Extract optimization of Ulva lactuca L. and biological activities of optimized extracts (2025)

Background

Algae are microscopic or macroscopic organisms that can photosynthesize and are found in both freshwater and saltwater ecosystems and are considered one of the cornerstones of life. In our study, the biological activities of extracts produced under the extract conditions that provided the highest biological activity of Ulva lactuca L. were determined.

Methods

Two different methods, Response Surface Method (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA) integration were used for optimization. In this context, the optimum extract conditions were determined as 54.940 ˚C temperature, 6.513h, 42.109 ethanol/water ratio according to the RSM method and 56.286 ˚C temperature, 7.2793h, 36.8625 ethanol/water ratio according to ANN-GA. The antioxidant activities of the optimized extracts were evaluated by Rel Assay kits, DPPH and FRAP methods. Anticholinesterase activities were determined by testing against acetylcholinesterase and butyrylcholinesterase enzymes. In addition, antiproliferative effects were examined in A549 lung cancer cell line and phenolic compound contents were analyzed by LC-MS/MS.

Results

As a result of the analyzes, it was seen that the extract obtained from the conditions recommended by ANN-GA exhibited higher activities. Optimized extracts of U. lactuca were found to have potential in terms of antioxidant activities. The highest total antioxidant value was determined as 6.272 ± 0.024 mmol/L. In addition, it was determined that extracts of U. lactuca produced under optimum conditions showed strong cytotoxic effects against A549 lung cancer cell line. In addition, gallic acid, 4-hydroxybenzoic acid, caffeic acid, vanillic acid, syringic acid, quercetin and kaempferol were found in the extracts of the algae produced under optimum conditions. The highest detected compound was caffeic acid. In addition to all these properties, it was seen that U. lactuca has anticholinesterase potential in our study.

Conclusion

In conclusion, optimized extracts of U. lactuca attract attention with their antioxidant and cytotoxic activities as well as anticholinesterase potential and can be considered as a potential source for cancer treatment and management of neurological diseases.

In addition to being a rich source of nutrients for health, seaweeds are also of interest as an environmentally friendly and sustainable food alternative. In terms of nutrition, they are beneficial to human health due to their protein, dietary fiber, vitamins (especially B12, C and E) and minerals (iodine, magnesium, calcium) content. In addition, they have antioxidant and anti-inflammatory properties thanks to bioactive components such as polyphenols and flavonoids. These properties make seaweed not only a part of a healthy diet, but also a valuable source for functional foods and pharmaceutical products [1, 2]. In recent years, antimicrobial and anticancer effects of seaweeds have also been emphasized. For example, extracts of Ulva lactuca and Gracilaria spp. species have shown potential in the prevention and treatment of various diseases. In addition, the use of bioactive compounds obtained from algae in food supplements, pharmaceuticals and cosmetics is rapidly increasing [3, 4]. In addition, Nori (Porphyra spp.), Wakame (Undaria pinnatifida) and Kombu (Laminaria spp.) are among the species commonly consumed in Asian cuisine. These species are used in dishes such as soup, salad and sushi, and are also processed as gelling agents and stabilizers in the food industry [5, 6]. In this context, in our study, the antioxidant, anticholinesterase and antiproliferative activities of the extracts produced under optimum conditions that maximize the biological activities of U. lactuca and the phenolic contents of these extracts were determined.

Ulva lactuca is a type of green algae commonly found in marine ecosystems, known as “sea lettuce”. This alga, which has a thin, wavy leaf-like structure, usually grows to 20–30cm in length and is easily recognized by its bright green color. It grows on seashores, especially in tidal areas, clinging to stones and rocks. It is widely found in tropical and temperate climates and is important for ecological balance. This photosynthetic algae is an important part of the food chain in aquatic ecosystems and also attracts attention with its various biological activities [7, 8]. U. lactuca, which is very rich in terms of nutritional value, stands out as part of a healthy diet with its high protein and fiber content. It is especially rich in minerals such as vitamin C, vitamin B12, iodine, magnesium and calcium. With these properties, it offers health benefits such as strengthening the immune system, supporting digestion and regulating energy metabolism [9, 10]. This algae is used in both food and biotechnological applications. U. lactuca, which is frequently preferred in soups, salads and spices in Asian cuisine, is a sustainable food source. It also contributes to the agricultural sector by being used as organic fertilizer and animal feed. It is also evaluated in environmentally friendly applications such as biofuel production and wastewater treatment [11]. Recent studies have shown that this species contains bioactive substances such as phenolic compounds, polyphenols and flavonoids, and that these substances have antioxidant, antimicrobial and anticancer properties. Therefore, the importance of U. lactuca is increasing in terms of both health and industrial potential [10].

The aim of this study was to optimize the extraction conditions of U. lactuca L. to determine the biological activities of its extracts, focusing on antioxidant, anticholinesterase, and antiproliferative effects, as well as identifying the phenolic compounds present, in order to assess its potential for cancer treatment and neurological disease management.

The algae samples used in the study were collected from İskenderun (Turkey). The algae samples was identified by Dr. Nuh Korkmaz (N.K-227). The moss samples are kept in the Laboratory of the Biology Department of Osmaniye Korkut Ata University.

Extraction procedure method

The extraction process was designed following a full factorial experimental approach, with three parameters—extraction temperature, extraction time, and ethanol/water ratio—evaluated at three levels each. A total of 27 experiments were conducted using the Gerhardt SOX-414 device under varying conditions: extraction temperatures of 45°C, 55°C, and 65°C; extraction times of 5, 10, and 15h; and ethanol/water ratios of 0%, 50%, and 100%. The resulting data were optimized using both the Response Surface Method (RSM) and an artificial intelligence-based approach integrating Artificial Neural Networks and Genetic Algorithms (ANN-GA).

RSM

In this study, optimization was carried out using the Response Surface Method (RSM). The independent variables included extraction temperature, extraction time, and ethanol/water ratio, while the response variable was the total antioxidant activity (TAS) of the extract. The optimization process utilized Design Expert 13 software, employing a second-order polynomial response model.

where \(\:{Y}_{k}\) was response variable (\(\:{Y}_{i}\) was TAS value of extract); \(\:{x}_{i}\) was coded process variables (\(\:{x}_{1}\) was extraction temperature, \(\:{x}_{2}\) was extraction time, and \(\:{x}_{3}\) was ethanol/water ratio) and \(\:{\beta}_{k0}\) is the value of fitted response at the design center point, respectively.

The model’s adequacy was assessed through the coefficient of determination (R²), ANOVA analysis, and p-values. Critical points were identified by analyzing the model’s derivatives to optimize the response variable. Furthermore, three-dimensional surface plots were created to illustrate the impact of the independent variables, offering a clearer insight into their influence on the response.

ANN-GA

The Artificial Neural Network (ANN) method was employed for modeling, with extraction temperature, extraction time, and ethanol/water ratio as inputs, and the TAS value as the output. Experimental data were split into 80% for training, 10% for validation, and 10% for testing. The Levenberg-Marquardt (LM) algorithm was utilized for the training process. To identify the optimal network, 20 different hidden neuron configurations (1 to 20) were evaluated. The learning rate and momentum coefficient were set to 0.5, the maximum number of iterations was fixed at 500, validation checks were capped at 50, and the error threshold was defined as 1 × 10⁻⁵. Each model underwent 1000 training sessions. Performance of the developed models was assessed using mean square error (MSE) and mean absolute percentage error (MAPE), calculated using Eq.1 and Eq.2.

where, is the experimental result, \(\:\text{p}\:\)is the prediction result, and \(\:\text{n}\) is the number of samples.

Optimization was carried out using the Genetic Algorithm (GA). Various population sizes were tested, and the roulette wheel selection method was employed. Single-point crossover was used as the crossover technique. The optimal number of iterations was identified by examining the convergence graphs. To ensure results closely approximated the global optimum, each optimization run was repeated at least 60 times.

Extractions for bioactivity

Extracts providing the highest level of biological activity of algae samples were obtained by taking into account optimum production conditions. In this context, ideal conditions were determined as 54.940 ˚C temperature, 6.513h and 42.109 ethanol/water ratio according to RSM method; optimum set was determined as 56.286 ˚C temperature, 7.2793h and 36.8625 ethanol/water ratio according to ANN-GA integration. The conditions closest to these determined parameters were optimized using Gerhardt SOX-414 device (Germany) and in a computer-aided environment. The obtained extracts were used as the basis in carrying out biological activity tests.

Phenolic analysis

Phenolic content of optimized algae extracts was investigated using Shimadzu LC-MS/MS-8030. During the analysis, extracts were screened for 24 different standard compounds. Separation was carried out using C-18 Intersil ODS-4 analytical column (3.0mm x 100mm, 2μm) kept at 40°C. Water containing 0.1% formic acid (Phase A) and methanol containing 0.1% formic acid (Phase B) were preferred as mobile phases. The flow rate was determined as 0.3 mL/min and the injection volume of the samples was set as 2 µL.

DPPH free radical scavenger activity test

Stock solutions of algae extracts were prepared using DMSO at a concentration of 1mg/mL. 1 mL of these solutions were mixed with 160 µL of 0.267 mM DPPH solution (4 mL in total, containing 0.004% methanol). The mixture was incubated at room temperature in a dark environment for 30min. At the end of the period, the absorbance of the solution was measured at 517nm using a spectrophotometer (Shimadzu UV-1601, Kyoto, Japan). The results were expressed as milligrams of Trolox Equivalent (mg TE/g) per gram of extract. Analyses were performed in three replicates [12].

Ferric Reducing Antioxidant Power (FRAP) test

A 100 µL stock solution was prepared from the optimized algae extracts. This solution was mixed with 2 mL of FRAP reagent. FRAP reagent was obtained by mixing 20 mM FeCl₃ 6H₂O solution prepared with 300 mM acetate buffer (pH 3.6), 40 mM HCl, and 10 mM 2,4,6-tris(2-pyridyl)-S-triazine (TPTZ) solution at a ratio of 10:1:1. The mixture was incubated at 37°C for 4min. After the process, absorbance measurements were carried out at 593nm using a spectrophotometer (Shimadzu UV-1601, Kyoto, Japan). The results were expressed in milligrams of Trolox Equivalent per extract (mg TE/g). Analyses were performed in three replicates [12].

Total antioxidant and oxidant status analysis

The total antioxidant status of optimized algae extracts was determined using the Rel Assay TAS kit (Rel Assay Diagnostics, Megatıp, Gaziantep, Turkey). The measurement results were expressed in mmol Trolox equivalent/L. Similarly, the total oxidant status was analyzed with the Rel Assay TOS kit and the results were recorded as µmol hydrogen peroxide equivalent/L. The oxidative stress index (OSI) value was calculated by dividing the TOS values ​​by the TAS values ​​and converting them into percentages. Analyses were performed in three replicates [13,14,15].

Antiproliferative activity tests

The antiproliferative effect of optimized algae extracts was evaluated in A549 lung cancer cell line. For this purpose, stock solutions were prepared at concentrations of 25, 50, 100 and 200µg/mL. After 70–80% confluence of the cells was achieved, the cells were dissociated with 3.0 mL of Trypsin-EDTA solution (Sigma-Aldrich, MO, USA) and transferred to culture plates. The plates were incubated for 24h to settle the cells. Then, the prepared extract solutions were applied to the cells and incubated once more for 24h. After the process, the supernatants were replaced with 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) solution (1mg/mL) and incubated at 37°C until purple precipitate formation was observed. The MTT solution was then dissolved with dimethyl sulfoxide (DMSO) (Sigma-Aldrich, MO, USA) and absorbance values ​​were measured at 570nm wavelength using Epoch spectrophotometer (BioTek Instruments, Winooska, VT). Analyses were performed in three replicates [16].

Anticholinesterase activity test

Anticholinesterase activities of optimized algae extracts were analyzed based on the Ellman method [17]. In this study, galantamine was used as a reference substance. Various stock solutions were prepared from algae extracts with concentrations ranging from 200 to 3.125µg/mL. For the test, 130 µL of 0.1M phosphate buffer (pH = 8) was added to the microplate, followed by 10 µL of stock solution and 20 µL of AChE or BChE enzyme solution, respectively. The mixture was incubated at 25°C in the dark for 10min. Then, 20 µL of DTNB solution (5,5′-dithiobis-(2-nitrobenzoic acid)) and 20 µL of substrate solution (acetylcholine iodide or butyrylcholine iodide) were added. Absorbance measurements were carried out at a wavelength of 412nm. Using the obtained data, IC50 values ​​of enzyme inhibition rates were calculated and expressed in µg/mL units. Analyses were performed in three replicates.

Statistical analysis

Analyses were performed in three replicates. All statistical analyses in this study were performed using the ‘SPSS 21.0 for Windows’ software. For comparisons involving multiple groups, a One-Way Analysis of Variance (ANOVA) was used to assess differences among them. The Duncan test was then applied at a significance level of α = 0.05 to identify specific group differences.

Optimization of extraction conditions

TAS values ​​obtained after the experimental study are given in Table1.

This study investigated the impact of extraction temperature, time, and ethanol/water ratio on the total antioxidant activity (TAS) of U. lactuca kernel extracts. Extraction temperature had a significant effect on TAS values, with the lowest values observed at 45°C, the highest at 55°C, and lower values again at 65°C. In terms of extraction time, 10h generally yielded the highest TAS values, while 15h resulted in a decrease in TAS. The ethanol/water ratio was also a crucial factor, with the highest TAS values obtained at a 50% ethanol ratio, while pure ethanol and pure water produced lower TAS values. In conclusion, the optimal conditions were found to be 55°C temperature, 10h extraction time, and a 50% ethanol ratio, suggesting that these parameters provide the best optimization for the antioxidant capacity of U. lactuca extracts.

In this study, two distinct optimization methods were employed using data obtained from experimental studies. For the optimization conducted with the Response Surface Method (RSM), linear, 2FI, quadratic, and cubic regression models were developed, with the quadratic model being selected due to its highest R² value. The R² value indicates the model’s effectiveness in explaining the dependent variable’s response based on the independent variables. A high R² value demonstrates the model’s suitability. In this study, the R² of the model was found to be 0.853.

The quadratic polynomial equation created as a result of the multiple regression analysis to determine the TAS values of U. lactuca is shown below.

In the equation \(\:{X}_{1}\), \(\:{X}_{2}\) ve \(\:{X}_{3}\) represent extraction temperature, extraction time and ethanol/water ratio, respectively. Response surface plots of TAS of U. lactuca were shown at Fig.1.

Among the extraction conditions investigated, the TAS value of U. lactuca extracts was most significantly affected by the extraction temperature and ethanol/water ratio (statistically significant at p < 0.05), while the extraction time had a lesser effect. According to RSM optimization, the optimal conditions were predicted to be a temperature of 54.009°C, an extraction time of 13.560h, and an ethanol/water ratio of 41.917%.

During the optimization process using artificial intelligence techniques, the experimental data were modeled using an artificial neural network (ANN), followed by optimization with a genetic algorithm (GA). The optimal prediction model was identified as having a 3-3-1 architecture, indicating that the model with three hidden neurons was found to be the most effective. The MSE, MAPE, and R values for this model were calculated as 0.0001, 0.130%, and 0.999, respectively, demonstrating a strong agreement between the model’s predictions and the actual data.

The optimization process was performed using the genetic algorithm (GA) with the best-selected ANN model. Among the different population sizes evaluated, a population size of 10 was identified as optimal. Following 20 iterations, the convergence graph (Fig.2) revealed that the objective function value stabilized after the second iteration.

Using the ANN-GA integration, the predicted optimal conditions were determined to be a temperature of 56.286°C, a duration of 7.279h, and an ethanol-to-water ratio of 36.862%.

Phenolic contents

Phenolic compounds are important components that help protect algae against environmental stress factors and show biological activity. Flavonoids, phenolic acids, tannins and their derivatives included in this group support the biological functions of algae. Phlorotannins, which are densely found in algae, attract attention with their antioxidant, anticarcinogenic and anti-inflammatory properties [18, 19]. Detailed analyzes of these compounds are usually performed with advanced technology devices such as LC-MS/MS. Thanks to these analyzes, the phenolic profile of algae is revealed comprehensively and their usability in both food and health fields is increased [20]. In our study, the phenolic contents of the optimized extract of U. lactuca were scanned on the LC-MS/MS device. The findings are shown in Table2.

U. lactuca is an important source of phenolic compounds among green algae. This algae is rich in phenolic compounds such as p-quercetin, kaempferol, and apigenin. These phenolic compounds exhibit strong antioxidant properties due to their free radical scavenging activities [10]. In addition, compounds such as naringin and catechin are also found in U. lactuca among flavonoids, and these compounds have inflammation-reducing and cell-protective effects [21]. In addition, tannins are also present in the phenolic content of U. lactuca and attract attention with their antibacterial activities [22]. In our study, the phenolic contents of the extracts of U. lactuca produced under optimum conditions that provide the highest biological activities were screened. As a result of the analyzes, 7 phenolic compounds were detected in both extracts of the algae. In addition, all of the compounds detected in the ANN-GA extract were determined to be higher. In our study, the phenolic compounds of U. lactuca were examined in detail and the presence of several important compounds was determined. These compounds include gallic acid, 4-hydroxybenzoic acid, caffeic acid, vanillic acid, syringic acid, quercetin and kaempferol. The analyses show that these phenolic compounds are found in different concentrations in both extracts. In particular, caffeic acid stands out as the highest detected compound in both extracts. Caffeic acid is an important phenolic acid, especially known for its antioxidant properties and widely found in plant-based products. It is found in high concentrations in plants and is known for its potential to reduce oxidative stress. This compound can help prevent cell damage by neutralizing free radicals in the body. Studies have also shown that caffeic acid has anti-inflammatory and anticarcinogenic effects [23,24,25]. This study shows that U. lactuca may be a rich source of phenolic compounds and has significant potential in the field of health, especially in terms of its caffeic acid content. It is known that phenolic compounds have various positive effects on human health as well as the capacity to increase the resistance of algae to environmental stress factors. In this context, it is anticipated that U. lactuca may find wider use in the food, cosmetics and pharmaceutical industries.

Antioxidant activity

Oxidative stress is a condition that occurs as a result of excessive accumulation of free radicals in cells and can cause damage to biological systems. Free radicals occur as a result of normal metabolic processes, but environmental factors, stress, poor nutrition and habits such as smoking can increase the severity of this condition. Long-term effects of oxidative stress have been associated with various diseases such as cancer, heart disease, diabetes and neurological diseases [26,27,28]. Antioxidants come into play to neutralize excessive free radicals in the body. Antioxidants protect cells from oxidative damage by neutralizing free radicals. Natural antioxidants such as vitamin C, vitamin E, selenium and phenolic compounds fulfill this protective function. Phenolic compounds, especially those obtained from plant sources, stand out with their strong antioxidant properties and therefore their positive effects on health are being investigated [29, 30]. In our study, the antioxidant potentials of optimized extracts of U. lactuca were determined. The findings are shown in Table3.

U. lactuca (green algae) attracts attention with its various biological activities and is an important source of natural compounds, especially with its antioxidant properties. This algae species contains many active compounds that show protective effects against oxidative damage in the body [31]. In the literature, the antioxidant activities of U. lactuca extracts tested with DPPH (2,2-diphenyl-1-picrylhydrazyl) and FRAP (Ferric Reducing Antioxidant Power) methods were found to be high. It is emphasized that the antioxidant capacity of algae can strengthen defense mechanisms against environmental stress factors and also has the potential to be beneficial to human health [32, 33]. In our study, the antioxidant activities of optimized extracts of U. lactuca were determined with DPPH and FRAP methods and it was seen that they had antioxidant potential. In addition, TAS, TOS and OSI values ​​were determined for the first time. There are TAS, TOS and OSI studies on plant species in the literature. In this context, the TAS value of Anthemis cotula was reported as 7.625 mmol/L, TOS value as 11.247 µmol/L and OSI value as 0.148 [34]. (Sabik et al., 2024). The TAS value of Hypericum spectabile was reported as 9.306 mmol/L, TOS value as 13.065 µmol/L and OSI value as 0.140 [35]. The TAS value of Arum dioscoridis was reported as 6.486 mmol/L, TOS value as 13.578 µmol/L and OSI value as 0.209 [36]. The TAS value of Alcea kurdica was reported as 3.298 mmol/L, TOS value as 8.312 µmol/L and OSI value as 0.252 [37]. It was observed that the ANN-GA extract of U. lactuca used in our study had higher TAS value compared to the RSM extract. It was determined that both extracts of U. lactuca had lower TAS values ​​than Anthemis cotula, Hypericum spectabile and Arum dioscoridis and higher TAS values ​​than Alcea kurdica. The TAS value is an indicator of the totality of antioxidant compounds found in natural products. In our study, it was determined that the optimized extracts of U. lactuca had antioxidant potential, and this finding shows that the seaweed has protective properties against environmental stress factors and may offer potential benefits in the field of health. This result reveals the importance of evaluating U. lactuca as a natural antioxidant source.

TOS value is an indicator of the totality of oxidant compounds produced in natural products. In our study, it was observed that U. lactuca’s ANN-GA extract had a higher TOS value compared to RSM extract. It was determined that both extracts of U. lactuca had lower TOS values ​​than A. cotula, H. spectabile and A. dioscoridis. In addition, it was observed that U. lactuca’s ANN-GA extract had a higher TOS value than A. kurdica, while RSM extract had a lower TOS value.

OSI value shows how much oxidant compounds are suppressed by antioxidant compounds. The OSI value of Ulva lactuca’s ANN-GA extract used in our study was determined to be higher than A. cotula and H. spectabile, while RSM extract was lower. In addition, it was determined that both extracts of U. lactuca had lower OSI values ​​than A. dioscoridis and A. kurdica. As a result, it was seen that the optimized extracts of U. lactuca had the potential to suppress oxidant compounds.

In our study, the biological activities of the optimized extracts of U. lactuca were examined in detail. As a result of the analyzes, it was determined that both extracts of U. lactuca had high antioxidant potential. In addition to the antioxidant activities tested especially with DPPH and FRAP methods, TAS, TOS and OSI values ​​were also determined for the first time. It was seen that ANN-GA extract had higher TAS and TOS values ​​compared to RSM extract and was also lower than some plant species in terms of OSI value. These findings show that U. lactuca has protective properties against environmental stress factors and offers potential benefits in the field of health. This finding raises the potential of optimized extracts of U. lactuca to be used as natural antioxidant sources, and encourages further investigation of this seaweed.

Antiproliferative activity

Algae are organisms with nutritional and medicinal properties that are widely found in marine and freshwater ecosystems. In recent years, research on the anticancer effects of algae has increased. Thanks to the biologically active compounds they contain, algae can prevent the growth of cancer cells, promote apoptosis (programmed cell death) and inhibit metastasis. The anticancer potential of algae attracts attention as an important area for researchers looking for new, natural treatment methods in cancer treatment [10, 38]. In our study, the activity of the optimized extract of U. lactuca against the A549 lung cancer cell line was determined. The findings are shown in Fig.3.

Many studies have examined the antiproliferative (cell proliferation inhibition) effects of U. lactuca. It is stated that these effects are associated with the potential to inhibit the growth of cancer cells. The compounds contained in U. lactuca, especially polysaccharides, phenolic compounds and flavonoids, can reduce oxidative stress by neutralizing free radicals, which can prevent the proliferation of cancer cells. In addition, U. lactuca has been shown to inhibit the G1 phase of the cell cycle and prevent cell division and proliferation [39,40,41]. In our study, the effects of optimized extracts of U. lactuca against the A549 lung cancer cell line were investigated. Studies have shown that ANN-GA extract of seaweed is more effective against A549 lung cancer cell line and both extracts show strong cytotoxic effects depending on the concentration, and these findings support the investigation of seaweed as a potential cancer treatment agent. In our study, antiproliferative effects of optimized extracts of U. lactuca on A549 lung cancer cell line were investigated. The analyses showed that the extract of U. lactuca obtained by the ANN-GA method showed stronger cytotoxic effects against A549 lung cancer cell line compared to the RSM extract. Both extracts exhibited significant antiproliferative activity depending on the concentration, and these findings support the use of U. lactuca as a potential cancer treatment agent. It was determined that extract optimization played an important role in increasing biological activity, and it was seen that the second extract in particular provided a more effective formulation in inhibiting the growth of cancer cells. The obtained results indicate that U. lactuca should be subjected to more detailed studies as a source of biological activity in cancer treatment.

Anticholinesterase activity

Cholinesterase inhibitors are compounds that inhibit enzymes and prevent the destruction of neurotransmitters. Thanks to these properties, cholinesterase inhibitors play an important role in the treatment of neurological diseases, especially Alzheimer’s disease (AD). Inhibition of acetylcholinesterase may help improve brain functions, since increasing acetylcholine levels can improve cognitive functions such as memory and learning [42, 43]. In our study, the anticholinesterase activity of the optimized extract of U. lactuca was determined. The IC50 values ​​of the obtained findings are shown in Table4.

In our study, anticholinesterase activities of U. lactuca extracts produced under optimum conditions that provide the highest biological activities were investigated. In the literature, the activity of sulfated polysaccharides obtained from U. lactuca in inhibiting acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) was reported with IC50 values ​​of 106.93µg/mL and 93.45µg/mL, respectively [44]. However, it was found that both extracts used in our study showed higher anticholinesterase activities. Especially, Ulva lactuca extract obtained by ANN-GA method exhibited stronger anticholineresterase activity compared to RSM extract, indicating that extract optimization plays an important role in increasing biological activity. However, both extracts were determined to have lower efficacy compared to standard galantamine. These findings reveal that U. lactuca has a strong potential in terms of anticholineresterase activity but needs further optimization for pharmaceutical applications. In addition, they show that U. lactuca can be an important source for the development of enzyme inhibition-based treatment strategies in biotechnology and pharmaceutical fields. These results emphasize that extract optimization is a critical step in increasing the biological activities of natural compounds and finding more effective treatment methods.

AChE:

Acetylcholinesterase

ANN:

Artificial Neural Network

ANN-GA:

Artificial Neural Network-Genetic Algorithm

BChE:

Butyrylcholinesterase

DMSO:

Dimethyl Sulfoxide

DPPH 2:

2-Diphenyl-1-Picrylhydrazyl

DTNB 5:

5′-Dithiobis-(2-Nitrobenzoic Acid)

FRAP:

Ferric Reducing Antioxidant Power

GA:

Genetic Algorithm

LC-MS/MS:

Liquid Chromatography-Mass Spectrometry/Mass Spectrometry

MAPE:

Mean Absolute Percentage Error

MSE:

Mean Squared Error

MTT:

3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide

OSI:

Oxidative Stress Index

OSI:

Oxidative stress index

R:

Correlation Coefficient

RSM:

Response Surface Methodology

TAS:

Total Antioxidant Status

TOS:

Total Oxidant Status

TPTZ:

2,4,6-Tris(2-Pyridyl)-S-Triazine

Authors and Affiliations

1. Faculty of Engineering and Natural Sciences, Department of Biology, Osmaniye Korkut Ata University, Osmaniye, Türkiye

   Nuh Korkmaz

Contributions

The experimental design, studies, analysis, writing and revisions of this manuscript were made by N.K.

Corresponding author

Correspondence to Nuh Korkmaz.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions