Chinese Clinical Named Entity Recognition(CNER)is a crucial step in extracting medical information and is of great significance in promoting medical informatization.However,CNER poses challenges due to the specificity...Chinese Clinical Named Entity Recognition(CNER)is a crucial step in extracting medical information and is of great significance in promoting medical informatization.However,CNER poses challenges due to the specificity of clinical terminology,the complexity of Chinese text semantics,and the uncertainty of Chinese entity boundaries.To address these issues,we propose an improved CNER model,which is based on multi-feature fusion and multi-scale local context enhancement.The model simultaneously fuses multi-feature representations of pinyin,radical,Part of Speech(POS),word boundary with BERT deep contextual representations to enhance the semantic representation of text for more effective entity recognition.Furthermore,to address the model’s limitation of focusing just on global features,we incorporate Convolutional Neural Networks(CNNs)with various kernel sizes to capture multi-scale local features of the text and enhance the model’s comprehension of the text.Finally,we integrate the obtained global and local features,and employ multi-head attention mechanism(MHA)extraction to enhance the model’s focus on characters associated with medical entities,hence boosting the model’s performance.We obtained 92.74%,and 87.80%F1 scores on the two CNER benchmark datasets,CCKS2017 and CCKS2019,respectively.The results demonstrate that our model outperforms the latest models in CNER,showcasing its outstanding overall performance.It can be seen that the CNER model proposed in this study has an important application value in constructing clinical medical knowledge graph and intelligent Q&A system.展开更多
Curry leaves, scientifically termed Murraya koenigii, are renowned in South Asian cuisine for their flavor enhancement and potential health benefits, including antioxidative, anti-inflammatory, and antidiabetic proper...Curry leaves, scientifically termed Murraya koenigii, are renowned in South Asian cuisine for their flavor enhancement and potential health benefits, including antioxidative, anti-inflammatory, and antidiabetic properties. This study aimed to evaluate the impact of thermal processing methods on curry leaves by analysing Total Phenolic Content (TPC), Total Flavonoid Content (TFC), antioxidant activity, and metabolizing enzyme inhibition. Fresh curry leaves were subjected to thermal treatments: Oven-dried at 60˚C and Air-dried at 25˚C for 2 weeks. Extracts were prepared using Ethanol and water solvents. Results indicated that Air-dried leaves exhibited significantly higher TPC (5132.65 mg GAE/100 g) and TFC (243.13 mg CE/100 g) compared to Fresh and Oven-dried leaves. Antioxidant assays show that oven-dried curry leaves at 60˚C displayed higher results in NORS, FRAP, and TEAC assays compared to Fresh and Air-dried leaves. Ethanol extracts showed better extraction of bioactive compounds than aqueous extracts. Moreover, Lipase inhibition activity was notably high, indicating potential health benefits. This study provides valuable insights into the effects of processing methods on curry leaf extracts, emphasizing the importance of solvent selection for optimal extraction of bioactive compounds.展开更多
Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend o...Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.展开更多
Characterizing foliar trait variation in sun and shade leaves can provide insights into inter-and intra-species resource use strategies and plant response to environmental change.However,datasets with records of multi...Characterizing foliar trait variation in sun and shade leaves can provide insights into inter-and intra-species resource use strategies and plant response to environmental change.However,datasets with records of multiple foliar traits from the same individual and including shade leaves are sparse,which limits our ability to investigate trait-trait,trait-environment relationships and trait coordination in both sun and shade leaves.We presented a comprehensive dataset of 15 foliar traits from sun and shade leaves sampled with leaf spectroscopy,including 424 individuals of 110 plant species from 19 sites across eastern North America.We investigated trait variation,covariation,scaling relationships with leaf mass,and the effects of environment,canopy position,and taxonomy on trait expression.Generally,sun leaves had higher leaf mass per area,nonstructural carbohydrates and total phenolics,lower mass-based chlorophyll a+b,carotenoids,phosphorus,and potassium,but exhibited species-specific characteristics.Covariation between sun and shade leaf traits,and trait-environment relationships were overall consistent across species.The main dimensions of foliar trait variation in seed plants were revealed including leaf economics traits,photosynthetic pigments,defense,and structural traits.Taxonomy and canopy position collectively explained most of the foliar trait variation.This study highlights the importance of including intra-individual and intra-specific trait variation to improve our understanding of ecosystem functions.Our findings have implications for efficient field sampling,and trait mapping with remote sensing.展开更多
To investigate the effects of drinking the soaking of Malus domeri(Bois)Chev.leaves on gut microbiota and metabolites of long-living elderly individuals in Hezhou city,Guangxi,China.It has been reported that longevity...To investigate the effects of drinking the soaking of Malus domeri(Bois)Chev.leaves on gut microbiota and metabolites of long-living elderly individuals in Hezhou city,Guangxi,China.It has been reported that longevity is closely related to metabolism and the gut microbiota.The 16S rRNA sequencing and liquid chromatography-mass spectrometry(LC-MS)were used to analysis fecal samples and explore the factors affecting longevity in the region.Interestingly,we discovered,that elderly individuals who had been drinking the soaking of M.domeri(Bois)Chev.leaves for a long time exhibited higher diversity of the gut microbiota than without drinking the soaking,notably.The proportions of Ruminococcaceae and Prevotella were decreased in those who did not drink this soaking.In addition,a total of 106 metabolites were characterized,and the people of long-lived people(>90 years old)and elderly people(<90 years old)who drinking soaking of M.domeri(Bois)Chev.leaves significantly altered the gut microbiota and upregulated levels of haplopine,farnesol,genipic acid,momordicinin,2-hydroxyestrone,hydroxyphenyllactic acid,caffeic acid,sophoraflavanone B,and soyasaponin I.We preliminarily determined that M.domeri(Bois)Chev.leaves consumption may be an important factor affecting longevity in this area.展开更多
Aim: This study aimed to investigate the protective effects of flavonoids from the stem and leaves of Scutellaria baicalensis Georgi (SSFs) against Aβ<sub>1-42</sub>-induced oligodendrocytes (OL) damage. ...Aim: This study aimed to investigate the protective effects of flavonoids from the stem and leaves of Scutellaria baicalensis Georgi (SSFs) against Aβ<sub>1-42</sub>-induced oligodendrocytes (OL) damage. Methods: Immunofluorescence was used for the detection of myelin-associated glycoprotein (MAG), a characteristic protein of rat oligodendrocytes (OLN-93 cells). To evaluate the potential protective effects of SSFs on OLN-93 cells injured by Aβ<sub>1-42</sub>, an injury model was established by subjecting OLN-93 cells to Aβ<sub>1-42</sub> exposed. Cell morphology was examined using an inverted microscope, while cell viability was assessed using the colorimetric method of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). Additionally, lactate dehydrogenase (LDH) was measured using the pyruvic acid reduction assay. The Ginkgo biloba leaf extract (GBE) injection was used as a positive control. Results: A total of >95% of the MAG immunofluorescence-positive cells were identified as oligodendrocytes. Gradually increasing concentrations of SSFs impaired the cells, and the maximum nondetrimental dose for OLN-93 cells was 75 mg/L. This study assessed the effects of SSFs on OLN-93 cells damaged by Aβ<sub>1-42</sub>. The results indicated that SSFs significantly improved OLN-93 cell morphological abnormal changes, increased the OLN-93 cell survival rate, and reduced LDH release. Conclusion: SSFs can alleviate Aβ<sub>1-42</sub>-induced damage of OL.展开更多
This study was to investigate the effects of three exogenous substances on chemical constituents of Isatis indigotica leavesand their efficacy in alleviating drought stress, and explore the methods of applying exogeno...This study was to investigate the effects of three exogenous substances on chemical constituents of Isatis indigotica leavesand their efficacy in alleviating drought stress, and explore the methods of applying exogenous substances to efficient cultivationof Isatis indigotica. Polyethylene glycol (PEG) was used to simulate drought stress to deal with seeds of Isatis indigotica at thegermination stage (concentration: 0, 10%, 15%, and 20%). Simultaneous operation of exogenous growth regulators [microbialinoculum (MI), γ-aminobutyric acid (GABA) and salicylic acid (SA)] and PEG were implemented in seeds of Isatis indigotica.The effects of drought stress and the mitigation of exogenous substances were observed by statistics of seed germination potential,germination rate, hypocotyl length, and radicle length of each treatment. The effects of exogenous substances on the content ofalkaloids, crude protein and free amino acids in the leaves of Isatis indigotica grown in a greenhouse were determined after sprayingexogenous substances on the plants. The differences of germination potential, germination rate, hypocotyl length, and radicle lengthamong 15% PEG stress treatment, 10% PEG stress treatment and the control were significant (P<0.05). According to the predesignedgermination standard, the seeds did not germinate under 20% PEG stress treatment. When the PEG concentration was 15%, the resultsof seed germination potential and germination rate after adding MI were significantly different from those under stress alone (P<0.05).When exposed to 10% PEG stress, the supplementation of GABA led to a notable increase in radicle length of Isatis indigotica seeds,showing significant differences compared to other three treatments. The application of MI and GABA under 15% PEG stress resultedin a significant increase in the radicle and hypocotyl length of Isatis indigotica seeds compared to other two treatments. The contentof the total alkaloids in leaves of Isatis indigotica was significantly increased after spraying GABA. Meanwhile, the contents of crudeprotein and the total free amino acids were kept constant after spraying exogenous substances. Application of MI and GABA couldalleviate drought stress of Isatis indigotica. The content of the total alkaloids in leaves of Isatis indigotica could significantly increaseafter spraying GABA.展开更多
The aim of the present study was to investigate on the inventory and determination of the nutritional value of cereals flour and cassava leaves powder in order to analyse their use in the production of infant flour. I...The aim of the present study was to investigate on the inventory and determination of the nutritional value of cereals flour and cassava leaves powder in order to analyse their use in the production of infant flour. In this paper, a A survey to identify the cereals used in the preparation of infant porridge in the Northern Cameroon was done by using 447 mothers having children between 06 and 59 months from areas (Gbakoungue, Sassa-Mbersi, Sanguere-Ngal and Kotkong-Wouldata) with high rate on malnourished children. Flour was prepared from the most preponderant cereals and Cassava leaves powder from varieties identified by the Regional Centre of Agricultural Research (CRRA) of Wakwa and local population. Flour and powder samples obtained were subjected to chemical composition analysis. Parameters analysed were crude proteins, total carbohydrates, ash, total fats, total phenols, total tannins, total carotenoids, vitamin C or cyanide. Also Iron, calcium and zinc were determined. The results revealed that white maize (62%) was the main cereal used in the preparation of infant porridge followed respectively by red sorghum, white rice and muskwari. Ten cassava varieties were identified: three (03) by CRRA (TME, 96/1/14 and IRAD 4115) and seven (south, gambada, sweet, Benin, six months, M. glaziovii and grouna) by local population. Amongst cereals flour, those from white maize indicated high protein (10.09%), carbohydrates (84.46%) and total fat (7.46%) contents. The powder from 96/14/14 cassava variety showed high amount of iron (11.98 mg/100g), calcium (751.02 g/100g) and low cyanide content (1.21 ppm) amongst all the cassava leaves powder samples. The supplementation of white maize flour by cassava leaves powder from 96/14/14 variety could therefore be recommended for the preparation of infant flours.展开更多
This paper analyzes the progress of handwritten Chinese character recognition technology,from two perspectives:traditional recognition methods and deep learning-based recognition methods.Firstly,the complexity of Chin...This paper analyzes the progress of handwritten Chinese character recognition technology,from two perspectives:traditional recognition methods and deep learning-based recognition methods.Firstly,the complexity of Chinese character recognition is pointed out,including its numerous categories,complex structure,and the problem of similar characters,especially the variability of handwritten Chinese characters.Subsequently,recognition methods based on feature optimization,model optimization,and fusion techniques are highlighted.The fusion studies between feature optimization and model improvement are further explored,and these studies further enhance the recognition effect through complementary advantages.Finally,the article summarizes the current challenges of Chinese character recognition technology,including accuracy improvement,model complexity,and real-time problems,and looks forward to future research directions.展开更多
Background:The use of industrial by-products rich in bioactive compounds as animal feeds can reduce greenhouse gas production.Paulownia leaves silage(PLS)was supplemented to dairy cows'diet and evaluated in vitro(...Background:The use of industrial by-products rich in bioactive compounds as animal feeds can reduce greenhouse gas production.Paulownia leaves silage(PLS)was supplemented to dairy cows'diet and evaluated in vitro(Exp.1;Rusitec)and in vivo(Exp.2,cannulated lactating dairy cows and Exp.3,non-cannulated lactating dairy cows).The study investigated the PLS effect on ruminal fermentation,microbial populations,methane production and concentration,dry matter intake(DMI),and fatty acid(FA)proportions in ruminal fluid and milk.Results:Several variables of the ruminal fluid were changed in response to the inclusion of PLS.In Exp.1,the p H increased linearly and quadratically,whereas ammonia and total volatile fatty acid(VFA)concentrations increased linearly and cubically.A linear,quadratic,and cubical decrease in methane concentration was observed with increasing dose of the PLS.Exp.2 revealed an increase in ruminal p H and ammonia concentrations,but no changes in total VFA concentration.Inclusion of PLS increased ruminal propionate(at 3 h and 6 h after feeding),isovalerate,and valerate concentrations.Addition of PLS also affected several populations of the analyzed microorganisms.The abundances of protozoa and bacteria were increased,whereas the abundance of archaea were decreased by PLS.Methane production decreased by 11%and 14%in PLS-fed cows compared to the control in Exp.2 and 3,respectively.Exp.3 revealed a reduction in the milk protein and lactose yield in the PLS-fed cows,but no effect on DMI and energy corrected milk yield.Also,the PLS diet affected the ruminal biohydrogenation process with an increased proportions of C18:3 cis-9 cis-12 cis-15,conjugated linoleic acid,C18:1 trans-11 FA,polyunsaturated fatty acids(PUFA),and reduced n6/n3 ratio and saturated fatty acids(SFA)proportion in milk.The relative transcript abundances of the 5 of 6 analyzed genes regulating FA metabolism increased.Conclusions:The dietary PLS replacing the alfalfa silage at 60 g/kg diet can reduce the methane emission and improve milk quality with greater proportions of PUFA,including conjugated linoleic acid,and C18:1 trans-11 along with reduction of SFA.展开更多
Objective:To investigate the relationship between triterpenoid saponin content and antioxidant,antimicrobial,and α-glucosidase inhibitory activities of 70%ethanolic,butanolic,aqueous,supernate and precipitate extract...Objective:To investigate the relationship between triterpenoid saponin content and antioxidant,antimicrobial,and α-glucosidase inhibitory activities of 70%ethanolic,butanolic,aqueous,supernate and precipitate extracts of Juglans regia leaves.Methods:Triterpenoid saponins of different Juglans regia leaf extracts were measured by the vanillin method.Antioxidant activity was evaluated against DPPH and ABTS free radicals.We also assessed α-glucosidase inhibitory and antimicrobial activities of the leaf extracts.Pearson’s correlation coefficient was evaluated to determine the correlation between the saponin content and biological activities.Results:The butanolic extract was most effective against DPPH with an IC50of 6.63μg/mL,while the aqueous extract showed the highest scavenging activity against ABTS free radical with an IC50of 42.27μg/mL.Pearson’s correlation analysis indicated a strong negative correlation (r=-0.956) between DPPH radical scavenging activity (IC50) and the saponin content in the samples examined.In addition,the aqueous extract showed the best α-glucosidase inhibitory activity compared with other extracts.All the extracts had fair antibacterial activity against Bacillus subtilis,Escherichia coli,and Klebsiella pneumoniae except for the aqueous extract.Conclusions:Juglans regia extracts show potent antioxidant,antimicrobial,and α-glucosidase inhibitory activities.There is a correlation between saponin levels in Juglans regia leaf extracts and the studied activities.However,additional research is required to establish these relationships by identifying the specific saponin molecules responsible for these activities and elucidating their mechanisms of action.展开更多
Spices and aromatic plants are products of plant origin used in food. They are used for the preparation of remedies, for seasoning dishes or for preserving food. This review takes stock of the diversity of spices and ...Spices and aromatic plants are products of plant origin used in food. They are used for the preparation of remedies, for seasoning dishes or for preserving food. This review takes stock of the diversity of spices and aromatic herbs, the chemical composition, the different properties and forms of use of six spices and aromatic herbs commonly used in Benin and around the world. These are Zingiber officinalis (ginger), Curcuma longa (curcuma), Syzygium aromaticum (clove) and three aromatic herbs Petroselinum crispum (parsley), Rosmarinus officinalis (rosemary), and Laurus nobilis (laurel). The methodology used is that of documentary research oriented towards the consultation of previous scientific documents that have highlighted the different pharmacological activities of the different species of spices and aromatic plants targeted. It is important to note that more than twenty plant species are used as spices and aromatic plants in Benin and around the world. Chemically, these different spices and aromatic herbs contain certain secondary metabolites such as flavonoids, tannins, coumarins, alkaloids, steroids, terpenes, saponins, and polyphenols. This diversity of secondary metabolites alone or in a possible synergy may be responsible for many beneficial properties attributed to spices and aromatic herbs.展开更多
In order to solve the shortcomings of current fatigue detection methods such as low accuracy or poor real-time performance,a fatigue detection method based on multi-feature fusion is proposed.Firstly,the HOG face dete...In order to solve the shortcomings of current fatigue detection methods such as low accuracy or poor real-time performance,a fatigue detection method based on multi-feature fusion is proposed.Firstly,the HOG face detection algorithm and KCF target tracking algorithm are integrated and deformable convolutional neural network is introduced to identify the state of extracted eyes and mouth,fast track the detected faces and extract continuous and stable target faces for more efficient extraction.Then the head pose algorithm is introduced to detect the driver’s head in real time and obtain the driver’s head state information.Finally,a multi-feature fusion fatigue detection method is proposed based on the state of the eyes,mouth and head.According to the experimental results,the proposed method can detect the driver’s fatigue state in real time with high accuracy and good robustness compared with the current fatigue detection algorithms.展开更多
Sentiment analysis in Chinese classical poetry has become a prominent topic in historical and cultural tracing,ancient literature research,etc.However,the existing research on sentiment analysis is relatively small.It...Sentiment analysis in Chinese classical poetry has become a prominent topic in historical and cultural tracing,ancient literature research,etc.However,the existing research on sentiment analysis is relatively small.It does not effectively solve the problems such as the weak feature extraction ability of poetry text,which leads to the low performance of the model on sentiment analysis for Chinese classical poetry.In this research,we offer the SA-Model,a poetic sentiment analysis model.SA-Model firstly extracts text vector information and fuses it through Bidirectional encoder representation from transformers-Whole word masking-extension(BERT-wwmext)and Enhanced representation through knowledge integration(ERNIE)to enrich text vector information;Secondly,it incorporates numerous encoders to remove text features at multiple levels,thereby increasing text feature information,improving text semantics accuracy,and enhancing the model’s learning and generalization capabilities;finally,multi-feature fusion poetry sentiment analysis model is constructed.The feasibility and accuracy of the model are validated through the ancient poetry sentiment corpus.Compared with other baseline models,the experimental findings indicate that SA-Model may increase the accuracy of text semantics and hence improve the capability of poetry sentiment analysis.展开更多
Fungal infection is a major cause of crop and fruit losses.Recognition of chitin,a component of fungal cell walls,endows plants with enhanced fungal resistance.Here,we found that mutation of tomato LysM receptor kinas...Fungal infection is a major cause of crop and fruit losses.Recognition of chitin,a component of fungal cell walls,endows plants with enhanced fungal resistance.Here,we found that mutation of tomato LysM receptor kinase 4(SlLYK4)and chitin elicitor receptor kinase 1(SlCERK1)impaired chitin-induced immune responses in tomato leaves.Compared with the wild type,sllyk4 and slcerk1 mutant leaves were more susceptible to Botrytis cinerea(gray mold).SlLYK4 extracellular domain showed strong binding affinity to chitin,and the binding of SlLYK4 induced SlLYK4-SlCERK1 association.Remarkably,qRT–PCR analysis indicated that SlLYK4 was highly expressed in tomato fruit,andβ-GLUCURONIDASE(GUS)expression driven by the SlLYK4 promoter was observed in tomato fruit.Furthermore,SlLYK4 overexpression enhanced disease resistance not only in leaves but also in fruit.Our study suggests that chitin-mediated immunity plays a role in fruit,providing a possible way to reduce fungal infection-related fruit losses by enhancing the chitin-induced immune responses.展开更多
Poplar is an important afforestation and urban greening species.Poplar leaf development occurs in stages,from young to mature and then from mature to senescent;these are accompanied by various phenotypic and physiolog...Poplar is an important afforestation and urban greening species.Poplar leaf development occurs in stages,from young to mature and then from mature to senescent;these are accompanied by various phenotypic and physiological changes.However,the associated transcriptional regulatory network is relatively unexplored.We first used principal component analysis to classify poplar leaves at different leaf positions into two stages:developmental maturity(the stage of maximum photosynthetic capacity);and the stage when photosynthetic capacity started to decline and gradually changed to senescence.The two stages were then further subdivided into five intervals by gene expression clustering analysis:young leaves,the period of cell genesis and functional differentiation(L1);young leaves,the period of development and initial formation of photosynthetic capacity(L3-L7);the period of maximum photosynthetic capacity of functional leaves(L9-L13);the period of decreasing photosynthetic capacity of functional leaves(L15-L27);and the period of senescent leaves(L29).Using a weighted co-expression gene network analysis of regulatory genes,high-resolution spatiotemporal transcriptional regulatory networks were constructed to reveal the core regulators that regulate leaf development.Spatiotemporal transcriptome data of poplar leaves revealed dynamic changes in genes and miRNAs during leaf development and identified several core regulators of leaf development,such as GRF5 and MYB5.This in-depth analysis of transcriptional regulation during leaf development provides a theoretical basis for exploring the biological basis of the transcriptional regulation of leaf development and the molecular design of breeding for delaying leaf senescence.展开更多
Leaf-color mutations have been studied extensively in plants.However,to better understand the complex mechanisms underlying the formation of leaf color,it is essential to continue discover novel genes involved in the ...Leaf-color mutations have been studied extensively in plants.However,to better understand the complex mechanisms underlying the formation of leaf color,it is essential to continue discover novel genes involved in the process of leaf color development.In this study,we identified a variegated-leaf(vg)mutant in tomato that exhibited defective phenotypes in thylakoids and photosynthesis.To clone the vg locus,an F2population was constructed from the cross between the vg mutant(Solanum lycopersicum)and the wild tomato LA1589(S.pimpinellifolium).Using the map-based cloning approach,the vg locus was mapped on chromosome 7 and narrowed down to a 128 kb region that contained 21 open reading frames(ORFs).The expression levels of ORF9,ORF10,and ORF13 were significantly lower in vg than in the wild-type plants,while the ORF11 transcript level was elevated in vg.We then mutagenized ORF9,ORF10,and ORF13 by the CRISPR/Cas9 system in the wild-type tomato background and found that only the ORF10 mutation reproduced the phenotype of variegated leaves,indicating that ORF10 represents VG and its down-regulated expression was responsible for the variegated leaf phenotype.ORF10 encodes a thylakoid formation protein and its mutant lines showed reduced levels of chlorophyll synthesis and photosynthesis.Taken together,these results suggest that VG is necessary for chloroplast development,chlorophyll synthesis,and photosynthesis in tomato.展开更多
The traditional recommendation algorithm represented by the collaborative filtering algorithm is the most classical and widely recommended algorithm in the practical industry.Most book recommendation systems also use ...The traditional recommendation algorithm represented by the collaborative filtering algorithm is the most classical and widely recommended algorithm in the practical industry.Most book recommendation systems also use this algorithm.However,the traditional recommendation algorithm represented by the collaborative filtering algorithm cannot deal with the data sparsity well.This algorithm only uses the shallow feature design of the interaction between readers and books,so it fails to achieve the high-level abstract learning of the relevant attribute features of readers and books,leading to a decline in recommendation performance.Given the above problems,this study uses deep learning technology to model readers’book borrowing probability.It builds a recommendation system model through themulti-layer neural network and inputs the features extracted from readers and books into the network,and then profoundly integrates the features of readers and books through the multi-layer neural network.The hidden deep interaction between readers and books is explored accordingly.Thus,the quality of book recommendation performance will be significantly improved.In the experiment,the evaluation indexes ofHR@10,MRR,andNDCGof the deep neural network recommendation model constructed in this paper are higher than those of the traditional recommendation algorithm,which verifies the effectiveness of the model in the book recommendation.展开更多
Coronavirus 2019(COVID-19)is the current global buzzword,putting the world at risk.The pandemic’s exponential expansion of infected COVID-19 patients has challenged the medical field’s resources,which are already fe...Coronavirus 2019(COVID-19)is the current global buzzword,putting the world at risk.The pandemic’s exponential expansion of infected COVID-19 patients has challenged the medical field’s resources,which are already few.Even established nations would not be in a perfect position to manage this epidemic correctly,leaving emerging countries and countries that have not yet begun to grow to address the problem.These problems can be solved by using machine learning models in a realistic way,such as by using computer-aided images during medical examinations.These models help predict the effects of the disease outbreak and help detect the effects in the coming days.In this paper,Multi-Features Decease Analysis(MFDA)is used with different ensemble classifiers to diagnose the disease’s impact with the help of Computed Tomography(CT)scan images.There are various features associated with chest CT images,which help know the possibility of an individual being affected and how COVID-19 will affect the persons suffering from pneumonia.The current study attempts to increase the precision of the diagnosis model by evaluating various feature sets and choosing the best combination for better results.The model’s performance is assessed using Receiver Operating Characteristic(ROC)curve,the Root Mean Square Error(RMSE),and the Confusion Matrix.It is observed from the resultant outcome that the performance of the proposed model has exhibited better efficient.展开更多
Diospyros mespiliformis Hochst. ex A. DC. (Ebenaceae) is a multi-use plant, including for therapeutic purposes. It is used in alternative medicine in Burkina Faso to treat conjunctivitis, menorrhagia, dysentery, and d...Diospyros mespiliformis Hochst. ex A. DC. (Ebenaceae) is a multi-use plant, including for therapeutic purposes. It is used in alternative medicine in Burkina Faso to treat conjunctivitis, menorrhagia, dysentery, and diarrhea. The aim of our study was to evaluate the chemical profile, antioxidant and anti-inflammatory activities, safety of use and spasmolytic effects of the aqueous decoction of Diospyros mespiliformis leaves. Phytochemical screening by HPTLC and assay of compounds of interest were carried out. Four methods were used to assess antioxidant activity. Inhibitory activity against 15-lipoxygenase and phospholipase A2 was assessed. Acute oral toxicity of the extract was tested on female mice (NMRI). Following these tests, the extract contained bioactive compounds of interest such as flavonoids, tannins, sterols, triterpenes, and saponosides. The total phenolic and flavonoid contents of the aqueous decoctate were 70.59 ± 3.20 mg EAT/g and 31.57 ± 0.78 mg EQ/g respectively. The extract was less active than Trolox with inhibitory concentrations of 50% (IC<sub>50</sub>) for the ABTS, DPPH, FRAP, and LPO tests of 7.53 ± 0.08 μg/mL, 29.47 ± 0.06 μg/mL, 1128.83 ± 4.82 mol EAA/g, and 32.30 ± 1.60 μg/mL respectively. The extract has an anti-inflammatory effect with inhibition of phospholipase A2 compared to betamethasone. In addition, the aqueous extract produced an antispasmodic effect with Emax of 70% and 80% respectively during contractions induced by BaCl<sub>2</sub> and ACh. Finally, this study provided basic scientific data and could justify the use of D. mespiliformis leaves in the treatment of diarrhea.展开更多
基金This study was supported by the National Natural Science Foundation of China(61911540482 and 61702324).
文摘Chinese Clinical Named Entity Recognition(CNER)is a crucial step in extracting medical information and is of great significance in promoting medical informatization.However,CNER poses challenges due to the specificity of clinical terminology,the complexity of Chinese text semantics,and the uncertainty of Chinese entity boundaries.To address these issues,we propose an improved CNER model,which is based on multi-feature fusion and multi-scale local context enhancement.The model simultaneously fuses multi-feature representations of pinyin,radical,Part of Speech(POS),word boundary with BERT deep contextual representations to enhance the semantic representation of text for more effective entity recognition.Furthermore,to address the model’s limitation of focusing just on global features,we incorporate Convolutional Neural Networks(CNNs)with various kernel sizes to capture multi-scale local features of the text and enhance the model’s comprehension of the text.Finally,we integrate the obtained global and local features,and employ multi-head attention mechanism(MHA)extraction to enhance the model’s focus on characters associated with medical entities,hence boosting the model’s performance.We obtained 92.74%,and 87.80%F1 scores on the two CNER benchmark datasets,CCKS2017 and CCKS2019,respectively.The results demonstrate that our model outperforms the latest models in CNER,showcasing its outstanding overall performance.It can be seen that the CNER model proposed in this study has an important application value in constructing clinical medical knowledge graph and intelligent Q&A system.
文摘Curry leaves, scientifically termed Murraya koenigii, are renowned in South Asian cuisine for their flavor enhancement and potential health benefits, including antioxidative, anti-inflammatory, and antidiabetic properties. This study aimed to evaluate the impact of thermal processing methods on curry leaves by analysing Total Phenolic Content (TPC), Total Flavonoid Content (TFC), antioxidant activity, and metabolizing enzyme inhibition. Fresh curry leaves were subjected to thermal treatments: Oven-dried at 60˚C and Air-dried at 25˚C for 2 weeks. Extracts were prepared using Ethanol and water solvents. Results indicated that Air-dried leaves exhibited significantly higher TPC (5132.65 mg GAE/100 g) and TFC (243.13 mg CE/100 g) compared to Fresh and Oven-dried leaves. Antioxidant assays show that oven-dried curry leaves at 60˚C displayed higher results in NORS, FRAP, and TEAC assays compared to Fresh and Air-dried leaves. Ethanol extracts showed better extraction of bioactive compounds than aqueous extracts. Moreover, Lipase inhibition activity was notably high, indicating potential health benefits. This study provides valuable insights into the effects of processing methods on curry leaf extracts, emphasizing the importance of solvent selection for optimal extraction of bioactive compounds.
基金funded by the Science and Technology Project of China Southern Power Grid(YNKJXM20210175)the National Natural Science Foundation of China(52177070).
文摘Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.
基金supported by National Natural Science Foundation of China(42001305)Guangdong Basic and Applied Basic Research Foundation(2022A1515011459)+3 种基金GDAS’Special Project of Science and Technology Development(2020GDASYL-20200102001)Guangzhou Basic and Applied Basic Research Foundation(2023A04J1534)to Z.W.the US National Science Foundation(NSF)Macrosystems Biology and NEON-Enabled Science grant 1638720 to P.A.T.E.L.K.and NSF Biology Integration Institute award ASCEND,DBI-2021898 to P.A.T.
文摘Characterizing foliar trait variation in sun and shade leaves can provide insights into inter-and intra-species resource use strategies and plant response to environmental change.However,datasets with records of multiple foliar traits from the same individual and including shade leaves are sparse,which limits our ability to investigate trait-trait,trait-environment relationships and trait coordination in both sun and shade leaves.We presented a comprehensive dataset of 15 foliar traits from sun and shade leaves sampled with leaf spectroscopy,including 424 individuals of 110 plant species from 19 sites across eastern North America.We investigated trait variation,covariation,scaling relationships with leaf mass,and the effects of environment,canopy position,and taxonomy on trait expression.Generally,sun leaves had higher leaf mass per area,nonstructural carbohydrates and total phenolics,lower mass-based chlorophyll a+b,carotenoids,phosphorus,and potassium,but exhibited species-specific characteristics.Covariation between sun and shade leaf traits,and trait-environment relationships were overall consistent across species.The main dimensions of foliar trait variation in seed plants were revealed including leaf economics traits,photosynthetic pigments,defense,and structural traits.Taxonomy and canopy position collectively explained most of the foliar trait variation.This study highlights the importance of including intra-individual and intra-specific trait variation to improve our understanding of ecosystem functions.Our findings have implications for efficient field sampling,and trait mapping with remote sensing.
基金supported by the National Natural Science Foundation of China (32072193)the Natural Science Foundation of Guangxi,China (2020GXNSFBA297083)。
文摘To investigate the effects of drinking the soaking of Malus domeri(Bois)Chev.leaves on gut microbiota and metabolites of long-living elderly individuals in Hezhou city,Guangxi,China.It has been reported that longevity is closely related to metabolism and the gut microbiota.The 16S rRNA sequencing and liquid chromatography-mass spectrometry(LC-MS)were used to analysis fecal samples and explore the factors affecting longevity in the region.Interestingly,we discovered,that elderly individuals who had been drinking the soaking of M.domeri(Bois)Chev.leaves for a long time exhibited higher diversity of the gut microbiota than without drinking the soaking,notably.The proportions of Ruminococcaceae and Prevotella were decreased in those who did not drink this soaking.In addition,a total of 106 metabolites were characterized,and the people of long-lived people(>90 years old)and elderly people(<90 years old)who drinking soaking of M.domeri(Bois)Chev.leaves significantly altered the gut microbiota and upregulated levels of haplopine,farnesol,genipic acid,momordicinin,2-hydroxyestrone,hydroxyphenyllactic acid,caffeic acid,sophoraflavanone B,and soyasaponin I.We preliminarily determined that M.domeri(Bois)Chev.leaves consumption may be an important factor affecting longevity in this area.
文摘Aim: This study aimed to investigate the protective effects of flavonoids from the stem and leaves of Scutellaria baicalensis Georgi (SSFs) against Aβ<sub>1-42</sub>-induced oligodendrocytes (OL) damage. Methods: Immunofluorescence was used for the detection of myelin-associated glycoprotein (MAG), a characteristic protein of rat oligodendrocytes (OLN-93 cells). To evaluate the potential protective effects of SSFs on OLN-93 cells injured by Aβ<sub>1-42</sub>, an injury model was established by subjecting OLN-93 cells to Aβ<sub>1-42</sub> exposed. Cell morphology was examined using an inverted microscope, while cell viability was assessed using the colorimetric method of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). Additionally, lactate dehydrogenase (LDH) was measured using the pyruvic acid reduction assay. The Ginkgo biloba leaf extract (GBE) injection was used as a positive control. Results: A total of >95% of the MAG immunofluorescence-positive cells were identified as oligodendrocytes. Gradually increasing concentrations of SSFs impaired the cells, and the maximum nondetrimental dose for OLN-93 cells was 75 mg/L. This study assessed the effects of SSFs on OLN-93 cells damaged by Aβ<sub>1-42</sub>. The results indicated that SSFs significantly improved OLN-93 cell morphological abnormal changes, increased the OLN-93 cell survival rate, and reduced LDH release. Conclusion: SSFs can alleviate Aβ<sub>1-42</sub>-induced damage of OL.
基金the Doctoral Research Initiation Foundation of Changzhi Medical College(BS202005)。
文摘This study was to investigate the effects of three exogenous substances on chemical constituents of Isatis indigotica leavesand their efficacy in alleviating drought stress, and explore the methods of applying exogenous substances to efficient cultivationof Isatis indigotica. Polyethylene glycol (PEG) was used to simulate drought stress to deal with seeds of Isatis indigotica at thegermination stage (concentration: 0, 10%, 15%, and 20%). Simultaneous operation of exogenous growth regulators [microbialinoculum (MI), γ-aminobutyric acid (GABA) and salicylic acid (SA)] and PEG were implemented in seeds of Isatis indigotica.The effects of drought stress and the mitigation of exogenous substances were observed by statistics of seed germination potential,germination rate, hypocotyl length, and radicle length of each treatment. The effects of exogenous substances on the content ofalkaloids, crude protein and free amino acids in the leaves of Isatis indigotica grown in a greenhouse were determined after sprayingexogenous substances on the plants. The differences of germination potential, germination rate, hypocotyl length, and radicle lengthamong 15% PEG stress treatment, 10% PEG stress treatment and the control were significant (P<0.05). According to the predesignedgermination standard, the seeds did not germinate under 20% PEG stress treatment. When the PEG concentration was 15%, the resultsof seed germination potential and germination rate after adding MI were significantly different from those under stress alone (P<0.05).When exposed to 10% PEG stress, the supplementation of GABA led to a notable increase in radicle length of Isatis indigotica seeds,showing significant differences compared to other three treatments. The application of MI and GABA under 15% PEG stress resultedin a significant increase in the radicle and hypocotyl length of Isatis indigotica seeds compared to other two treatments. The contentof the total alkaloids in leaves of Isatis indigotica was significantly increased after spraying GABA. Meanwhile, the contents of crudeprotein and the total free amino acids were kept constant after spraying exogenous substances. Application of MI and GABA couldalleviate drought stress of Isatis indigotica. The content of the total alkaloids in leaves of Isatis indigotica could significantly increaseafter spraying GABA.
文摘The aim of the present study was to investigate on the inventory and determination of the nutritional value of cereals flour and cassava leaves powder in order to analyse their use in the production of infant flour. In this paper, a A survey to identify the cereals used in the preparation of infant porridge in the Northern Cameroon was done by using 447 mothers having children between 06 and 59 months from areas (Gbakoungue, Sassa-Mbersi, Sanguere-Ngal and Kotkong-Wouldata) with high rate on malnourished children. Flour was prepared from the most preponderant cereals and Cassava leaves powder from varieties identified by the Regional Centre of Agricultural Research (CRRA) of Wakwa and local population. Flour and powder samples obtained were subjected to chemical composition analysis. Parameters analysed were crude proteins, total carbohydrates, ash, total fats, total phenols, total tannins, total carotenoids, vitamin C or cyanide. Also Iron, calcium and zinc were determined. The results revealed that white maize (62%) was the main cereal used in the preparation of infant porridge followed respectively by red sorghum, white rice and muskwari. Ten cassava varieties were identified: three (03) by CRRA (TME, 96/1/14 and IRAD 4115) and seven (south, gambada, sweet, Benin, six months, M. glaziovii and grouna) by local population. Amongst cereals flour, those from white maize indicated high protein (10.09%), carbohydrates (84.46%) and total fat (7.46%) contents. The powder from 96/14/14 cassava variety showed high amount of iron (11.98 mg/100g), calcium (751.02 g/100g) and low cyanide content (1.21 ppm) amongst all the cassava leaves powder samples. The supplementation of white maize flour by cassava leaves powder from 96/14/14 variety could therefore be recommended for the preparation of infant flours.
文摘This paper analyzes the progress of handwritten Chinese character recognition technology,from two perspectives:traditional recognition methods and deep learning-based recognition methods.Firstly,the complexity of Chinese character recognition is pointed out,including its numerous categories,complex structure,and the problem of similar characters,especially the variability of handwritten Chinese characters.Subsequently,recognition methods based on feature optimization,model optimization,and fusion techniques are highlighted.The fusion studies between feature optimization and model improvement are further explored,and these studies further enhance the recognition effect through complementary advantages.Finally,the article summarizes the current challenges of Chinese character recognition technology,including accuracy improvement,model complexity,and real-time problems,and looks forward to future research directions.
基金a grant from the National Science Center,Poland(Grant No.2016/23/B/NZ9/03427)co-financed within the framework of the Polish Ministry of Science and Higher Education’s program:“Regional Initiative Excellence”in the years 2019–2022(No.005/RID/2018/19)“financing amount 12000000,00 PLN”。
文摘Background:The use of industrial by-products rich in bioactive compounds as animal feeds can reduce greenhouse gas production.Paulownia leaves silage(PLS)was supplemented to dairy cows'diet and evaluated in vitro(Exp.1;Rusitec)and in vivo(Exp.2,cannulated lactating dairy cows and Exp.3,non-cannulated lactating dairy cows).The study investigated the PLS effect on ruminal fermentation,microbial populations,methane production and concentration,dry matter intake(DMI),and fatty acid(FA)proportions in ruminal fluid and milk.Results:Several variables of the ruminal fluid were changed in response to the inclusion of PLS.In Exp.1,the p H increased linearly and quadratically,whereas ammonia and total volatile fatty acid(VFA)concentrations increased linearly and cubically.A linear,quadratic,and cubical decrease in methane concentration was observed with increasing dose of the PLS.Exp.2 revealed an increase in ruminal p H and ammonia concentrations,but no changes in total VFA concentration.Inclusion of PLS increased ruminal propionate(at 3 h and 6 h after feeding),isovalerate,and valerate concentrations.Addition of PLS also affected several populations of the analyzed microorganisms.The abundances of protozoa and bacteria were increased,whereas the abundance of archaea were decreased by PLS.Methane production decreased by 11%and 14%in PLS-fed cows compared to the control in Exp.2 and 3,respectively.Exp.3 revealed a reduction in the milk protein and lactose yield in the PLS-fed cows,but no effect on DMI and energy corrected milk yield.Also,the PLS diet affected the ruminal biohydrogenation process with an increased proportions of C18:3 cis-9 cis-12 cis-15,conjugated linoleic acid,C18:1 trans-11 FA,polyunsaturated fatty acids(PUFA),and reduced n6/n3 ratio and saturated fatty acids(SFA)proportion in milk.The relative transcript abundances of the 5 of 6 analyzed genes regulating FA metabolism increased.Conclusions:The dietary PLS replacing the alfalfa silage at 60 g/kg diet can reduce the methane emission and improve milk quality with greater proportions of PUFA,including conjugated linoleic acid,and C18:1 trans-11 along with reduction of SFA.
基金supported by the Deanship of Scientific Research at Umm Al-Qura University(Grant code:22UQU4331128DSR77).
文摘Objective:To investigate the relationship between triterpenoid saponin content and antioxidant,antimicrobial,and α-glucosidase inhibitory activities of 70%ethanolic,butanolic,aqueous,supernate and precipitate extracts of Juglans regia leaves.Methods:Triterpenoid saponins of different Juglans regia leaf extracts were measured by the vanillin method.Antioxidant activity was evaluated against DPPH and ABTS free radicals.We also assessed α-glucosidase inhibitory and antimicrobial activities of the leaf extracts.Pearson’s correlation coefficient was evaluated to determine the correlation between the saponin content and biological activities.Results:The butanolic extract was most effective against DPPH with an IC50of 6.63μg/mL,while the aqueous extract showed the highest scavenging activity against ABTS free radical with an IC50of 42.27μg/mL.Pearson’s correlation analysis indicated a strong negative correlation (r=-0.956) between DPPH radical scavenging activity (IC50) and the saponin content in the samples examined.In addition,the aqueous extract showed the best α-glucosidase inhibitory activity compared with other extracts.All the extracts had fair antibacterial activity against Bacillus subtilis,Escherichia coli,and Klebsiella pneumoniae except for the aqueous extract.Conclusions:Juglans regia extracts show potent antioxidant,antimicrobial,and α-glucosidase inhibitory activities.There is a correlation between saponin levels in Juglans regia leaf extracts and the studied activities.However,additional research is required to establish these relationships by identifying the specific saponin molecules responsible for these activities and elucidating their mechanisms of action.
文摘Spices and aromatic plants are products of plant origin used in food. They are used for the preparation of remedies, for seasoning dishes or for preserving food. This review takes stock of the diversity of spices and aromatic herbs, the chemical composition, the different properties and forms of use of six spices and aromatic herbs commonly used in Benin and around the world. These are Zingiber officinalis (ginger), Curcuma longa (curcuma), Syzygium aromaticum (clove) and three aromatic herbs Petroselinum crispum (parsley), Rosmarinus officinalis (rosemary), and Laurus nobilis (laurel). The methodology used is that of documentary research oriented towards the consultation of previous scientific documents that have highlighted the different pharmacological activities of the different species of spices and aromatic plants targeted. It is important to note that more than twenty plant species are used as spices and aromatic plants in Benin and around the world. Chemically, these different spices and aromatic herbs contain certain secondary metabolites such as flavonoids, tannins, coumarins, alkaloids, steroids, terpenes, saponins, and polyphenols. This diversity of secondary metabolites alone or in a possible synergy may be responsible for many beneficial properties attributed to spices and aromatic herbs.
文摘In order to solve the shortcomings of current fatigue detection methods such as low accuracy or poor real-time performance,a fatigue detection method based on multi-feature fusion is proposed.Firstly,the HOG face detection algorithm and KCF target tracking algorithm are integrated and deformable convolutional neural network is introduced to identify the state of extracted eyes and mouth,fast track the detected faces and extract continuous and stable target faces for more efficient extraction.Then the head pose algorithm is introduced to detect the driver’s head in real time and obtain the driver’s head state information.Finally,a multi-feature fusion fatigue detection method is proposed based on the state of the eyes,mouth and head.According to the experimental results,the proposed method can detect the driver’s fatigue state in real time with high accuracy and good robustness compared with the current fatigue detection algorithms.
文摘Sentiment analysis in Chinese classical poetry has become a prominent topic in historical and cultural tracing,ancient literature research,etc.However,the existing research on sentiment analysis is relatively small.It does not effectively solve the problems such as the weak feature extraction ability of poetry text,which leads to the low performance of the model on sentiment analysis for Chinese classical poetry.In this research,we offer the SA-Model,a poetic sentiment analysis model.SA-Model firstly extracts text vector information and fuses it through Bidirectional encoder representation from transformers-Whole word masking-extension(BERT-wwmext)and Enhanced representation through knowledge integration(ERNIE)to enrich text vector information;Secondly,it incorporates numerous encoders to remove text features at multiple levels,thereby increasing text feature information,improving text semantics accuracy,and enhancing the model’s learning and generalization capabilities;finally,multi-feature fusion poetry sentiment analysis model is constructed.The feasibility and accuracy of the model are validated through the ancient poetry sentiment corpus.Compared with other baseline models,the experimental findings indicate that SA-Model may increase the accuracy of text semantics and hence improve the capability of poetry sentiment analysis.
基金This work was supported by the Key Research and Development Program of Zhejiang Province(2021C02009,2021C02064-7,and 2022C02016)the National Natural Science Foundation of China(31770263 and 31970279)the National Key Research and Development Program of China(2018YFD1000800).
文摘Fungal infection is a major cause of crop and fruit losses.Recognition of chitin,a component of fungal cell walls,endows plants with enhanced fungal resistance.Here,we found that mutation of tomato LysM receptor kinase 4(SlLYK4)and chitin elicitor receptor kinase 1(SlCERK1)impaired chitin-induced immune responses in tomato leaves.Compared with the wild type,sllyk4 and slcerk1 mutant leaves were more susceptible to Botrytis cinerea(gray mold).SlLYK4 extracellular domain showed strong binding affinity to chitin,and the binding of SlLYK4 induced SlLYK4-SlCERK1 association.Remarkably,qRT–PCR analysis indicated that SlLYK4 was highly expressed in tomato fruit,andβ-GLUCURONIDASE(GUS)expression driven by the SlLYK4 promoter was observed in tomato fruit.Furthermore,SlLYK4 overexpression enhanced disease resistance not only in leaves but also in fruit.Our study suggests that chitin-mediated immunity plays a role in fruit,providing a possible way to reduce fungal infection-related fruit losses by enhancing the chitin-induced immune responses.
基金This research was supported by the National Key R&D Program of China during the 14th Five-year Plan Period(2021YFD2200105).
文摘Poplar is an important afforestation and urban greening species.Poplar leaf development occurs in stages,from young to mature and then from mature to senescent;these are accompanied by various phenotypic and physiological changes.However,the associated transcriptional regulatory network is relatively unexplored.We first used principal component analysis to classify poplar leaves at different leaf positions into two stages:developmental maturity(the stage of maximum photosynthetic capacity);and the stage when photosynthetic capacity started to decline and gradually changed to senescence.The two stages were then further subdivided into five intervals by gene expression clustering analysis:young leaves,the period of cell genesis and functional differentiation(L1);young leaves,the period of development and initial formation of photosynthetic capacity(L3-L7);the period of maximum photosynthetic capacity of functional leaves(L9-L13);the period of decreasing photosynthetic capacity of functional leaves(L15-L27);and the period of senescent leaves(L29).Using a weighted co-expression gene network analysis of regulatory genes,high-resolution spatiotemporal transcriptional regulatory networks were constructed to reveal the core regulators that regulate leaf development.Spatiotemporal transcriptome data of poplar leaves revealed dynamic changes in genes and miRNAs during leaf development and identified several core regulators of leaf development,such as GRF5 and MYB5.This in-depth analysis of transcriptional regulation during leaf development provides a theoretical basis for exploring the biological basis of the transcriptional regulation of leaf development and the molecular design of breeding for delaying leaf senescence.
基金supported by the National Natural Science Foundation of China(Grant Nos.31672149,31772317,and 32072595)China Postdoctoral Science Foundation(Grant No.2021M691174)。
文摘Leaf-color mutations have been studied extensively in plants.However,to better understand the complex mechanisms underlying the formation of leaf color,it is essential to continue discover novel genes involved in the process of leaf color development.In this study,we identified a variegated-leaf(vg)mutant in tomato that exhibited defective phenotypes in thylakoids and photosynthesis.To clone the vg locus,an F2population was constructed from the cross between the vg mutant(Solanum lycopersicum)and the wild tomato LA1589(S.pimpinellifolium).Using the map-based cloning approach,the vg locus was mapped on chromosome 7 and narrowed down to a 128 kb region that contained 21 open reading frames(ORFs).The expression levels of ORF9,ORF10,and ORF13 were significantly lower in vg than in the wild-type plants,while the ORF11 transcript level was elevated in vg.We then mutagenized ORF9,ORF10,and ORF13 by the CRISPR/Cas9 system in the wild-type tomato background and found that only the ORF10 mutation reproduced the phenotype of variegated leaves,indicating that ORF10 represents VG and its down-regulated expression was responsible for the variegated leaf phenotype.ORF10 encodes a thylakoid formation protein and its mutant lines showed reduced levels of chlorophyll synthesis and photosynthesis.Taken together,these results suggest that VG is necessary for chloroplast development,chlorophyll synthesis,and photosynthesis in tomato.
基金This work was partly supported by the Basic Ability Improvement Project for Young andMiddle-aged Teachers in Guangxi Colleges andUniversities(2021KY1800,2021KY1804).
文摘The traditional recommendation algorithm represented by the collaborative filtering algorithm is the most classical and widely recommended algorithm in the practical industry.Most book recommendation systems also use this algorithm.However,the traditional recommendation algorithm represented by the collaborative filtering algorithm cannot deal with the data sparsity well.This algorithm only uses the shallow feature design of the interaction between readers and books,so it fails to achieve the high-level abstract learning of the relevant attribute features of readers and books,leading to a decline in recommendation performance.Given the above problems,this study uses deep learning technology to model readers’book borrowing probability.It builds a recommendation system model through themulti-layer neural network and inputs the features extracted from readers and books into the network,and then profoundly integrates the features of readers and books through the multi-layer neural network.The hidden deep interaction between readers and books is explored accordingly.Thus,the quality of book recommendation performance will be significantly improved.In the experiment,the evaluation indexes ofHR@10,MRR,andNDCGof the deep neural network recommendation model constructed in this paper are higher than those of the traditional recommendation algorithm,which verifies the effectiveness of the model in the book recommendation.
基金This work was supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia(Project no.GRANT 324).
文摘Coronavirus 2019(COVID-19)is the current global buzzword,putting the world at risk.The pandemic’s exponential expansion of infected COVID-19 patients has challenged the medical field’s resources,which are already few.Even established nations would not be in a perfect position to manage this epidemic correctly,leaving emerging countries and countries that have not yet begun to grow to address the problem.These problems can be solved by using machine learning models in a realistic way,such as by using computer-aided images during medical examinations.These models help predict the effects of the disease outbreak and help detect the effects in the coming days.In this paper,Multi-Features Decease Analysis(MFDA)is used with different ensemble classifiers to diagnose the disease’s impact with the help of Computed Tomography(CT)scan images.There are various features associated with chest CT images,which help know the possibility of an individual being affected and how COVID-19 will affect the persons suffering from pneumonia.The current study attempts to increase the precision of the diagnosis model by evaluating various feature sets and choosing the best combination for better results.The model’s performance is assessed using Receiver Operating Characteristic(ROC)curve,the Root Mean Square Error(RMSE),and the Confusion Matrix.It is observed from the resultant outcome that the performance of the proposed model has exhibited better efficient.
文摘Diospyros mespiliformis Hochst. ex A. DC. (Ebenaceae) is a multi-use plant, including for therapeutic purposes. It is used in alternative medicine in Burkina Faso to treat conjunctivitis, menorrhagia, dysentery, and diarrhea. The aim of our study was to evaluate the chemical profile, antioxidant and anti-inflammatory activities, safety of use and spasmolytic effects of the aqueous decoction of Diospyros mespiliformis leaves. Phytochemical screening by HPTLC and assay of compounds of interest were carried out. Four methods were used to assess antioxidant activity. Inhibitory activity against 15-lipoxygenase and phospholipase A2 was assessed. Acute oral toxicity of the extract was tested on female mice (NMRI). Following these tests, the extract contained bioactive compounds of interest such as flavonoids, tannins, sterols, triterpenes, and saponosides. The total phenolic and flavonoid contents of the aqueous decoctate were 70.59 ± 3.20 mg EAT/g and 31.57 ± 0.78 mg EQ/g respectively. The extract was less active than Trolox with inhibitory concentrations of 50% (IC<sub>50</sub>) for the ABTS, DPPH, FRAP, and LPO tests of 7.53 ± 0.08 μg/mL, 29.47 ± 0.06 μg/mL, 1128.83 ± 4.82 mol EAA/g, and 32.30 ± 1.60 μg/mL respectively. The extract has an anti-inflammatory effect with inhibition of phospholipase A2 compared to betamethasone. In addition, the aqueous extract produced an antispasmodic effect with Emax of 70% and 80% respectively during contractions induced by BaCl<sub>2</sub> and ACh. Finally, this study provided basic scientific data and could justify the use of D. mespiliformis leaves in the treatment of diarrhea.