Global Analysis Research Articles

Modeling the dynamics of tumor–immune response: a reaction–diffusion approach integrating chemotherapy effects and global sensitivity analysis

Modeling the dynamics of tumor–immune response: a reaction–diffusion approach integrating chemotherapy effects and global sensitivity analysis

A comprehensive mathematical analysis of fractal–fractional order nonlinear re-infection model

In recent times, various real word problems including infectious diseases, engineering problems, and chemical processes, etc are modelled by using differential equations with fractals and fractional orders. The mentioned area provides a powerful tool to investigate the aforesaid problems from different perspectives like analysis, numerical investigation, and qualitative theory. Similarly, one of the global issue is devoted to re-infection of viral diseases like COVID-19. The said behaviour has produced very saviour impact on human life worldwide. Also, this is very critical for health system of a country as well as for its economics situation. To study the aforesaid phenomenon of re-infection, a hybrid type fractal–fractional three compartments model is formulated. The basic results related to boundedness, positivity, equilibrium points, basic reproductive number, and sensitivity analysis of the basic threshold are included in the theoretical aspect. Additionally, the Volterra–Lyapunov approach is used to establish both local and global stability analysis under fractals and fractional derivative. Furthermore, utilizing techniques from numerical functional analysis and fixed point theory, the existence and Hyers–Ulam stability of the solutions are also examined. A numerical algorithm based on Lagrange’s interpolation polynomials is extended to simulate the results of various compartments. Graphical interpretations corresponding to different fractals–fractional order values are presented. For verification of our numerical results, a comparison is provided between the real and simulated data. Here it should be kept in mind that the differential operator of fractals–fractional order is considered with Mittag-Leffler kernel. The mentioned operator is more general among the available fractals fractional differential operators in literature.

Exploration of potential biomarkers for prurigo nodularis based on plasma-metabolome analysis.

Prurigo nodularis (PN) is a chronic and debilitating skin disease with severe itching that negatively impacts patients' quality of life and mental state. However, the treatment options for PN remain limited. Global metabolomics analysis can offer effective information on energy metabolism, pathogenesis and potential diagnostic biomarkers. No study on metabolomic analysis of PN has been reported. To further understand the mechanisms of PN and analyse the plasma metabolite profiles in patients with PN. Targeted-metabolome analysis of 306 metabolites in plasma from 18 patients with PN and 19 healthy controls was performed using Liquid Chromatography-tandem Mass Spectrometer analysis. We identified 31 differential metabolites. Most acylcarnitines, long-chain fatty acids, alpha-aminobutyric acid, hydroxybutyric acid and lactic acid among these metabolites were up-regulated in patients with PN; in contrast, glucaric acid, suberic acid, bile acid derivatives and most amino acids were down-regulated. Positive correlations exist between glucaric acid and itching severity and acylcarnitines and insomnia. Suberic acid and the Investigator's Global Assessment (IGA) scores correlate negatively. Metabolite variation reflects the dysregulation of energy metabolism and chronic systematic inflammation in PN. Several metabolites, such as glucaric acid, suberic acid and acylcarnitines, merit further study as potential biomarkers of disease severity in PN.

Beyond tradition: charting a greener future for cassava starch industry using multi-criteria decision-making

Cassava, a staple food crop, is widely used for starch production, but its inconsistent supply, price volatility, and substantial waste generation pose challenges to the cassava industrial market's growth. This study aims to identify a sustainable biorefinery pathway by optimizing conventional cassava starch plants (business-as-usual, BAU) for economic and environmental benefits. Four scenarios were evaluated: animal feed from peel waste (Scenario 1), fungal protein from thippi waste (Scenario 2), fish feed from digested wastewater (Scenario 3), and conversion of all waste streams into animal feed, fish feed, and fungal protein (Scenario 4). Scenario 4 emerged as the best pathway using the multi-criteria decision-making (MCDM) approach, with a performance score of 0.282. Despite the highest energy consumption (18.91 MWh), Scenario 4 was favored for producing four value-added products alongside starch, yielding the highest profit at USD 8.85 million. In contrast, profits for BAU, Scenario 1, Scenario 2, and Scenario 3 were 1.91, 2.30, 5.01, and USD 8.79 million, respectively. Waste valorization in Scenarios 1, 2, 3, and 4 resulted in CO2 avoidance of 36.5., 42.6., 21.7, and 57.45 t CO2eq., respectively. However, producing value-added products increased energy consumption by 13, 73, 7, and 74% compared to BAU (4.58 MWh). The global warming potential analysis showed negative values for scenarios 2 and 4, at -436 and -434 kg CO2eq./t root, respectively. This study highlights the potential of a biorefinery approach for sustainable cassava starch production, providing insights for future research and policy development.

53188 A Global Analysis of Cutaneous Lymphomatoid Reactions after COVID-19 Vaccination

53188 A Global Analysis of Cutaneous Lymphomatoid Reactions after COVID-19 Vaccination

Discussion on a Fire Risk Index based on Minas Gerais’ cultural heritage fire safety regulation

The Global Risk Analysis method, introduced by Gouveia (2006) and incorporated into Technical Instruction No. 35 of the Minas Gerais Fire Department, has undergone updates over the years. This study analyzed the different versions of the GRA method to identify changes, their impacts on results, and current limitations. A trend of reduced risk and increased safety was observed, suggesting an overestimation of the safety coefficient and inadequate building protection. It is recommended to improve the scope, balance of attributes, and documentation of the method to keep it current and reliable.

Precipitation and temperature primarily determine the reptile distributions in China

Reptiles make up one‐third of tetrapods, however they are often omitted from global conservation analyses. Understanding the determinants of reptile distribution is the foundation for reptile conservation research. We assembled a dataset on the distribution of 231 reptile species (nearly 50% of recorded species in China). We then investigated the association of species range filling (the proportion of observed ranges compared to species potential climate distributions) with climate, range size, topography and human activity, using three regression methods. At the species level, we found the most primary factors influencing the recent distribution pattern of reptiles across China were the mean annual precipitation (MAP) and the mean annual temperature (MAT). In contrast, human activity came in last. Similarly, at a spatial level, MAP and MAT were still the most important factors. Geographically, the south and east of China support the highest reptile diversity, partially due to high precipitation. Contrary to the prevailing notion that reptile distributions are primarily shaped by human activities, our study re‐emphasizes the importance of climate in determining reptile distribution. It accentuates the necessity of integrating climate variables into future animal conservation strategies in China. Our findings also offer valuable insights for informing conservation practices, including the site planning of natural reserves and national parks, as well as monitoring of environmental factors in protected areas.

Re-routing MAP kinase signaling for penetration peg formation in predator yeasts.

Saccharomycopsis yeasts are natural organic sulfur auxotrophs due to lack of genes required for the uptake and assimilation of sulfate/sulfite. Starvation for methionine induces a shift to a predatory, mycoparasitic life strategy that is unique amongst ascomycetous yeasts. Similar to fungal plant pathogens that separated from Saccharomycopsis more than 400 million years ago, a specialized infection structure called penetration peg is used for prey cell invasion. Penetration pegs are highly enriched with chitin. Here we demonstrate that an ancient and conserved MAP kinase signaling pathway regulates penetration peg formation and successful predation in the predator yeast S. schoenii. Deletion of the MAP kinase gene SsKIL1, a homolog of the Saccharomyces cerevisiae ScKSS1/ScFUS3 and the rice blast Magnaporthe oryzae MoPMK1 genes, as well as deletion of the transcription factor SsSTE12 generate non-pathogenic mutants that fail to form penetration pegs. Comparative global transcriptome analyses using RNAseq indicate loss of the SsKil1-SsSte12-dependent predation response in the mutant strains, while a methionine starvation response is still executed. Within the promoter sequences of genes upregulated during predation we identified a cis-regulatory element similar to the ScSte12 pheromone response element. Our results indicate that, re-routing MAP-kinase signaling by re-wiring Ste12 transcriptional control towards predation specific genes contributed to the parallel evolution of this predacious behaviour in predator yeasts. Consequently, we found that SsSTE12 is dispensable for mating.

Global stability analysis, stabilization and synchronization of an SEIR epidemic model

In this paper, we investigate an SEIR epidemic model in which recruitment is assumed to be regulated by a constant function. The SEIR model is a widely-used epidemiological framework that categorises the population into four distinct groups: Susceptible, Exposed, Infectious, and Removed. It employs a system of differential equations to describe the transitions of individuals among these groups, making it a valuable tool for understanding and modelling the dynamics of infectious diseases. Mathematical analysis is used to study the dynamic behaviour of this model. We first determine the basic reproduction number, denoted as R 0 , which governs the dynamics of the SEIR model. Our findings reveal that when R 0 is less than 1, the unique disease-free equilibrium is asymptotically stable, and there is no endemic equilibrium. However, when R 0 exceeds 1, the disease-free equilibrium becomes unstable, and a unique, asymptotically stable endemic equilibrium emerges. Furthermore, by constructing appropriate Lyapunov functions, we have studied the global asymptotic stability of the two equilibrium points. On the other hand, we have used the backstepping method to design a control law that stabilises the SEIR model towards the disease-free equilibrium, which means the eradication of the disease from the target population. Next, we have used the same method to synchronise the SEIR drive system and the SEIR response system. This method is used to stabilise the synchronisation error dynamics arising from the mismatch between the drive and response systems. Finally, we presented numerical simulations to illustrate the theoretical results.

Global 13C tracing and metabolic flux analysis of intact human liver tissue ex vivo.

Liver metabolism is central to human physiology and influences the pathogenesis of common metabolic diseases. Yet, our understanding of human liver metabolism remains incomplete, with much of current knowledge based on animal or cell culture models that do not fully recapitulate human physiology. Here, we perform in-depth measurement of metabolism in intact human liver tissue ex vivo using global 13C tracing, non-targeted mass spectrometry and model-based metabolic flux analysis. Isotope tracing allowed qualitative assessment of a wide range of metabolic pathways within a single experiment, confirming well-known features of liver metabolism but also revealing unexpected metabolic activities such as de novo creatine synthesis and branched-chain amino acid transamination, where human liver appears to differ from rodent models. Glucose production ex vivo correlated with donor plasma glucose, suggesting that cultured liver tissue retains individual metabolic phenotypes, and could be suppressed by postprandial levels of nutrients and insulin, and also by pharmacological inhibition of glycogen utilization. Isotope tracing ex vivo allows measuring human liver metabolism with great depth and resolution in an experimentally tractable system.

Modeling fisheries and carbon sequestration ecosystem services under deep uncertainty in the ocean twilight zone.

Mesopelagic fishes are a vital component of the biological carbon pump and are, to date, largely unexploited. In recent years, there has been an increased interest in harvesting the mesopelagic zone to produce fish feed for aquaculture. However, great uncertainties exist in how the mesopelagic zone interacts with the climate and food webs, presenting a dilemma for policy. Here, we investigate the consequences of potential policies relating to mesopelagic harvest quotas with a dynamic social-ecological modeling approach, combining system dynamics and global sensitivity analyses informed by participatory modeling. Our analyses reveal that, in simulations of mesopelagic fishing scenarios, uncertainties about mesopelagic fish population dynamics have the most pronounced influence on potential outcomes. The analysis also shows that prioritizing the development of the fishing industry over environmental protection would lead to a significantly higher social cost of climate change to society. Given the large uncertainties and the potential large impacts on oceanic carbon sequestration, a precautionary approach to developing mesopelagic fisheries is warranted.

Prokaryotic-virus-encoded auxiliary metabolic genes throughout the global oceans.

Prokaryotic microbes have impacted marine biogeochemical cycles for billions of years. Viruses also impact these cycles, through lysis, horizontal gene transfer, and encoding and expressing genes that contribute to metabolic reprogramming of prokaryotic cells. While this impact is difficult to quantify in nature, we hypothesized that it can be examined by surveying virus-encoded auxiliary metabolic genes (AMGs) and assessing their ecological context. We systematically developed a global ocean AMG catalog by integrating previously described and newly identified AMGs and then placed this catalog into ecological and metabolic contexts relevant to ocean biogeochemistry. From 7.6 terabases of Tara Oceans paired prokaryote- and virus-enriched metagenomic sequence data, we increased known ocean virus populations to 579,904 (up 16%). From these virus populations, we then conservatively identified 86,913 AMGs that grouped into 22,779 sequence-based gene clusters, 7248 (~ 32%) of which were not previously reported. Using our catalog and modeled data from mock communities, we estimate that ~ 19% of ocean virus populations carry at least one AMG. To understand AMGs in their metabolic context, we identified 340 metabolic pathways encoded by ocean microbes and showed that AMGs map to 128 of them. Furthermore, we identified metabolic "hot spots" targeted by virus AMGs, including nine pathways where most steps (≥ 0.75) were AMG-targeted (involved in carbohydrate, amino acid, fatty acid, and nucleotide metabolism), as well as other pathways where virus-encoded AMGs outnumbered cellular homologs (involved in lipid A phosphates, phosphatidylethanolamine, creatine biosynthesis, phosphoribosylamine-glycine ligase, and carbamoyl-phosphate synthase pathways). Together, this systematically curated, global ocean AMG catalog and analyses provide a valuable resource and foundational observations to understand the role of viruses in modulating global ocean metabolisms and their biogeochemical implications. Video Abstract.

Extraction of transhelicity worm-gear distributions and opportunities at the Electron-Ion Collider in China

We present a global analysis of the transhelicity worm-gear distribution function, g1T⊥, by fitting the longitudinal-transverse double-spin asymmetry data of the semi-inclusive deep inelastic scattering. The analysis is performed within the framework of transverse momentum dependent factorization and evolution. It is found that the u-quark favors a positive distribution and the d-quark favors a negative distribution, which is consistent with previous model calculations and phenomenological extractions. Based on the fit to existing world data, we also study the impact of the proposed Electron-Ion Collider in China and conclude that it can significantly improve the precision of the worm-gear distribution function and hence enhance our understanding of nucleon spin structures. Published by the American Physical Society 2024

Single-cell new RNA sequencing reveals principles of transcription at the resolution of individual bursts.

Analyses of transcriptional bursting from single-cell RNA-sequencing data have revealed patterns of variation and regulation in the kinetic parameters that could be inferred. Here we profiled newly transcribed (4-thiouridine-labelled) RNA across 10,000 individual primary mouse fibroblasts to more broadly infer bursting kinetics and coordination. We demonstrate that inference from new RNA profiles could separate the kinetic parameters that together specify the burst size, and that the synthesis rate (and not the transcriptional off rate) controls the burst size. Importantly, transcriptome-wide inference of transcriptional on and off rates provided conclusive evidence that RNA polymerase II transcribes genes in bursts. Recent reports identified examples of transcriptional co-bursting, yet no global analyses have been performed. The deep new RNA profiles we generated with allelic resolution demonstrated that co-bursting rarely appears more frequently than expected by chance, except for certain gene pairs, notably paralogues located in close genomic proximity. Altogether, new RNA single-cell profiling critically improves the inference of transcriptional bursting and provides strong evidence for independent transcriptional bursting of mammalian genes.

Decision-Making Model Supporting Eco-Innovation in Energy Production Based on Quality, Cost and Life Cycle Assessment (LCA)

Currently, the development of renewable energy products (RES) encourages the search for innovative solutions that take into account key criteria from the point of view of their sustainable development. Despite efforts in this area, there is a lack of approaches and tools to support this process. Therefore, the aim of the research was to develop a decision-making model supporting eco-innovation in products based on the key criteria of sustainable development: quality (customer satisfaction with use), environmental impact in the life cycle (LCA), and the cost of investment incurred in the product development. The functioning of the model was based on the following factors: (i) obtaining the voice of customers (VoC) and processing it into product criteria as part of the development of alternative production solutions (prototypes), (ii) prospective quality assessment and subsequent life cycle assessment of prototypes, (iii) cost analysis taking into account both quality and environmental criteria, (iv) interpretation of results and search for eco-innovative product solutions. Development decision-making is additionally supported by techniques implemented in the model, e.g., the CRITIC method, the LCA method with Ecoinvent database in OpenLCA, the CEA method, and the morphology method. The model was illustrated and tested for photovoltaic (PV) panels, after which a global sensitivity analysis was performed in Statistica. The test results showed that the main factor that influenced the PV development decisions was the investment cost, followed by quality (customer satisfaction) and then environmental impact in LCA.

Survivorship program including long-term toxicities and quality-of-life development over 10 years in a randomized trial in operable stage III non-small-cell lung cancer (ESPATUE).

Over 40% stage-III non-small-cell lung cancer (NSCLC) patients (pts) experience 5-year survival following multimodality treatment. Nevertheless, little is known about relevant late toxicities and quality-of-life (QoL) in the further long-term follow-up. Therefore, we invited pts from our randomized phase-III trial (Eberhardt et al., Journal of Clinical Oncology 2015) after 10 years from diagnosis to participate within a structured survivorship program (SSP) including follow-up imaging, laboratory parameters, cardio-pulmonary investigations, long-term toxicity evaluations and QoL questionnaires. Of 246 pts initially accrued, 161 were considered potentially resectable following the induction therapy and were randomized (80 to arm A: definitive chemoradiation; 81 to arm B: definitive surgery; 85 not randomized for different reasons; group C). 31 from 37 pts still alive after 10 years agreed to the SSP (13 in A; 12 in B; 6 in C). Clinically relevant long-term toxicities (grade 3 and 4) were rarely observed with no signal favoring any of the randomization arms. Furthermore, available data from the global QoL analysis did not show a signal favoring any definitive locoregional approach (Mean QoL in SSP A pts: 56.41/100, B pts: 64.39/100) and no late decline in comparison to baseline and early 1-year follow-up. This is the first comprehensive SSP of very late survival follow-up reported in stage-III NSCLC treated within a randomized multimodality trial and it may serve as important baseline information for physicians and pts deciding for a locoregional treatment option.

Reliability-centered availability collaborative optimization allocation approach for machine tools

The availability of computer numerical control (CNC) machine tools is a comprehensive reflection of reliability and maintainability. To ensure the availability requirements of products, it is necessary to allocate the availability indicators of the entire machine to all units. Traditional methods based on reliability allocation or maintainability allocation ignore the coupling relationships among them, which cannot comprehensively improve the availability level of machine tools. Therefore, in this paper, a availability collaborative optimization allocation model for CNC machine tools is proposed to maximize the availability under the optimal combination of failure rate and repair rate. Firstly, a two-stage reliability allocation model based on different allocation mechanisms is established by taking the Function-Motion-Action (FMA) decomposition tree as the allocation path. In the first stage, the allocation weights are determined based on global sensitivity analysis. In the second stage, the reliability optimization allocation model based on Copula function is established. Then, with reliability as the center, an availability collaborative optimization allocation model constrained by maintainability is constructed, and the non-dominated sorting genetic algorithm II (NSGA-II) algorithm is used to solve the model. Finally, a CNC gear milling machine is taken as an example to verify the rationality and effectiveness of the method on product availability requirements under collaborative allocation.

Conserved amino acid residues and gene expression patterns associated with the substrate preferences of the competing enzymes FLS and DFR.

Flavonoids, an important class of specialized metabolites, are synthesized from phenylalanine and present in almost all plant species. Different branches of flavonoid biosynthesis lead to products like flavones, flavonols, anthocyanins, and proanthocyanidins. Dihydroflavonols form the branching point towards the production of non-colored flavonols via flavonol synthase (FLS) and colored anthocyanins via dihydroflavonol 4-reductase (DFR). Despite the wealth of publicly accessible data, there remains a gap in understanding the mechanisms that mitigate competition between FLS and DFR for the shared substrate, dihydroflavonols. An angiosperm-wide comparison of FLS and DFR sequences revealed the amino acids at positions associated with the substrate specificity in both enzymes. A global analysis of the phylogenetic distribution of these amino acid residues revealed that monocots generally possess FLS with Y132 (FLSY) and DFR with N133 (DFRN). In contrast, dicots generally possess FLSH and DFRN, DFRD, and DFRA. DFRA, which restricts substrate preference to dihydrokaempferol, previously believed to be unique to strawberry species, is found to be more widespread in angiosperms and has evolved independently multiple times. Generally, angiosperm FLS appears to prefer dihydrokaempferol, whereas DFR appears to favor dihydroquercetin or dihydromyricetin. Moreover, in the FLS-DFR competition, the dominance of one over the other is observed, with typically only one gene being expressed at any given time. This study illustrates how almost mutually exclusive gene expression and substrate-preference determining residues could mitigate competition between FLS and DFR, delineates the evolution of these enzymes, and provides insights into mechanisms directing the metabolic flux of the flavonoid biosynthesis, with potential implications for ornamental plants and molecular breeding strategies.

A Prospective Study on the Economic Effects of China-GCC FTA - Simulation and Analyses Based on GTAP Model

In the context of the "Belt and Road" initiative, this paper is based on the China-GCC FTA negotiations, and uses the Global Trade Analysis Model (GTAP) to construct six scenarios of tariff reduction in key sectors and reduction of technical barriers to trade (TBT) between China and the GCC countries, and to assess the impacts of the construction of the FTA on the economies of China and related countries. The paper shows that increased trade liberalization has a positive economic impact on the China-GCC FTA. At the same time, tariff changes in the manufacturing and oil and gas industries dominated the tariff reductions, but the reduction of technical barriers to trade (TBT) has a particularly significant impact compared to tariffs. Bilateral trade will contribute more remarkably to China's continued economic growth than in the GCC countries. Reductions in trade barriers will effectively boost production demand in Chinese and GCC countries, contributing imports, exports and output, which will benefit both economies, specially, China's trade surpluses increasing particularly in various sectors.

Variance-based global sensitivity analysis of the performance of a proton exchange membrane water electrolyzer

This study is threefold objective. First, a nonlinear one-dimensional steady-state simulation model for hydrogen production from proton exchange membrane water electrolyzer (PEMWE) is established. The model comprehensively addresses activation, diffusion overpotentials and ohmic potential drop, and particularly incorporating Nafion membrane properties in the presence of liquid water. The model is enhanced by analyzing the hydrogen crossover, introducing corresponding diffusion equations to evaluate Faraday efficiency. The model accurately quantifies voltage efficiency, hydrogen production rate and specific energy consumption, and it is validated with published experimental data found in the scientific literature. Second, a variance-based global sensitivity analysis (GSA) on the model, is employed as a metric to assess the impact of operating conditions and material characteristics on three objective functions: the hydrogen production rate; the voltage efficiency and the specific energy consumption. Third, to support the GSA analysis, genetic algorithm (GA) technique is performed to maximize hydrogen production rate while minimizing specific energy consumption. In the course of this novel investigation, it was discerned that the number of cells, the cross-sectional area of the electrolyzer, the current density and temperature all exerted a significant impact on the three objective functions. This combined approach GSA-GA provides a thorough exploration of parameter influences and an efficient optimization strategy for enhancing the model's performance. These findings provide valuable insights that can guide analysis of the performance and the optimization of the PEMWE system.