Faculty Bibliography

Hippocampal somatostatin-expressing (Sst) GABAergic interneurons (INs) exhibit considerable anatomical and functional heterogeneity. Recent single-cell transcriptome analyses have provided a comprehensive Sst-IN subpopulations census, a plausible molecular ground truth of neuronal identity whose links to specific functionality remain incomplete. Here, we designed an approach to identify and access subpopulations of Sst-INs based on transcriptomic features. Four mouse models based on single or combinatorial Cre- and Flp- expression differentiated functionally distinct subpopulations of CA1 hippocampal Sst-INs that largely tiled the morpho-functional parameter space of the Sst-INs superfamily. Notably, the Sst;;Tac1 intersection revealed a population of bistratified INs that preferentially synapsed onto fast-spiking interneurons (FS-INs) and were sufficient to interrupt their firing. In contrast, the Ndnf;;Nkx2-1 intersection identified a population of oriens lacunosum-moleculare INs that predominantly targeted CA1 pyramidal neurons, avoiding FS-INs. Overall, our results provide a framework to translate neuronal transcriptomic identity into discrete functional subtypes that capture the diverse specializations of hippocampal Sst-INs.

Magnetic resonance imaging (MRI) has experienced remarkable advancements in the integration of artificial intelligence (AI) for image acquisition and reconstruction. The availability of raw k-space data is crucial for training AI models in such tasks, but public MRI datasets are mostly restricted to DICOM images only. To address this limitation, the fastMRI initiative released brain and knee k-space datasets, which have since seen vigorous use. In May 2023, fastMRI was expanded to include biparametric (T2- and diffusion-weighted) prostate MRI data from a clinical population. Biparametric MRI plays a vital role in the diagnosis and management of prostate cancer. Advances in imaging methods, such as reconstructing under-sampled data from accelerated acquisitions, can improve cost-effectiveness and accessibility of prostate MRI. Raw k-space data, reconstructed images and slice, volume and exam level annotations for likelihood of prostate cancer are provided in this dataset for 47468 slices corresponding to 1560 volumes from 312 patients. This dataset facilitates AI and algorithm development for prostate image reconstruction, with the ultimate goal of enhancing prostate cancer diagnosis.

GABAergic inhibitory interneurons, originating from the embryonic ventral forebrain territories, traverse a convoluted migratory path to reach the neocortex. These interneuron precursors undergo sequential phases of tangential and radial migration before settling into specific laminae during differentiation. Here, we show that the developmental trajectory of FoxG1 expression is dynamically controlled in these interneuron precursors at critical junctures of migration. By utilizing mouse genetic strategies, we elucidate the pivotal role of precise changes in FoxG1 expression levels during interneuron specification and migration. Our findings underscore the gene dosage-dependent function of FoxG1, aligning with clinical observations of FOXG1 haploinsufficiency and duplication in syndromic forms of autism spectrum disorders. In conclusion, our results reveal the finely tuned developmental clock governing cortical interneuron development, driven by temporal dynamics and the dose-dependent actions of FoxG1.

Monitoring the coordinated signaling of dopamine (DA) and serotonin (5-HT) is important for advancing our understanding of the brain. However, the co-detection and robust quantification of these signals at low concentrations is yet to be demonstrated. Here, we present the quantification of DA and 5-HT using nano-graphitic (NG) sensors together with fast-scan cyclic voltammetry (FSCV) employing an engineered N-shape potential waveform. Our method yields 6% error in quantifying DA and 5-HT analytes present in in vitro mixtures at concentrations below 100 nM. This advance is due to the electrochemical properties of NG sensors which, in combination with the engineered FSCV waveform, provided distinguishable cyclic voltammograms (CVs) for DA and 5-HT. We also demonstrate the generalizability of the prediction model across different NG sensors, which arises from the consistent voltammetric fingerprints produced by our NG sensors. Curiously, the proposed engineered waveform also improves the distinguishability of DA and 5-HT CVs obtained from traditional carbon fiber (CF) microelectrodes. Nevertheless, this improved distinguishability of CVs obtained from CF is inferior to that of NG sensors, arising from differences in the electrochemical properties of the sensor materials. Our findings demonstrate the potential of NG sensors and our proposed FSCV waveform for future brain studies.

BACKGROUND:Hypometabolism tied to mitochondrial dysfunction occurs in the aging brain and in neurodegenerative disorders, including in Alzheimer's disease, in Down syndrome, and in mouse models of these conditions. We have previously shown that mitovesicles, small extracellular vesicles (EVs) of mitochondrial origin, are altered in content and abundance in multiple brain conditions characterized by mitochondrial dysfunction. However, given their recent discovery, it is yet to be explored what mitovesicles regulate and modify, both under physiological conditions and in the diseased brain. In this study, we investigated the effects of mitovesicles on synaptic function, and the molecular players involved. METHODS:Hippocampal slices from wild-type mice were perfused with the three known types of EVs, mitovesicles, microvesicles, or exosomes, isolated from the brain of a mouse model of Down syndrome or of a diploid control and long-term potentiation (LTP) recorded. The role of the monoamine oxidases type B (MAO-B) and type A (MAO-A) in mitovesicle-driven LTP impairments was addressed by treatment of mitovesicles with the irreversible MAO inhibitors pargyline and clorgiline prior to perfusion of the hippocampal slices. RESULTS:Mitovesicles from the brain of the Down syndrome model reduced LTP within minutes of mitovesicle addition. Mitovesicles isolated from control brains did not trigger electrophysiological effects, nor did other types of brain EVs (microvesicles and exosomes) from any genotype tested. Depleting mitovesicles of their MAO-B, but not MAO-A, activity eliminated their ability to alter LTP. CONCLUSIONS:Mitovesicle impairment of LTP is a previously undescribed paracrine-like mechanism by which EVs modulate synaptic activity, demonstrating that mitovesicles are active participants in the propagation of cellular and functional homeostatic changes in the context of neurodegenerative disorders.

Metastatic disease remains the leading cause of death due to cancer, yet the mechanism(s) of metastasis and its timely detection remain to be elucidated. Neutrophil elastase (NE), a serine protease secreted by neutrophils, is a crucial mediator of chronic inflammation and tumor progression. In this study, we used the PyMT model (NE+/+ and NE-/-) of breast cancer to interrogate the tumor-intrinsic and -extrinsic mechanisms by which NE can promote metastasis. Our results showed that genetic ablation of NE significantly reduced lung metastasis and improved metastasis-free survival. RNA-sequencing analysis of primary tumors indicated differential regulation of tumor-intrinsic actin cytoskeleton signaling pathways by NE. These NE-regulated pathways are critical for cell-to-cell contact and motility and consistent with the delay in metastasis in NE-/- mice. To evaluate whether pharmacologic inhibition of NE inhibited pulmonary metastasis and phenotypically mimicked PyMT NE-/- mice, we utilized AZD9668, a clinically available and specific NE inhibitor. We found AZD9668 treated PyMT-NE+/+ mice showed significantly reduced lung metastases, improved recurrence-free, metastasis-free and overall survival, and their tumors showed similar molecular alterations as those observed in PyMT-NE-/- tumors. Finally, we identified a NE-specific signature that predicts recurrence and metastasis in patients with breast cancer. Collectively, our studies suggest that genetic ablation and pharmacologic inhibition of NE reduces metastasis and extends survival of mouse models of breast cancer, providing rationale to examine NE inhibitors as a treatment strategy for the clinical management of patients with metastatic breast cancer.

The causal connectivity of a network is often inferred to understand network function. It is arguably acknowledged that the inferred causal connectivity relies on the causality measure one applies, and it may differ from the network's underlying structural connectivity. However, the interpretation of causal connectivity remains to be fully clarified, in particular, how causal connectivity depends on causality measures and how causal connectivity relates to structural connectivity. Here, we focus on nonlinear networks with pulse signals as measured output, e.g., neural networks with spike output, and address the above issues based on four commonly utilized causality measures, i.e., time-delayed correlation coefficient, time-delayed mutual information, Granger causality, and transfer entropy. We theoretically show how these causality measures are related to one another when applied to pulse signals. Taking a simulated Hodgkin-Huxley network and a real mouse brain network as two illustrative examples, we further verify the quantitative relations among the four causality measures and demonstrate that the causal connectivity inferred by any of the four well coincides with the underlying network structural connectivity, therefore illustrating a direct link between the causal and structural connectivity. We stress that the structural connectivity of pulse-output networks can be reconstructed pairwise without conditioning on the global information of all other nodes in a network, thus circumventing the curse of dimensionality. Our framework provides a practical and effective approach for pulse-output network reconstruction.

BACKGROUND/UNASSIGNED:variants. METHODS/UNASSIGNED: RESULTS/UNASSIGNED:) related to intracellular calcium homeostasis, heart rate, RAS signaling, and induction of pacemaker-nodal-like transcriptional programming. Immunoblotting confirmed increased protein levels for genes of interest and suppressed MAPK (mitogen-activated protein kinase) activity in mutant ACMs. CONCLUSIONS/UNASSIGNED:

Identifying directed information flow or Granger causality between multivariate time series is important for a wide range of applications in science and engineering. However, traditional data-driven approaches are insufficient to assess Granger causality between multimodal data with distinct temporal resolution. Here we propose a new analysis approach to address this challenge and present quantitative characterizations and statistical assessment on frequency-dependent directed information flow ("generalized spectral causality"). We validate our approach with intensive computer simulations on bivariate and trivariate systems for various conditions.