The secondary metabolites profiling of Nymphaea nouchali stem (NNSE) extract was carried out using a high-resolution mass spectroscopic technique. The antioxidant effects of NNSE, as well as the underlying mechanisms, were also investigated in tert-butyl hydroperoxide (t-BHP)-stimulated oxidative stress in RAW264.7 cells. Tandem mass spectroscopy with (−) negative mode tentatively revealed the presence of 54 secondary metabolites in NNSE. Among them, phenolic acids and flavonoids were predominant. Phenolic acids (brevifolincarboxylic acid, p-coumaroyltartaric acid, niazinin B, lalioside, 3-feruloylquinic acid, and gallic acid-O-rutinoside), flavonoids (elephantorrhizol, apigenin-6-C-galactoside 8-C-arabinoside, and vicenin-2), sialic acid (2-deoxy-2,3-dehydro-N-acetylneuraminic acid), and terpenoid (α-γ-onoceradienedione) were identified in NNSE for the first time. Unbridled reactive oxygen species/nitrogen species (ROS/RNS) and redox imbalances participate in the induction and development of many oxidative stress-linked diseases. The NNSE exhibited significant free radical scavenging capabilities and was also able to reduce t-BHP-induced cellular generation in RAW264.7 cells. The NNSE prevented oxidative stress by inducing the endogenous antioxidant system and the levels of heme oxygenase-1 (HO-1) by upregulating Nrf2 through the modulation of mitogen-activated protein kinases (MAPK), such as phosphorylated p38 and c-Jun N terminal kinase. Collectively, these results indicate that the NNSE exhibits potent effects in preventing oxidative stress-stimulated diseases and disorders through the modulation of the MAPK/Nrf2/HO-1 signaling pathway. Our findings provide new insights into the cytoprotective effects and mechanisms of Nymphaea nouchali stem extract against oxidative stress, which may be a useful remedy for oxidative stress-induced disorders.

Sargassum fusiforme (SF) is a popular edible brown macroalga found in Korea, Japan, and China and is known for its health-promoting properties. In this study, we used two sophisticated models to obtain optimized conditions for high antioxidant activity and metabolite profiling using high-resolution mass spectrometry. A four-factor central composite design was used to optimize the microwave-assisted extraction and achieve the maximum antioxidant activities of DPPH (Y₁: 28.01 % inhibition), ABTS (Y₂: 36.07 % inhibition), TPC (Y₃: 43.65 mg GAE/g), and TFC (Y₄: 17.67 mg CAE/g), which were achieved under the optimized extraction conditions of X₁: 47.67 %, X₂: 2.96 min, X₃: 139.54 °C, and X₄: 600.00 W. Moreover, over 79 secondary metabolites were tentatively identified, of which 12 compounds were reported for the first time in SF, including five phenolic (isopropyl 3-(3,4-dihydroxyphenyl)-2-hydroxypropanoate, 3,4-dihydroxyphenylglycol, scopoletin, caffeic acid 4-sulfate, and cinnamoyl glucose), two flavonoids (4’,7-dihydroxyisoflavone and naringenin), three phlorotannins (diphlorethohydroxycarmalol, dibenzodioxin-1,3,6,8-tetraol, and fucophlorethol), and two other compounds (dihydroxyphenylalanine and 5-hydroxybenzofuran-2(3H)-one) being identified for the first time in optimized SF extract. These compounds may also be involved in improving the antioxidant potential of the extract. Therefore, optimized models can provide better estimates and predictive capabilities that would assist in finding new bioactive compounds with improved biological activities that can be further applied at a commercial level.

The Ajwa date (Phoenix dactylifera L., Arecaceae family) is a popular edible fruit consumed all over the world. The profiling of the polyphenolic compounds of optimized unripe Ajwa date pulp (URADP) extracts is scarce. The aim of this study was to extract polyphenols from URADP as effectively as possible by using response surface methodology (RSM). A central composite design (CCD) was used to optimize the extraction conditions with respect to ethanol concentration, extraction time, and temperature and to achieve the maximum amount of polyphenolic compounds. High-resolution mass spectrometry was used to identify the URADP’s polyphenolic compounds. The DPPH-, ABTS-radical scavenging, α-glucosidase, elastase and tyrosinase enzyme inhibition of optimized extracts of URADP was also evaluated. According to RSM, the highest amounts of TPC (24.25 ± 1.02 mgGAE/g) and TFC (23.98 ± 0.65 mgCAE/g) were obtained at 52% ethanol, 81 min time, and 63 °C. Seventy (70) secondary metabolites, including phenolic, flavonoids, fatty acids, and sugar, were discovered using high-resolution mass spectrometry. In addition, twelve (12) new phytoconstituents were identified for the first time in this plant. Optimized URADP extract showed inhibition of DPPH-radical (IC₅₀ = 87.56 mg/mL), ABTS-radical (IC₅₀ = 172.36 mg/mL), α-glucosidase (IC₅₀ = 221.59 mg/mL), elastase (IC₅₀ = 372.25 mg/mL) and tyrosinase (IC₅₀ = 59.53 mg/mL) enzymes. The results revealed a significant amount of phytoconstituents, making it an excellent contender for the pharmaceutical and food industries.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor and cognitive impairments. Early detection is critical for effective intervention, but current diagnostic methods often lack accuracy and generalizability. Electroencephalography (EEG) offers a noninvasive means to monitor neural activity, revealing abnormal brain oscillations linked to PD pathology. However, deep learning models for EEG analysis frequently struggle to balance high accuracy with robust generalization across diverse patient populations. To overcome these challenges, this study proposes a convolutional transformer enhanced sequential model (CTESM), which integrates convolutional neural networks, transformer attention blocks, and long short-term memory layers to capture spatial, temporal, and sequential EEG features. Enhanced by biologically informed feature extraction techniques, including spectral power analysis, frequency band ratios, wavelet transforms, and statistical measures, the model was trained and evaluated on a publicly available EEG dataset comprising 31 participants (15 with PD and 16 healthy controls), recorded using 40 channels at a 500 Hz sampling rate. The CTESM achieved an exceptional classification accuracy of 99.7% and demonstrated strong generalization on independent test datasets. Rigorous evaluation across distinct training, validation, and testing phases confirmed the model’s robustness, stability, and predictive precision. These results highlight the CTESM’s potential for clinical deployment in early PD diagnosis, enabling timely therapeutic interventions and improved patient outcomes.

This study sought to optimize the ultrasonic-assisted extraction of polyphenolic compounds from unmature Ajwa date seeds (UMS), conduct untargeted metabolite identification and assess antioxidant and depigmenting activities. Response surface methodology (RSM) utilizing the Box–Behnken design (BBD) and artificial neural network (ANN) modeling was applied to optimize extraction conditions, including the ethanol concentration, extraction temperature and time. The determined optimal conditions comprised the ethanol concentration (62.00%), extraction time (29.00 min), and extraction temperature (50 °C). Under these conditions, UMS exhibited total phenolic content (TPC) and total flavonoid content (TFC) values of 77.52 ± 1.55 mgGAE/g and 58.85 ± 1.12 mgCE/g, respectively, with low relative standard deviation (RSD%) and relative standard error (RSE%). High-resolution mass spectrometry analysis unveiled the presence of 104 secondary metabolites in UMS, encompassing phenols, flavonoids, sesquiterpenoids, lignans and fatty acids. Furthermore, UMS demonstrated robust antioxidant activities in various cell-free antioxidant assays, implicating engagement in both hydrogen atom transfer and single electron transfer mechanisms. Additionally, UMS effectively mitigated tert-butyl hydroperoxide (t-BHP)-induced cellular reactive oxygen species (ROS) generation in a concentration-dependent manner. Crucially, UMS showcased the ability to activate mitogen-activated protein kinases (MAPKs) and suppress key proteins including tyrosinase (Tyr), tyrosinase-related protein-1 and -2 (Trp-1 and -2) and microphthalmia-associated transcription factor (MITF), which associated melanin production in MNT-1 cell. In summary, this study not only optimized the extraction process for polyphenolic compounds from UMS but also elucidated its diverse secondary metabolite profile. The observed antioxidant and depigmenting activities underscore the promising applications of UMS in skincare formulations and pharmaceutical developments.

The date palm (Phoenix dactylifera L.) is a popular edible fruit consumed all over the world and thought to cure several chronic diseases and afflictions. The profiling of the secondary metabolites of optimized ripe Ajwa date pulp (RADP) extracts is scarce. The aim of this study was to optimize the heat extraction (HE) of ripe Ajwa date pulp using response surface methodology (RSM) and artificial neural network (ANN) modeling to increase its polyphenolic content and antioxidant activity. A central composite design was used to optimize HE to achieve the maximum polyphenolic compounds and antioxidant activity of target responses as a function of ethanol concentration, extraction time, and extraction temperature. From RSM estimates, 75.00% ethanol and 3.7 h (extraction time), and 67 °C (extraction temperature) were the optimum conditions for generating total phenolic content (4.49 ± 1.02 mgGAE/g), total flavonoid content (3.31 ± 0.65 mgCAE/g), 2,2-diphenyl-1-picrylhydrazyl (11.10 ± 0.78 % of inhibition), and cupric-reducing antioxidant capacity (1.43 µM ascorbic acid equivalent). The good performance of the ANN was validated using statistical metrics. Seventy-one secondary metabolites, including thirteen new bioactive chemicals (hebitol II, 1,2-di-(syringoyl)-hexoside, naringin dihydrochalcone, erythron-guaiacylglycerol-β-syringaresinol ether hexoside, erythron-1-(4′-O-hexoside-3,5-dimethoxyphenyl)-2-syrngaresinoxyl-propane-1,3-diol, 2-deoxy-2,3-dehydro-N-acetyl-neuraminic acid, linustatin and 1-deoxynojirimycin galactoside), were detected using high-resolution mass spectroscopy. The results revealed a significant concentration of phytoconstituents, making it an excellent contender for the pharmaceutical and food industries.