Flexibility and sensitivity in gene regulation out of equilibrium.

Cells adapt to environments and tune gene expression by controlling the concentrations of proteins and their kinetics in regulatory networks. In both eukaryotes and prokaryotes, experiments and theory increasingly attest that these networks can and do consume biochemical energy. How does this dissipation enable cellular behaviors forbidden in equilibrium? This open question demands quantitative models that transcend thermodynamic equilibrium. Here, we study the control of simple, ubiquitous gene regulatory networks to explore the consequences of departing equilibrium in transcription. Employing graph theory to model a set of especially common regulatory motifs, we find that dissipation unlocks nonmonotonicity and enhanced sensitivity of gene expression with respect to a transcription factor's concentration. These features allow a single transcription factor to act as both a repressor and activator at different concentrations or achieve outputs with multiple concentration regimes of locally enhanced sensitivity. We systematically dissect how energetically driving individual transitions within regulatory networks, or pairs of transitions, generates a wide range of more adjustable and sensitive phenotypic responses than in equilibrium. These results generalize to more complex regulatory scenarios, including combinatorial control by multiple transcription factors, which we relate and often find collapse to simple mathematical behaviors. Our findings quantify necessary conditions and detectable consequences of energy expenditure. These richer mathematical behaviors-feasibly accessed using biological energy budgets and rates-may empower cells to accomplish sophisticated regulation with simpler architectures than those required at equilibrium.

Optogenetic dissection of transcriptional repression in a multicellular organism.

Transcriptional control is fundamental to cellular function. However, despite knowing that transcription factors can repress or activate specific genes, how these functions are implemented at the molecular level has remained elusive, particularly in the endogenous context of developing animals. Here, we combine optogenetics, single-cell live-imaging, and mathematical modeling to study how a zinc-finger repressor, Knirps, induces switch-like transitions into long-lived quiescent states. Using optogenetics, we demonstrate that repression is rapidly reversible (~1 min) and memoryless. Furthermore, we show that the repressor acts by decreasing the frequency of transcriptional bursts in a manner consistent with an equilibrium binding model. Our results provide a quantitative framework for dissecting the in vivo biochemistry of eukaryotic transcriptional regulation.

Energy Aware Technology Mapping of Genetic Logic Circuits.

Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers -as caused by the additional burden of artificial genetic circuits- shifts a cell's priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state (NESS) model of gene expression, capturing characteristics like energy dissipation -which we link to the entropy production rate- and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit's functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37.2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energy efficiency of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo.

Energy Aware Technology Mapping of Genetic Logic Circuits.

Energy and its dissipation are fundamental to all living systems, including cells. Insufficient abundance of energy carriers─as caused by the additional burden of artificial genetic circuits─shifts a cell's priority to survival, also impairing the functionality of the genetic circuit. Moreover, recent works have shown the importance of energy expenditure in information transmission. Despite living organisms being non-equilibrium systems, non-equilibrium models capable of accounting for energy dissipation and non-equilibrium response curves are not yet employed in genetic design automation (GDA) software. To this end, we introduce Energy Aware Technology Mapping, the automated design of genetic logic circuits with respect to energy efficiency and functionality. The basis for this is an energy aware non-equilibrium steady state model of gene expression, capturing characteristics like energy dissipation─which we link to the entropy production rate─and transcriptional bursting, relevant to eukaryotes as well as prokaryotes. Our evaluation shows that a genetic logic circuit's functional performance and energy efficiency are disjoint optimization goals. For our benchmark, energy efficiency improves by 37.2% on average when comparing to functionally optimized variants. We discover a linear increase in energy expenditure and overall protein expression with the circuit size, where Energy Aware Technology Mapping allows for designing genetic logic circuits with the energetic costs of circuits that are one to two gates smaller. Structural variants improve this further, while results show the Pareto dominance among structures of a single Boolean function. By incorporating energy demand into the design, Energy Aware Technology Mapping enables energy efficiency by design. This extends current GDA tools and complements approaches coping with burden in vivo.

Handgrip strength as a predictor of 1­year mortality after hip fracture surgery in the Colombian Andes Mountains.

Hip fracture is a public health problem recognized worldwide and a potentially catastrophic threat for older persons, even carrying a demonstrated excess of mortality. Handgrip strength (HGS) has been identified as a predictor of different outcomes (mainly mortality and disability) in several groups with hip fracture. PURPOSE: The aim of this study was to determine the association between low HGS and 1-year mortality in a cohort of older patients over 60 years old with fragility hip fractures who underwent surgery in the Colombian Andes Mountains. METHODS: A total of 126 patients (median age 81 years, women 77%) with a fragility hip fracture during 2019-2020 were admitted to a tertiary care hospital. HGS was measured using dynamometry upon admission, and data about sociodemographic, clinical and functional, laboratory, and surgical intervention variables were collected. They were followed up until discharge. Those who survived were contacted by telephone at one, three, and 12 months. Bivariate, multivariate, and Kaplan-Meier analyses with survival curves were performed. RESULTS: The prevalence of low HGS in the cohort was 71.4%, and these patients were older, had poorer functional and cognitive status, higher comorbidity, higher surgical risk, time from admission to surgery > 72 h, lower hemoglobin and albumin values, and greater intra-hospital mortality at one and three months (all p < 0.01). Mortality at one year in in patients with low HGS was 42.2% and 8.3% in those with normal HGS, with a statistically significant difference (p = 0.000). In the multivariate analysis, low HGS and dependent gait measured by Functional Ambulation Classification (FAC) were the factors affecting postoperative 1-year mortality in older adults with hip fractures. CONCLUSION: In this study of older people with fragility hip fractures, low HGS and dependent gait were independent predictive markers of 1-year mortality.

DRMY1 promotes robust morphogenesis in Arabidopsis by sustaining the translation of cytokinin-signaling inhibitor proteins.

Robustness is the invariant development of phenotype despite environmental changes and genetic perturbations. In the Arabidopsis flower bud, four sepals robustly initiate and grow to a constant size to enclose and protect the inner floral organs. We previously characterized the mutant development-related myb-like 1 (drmy1), where 3-5 sepals initiate variably and grow to different sizes, compromising their protective function. The molecular mechanism underlying this loss of robustness was unclear. Here, we show that drmy1 has reduced TARGET OF RAPAMYCIN (TOR) activity, ribosomal content, and translation. Translation reduction decreases the protein level of ARABIDOPSIS RESPONSE REGULATOR7 (ARR7) and ARABIDOPSIS HISTIDINE PHOSPHOTRANSFER PROTEIN 6 (AHP6), two cytokinin-signaling inhibitors that are normally rapidly produced before sepal initiation. The resultant upregulation of cytokinin signaling disrupts robust auxin patterning and sepal initiation. Our work shows that the homeostasis of translation, a ubiquitous cellular process, is crucial for the robust spatiotemporal patterning of organogenesis.

Spatial microenvironments tune immune response dynamics in the Drosophila larval fat body.

Immune responses in tissues display intricate patterns of gene expression that vary across space and time. While such patterns have been increasingly linked to disease outcomes, the mechanisms that generate them and the logic behind them remain poorly understood. As a tractable model of spatial immune responses, we investigated heterogeneous expression of antimicrobial peptides in the larval fly fat body, an organ functionally analogous to the liver. To capture the dynamics of immune response across the full tissue at single-cell resolution, we established live light sheet fluorescence microscopy of whole larvae. We discovered that expression of antimicrobial peptides occurs in a reproducible spatial pattern, with enhanced expression in the anterior and posterior lobes of the fat body. This pattern correlates with microbial localization via blood flow but is not caused by it: loss of heartbeat suppresses microbial transport but leaves the expression pattern unchanged. This result suggests that regions of the tissue most likely to encounter microbes via blood flow are primed to produce antimicrobials. Spatial transcriptomics revealed that these immune microenvironments are defined by genes spanning multiple biological processes, including lipid-binding proteins that regulate host cell death by the immune system. In sum, the larval fly fat body exhibits spatial compartmentalization of immune activity that resembles the strategic positioning of immune cells in mammals, such as in the liver, gut, and lymph nodes. This finding suggests that tissues may share a conserved spatial organization that optimizes immune responses for antimicrobial efficacy while preventing excessive self-damage.

High-resolution compound-specific mapping in works of art via data fusion of MA-XRPD with hyperspectral data (part 1: Method evaluation).

BACKGROUND: Hyperspectral imaging techniques have emerged as powerful tools for non-invasive investigation of artworks. This paper employs either reflectance imaging spectroscopy (RIS) or macroscopic X-ray fluorescence (MA-XRF) imaging in combination with macroscopic X-ray powder diffraction (MA-XRPD) for state-of-the-art chemical imaging of painted cultural heritage artefacts. While RIS can provide molecular information and MA-XRF can offer elemental distribution maps of paintings of high lateral resolution, the unique advantage of MA-XRPD lies in its ability to visualize the distributions of specific pigments and estimate in a quantitative manner the relative concentrations of the crystalline phases at the surface of artworks. However, MA-XRPD is more time-consuming and offers a lower lateral resolution than RIS and MA-XRF. RESULTS: This study introduces a machine learning (ML) approach to obtain the distribution of specific compounds on the surface of artworks with a resolution that is comparable to that of RIS and MA-XRF data but with the compound specificity of MA-XRPD. The general aim is to expedite non-destructive artwork imaging analysis by fusing data from different imaging modalities via machine learning models. The effect of preprocessing techniques to enhance the predictive accuracy of the models is explored. The paper demonstrates the method's efficacy on a 16th-century illuminated manuscript, showcasing the feasibility of predicting compound-specific distribution maps. Three evaluation methods-visual examination of the predicted distribution, root mean square errors (RMSE), and feature permutation importance (FPI)-are employed to assess model performance. Fusing MA-XRF with MA-XRPD led to the best RMSE scores overall. However, fusing the RIS and MA-XRPD data blocks also yield very satisfactory and easily interpretable high-resolution compound maps. SIGNIFICANCE: While MA-XRPD allows for highly specific imaging of artworks, its time-consuming nature and limited resolution presents a bottleneck during non-invasive imaging of painted works of art. By integrating data from more time-efficient hyperspectral techniques such as MA-XRF and RIS, and employing machine learning, we expedite the process without compromising accuracy. The fusion process can also denoise the distribution maps, improving their readability for heritage professionals and art historical scholars.

Targeted mutagenesis of specific genomic DNA sequences in animals for the in vivo generation of variant libraries.

Understanding how the number, placement and affinity of transcription factor binding sites dictates gene regulatory programs remains a major unsolved challenge in biology, particularly in the context of multicellular organisms. To uncover these rules, it is first necessary to find the binding sites within a regulatory region with high precision, and then to systematically modulate this binding site arrangement while simultaneously measuring the effect of this modulation on output gene expression. Massively parallel reporter assays (MPRAs), where the gene expression stemming from 10,000s of in vitro-generated regulatory sequences is measured, have made this feat possible in high-throughput in single cells in culture. However, because of lack of technologies to incorporate DNA libraries, MPRAs are limited in whole organisms. To enable MPRAs in multicellular organisms, we generated tools to create a high degree of mutagenesis in specific genomic loci in vivo using base editing. Targeting GFP integrated in genome of Drosophila cell culture and whole animals as a case study, we show that the base editor AID evoCDA1 stemming from sea lamprey fused to nCas9 is highly mutagenic. Surprisingly, longer gRNAs increase mutation efficiency and expand the mutating window, which can allow the introduction of mutations in previously untargetable sequences. Finally, we demonstrate arrays of >20 gRNAs that can efficiently introduce mutations along a 200bp sequence, making it a promising tool to test enhancer function in vivo in a high throughput manner.

Aging in Indigenous Communities: Perspective from Two Ancestral Communities in the Colombian Andean-Amazon Region.

The phenomenon of world aging is not foreign to indigenous communities. In the last few years, research about these communities around the world has increased, but aging in indigenous towns still has not been studied widely. The purpose of this research is to interpret the meaning of old age in two indigenous communities from the Colombian Andean-Amazon region (the Inga and Kamëntsa) to reinforce the relevance of the local sociocultural context within the configuration of the meaning of old age and to emphasize the importance of considering particular regional characteristics for the design of policies and interventions aiming to recognize and integrate indigenous populations. This is a qualitative study with an interactionism-symbolism approach. In total, six indigenous people older than 60 years from two ancestral communities from the Colombian Andean-Amazon region participated in the in-depth interviews. Data analysis was carried out in three moments: discovery, coding, and relativization of the information. The results show that old age means wisdom, "I am wise," which is supported in the cosmology and the trajectory of life, reinforces the identity and autonomy, and allows them to be agents in the dynamics of their communities from the "I do," in other words, their roles as builders of the family-society and as guards of ancestral knowledge. The loss of this knowledge and the elements that it is composed of uproot them and put them at risk of disappearing as individuals and as a collective. In conclusion, the meaning of old age in these communities is not centered on a determinate age; you are not old, you are wise, and as such, they play a central role in their communities. Moreover, wisdom is built in parallel with their cosmology and assigns them the task of safekeeping ancestral knowledge. In order to do this, they use oral tradition as a tool, words that are born in their territories, travel in a nonlinear timeline, and get strengthened by the community while also protecting it and building it. Knowing what aging means for Indigenous communities can facilitate to the development of policies and initiatives and to provide culturally appropriate and effective programs.

Determining Factors to Understand the External Quantum Efficiency Values: Study Carried Out with Copper(I)-I and 1,2-Bis(4-pyridyl)ethane Coordination Polymers as Downshifters in Photovoltaic Modules.

Downshifters refer to compounds with the capacity to absorb UV photons and transform them into visible light. The integration of such downshifters has the potential to improve the efficiency of commercial photovoltaic modules. Initially, costly lanthanide derivatives and organic fluorescent dyes were introduced, resulting in a heightened module efficiency. In a novel research direction guided by the same physicochemical principles, the utilization of copper(I) coordination compounds is proposed. This choice is motivated by its simpler and more economical synthesis, primarily due to copper being a more abundant and less toxic element. Our proposal involves employing 1,2-bis(4-pyridyl) ethane (bpe), an economically viable commercial ligand, in conjunction with CuI to synthesize coordination polymers: [CuI(bpe)]n(1), [Cu3I3(bpe)3]n(2), and [CuI(bpe)0.5]n(3). These polymers exhibit the ability to absorb UV photons and emit light within the green and orange spectra. To conduct external quantum efficiency studies, the compounds are dispersed on glass and then encapsulated with ethylene vinyl acetate through heating to 150 °C. Interestingly, during these procedural steps, the solvents and temperatures employed induce a phase transformation, which has been thoroughly examined through both experimental analysis and theoretical calculations. The outcomes of these studies reveal an enhancement in external quantum efficiency with [Cu3I3(bpe)3]n(2), at a cost significantly lower (between 340 and 350 times) than that associated with lanthanide DS complexes.

Deciphering regulatory architectures from synthetic single-cell expression patterns.

For the vast majority of genes in sequenced genomes, there is limited understanding of how they are regulated. Without such knowledge, it is not possible to perform a quantitative theory-experiment dialogue on how such genes give rise to physiological and evolutionary adaptation. One category of high-throughput experiments used to understand the sequence-phenotype relationship of the transcriptome is massively parallel reporter assays (MPRAs). However, to improve the versatility and scalability of MPRA pipelines, we need a "theory of the experiment" to help us better understand the impact of various biological and experimental parameters on the interpretation of experimental data. These parameters include binding site copy number, where a large number of specific binding sites may titrate away transcription factors, as well as the presence of overlapping binding sites, which may affect analysis of the degree of mutual dependence between mutations in the regulatory region and expression levels. To that end, in this paper we create tens of thousands of synthetic single-cell gene expression outputs using both equilibrium and out-of-equilibrium models. These models make it possible to imitate the summary statistics (information footprints and expression shift matrices) used to characterize the output of MPRAs and from this summary statistic to infer the underlying regulatory architecture. Specifically, we use a more refined implementation of the so-called thermodynamic models in which the binding energies of each sequence variant are derived from energy matrices. Our simulations reveal important effects of the parameters on MPRA data and we demonstrate our ability to optimize MPRA experimental designs with the goal of generating thermodynamic models of the transcriptome with base-pair specificity. Further, this approach makes it possible to carefully examine the mapping between mutations in binding sites and their corresponding expression profiles, a tool useful not only for better designing MPRAs, but also for exploring regulatory evolution.

Deciphering regulatory architectures from synthetic single-cell expression patterns.

For the vast majority of genes in sequenced genomes, there is limited understanding of how they are regulated. Without such knowledge, it is not possible to perform a quantitative theory-experiment dialogue on how such genes give rise to physiological and evolutionary adaptation. One category of high-throughput experiments used to understand the sequence-phenotype relationship of the transcriptome is massively parallel reporter assays (MPRAs). However, to improve the versatility and scalability of MPRA pipelines, we need a "theory of the experiment" to help us better understand the impact of various biological and experimental parameters on the interpretation of experimental data. These parameters include binding site copy number, where a large number of specific binding sites may titrate away transcription factors, as well as the presence of overlapping binding sites, which may affect analysis of the degree of mutual dependence between mutations in the regulatory region and expression levels. To that end, in this paper we create tens of thousands of synthetic single-cell gene expression outputs using both equilibrium and out-of-equilibrium models. These models make it possible to imitate the summary statistics (information footprints and expression shift matrices) used to characterize the output of MPRAs and from this summary statistic to infer the underlying regulatory architecture. Specifically, we use a more refined implementation of the so-called thermodynamic models in which the binding energies of each sequence variant are derived from energy matrices. Our simulations reveal important effects of the parameters on MPRA data and we demonstrate our ability to optimize MPRA experimental designs with the goal of generating thermodynamic models of the transcriptome with base-pair specificity. Further, this approach makes it possible to carefully examine the mapping between mutations in binding sites and their corresponding expression profiles, a tool useful not only for better designing MPRAs, but also for exploring regulatory evolution.

Single-cell transcriptional dynamics in a living vertebrate.

The ability to quantify transcriptional dynamics in individual cells via live imaging has revolutionized our understanding of gene regulation. However, such measurements are lacking in the context of vertebrate embryos. We addressed this deficit by applying MS2-MCP mRNA labeling to the quantification of transcription in zebrafish, a model vertebrate. We developed a platform of transgenic organisms, light sheet fluorescence microscopy, and optimized image analysis that enables visualization and quantification of MS2 reporters. We used these tools to obtain the first single-cell, real-time measurements of transcriptional dynamics of the segmentation clock. Our measurements challenge the traditional view of smooth clock oscillations and instead suggest a model of discrete transcriptional bursts that are organized in space and time. Together, these results highlight how measuring single-cell transcriptional activity can reveal unexpected features of gene regulation and how this data can fuel the dialogue between theory and experiment.

Incidence of type 1 diabetes in Chilean children between 2006 and 2021: significant increase during the COVID-19 pandemic.

AIMS: An increase in type 1 diabetes (T1D) incidence has been observed in several countries during the COVID-19 pandemic. The objective of this study is to determine T1D incidence trends in Chilean children between 2006 and 2021, and specifically evaluate the effect of the COVID-19 pandemic in this population. METHODS: We reviewed mandatory notifications of T1D in Chile's public and private health system in youth < 20 years between 2006 and 2021, and compared COVID-19 pre-pandemic and pandemic incidence. RESULTS: In Chile, 9472 new T1D cases in children were confirmed between 2006 and 2021. The mean annual T1D incidence in the entire period was 12.7/100,000 inhabitants, with an incidence of 11.7/100,000 between 2006 and 2019 vs. 20.2/100,000 during 2020-2021 (ß = 0.691, [95%CI 0.479-0903], p < 0.001.) The highest incidence was observed in the 10-14 years age group, but a significant increasing incidence was observed in all age groups. The second year of the COVID-19 pandemic, 2021, had the highest incidence rate of the study period. While a 5% mean annual increase was observed between 2006 and 2019, in 2021 the T1D incidence jumped 28.5% compared with the two previous years. We found a higher T1D incidence in population with private insurance than public insurance (14.8 vs. 11.7/100.000, respectively, RR = 1.26 [95%CI 1.03-1.53], p < 0.027). CONCLUSIONS: T1D incidence rates in Chilean youth doubled between 2006 and 2018, subsequently presenting a striking increase during the COVID-19 pandemic.

Optogenetic control of YAP reveals a dynamic communication code for stem cell fate and proliferation.

YAP is a transcriptional regulator that controls pluripotency, cell fate, and proliferation. How cells ensure the selective activation of YAP effector genes is unknown. This knowledge is essential to rationally control cellular decision-making. Here we leverage optogenetics, live-imaging of transcription, and cell fate analysis to understand and control gene activation and cell behavior. We reveal that cells decode the steady-state concentrations and timing of YAP activation to control proliferation, cell fate, and expression of the pluripotency regulators Oct4 and Nanog. While oscillatory YAP inputs induce Oct4 expression and proliferation optimally at frequencies that mimic native dynamics, cellular differentiation requires persistently low YAP levels. We identify the molecular logic of the Oct4 dynamic decoder, which acts through an adaptive change sensor. Our work reveals how YAP levels and dynamics enable multiplexing of information transmission for the regulation of developmental decision-making and establishes a platform for the rational control of these behaviors.

A bistable autoregulatory module in the developing embryo commits cells to binary expression fates.

Bistable autoactivation has been proposed as a mechanism for cells to adopt binary fates during embryonic development. However, it is unclear whether the autoactivating modules found within developmental gene regulatory networks are bistable, unless their parameters are quantitatively determined. Here, we combine in vivo live imaging with mathematical modeling to dissect the binary cell fate dynamics of the fruit fly pair-rule gene fushi tarazu (ftz), which is regulated by two known enhancers: the early (non-autoregulating) element and the autoregulatory element. Live imaging of transcription and protein concentration in the blastoderm revealed that binary Ftz fates are achieved as Ftz expression rapidly transitions from being dictated by the early element to the autoregulatory element. Moreover, we discovered that Ftz concentration alone is insufficient to activate the autoregulatory element, and that this element only becomes responsive to Ftz at a prescribed developmental time. Based on these observations, we developed a dynamical systems model and quantitated its kinetic parameters directly from experimental measurements. Our model demonstrated that the ftz autoregulatory module is indeed bistable and that the early element transiently establishes the content of the binary cell fate decision to which the autoregulatory module then commits. Further in silico analysis revealed that the autoregulatory element locks the Ftz fate quickly, within 35 min of exposure to the transient signal of the early element. Overall, our work confirms the widely held hypothesis that autoregulation can establish developmental fates through bistability and, most importantly, provides a framework for the quantitative dissection of cellular decision-making.

Structural and Theoretical Study of Copper(II)-5-fluoro Uracil Acetate Coordination Compounds: Single-Crystal to Single-Crystal Transformation as Possible Humidity Sensor.

This paper describes the synthesis and characterization of seven different copper(II) coordination compounds, as well as the formation of a protonated ligand involving all compounds from the same reaction. Their synthesis required hydrothermal conditions, causing the partial in situ transformation of 5-fluoro uracil-1-acetic acid (5-FUA) into an oxalate ion (ox), as well as the protonation of the 4,4'-bipyridine (bipy) ligand through a catalytic process resulting from the presence of Cu(II) within the reaction. These initial conditions allowed obtaining the new coordination compounds [Cu2(5-FUA)2(ox)(bipy)]n·2n H2O (CP2), [Cu(5-FUA)2(H2O)(bipy)]n·2n H2O (CP3), as well as the ionic pair [(H2bipy)+2 2NO3-] (1). The mother liquor evolved rapidly at room temperature and atmospheric pressure, due to the change in concentration of the initial reagents and the presence of the new chemical species generated in the reaction process, yielding CPs [Cu(5-FUA)2(bipy)]n·3.5n H2O, [Cu3(ox)3(bipy)4]n and [Cu(ox)(bipy)]n. The molecular compound [Cu(5-FUA)2(H2O)4]·4H2O (more thermodynamically stable) ended up in the mother liquor after filtration at longer reaction times at 25 °C and 1 atm., cohabiting in the medium with the other crystalline solids in different proportions. In addition, the evaporation of H2O caused the single-crystal to single-crystal transformation (SCSC) of [Cu(5-FUA)2(H2O)(bipy)]n·2n H2O (CP3) into [Cu(5-FUA)2(bipy)]n·2n H2O (CP4). A theoretical study was performed to analyze the thermodynamic stability of the phases. The observed SCSC transformation also involved a perceptible color change, highlighting this compound as a possible water sensor.

2D Cu(I)-I Coordination Polymer with Smart Optoelectronic Properties and Photocatalytic Activity as a Versatile Multifunctional Material.

This work presents two isostructural Cu(I)-I 2-fluoropyrazine (Fpyz) luminescent and semiconducting 2D coordination polymers (CPs). Hydrothermal synthesis allows the growth of P-1 space group single crystals, whereas solvent-free synthesis produces polycrystals. Via recrystallization in acetonitrile, P21 space group single crystals are obtained. Both show a reversible luminescent response to temperature and pressure. Structure determination by single-crystal X-ray diffraction at 200 and 100 K allows us to understand their response as a function of temperature. Applying hydrostatic/uniaxial pressure or grinding also generates significant variations in their emission. The high structural flexibility of the Cu(I)-I chain is significantly linked to the corresponding alterations in structure. Remarkably, pressure can increase the conductivity by up to 3 orders of magnitude. Variations in resistivity are consistent with changes in the band gap energy. The experimental results are in agreement with the DFT calculations. These properties may allow the use of these CPs as optical pressure or temperature sensors. In addition, their behavior as a heterogeneous photocatalyst of persistent organic dyes has also been investigated.

DRMY1 promotes robust morphogenesis by sustaining translation of a hormone signaling protein.

Robustness is the invariant development of phenotype despite environmental changes and genetic perturbations. In the Arabidopsis flower bud, four sepals initiate at robust positions and times and grow to equal size to enclose and protect the inner floral organs. We previously characterized the mutant development related myb-like1 (drmy1), where 3-5 sepals initiate at irregular positions and variable times and grow to different sizes, compromising their protective function. The molecular mechanism underlying this loss of robustness was unclear. Here, we show that drmy1 has reduced TARGET OF RAPAMYCIN (TOR) activity, ribosomal content, and translation. Translation reduction decreases the protein level of ARABIDOPSIS RESPONSE REGULATOR7 (ARR7), a rapidly synthesized and degraded cytokinin signaling inhibitor. The resultant upregulation of cytokinin signaling disrupts the robust positioning of auxin signaling, causing variable sepal initiation. Our work shows that the homeostasis of translation, a ubiquitous cellular process, is crucial for the robust spatiotemporal patterning of organogenesis.