Optimizing Spatial Relationships in GCN to Improve the Classification Accuracy of Remote Sensing Images

Semantic segmentation of remote sensing images is one of the core tasks of remote sensing image interpretation.With the continuous develop-ment of artificial intelligence technology,the use of deep learning methods for interpreting remote-sensing images has matured.Existing neural networks disregard the spatial relationship between two targets in remote sensing images.Semantic segmentation models that combine convolutional neural networks(CNNs)and graph convolutional neural networks(GCNs)cause a lack of feature boundaries,which leads to the unsatisfactory segmentation of various target feature boundaries.In this paper,we propose a new semantic segmentation model for remote sensing images(called DGCN hereinafter),which combines deep semantic segmentation networks(DSSN)and GCNs.In the GCN module,a loss function for boundary information is employed to optimize the learning of spatial relationship features between the target features and their relationships.A hierarchical fusion method is utilized for feature fusion and classification to optimize the spatial relationship informa-tion in the original feature information.Extensive experiments on ISPRS 2D and DeepGlobe semantic segmentation datasets show that compared with the existing semantic segmentation models of remote sensing images,the DGCN significantly optimizes the segmentation effect of feature boundaries,effectively reduces the noise in the segmentation results and improves the segmentation accuracy,which demonstrates the advancements of our model.

A novel mouse model of central cord syndrome

Patients with potential spinal stenosis are susceptible to central cord syndrome induced by blunt trauma.Suitable animal models are helpful for studying the pathogenesis and treatment of such injuries.In this study,we established a mouse model of acute blunt traumatic spinal cord injury by compressing the C6 spinal cord with 5 and 10 g/mm~2 compression weights to simulate cervical central cord syndrome.Behavioral testing confirmed that this model exhibited the characteristics of central cord syndrome because motor function in the front paws was impaired,whereas basic motor and sensory functions of the lower extremities were retained.Hematoxylin-eosin staining showed that the diseased region of the spinal cord in this mouse model was restricted to the gray matter of the central cord,whereas the white matter was rarely affected.Magnetic resonance imaging showed a hypointense signal in the lesion after mild and severe injury.In addition,immunofluorescence staining showed that the degree of nerve tract injury in the spinal cord white matter was mild,and that there was a chronic inflammation reaction.These findings suggest that this mouse model of central cord syndrome can be used as a model for preclinical research,and that gray matter is most vulnerable to injury in central cord syndrome,leading to impaired motor function.

Development of a method to quantify total and free irinotecan and 7-ethyl-10-hydroxycamptothecin(SN-38) for pharmacokinetic and bio-distribution studies after administration of irinotecan liposomal formulation

In 2015,liposomal formulation of irinotecan(ONIVYDE)has been approved by FDA and widely applied in the treatment of pancreatic cancer.ONIVYDE is a novel liposome formulation,entrapping CPT-11 in the aqueous core of vesicles using a modified gradient loading method.Due to toxicity concerns,it is essential to explore a rapid and reliable method to effectively isolate and quantify the non-liposomal,namely,free CPT-11and total CPT-11 in plasma.This study focuses on separation of non-liposomal CPT-11,evaluation of the pharmacokinetics of free CPT-11 and total CPT-11 and bio-distribution after intravenous administration of CPT-11 liposome.Free CPT-11 in plasma was separated by solid-phase extraction(SPE).The amount of total CPT-11 and main metabolite 7-ethyl-10-hydroxycamptothecin(SN-38)in plasma was quantified by ultra-performance liquid chromatography–MS/MS.The calibration curves fitted well and lower limit of quantitation for SN-38,free CPT-11,total CPT-11 and CPT-11 in tissue and were 5 ng/ml,10 ng/ml,4.44 ng/ml and 25 ng/ml respectively.The recoveries,precision and accuracy of the method appear satisfactory.Using this method,the pharmacokinetics and bio-distribution of CPT-11 liposome formulation after an intravenous dose of 2.5 mg/kg were then investigated.

A computer-aided chem-photodynamic drugs self-delivery system for synergistically enhanced cancer therapy

The therapeutic strategy that gives consideration to the combination of photodynamic therapy and chemotherapy,has emerged as a potential development of effective anti-cancer medicine.Nevertheless,co-delivery of photosensitizers(PSs)and chemotherapeutic drugs in traditional carriers still remains great limitations due to low drug loadings and poor biocompatibility.Herein,we have utilized a computer-aided strategy to achieve a desired carrier-free self-delivery of pyropheophorbide a(PPa,a common PS)and podophyllotoxin(PPT,a classical chemotherapeutic drug)for synergistic cancer therapy.First,the computational simulation method identified the similar molecular sizes and rigid molecular structures between two drugs molecules.Based on the molecular docking,the intermolecular interactions were found to includeπ-πstackings,hydrophobic interactions and hydrogen bonds.Next,both drugs could co-assemble into nanoparticles(NPs)via one-step nanoprecipitation method.The various spectral experiments(UV,IR and FL)were conducted to evaluate the formation mechanism of spherical NPs.Moreover,in vitro and in vivo experiments systematically demonstrated that PPT/PPa NPs not only showed better cellular uptake efficiency,stronger cytotoxicity and higher accumulation in tumor sites,but also exhibited synergistic antitumor effect in female BALB/C bearing-4T1 tumor mice.Such a computer-aided design strategy of chem-photodynamic drugs self-delivery systems pave the way for efficient synergistic cancer therapy.

Elaborately engineering of lipid nanoparticle for targeting delivery of siRNA and suppressing acute liver injury

Small interfering RNA(siRNA)-based gene silencing has been considered as a potential therapy modality against inflammatory diseases.Nevertheless,the effective delivery of siRNA to desired destination still remains challenging due to poor stability,high molecular weight and negative charge.Currently,ionizable lipid nanoparticle(LNP)has been extensively used as vector for effective delivery of siRNA.Herein,we report a mannose-modified LNP(M-MC_(3) LNP@TNFα)loading tumor necrosis factorα(TNFα)siRNA for targeting liver macrophages,achieving effectively inhibit acute liver injury.The M-MC_(3) LNP@TNFαnot only increases the internalization of LNP by macrophages,but also enhances the gene silencing efficiency of TNFαin vitro.Additionally,the M-MC_(3) LNP@TNFαexhibits higher accumulation in liver of healthy mice than that of MC_(3) LNP@TNFα(un-modified LNP)owing to the targeting effect of mannose.As expected,the M-MC_(3) LNP@TNFαsignificantly suppresses the expression of TNFαand ameliorates liver damage in acute liver injury model.Such a LNP targeting siRNA delivery holds great potential for the treatment of diseases associated with liver in the future.

Self-adaptive non-covalent albumin-binding near-infrared probe conjugates enabling precise sentinel lymph node metastasis illumination and primary tumor imaging

Tumor sentinel lymph node(SLN)metastasis plays a vital role in tumor staging and therapeutic decision-making process.However,precise diagnosis of primary tumors and lymphatic metastases is still hindered by low imaging resolution and poor photostability of fluorescent probes.Herein,we report three novel IR820-fatty acid(FA)conjugates(IR-OA,IR-LA,and IR-PA)for precise lymphatic metastasis illumination and primary tumor diagnosis.The IR-FA conjugates are able to non-covalently bound to albumin in vivo,and the fluorescence quantum yield is significantly enhanced after incubation with bovine serum albumin(BSA)in vitro.Moreover,the BSA-IR-FA conjugates display large Stokes shift(>120 nm),dramatically improving in vivo imaging resolution.Among them,IR-PA demonstrates distinct advantage over IR-OA,IR-LA,and IR-maleimide(MAL)(fluorescent probe previously reported by our group)in terms of fluorescence quantum yield,photostability,and imaging resolution.As a result,IR-PA exhibits satisfactory imaging results with high fluorescence intensity and imaging resolution in sentinel lymph node metastasis illumination and primary tumor location.Our findings provide a self-adaptive albumin-binding near-infrared probe conjugate for accurate diagnosis of primary tumors and lymphatic metastases.

Genomic and metabolomic insights into the selection and differentiation of bioactive compounds in citrus

Bioactive compounds play an increasingly prominent role in breeding functional and nutritive fruit crops such as citrus.However,the genomic and metabolic bases for the selection and differentiation underlying bioactive compound variations in citrus remain poorly understood.In this study,we constructed a species-level variation atlas of genomes and metabolomes using 299 citrus accessions.A total of 19829 significant SNPs were targeted to 653 annotated metabolites,among which multiple significant signals were identified for secondary metabolites,especially flavonoids.Significant differential accumulation of bioactive compounds in the phenylpropane pathway,mainly flavonoids and coumarins,was unveiled across ancestral citrus species during differentiation,which is likely associated with the divergent haplotype distribution and/or expression profiles of relevant genes,including p-coumaroyl coenzyme A 2′-hydroxylases,flavone synthases,cytochrome P450 enzymes,prenyltransferases,and uridine diphosphate glycosyltransferases.Moreover,we systematically evaluated the beneficial bioactivities such as the antioxidant and anticancer capacities of 219 citrus varieties,and identified robust associations between distinct bioactivities and specific metabolites.Collectively,these findings provide citrus breeding options for enrichment of beneficial flavonoids and avoidance of potential risk of coumarins.Our study will accelerate the application of genomic and metabolic engineering strategies in developing modern healthy citrus cultivars.