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This study assesses the progression of damage occurring on glass fiber reinforced polyester composite specimens using acoustic emission (AE) parameters. Its aims are to improve understanding of the particular characteristics of AE signals; and also to determine the relationship between AE signals and the failure of the material. Time and frequency domain trends were analysed at four different applied loads (60.97, 67.75, 74.52 and 81.30 MPa) representing 45–60% of the ultimate tensile strength of material. The relevant AE parameters were analysed both in the early stages of the test and as the material neared the fracture zone. The results showed a high degree of correlation between the root mean square and number of hits AE values and the number of cycles to failure, of 92.99 and 92.19%, respectively. This correlation, as well as AE basic parameters, suggests that AE can be a valuable tool to predict the fatigue life and detect the onset of damage in such composite materials. [ABSTRACT FROM AUTHOR]

In this study, a double-layer active and intelligent packaging system was developed based on two main natural macromolecules i.e. protein and carbohydrate with green perspective. Firstly, the salep-based films containing different concentrations (0-8 % w/w) of the inclusion complex of β-cyclodextrin/black chickpea anthocyanins (βCD/BCPA) were produced. The salep film containing 8 % of βCD/BCPA complex was specified as the optimized film sample based on its performance as a color indicator. The electrospinning of black chickpea protein isolate nanofibers (BCPI NFs) containing citral nanoliposomes (NLPs) was done on the optimized salep film. The cross-sectional field emission scanning electron microscopy approved the creation of double-layer structure of the developed film. The study of chemical and crystalline structure, as well as the thermal properties of the film exhibited the physical attachment of BCPI electrospun NFs on salep film. The effectiveness of the developed system was studied in detection of spoilage and increasing the shelf life of seafood products, including shrimp and fish fillet. The performance of the intelligent layer in detection of freshness/spoilage was acceptable for both seafood products. In addition, the active layer of the film controlled the changes of pH, total volatile basic nitrogen, oxidation, and microbial load in samples during storage time., Competing Interests: Declaration of competing interest The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: Anaplastic thyroid carcinoma (ATC) is a highly aggressive and lethal thyroid cancer subtype with a poor prognosis. Recent advancements in machine learning (ML) have the potential to improve survival predictions. This study aimed to develop and validate ML models using the SEER database to predict 3-month, 6-month, and 12-month (overall survival) OS in ATC patients., Methods: Clinical and demographic data for patients with ATC from the SEER database (2004-2015) were utilized. Five ML algorithms-AdaBoost, support vector machines, gradient boosting classifiers, random forests, and naive Bayes-were evaluated. The data were split into training and testing sets (7:3 ratio), and the models were tuned using fivefold cross-validation. Model performance was assessed using the concordance index (C-index) and Brier score, with 95% confidence intervals reported., Results: The gradient boosting model achieved the greatest performance for 3-month survival (C-index: 0.8197, 95% CI 0.7682-0.8689; Brier score: 0.1802), and the AdaBoost model achieved the greatest performance in 6-month survival (C-index: 0.8473, 95% CI 0.7979-0.8933; Brier score: 0.1775). The SVC model showed superior performance for 12-month survival (C-index: 0.8347, 95% CI 0.7866-0.8816; Brier score: 0.1476). Using SHAP with a gradient boosting model, the top five features affecting 6-month OS were identified: surgery, the presence of stage IVC, radiation, chemotherapy, and tumor size. Treatment improved survival, while higher stages reduced survival, with smaller tumors generally linked to better outcomes., Conclusion: ML algorithms can accurately predict short-term survival in ATC patients. These models can potentially guide clinical decision-making and individualized treatment strategies., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Guided by the reserve capacity model, we evaluated the unique relationships between socioeconomic status (SES), reserve capacity (helplessness, self-efficacy, social support), and negative emotions on pain in patients with Rheumatoid Arthritis (RA)., Methods: The secondary analysis used baseline, cross-sectional data from 106 adults in a clinical trial comparing behavioral treatments for RA. Patients were eligible if they were ≥ 18 years old, met the ACR criteria for RA (determined by study rheumatologist), had stable disease and drug regimens for 3 months, and did not have a significant comorbid condition. Structural equation modeling evaluated the direct effects of SES, reserve capacity (helplessness- Arthritis Helplessness Index, self-efficacy -Personal Mastery Scale, social support- Social Provisions Scale) and negative emotions (stress and depressive symptoms- Perceived Stress Scale and Hamilton Depression Rating Scale) on pain (Rapid Assessment of Disease Activity in Rheumatology-RADAR & visual analog scale-VAS), and the indirect effects of SES as mediated by reserve capacity and negative emotions. The SEM model was evaluated using multiple fit criteria: χ 2 goodness-of-fit statistic, the comparative fit index (CFI), the standardized root mean square residual (SRMR), and the root mean square error of approximation (RMSEA)., Results: Participants were mostly female (85%), 55.45 years old on average, self-identified as white (61%), Hispanic (16%), black (13%), and other (10%), and had RA for an average of 10.63 years. Results showed that low SES contributed to worse pain, through lower reserve capacity and higher negative emotions. Mediational analyses showed that reserve capacity and negative emotions partially mediated the effect of SES on pain. The final model explained 39% of the variance in pain., Conclusions: The findings indicate that lower SES was related to worse clinical pain outcomes and negative emotions and reserve capacity (helplessness, social support, and self-efficacy) mediated the effect of SES on pain. A primary limitation is the small sample size; future studies should evaluate this model further in larger, longitudinal approaches. Interventions that target negative emotions in patients with low SES may facilitate better pain control with RA., Trial Registration: clinicaltrials.gov NCT00072657 01/02/2004 20/03/2009., (© 2024. The Author(s).)

This experiment was carried out to provide a comprehensive insight into the protein activities involved in dormancy establishment in seeds of common cocklebur (Xanthium strumarium), an annual plant with two dimorphic seeds contained in one casing known as a burr. These consist of a smaller dormant seed and a larger non-dormant seed. The proteome profile was compared between developing dormant and non-dormant seeds of Xanthium strumarium at five consecutive stages including three, 10, 20, 30, and 45 days after burr emergence (stages 1 to 5). We identified 6524 proteins in total, and approximately 3.6% of these were differentially abundant proteins (DAPs) between the two seed types. Both seed types showed fundamental changes in developmental programs during the examined stages. More than 38% of all DAPs were observed at the first stage, supporting the importance of the early developmental stage in seed fate determination. The detected DAPs at stage 1 were mainly associated with the cell division phase, which showed a delay in the dormant seeds. Over-representation of proteins responsible for cell wall biosynthesis, cytokinesis, and seed development were detected for non-dormant seeds at the first stage, while dormancy-associated proteins showed less abundance. Stage 3 was the critical stage for switching processes toward seed maturation and abscisic acid (ABA) signaling. Interestingly, higher abundance proteins in the mature non-dormant seed were mainly involved in the facilitation of seed germination. Taken together, the temporal pattern of the accumulated proteins in developing dormant seeds demonstrated a delay in the initiation of active cell division, enriched response to ABA, and defects in seed maturation. Moreover, stored proteins in the mature dormant seed delay germination but not dormancy induction. Finally, our results suggest that dormancy may be established at a stage of seed development earlier than previously thought., (© 2024 Scandinavian Plant Physiology Society.)

Purpose: Despite the rising incidence of differentiated thyroid cancer (DTC), mortality rates have remained relatively low yet crucial for effective patient management. This study aims to develop a deep neural network capable of predicting mortality in patients with differentiated thyroid cancer., Methods: Leveraging data from the Surveillance, Epidemiology, and End Results (SEER) database, we developed Thy-DAMP (Deep Artificial Neural Network Model for Prediction of Thyroid Cancer) to forecast mortality in DTC patients. The dataset comprised demographic, histologic, and staging information. Following data normalization and feature encoding, the dataset was partitioned into training, testing, and validation subsets, with model hyperparameters fine-tuned via cross-validation., Results: Among the 63,513 patients, the mean age was 48.22 years (SD = 14.8), with 77.32% being female. Papillary carcinoma emerged as the predominant subtype, representing 62.94% of cases. The majority presented with stage I disease (73.96%). Thy-DAMP demonstrated acceptable performance metrics on both the test and validation sets. Sensitivity was 83.24% (95% CI 76.95-88.40%), specificity was 93.53% (95% CI 93.01-94.02%), and accuracy stood at 93.33% (95% CI 92.82-93.83%). The model exhibited a positive predictive value of 19.76% (95% CI 18.20-21.42%) and a negative predictive value of 99.66% (95% CI 99.53-99.75%). Additionally, Thy-DAMP demonstrated a positive likelihood ratio of 12.86 (95% CI 11.62-14.23), a negative likelihood ratio of 0.18 (95% CI 0.13-0.25), and an area under the receiver operating characteristic curve (AUROC) of 0.95. The model was externally validated on a separate dataset with nearly identical performance., Conclusion: Thy-DAMP showcases considerable promise in accurately predicting mortality in DTC patients, leveraging limited set of patient data., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Nanoparticle-mediated mRNA delivery has emerged as a promising therapeutic modality, but its growth is still limited by the discovery and optimization of effective and well-tolerated delivery strategies. Lipid nanoparticles containing charged or ionizable lipids are an emerging standard for in vivo mRNA delivery, so creating facile, tunable strategies to synthesize these key lipid-like molecules is essential to advance the field. Here, we generate a library of N-substituted glycine oligomers, peptoids, and undertake a multistage down-selection process to identify lead candidate peptoids as the ionizable component in our Nutshell nanoparticle platform. First, we identify a promising peptoid structural motif by clustering a library of >200 molecules based on predicted physical properties and evaluate members of each cluster for reporter gene expression in vivo. Then, the lead peptoid motif is optimized using design of experiments methodology to explore variations on the charged and lipophilic portions of the peptoid, facilitating the discovery of trends between structural elements and nanoparticle properties. We further demonstrate that peptoid-based Nutshells leads to expression of therapeutically relevant levels of an anti-respiratory syncytial virus antibody in mice with minimal tolerability concerns or induced immune responses compared to benchmark ionizable lipid, DLin-MC3-DMA. Through this work, we present peptoid-based nanoparticles as a tunable delivery platform that can be optimized toward a range of therapeutic programs.

Cereal plants form complex networks with their associated microbiome in the soil environment. A complex system including variations of numerous parameters of soil properties and host traits shapes the dynamics of cereal microbiota under drought. These multifaceted interactions can greatly affect carbon and nutrient cycling in soil and offer the potential to increase plant growth and fitness under drought conditions. Despite growing recognition of the importance of plant microbiota to agroecosystem functioning, harnessing the cereal root microbiota remains a significant challenge due to interacting and synergistic effects between root traits, soil properties, agricultural practices, and drought-related features. A better mechanistic understanding of root-soil-microbiota associations could lead to the development of novel strategies to improve cereal production under drought. In this review, we discuss the root-soil-microbiota interactions for improving the soil environment and host fitness under drought and suggest a roadmap for harnessing the benefits of these interactions for drought-resilient cereals. These methods include conservative trait-based approaches for the selection and breeding of plant genetic resources and manipulation of the soil environments., Competing Interests: Conflict of interest The authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier GmbH.. All rights reserved.)

In recent years, development of biopolymeric nanofibers as an active biodegradable packaging system has attracted specific attention. The objective of this research was to develop zein-based electrospun nanofibers (NFs) incorporated with geraniol-loaded nanoliposomes (G-loaded NLPs). Geraniol was encapsulated into NLPs with an efficiency of 79.23%. The particle size and zeta potential of G-loaded NLPs were 121.50 nm and -38.30 mV, respectively. The successful loading of geraniol in the NLPs was approved by Fourier transform infrared (FT-IR) spectroscopy. The liposomal vesicles showed spherical shapes. G-loaded NLPs were added in the zein-based electrospun NFs at three different concentrations (0.25, 0.5, and 1%w/v). All NFs samples exhibited fibrillar structure. The increase of NLPs concentration enhanced the thermal stability of the NFs. However, the crystalline structure of zein NFs did not change by the addition of G-loaded NLPs. The highest surface hydrophobicity was related to the NFs containing 1% G-loaded NLPs. The mechanical parameters of NFs depend on the concentration of NLPs. The NFs incorporated with G-loaded NLPs showed inhibition activity against four foodborne pathogenic bacteria ( Staphylococcus aureus , Listeria monocytogenes , Escherichia coli , and Salmonella typhimurium ) with an inhibition zone of 4.5-22 mm. Moreover, the α-diphenyl-β-picrylhydrazyl (DPPH) scavenging activity of NFs samples was located at the range of 20%-48%. These findings represent the Efficiency of the G-loaded NLPs for use as bioactive compound in the zein-based NFs as an active packaging material., Competing Interests: The authors declare no competing interests., (© 2024 The Authors. Food Science & Nutrition published by Wiley Periodicals LLC.)

Objectives: This study assessed the effects of two remineralizing agents namely MI Paste Plus containing casein phosphopeptide amorphous calcium phosphate fluoride (CPP-ACFP) and Remin Pro containing hydroxyapatite, fluoride and xylitol (HFX) with/without erbium-doped yttrium aluminium garnet (Er:YAG) and CO 2 laser irradiation on demineralized enamel microhardness. Materials and Methods: In this in vitro study, 70 sound human premolars were mesiodistally sectioned, demineralized at a pH of 4.6 for 8 hours, and randomly divided into 7 remineralization groups (n=10): of (I) MI Paste Plus (CPP-ACFP), (II) Remin Pro (HFX), (III) MI Paste Plus+CO 2 laser (0.7 W power, 50 Hz), (IV) Remin Pro+CO 2 laser, (V) MI Paste Plus+Er:YAG laser (1 W power, 10 Hz), (VI) Remin Pro+Er:YAG laser, and (VII) negative control. The Vickers hardness number of specimens was then measured. The groups were compared by one-way ANOVA and Tukey's test (α=0.05). Results: The mean microhardness was 319.8±49.9, 325.3±44.6, 359.4±35.7, 296.4±33.7, 319.9±58.1, 358.9±28.4, and 240.0±41.6 kg/mm2 in groups 1 to 7, respectively. The difference in microhardness was significant among the groups (P<0.0001). Pairwise comparisons revealed significant differences in microhardness between all groups (P≤0.03) except between groups 1 and 2, 1 and 5, 2 and 5, and 3 and 6 (P>0.05). Conclusion: Both Remin Pro (containing HFX) and MI Paste Plus (containing CPP-ACFP) can cause enamel remineralization. MI Paste Plus+CO 2 laser irradiation and Remin Pro+Er:YAG laser irradiation were significantly more effective than the application of each remineralizing agent alone ., Competing Interests: None declared., (Copyright © 2024 The Authors. Published by Tehran University of Medical Sciences.)

Cancer-associated fibroblasts (CAFs) have distinct roles within the tumor microenvironment, which can impact the mode and efficacy of tumor cell migration. CAFs are known to increase invasion of less-aggressive breast cancer cells through matrix remodeling and leader-follower dynamics. Here, we demonstrate that CAFs communicate with breast cancer cells through the formation of contact-dependent tunneling nanotubes (TNTs), which allow for the exchange of cargo between cell types. CAF mitochondria are an integral cargo component and are sufficient to increase the 3D migration of cancer cells. This cargo transfer results in an increase in mitochondrial ATP production in cancer cells, whereas it has a negligible impact on glycolytic ATP production. Manually increasing mitochondrial oxidative phosphorylation (OXPHOS) by providing extra substrates for OXPHOS fails to enhance cancer cell migration unless glycolysis is maintained at a constant level. Together, these data indicate that tumor-stromal cell crosstalk via TNTs and the associated metabolic symbiosis is a finely controlled mechanism by which tumor cells co-opt their microenvironment to promote cancer progression and may become a potential therapeutic target., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2023. Published by The Company of Biologists Ltd.)

Nowadays, pyrethroid (Py) insecticides are commonly used against household insect pests and housefly. The combination of Py and organophosphates (OP) are also utilized to combat these insects. The resistance status of Iranian housefly populations to them and carbamate (CB) insecticides is uncertain. This study investigates the presence of acetylcholinesterase (AChE) mutations related to the resistance of Musca domestica to OP and/or CB insecticides in Northwestern Iran. Nucleotides 1041-1776, based on their positions in the ACE gene of aabys strain, were amplified and sequenced in houseflies collected from West Azerbaijan, Gilan, and Ardebil Provinces, Iran. Among 12 single-nucleotide polymorphisms detected, 3 mismatches were found at nucleotides 1174 (T/A, G), 1473 (G/T, C), and 1668 (T/A), leading to amino acid substitutions in V260L, G342A/V, and F407Y positions with various combinations. Genotyping results showed that 85% of specimens had at least one of these substitutions. In addition, the Iranian housefly population was composed of 5 insensitive and sensitive alleles. For the first time, the current study reports the presence of V260L, G342A, G342V, and F407Y substitutions in M. domestica specimens collected from Northwestern Iran. The selection of multiple alleles in field populations might be due to the application of various pesticides/insecticides during extended periods in the region. These molecular levels signify the presence of control problems in the area and the need for developing effective control strategies for such populations., (© The Author(s) 2023. Published by Oxford University Press on behalf of Entomological Society of America.)