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Daqu is usually produced in an open environment, which makes its quality unstable. The microbial community of Daqu largely determines its quality. Therefore, in order to improve the fermentation characteristics of Daqu, samples were collected from Jinsha County (MT1), Xishui County (MT2), and Maotai Town (MT3) in Guizhou Province to explore the microbial diversity of Daqu and its impact on Daqu's metabolites.Off-target metabolomics was used to detect metabolites, and high-throughput sequencing was used to detect microorganisms. Metabolomics results revealed that MT1 and MT2 had the highest relative fatty acid content, whereas MT3 had the highest organooxygen compound content. Principal component analysis and partial least squares discriminant analysis revealed significant differences in the metabolites among the three groups, followed by the identification of 33 differential metabolites (key metabolites) filtered using the criteria of variable importance in projection >1 and p < 0.001. According to the microbiological results, Proteobacteria was the dominant bacteria phylum in three samples. Gammaproteobacteria was the dominant class in MT1(26.84 %) and MT2(36.54 %), MT3 is Alphaproteobacteria(25.66 %). And Caulobacteraceae was the dominant family per the abundance analysis, MTI was 24.32 %, MT2 and MT3 were 33.71 % and 24.40 % respectively. Three samples dominant fungi phylum were Ascomycota, and dominant fungi family were Thermoascaceae. Pseudomonas showed a significant positive connection with various fatty acyls, according to correlation analyses between dominant microorganisms (genus level) and key metabolites. Fatty acyls and Thermomyces showed a positive correlation, but Thermoascus had the reverse relation. These findings offer a theoretical framework for future studies on the impact of metabolites on Baijiu quality during fermentation.

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Predicting regional carbon dioxide (CO2) emissions is essential for advancing toward global carbon neutrality. This study introduces a novel CO2 emissions prediction model tailored to the unique environmental, economic, and energy consumption of Shanghai Chongming. Utilizing an innovative hybrid approach, the study first applies grey relational analysis to evaluate the influence of economic activity, natural conditions, and energy consumption on CO2 emissions. This is followed by the implementation of a dual-channel pooled convolutional neural network (DCNN) that captures both local and global features of the data, enhanced through feature stacking. Gated recurrent unit (GRU) network then assesses the temporal aspects of these features, culminating in precise CO2 emission predictions for the region. The results indicate: (1) The proposed hybrid model achieves accurate predictions based on accounting data, with high precision, low error, and good stability. (2) The study found an overall increase in Chongming's carbon emissions from 2000 to 2022, with the prediction results being generally consistent with existing research findings. (3) The proposed method, based on Chongming's CO2 emission predictions, addresses issues such as the scarcity of effective accounting data and inaccuracies in traditional calculation methods. The results can provide effective technical support for local government policies on carbon reduction and promote sustainable development.

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Asparagus by-products are the promising resource that urgently need to be re-valorized. This study investigated the dynamic changes in physicochemical properties, organic acids, free amino acids, volatile flavor compounds, microbial succession, and their correlations during 7-day spontaneous fermentation of asparagus by-products. Dominant organic acids (lactic acid and acetic acid) and free amino acids (Ser, Glu, and Ala) increased with fermentation time, with lactic acid reaching 7.73 ± 0.05 mg/mL and Ser increasing 56-fold after 7 days. A total of 58 volatile flavor compounds were identified using headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPEM/GC-MS), with esters, alcohols and acids as the main volatile flavor compounds. Fourteen volatile flavor compounds had odor activity value >1. High-throughput sequencing showed Firmicutes and Proteobacteria as the main bacterial phyla, dominated by lactic acid bacteria (Levilactobacillus, Lactiplantibacillus, Weissella). Correlation analysis revealed that five bacterial genera (Levilactobacillus, Lactiplantibacillus, Enterobacter, Pediococcus and Acetobacter) were highly correlated with organic acids, free amino acids, and volatile flavor compounds, indicating their pivotal role in forming the characteristic flavor of fermented asparagus by-products (FAPS). This study provides new insights into the flavor and microbial profile of FAPS, offering a strategy for value-added processing and industrial production.

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In southern China, seasonal droughts and low soil phosphorus content constrain the productivity of Eucalyptus trees. To understand the rhizosphere microbiome response to the dry season, metagenomic sequencing analysis was used to investigate the 6-year-old Eucalyptus rhizosphere microbiome under four different irrigation and fertilization treatments. The results showed that irrigation and fertilization during the dry season significantly altered the composition of microbiome in the rhizosphere soil of Eucalyptus plantations. The soil physicochemical properties and enzyme activity explained 30.73 % and 29.75 % of the changes in bacterial and fungal community structure in Eucalyptus rhizosphere soil, respectively. Irrigation and fertilization during the dry season significantly altered the physicochemical properties of rhizosphere soil. Compared with the seasonal drought without fertilizer treatment (CK), the dry season irrigation with fertilizer treatment (WF) significantly increased the content of total nitrogen (46.34 %), available nitrogen (37.72 %), available phosphorus (440.9 %), and organic matter (35.34 %). Soil organic matter (OM), pH, and available phosphorus (AP) were key environmental factors influencing the microbial community composition. Moreover, irrigation and fertilization promoted carbon fixation and nitrogen and phosphorus mineralization, increasing soil OM content and the availability of inorganic nitrogen and phosphorus. Meanwhile, compared to the CK, the increase of acid phosphatase (16.81 %), invertase (146.89 %)and urease (59.45 %) in rhizosphere soil under irrigation (W) treatment further proves that dry season irrigation promote the soil carbon, nitrogen and phosphorus cycles. Irrigation and fertilization treatment alleviated the constraints of low phosphorus in southern China's soil, which promoted Eucalyptus productivity. In conclusion, we suggest implementing reasonable irrigation and fertilization strategies in the production practice of Eucalyptus and utilizing microbial resources to improve soil fertility and Eucalyptus productivity.

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Unsustainable straw treatment methods detrimentally affect the environment and ecology. Aerobic fermentation (AE) and anaerobic fermentation (AN) are environmentally friendly treatments that better utilise straw resources. In this study, high-throughput sequencing was used to investigate the effects of AE and AN on nutrient content and microbial community structure during tomato straw fermentation. Nitrate nitrogen, available phosphorus, available potassium, and fulvic acid contents following AE were 1250.04 mg/kg, 80.34 %, 161.39 %, and 49.31 %, respectively, which were higher than those following AN. Ammonium nitrogen, humic acid, and humic substance levels following AN were 309.07 %, 31.18 %, and 17.38 %, respectively, which were higher than those following AE. Firmicutes (24.76 %) and Actinobacteria (12.93 %) were more abundant following AE, whereas Proteobacteria (33.82 %) and Bacteroidetes (33.82 %) exhibited higher abundance following AN. AE more effectively eliminated pathogenic bacteria (22.01%-0.26 %) and encouraged stronger interactions between dominant bacterial genera. Redundancy and Mantel test analyses revealed that electrical conductivity and temperature were the most important environmental factors affecting bacterial communities in AE and AN, respectively. AE had a stronger effect on effective nutrient release from tomato straw, implying its greater application potential as a fertiliser. Overall, our study provides a theoretical basis for the optimisation of fermentation methods and processes.

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Beef flavor profiles are strongly influenced by cooking methods and lipid composition. However, the effect of instant-boiling on the aroma of different beef slices was unclear. This study investigated the lipid profiles and instant-boiling volatile profiles of chuck tender (M. Supraspinatus), sirloin (M. Longissimus dorsi) and silverside (M. Biceps femoris). Quantitative lipidomics identified 336 lipid molecular species, of which 84-112 were quantitatively different among the three beef slices. Sirloin had lower phosphatidylcholine, phosphatidylinositol, phosphatidylglycerol and free fatty acids than chuck tender and silverside. The unsaturated fatty acid acyl chains in phosphatidylethanolamine differed significantly. Solid phase microextraction-gas chromatography-olfactometry-mass spectrometry (SPME-GC-O-MS) identified hexanal, octanal, nonanal, decanal, (E)-2-octenal, (E)-2-nonenal, (E)-2-undecenal, (E,E)-2,4-nonadienal, (E,E)-2,4-decadienal, 1-octen-3-ol, 2-pentylfuran and acetoin as the aroma-active compounds of instant-boiled beef. Unsaturated free fatty acids and phosphatidylglycerols with unsaturated fatty acid residues positively correlated with the aroma-active compounds and might be crucial in flavor differences among the three beef slices. These findings provide greater understanding of the lipid and instant-boiling aroma-active compound profiles in chuck tender, sirloin and silverside, and reflect the suitability of different beef slices for instant-boiling from the aroma perspective.

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Matcha shows promise for diabetes, obesity, and gut microbiota disorders. Studies suggest a significant link between gut microbiota, metabolites, and obesity. Thus, matcha may have a positive impact on obesity by modulating gut microbiota and metabolites. This study used 16S rDNA sequencing and untargeted metabolomics to examine the cecal contents in mice. By correlation analysis, we explored the potential mechanisms responsible for the positive effects of matcha on obesity. The results indicated that matcha had a mitigating effect on the detrimental impacts of a high-fat diet (HFD) on multiple physiological indicators in mice, including body weight, adipose tissue weight, serum total cholesterol (TC), and low-density lipoprotein (LDL) levels, as well as glucose tolerance. Moreover, it was observed that matcha had an impact on the structural composition of gut microbiota and gut metabolites. Specifically, matcha was able to reverse the alterations in the abundance of certain obesity-improving bacteria, such as Alloprevotella, Ileibacterium, and Rikenella, as well as the abundance of obesity-promoting bacteria Romboutsia, induced by a HFD. Furthermore, matcha can influence the levels of metabolites, including formononetin, glutamic acid, pyroglutamic acid, and taurochenodeoxycholate, within the gastrointestinal tract. Additionally, matcha enhances caffeine metabolism and the HIF-1 signaling pathway in the KEGG pathway. The results of the correlation analysis suggest that formononetin, theobromine, 1,3,7-trimethyluric acid, and Vitamin C displayed negative correlation with both the obesity phenotype and microbiota known to exacerbate obesity, while demonstrating positive correlations with microbiota that alleviated obesity. However, glutamic acid, pyroglutamic acid, and taurochenodeoxycholate had the opposite effect. In conclusion, the impact of matcha on gut metabolites may be attributed to its modulation of the abundance of Alloprevotella, Ileibacterium, Rikenella, and Romboutsia within the gastrointestinal tract, thereby potentially contributing to the amelioration of obesity.

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While key aroma and taste compounds of Keemun Congou black teas (KCBT) form during aeration and thermal stages, it is still unknown whether these processing stages also produce non-volatile color-contributing metabolites. Through integrating metabolomics with correlation and ridge regression analyses, 190 metabolites were identified as marker compounds that reclassified 15 KCBT samples collected from five processing stages into four groups. Meanwhile, the results of quantification and heatmap analysis showed that the concentrations of theaflavins and theasinensins significantly increased, as catechin decreased, after rolling, while flavonoid aglycones and polyunsaturated fatty acids increased throughout drying. Regression analysis between marker compound levels and total color difference values (∆E) revealed that the major color contributors were 3,5-dicaffeoylquinic acid, glucosyl-dehydrodigallic acid, theacitrin A, kaempferol-O-robinobioside, and (-)-epigallocatechin, with regression coefficients (absolute value) exceeding 4 × 10-2. Overall, the present study confirmed that rolling and drying were the two vital stages responsible for the color formation of KCBT.

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Black tea is highly favored by consumers worldwide, with enzymatic reactions being recognized as a pivotal factor influencing tea quality. The role of microorganisms in shaping the composition of black tea has emerged as a focus of research due to their involvement in enzyme catalysis and metabolic processes. In this study, full-length amplicon sequencing combined with qPCR more accurately reflected microbial profile, and Pantoea, Pseudomonas, Paucibacter, and Cladosporium were identified as the main microbial genera. Moreover, by comprehensively analyzing color, aroma, and taste components over time in black tea samples, correlations were established between the dominant genus and various quality factors. Notably, peroxidase activity levels, total soluble sugar content, and tea pigments concentration exhibited significant associations with the dominant genus. Consequently, this microbiological perspective facilitated the exploration of driving factors for improving black tea quality while establishing a theoretical foundation for quality control in industrial production.

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Background: In volleyball, the jump serve is a crucial and commonly used serving technique. Nonetheless, the angular momentum developed during the jump serve remains unexplored. The objectives of the current study were to determine the angular momentum manifesting during the airborne phase of the jump serve and to analyse the correlations between the angular momentum variables and arm swing speed. Methods: Three-dimensional coordinate data were obtained during the jump serves of 17 professional male volleyball players. Correlation and linear regression analyses were used to identify the angular momentum variables linked to the arm swing speed at ball impact (BI). Results: The arm swing speed at BI exhibited significant correlations with the peak angular momentum of the attack arm (r = 0.551, p = 0.024), non-attack arm (r = 0.608, p = 0.011), non-attack leg (r = -0.516, p = 0.034), forearm (r = 0.527, p = 0.032), and hand (r = 0.824, p < 0.001). A stepwise regression model (R2 = 0.35, p = 0.043) predicted arm swing speed based on the peak angular momentum of the non-attack leg, forearm, and hand. Conclusions: The study results suggest that during the arm-acceleration phase, (1) increasing angular momentum with the non-attack leg helps maintain aerial body balance, thereby enhancing arm swing execution, and (2) controlling the magnitude and timing of the force exerted by the elbow and wrist is crucial for effectively transmitting angular momentum, contributing to an increase in arm swing speed.

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BACKGROUND: Acute lymphoblastic leukemia (ALL) is a common hematologic cancer with unique incidence and prognosis patterns in people of all ages. Recent molecular biology advances have illuminated ALL's complex molecular pathways, notably the Hedgehog (Hh) signaling system and non-coding RNAs (ncRNAs). This work aimed to unravel the molecular complexities of the link between Hh signaling and ALL by concentrating on long non-coding RNAs (lncRNAs) and their interactions with significant Hh pathway genes. METHODS: To analyze differentially expressed lncRNAs and genes in ALL, microarray data from the Gene Expression Omnibus (GEO) was reanalyzed using a systems biology approach. Hh signaling pathway-related genes were identified and their relationship with differentially expressed long non-coding RNAs (DElncRNAs) was analyzed using Pearson's correlation analysis. A regulatory network was built by identifying miRNAs that target Hh signaling pathway-related mRNAs. RESULTS: 193 DEGs and 226 DElncRNAs were found between ALL and normal bone marrow samples. Notably, DEGs associated with the Hh signaling pathway were correlated to 26 DElncRNAs. Later studies showed interesting links between DElncRNAs and biological processes and pathways, including drug resistance, immune system control, and carcinogenic characteristics. DEGs associated with the Hh signaling pathway have miRNAs in common with miRNAs already known to be involved in ALL, including miR-155-5p, and miR-211, highlighting the complexity of the regulatory landscape in this disease. CONCLUSION: The complex connections between Hh signaling, lncRNAs, and miRNAs in ALL have been unveiled in this study, indicating that DElncRNAs linked to Hh signaling pathway genes could potentially serve as therapeutic targets and diagnostic biomarkers for ALL.

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Coconut milk products are susceptible to bacterial damage, necessitating sterilization methods that often compromise nutrient and aroma integrity. This study investigates the effects of different thermal sterilisation methods on coconut milk aroma using headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) and headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS). We assessed the impact of pasteurisation (PAS, 70 °C, 25 min), high-temperature sterilisation (HTS, 121.1 °C, 15 min), and ultra-high temperature sterilisation (UHT, 130 °C, 5 s) through clustered heat maps and correlation analyses. Significant differences were observed (p < 0.05), with 37 and 52 substances detected by HS-GC-IMS and HS-SPME-GC-MS, respectively, identifying 12 key aroma compounds. UHT treatment primarily reduced 8 acids, maintaining a compositional structure and sensory profile similar to raw coconut milk. PAS and HTS treatments decreased the sensory intensity of overall coconut milk aroma, creamy, and floral notes, correlating with the presence of 2-heptanol, nonanal, 4-methylvaleric acid, and 2-tridecanone. These methods increased cooked notes, associated with 5-methyl-3-heptanone, 3-butyn-1-ol, hydroxyacetone, and acetoin. Rancidity was linked to acids such as isobutyric acid, isovaleric acid, and heptanoic acid, with high temperatures effectively reducing these compounds. Prolonged temperature changes in PAS and HTS accelerated lipid oxidative degradation and the Maillard reaction, involving free fatty acids in the formation of alcohols, aldehydes, esters, and lactones. These findings provide a theoretical basis for studying coconut milk flavour deterioration.

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Exploring the temporal and spatial dynamics of vegetation coverage in the Heilongjiang Basin and its response to climate change can provide a theoretical basis and data support for integrated basin management for three countries (Mongolia, China and Russia) in the region. We used MOD13Q1 remote sensing data from Google Earth Engine (GEE) platform between 2000 and 2020 to process the normalized vegetation index (NDVI) through the maximum value composites method, and calculated the vegetation coverage (FVC) using the dimidiate pixel model. The Sen+MK trend analysis method was employed to monitor the dynamics of FVC, while the Pearson correlation coefficient was utilized to quantify the responses of FVC to climate change. The results showed that the overall FVC in the Heilongjiang Basin exhibited a slight decreasing trend during 2000-2020, with an annual rate of 0.1%. The FVC in Mongolia showed a fluctuating increase trend (0.13%), while slight decrease trends were observed for Russia (0.15%) and China (0.08%). The FVC predominantly slightly degraded and severely degraded, accounting for 34% and 17% of the area, respectively, while the significantly improved area only accounted for 9%. The impact of precipitation on FVC in the study area was significantly greater than that of temperature. The proportion of areas where precipitation and temperature had a significant impact on FVC was 8.2% and 2.2%, respectively. The correlation coefficient between precipitation and FVC was the highest in Mongolia (r=0.446, P<0.05), and the lowest in Russian region (r=-0.442, P< 0.05).

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BACKGROUND: The control of schistosomiasis is particularly difficult in sub-Saharan Africa, which currently harbours 95% of this disease. The target population for preventive chemotherapy (PC) is expanded to all age group at risk of infection, thus increasing the demands of praziquantel (PZQ) tablets according to the new released guideline by World Health Organization. Due to the gap between available PZQ for PC and requirements, alternative approaches to assess endemicity of schistosomiasis in a community, are urgently needed for more quick and precise methods. We aimed to find out to which degree the infection status of snails can be used to guide chemotherapy against schistosomiasis. METHODS: We searched literature published from January 1991 to December 2022, that reported on the prevalence rates of Schistosoma mansoni, S. haematobium in the intermediate snails Biomphalaria spp. and Bulinus spp., respectively, and in humans. A random effect model for meta-analyses was used to calculate the pooled prevalence estimate (PPE), with heterogeneity assessed using I-squared statistic (I2), with correlation and regression analysis for the exploration of the relationship between human S. mansoni and S. haematobium infections and that in their specific intermediate hosts. RESULTS: Forty-seven publications comprising 59 field investigations were included. The pooled PPE of schistosomiasis, schistosomiasis mansoni and schistosomiasis haematobium in humans were 27.5% [95% confidence interval (CI): 24.0-31.1%], 25.6% (95% CI: 19.9-31.3%), and 28.8% (95% CI: 23.4-34.3%), respectively. The snails showed an overall infection rate of 8.6% (95% CI: 7.7-9.4%), with 12.1% (95% CI: 9.9-14.2%) in the Biomphalaria spp. snails and 6.9% (95% CI: 5.7-8.1%) in the Bulinus spp. snails. The correlation coefficient was 0.3 (95% CI: 0.01-0.5%, P < 0.05) indicating that the two variables, i.e. all intermediate host snails on the one hand and the human host on the other, were positively correlated. CONCLUSIONS: The prevalence rate of S. mansoni and S. haematobium is still high in endemic areas. Given the significant, positive correlation between the prevalence of schistosomes in humans and the intermediate snail hosts, more attention should be paid to programme integration of snail surveillance in future.

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Purpose: Attention-deficit hyperactivity disorder (ADHD) stands as a significant psychiatric and neuro-developmental disorder with global prevalence. The prevalence of ADHD among school children in India is estimated to range from 5% to 8%. However, certain studies have reported higher prevalence rates, reaching as high as 11%. Utilizing electroencephalography (EEG) signals for the early detection and classification of ADHD in children is crucial. Methods: In this study, we introduce a CNN architecture characterized by its simplicity, comprising solely two convolutional layers. Our approach involves pre-processing EEG signals through a band-pass filter and segmenting them into 5-s frames. Following this, the frames undergo normalization and canonical correlation analysis. Subsequently, the proposed CNN architecture is employed for training and testing purposes. Results: Our methodology yields remarkable results, with 100% accuracy, sensitivity, and specificity when utilizing the complete 19-channel EEG signals for diagnosing ADHD in children. However, employing the entire set of EEG channels presents challenges related to the computational complexity. Therefore, we investigate the feasibility of using only frontal brain EEG channels for ADHD detection, which yields an accuracy of 99.08%. Conclusions: The proposed method yields high accuracy and is easy to implement, hence, it has the potential for widespread practical deployment to diagnose ADHD.

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Zearalenone (ZEN), a mycotoxin produced by Fusarium species, is known for its reproductive toxicity as an estrogen analogue. However, there are limited knowledge about its hepatointestinal toxicity, as well as the role that gut microbiota and metabolites play in this process. In this study, a total of 24 thirty-week-old hens were fed to investigate the hepatointestinal toxicity subjected to long-term ZEN consumption at 2.0 mg/kg for 90 d. And we employed uncultured 16S rRNA sequencing for gut microbiota and untargeted metabolomics for fecal metabolites assessment. Notably, ZEN induced significant hepatic damage, as evidenced by hepatocyte necrosis, inflammatory cell infiltrate, increased liver lipopolysaccharide (LPS) and blood aspartate aminotransferase (AST) levels (P < 0.05). The decreased villus height, disruption of simple columnar epithelial cells, and exposure of the mucosal intrinsic layer were observed in the intestine. The gut microbial community composition and metabolites differed between ZEN group and control group. ZEN group exhibited higher gut microbial diversity (P < 0.05), lower Firmicutes/Bacteroidetes ratio and Lactobacillus abundance, and higher abundance in the genus such as Bacteroidetes, Parabacteroidetes and Desulfovibrio. Metabolomic analysis showed that ZEN treatment altered biosynthesis of siderophore group nonribosomal peptides and phenylpropanoids, metabolism of amino acid, digestion and absorption of vitamin and ABC transporters. Differential metabolites suggested that ZEN increase the risk of estrogen disorder, nucleic acid degradation, intestinal oxidative stress and inflammation. Neural network analysis showed that Ruminococcus was positively correlated with glyceric acid, and Prevotella was positively correlated with phenylacetylglycine. Both metabolites were positively correlated with blood AST level (P < 0.05), suggesting that intestinal microbe Ruminococcus and Prevotella might exacerbate liver damage by producing these harmful metabolites. Overall, we conclude that ZEN has damaged hepatointestinal system and the altered gut microbiota with resultant metabolite changes contribute to the adverse hepatointestinal effects of ZEN on laying hens. This study underscores the need for monitoring and mitigating ZEN exposure in poultry diets, highlighting its broader implications for animal health and food safety.

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In the majority of downstream analysis pipelines for single-cell RNA sequencing (scRNA-seq), techniques like dimensionality reduction and feature selection are employed to address the problem of high-dimensional nature of the data. These approaches involve mapping the data onto a lower-dimensional space, eliminating less informative genes, and pinpointing the most pertinent features. This process ultimately leads to a reduction in the number of dimensions used for downstream analysis, which in turn speeds up the computation of large-scale scRNA-seq data. Most approaches are directed to isolate from biological background the genes characterizing different cells and or the condition under study by establishing lists of differentially expressed or coexpressed genes. Herein, we present scRNA-Explorer an open-source online tool for simplified and rapid scRNA-seq analysis designed with the end user in mind. scRNA-Explorer utilizes: (i) Filtering out uninformative cells in an interactive manner via a web interface, (ii) Gene correlation analysis coupled with an extra step of evaluating the biological importance of these correlations, and (iii) Gene enrichment analysis of correlated genes in order to find gene implication in specific functions. We developed a pipeline to address the above problem. The scRNA-Explorer pipeline allows users to interrogate in an interactive manner scRNA-sequencing data sets to explore via gene expression correlations possible function(s) of a gene of interest. scRNA-Explorer can be accessed at https://bioinformatics.med.uoc.gr/shinyapps/app/scrnaexplorer.

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Cyanra cardunclus L. var. ferocissima is widely used in Morocco as a food and in traditional medicine. Therefore, this study aimed to determine, for the first time, the phytochemical content and antioxidant and anti-inflammatory activities of this variety. Qualitative tests were used to screen for the phytochemical compounds present in the extract, and spectrophotometric methods were used for quantification. The sugar profiles were determined using HPLC. Antioxidant activity was determined in vitro using DPPH, FRAP, and total antioxidant activity assays, and anti-inflammatory activity was assessed using serum albumin denaturation and membrane stabilization assays. The extract contained a high amount of total polyphenols, hydrocinnamic acids, anthocyanins, chlorophyll, ortho-diphenols, terpenoids, and triterpenoids. In addition, five sugars were identified with high amounts of raffinose and sucrose. The extract exerted considerable antioxidant activity by scavenging radicals and reducing power. It exerts anti-inflammatory effects by inhibiting protein denaturation and heat-inducing hemolysis. From the correlation results, anthocyanin, polyphenol, and triterpenoid contents were strongly correlated with DPPH free radical scavenging activity. Orthodiphenols, flavonols, and chlorophyll α were strongly correlated with FRAP, whereas orthodiphenols, hydrocinnamic acids, and triterpenoids were strongly correlated with total antioxidant activity. In terms of anti-inflammatory activity, orthodiphenols, hydrocinnamic acids, and triterpenoids correlated strongly with inhibition of bovine serum albumin denaturation activity, whereas terpenoids, flavonols, and chlorophyll correlated strongly with red cell membrane-stabilizing activity. In conclusion, the Moroccan Cynara cardunclus var. ferocissima leaf methanolic extract constitutes a promising source of phytochemicals with considerable antioxidant and anti-inflammatory activity.

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OBJECTIVES: This study aimed to compare plasma concentrations of anesthetic drugs administered during Cesarean section with low Apgar score in neonates deliveried under general anesthesia and analyze associated risk factors. METHODS: Data from 76 neonates undergoing Cesarean section under general anesthesia with blood concentrations of anesthetic drugs were analyzed. A low Apgar score was defined as ≤ 7. Perioperative maternal and neonatal data were collected and analyzed. Neonates were divided into a control group (Group CON, n = 65) and a low Apgar score group (Group LAS, n = 11) based on Apgar score. RESULTS: There were no significant differences in the plasma concentrations of anesthetic drugs in maternal artery, umbilical vein or umbilical artery blood between the two groups. Risk factors for neonatal low Apgar scores during Cesarean section under general anesthesia were premature delivery (aOR 10.2, 95% CI = 1.8-56.9) and preoperative fetal distress (aOR 9.6, 95% CI = 1.3-69.0). The prediction model was: probability = 1/(e­Y), Y= -4.607 + 2.318× (premature delivery) + 2.261× (fetal distress) (yes = 1, no = 0). The Hosmer-Lemeshow test showed χ²= 9.587, P = 0.213, and the area under the curve (AUC) was 0.850 (0.670 ~ 1.000). With a cutoff value of 0.695, sensitivity and specificity were 81.8% and 87.7%, respectively. CONCLUSIONS: There was no correlation between blood concentration of general anesthetic drugs and Apgar score or occurrence of neonatal low Apgar scores. Premature delivery and preoperative fetal distress were identified as independent risk factors for neonatal low Apgar scores after Cesarean section under general anesthesia.

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