Search Results (128)

Opuntia macrorhiza, commonly referred to as red prickly pear, is a type of cactus fruit. The Opuntia macrorhiza (OM) fruit is rich in polyphenols and contains a high amount of ascorbic acid and betalains. The fruit peels have demonstrated many biological abilities, including antioxidant, antifungal, and antibacterial activities. Ultrasound probe-assisted extraction (UPAE) is a highly promising method for efficiently extracting valuable molecules from natural sources. The objective of this study is to optimize the parameters of UPAE, including the appropriate solvent, liquid-to-solid ratio, extraction duration, and pulsation level. The aim is to maximize the yield of bioactive compounds (polyphenols, betalains, and ascorbic acid) from OM fruits (pulps and peels) and assess their antioxidant activities using Taguchi design. The optimal extraction conditions through the partial least squares method for OM pulp were determined to be aqueous extraction for 12 min with a liquid-to-solid ratio of 60 mL/g and 48 pulses/min, while for OM peels they were determined to be aqueous extraction for 20 min with a liquid-to-solid ratio of 60 mL/g and a pulsation of 48 pulses/min. The optimum UPAE conditions were compared with the values obtained from the optimum extraction under stirring extraction (STE). Overall, UPAE exhibited higher yields than STE. The obtained total polyphenol content ranged from 10.27 to 13.07 mg gallic acid equivalents/g dry weight, while the betalain content ranged from 974 to 1099 μg/g dry weight. Overall, these fruits demonstrated potential as new components for food and medicinal uses due to their good health effects and lack of toxicity. Full article

Background: It is well established in the literature that pregnancy-associated plasma protein-A (PAPP-A) is linked to several adverse pregnancy outcomes, including pre-eclampsia (PE), fetal growth restriction (FGR), and preterm birth (PTB) in singleton pregnancies. However, data regarding such an association in twin pregnancies are lacking. The primary goal of this systematic review and meta-analysis was to assess the potential value of low PAPP-A levels in the prediction of the subsequent development of hypertensive disorders of pregnancy (HDPs), PTB, and small for gestational age (SGA)/FGR fetuses in twin pregnancies and investigate its association with the development of gestational diabetes, intrauterine death (IUD) of at least one twin, and birth weight discordance (BWD) among the fetuses. Methods: Medline, Scopus, CENTRAL, Clinicaltrials.gov, and Google Scholar databases were systematically searched from inception until 31 July 2024. All observational studies reporting low PAPP-A levels after the performance of the first-trimester combined test as part of the screening for chromosomal abnormalities with reported adverse pregnancy outcomes were included. Results: The current systematic review encompassed a total of 11 studies (among which 6 were included in the current meta-analysis) that enrolled a total of 3741 patients. Low PAPP-A levels were not associated with HDPs (OR 1.25, 95% CI 0.78, 2.02, I-square test: 13%). Low PAPP-A levels were positively associated with both the development of preterm birth prior to 32 (OR 2.85, 95% CI 1.70, 4.77, I-square test: 0%) and 34 weeks of gestational age (OR 2.09, 95% CI 1.34, 3.28, I-square test: 0%). Furthermore, low PAPP-A levels were positively associated with SGA/FGR (OR 1.58, 95% CI 1.04, 2.41, I-square test: 0%). Prediction intervals indicated that the sample size that was used did not suffice to support these findings in future studies. Conclusions: Our study indicated that low PAPP-A levels are correlated with an increased incidence of adverse perinatal outcomes in twin pregnancies. Identifying women at elevated risk for such adversities in twin pregnancies may facilitate appropriate management and potential interventions, but additional studies are required to identify the underlying mechanism linking PAPP-A with those obstetrical complications. Full article

Pears are popular among consumers for their juicy and delicious taste. In this study, the sugar and organic acid compositions of pear fruits with different texture types during development were determined by ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS), and fruit texture traits were determined by a texture analyzer. The results showed that the dominant sugar in soft and crispy types of pear fruits was fructose. The main difference between pears was the second-highest sugar component; glucose content was higher in crispy-flesh pear fruits while sucrose content was higher in soft-flesh pear fruits. The composition of organic acid components in both texture types of pear fruits was similar. The turning points of changes in the content of sucrose, sorbitol, glucose and quinic acid were different between different-textured pear varieties. A Pearson correlation analysis showed that sugar and organic acid components were significantly correlated with single fruit weight and soluble solid contents (SSCs), respectively. There was a high correlation among texture traits, individual sugars and organic acids. A partial least squares discriminant analysis (PLS-DA) VIP score plot showed that the differential traits with scores greater than 1 were total soluble sugars/total organic acids (TSSs/TAs), fracture and malic acid/citric acid (MA/CA), which could distinguish pear fruits of different texture types better and reflect the uneven quality differences among pear fruits adapted to different origins. The comprehensive analysis results of the flesh texture parameters and sugar and organic acid components are in line with objective reality and will provide a reference for quantitative indicators of the sensory evaluation of pear varieties as well as for molecular mechanism research on trait differences. Full article

Comprehensively clarifying the influencing factors of carbon emissions is crucial to realizing carbon emission reduction targets in China. To address this issue, this paper develops a four-level carbon emission influencing factor system from six perspectives: population, economy, energy, water resources, main pollutants, and afforestation. To analyze how these factors affect carbon emissions, we propose an improved partial least squares structural equation model (PLS-SEM) based on a random forest (RF), named RF-PLS-SEM. In addition, the entropy weight method (EWM) is employed to evaluate the low-carbon development level according to the results of the RF-PLS-SEM. This paper takes Shandong Province as an example for empirical analysis. The results demonstrate that the improved model significantly improves accuracy from 0.8141 to 0.9220. Moreover, water resources and afforestation have relatively small impacts on carbon emissions. Primary and tertiary industries are negative influencing factors that inhibit the growth of carbon emissions, whereas total energy consumption, the volume of wastewater discharged and of common industrial solid waste are positive and direct influencing factors, and population density is indirect. In particular, this paper explores the important role of fisheries in reducing carbon emissions and discusses the relationship between population aging and carbon emissions. In terms of the level of low-carbon development, the assessment system of carbon emission is constructed from four dimensions, namely, population, economy, energy, and main pollutants, showing weak, basic, and sustainable stages of low-carbon development during the 1997–2012, 2013–2020, and 2021–2022 periods, respectively. Full article

Growth performance is an important economic trait of broilers but the related serum metabolomics remains unclear. In this study, we utilized non-targeted metabolomics using ultra-high-performance liquid phase tandem mass spectrometry (UHPLC-MS/MS) to establish metabolite profiling in the serum of Chinese Wumeng black-bone chickens. The biomarker metabolites in serum associated with growth performance of chickens were identified by comparing the serum metabolome differences between chickens that significantly differed in their weights at 160 days of age when fed identical diets. A total of 766 metabolites were identified including 13 differential metabolite classes such as lipids and lipid-like molecules, organic acids and their derivatives, and organoheterocyclic compounds. The results of difference analysis using a partial least squares discriminant analysis (PLS-DA) model indicated that the low-body-weight group could be differentiated based on inflammatory markers including prostaglandin a2, kynurenic acid and fatty acid esters of hydroxy fatty acids (FAHFA), and inflammation-related metabolic pathways including tryptophan and arachidonic acid metabolism. In contrast, the sera of high-body-weight chickens were enriched for riboflavin and 2-isopropylmalic acid and for metabolic pathways including riboflavin metabolism, acetyl group transfer into mitochondria, and the tricarboxylic acid (TCA) cycle. These results provide new insights into the practical application of improving the growth performance of local chickens. Full article

Finite impulse response (FIR) filters are explicitly used in decisive applications such as communication and signal processing areas. Advancement in the latest technologies necessitates specific designs with optimal characteristics. This research work proposes the realization of an efficient distributed arithmetic adaptive FIR filter (DAAFA) architecture using radix-4 and radix-8 computation. Distributed arithmetic (DA) is extensively used to calculate the sum of products without involving a multiplier. The proposed fixed-point realization of a single multiply and accumulate (MAC) FIR adaptive filter is implemented with minimum complex design. The total longest-way computation time is a combination of the delay that occurred in the error calculation module and the delay involved in updating the filter weights. The longest-way computation time of the filter structure is higher, which results in increased latency. In addition, the approximate design of the radix DA multiplier structure is constructed using Booth recoding, partial product formation block and shifting-based accumulation block. Further, the approximate design of DA offers a reduction in complexity and area with respect to the number of slices and enhances the operating speed. The partial product is created using shifters and efficient adders, which further enhances the performance of the realization. This work is implemented in Xilinx and Altera devices and is compared with the present literature. From the synthesis results, it is observed that the propounded design outperforms in terms of complexity, slice delay product and ultimate speed of exertion. The suggested architecture was found to be decisive in terms of area, delay and complexity abatement. The results indicate that the propounded design achieves area reduction (slices) of about 92.03% compared to the existing design. Also, a speed enhancement of about 90.7% is accomplished for the proposed architecture. Nonetheless, the devised architecture utilizes the least means square approach, which enhances the convergence rate notably. Full article

Sarcopenia, a multifactorial systemic disorder, has attracted extensive attention, yet its pathogenesis is not fully understood, partly due to limited research on the relationship between lipid metabolism abnormalities and sarcopenia. Lipidomics offers the possibility to explore this relationship. Our research utilized LC/MS-based nontargeted lipidomics to investigate the lipid profile changes as-sociated with sarcopenia, aiming to enhance understanding of its underlying mechanisms. The study included 40 sarcopenia patients and 40 control subjects matched 1:1 by sex and age. Plasma lipids were detected and quantified, with differential lipids identified through univariate and mul-tivariate statistical analyses. A weighted correlation network analysis (WGCNA) and MetaboAna-lyst were used to identify lipid modules related to the clinical traits of sarcopenia patients and to conduct pathway analysis, respectively. A total of 34 lipid subclasses and 1446 lipid molecules were detected. Orthogonal partial least squares discriminant analysis (OPLS-DA) identified 80 differen-tial lipid molecules, including 38 phospholipids. Network analysis revealed that the brown module (encompassing phosphatidylglycerol (PG) lipids) and the yellow module (containing phosphati-dylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM) lipids) were closely associated with the clinical traits such as maximum grip strength and skeletal muscle mass (SMI). Pathway analysis highlighted the potential role of the glycerophospholipid metabolic pathway in lipid me-tabolism within the context of sarcopenia. These findings suggest a correlation between sarcopenia and lipid metabolism disturbances, providing valuable insights into the disease’s underlying mechanisms and indicating potential avenues for further investigation. Full article

Background: Matrix metalloproteinases (MMPs) play an important role in the pathophysiology of atherosclerosis. Reportedly, statins can decrease MMP activity in patients with atherosclerotic cardiovascular disease, but this effect has not been studied in healthy individuals. Methods: MMPs 2, 7, and 9 and several other parameters were measured before and after a four-week course of moderate-dose atorvastatin (20 mg/day) in 21 healthy individuals. Results: Atorvastatin treatment resulted in lower total cholesterol, LDL-cholesterol, non-HDL-cholesterol, and triglycerides (p < 0.001 for all), but higher levels of plasma enzymes AST, ALT, CK, and LDH (p < 0.05 for all). No effect of atorvastatin on plasma MMP median concentrations was recorded. Before treatment, moderate positive significant correlations were found between MMP-7 and age, blood lipids, and blood count-derived inflammatory markers. Pre-treatment MMP-7 was best predicted by the total cholesterol-to-HDL cholesterol ratio in a remnant cholesterol-weighted least squares regression model. After atorvastatin treatment, MMP-7 no longer correlated with these markers. Conclusions: While the effect of statins on plasma MMPs in atherosclerosis is controversial, short-term moderate-dose atorvastatin treatment does not seem to affect levels of MMPs 2, 7, and 9 in healthy individuals. However, an intriguing correlation between MMP-7 and atherosclerosis-related blood lipids and neutrophil-associated inflammatory biomarkers seems to be disrupted by atorvastatin independently of hsCRP, possibly via pleiotropic effects. Full article

This study explored the use of mandarin peels as an important source of health-promoting compounds by utilizing green methods (i.e., pulsed electric field and ultrasound-assisted extraction), along with conventional stirring. The impact of several extraction parameters, such as extraction duration, temperature, and solvent composition, on the recovery of bioactive compounds was evaluated through a response surface methodology. To identify the most effective conditions for all assays, a partial least-squares analysis was implemented. It was revealed that a combination of the above techniques was optimal at 80 °C for 30 min, with 75% v/v of ethanol in water as the extraction solvent. The concentration of bioactive compounds in the optimum extract had a total polyphenol content of 18.69 mg of gallic acid equivalents (GAE) per gram of dry weight (dw), and an ascorbic acid concentration of 18.25 mg/g dw. However, correlation analyses revealed a rather negative relationship between these bioactive compounds. The chromatographic analysis of optimum extracts supported this result by quantifying 20.53 mg/g dw of total individual polyphenols, with hesperidin being the dominant compound (13.98 mg/g dw). The antioxidant assays, including ferric-reducing antioxidant power and DPPH^• inhibition activity, were measured at 123.21 and 65.12 μmol of ascorbic acid equivalents (AAE) per gram of dw, respectively. This research enhances the valorization of mandarin peels as a renewable source of bioactive compounds, providing the opportunity to generate high-added-value products from food waste in the food and pharmaceutical sectors. Full article

The assessment of total risk-weighted assets (LTRWAs) in the banking sector is of the utmost importance. It serves as a critical component for regulatory compliance, risk management, and capital adequacy. By accurately assessing LTRWAs, banks can effectively meet regulatory requirements, efficiently allocate capital resources, and proactively manage risks. Moreover, the accurate assessment of LTRWAs supports performance evaluation and fosters investor confidence in the financial stability of banks. This study presents statistical analyses and machine learning methods to identify factors influencing LTRWAs. Data from Bahrain, Jordan, Qatar, the United Arab Emirates, and Yemen, spanning from 2010 to 2021, was utilized. Various statistical tests and models, including ordinary least squares, fixed effect, random effect, correlation, variance inflation factor, tolerance tests, and fintech models, were conducted. The results indicated significant impacts of the unemployment rate, inflation rate, natural logarithm of the loan-to-asset ratio, and natural logarithm of total assets on LTRWAs in regression models. The dataset was divided into a training group (90% of the data) and a testing group (10% of the data) to evaluate the predictive capabilities of various fintech models, including an adaptive network-based fuzzy inference system (ANFIS), a hybrid neural fuzzy inference system (HyFIS), a fuzzy system with the heuristic gradient descent (FS.HGD), and fuzzy inference rules with the descent method (FIR.DM) models. The selection of the optimal model is contingent upon assessing its performance according to specific error criteria. The HyFIS model outperformed others with lower errors in predicting LTRWAs. Independent t-tests confirmed statistically significant differences between original and predicted LTRWA for all models, with HyFIS showing closer predictions. This study provides valuable insights into LTRWA prediction using advanced statistical and machine learning techniques, based on a dataset from multiple countries and years. Full article

The role of spatial factors in reducing carbon emissions has been receiving increasing attention from researchers; however, these impacts may involve spatial heterogeneity. In this study, 337 prefecture-level cities in China were taken as the research object. Based on national-level urban data, the global impact of urban spatial form on carbon emissions was then investigated using ordinary least squares regression, the spatial error model, and the spatial lag model. The local effects of urban spatial form on carbon emissions in different cities were then investigated using geographically weighted regression. The findings are as follows. Overall, the larger the urban built-up area and the more fragmented and decentralized the urban land use, the greater the carbon emissions. Conversely, the more centralized the urban center of a city, the lower its carbon emissions. Locally, for some Chinese cities, the total area, landscape shape index, and mean Euclidean nearest-neighbor distance were found to have significant positive effects on carbon emissions, while the largest-patch index had a significant negative impact. For all Chinese cities, the patch density was found to have no significant effect on carbon emissions. In 29% of the cities in which the landscape division index was found to significantly affect carbon emissions, this effect was positive, while it was negative in the remaining 71%. The policy implications emerging from this study lie in the need for decision-makers and urban planners to guide the shaping of low-carbon urban spatial forms. Full article

Osmanthus fragrans, belonging to the family Oleaceae, is listed as one of the most important traditional ornamental plant species in China. A new cultivar O. fragrans ‘Wucaigui’ has a very diversified form in terms of leaf colors, in which the leaf color changes from red to yellow-green and finally to dark green. To understand the mechanisms involved in leaf color changes, metabolome and transcriptome studies were performed on leaves at different developmental stages. A total of 79 metabolites, two chlorophyll, 26 carotenoids, and 51 anthocyanins, were detected in the 6 different developmental stages. An orthogonal partial least squares discriminant analysis identified key metabolites at different developmental stages, including lutein, pelargonidin-3-O-(6-O-p-coumaroyl)-glucoside, neoxanthin, and α-carotene. A total of 48,837 genes were obtained by transcriptome sequencing, including 3295 novel genes. Using a weighted gene co-expression network analysis to study the correlations between key metabolites and differentially expressed genes, we determined the characteristic modules having the highest correlations with key metabolites and selected associated candidate genes. Five genes (OfSHOU4L, OfATL1B, OfUGE5 OfEIF1AX, and OfUGE3) were finally identified as hub genes using real-time fluorescence quantitative PCR. In addition, we proposed a model based on the changes in key metabolite contents and the network regulatory map during the changes in O. fragrans ‘Wucaigui’ leaf color. The positive regulation of OfUGE3 led to an increase in the lutein content, which resulted in the leaves changing from grayish brown to moderate brown; during the change from moderate brown to dark greenish-yellow, the positive regulation of three genes (OfHOU4L, OfATL1B, and OfUGE5) increased the content of pelargonidin-3-O-(6-O-p-coumaroyl)-glucoside and the red color of the leaves gradually faded to dark greenish-yellow and then to strong yellow-green; the positive regulation of OfEIF1AX increased the content of neoxanthin; the stages in which the color changed from strong yellow-green to yellow-green and then to moderate olive-green were positively regulated by OfUGE3, which resulted in higher α-carotene content. These findings provided new insights into the mechanisms underlying the processes involved in O. fragrans ‘Wucaigui’ leaf color changes at the metabolic and transcriptional levels. This work seeks to contribute to the development of artificial regulate and control technology in the breeding and production of O. fragrans and other ornamental plants. Full article

Herein, we present an integrative investigation of the nutritional and nutraceutical potential of Lactarius indigo, Clitocybe nuda, Clitocybe subclavipes, Russula delica, Russula brevipes, Clitocybe squamulosa, and Amanita jacksonii, which are edible mushrooms consumed in the northeastern highlands of Puebla, Mexico. The content of protein oscillated from 4.8 to 10.9 g 100 g⁻¹ fresh weight (FW) whereas that of fiber ranged from 8.8 to 19.7 g 100 g⁻¹ FW. The edible species presented low amounts of fat (1.5–3.4 g 100 g⁻¹ FW) and reducing sugars (0.8–2.9 g 100 g⁻¹ FW), whereas the content of vitamin C oscillated from 6.5 to 84.8 mg 100 g⁻¹ dry weight (DW). In addition, four vitamins of B complex (thiamine, riboflavin, vitamin B₆, and folate) were determined in different concentrations. A high abundance of potassium (92.3–294.3 mg 100 g⁻¹ DW), calcium (139.1–446.9 mg 100 g⁻¹ DW), and magnesium (81.3–339.1 mg 100 g⁻¹ DW) was determined in most of the edible mushrooms, as well as detectable levels of p-hydroxybenzoic acid (2.2–48.7 mg 100 g⁻¹ DW), protocatechuic acid (0.5–50.8 mg 100 g⁻¹ DW), oleic acid (14.2–98.3 mg 100 g⁻¹ DW), linoleic acid (748–1549.6 mg 100 g⁻¹ DW), and linolenic acid (from 9.1 to 83.6 mg 100 g⁻¹ DW). The total phenol content and antioxidant capacity significantly (p < 0.05) varied among the studied species, and their capacity to inhibit enzymes involved in glucose, lipid, and polyamine metabolism. Nevertheless, the hydroalcoholic extracts from A. jacksonii and L. indigo efficiently inhibited alpha-glucosidase and ornithine decarboxylase (IC₅₀ < 50 µg mL⁻¹), respectively. The evaluation of the same extracts on microorganisms associated with the gastrointestinal tract showed negligible toxicity on probiotics (MIC > 500 µg mL⁻¹) and moderate toxicity against pathogenic bacteria (MIC < 400 µg mL⁻¹). Based on the studied parameters, principal component analysis and orthogonal partial least squares discriminant analysis clustered these edible mushrooms into two main groups with similar biological or chemical properties. Full article

The objective was to evaluate the effects of benzoic acid, bromelain, adipic acid, and humic substance supplementation on nitrogen balance, urinary pH, slurry pH, and manure odorous compounds in pigs. Fifteen castrated male pigs with an initial body weight of 37.9 kg (standard deviation = 4.1) were individually housed in metabolism crates. The animals were allocated to a triplicated 5 × 2 incomplete Latin square design with 15 animals, 5 experimental diets, and 2 periods. The basal diet mainly consisted of corn, soybean meal, and rapeseed meal. Four experimental diets were prepared by supplementing each additive at a concentration of 10 g/kg at the expense of corn starch to the basal diet. Each period consisted of a 4-day adaptation period, a 24 h collection period for slurry sampling, and a 4-day collection period for feces and urine. The feces and urine collected for 24 h on day 5 were mixed at a ratio of fecal weight and urine weight to obtain slurry samples. The apparent total tract digestibility N in pigs fed the humic substance diet was the least (p < 0.05) compared to the other groups. The daily retained N and N retention as % ingested tended (p < 0.10) to be the lowest in the adipic acid group among the treatments. The urinary pH in pigs fed the adipic acid diet was less (p < 0.05) than that in other groups except the benzoic acid group. The slurry pH tended to differ among the treatment groups (p = 0.074) with the lowest value in the pigs fed the adipic acid diet. The concentrations of indole in slurry (p = 0.084) and isovalerate in feces (p = 0.062) tended to differ among the groups with the lowest values in the pigs fed the humic substance diet. In conclusion, adipic acid supplementation in pig diets can decrease urinary pH and slurry pH. Although benzoic acid and adipic acid have limited effects in reducing odorous compounds, humic substances have the potential to reduce some odorous compounds. Full article

The Booroola fecundity (FecB) mutation in the bone morphogenetic protein receptor type 1B (BMPR1B) gene increases ovulation in sheep. However, its effect on follicular maturation is not fully understood. Therefore, we collected granulosa cells (GCs) at a critical stage of follicle maturation from nine wild-type (WW), nine heterozygous FecB mutant (WB), and nine homozygous FecB mutant (BB) Small Tail Han sheep. The GCs of three ewes were selected at random from each genotype and consolidated into a single group, yielding a total of nine groups (three groups per genotype) for proteomic analysis. The tandem mass tag technique was utilized to ascertain the specific proteins linked to multiple ovulation in the various FecB genotypes. Using a general linear model, we identified 199 proteins significantly affected by the FecB mutation with the LIMMA package (p < 0.05). The differential abundance of proteins was enriched in pathways related to cholesterol metabolism, carbohydrate metabolism, amino acid biosynthesis, and glutathione metabolism. These pathways are involved in important processes for GC-regulated ‘conservation’ of oocyte maturation. Further, the sparse partial least-squares discriminant analysis and the Fuzzy-C-mean clustering method were combined to estimate weights and cluster differential abundance proteins according to ovulation to screen important ovulation-related proteins. Among them, ZP2 and ZP3 were found to be enriched in the cellular component catalog term “egg coat”, as well as some apolipoproteins, such as APOA1, APOA2, and APOA4, enriched in several Gene Ontology terms related to cholesterol metabolism and lipoprotein transport. A higher abundance of these essential proteins for oocyte maturation was observed in BB and WB genotypes compared with WW ewes. These proteins had a high weight in the model for discriminating sheep with different FecB genotypes. These findings provide new insight that the FecB mutant in GCs improves nutrient metabolism, leading to better oocyte maturation by altering the abundance of important proteins (ZP2, ZP3, and APOA1) in favor of increased ovulation or better oocyte quality. Full article