Recent Developments in the Biosynthesis of Aziridines.

Only 0.016 % of all known natural products contain an aziridine ring, but this unique structural feature imparts high reactivity and cytotoxicity to the compounds in which it is found. Until 2021, no naturally occurring aziridine-forming enzymes had been identified. Since 2021, the biosynthetic enzymes for ~10 % of known aziridine containing natural products have been identified and characterized. This article describes the recent advances in our understanding of enzyme-catalyzed aziridine formation in the context of historical methods for aziridine formation through synthetic chemistry.

Explore your experimental designs and theories before you exploit them!

In many areas of the social and behavioral sciences, the nature of the experiments and theories that best capture the underlying constructs are themselves areas of active inquiry. Integrative experiment design risks being prematurely exploitative, hindering exploration of experimental paradigms and of diverse theoretical accounts for target phenomena.

Knowing what to know: Implications of the choice of prior distribution on the behavior of adaptive design optimization.

Adaptive design optimization (ADO) is a state-of-the-art technique for experimental design (Cavagnaro et al., 2010). ADO dynamically identifies stimuli that, in expectation, yield the most information about a hypothetical construct of interest (e.g., parameters of a cognitive model). To calculate this expectation, ADO leverages the modeler's existing knowledge, specified in the form of a prior distribution. Informative priors align with the distribution of the focal construct in the participant population. This alignment is assumed by ADO's internal assessment of expected information gain. If the prior is instead misinformative, i.e., does not align with the participant population, ADO's estimates of expected information gain could be inaccurate. In many cases, the true distribution that characterizes the participant population is unknown, and experimenters rely on heuristics in their choice of prior and without an understanding of how this choice affects ADO's behavior. Our work introduces a mathematical framework that facilitates investigation of the consequences of the choice of prior distribution on the efficiency of experiments designed using ADO. Through theoretical and empirical results, we show that, in the context of prior misinformation, measures of expected information gain are distinct from the correctness of the corresponding inference. Through a series of simulation experiments, we show that, in the case of parameter estimation, ADO nevertheless outperforms other design methods. Conversely, in the case of model selection, misinformative priors can lead inference to favor the wrong model, and rather than mitigating this pitfall, ADO exacerbates it.

Comparison of Cas9 activators in multiple species.

Several programmable transcription factors exist based on the versatile Cas9 protein, yet their relative potency and effectiveness across various cell types and species remain unexplored. Here, we compare Cas9 activator systems and examine their ability to induce robust gene expression in several human, mouse, and fly cell lines. We also explore the potential for improved activation through the combination of the most potent activator systems, and we assess the role of cooperativity in maximizing gene expression.

Think of the consequences: A decade of discourse about same-sex marriage.

Approaching issues through the lens of nonnegotiable values increases the perceived intractability of debate (Baron & Spranca in Organizational Behavior and Human Decision Processes, 70, 1-16, 1997), while focusing on the concrete consequences of policies instead results in the moderation of extreme opinions (Fernbach, Rogers, Fox, & Sloman in Psychological Science, 24, 939-946, 2013) and a greater likelihood of conflict resolution (Baron & Leshner in Journal of Experimental Psychology: Applied, 6, 183-194, 2000). Using comments on the popular social media platform Reddit from January 2006 until September 2017, we showed how changes in the framing of same-sex marriage in public discourse relate to changes in public opinion. We used a topic model to show that the contributions of certain protected-values-based topics to the debate (religious arguments and freedom of opinion) increased prior to the emergence of a public consensus in support of same-sex marriage (Gallup, 2017), and declined afterward. In contrast, the discussion of certain consequentialist topics (the impact of politicians' stance and same-sex marriage as a matter of policy) showed the opposite pattern. Our results reinforce the meaningfulness of protected values and consequentialism as relevant dimensions for describing public discourse and highlight the usefulness of unsupervised machine-learning methods in tackling questions about social attitude change.

Beyond collective intelligence: Collective adaptation.

We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for 'intelligent' collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation. We call for a transdisciplinary, quantitative and societally useful social science that can help us to understand our rapidly changing and ever more complex societies, avoid collective disasters and reach the full potential of our ability to organize in adaptive collectives.

Neuroimaging-based analysis of DBS outcomes in pediatric dystonia: Insights from the GEPESTIM registry.

INTRODUCTION: Deep brain stimulation (DBS) is an established treatment in patients of various ages with pharmaco-resistant neurological disorders. Surgical targeting and postoperative programming of DBS depend on the spatial location of the stimulating electrodes in relation to the surrounding anatomical structures, and on electrode connectivity to a specific distribution pattern within brain networks. Such information is usually collected using group-level analysis, which relies on the availability of normative imaging resources (atlases and connectomes). Analysis of DBS data in children with debilitating neurological disorders such as dystonia would benefit from such resources, especially given the developmental differences in neuroimaging data between adults and children. We assembled pediatric normative neuroimaging resources from open-access datasets in order to comply with age-related anatomical and functional differences in pediatric DBS populations. We illustrated their utility in a cohort of children with dystonia treated with pallidal DBS. We aimed to derive a local pallidal sweetspot and explore a connectivity fingerprint associated with pallidal stimulation to exemplify the utility of the assembled imaging resources. METHODS: An average pediatric brain template (the MNI brain template 4.5-18.5 years) was implemented and used to localize the DBS electrodes in 20 patients from the GEPESTIM registry cohort. A pediatric subcortical atlas, analogous to the DISTAL atlas known in DBS research, was also employed to highlight the anatomical structures of interest. A local pallidal sweetspot was modeled, and its degree of overlap with stimulation volumes was calculated as a correlate of individual clinical outcomes. Additionally, a pediatric functional connectome of 100 neurotypical subjects from the Consortium for Reliability and Reproducibility was built to allow network-based analyses and decipher a connectivity fingerprint responsible for the clinical improvements in our cohort. RESULTS: We successfully implemented a pediatric neuroimaging dataset that will be made available for public use as a tool for DBS analyses. Overlap of stimulation volumes with the identified DBS-sweetspot model correlated significantly with improvement on a local spatial level (R = 0.46, permuted p = 0.019). The functional connectivity fingerprint of DBS outcomes was determined to be a network correlate of therapeutic pallidal stimulation in children with dystonia (R = 0.30, permuted p = 0.003). CONCLUSIONS: Local sweetspot and distributed network models provide neuroanatomical substrates for DBS-associated clinical outcomes in dystonia using pediatric neuroimaging surrogate data. Implementation of this pediatric neuroimaging dataset might help to improve the practice and pave the road towards a personalized DBS-neuroimaging analyses in pediatric patients.

A Social Interpolation Model of Group Problem-Solving.

How do people use information from others to solve complex problems? Prior work has addressed this question by placing people in social learning situations where the problems they were asked to solve required varying degrees of exploration. This past work uncovered important interactions between groups' connectivity and the problem's complexity: the advantage of less connected networks over more connected networks increased as exploration was increasingly required for optimally solving the problem at hand. We propose the Social Interpolation Model (SIM), an agent-based model to explore the cognitive mechanisms that can underlie exploratory behavior in groups. Through results from simulation experiments, we conclude that "exploration" may not be a single cognitive property, but rather the emergent result of three distinct behavioral and cognitive mechanisms, namely, (a) breadth of generalization, (b) quality of prior expectation, and (c) relative valuation of self-obtained information. We formalize these mechanisms in the SIM, and explore their effects on group dynamics and success at solving different kinds of problems. Our main finding is that broad generalization and high quality of prior expectation facilitate successful search in environments where exploration is important, and hinder successful search in environments where exploitation alone is sufficient.

Can we detect conditioned variation in political speech? two kinds of discussion and types of conversation.

Previous work has demonstrated that certain speech patterns vary systematically between sociodemographic groups, so that in some cases the way a person speaks is a valid cue to group membership. Our work addresses whether or not participants use these linguistic cues when assessing a speaker's likely political identity. We use a database of speeches by U.S. Congressional representatives to isolate words that are statistically diagnostic of a speaker's party identity. In a series of four studies, we demonstrate that participants' judgments track variation in word usage between the two parties more often than chance, and that this effect persists even when potentially interfering cues such as the meaning of the word are controlled for. Our results are consistent with a body of literature suggesting that humans' language-related judgments reflect the statistical distributions of our environment.

Electrical signals affect the cardiomyocyte transcriptome independently of contraction.

Cardiomyocytes in vivo are continuously subjected to electrical signals that evoke contractions and instigate drastic changes in the cells' morphology and function. Studies on how electrical stimulation affects the cardiac transcriptome have remained limited to a small number of heart-specific genes. Furthermore, these studies have ignored the interplay between the electrical excitation and the subsequent contractions. We carried out a genomewide assessment of the effects of electrical signaling on gene expression, while distinguishing between the effects deriving from the electrical pulses themselves and the effects instigated by the evoked contractions. Changes in gene expression in primary cultures of neonatal ventricular cardiomyocytes from Lewis Rattus norvegicus were investigated with microarrays and RT-quantitative PCR (QPCR). A series of experiments was included in which the culture medium was supplemented with the contraction inhibitor blebbistatin to allow for electrical stimulation in the absence of contraction. Electrical stimulation was shown to directly enhance calcium handling and induce cardiomyocyte differentiation by arresting cell division and activating key cardiac transcription factors as well as additional differentiation mechanisms such as wnt signaling. Several genes involved in metabolism were also directly activated by electrical stimulation. Furthermore, our data suggest that contraction exerts negative feedback on the transcription of various genes. Together, these observations indicate that intercellular electric currents between adjacent cardiomyocytes have an important role in cardiomyocyte development. They act at least partially through a pulse-specific gene expression program that is activated independently from the evoked contractions.

Functional annotation of heart enriched mitochondrial genes GBAS and CHCHD10 through guilt by association.

Despite the mitochondria ubiquitous nature many of their components display divergences in their expression profile across different tissues. Using the bioinformatics-approach of guilt by association (GBA) we exploited these variations to predict the function of two so far poorly annotated genes: Coiled-coil-helix-coiled-coil-helix domain containing 10 (CHCHD10) and glioblastoma amplified sequence (GBAS). We predicted both genes to be involved in oxidative phosphorylation. Through in vitro experiments using gene-knockdown we could indeed confirm this and furthermore we asserted CHCHD10 to play a role in complex IV activity.

N,N'-(2,2'-Dithiodi-o-phenyl-ene)bis-(furan-2-carboxamide).

The reaction of 2,2'-dithio-bis(benzenamine) with furan-2-carbonyl chloride produced the bis-amide title compound, C(22)H(16)N(2)O(4)S(2), which, in the crystal, formed a helix; the structure consists of two planar furanoylbenzenamines related by an improper rotation of 96.3° about the S-S bond. The N-furanoylbenzenamine units are planar (maximum deviations = 0.316 and 0.132 Å). Each electron-deficient acyl-furan stacks (centroid-centroid separations of the two pairs of π-π stacked aromatic rings are 3.918 and 3.953 Å) with the electron-rich benzenamine of the other N-furan-oyl-benzenamine unit, leading to a spiral structure. The conformation is stabilized by two bifurcated intramolecular N-H⋯(O,S) interactions.

Replication Errors Made During Oogenesis Lead to Detectable De Novo mtDNA Mutations in Zebrafish Oocytes with a Low mtDNA Copy Number.

Of all pathogenic mitochondrial DNA (mtDNA) mutations in humans, ∼25% is de novo, although the occurrence in oocytes has never been directly assessed. We used next-generation sequencing to detect point mutations directly in the mtDNA of 3-15 individual mature oocytes and three somatic tissues from eight zebrafish females. Various statistical and biological filters allowed reliable detection of de novo variants with heteroplasmy ≥1.5%. In total, we detected 38 de novo base substitutions, but no insertions or deletions. These 38 de novo mutations were present in 19 of 103 mature oocytes, indicating that ∼20% of the mature oocytes carry at least one de novo mutation with heteroplasmy ≥1.5%. This frequency of de novo mutations is close to that deducted from the reported error rate of polymerase gamma, the mitochondrial replication enzyme, implying that mtDNA replication errors made during oogenesis are a likely explanation. Substantial variation in the mutation prevalence among mature oocytes can be explained by the highly variable mtDNA copy number, since we previously reported that ∼20% of the primordial germ cells have a mtDNA copy number of ≤73 and would lead to detectable mutation loads. In conclusion, replication errors made during oogenesis are an important source of de novo mtDNA base substitutions and their location and heteroplasmy level determine their significance.

Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure.

An improved dynamic programming algorithm is reported for RNA secondary structure prediction by free energy minimization. Thermodynamic parameters for the stabilities of secondary structure motifs are revised to include expanded sequence dependence as revealed by recent experiments. Additional algorithmic improvements include reduced search time and storage for multibranch loop free energies and improved imposition of folding constraints. An extended database of 151,503 nt in 955 structures? determined by comparative sequence analysis was assembled to allow optimization of parameters not based on experiments and to test the accuracy of the algorithm. On average, the predicted lowest free energy structure contains 73 % of known base-pairs when domains of fewer than 700 nt are folded; this compares with 64 % accuracy for previous versions of the algorithm and parameters. For a given sequence, a set of 750 generated structures contains one structure that, on average, has 86 % of known base-pairs. Experimental constraints, derived from enzymatic and flavin mononucleotide cleavage, improve the accuracy of structure predictions.