Future Production Research Articles

Construction and Expression of Fc-FGF21 by Different Expression Systems and Comparison of Their Similarity and Difference with Efruxifermin by In Vitro and In Vivo Studies.

Non-alcoholic steatohepatitis (NASH) is a potential serious disease, which almost has no available medicine for effective treatment today. Efruxifermin is a bivalent Fc-FGF21 candidate drug developed by Akero Therapeutics that has shown promising results in preclinical and clinical trials for NASH and may be approved in future. However, it is produced by Escherichia coli (E. coli) expressing system, which has no glycosylation modifications and is hard to purify for inclusion body. Suspension mammalian cell expression systems, human embryonic kidney 293 (HEK293), and Chinese hamster ovary (CHO) are good choice for protein expression of biopharmaceutical use. In this report, the objective was to produce Fc-FGF21 by mammalian cell expression systems, which enabled necessary glycosylation modifications to occur on the Fc-FGF21 protein and was relatively easy for future large-scale production. We observed that the target protein Fc-FGF21 could be easily degraded in CHO system, such as CHOK1SV or CHOZN, and it was hard to purify, whereas it was more stable in the HEK293 expressing system. Then, similarity between Fc-FGF21 from E. coli and Fc-FGF21 from HEK293 was focused by in vitro and in vivo studies, and we observed no significant difference between the proteins expressed from the two different expressing systems, indicating that a biosimilar of Efruxifermin has been developed successfully. Proteomics analysis from in vivo study samples further identified some potential biomarkers or FGF21 related signaling pathways. Taken together, this study demonstrates a good example of how to develop and validate a biosimilar for therapeutic purposes. In future, more efforts, such as mutation to FGF21 or linking FGF21 with effective antibody to form dual targets, could be done to obtain more effective FGF21 analogs.

Salivary pH, but not conductivity, is an indicator of diarrhea in neonatal calves

Neonatal calf diarrhea is a frequent disease of calves and may result in dehydration and metabolic acidosis. The disease causes mortality and reduces growth and future productivity. Early identification of disease improves calf outcomes and thus there is increasing interest in technological methods for detecting disease. Dehydration leads to the blood becoming more concentrated and this can be measured using serum osmolality. Research in humans has shown that saliva conductivity is correlated with serum osmolality. Saliva conductivity may therefore offer a non-invasive opportunity to assess hydration status in calves. Furthermore, as blood pH is a prognostic indicator and there is ion exchange in the salivary ducts, saliva pH may act as an indicator of metabolic acidosis. This observational study aimed to assess the relationship of saliva conductivity and pH with the clinical and biochemical parameters of calves suffering from neonatal calf diarrhea. One hundred and forty-one dairy-bred calves were recruited onto the study at approximately 1 week of age. The health of the calves was assessed daily. Calves had blood and saliva samples taken weekly until 25 days of age or the development of neonatal calf diarrhea. When calves developed diarrhea, they were sampled for three consecutive days. Hematocrit, plasma total protein, saliva pH and saliva conductivity were measured at each sampling. Saliva pH and saliva conductivity were measured using portable meters (LAQUAtwin-pH-33 and LAQUAtwin-EC22). In a subset of 30 matched samples, serum proteins and electrolytes were also measured. Saliva conductivity was not associated with diarrhea or dehydration. Saliva pH was lower in calves with diarrhea, regardless of hydration status. The Lin’s concordance correlation coefficients between saliva variables and hematocrit and strong ion difference were negligible. Dehydrated calves with diarrhea had a higher hematocrit and albumin and the lowest sodium and SID. Calves with diarrhea and no dehydration had a lower plasma total protein. While saliva conductivity has been associated with measures of dehydration in humans, this does not appear to be the case in calves. Saliva pH has not previously been considered for disease detection; however as it is associated with diarrhea, further research is warranted.

The combined effects of climate, soil, and rhizospheric microorganisms determine the quality and suitable production zones of Stellaria dichotoma L. var. lanceolata Bge. in China

BackgroundStellaria dichotoma L. var. lanceolata Bge. (S. lanceolata) is a psammophytic plant endemic to the northwest region of China and has now developed into a cultivated economic crop. It is the original plant species used in traditional Chinese medicine as Yinchaihu. Recently, the lack of scientifically guided production zoning has exacerbated the arbitrary introduction and expansion of S. lanceolata cultivation, resulting in significant changes to its habitat and quality.MethodsThis study utilizes distribution data of wild S. lanceolata along with data from 33 environmental factors to analyze the primary habitat factors influencing the species' distribution using the Maxent model, simulating both current and future suitable production zones. Additionally, amplicon sequencing was employed to investigate changes in rhizospheric soil microorganisms across different cultivation sites and years. Furthermore, metabolomics, near-infrared spectroscopy, and the quantification of active ingredient content were used to assess the effects of various suitable zones on S. lanceolata.ResultsThe migration trends of S. lanceolata toward the central and eastern regions of Inner Mongolia revealed that elev, bio_4, bio_13, bio_11, and S_clay are the primary ecological and soil factors influencing suitability zoning, contributing a cumulative rate of 80.5%. The rhizosphere microbial environment shifted significantly from high to medium suitability habitats. As cultivation duration increased, the diversity of fungi and bacteria and the functional genera within the rhizosphere exhibited significant changes. Notably, there were substantial alterations in metabolic processes and substance accumulation during the transition from high to medium and low suitability zones, resulting in the identification of 281 and 370 differential metabolites, respectively. Additionally, the near-infrared spectral characteristics and active ingredient content of S. lanceolata in high suitability zones displayed distinct specificity. In particular, the contents of total flavonoids (2.772 mg·g−1), dichotomines B (0.057 mg·g−1), and quercetin-3-O-β-D-glucoside (0.312 mg·g−1) were notably higher, with the overall quality score surpassing that of other suitable zones. ConclusionThis study revealed the key climatic, soil, and rhizosphere microbial environmental factors influencing the quality formation of S. lanceolata and the selection of suitable production zones, offering guidance for sustainable development and production zone planning.Graphical

Prediction of Water-Richness Zoning of Weathered Bedrock Based on Whale Optimisation Algorithm and Random Forest

To effectively predict the water richness of weathered bedrock aquifers, the West First Plate area of the Hongliulin coal mine was taken as the study area, and 42 sets of pumping test borehole data from the weathered bedrock in the study area were used as training and testing samples. A total of five indicators related to the water richness of weathered bedrock, namely, the aquifer thickness, sand–base ratio, core take rate, degree of weathering, and lithological structure index, were selected. A prediction model for the water richness of weathered bedrock aquifers (WOA-RF) was subsequently proposed by combining the whale optimisation algorithm (WOA) and random forest (RF). This model can predict the water-richness level of weathered bedrock in an area with no pumping test data. The geological information from 98 sets of exploration boreholes in the study area was comprehensively used to achieve water-richness zoning of the weathered bedrock. The results indicated that the WOA is effective in optimising parameters and improving model performance. The accuracies of the optimal WOA-RF model in the training set and the test set were 93.1% and 92.3%, respectively. Compared with those of the single RF model, the accuracy, recall, and F1 value of the optimal WOA-RF model were increased by 11.3%, 18.2%, and 11%, respectively, and the differences before and after optimisation were obvious. A comparison and analysis of the predictive performance of each model revealed that the overall performance of the WOA-RF model was better than that of the other models. The weathered bedrock in the study area as a whole is weakly to moderately rich in water, and the predicted results are in good agreement with reality, which can provide a reference for future safe production in the West First Plate area.

The effectiveness of putative wearable repellent technologies to protect against mosquito biting and Aedes-borne diseases, and their economic impact.

Viruses transmitted by mosquitoes threaten the health of millions of people worldwide. There is an urgent need for new tools for personal protection to ensure that vulnerable individuals are protected from infectious bites when outdoors. Here, we test the efficacy of wash-in and spray-on repellents against Aedes aegypti. When applied as a treatment on clothing as well as skin, the novel repellent compound delta-undecalactone provided up to 100% protection initially, and over 50% bite prevention for more than 7 hours. Mathematical modelling indicated that if such a repellent, with 100% initial efficacy, were to be applied twice daily by 80% of the population, more than 30% of Zika virus infections could be averted in an outbreak scenario with a basic reproduction number R0 = 2.2. In a less severe outbreak (R0 = 1.6), the same repellent regimen could avert 96% of infections. If there was much lower uptake, with only 40% of people using the repellent twice per day, just 4% of Zika cases would be averted (outbreak R0 = 2.2). Similar results were found in other scenarios tested for dengue and chikungunya outbreaks. Our model can be extrapolated to other repellents and guide future product development, and provides support to the concept that effective repellents that are used regularly and appropriately could be cost-effective interventions to prevent ill health from arboviral diseases.

Merger of Single-Atom Catalysis and Photothermal Catalysis for Future Chemical Production.

Photothermal catalysis is an emerging field with significant potential for sustainable chemical production processes. The merger of single-atom catalysts (SACs) and photothermal catalysis has garnered widespread attention for its ability to achieve precise bond activation and superior catalytic performance. This review provides a comprehensive overview of the recent progress of SACs in photothermal catalysis, focusing on their underlying mechanisms and applications. The dynamic structural evolution of SACs during photothermal processes is highlighted, and the current advancements and future perspectives in the design, screening, and scaling up of SACs for photothermal processes are discussed. This review aims to provide insights into their continued development in this rapidly evolving field.

Envisioning the incorporation of Generative Artificial Intelligence into future product design education: Insights from practitioners, educators, and students

The advancement of Generative Artificial Intelligence (GenAI) has introduced diverse opportunities and challenges in product design, demanding a corresponding evolution in design education. This study investigated GenAI’s roles in product design and its implications for design education through semi-structured interviews with 24 participants, comprising practitioners, educators, and students, who had hands-on experience leveraging GenAI in design. Through thematic analysis, we identified critical functions of GenAI in product design, including generating inspiration, exploring potential solutions, conducting prototyping, performing evaluations, finalizing detailed outputs, and serving as design materials, presenting both opportunities and challenges. Moreover, fully incorporating GenAI in product design requires adaptation in educational initiatives, including capability development, curriculum content, and assessment methods. This study provides insights from a multi-stakeholder perspective, revealing the roles of GenAI in product design and advancing educational curricula to prepare the next-generation designers to be proficient in effectively leveraging GenAI for innovation.

Projections of standardised energy indices in future climate scenarios

Abstract Renewable energy is becoming an increasingly important component of energy systems. However, renewable energy production is heavily dependent on the prevailing weather conditions, which are changing as a result of climate change. It is therefore necessary to build energy systems that are robust to energy shortages caused by weather-dependent changes to energy demand and renewable energy production. To design such systems, we must monitor how changes in the climate are expected to influence future energy production and demand; this is important for policymakers to decide when, where, and by how much renewable energy installed capacities should be increased, for example. In this paper, we study the behaviour of standardised energy indices in future European climate projections, and use this to monitor how characteristics of energy production droughts in Europe are expected to change in the future. We use these results to make suggestions regarding how the energy mix should be adapted in the future to decrease the risk of energy production droughts.

Overview of Operational Global and Regional Ocean Colour Essential Ocean Variables Within the Copernicus Marine Service

The Ocean Colour Thematic Assembly Centre (OCTAC) of the Copernicus Marine Service delivers state-of-the-art Ocean Colour core products for both global oceans and European seas, derived from multiple satellite missions. Since 2015, the OCTAC has provided global and regional high-level merged products that offer value-added information not directly available from space agencies. This is achieved by integrating observations from various missions, resulting in homogenized, inter-calibrated datasets with broader spatial coverage than single-sensor data streams. OCTAC enhanced continuously the basin-level accuracy of essential ocean variables (EOVs) across the global ocean and European regional seas, including the Atlantic, Arctic, Baltic, Mediterranean, and Black seas. From 2019 onwards, new EOVs have been introduced, focusing on phytoplankton functional groups, community structure, and primary production. This paper provides an overview of the evolution of the OCTAC catalogue from 2015 to date, evaluates the accuracy of global and regional products, and outlines plans for future product development.

Use of multiple reference data sources to cross-validate gridded snow water equivalent products over North America

Abstract. We use snow course and airborne gamma data available over North America to compare the validation of gridded snow water equivalent (SWE) products when evaluated with one reference dataset versus the other. We assess product performance across both non-mountainous and mountainous regions, determining the sensitivity of relative product rankings and absolute performance measures. In non-mountainous areas, product performance is insensitive to the choice of SWE reference dataset (snow course or airborne gamma): the validation statistics (bias, unbiased root mean squared error, and correlation) are consistent with one another. In mountainous areas, the choice of reference dataset has little impact on relative product ranking but a large impact on assessed error magnitudes (bias and unbiased root mean squared error). Further analysis indicates the agreement in non-mountainous regions occurs because the reference SWE estimates themselves agree up to spatial scales of at least 50 km, comparable to the grid spacing of most available SWE products. In mountain areas, there is poor agreement between the reference datasets, even at short distances (< 5 km). We determine that differences in assessed error magnitudes result primarily from the range of SWE magnitudes sampled by each method, although their respective spatiotemporal distribution and elevation differences between the reference measurements and grid centroids also play a role. We use this understanding to produce a combined reference SWE dataset for North America, applicable to future gridded SWE product evaluations and other applications.

Developing A Risk Control System for Fintech Products Using Big Data and Real-Time Analysis Technology

Big data technology has revolutionized the financial sector, significantly impacting the design and operation of future financial products. This paper explores the use of big data technology in risk control in financial products, examining its potential benefits and challenges in product design. By briefly introducing the operation logic of big data, this paper analyzes the application of big data in financial products for risk control and the challenges it faces. The study reveals that big data technology enhances the efficiency of financial technology companies in internal management and decision-making, while significantly reducing systemic risk in their financial product design. Big data technology has exacerbated the conflict between traditional financial institutions and fintech companies, as well as the interest conflict between fintech companies, users, and regulatory authorities. Therefore, Big data financial products not only need to improve their information processing methods and information analysis methods internally, but also need to deal with the conflicts between their users, issuers, and financial regulatory authorities and with the traditional financial sector.

Heterologous Biosynthesis of Taxifolin in Yarrowia lipolytica: Metabolic Engineering and Genome-Scale Metabolic Modeling.

Taxifolin, also known as dihydroquercetin (DHQ), is a flavonoid recognized for its potent antioxidant properties and a wide range of biological activities, including anti-tumor, antiviral, and immunomodulatory effects. Conventional extraction and chemical synthesis methods for taxifolin are often limited by low yields and associated environmental concerns. In this study, we investigated the heterologous biosynthesis of taxifolin in Yarrowia lipolytica through a combination of metabolic engineering and genome-scale metabolic modeling (GSM), complemented by flux balance analysis (FBA). We engineered Yarrowia lipolytica by introducing key biosynthetic genes and successfully synthesized taxifolin using naringenin (NAR) as a substrate, chosen for its low cost. Fermentation experiments demonstrated an optimal taxifolin yield of 10% at a substrate concentration of 200mg/L naringenin, with a maximum yield of 26.4mg/L taxifolin at 1g/L naringenin. To further enhance production, we applied a marker-free Cre-loxP-based gene integration method, allowing stable genomic integration of key genes, which increased taxifolin yield to 34.9mg/L at 1g/L naringenin. Additionally, intermediate metabolites eriodictyol (ERI) and dihydrokaempferol (DHK) accumulated to concentrations of 89.2mg/L and 21.7mg/L, respectively. Furthermore, we integrated metabolic data into a GSM and applied FBA to optimize the taxifolin biosynthetic pathway. Through Pareto frontier analysis, sensitivity analysis, flux variability analysis, and single gene deletion simulations, we identified key genetic modifications that significantly enhanced taxifolin yield. Overexpression of GND1 and IDP2 increased yields by 94% and 155%, respectively, while knockout of LIP2 led to a 46% increase. Using tri-baffled shake flasks to improve oxygen supply resulted in a 120% yield increase, whereas YPG medium decreased yield by 59%, validating our model's accuracy. To ensure stable and efficient gene expression, we integrated multi-copy constructs into the ribosomal DNA (rDNA) locus of Yarrowia lipolytica, doubling taxifolin production. These results demonstrate the effectiveness of GSM and FBA in addressing bottlenecks in microbial taxifolin biosynthesis and provide a basis for future optimization and large-scale production.

A moving target: trade-offs between maximizing carbon and minimizing hydraulic stress for plants in a changing climate.

Observational evidence indicates that tree leaf area may acclimate in response to changes in water availability to alleviate hydraulic stress. However, the underlying mechanisms driving leaf area changes and consequences of different leaf area allocation strategies remain unknown. Here, we use a trait-based hydraulically enabled tree model with two endmember leaf area allocation strategies, aimed at either maximizing carbon gain or moderating hydraulic stress. We examined the impacts of these strategies on future plant stress and productivity. Allocating leaf area to maximize carbon gain increased productivity with high CO2, but systematically increased hydraulic stress. Following an allocation strategy to avoid increased future hydraulic stress missed out on 26% of the potential future net primary productivity in some geographies. Both endmember leaf area allocation strategies resulted in leaf area decreases under future climate scenarios, contrary to Earth system model (ESM) predictions. Leaf area acclimation to avoid increased hydraulic stress (and potentially the risk of accelerated mortality) was possible, but led to reduced carbon gain. Accounting for plant hydraulic effects on canopy acclimation in ESMs could limit or reverse current projections of future increases in leaf area, with consequences for the carbon and water cycles, and surface energy budgets.

Improving Iron Content in Sustainable Mycoprotein Production through Seawater Fermentation

The growing global population and rising protein demand are straining freshwater resources. Fusarium venenatum (Fv) mycoprotein offers a sustainable protein alternative, with environmental efficiency and potential health benefits. However, its low iron content remains a concern, especially for vegetarians and vegans. This study introduces a sustainable approach, employing seawater as a fermentation medium for Fv production. Our analysis reveals that mycoprotein derived from SEA Fv exhibits elevated levels of sodium and calcium, with a notably high iron content (2.2 mg/100g wet weight). The sodium content, while 3.31 times higher than in non-seawater fermentation, remains within recommended daily intake parameters. No plasticizers or heavy metals were detected in the SEA Fv cell body, minimizing long-term toxicity risks from seawater use. A unique metabolite, dihydroorotic acid, was identified from an in-house library of 774 metabolites, serving as an internal biomarker for seawater-based production methods. An acute safety study condensing 600g of SEA Fv to simulate high mycoprotein digestion showed no effects on key physical behaviors or major organs, including the heart and lungs. This positions the product as a viable protein alternative with enhanced iron content, highlighting seawater-based fermentation as a sustainable method for future food production and industry progress.

Time-varying stock return correlation, news shocks, and business cycles

The cross-sectional average of the pairwise correlations between U.S. stock returns is considered as a measure of risk to aggregate wealth priced by the stock market. We show that this measure predicts future U.S. output growth at a horizon of one to four years. A stronger average correlation of stock returns foreshadows significantly lower future output growth, even when controlling for some other widely used financial predictors. An innovation to average correlation gives rise to macroeconomic dynamics that resemble negative news about future total factor productivity (TFP) in a vector autoregression. TFP news shocks thus appear to be a key source of aggregate risk priced into stocks.

Influence of sonication-assisted fermentation on the physicochemical features and antioxidant activities of yogurts fortified by polyphenol-rich pineapple peel powder with varied chemical profiling

This study investigated the effects of pineapple peel powder with varied chemical profiles and sonication-assisted polyphenol biotransformation during fermentation on the quality characteristics of yogurt products. It aimed at exploring the feasibility of sonication-assisted fermentation to enhance the physicochemical properties, control post-acidification, and improve antioxidant activities in yogurts fortified with polyphenol-rich pineapple peel powder. Targeted analysis showed that polyphenol-rich pineapple dietary fiber obtained by ultrasonication-assisted extraction (NPFU) exhibited the slowest rates of acidification, highest antioxidant capacity, and lowest degree of whey separation at 21.67 %. Sonication pretreatments significantly increased transformation of free phenolic acids derived from pineapple peel fiber during fermentation, particularly increasing the accumulation of ferulic acid, caffeic acid and 5-hydroxyflavone, revealing the positive effects of sonication-mediated fermentation in promoting the hydrolysis of conjugated phenolics into free fractions. Yogurts fortified with pineapple peel fiber displayed significantly higher antioxidant activities (p < 0.05) compared to those with pineapple peel whole powder, corresponding with the increased free phenolics. Non-targeted metabolomics analysis was employed to explore the mechanisms underlying the alleviated post-acidification by sonication-assisted fermentation during storage. Metabolomic profiling revealed that the bioactive components from pineapple peel extract significantly influenced the metabolism pathways of lactic acid bacteria particularly involving galactose metabolism, glycerophospholipid metabolism, closely associated with the acid production of the strains and the regulation of the post-acidification rates of yogurt during storage. These results confirmed the potential of ultrasound-assisted fermentation combined with the addition of pineapple dietary fiber to enhance yogurt quality, providing an innovative tool to develop future yogurt products with high marketability.

Fully biologic endothelialized-tissue-engineered vascular conduits provide antithrombotic function and graft patency.

Tissue-engineered vascular conduits (TEVCs), often made by seeding autologous bone marrow cells onto biodegradable polymeric scaffolds, hold promise toward treating single-ventricle congenital heart defects (SVCHDs). However, the clinical adoption of TEVCs has been hindered by a high incidence of graft stenosis in prior TEVC clinical trials. Herein, we developed endothelialized TEVCs by coating the luminal surface of decellularized human umbilical arteries with human induced pluripotent stem cell (hiPSC)-derived endothelial cells (ECs), followed by shear stress training, in flow bioreactors. These TEVCs provided immediate antithrombotic function and expedited host EC recruitment after implantation as interposition inferior vena cava grafts in nude rats. Graft patency was maintained with no thrombus formation, followed by complete replacement of host ECs. Our study lays the foundation for future production of fully biologic TEVCs composed of hiPSC-derived ECs as an innovative therapy for SVCHDs.

Optimizing Well Trajectories for Enhanced Oil Production in Naturally Fractured Reservoirs: Integrating Particle Swarm Optimization with an Innovative Semi-Analytical Model Framework

Summary Well trajectory optimization is a crucial component in the drilling engineering of naturally fractured reservoirs. The complex heterogeneity and anisotropy of such reservoirs significantly affect the pressure drop distribution within the well and, consequently, the oil well’s output, impacting the economic benefits of the well. Therefore, optimizing the well segment trajectory is key to efficient reservoir development. However, traditional well trajectory optimization methods primarily focus on geological structures and drilling engineering costs, often overlooking future production benefits of the oil well. This paper proposes a new method that first establishes a semi-analytical production prediction model capable of describing complex well trajectories. Although the semi-analytical model has unique advantages in well trajectory description, it typically treats the reservoir as a homogeneous entity, which complicates handling complex reservoir characteristics. To overcome this limitation, we combined optimization algorithms and neural networks to construct a framework for addressing reservoir heterogeneity (Semianalytical Model Framework for Unconventional Wells in Heterogeneous Reservoirs, USAMF-HR), enhancing the semi-analytical model’s ability to describe reservoir heterogeneity. Building on this framework, we applied the particle swarm optimization (PSO) algorithm and introduced constraints on the rationalization of initial well trajectories, as well as limits on particle movement speed and displacement, with the maximization of net present value (NPV) as the objective function, to optimize well trajectory coordinates. Through specific case analysis, the reasonableness and practicality of this method have been verified. The results show that this method can quickly and effectively plan the optimal well trajectory, significantly increasing productivity while reducing costs.

Crystallization of CoWB ternary boride in nickel-based metallic glass

The crystallization kinetics of CoWB ternary boride were investigated through non-isothermal differential scanning calorimetry experiments, using a Ni-based metallic glass precursor as the starting material. The effects of isothermal heat treatment temperature on the phase evolutions were also systematically studied. The results showed that the melt crystallization and glass crystallization behaviors of the alloy differ from each other. The continuous heating transformation diagram plotted from non-isothermal analyses is consistent with the results of isothermal heat treatments. A broad ternary boride precipitation zone was demonstrated, involving the gradual precipitation of CoWB crystals. Avrami exponent values for the early crystallization stage showed that the crystallization mechanism of CoWB is governed by the interface-controlled three-dimensional growth mechanism, and nucleation rate is high. As the crystallization progresses, a diffusion-controlled growth occurs and the nucleation rate decreases. This study offers insights into the heat treatment of CoWB-reinforced nickel matrix nanocomposites, benefiting future research and industrial production processes.

Proteomics: An Essential Tool to Study Plant-Specialized Metabolism

Plants are a valuable source of specialized metabolites that provide a plethora of therapeutic applications. They are natural defenses that plants use to adapt and respond to their changing environment. Decoding their biosynthetic pathways and understanding how specialized plant metabolites (SPMs) respond to biotic or abiotic stress will provide vital knowledge for plant biology research and its application for the future sustainable production of many SPMs of interest. Here, we focus on the proteomic approaches and strategies that help with the study of plant-specialized metabolism, including the: (i) discovery of key enzymes and the clarification of their biosynthetic pathways; (ii) study of the interconnection of both primary (providers of carbon and energy for SPM production) and specialized (secondary) metabolism; (iii) study of plant responses to biotic and abiotic stress; (iv) study of the regulatory mechanisms that direct their biosynthetic pathways. Proteomics, as exemplified in this review by the many studies performed to date, is a powerful tool that forms part of omics-driven research. The proteomes analysis provides an additional unique level of information, which is absent from any other omics studies. Thus, an integrative analysis, considered versus a single omics analysis, moves us more closely toward a closer interpretation of real cellular processes. Finally, this work highlights advanced proteomic technologies with immediate applications in the field.