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This article describes a quantitative assessment method proposed to quickly identify the degree of deterioration of hardened leather artefacts. We used three techniques to artificially age samples, namely, dry-heat ageing (DH), UV-ageing (UV), and alkali-thermal ageing (AT). The deterioration mechanisms were studied via thermogravimetry/derivative thermogravimetry (TG/DTG) and attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). Combined with amide III band deconvolution and second derivative fitting, we constructed a method for assessing the degree of deterioration by the relative content of random coils (referred to as R) in the secondary structure of the protein. The results show that with increasing ageing time, the macrostructures and microstructures of the leather changed to varying degrees. This study elucidates the differential behaviour of vegetable-tanned leather collagen under oxidative and hydrolytic mechanisms. Based on the deterioration characteristics and fitting results, we divided the hardened leather into the following three levels. Mild deterioration: 0 ≤ R ≤ 5%; leather with reduced pores and slight dryness and hardness but with a stable collagen structure; if the β-sheet content is ≥ 68% at this point, the leather may be recrosslinked by ultraviolet irradiation. Moderate deterioration: 6 ≤ R ≤ 25%; partial hydrogen bond breaking in leather, loosening of the collagen–tan matrix, dry and hard curling of the leather surface, and fibre cementation. Severe deterioration: R ≥ 40%, β-sheet ≤ 24%, and the α-helix is higher; surface reflection, severe macroscopic deformation and embrittlement, and the breakdown and gelatinization of the three-stranded helical structure of leather proteins. The quantitative analysis method was suitable for studying the deterioration mechanisms and assessing the degree of deterioration in Heishanling leather artefacts, which also provides a new practical scheme for assessing the degree of hardened leather. [ABSTRACT FROM AUTHOR]

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Laccase is an enzyme that plays an important role in fungi, including lignin degradation, stress defense, and formation of fruiting bodies. Auricularia auricula-judae is a white-rot fungus in the Basidiomycota phylum, capable of delignifying wood. In this study, seven genes belonging to the laccase family were identified through de novo sequencing, containing Cu-Oxidase, Cu-Oxidase_2, and Cu-Oxidase_3 domains. Subsequently, the physical characteristics, phylogenetic relationships, protein secondary structure, and tertiary structure of the laccase family (AaLac1–AaLac7) were analyzed. Prediction of N-glycosylation sites identified 2 to 10 sites in the laccase family, with AaLac7 having the highest number of sites at 10. Sequence alignment and analysis of the laccase family showed high consistency in signature sequences. Phylogenetic analysis confirmed the relationship among laccases within the family, with AaLac3–AaLac4 and AaLac5–AaLac6 being closely positioned on the tree, exhibiting high similarity in tertiary structure predictions. This study identified and analyzed laccase family genes in Auricularia auricula-judae using de novo sequencing, offering a simple method for identifying and analyzing the laccase family in organisms with unknown genetic information. [ABSTRACT FROM AUTHOR]

Abstract This article describes a quantitative assessment method proposed to quickly identify the degree of deterioration of hardened leather artefacts. We used three techniques to artificially age samples, namely, dry-heat ageing (DH), UV-ageing (UV), and alkali-thermal ageing (AT). The deterioration mechanisms were studied via thermogravimetry/derivative thermogravimetry (TG/DTG) and attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). Combined with amide III band deconvolution and second derivative fitting, we constructed a method for assessing the degree of deterioration by the relative content of random coils (referred to as R) in the secondary structure of the protein. The results show that with increasing ageing time, the macrostructures and microstructures of the leather changed to varying degrees. This study elucidates the differential behaviour of vegetable-tanned leather collagen under oxidative and hydrolytic mechanisms. Based on the deterioration characteristics and fitting results, we divided the hardened leather into the following three levels. Mild deterioration: 0 ≤ R ≤ 5%; leather with reduced pores and slight dryness and hardness but with a stable collagen structure; if the β-sheet content is ≥ 68% at this point, the leather may be recrosslinked by ultraviolet irradiation. Moderate deterioration: 6 ≤ R ≤ 25%; partial hydrogen bond breaking in leather, loosening of the collagen–tan matrix, dry and hard curling of the leather surface, and fibre cementation. Severe deterioration: R ≥ 40%, β-sheet ≤ 24%, and the α-helix is higher; surface reflection, severe macroscopic deformation and embrittlement, and the breakdown and gelatinization of the three-stranded helical structure of leather proteins. The quantitative analysis method was suitable for studying the deterioration mechanisms and assessing the degree of deterioration in Heishanling leather artefacts, which also provides a new practical scheme for assessing the degree of hardened leather. Graphical Abstract

Protein secondary structure prediction (PSSP) is a pivotal research endeavour that plays a crucial role in the comprehensive elucidation of protein functions and properties. Current prediction methodologies are focused on deep-learning techniques, particularly focusing on multi-factor features. Diverging from existing approaches, in this study, we placed special emphasis on the effects of amino acid properties and protein secondary structure propensity scores (SSPs) on secondary structure during the meticulous selection of multi-factor features. This differential feature-selection strategy results in a distinctive and effective amalgamation of the sequence and property features. To harness these multi-factor features optimally, we introduced a hybrid deep feature extraction model. The model initially employs mechanisms such as dilated convolution (D-Conv) and a channel attention network (SENet) for local feature extraction and targeted channel enhancement. Subsequently, a combination of recurrent neural network variants (BiGRU and BiLSTM), along with a transformer module, was employed to achieve global bidirectional information consideration and feature enhancement. This approach to multi-factor feature input and multi-level feature processing enabled a comprehensive exploration of intricate associations among amino acid residues in protein sequences, yielding a Q3 accuracy of 84.9% and an Sov score of 85.1%. The overall performance surpasses that of the comparable methods. This study introduces a novel and efficient method for determining the PSSP domain, which is poised to deepen our understanding of the practical applications of protein molecular structures.

In order to improve the baking characteristics and nutritional quality of mung bean bread, mung bean sourdough was made by fermenting mung bean flour using Northwest leavening head, and then combined with yeast as a compound leavening agent to make mung bean bread. The microbial composition of the Northwest leavening head was analyzed to clarify the composition of its microflora, the Fourier transform infrared spectrometer and rheometer were used to analyze the changing pattern of the secondary structure and viscoelasticity of gluten proteins in the dough of the mung bean bread, and the texture meter was used in combination with the sensory assessment to evaluate the sensory quality of the mung bean bread. The results showed that the phytic acid content of the mung bean sourdough fermented in the Northwest fermentation head was reduced by 44.71% at 6 h of fermentation, and the pH and total titration acidity (TTA) were 6.29 and 11.03 mL, respectively. Compared with the control group, the bread with added mung bean sourdough showed a decrease in the modulus of elasticity and viscous modulus of the dough, an increase in the plasticity of the dough, the content of α-helices and β-folds in the secondary structure of proteins, and the stability of the dough. The antioxidant results showed that the scavenging ability of mung bean bread for both DPPH and ABTS+ free radicals also significantly increased (P

Background: Protein secondary structure prediction (PSSP) is a critical task in computational biology, pivotal for understanding protein function and advancing medical diagnostics. Recently, approaches that integrate multiple amino acid sequence features have gained significant attention in PSSP research. Objectives: We aim to automatically extract additional features represented by evolutionary information from a large number of sequences while simultaneously incorporating positional information for more comprehensive sequence features. Additionally, we consider the interdependence between secondary structures during the prediction stage. Methods: To this end, we propose a deep neural network model, ILMCNet, which utilizes a language model and Conditional Random Field (CRF). Protein language models (PLMs) pre-trained on sequences from multiple large databases can provide sequence features that incorporate evolutionary information. ILMCNet uses positional encoding to ensure that the input features include positional information. To better utilize these features, we propose a hybrid network architecture that employs a Transformer Encoder to enhance features and integrates a feature extraction module combining a Convolutional Neural Network (CNN) with a Bidirectional Long Short-Term Memory Network (BiLSTM). This design enables deep extraction of localized features while capturing global bidirectional information. In the prediction stage, ILMCNet employs CRF to capture the interdependencies between secondary structures. Results: Experimental results on benchmark datasets such as CB513, TS115, NEW364, CASP11, and CASP12 demonstrate that the prediction performance of our method surpasses that of comparable approaches. Conclusions: This study proposes a new approach to PSSP research and is expected to play an important role in other protein-related research fields, such as protein tertiary structure prediction. [ABSTRACT FROM AUTHOR]

Native huauzontle protein (Pnative) structure was modified by thermal (Pheat), ultrasound (PUS) and pH shifting (PpH11). Soluble complexes (SC) were formed between the huauzontle proteins and a commercial octenyl succinic anhydride modified starch (S). The secondary structure of the native and modified huauzontle proteins differed in terms of abundance of β-sheet, α-helix, and β-turn structures. The pH at which maximum presence of SC was observed varied from 5.1 for Pnative-S to 5.8 for Pus-S complexes, and being the required protein: polysaccharide weight ratio of 1:1 for Pnative-S and of 1:2 for the modified proteins-S. FT-IR confirmed the formation of SC, as the characteristic carboxylate group in S disappeared from its spectra. Also, the absorption peaks of the proteins in the Amide I and II bands shifted slightly from 1630 to 1635 cm− 1 and 1520 to 1510 cm− 1 in the SC, indicating conformational changes due to protein-starch interactions. Aggregation of the biopolymers into relatively large particles was observed by SEM in the SC made with modified proteins. SC showed significant differences in the in vitro protein digestibility values, the lowest (85.1 ± 2.3%) occurring for Pnative-S and the highest (92.7 ± 0.7%) for PUS-S. PpH11-S presented the highest resistant starch content (92.6 ± 0.4%). It is concluded that the modification of Pnative through heat, ultrasound and pH shifting allowed establishing different driving conditions for the formation of SC with S, and in vitro digestibility of protein and starch could also be modified. The improved nutritional properties of SC through modification of the protein structure make them potential ingredients for the formulation of sports drinks or low-calorie dairy products. [ABSTRACT FROM AUTHOR]

BACKGROUND: Goat milk is considered a nutritionally superior resource, owing to its advantageous nutritional attributes. Nevertheless, it is susceptible to spoilage and the persistence of pathogens. Electron beam irradiation stands as a promising non‐thermal processing technique capable of prolonging shelf life with minimal residue and a high degree of automation. RESULTS: The effects of electron beam irradiation (2, 3, 5, and 7 kGy) on microorganisms, physicochemical properties, and protein structure of goat milk compared with conventional pasteurized goat milk (PGM) was evaluated. It was found that a 2 kGy electron beam irradiation reduces the total microbial count of goat milk by 6‐logs, and the irradiated goat milk protein secondary structure showed a significant decrease in ɑ‐helix content. Low irradiation doses led to microaggregation and crosslinking. In contrast, high doses (≥ 5 kGy) slightly disrupted the aggregates and decreased the particle size, disrupting the microscopic surface structure of goat milk, verified by scanning electron microscopy and confocal laser scanning microscopy. CONCLUSION: The irradiation of goat milk with a 2 kGy electron beam may effectively inactivate harmful microorganisms in the milk and maintain/or improve the physicochemical quality and protein structure of goat milk compared to thermal pasteurization. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Objective: Obesity, which arises from changes in lifestyle and feeding habits, poses a threat to human health. One essential contributor to the increase in obesity rates is the popularity of high-calorie diets. This study aims to investigate high-fat (HFD) and high-carbohydrate (HCD) diet-induced molecular changes in protein secondary structure in longissimus dorsi skeletal muscle tissues of female inbred C57BL/6J mice by utilizing Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy. Materials and Methods: Mice were fed a control diet, HCD, or HFD for 24 weeks. Their skeletal muscle tissues were collected, and their spectra were recorded using a Bruker Invenio S ATR-FTIR spectrometer in the 4000-400 cm-1 region. Results: The protein secondary structure profiles of the HCD group demonstrated a significant rise in antiparallel β-sheet and β-turn and a decline in parallel β-sheets, together with the insignificant increase in aggregated β-sheets and a decrease in α-helix. The impact of an HFD on protein conformation is less pronounced than HCD. The HFD diet led to an increase in antiparallel β-sheets and a decrease in parallel βsheets. Although insignificant, an increase was observed in β-turn and α-helix. Conclusion: These results propose the appearance of protein aggregation and/or formation of proteinprotein intermolecular interaction in skeletal muscle tissues of female inbred C57BL/6J mice. Collectively, these data suggest that both high-calorie diets impair secondary structures of protein in skeletal muscle that may affect its metabolic function. [ABSTRACT FROM AUTHOR]

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Copyright of Food & Fermentation Industries is the property of Food & Fermentation Industries and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to improve the phenomenon that frozen cooked noodles are susceptible to the formation of ice crystals and quality deterioration during storage, the effects of mannosylerythritol lipids (MELs) versus sucrose ester (SE) on the proportion of freezable water, water distribution, quality characteristics, gelatinization characteristics of wheat flour and the secondary structures of proteins in frozen cooked noodles were investigated. The results showed that the addition of 0.30%–1.10% (m/m) MELs could promote the conversion of free water to bound water in frozen cooked noodles, reduce the proportion of freezable water, and increase the binding of water to macromolecules such as protein and starch. Compared with the blank and SE groups, the quality of frozen cooked noodles made with 0.70% MELs was better, and the hardness was (4 335.317 ± 48.047) g, which was 25.36% higher than that of the blank group. The tensile force and tensile distance at break were (11.22 ± 0.15) g and (69.09 ± 1.34) mm, respectively. The water absorption rate increased significantly, and the cooking loss rate was the smallest, suggesting MELs to be more effective in improving the cooking quality of noodles than SE. At the same time, MELs could effectively delay the retrogradation rate of wheat flour starch, increase the proportions of the secondary structure fractions β-sheet and α-helix, and strengthen the gluten network structure.

The effects of high-pressure homogenization (HPH) at different pressures (30, 40, 50 and 60 MPa) on the hydration properties and crystallinity of bamboo shoot dietary fiber (BSDF) were studied as well as the effect of HPH-treated BSDF on the gel strength, water-holding capacity (WHC), protein secondary structure, chemical interactions and microstructure of heat-induced gels from shrimp surimi. The results showed that the WHC, oil-holding capacity (OHC), and swelling capacity of BSDF were positively correlated with homogenization pressure (P < 0.05). However, too small size of fiber particles affected its combination with hydrophilic groups, which could reduce the water absorption and swelling properties. X-ray diffraction (XRD) and scanning electron microscopic (SEM) results demonstrated that the crystallinity of BSDF decreased after medication, and the fiber bundle structure was destroyed, becoming loose and porous. Compared with the surimi added with unmodified BSDF, the gel strength of shrimp surimi added with BSDF treated at 30, 40, 50, and 60 MPa were increased by 10.04%, 17.87%, 28.76%, 28.49%, and WHC increased by 3.48%, 5.74%, 13.04%, and 12.70%, respectively. Fourier transform infrared (FTIR) spectral analysis showed that the contents of α-helix and random coil in the modified BSDF-supplemented shrimp surimi gel decreased, while the contents of β-sheet and β-turn increased significantly, suggesting more stable secondary structure of proteins. The results of chemical interaction analysis showed that modified BSDF promoted the hydrophobic interactions and the formation of disulfide bonds in shrimp surimi gel, with a more pronounced effect being observed with BSDF treated at 50 and 60 MPa. SEM results showed that shrimp surimi gel added with BSDF treated at 60 MPa had a more uniform and denser three-dimensional network structure. These results showed that HPH treatment could improve the hydration properties, and reduce the crystallinity of BSDF, and HPH-treated BSDF could significantly enhance the gelation properties of heat-induced shrimp surimi, which will provide a theoretical basis for improving the application of BSDF in shrimp surimi gels.

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Food Science & Biotechnology is the property of Journal of Food Science & Biotechnology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study evaluated the effects of photothermal aging and the particle sizes of pigments upon the proteinaceous binder used in ancient wall paintings. Changes in the morphological characteristics, thermal properties, spectral characteristics, and protein secondary structure for pure and mixed samples after aging were studied by laser particle size analysis, scanning electron microscopy (SEM), thermogravimetric analysis with differential scanning calorimetry (TGA-DSC), and attenuated total reflection – Fourier transform infrared spectroscopy (ATR-FTIR). The morphology was flatter for the mixed samples with smaller particle sizes, while those with larger particle sizes were filled with interstices, and severe cracking and flaking appeared after aging. By comparison with pure rabbit skin glue, TGA-DSC showed that the thermal stability decreased for the mixed samples as the particle size increased. ATR-FTIR demonstrated that the intensities of the absorbance peaks for the glue increased as the size of the azurite pigment particles decreased. The spectra for the mixed samples after aging were blue-shifted for amide I and red-shifted for amide II, where the shifts were higher as the particle size decreased. In addition, the infrared peak fitting confirmed that the protein secondary structure contents significantly changed after aging and the changes were correlated with the sizes of the particles. [ABSTRACT FROM AUTHOR]

This research examined the impact of defatted coconut flour (DCF)-based oleogels on the quality of surimi. Microscopic analysis indicated that the dietary fiber present in DCF could act as the main structure of the oleogels network. The formation of the oleogels network primarily relies on the tensile intramolecular or intermolecular hydrogen bonds between DCF and corn oil. The oleogels displayed oil binding capacity of up to 96.95% and exhibited favorable mechanical and rheological properties. Efforts were undertaken to integrate the acquired oleogels into silver carp surimi to create oil-fortified surimi products. Adding oleogels significantly enhanced the gel strength, texture, and water-holding capacity of surimi compared to adding corn oil. Especially, oleogels containing 5.0 % (w/v) DCF concentration elevated the lipid content in the surimi and preserved the gel and texture properties. Therefore, incorporating oleogels in surimi presents a potential solution for enhancing the nutritional content of surimi products.

In order to verify the nutritional and quality properties of gluten-free breads supplemented with flour from cacay seed cake (CF), a mixing design was used, in which part of the rice (R) was replaced with CF and dietary fiber concentrates (DFC) from papaya pulp and peel. The results showed that supplementation of the formulations with CF and DFC produced an increase in the gel strength parameter (S) of the batter before baking, with respect to that of a control formulation (542 vs. 3.1 Pa.sn, respectively). It was also found that there was an improvement in the specific volume (1.598 vs. 1.32 cm3/g), crumb pore diameter (3.4 vs. 2.2 mm), protein content (10.5 vs. 2.6 g/100 g) and total dietary fiber (9.9 vs. 1.2 g/100 g) of the supplement breads (SB) over the control breads (CB). The results of the creep and recovery test parameters, performed on the bread crumb, showed a greater elastic response in the SB, evidenced by a greater recovery of the crumb structure. It is concluded that CF and DFC as ingredients improve the nutritional content of gluten-free baked goods and also that the improvements in specific volume and pore size would be related to dietary fiber.

The quantitative and highly sensitive detection of biomarkers such as Tau proteins and Aβ polypeptides is considered one of the most effective methods for the early diagnosis of Alzheimer's disease (AD). Surface-enhanced Raman spectroscopy (SERS) detection is a promising method that faces, however, challenges like insufficient sensitivity due to the non-optimized nanostructures for specialized analyte sizes and insufficient control of the location of SERS hot spots. Thus, the SERS detection of AD biomarkers is restricted. We reported here an in-depth study of the analytical Raman enhancement factor (EF) of the wafer-scale graphene-Au nanopyramid hybrid SERS substrates using a combination of both theoretical calculation and experimental measurements. Experimental results show that larger nanopyramids and smaller gap spacing lead to a larger SERS EF, with an optimized analytical EF up to 1.1 × 1010. The hybrid SERS substrate exhibited detection limits of 10–15 M for Tau and phospho-Tau (P-Tau) proteins and 10–14 M for Aβ polypeptides, respectively. Principal component analysis correctly categorized the SERS spectra of different biomarkers at ultralow concentrations (10–13 M) using the optimized substrate. Amide III bands at 1200–1300 cm–1 reflect different structural conformations of proteins or polypeptides. Tau and P-Tau proteins are inherently disordered with a few α-helix residuals. The structure of Aβ42 polypeptides transitioned from the α-helix to the β-sheet as the concentration increased. These results demonstrate that the hybrid SERS method could be a simple and effective way for the label-free detection of protein biomarkers to enable the rapid early diagnosis of AD and other diseases. [ABSTRACT FROM AUTHOR]

Bioprosthetic valves are employed to replace defective heart valves. However, structural degeneration is prevalent in bioprosthetic valves because the heart valve leaflets are exposed to extreme and repetitive cardiovascular pressure. Herein, a silk fibroin‐based heart valve leaflet, which executes the physiological role of a heart valve, is developed. To this end, a templated assembly technology is developed. Notably, a physically optimal hierarchical structure for replacing the natural heart valve leaflet is realized by numerous firmly stacked β‐sheet crystals distributed within collective tyrosine‐reinforcing amorphous strands. Almost half (46.9%) of the silk fibroin‐based heart valve leaflet comprises strongly stacked β‐sheet crystals, leading to a 292% enhancement in stacking strength. The templated assembly results in the entanglement of amorphous strands, upregulating the non‐covalent interactions within the tyrosine. Consequently, the strength is enhanced by 1380% compared to native silk fibroin. Moreover, the templated assembly enhances the static and dynamic mechanical properties, thereby delivering a desirable performance for its use in heart valve replacement. Interestingly, the aortic valve composed of silk fibroin‐based leaflets does not fail under the cardiovascular pressure of 60–180 mmHg. Furthermore, the valve performance is satisfactory and surmounts the requirements of the industrial standard ISO 5840. [ABSTRACT FROM AUTHOR]

High salinity inhibits microbial activity in the bioremediation of saline wastewater. To alleviate osmotic stress, glycine betaine (GB), an osmoprotectant, is added to enhance the secretion of extracellular polymeric substances (EPS). These EPS are pivotal in withstanding environmental stressors, yet the intricate interplay between GB supplementation and microbial responses through EPS modifications—encompassing composition, molecular architecture, and electrochemical features—remains elusive in hypersaline conditions. Here we show microbial strategies for salinity endurance by investigating the impact of GB on the dynamic alterations of EPS properties. Our findings reveal that GB supplementation at 3.5% salinity elevates the total EPS (T-EPS) content from 12.50 ± 0.05 to 24.58 ± 0.96 mg per g dry cell weight. The observed shift in zeta potential from −28.95 to −6.25 mV at 0% and 3.5% salinity, respectively, with GB treatment, indicates a reduction in electrostatic repulsion and compaction. Notably, the EPS protein secondary structure transition from β-sheet to α-helix, with GB addition, signifies a more compact protein configuration, less susceptible to salinity fluctuations. Electrochemical analyses, including cyclic voltammetry (CV) and differential pulse voltammetry (DPV), reveal GB's role in promoting the release of exogenous electron shuttles, such as flavins and c-type cytochromes (c-Cyts). The enhancement in DPV peak areas (QDPV) with GB addition implies an increase in available extracellular electron transfer sites. This investigation advances our comprehension of microbial adaptation mechanisms to salinity through EPS modifications facilitated by GB in saline habitats.

The scope of the present study was to study the effect of different populations of Hermetia illucens, commonly known as black soldier fly (BSF), on the major components and volatile composition of the derived freeze-dried flours. Potential differences in the composition of different life cycle stages of BSF, i.e., larvae and pupae, were also investigated. The flours obtained from larvae of two BSF populations from Greece (GR) and Portugal (PO) (L-GR and L-PO, respectively) demonstrated similar major chemical compositions. Pupae (Pu-PO) were richer in chitin compared to larvae. Differences were spotted in their fatty acid profiles and volatile fractions. The saturated/unsaturated lipid fraction ratio was 1.5 in L-GR, higher in L-PO (2.5), and even higher in the case of Pu-PO (4.0). Seventeen (17) compounds were detected in the volatile fraction of the Pu-PO samples and 24 in the volatile fraction of the L-GR and L-PO samples. Notably, dodecanoic acid ethyl ester was the predominant volatile compound in all samples. The proteins of both larvae and pupae were dominated by β-sheet structures. The present study's findings are valuable for designing food or feed products based on BSF components and could be important for applying suitable manufacturing and processing procedures.

Hardness of wheat endosperm is a physical property that depends on the genetic makeup of the grain and varies amongst different types/varieties. It is associated with proteins, particularly 14–15 kDa friabilins, which exist in higher amounts at the surface of starch in soft wheat grains while either absent or occur in smaller quantities on granules of hard wheat varieties. The storage proteins in hard wheat flours exhibit a higher proportion of polymeric proteins, β-sheets and β-turns. Soft wheat starches show lower crystallinity, amylose-lipid complex content and proportion of A-type granules (disk or lenticular-shaped granules with diameter >10 µm) while higher gelatinisation temperatures, swelling, breakdown susceptibility and retrogradation than hard wheat starches. Flours from hard and soft wheat also differ for processing and end-use quality based on differences in dough rheological properties, solvent retention capacities and particle size.

To explore the effects of crushing processes on the rheological properties and edible quality of minced meat, blunt cutting tool and sharp cutting tool on two devices of beating machine and chopping machine were used to prepare minced meat. The pH value, salt soluble protein content, protein secondary structure, particle size distribution, color, stability and cooking loss, water holding capacity, texture characteristics and microstructure of minced meat gel were investigated. The results showed that the four crushing processes had different degrees of muscle fiber fragmentation, resulting in different properties of the low-fat minced meat and the resulting gel. Compared with the beater, the low-fat minced meat treated by the chopper had a higher G′ value in the temperature scanning. The low-fat minced meat beaten with blunt knife had the lowest viscosity and showed poor stability in frequency scanning. The high intensity cutting action of the chopper resulted in a lower end temperature and smaller particle size of the broken low-fat minced meat, and higher water holding capacity of the low-fat minced meat gel. Compared with the other three processes, the blunt knife chopped low-fat minced meat had the highest redness value (15.95), pH value (6.66), salt-soluble protein content (77.05 mg/mL), relative content of β-fold (43.71%), and the low-fat minced meat gel had the lowest cooking loss (17.48%), the highest hardness (4147.72 g), gumminess (2883.72), chewiness (2496.02 g), sensory scores, which may be attributed to the tighter microstructure of low-fat minced meat gel formed by this treatment with moderate muscle fragmentation. Therefore, the blunt chopping is suitable for the crushing production of low-fat minced meat, which can improve its salt-soluble protein content, relative content of β-sheet, redness, water holding capacity and texture properties.

The effects of different freezing temperatures (–20 ℃, –40 ℃, –80 ℃) on the re-steaming quality and component properties of frozen whole wheat steamed bread with different whole wheat flour replacement rates (30%, 50%, 100%) were analyzed. The results showed that the specific volume retention of the re-steamed whole wheat steamed bread was higher and the texture quality of the re-steamed whole wheat steamed bread was better with the lower freezing temperature and the faster freezing speed. Freezing temperature had no significant effect on the height/diameter ratio of frozen steamed bread with different whole wheat flour replacement rate. At –20 ℃, the hardness of frozen steamed bread with different whole wheat flour replacement rate was significantly higher than that of fresh steamed bread after re-steaming. At –80 ℃, the hardness of steamed breads is similar to that of fresh steamed bread after re-steaming. With the decrease of freezing temperature, the starch gelatinization enthalpy of frozen whole wheat steamed bread was lower, and the index value of starch gelatinization characteristics of 100% frozen whole wheat steamed bread was similar to that of fresh steamed bread, 30% and 50% whole wheat steamed bread were closer to that of fresh steamed buns at –40 ℃ freezing temperature. The lower the extractability of gluten protein was in frozen steamed buns at lower freezing temperature, the smaller the damage of gluten protein structure was. The damage to the internal microstructure of whole wheat steamed buns was smaller at lower freezing temperature, and its quality was closer to that of fresh steamed buns. In short, the lower freezing temperature is conducive to keeping the better quality of whole wheat steamed buns. To provide basis and reference for frozen whole wheat steamed buns processing and quality improvement.

In this study, the effects of six thawing methods (flowing water thawing, FWT; water immersion thawing, WIT; room temperature air thawing, RTAT; low temperature air thawing, LTAT; ultrasonic-assisted thawing, UAT; and microwave thawing, MT) on water holding capacity (WHC), shear force, tissue microstructure, thiobaric acid active substances (TBARS), myofibrillar fragmentation index (MFI), protein secondary structure and myofibrillar protein (MP) oxidation of frozen chicken feet were investigated. The results demonstrated that UAT improved the sample tenderness with a minimum shear force of 775.67 ± 63.30 g. The WHC of the UAT sample also presented a high level; the thawing and cooking losses reached 4.20 ± 0.33% and 3.23 ± 0.35%, respectively. Although the LTAT sample presented a lower loss in the thaw (2.72 ± 0.23%) and a high α-helix content (30.54 ± 1.69%), it showed a significantly higher TBARS value (0.62 mg MDA/kg) (P

This study was conducted in order to explore the effect of lead (Pb) stress on the nutritional value and flavor of barley seedling powder. Fourier transform infrared (FTIR) spectroscopy and targeted metabolomics based on liquid chromatography-mass spectrometry (LC-MS) were used for quantitative and qualitative analysis of protein secondary structure and amino acid contents in barley seedling powders with and without Pb stress during growth. The results showed that Pb stress led to the transformation of protein secondary structure in barley seedlings from disordered (β-turn and random coil) to ordered (α-helix) structure. Through high-throughput targeted metabolomic analysis, a total of 25 amino acids were identified and quantified in barley seedling powder. Pb stress decreased the contents of Arg, Pro and His, but increased the content of Val, which proves that Pb could reduce the nutritional value and sweetness, and increase the bitterness of barley seedling powder. These results provide some basic data for the development of barley-based health foods.

Abstract Background Protein secondary structures that link simple 1D sequences to complex 3D structures can be used as good features for describing the local properties of protein, but also can serve as key features for predicting the complex 3D structures of protein. Thus, it is very important to accurately predict the secondary structure of the protein, which contains a local structural property assigned by the pattern of hydrogen bonds formed between amino acids. In this study, we accurately predict protein secondary structure by capturing the local patterns of protein. For this objective, we present a novel prediction model, AttSec, based on transformer architecture. In particular, AttSec extracts self-attention maps corresponding to pairwise features between amino acid embeddings and passes them through 2D convolution blocks to capture local patterns. In addition, instead of using additional evolutionary information, it uses protein embedding as an input, which is generated by a language model. Results For the ProteinNet DSSP8 dataset, our model showed 11.8% better performance on the entire evaluation datasets compared with other no-evolutionary-information-based models. For the NetSurfP-2.0 DSSP8 dataset, it showed 1.2% better performance on average. There was an average performance improvement of 9.0% for the ProteinNet DSSP3 dataset and an average of 0.7% for the NetSurfP-2.0 DSSP3 dataset. Conclusion We accurately predict protein secondary structure by capturing the local patterns of protein. For this objective, we present a novel prediction model, AttSec, based on transformer architecture. Although there was no dramatic accuracy improvement compared with other models, the improvement on DSSP8 was greater than that on DSSP3. This result implies that using our proposed pairwise feature could have a remarkable effect for several challenging tasks that require finely subdivided classification. Github package URL is https://github.com/youjin-DDAI/AttSec .

Functional characteristics of lentil's protein have a significant impact on texture of developed food products and are an important consideration for ingredient manufacturers in food industries. Soaking/germination and thermal treatments are well-known methods in modifying these characteristics by altering protein structure. Therefore, in this study, the combination of these methods at two heat intensity categories, above and below protein denaturation, was utilized to examine modification of the structural, nutritional, and functional properties of processed lentil flours. The results showed that processing of lentil seeds impacted their protein secondary structure from ordered to disordered structures, by decreasing β-sheet and α-helix and increasing intermolecular β aggregates and random coil conformation. In terms of nutritional value, the applied processing improved lentil flours by higher protein content after germination and enhanced protein digestibility after thermal processing. Generally, protein solubility was negatively affected by thermal conditions, with microwave-infrared drying having the most significant impact on reducing protein solubility. Mostly, the processing did not noticeably affect the emulsifying activity and oil binding capacity, while it significantly reduced emulsifying stability at high-temperature methods. The findings suggests that germination-thermal processing combination enhances nutritional/functional properties of lentil flours and provides opportunities for their incorporation into value-added food product formulations.

Protein secondary structure prediction is a subproblem of protein folding. A light-weight algorithm capable of accurately predicting secondary structure from only the protein residue sequence could provide useful input for tertiary structure prediction, alleviating the reliance on multiple sequence alignments typically seen in today's best-performing models. Unfortunately, existing datasets for secondary structure prediction are small, creating a bottleneck. We present PS4, a dataset of 18,731 nonredundant protein chains and their respective secondary structure labels. Each chain is identified, and the dataset is nonredundant against other secondary structure datasets commonly seen in the literature. We perform ablation studies by training secondary structure prediction algorithms on the PS4 training set and obtains state-of-the-art accuracy on the CB513 test set in zero shots.

Copyright of Science & Technology of Cereals, Oils & Foods is the property of Science & Technology of Cereals, Oils & Foods Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chinese Institute of Food Science & Technology / Zhongguo Shipin Xuebao is the property of Journal of Chinese Institute of Food Science & Technology Periodical Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: The physicochemical and gelation properties of krill mince were investigated in relation to the cryoprotective effect of kappa‐carrageenan (KC), carrageenan oligosaccharides (CGO), chitosan oligosaccharides (COS), and alginate oligosaccharides (AOS). The water‐holding capacity of krill mince decreased during freezing–thawing (FT) circles, but KC and three oligosaccharides prevented this decline by increasing hydrogen and ionic bonding. The denaturation and degradation of proteins in krill samples added with oligosaccharides were alleviated with less decrease in protein solubility and Ca2+‐ATPase activity, as well as higher intensity protein bands of myosin heavy chain and paramyosin subject to 9‐FT circles. The notable increase in TBARS value (P < 0.05) was observed after 3‐FT circles, however, with relatively lower values with the addition of AOS and CGO, demonstrating antioxidative ability against lipid oxidation. Additionally, CGO exhibited higher protein secondary structure maintenance stability, evidenced by a less dramatic decrease in α‐helical fraction than other oligosaccharides. The overall gelation and textural properties of krill mince with CGO could be better maintained with no more than 3‐FT circles. [ABSTRACT FROM AUTHOR]

Abstract Background Dietary bamboo leaf flavonoids (BLFs) are rarely used in poultry production, and it is unknown whether they influence meat texture profile, perceived color, or microstructure. Results A total of 720 one-day-old Arbor Acres broilers were supplemented with a basal diet with 20 mg bacitracin/kg, 50 mg BLFs/kg, or 250 mg BLFs/kg or without additions. Data showed that the dietary BLFs significantly (P

Protein structure prediction (PSP) is a vital challenge in bioinformatics, structural biology and drug discovery. Protein secondary structure (SS) prediction is critical since three-dimensional (3D) structures are primarily made up of secondary structures. With the advancement of deep learning approaches, SS classification accuracy has been significantly improved. Many existing methods use an ensemble of complex neural networks to improve SS prediction. Because of the high dimensionality of the hyperparameter space, deep neural networks with complex architectures are typically challenging to train effectively. Also, predicting secondary structures in the boundary regions between different types of SS is challenging. This study presents Multi-S3P, which employs bidirectional Long-Short-Term-Memory (BILSTM) and Convolutional Neural Networks (CNN) with a self-attention mechanism to improve the secondary structure prediction using an effective training strategy to capture the unique characteristics of each type of secondary structure and combine them more effectively. The ensemble of CNN and BILSTM can learn both contextual information and long-range interactions between the residues. In addition, using a self-attention mechanism allows the model to focus on the most important features for improving performance. We used the SPOT-1D dataset for the training and validation of our model using a set of four input features derived from amino acid sequences. Further, the model was tested on four popular independent test datasets and compared with various state-of-the-art predictors. The presented results show that Multi-S3P outperformed the other methods in terms of Q3, Q8 accuracy and other performance metrics, achieving the highest Q3 accuracy of 87.57% and a Q8 accuracy of 77.56% on the TEST2016 test set. More importantly, Multi-S3P demonstrates high performance in SS boundary regions. Our experiment also demonstrates that the combination of different input features and a multi-network-based training strategy significantly improved the performance.

The effects of propylene glycol alginate (PGA) on the storage stability of frozen whole wheat flour dough were investigated, as well as the changes in baking quality of the frozen dough. The stability of frozen dough was evaluated by measuring the fermentation characteristics, rheological properties, secondary structure of protein, microstructure, specific volume, texture properties, internal texture structure, and aging degree of frozen dough after 1, 2, 3, 4 and 5 weeks after adding 0.3% PGA to whole wheat flour dough. The results showed that after 5 weeks of frozen storage, the frozen dough with PGA had a higher water holding capacity, as well as improved fermentation and rheological properties, as compared to the control group. After 5 weeks of freezing, compared with bread made from unfrozen dough, the specific volume of bread in control group and PGA group decreased by 19.872% and 14.153%, bread hardness increased by 64.186% and 36.386%, and area fraction (AF) decreased by 3.497% and 2.300% respectively for bread made from dough with and without PGA after 5 weeks frozen storage. Accordingly, the retrogradation enthalpy value increased by 65.142% and 42.416%. The addition of PGA to frozen dough could slow down the increase of relative content of β-sheet and the decrease of relative content of β-turn structures caused by frozen storage. SEM photos of the frozen dough supplemented with PGA revealed fewer and even-sized holes, and the integrity and continuity of gluten network structure increased. These findings suggest that PGA can help slow down the deterioration of dough during frozen storage, improving frozen dough stability and baking properties.

Hair or bristle is one of the key by-products of humane slaughter of pigs. In the present study, Fourier-transform infrared (FTIR) spectroscopy was used for examining protein secondary structure of hair fiber from different breeds of pigs (Ghungroo, Ninag Megha, Hampshire, and Duroc). Prominent amide I (1635–1648 cm−1) and amide II (1517–1528 cm −1) bands could be observed in the spectra. Differences in presence/absence of certain FTIR bands between breeds suggests influence of genetic background in the structure of hair fiber. Deconvolution resolved secondary structure of protein in amide I region of spectra into corresponding α-helix (38.0 ± 2.9%), β-sheets (32.2 ± 2.0%), β-turns (19.4 ± 3.1%) and unorganized structural components (10.3 ± 2.5%). Heating of fibers from 80°C to 120°C resulted in changes in amide regions and α-helix to β-sheet ratio of amide I band. Further, correlations were calculated between area under the curve of various FTIR bands and tensile properties of the fiber. Area of FTIR band at 1635 cm −1 was positively correlated with tenacity, initial modulus, extensibility, and work of rupture (r = 0.30 to 0.39). In nutshell, the study reveals subtle differences in secondary structure of hair with respect to breed or temperature treatment and suggests relation between FTIR spectral characteristics and tensile properties.

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Determining Secondary Structure Elements (SSEs) for any protein is crucial as an intermediate step for experimental tertiary structure determination. SSEs are identified using popular tools such as DSSP and STRIDE. These tools use atomic information to locate hydrogen bonds to identify SSEs. When some spatial atomic details are missing, locating SSEs becomes a hinder. To address the problem, when some atomic information is missing, three approaches for classifying SSE types using C α atoms in protein chains were developed: (1) a mathematical approach, (2) a deep learning approach, and (3) an ensemble of five machine learning models. The proposed methods were compared against each other and with a state-of-the-art approach, PCASSO. [ABSTRACT FROM AUTHOR]

Mid-infrared spectroscopy is one of the major analytical techniques employed for measurements of protein structure in solution. Traditional Fourier Transform-Infrared (FT-IR) measurement is limited by its blackbody light source that is inherently spatially incoherent and has low optical power output. This limitation is pronounced when working with proteins in aqueous solutions. Strong absorbance of water in protein amide I region 1600–1700 cm−1 restricts light path length to <10 μm and imposes significant experimental challenges in sample and flow cell handling. Emerging laser spectroscopic techniques use high-power coherent laser as light source that overcomes the limitation in FT-IR measurement. In this study, we employed an innovative infrared spectrometer that uses quantum cascade laser (QCL) as light source. Continuous infrared radiation from this laser source can be swiftly swept within the amide I region (1600–1700 cm−1) and amide II region (1500–1600 cm−1), which makes this technique ideal for protein secondary structure study. Protein solutions as low as 0.5 mg/mL were measured rapidly without any sample preparation. Infrared spectra of model proteins were thus collected, and a chemometric model based on partial least squares regression was developed to quantify α-helix and β-strand motifs in protein secondary structure. The model was applied to measurement of the native secondary structure of commercial therapeutic proteins and bovine serum albumin (BSA) and in thermal degradation studies. [ABSTRACT FROM AUTHOR]

Background: Protein secondary structures that link simple 1D sequences to complex 3D structures can be used as good features for describing the local properties of protein, but also can serve as key features for predicting the complex 3D structures of protein. Thus, it is very important to accurately predict the secondary structure of the protein, which contains a local structural property assigned by the pattern of hydrogen bonds formed between amino acids. In this study, we accurately predict protein secondary structure by capturing the local patterns of protein. For this objective, we present a novel prediction model, AttSec, based on transformer architecture. In particular, AttSec extracts self-attention maps corresponding to pairwise features between amino acid embeddings and passes them through 2D convolution blocks to capture local patterns. In addition, instead of using additional evolutionary information, it uses protein embedding as an input, which is generated by a language model. Results: For the ProteinNet DSSP8 dataset, our model showed 11.8% better performance on the entire evaluation datasets compared with other no-evolutionary-information-based models. For the NetSurfP-2.0 DSSP8 dataset, it showed 1.2% better performance on average. There was an average performance improvement of 9.0% for the ProteinNet DSSP3 dataset and an average of 0.7% for the NetSurfP-2.0 DSSP3 dataset. Conclusion: We accurately predict protein secondary structure by capturing the local patterns of protein. For this objective, we present a novel prediction model, AttSec, based on transformer architecture. Although there was no dramatic accuracy improvement compared with other models, the improvement on DSSP8 was greater than that on DSSP3. This result implies that using our proposed pairwise feature could have a remarkable effect for several challenging tasks that require finely subdivided classification. Github package URL is https://github.com/youjin-DDAI/AttSec. [ABSTRACT FROM AUTHOR]

BACKGROUND: Polysaccharides are the most widely used additives to enhance the quality of surimi gels. Oat β‐glucan (OG), a functional polysaccharide, is known to affect the gelation characteristics of surimi. However, it has been rarely reported. Therefore, the effect of OG at different levels on gelling properties, protein conformation, and microstructures of silver carp surimi gels were investigated. RESULTS: An increase in the OG content from 0 to 1.0% significantly improved the hardness, springiness, chewiness, puncture properties, storage modulus, and loss modulus of surimi gels. Moreover, the incorporation of OG (0–1.0%) facilitated the unfolding of proteins, resulting in the conformational transformation from α‐helix to β‐sheet and β‐turn. Consequently, surimi–OG gels displayed a denser network structure with smaller and more uniform voids. Furthermore, partial free water in the gel network was converted into immobile water, increasing the water‐holding capacity. However, a further increase in the OG concentration (1.0–2.0%) resulted in a looser and more uneven network structure with large and numerous cavities. In addition, the whiteness of composite gels decreased with increasing content of OG. CONCLUSION: The addition of 1.0% OG dramatically improved the gelation performance of silver carp surimi, providing a theoretical foundation for the exploitation and manufacture of functional surimi products. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]