Gut Analysis Toolbox: Automating quantitative analysis of enteric neurons.

The enteric nervous system (ENS) consists of an extensive network of neurons and glial cells embedded within the wall of the gastrointestinal (GI) tract. Alterations in neuronal distribution and function are strongly associated with GI dysfunction. Current methods for assessing neuronal distribution suffer from undersampling, partly due to challenges associated with imaging and analyzing large tissue areas, and operator bias due to manual analysis. We present the Gut Analysis Toolbox (GAT), an image analysis tool designed for characterization of enteric neurons and their neurochemical coding using 2D images of GI wholemount preparations. It is developed in Fiji, has a user-friendly interface and offers rapid and accurate segmentation via custom deep learning (DL) based cell segmentation models developed using StarDist, and a ganglion segmentation model in deepImageJ. We use proximal neighbor-based spatial analysis to reveal differences in cellular distribution across gut regions using a public dataset. In summary, GAT provides an easy-to-use toolbox to streamline routine image analysis tasks in ENS research. GAT enhances throughput allowing unbiased analysis of larger tissue areas, multiple neuronal markers and numerous samples rapidly.

Rigorous Characterization of Allosteric Modulation of the Human Metabotropic Glutamate Receptor 1 Reveals Probe- and Assay-Dependent Pharmacology.

Allosteric modulation of metabotropic glutamate receptor subtype 1 (mGlu1) represents a viable therapeutic target for treating numerous central nervous system disorders. Although multiple chemically distinct mGlu1 positive (PAMs) and negative (NAMs) allosteric modulators have been identified, drug discovery paradigms have not included rigorous pharmacological analysis. In the present study, we hypothesized that existing mGlu1 allosteric modulators possess unappreciated probe-dependent or biased pharmacology. Using human embryonic kidney 293 (HEK293A) cells stably expressing human mGlu1, we screened mGlu1 PAMs and NAMs from divergent chemical scaffolds for modulation of different mGlu1 orthosteric agonists in intracellular calcium (iCa2+) mobilization and inositol monophosphate (IP1) accumulation assays. Operational models of agonism and allosterism were used to derive estimates for important pharmacological parameters such as affinity, efficacy, and cooperativity. Modulation of glutamate and quisqualate-mediated iCa2+ mobilization revealed probe dependence at the level of affinity and cooperativity for both mGlu1 PAMs and NAMs. We also identified the previously described mGlu5 selective NAM PF-06462894 as an mGlu1 NAM with a different pharmacological profile from other NAMs. Differential profiles were also observed when comparing ligand pharmacology between iCa2+ mobilization and IP1 accumulation. The PAMs Ro67-4853 and CPPHA displayed apparent negative cooperativity for modulation of quisqualate affinity, and the NAMs CPCCOEt and PF-06462894 had a marked reduction in cooperativity with quisqualate in IP1 accumulation and upon extended incubation in iCa2+ mobilization assays. These data highlight the importance of rigorous assessment of mGlu1 modulator pharmacology to inform future drug discovery programs for mGlu1 allosteric modulators. SIGNIFICANCE STATEMENT: Metabotropic glutamate receptor subtype 1 (mGlu1) positive and negative allosteric modulators have therapeutic potential in multiple central nervous system disorders. We show that chemically distinct modulators display differential pharmacology with different orthosteric ligands and across divergent signaling pathways at human mGlu1. Such complexities in allosteric ligand pharmacology should be considered in future mGlu1 allosteric drug discovery programs.

Beta-blockade enhances anthracycline control of metastasis in triple-negative breast cancer.

Beta-adrenergic blockade has been associated with improved cancer survival in patients with triple-negative breast cancer (TNBC), but the mechanisms of these effects remain unclear. In clinical epidemiological analyses, we identified a relationship between beta-blocker use and anthracycline chemotherapy in protecting against TNBC progression, disease recurrence, and mortality. We recapitulated the effect of beta-blockade on anthracycline efficacy in xenograft mouse models of TNBC. In metastatic 4T1.2 and MDA-MB-231 mouse models of TNBC, beta-blockade improved the efficacy of the anthracycline doxorubicin by reducing metastatic development. We found that anthracycline chemotherapy alone, in the absence of beta-blockade, increased sympathetic nerve fiber activity and norepinephrine concentration in mammary tumors through the induction of nerve growth factor (NGF) by tumor cells. Moreover, using preclinical models and clinical samples, we found that anthracycline chemotherapy up-regulated ß2-adrenoceptor expression and amplified receptor signaling in tumor cells. Neurotoxin inhibition of sympathetic neural signaling in mammary tumors using 6-hydroxydopamine or genetic deletion of NGF or ß2-adrenoceptor in tumor cells enhanced the therapeutic effect of anthracycline chemotherapy by reducing metastasis in xenograft mouse models. These findings reveal a neuromodulatory effect of anthracycline chemotherapy that undermines its potential therapeutic impact, which can be overcome by inhibiting ß2-adrenergic signaling in the tumor microenvironment. Supplementing anthracycline chemotherapy with adjunctive ß2-adrenergic antagonists represents a potential therapeutic strategy for enhancing the clinical management of TNBC.

Application of the probability-based Maryland Biological Stream Survey to the state's assessment of water quality standards.

The Clean Water Act presents a daunting task for states by requiring them to assess and restore all their waters. Traditional monitoring has led to two beliefs: (1) ad hoc sampling (i.e., non-random) is adequate if enough sites are sampled and (2) more intensive sampling (e.g., collecting more organisms) at each site is always better. We analyzed the 1,500 Maryland Biological Stream Survey (MBSS) random sites sampled in 2000-2004 to describe the variability of Index of Biotic Integrity (IBI) scores at the site, reach, and watershed scales. Average variability for fish and benthic IBI scores increased with increasing spatial scale, demonstrating that single site IBI scores are not representative at watershed scales and therefore at best 25% of a state's stream length can be representatively sampled with non-random designs. We evaluated the effects on total taxa captured and IBI precision of sampling for twice as many benthic macroinvertebrates at 73 MBSS sites with replicate samples. When sampling costs were fixed, the precision of the IBI decreased as the number of sites had to be reduced by 15%. Only 1% more taxa were found overall when the 73 sites where combined. We concluded that (1) comprehensive assessment of a state's waters should be done using probability-based sampling that allows the condition across all reaches to be inferred statistically and (2) additional site sampling effort should not be incorporated into state biomonitoring when it will reduce the number of sites sampled to the point where overall assessment precision is lower.

MicroTrack: an algorithm for concurrent projectome and microstructure estimation.

This paper presents MicroTrack, an algorithm that combines global tractography and direct microstructure estimation using diffusion-weighted imaging data. Previous work recovers connectivity via tractography independently from estimating microstructure features, such as axon diameter distribution and density. However, the two estimates have great potential to inform one another given the common assumption that microstructural features remain consistent along fibers. Here we provide a preliminary examination of this hypothesis. We adapt a global tractography algorithm to associate axon diameter with each putative pathway and optimize both the set of pathways and their microstructural parameters to find the best fit of this holistic white-matter model to the MRI data. We demonstrate in simulation that, with a multi-shell HARDI acquisition, this approach not only improves estimates of microstructural parameters over voxel-by-voxel estimation, but provides a solution to long standing problems in tractography. In particular, a simple experiment demonstrates the resolution of the well known ambiguity between crossing and kissing fibers. The results strongly motivate further development of this kind of algorithm for brain connectivity mapping.