BnaWRKY75 positively regulates the resistance against Sclerotinia sclerotiorum in ornamental Brassica napus

With the development of tourism at home and abroad,Rapeseed(Brassica napus)has become an important ornamental plant.However,its ornamental value at the inflorescence stage is greatly reduced by Sclerotinia sclerotiorum.Identification of important genes in the defense responses is critical for molecular breeding,which is an important strategy for controlling the disease.In this study,we isolated a B.napus WRKY transcription factor gene,BnaWRKY75.BnaWRKY75 was found to encode a nucleus-localized protein and exhibited relatively high expression in the stems.Arabidopsis thaliana transgenic plants expressing BnaWRKY75 showed enhanced resistance to S.sclerotiorum,and both ProBnaWRKY75:GUS and gene expression analyses showed that BnaWRKY75 was highly responsive to S.sclerotiorum infection,indicating the involvement of BnaWRKY75 in response to this infection.Furthermore,overexpression(OE)of BnaWRKY75 in B.napus significantly enhanced the resistance to S.sclerotiorum,whereas the resistance was reduced in RNAi transgenic B.napus plants.Moreover,the BnaWRKY75-OE B.napus plants exhibited constitutive activation of salicylic acid-,jasmonic acid-,and ethylene-mediated defense responses and the inhibition of both H_(2)O_(2)and O_(2)·^(-)accumulation in response to this pathogen.By contrast,BnaWRKY75-RNAi plants showed a reverse pattern,suggesting that BnaWRKY75 is involved in hormonal signaling pathways and in the control of reactive oxygen species accumulation.In conclusion,these data indicate that BnaWRKY75,a regulator of multiple defense responses,positively regulates resistance against S.sclerotiorum,which may guide the improvement of resistance in rapeseed.

基于Android平台的高校食堂点餐系统的设计与实现

随着生活水平的提高,高校在校学生对于食堂饭菜要求也提高了,他们对大学食堂的现状并不是很满意,问题集中在两个方面:一是菜的品种单一,吃多了不可口同时也缺乏营养;二是下课放学高峰期食堂过于拥堵,难以买到饭菜,影响就餐心情。针对以上两个问题,本文设计并开发了一款基于Android的高校食堂点餐系统。该系统在大学食堂的应用,将有利地缓解食堂高峰期排队买饭的压力,送餐上门的服务,将切实为学生提供便利,解决学校食堂由于高峰拥堵导致的学生用户外流的问题。

Hepatoid Carcinoma of the Pancreas:a Case Report

Case Report A 37-year old female patient suffering from an upper abdominal pain,accompanied by recent emaciation and anorexia that resulted from a two-month epigastric lump,visited a doctor in our hospital in January,2007.Physical examination of the patient by palpation identified a 10.0×8.0 cm2 lump from the xiphoid process above the middle and superior abdomen.The lesion was hard with a rough surface,the upper boundary unsharp,and the inferior and right boundary clearly apparent.The pain at the site of the lump was only apparent with touching at that site.

Engineering Sodium Metal Anode with Sodiophilic Bismuthide Penetration for Dendrite-Free and High-Rate Sodium-Ion Battery

Sodium(Na)metal batteries with a high volumetric energy density that can be operated at high rates are highly desirable.However,an uneven Na-ion migration in bulk Na anodes leads to localized deposition/dissolution of sodium during high-rate plating/stripping behaviors,followed by severe dendrite growth and loose stacking.Herein,we engineer the Na hybrid anode with sodiophilic Na_(3)Bi-penetration to develop the abundant phase-boundary ionic transport channels.Compared to intrinsic Na,the reduced adsorption energy and ion-diffusion barrier on Na_(3)Bi ensure even Na^(+)nucleation and rapid Na^(+)migration within the hybrid electrode,leading to uniform deposition and dissolution at high current densities.Furthermore,the bismuthide enables compact Na deposition within the sodiophilic framework during cycling,thus favoring a high volumetric capacity.Consequently,the obtained anode was endowed with a high current density(up to 5 mA∙cm^(−2)),high areal capacity(up to 5 mA∙h∙cm^(−2)),and long-term cycling stability(up to 2800 h at 2 mA∙cm^(−2)).

Volatile oil from Litsea lancilimba Merr.: a review of its chemical structure and biological activity

Litsea lancilimba Merr.is a Cinnamomum plant of Lauraceae.Phytochemical investigations of the Litsea lancilimba Merr.have resulted in the isolation of Volatile oil,flavonoid glycosides,tannins,alkaloids,lignans,organic acids and so on.Studies have showed that volatile oil is the main chemical component.Recent trials have demonstrated the efficacy of Litsea lancilimba Merr.in strengthening the function of stomach.The fruits have also been demonstrated to possess anti-inflammatory and bacteriostatic activities.This review deals mainly with the chemical structure and biological activities of Litsea lancilimba Merr.oil.

Phenolic compounds from Elephantopus scaber L.

Eight compounds,(+)-syringaresinol(1),apigenin(2),3,5-dimethoxy-4-hydxyphenylpropanol(3),3,4,5-trimethoxy benzoic acid,(4)ferulaic acid(5),trans-p-hydroxycinnamic methyl ester(6),4-hydroxy-3-methoxybenz-oic acid(7)and p-methoxy benzoic acid(8)were isolated from the 70%ethanol extract of the whole herb of Elephantopus scaber L.The structures of all compounds were identified by spectral data analysis.All compounds were obtained for the first time from Elephantopus scaber L..

Network pharmacology-based virtual screening of the active volatile oil ingredients of Litsea lancilimba Merr. and their potential targets for treating liver cancer

Liver cancer remains the dominant cause of cancer-related death, despite the advent of targeted therapies and immunotherapies. Therefore, there is an urgent need to explore novel chemotherapeutic agents and effective strategies against the cancer. There are a lot of monoterpenes and sesquiterpenoids in L. lancilimba. It has been reported that monoterpenes and sesquiterpenoids have certain anti-tumor effects. Literature investigation has also shown that Litsea lancilimba Merr. has antibacterial and antiviral effects. In this experiment, we used network pharmacology to screen the active compounds from L. lancilimba and their potential targets for treating liver cancer. Four active volatile oil ingredients and four potential targets have been identified. Our results provide the lead compound from L. lancilimba in the treatment of liver cancer.

Label-Free Virtual HER2 Immunohistochemical Staining of Breast Tissue using Deep Learning

The immunohistochemical(IHC)staining of the human epidermal growth factor receptor 2(HER2)biomarker is widely practiced in breast tissue analysis,preclinical studies,and diagnostic decisions,guiding cancer treatment and investigation of pathogenesis.HER2 staining demands laborious tissue treatment and chemical processing performed by a histotechnologist,which typically takes one day to prepare in a laboratory,increasing analysis time and associated costs.Here,we describe a deep learning-based virtual HER2 IHC staining method using a conditional generative adversarial network that is trained to rapidly transform autofluorescence microscopic images of unlabeled/label-free breast tissue sections into bright-field equivalent microscopic images,matching the standard HER2 IHC staining that is chemically performed on the same tissue sections.The efficacy of this virtual HER2 staining framework was demonstrated by quantitative analysis,in which three board-certified breast pathologists blindly graded the HER2 scores of virtually stained and immunohistochemically stained HER2 whole slide images(WSIs)to reveal that the HER2 scores determined by inspecting virtual IHC images are as accurate as their immunohistochemically stained counterparts.A second quantitative blinded study performed by the same diagnosticians further revealed that the virtually stained HER2 images exhibit a comparable staining quality in the level of nuclear detail,membrane clearness,and absence of staining artifacts with respect to their immunohistochemically stained counterparts.This virtual HER2 staining framework bypasses the costly,laborious,and time-consuming IHC staining procedures in laboratory and can be extended to other types of biomarkers to accelerate the IHC tissue staining used in life sciences and biomedical workflow.

Sex-biased single-cell genetic landscape in mice with autism spectrum disorder

Autistic spectrum disorder(ASD)is a male-biased,heterogeneous neurodevelopmental disorder that affects approximately 1%e2%of the population.Prenatal exposure to valproic acid(VPA)is a recognized risk factor for ASD,but the cellular and molecular basis of VPA-induced ASD at the single-cell resolution is unclear.Here,we aim to compare the cellular and molecular differences in the hippocampus between male and female prenatal mice with ASD at the single-cell transcriptomic level.The transcriptomes of more than 45,000 cells are assigned to 12 major cell types,including neurons,glial cells,vascular cells,and immune cells.Cell type-specific genes with altered expression after prenatal VPA exposure are analyzed,and the largest number of differentially expressed genes(DEGs)are found in neurons,choroid plexus epithelial cells,and microglia.In microglia,several pathways related to inflammation are found in both males and females,including the tumor necrosis factor(TNF),nuclear factor kappa B(NF-kB),toll-like receptor(TLR),and mitogen-activated protein kinase(MAPK)signaling pathways,which are important for the induction of autistic-like behavior.Additionally,we note that several X-linked genes,including Bex1,Bex3,and Gria3,were among the male-specific DEGs of neurons.This pioneering study describes the landscape of the transcriptome in the hippocampus of autistic mice.The elucidation of sexual differences could provide innovative strategies for the prevention and treatment of ASD.

Continued evolution of the Eurasian avian-like H1N1 swine influenza viruses in China

Animal influenza viruses continue to pose a threat to human public health. The Eurasian avian-like H1N1(EA H1N1) viruses are widespread in pigs throughout Europe and China and have caused human infections in several countries, indicating their pandemic potential. To carefully monitor the evolution of the EA H1N1 viruses in nature, we collected nasal swabs from 103,110pigs in 22 provinces in China between October 2013 and December 2019, and isolated 855 EA H1N1 viruses. Genomic analysis of 319 representative viruses revealed that these EA H1N1 viruses formed eight different genotypes through reassortment with viruses of other lineages circulating in humans and pigs, and two of these genotypes(G4 and G5) were widely distributed in pigs.Animal studies indicated that some strains have become highly pathogenic in mice and highly transmissible in ferrets via respiratory droplets. Moreover, two-thirds of the EA H1N1 viruses reacted poorly with ferret serum antibodies induced by the currently used H1N1 human influenza vaccine, suggesting that existing immunity may not prevent the transmission of the EA H1N1 viruses in humans. Our study reveals the evolution and pandemic potential of EA H1N1 viruses and provides important insights for future pandemic preparedness.

Deep learning-enabled virtual histological staining of biological samples

Histological staining is the gold standard for tissue examination in clinical pathology and life-science research,which visualizes the tissue and cellular structures using chromatic dyes or fluorescence labels to aid the microscopic assessment of tissue.However,the current histological staining workflow requires tedious sample preparation steps,specialized laboratory infrastructure,and trained histotechnologists,making it expensive,time-consuming,and not accessible in resource-limited settings.Deep learning techniques created new opportunities to revolutionize staining methods by digitally generating histological stains using trained neural networks,providing rapid,cost-effective,and accurate alternatives to standard chemical staining methods.These techniques,broadly referred to as virtual staining,were extensively explored by multiple research groups and demonstrated to be successful in generating various types of histological stains from label-free microscopic images of unstained samples;similar approaches were also used for transforming images of an already stained tissue sample into another type of stain,performing virtual stain-to-stain transformations.In this Review,we provide a comprehensive overview of the recent research advances in deep learning-enabled virtual histological staining techniques.The basic concepts and the typical workflow of virtual staining are introduced,followed by a discussion of representative works and their technical innovations.We also share our perspectives on the future of this emerging field,aiming to inspire readers from diverse scientifc fields to further expand the scope of deep learning-enabled virtual histological staining techniques and their applications.

Influence of Recent Trial History on Interval Timing

Interval timing is involved in a variety of cognitive behaviors such as associative learning and decision-making.While it has been shown that time estimation is adaptive to the temporal context,it remains unclear how interval timing behavior is influenced by recent trial history.Here we found that,in mice trained to perform a licking-based interval timing task,a decrease of inter-reinforcement interval in the previous trial rapidly shifted the time of anticipatory licking earlier.Optogenetic inactivation of the anterior lateral motor cortex(ALM),but not the medial prefrontal cortex,for a short time before reward delivery caused a decrease in the peak time of anticipatory licking in the next trial.Electrophysiological recordings from the ALM showed that the response profiles preceded by short and long inter-reinforcement intervals exhibited task-engagement-dependent temporal scaling.Thus,interval timing is adaptive to recent experience of the temporal interval,and ALM activity during time estimation reflects recent experience of interval.

Design and experiment of the soil-covering and soil-compacting device for seedling raising and sowing of trough type panax notoginseng

In order to improve the seedling quality of Panax notoginseng,combined with the special agronomic requirements of Panax notoginseng,a sharp angle roller soil-covering and soil-compacting device integrating the functions of soil-covering and soil-compacting was designed.Based on the theoretical analysis of seed ditch conditions,soil-covering process and soilcompacting process,the structure of soil-covering and soil-compacting device was designed.Through theoretical analysis and calculation,the diameter and length of soil-covering and soil-compacting wheel were 20 cm and 10.7-14.1 cm,respectively,the sharp angle and height range were 45°-105°and 0.8-1.6 cm respectively,and the spring stiffness was 38.54 N/mm;Using the discrete element method to simulate the soil-covering and soil-compacting process,it was obtained that when the sharp angle range was 60°-90°,the sharp angle height range was 0.8-1.2 cm,and the soil-covering effect was better;Taking the forward speed,ballast pressure,sharp angle and sharp angle height of the planter as the test factors,and taking the soil-covering thickness,grain spacing and soil compactness as the indexes,the four factor and three-level Box-Behnken Design test was carried out.The response surface test analysis method was used to establish the regression equation between the factors and indexes,and determine the best parameter combination:the forward speed was 6.5 m/min,the ballast pressure was 360.5 N,the sharp angle was 67°,and the sharp angle height was 1 cm,at this time,the soil-covering thickness was 0.64 cm,the grain spacing was 5.03 cm,and the soil compactness was 321.77 kPa.According to the soil trough test,the design of soil-covering and soil-compacting device met the agronomic requirements of plant spacing,soil-compactness and soil-covering thickness during seedling sowing of Panax notoginseng.The research results can provide a reference for the design of Panax notoginseng seedling planter integrating pressing hole(ditching),sowing,soil-covering and soil-compacting.

Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue

Histological staining is a vital step in diagnosing various diseases and has been used for more than a century to provide contrast in tissue sections,rendering the tissue constituents visible for microscopic analysis by medical experts.However,this process is time consuming,labour intensive,expensive and destructive to the specimen.Recently,the ability to virtually stain unlabelled tissue sections,entirely avoiding the histochemical staining step,has been demonstrated using tissue-stain-specific deep neural networks.Here,we present a new deep-learning-based framework that generates virtually stained images using label-free tissue images,in which different stains are merged following a micro-structure map defined by the user.This approach uses a single deep neural network that receives two different sources of information as its input:(1)autofluorescence images of the label-free tissue sample and(2)a“digital staining matrix”,which represents the desired microscopic map of the different stains to be virtually generated in the same tissue section.This digital staining matrix is also used to virtually blend existing stains,digitally synthesizing new histological stains.We trained and blindly tested this virtual-staining network using unlabelled kidney tissue sections to generate micro-structured combinations of haematoxylin and eosin(H&E),Jones’silver stain,and Masson’s trichrome stain.Using a single network,this approach multiplexes the virtual staining of label-free tissue images with multiple types of stains and paves the way for synthesizing new digital histological stains that can be created in the same tissue cross section,which is currently not feasible with standard histochemical staining methods.

Using bioprinting and spheroid culture to create a skin model with sweat glands and hair follicles

Background:Sweat glands(SGs)and hair follicles(HFs)are two important cutaneous appendages that play crucial roles in homeostatic maintenance and thermoregulation,and their interaction is involved in wound healing.SGs can be regenerated from mesenchymal stem cell-laden 3D bioprinted scaffolds,based on our previous studies,whereas regeneration of HFs could not be achieved in the same model.Due to the lack of an in vitro model,the underlying molecular mechanism of the interaction between SGs and HFs in regeneration could not be fully understood.The purpose of the present study was to establish an in vitro model of skin constructs with SGs and HFs and explore the interaction between these two appendages in regeneration.Methods:To investigate the interaction effects between SGs and HFs during their regeneration processes,a combined model was created by seeding HF spheroids on 3D printed SG scaffolds.The interaction between SG scaffolds and HF spheroids was detected using RNA expression and immunofluorescence staining.The effects of microenvironmental cues on SG and HF regeneration were analysed by altering seed cell types and plantar dermis homogenate in the scaffold.Results:According to this model,we overcame the difficulties in simultaneously inducing SG and HF regeneration and explored the interaction effects between SG scaffolds and HF spheroids.Surprisingly,HF spheroids promoted both SG and HF differentiation in SG scaffolds,while SG scaffolds promoted SG differentiation but had little effect on HF potency in HF spheroids.Specifically,microenvironmental factors(plantar dermis homogenate)in SG scaffolds effectively promoted SG and HF genesis in HF spheroids,no matter what the seed cell type in SG scaffolds was,and the promotion effects were persistent.Conclusions:Our approach elucidated a new model for SG and HF formation in vitro and provided an applicable platform to investigate the interaction between SGs and HFs in vitro.This platform might facilitate 3D skin constructs with multiple appendages and unveil the spatiotemporal molecular program of multiple appendage regeneration.

Stiffness-mediated mesenchymal stem cell fate decision in 3D-bioprinted hydrogels

Background:Hydrogels with tuneable mechanical properties are an attractive material platform for 3D bioprinting.Thus far,numerous studies have confirmed that the biophysical cues of hydrogels,such as stiffness,are known to have a profound impact on mesenchymal stem cell(MSC)differentiation;however,their differentiation potential within 3D-bioprinted hydrogels is not completely understood.Here,we propose a protocol for the exploration of how the stiffness of alginate–gelatin(Alg-Gel)composite hydrogels(the widely used bioink)affects the differentiation of MSCs in the presence or absence of differentiation inducing factors.Methods:Two types of Alg-Gel composite hydrogels(Young’s modulus:50 kPa vs.225 kPa)were bioprinted independently of porosity.Then,stiffness-induced biases towards adipogenic and osteogenic differentiation of the embedded MSCs were analysed by co-staining with alkaline phosphatase(ALP)and oil red O.The expression of specific markers at the gene level was detected after a 3-day culture.Results:Confocal microscopy indicated that all tested hydrogels supported MSC growth and viability during the culture period.Higher expression of adipogenic and osteogenic markers(ALP and lipoprotein lipase(LPL))in stiffer 3D-bioprinted matrices demonstrated a more significant response of MSCs to stiffer hydrogels with respect to differentiation,which was more robust in differentiation-inducing medium.However,the LPL expression in stiffer 3D-bioprinted constructs was reduced at day 3 regardless of the presence of differentiation-inducing factors.Although MSCs embedded in softer hydrogels to some extent proceeded toward adipogenic and osteogenic lineages within a few days,their differentiation seemed to be slower and more limited.Interestingly,the hydrogel itself(without differentiation-inducing factors)exhibited a slight effect on whether MSCs differentiated towards an adipogenic or an osteogenic fate.Considering that the mechanoregulated protein Yes-associated protein(YAP)is involved in MSC fate decisions,we further found that inhibition of YAP significantly downregulated the expression of ALP and LPL in MSCs in stiffer constructs regardless of the induced growth factors present.Conclusions:These results demonstrate that the differentiation of MSCs in 3D-bioprinted matrices is dependent on hydrogel stiffness,which emphasizes the importance of biophysical cues as a determinant of cellular behaviour.

3D-bioprinted microenvironments for sweat gland regeneration

The development of 3D bioprinting in recent years has provided new insights into the creation of in vitro microenvironments for promoting stem cell-based regeneration.Sweat glands(SGs)are mainly responsible for thermoregulation and are a highly differentiated organ with limited regenerative ability.Recent studies have focused on stem cell-based therapies as strategies for repairing SGs after deep dermal injury.In this review,we highlight the recent trend in 3D bioprinted native-like microenvironments and emphasize recent advances in functional SG regeneration using this technology.Furthermore,we discuss five possible regulatory mechanisms in terms of biochemical factors and structural and mechanical cues from 3D bioprinted microenvironments,as well as the most promising regulation from neighbor cells and the vascular microenvironment.

Biopsy-free in vivo virtual histology of skin using deep learning

An invasive biopsy followed by histological staining is the benchmark for pathological diagnosis of skin tumors.The process is cumbersome and time-consuming,often leading to unnecessary biopsies and scars.Emerging noninvasive optical technologies such as reflectance confocal microscopy(RCM)can provide label-free,cellular-level resolution,in vivo images of skin without performing a biopsy.Although RCM is a useful diagnostic tool,it requires specialized training because the acquired images are grayscale,lack nuclear features,and are difficult to correlate with tissue pathology.Here,we present a deep learning-based framework that uses a convolutional neural network to rapidly transform in vivo RCM images of unstained skin into virtually-stained hematoxylin and eosin-like images with microscopic resolution,enabling visualization of the epidermis,dermal-epidermal junction,and superficial dermis layers.The network was trained under an adversarial learning scheme,which takes ex vivo RCM images of excised unstained/label-free tissue as inputs and uses the microscopic images of the same tissue labeled with acetic acid nuclear contrast staining as the ground truth.We show that this trained neural network can be used to rapidly perform virtual histology of in vivo,label-free RCM images of normal skin structure,basal cell carcinoma,and melanocytic nevi with pigmented melanocytes,demonstrating similar histological features to traditional histology from the same excised tissue.This application of deep learning-based virtual staining to noninvasive imaging technologies may permit more rapid diagnoses of malignant skin neoplasms and reduce invasive skin biopsies.

Natural nanomaterial as hard template for scalable synthesizing holey carbon naonsheet/nanotube with in-plane and out-of-plane pores for electrochemical energy storage

Tuning porous structure of carbon nanomaterials has been found to be important for their performance enhancement in electrochemical energy storage applications. In this work we employed a natural nanomaterial kaolinite, which is abundant and cheap, as hard template to synthesis porous carbon nanomaterial. By tuning the structure of hard template kaolinite, we have achieved a template directed formation of holey carbon nanosheet/nanotube materials. This carbon nanomaterials with hierarchical in-plane and out-of-plane pores have shown electrochemical energy storage capacity of 286 F/g（equal to 314 F/cm^3） at 0.1 A/g and 85 F/g（equal to 93 F/cm^3） at 100 A/g, which is comparable to variety of reported carbon based electrochemical energy storage electrode materials.

Seismic wave equations in tight oil/gas sandstone media

Tight oil/gas medium is a special porous medium,which plays a significant role in oil and gas exploration.This paper is devoted to the derivation of wave equations in such a media,which take a much simpler form compared to the general equations in the poroelasticity theory and can be employed for parameter inversion from seismic data.We start with the fluid and solid motion equations at a pore scale,and deduce the complete Biot’s equations by applying the volume averaging technique.The underlying assumptions are carefully clarified.Moreover,time dependence of the permeability in tight oil/gas media is discussed based on available results from rock physical experiments.Leveraging the Kozeny-Carman equation,time dependence of the porosity is theoretically investigated.We derive the wave equations in tight oil/gas media based on the complete Biot’s equations under some reasonable assumptions on the media.The derived wave equations have the similar form as the diffusiveviscous wave equations.A comparison of the two sets of wave equations reveals explicit relations between the coefficients in diffusive-viscous wave equations and the measurable parameters for the tight oil/gas media.The derived equations are validated by numerical results.Based on the derived equations,reflection and transmission properties for a single tight interlayer are investigated.The numerical results demonstrate that the reflection and transmission of the seismic waves are affected by the thickness and attenuation of the interlayer,which is of great significance for the exploration of oil and gas.