Search Results (65)

Neurodegenerative disorders, mental conditions, and cognitive decline represent significant challenges worldwide, with growing pieces of evidence implicating alterations in neurotrophin signaling as central to these diseases. Neurotrophins—such as nerve growth factor (NGF) and brain-derived neurotrophic factor (BDNF)—are indispensable for neuronal survival, differentiation, and synaptic plasticity, and their dysregulation is closely associated with various neuropathological situations. Similarly, dietary plant polyphenols, abundant in vegetables, fruits, wine, tea, and extra virgin olive oil, show powerful anti-inflammatory, antioxidant, and anti-apoptotic activities. This narrative review critically addresses the evolving body of evidence that links plant polyphenols and brain neurotrophins, emphasizing several molecular mechanisms by which polyphenols regulate and modulate neurotrophin signaling. Crucial pathways include mitigation of neuroinflammatory responses, activation of intracellular cascades such as the cAMP response element-binding protein (CREB), epigenetic modulation, and the diminution of oxidative stress. Together, these effects contribute to potentiated enhanced synaptic function, neuronal integrity, and better learning and memory processes. Moreover, this narrative review examines how polyphenol-induced upregulation of neurotrophins may alleviate conditions associated not only with neurodegeneration but also with addiction and mood disorders, suggesting extensive therapeutic approaches. Findings from clinical investigations and animal models are presented to sustain the neuroprotective role of polyphenol-rich diets. Lastly, future research directions are recommended, focusing on polyphenol bioavailability optimization, considering combinatory dietary stratagems, and proposing personalized nutritional interventions. This wide-ranging perspective highlights plant polyphenols as encouraging modulators of neurotrophin pathways and supports their inclusion in approaches aimed at promoting brain health and counteracting neurodegenerative decline. Full article

The objective of this study was to carry out a study on continuous and intermittent drying (intermittency ratio α = 2/3) of osmotically pretreated melon pieces, cut in the form of a parallelepiped. An osmotic dehydration pretreatment was performed using an incubator with mechanical shaking. Drying processes were carried out using an oven with forced air circulation at temperatures of 50 and 70 °C. The data were modeled by means of empirical equations, in order to compare the drying kinetics and analyze the impact of the intermittent process on energy savings and preservation of bioactive compounds in the final product. The experiments were also described using a diffusion model in Cartesian coordinates, with a third-kind boundary condition, in order to analyze the moisture distribution inside each piece of fruit over time. Among the empirical equations analyzed, Page’s was the one that best described the continuous and intermittent drying of osmotically pretreated melon pieces. In order to obtain dried melon, intermittent drying significantly reduced the effective processing time and, consequently, energy consumption, preserving the bioactive compounds more intensely (particularly at a temperature of 50 °C), compared to continuous drying. The diffusion model adequately described all the drying experiments, and it was found that the effective mass diffusivity increased significantly with the application of intermittency. Full article

Plastic injection molding is a widespread industrial process in manufacturing. This article investigates the energy consumption in the injection molding process of fruit containers, proposing a new use strategy for the application of artificial intelligence algorithms. The aim is to optimize the process parameters, such as the mold temperatures, the injector temperatures, and the cycle time, to minimize energy consumption. This new use strategy, a hybrid use strategy, combines an unsupervised autoencoder with the K-Means algorithm to analyze production data and identify factors influencing energy consumption. The results show the capability of discovering different operating modes at different levels of energy requirements. An analysis of the process parameters reveals that the number of parts left to complete production, the current cycle counter, the number of shots left to complete the production, the material needed to complete the production, and the total time dedicated to production, so far, are the most relevant features for the optimization of the energy consumption per single piece. The study demonstrates the potential of common artificial intelligence algorithms if appropriately used to improve the sustainability of the plastic injection molding process. Full article

The traditional shrub fruits harvesting method is manual picking, while the efficiency is low, which seriously restricts the development of Lycium barbarum L. industry. In order to mechanize the harvesting process of Lycium barbarum L. and improve the correct picking rate while reducing the damage rate of Lycium barbarum L. harvesting, it is very important to analyze the kinematic model of the fruit-bearing branch during vibration harvesting. Through the measurement and analysis of the natural characteristics and physical parameters of the branches, a simplified model of Lycium barbarum L. shrub fruit-bearing branch was built by Solidworks 2023 software, and the appropriate material properties were selected. Through modal analysis and harmonious response analysis, the response characteristics data of fruit-bearing branches of Lycium barbarum L. shrub were obtained. In Qinghai Nuomuhong Farm, the field vibration harvesting kinematic model feature analysis test was carried out, and the acceleration data of the vibration harvesting process were collected by using the acceleration sensor, and through the analysis of the frequency spectrum characteristics of the data, it was concluded that when the excitation frequency was maintained between 8 and 14 Hz, the Lycium barbarum L. fell off well and the picking rate can reach 97.56%, the efficiency can reach 6.88 pieces of fruit per second, and the branch damage was acceptable, which theoretically met the needs of harvesting. Full article

This study examines the semantic variation in fruit and vegetable classifier usage in Amman, Jordan, employing a cognitive sociolinguistic approach. The semantic variation revolves around using idiomatic classifiers, such as raːs basˤal (“head of onion”), in contrast to neutral classifiers, i.e., ħabbet basˤal (“a piece of onion”) or numerals, such as basˤalteːn (“two onions”). This study focuses on classifiers used with fruits and vegetables, which are particularly relevant due to their physical shapes often prompting metaphorical classifiers and their tendency to take Arabic collective forms that are grammatically singular but semantically plural, complicating the issue of counting and potentially leading to the innovation of novel classifiers. The sample comprised 50 individuals from Amman, stratified based on their gender, age, and education. Data were collected through semi-structured interviews. The findings reveal a statistically significant inclination among older, male, and less formally educated speakers towards favoring idiomatic classifiers over the neutral options. This preference suggests that the choice between idiomatic and neutral classifiers may be influenced by social factors. We categorized the metaphors underlying the idiomatic classifiers as entrenched, conventionalized, and transparent, based on Müller (2009). The context of conventional metaphors demonstrates that the source domains of these metaphors could be active for a speaker at a specific moment but may not be active for another speaker at another moment, proposing that metaphoricity is not only a property of a linguistic item but also the cognitive achievement of a certain speaker. The preference for idiomatic classifiers, we argue, may be associated with notions of lower refinement, traditionalism, or reduced prestige. Full article

Multi-factor authentication (MFA) is a system for authenticating an individual’s identity using two or more pieces of data (known as factors). The reason for using more than two factors is to further strengthen security through the use of additional data for identity authentication. Sequential MFA requires a number of steps to be followed in sequence for authentication; for example, with three factors, the system requires three authentication steps. In this case, to proceed with MFA using a deep learning approach, three artificial neural networks (ANNs) are needed. In contrast, in parallel MFA, the authentication steps are processed simultaneously. This means that processing is possible with only one ANN. A convolutional neural network (CNN) is a method for learning images through the use of convolutional layers, and researchers have proposed several systems for MFA using CNNs in which various modalities have been employed, such as images, handwritten text for authentication, and multi-image data for machine learning of facial emotion. This study proposes a CNN-based parallel MFA system that uses concatenation. The three factors used for learning are a face image, an image converted from a password, and a specific image designated by the user. In addition, a secure password image is created at different bit-positions, enabling the user to securely hide their password information. Furthermore, users designate a specific image other than their face as an auxiliary image, which could be a photo of their pet dog or favorite fruit, or an image of one of their possessions, such as a car. In this way, authentication is rendered possible through learning the three factors—that is, the face, password, and specific auxiliary image—using the CNN. The contribution that this study makes to the existing body of knowledge is demonstrating that the development of an MFA system using a lightweight, mobile, multi-factor CNN (MMCNN), which can even be used in mobile devices due to its low number of parameters, is possible. Furthermore, an algorithm that can securely transform a text password into an image is proposed, and it is demonstrated that the three considered factors have the same weight of information for authentication based on the false acceptance rate (FAR) values experimentally obtained with the proposed system. Full article

Currently, a clear interest has been given to berries due to their richness in active metabolites, including anthocyanins and non-coloured phenolics. Therefore, the main aim of the present work is to investigate the phenolic profile, antioxidant abilities, and antiproliferative effects on normal human dermal fibroblasts (NHDF) and human colon carcinoma cell line (Caco-2) cells of phenolic-rich extracts from three red fruits highly appreciated by consumers: two species of blackberries (Rubus fruticosus and Rubus ulmifolius) and one species of mulberry (Morus nigra). A total of 19 different phenolics were identified and quantified by HPLC-DAD-ESI/MSⁿ and HPLC-DAD, respectively. Focusing on the biological potential of the phenolic-rich extracts, all of them revealed notable scavenging abilities. Concerning the antiproliferative properties, R. fruticosus presented a cytotoxic selectivity for Caco-2 cells compared to NHDF cells. To deeper explore the biological potential, combinations with positive controls (ascorbic acid and 5-fluorouracil) were also conducted. Finally, the obtained data are another piece of evidence that the combination of phenolic-rich extracts from natural plants with positive controls may reduce clinical therapy costs and the possible toxicity of chemical drugs. Full article

Nowadays, consumers are more aware of the effects of their diet on their health, and thus demand natural or minimally processed food products. Therefore, research has focused on processes that assure safe products without jeopardizing their nutritional properties. In this context, this work aimed to evaluate the effects of high-pressure processing (550 MPa/3 min/15 °C, HPP) on a fruit salad (composed of melon juice and pieces of Golden apple and Rocha pear) throughout 35 days of storage at 4 °C. For the physicochemical properties analysed (browning degree, polyphenol oxidase activity, antioxidant activity (ABTS assay), and volatile profile), a freshly made fruit salad was used, while for the microbiological tests (total aerobic mesophiles, and yeast and moulds) spoiled melon juice was added to the fruit salad to increase the microbial load and mimic a challenge test with a high initial microbial load. It was determined that processed samples were more microbiologically stable than raw samples, as HPP enabled a reduction of almost 4-log units of both total aerobic mesophiles and yeasts and moulds, as well as an almost 1.5-fold increase in titratable acidity of the unprocessed samples compared to HPP samples. Regarding browning degree, a significant increase (p < 0.05) was observed in processed versus unprocessed samples (roughly/maximum 68%), while the addition of ascorbic acid decreased the browning of the samples by 29%. For antioxidant activity, there were no significant differences between raw and processed samples during the 35 days of storage. An increase in the activity of polyphenol oxidase immediately after processing (about 150%) was confirmed, which was generally similar or higher during storage compared with the raw samples. Regarding the volatile profile of the product, it was seen that the compounds associated with melon represented the biggest relative percentage and processed samples revealed a decrease in the relative quantity of these compounds compared to unprocessed. Broadly speaking, HPP was shown to be efficient in maintaining the stability and overall quality of the product while assuring microbial safety (by inactivating purposely inoculated microorganisms), which allows for longer shelf life (7 versus 28 days for unprocessed and processed fruit salad, respectively). Full article

Dioecious plants are often used in landscaping because of sex differences in individual appearance, resistance and ornamental value. Although a large number of studies have investigated the overall differences in resource allocation between different sexes in dioecious plants, the effects of environmental factors such as temperature and precipitation on resource allocation in sex-dimorphic plants are not fully understood. In order to explore the influencing factors, 39 works of literature on dioecious plant resource allocation published in English databases from 1992 to 2023 were selected, and the biomass data of dioecious plant stems, leaves, flowers and fruits from these pieces of literature were extracted. A total of 545 independent experimental groups were obtained, which were divided into four groups for analysis, and the data were analyzed using METAWIN 2.1 software. Four sets of data were used to quantitatively study the effects of different temperatures, precipitations and life forms on the resource allocation of dioecious plants of different sexes in large-scale space. The results showed that female plants invested more resources in reproductive growth and less resources in vegetative growth. In terms of total biomass, the average biomass of female plants was 3.09% higher than that of male plants, indicating that female plants reduced nutrient investment to compensate for reproductive investment in the process of resource allocation. Temperature and precipitation significantly affect the adaptability of male and female plants to environmental changes and the cooperative relationships among the stressed components. The vegetative biomass investment of female plants showed a positive correlation with the increase in temperature, while the reproductive biomass showed a negative correlation with the decrease. The average annual precipitation had little effect on the vegetative biomass of dioecious plants, but had a significant effect on reproductive biomass. The study of this trade-off relationship is helpful in revealing the relationship between vegetative growth and reproductive growth of plants, exploring the countermeasures of plant life history, and providing a scientific basis for urban landscaping and urban forest management. Full article

The integration of semi-transparent photovoltaics into the roof of greenhouses is an emerging technique used in recent years, due to the simultaneous energy and food production from the same piece of land. Although shading in many cases is a solution to maintain the desired microclimate, in the case of photovoltaic installations, the permanent shading of the crop is a challenge, due to the importance of light to the growth, morphogenesis, and other critical physiological processes. In this study, the effect of shade from semi-transparent photovoltaics on a strawberry crop (Fragaria x ananassa Duch.) was examined, in terms of growth and quality (phenolic and flavonoid concentration of fruits). According to the results, in non-shaded plants, there was a trend of larger plants, but without a significant change in leaf number, while the total number of flowers was slightly higher at the end of the cultivation period. Moreover, it was found that the percentage change between the number of ripe fruits was smaller than that of the corresponding change in fruit weight, implying the increased size of the fruits in non-shaded plants. Finally, regarding the antioxidant capacity, it was clearly demonstrated that shading increased the total phenolic content, as well as the free-radical-scavenging activity of the harvested fruits. Although the shading from the semi-transparent photovoltaics did not assist the production of large fruits, it did not affect their number and increased some of their quality characteristics. In addition, the advantageous impact of the semi-transparent photovoltaics in the energy part must not be neglected. Full article

In banana cultivation, a considerable amount of the production is wasted every year because of various constraints present in the post-harvest management chain. Converting green banana pulp and peels into flour could help to reduce losses and enable the food sector to keep the product for an entire year or more. In order to use green banana fruit and peel flour in the food industry as a raw ingredient such as in bakery and confectionery items—namely biscuits, cookies, noodles, nutritious powder, etc.—it is essential to standardize the process for the production of the flour. As a result, the purpose of this study was to investigate the influence of pretreatment and temperature on the drying capabilities and quality of dried green banana peel. The green banana peel pieces were pretreated with 0.5 and 1.0% KMS (potassium metabisulfite), and untreated samples were taken as control, and dried at 40°, 50°, and 60 °C in a tray dryer. To reduce the initial moisture content of 90–91.58% (wb) to 6.25–9.73% (wb), a drying time of 510–360 min was required in all treatments. The moisture diffusivity (D_eff) increased with temperature, i.e., D_eff increased from 5.069–6.659 × 10⁻⁸, 6.013–7.653 × 10⁻⁸, and 4.969–6.510 × 10⁻⁸ m²/s for the control sample, 0.5% KMS, and 1.0% KMS, respectively. The Page model was determined to be the best suited for the drying data with the greatest R² and the least χ² and RSME values in comparison with the other two models. When 0.5% KMS-pretreated materials were dried at 60 °C, the water activity and drying time were minimal. Hue angle, chroma, and rehydration ratio were satisfactory and within the acceptable limits for 0.5% KMS-pretreated dried banana peel at 60 °C. Full article

Chemical management of the peach fly, Bactrocera zonata has been compromised due to adverse effects of pesticide residues that not only contaminate environment but also affect non-target organisms including beneficial insects, birds, aquatic life, and soil microorganisms. They can be impacted through direct exposure or by consuming contaminated prey or plants. The present study was designed keeping in view this increasing demand of the consumers to get pesticide residue free fruit and vegetable produce because it reflects the growing consumer concern for food safety and environmental sustainability, motivating the need for alternative pest management strategies. The field experiment was conducted to determine the best slow-release formulation prepared by mixing the following five different types of waxes, including Candelilla wax (CanW), Paraffin wax (PW), Carnauba wax (CarW), Lanolin wax (LW) and Bees wax (BW) with methyl eugenol (ME) (to attract male B. zonata). The selection of the five different types of waxes was likely based on their biodegradability, availability, and potential for slow-release properties. The result revealed that formulations containing SRF-7[LW], SRF-9[CanW], SRF-8[BW], SRF-9[CarW] and SRF-9[PW] exhibited the maximum capture of 42.10 ± 8.14, 43.30 ± 1.76, 34.30 ± 2.96, 35.30 ± 3.18 and 22.70 ± 3.18 male B. zonata per trap per day, respectively. These effective formulations were further evaluated in experiment in which the comparative trapping efficiency of each wax formulation was assessed. The results demonstrated that formulation containing SRF-9[CanW] was expressed maximum capture 13.77 ± 1.26 male B. zonata per trap per day. These formulations were further evaluated in another experiment in which the trapping efficiency was assessed by four different application methods (simple bottle trap, simple bottle trap with water, yellow sticky trap and jute piece with sticky material). The results demonstrated that formulation containing SRF-9[CarW] applied by yellow sticky trap (YST) trapped 61.74 + 7.69 male B. zonata per trap per day and proved more effective. This formulation can be recommended for trapping and management of male population of B. zonata in fruit orchards. This study can influence eco-friendly B. zonata pest control policies, reducing chemical pesticide usage and promoting agricultural sustainability. Future research should study the long-term impact of slow-release formulations on agricultural sustainability, including pest control, crop yield, and agroecosystem health. Full article

Cancer rates are increasing, and cancer is one of the main causes of death worldwide. Amygdalin, also known as vitamin B17 (and laetrile, a synthetic compound), is a cyanogenic glycoside compound that is mainly found in the kernels and pulps of fruits. This compound has been proposed for decades as a promising naturally occurring substance which may provide anticancer effects. This is a comprehensive review which critically summarizes and scrutinizes the available studies exploring the anticancer effect of amygdalin, highlighting its potential anticancer molecular mechanisms as well as the need for a nontoxic formulation of this substance. In-depth research was performed using the most accurate scientific databases, e.g., PubMed, Cochrane, Embase, Medline, Scopus, and Web of Science, applying effective, characteristic, and relevant keywords. There are several pieces of evidence to support the idea that amygdalin can exert anticancer effects against lung, breast, prostate, colorectal, cervical, and gastrointestinal cancers. Amygdalin has been reported to induce apoptosis of cancer cells, inhibiting cancer cells’ proliferation and slowing down tumor metastatic spread. However, only a few studies have been performed in in vivo animal models, while clinical studies remain even more scarce. The current evidence cannot support a recommendation of the use of nutritional supplements with amygdalin due to its cyano-moiety which exerts adverse side effects. Preliminary data have shown that the use of nanoparticles may be a promising alternative to enhance the anticancer effects of amygdalin while simultaneously reducing its adverse side effects. Amygdalin seems to be a promising naturally occurring agent against cancer disease development and progression. However, there is a strong demand for in vivo animal studies as well as human clinical studies to explore the potential prevention and/or treatment efficiency of amygdalin against cancer. Moreover, amygdalin could be used as a lead compound by effectively applying recent developments in drug discovery processes. Full article

Given the allergic reaction caused by mangoes, nonthermal food technologies for allergenicity reduction are urgently desired. This study aimed to assess the impact of kombucha fermentation on the allergenicity of mangoes. The total proteins, soluble proteins, peptides, amino acid nitrogen, the SDS–PAGE profiles of the protein extracts, and immunoreactivity of the sediment and supernatant were measured in two fermentation systems (juices and pieces fermentation). Throughout the fermentation, the pH decreased from about 4.6 to about 3.6, and the dissolved oxygen reduced about 50% on average. However, the protein degradation and sensitization reduction of mangoes were different between the two fermentation systems. In juices fermentation, there was a drop in proteins and peptides but an increase in amino acids, due to the conversion of proteins and peptides into amino acids both in the supernatant and sediment. The allergenicity decreased both in the solid and liquid phases of juices fermentation. In pieces fermentation, proteins and peptides were decreased in the solid phase but increased in the liquid phase. This was due to the fact that proteins and peptides were partly transported into the culture liquid, resulting in a decrease of allergenicity in fruit pieces and an increase in culture liquid. The principal component analysis results showed that the fermentation type had significant effects on the protein degradation and sensitization reduction, while mango variety had no significant effect. These results demonstrate that kombucha fermentation can reduce the allergenicity of mangoes, and it is more effective in juices fermentation than in pieces fermentation. The present study provides a theoretical basis for developing hypoallergenic mango products. Full article

Internal browning caused by prolonged cold storage poses a significant challenge to the visual appearance and flavor of Asian pears, which are economically valuable and a primary fruit exported from Korea. To address this issue, we established a cost-effective portable non-destructive piece of testing instrument using visible and near-infrared spectroscopy, focusing on the detection and discrimination of internal browning in ‘Greensis’ pears. Our investigation underscores the challenge of visually confirming browning, necessitating alternative methods for accurate assessment. Through comprehensive analysis involving three to four segments of 32 ‘Greensis’ pears, a robust calibration equation was derived. By employing partial least square regression on the absorption spectra within a 650–950 nm range, we developed a predictive model for detecting and quantifying browning. Through principal component analysis, normal pears were distinctly segregated from those exhibiting browning symptoms (discrimination accuracy of 95%). Furthermore, we established that pears with a browning index of 25 ± 2.0 are highly susceptible to browning following extended cold storage. Consequently, our proposed portable non-destructive instrument serves as a pivotal tool for farmers and fruit distributors, enabling efficient and precise selection of high-quality pears in an instance. Overall, our study introduces a practical solution to a pressing issue in the Asian pear industry. Full article