Development Time Research Articles

Noncanonical inheritance of phenotypic information by protein amyloids.

All known heritable phenotypic information in animals is transmitted by direct inheritance of nucleic acids, their covalent modifications or histone modifications that modulate expression of associated genomic regions. Nonetheless, numerous familial traits and disorders cannot be attributed to known heritable molecular factors. Here we identify amyloid-like protein structures that are stably inherited in wild-type animals and influence traits. Their perturbation by genetic, environmental or pharmacological treatments leads to developmental phenotypes that can be epigenetically passed onto progeny. Injection of amyloids isolated from different phenotypic backgrounds into naive animals recapitulates the associated phenotype in offspring. Genetic and proteomic analyses reveal that the 26S proteasome and its conserved regulators maintain heritable amyloids across generations, which enables proper germ cell sex differentiation. We propose that inheritance of a proteinaceous epigenetic memory coordinates developmental timing and patterning with the environment to confer adaptive fitness.

Characterizing the capability frontier: Key attributes determining the development of capabilities

AbstractSystem Dynamics research on capability traps, where organizations remain in low capability and performance equilibrium because of poor resource allocation, spans over two decades and various industries, including agriculture, industry, and humanitarian aid. However, there is a gap in understanding how specific capability attributes affect resource allocation decisions. This study advances the capability trap literature by developing a theoretical model analyzing how key capability attributes—development time, erosion time, and productivity—impact organizational performance and managers' decisions. We introduce the concept of a “capability region”, an attractive area for capability investments, delineated by a “capability frontier” determined by threshold values of these three attributes. This model helps managers understand the factors driving capability development and supports better decision‐making, especially in sustainable practices. By identifying where sustainability‐related capability investments are likely to succeed, this research offers practical guidance for organizations to escape or avoid capability traps, promoting sustainable growth and adaptation.

The Effect of Soil Type and Moisture on the Development of Forensically Important Megaselia scalaris and Dohrniphora cornuta (Diptera: Phoridae).

Necrophagous phorid flies are common insects found on buried corpses, and their developmental data play a crucial role in estimating the post-burial interval (PBI). This study aimed to investigate the effects of soil type and moisture content on some life cycle parameters of two forensically important insects, Megaselia scalaris (Loew, 1866) and Dohrniphora cornuta (Bigot, 1857) (Diptera: Phoridae). Larval and pupal survival, development time, and larval body length of M. scalaris and D. cornuta were observed in three different soil types (loamy sand, sandy loam A, and sandy loam B) with six moisture contents (0%, 20%, 40%, 60%, 80%, and 100%). The results indicated that soil types, soil moisture, and their interaction significantly influenced the growth and development of both species, with moisture being the most influential factor. In each soil, 20% and 40% moisture contents were more suitable for their growth and development. Both the development time and maximum larval body length were significantly different among soil types and moisture contents. The larval period of both species lasted the longest in all soils with 0% moisture content. Additionally, a regression analysis of the relationship between larval body length and development time was performed at different moisture contents in three soils. This study expanded our knowledge of the factors that influence the development of necrophagous insects and provided some reference data for applications of M. scalaris and D. cornuta in PBI estimation.

A Sex-Specific Trade-Off Between Pesticide Resistance and Tolerance to Heat-Induced Sterility in Tetranychus urticae.

Current pest management relies extensively on pesticide application worldwide, despite the frequent rise of pesticide resistance in crop pests. This is particularly worrisome because resistance is often not costly enough to be lost in populations after pesticide application, resulting in increased dependency on pesticide application. As climate warming increases, effort should be put into understanding how heat tolerance will affect the persistence of pesticide resistance in populations. To address this, we measured heat tolerance in two populations of the spider mite crop pest Tetranychus urticae that differ in the presence or absence of a target-site mutation conferring resistance to etoxazole pesticide. We found that developmental time and fertility, but not survival, were negatively affected by increasing temperatures in the susceptible population. Furthermore, we found no difference between resistant and susceptible populations in all life-history traits when both sexes developed at control temperature, nor when females developed at high temperature. Resistant heat-stressed males, in contrast, showed lower fertility than susceptible ones, indicating a sex-specific trade-off between heat tolerance and pesticide resistance. This suggests that global warming could lead to reduced pesticide resistance in natural populations. However, resistant females, being as affected by high temperature as susceptible individuals, may buffer the toll in resistant male fertility, and the shorter developmental time at high temperatures may accelerate adaptation to temperature, the pesticide or the cost thereof. Ultimately, the complex dynamic between these two factors will determine whether resistant populations can persist under climate warming.

Generic Enrichment Method for Liquid Chromatography-Multiple Reaction Monitoring-Mass Spectrometry Assay for Quantitative Measurement of Biological Therapeutics in Serum.

The study aims to leverage the capabilities of Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry (LC-MRM), a key technique in quantifying therapeutic proteins in pharmacokinetic studies. The focus is on demonstrating an enrichment method using ProteoMiner beads, which can be integrated with LC-MRM to detect low-abundance biotherapeutics in serum, such as monoclonal antibodies and gene therapy products. The ProteoMiner enrichment method was employed and integrated with LC-MRM. The lower limit of quantification of serum drug substance concentrations was compared with that achievable with immuno-enrichment. The method used commercially available reagents, eliminating the need for assay-specific antibodies and reducing potential bias and development time. The ProteoMiner enrichment method showed comparable performance to immuno-enrichment, meeting traditional assay requirements in terms of precision, accuracy, and specificity. The ProteoMiner enrichment method, when combined with LC-MRM, offers a reliable and efficient alternative to immuno-enrichment for detecting and quantifying low-abundance biotherapeutics in serum. This approach, which uses commercially available reagents, can eliminate the bias and time associated with the development of assay-specific antibodies. It holds significant potential for accelerating pharmacokinetic analysis in both early and late stages of pharmaceutical development.

1551P Breakthrough therapy cancer drugs and indications with FDA approval: Development time, innovation, trials, clinical benefit, epidemiology, and price

1551P Breakthrough therapy cancer drugs and indications with FDA approval: Development time, innovation, trials, clinical benefit, epidemiology, and price

ParaCPI: A Parallel Graph Convolutional Network for Compound-Protein Interaction Prediction.

Identifying compound-protein interactions (CPIs) is critical in drug discovery, as accurate prediction of CPIs can remarkably reduce the time and cost of new drug development. The rapid growth of existing biological knowledge has opened up possibilities for leveraging known biological knowledge to predict unknown CPIs. However, existing CPI prediction models still fall short of meeting the needs of practical drug discovery applications. A novel parallel graph convolutional network model for CPI prediction (ParaCPI) is proposed in this study. This model constructs feature representation of compounds using a unique approach to predict unknown CPIs from known CPI data more effectively. Experiments are conducted on five public datasets, and the results are compared with current state-of-the-art (SOTA) models under three different experimental settings to evaluate the model's performance. In the three cold-start settings, ParaCPI achieves an average performance gain of 26.75%, 23.84%, and 14.68% in terms of area under the curve compared with the other SOTA models. In addition, the results of the experiments in the case study show ParaCPI's superior ability to predict unknown CPIs based on known data, with higher accuracy and stronger generalization compared with the SOTA models. Researchers can leverage ParaCPI to accelerate the drug discovery process.

HODNOTENIE POROZUMENIA KONCEPTU FUNKCIE, JEJ ROZNYM REPREZENTACIAM A PREPOJENIAM MEDZI NIMI

In these times of change and constant development, it is important that pedagogical approaches reflect modern trends and the needs of students. In mathematics, the notion of function is one of the key concepts. Despite the fact that the concept of function starts to be built in primary school, even in secondary school many students show gaps in their understanding of the concept of function, its different representations and the links between them. Our research focuses on the application of inquiry-based teaching (IBT) in the learning of the concept and properties of functions. This paper describes the initial stage of research based on a design-based research strategy oriented towards the design and development of methodological materials for teaching functions. The second part of the paper consists of the evaluation of a test designed to assess the development of functional thinking of primary school students.

The indispensable role of time in autonomous development

Advances in single-cell analysis have led to a picture of development largely in agreement with Waddington’s eponymous epigenetic landscape, in which a cell’s fate is determined by its basin of attraction in a high-dimensional gene-expression space. Yet conceptual gaps remain as to how a single progenitor can simultaneously generate multiple endpoints, and why time should be required of the process at all. We propose a theoretical model based on the Hamiltonian mechanics of n-dimensional rotational motion, which resolves these paradoxes. We derive the result that systems which become different from themselves over time must initially move in a direction not towards their ultimate endpoints, and propose that this process of resolving ambiguity can be quantified (in an information-theoretic sense) by the volume subtended in gene-expression space by the trajectories taken by the system towards its endpoints. We discuss the implications of this theory for the analysis of single-cell gene-expression data in studies of development.

Artificial Intelligence Supporting Early Automotive Engineering Processes

Abstract Due to progressive increase of complexity, the automotive industry is subject to constantly changing trends varying from the introduction of greener products and components to the deployment of technological advances in development and engineering processes. In relation to both, sustainable automotive products as well as the deployment of technological advances, the integration of AI (Artificial Intelligence) approaches in combination with virtual products in automotive development and engineering processes is of great importance. In combination with knowledge-based CAx (Computer-Aided engineering), the integration of AI approaches delivers an enormous potential to enhance automotive development processes. In addition to process optimizations, the integration of various AI approaches considers sustainability (e.g., optimization of component geometries and materials, reduction of emissions over the entire life cycle, CO2 reduction through improved development) and economical aspects (e.g., resources savings throughout the entire development process, time and cost savings through earlier error detection, avoidance of unnecessary process steps). The present approach deals with the integration of AI and knowledge-based engineering methods in the early phases of automotive development and engineering processes. Furthermore, the paper points to the time, cost and resources reduction potential, leading to earlier market entries and a greener industry. Finally, the paper demonstrates the integration of AI technologies into industrial development and engineering processes based on selected application scenarios.

Efficacy of Mucosamin Spray as an Adjunct for Prevention of Oral Mucositis in Children under Chemotherapy: A Two-Center Randomized Clinical Trial.

Chemotherapy-induced mucositis is the most common complication during cancer treatment. This complication can lead to pain, increased risk of infection and malnutrition. Therefore, it is important to find a solution to reduce the severity and duration of side effects. This study aimed to assess the efficacy of Mucosamin spray as an adjunct for prevention of oral mucositis in children under chemotherapy. This parallel-design clinical trial evaluated 48 patients aged 5 to 15 years with leukemia and lymphoma presenting to the Hematology Department of Mofid and Mahak Hospitals. The patients were randomly divided into two groups (n=24). Before starting chemotherapy, all patients received oral hygiene instructions (toothbrushing without flossing). Patients in both groups were requested to use a mouthwash composed of nystatin, aluminum-magnesium hydroxide suspension (aluminum MgS), and diphenhydramine for 1 min every morning on a daily basis starting the day before treatment. Patients in the intervention group were also requested to spray their entire oral mucosa with Mucosamin spray 3 times a day in addition to using the mouthwash. Patients were requested to refrain from eating and drinking for 1h after spraying. The patients were clinically examined by a senior dental student once every other day for 20 days regarding the occurrence, severity, and duration of oral mucositis. Data were analyzed using the Chi-square and Mann-Whitney tests, Kaplan-Meier survival analysis, and log rank test. No significant difference was noted between the two groups in the incidence, severity, or time of development of mucositis (p> 0.05). The 7-day non-recovery percentage was 72.7% (SE= 13.4) and 25.0% (SE= 15.3) in the control and test groups, respectively, indicating shorter duration (faster healing) of mucositis in the intervention group (p= 0.01). Within the limitations of this study, it seems that prophylactic application of Mucosamin spray can shorten the course of oral mucositis, in case of its occurrence.

Assessment of rural sustainable development and analysis and prediction of obstacles and coupled coordinated development: A case study of Zaozhuang City

In China, the Innovation Demonstration Zone for the National Sustainable Development Agenda is a key initiative for executing the United Nations (UN) 2030 Agenda for Sustainable Development. The Zone also plays critical roles in addressing the developmental bottlenecks that China faces and sharing Chinese insights into global sustainable development efforts. On July 15, 2022, the State Council endorsed the Zone’s establishment in Zaozhuang City, Shandong Province, where it focuses on innovation-led sustainable development in rural areas. Research into the levels, impediments, interdependencies, and evolutionary trends of rural sustainable development is crucial. Therefore, this research aimed to assist in comprehensively assessing developmental challenges and facilitating the harmonious advancement of social, economic, and environmental aspects in rural areas. In pursuit of the three fundamental dimensions of the UN’s Sustainable Development Goals (SDGs), namely development’s drivers, quality, and equity, this study was grounded in China’s national Rural Revitalization Strategy and the demands of sustainable development strategies. It also aligns with the UN 2030 Agenda for Sustainable Development and the associated SDG indicators. Focusing on four key areas, namely production elements, natural elements, social elements, and rural governance, this study developed an evaluation index system for assessing the level of rural sustainable development. It employed a range of analytical models, including the game theory-based combination empowerment method, barrier degree model, coupling degree model, coupling coordination degree model, and gray prediction GM(1,1) model, to analyze the status and evolving trends of rural sustainable development in Zaozhuang City from 2015 to 2022. The key findings were as follows: ① Relative to the baseline year 2015, the sustainable development level in Zaozhuang’s rural areas has shifted toward an improved state overall. ② The primary barrier to achieving rural sustainable development in Zaozhuang is the city’s rural governance system. ③ While the components of rural sustainable development in Zaozhuang are in the early stages of both basic and moderate coordination, an overall enhancement has occurred in their integrative coordination. ④ Between 2023 and 2025, the level of integrative coordination in Zaozhuang is expected to rise steadily. However, reaching a state of advanced coordination will require additional time for development.

Development and functional testing of battery management system algorithm for an electric bicycle using hardware in the loop testbench

An embedded Battery Management System (BMS) ensures the effective functionality and longevity of the vehicle battery systems. Testing the BMS using the Hardware in Loop (HIL) approach effectively increases safety and reduces product development time in the manufacturing sector. This research aims to develop an efficient battery management system with two-level protection for electric bicycles and test its functionality in the HIL configuration. The bicycle traction model and battery management system were first developed using a model-based design. Further, the model is tested and validated using battery emulators in the HIL methodology. The battery management system receives input data, such as current, voltage, and temperature, and monitors these parameters. The first level of protection involves the vehicle user receiving the warning when the monitoring parameters values exceed the given first safety threshold. As per the second safety threshold values, the BMS trips off the charging or discharging process when the voltage is 51V, the charge current is 5A, the discharge current is -5A and the IC temperature is 80 degrees. Also, BMS balances the cells in 3.84 min using passive balancing. Additionally, the BMS delivers a controlled current of 2.5A for safe battery charging. This methodology increases safety by reducing the potential risks of testing the BMS algorithms in the actual electric bicycle.

Experimental study on multi-point ignition of NH3/air by high-frequency nanosecond dielectric barrier discharge

Non-equilibrium plasma ignition technology, with its ability to expand ignition limits and increase ignition volume, is considered an important development direction of advanced ignition systems, and has significant advantages in improving ignition stability and combustion rate. This study investigates the ignition and combustion assistance effect of high-frequency nanosecond surface dielectric barrier discharge (nSDBD) on NH3/air mixture in a constant volume combustion chamber (CVCC). The study reveals the influence of high-frequency nSDBD on the growth process of the flame kernel in NH3/air mixture. As the discharge pulse number (PN) increases, the flame kernel develops from the middle position of the discharge filament to the head of the discharge filament, while there is no obvious flame at the root and middle of the discharge filament. Continuous discharge causes the flame kernel to appear concave and the center of the flame kernel to shift towards the wall of the CVCC. In the NH3/air mixture, the initial flame kernels exhibit dissipation phenomenon, resulting in a discrepancy between the number of initial flame kernels and the number of stable combustion flame kernels. As the discharge frequency or pulse number increases, and the number of stable combustion flame kernel increases. The adjustment of discharge frequency and pulse number can effectively control the flame development time (FDT) and flame rise time (FRT) of NH3/air mixture. As PN increases, both FDT and FRT are shortened. When discharge frequency is 20 kHz, the maximum shortening of FDT and FRT are 30 ms and 14 ms, respectively, about 55 % and 30 %. The effects of discharge frequency on FDT and FRT exhibit a non-monotonic variation pattern, and it is necessary to comprehensively consider various discharge parameters to achieve the best ignition effect. The ignition success rate curve of high-frequency nSDBD in NH3/air mixture is steep. The study results of this paper provide new discoveries and experimental data for advanced ignition systems.

The effect of larval exposure to acids and detergents on the life history of the major malaria vector Anopheles arabiensis Patton (Diptera: Culicidae).

Anopheles arabiensis, a highly adaptable member of the Anopheles gambiae complex, poses a challenge for control efforts due to its outdoor biting and resting behaviour. Consequently, indoor insecticide-based control methodsare ineffective against An. arabiensis. Furthermore, An. arabiensis are adapting to breeding in polluted waters, and may be contributing to residual malaria and malaria in urban areas. There have been some advances in understanding the effect of rural pollutants on Anopheles mosquitoes, but the effect of urban pollutants is poorly understood. Thus, in this study, the effect of acidic pollutants [nitric acid (HNO3) and hydrochloric acid (HCl)] and alkaline pollutants (phosphate-free and phosphate-containing detergent) on two laboratory-reared An. arabiensis strains - an insecticide susceptible strain (SENN) and an insecticide-resistant strain selected from SENN (SENN-DDT) - were determined. The median lethal concentration (LC50) and larval exposure on larval development, adult longevity and insecticide tolerance were evaluated. Nitric acid and phosphate-containing detergent were found to be more toxic than HCl and phosphate-free detergent in terms of LC50 values. Detergent exposure (both phosphate-containing and phosphate-free) increased adult longevity of both strains. Nitric acid reduced larval development time in both SENN and SENN-DDT, whereas HCl reduced larval development time in SENN only. By contrast, both phosphate-containing and phosphate-free detergents increased larval development time of both strains. Furthermore, HNO3 and phosphate-containing detergent increased insecticide tolerance the most. The two An. arabiensis strains responded to urban pollutants differently. Thus, this study provides insight into the adaptation of An. arabiensis to acidic and alkaline urban pollutants. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Enhancing Biological Control Efficacy: Insights into the Feeding Behavior and Fitness of the Omnivorous Pest Lygus lineolaris.

Lygus lineolaris (Palisot de Beauvois) (Hemiptera: Miridae), a true omnivorous insect, poses a significant threat to agriculture in the Neartic region. Understanding the feeding behavior of L. lineolaris is crucial for developing integrated pest management strategies. This study aimed to evaluate the effects of different diets on the fitness of L. lineolaris, with a focus on the diet source, feeding regime (phytophagy, zoophagy, and phytozoophagy), and number of diet items. The experimental design in the laboratory investigated the impacts of strawberry, canola and buckwheat flowers, as well as spider mites and aphids to explore relationships found in a conventional strawberry field. Results reveal that diet source, feeding regime, and the number of diet items influence L. lineolaris performance (i.e., survivorship rate, developmental time, and adult weight and length). Improvements in fitness are indicated by higher nymphal survival, shorter developmental time, and larger adults. Immature stages of L. lineolaris show improved fitness when provided with diets rich in canola compared to strawberry flowers and spider mites. Furthermore, the inclusion of multiple diet items in phytozoophagous regimes enhances insect performance. The findings emphasize the significance of understanding L. lineolaris' nutritional requirements and the biodiversity of target ecosystems for modeling energy flows and designing effective IPM strategies against this pest. This research contributes to the knowledge base for biological control programs targeting L. lineolaris in agricultural systems.

The Impact of Artificial Intelligence Virtual Oral Tutoring APPs on Chinese Youth’s Anxiety in Oral English learning——Interview Research Based on Users of Artificial Intelligence Speaking Tutoring APPs

Foreign language learning anxiety is a long-standing topic that people use to guide foreign language teaching and the setting of foreign language education scenarios by studying the anxiety emotions that exist in foreign language learning. However, in today’s era of artificial intelligence (AI), with the release of ChatGPT, large language model AI technology is widely used. In such a new context, various AI virtual foreign language oral coaches have emerged. Due to the short development time of the large language model technology, the foreign language training model built on this technology is still in the initial stage of development, and the research on this field is very limited. The research on the improvement of foreign language learning emotions brought by GAI is even rarer. The foreign language learning method provided by the AI coach. What help does it have for foreign language learning? Does it alleviate foreign language learning anxiety? It has become a blank in foreign language learning emotion research. This study used semi-structured interviews with 10 Chinese young people between the ages of 20 and 40. Using the method of thematic analysis, the data of this interview were recorded and analyzed, and the conclusions reached were explained from the control value theory, and it was found that AI robots can alleviate many aspects of anxiety in foreign language oral learning, such as: communicative anxiety, situational anxiety, oral anxiety, hearing anxiety, and cognitive anxiety. It is very friendly to socially phobic people, providing emotional companionship and cognitive support for students who are lonely and helpless in foreign language oral communication, although the effect of foreign language improvement is different for different students, but it has an obvious effect on alleviating anxiety when learning foreign languages, and it is unexpectedly found that the AI robot foreign language coach also has the role of emotional companionship for learners, in addition to helping to alleviate anxiety, it can also provide positive emotional value through care, companionship, communication, etc. The findings of this paper are helpful to understand the help of AI technology on foreign language learning emotions, and to provide support for subsequent research on AI accompanying foreign language learning.

Gynecomastia and Its Management In Boys With Partial Androgen Insensitivity Syndrome.

Partial androgen insensitivity syndrome (PAIS) is a rare condition that is reported to be commonly associated with gynecomastia in males. To assess the management of gynecomastia in male PAIS. Retrospective review of males with PAIS over the age of 10 years in the I-DSD registry. Of the 205 eligible cases, information was available for 57 from 13 centers. An androgen receptor gene variant was confirmed in 45 (79%) with a median age at first presentation of 1.0 year (range 0.1, 26.0). Of the 45 genetically confirmed cases, gynecomastia was present in 41 (91%) with a median age at the time of gynecomastia development of 13.5 years (11.0, 29.0). In the other 4 (9%) with no gynecomastia, the median age at last assessment was 15.7 years (10.6, 17.0). In 30 cases with information available, micropenis was present at the time of gynecomastia development in 23 (77%). Of the 35 with information available, 2 (6%) exhibited spontaneous resolution between the ages of 15 and 21 years and 25 (71%) had breast surgery at a median age of 15.7 years (14.0, 23.0). Of these 25, 9 (26%) had previously received medical therapy. The median clinician score of effectiveness for medical therapy was 3 (1, 8) compared to 10 (3, 10) for surgery (P < .0001). In 31 with information available, 13 (42%) had received psychology support. Gynecomastia is common in PAIS but not universal. Surgical management may be more effective than medical therapy, but there is a need for further standardized and systematic studies.

MFF-DTA: Multi-scale feature fusion for drug-target affinity prediction

Accurately predicting drug-target affinity is crucial in expediting the discovery and development of new drugs, which is a complex and risky process. Identifying these interactions not only aids in screening potential compounds but also guides further optimization. To address this, we propose a multi-perspective feature fusion model, MFF-DTA, which integrates chemical structure, biological sequence, and other data to comprehensively capture drug-target affinity features. The MFF-DTA model incorporates multiple feature learning components, each of which is capable of extracting drug molecular features and protein target information, respectively. These components are able to obtain key information from both global and local perspectives. Then, these features from different perspectives are efficiently combined using specific splicing strategies to create a comprehensive representation. Finally, the model uses the fused features to predict drug-target affinity. Comparative experiments show that MFF-DTA performs optimally on the Davis and KIBA data sets. Ablation experiments demonstrate that removing specific components results in the loss of unique information, thus confirming the effectiveness of the MFF-DTA design. Improvements in DTA prediction methods will decrease costs and time in drug development, enhancing industry efficiency and ultimately benefiting patients.

Endocranial development in non-avian dinosaurs reveals an ontogenetic brain trajectory distinct from extant archosaurs

Modern birds possess highly encephalized brains that evolved from non-avian dinosaurs. Evolutionary shifts in developmental timing, namely juvenilization of adult phenotypes, have been proposed as a driver of head evolution along the dinosaur-bird transition, including brain morphology. Testing this hypothesis requires a sufficient developmental sampling of brain morphology in non-avian dinosaurs. In this study, we harness brain endocasts of a postnatal growth series of the ornithischian dinosaur Psittacosaurus and several other immature and mature non-avian dinosaurs to investigate how evolutionary changes to brain development are implicated in the origin of the avian brain. Using three-dimensional characterization of neuroanatomical shape across archosaurian reptiles, we demonstrate that (i) the brain of non-avian dinosaurs underwent a distinct developmental trajectory compared to alligators and crown birds; (ii) ornithischian and non-avialan theropod dinosaurs shared a similar developmental trajectory, suggesting that their derived trajectory evolved in their common ancestor; and (iii) the evolutionary shift in developmental trajectories is partly consistent with paedomorphosis underlying overall brain shape evolution along the dinosaur-bird transition; however, the heterochronic signal is not uniform across time and neuroanatomical region suggesting a highly mosaic acquisition of the avian brain form.