Fabrication, characterization and numerical validation of a novel thin-wall hydrogel vessel model for cardiovascular research based on a patient-specific stenotic carotid artery bifurcation.

In vitro vascular models, primarily made of silicone, have been utilized for decades for studying hemodynamics and supporting the development of implants for catheter-based treatments of diseases such as stenoses and aneurysms. Hydrogels have emerged as prominent materials in tissue-engineering applications, offering distinct advantages over silicone models for fabricating vascular models owing to their viscoelasticity, low friction, and tunable mechanical properties. Our study evaluated the feasibility of fabricating thin-wall, anatomical vessel models made of polyvinyl alcohol hydrogel (PVA-H) based on a patient-specific carotid artery bifurcation using a combination of 3D printing and molding technologies. The model's geometry, elastic modulus, volumetric compliance, and diameter distensibility were characterized experimentally and numerically simulated. Moreover, a comparison with silicone models with the same anatomy was performed. A PVA-H vessel model was integrated into a mock circulatory loop for a preliminary ultrasound-based assessment of fluid dynamics. The vascular model's geometry was successfully replicated, and the elastic moduli amounted to 0.31 ± 0.007 MPa and 0.29 ± 0.007 MPa for PVA-H and silicone, respectively. Both materials exhibited nearly identical volumetric compliance (0.346 and 0.342% mmHg-1), which was higher compared to numerical simulation (0.248 and 0.290% mmHg-1). The diameter distensibility ranged from 0.09 to 0.20% mmHg-1 in the experiments and between 0.10 and 0.18% mmHg-1 in the numerical model at different positions along the vessel model, highlighting the influence of vessel geometry on local deformation. In conclusion, our study presents a method and provides insights into the manufacturing and mechanical characterization of hydrogel-based thin-wall vessel models, potentially allowing for a combination of fluid dynamics and tissue engineering studies in future cardio- and neurovascular research.

Endophyte mediated biocontrol mechanisms of phytopathogens in agriculture.

The global human population is growing and demand for food is increasing. Global agriculture faces numerous challenges, including excessive application of synthetic pesticides, emergence of herbicide-and pesticide-resistant pathogenic microbes, and more frequent natural disasters associated with global warming. Searches for valuable endophytes have increased, with the aim of making agriculture more sustainable and environmentally friendly. Endophytic microbes are known to have a variety of beneficial effects on plants. They can effectively transfer nutrients from the soil into plants, promote plant growth and development, increase disease resistance, increase stress tolerance, prevent herbivore feeding, reduce the virulence of pathogens, and inhibit the growth of rival plant species. Endophytic microbes can considerably minimize the need for agrochemicals, such as fertilizers, fungicides, bactericides, insecticides, and herbicides in the cultivation of crop plants. This review summarizes current knowledge on the roles of endophytes focusing on their mechanisms of disease control against phytopathogens through the secretion of antimicrobial substances and volatile organic compounds, and the induction of systemic resistance in plants. Additionally, the beneficial roles of these endophytes and their metabolites in the control of postharvest diseases in plants have been summarized.

Children's oppositional defiant disorder symptoms and neural synchrony in mother-child interactions: An fNIRS study.

Interpersonal neural synchrony (INS) between mothers and children responds to the temporal similarity of brain signals in joint behavior between dyadic partners and is considered an important neural indicator of the formation of adaptive social interaction bonds. Parent-child interactions are particularly important for the development and maintenance of oppositional defiant disorder (ODD) in children, but the underlying neurocognitive mechanisms are unknown. Therefore, in the current study we measured INS between mothers and children in interactions by using simultaneous functional Near-infrared Spectroscopy (fNIRS), and explored its association with ODD symptoms in children. Seventy-two mother-child dyads were recruited to participate in the study, including 35 children with ODD and 37 healthy children to be used as a control. Each mother-child dyad was measured for neural activity in frontal, parietal, and temporal lobe regions while completing free-play as well as positive, and negative topic discussion tasks. We used Phase-locked value to calculate the synchrony strength and then used the K-means algorithm and k-space based alignment tests to confirm the specific patterns of parent-child synchrony in different brain areas. The results showed that, in free-play (right MFG and bilateral SFG), positive (left TPJ and bilateral SFGdor), and negative (bilateral SFGmed, right ANG, and left MFG) topic discussions, the mother-child pairs showed different patterns of INS. These specific INS patterns were significantly lower in the ODD group compared to the control group and were negatively associated with ODD symptoms in children. Network analyses showed that these INS patterns were connected to different nodes in the ODD symptom network. Our findings suggest that ODD mother-child dyads exhibit lower neural synchrony across a wide range of parent-child interactions. Neural synchrony in the context of interpersonal interactions provides new insights into understanding the neural mechanisms of ODD and can be used as an indicator of neural and socio-environmental factors in the network of psychological disorder symptoms.

Interplay among manures, vegetable types, and tetracycline resistance genes in rhizosphere microbiome.

The rapid global emergence of antibiotic resistance genes (ARGs) is a substantial public health concern. Livestock manure serves as a key reservoir for tetracycline resistance genes (TRGs), serving as a means of their transmission to soil and vegetables upon utilization as a fertilizer, consequently posing a risk to human health. The dynamics and transfer of TRGs among microorganisms in vegetables and fauna are being investigated. However, the impact of different vegetable species on acquisition of TRGs from various manure sources remains unclear. This study investigated the rhizospheres of three vegetables (carrots, tomatoes, and cucumbers) grown with chicken, sheep, and pig manure to assess TRGs and bacterial community compositions via qPCR and high-throughput sequencing techniques. Our findings revealed that tomatoes exhibited the highest accumulation of TRGs, followed by cucumbers and carrots. Pig manure resulted in the highest TRG levels, compared to chicken and sheep manure, in that order. Bacterial community analyses revealed distinct effects of manure sources and the selective behavior of individual vegetable species in shaping bacterial communities, explaining 12.2% of TRG variation. Firmicutes had a positive correlation with most TRGs and the intl1 gene among the dominant phyla. Notably, both the types of vegetables and manures significantly influenced the abundance of the intl1 gene and soil properties, exhibiting strong correlations with TRGs and elucidating 30% and 17.7% of TRG variance, respectively. Our study delineated vegetables accumulating TRGs from manure-amended soils, resulting in significant risk to human health. Moreover, we elucidated the pivotal roles of bacterial communities, soil characteristics, and the intl1 gene in TRG fate and dissemination. These insights emphasize the need for integrated strategies to reduce selection pressure and disrupt TRG transmission routes, ultimately curbing the transmission of tetracycline resistance genes to vegetables.

Fluid-structure interaction simulation of mechanical aortic valves: a narrative review exploring its role in total product life cycle.

Over the last years computer modelling and simulation has emerged as an effective tool to support the total product life cycle of cardiovascular devices, particularly in the device preclinical evaluation and post-market assessment. Computational modelling is particularly relevant for heart valve prostheses, which require an extensive assessment of their hydrodynamic performance and of risks of hemolysis and thromboembolic complications associated with mechanically-induced blood damage. These biomechanical aspects are typically evaluated through a fluid-structure interaction (FSI) approach, which enables valve fluid dynamics evaluation accounting for leaflets movement. In this context, the present narrative review focuses on the computational modelling of bileaflet mechanical aortic valves through FSI approach, aiming to foster and guide the use of simulations in device total product life cycle. The state of the art of FSI simulation of heart valve prostheses is reviewed to highlight the variety of modelling strategies adopted in the literature. Furthermore, the integration of FSI simulations in the total product life cycle of bileaflet aortic valves is discussed, with particular emphasis on the role of simulations in complementing and potentially replacing the experimental tests suggested by international standards. Simulations credibility assessment is also discussed in the light of recently published guidelines, thus paving the way for a broader inclusion of in silico evidence in regulatory submissions. The present narrative review highlights that FSI simulations can be successfully framed within the total product life cycle of bileaflet mechanical aortic valves, emphasizing that credible in silico models evaluating the performance of implantable devices can (at least) partially replace preclinical in vitro experimentation and support post-market biomechanical evaluation, leading to a reduction in both time and cost required for device development.

Rexinoids Induce Differential Gene Expression in Human Glioblastoma Cells and Protein-Protein Interactions in a Yeast Two-Hybrid System.

Rexinoids are compounds that bind to the rexinoid X receptor (RXR) to modulate gene expression and have been proposed as a new class of therapeutics to treat Alzheimer's disease. Different rexinoids will initiate downstream effects that can be quite marked even though such compounds can be structurally similar and have comparable RXR binding affinities. RXR can both homo- and heterodimerize, and these protein-protein interactions and subsequent transactivating potential lead to differential gene expression, depending on the RXR dimeric partner, additional cofactors recruited, and downstream transcription factors that are up- or downregulated. Expression analysis was performed in the U87 human glioblastoma cell line treated with a panel of rexinoids, and our analysis demonstrated that rexinoids with similar RXR EC50 values can have pronounced differences in differential gene expression. Rexinoid binding likely leads to distinctive RXR conformations that cause major downstream gene expression alterations via modulation of RXR interacting proteins. Yeast two-hybrid analysis of RXR bait with two RXR interacting partners demonstrates that rexinoids drive differential binding of RXR to distinctive protein partners. Physiochemical analysis of the rexinoids reveals that the molecules cluster similarly to their gene expression patterns. Thus, rexinoids with similar RXR binding affinities drive differential gene expression by stimulating additional binding patterns in RXR and its homo- and heteropartners, driven by the physicochemical characteristics of these molecules.

Insights into the Early Steps of the Symbiotic Interaction between Soybean (Glycine max) and Sinorhizobium fredii Symbiosis Using Transcriptome, Small RNA, and Degradome Sequencing.

Symbiotic nitrogen fixation carried out by the soybean-rhizobia symbiosis increases soybean yield and reduces the amount of nitrogen fertilizer that has been applied. MicroRNAs (miRNAs) are crucial in plant growth and development, prompting an investigation into their role in the symbiotic interaction of soybean with partner rhizobia. Through integrated small RNA, transcriptome, and degradome sequencing analysis, 1215 known miRNAs, 314 of them conserved, and 187 novel miRNAs were identified, with 44 differentially expressed miRNAs in soybean roots inoculated with Sinorhizobium fredii HH103 and a ttsI mutant. The study unveiled that the known miRNA gma-MIR398a-p5 was downregulated in the presence of the ttsI mutation, while the target gene of gma-MIR398a-p5, Glyma.06G007500, associated with nitrogen metabolism, was upregulated. The results of this study offer insights for breeding high-efficiency nitrogen-fixing soybean varieties, enhancing crop yield and quality.

Effect of molecular crowders on ligand binding kinetics with G-quadruplex DNA probed by fluorescence correlation spectroscopy.

Guanine-rich single-stranded DNA folds into G-quadruplex DNA (GqDNA) structures, which play crucial roles in various biological processes. These structures are also promising targets for ligands, potentially inducing antitumor effects. While thermodynamic parameters of ligand/DNA interactions are well-studied, the kinetics of ligand interaction with GqDNA, particularly in cell-like crowded environments, remain less explored. In this study, we investigate the impact of molecular crowding agents (glucose, sucrose, and ficoll 70) at physiologically relevant concentrations (20% w/v) on the association and dissociation rates of the benzophenoxazine-core based ligand, cresyl violet (CV), with human telomeric antiparallel-GqDNA. We utilized fluorescence correlation spectroscopy (FCS) along with other techniques. Our findings reveal that crowding agents decrease the binding affinity of CV to GqDNA, with the most significant effect-a nearly three-fold decrease-observed with ficoll 70. FCS measurements indicate that this decrease is primarily due to a viscosity-induced slowdown of ligand association in the crowded environment. Interestingly, dissociation rates remain largely unaffected by smaller crowders, with only small effect observed in presence of ficoll 70 due to direct but weak interaction between the ligand and ficoll. These results along with previously reported data provide valuable insights into ligand/GqDNA interactions in cellular contexts, suggesting a conserved mechanism of saccharide crowder influence, regardless of variations in GqDNA structure and ligand binding mode. This underscores the importance of considering crowding effects in the design and development of GqDNA-targeted drugs for potential cancer treatment.

Motor Control in Parkinson's Disease During the Performance of Multi-Joint Reversal Movements.

We tested if the movement slowness of individuals with Parkinson's disease is related to their decreased ability to generate adequate net torques and linearly coordinate them between joints. This cross-sectional study included ten individuals with Parkinson's disease and ten healthy individuals. They performed planar movements with a reversal over three target distances. We calculated joint kinematics of the elbow and shoulder using spatial orientation. The muscle, interaction, and net torques were integrated into the acceleration/deceleration phases of the fingertip speed. We calculated the linear correlations of those torques between joints. Both groups modulated the elbow and shoulder net torques with target distances. They linearly coupled the production of torques. Both groups did not modulate the interaction torques. The movement slowness in Parkinson's disease was related to the difficulty in generating the appropriate muscle and net torques in the task. The interaction torques do not seem to play any role in movement control.

Qualitative and Untargeted Volatilome Fingerprinting of Aspergillus sp. and Bulbithecium sp. by HS-SPME-GCMS and Functional Interactions.

Research on fungal volatile organic compounds (VOCs) has increased worldwide in the last 10 years, but marine fungal volatilomes remain underexplored. Similarly, the hormone-signaling pathways, agronomic significance, and biocontrol potential of VOCs in plant-associated fungi make the area of research extremely promising. In the current investigation, VOCs of the isolates-Aspergillus sp. GSBT S13 and GSBT S14 from marine sediments, and Bulbithecium sp. GSBT E3 from Eucalyptus foliage were extracted using Head Space solid phase microextraction, followed by gas chromatography-mass spectrometry, identification, statistical analyses, and prediction of functions by KEGG COMPOUND and STITCH 5.0 databases. The significance of this research is fingerprinting VOCs of the isolates from distinct origins, identification of compounds using three libraries (NIST02, NIST14, and W9N11), and using bioinformatic tools to perform functional analysis. The most important findings include the identification of previously unreported compounds in fungi-1-methoxy naphthalene, diethyl phthalate, pentadecane, pristane, and nonanal; the prediction of the involvement of small molecules in the degradation of aromatic compound pathways and activation, inhibition, binding, and catalysis of metabolites with predicted protein partners. This study has ample opportunity to validate the findings and understand the mechanism or mode of action, the interspecies interactions, and the role of the metabolites in geochemical cycles.

Hydrolyzed Chicken Meat Extract and Its Bioactive Cyclopeptides Protect Neural Function by Attenuating Inflammation and Apoptosis via PI3K/AKT and AMPK Pathways.

Cognitive decline is inevitable with age, and due to the lack of well-established pharmacotherapies for neurodegenerative disorders, dietary supplements have become important alternatives to ameliorate brain deterioration. Hydrolyzed chicken meat extract (HCE) and its bioactive components were previously found to improve neuroinflammation and cognitive decline by regulating microglia polarization. However, the effects and mechanisms of these bioactives on neurons remain unclear. Here, the most potent bioactive component on neural function in HCE was screened out, and the detailed mechanism was clarified through in vivo and in vitro experiments. We found that HCE, cyclo(Val-Pro), cyclo(Phe-Phe), cyclo(His-Pro), cyclo(Leu-Lys), and arginine exerted stronger anti-inflammatory and antioxidant effects among the 12 bioactives in amyloid ß (Aß)-treated HT-22 cells. Further transcriptome sequencing and polymerase chain reaction (PCR) array analysis showed that these bioactives participated in different signaling pathways, and cyclo(Val-Pro) was identified as the most potent cyclic dipeptide. In addition, the antiapoptotic and neuroprotective effect of cyclo(Val-Pro) was partly regulated by the activation of PI3K/AKT and AMPK pathways, and the inhibition of these pathways abolished the effect of cyclo(Val-Pro). Moreover, cyclo(Val-Pro) enhanced cognitive function and neurogenesis and alleviated neuroinflammation and oxidative stress in middle-aged mice, with an effect similar to HCE. Hippocampal transcriptome analysis further revealed that HCE and cyclo(Val-Pro) significantly enriched the neuroactive ligand-receptor interaction pathway, verified by enhanced neurotransmitter levels and upregulated neurotransmitter receptor-related gene expression. Therefore, the mechanism of cyclo(Val-Pro) on neural function might be associated with PI3K/AKT and AMPK pathway-mediated antiapoptotic effect and neurogenesis and the activation of the neurotransmitter-receptor pathway.

Impact of a High-Fat Meal on the Pharmacokinetics of Sotorasib, a KRAS G12C Inhibitor.

Sotorasib is a small molecule drug that specifically and irreversibly inhibits the KRAS p.G12C mutant protein. This analysis investigated the impact of a high-calorie high-fat meal on the pharmacokinetics, safety, and tolerability of sotorasib in both healthy volunteers and patients with KRAS G12C advanced solid tumors. Each subject received a single oral dose of 360 or 960 mg of sotorasib under fasted conditions or with a high-fat meal (fed conditions). The geometric least squares means (GLSM) ratios (fed/fasted) for 360 mg of sotorasib Cmax and AUCinf were 1.03 and 1.38, respectively, in healthy volunteers (N = 14). The GLSM ratios (fed/fasted) for Cmax and AUC0-24h were 1.38 and 1.75, respectively, with 360 mg of sotorasib in cancer patients (N = 2). The GLSM ratios (fed/fasted) for Cmax and AUC0-24h were 0.660 and 1.25, respectively, with 960 mg of sotorasib in cancer patients (N = 8). Sotorasib was well tolerated in fast and fed conditions. The impact of a high-fat meal on sotorasib exposure is less than a 2-fold increase or decrease in Cmax and AUCs.

Frictional Properties of Two-Dimensional Materials: Data-Driven Machine Learning Predictive Modeling.

Friction, typically associated with reduced efficiency and reliability of machines and devices, occurs when two objects are displaced against each other. This is a strongly material-dependent phenomenon, and the emergence of many 2D materials has opened up new opportunities to design systems with desired tribological properties. Here, we combine high throughput simulations and machine learning models to develop a statistical approach of adhesion, van der Waals, and corrugation energies of a large dataset of monolayered materials. The machine learning models are used to predict these closely related to friction energetic properties and link them to easily accessible atomistic and monolayer features. This approach elevates the materials' perspective of frictional properties. It demonstrates that data-driven models are extremely useful in discovering important structure-property functionalities for frictional property interpretations as a fruitful route toward desired tribological materials.

The role of reactive oxygen species in plant-virus interactions.

Reactive oxygen species (ROS) play a complex role in interactions between plant viruses and their host plants. They can both help the plant defend against viral infection and support viral infection and spread. This review explores the various roles of ROS in plant-virus interactions, focusing on their involvement in symptom development and the activation of plant defense mechanisms. The article discusses how ROS can directly inhibit viral infection, as well as how they can regulate antiviral mechanisms through various pathways involving miRNAs, virus-derived small interfering RNAs, viral proteins, and host proteins. Additionally, it examines how ROS can enhance plant resistance by interacting with hormonal pathways and external substances. The review also considers how ROS might promote viral infection and transmission, emphasizing their intricate role in plant-virus dynamics. These insights offer valuable guidance for future research, such as exploring the manipulation of ROS-related gene expression through genetic engineering, developing biopesticides, and adjusting environmental conditions to improve plant resistance to viruses. This framework can advance research in plant disease resistance, agricultural practices, and disease control.

Analyzing VEGFA/VEGFR1 Interaction: Application of the Resonant Recognition Model-Stockwell Transform Method to Explore Potential Therapeutics for Angiogenesis-Related Diseases.

The interaction between vascular endothelial growth factor A (VEGFA) and VEGF receptor 1(VEGFR1) is a central focus for drug development in pathological angiogenesis, where aberrant angiogenesis underlies various anomalies necessitating therapeutic intervention. Identifying hotspots of these proteins is crucial for developing new therapeutics. Although machine learning techniques have succeeded significantly in prediction tasks, they struggle to pinpoint hotspots linked to angiogenic activity accurately. This study involves the collection of diverse VEGFA and VEGFR1 protein sequences from various species via the UniProt database. Electron-ion interaction Potential (EIIP) values were assigned to individual amino acids and transformed into frequency-domain representations using discrete Fast Fourier Transform (FFT). A consensus spectrum emerged by consolidating FFT data from multiple sequences, unveiling specific characteristic frequencies. Subsequently, the Stockwell Transform (ST) was employed to yield the hotspots. The Resonant Recognition Model (RRM) identified a characteristic frequency of 0.128007 with an associated wavelength of 1570 nm and RRM-ST identified hotspots for VEGFA (Human 36, 46, 48, 67, 71, 74, 82, 86, 89, 93) and VEGFR1 (Human 224, 259, 263, 290, 807, 841, 877, 881, 885, 892, 894, 909, 913, 1018, 1022, 1026, 1043). These findings were cross-validated by Hotspots Wizard 3.0 webserver and Protein Data Bank (PDB). The study proposes using a 1570 nm wavelength for photo bio modulation to boost VEGFA/VEGFR1 interaction in the condition that is needed. It also aims to reduce VEGFA/VEGFR2 interaction, limiting harmful angiogenesis in conditions like diabetic retinopathy. Also, the identified hotspots assist in designing agonistic or antagonistic peptides tailored to specific medical requirements with abnormal angiogenesis.

Unravelling the involvement of protein disorder in cyanobacterial stress responses.

This study explored the involvement of Intrinsically Disordered Proteins, (IDPs) in cyanobacterial stress response. IDPs possess distinct physicochemical properties, which allow them to execute diverse functions. Anabaena PCC 7120, the model photosynthetic, nitrogen-fixing cyanobacterium encodes 688 proteins (11 % of total proteome) with at least one intrinsically disordered region (IDR). Of these, 130 proteins that showed >30 % overall disorder were designated as IDPs. Physico-chemical analysis, showed these IDPs to adopt shapes ranging from 'globular' to 'tadpole-like'. Upon exposure to NaCl, 41 IDP-encoding genes were found to be differentially expressed. Surprisingly, most of these were induced, indicating the importance of IDP-accumulation in overcoming salt stress. Subsequently, six IDPs were identified to be induced by multiple stresses (salt, ammonium and selenite). Interestingly, the presence of these 6-multiple stress-induced IDPs was conserved in filamentous cyanobacteria. Utilizing the experimental proteomic data of Anabaena, these 6 IDPs were found to interact with many proteins involved in diverse pathways, underscoring their physiological importance as protein hubs. This study lays the framework for IDP-related research in Anabaena by (a) identifying, as well as physiochemically characterizing, all the disordered proteins and (b) uncovering a subset of IDPs that are likely to be critical in stress adaptation.

Spectroscopic, electrochemical, and molecular docking studies of the interaction between the antihistamine drug desloratadine and dsDNA.

Through the utilization of fluorescence spectroscopy, electrochemical, and molecular docking methods, this research investigates the interaction between the antihistamine drug desloratadine and calf thymus double-stranded DNA (ct-dsDNA). Deoxyguanosine (dGuo) and deoxyadenosine (dAdo) oxidation signals were diminished by incubation with varying concentrations of desloratadine, as determined by differential pulse voltammetry (DPV). This change was ascribed to desloratadine's binding mechanism to ct-dsDNA. The binding constant (Kb) between desloratadine and ct-dsDNA was determined to be 2.2 × 105 M-1 throughout electrochemical experiments. In order to further develop our comprehension of the interaction mechanism between desloratadine and ct-dsDNA, a series of spectroscopic experiments and molecular docking simulations were conducted. The Kb value was found to be 8.85 × 104 M-1 at a temperature of 25 °C by the use of fluorescence spectroscopic techniques. In summary, the utilization of electrochemical and spectroscopic techniques, alongside molecular docking investigations, has led to the prediction that desloratadine has the capability to interact with ct-dsDNA by groove binding.

Dynamic framework for large-scale modeling of membranes and peripheral proteins.

In this chapter, we present a novel computational framework to study the dynamic behavior of extensive membrane systems, potentially in interaction with peripheral proteins, as an alternative to conventional simulation methods. The framework effectively describes the complex dynamics in protein-membrane systems in a mesoscopic particle-based setup. Furthermore, leveraging the hydrodynamic coupling between the membrane and its surrounding solvent, the coarse-grained model grounds its dynamics in macroscopic kinetic properties such as viscosity and diffusion coefficients, marrying the advantages of continuum- and particle-based approaches. We introduce the theoretical background and the parameter-space optimization method in a step-by-step fashion, present the hydrodynamic coupling method in detail, and demonstrate the application of the model at each stage through illuminating examples. We believe this modeling framework to hold great potential for simulating membrane and protein systems at biological spatiotemporal scales, and offer substantial flexibility for further development and parametrization.

"They Don't Come With a Handbook": Exploring Design Opportunities for Supporting Parent-Child Interaction around Emotions in the Family Context.

Parenting practices have a profound effect on children's well-being and are a core target of several psychological interventions for child mental health. However, there is only limited understanding in HCI so far about how to design socio-technical systems that could support positive shifts in parent-child social practices in situ. This paper focuses on parental socialisation of emotion as an exemplar context in which to explore this question. We present a two-step study, combining theory-driven identification of plausible design directions with co-design workshops with 22 parents of children aged 6-10 years. Our data suggest the potential for technology-enabled systems that aim to facilitate positive changes in parent-child social practices in situ, and highlight a number of plausible design directions to explore in future work.

Review: Cancer and neurodevelopmental disorders: multi-scale reasoning and computational guide.

The connection and causality between cancer and neurodevelopmental disorders have been puzzling. How can the same cellular pathways, proteins, and mutations lead to pathologies with vastly different clinical presentations? And why do individuals with neurodevelopmental disorders, such as autism and schizophrenia, face higher chances of cancer emerging throughout their lifetime? Our broad review emphasizes the multi-scale aspect of this type of reasoning. As these examples demonstrate, rather than focusing on a specific organ system or disease, we aim at the new understanding that can be gained. Within this framework, our review calls attention to computational strategies which can be powerful in discovering connections, causalities, predicting clinical outcomes, and are vital for drug discovery. Thus, rather than centering on the clinical features, we draw on the rapidly increasing data on the molecular level, including mutations, isoforms, three-dimensional structures, and expression levels of the respective disease-associated genes. Their integrated analysis, together with chromatin states, can delineate how, despite being connected, neurodevelopmental disorders and cancer differ, and how the same mutations can lead to different clinical symptoms. Here, we seek to uncover the emerging connection between cancer, including pediatric tumors, and neurodevelopmental disorders, and the tantalizing questions that this connection raises.