ASCL1 represses a SOX9+ neural crest stem-like state in small cell lung cancer.

ASCL1 is a neuroendocrine lineage-specific oncogenic driver of small cell lung cancer (SCLC), highly expressed in a significant fraction of tumors. However, ∼25% of human SCLC are ASCL1-low and associated with low neuroendocrine fate and high MYC expression. Using genetically engineered mouse models (GEMMs), we show that alterations in Rb1/Trp53/Myc in the mouse lung induce an ASCL1+ state of SCLC in multiple cells of origin. Genetic depletion of ASCL1 in MYC-driven SCLC dramatically inhibits tumor initiation and progression to the NEUROD1+ subtype of SCLC. Surprisingly, ASCL1 loss promotes a SOX9+ mesenchymal/neural crest stem-like state and the emergence of osteosarcoma and chondroid tumors, whose propensity is impacted by cell of origin. ASCL1 is critical for expression of key lineage-related transcription factors NKX2-1, FOXA2, and INSM1 and represses genes involved in the Hippo/Wnt/Notch developmental pathways in vivo. Importantly, ASCL1 represses a SOX9/RUNX1/RUNX2 program in vivo and SOX9 expression in human SCLC cells, suggesting a conserved function for ASCL1. Together, in a MYC-driven SCLC model, ASCL1 promotes neuroendocrine fate and represses the emergence of a SOX9+ nonendodermal stem-like fate that resembles neural crest.

Synchronous inhibitory pathways create both efficiency and diversity in the retina.

Sensory receptive fields combine features that originate in different neural pathways. Retinal ganglion cell receptive fields compute intensity changes across space and time using a peripheral region known as the surround, a property that improves information transmission about natural scenes. The visual features that construct this fundamental property have not been quantitatively assigned to specific interneurons. Here, we describe a generalizable approach using simultaneous intracellular and multielectrode recording to directly measure and manipulate the sensory feature conveyed by a neural pathway to a downstream neuron. By directly controlling the gain of individual interneurons in the circuit, we show that rather than transmitting different temporal features, inhibitory horizontal cells and linear amacrine cells synchronously create the linear surround at different spatial scales and that these two components fully account for the surround. By analyzing a large population of ganglion cells, we observe substantial diversity in the relative contribution of amacrine and horizontal cell visual features while still allowing individual cells to increase information transmission under the statistics of natural scenes. Established theories of efficient coding have shown that optimal information transmission under natural scenes allows a diverse set of receptive fields. Our results give a mechanism for this theory, showing how distinct neural pathways synthesize a sensory computation and how this architecture both generates computational diversity and achieves the objective of high information transmission.

Protein3D: Enabling analysis and extraction of metal-containing sites from the Protein Data Bank with molSimplify.

Metalloenzymes catalyze a wide range of chemical transformations, with the active site residues playing a key role in modulating chemical reactivity and selectivity. Unlike smaller synthetic catalysts, a metalloenzyme active site is embedded in a larger protein, which makes interrogation of electronic properties and geometric features with quantum mechanical calculations challenging. Here we implement the ability to fetch crystallographic structures from the Protein Data Bank and analyze the metal binding sites in the program molSimplify. We show the usefulness of the newly created protein3D class to extract the local environment around non-heme iron enzymes containing a two histidine motif and prepare 372 structures for quantum mechanical calculations. Our implementation of protein3D serves to expand the range of systems molSimplify can be used to analyze and will enable high-throughput study of metal-containing active sites in proteins.

Conformal antireflection coatings for optical dome covers by atomic layer deposition.

Complex 3D-shaped optics are difficult to coat with conventional technologies. In this research, large top-open optical glass cubes with a 100 mm side length were functionalized to simulate large dome-shaped optics. Antireflection coatings for the visible range (420-670 nm) and for a single wavelength (550 nm) were applied by atomic layer deposition simultaneously on two and six demonstrators, respectively. Reflectance measurements on both the inner and outer glass surfaces confirm a conformal AR coating with a residual reflectance significantly below 0.3% for visible wavelengths and 0.2% for single wavelengths on nearly the entire surface of the cubes.

Probing the Mechanism of Isonitrile Formation by a Non-Heme Iron(II)-Dependent Oxidase/Decarboxylase.

The isonitrile moiety is an electron-rich functionality that decorates various bioactive natural products isolated from diverse kingdoms of life. Isonitrile biosynthesis was restricted for over a decade to isonitrile synthases, a family of enzymes catalyzing a condensation reaction between l-Trp/l-Tyr and ribulose-5-phosphate. The discovery of ScoE, a non-heme iron(II) and α-ketoglutarate-dependent dioxygenase, demonstrated an alternative pathway employed by nature for isonitrile installation. Biochemical, crystallographic, and computational investigations of ScoE have previously been reported, yet the isonitrile formation mechanism remains obscure. In the present work, we employed in vitro biochemistry, chemical synthesis, spectroscopy techniques, and computational simulations that enabled us to propose a plausible molecular mechanism for isonitrile formation. Our findings demonstrate that the ScoE reaction initiates with C5 hydroxylation of (R)-3-((carboxymethyl)amino)butanoic acid to generate 1, which undergoes dehydration, presumably mediated by Tyr96 to synthesize 2 in a trans configuration. (R)-3-isocyanobutanoic acid is finally generated through radical-based decarboxylation of 2, instead of the common hydroxylation pathway employed by this enzyme superfamily.

Robust and replicable measurement for prepulse inhibition of the acoustic startle response.

Measuring animal behavior in the context of experimental manipulation is critical for modeling, and understanding neuropsychiatric disease. Prepulse inhibition of the acoustic startle response (PPI) is a behavioral phenomenon studied extensively for this purpose, but the results of PPI studies are often inconsistent. As a result, the utility of this phenomenon remains uncertain. Here, we deconstruct the phenomenon of PPI and confirm several limitations of the methodology traditionally utilized to describe PPI, including that the underlying startle response has a non-Gaussian distribution, and that the traditional PPI metric changes with different stimuli. We then develop a novel model that reveals PPI to be a combination of the previously appreciated scaling of the startle response, as well as a scaling of sound processing. Using our model, we find no evidence for differences in PPI in a rat model of Fragile-X Syndrome (FXS) compared with wild-type controls. These results in the rat provide a reliable methodology that could be used to clarify inconsistent PPI results in mice and humans. In contrast, we find robust differences between wild-type male and female rats. Our model allows us to understand the nature of these differences, and we find that both the startle-scaling and sound-scaling components of PPI are a function of the baseline startle response. Males and females differ specifically in the startle-scaling, but not the sound-scaling, component of PPI. These findings establish a robust experimental and analytical approach that has the potential to provide a consistent biomarker of brain function.

Memory Alone Does Not Account for the Way Rats Learn a Simple Spatial Alternation Task.

Animal behavior provides context for understanding disease models and physiology. However, that behavior is often characterized subjectively, creating opportunity for misinterpretation and misunderstanding. For example, spatial alternation tasks are treated as paradigmatic tools for examining memory; however, that link is actually an assumption. To test this assumption, we simulated a reinforcement learning (RL) agent equipped with a perfect memory process. We found that it learns a simple spatial alternation task more slowly and makes different errors than a group of male rats, illustrating that memory alone may not be sufficient to capture the behavior. We demonstrate that incorporating spatial biases permits rapid learning and enables the model to fit rodent behavior accurately. Our results suggest that even simple spatial alternation behaviors reflect multiple cognitive processes that need to be taken into account when studying animal behavior.SIGNIFICANCE STATEMENT Memory is a critical function for cognition whose impairment has significant clinical consequences. Experimental systems aimed at testing various sorts of memory are therefore also central. However, experimental designs to test memory are typically based on intuition about the underlying processes. We tested this using a popular behavioral paradigm: a spatial alternation task. Using behavioral modeling, we show that the straightforward intuition that these tasks just probe spatial memory fails to account for the speed at which rats learn or the types of errors they make. Only when memory-independent dynamic spatial preferences are added can the model learn like the rats. This highlights the importance of respecting the complexity of animal behavior to interpret neural function and validate disease models.

Humanin induces conformational changes in the apoptosis regulator BAX and sequesters it into fibers, preventing mitochondrial outer-membrane permeabilization.

The mitochondrial, or intrinsic, apoptosis pathway is regulated mainly by members of the B-cell lymphoma 2 (BCL-2) protein family. BCL-2-associated X apoptosis regulator (BAX) plays a pivotal role in the initiation of mitochondria-mediated apoptosis as one of the factors causing mitochondrial outer-membrane permeabilization (MOMP). Of current interest are endogenous BAX ligands that inhibit its MOMP activity. Mitochondrial-derived peptides (MDPs) are a recently identified class of mitochondrial retrograde signaling molecules and are reported to be potent apoptosis inhibitors. Among them, humanin (HN) has been shown to suppress apoptosis by inhibiting BAX translocation to the mitochondrial outer membrane, but the molecular mechanism of this interaction is unknown. Here, using recombinant protein expression, along with light-scattering, CD, and fluorescence spectroscopy, we report that HN and BAX can form fibers together in vitro Results from negative stain EM experiments suggest that BAX undergoes secondary and tertiary structural rearrangements and incorporates into the fibers, and that its membrane-associating C-terminal helix is important for the fibrillation process. Additionally, HN mutations known to alter its anti-apoptotic activity affect fiber morphology. Our findings reveal for the first time a potential mechanism by which BAX can be sequestered by fibril formation, which can prevent it from initiating MOMP and committing the cell to apoptosis.

Impact of Dehydroamino Acids on the Structure and Stability of Incipient 310-Helical Peptides.

A comparative study of the impact of small, medium-sized, and bulky α,ß-dehydroamino acids (ΔAAs) on the structure and stability of Balaram's incipient 310-helical peptide (1) is reported. Replacement of the N-terminal Aib residue of 1 with a ΔAA afforded peptides 2a-c that maintained the 310-helical shape of 1. In contrast, installation of a ΔAA in place of Aib-3 yielded peptides 3a-c that preferred a ß-sheet-like conformation. The impact of the ΔAA on peptide structure was independent of size, with small (ΔAla), medium-sized (Z-ΔAbu), and bulky (ΔVal) ΔAAs exerting similar effects. The proteolytic stabilities of 1 and its analogs were determined by incubation with Pronase. Z-ΔAbu and ΔVal increased the resistance of peptides to proteolysis when incorporated at the 3-position and had negligible impact on stability when placed at the 1-position, whereas ΔAla-containing peptides degraded rapidly regardless of position. Exposure of peptides 2a-c and 3a-c to the reactive thiol cysteamine revealed that ΔAla-containing peptides underwent conjugate addition at room temperature, while Z-ΔAbu- and ΔVal-containing peptides were inert even at elevated temperatures. These results suggest that both bulky and more accessible medium-sized ΔAAs should be valuable tools for bestowing rigidity and proteolytic stability on bioactive peptides.

Inferring hidden structure in multilayered neural circuits.

A central challenge in sensory neuroscience involves understanding how neural circuits shape computations across cascaded cell layers. Here we attempt to reconstruct the response properties of experimentally unobserved neurons in the interior of a multilayered neural circuit, using cascaded linear-nonlinear (LN-LN) models. We combine non-smooth regularization with proximal consensus algorithms to overcome difficulties in fitting such models that arise from the high dimensionality of their parameter space. We apply this framework to retinal ganglion cell processing, learning LN-LN models of retinal circuitry consisting of thousands of parameters, using 40 minutes of responses to white noise. Our models demonstrate a 53% improvement in predicting ganglion cell spikes over classical linear-nonlinear (LN) models. Internal nonlinear subunits of the model match properties of retinal bipolar cells in both receptive field structure and number. Subunits have consistently high thresholds, supressing all but a small fraction of inputs, leading to sparse activity patterns in which only one subunit drives ganglion cell spiking at any time. From the model's parameters, we predict that the removal of visual redundancies through stimulus decorrelation across space, a central tenet of efficient coding theory, originates primarily from bipolar cell synapses. Furthermore, the composite nonlinear computation performed by retinal circuitry corresponds to a boolean OR function applied to bipolar cell feature detectors. Our methods are statistically and computationally efficient, enabling us to rapidly learn hierarchical non-linear models as well as efficiently compute widely used descriptive statistics such as the spike triggered average (STA) and covariance (STC) for high dimensional stimuli. This general computational framework may aid in extracting principles of nonlinear hierarchical sensory processing across diverse modalities from limited data.

Adaptive feature detection from differential processing in parallel retinal pathways.

To transmit information efficiently in a changing environment, the retina adapts to visual contrast by adjusting its gain, latency and mean response. Additionally, the temporal frequency selectivity, or bandwidth changes to encode the absolute intensity when the stimulus environment is noisy, and intensity differences when noise is low. We show that the On pathway of On-Off retinal amacrine and ganglion cells is required to change temporal bandwidth but not other adaptive properties. This remarkably specific adaptive mechanism arises from differential effects of contrast on the On and Off pathways. We analyzed a biophysical model fit only to a cell's membrane potential, and verified pharmacologically that it accurately revealed the two pathways. We conclude that changes in bandwidth arise mostly from differences in synaptic threshold in the two pathways, rather than synaptic release dynamics as has previously been proposed to underlie contrast adaptation. Different efficient codes are selected by different thresholds in two independently adapting neural pathways.

Critical and maximally informative encoding between neural populations in the retina.

Computation in the brain involves multiple types of neurons, yet the organizing principles for how these neurons work together remain unclear. Information theory has offered explanations for how different types of neurons can maximize the transmitted information by encoding different stimulus features. However, recent experiments indicate that separate neuronal types exist that encode the same filtered version of the stimulus, but then the different cell types signal the presence of that stimulus feature with different thresholds. Here we show that the emergence of these neuronal types can be quantitatively described by the theory of transitions between different phases of matter. The two key parameters that control the separation of neurons into subclasses are the mean and standard deviation (SD) of noise affecting neural responses. The average noise across the neural population plays the role of temperature in the classic theory of phase transitions, whereas the SD is equivalent to pressure or magnetic field, in the case of liquid-gas and magnetic transitions, respectively. Our results account for properties of two recently discovered types of salamander Off retinal ganglion cells, as well as the absence of multiple types of On cells. We further show that, across visual stimulus contrasts, retinal circuits continued to operate near the critical point whose quantitative characteristics matched those expected near a liquid-gas critical point and described by the nearest-neighbor Ising model in three dimensions. By operating near a critical point, neural circuits can maximize information transmission in a given environment while retaining the ability to quickly adapt to a new environment.

Potential involvement of mi-RNA 574-3p in progression of prostate cancer: A bioinformatic study.

Aberrant gene expression is a hallmark of prostate cancer (PCa), the second deadliest disease affecting males worldwide. Dysregulation of miRNA has been associated with the progression of PCa and in recent studies, miRNA 574-3p was found to be upregulated in cancerous prostate tissue. In this study, we characterize the effects of upregulated miRNA 574-3p on gene expression in the tumor microenvironment through different bioinformatic tools such as Diana-Tools, the KEGG Pathway Database, and the Reactome Database. We have identified nine regulatory genes that are targeted by miRNA 574-3p and downregulated in prostate cells. Pathway analysis of these genes shows that they are involved in the regulation of the Notch signaling pathway, Wnt signaling pathway, apoptosis, DNA damage response, G1 to S cell-cycle control, inflammatory response pathway, angiogenesis, translation factors, and the expression of oncogenes. Our results show the oncogenic potential of miRNA 574-3p in PCa progression and metastasis. Moreover, this study highlights the complex molecular mechanisms and pathways affected by the upregulation of miRNA 574-3p in prostate cells. In future studies, the presented data may aid in designing new therapies for PCa with improved efficacy.

Synaptic consolidation: from synapses to behavioral modeling.

Synaptic plasticity, a key process for memory formation, manifests itself across different time scales ranging from a few seconds for plasticity induction up to hours or even years for consolidation and memory retention. We developed a three-layered model of synaptic consolidation that accounts for data across a large range of experimental conditions. Consolidation occurs in the model through the interaction of the synaptic efficacy with a scaffolding variable by a read-write process mediated by a tagging-related variable. Plasticity-inducing stimuli modify the efficacy, but the state of tag and scaffold can only change if a write protection mechanism is overcome. Our model makes a link from depotentiation protocols in vitro to behavioral results regarding the influence of novelty on inhibitory avoidance memory in rats.

The choice-wide behavioral association study: data-driven identification of interpretable behavioral components.

Behavior contains rich structure across many timescales, but there is a dearth of methods to identify relevant components, especially over the longer periods required for learning and decision-making. Inspired by the goals and techniques of genome-wide association studies, we present a data-driven method-the choice-wide behavioral association study: CBAS-that systematically identifies such behavioral features. CBAS uses a powerful, resampling-based, method of multiple comparisons correction to identify sequences of actions or choices that either differ significantly between groups or significantly correlate with a covariate of interest. We apply CBAS to different tasks and species (flies, rats, and humans) and find, in all instances, that it provides interpretable information about each behavioral task.

Gamma camera imaging characteristics of 166Ho and 99mTc used in Selective Internal Radiation Therapy.

BACKGROUND: The administration of a 166Ho scout dose is available as an alternative to 99mTc particles for pre-treatment imaging in Selective Internal Radiation Therapy (SIRT). It has been reported that the 166Ho scout dose may be more accurate for the prediction of microsphere distribution and the associated therapy planning. The aim of the current study is to compare the scintigraphic imaging characteristics of both isotopes, considering the objectives of the pre-treatment imaging using clinically geared phantoms. METHODS: Planar and SPECT/CT images were obtained using a NEMA image quality phantom in different phantom setups and another body-shaped phantom with several inserts. The influence of collimator type, count statistics, dead time effects, isotope properties and patient obesity on spatial resolution, contrast recovery and the detectability of small activity accumulations was investigated. Furthermore, the effects of the imaging characteristics on personalized dosimetry are discussed. RESULTS: The images with 99mTc showed up to 3 mm better spatial resolution, up to two times higher contrast recovery and significantly lower image noise than those with 166Ho. The contrast-to-noise ratio was up to five times higher for 99mTc than for 166Ho. Only when using 99mTc all activity-filled spheres could be distinguished from the activity-filled background. The measurements mimicking an obese patient resulted in a degraded image quality for both isotopes. CONCLUSIONS: Our measurements demonstrate better scintigraphic imaging properties for 99mTc compared to 166Ho in terms of spatial resolution, contrast recovery, image noise, and lesion detectability. While the 166Ho scout dose promises better prediction of the microsphere distribution, it is important to consider the inferior imaging characteristics of 166Ho, which may affect individualized treatment planning in SIRT.

Investigation of Photodynamic Therapy Promoted by Cherenkov Light Activated Photosensitizers-New Aspects and Revelations.

This work investigates the proposed enhanced efficacy of photodynamic therapy (PDT) by activating photosensitizers (PSs) with Cherenkov light (CL). The approaches of Yoon et al. to test the effect of CL with external radiation were taken up and refined. The results were used to transfer the applied scheme from external radiation therapy to radionuclide therapy in nuclear medicine. Here, the CL for the activation of the PSs (psoralen and trioxsalen) is generated by the ionizing radiation from rhenium-188 (a high-energy beta-emitter, Re-188). In vitro cell survival studies were performed on FaDu, B16 and 4T1 cells. A characterization of the PSs (absorbance measurement and gel electrophoresis) and the CL produced by Re-188 (luminescence measurement) was performed as well as a comparison of clonogenic assays with and without PSs. The methods of Yoon et al. were reproduced with a beam line at our facility to validate their results. In our studies with different concentrations of PS and considering the negative controls without PS, the statements of Yoon et al. regarding the positive effect of CL could not be confirmed. There are slight differences in survival fractions, but they are not significant when considering the differences in the controls. Gel electrophoresis showed a dominance of trioxsalen over psoralen in conclusion of single and double strand breaks in plasmid DNA, suggesting a superiority of trioxsalen as a PS (when irradiated with UVA). In addition, absorption measurements showed that these PSs do not need to be shielded from ambient light during the experiment. An observational test setup for a PDT nuclear medicine approach was found. The CL spectrum of Re-188 was measured. Fluctuating inconclusive results from clonogenic assays were found.

Alpha-Emitting Radionuclides: Current Status and Future Perspectives.

The use of radionuclides for targeted endoradiotherapy is a rapidly growing field in oncology. In particular, the focus on the biological effects of different radiation qualities is an important factor in understanding and implementing new therapies. Together with the combined approach of imaging and therapy, therapeutic nuclear medicine has recently made great progress. A particular area of research is the use of alpha-emitting radionuclides, which have unique physical properties associated with outstanding advantages, e.g., for single tumor cell targeting. Here, recent results and open questions regarding the production of alpha-emitting isotopes as well as their chemical combination with carrier molecules and clinical experience from compassionate use reports and clinical trials are discussed.

Active Learning Exploration of Transition-Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores.

Transition-metal chromophores with earth-abundant transition metals are an important design target for their applications in lighting and nontoxic bioimaging, but their design is challenged by the scarcity of complexes that simultaneously have well-defined ground states and optimal target absorption energies in the visible region. Machine learning (ML) accelerated discovery could overcome such challenges by enabling the screening of a larger space but is limited by the fidelity of the data used in ML model training, which is typically from a single approximate density functional. To address this limitation, we search for consensus in predictions among 23 density functional approximations across multiple rungs of "Jacob's ladder". To accelerate the discovery of complexes with absorption energies in the visible region while minimizing the effect of low-lying excited states, we use two-dimensional (2D)efficient global optimization to sample candidate low-spin chromophores from multimillion complex spaces. Despite the scarcity (i.e., ∼0.01%) of potential chromophores in this large chemical space, we identify candidates with high likelihood (i.e., >10%) of computational validation as the ML models improve during active learning, representing a 1000-fold acceleration in discovery. Absorption spectra of promising chromophores from time-dependent density functional theory verify that 2/3 of candidates have the desired excited-state properties. The observation that constituent ligands from our leads have demonstrated interesting optical properties in the literature exemplifies the effectiveness of our construction of a realistic design space and active learning approach.