Nanoparticles.

The development of cell-specific photoacoustic (PA) contrast agents within systems of fluidic flow provides opportunities for the accurate detection of early stage cancer metastasis. Despite the promise of exogenous contrast agents for use in clinical settings, applications are currently limited by both material biocompatibility and target specificity. In this study, folic acid functionalized copper sulfide nanoparticles (FA-CuS NPs) are synthesized to enable ovarian-cancer-specific binding and PA detection in a custom flow system. Folate receptors, known to be overexpressed on the surface of ovarian cancer cells, have remained an ideal candidate for specific targeting through functionalization on nanoparticles and other contrast agents. In combination with copper sulfide nanoparticles' strong absorbance in the near-infrared (NIR), these FA-CuS NPs are an ideal contrast agent capable of being detected by photoacoustic flow cytometry. For the first time, this study shows a potential PA contrast agent to accurately identify ovarian circulating tumor cells in flow.