Systems Biology Research Articles

LipidSig 2.0: integrating lipid characteristic insights into advanced lipidomics data analysis.

In the field of lipidomics, where the complexity of lipid structures and functions presents significant analytical challenges, LipidSig stands out as the first web-based platform providing integrated, comprehensive analysis for efficient data mining of lipidomic datasets. The upgraded LipidSig 2.0 (https://lipidsig.bioinfomics.org/) simplifies the process and empowers researchers to decipher the complex nature of lipids and link lipidomic data to specific characteristics and biological contexts. This tool markedly enhances the efficiency and depth of lipidomic research by autonomously identifying lipid species and assigning 29 comprehensive characteristics upon data entry. LipidSig 2.0 accommodates 24 data processing methods, streamlining diverse lipidomic datasets. The tool's expertise in automating intricate analytical processes, including data preprocessing, lipid ID annotation, differential expression, enrichment analysis, and network analysis, allows researchers to profoundly investigate lipid properties and their biological implications. Additional innovative features, such as the 'Network' function, offer a system biology perspective on lipid interactions, and the 'Multiple Group' analysis aids in examining complex experimental designs. With its comprehensive suite of features for analyzing and visualizing lipid properties, LipidSig 2.0 positions itself as an indispensable tool for advanced lipidomics research, paving the way for new insights into the role of lipids in cellular processes and disease development.

Glycoproteomic and proteomic analysis of Burkholderia cenocepacia reveals glycosylation events within FliF and MotB are dispensable for motility.

Burkholderia cenocepacia is an opportunistic pathogen of concern within the Cystic Fibrosis community. Despite a greater appreciation of the unique physiology of B. cenocepacia gained over the last 20 years a complete understanding of the proteome and especially the O-glycoproteome, is lacking. In this study, we utilize systems biology approaches to expand the known B. cenocepacia glycoproteome as well as track the dynamics of glycoproteins across growth phases, culturing media and in response to the loss of glycosylation. We show that the glycoproteome of B. cenocepacia is largely stable across conditions and that the loss of glycosylation only impacts five glycoproteins including the motility associated proteins FliF and MotB. Examination of MotB and FliF shows, while these proteins are essential for motility, glycosylation is dispensable. Combined this work supports that B. cenocepacia glycosylation can be dispensable for protein function and may influence protein properties beyond stability.

Network pharmacology speaking to ethnopharmacology: new data on an ancient remedy

Network pharmacology as a “green approach”, predicting metabolite behaviours chemically and biologically and guid¬ing biological experimental design, is a new strategy aiming to uncover the mechanism of action of natural products as drug candidates. It provides a powerful way to identify novel mechanisms of natural products with potential thera¬peutic effects. This approach has emerged as a powerful tool to overcome the limitations of traditional methods, such as the ability to predict the adverse effects of a drug and the likelihood of failure during clinical trials, by applying systems biology principles to the field of pharmacology. This method combines the multi-omics dataset, computer modeling, and chemical biology so as to reveal pharmaceutical actions and guide drug discovery. Therefore, computer-aided drug design combined with network pharmacology can be viewed as a novel in silico screening ap¬proach to drug discovery, by utilising chemoinformatics, bioinformatics, structure biology, and chemical biology. This strategy includes target-based virtual screening - molecular docking, ligand similarity-based virtual screening, and inverse screening (Inver-dock), providing a powerful tool for target identification of drug candidates, multitarget dis¬covery, and natural bioactive product profiling. It can also be used for selectivity profiling of drugs, drug repositioning, safety profiling, and metabolism profiling prediction (ADMET).

Biomarkers of Alzheimer's Disease Associated with Programmed Cell Death Reveal Four Repurposed Drugs.

Alzheimer's disease (AD) is a neurodegenerative disorder and the most common cause of dementia. Programmed cell death (PCD) is mainly characterized by unique morphological features and energy-dependent biochemical processes. The predominant pathway leading to cell death in AD has not been thoroughly analyzed, although there is evidence of neuron loss in AD and numerous pathways of PCD have been associated with this process. A better understanding of the systems biology underlying the relationship between AD and PCD could lead to the development of new therapeutic approaches. To this end, publicly available transcriptome data were examined using bioinformatic methods such as differential gene expression and weighted gene coexpression network analysis (WGCNA) to find PCD-related AD biomarkers. The diagnostic significance of these biomarkers was evaluated using a logistic regression-based predictive model. Using these biomarkers, a multifactorial regulatory network was developed. Last, a drug repositioning study was conducted to propose new drugs for the treatment of AD targeting PCD. The development of 3PM (predictive, preventive, and personalized) drugs for the treatment of AD would be enabled by additional research on the effects of these drugs on this disease.

Abstract PO1-14-09: Age-related remodeling of the systemic and breast microenvironment promotes a tumor-permissive locale for ER+ breast cancer in older women

Abstract Introduction: The peak incidence of ER+ breast cancer occurs in women around the age of 70. Compared to younger cohorts, we and others have shown that older patients with ER+ breast cancer have an enrichment of luminal disease and experience fewer recurrences, suggesting overtreatment. Differences in the biological phenotypes of tumors in older women remain poorly understood and treatment remains challenging as older patients are underrepresented in clinical trials. In this study, we hypothesized that aging alters both local and systemic hormones and inflammatory cytokines, creating a permissive environment for tumor formation and growth. To address this hypothesis, we employed a systems biology approach across multiple model systems and tissue samples. Methods: Our study included specimens from two cohorts of patients: (1) n = 90 women without breast cancer obtained from the Komen Tissue Bank, from whom we obtained matched plasma and non-cancerous breast tissue (n = 30 across age groups comprising of young donors (35-45yo), middle-aged donors (55-69yo), and older donors (≥ 70yo); and (2) n = 115 women with ER+ breast cancer (n = 25 young patients, n = 57 middle-aged patients, and n = 33 older patients) obtained from our institutional biobank, including matched plasma, tumor tissue, and tumor-adjacent tissue. From each of these sets of specimens, we measured estrogen disposition using mass spectrometry, a 22-plex panel of inflammatory markers, and transcriptomic changes using RNA-seq. Using scRNA-seq and multiplexed IHC, we further characterized the immune changes that occur with age. Lastly, we used an aged, carcinogen-induced ER+ tumor model in F344 rats (obtained from the NIA) to model tumor development and growth. Results: In the plasma, estradiol (E2) drastically decreased in post-menopausal women, leaving estrone (E1) as the predominant circulating estrogen in older women. However, the breast tumor microenvironment (TME) showed comparable levels of E1 and E2 across age groups. Multi-class concordance analysis of breast cancer tissue from RNA revealed significant increases in gene expression of the HSD17B7 enzyme and decreases in HSD17B2 enzyme across age, likely elevating local E1-to-E2 conversion and yielding high local E2 levels despite low circulating levels specifically in older women. In older patients with ER+ breast cancer, there was a significant increase in a chemokine network characterized by CCL2 and CXCL9 within the TME. scRNA-seq revealed enrichment of inflammatory M2-like macrophages in the aged TME. Immune dysfunction and decreased immunosurveillance in older patients manifested with widespread decreases in the presence of cytotoxic lymphocytes and decreased pathway enrichment of key immune pathways, such as JAK/STAT and IFNy signaling. mIHC analysis revealed decreases in CD4 and CD8 T cells and increases in M2-like macrophages in older patients in both tumor and stromal regions. Lastly, in the carcinogen-induced F344 rat model, aged rats (~ 24mo, human equivalent 60-70yo) had a shorter tumor-free interval than the younger rats (~ 4-6mo, human equivalent 20-30yo), likely due to increases in tumor-promoting inflammation and decreased immune surveillance. Ongoing mechanistic work is focused on macrophage-patient derived organoid co-cultures evaluating the functional relevance of E2, CCL2, and CXCL9 in shaping the aged TME. Conclusions: Our study of systemic and local breast hormones and cytokines in both healthy individuals and breast cancer patients showed that older women with ER+ breast cancer harbor different systemic and local environments compared to younger women. The aged TME is characterized by high E2, cytotoxic lymphocyte depletion, and immune dysfunction, creating a permissive environment for tumor formation. Future translational work should be aimed at chemo-preventative strategies to reduce the age-related chronic inflammation and immune dysfunction. Citation Format: Neil Carleton, Jian Zou, Sanghoon Lee, Dixcy Jaba Sheeba John Mary, Ruxuan Li, Jennifer Atkinson, Ziyu Huang, Hatice Osmanbeyoglu, Peter Lucas, Emilia Diego, Michael Lotze, George Tseng, Jagmohan Hooda, Ioannis Zervantonakis, Priscilla McAuliffe, Steffi Oesterreich, ADRIAN LEE. Age-related remodeling of the systemic and breast microenvironment promotes a tumor-permissive locale for ER+ breast cancer in older women [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-14-09.

Network Pharmacology Prediction and Metabolomics Validation of the Novel Targets of Morus alba L. against High-Fat Diet-Induced Diabetes Mellitus in C57/6J Mice

Diabetes mellitus (DM) is an endocrine-metabolic disorder that has limited approaches to treat effectively. Morus alba L., also known as mulberry, is a well-known medicinal plant, and its branch bark has shown hypoglycemic activity. It is rich in antioxidant and anti-inflammatory ingredients. In this study, we used metabolomics combined with network pharmacology to investigate the molecular mechanism and potential key targets of mulberry branch bark powder (MBBP) for treating DM. Serum metabolomics was performed to analyze the differences in metabolites and enrich metabolic pathways. Network pharmacology, based on systems biology tools, was applied to generate the pathway-target-compound network. Integrated analyses were then used to screen for key targets. To verify the obtained key targets, we used a molecular docking method and experimental validation. Our findings revealed that thirty-five endogenous metabolites contributed to the therapeutic impact of MBBP against DM. The analysis of 10 hub genes in the compound-target network partially supported the enrichment of metabolic pathways. Further analysis focused on two compounds (eugenol and mulberrofuran A) and three key targets (NOS2, MAOA, and CYP1A1). This study explores the active compounds of MBBP against DM and provides a novel perspective for improving DM treatment based on key targets.

Lipid metabolism in crocodilians: a field with promising applications in the field of ecotoxicology.

In the last years, lipid physiology has become an important research target for systems biology applied to the field of ecotoxicology. Lipids are not only essential components of biological membranes, but also participate in extra and intracellular signaling processes and as signal transducers and amplifiers of regulatory cascades. Particularly in sauropsids, lipids are the main source of energy for reproduction, growth, and embryonic development. In nature, organisms are exposed to different stressors, such as parasites, diseases and environmental contaminants, which interact with lipid signaling and metabolic pathways, disrupting lipid homeostasis. The system biology approach applied to ecotoxicological studies is crucial to evaluate metabolic regulation under environmental stress produced by xenobiotics. In this review, we cover information of molecular mechanisms that contribute to lipid metabolism homeostasis in sauropsids, specifically in crocodilian species. We focus on the role of lipid metabolism as a powerful source of energy and its importance during oocyte maturation, which has been increasingly recognized in many species, but information is still scarce in crocodiles. Finally, we highlight priorities for future research on the influence of environmental stressors on lipid metabolism, their potential effect on the reproductive system and thus on the offspring, and their implications on crocodilians conservation.

Development of Functional Foods with Enhanced Health Benefits

Purpose: This study aimed to explore the development of functional foods with enhanced health benefits. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to the development of functional foods with enhanced health benefits. Preliminary empirical review revealed that these innovative food products offer promising avenues for improving health outcomes and preventing chronic diseases. By formulating functional foods with targeted bioactive compounds, researchers tailored interventions to address prevalent health concerns such as gut dysbiosis, hyperlipidemia, oxidative stress, and nutrient deficiencies. The study emphasized the need for continued research and innovation to optimize formulations, mechanisms of action, and delivery systems. Collaboration between researchers, food scientists, healthcare professionals, policymakers, and the food industry was highlighted as essential for driving innovation and translating scientific findings into tangible interventions that benefit public health. Overall, the study highlighted the potential of functional foods to revolutionize nutrition and disease prevention strategies. Unique Contribution to Theory, Practice and Policy: The Nutritional Epidemiology, Nutrigenomics and Systems Biology model may be used to anchor future studies on the development of functional foods with enhanced health benefits. The contributed significantly to theory, practice, and policy in the field of nutrition and public health. It provided valuable insights into the complex interactions between bioactive compounds and physiological processes, advancing theoretical frameworks in nutrition science. By emphasizing evidence-based formulation and product optimization, the study offered practical guidance for food scientists and manufacturers in creating functional foods with demonstrable health benefits. Moreover, the study advocated for transparent labeling and regulatory oversight to ensure consumer safety and quality control. Overall, its recommendations facilitated the integration of functional foods into dietary guidelines and public health initiatives, promoting improved health outcomes and reduced chronic disease burden.

Role of Probiotic Strains in Ensuring Food Safety

Purpose: The general objective of this study was to examine the role of probiotic strains in ensuring food safety. Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library. Findings: The findings reveal that there exists a contextual and methodological gap relating to the role of probiotic strains in ensuring food safety. Preliminary empirical review revealed that that probiotics offer promising avenues for enhancing microbial safety in food products. Through a comprehensive review of existing literature and empirical studies, researchers found that probiotics exhibited varied but significant antimicrobial activity against foodborne pathogens, thus reducing the risk of foodborne illnesses. The study emphasized the importance of strain-specific evaluation and standardized protocols for assessing probiotic efficacy. Furthermore, interdisciplinary collaborations were identified as crucial for translating scientific findings into practical applications for public health. Overall, the study highlighted the significant potential of probiotic strains in improving food safety outcomes, with further research needed to optimize formulations and address knowledge gaps. Unique Contribution to Theory, Practice and Policy: Ecological Theory of Gut Microbiota, Host-Microbiota Mutualism theory and Systems Biology Approach to Gut Microbiome may be used to anchor future studies on probiotic strains in ensuring food safety. The study emphasized advancing understanding of microbial ecology in the gastrointestinal tract, developing evidence-based guidelines for probiotic use, and aligning policies with scientific evidence. Recommendations included investing in research and education initiatives, fostering interdisciplinary collaborations, and promoting international cooperation. By integrating ecological principles, developing standardized protocols, and aligning policies with scientific evidence, stakeholders were able to harness the potential of probiotics to enhance food safety and public health, ultimately benefiting consumers worldwide.

In silico analysis of the key molecules of SARS-CoV-2: ACE2 and TMPRSS2 in head and neck cancer

It has been reported that cancer patients are more susceptible to SARS-CoV-2 infection due to their immunocompromised state. Although ACE2 and TMPRSS2 are essential for SARS-CoV-2 virus entry, the significant role of these molecules in HNSC is still unknown. Thus, the study aimed to delineate the fundamental role these molecules in HNSC using a systems biology approach. The transcriptional profile of ACE2 and TMPRSS2 in HNSC was evaluated using the TIMER and UALCAN databases. The association between the mRNA levels of ACE2 and TMPRSS2 was assessed using GEPIA2. cBioPortal was used to assess the genetic alterations in the ACE2 and TMPRSS2 protein sequences involved in HNSC. The gene associated with COVID-19 and HNSC was identified using the CTD database. Finally, the STRING and PANTHER online platforms were used to construct a protein-protein interaction (PPI) network and to determine the functional role of genes retrieved from the CTD database, respectively. ACE2 expression was found to be unaltered in HNSC and uninfected HNSC datasets compared to normal and HPV-infected HNSC datasets, respectively. However, the TMPRSS2 levels in HNSC and HPV-infected HNSC were significantly (P ≤ 0.001) downregulated and upregulated compared to healthy controls and uninfected HNSC, respectively. A significant (P ≤ 0.014) but weak positive correlation was noted between ACE2 and TMPRSS2 in HNSC. The PPI network also showed significant involvement of COVID-19 and HNSC-related genes in catalysis, binding activity, and several cancers signaling pathways. Based on the in-silico analysis, it could be concluded that ACE2 and TMPRSS2, the key molecules of SARS-CoV-2, might be involved in HNSC. However, the long-term effects of SARS-CoV-2 infection, if any, on HNSC patients in clinical settings require further study.

Systems Biology Dissection of PTSD in Multiple Regions, Omics, and Cell-Types of the Brain

Systems Biology Dissection of PTSD in Multiple Regions, Omics, and Cell-Types of the Brain

Possible New Candidates Involved to Thalidomide-Related Limbs and Cardiac Defects: A Systems Biology Approach.

Thalidomide is a known teratogen that causes malformations especially in heart and limbs. Its mechanism of teratogenicity is still not fully elucidated. Recently, a new target of thalidomide was described, TBX5, and was observed a new interaction between HAND2 and TBX5 that is disrupted in the presence of thalidomide. Therefore, our study aimed to raise potential candidates for thalidomide teratogenesis, through systems biology, evaluating HAND2 and TBX5 interaction and heart and limbs malformations of thalidomide. Genes and proteins related to TBX5 and HAND2 were selected through TF2DNA, REACTOME, Human Phenotype Ontology, and InterPro databases. Networks were assembled using STRING © database. Network analysis were performed in Cytoscape © and R v3.6.2. Differential gene expression (DGE) analysis was performed through gene expression omnibus. We constructed a network for HAND2 and TBX5 interaction; a network for heart and limbs malformations of TE; and the two joined networks. We observed that EP300 protein seemed to be important in all networks. We also looked for proteins containing C2H2 domain in the assembled networks. ZIC3, GLI1, GLI3, ZNF148, and PRDM16 were the ones present in both heart and limbs malformations of TE networks. Furthermore, in the DGE analysis after treatment with thalidomide, we observed that FANCB, ESCO2, and XRCC2 were downregulated and present both in heart and limbs networks. Through systems biology, we were able to point to different new proteins and genes, and selected specially EP300, which was important in all the analyzed networks, to be further evaluated in the TE teratogenicity.

Characterization of a Clinically and Biologically Defined Subgroup of Patients with Autism Spectrum Disorder and Identification of a Tailored Combination Treatment

Autism spectrum disorder (ASD) is a heterogeneous group of neurodevelopmental disorders (NDDs) with a high unmet medical need. The diagnosis of ASD is currently based on behavior criteria, which overlooks the diversity of genetic, neurophysiological, and clinical manifestations. Failure to acknowledge such heterogeneity has hindered the development of efficient drug treatments for ASD and other NDDs. DEPI (Databased Endophenotyping Patient Identification) is a systems biology, multi-omics, and machine learning-driven platform enabling the identification of subgroups of patients with NDDs and the development of patient-tailored treatments. In this study, we provide evidence for the validation of a first clinically and biologically defined subgroup of patients with ASD identified by DEPI, ASD Phenotype 1 (ASD-Phen1). Among 313 screened patients with idiopathic ASD, the prevalence of ASD-Phen1 was observed to be ~24% in 84 patients who qualified to be enrolled in the study. Metabolic and transcriptomic alterations differentiating patients with ASD-Phen1 were consistent with an over-activation of NF-κB and NRF2 transcription factors, as predicted by DEPI. Finally, the suitability of STP1 combination treatment to revert such observed molecular alterations in patients with ASD-Phen1 was determined. Overall, our results support the development of precision medicine-based treatments for patients diagnosed with ASD.

Strategic pathway analysis for dual management of epilepsy and comorbid depression: a systems biology perspective

Strategic pathway analysis for dual management of epilepsy and comorbid depression: a systems biology perspective

The Role of HSP90 and TRAP1 Targets on Treatment in Hepatocellular Carcinoma.

Hepatocellular Carcinoma (HCC) is the predominant form of liver cancer and arises due to dysregulation of the cell cycle control machinery. Heat Shock Protein 90 (HSP90) and mitochondrial HSP90, also referred to as TRAP1 are important critical chaperone target receptors for early diagnosis and targeting HCC. Both HSP90 and TRAP1 expression was found to be higher in HCC patients. Hence, the importance of HSP90 and TRAP1 inhibitors mechanism and mitochondrial targeted delivery of those inhibitors function is widely studied. This review also focuses on importance of protein-protein interactions of HSP90 and TRAP1 targets and association of its interacting proteins in various pathways of HCC. To further elucidate the mechanism, systems biology approaches and computational biology approach studies are well explored in the association of inhibition of herbal plant molecules with HSP90 and its mitochondrial type in HCC.

Sarcopenia as a Risk Factor for Alzheimer’s Disease: Genetic and Epigenetic Perspectives

Sarcopenia, defined as the age-associated loss of muscle mass and increased fragility with age, is increasing worldwide. The condition often precedes the development of Alzheimer’s disease, thereby decreasing the levels of mobility and physical activity in those affected. Indeed, the loss of muscle mass has, in some studies, been associated with an increased risk of Alzheimer’s disease and other dementias. However, a detailed understanding of the interplay between both conditions is not available and needs to be thoroughly addressed. In the following review, we focus on several genes, specifically APOE, BDNF, ACE, FTO, and FNDC5, that have been associated with both conditions. We also discuss the epigenetic regulation of each of these genes along with non-coding RNAs (ncRNAs) that may have a role in the development of both the sarcopenic and Alzheimer’s disease phenotypes. Finally, we assert that the application of systems biology will unravel the relationship between sarcopenia and Alzheimer’s disease and believe that the prevention of muscle loss in older age will reduce the incidence of debilitating cognitive decline.

HCMMD: systematic evaluation of metabolites in body fluids as liquid biopsy biomarker for human cancers.

Metabolomics is a rapidly expanding field in systems biology used to measure alterations of metabolites and identify metabolic biomarkers in response to disease processes. The discovery of metabolic biomarkers can improve early diagnosis, prognostic prediction, and therapeutic intervention for cancers. However, there are currently no databases that provide a comprehensive evaluation of the relationship between metabolites and cancer processes. In this review, we summarize reported metabolites in body fluids across pan-cancers and characterize their clinical applications in liquid biopsy. We conducted a search for metabolic biomarkers using the keywords ("metabolomics" OR "metabolite") AND "cancer" in PubMed. Of the 22,254 articles retrieved, 792 were deemed potentially relevant for further review. Ultimately, we included data from 573,300 samples and 17,083 metabolic biomarkers. We collected information on cancer types, sample size, the human metabolome database (HMDB) ID, metabolic pathway, area under the curve (AUC), sensitivity and specificity of metabolites, sample source, detection method, and clinical features were collected. Finally, we developed a user-friendly online database, the Human Cancer Metabolic Markers Database (HCMMD), which allows users to query, browse, and download metabolite information. In conclusion, HCMMD provides an important resource to assist researchers in reviewing metabolic biomarkers for diagnosis and progression of cancers.

Elucidating a genomic signature associated with behavioral and executive function after moderate to severe pediatric TBI: a systems biology informed approach

Introduction: There is significant unexplained variability in behavioral and executive functioning after pediatric traumatic brain injury (TBI). Prior research indicates that there are likely genetic contributions; however, current research is limited. The purpose of this study is to use a systems biology informed approach to characterize the genomic signature related to behavioral and executive functioning ∼12 months after moderate through severe TBI in children.Methods: Participants were from two prospective cohorts of children with severe TBI (Cohort #1) and moderate-severe TBI and an orthopedic injury (OI) group (Cohort #2). Participants included 196 children (n = 72 and n = 124 total from each respective cohort), ranging in age between 0–17 years at the time of injury. In total, 86 children had severe TBI, 49 had moderate TBI, and 61 had an OI. Global behavioral functioning assessed via the Child Behavior Checklist and executive function assessed via the Behavioral Rating Inventory of Executive Function at ∼ 12 months post injury served as outcomes. To test for a genomic signature, we compared the number of nominally significant (p < 0.05) polymorphisms associated with the outcomes in our systems biology identified genes to a set 10,000 permutations using control genes (e.g., not implicated by systems biology). We used the ToppFun application from Toppgene Suite to identify enriched biologic processes likely to be associated with behavioral and executive function outcomes.Results: At 12 months post injury, injury type (TBI vs OI) by polymorphism interaction was significantly enriched in systems biology selected genes for behavioral and executive function outcomes, suggesting these genes form a genomic signature. Effect sizes of the associations from our genes of interest ranged from .2–.5 for the top 5% of variants. Systems biology analysis of the variants associated with the top 5% effect sizes indicated enrichment in several specific biologic processes and systems.Discussion: Findings indicate that a genomic signature may explain heterogeneity of behavioral and executive outcomes after moderate and severe TBI. This work provides the foundation for constructing genomic signatures and integrating systems biology and genetic information into future recovery, prognostic, and treatment algorithms.

Random walk simulation by population dynamics P systems

AbstractPDP systems have been widely used for real-life applications, such as systems biology, ecosystems, physics or economy, among others. Complex systems related with these areas are simulated in the framework of Membrane Computing using objects and membranes that can represent entities or places in the real-life process. In physics, the study of a particle in different fluids, depending on their composition, is really interesting for several applications. A first approximation to this field is to think that particles move randomly in the available space, without any force that constrains their movements. This behavior is known as random walk, and it is used not only in physics but in economics, genetics, and ecology among other areas. In this paper, we introduce generic PDP systems for simulating the behavior of particles, both for one-dimensional spaces and for two-dimensional spaces, using different simulators to analyze the computational resources consumed.

Molecular Plant Physiology for Model Plants under Abiotic Stress Conditions

Extreme temperatures, drought, and high soil salinity are some of the significant abiotic stresses that can severely impact crop yields, posing a threat to global food production. Comprehensive studies on model plant species are crucial for understanding their biochemical, physiological, and molecular responses to abiotic stresses. Identifying stress response mechanisms and potential targets can aid in developing stress-tolerant crop varieties. Additionally, elucidating the functions of reactive oxygen species is essential for this research area. In model plants, the perception of abiotic stresses is a complex phenomenon that entails intricate interactions between hormones, gene regulation, and physiology. The presence of specific stress receptors and sensors contributes to this perception. Activating signaling pathways involves a cascade of events, starting with generating reactive oxygen species, then calcium signaling and MAP kinase signaling. Because of these processes, transcription factors and genes susceptible to stress are ultimately activated in the latter stages. It starts with a series of physiological and biochemical modifications, which entail adjustments in photosynthesis and the accumulation of osmoprotectants. We have gained significant insights from studying model plant stress responses, but there remain considerable challenges in effectively applying these findings to enhance crop resilience. These challenges contribute to reproducing the results across various species. These difficulties arise because of phenotypes, molecular mechanisms, and genetic differences. The utilization of model plants will persist in their crucial role as essential systems for unraveling the complexities of plant stress responses. They will play a vital role in overcoming present constraints, particularly in areas such as the mathematical modeling of plant physiology. The exploration of gene function across species can significantly contribute to efforts aimed at improving crops. The key to addressing threats to global food security and promoting crop stress resilience lies in adopting a multi-pronged approach that uses model plant systems.