Evidence of a Uranium-Paddlewheel Node in a Catecholate-Based Metal-Organic Framework.

The interactions between uranium and non-innocent organic species are an essential component of fundamental uranium redox chemistry. However, they have seldom been explored in the context of multidimensional, porous materials. Uranium-based metal-organic frameworks (MOFs) offer a new angle to study these interactions, as these self-assembled species stabilize uranium species through immobilization by organic linkers within a crystalline framework, while potentially providing a method for adjusting metal oxidation state through coordination of non-innocent linkers. We report the synthesis of the MOF NU-1700, assembled from U4+ -paddlewheel nodes and catecholate-based linkers. We propose this highly unusual structure, which contains two U4+ ions in a paddlewheel built from four linkers-a first among uranium materials-as a result of extensive characterization via powder X-ray diffraction (PXRD), sorption, transmission electron microscopy (TEM), and thermogravimetric analysis (TGA), in addition to density functional theory (DFT) calculations.

Exploring mechanistic routes for light alkane oxidation with an iron-triazolate metal-organic framework.

In this work, we computationally explore the formation and subsequent reactivity of various iron-oxo species in the iron-triazolate framework Fe2(µ-OH)2(bbta) (H2bbta = 1H,5H-benzo(1,2-d:4,5-d')bistriazole) for the catalytic activation of strong C-H bonds. With the direct conversion of methane to methanol as the probe reaction of interest, we use density functional theory (DFT) calculations to evaluate multiple mechanistic pathways in the presence of either N2O or H2O2 oxidants. These calculations reveal that a wide range of transition metal-oxo sites - both terminal and bridging - are plausible in this family of metal-organic frameworks, making it a unique platform for comparing the electronic structure and reactivity of different proposed active site motifs. Based on the DFT calculations, we predict that Fe2(µ-OH)2(bbta) would exhibit a relatively low barrier for N2O activation and energetically favorable formation of an [Fe(O)]2+ species that is capable of oxidizing C-H bonds. In contrast, the use of H2O2 as the oxidant is predicted to yield an assortment of bridging iron-oxo sites that are less reactive. We also find that abstracting oxo ligands can exhibit a complex mixture of both positive and negative spin density, which may have broader implications for relating the degree of radical character to catalytic activity. In general, we consider the coordinatively unsaturated iron sites to be promising for oxidation catalysis, and we provide several recommendations on how to further tune the catalytic properties of this family of metal-triazolate frameworks.

Fine-Tuning a Robust Metal-Organic Framework toward Enhanced Clean Energy Gas Storage.

The development of adsorbents with molecular precision offers a promising strategy to enhance storage of hydrogen and methane─considered the fuel of the future and a transitional fuel, respectively─and to realize a carbon-neutral energy cycle. Herein we employ a postsynthetic modification strategy on a robust metal-organic framework (MOF), MFU-4l, to boost its storage capacity toward these clean energy gases. MFU-4l-Li displays one of the best volumetric deliverable hydrogen capacities of 50.2 g L-1 under combined temperature and pressure swing conditions (77 K/100 bar → 160 K/5 bar) while maintaining a moderately high gravimetric capacity of 9.4 wt %. Moreover, MFU-4l-Li demonstrates impressive methane storage performance with a 5-100 bar usable capacity of 251 cm3 (STP) cm-3 (0.38 g g-1) and 220 cm3 (STP) cm-3 (0.30 g g-1) at 270 and 296 K, respectively. Notably, these hydrogen and methane storage capacities are significantly improved compared to those of its isoreticular analogue, MFU-4l, and place MFU-4l-Li among the best MOF-based materials for this application.

Tuning the Redox Activity of Metal-Organic Frameworks for Enhanced, Selective O2 Binding: Design Rules and Ambient Temperature O2 Chemisorption in a Cobalt-Triazolate Framework.

Metal-organic frameworks (MOFs) with coordinatively unsaturated metal sites are appealing as adsorbent materials due to their tunable functionality and ability to selectively bind small molecules. Through the use of computational screening methods based on periodic density functional theory, we investigate O2 and N2 adsorption at the coordinatively unsaturated metal sites of several MOF families. A variety of design handles are identified that can be used to modify the redox activity of the metal centers, including changing the functionalization of the linkers (replacing oxido donors with sulfido donors), anion exchange of bridging ligands (considering µ-Br-, µ-Cl-, µ-F-, µ-SH-, or µ-OH- groups), and altering the formal oxidation state of the metal. As a result, we show that it is possible to tune the O2 affinity at the open metal sites of MOFs for applications involving the strong and/or selective binding of O2. In contrast with O2 adsorption, N2 adsorption at open metal sites is predicted to be relatively weak across the MOF dataset, with the exception of MOFs containing synthetically elusive V2+ open metal sites. As one example from the screening study, we predicted that exchanging the µ-Cl- ligands of M2Cl2(BBTA) (H2BBTA = 1H,5H-benzo(1,2-d:4,5-d')bistriazole) with µ-OH- groups would significantly enhance the strength of O2 adsorption at the open metal sites without a corresponding increase in the N2 affinity. Experimental investigation of Co2Cl2(BBTA) and Co2(OH)2(BBTA) confirms that the former exhibits weak physisorption of both N2 and O2, whereas the latter is capable of chemisorbing O2 at room temperature in a highly selective manner. The O2 chemisorption behavior is attributed to the greater electron-donating character of the µ-OH- ligands and the presence of H-bonding interactions between the µ-OH- bridging ligands and the reduced O2 adsorbate.

Comparing GGA, GGA+U, and meta-GGA functionals for redox-dependent binding at open metal sites in metal-organic frameworks.

Metal-organic frameworks (MOFs) with open metal sites have been widely investigated for the selective adsorption of small molecules via redox mechanisms where charge transfer can take place between the binding site and the adsorbate of interest. Quantum-chemical screening methods based on density functional theory have emerged as a promising route to accelerate the discovery of MOFs with enhanced binding affinities toward various adsorbates. However, the success of this approach is linked to the accuracy of the underlying density functional approximations (DFAs). In this work, we compare commonly used generalized gradient approximation (GGA), GGA+U, and meta-GGA exchange-correlation functionals in modeling redox-dependent binding at open metal sites in MOFs using O2 and N2 as representative small molecules. We find that the self-interaction error inherent to the widely used Perdew, Burke, and Ernzerhof (PBE) GGA predicts metal sites that are artificially redox-active, as evidenced by their strong binding affinities, short metal-adsorbate bond distances, and large degree of charge transfer. The incorporation of metal-specific, empirical Hubbard U corrections based on the transition metal oxide literature systematically reduces the redox activity of the open metal sites, often improving agreement with experiment. Additionally, the binding behavior shifts from strong chemisorption to weaker physisorption as a function of U. The M06-L meta-GGA typically predicts binding energies between those of PBE-D3(BJ) and PBE-D3(BJ)+U when using empirically derived U values from the transition metal oxide literature. Despite the strong sensitivity of the binding affinities toward a given DFA, the GGA, GGA+U, and meta-GGA approaches often yield the same qualitative trends and structure-property relationships.

High-Valent Metal-Oxo Species at the Nodes of Metal-Triazolate Frameworks: The Effects of Ligand Exchange and Two-State Reactivity for C-H Bond Activation.

Through quantum-chemical calculations, we investigate a family of metal-organic frameworks (MOFs) containing triazolate linkers, M2 X2 (BBTA) (M=metal, X=bridging anion, H2 BBTA=1H,5H-benzo(1,2-d:4,5-d')bistriazole), for their ability to form terminal metal-oxo sites and subsequently activate the C-H bond of methane. By varying the metal and bridging anion in the framework, we show how to significantly tune the reactivity of this series of MOFs. The electronic structure of the metal-oxo active site is analyzed for each combination of metal and bridging ligand, and we find that spin density localized on the oxo ligand is not an inherent requirement for low C-H activation barriers. For the Mn- and Fe-containing frameworks, a transition from ferromagnetic to antiferromagnetic coupling between the metal binding site and terminal oxo ligand during the C-H activation process can greatly reduce the kinetic barrier, a unique case of two-state reactivity without a change in the net spin multiplicity.

Identifying promising metal-organic frameworks for heterogeneous catalysis via high-throughput periodic density functional theory.

Metal-organic frameworks (MOFs) are a class of nanoporous materials with highly tunable structures in terms of both chemical composition and topology. Due to their tunable nature, high-throughput computational screening is a particularly appealing method to reduce the time-to-discovery of MOFs with desirable physical and chemical properties. In this work, a fully automated, high-throughput periodic density functional theory (DFT) workflow for screening promising MOF candidates was developed and benchmarked, with a specific focus on applications in catalysis. As a proof-of-concept, we use the high-throughput workflow to screen MOFs containing open metal sites (OMSs) from the Computation-Ready, Experimental MOF database for the oxidative C-H bond activation of methane. The results from the screening process suggest that, despite the strong C-H bond strength of methane, the main challenge from a screening standpoint is the identification of MOFs with OMSs that can be readily oxidized at moderate reaction conditions. © 2019 Wiley Periodicals, Inc.

Tetrazine-Linked Covalent Organic Frameworks With Acid Sensing and Photocatalytic Activity.

The first synthesis and comprehensive characterization of two vinyl tetrazine-linked covalent organic frameworks (COF), TA-COF-1 and TA-COF-2, are reported. These materials exhibit high crystallinity and high specific surface areas of 1323 and 1114 m2 g-1. The COFs demonstrate favorable band positions and narrow band gaps suitable for light-driven applications. These advantages enable TA-COFs to act as reusable metal-free photocatalysts in the arylboronic acids oxidation and light-induced coupling of benzylamines. In addition, these TA-COFs show acid sensing capabilities, exhibiting visible and reversible color changes upon exposure to HCl solution, HCl vapor, and NH3 vapor. Further, the TA-COFs outperform a wide range of previously reported COF photocathodes. The tetrazine linker in the COF skeleton represents a significant advancement in the field of COF synthesis, enhancing the separation efficiency of charge carriers during the photoreaction and contributing to their photocathodic properties. TA-COFs can also degrade 5-nitro-1,2,4-triazol-3-one (NTO), an insensitive explosive present in industrial wastewater, in 20 min in a sunlight-driven photocatalytic process; thus, revealing dual functionality of the protonated TA-COFs as both photodegradation and Brønsted acid catalysts. This pioneering work opens new avenues for harnessing the potential of the tetrazine linker in COF-based materials, facilitating advances in catalysis, sensing, and other related fields.

Structured information extraction from scientific text with large language models.

Extracting structured knowledge from scientific text remains a challenging task for machine learning models. Here, we present a simple approach to joint named entity recognition and relation extraction and demonstrate how pretrained large language models (GPT-3, Llama-2) can be fine-tuned to extract useful records of complex scientific knowledge. We test three representative tasks in materials chemistry: linking dopants and host materials, cataloging metal-organic frameworks, and general composition/phase/morphology/application information extraction. Records are extracted from single sentences or entire paragraphs, and the output can be returned as simple English sentences or a more structured format such as a list of JSON objects. This approach represents a simple, accessible, and highly flexible route to obtaining large databases of structured specialized scientific knowledge extracted from research papers.

Free-atom-like d states beyond the dilute limit of single-atom alloys.

Through a data-mining and high-throughput density functional theory approach, we identify a diverse range of metallic compounds that are predicted to have transition metals with "free-atom-like" d states that are highly localized in terms of their energetic distribution. Design principles that favor the formation of localized d states are uncovered, among which we note that site isolation is often necessary but that the dilute limit, as in most single-atom alloys, is not a pre-requisite. Additionally, the majority of localized d state transition metals identified from the computational screening study exhibit partial anionic character due to charge transfer from neighboring metal species. Using CO as a representative probe molecule, we show that localized d states for Rh, Ir, Pd, and Pt tend to reduce the binding strength of CO compared to their pure elemental analogues, whereas this does not occur as consistently for the Cu binding sites. These trends are rationalized through the d-band model, which suggests that the significantly reduced d-band width results in an increased orthogonalization energy penalty upon CO chemisorption. With the multitude of inorganic solids that are predicted to have highly localized d states, the results of the screening study are likely to result in new avenues for heterogeneous catalyst design from an electronic structure perspective.

An Ecosystem for Digital Reticular Chemistry.

The vastness of the materials design space makes it impractical to explore using traditional brute-force methods, particularly in reticular chemistry. However, machine learning has shown promise in expediting and guiding materials design. Despite numerous successful applications of machine learning to reticular materials, progress in the field has stagnated, possibly because digital chemistry is more an art than a science and its limited accessibility to inexperienced researchers. To address this issue, we present mofdscribe, a software ecosystem tailored to novice and seasoned digital chemists that streamlines the ideation, modeling, and publication process. Though optimized for reticular chemistry, our tools are versatile and can be used in nonreticular materials research. We believe that mofdscribe will enable a more reliable, efficient, and comparable field of digital chemistry.

Relative Effectiveness of BNT162b2, mRNA-1273, and Ad26.COV2.S Vaccines and Homologous Boosting in Preventing COVID-19 in Adults in the US.

Background: Few head-to-head comparisons have been performed on the real-world effectiveness of coronavirus disease 2019 (COVID-19) booster vaccines. We evaluated the relative effectiveness (rVE) of a primary series of mRNA-1273 vs BNT162b2 and Ad26.COV2.S and a homologous mRNA booster against any medically attended, outpatient, and hospitalized COVID-19. Methods: A data set linking primary care electronic medical records with medical claims data was used for this retrospective cohort study of US patients age ≥18 years vaccinated with a primary series between February and October 2021 (Part 1) and a homologous mRNA booster between October 2021 and January 2022 (Part 2). Adjusted hazard ratios (HRs) were derived from 1:1 matching adjusted across potential covariates. rVE was (1 - HRadjusted) × 100. Additional analysis was performed across regions and age groups. Results: Following adjustment, Part 1 rVE for mRNA-1273 vs BNT162b2 was 23% (95% CI, 22%-25%), 23% (95% CI, 22%-25%), and 19% (95% CI, 14%-24%), while the rVE for mRNA-1273 vs Ad26.COV2.S was 50% (95% CI, 48%-51%), 50% (95% CI, 48%-52%), and 57% (95% CI, 53%-61%) against any medically attended, outpatient, and hospitalized COVID-19, respectively. The adjusted rVE in Part 2 for mRNA-1273 vs BNT162b2 was 14% (95% CI, 10%-18%), 13% (95% CI, 8%-17%), and 19% (95% CI, 1%-34%) against any medically attended, outpatient, and hospitalized COVID-19, respectively. rVE against medically attended COVID-19 was higher in adults age ≥65 years (35%; 95% CI, 24%-47%) than in those age 18-64 years (13%; 95% CI, 9%-17%) after the booster. Conclusions: In this study, mRNA-1273 was more effective than BNT162b2 or Ad26.COV2.S following a primary series during the Delta-dominant period and more effective than BNT162b2 as a booster during the Omicron-dominant period.

Comparative Effectiveness of Bivalent (Original/Omicron BA.4/BA.5) COVID-19 Vaccines in Adults.

The emergence of Omicron variants coincided with declining vaccine-induced protection against SARS-CoV-2. Two bivalent mRNA vaccines, mRNA-1273.222 (Moderna) and BNT162b2 Bivalent (Pfizer-BioNTech), were developed to provide greater protection against the predominate circulating variants by including mRNA that encodes both the ancestral (original) strain and BA.4/BA.5. We estimated their relative vaccine effectiveness (rVE) in preventing COVID-19-related outcomes in the US using a nationwide dataset linking primary care electronic health records and pharmacy/medical claims data. The study population (aged ≥18 years) received either vaccine between 31 August 2022 and 28 February 2023. We used propensity score weighting to adjust for baseline differences between groups. We estimated the rVE against COVID-19-related hospitalizations (primary outcome) and outpatient visits (secondary) for 1,034,538 mRNA-1273.222 and 1,670,666 BNT162b2 Bivalent vaccine recipients, with an adjusted rVE of 9.8% (95% confidence interval: 2.6-16.4%) and 5.1% (95% CI: 3.2-6.9%), respectively, for mRNA-1273.222 versus BNT162b2 Bivalent. The incremental relative effectiveness was greater among adults ≥ 65; the rVE against COVID-19-related hospitalizations and outpatient visits in these patients was 13.5% (95% CI: 5.5-20.8%) and 10.7% (8.2-13.1%), respectively. Overall, we found greater effectiveness of mRNA-1273.222 compared with the BNT162b2 Bivalent vaccine in preventing COVID-19-related hospitalizations and outpatient visits, with increased benefits in older adults.

Neural coding of taste by simultaneously recorded cells in the nucleus of the solitary tract of the rat.

The nucleus of the solitary tract (NTS) receives input from taste buds on the rostral tongue from the chorda tympani (CT) nerve. How this input is processed by the NTS was the subject of the present investigation. Here we used tetrodes to record from pairs or small groups of NTS cells as they responded to taste stimuli or electrical stimulation of the CT nerve in urethane-anesthetized rats. Once a pair (or small group) of NTS cells were isolated and identified as showing an evoked response to CT nerve stimulation, taste stimuli were presented in separate trials. Tastants consisted of 0.1 M NaCl, 0.01 M HCl, 0.01 M quinine HCl, and 0.5 M sucrose. Responses to various patterns of CT stimulation were then recorded. Functional connections among simultaneously recorded NTS cells were implied from analysis of cross-correlation functions of spike trains. We identified four groups of cells, not all of which responded to taste, with staggered latencies of response to CT nerve stimulation, ranging from ∼3 to 35 ms in ∼8- to 12-ms increments. Analyses of putative functional connectivity along with latencies of CT-evoked responses suggested that CT input arrives at the NTS in pulses or waves, each of which activates recurrent excitatory connections among NTS cells. These actions may amplify the incoming signal and refine its temporal pattern.

Three Newly Recognized Likely Pathogenic Gene Variants Associated with Hereditary Transthyretin Amyloidosis.

INTRODUCTION: Hereditary transthyretin amyloidosis (ATTRv [variant]) is a clinically heterogeneous, progressively debilitating, fatal disease resulting from the deposition of insoluble amyloid fibrils in various organs and tissues. Early diagnosis of ATTRv can be facilitated with genetic testing; however, such testing of the TTR gene identifies variants of uncertain significance (VUS) in a minority of cases, a small percentage of which have the potential to be pathogenic. The Akcea/Ambry VUS Initiative is dedicated to gathering molecular, clinical, and inheritance data for each TTR VUS identified by genetic testing programs to reclassify TTR variants to a clinically actionable status (e.g., variant likely pathogenic [VLP]) where appropriate. METHODS: Classification criteria used here, based on recommendations from the American College of Medical Genetics and Genomics, are stringent and comprehensive, requiring distinct lines of evidence supporting pathogenesis. RESULTS: Three TTR variants have been reclassified from VUS to VLP, including c.194C>T (p.A65V), c.172G>C (p.D58H), and c.239C>T (p.T80I). In each case, the totality of genetic, structural, and clinical evidence provided strong support for pathogenicity. CONCLUSIONS: Based on several lines of evidence, three TTR VUS were reclassified as VLP, resulting in a high likelihood of disease diagnosis for those and subsequent patients as well as at-risk family members.

Temporal coding of taste in the parabrachial nucleus of the pons of the rat.

Recent studies have provided evidence that temporal coding contributes significantly to encoding taste stimuli at the first central relay for taste, the nucleus of the solitary tract (NTS). However, it is not known whether this coding mechanism is also used at the next synapse in the central taste pathway, the parabrachial nucleus of the pons (PbN). In the present study, electrophysiological responses to taste stimuli (sucrose, NaCl, HCl, and quinine) were recorded from 44 cells in the PbN of anesthetized rats. In 29 cells, the contribution of the temporal characteristics of the response to the discrimination of various taste qualities was assessed. A family of metrics that quantifies the similarity of two spike trains in terms of spike count and spike timing was used. Results showed that spike timing in 14 PbN cells (48%) conveyed a significant amount of information about taste quality, beyond what could be conveyed by spike count alone. In another 14 cells (48%), the rate envelope (time course) of the response contributed significantly more information than spike count alone. Across cells there was a significant correlation (r = 0.51; P < 0.01) between breadth of tuning and the proportion of information conveyed by temporal dynamics. Comparison with previous data from the NTS (Di Lorenzo PM and Victor JD. J Neurophysiol 90: 1418-31, 2003 and J Neurophysiol 97: 1857-1861, 2007) showed that temporal coding in the NTS occurred in a similar proportion of cells and contributed a similar fraction of the total information at the same average level of temporal precision, even though trial-to-trial variability was higher in the PbN than in the NTS. These data suggest that information about taste quality conveyed by the temporal characteristics of evoked responses is transmitted with high fidelity from the NTS to the PbN.

ATTR amyloidosis during the COVID-19 pandemic: insights from a global medical roundtable.

BACKGROUND: The global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causing the ongoing coronavirus disease 2019 (COVID-19) pandemic has raised serious concern for patients with chronic disease. A correlation has been identified between the severity of COVID-19 and a patient's preexisting comorbidities. Although COVID-19 primarily involves the respiratory system, dysfunction in multiple organ systems is common, particularly in the cardiovascular, gastrointestinal, immune, renal, and nervous systems. Patients with amyloid transthyretin (ATTR) amyloidosis represent a population particularly vulnerable to COVID-19 morbidity due to the multisystem nature of ATTR amyloidosis. MAIN BODY: ATTR amyloidosis is a clinically heterogeneous progressive disease, resulting from the accumulation of amyloid fibrils in various organs and tissues. Amyloid deposition causes multisystem clinical manifestations, including cardiomyopathy and polyneuropathy, along with gastrointestinal symptoms and renal dysfunction. Given the potential for exacerbation of organ dysfunction, physicians note possible unique challenges in the management of patients with ATTR amyloidosis who develop multiorgan complications from COVID-19. While the interplay between COVID-19 and ATTR amyloidosis is still being evaluated, physicians should consider that the heightened susceptibility of patients with ATTR amyloidosis to multiorgan complications might increase their risk for poor outcomes with COVID-19. CONCLUSION: Patients with ATTR amyloidosis are suspected to have a higher risk of morbidity and mortality due to age and underlying ATTR amyloidosis-related organ dysfunction. While further research is needed to characterize this risk and management implications, ATTR amyloidosis patients might require specialized management if they develop COVID-19. The risks of delaying diagnosis or interrupting treatment for patients with ATTR amyloidosis should be balanced with the risk of exposure in the health care setting. Both physicians and patients must adapt to a new construct for care during and possibly after the pandemic to ensure optimal health for patients with ATTR amyloidosis, minimizing treatment interruptions.

Taste-specific cell assemblies in a biologically informed model of the nucleus of the solitary tract.

Although the cellular organization of many primary sensory nuclei has been well characterized, questions remain about the functional architecture of the first central relay for gustation, the rostral nucleus of the solitary tract (NTS). Here we used electrophysiological data recorded from single cells in the NTS to inform a network model of taste processing. Previous studies showed that electrical stimulation of the chorda tympani (CT) nerve initiates two types of inhibitory influences with different time courses in separate groups of NTS cells. Each type of inhibition targeted cells with distinct taste response properties. Further analyses of these data identified three NTS cell types differentiated by their latency of evoked response, time course of CT evoked inhibition, and degree of selectivity across taste qualities. Based on these results, we designed a model of the NTS consisting of discrete, reciprocally connected, stimulus-specific "cell" assemblies. Input to the network of integrate-and-fire model neurons was based on electrophysiological recordings from the CT nerve. Following successful simulation of paired-pulse CT stimulation, the network was tested for its ability to discriminate between two "taste" stimuli. Network dynamics of the model produced biologically plausible responses from each unit type and enhanced discrimination between taste qualities. We propose that an interactive network of taste quality specific cell assemblies, similar to our model, may account for the coherence in across-neuron patterns of NTS responses between similar tastants.

Hippocampal-prefrontal theta-gamma coupling during performance of a spatial working memory task.

Cross-frequency coupling supports the organization of brain rhythms and is present during a range of cognitive functions. However, little is known about whether and how long-range cross-frequency coupling across distant brain regions subserves working memory. Here we report that theta-slow gamma coupling between the hippocampus and medial prefrontal cortex (mPFC) is augmented in a genetic mouse model of cognitive dysfunction. This increased cross-frequency coupling is observed specifically when the mice successfully perform a spatial working memory task. In wild-type mice, increasing task difficulty by introducing a long delay or by optogenetically interfering with encoding, also increases theta-gamma coupling during correct trials. Finally, epochs of high hippocampal theta-prefrontal slow gamma coupling are associated with increased synchronization of neurons within the mPFC. These findings suggest that enhancement of theta-slow gamma coupling reflects a compensatory mechanism to maintain spatial working memory performance in the setting of increased difficulty.

Electrophysiological endophenotypes in rodent models of schizophrenia and psychosis.

Schizophrenia is caused by a diverse array of risk factors and results in a similarly diverse set of symptoms. Electrophysiological endophenotypes lie between risks and symptoms and have the potential to link the two. Electrophysiological studies in rodent models, described here, demonstrate that widely differing risk factors result in a similar set of core electrophysiological endophenotypes, suggesting the possibility of a shared neurobiological substrate.