The isolation of high quality RNA is a crucial technique in plant molecular biology. The quality of RNA determines the reliability of downstream process like real time PCR. In this paper, we reported a high quality RN...The isolation of high quality RNA is a crucial technique in plant molecular biology. The quality of RNA determines the reliability of downstream process like real time PCR. In this paper, we reported a high quality RNA extraction protocol for a variety of plant species. Our protocol is time effective than traditional RNA extraction methods. The method takes only an hour to complete the procedure. Spectral measurement and electrophoresis were used to demonstrate RNA quality and quantity. The extracted RNA was further used for cDNA synthesis, expression analysis and copy number determination through Real Time PCR. The results indicate that RNA was of good quality and fit for real time PCR. This high throughput plant RNA extraction protocol can be used to isolate high quality RNA from diverse plants for real time PCR and other downstream applications.展开更多
Objective: To better characterize nonunion endochondral bone healing and evaluate novel therapeutic approaches for critical size defect healing in clinically challenging bone repair, a segmental defect model of bone i...Objective: To better characterize nonunion endochondral bone healing and evaluate novel therapeutic approaches for critical size defect healing in clinically challenging bone repair, a segmental defect model of bone injury was adapted from the threepoint bending closed fracture technique in the murine femur.Methods: The mouse femur was surgically stabilized with an intramedullary threaded rod with plastic spacers and the defect adjusted to different sizes. Healing of the different defects was analyzed by radiology and histology to 8 weeks postsurgery. To determine whether this model was effective for evaluating the benefits of molecular therapy, BMP-2 was applied to the defect and healing then examined.Results: Intramedullary spacers were effective in maintaining the defect. Callus bone formation was initiated but was arrested at defect sizes of 2.5 mm and above, with no more progress in callus bone development evident to 8 weeks healing. Cartilage development in a critical size defect attenuated very early in healing without bone development, in contrast to the closed femur fracture healing, where callus cartilage was replaced by bone. BMP-2 therapy promoted osteogenesis of the resident cells of the defect, but there was no further callus development to indicate that healing to pre-surgery bone structure was successful.Conclusions: This segmental defect adaptation of the closed femur fracture model of murine bone repair severely impairs callus development and bone healing, reflecting a challenging bone injury. It is adjustable and can be compared to the closed fracture model to ascertain healing deficiencies and the efficacy of therapeutic approaches.展开更多
The dynamical cluster-decay model (DCM) is employed to investigate the decay of ^(6870)Ge~* compound nuclei formed respectively via tightly (~4He) and loosely (~6He) bound projectiles, using ^(64)Zn target. The study ...The dynamical cluster-decay model (DCM) is employed to investigate the decay of ^(6870)Ge~* compound nuclei formed respectively via tightly (~4He) and loosely (~6He) bound projectiles, using ^(64)Zn target. The study is carried out over a wide energy range (E_(c.m.)～5 MeV to 16 MeV) by including the quadrupole deformations (β_(2i)) and optimum orientations (θ_i^(opt)) of the decaying fragments. The fusion cross-sections, obtained by adding various evaporation channels show nice agreement with the experimental data for ~4He+^(64)Zn reaction. The contribution from competing compound inelastic scattering channel is also analyzed particularly for ^(68)Ge~* nucleus at above barrier energies. On the other hand,the decrement in the fusion cross-sections of ^(70)Ge~* nuclear system is addressed by presuming that ^(65)Zn ER is formed via two different modes:(i) the αn evaporation of ^(70Ge)~* nucleus, and(ii) 1n-evaporation of ^(66)Zn~*nuclear system,formed via breakup and 2n-transfer channels due to halo structure of the ~6He projectile. Besides this, the suppression in2 np evaporation cross-sections suggests the contribution of another breakup and transfer process of ~6He i.e. ~4He+ ^(64)Zn.The contribution of breakup+transfer channels for ~6He+^(64)Zn reaction is duly addressed by applying relevant energy corrections due to the breakup of "~6He" projectile into 2n and ~4He. In addition to this, the barrier lowering, angular momentum and energy dependence effects are also explored in view of the dynamics of chosen reactions.展开更多
Lepidium sativum（commonly known as garden cress） belongs to the family Brassicaceae. It is a fastgrowing erect, annual herbaceous plant. Its seeds possess significant fracture healing, anti-asthmatic, anti-diabetic,...Lepidium sativum（commonly known as garden cress） belongs to the family Brassicaceae. It is a fastgrowing erect, annual herbaceous plant. Its seeds possess significant fracture healing, anti-asthmatic, anti-diabetic,hypoglycemic, nephrocurative and nephroprotective activities. In the present study, we assessed the genetic diversity of various genotypes of L. sativum using inter-simple sequence repeat（ISSR） markers. Out of 41 ISSR primers screened, 32 primers showed significant, clear and reproducible bands. A total of 510 amplified bands were obtained using 32 ISSR primers, out of which 422 bands were polymorphic and 88 bands were monomorphic. The percentage of polymorphism was found to be 82. A total of 35 unique alleles ranging insize from 200 to 2,900 bp were observed.Cluster analysis based on unweighted pair-group method,arithmetic mean divided the 18 genotypes into two main clusters, with the first having only HCS-08 genotype of L.sativum and other having all of the other 17 genotypes. The Jaccard similarity coefficient revealed a broad range32–72 % genetic relatedness among the 18 genotypes.展开更多
Pecan is the only native north American tree nut.The USA produces approximately 80%of the world’s pecans.Pecan trees have an extended juvenility,10 years to the first nut crop.With mature bearing they begin alternate...Pecan is the only native north American tree nut.The USA produces approximately 80%of the world’s pecans.Pecan trees have an extended juvenility,10 years to the first nut crop.With mature bearing they begin alternate bearing;alternating large and small crops.Theoretically,a heavy crop inhibits flower induction in the current year resulting in a low crop the following year.The flowering of perennial trees involves a complex interplay of multiple hormones.The possible molecular mechanisms regulating tree flowering can be revealed by endogenous plant hormone quantification,exogenous hormone application and RNA-sequencing.In this review,we synthesize the investigations of transcriptomic analysis and exogenous hormone treatments on bud break and flowering in fruit/nut trees with a focus on pecan.Knowledge of how hormones regulate flowering suggest they are a potential tool for improving return bloom and mitigating alternate bearing.展开更多
Tau protein aggregation is a hallmark of a diverse group of neurodegenerative disorders known as tauopathies,including Alzheimer’s disease,Pick’s disease,and progressive supranuclear palsy.These disorders are charac...Tau protein aggregation is a hallmark of a diverse group of neurodegenerative disorders known as tauopathies,including Alzheimer’s disease,Pick’s disease,and progressive supranuclear palsy.These disorders are characterized by the misfolding of tau intoβ-sheet-rich fibrils,disrupting neuronal function and contributing to disease progression.This review presents a comprehensive overview of the advances in molecular imaging that have deepened our understanding of tau pathology.We begin by examining tau’s domain architecture,isoform diversity,and aggregation mechanisms,highlighting the central role of the microtubule-binding region in fibril formation.The review then explores the structural polymorphism of tau fibrils across tauopathies,emphasizing the significance of cryo-electron microscopy in resolving disease-specific conformers.We discuss the fluorescence and radioimaging as powerful tools for detecting tau aggregates at the nanoscale.Particular focus is given to the development of tau-selective fluorescent probes and positron emission tomography tracers,detailing their design strategies,binding mechanisms,and diagnostic potential.Emerging approaches such as super-resolution imaging and sensor arrays are also considered for their ability to enhance sensitivity and specificity.By integrating insights from structural biology,chemical imaging,and molecular neuroscience,this review provides a multiscale framework for understanding tau aggregation and its implications for diagnosis and therapeutic intervention.展开更多
In recent time, data analysis using machine learning accelerates optimized solutions on clinical healthcare systems. The machine learning methods greatly offer an efficient prediction ability in diagnosis system alter...In recent time, data analysis using machine learning accelerates optimized solutions on clinical healthcare systems. The machine learning methods greatly offer an efficient prediction ability in diagnosis system alternative with the clinicians. Most of the systems operate on the extracted features from the patients and most of the predicted cases are accurate. However, in recent time, the prevalence of COVID-19 has emerged the global healthcare industry to find a new drug that suppresses the pandemic outbreak. In this paper, we design a Deep Neural Network(DNN)model that accurately finds the protein-ligand interactions with the drug used. The DNN senses the response of protein-ligand interactions for a specific drug and identifies which drug makes the interaction that combats effectively the virus. With limited genome sequence of Indian patients submitted to the GISAID database, we find that the DNN system is effective in identifying the protein-ligand interactions for a specific drug.展开更多
The three-dimensional problem involving diffraction of water wave by a finite floating rigid dock over an arbitrary bottom is studied for two cases(1)in the absence of wall(2)in the presence of wall.The problem is han...The three-dimensional problem involving diffraction of water wave by a finite floating rigid dock over an arbitrary bottom is studied for two cases(1)in the absence of wall(2)in the presence of wall.The problem is handled for its solution with the aid of step method.Here both asymmetric and symmetric arbitrary bottom profile is approximated using successive steps.Step approximation helps to apply the matched eigenfunction expansion method,in result,system of algebraic equations are obtained which are solved to determine the hydrodynamic quantities,namely,force experienced by rigid floating dock as well as rigid seawall,free surface elevation,transmission and reflection coefficients associated with transmission and reflected waves respectively.The effects of various structural and system parameters are examined on these hydrodynamics quantities.The appropriate values of length and thickness of dock,water depth and angle of incidence provide the salient information to marine and coastal engineers to design the offshore structures and creation of parabolic trench on the bottom.The present results are compared with known results in special case of bottom topography.The energy balance relation is derived and checked.展开更多
Purpose-The study aims to enhance the detection and classification of conjunctival eye diseases’severity through the development of ConjunctiveNet,an innovative deep learning framework.This model incorporates advance...Purpose-The study aims to enhance the detection and classification of conjunctival eye diseases’severity through the development of ConjunctiveNet,an innovative deep learning framework.This model incorporates advanced preprocessing techniques and utilizes a modified Otsu’s method for improved image segmentation,aiming to improve diagnostic accuracy and efficiency in healthcare settings.Design/methodology/approach-ConjunctiveNet employs a convolutional neural network(CNN)enhanced through transfer learning.The methodology integrates rescaling,normalization,Gaussian blur filtering and contrast-limited adaptive histogram equalization(CLAHE)for preprocessing.The segmentation employs a novel modified Otsu’s method.The framework’s effectiveness is compared against five pretrained CNN architectures including AlexNet,ResNet-50,ResNet-152,VGG-19 and DenseNet-201.Findings-The study finds that ConjunctiveNet significantly outperforms existing models in accuracy for detecting various severity stages of conjunctival eye conditions.The model demonstrated superior performance in classifying four distinct severity stages-initial,moderate,high,severe and a healthy stage-offering a reliable tool for enhancing screening and diagnosis processes in ophthalmology.Originality/value-ConjunctiveNet represents a significant advancement in the automated diagnosis of eye diseases,particularly conjunctivitis.Its originality lies in the integration of modified Otsu’s method for segmentation and its comprehensive preprocessing approach,which collectively enhance its diagnostic capabilities.This framework offers substantial value to the field by improving the accuracy and efficiency of conjunctival disease severity classification,thus aiding in better healthcare delivery.展开更多
文摘The isolation of high quality RNA is a crucial technique in plant molecular biology. The quality of RNA determines the reliability of downstream process like real time PCR. In this paper, we reported a high quality RNA extraction protocol for a variety of plant species. Our protocol is time effective than traditional RNA extraction methods. The method takes only an hour to complete the procedure. Spectral measurement and electrophoresis were used to demonstrate RNA quality and quantity. The extracted RNA was further used for cDNA synthesis, expression analysis and copy number determination through Real Time PCR. The results indicate that RNA was of good quality and fit for real time PCR. This high throughput plant RNA extraction protocol can be used to isolate high quality RNA from diverse plants for real time PCR and other downstream applications.
基金Loma Linda Veterans Association for Research and EducationGrant/Award Number Seed Grant(to CR)+2 种基金US Department of Veterans AffairsGrant/Award Number Merit Review Award#5 I01 BX002519-04(to CR)Senior Research Career Scientist Award(to SM)。
文摘Objective: To better characterize nonunion endochondral bone healing and evaluate novel therapeutic approaches for critical size defect healing in clinically challenging bone repair, a segmental defect model of bone injury was adapted from the threepoint bending closed fracture technique in the murine femur.Methods: The mouse femur was surgically stabilized with an intramedullary threaded rod with plastic spacers and the defect adjusted to different sizes. Healing of the different defects was analyzed by radiology and histology to 8 weeks postsurgery. To determine whether this model was effective for evaluating the benefits of molecular therapy, BMP-2 was applied to the defect and healing then examined.Results: Intramedullary spacers were effective in maintaining the defect. Callus bone formation was initiated but was arrested at defect sizes of 2.5 mm and above, with no more progress in callus bone development evident to 8 weeks healing. Cartilage development in a critical size defect attenuated very early in healing without bone development, in contrast to the closed femur fracture healing, where callus cartilage was replaced by bone. BMP-2 therapy promoted osteogenesis of the resident cells of the defect, but there was no further callus development to indicate that healing to pre-surgery bone structure was successful.Conclusions: This segmental defect adaptation of the closed femur fracture model of murine bone repair severely impairs callus development and bone healing, reflecting a challenging bone injury. It is adjustable and can be compared to the closed fracture model to ascertain healing deficiencies and the efficacy of therapeutic approaches.
基金Supported by CSIR-Scheme No.03(1341)/15/EMR-IIthe University Grants Commission(UGC),in the form of Maulana Azad National Fellowship(MANF)
文摘The dynamical cluster-decay model (DCM) is employed to investigate the decay of ^(6870)Ge~* compound nuclei formed respectively via tightly (~4He) and loosely (~6He) bound projectiles, using ^(64)Zn target. The study is carried out over a wide energy range (E_(c.m.)～5 MeV to 16 MeV) by including the quadrupole deformations (β_(2i)) and optimum orientations (θ_i^(opt)) of the decaying fragments. The fusion cross-sections, obtained by adding various evaporation channels show nice agreement with the experimental data for ~4He+^(64)Zn reaction. The contribution from competing compound inelastic scattering channel is also analyzed particularly for ^(68)Ge~* nucleus at above barrier energies. On the other hand,the decrement in the fusion cross-sections of ^(70)Ge~* nuclear system is addressed by presuming that ^(65)Zn ER is formed via two different modes:(i) the αn evaporation of ^(70Ge)~* nucleus, and(ii) 1n-evaporation of ^(66)Zn~*nuclear system,formed via breakup and 2n-transfer channels due to halo structure of the ~6He projectile. Besides this, the suppression in2 np evaporation cross-sections suggests the contribution of another breakup and transfer process of ~6He i.e. ~4He+ ^(64)Zn.The contribution of breakup+transfer channels for ~6He+^(64)Zn reaction is duly addressed by applying relevant energy corrections due to the breakup of "~6He" projectile into 2n and ~4He. In addition to this, the barrier lowering, angular momentum and energy dependence effects are also explored in view of the dynamics of chosen reactions.
文摘Lepidium sativum（commonly known as garden cress） belongs to the family Brassicaceae. It is a fastgrowing erect, annual herbaceous plant. Its seeds possess significant fracture healing, anti-asthmatic, anti-diabetic,hypoglycemic, nephrocurative and nephroprotective activities. In the present study, we assessed the genetic diversity of various genotypes of L. sativum using inter-simple sequence repeat（ISSR） markers. Out of 41 ISSR primers screened, 32 primers showed significant, clear and reproducible bands. A total of 510 amplified bands were obtained using 32 ISSR primers, out of which 422 bands were polymorphic and 88 bands were monomorphic. The percentage of polymorphism was found to be 82. A total of 35 unique alleles ranging insize from 200 to 2,900 bp were observed.Cluster analysis based on unweighted pair-group method,arithmetic mean divided the 18 genotypes into two main clusters, with the first having only HCS-08 genotype of L.sativum and other having all of the other 17 genotypes. The Jaccard similarity coefficient revealed a broad range32–72 % genetic relatedness among the 18 genotypes.
基金supported by Oklahoma Department of Agriculture,Food,&Forestry Specialty Crop Grant Program and Oklahoma Pecan Growers’Association.
文摘Pecan is the only native north American tree nut.The USA produces approximately 80%of the world’s pecans.Pecan trees have an extended juvenility,10 years to the first nut crop.With mature bearing they begin alternate bearing;alternating large and small crops.Theoretically,a heavy crop inhibits flower induction in the current year resulting in a low crop the following year.The flowering of perennial trees involves a complex interplay of multiple hormones.The possible molecular mechanisms regulating tree flowering can be revealed by endogenous plant hormone quantification,exogenous hormone application and RNA-sequencing.In this review,we synthesize the investigations of transcriptomic analysis and exogenous hormone treatments on bud break and flowering in fruit/nut trees with a focus on pecan.Knowledge of how hormones regulate flowering suggest they are a potential tool for improving return bloom and mitigating alternate bearing.
基金supported by the Australian Research Council(Grants DE210101176 and DP22010339)the Victorian State Government for the Veski FAIR Fellowship。
文摘Tau protein aggregation is a hallmark of a diverse group of neurodegenerative disorders known as tauopathies,including Alzheimer’s disease,Pick’s disease,and progressive supranuclear palsy.These disorders are characterized by the misfolding of tau intoβ-sheet-rich fibrils,disrupting neuronal function and contributing to disease progression.This review presents a comprehensive overview of the advances in molecular imaging that have deepened our understanding of tau pathology.We begin by examining tau’s domain architecture,isoform diversity,and aggregation mechanisms,highlighting the central role of the microtubule-binding region in fibril formation.The review then explores the structural polymorphism of tau fibrils across tauopathies,emphasizing the significance of cryo-electron microscopy in resolving disease-specific conformers.We discuss the fluorescence and radioimaging as powerful tools for detecting tau aggregates at the nanoscale.Particular focus is given to the development of tau-selective fluorescent probes and positron emission tomography tracers,detailing their design strategies,binding mechanisms,and diagnostic potential.Emerging approaches such as super-resolution imaging and sensor arrays are also considered for their ability to enhance sensitivity and specificity.By integrating insights from structural biology,chemical imaging,and molecular neuroscience,this review provides a multiscale framework for understanding tau aggregation and its implications for diagnosis and therapeutic intervention.
文摘In recent time, data analysis using machine learning accelerates optimized solutions on clinical healthcare systems. The machine learning methods greatly offer an efficient prediction ability in diagnosis system alternative with the clinicians. Most of the systems operate on the extracted features from the patients and most of the predicted cases are accurate. However, in recent time, the prevalence of COVID-19 has emerged the global healthcare industry to find a new drug that suppresses the pandemic outbreak. In this paper, we design a Deep Neural Network(DNN)model that accurately finds the protein-ligand interactions with the drug used. The DNN senses the response of protein-ligand interactions for a specific drug and identifies which drug makes the interaction that combats effectively the virus. With limited genome sequence of Indian patients submitted to the GISAID database, we find that the DNN system is effective in identifying the protein-ligand interactions for a specific drug.
文摘The three-dimensional problem involving diffraction of water wave by a finite floating rigid dock over an arbitrary bottom is studied for two cases(1)in the absence of wall(2)in the presence of wall.The problem is handled for its solution with the aid of step method.Here both asymmetric and symmetric arbitrary bottom profile is approximated using successive steps.Step approximation helps to apply the matched eigenfunction expansion method,in result,system of algebraic equations are obtained which are solved to determine the hydrodynamic quantities,namely,force experienced by rigid floating dock as well as rigid seawall,free surface elevation,transmission and reflection coefficients associated with transmission and reflected waves respectively.The effects of various structural and system parameters are examined on these hydrodynamics quantities.The appropriate values of length and thickness of dock,water depth and angle of incidence provide the salient information to marine and coastal engineers to design the offshore structures and creation of parabolic trench on the bottom.The present results are compared with known results in special case of bottom topography.The energy balance relation is derived and checked.
文摘Purpose-The study aims to enhance the detection and classification of conjunctival eye diseases’severity through the development of ConjunctiveNet,an innovative deep learning framework.This model incorporates advanced preprocessing techniques and utilizes a modified Otsu’s method for improved image segmentation,aiming to improve diagnostic accuracy and efficiency in healthcare settings.Design/methodology/approach-ConjunctiveNet employs a convolutional neural network(CNN)enhanced through transfer learning.The methodology integrates rescaling,normalization,Gaussian blur filtering and contrast-limited adaptive histogram equalization(CLAHE)for preprocessing.The segmentation employs a novel modified Otsu’s method.The framework’s effectiveness is compared against five pretrained CNN architectures including AlexNet,ResNet-50,ResNet-152,VGG-19 and DenseNet-201.Findings-The study finds that ConjunctiveNet significantly outperforms existing models in accuracy for detecting various severity stages of conjunctival eye conditions.The model demonstrated superior performance in classifying four distinct severity stages-initial,moderate,high,severe and a healthy stage-offering a reliable tool for enhancing screening and diagnosis processes in ophthalmology.Originality/value-ConjunctiveNet represents a significant advancement in the automated diagnosis of eye diseases,particularly conjunctivitis.Its originality lies in the integration of modified Otsu’s method for segmentation and its comprehensive preprocessing approach,which collectively enhance its diagnostic capabilities.This framework offers substantial value to the field by improving the accuracy and efficiency of conjunctival disease severity classification,thus aiding in better healthcare delivery.
