Artificial intelligence, particularly machine learning, has profoundly reshaped drug discovery, addressing longstanding challenges such as exorbitant costs and protracted timelines. Conventional approaches often exceed $2.6 billion per drug over 12-15 years, with attrition rates nearing 90%; AI mitigates these through advanced target identification, high-throughput virtual screening, and generative molecule design. The present review synthesizes pivotal studies of several years drawn from PubMed, Scopus, and leading journals, including ACS Omega and Nature Reviews. It encompasses supervised quantitative structure-activity relationship models, neural networks, graph convolutional networks, and generative adversarial networks for de novo drug design. Emphasis is placed on machine learning's capacity to process vast omics and cheminformatics datasets, with critical attention to how data quality, measurement uncertainty, and analytical method variability fundamentally constrain predictive accuracy. In practice, AI empowers scientists by automating hypothesis generation, exemplified by AlphaFold's structural predictions and enabling early toxicity forecasting or drug repurposing, yet these computational advances remain dependent on rigorous experimental validation through orthogonal analytical techniques. A distinctive contribution of this review lies in its systematic integration of analytical chemistry as the foundational discipline underpinning reliable AI predictions. We present a conceptual framework, the Analytical Integrity Spectrum, that traces the bidirectional relationship between analytical measurements and computational models, emphasizing how measurement uncertainty, data quality, and experimental validation collectively determine the trustworthiness of AI-driven discoveries. The chemistry-focused synthesis distinguishes the present work from computational reviews by critically examining representative case studies of AI-discovered compounds, including their molecular structures, scaffolds, and experimental outcomes. This review provides a tangible assessment of AI's impact on medicinal chemistry. The review further examines AI's emerging application to climate-resilient supply chains, forecasting disruptions from environmental events while emphasizing the analytical monitoring essential for maintaining pharmaceutical quality during transport. Persistent challenges, including dataset biases, activity cliff insensitivity, and validation uncertainty, are traced to their analytical origins. Future prospects encompass federated learning, quantum-accelerated simulations, and standardized analytical data formats that preserve measurement integrity for machine learning. Ultimately, AI equips researchers with transformative tools for accelerated, equitable therapeutic innovation, provided that computational predictions remain grounded in the experimental reality that analytical chemistry provides.
The development of magnetoelectric multiferroic materials, which combine and couple (ferro)magnetism and ferroelectricity in the same material, are discussed from a chemist's perspective. The chemical challenges that must be overcome to combine (ferro)magnetism and ferroelectricity are highlighted and the developments in crystal chemistry that have enabled identification of new multiferroics are outlined. The chemical applications of multiferroic materials are described and open questions that are particularly amenable to chemical solutions are discussed.
As a crucial high-performance thermosetting material, EP exhibits significant limitations in high-end applications due to its high crosslink density, resulting in brittleness, poor impact resistance, flammability, and lack of self-healing capability. CD and its CP derivatives offer a novel paradigm for optimising EP properties and enabling functional innovation through their unique 'hydrophobic interior-hydrophilic exterior' cavity structure and dynamically reversible host-guest interactions. This paper systematically reviews the functionalisation progress of CD and CP systems in epoxy resins, covering three aspects: an introduction to CD and CP; the synthesis of CD and CP derivatives for EP applications; and the application performance and mechanism of action of CD and CP in EP.
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Covering: This review covers literature from 2015 to present.It is widely recognised that there is a significant gap between bacterial natural product potential and detected/described products. As such, there are several recent reviews on elicitation strategies for natural products discovery, which are often laboratory focused. Recently, a move to more ecology-focused approaches to understand the function of metabolites in nature and what impacts expression has been a growing trend. In this review, we aim to capture work done that goes beyond laboratory conditions and address ecological studies focussed on what impacts bacterial chemistry, covering both abiotic and biotic influences. We aim to touch on the impact of biodiversity loss, changes in ecosystems and future climate parameters and the implications this will have on natural products chemistry and biodiscovery efforts, the scale and consequences of which are not known.
Parkinson's disease (PD) significantly affects patients' quality of life. Natural plant therapies, characterized by holistic, multi-target regulatory effects, have demonstrated unique value in managing complex diseases, particularly through regulating autophagy, inhibiting neuroinflammation, and reducing oxidative stress. Combined with their favourable safety profile-especially lower hepatotoxicity and nephrotoxicity-they represent an important direction in anti-PD drug development. This review systematically examines the ethnopharmacological applications of natural plants that regulate autophagy in PD treatment, summarizing current progress and challenges to inform traditional Chinese medicine (TCM) modernization and anti-PD drug development. This study investigates natural herbal therapies for PD, focusing on their regulatory mechanisms of autophagy. Primary sources included traditional medical classics and ethnomedicinal literature, supplemented by data from online databases such as PubMed, China National Knowledge Infrastructure (CNKI), Web of Science, and Wanfang. A systematic search was conducted using keywords including "PD," "autophagy," "regulatory mechanisms," "medicinal plants," "TCM compound preparations," "single herbal extracts," and "active compounds" to identify relevant studies published in recent years. Original research articles (in vitro, in vivo, or clinical) and high-quality reviews with mechanistic data involving autophagy in PD were included. Topical-independent literature, thesis, conference abstracts, books, case reports, and commentaries were excluded. Only articles published in English or Chinese were considered. Incorporating medicinal plants into PD management offers significant advantages in multi-target regulation and safety. However, a critical examination reveals several complexities. While modulating multiple autophagy-related pathways provides a theoretical advantage over single-target drugs, this broad-spectrum activity raises concerns about target specificity and off-target effects, which remain poorly characterized. Current evidence largely relies on correlational observations rather than direct mechanistic validation, leaving uncertainty about whether these compounds genuinely engage key autophagy targets under physiological conditions. Regarding safety, although centuries of traditional use of TCM compound preparations imply tolerability, assuming medicinal plants are inherently safer than Western drugs is problematic, as many constituents exhibit dose-dependent toxicity, and the lack of rigorous long-term trials limits generalizability. Furthermore, the prevailing reductionist approach-isolating active components for mechanistic studies-may overlook synergistic interactions inherent in herbal formulations, thus failing to capture their full therapeutic potential. Bridging traditional knowledge and modern evidence-based medicine requires not only advanced target identification techniques but also a holistic framework that respects herbal therapy's foundations while subjecting it to the same scientific scrutiny as conventional treatments. Although medicinal plants have garnered considerable attention for the treatment of PD, claims of their "significant clinical efficacy" should be approached with caution. Current evidence is primarily derived from basic research or observational studies and lacks validation through rigorous randomized controlled trials. Moreover, while autophagy regulation remains a prominent area of research, the multi-component and multi-target nature of compound formulations means their mechanisms cannot be explained by a single pathway. The transition from traditional use to evidence-based treatment continues to face challenges, including standardization, quality control, and dosage optimization. Therefore, although medicinal plants show potential, their therapeutic value must be confirmed through more rigorous methodologies and large-scale clinical trials.
Monoclonal antibodies (mAbs) targeting the Calcitonin Gene-Related Peptide (CGRP) pathway are safe and effective treatments for migraine prevention. However, the high cost of these novel therapies has led to reimbursement policies requiring patients to try multiple traditional preventives before access. Here, we evaluate the real-world effectiveness of onabotulinumtoxinA (BoNT-A) as first-line treatment and describe the sequential transition to anti-CGRP monoclonal antibodies in patients who did not achieve sufficient response, within the Polish chronic migraine treatment program. In this retrospective cohort study, we included 94 patients with chronic migraine who received BoNT-A treatment according to the PREEMPT protocol every 3-4 months for 12 months as first-line treatment. Headache diaries and documentation were used to evaluate reductions in monthly headache days (MHD) and MIDAS scores. Patients were divided into two subgroups based on their response after three BoNT-A administrations: insufficient response (≤ 50% reduction in MHD) and sufficient response (> 50% reduction in MHD). We included 94 patients (93.62% female, age range 22-66 years). Following three BoNT-A injection cycles, 70 patients (74.47%) did not achieve the ≥ 50% response threshold and were sequentially transitioned to fremanezumab per programme protocol. In the insufficient response group, MHD decreased from 18.26 ± 4.46 to 13.90 ± 4.64 days (t(69) = 15.49, p < 0.001), representing a 23.9% reduction, while MIDAS scores decreased from 93.77 ± 41.80 to 61.69 ± 35.56 (t(69) = 10.22, p < 0.001, 34.2% reduction). In the sufficient response group (n = 24, 25.53%), MHD decreased from 17.83 ± 1.95 to 7.83 ± 1.83 days after 3 injections (56.1% reduction, t(23) = 31.97, p < 0.001), and further to 4.13 ± 1.77 days after 5 injections (76.7% reduction, t(22) = 32.59, p < 0.001). Pearson's correlation analysis revealed moderate positive correlation between MHD and MIDAS after 3 injections (r = 0.392, p < 0.001), which weakened substantially after 5 injections (r = 0.082, p = 0.691). Baseline MIDAS scores were numerically higher in the sufficient response group (116.62 ± 61.12 vs. 93.77 ± 41.80, t(92) = 2.04, p = 0.044); however, given the outcome-dependent nature of group allocation, this difference should not be interpreted causally or as a prognostic marker. For patients who did not experience sufficient improvement after the third BoNT-A administration, treatment was changed to fremanezumab. Our real-world data demonstrate that 74.47% of patients with chronic migraine did not achieve the ≥ 50% MHD reduction threshold after three onabotulinumtoxinA injections, supporting the current Polish therapeutic algorithm that allows sequential transition to anti-CGRP monoclonal antibodies for insufficient responders.
The present study addressed the complex nature of fatigue in soccer, examining its physical, psychological, neuromuscular, and metabolic dimensions. It evaluated the impact of these different types of fatigue on players' performance, highlighting the importance of comprehensive fatigue-management strategies for enhancing performance and reducing injury risk among soccer players. The primary aim of this study was to investigate the effects of various types of fatigue on performance of male soccer players across different competitive levels, through a systematic review and meta-analysis of randomized controlled trials. A total of 37 randomized controlled trials involving male soccer players were included, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to assess the multifaceted impacts of fatigue. Key findings revealed that neuromuscular fatigue had the highest mean effect size (0.63), with substantial consistency across studies (95% CI: 0.45-0.80, I2 = 99.79%). Physical and metabolic fatigue both showed a mean effect size of 0.38, though they differed in variability; metabolic fatigue demonstrated considerable heterogeneity (I2 = 98.73%), reflecting diverse physiological responses, while physical fatigue showed moderate consistency (I2 = 98.20%). Psychological fatigue had a significant impact on performance (mean effect size: 0.57), with variability (I2 = 97.08%) suggesting context-dependent effects. These results underscore the necessity of a multimodal approach that integrates physical, metabolic, neuromuscular, and psychological interventions to optimize soccer performance and mitigate injury risk. Practical implications include the adoption of targeted recovery strategies such as inter-set recovery intervals and whole-body vibration techniques, as well as the implementation of mental resilience and cognitive training to manage psychological fatigue. Such strategies are essential for developing individualized training and recovery protocols that enhance athletic performance and support long-term career sustainability.
Congenital malformations (CMs) are the leading cause of infant mortality. Still, the aetiology remains unknown in 70% of cases. The most accepted hypothesis is that hereditary and environmental elements concur in altering embryo-fetal development. Recently, the role of the environment has been emphasised.Women are exposed to several xenobiotics during pregnancy. This review aims to study the available literature on the exposure of pregnant women to pesticides through drinking water to see if there is any evidence of correlation to the onset of any kind of congenital anomalies. We will conduct a systematic literature review in The Cochrane Library, Embase and PubMed for studies published between 1 January 2005 and 31 January 2026. Articles will be included if they examine pregnant women as the study population, exposure to pesticide active ingredients and metabolites present in drinking water, and any type of CM in their children as the main outcome. The screening of title, abstract and full text as well as the data extraction will be conducted independently through two investigators. A third investigator will resolve any eventual conflicts. Each included study will be evaluated according to the NIH's quality assessment tools. Grading of Recommendations Assessment, Development and Evaluation approach will be used for summarising and assessing certainty in the bodies of evidence produced by the review. This study is registered with PROSPERO, CRD420251063011. The completed work will be published in a scientific journal for dissemination. Due to the nature of the study, an ethical approval is not necessary since no patient data or other information will be directly collected.
Computational fluid dynamics (CFD)-based numerical calculation of fractional flow reserve (FFRCT) and instantaneous wave-free ratio (iFRCT) is a crucial non-invasive technology for assessing myocardial ischemia. Their diagnostic accuracy depends on precisely calculating epicardial coronary stenosis resistance and coronary microcirculatory resistance. However, conventional CFD models face two main limitations. First, they assume rigid vessel walls, failing to capture how different plaque types affect stenosis resistance through neural regulation-induced vasodilation changes. Second, the presence of compensatory mechanisms in coronary microcirculation leads to inaccuracies in calculating microcirculatory resistance. These physiological oversimplifications, combined with the low computational efficiency of traditional CFD, compromise diagnostic accuracy and hinder real-time clinical application. This paper systematically reviews existing FFRCT/iFRCT computational models, their limitations, and current research on model improvement and computational efficiency. Given the acute nature and high mortality of myocardial infarction, future efforts should focus on establishing high-fidelity cardiovascular simulation models by integrating multi-modal clinical data. Combining artificial intelligence with digital twin technology could enable dynamic early warning for acute myocardial ischemia and infarction in daily life applications. This direction represents a promising future development path for non-invasive diagnostic technologies and holds significant clinical value.
Plant-based proteins are novel nutrient sources that are widely available in nature and cost-effective to produce compared to animal proteins, while contributing to lower greenhouse gas emissions and reducing risks to both environmental and human health. Thus, the present work comprehensively reviews plant-based proteins as an alternative to conventional / animal proteins. The review article highlights why plant proteins should be considered a novel nutrient source and an alternative to animal proteins. Various plant protein-derived sources and their corresponding extraction methods, along with their associated limitations, are reviewed. In addition, the review article highlights plant protein modification methods, interfacial behavior, protein structure, interactions, and functional properties. The effects of different physical and environmental conditions and factors on the functional and nutritional properties of plant proteins are also discussed. In addition, the challenges associated with plant proteins, such as allergenicity, consumer acceptance and perceptions, food safety, regulatory issues, and technological challenges, are also explored.
In current years, the elimination of heavy metals from wastewater systems has become a global concern due to persistent adverse effects on ecosystems and human health. Adsorption technique has gained much attention for the removal of heavy metals from aquatic environments because of advantages like great efficiency, cost-effectiveness and simple operation. Biochar, a carbonaceous material, has been extensively applied for removing heavy metals from aqueous systems due to its low cost and eco-friendly nature. However, numerous existing studies are focusing on elimination of heavy metals from wastewater by using biochar as an adsorbent, but very few emphasize on re-utilization of spent biochar, which is a crucial concern. This is because if spent biochar is discharged or landfilled untreated into the environment can increase the risk of secondary pollution thus harming the ecosystem and mankind. Therefore, the present paper critically reviews the recent applications of biochar in removing heavy metals from wastewater along with potential electrochemical applications of metals loaded biochar in developing super-capacitors or other energy storage devices. The review also comprehensively discussed the characteristics of different biomass feedstock, methods used for biochar production and various physical, chemical and biological biochar engineering techniques. The key mechanisms involved in adsorption of heavy metals from aquatic systems through biochar have been reviewed. The paper also highlighted technical barriers, benefits-cost analysis, market status, future directions and scope of biochar as an adsorbent. Hence, the review will assist the successful development of highly efficient biochar-based adsorption techniques for eliminating heavy metals from aqueous environments.
Sustainable carbon management through innovative strategies is essential to address the dual crises of climate change and resource scarcity. Electrochemical CO2 reduction reaction (CO2RR) and biomass electrooxidation (BEO) represent two promising pathways for converting CO2 and renewable biomass into valuable chemicals. While previous reviews have broadly covered replacing the energy-intensive anodic oxygen evolution reaction (OER) for CO2RR, they often lack an integrated analysis of the complementary challenges and design principles for CO2RR & BEO coupling system. This review fills this gap by critically analyzing their core key limitations, notably the high energy cost of OER in CO2RR and the low economic return from the hydrogen evolution reaction (HER) in BEO; meanwhile, the design principles, e.g., potential matching, pH and product compatibility, for the couple system are proposed. Moreover, coupled systems that effectively exploit the complementary nature of CO2RR & BEO are systematically presented, including CO2RR paired with the oxidation of biomass-derived molecules and other substrates (e.g., glucose, alcohols, aldehydes, methane, chlorides, sulfides) and BEO coupled with other cathodic reductions (e.g., furfural, 4-nitrophenol). Meanwhile, their compatibility in term of potential, pH and product were analyzed and compared. Finally, future research directions are outlined, with emphasis on innovative catalysts design, system-level optimization, and scalable implementation. This work provides a focused perspective on advancing sustainable resource utilization through electrochemical coupling.
The blood-brain barrier (BBB) is a highly specialized interface that preserves neural homeostasis but severely limits the entry of therapeutic agents, posing a major challenge for central nervous system (CNS) drug development. While invasive approaches such as intracerebral injection and focused ultrasound can transiently bypass the barrier, their complexity and safety concerns restrict clinical applicability, particularly in chronic conditions. Non-invasive strategies that exploit endogenous transport mechanisms-carrier-mediated uptake, adsorptive-mediated transcytosis (AMT), and receptor-mediated transcytosis (RMT)-may offer a safer solution. Within this framework, brain shuttles have emerged as molecular vectors designed to cooperate with endothelial biology rather than disrupt it. These include antibodies, proteins, small molecules, and peptides, each with distinct advantages and limitations. Among them, peptides stand out for their versatility, manufacturability, and chemical tunability. Advances in solid-phase synthesis, non-natural modifications, and rational design have enabled peptides to achieve a balance between uptake efficiency and release beyond the endothelium. Their modular nature supports conjugation to diverse payloads, including small molecules, proteins, nucleic acids, and nanoparticles, while maintaining functional integrity. Peptide shuttles also offer broader receptor targeting and compatibility with multiple administration routes, positioning them as a cornerstone of future CNS delivery platforms. This chapter provides a mechanistic overview of the BBB, reviews invasive and non-invasive delivery strategies, and introduces the concept and evolution of brain shuttle peptides. It sets the stage for subsequent discussions on discovery methodologies, chemical optimization, validation models, and translational pathways, highlighting the promise of peptide-enabled systems to transform therapeutic access to the brain.
Persistent toxic substances (PTS), including heavy metals, persistent organic pollutants (POPs), and persistent, mobile, and toxic/very persistent and very mobile (PMT/vPvM) substances present an increasing menace to soil health, alimentary systems, atmospheric cleanliness as well as human health. Despite the large amount of literature on each of the individual groups of contaminants, there is still no unified model that connects the dynamics of the soil-atmosphere environment, bioaccumulation in the food chain, new detection techniques, and policy measures. This review presents an interdisciplinary synthesis of dynamics in the PTS in the agricultural environment, explicitly incorporating (i) historic contaminants and emerging PMT/vPvM chemicals, (ii) soil-crop-livestock-human transfer pathways, and (iii) the state-of-the-art remediation and monitoring technologies into a single management framework. We critically evaluated conventional remediation methods alongside next-generation methods, such as engineered consortia of microorganisms, synergistic phytotransformation of plants and microbes, biochar-assisted immobilization, nanosensor-based detection, IoT-based soil sensing, precision agriculture, machine-learning-driven risk prediction, and blockchain-based traceability. Contrary to the previous reviews, which only take into account the remediation, detection, and policy separately, this study presents a systems-based approach, which integrates technological innovation, sustainable agronomic practices, and multilayered governance tools (such as the Stockholm Convention, REACH, and national soil action plans). We highlight the fact that the combination of smart agricultural technology and regenerative land management will help reduce the accumulation of PTS and maintain productivity, especially in resource-scarcity settings. The review outlines the research gaps, including contaminant-microbiome interactions, longitudinal deterioration of ecosystem services, and socioeconomic barriers to technology adoption. We propose a transdisciplinary roadmap that aligns environmental toxicology, soil science, public health, and policy innovation to mitigate PTS and safeguard food security. This integrative approach provides a strategic framework for advancing sustainable management of persistent toxic substances in agricultural systems. This study looks at persistent toxic substances (PTS), harmful chemicals like some pesticides, industrial pollutants, and heavy metals that do not easily break down in the environment. Because they linger in soil, water, air, and food, they can move through the food chain and affect both ecosystems and people.In this study, the authors reviewed recent research and real-world cases to explain where PTS come from (e.g., farming chemicals, industrial waste, plastics), how they spread (air, water, and soil), and what health problems they can cause (such as hormone disruption, breathing issues, nerve damage, and cancer). They also examined solutions, from traditional cleanup methods to newer, nature-based options.
Oral fluid has attracted increasing interest as an alternative biological matrix for monitoring pharmaceutical compounds in clinical and forensic toxicology. Its noninvasive nature, simple collection procedures, and suitability for repeated sampling make it particularly attractive for large-scale drug screening, medical diagnosis, long-term treatment monitoring, and point-of-care applications. Compared with blood sampling, oral fluid collection is better accepted by patients and does not require trained personnel, facilitating its use in decentralized or real-time testing scenarios. In addition, drug concentrations in oral fluid frequently reflect the pharmacologically active unbound fraction of compounds, which may enhance its clinical relevance for individualized dosing and evaluation of therapeutic response. Several studies have reported meaningful correlations between drug concentrations measured in oral fluid and those determined in blood (plasma or serum) for different therapeutic classes, including antiepileptics, antidepressants, analgesics, antibiotics, and immunosuppressants. These characteristics support the growing interest in oral fluid as a useful matrix for therapeutic drug monitoring strategies aimed at optimizing treatment while reducing the risk of adverse effects. This review summarizes and critically discusses recent developments in analytical approaches for the detection of pharmaceutical compounds acting on the central nervous system in oral fluid and their potential application in drug monitoring. Oral fluid (saliva) is increasingly being used as an alternative to blood for measuring medicines in the body. Collecting saliva is simple, painless, and does not require specialized training, making it easier to use in many settings, including routine medical care and large-scale testing. Because samples can be taken frequently without discomfort, saliva testing is especially useful for monitoring patients over time. In many cases, the amount of a drug found in saliva reflects the active portion of the drug in the body. This means it may provide useful information about how well a treatment is working and help guide dose adjustments for individual patients. Research has shown that, for several types of medicines—such as those used to treat epilepsy, depression, pain, infections, and organ transplant rejection—drug levels in saliva are often related to levels found in blood. Overall, saliva testing shows promise as a practical and patient-friendly approach for monitoring medications. This article reviews recent scientific advances in how drugs can be measured in saliva and discusses how this method could be used to improve treatment and reduce unwanted side effects.
To meet demand for bioactive, homogeneously modified peptides for both fundamental research and therapeutic development, synthetic methods that are programmable, broadly applicable and inherently sustainable are urgently needed. The mild reaction conditions and precise tunability of electrochemical transformations provide appealing opportunities to carefully navigate the rich redox-active landscape of canonical and non-canonical amino acid functionalities. Modern technological breakthroughs in synthetic electro-organic chemistry are further expanding capabilities, propelling the field of electrochemical peptide modifications into an era of accelerating innovation. This Review highlights recent advances (2020-present) in electrochemical peptide synthesis and residue-specific modifications in a graphically rich format that emphasizes the expanding diversity of available electrochemical strategies and their broader compatibility with complex peptide substrates. Outstanding challenges and opportunities for further innovation are discussed.
Natural food pigments primarily originate from two sources: chemical synthesis and plant-derived production. With the rapid advancement of society and technology, there is a growing demand for environmentally friendly and healthy food options. Consequently, the demand for safe, nontoxic, and sustainable sources of natural pigments has risen sharply. Natural pigments are biosynthesized during the growth and metabolic processes of plant tissues, and compounds derived from these pigments exhibit a wide range of biological activities that are beneficial to human health and disease treatment. However, due to their inherent instability and low abundance, increasing research efforts have been directed toward the bioengineering of natural pigment production. This review classifies natural pigments into five major structural categories: pyrrole, isoprenoids, quinones, phenols, and betalains. Unlike previous reviews that focused on a single pigment component or specific application fields, this review systematically integrates the biosynthetic pathways, synthetic biology strategies, pharmacological activity mechanisms, and application progress in medicine, health care, and cosmetics of natural pigment-containing medicinal materials. It emphasizes their multiple potentials as "functional pigments" in the development of natural medicines. Additionally, the review combines emerging technologies such as metabolic engineering, artificial intelligence (AI)-assisted screening, and biosensing, proposing a cross-disciplinary development path from basic synthesis to high-value applications and demonstrating strong systematicity and a forward-looking nature. It provides a new integrated perspective for innovative research on natural pigment components.