Insects exhibit a vast array of morphological specializations. Recent eco-evo-devo studies have provided a fresh perspective into how insect morphology can respond to the environment, both plastically and adaptively. Here, we performed a systematic literature analysis to identify biases and gaps in research on the molecular mechanisms underlying insect morphological adaptation and plasticity. We found that plasticity studies are increasingly present in the literature, while adaptation studies lag behind. Additionally, we observed a disproportionate focus on a few insect orders and specific traits like wings and body size. We highlight the need to explore the broader insect diversity, including understudied groups and unexplored traits like reproductive organs, as well as utilize advanced methods to capture subtle morphological variation. Studying a wider range of species with diverse morphologies and ecological features, as well as implementing modern genome-wide tools, can reveal the full spectrum of mechanisms underlying morphological adaptation and plasticity in insects.

The recently developed ALBI-Sarcopenia score has demonstrated effectiveness in predicting mortality in hepatocellular carcinoma (HCC), emerging as a crucial factor in guiding treatment decisions. To assess the utility of the ALBI-Sarcopenia score in predicting the success of HCC treatment. A prospective study involving 262 liver cirrhosis with HCC patients were assigned to various treatment strategies according to Barcelona clinics of liver disease (BCLC) classification. Patients were followed up for 12 months reporting laboratory data, sarcopenia, ALBI-Sarcopenia score, and outcomes. Sarcopenia was prevalent in 43.1% (48.35% males and 31.25% females, P = 0.042). Most patients were HCV-positive (88.9%) and classified as CTP A (55.7%) or BCLC B (54.2%). Over the study period, TACE was the most administered treatment (41.2% at baseline), followed by a progressive shift toward best supportive care as disease severity increased. Complete response rates declined from 31.7% at 1 month to 21.4% at 12 months, while progressive disease rates increased from 21.8 to 37.8% over the same period. At 12 months, the ALBI-Sarcopenia score demonstrated the highest predictive accuracy for treatment response (AUC:0.69, p = 0.001), outperforming both the ALBI (AUC: 0.631, p = 0.001) and MELD (AUC:0.623, p = 0.003) scores. Logistic regression identified ALBI-Sarcopenia as a significant independent predictor of response at 1 month (OR:1.25, 95% CI:0.881-1.971, p = 0.002) and 12 months (OR:2.189, 95% CI:0.992-4.937, p = 0.001). The ALBI-Sarcopenia score is a robust predictor of treatment outcomes in HCC, offering superior prognostic accuracy compared to traditional scoring systems, and enhancing patient stratification for optimized treatment planning.

Epigenetic mechanisms are mediators of interactions between aging, genetics, and environmental factors in sporadic Parkinson's disease (PD). Multiple studies have explored the DNA modifications in PD, but few focus on 5-hydroxymethylcytosine (5-hmC), which is important in the central nervous system and sensitive to environmental exposures. To date, studies have not differentiated between 5-methylcytosine (5-mC) and 5-hmC or have analyzed them separately. In this study, we modeled paired 5-mC and 5-hmC data simultaneously. We identified 108 cytosines with significant PD-associated shifts between these marks in an enriched neuronal population from PD postmortem parietal cortex, within 83 genes and 34 enhancers associated with 67 genes. These data potentially link epigenetic regulation of genes related to LRRK2 and endolysosomal sort (RAB32 and AGAP1), and genes involved in neuroinflammation, the inflammasome, and neurodevelopment with early changes in PD and suggest that there are significant shifts between 5mC and 5hmC associated with PD in genes not captured by standard methods.

Glial cells are key players in the regulation of nervous system functioning in both the central and enteric nervous systems. Glial cells are dynamic and respond to environmental cues to modulate their activity. Increasing evidence suggests that these signals include those originating from the gut microbiota, the community of microorganisms, including bacteria, viruses, archaea, and protozoa, that inhabit the gut. The gut microbiota and the brain communicate in a bidirectional manner across multiple signaling pathways and interfaces that together comprise the microbiota-gut-brain axis. Here, we detail the role of glial cells, including astrocytes, microglia, and oligodendrocytes in the central nervous system, and glial cells in the enteric nervous system along this gut-brain axis. We review what is known regarding the modulation of glia by microbial signals, in particular by microbial metabolites which signal to the brain through systemic circulation and via the vagus nerve. In addition, we highlight what is yet to be discovered regarding the role of other gut microbiota signaling pathways in glial cell modulation and the challenges of research in this area.

Studies have investigated the role of different parenting intervention programs in the early development of children. Here we aimed to determine the long-term efficacy of Care for Child Development (CCD) guideline interventions on behavioral dimensions of children's development.

This randomized clinical trial took place at an outpatient public Pediatrics clinic in Isfahan, Iran from February 2020 to May 2024. Pregnant women between the ages of 18 and 45 in their third trimester were included in the study, and their children were followed for 48 months. The intervention group participated in 5 educational group sessions, each session lasting approximately 45 min. The control group underwent routine education on childcare, as suggested by WHO. The main outcome was the children's socio-emotional behavior problems using the Children Behavior Checklist (CBCL) at 18, 36, and 48 months. The comparisons between groups were done using independent two-sample t-tests, or the Mann-Whitney test and the Chi-square test. Statistical software SPSS 22 was utilized for data analysis.

Finally, the data of 166 participants (70 in the intervention group and 96 in the control group) were included in the current study. The adjusted mean differences between the intervention and control groups significantly differed in some scales after follow-up. After 36 months of follow-up, the scores in the following aspects were significantly lower in the intervention group: emotional problems, anxiety, seclusion problems, sleep disorders, aggressive behavior, and the total problem. After 48 months, only sleep problems were significantly lower in the intervention group.

According to the results of this intervention, delivering parenting interventions through group sessions according to the CCD recommendation indicated weak efficacy during long-term follow-ups. Further trials are needed to assess the effects of these programs on parents.

IRCT20190128042533N2, Date of Registration: 16 January 2020, www.irct.ir .

Maternal education was strongly correlated with adolescent brain morphology, cognitive performances, and mental health. However, the molecular basis for the effects of maternal education on the structural neurodevelopment remains unknown. Here, we conducted gene-environment-wide interaction study using the Adolescent Brain Cognitive Development cohort. Seven genomic loci with significant gene-environment interactions (G×E) on regional gray matter volumes were identified, with enriched biological functions related to metabolic process, inflammatory process, and synaptic plasticity. Additionally, genetic overlapping results with behavioral and disease-related phenotypes indicated shared biological mechanism between maternal education modified neurodevelopment and related behavioral traits. Finally, by decomposing the multidimensional components of maternal education, we found that socioeconomic status, rather than family environment, played a more important role in modifying the genetic effects on neurodevelopment. In summary, our study provided analytical evidence for G×E effects regarding adolescent neurodevelopment and explored potential biological mechanisms as well as social mechanisms through which maternal education could modify the genetic effects on regional brain development.

The propensity of humans and non-human animals to discount future returns for short-term benefits is well established. This contrasts with the ability of organisms to unfold complex developmental sequences over months or years efficiently. Research has focused on various descriptive and predictive parameters of 'temporal discounting' in behavior, and researchers have proposed models to explain temporal preference in terms of fitness-maximizing outcomes. Still, the underlying ultimate cause of this phenomenon has not been deeply explored across taxa. Here, we propose an ultimate (i.e., evolutionary) causal explanation for the selection of temporal discounting largely conserved across taxa. We propose that preference for a short-term reward (e.g., heightened impulsivity) often is less than optimal and likely is the product of constraints imposed on natural selection with respect to predicting events in a temporal framework in the context of future uncertainty. Using a simple Newtonian model for time across a fitness landscape in which movement by organisms is only possible in one direction, we examine several factors that influence the ability of an organism to choose a distant reward over a more temporally proximate reward: including the temporal distance of the far reward, the relative value of the distant reward, and the effect of uncertainty about the value and presence of the distant reward. Our results indicate that an organism may choose a more distant reward, but only if it is not too far into the future and has a substantially higher-value fitness payoff relative to the short-term reward. Notably, any uncertainty about the distant reward made it extremely unlikely for an organism to choose the delayed reward strategy compared to choosing a closer reward, even if the distant reward had a much higher payoff because events that are uncertain are only partially visible to natural selection pressures. The results help explain why natural selection is constrained to promote more optimal behavioral strategies and why it has difficulty selecting a distant reward over a lower-value short-term reward. The degree of uncertainty is an especially salient ecological variable in promoting and preferencing short-term behavioral strategies across taxa. These results further help illustrate why, from an ultimate causal perspective, human and non-human taxa have difficulty making more optimal long-term decisions.

Africa, a continent considered to be the cradle of human beings has the largest genetic diversity among its population than other continents. This review discusses the implications of this high African genetic diversity to the development of personalized and precision medicine.

A comprehensive search across PubMed, Google Scholar, Science Direct, DOAJ, AJOL, and the Cochrane Library electronic databases and manual Google searches was conducted using key terms "genetics", "genetic diversity", "Africa", "precision medicine", and "personalized medicine". Updated original and review studies focusing on the implications of African high genetic diversity on personalized and precision medicine were included. Included studies were thematically synthesized to elucidate their positive or negative implications for personalized healthcare, aiming to foster informed clinical practice and scientific inquiry.

African populations' high genetic diversity presents opportunities for personalized and precision medicine including improving pharmacogenomics, understanding gene interactions, discovering new variants, mapping disease genes, creating updated genomic reference panels, and validating biomarkers. However, challenges include underrepresentation in studies, scarcity of reference genomes, inaccuracy of genetic testing and interpretation, and ancestry misclassification. Addressing these requires the establishment of genomic research centers, increasing funding, creating biobanks and repositories, education, infrastructure, and international cooperation to enhance healthcare equity and outcomes through personalized and precision medicine.

High African genetic diversity presents both positive and negative implications for personalized and precision medicine. Deep further research is recommended to harness the challenges and use the opportunities to develop customized treatments.

In this study, we aimed to explore the interaction mechanism between bovine serum albumin (BSA) and a Schiff base compound derived from 2,4-dinotrophenyl hydrazine (L) using various spectroscopic techniques. The interaction between BSA and synthesizing molecule can provide insights into binding affinity, conformational changes and potential applications in drug delivery or biochemistry. The interaction between BSA and L was studied by using UV-Vis and fluorescence titration analysis. The fluorescence quenching emission was observed at 343 nm, upon addition of L to the buffer solution of BSA. The binding between BSA and ligand is static in nature using fluorescence quenching emission. The thermodynamic parameters were calculated from the temperature-dependent binding constants (i.e., ∆H = -0.318 kcal/mol, ∆G = -7.857 kcal/mol and ∆S = 0.023 kcal/mol), which indicated that the protein-ligand complex formation between L and BSA is mainly due to the electrostatic interactions. The experimental and theoretical results showed excellent agreement with respect to the mechanism of binding and binding constants. The molecular docking and molecular dynamic analysis experiments were performed to establish the interaction between protein and ligand.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by heterogeneous symptoms and genetic underpinnings. Recent advancements in genetic and epigenetic research have provided insights into the intricate mechanisms contributing to ASD, influencing both diagnosis and therapeutic strategies.

To explore the genetic architecture of ASD, elucidate mechanistic insights into genetic mutations, and examine gene-environment interactions.

A comprehensive systematic review was conducted, integrating findings from studies on genetic variations, epigenetic mechanisms (such as DNA methylation and histone modifications), and emerging technologies [including Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9 and single-cell RNA sequencing]. Relevant articles were identified through systematic searches of databases such as PubMed and Google Scholar.

Genetic studies have identified numerous risk genes and mutations associated with ASD, yet many cases remain unexplained by known factors, suggesting undiscovered genetic components. Mechanistic insights into how these genetic mutations impact neural development and brain connectivity are still evolving. Epigenetic modifications, particularly DNA methylation and non-coding RNAs, also play significant roles in ASD pathogenesis. Emerging technologies like CRISPR-Cas9 and advanced bioinformatics are advancing our understanding by enabling precise genetic editing and analysis of complex genomic data.

Continued research into the genetic and epigenetic underpinnings of ASD is crucial for developing personalized and effective treatments. Collaborative efforts integrating multidisciplinary expertise and international collaborations are essential to address the complexity of ASD and translate genetic discoveries into clinical practice. Addressing unresolved questions and ethical considerations surrounding genetic research will pave the way for improved diagnostic tools and targeted therapies, ultimately enhancing outcomes for individuals affected by ASD.

The majority of Parkinson's disease (PD) cases are due to a complex interaction between aging, genetics, and environmental factors; epigenetic mechanisms are thought to act as important mediators of these risk factors. While multiple studies to date have explored the role of DNA modifications in PD, few focus on 5-hydroxymethylcytosine (5hmC). Because 5hmC occurs at its highest levels in the brain and is thought to be particularly important in the central nervous system, particularly in the response to neurotoxicants, it is important to explore the potential role of 5hmC in PD. This study expands on our previously published epigenome-wide association study (EWAS) performed on DNA isolated from neuron-enriched nuclei from human postmortem parietal cortex from the Banner Sun Health Research Institute Brain Bank. The study aimed to identify paired changes in 5hmC and 5mC in PD in enriched neuronal nuclei isolated from PD post-mortem parietal cortex and age- and sex-matched controls. We performed oxidative bisulfite (oxBS) conversion and paired it with our previously published bisulfite (BS)-based EWAS on the same samples to identify cytosines with significant shifts between these two related epigenetic marks. Interaction differentially modified cytosines (iDMCs) were identified using our recently published mixed-effects model for co-analyzing βmC and βhmC data.

We identified 1,030 iDMCs with paired changes in 5mC and 5hmC (FDR < 0.05) that map to 695 genes, including PARK19 (DNAJC6), a familial PD gene, and PTPRN2 (IA-2), which has been previously implicated in PD in both epigenetic and mechanistic studies. The majority of iDMC-containing genes have not previously been implicated in PD and were not identified in our previous BS-based EWAS.

These data potentially link epigenetic regulation of the PARK19 and PTPRN2 loci in the pathogenesis of idiopathic PD. In addition, iDMC-containing genes have known functions in synaptic formation and function, cell cycle and senescence, neuroinflammation, and epigenetic regulation. These data suggest that there are significant shifts between 5mC and 5hmC associated with PD in genes relevant to PD pathogenesis that are not captured by analyzing BS-based data alone or by analyzing each mark as a distinct dataset.

Understanding the complex interplay of genetic and environmental factors in disease etiology and the role of gene-environment interactions (GEIs) across human development stages is important. We review the state of GEI research, including challenges in measuring environmental factors and advantages of GEI analysis in understanding disease mechanisms. We discuss the evolution of GEI studies from candidate gene-environment studies to genome-wide interaction studies (GWISs) and the role of multi-omics in mediating GEI effects. We review advancements in GEI analysis methods and the importance of large-scale datasets. We also address the translation of GEI findings into precision environmental health (PEH), showcasing real-world applications in healthcare and disease prevention. Additionally, we highlight societal considerations in GEI research, including environmental justice, the return of results to participants, and data privacy. Overall, we underscore the significance of GEI for disease prediction and prevention and advocate for integrating the exposome into PEH omics studies.

Integrated fetal, neonatal, and pediatric training constitute an interdisciplinary fetal-neonatal neurology (FNN) program. A dynamic neural exposome concept strengthens curriculum content. Trainees participate in mentoring committee selection for guidance during a proposed two-year program. Prenatal to postnatal clinical learning re-enforces early toxic stressor interplay that influences gene-environment interactions. Maternal-placental-fetal triad, neonatal, or childhood diseases require diagnostic and therapeutic decisions during the first 1,000 days when 80 % of neural connections contribute to life-course phenotypic expression. Pediatric follow-up through 3 years adjusts to gestational ages of preterm survivors. Cumulative reproductive, pregnancy, pediatric and adult exposome effects require educational experiences that emphasize a principle-to-practice approach to a brain capital strategy across the lifespan. More rigorous training during fetal, neonatal, and pediatric rotations will be offered to full time trainees. Adult neurology residents, medical students, and trainees from diverse disciplines will learn essential topics during time-limited rotations. Curriculum content will require periodic re-assessments using educational science standards that maintain competence while promoting creative and collaborative problem-solving. Continued career-long learning by FNN graduates will strengthen shared healthcare decisions by all stakeholders. Recognition of adaptive or maladaptive neuroplasticity mechanisms requires analytic skills that identify phenotypes associated with disease pathways. Developmental origins and life-course concepts emphasize brain health across the developmental-aging continuum, applicable to interdisciplinary research collaborations. Social determinants of health recognize diversity, equity, and inclusion priorities with each neurological intervention, particularly for those challenged with disparities. Diagnostic and therapeutic strategies must address resource challenges particularly throughout the Global South to effectively lower the worldwide burden of neurologic disease. Sustainable development goals proposed by the World Health Organization offer universally applicable guidelines in response to ongoing global and regional polycrises. Gender, race, ethnicity, and socio-economic equality promote effective preventive, rescue and reparative neuroprotective interventions. Global synergistic efforts can be enhanced by establishing leadership within academic teaching hubs in FNN training to assist with structure and guidance for smaller healthcare facilities in each community that will improve practice, education and research objectives. Reduced mortality with an improved quality of life must prioritize maternal-pediatric health and well-being to sustain brain health across each lifespan with transgenerational benefits.

To date, the treatable traits (TTs) approach has been applied in the context of managing diagnosed diseases. TTs are clinical characteristics and risk factors that can be identified clinically and/or biologically, and that merit treatment if present. There has been an exponential increase in the uptake of this approach by both researchers and clinicians. Realizing the potential of the TTs approach to pre-clinical disease, this expert review proposes that it is timely to consider acting on TTs present before a clinical diagnosis is made, which might help to prevent development of the full disease. Such an approach is ideal for diseases where there is a long pre-clinical phase, such as in chronic obstructive pulmonary disease (COPD). The term 'pre-COPD' has been recently proposed to identify patients with respiratory symptoms and/or structural or functional abnormalities without airflow limitation. They may eventually develop airflow limitation with time but patients with pre-COPD are likely to have traits that are already treatable. This review first outlines the contribution of recently generated knowledge into lifetime lung function trajectories and the conceptual framework of 'GETomics' to the field of pre-COPD. GETomics is a dynamic and cumulative model of interactions between genes and the environment throughout the lifetime that integrates information from multi-omics to understand aetiology and mechanisms of diseases. This review then discusses the current evidence on potential TTs in pre-COPD patients and makes recommendations for practice and future research. At a broader level, this review proposes that introducing the TTs in pre-COPD may help reenergize the preventive approaches to health and diseases.

Adolescence is a timed process with an onset, tempo, and duration. Nevertheless, the temporal dimension, especially the pace of maturation, remains an insufficiently studied aspect of developmental progression. The primary objective is to estimate the precise influence of pubertal maturational tempo on the configuration of associative brain regions. To this end, the connection between maturational stages and the level of hierarchical organization of large-scale brain networks in 12-13-year-old females is analyzed. Skeletal maturity is used as a proxy for pubertal progress. The degree of maturity is defined by the difference between bone age and chronological age. To assess the level of hierarchical organization in the brain, the temporal dynamic of closed eye resting state high-density electroencephalography (EEG) in the alpha frequency range is analyzed. Different levels of hierarchical order are captured by the measured asymmetry in the directionality of information flow between different regions. The calculated EEG-based entropy production of participant groups is then compared with accelerated, average, and decelerated maturity. Results indicate that an average maturational trajectory optimally aligns with cerebral hierarchical order, and both accelerated and decelerated timelines result in diminished cortical organization. This suggests that a "Goldilocks rule" of brain development is favoring a particular maturational tempo.

Through investigating the combined impact of the environmental exposures experienced by an individual throughout their lifetime, exposome research provides opportunities to understand and mitigate negative health outcomes. While current exposome research is driven by epidemiological studies that identify associations between exposures and effects, new frameworks integrating more substantial population-level metadata, including electronic health and administrative records, will shed further light on characterizing environmental exposure risks. Molecular biology offers methods and concepts to study the biological and health impacts of exposomes in experimental and computational systems. Of particular importance is the growing use of omics readouts in epidemiological and clinical studies. This paper calls for the adoption of mechanistic molecular biology approaches in exposome research as an essential step in understanding the genotype and exposure interactions underlying human phenotypes. A series of recommendations are presented to make the necessary and appropriate steps to move from exposure association to causation, with a huge potential to inform precision medicine and population health. This includes establishing hypothesis-driven laboratory testing within the exposome field, supported by appropriate methods to read across from model systems research to human.

Earlier pubertal timing is an important predictor of emotional and behavioral problems during adolescence. The current study undertook a comprehensive investigation of whether the social environment can buffer or amplify the associations between pubertal timing and emotional and behavioral problems.

Research questions were examined in the Adolescent Brain Cognitive Development (ABCD) Study, a large population representative sample in the United States. We examined interactions between pubertal timing and the shared effects of a range of proximal and distal social environmental influences (i.e., parents, peers, schools, neighborhoods, socioeconomic status) in 10- to 13-year-olds.

Results revealed significant interaction between timing and proximal social influences (i.e., the "microsystem") in predicting emotional and behavioral problems. In general, adolescents with earlier pubertal timing and unfavorable (high levels of negative and low levels of positive) influences in the microsystem exhibited greater problems. Both males and females exhibited such associations for rule-breaking problems, while females alone exhibited associations for depressive problems. Results also illustrate the relative strength of each social context at moderating risk for emotional and behavioral problems in earlier versus later pubertal maturers.

These findings highlight the importance of proximal social influences in buffering vulnerability for emotional and behavioral problems related to earlier puberty. Findings also illustrate the broad implications of latent environmental factors, reflecting common variance of multiple social influences that typically covary with one another.

Background Children with Special Health Care Needs (CSHCN) represent a diverse pediatric population requiring healthcare services beyond typical childhood needs. This study analyzes data from the 2016-2020 National Survey of Children's Health Database to elucidate demographic patterns, prevalence rates, and nuanced factors influencing the health and well-being of CSHCN. Methods This retrospective observational study focuses on children aged 0-17 who are identified as CSHCN based on Maternal and Child Health Bureau criteria. A comprehensive analysis of the National Survey of Children's Health (NSCH) database examines key variables, including health outcomes, healthcare utilization, parental-reported health status, and socio-demographic factors. Stratified random sampling ensures national representation. Results The study encompassed 40,335 patients, revealing that 14.6% (CI: 14.0-15.3, n=6,445) of CSHCN received care in a well-functioning system. Across age groups, 19.1% (CI: 14.0-15.3, n=6,445) of CSHCN aged 0-5 received ongoing treatment, contrasting with 5.7% (CI: 5.2-6.2, n=1,599) in the 12-17 years group. Males exhibited a prevalence of 15% (CI: 14.1-15.9, n=3,674), and females had 14.2% (CI: 13.2-15.2, n=2,771). Racial disparities were noted; non-Hispanic Native Hawaiian/Other Pacific Islander children had a 3% (CI: 1.1-8.1, n=6) prevalence. Across Federal Poverty Level categories, prevalence ranged from 12.5% (CI: 11.5-13.6, n=1,753) to 17.7% (CI: 16.6-18.9, n=2,856). Notably, 18.5% (CI: 17.4-19.7, n=3,515) of children without adverse experiences were CSHCN. Among CSHCN in two-parent currently married households, 15.9% (CI: 15.0-16.8, n=4,330) received treatment, while those in unmarried households had a prevalence of 12.9% (CI: 10.5-15.7, n=335). CSHCN with parents born in the United States showed a prevalence of 15.4% (CI: 14.7-16.1, n=5,257). Conclusion This study provides valuable insights into the prevalence and demographic patterns of CSHCN. Limitations include potential recall bias and the retrospective study design. Despite these constraints, the findings lay a foundation for future research and targeted interventions, fostering a deeper understanding of the evolving landscape of pediatric healthcare in the United States.

In this special communication, an overview of the research on trauma, resilience, and action items for the pediatric physical therapist (PT) is addressed. The experiences of early childhood, positive and negative, impact overall development and well-being throughout the lifespan. Childhood trauma can include exposure to abuse, neglect, violence, racism, or medical procedures. These adverse childhood experiences are associated with poor physical and mental health outcomes that can extend into adulthood and can appear in the pediatric rehabilitative realm as caregivers who become labeled noncompliant. Trauma is common and impacts all children; however, some populations, such as children with disabilities, have greater risk for experiencing adversity. An individual's trauma history is not always visible, necessitating a standard approach. Pediatric PTs must take an intentional approach to address the detrimental effects of trauma on those we serve. Many organizations recommend adopting trauma-informed care as the standard of care for all populations.

Atherosclerosis is the leading cause of death worldwide, and the predominant risk factors are advanced age and high-circulating low-density lipoprotein cholesterol (LDL-C). However, the findings of atherosclerosis in relatively young mummified remains and a lack of atherosclerosis in chimpanzees despite high LDL-C call into question the role of traditional cardiovascular risk factors. The inflammatory theory of atherosclerosis may explain the discrepancies between traditional risk factors and observed phenomena in current literature. Following the divergence from chimpanzees several millennia ago, loss of function mutations in immune regulatory genes and changes in gene expression have resulted in an overactive human immune system. The ubiquity of atherosclerosis in the modern era may reflect a selective pressure that enhanced the innate immune response at the cost of atherogenesis and other chronic disease states. Evidence provided from the fields of genetics, evolutionary biology, and paleoanthropology demonstrates a sort of circular dependency between inflammation, immune system functioning, and evolution at both a species and cellular level. More recently, the role of proinflammatory stimuli, somatic mutations, and the gene-environment effect appear to be underappreciated elements in the development and progression of atherosclerosis. Neurobiological stress, metabolic syndrome, and traditional cardiovascular risk factors may instead function as intermediary links between inflammation and atherosclerosis. Therefore, considering evolution as a mechanistic process and atherosclerosis as part of the inertia of evolution, greater insight into future preventative and therapeutic interventions for atherosclerosis can be gained by examining the past.

Candidate gene analysis approaches have shown that colorectal cancer (CRC) risk attributable to diet may differ according to genotype. A genome-wide approach further allows for the exploration of underlying pathways for associations between diet and CRC risk across the genome.

To identify genetic variants that modify diet-CRC associations and to further explore the underlying pathways in the cause of CRC.

This nested case-control study used data on White British participants from the prospective cohort UK Biobank. Participants were recruited between March 13, 2006, and October 1, 2010, and data were censored June 25, 2021.

The average frequency intake of 11 dietary factors in the year preceding baseline was obtained via a touchscreen questionnaire. After quality control for more than 93 million variants of imputed genetic data, 4 122 345 variants remained.

Colorectal cancer cases were identified according to the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. Genome-wide interaction analysis was performed to test interactions between dietary factors and variants using a conditional logistic regression model. Summary statistics of interactions at the variant level were used to calculate empirical P values for interactions at gene and gene-set levels in gene-based and gene-set enrichment analyses.

A total of 4686 participants with CRC (mean [SD] age, 60.7 [6.6] years; 2707 men [57.8%]) received a new diagnosis during a median of 12.4 years (IQR, 11.6-13.1 years) of follow-up. Once a case was detected, 3 matched controls were identified, for a total of 14 058 controls (mean [SD] age, 60.4 [6.6] years; 8121 men [57.8%]). A total of 324 variants were identified that interacted with diet consumption at the suggestive threshold (P < 1 × 10-5). In gene-based analysis, aggregation of multiple EPDR1 gene variants was found to interact with fish intake regarding CRC risk. Furthermore, gene-set enrichment analysis found that several sets of protein-coding genes, which were overrepresented with particular functions and pathways, interacted with the consumption of milk (ART), cheese (OR), tea (KRT), and alcohol (PRM and TNP).

In this nested case-control study, the risk of CRC associated with fish intake was modified by multiple single-nucleotide polymorphisms of the EPDR1 gene. The findings further suggested possible functions and pathways that might link the consumption of milk, cheese, tea, and alcohol with CRC development.

Livestock on the Qinghai-Tibetan Plateau is of great importance for the livelihood of the local inhabitants and the ecosystem of the plateau. The natural, harsh environment has shaped the adaptations of local livestock while providing them with requisite eco-services. Over time, unique genes and metabolic mechanisms (nitrogen and energy) have evolved which enabled the yaks to adapt morphologically and physiologically to the Qinghai-Tibetan Plateau. The rumen microbiota has also co-evolved with the host and contributed to the host's adaptation to the environment. Understanding the complex linkages between the rumen microbiota, the host, and the environment is essential to optimizing the rumen function to meet the growing demands for animal products while minimizing the environmental impact of ruminant production. However, little is known about the mechanisms of host-rumen microbiome-environment linkages and how they ultimately benefit the animal in adapting to the environment. In this review, we pieced together the yak's adaptation to the Qinghai-Tibetan Plateau ecosystem by summarizing the natural selection and nutritional features of yaks and integrating the key aspects of its rumen microbiome with the host metabolic efficiency and homeostasis. We found that this homeostasis results in higher feed digestibility, higher rumen microbial protein production, higher short-chain fatty acid (SCFA) concentrations, and lower methane emissions in yaks when compared with other low-altitude ruminants. The rumen microbiome forms a multi-synergistic relationship among the rumen microbiota services, their communities, genes, and enzymes. The rumen microbial proteins and SCFAs act as precursors that directly impact the milk composition or adipose accumulation, improving the milk or meat quality, resulting in a higher protein and fat content in yak milk and a higher percentage of protein and abundant fatty acids in yak meat when compared to dairy cow or cattle. The hierarchical interactions between the climate, forage, rumen microorganisms, and host genes have reshaped the animal's survival and performance. In this review, an integrating and interactive understanding of the host-rumen microbiome environment was established. The understanding of these concepts is valuable for agriculture and our environment. It also contributes to a better understanding of microbial ecology and evolution in anaerobic ecosystems and the host-environment linkages to improve animal production.

Gene expression during brain development or abnormal development is a biological process that is highly dynamic in spatio and temporal. Previous studies have mainly focused on individual brain regions or a certain developmental stage. Our motivation is to address this gap by incorporating spatio-temporal information to gain a more complete understanding of brain development or abnormal brain development, such as Alzheimer's disease (AD), and to identify potential determinants of response. In this study, we propose a novel two-step framework based on spatial-temporal information weighting and multi-step decision trees. This framework can effectively exploit the spatial similarity and temporal dependence between different stages and different brain regions, and facilitate differential gene analysis in brain regions with high heterogeneity. We focus on two datasets: the AD dataset, which includes gene expression data from early, middle and late stages, and the brain development dataset, spanning fetal development to adulthood. Our findings highlight the advantages of the proposed framework in discovering gene classes and elucidating their impact on brain development and AD progression across diverse brain regions and stages. These findings align with existing studies and provide insights into the processes of normal and abnormal brain development.

Tree growth is the consequence of developmental interactions between above- and below-ground compartments. However, a comprehensive view of the genetic architecture of growth as a cohesive whole is poorly understood. We propose a systems biology approach for mapping growth trajectories in genome-wide association studies viewing growth as a complex (phenotypic) system in which above- and below-ground components (or traits) interact with each other to mediate systems behavior. We further assume that trait-trait interactions are controlled by a genetic system composed of many different interactive genes and integrate the Lotka-Volterra predator-prey model to dissect phenotypic and genetic systems into pleiotropic and epistatic interaction components by which the detailed genetic mechanism of above- and below-ground co-growth can be charted. We apply the approach to analyze linkage mapping data of Populus euphratica, which is the only tree species that can grow in the desert, and characterize several loci that govern how above- and below-ground growth is cooperated or competed over development. We reconstruct multilayer and multiplex genetic interactome networks for the developmental trajectories of each trait and their developmental covariation. Many significant loci and epistatic effects detected can be annotated to candidate genes for growth and developmental processes. The results from our model may potentially be useful for marker-assisted selection and genetic editing in applied tree breeding programs. The model provides a general tool to characterize a complete picture of pleiotropic and epistatic genetic architecture in growth traits in forest trees and any other organisms.

In this paper, we present demographic, clinical, anamnestic, cognitive, and functional data, as well as haematological, haematochemical, immunological, and genetic parameters of an exceptional individual: A.T., a semi-supercentenarian who held the title of the oldest living Italian male centenarian from 28 December 2020, to 23 September 2021. The purpose of this study is to provide fresh insights into extreme phenotypes, with a particular focus on immune-inflammatory parameters. To the best of our knowledge, this study represents the first phenotypic investigation of a semi-supercentenarian, illustrating both INFLA-score, a metric designed to assess the cumulative impact of inflammatory markers and indicators of age-related immune phenotype (ARIP), recognized as significant gauges of biological ageing. The aim of this study was, indeed, to advance our understanding of the role of immune-inflammatory responses in achieving extreme longevity. The results of laboratory tests, as well as clinical history and interview data, when compared to the results of our recent study on Sicilian centenarians, demonstrate an excellent state of health considering his age. Consistent with previous studies, we observed increased IL-6 inflammatory markers and INFLA score in A.T. More interestingly, the semi-supercentenarian showed values of ARIP indicators such as naïve CD4+ cells, CD4+/CD8+ ratio, and CD4+TN/TM ratio in the range of young adult individuals, suggesting that his immune system's biological age was younger than the chronological one. The results support the notion that the immune system can play a role in promoting extreme longevity. However, this does not rule out the involvement of other body systems or organs in achieving extreme longevity.

The "exposome" covers all disease determinants across a lifetime. Many exposome factors could induce epigenetic changes, especially in DNA methylation. Yet, the role of these modifications in disease development remains partly understood. Although the possible relationship among the exposome factors, epigenetic modifications, and health/disease has been investigated extensively, all previous studies start from the assumption that epigenetic changes are always detrimental to (or represent an adverse effect on) the health of the affected individual. We hereby propose a new approach to investigate these modifications, and their possible relation with human health, in the context of the exposome. Our hypothesis is based on the possibility that some environmentally-induced changes are plastic entities, responding physiologically to the environment to allow individual adaptation. Briefly, after evaluating the association between environmental exposure and the variation of a given biological parameter through regression models, we use the estimated regression function to predict values for each study subject. We then calculated the relative percent difference (PD) between the measured (i.e., observed) biological parameter and the predicted (i.e., expected) from the model. Notably, we have tested our hypothesis using two distinct models, specifically focusing on LINE-1 methylation and extracellular vesicles (EVs). We hypothesize that the greater the difference between the observed and the expected, the greater the inability of the subject to adapt to external stimuli.

Williams syndrome (WS) is a neurodevelopmental disorder caused by a microdeletion in the q11.23 region of chromosome 7. Recent case series reports and clinical case studies have suggested that the cognitive, behavioral, emotional, and social profile in WS could depend on the genes involved in the deletion. The objective of this systematic review was to analyze and synthesize the variability of the cognitive and behavioral profile of WS with atypical deletion and its probable relationship with the affected genes. The medical subject headings searched were "Williams syndrome," "genotype," "phenotype," "cognitive profile," and "atypical deletion." The studies included were in English or Spanish, with children and adults, and published between January 2000 and October 2022. Twenty-three studies are reported. The characteristics of the participants, the genes involved, the neuropsychological domains and instruments, and the prevalence of the WS cognitive profile criteria were used for the genotype-phenotype analysis. The genes with a major impact on the cognitive profile of WS were (a) LIMK1 and those belonging to the GTF2I family, the former with a greater influence on visuospatial abilities; (b) GTF2IRD1 and GTF2I, which have an impact on intellectual capacity as well as on visuospatial and social skills; (c) FZD9, BAZ1B, STX1A, and CLIP2, which influence the cognitive profile if other genes are also effected; and (d) GTF2IRD2, which is related to the severity of the effect on visuospatial and social skills, producing a behavioral phenotype like that of the autism spectrum. The review revealed four neuropsychological phenotypes, depending on the genes involved, and established the need for more comprehensive study of the neuropsychological profile of these patients. Based on the results found, we propose a model for the investigation of and clinical approach to the WS neuropsychological phenotype.

In the last couple of decades, the study of human living brain has benefitted of neuroimaging and non-invasive electrophysiological techniques, which are particularly valuable during development. A number of studies allowed to trace the usual stages leading from pregnancy to adult age, and relate them to functional and behavioral measurements. It was also possible to explore the effects of some interventions, behavioral or not, showing that the commonly followed pathway to adulthood may be steered by external interventions. These events may result in behavioral modifications but also in structural changes, in some cases limiting plasticity or extending/modifying critical periods. In this review, we outline the healthy human brain development in the absence of major issues or diseases. Then, the effects of negative (different stressors) and positive (music training) environmental stimuli on brain and behavioral development is depicted. Hence, it may be concluded that the typical development follows a course strictly dependent from environmental inputs, and that external intervention can be designed to positively counteract negative influences, particularly at young ages. We also focus on the social aspect of development, which starts in utero and continues after birth by building social relationships. This poses a great responsibility in handling children education and healthcare politics, pointing to social accountability for the responsible development of each child.

Individuals with obesity tend to discount the future (delay discounting), focusing on immediate gratification. Delay discounting is reliably related to indicators of economic scarcity (i.e., insufficient resources), including lower income and decreased educational attainment in adults. It is unclear whether the impact of these factors experienced by parents also influence child delay discounting between the ages of 8 and 12-years in families with obesity.

The relationship between indices of family income and delay discounting was studied in 452 families with parents and 6-12-year-old children with obesity. Differences in the relationships between parent economic, educational and Medicaid status, and parent and child delay discounting were tested.

Results showed lower parent income (p = 0.019) and Medicaid status (p = 0.021) were differentially related to greater parent but not child delay discounting among systematic responders.

These data suggest differences in how indicators of scarcity influence delay discounting for parents and children, indicating that adults with scarce resources may be shaped to focus on immediate needs instead of long-term goals. It is possible that parents can reduce the impact of economic scarcity on their children during preadolescent years. These findings suggest a need for policy change to alleviate the burden of scarce conditions and intervention to modify delay discounting rate and to improve health-related choices and to address weight disparities.

The overall disease burden of pediatric infection is high, with widely varying clinical outcomes including death. Among the most vulnerable children, those with inborn errors of immunity, reduced penetrance and variable expressivity are common but poorly understood. There are several genetic mechanisms that influence phenotypic variation in inborn errors of immunity, as well as a body of knowledge on environmental influences and specific pathogen triggers. Critically, recent advances are illuminating novel nuances for fundamental concepts on disease penetrance, as well as raising new areas of inquiry. The last few decades have seen the identification of almost 500 causes of inborn errors of immunity, as well as major advancements in our ability to characterize somatic events, the microbiome, and genotypes across large populations. The progress has not been linear, and yet, these developments have accumulated into an enhanced ability to diagnose and treat inborn errors of immunity, in some cases with precision therapy. Nonetheless, many questions remain regarding the genetic and environmental contributions to phenotypic variation both within and among families. The purpose of this review is to provide an updated summary of key concepts in genetic and environmental contributions to phenotypic variation within inborn errors of immunity, conceptualized as including dynamic, reciprocal interplay among factors unfolding across the key dimension of time. The associated findings, potential gaps, and implications for research are discussed in turn for each major influencing factor. The substantial challenge ahead will be to organize and integrate information in such a way that accommodates the heterogeneity within inborn errors of immunity to arrive at a more comprehensive and accurate understanding of how the immune system operates in health and disease. And, crucially, to translate this understanding into improved patient care for the millions at risk for serious infection and other immune-related morbidity.

Human health is determined both by genetics (G) and environment (E). This is clearly illustrated in groups of individuals who are exposed to the same environmental factor showing differential responses. A quantitative measure of the gene-environment interactions (GxE) effects has not been developed and in some instances, a clear consensus on the concept has not even been reached; for example, whether cancer is predominantly emerging from "bad luck" or "bad lifestyle" is still debated. In this article, we provide a panel of examples of GxE interaction as drivers of pathogenesis. We highlight how epigenetic regulations can represent a common connecting aspect of the molecular bases. Our argument converges on the concept that the GxE is recorded in the cellular epigenome, which might represent the key to deconvolute these multidimensional intricated layers of regulation. Developing a key to decode this epigenetic information would provide quantitative measures of disease risk. Analogously to the epigenetic clock introduced to estimate biological age, we provocatively propose the theoretical concept of an "epigenetic score-meter" to estimate disease risk.

Although systemic inequities, broadly defined, are associated with health disparities in adults, there is a dearth of research linking contextual measures of exclusionary policies or prejudicial attitudes to health impairments in children, particularly among Latino populations. In this study, we examined a composite measure of systemic inequities in relation to the cooccurrence of multiple health problems in Latino children in the United States.

Participants included 17 855 Latino children aged 3 to 17 years from the National Survey of Children's Health (2016-2020). We measured state-level systemic inequities using a factor score that combined an index of exclusionary state policies toward immigrants and aggregated survey data on prejudicial attitudes toward immigrants and Latino individuals. Caregivers reported on 3 categories of child health problems: common health difficulties in the past year, current chronic physical health conditions, and current mental health conditions. For each category, we constructed a variable reflecting 0, 1, or 2 or more conditions.

In models adjusted for sociodemographic covariates, interpersonal discrimination, and state-level income inequality, systemic inequities were associated with 1.13 times the odds of a chronic physical health condition (95% confidence interval: 1.02-1.25) and 1.24 times the odds of 2 or more mental health conditions (95% confidence interval: 1.06-1.45).

Latino children residing in states with higher levels of systemic inequity are more likely to experience mental health or chronic physical health conditions relative to those in states with lower levels of systemic inequity.

Risk assessment methodology, mostly commonly used, faces the complexity of the environment. Populations are exposed to multiple sources of chemicals throughout life and the chemical mixtures they are exposed change during time (lifestyle factors, regulatory decisions, etc). The risk assessment needs to consider these dynamics and the evolution of the body with age, in order to refine the exposure assessment to chemicals and to predict the health impact of these exposures. This review highlights the latest methodologies developed to improve risk assessment, especially cor heavy metals. The methodologies aim to better describe the chemical toxicokinetic and toxicodynamic as well as the exposure assessment. Human Biomonitoring (HBM) data give great opportunities to link biomarkers of exposure with an adverse effect. Physiologically-Based Toxicokinetic (PBTK) models are more and more used to simulate the evolution of biomarkers in organisms, considering the external exposures and the physiological evolutions. PBTK models may also be used to determine the routes of exposure or to predict the impacts of schemes of exposure. The major limit is the integration of several chemicals in mixture with common adverse effects and the interactions between them.

Recent developments in various domains have led to a growing interest in the potential of artificial intelligence to enhance our lives and environments. In particular, the application of artificial intelligence in the management of complex human diseases, such as cancer, has garnered significant attention. The evolution of artificial intelligence is thought to be influenced by multiple factors, including human intervention and environmental factors. Similarly, tumors, being heterogeneous and complex diseases, continue to evolve due to changes in the physical, chemical, and biological environment. Additionally, the concept of cellular intelligence within biological systems has been recognized as a potential attribute of biological entities. Therefore, it is plausible that the tumor intelligence present in cancer cells of affected individuals could undergo super-evolution due to changes in the pro-tumor environment. Thus, a comparative analysis of the evolution of artificial intelligence and super-complex tumor intelligence could yield valuable insights to develop better artificial intelligence-based tools for cancer management.

Gene-environment interactions are believed to play a role in multifactorial phenotypes, although poorly described mechanistically. Cleft lip/palate (CLP), the most common craniofacial malformation, has been associated with both genetic and environmental factors, with little gene-environment interaction experimentally demonstrated. Here, we study CLP families harbouring CDH1/E-Cadherin variants with incomplete penetrance and we explore the association of pro-inflammatory conditions to CLP. By studying neural crest (NC) from mouse, Xenopus and humans, we show that CLP can be explained by a 2-hit model, where NC migration is impaired by a combination of genetic (CDH1 loss-of-function) and environmental (pro-inflammatory activation) factors, leading to CLP. Finally, using in vivo targeted methylation assays, we demonstrate that CDH1 hypermethylation is the major target of the pro-inflammatory response, and a direct regulator of E-cadherin levels and NC migration. These results unveil a gene-environment interaction during craniofacial development and provide a 2-hit mechanism to explain cleft lip/palate aetiology.

Neuroplasticity refers to the ability of brain circuits to reorganize and change the properties of the network, resulting in alterations in brain function and behavior. It is traditionally believed that neuroplasticity is influenced by external stimuli, learning, and experience. Intriguingly, there is new evidence suggesting that endogenous signals from the body's periphery may play a role. The gut microbiota, a diverse community of microorganisms living in harmony with their host, may be able to influence plasticity through its modulation of the gut-brain axis. Interestingly, the maturation of the gut microbiota coincides with critical periods of neurodevelopment, during which neural circuits are highly plastic and potentially vulnerable. As such, dysbiosis (an imbalance in the gut microbiota composition) during early life may contribute to the disruption of normal developmental trajectories, leading to neurodevelopmental disorders. This review aims to examine the ways in which the gut microbiota can affect neuroplasticity. It will also discuss recent research linking gastrointestinal issues and bacterial dysbiosis to various neurodevelopmental disorders and their potential impact on neurological outcomes.

Epigenetic processes are fast emerging as a promising molecular system in the search for both biomarkers and mechanisms underlying human health and disease risk, including psychopathology.

In this review, we discuss the application of epigenetics (specifically DNA methylation) to research in child and adolescent mental health, with a focus on the use of developmentally sensitive datasets, such as prospective, population-based cohorts. We look back at lessons learned to date, highlight current developments in the field and areas of priority for future research. We also reflect on why epigenetic research on child and adolescent mental health currently lags behind other areas of epigenetic research and what we can do to overcome existing barriers.

To move the field forward, we advocate for the need of large-scale, harmonized, collaborative efforts that explicitly account for the time-varying nature of epigenetic and mental health data across development.

We conclude with a perspective on what the future may hold in terms of translational applications as more robust signals emerge from epigenetic research on child and adolescent mental health.

Extracellular vesicles (EVs) are present in numerous peripheral bodily fluids and function in critical biological processes, including cell-to-cell communication. Most relevant to the present study, EVs contain microRNAs (miRNAs), and initial evidence from the field indicates that miRNAs detected in circulating EVs have been previously associated with mental health disorders. Here, we conducted an exploratory longitudinal and cross-sectional analysis of miRNA expression in serum EVs from adolescent participants. We analyzed data from a larger ongoing cohort study, evaluating 116 adolescent participants at two time points (wave 1 and wave 2) separated by three years. Two separate data analyses were employed: A cross-sectional analysis compared individuals diagnosed with Major Depressive Disorder (MDD), Anxiety disorders (ANX) and Attention deficit/Hyperactivity disorder (ADHD) with individuals without psychiatric diagnosis at each time point. A longitudinal analysis assessed changes in miRNA expression over time between four groups showing different diagnostic trajectories (persistent diagnosis, first incidence, remitted and typically developing/control). Total EVs were isolated, characterized by size distribution and membrane proteins, and miRNAs were isolated and sequenced. We then selected differentially expressed miRNAs for target prediction and pathway enrichment analysis. In the longitudinal analysis, we did not observe any statistically significant results. In the cross-sectional analysis: in the ADHD group, we observed an upregulation of miR-328-3p at wave 1 only; in the MDD group, we observed a downregulation of miR-4433b-5p, miR-584-5p, miR-625-3p, miR-432-5p and miR-409-3p at wave 2 only; and in the ANX group, we observed a downregulation of miR-432-5p, miR-151a-5p and miR-584-5p in ANX cases at wave 2 only. Our results identified previously observed and novel differentially expressed miRNAs and their relationship with three mental health disorders. These data are consistent with the notion that these miRNAs might regulate the expression of genes associated with these traits in genome-wide association studies. The findings support the promise of continued identification of miRNAs contained within peripheral EVs as biomarkers for mental health disorders.

Genetics has been an important tool for discovering new aspects of biology across life. In humans, there is growing momentum behind the application of this knowledge to drive innovation in clinical care, most notably through developments in precision medicine. Nowhere has the impact of genetics on clinical practice been more striking than in the field of rare disorders. For most of these conditions, individual disease susceptibility is influenced by DNA sequence variation in a single or a small number of genes. In contrast, most common disorders are multifactorial and are caused by a complex interplay of multiple genetic, environmental and stochastic factors. The longstanding division of human disease genetics into rare and common components has obscured the continuum of human traits and echoes aspects of the century-old debate between the Mendelian and biometric views of human genetics. In this article, we discuss the differences in data and concepts between rare and common disease genetics. Opportunities to unify these two areas are noted and the importance of adopting a holistic perspective that integrates diverse genetic and environmental factors is discussed.

The cooperative strategy of phenotypic traits during the growth of plants reflects how plants allocate photosynthesis products, which is the most favorable decision for them to optimize growth, survival, and reproduction response to changing environment. Up to now, we still know little about why plants make such decision from the perspective of biological genetic mechanisms.

In this study, we construct an analytical mapping framework to explore the genetic mechanism regulating the interaction of two complex traits. The framework describes the dynamic growth of two traits and their interaction as Differential Interaction Regulatory Equations (DIRE), then DIRE is embedded into QTL mapping model to identify the key quantitative trait loci (QTLs) that regulate this interaction and clarify the genetic effect, genetic contribution and genetic network structure of these key QTLs. Computer simulation experiment proves the reliability and practicability of our framework.

In order to verify that our framework is universal and flexible, we applied it to two sets of data from Populus euphratica, namely, aboveground stem length - underground taproot length, underground root number - underground root length, which represent relationships of phenotypic traits in two spatial dimensions of plant architecture. The analytical result shows that our model is well applicable to datasets of two dimensions.

Our model helps to better illustrate the cooperation-competition patterns between phenotypic traits, and understand the decisions that plants make in a specific environment that are most conducive to their growth from the genetic perspective.