Cardioids reveal self-organizing principles of human cardiogenesis.

Organoids capable of forming tissue-like structures have transformed our ability to model human development and disease. With the notable exception of the human heart, lineage-specific self-organizing organoids have been reported for all major organs. Here, we established self-organizing cardioids from human pluripotent stem cells that intrinsically specify, pattern, and morph into chamber-like structures containing a cavity. Cardioid complexity can be controlled by signaling that instructs the separation of cardiomyocyte and endothelial layers and by directing epicardial spreading, inward migration, and differentiation. We find that cavity morphogenesis is governed by a mesodermal WNT-BMP signaling axis and requires its target HAND1, a transcription factor linked to developmental heart chamber defects. Upon cryoinjury, cardioids initiated a cell-type-dependent accumulation of extracellular matrix, an early hallmark of both regeneration and heart disease. Thus, human cardioids represent a powerful platform to mechanistically dissect self-organization, congenital heart defects and serve as a foundation for future translational research.

The Centrosome Is a Selective Condensate that Nucleates Microtubules by Concentrating Tubulin.

Centrosomes are non-membrane-bound compartments that nucleate microtubule arrays. They consist of nanometer-scale centrioles surrounded by a micron-scale, dynamic assembly of protein called the pericentriolar material (PCM). To study how PCM forms a spherical compartment that nucleates microtubules, we reconstituted PCM-dependent microtubule nucleation in vitro using recombinant C. elegans proteins. We found that macromolecular crowding drives assembly of the key PCM scaffold protein SPD-5 into spherical condensates that morphologically and dynamically resemble in vivo PCM. These SPD-5 condensates recruited the microtubule polymerase ZYG-9 (XMAP215 homolog) and the microtubule-stabilizing protein TPXL-1 (TPX2 homolog). Together, these three proteins concentrated tubulin ∼4-fold over background, which was sufficient to reconstitute nucleation of microtubule asters in vitro. Our results suggest that in vivo PCM is a selective phase that organizes microtubule arrays through localized concentration of tubulin by microtubule effector proteins.

Consecutive palmitoylation and phosphorylation orchestrates NLRP3 membrane trafficking and inflammasome activation.

NLRP3 inflammasome activation, essential for cytokine secretion and pyroptosis in response to diverse stimuli, is closely associated with various diseases. Upon stimulation, NLRP3 undergoes subcellular membrane trafficking and conformational rearrangements, preparing itself for inflammasome assembly at the microtubule-organizing center (MTOC). Here, we elucidate an orchestrated mechanism underlying these ordered processes using human and murine cells. Specifically, NLRP3 undergoes palmitoylation at two sites by palmitoyl transferase zDHHC1, facilitating its trafficking between subcellular membranes, including the mitochondria, trans-Golgi network (TGN), and endosome. This dynamic trafficking culminates in the localization of NLRP3 to the MTOC, where LATS1/2, pre-recruited to MTOC during priming, phosphorylates NLRP3 to further facilitate its interaction with NIMA-related kinase 7 (NEK7), ultimately leading to full NLRP3 activation. Consistently, Zdhhc1-deficiency mitigated LPS-induced inflammation and conferred protection against mortality in mice. Altogether, our findings provide valuable insights into the regulation of NLRP3 membrane trafficking and inflammasome activation, governed by palmitoylation and phosphorylation events.

Microtubule specialization by +TIP networks: from mechanisms to functional implications.

To fulfill their actual cellular role, individual microtubules become functionally specialized through a broad range of mechanisms. The 'search and capture' model posits that microtubule dynamics and functions are specified by cellular targets that they capture (i.e., a posteriori), independently of the microtubule-organizing center (MTOC) they emerge from. However, work in budding yeast indicates that MTOCs may impart a functional identity to the microtubules they nucleate, a priori. Key effectors in this process are microtubule plus-end tracking proteins (+TIPs), which track microtubule tips to regulate their dynamics and facilitate their targeted interactions. In this review, we discuss potential mechanisms of a priori microtubule specialization, focusing on recent findings indicating that +TIP networks may undergo liquid biomolecular condensation in different cell types.

Programmed disassembly of a microtubule-based membrane protrusion network coordinates 3D epithelial morphogenesis in Drosophila.

Comprehensive analysis of cellular dynamics during the process of morphogenesis is fundamental to understanding the principles of animal development. Despite recent advancements in light microscopy, how successive cell shape changes lead to complex three-dimensional tissue morphogenesis is still largely unresolved. Using in vivo live imaging of Drosophila wing development, we have studied unique cellular structures comprising a microtubule-based membrane protrusion network. This network, which we name here the Interplanar Amida Network (IPAN), links the two wing epithelium leaflets. Initially, the IPAN sustains cell-cell contacts between the two layers of the wing epithelium through basal protrusions. Subsequent disassembly of the IPAN involves loss of these contacts, with concomitant degeneration of aligned microtubules. These processes are both autonomously and non-autonomously required for mitosis, leading to coordinated tissue proliferation between two wing epithelia. Our findings further reveal that a microtubule organization switch from non-centrosomal to centrosomal microtubule-organizing centers (MTOCs) at the G2/M transition leads to disassembly of non-centrosomal microtubule-derived IPAN protrusions. These findings exemplify how cell shape change-mediated loss of inter-tissue contacts results in 3D tissue morphogenesis.

The spindle checkpoint proteins BUB1 and BUBR1: (SLiM)ming down to the basics.

Benzimidazole 1 (BUB1) and budding uninhibited by benzimidazole 1-related 1 (BUBR1) are multidomain paralogs with key roles in chromosome alignment during mitosis and the spindle assembly checkpoint (SAC), an evolutionarily conserved signaling pathway that monitors errors in chromosome segregation during cell division in eukaryotes. Although BUB1 and BUBR1 share a similar domain organization and short linear interaction motifs (SLiMs), they control distinct aspects of chromosome congression and the SAC. Here we discuss the roles of BUB1 and BUBR1 SLiMs in mitosis and complement this with additional insights gleamed from studying their evolution. We show that BUB1 and BUBR1 SLiMs form highly specific interactions that are carefully orchestrated in space and time and contend that they define BUB1 and BUBR1 as organizing hubs that drive SAC signaling and ensure genome stability.

The microtubule end-binding proteins EB1 and Patronin modulate the spatiotemporal dynamics of myosin and pattern pulsed apical constriction.

Apical constriction powers amnioserosa contraction during Drosophila dorsal closure. The nucleation, movement and dispersal of apicomedial actomyosin complexes generates pulsed apical constrictions during early closure. Persistent apicomedial and circumapical actomyosin complexes drive unpulsed constrictions that follow. Here, we show that the microtubule end-binding proteins EB1 and Patronin pattern constriction dynamics and contraction kinetics by coordinating the balance of actomyosin forces in the apical plane. We find that microtubule growth from moving Patronin platforms governs the spatiotemporal dynamics of apicomedial myosin through the regulation of RhoGTPase signaling by transient EB1-RhoGEF2 interactions. We uncover the dynamic reorganization of a subset of short non-centrosomally nucleated apical microtubules that surround the coalescing apicomedial myosin complex, trail behind it as it moves and disperse as the complex dissolves. We demonstrate that apical microtubule reorganization is sensitive to Patronin levels. Microtubule depolymerization compromised apical myosin enrichment and altered constriction dynamics. Together, our findings uncover the importance of reorganization of an intact apical microtubule meshwork, by moving Patronin platforms and growing microtubule ends, in enabling the spatiotemporal modulation of actomyosin contractility and, through it, apical constriction.

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections.

A crucial feature of life is its spatial organization and compartmentalization on the molecular, cellular, and tissue levels. Spatial transcriptomics (ST) technology has opened a new chapter of the sequencing revolution, emerging rapidly with transformative effects across biology. This technique produces extensive and complex sequencing data, raising the need for computational methods for their comprehensive analysis and interpretation. We developed the ST browser web tool for the interactive discovery of ST images, focusing on different functional aspects such as single gene expression, the expression of functional gene sets, as well as the inspection of the spatial patterns of cell-cell interactions. As a unique feature, our tool applies self-organizing map (SOM) machine learning to the ST data. Our SOM data portrayal method generates individual gene expression landscapes for each spot in the ST image, enabling its downstream analysis with high resolution. The performance of the spatial browser is demonstrated by disentangling the intra-tumoral heterogeneity of melanoma and the microarchitecture of the mouse brain. The integration of machine-learning-based SOM portrayal into an interactive ST analysis environment opens novel perspectives for the comprehensive knowledge mining of the organization and interactions of cellular ecosystems.

Fungal microtubule organizing centers are evolutionarily unstable structures.

For most Eukaryotic species the requirements of cilia formation dictate the structure of microtubule organizing centers (MTOCs). In this study we find that loss of cilia corresponds to loss of evolutionary stability for fungal MTOCs. We used iterative search algorithms to identify proteins homologous to those found in Saccharomyces cerevisiae, and Schizosaccharomyces pombe MTOCs, and calculated site-specific rates of change for those proteins that were broadly phylogenetically distributed. Our results indicate that both the protein composition of MTOCs as well as the sequence of MTOC proteins are poorly conserved throughout the fungal kingdom. To begin to reconcile this rapid evolutionary change with the rigid structure and essential function of the S. cerevisiae MTOC we further analyzed how structural interfaces among proteins influence the rates of change for specific residues within a protein. We find that a more stable protein may stabilize portions of an interacting partner where the two proteins are in contact. In summary, while the protein composition and sequences of the MTOC may be rapidly changing the proteins within the structure have a stabilizing effect on one another. Further exploration of fungal MTOCs will expand our understanding of how changes in the functional needs of a cell have affected physical structures, proteomes, and protein sequences throughout fungal evolution.

HOP stabilizes the HSFA1a and plays a main role in the onset of thermomorphogenesis.

Living organisms have the capacity to respond to environmental stimuli, including warm conditions. Upon sensing mild temperature, plants launch a transcriptional response that promotes morphological changes, globally known as thermomorphogenesis. This response is orchestrated by different hormonal networks and by the activity of different transcription factors, including the heat shock factor A1 (HSFA1) family. Members of this family interact with heat shock protein 70 (HSP70) and heat shock protein 90 (HSP90); however, the effect of this binding on the regulation of HSFA1 activity or of the role of cochaperones, such as the HSP70-HSP90 organizing protein (HOP) on HSFA1 regulation, remains unknown. Here, we show that AtHOPs are involved in the folding and stabilization of the HSFA1a and are required for the onset of the transcriptional response associated to thermomorphogenesis. Our results demonstrate that the three members of the AtHOP family bind in vivo to the HSFA1a and that the expression of multiple HSFA1a-responsive-responsive genes is altered in the hop1 hop2 hop3 mutant under warm temperature. Interestingly, HSFA1a is accumulated at lower levels in the hop1 hop2 hop3 mutant, while control levels are recovered in the presence of the proteasome inhibitor MG132 or the synthetic chaperone tauroursodeoxycholic acid (TUDCA). This uncovers the HSFA1a as a client of HOP complexes in plants and reveals the participation of HOPs in HSFA1a stability.

The role of the co-chaperone HOP in plant homeostasis during development and stress.

Proteins need to acquire their native structure in order to become fully functional. In specific cases, the active conformation is obtained spontaneously; nevertheless, many proteins need the assistance of chaperones and co-chaperones to be properly folded. These proteins help to maintain protein homeostasis under control conditions and under different stresses. HOP (HSP70-HSP90 organizing protein) is a highly conserved family of co-chaperones that assist HSP70 and HSP90 in the folding of specific proteins. In the last few years, findings in mammals and yeast have revealed novel functions of HOP and re-defined the role of HOP in protein folding. Here, we provide an overview of the most important aspects of HOP regulation and function in other eukaryotes and analyse whether these aspects are conserved in plants. In addition, we highlight the HOP clients described in plants and the role of HOP in plant development and stress response.

Viral Fitness Landscapes Based on Self-organizing Maps.

The creation of fitness maps from viral populations especially in the case of RNA viruses, with high mutation rates producing quasispecies, is complex since the mutant spectrum is in a very high-dimensional space. In this work, a new approach is presented using a class of neural networks, Self-Organized Maps (SOM), to represent realistic fitness landscapes in two RNA viruses: Human Immunodeficiency Virus type 1 (HIV-1) and Hepatitis C Virus (HCV). This methodology has proven to be very effective in the classification of viral quasispecies, using as criterium the mutant sequences in the population. With HIV-1, the fitness landscapes are constructed by representing the experimentally determined fitness on the sequence map. This approach permitted the depiction of the evolutionary paths of the variants subjected to processes of fitness loss and gain in cell culture. In the case of HCV, the efficiency was measured as a function of the frequency of each haplotype in the population by ultra-deep sequencing. The fitness landscapes obtained provided information on the efficiency of each variant in the quasispecies environment, that is, in relation to the entire spectrum of mutants. With the SOM maps, it is possible to determine the evolutionary dynamics of the different haplotypes.

Research on low-power driving fatigue monitoring method based on spiking neural network.

Fatigue driving is one of the leading causes of traffic accidents, and the rapid and accurate detection of driver fatigue is of paramount importance for enhancing road safety. However, the application of deep learning models in fatigue driving detection has long been constrained by high computational costs and power consumption. To address this issue, this study proposes an approach that combines Self-Organizing Map (SOM) and Spiking Neural Networks (SNN) to develop a low-power model capable of accurately recognizing the driver's mental state. Initially, spatial features are extracted from electroencephalogram (EEG) signals using the SOM network. Subsequently, the extracted weight vectors are encoded and fed into the SNN for fatigue driving classification. The research results demonstrate that the proposed method effectively considers the spatiotemporal characteristics of EEG signals, achieving efficient fatigue detection. Simultaneously, this approach successfully reduces the model's power consumption. When compared to traditional artificial neural networks, our method reduces energy consumption by approximately 12.21-42.59%.

PM10-bound trace elements in pan-European urban atmosphere.

Although many studies have discussed the impact of Europe's air quality, very limited research focused on the detailed phenomenology of ambient trace elements (TEs) in PM10 in urban atmosphere. This study compiled long-term (2013-2022) measurements of speciation of ambient urban PM10 from 55 sites of 7 countries (Switzerland, Spain, France, Greece, Italy, Portugal, UK), aiming to elucidate the phenomenology of 20 TEs in PM10 in urban Europe. The monitoring sites comprised urban background (UB, n = 26), traffic (TR, n = 10), industrial (IN, n = 5), suburban background (SUB, n = 7), and rural background (RB, n = 7) types. The sampling campaigns were conducted using standardized protocols to ensure data comparability. In each country, PM10 samples were collected over a fixed period using high-volume air samplers. The analysis encompassed the spatio-temporal distribution of TEs, and relationships between TEs at each site. Results indicated an annual average for the sum of 20 TEs of 90 ± 65 ng/m3, with TR and IN sites exhibiting the highest concentrations (130 ± 66 and 131 ± 80 ng/m3, respectively). Seasonal variability in TEs concentrations, influenced by emission sources and meteorology, revealed significant differences (p < 0.05) across all monitoring sites. Estimation of TE concentrations highlighted distinct ratios between non-carcinogenic and carcinogenic metals, with Zn (40 ± 49 ng/m3), Ti (21 ± 29 ng/m3), and Cu (23 ± 35 ng/m3) dominating non-carcinogenic TEs, while Cr (5 ± 7 ng/m3), and Ni (2 ± 6 ng/m3) were prominent among carcinogenic ones. Correlations between TEs across diverse locations and seasons varied, in agreement with differences in emission sources and meteorological conditions. This study provides valuable insights into TEs in pan-European urban atmosphere, contributing to a comprehensive dataset for future environmental protection policies.

Implication of self-organizing map, stable isotopes combined with MixSIAR model for accurate nitrogen control in a well-protected reservoir.

Nitrogen pollution and eutrophication in reservoirs is a global environmental geochemical concern. Occasional algal blooms still exist in reservoirs that have undergone pollution treatment. The lack of quantitative evidence of nitrogen sources and fate limits long-term stable ecological safety management. This work applied an approach integrated zonal mapping, stable isotopes (δ18OH2O, δ15Nnitrate, δ18Onitrate, and δ13C-DIC) and a Bayesian isotope model to analyze regional and seasonal differences in the contribution and sources of nitrogen to a well-protected reservoir. The values of δ18Onitrate and the positive relationship between NO3- and δ13C-DIC suggested that nitrification was the primary NO3- production in the rivers. While Denitrification was present at only a few sites. Results of the MixSIAR model coupled the NO3-/Cl- indicator revealed that the domestic sewage contributed high riverine NO3- loading (68.6 ± 10.6 %) in the dry season. In the wet season, the main nitrate sources of upper watershed were ammonia and carbamide fertilizers (47.5 % and 40.3 %). While the domestic sewage was still the major contributor of downstream region (a dense residential area), indicating possible problems with rainwater and sewage drainage networks. The results implied that the colleting and treatment of sewages were the priority in downstream region, and non-point source pollution control and wastewater treatment plant upgrading were essential to control nitrate pollution in the two upstream regions. These findings provide new insights into precise nitrogen pollution traceability and identification of treatment priorities in the sub-region, and promote the management other well-protected watershed in similar need of further nitrogen contamination control.

Groundwater hydrochemistry, source identification and health assessment based on self-organizing map in an intensive mining area in Shanxi, China.

The Changzhi Basin in Shanxi is renowned for its extensive mining activities. It's crucial to comprehend the spatial distribution and geochemical factors influencing its water quality to uphold water security and safeguard the ecosystem. However, the complexity inherent in hydrogeochemical data presents challenges for linear data analysis methods. This study utilizes a combined approach of self-organizing maps (SOM) and K-means clustering to investigate the hydrogeochemical sources of shallow groundwater in the Changzhi Basin and the associated human health risks. The results showed that the groundwater chemical characteristics were categorized into 48 neurons grouped into six clusters (C1-C6) representing different groundwater types with different contamination characteristics. C1, C3, and C5 represent uncontaminated or minimally contaminated groundwater (Ca-HCO3 type), while C2 signifies mixed-contaminated groundwater (HCO3-Ca type, Mixed Cl-Mg-Ca type, and CaSO4 type). C4 samples exhibit impacts from agricultural activities (Mixed Cl-Mg-Ca), and C6 reflects high Ca and NO3- groundwater. Anthropogenic activities, especially agriculture, have resulted in elevated NO3- levels in shallow groundwater. Notably, heightened non-carcinogenic risks linked to NO3-, Pb, F-, and Mn exposure through drinking water, particularly impacting children, warrant significant attention. This research contributes valuable insights into sustainable groundwater resource development, pollution mitigation strategies, and effective ecosystem protection within intensive mining regions like the Changzhi Basin. It serves as a vital reference for similar areas worldwide, offering guidance for groundwater management, pollution prevention, and control.

Aggression heuristics underlie animal dominance hierarchies and provide evidence of group-level social information.

Members of a social species need to make appropriate decisions about who, how, and when to interact with others in their group. However, it has been difficult for researchers to detect the inputs to these decisions and, in particular, how much information individuals actually have about their social context. We present a method that can serve as a social assay to quantify how patterns of aggression depend upon information about the ranks of individuals within social dominance hierarchies. Applied to existing data on aggression in 172 social groups across 85 species in 23 orders, it reveals three main patterns of rank-dependent social dominance: the downward heuristic (aggress uniformly against lower-ranked opponents), close competitors (aggress against opponents ranked slightly below self), and bullying (aggress against opponents ranked much lower than self). The majority of the groups (133 groups, 77%) follow a downward heuristic, but a significant minority (38 groups, 22%) show more complex social dominance patterns (close competitors or bullying) consistent with higher levels of social information use. These patterns are not phylogenetically constrained and different groups within the same species can use different patterns, suggesting that heuristic use may depend on context and the structuring of aggression by social information should not be considered a fixed characteristic of a species. Our approach provides opportunities to study the use of social information within and across species and the evolution of social complexity and cognition.

"We been dying, and you got me on a call helping you stay alive": Black and Latinx youth organizers' experiences of racism in gun violence prevention organizations.

This study explored Black and Latinx youth organizers' experiences of racism within national gun violence prevention organizing spaces. Interview data were analyzed from 17 Black and/or Latinx youth (Mage = 20.17, 47% women) across the United States who organized against gun violence. The findings identified three forms of racism that Black and Latinx organizers experienced in national organizations: (1) being tokenized for their racial identities and experiences without having real decision making power; (2) feeling a burden to educate their white peers about the structural causes of gun violence and how to improve organizing spaces for other youth of color; and (3) being silenced in their racially conscious organizing efforts to address the structural causes of gun violence in their communities. This research highlights how Black and Latinx youth gun violence prevention organizers contend both with structural racism in their everyday lives and racism in organizing spaces.

The straw that broke the nurse's back-Using psychological contract breach to understand why nurses leave.

AIM: To deepen our understanding of why nurses decide to leave their occupation instead of changing jobs, we examined the antecedents that led to this decision through the theoretical lens of psychological contract breach. DESIGN: A qualitative design with semi-structured interviews. METHODS: We collected 28 interviewees from our social networks and a social media platform. We included professional nurses who had decided to leave or had left the occupation. We analysed our data with reflexive thematic analysis, thereby giving space for the interviewee voices to rise. RESULTS: We identified various experiences of dissonance between interviewee expectations and reality. The interviewees expressed unfulfilled expectations or psychological contract breaches in relation to their occupation on different levels and over extended time periods. The psychological contract breaches and decisions to leave the occupation were built up over time because of continuous disappointment and dissonance between expectations and reality. The frustration, dissonance and unfulfilled expectations were expressed towards the institution of nursing rather than a specific employer or organization. CONCLUSION: Unfulfilled expectations over a longer period might cause psychological contract breach, leading to turnover intentions. Our research brings novel insights into the psychological contract, as our findings indicate that the psychological contract can be formed and breached, also between the employee and the occupation. This means that turnover intentions might result in nurses leaving the profession rather than seeking work in new organizations. IMPACT: The study addresses the problem of nurse shortage by showing the root reasons for deciding to leave the occupation. Our findings show how psychological contract breaches over time erupt as turnover intentions regarding the occupation rather than a job. The results guide healthcare managers and decision-makers to recognize factors leading to a psychological contract breach, thereby enabling the retention of nurses. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Electroencephalogram-Based Facial Gesture Recognition Using Self-Organizing Map.

Brain-computer interfaces (BCIs) allow information to be transmitted directly from the human brain to a computer, enhancing the ability of human brain activity to interact with the environment. In particular, BCI-based control systems are highly desirable because they can control equipment used by people with disabilities, such as wheelchairs and prosthetic legs. BCIs make use of electroencephalograms (EEGs) to decode the human brain's status. This paper presents an EEG-based facial gesture recognition method based on a self-organizing map (SOM). The proposed facial gesture recognition uses α, ß, and θ power bands of the EEG signals as the features of the gesture. The SOM-Hebb classifier is utilized to classify the feature vectors. We utilized the proposed method to develop an online facial gesture recognition system. The facial gestures were defined by combining facial movements that are easy to detect in EEG signals. The recognition accuracy of the system was examined through experiments. The recognition accuracy of the system ranged from 76.90% to 97.57% depending on the number of gestures recognized. The lowest accuracy (76.90%) occurred when recognizing seven gestures, though this is still quite accurate when compared to other EEG-based recognition systems. The implemented online recognition system was developed using MATLAB, and the system took 5.7 s to complete the recognition flow.