Loss of circulating CD8α+ NK cells during human Mycobacterium tuberculosis infection

Natural Killer (NK) cells can recognize and kill Mtb-infected cells in vitro, however their role after natural human exposure has not been well-studied. To identify Mtb-responsive NK cell populations, we analyzed the peripheral blood of healthy household contacts of active Tuberculosis (TB) cases and source community donors in an endemic region of Port-au-Prince, Haiti by flow cytometry. We observed higher CD8α expression on NK cells in putative resistors (IGRA-contacts) with a progressive loss of these circulating cells during household-associated latent infection and disease. In vitro assays and CITE-seq analysis of CD8α+ NK cells demonstrated enhanced maturity, cytotoxic gene expression, and response to cytokine stimulation relative to CD8α- NK cells. CD8α+ NK cells also displayed dynamic surface expression dependent on MHC I in contrast to conventional CD8+ T cells. Together, these results support a specialized role for CD8α+ NK cell populations during Mtb infection correlating with disease resistance.

Fatty acid binding protein 5 inhibition attenuates pronociceptive cytokine/chemokine expression and suppresses osteoarthritis pain: A comparative human and rat study

OBJECTIVE

Osteoarthritis (OA) is often accompanied by debilitating pain that is refractory to available analgesics due in part to the complexity of signaling molecules that drive OA pain and our inability to target these in parallel. Fatty acid binding protein 5 (FABP5) is a lipid chaperone that regulates inflammatory pain; however, its contribution to OA pain has not been characterized.

DESIGN

This combined clinical and pre-clinical study utilized synovial tissues obtained from subjects with end-stage OA and rats with monoiodoacetate-induced OA. Cytokine and chemokine release from human synovia incubated with a selective FABP5 inhibitor was profiled with cytokine arrays and ELISA. Immunohistochemical analyses were conducted for FABP5 in human and rat synovium. The efficacy of FABP5 inhibitors on pain was assessed in OA rats using incapacitance as an outcome. RNA-seq was then performed to characterize the transcriptomic landscape of synovial gene expression in OA rats treated with FABP5 inhibitor or vehicle.

RESULTS

FABP5 was expressed in human synovium and FABP5 inhibition reduced the secretion of pronociceptive cytokines (interleukin-6 [IL6], IL8) and chemokines (CCL2, CXCL1). In rats, FABP5 was upregulated in the OA synovium and its inhibition alleviated incapacitance. The transcriptome of the rat OA synovium exhibited >6000 differentially expressed genes, including the upregulation of numerous pronociceptive cytokines and chemokines. FABP5 inhibition blunted the upregulation of the majority of these pronociceptive mediators.

CONCLUSIONS

FABP5 is expressed in the OA synovium and its inhibition suppresses pronociceptive signaling and pain, indicating that FABP5 inhibitors may constitute a novel class of analgesics to treat OA.

Prevalence of bias against neurodivergence-related terms in artificial intelligence language models

Given the increasing role of artificial intelligence (AI) in many decision-making processes, we investigate the presence of AI bias towards terms related to a range of neurodivergent conditions, including autism, ADHD, schizophrenia, and obsessive-compulsive disorder (OCD). We use 11 different language model encoders to test the degree to which words related to neurodiversity are associated with groups of words related to danger, disease, badness, and other negative concepts. For each group of words tested, we report the mean strength of association (Word Embedding Association Test [WEAT] score) averaged over all encoders and find generally high levels of bias. Additionally, we show that bias occurs even when testing words associated with autistic or neurodivergent strengths. For example, embedders had a negative average association between words related to autism and words related to honesty, despite honesty being considered a common strength of autistic individuals. Finally, we introduce a sentence similarity ratio test and demonstrate that many sentences describing types of disabilities, for example, "I have autism" or "I have epilepsy," have even stronger negative associations than control sentences such as "I am a bank robber."

Compact, ultrastable, high repetition-rate 2 μm and 3 μm fiber laser for seeding mid-IR OPCPA

We report a compact and reliable ultrafast fiber laser system optimized for seeding a high energy, 2 μm pumped, 3 μm wavelength optical parametric chirped pulse amplification to drive soft X-ray high harmonics. The system delivers 100 MHz narrowband 2 μm pulses with >1 nJ energy, synchronized with ultra-broadband optical pulses with a ∼1 μm FWHM spectrum centered at 3 μm with 39 pJ pulse energy. The 2 μm and 3 μm pulses are derived from a single 1.5 μm fiber oscillator, fully fiber integrated with free-space downconversion for the 3 μm. The system operates hands-off with power instabilities <0.2% over extended periods of time.

Tantalum pentoxide: a new material platform for high-performance dielectric metasurface optics in the ultraviolet and visible region

Dielectric metasurfaces, composed of planar arrays of subwavelength dielectric structures that collectively mimic the operation of conventional bulk optical elements, have revolutionized the field of optics by their potential in constructing high-efficiency and multi-functional optoelectronic systems on chip. The performance of a dielectric metasurface is largely determined by its constituent material, which is highly desired to have a high refractive index, low optical loss and wide bandgap, and at the same time, be fabrication friendly. Here, we present a new material platform based on tantalum pentoxide (Ta2O5) for implementing high-performance dielectric metasurface optics over the ultraviolet and visible spectral region. This wide-bandgap dielectric, exhibiting a high refractive index exceeding 2.1 and negligible extinction coefficient across a broad spectrum, can be easily deposited over large areas with good quality using straightforward physical vapor deposition, and patterned into high-aspect-ratio subwavelength nanostructures through commonly-available fluorine-gas-based reactive ion etching. We implement a series of high-efficiency ultraviolet and visible metasurfaces with representative light-field modulation functionalities including polarization-independent high-numerical-aperture lensing, spin-selective hologram projection, and vivid structural color generation, and the devices exhibit operational efficiencies up to 80%. Our work overcomes limitations faced by scalability of commonly-employed metasurface dielectrics and their operation into the visible and ultraviolet spectral range, and provides a novel route towards realization of high-performance, robust and foundry-manufacturable metasurface optics.

Estimating the effects of vegetation and increased albedo on the urban heat island effect with spatial causal inference

The urban heat island effect causes increased heat stress in urban areas. Cool roofs and urban greening have been promoted as mitigation strategies to reduce this effect. However, evaluating their efficacy remains a challenge, as potential temperature reductions depend on local characteristics. Existing methods to characterize their efficacy, such as computational fluid dynamics and urban canopy models, are computationally burdensome and require a high degree of expertise to employ. We propose a data-driven approach to overcome these hurdles, inspired by recent innovations in spatial causal inference. This approach allows for estimates of hypothetical interventions to reduce the urban heat island effect. We demonstrate this approach by modeling evening temperature in Durham, North Carolina, using readily retrieved air temperature, land cover, and satellite data. Hypothetical interventions such as lining streets with trees, cool roofs, and changing parking lots to green space are estimated to decrease evening temperatures by a maximum of 0.7-0.9   [Formula: see text], with reduced effects on temperature as a function of distance from the intervention. Because of the ease of data access, this approach may be applied to other cities in the U.S. to help them come up with city-specific solutions for reducing urban heat stress.

Estimating a brain network predictive of stress and genotype with supervised autoencoders

Targeted brain stimulation has the potential to treat mental illnesses. We develop an approach to help design protocols by identifying relevant multi-region electrical dynamics. Our approach models these dynamics as a superposition of latent networks, where the latent variables predict a relevant outcome. We use supervised autoencoders (SAEs) to improve predictive performance in this context, describe the conditions where SAEs improve predictions, and provide modelling constraints to ensure biological relevance. We experimentally validate our approach by finding a network associated with stress that aligns with a previous stimulation protocol and characterizing a genotype associated with bipolar disorder.

Estimating Causal Effects using a Multi-task Deep Ensemble

A number of methods have been proposed for causal effect estimation, yet few have demonstrated efficacy in handling data with complex structures, such as images. To fill this gap, we propose Causal Multi-task Deep Ensemble (CMDE), a novel framework that learns both shared and group-specific information from the study population. We provide proofs demonstrating equivalency of CDME to a multi-task Gaussian process (GP) with a coregionalization kernel a priori. Compared to multi-task GP, CMDE efficiently handles high-dimensional and multi-modal covariates and provides pointwise uncertainty estimates of causal effects. We evaluate our method across various types of datasets and tasks and find that CMDE outperforms state-of-the-art methods on a majority of these tasks.

Numerical investigation of gas-filled multipass cells in the enhanced dispersion regime for clean spectral broadening and pulse compression

We show via numerical simulations that the regime of enhanced frequency chirp can be achieved in gas-filled multipass cells. Our results demonstrate that there exists a region of pulse and cell parameters for which a broad and flat spectrum with a smooth parabolic-like phase can be generated. This spectrum is compatible with clean ultrashort pulses, whose secondary structures are always below the 0.5% of its peak intensity such that the energy ratio (the energy contained within the main peak of the pulse) is above 98%. This regime makes multipass cell post-compression one of the most versatile schemes to sculpt a clean intense ultrashort optical pulse.

Nonlinear post-compression in multi-pass cells in the mid-IR region using bulk materials

We numerically investigate the regime of nonlinear pulse compression at mid-IR wavelengths in a multi-pass cell (MPC) containing a dielectric plate. This post-compression setup allows for ionization-free spectral broadening and self-compression while mitigating self-focusing effects. We find that self-compression occurs for a wide range of MPC and pulse parameters and derive scaling rules that enable its optimization. We also reveal the solitonic dynamics of the pulse propagation in the MPC and its limitations and show that spatiotemporal/spectral couplings can be mitigated for appropriately chosen parameters. In addition, we reveal the formation of spectral features akin to quasi-phase matched degenerate four-wave mixing. Finally, we present two case studies of self-compression at 3-μm and 6-μm wavelengths using pulse parameters compatible with driving high-field physics experiments. The simulations presented in this paper set a framework for future experimental work using few-cycle pulses at mid-IR wavelengths.

Estimating Potential Outcome Distributions with Collaborating Causal Networks

Traditional causal inference approaches leverage observational study data to estimate the difference in observed (factual) and unobserved (counterfactual) outcomes for a potential treatment, known as the Conditional Average Treatment Effect (CATE). However, CATE corresponds to the comparison on the first moment alone, and as such may be insufficient in reflecting the full picture of treatment effects. As an alternative, estimating the full potential outcome distributions could provide greater insights. However, existing methods for estimating treatment effect potential outcome distributions often impose restrictive or overly-simplistic assumptions about these distributions. Here, we propose Collaborating Causal Networks (CCN), a novel methodology which goes beyond the estimation of CATE alone by learning the full potential outcome distributions. Estimation of outcome distributions via the CCN framework does not require restrictive assumptions of the underlying data generating process (e.g. Gaussian errors). Additionally, our proposed method facilitates estimation of the utility of each possible treatment and permits individual-specific variation through utility functions (e.g. risk tolerance variability). CCN not only extends outcome estimation beyond traditional risk difference, but also enables a more comprehensive decision making process through definition of flexible comparisons. Under assumptions commonly made in the causal inference literature, we show that CCN learns distributions that asymptotically capture the correct potential outcome distributions. Furthermore, we propose an adjustment approach that is empirically effective in alleviating sample imbalance between treatment groups in observational studies. Finally, we evaluate the performance of CCN in multiple experiments on both synthetic and semi-synthetic data. We demonstrate that CCN learns improved distribution estimates compared to existing Bayesian and deep generative methods as well as improved decisions with respects to a variety of utility functions.

The evolution of multi-gene families and metabolic pathways in the evening primroses (Oenothera: Onagraceae): A comparative transcriptomics approach

The plant genus Oenothera has played an important role in the study of plant evolution of genomes and plant defense and reproduction. Here, we build on the 1kp transcriptomic dataset by creating 44 new transcriptomes and analyzing a total of 63 transcriptomes to present a large-scale comparative study across 29 Oenothera species. Our dataset included 30.4 million reads per individual and 2.3 million transcripts on average. We used this transcriptome resource to examine genome-wide evolutionary patterns and functional diversification by searching for orthologous genes and performed gene family evolution analysis. We found wide heterogeneity in gene family evolution across the genus, with section Oenothera exhibiting the most pronounced evolutionary changes. Overall, more significant gene family expansions occurred than contractions. We also analyzed the molecular evolution of phenolic metabolism by retrieving proteins annotated for phenolic enzymatic complexes. We identified 1,568 phenolic genes arranged into 83 multigene families that varied widely across the genus. All taxa experienced rapid phenolic evolution (fast rate of genomic turnover) involving 33 gene families, which exhibited large expansions, gaining about 2-fold more genes than they lost. Upstream enzymes phenylalanine ammonia-lyase (PAL) and 4-coumaroyl: CoA ligase (4CL) accounted for most of the significant expansions and contractions. Our results suggest that adaptive and neutral evolutionary processes have contributed to Oenothera diversification and rapid gene family evolution.

Photonic crystal resonators for inverse-designed multi-dimensional optical interconnects

We experimentally demonstrate a 400 Gbit/s optical communication link utilizing wavelength-division multiplexing and mode-division multiplexing for a total of 40 channels. This link utilizes a novel, to the best of our knowledge, 400 GHz frequency comb source based on a chip-scale photonic crystal resonator. Silicon-on-insulator photonic inverse-designed 4 × 4 mode-division multiplexer structures enable a fourfold increase in data capacity. We show less than -10 dBm of optical receiver power for error-free data transmission in 34 out of a total of 40 channels using a PRBS31 pattern.

Directed Spectral Measures Improve Latent Network Models Of Neural Populations

Systems neuroscience aims to understand how networks of neurons distributed throughout the brain mediate computational tasks. One popular approach to identify those networks is to first calculate measures of neural activity (e.g. power spectra) from multiple brain regions, and then apply a linear factor model to those measures. Critically, despite the established role of directed communication between brain regions in neural computation, measures of directed communication have been rarely utilized in network estimation because they are incompatible with the implicit assumptions of the linear factor model approach. Here, we develop a novel spectral measure of directed communication called the Directed Spectrum (DS). We prove that it is compatible with the implicit assumptions of linear factor models, and we provide a method to estimate the DS. We demonstrate that latent linear factor models of DS measures better capture underlying brain networks in both simulated and real neural recording data compared to available alternatives. Thus, linear factor models of the Directed Spectrum offer neuroscientists a simple and effective way to explicitly model directed communication in networks of neural populations.

Missed Opportunities for Human Immunodeficiency Virus (HIV) Testing During Injection Drug Use-Related Healthcare Encounters Among a Cohort of Persons Who Inject Drugs With HIV Diagnosed During an Outbreak-Cincinnati/Northern Kentucky, 2017-2018

BACKGROUND

Persons who inject drugs (PWID) have frequent healthcare encounters related to their injection drug use (IDU) but are often not tested for human immunodeficiency virus (HIV). We sought to quantify missed opportunities for HIV testing during an HIV outbreak among PWID.

METHODS

PWID with HIV diagnosed in 5 Cincinnati/Northern Kentucky counties during January 2017-September 2018 who had ≥1 encounter 12 months prior to HIV diagnosis in 1 of 2 Cincinnati/Northern Kentucky area healthcare systems were included in the analysis. HIV testing and encounter data were abstracted from electronic health records. A missed opportunity for HIV testing was defined as an encounter for an IDU-related condition where an HIV test was not performed and had not been performed in the prior 12 months.

RESULTS

Among 109 PWID with HIV diagnosed who had ≥1 healthcare encounter, 75 (68.8%) had ≥1 IDU-related encounters in the 12 months before HIV diagnosis. These 75 PWID had 169 IDU-related encounters of which 86 (50.9%) were missed opportunities for HIV testing and occurred among 46 (42.2%) PWID. Most IDU-related encounters occurred in the emergency department (118/169; 69.8%). Using multivariable generalized estimating equations, HIV testing was more likely in inpatient compared with emergency department encounters (adjusted relative risk [RR], 2.72; 95% confidence interval [CI], 1.70-4.33) and at the healthcare system receiving funding for emergency department HIV testing (adjusted RR, 1.76; 95% CI, 1.10-2.82).

CONCLUSIONS

PWID have frequent IDU-related encounters in emergency departments. Enhanced HIV screening of PWID in these settings can facilitate earlier diagnosis and improve outbreak response.

Machine learning does not improve upon traditional regression in predicting outcomes in atrial fibrillation: an analysis of the ORBIT-AF and GARFIELD-AF registries

AIMS

Prediction models for outcomes in atrial fibrillation (AF) are used to guide treatment. While regression models have been the analytic standard for prediction modelling, machine learning (ML) has been promoted as a potentially superior methodology. We compared the performance of ML and regression models in predicting outcomes in AF patients.

METHODS AND RESULTS

The Outcomes Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF) and Global Anticoagulant Registry in the FIELD (GARFIELD-AF) are population-based registries that include 74 792 AF patients. Models were generated from potential predictors using stepwise logistic regression (STEP), random forests (RF), gradient boosting (GB), and two neural networks (NNs). Discriminatory power was highest for death [STEP area under the curve (AUC) = 0.80 in ORBIT-AF, 0.75 in GARFIELD-AF] and lowest for stroke in all models (STEP AUC = 0.67 in ORBIT-AF, 0.66 in GARFIELD-AF). The discriminatory power of the ML models was similar or lower than the STEP models for most outcomes. The GB model had a higher AUC than STEP for death in GARFIELD-AF (0.76 vs. 0.75), but only nominally, and both performed similarly in ORBIT-AF. The multilayer NN had the lowest discriminatory power for all outcomes. The calibration of the STEP modelswere more aligned with the observed events for all outcomes. In the cross-registry models, the discriminatory power of the ML models was similar or lower than the STEP for most cases.

CONCLUSION

When developed from two large, community-based AF registries, ML techniques did not improve prediction modelling of death, major bleeding, or stroke.

Estimating Uncertainty Intervals from Collaborating Networks

Effective decision making requires understanding the uncertainty inherent in a prediction. In regression, this uncertainty can be estimated by a variety of methods; however, many of these methods are laborious to tune, generate overconfident uncertainty intervals, or lack sharpness (give imprecise intervals). We address these challenges by proposing a novel method to capture predictive distributions in regression by defining two neural networks with two distinct loss functions. Specifically, one network approximates the cumulative distribution function, and the second network approximates its inverse. We refer to this method as Collaborating Networks (CN). Theoretical analysis demonstrates that a fixed point of the optimization is at the idealized solution, and that the method is asymptotically consistent to the ground truth distribution. Empirically, learning is straightforward and robust. We benchmark CN against several common approaches on two synthetic and six real-world datasets, including forecasting A1c values in diabetic patients from electronic health records, where uncertainty is critical. In the synthetic data, the proposed approach essentially matches ground truth. In the real-world datasets, CN improves results on many performance metrics, including log-likelihood estimates, mean absolute errors, coverage estimates, and prediction interval widths.

Attention-Based Network for Weak Labels in Neonatal Seizure Detection

Seizures are a common emergency in the neonatal intesive care unit (NICU) among newborns receiving therapeutic hypothermia for hypoxic ischemic encephalopathy. The high incidence of seizures in this patient population necessitates continuous electroencephalographic (EEG) monitoring to detect and treat them. Due to EEG recordings being reviewed intermittently throughout the day, inevitable delays to seizure identification and treatment arise. In recent years, work on neonatal seizure detection using deep learning algorithms has started gaining momentum. These algorithms face numerous challenges: first, the training data for such algorithms comes from individual patients, each with varying levels of label imbalance since the seizure burden in NICU patients differs by several orders of magnitude. Second, seizures in neonates are usually localized in a subset of EEG channels, and performing annotations per channel is very time-consuming. Hence models which make use of labels only per time periods, and not per channels, are preferable. In this work we assess how different deep learning models and data balancing methods influence learning in neonatal seizure detection in EEGs. We propose a model which provides a level of importance to each of the EEG channels - a proxy to whether a channel exhibits seizure activity or not, and we provide a quantitative assessment of how well this mechanism works. The model is portable to EEG devices with differing layouts without retraining, facilitating its potential deployment across different medical centers. We also provide a first assessment of how a deep learning model for neonatal seizure detection agrees with human rater decisions - an important milestone for deployment to clinical practice. We show that high AUC values in a deep learning model do not necessarily correspond to agreement with a human expert, and there is still a need to further refine such algorithms for optimal seizure discrimination.

Relative Average Look Duration and its Association with Neurophysiological Activity in Young Children with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is characterized by early attentional differences that often precede the hallmark symptoms of social communication impairments. Development of novel measures of attentional behaviors may lead to earlier identification of children at risk for ASD. In this work, we first introduce a behavioral measure, Relative Average Look Duration (RALD), indicating attentional preference to different stimuli, such as social versus nonsocial stimuli; and then study its association with neurophysiological activity. We show that (1) ASD and typically developing (TD) children differ in both (absolute) Average Look Duration (ALD) and RALD to stimuli during an EEG experiment, with the most pronounced differences in looking at social stimuli; and (2) associations between looking behaviors and neurophysiological activity, as measured by EEG, are different for children with ASD versus TD. Even when ASD children show attentional engagement to social content, our results suggest that their underlying brain activity is different than TD children. This study therefore introduces a new measure of social/nonsocial attentional preference in ASD and demonstrates the value of incorporating attentional variables measured simultaneously with EEG into the analysis pipeline.

Sources of volatile organic compounds in suburban homes in Shanghai, China, and the impact of air filtration on compound concentrations

Air pollution in China is an ongoing concern, with subsets of the population (e.g., asthmatic children) especially susceptible to the associated health effects. In addition, people spend the majority of their time indoors, where pollutant composition may differ from the better characterized ambient environment. Although volatile organic compounds (VOCs) present health risks and have high concentrations indoors, their sources have not been thoroughly quantified in typical homes in suburban China. Similarly lacking is an understanding of how well a purifier with high efficiency particulate air and activated carbon filters can remove VOCs in a real-world setting in China. In this study, we a) quantified total VOCs (TVOC) and 900 + individual VOCs in 20 homes in China, b) identified potential sources of VOCs, and c) evaluated impacts of filtration. We used non-negative matrix factorization, a variable reduction technique, to identify sources. TVOC and individual compounds had higher concentrations indoors than outdoors (mean [range] indoors, filtration with pre-filter only: 302 [56-793] μg m-3; outdoors, entire study: 92 [26-629] μg m-3), indicating prevalent sources indoors. Many compounds detected have not, to our knowledge, been measured in homes in China. Some compounds (e.g., octanal, heptanal, ⍺-cedrene) were specific to the indoor environment, a few were ubiquitous (e.g., acetaldehyde, formaldehyde), and others were detected infrequently. These compounds may originate from consumer products, solvents, vehicle emissions, a hexane source, wooden products, and cooking. Filtration may improve air quality indoors by lowering concentrations of some VOCs, and, specifically, contributions related to solvents and consumer products.

Genetic and pharmacological validation of TAK1 inhibition in macrophages as a therapeutic strategy to effectively inhibit TNF secretion

Immune challenge of invading macrophages at sites of infection is associated with release of TNF, which triggers a local cytokine storm as part of the normal inflammatory response. Whereas this response maybe beneficial in fighting off infections, similar responses triggered in autoimmune diseases contribute significantly to the underlying damaging pathology associated with these diseases. Here we show that Takinib, a highly discriminatory inhibitor of transforming growth factor Beta- activated kinase 1 (TAK1), selectively and potently reduces TNF production in pro-inflammatory THP-1 macrophages. A complete survey of 110 cytokines, showed robust loss of proinflammatory cytokine responsiveness to lipopolysaccharide (LPS) and interferon gamma (IFNγ) challenge in response to Takinib. The mechanisms of action of Takinib was recapitulated in TAK1 KO macrophages. TAK1 KO cells showed significant loss of TNF production as well as release of IL-6 in response to LPS challenge. Furthermore, Takinib blocked the ability of exogenously added LPS to promote phosphorylation of, c-Jun, p38 protein kinases as well as downstream transcription factors regulated by nuclear factor κ-light-chain-enhancer of activated B cells (NFκB). In a mouse LPS challenge model, Takinib significantly reduced TNF serum levels. Our findings demonstrate that Takinib has utility in the treatment inflammatory disease by locally suppressing TNF production from invading macrophages.

Abstract 4397: Tak-1 inhibition re-sensitizes cancer cells to TNFα

Identifying new pharmaceutical targets in cancer has been a long lasting goal of academia. Complex genomic changes coupled with a cancer cell's ability to adapt make tumors particularly difficult to target. To this end, we have identified the TAK1 kinase in the TNFα pathway as a potential mediator of cell survival or apoptosis. Here we evaluate the apoptotic effects of a novel TAK1 inhibitor, Takinib. The selectivity of Takinib was established with an IC50 of 9nm for TAK1, followed by an IC50 for IRAK4 and IRAK1 at 120nm and 390nm respectively. Treatment of MDA-MB-231 cells with Takinib on its own is not sufficient to induce consequential cell death. However, combination therapy with TNFα induces caspase 3/7 activity and subsequent cell death in a dose-dependent manner. Genetic knock out of TAK1 expression in MDA-MB-231 cells with the CRISPR/Cas9 system significantly sensitized previous resistant cells to TNFα. Furthermore, we have shown that activation of human THP-1 cells with LPS is sufficient to produce TNFα levels necessary to facilitate Takinib mediated cell death, indicating that potential immunotherapy applications may be possible. Together these findings support the idea that TAK1 may be an effective target in the TNFα pathway, shifting the cellular mechanisms from pro survival to pro apoptosis.

Citation Format: Scott Scarneo, Madeline Sell, Juliane Totzke, David Carlson, Phillip Hughes, Tim Haystead. Tak-1 inhibition re-sensitizes cancer cells to TNFα [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4397.

Deuterated silicon nitride photonic devices for broadband optical frequency comb generation

We report and characterize low-temperature, plasma-deposited deuterated silicon nitride films for nonlinear integrated photonics. With a peak processing temperature less than 300°C, it is back-end compatible with complementary metal-oxide semiconductor substrates. We achieve microresonators with a quality factor of up to 1.6×10⁶ at 1552 nm and >1.2×10⁶ throughout λ=1510-1600  nm, without annealing or stress management (film thickness of 920 nm). We then demonstrate the immediate utility of this platform in nonlinear photonics by generating a 1 THz free-spectral-range, 900 nm bandwidth modulation-instability microresonator Kerr comb and octave-spanning, supercontinuum-broadened spectra.

199 Efficient Knock-out of Ovine β-Lactoglobulin (BLG) Gene and Knock-in of Recombinant Human Factor IX (rhFIX) Under BLG Native Regulatory Sequences in Somatic Cells and Zygotes Using TALEN Nuclease

Site-specific genetic engineering is a valuable tool for pharmaceutical research and development of biomedical models. Despite engineered nucleases allow targeted gene edition in a rather simple fashion; few reports are available so far on specific gene knock-in (KI) combined with engineered nucleases in domestic species. Here, we evaluated the possibility of inducing specific KI of cDNAs coding for proteins of pharmaceutical interest under the control of milk native promoter sequences, taking advantage of the TALEN system, both in ovine somatic cells and in zygotes. We designed 2 TALENs, targeting exons 1 and 5 of ovine β-lactoglobulin gene (BLG), respectively, and a homologous recombination vector (pHR), carrying recombinant human factor IX (rhFIX) flanked by homology arms contiguous to the TALEN target sites. In an initial set of experiments, 5 × 105 to 1 × 106 ovine fibroblasts were transfected with 1 μg of each TALEN mRNA, with or without 50 ng μL−1 pHR. The feasibility of inducing knock-out (KO) was confirmed by Cel1 assay. The deletion of the genomic region between TALEN target sites and the occurrence of HR in cell lysates were assessed by PCR. Also, 576 individual colonies were picked up and analyzed by PCR. The deletion of the region between TALEN target sites was achieved with 7.8% efficiency (45/576). The incidence of HR in cells was 0.5% (3/576), as detected by PCR. In order to evaluate the system in zygotes, laparoscopic AI was performed on synchronized and superovulated ewes. Zygotes were recovered 16 h after AI and cytoplasmically injected with (1) 5 ng μL−1 TALEN mix (2.5 ng μL−1 oaBLG T1.1 + 2.5 ng μL−1 oaBLG T5.1) (5TM); (2) 5 ng μL−1 TALEN mix + 25 ng μL−1 pHR-hFIX plasmid (5TM+25pRH); or (3) 15 ng μL−1 TALEN mix (7.5 ng μL−1 oaBLG T1.1 + 7.5 ng μL−1 oaBLG T5.1) + 50 ng μL−1 pHR-hFIX (15TM+50pRH). A non-injected control (NIC) was also included. Embryo analysis was conducted on whole-genome amplified DNA from blastocysts, followed by PCR and sequencing. Non-parametric Fisher test was applied to detect significant differences among treatments. Although blastocyst rates for NIC and 5TM did not statistically differ, 5TM+25pRH and 15TM+50pRH groups resulted in lower blastocysts rates than the NIC [P < 0.05; 13/17 (76%), 6/15 (40%), 4/15 (26%) and 2/14 (14%) for NIC, 5TM, 5TM+25pRH and 15TM+50pRH respectively]. It was possible to detect the PCR product compatible with deletion of the entire region among TALEN target sites in 6/6 blastocysts (100%) from the group 5TM, 3/4 blastocysts (75%) from the group 5TM+25pRH and 2/2 (100%) blastocysts from the group 15TM+50pRH. HR was detected in 1/2 (50%) blastocysts injected with 15TM+50pRH and in 1/4 (25%) blastocysts injected with 5TM+25pRH, by PCR and sequencing of the PCR products. Our results indicate that TALEN combined with homologous recombination constitutes a powerful platform for the production of proteins of pharmaceutical interest under native regulatory sequences in the milk of genetically modified animals.

Dynamically Timed Stimulation of Corticolimbic Circuitry Activates a Stress-Compensatory Pathway

BACKGROUND

The prefrontal cortex plays a critical role in regulating emotional behaviors, and dysfunction of prefrontal cortex-dependent networks has been broadly implicated in mediating stress-induced behavioral disorders including major depressive disorder.

METHODS

Here we acquired multicircuit in vivo activity from eight cortical and limbic brain regions as mice were subjected to the tail suspension test (TST) and an open field test. We used a linear decoder to determine whether cellular responses across each of the cortical and limbic areas signal movement during the TST and open field test. We then performed repeat behavioral testing to identify which brain areas show cellular adaptations that signal the increase in immobility induced by repeat TST exposure.

RESULTS

The increase in immobility observed during repeat TST exposure is linked to a selective functional upregulation of cellular activity in infralimbic cortex and medial dorsal thalamus, and to an increase in the spatiotemporal dynamic interaction between these structures. Inducing this spatiotemporal dynamic using closed-loop optogenetic stimulation is sufficient to increase movement in the TST in stress-naive mice, while stimulating above the carrier frequency of this circuit suppressed movement. This demonstrates that the adaptations in infralimbic cortex-medial dorsal thalamus circuitry observed after stress reflect a compensatory mechanism whereby the brain drives neural systems to counterbalance stress effects.

CONCLUSIONS

Our findings provide evidence that targeting endogenous spatiotemporal dynamics is a potential therapeutic approach for treating stress-induced behavioral disorders, and that dynamics are a critical axis of manipulation for causal optogenetic studies.

Abstract 524: Characterizing the in vitro and in vivo effects of the PIM kinase inhibitor HS140 in triple-negative human breast cancer

Triple-negative breast cancer (TNBC) lacks expression of the estrogen receptor (ER), the progesterone receptor (PR) and the ERBB2 (also known as HER2) receptor, making it the worse subtype of all breast cancers. Currently, there are no molecular targeted therapies for this cancer and chemotherapy is only successful in a limited number of patients. Recent studies suggest that members of the oncogenic PIM kinase family, especially PIM-1, play a significant role in the growth of TNBC. However, there is very limited information on the role other PIM family members have in the growth and development of TNBCs. As an attempt to address this concern, we treated a panel of TNBC cell lines with HS140, a PIM-2 kinase inhibitor developed in the laboratory. Using cytotoxicity assays, we were able to demonstrate a decrease in anchorage-dependent growth of cell lines at different concentrations of HS140. Also, a triple negative breast cancer GEMM (C3TAg) was used for an efficacy study. Mice (FVB/N background) have C(3)SV40 T-antigen resulting in inactivation of p53 and Rb. Nine mice received HS140 treatment (80mg/kg BIW IP) and 14 left untreated for control (non-treatment [NT]). All mice were monitored for weight loss and timespan to tumor development 5 times weekly. Tumor volumes at 21 days were significantly (Mann-Whitney, p=0.0002) reduced in the treated cohort with a mean of 109mm3 (range of 0-5000) compared to untreated 1393mm3 (0-239). We observed no toxicities with body mass stable at the treatment dose of 80mg/kg. Additionally, three mice from untreated and three mice from treated cohorts were chosen for blood sampling pre- and post-treatment via a submandibular bleed; no significant differences were noted in WBC, RBC, PLT, or HGB between untreated and treated cohorts. Overall, these results suggest that other members of the PIM kinase family, including PIM-2, have an important function in the growth and development of TNBC and may serve as a potential molecular target for future therapeutics.

Citation Format: Michael Cobb, Lucas Hunter, David Carlson, David Darr, Timothy Haystead, Antonio T. Baines. Characterizing the in vitro and in vivo effects of the PIM kinase inhibitor HS140 in triple-negative human breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 524. doi:10.1158/1538-7445.AM2017-524

Dysregulation of Prefrontal Cortex-Mediated Slow-Evolving Limbic Dynamics Drives Stress-Induced Emotional Pathology

Circuits distributed across cortico-limbic brain regions compose the networks that mediate emotional behavior. The prefrontal cortex (PFC) regulates ultraslow (<1 Hz) dynamics across these networks, and PFC dysfunction is implicated in stress-related illnesses including major depressive disorder (MDD). To uncover the mechanism whereby stress-induced changes in PFC circuitry alter emotional networks to yield pathology, we used a multi-disciplinary approach including in vivo recordings in mice and chronic social defeat stress. Our network model, inferred using machine learning, linked stress-induced behavioral pathology to the capacity of PFC to synchronize amygdala and VTA activity. Direct stimulation of PFC-amygdala circuitry with DREADDs normalized PFC-dependent limbic synchrony in stress-susceptible animals and restored normal behavior. In addition to providing insights into MDD mechanisms, our findings demonstrate an interdisciplinary approach that can be used to identify the large-scale network changes that underlie complex emotional pathologies and the specific network nodes that can be used to develop targeted interventions.

Neuroprosthetic Decoder Training as Imitation Learning

Neuroprosthetic brain-computer interfaces function via an algorithm which decodes neural activity of the user into movements of an end effector, such as a cursor or robotic arm. In practice, the decoder is often learned by updating its parameters while the user performs a task. When the user's intention is not directly observable, recent methods have demonstrated value in training the decoder against a surrogate for the user's intended movement. Here we show that training a decoder in this way is a novel variant of an imitation learning problem, where an oracle or expert is employed for supervised training in lieu of direct observations, which are not available. Specifically, we describe how a generic imitation learning meta-algorithm, dataset aggregation (DAgger), can be adapted to train a generic brain-computer interface. By deriving existing learning algorithms for brain-computer interfaces in this framework, we provide a novel analysis of regret (an important metric of learning efficacy) for brain-computer interfaces. This analysis allows us to characterize the space of algorithmic variants and bounds on their regret rates. Existing approaches for decoder learning have been performed in the cursor control setting, but the available design principles for these decoders are such that it has been impossible to scale them to naturalistic settings. Leveraging our findings, we then offer an algorithm that combines imitation learning with optimal control, which should allow for training of arbitrary effectors for which optimal control can generate goal-oriented control. We demonstrate this novel and general BCI algorithm with simulated neuroprosthetic control of a 26 degree-of-freedom model of an arm, a sophisticated and realistic end effector.

Pre-Clovis occupation 14,550 years ago at the Page-Ladson site, Florida, and the peopling of the Americas

Stone tools and mastodon bones occur in an undisturbed geological context at the Page-Ladson site, Florida. Seventy-one radiocarbon ages show that ~14,550 calendar years ago (cal yr B.P.), people butchered or scavenged a mastodon next to a pond in a bedrock sinkhole within the Aucilla River. This occupation surface was buried by ~4 m of sediment during the late Pleistocene marine transgression, which also left the site submerged. Sporormiella and other proxy evidence from the sediments indicate that hunter-gatherers along the Gulf Coastal Plain coexisted with and utilized megafauna for ~2000 years before these animals became extinct at ~12,600 cal yr B.P. Page-Ladson expands our understanding of the earliest colonizers of the Americas and human-megafauna interaction before extinction.

The ADMSEP Milestones Project

OBJECTIVE

Credentialing bodies mandate that a medical school's curriculum be based upon recognized guidelines. Within the field of psychiatry, the Association of Directors of Medical Student Education in Psychiatry (ADMSEP) has previously published recommended guidelines for the pre-clinical and clerkship curriculum. Ongoing changes within the Liaison Committee on Medical Education's requirements for medical school curricula, and the publication of the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition, necessitated review of these guidelines.

METHODS

ADMSEP convened a task force of psychiatric educators to develop a consensus report outlining new guidelines. The ADMSEP membership reviewed and approved this final document.

RESULTS

The guidelines outline six core learning objectives with corresponding competencies. Each of these competencies specifies accompanying milestones to be achieved through the course of medical school.

CONCLUSIONS

ADMSEP believes these guidelines will aid educators in crafting a school's psychiatric curriculum. Clearly articulated milestones may foster the further development of validated educational and assessment tools by ADMSEP and other organizations.

Recovery of Native Renal Function in Patients with Hepatorenal Syndrome Following Combined Liver and Kidney Transplant with Mercaptoacetyltriglycine-3 Renogram: Developing a Methodology

Many patients with hepatorenal syndrome (HRS) end up receiving a combined liver and kidney transplant (CKLT) with preservation of native kidneys, specially type 1 HRS since is characterizes by a very rapid deterioration of renal function. Eventually, most of the patients regain renal function, but it is unknown if this is due to the transplanted kidney, the recovery of native renal function, or both. The aim of this study is to evaluate if there is recovery of native renal function in patients with HRS following CKLT. 22 patients (16 men; 6 women) with history of HRS and status post CKLT were studied. Mercapto-acetyltriglycine-3 renograms in the anterior and posterior views with the three kidneys in the field of view were simultaneously acquired. The renograms were analyzed by creating regions of interest around the transplanted and native kidneys. Relative contribution to the renal function, clearance, and effective renal plasma flow for the transplanted and native kidneys were obtained. 1/22 (4.5%) patients presented with a very poor functioning transplanted kidney, in 15/22 (68%) cases the combined native renal function was markedly poorer than the transplanted renal function and in 6/22 (27%) native kidneys showed a contribution to the renal function similar to the transplanted kidney. In conclusion, our series show that around 32% of the HRS patients recovered their native renal function after CKLT. Identification of common factors that affect recovery of native renal function may help to avoid unnecessary renal transplants, significantly reducing morbidity and cost, while facilitating a reallocation of scarce donor resources.

Laryngotracheal mucormycosis: Report of a case

Airway mucormycosis is a deadly opportunistic infection that affects immunocompromised persons, particularly diabetics and those undergoing chemotherapy. Although it is typically a pulmonary or sinonasal infection, mucormycosis can affect the larynx and trachea, with devastating results. We report the case of a 46-year-old man with human immunodeficiency virus infection, hepatitis C infection, neurosyphilis, and recently diagnosed Burkitt lymphoma who presented with dysphonia and stridor after receiving one dose of intrathecal chemotherapy. Flexible laryngoscopy detected the presence of fibrinous material that was obstructing nearly the entire glottis. Surgical debridement revealed a firm mucosal attachment; there was little bleeding when it was removed. After debridement, the patient's dyspnea improved only to recur 2 days later. After an awake tracheotomy, laryngoscopy and bronchoscopy identified necrosis extending from the supraglottic area to the carina tracheae. Biopsies demonstrated hyphal architecture consistent with mucormycosis. Despite continued debridements, the fibrinous material reaccumulated. The patient was placed in hospice care; his airway remained patent, but he died from other causes several weeks after presentation. The management of airway mucormycosis is challenging and complex. Fungal airway infections should be considered in the differential diagnosis of an immunosuppressed patient who presents with dyspnea, dysphonia, and vocal fold immobility. Timely diagnosis and management are critical for a successful outcome, although the prognosis is poor if the infection is widespread, even with the best of efforts.

Future Directions for the World Climate Research Programme

The worldwide climate research community has talent, dedication, and a clear sense of knowledge gaps. It needs to close those gaps and convey its messages effectively to user communities.

Effects of aspirin & simvastatin and aspirin, simvastatin, & lipoic acid on heme oxygenase-1 in healthy human subjects

BACKGROUND

Heme oxygenase 1 (HO-1) degrades heme and protects against oxidative stress. In vitro and animal models suggest that HO-1 is beneficial in several diseases (e.g., postoperative ileus, gastroparesis, acute pancreatitis, and colitis). However, the only drugs (i.e., hemin and heme arginate) which pharmacologically upregulate HO-1 in humans are expensive and can only be administered intravenously. Our aims were to compare the effects of placebo, aspirin, and simvastatin alone, and with α-lipoic acid, on HO-1 protein concentration and activity in humans.

METHODS

This randomized, double-blind, placebo-controlled study compared the effects of three oral regimens administered for 7 days, i.e., placebo; aspirin (325 mg twice daily) and simvastatin (40 mg twice daily); aspirin, simvastatin, and the sodium salt of R- α-lipoic acid (NaRLA, 600 mg three times daily) on markers of HO-1 activation (i.e., plasma HO-1 protein concentration and venous monocyte HO-1 protein activity) in 18 healthy subjects (14 females). Markers of HO-1 activation were evaluated at baseline, days 2, and 7.

KEY RESULTS

Baseline HO-1 protein concentrations and activity were similar among the three groups. Compared to placebo, aspirin and simvastatin combined, or together with NaRLA did not affect HO-1 protein concentration or activity at 2 or 7 days. HO-1 protein concentrations and activity were correlated on day 7 (r = 0.75, p = 0.0004) but not at baseline and on day 2.

CONCLUSIONS & INFERENCES

At therapeutic doses, aspirin, simvastatin, and α-lipoic acid do not increase plasma HO-1 protein concentration or venous monocyte HO-1 activity in healthy humans.