Faculty Bibliography

BACKGROUND:Identifying factors associated with uncomplicated and complicated opioid use is essential, especially with regard to safety concerns in impaired kidney function. Literature about opioid prescription and their potential complications in patients with different stages of chronic kidney disease (CKD) is scarce. This study describes opioid use and poisoning in hospitalized CKD patients. METHODS:The National Inpatient Database (NIS) was queried from 2016 to 2020 to identify which patients with known CKD stages were admitted with diagnoses of uncomplicated and complicated opioid use, and opioid poisoning. Patients with end-stage kidney disease receiving any form of renal replacement therapy were excluded. CKD1 served as a reference, and demographic and socio-economic characteristics were accounted for. Logistic regressions were performed to evaluate the relationship between CKD stages and each condition. RESULTS:The final cohort included 2,917,404 (14,587,017 weighted) CKD patients, of whom 1.763 ± 0.023% and 1.177 ± 0.016% had uncomplicated and complicated opioid use, respectively. Odds of uncomplicated use were lower with more advanced CKD stages. We observed an increase of complicated use with milder forms of CKD. No differences in odds of complicated opioid use were found when CKD4-5 patients were compared to CKD1. After adjustment, opioid use was found to be the main predictor of poisoning in hospitalized CKD patients. CONCLUSION/CONCLUSIONS:Prescribers appear to be more cautious in patients with advanced CKD, with lower odds of being on opioid analgesics in this group. Most CKD patients had higher odds of complicated use, and poisoning was essentially driven by complicated opioid use rather than CKD stage.

Motor neurons have highly diverse anatomical, functional and molecular features, and differ significantly in their susceptibility in disease. Extraocular motor neurons, residing in the oculomotor, trochlear and abducens cranial nuclei (nIII, nIV and nVI), control eye movements. Recent work has begun to clarify the developmental mechanisms by which functional diversity among extraocular motor neurons arises. However, we know little about the role and consequences of extraocular motor neuron diversity in eye movement control. Here, we highlight recent work investigating the anatomical, functional and molecular features of extraocular motor neurons. Further, we frame hypotheses where studying ocular motor circuits in the larval zebrafish is poised to illuminate the consequences of motor neuron diversity for behavior.

Small-animal diffusion MRI (dMRI) has been used for methodological development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. The steps from animal setup and monitoring, to acquisition, analysis, and interpretation are complex, with many decisions that may ultimately affect what questions can be answered using the resultant data. This work aims to present selected considerations and recommendations from the diffusion community on best practices for preclinical dMRI of in vivo animals. We describe the general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in animal species and disease models and discuss why some may be more or less appropriate for different studies. We, then, give recommendations for in vivo acquisition protocols, including decisions on hardware, animal preparation, and imaging sequences, followed by advice for data processing including preprocessing, model-fitting, and tractography. Finally, we provide an online resource that lists publicly available preclinical dMRI datasets and software packages to promote responsible and reproducible research. In each section, we attempt to provide guides and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should focus. Although we mainly cover the central nervous system (on which most preclinical dMRI studies are focused), we also provide, where possible and applicable, recommendations for other organs of interest. An overarching goal is to enhance the rigor and reproducibility of small animal dMRI acquisitions and analyses, and thereby advance biomedical knowledge.

BACKGROUND:The diagnosis and treatment of tumors often depend on molecular-genetic data. However, rapid and iterative access to molecular data is not currently feasible during surgery, complicating intraoperative diagnosis and precluding measurement of tumor cell burdens at surgical margins to guide resections. METHODS:Here, we introduce Ultra-Rapid droplet digital PCR (UR-ddPCR), a technology that achieves the fastest measurement, to date, of mutation burdens in tissue samples, from tissue to result in 15 min. Our workflow substantially reduces the time from tissue biopsy to molecular diagnosis and provides a highly accurate means of quantifying residual tumor infiltration at surgical margins. FINDINGS/RESULTS: = 0.995). CONCLUSIONS:The technology and workflow developed here enable intraoperative molecular-genetic assays with unprecedented speed and sensitivity. We anticipate that our method will facilitate novel point-of-care diagnostics and molecularly guided surgeries that improve clinical outcomes. FUNDING/BACKGROUND:This study was funded by the National Institutes of Health and NYU Grossman School of Medicine institutional funds. Reagents and instruments were provided in kind by Bio-Rad.

INTRODUCTION/BACKGROUND:MicroRNA (miRNA) activity is increasingly appreciated as a key regulator of pathophysiologic pathways in Alzheimer's disease (AD). However, the role of miRNAs during the progression of AD, including resilience and prodromal syndromes such as mild cognitive impairment (MCI), remains underexplored. METHODS:We performed miRNA-sequencing on samples of posterior cingulate cortex (PCC) obtained post mortem from Rush Religious Orders Study participants diagnosed ante mortem with no cognitive impairment (NCI), MCI, or AD. NCI subjects were subdivided as low pathology (Braak stage I/II) or high pathology (Braak stage III/IV), suggestive of resilience. Bioinformatics approaches included differential expression, messenger RNA (mRNA) target prediction, interactome modeling, functional enrichment, and AD risk modeling. RESULTS:We identified specific miRNA groups, mRNA targets, and signaling pathways distinguishing AD, MCI, resilience, ante mortem neuropsychological test performance, post mortem neuropathological burden, and AD risk. DISCUSSION/CONCLUSIONS:These findings highlight the potential of harnessing miRNA activity to manipulate disease-modifying pathways in AD, with implications for precision medicine. HIGHLIGHTS/CONCLUSIONS:MicroRNA (MiRNA) dysregulation is a well-established feature of Alzheimer's disease (AD). Novel miRNAs also distinguish subjects with mild cognitive impairment and putative resilience. MiRNAs correlate with cognitive performance and neuropathological burden. Select miRNAs are associated with AD risk with age as a significant covariate. MiRNA pathways include insulin, prolactin, kinases, and neurite plasticity.

Obstructive sleep apnea (OSA) exerts pathogenic effects through a combination of sleep fragmentation (SF) and intermittent hypoxia (IH). The mechanisms through which sleep disruption impacts memory might arise by investigating disruption of specific sleep stages and, when such disruption occurs through OSA, by evaluating the individual contributions of SF and IH. Given region-specific EEG slow activity during non-REM sleep has been associated with overnight declarative, motor and spatial memory formation, we investigated the effects of disrupting slow wave sleep (SWS) on a virtual maze navigation task. Thirty three participants (24 male, 56 years old [range 28-68 years] with OSA (baseline AHI4%>20/hour) who were habitually well-treated and adherent to CPAP completed 3 timed trials on a 3D spatial maze before and after polysomnographically (PSG) recorded sleep. We restricted CPAP withdrawal to SWS through real-time monitoring of the PSG under three conditions: 1) stable-SWS on therapeutic CPAP, 2) SWS-CPAP withdrawal containing SF and IH, and 3) SWS-CPAP withdrawal with supplemental oxygen containing SF with reduced IH. SWS-specific CPAP withdrawal (with or without supplemental oxygen) did not significantly impact EEG slow oscillation or spatial navigational memory, despite effectively reducing %SWS and SWS bout length. Greater regional EEG slow oscillation (0.6-1Hz), but not delta (1-4Hz) activity, was associated with improvements in overnight memory during stable SWS in the CPAP condition. These observations suggest that slow oscillations may be important for overnight memory processing, and sleep disruptions of sufficient magnitude to reduce slow oscillations may be required to capture demonstrable change in spatial navigation performance.

Active avoidance is a core behavior for human coping, and its excess is common across psychiatric diseases. The decision to actively avoid a threat is influenced by cost and reward. Yet, threat, avoidance, and reward have been studied in silos. We discuss behavioral and brain circuits of active avoidance and the interactions with fear and threat. In addition, we present a neural toggle switch model enabling fear-to-anxiety transition and approaching reward vs. avoiding harm decision. To fully comprehend how threat, active avoidance, and reward intersect, it is paramount to develop one shared experimental approach across phenomena and behaviors, which will ultimately allow us to better understand human behavior and pathology.

Preclinical diffusion MRI (dMRI) has proven value in methods development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages that facilitate high spatial resolution and high SNR images, cutting-edge diffusion contrasts, and direct comparison with histological data as a methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work concludes a three-part series of recommendations and considerations for preclinical dMRI. Herein, we describe best practices for dMRI of ex vivo tissue, with a focus on image pre-processing, data processing, and comparisons with microscopy. In each section, we attempt to provide guidelines and recommendations but also highlight areas for which no guidelines exist (and why), and where future work should lie. We end by providing guidelines on code sharing and data sharing and point toward open-source software and databases specific to small animal and ex vivo imaging.