Human Anatomical Structures Research Articles

The Buccal Fat Pad: A Unique Human Anatomical Structure and Rich and Easily Accessible Source of Mesenchymal Stem Cells for Tissue Repair.

Buccal fat pads are biconvex adipose tissue bags that are uniquely found on both sides of the human face along the anterior border of the masseter muscles. Buccal fat pads are important determinants of facial appearance, facilitating gliding movements of facial masticatory and mimetic muscles. Buccal fad pad flaps are used for the repair of oral defects and as a rich and easily accessible source of mesenchymal stem cells. Here, we introduce the buccal fat pad anatomy and morphology and report its functions and applications for oral reconstructive surgery and for harvesting mesenchymal stem cells for clinical use. Future frontiers of buccal fat pad research are discussed. It is concluded that many biological and molecular aspects still need to be elucidated for the optimal application of buccal fat pad tissue in regenerative medicine.

Pengaruh Variasi mAs terhadap Densitas pada Hasil Radiograf Os Femur

Background: The human body's anatomical structure may be seen in radiological image findings. The proper exposure factor must be given in order to produce radiographic findings. The amperage value times the exposure period is equal to mAs. A darker image will result from a larger mA factor or longer exposure time. However, by choosing the appropriate exposure factor, an optimal radiograph density can be produced that can clearly display the difference in thickness and density between organs. The purpose of this study is to determine the results of how density affects the results of radiographs of the os femur.Methods: This research is quantitative using experimental methods to find out how the effect of mAs variations and how much the range of changes in value on density in AP projection femur examinations using mAs variations namely mAs 4, 8, 10, 12, 20, 25, and 32 with a fixed kV of 70 kV.Results: The results of this study indicate that there is a change in the effect of density quality on the variation of mAs on the radiograph results of the femoral os using the Friedman test p-value 0.001 which means less than 0.05. And the range of changes in density values at the caput femur, collum femur, collum femur, and greater trochanter there are changes in each mAs variation. The value of density variation against 7 mAs variations in radiograph results at variations of 4 to 32 mAs shows the density value increases by 0.14, for the range of increase in each variation it is ± from 0.02 to 0.05.Conclusions: The purpose of this study is to determine the results of how density is affected and the results of how the range of changes in density values on femur radiographs.

MRI brain tumor detection using deep learning and machine learning approaches

The development of aberrant brain cells, some of which may become cancerous, is known as a brain tumour. The quality of life and life expectancy of patients are enhanced by early and timely illness identification and treatment plans. Magnetic Resonance Imaging (MRI) scans are the most common approach for finding brain tumors. However, the ability of radiologists and other clinical experts to identify, segment, and remove contaminated tumour regions from MRI images is a critical factor in a process that is iterative and labor-intensive and relies on those individuals' abilities in these areas. Concepts for image processing may envision the diverse human organ anatomical structures. It is difficult to find abnormal brain regions using simple imaging methods. Over the last several years, interest in the emerging machine learning field of “Deep Learning (DL)" has grown significantly. It was extensively used in numerous applications and shown to be an effective Machine Learning (ML) technique for many of the challenging issues. This research suggests a novel MRI brain tumour detection method based on DL and ML. Initially the MRI images are collected and preprocessed using Adaptive Contrast Enhancement Algorithm (ACEA) and median filter. Fuzzy c-means based segmentation is done to segment the preprocessed images. The features like energy, mean, entropy and contrast are extracted using Gray-level co-occurrence matrix (GLCM). The abnormal tissues are classified using the proposed Ensemble Deep Neural Support Vector Machine (EDN-SVM) classifier. The numerical findings reveal a better accuracy (97.93 %), sensitivity (92 %), and specificity (98 %) in recognizing aberrant and normal tissue from brain MRIimages, which supports the effectiveness of the approach that was recommended.

Temporal Fractals in the Mammalian Hypothalamus and Music

Temporal Fractals in the Mammalian Hypothalamus and Music

Multicriteria Optimization of Lower Limb Exoskeleton Mechanism

Typical leg exoskeletons employ open-loop kinematic chains with motors placed directly on movable joints; while this design offers flexibility, it leads to increased costs and heightened control complexity due to the high number of degrees of freedom. The use of heavy servo-motors to handle torque in active joints results in complex and bulky designs, as highlighted in the existing literature. In this analytical study, we introduced a novel synthesis method with analytical solutions provided for synthesizing the lower-limb exoskeleton. Furthermore, we proposed a mathematical model of multicriteria optimization; as a result, we obtained several lower-limb exoskeleton mechanisms comprising only six links, well-suited to the human anatomical structure, exhibit superior trajectory accuracy, efficient force transmission, satisfactory step height, and having internal transfer segment of the foot.

Scintigraphic signs of kidney injuries of I–IV degrees of severity and their compliance with the OIS/OI AAST classification: observational study

INTRODUCTION: Mechanical effects on the kidney result in parenchymal disruption, haemorrhage formation, classified by OIS/OI AAST. Scintigraphy with 99Tc-DMSA can determine the presence, prevalence of areas of ischaemia and implications for renal function.OBJECTIVE: By radiopharmaceutical accumulation, to assess the function of the injured kidney and to establish the consistency of the scintigraphic images with the radiological findings of the OIS/OI AAST classification.MATERIAL AND METHODS: Scintigraphy with 99Tc-DMSA was performed in the immediate posttraumatic period in 196 patients who had Grade I–IV organ damage according to the OIS/OI AAST classification. The shape, size, and contours of the kidneys were visually evaluated. Based on the calculation of the uniformity and intensity of the indicator inclusion in the parenchyma the relative (total) kidney function was established. The degree and localisation of kidney damage were revealed on the basis of primary ultrasound and MSCT results.RESULTS: In the acute period of injury, Grade I–II were characterised by diffuse irregular distribution of 99Tc-DMSA (from 75.0 to 100% of cases), but with increasing area and volume of injury, focal scintigraphic symptoms appeared (up to 25.0% of cases).In Grade III–IV, localised or extended focal deformation of the image contour and reduction of the overall kidney function prevailed. Comparative evaluation of CT findings with visual scintigraphy data demonstrated symmetry of visual information with sufficient accessibility, perceptibility, accuracy and correlated with OIS/OI AAST classification.DISCUSSION: Scintigram interpretation involves the interaction of two components: visual perception and subject-specific knowledge of human anatomical structures. This significantly differentiates it from clinicians’ conventional conception of the diagnostic process. Semiotics in the images included diffuse and focal changes, the basis of which is a disorder of haemocirculation with impaired uptake of radiopharmaceutical in the kidney parenchyma. For Grade I–II, hypoactive areas indicating the absence of significant damage are typical. Grade III–IV are characterised by localised areas due to reduced volume of functioning parenchyma.CONCLUSION: Scintigraphy in blunt kidney trauma demonstrates haemocirculatory abnormalities in the organ and a decrease in the amount of functioning parenchyma. Comparison of radionuclide images with computer imaging has a high degree of identity. The type of scintigrams allows grading them according to the OIS/OI AAST degree systematisation, which standardises the interpretation of radiological findings to improve the objectivity and quality of the study reports. Assessment of overall renal function makes it possible to predict the rehabilitative outlook of the injured kidney and the need for correction.

Microphysiological Constructs and Systems: Biofabrication Tactics, Biomimetic Evaluation Approaches, and Biomedical Applications.

In recent decades, microphysiological constructs and systems (MPCs and MPSs) have undergone significant development, ranging from self-organized organoids to high-throughput organ-on-a-chip platforms. Advances in biomaterials, bioinks, 3D bioprinting, micro/nanofabrication, and sensor technologies have contributed to diverse and innovative biofabrication tactics. MPCs and MPSs, particularly tissue chips relevant to absorption, distribution, metabolism, excretion, and toxicity, have demonstrated potential as precise, efficient, and economical alternatives to animal models for drug discovery and personalized medicine. However, current approaches mainly focus on the in vitro recapitulation of the human anatomical structure and physiological-biochemical indices at a single or a few simple levels. This review highlights the recent remarkable progress in MPC and MPS models and their applications. The challenges that must be addressed to assess the reliability, quantify the techniques, and utilize the fidelity of the models are also discussed.

A review study on Jaal and it’s Modern Correlation

The Rachana Sharir is branch of Ayurveda in which human anatomy is explained according to Ayurved Samhita. The knowledge of human anatomy is very much important for treatment of disease and other surgical procedures. Paribhasha Sharir is concept of Ayurveda in which different anatomical structure are explained in Ayurvedic term. It’s one of the important contributions of Ayurveda in the medical field. It needs to be correlated with modern anatomy which further can be used in surgery purpose and also help in acupuncture or acupressure therapy. It will be the sort of proof that the structure present in modern anatomy were far ago explained in Ayurvedic Samhita. In Paribhasha Sharir a structure called Jaal or plexus is explained which means a binding structure which hold Maans (muscular plexus), Sira (vascular plexus), Snayu (ligamentum plexus) and Asthi (bony plexus) in one place and forming the network or Jaal like structure, there are 4 structure present in bilateral Miniband Sandhi i.e., wrist and Gulfa Sandhi i.e., ankle joint. In each joint there is involvement of four anatomical structure namely Maans, Sira, Snayu, Asthi. It can be correlated with human anatomical structure namely network of muscle tendons, palmer or planter arches, retinaculum, juncture of carpel and tarsal bones respectively.

Less Is More: Unsupervised Mask-Guided Annotated CT Image Synthesis With Minimum Manual Segmentations.

As a pragmatic data augmentation tool, data synthesis has generally returned dividends in performance for deep learning based medical image analysis. However, generating corresponding segmentation masks for synthetic medical images is laborious and subjective. To obtain paired synthetic medical images and segmentations, conditional generative models that use segmentation masks as synthesis conditions were proposed. However, these segmentation mask-conditioned generative models still relied on large, varied, and labeled training datasets, and they could only provide limited constraints on human anatomical structures, leading to unrealistic image features. Moreover, the invariant pixel-level conditions could reduce the variety of synthetic lesions and thus reduce the efficacy of data augmentation. To address these issues, in this work, we propose a novel strategy for medical image synthesis, namely Unsupervised Mask (UM)-guided synthesis, to obtain both synthetic images and segmentations using limited manual segmentation labels. We first develop a superpixel based algorithm to generate unsupervised structural guidance and then design a conditional generative model to synthesize images and annotations simultaneously from those unsupervised masks in a semi-supervised multi-task setting. In addition, we devise a multi-scale multi-task Fréchet Inception Distance (MM-FID) and multi-scale multi-task standard deviation (MM-STD) to harness both fidelity and variety evaluations of synthetic CT images. With multiple analyses on different scales, we could produce stable image quality measurements with high reproducibility. Compared with the segmentation mask guided synthesis, our UM-guided synthesis provided high-quality synthetic images with significantly higher fidelity, variety, and utility ( by Wilcoxon Signed Ranked test).

Polymer composites for obtaining human anatomic structures

Composites based on PLA with the addition of 3, 6 and 10 wt% silica, hydroxyapatite and bentonite were obtained by twin-screw extrusion. Maleic anhydride grafted polyethylene was used to enhance interface interactions. The influence of the fillers used on the Charpy impact strength, Rockwell hardness, tensile properties and processing shrinkage was investigated. Test samples were obtained by 3D printing. The highest impact strength and hardness were obtained for the composite containing 10 wt% hydroxyapatite. PLA with 10 wt% hydroxyapatite and 3 wt% bentonite was used to obtain anatomical structures by 3D printing.

Mitigating Under-Sampling Artifacts in 3D Photoacoustic Imaging Using Res-UNet Based on Digital Breast Phantom.

In recent years, photoacoustic (PA) imaging has rapidly grown as a non-invasive screening technique for breast cancer detection using three-dimensional (3D) hemispherical arrays due to their large field of view. However, the development of breast imaging systems is hindered by a lack of patients and ground truth samples, as well as under-sampling problems caused by high costs. Most research related to solving these problems in the PA field were based on 2D transducer arrays or simple regular shape phantoms for 3D transducer arrays or images from other modalities. Therefore, we demonstrate an effective method for removing under-sampling artifacts based on deep neural network (DNN) to reconstruct high-quality PA images using numerical digital breast simulations. We constructed 3D digital breast phantoms based on human anatomical structures and physical properties, which were then subjected to 3D Monte-Carlo and K-wave acoustic simulations to mimic acoustic propagation for hemispherical transducer arrays. Finally, we applied a 3D delay-and-sum reconstruction algorithm and a Res-UNet network to achieve higher resolution on sparsely-sampled data. Our results indicate that when using a 757 nm laser with uniform intensity distribution illuminated on a numerical digital breast, the imaging depth can reach 3 cm with 0.25 mm spatial resolution. In addition, the proposed DNN can significantly enhance image quality by up to 78.4%, as measured by MS-SSIM, and reduce background artifacts by up to 19.0%, as measured by PSNR, even at an under-sampling ratio of 10%. The post-processing time for these improvements is only 0.6 s. This paper suggests a new 3D real time DNN method addressing the sparse sampling problem based on numerical digital breast simulations, this approach can also be applied to clinical data and accelerate the development of 3D photoacoustic hemispherical transducer arrays for early breast cancer diagnosis.

The Presence of Unusual Foramina in the Femoral Intercondylar and Trochanteric Fossae on Skeletonized Individuals from Tanzania

According to the standard nomenclature, skeletal land marks are all identified by their given names in the world of human skeletal anatomy. But it is also clear that the discovery of new anatomical features continues because human beings have so many anatomical variations caused by genetics, functions, geographical adaptations, and diseases; they are all described and given names. Therefore, an anatomical feature that is rare and undescribed is certainly a discovery and it deserves to be recorded. The discovery of anatomical features on the epiphyseial ends of the femur reported here adds two new names, namely the intercondylar fossa foramen and the trochanteric fossa foramen in that long list of human skeletal anatomical structures. The intercondylar fossa foramen is an outlet found in the intercondylar fossa of the distal femur. It passes through the diaphysis of the femur and emerges in the trochanteric fossa of the femoral neck; and vice versa is the trochanteric fossa foramen. This feature was first observed on one skeletonized archaeological individual and later on five cadaveric remains. There seems to be a presence of this anatomical variation within the Tanzanian population. Only a small percentage of people have this unusual anatomical feature of the intercondylar fossa foramen, which might be a developmental ossification failure or a particular genetic-based trait. These features were assessed in the laboratory of the Anatomy Department at the Muhimbili University of Health and Allied Sciences (MUHAS) using a Dino-lite digital microscope and X-ray images.

Splitting Vertices in 2-Layer Graph Drawings.

Bipartite graphs model the relationships between two disjoint sets of entities in several applications and are naturally drawn as 2-layer graph drawings. In such drawings, the two sets of entities (vertices) are placed on two parallel lines (layers), and their relationships (edges) are represented by segments connecting vertices. Methods for constructing 2-layer drawings often try to minimize the number of edge crossings. We use vertex splitting to reduce the number of crossings, by replacing selected vertices on one layer by two (or more) copies and suitably distributing their incident edges among these copies. We study several optimization problems related to vertex splitting, either minimizing the number of crossings or removing all crossings with fewest splits. While we prove that some variants are ${\mathsf {NP}}$NP-complete, we obtain polynomial-time algorithms for others. We run our algorithms on a benchmark set of bipartite graphs representing the relationships between human anatomical structures and cell types.

Application of a linear interpolation algorithm in radiation therapy dosimetry for 3D dose point acquisition

Air-vented ion chambers are generally used in radiation therapy dosimetry to determine the absorbed radiation dose with superior precision. However, in ion chamber detector arrays, the number of array elements and their spacing do not provide sufficient spatial sampling, which can be overcome by interpolating measured data. Herein, we investigated the potential principle of the linear interpolation algorithm in volumetric dose reconstruction based on computed tomography images in the volumetric modulated arc therapy (VMAT) technique and evaluated how the ion chamber spacing and anatomical mass density affect the accuracy of interpolating new data points. Plane measurement doses on 83 VMAT treatment plans at different anatomical sites were acquired using Octavius 729, Octavius1500, and MatriXX ion chamber detector arrays, followed by the linear interpolation to reconstruct volumetric doses. Dosimetric differences in planning target volumes (PTVs) and organs at risk (OARs) between treatment planning system and reconstruction were evaluated by dose volume histogram metrics. The average percentage dose deviations in the mean dose (Dmean) of PTVs reconstructed by 729 and 1500 arrays ranged from 4.7 to 7.3% and from 1.5 to 2.3%, while the maximum dose (Dmax) counterparts ranged from 2.3 to 5.5% and from 1.6 to 7.6%, respectively. The average percentage dose/volume deviations of mixed PTVs and OARs in the abdomen/gastric and pelvic sites were 7.6%, 3.5%, and 7.2%, while mediastinum and lung plans showed slightly larger values of 8.7%, 5.1%, and 8.9% for 729, 1500, and MatriXX detector arrays, respectively. Our findings indicated that the smaller the spacing between neighbouring detectors and the more ion chambers present, the smaller the error in interpolating new data points. Anatomical regions with small local mass density inhomogeneity were associated with superior dose reconstruction. Given a large mass density difference in the various human anatomical structures and the characteristics of the linear interpolation algorithm, we suggest that an alternative data interpolation method should be used in radiotherapy dosimetry.

Neurorobotics and neuroprostheses: Towards a new anatomy.

The idea of this Special Issue arose from the technological advances in bionic, robotic, and neural rehabilitation systems and the common need to comprehend in detail how human anatomical structures can be replicated or controlled. Motor control theories, among others, include the generalized control program theory, the equilibrium point hypothesis, or the optimal control approach in which neural commands to the muscles are a result of the central nervous system solving an optimization problem for a specific cost function. No matter the alternative interpretation selected to replicate biological control of human movements, artificial "anatomies" should consider not only motor capabilities from the central nervous system but integrate bioinspired mechanical features (such as compliance) in artificial limbs. The development of wearable robotics and neuroprosthetic systems for human movement compensation and control is naturally inspired by human anatomy and biology. Cutting-edge technological advances in the field of biomedical and neural engineering are bringing us more and more close to a new artificial anatomy with which humans could augment their motor capabilities or replace them after they are compromised. Either augmentative/assistive or rehabilitation technologies in the near future will require engineering solutions based on novel approaches to create usable neurorobotic and neuroprosthetic systems for the most relevant societal needs.

Finite element analysis of the effect of intracranial hemorrhages on postmortem cranioencephalic temperature

Aim. To assess the local influence of intracranial hemorrhages of various types on postmortem cranioencephalic temperature by means of finite element modeling of the postmortem temperature field of the head.Methods. The geometry and postmortem heat exchange of human head anatomical structures were simulated using the ELCUT 6.5 software application based on the finite element method, both in the absence and presence of meningeal and intraventricular hemorrhages.Results. A twodimensional finite element model for determining the postmortem temperature field of the head in the presence of various intracranial hemorrhages under the conditions of convective heat exchange with the air was developed. The absence of a significant direct effect of intracranial hemorrhages on cranioencephalic temperature was confirmed.Conclusions. Cranioencephalic temperature can be used to determine the postmortem interval in the presence of any intracranial hemorrhages. In order to exclude errors associated with possible hyperthermic death, as well as those caused by local exposure to intraventricular hemorrhages, cranioencephalic temperature should be used to determine the postmortem interval only after its reduction to values lower than 36 °C.

OFİS TASARIMINDA ERGONOMİK KOŞULLARIN SAĞLANMASININ ÖNEMİ

Ofis organizasyonlarının sosyal yapısı ile teknik yapısının bütünleştirilmesi, günümüz iş hayatının önemli konularından birini oluşturmakta olup çalışanın sağlıklı, verimli, istekli ve işiyle uyumlu çalışabilmesi için oldukça önemlidir. Ergonomi, insan ve bulunduğu çevrenin fiziksel ve psikolojik açıdan birbirleri ile uyumlandırılması, insanın bedensel ve ruhsal yönden zorlamadan yeteneklerini en rahat şekilde kullanabilme süreci olarak tanımlanmaktadır. Günümüz modern dünyasında ofis çalışanlarının çoğu çalışma ortamının çevresel ve fiziksel koşulları açısından çeşitli problemlerle karşılaşmakta ve bu durum çalışanların beden ve ruh sağlığı ile iş verimliliklerini olumsuz etkilemektedir. Günümüzde, teknolojik alanda yaşanan değişim ve gelişim çalışan bireylerin hem bedensel ve hem de düşünsel yeteneklerini zorlamaktadır. Çalışanın gelişen teknoloji, makineler ve çalışma sistemleri karşısında yetersiz kalmasının önlendiği ve ergonomik açıdan sağlığının düşünüldüğü ofis mekânlarının düzenlenmesi gerekmektedir. Tüm bu düzenlemeler insanın antropometrik ölçüleri, anatomik yapısı, fizyolojik kapasitesi ve toleransları göz önünde bulundurularak yapılmalıdır. Ergonominin temel fonksiyonu olan çalışanın iş yerinde verimli, sağlıklı ve güvenli çalışabilmeleri için gerekli iş organizasyonunun insan özelliklerine uygun olarak düzenlenmesi sağlanarak; çalışan sağlığı ve iş güvenliği koşulları iyileştirilmeli, fizyolojik ve psikolojik açıdan çalışma performansı artırılmalıdır. Bu çalışmanın amacı, ergonomi biliminin önemine değinilerek ofis ergonomisinin iş verimine etkisini incelemektir. Bu amaç doğrultusunda çalışma mekânını oluşturan bileşenler perspektifinde çalışan sağlığı ve iş verimi analiz edilmiştir. Yapılan araştırma sonucunda çalışma çevrelerinde aydınlatma sistemi, ses ve gürültü denetimi, iklimlendirme sistemi, araç-gereç uyumu ve renk tercihi gibi faktörlerin çalışanlar üzerinde önemli etkileri olduğu görülmüştür.

Activity Monitoring During the Instruction of Gross Anatomy

Over the past decades, a compendium of various physical activities has been compiled that ranges from more vigorous activities in the occupational and recreational domains, to mundane household tasks and chores. These have been developed to allow users to understand their individual activity profile for intake and caloric expenditure. Teaching gross anatomical dissection courses is physically demanding, and anecdotally, has a different activity profile than teaching other courses. The purpose of this study was to quantify the basic activity profile of gross anatomical instruction and compare these measure to other occupation tasks. For a period of 4‐years, faculty and laboratory staff (n=52; 35.6 years + 8) were provided commercially available activity monitors (Fitbit Charge, Fitbit, San Francisco, CA) and were worn during all gross anatomy lab dissections (272 min/session + 38) in a semester‐long class. Data were collected and reported after each class session including, steps, caloric expenditure and time of activity. The average caloric expenditure/session was 569.47 kCal (SD = 33.8), or 126.55 kCal/hour during the instruction of gross anatomy lab experiences and was found to be similar to general carpentry (145 kCal/hour) and custodial work (136 kCal/hour). However, the profession that was most similar was nursing. A recent study has shown (Allan, et al, Journal of Research in Nursing, 2019) that ward nurses on 12‐hour shifts exhibit caloric expenditure of 1512kCal/shift, or 126.75 kCal/hour. When the objective tasks are compared, its not surprising that these professions exhibit similar results. Both repeatedly perform work from station‐to‐station throughout the day requiring above average amounts of standing and walking. Further, the work performed at a station also requires a mixture of finite precision and moving of the subject/patient. Although these data aren’t unique or novel, it may be of particular interest to those that perform this occupation skill. Guiding the dissection experiences for medical and allied health students is a vigorous and strenuous job that requires the background and familiarity human anatomical structures with physical demands that are more extensive than a typical class or laboratory setting.

Artificial Intelligence Radiotherapy Planning: Automatic Segmentation of Human Organs in CT Images Based on a Modified Convolutional Neural Network.

Objective:Precise segmentation of human organs and anatomic structures (especially organs at risk, OARs) is the basis and prerequisite for the treatment planning of radiation therapy. In order to ensure rapid and accurate design of radiotherapy treatment planning, an automatic organ segmentation technique was investigated based on deep learning convolutional neural network.MethodA deep learning convolutional neural network (CNN) algorithm called BCDU-Net has been modified and developed further by us. Twenty two thousand CT images and the corresponding organ contours of 17 types delineated manually by experienced physicians from 329 patients were used to train and validate the algorithm. The CT images randomly selected were employed to test the modified BCDU-Net algorithm. The weight parameters of the algorithm model were acquired from the training of the convolutional neural network.ResultThe average Dice similarity coefficient (DSC) of the automatic segmentation and manual segmentation of the human organs of 17 types reached 0.8376, and the best coefficient reached up to 0.9676. It took 1.5–2 s and about 1 h to automatically segment the contours of an organ in an image of the CT dataset for a patient and the 17 organs for the CT dataset with the method developed by us, respectively.ConclusionThe modified deep neural network algorithm could be used to automatically segment human organs of 17 types quickly and accurately. The accuracy and speed of the method meet the requirements of its application in radiotherapy.

Recombinant Plasminogen Activator Modified Nanoparticles for Targeting Thrombolysis in Branch Retinal Vein Occlusion.

Branch Retinal Vein Occlusion (BRVO) is the second chronic branch retinal vascular disease that causes abnormal vision loss after acute branch retinal disease in type 2 diabetes. There is no scientific conclusion about its specific pathogenic mechanism at present. Most clinical scholars generally support the theory that the partial human anatomical structure and various systemic risk psychological factors cause insufficient oxygen supply and hemostasis in the local branch retinal arteries. The research results of this article aim to reconstruct a non-nanocell-targeted thrombolytic drug delivery system without modification of rtPA without polyethylene glycol-methyl polycaprolactone and to re-evaluate its thrombus targeting and dissolution. The effect and safety of thrombus provide a new strategy for realizing combined treatment of thrombus. It is a study on the targeting of rtPA-NP to thrombus and its thrombolytic properties. HPLC method was used to detect the binding of fibrin clot prepared in vitro with coumarin-6 labeled NP and rtPA-NP; immunofluorescence technique was used to observe the location of nanomedicine and fibrin clot in branch retinal vein occlusion model Condition. The rtPA-NP drug delivery system constructed in this study not only retains the activity of rtPA and good thrombus targeting but also significantly prolongs its half-life and simplifies the way of administration. The therapeutic efficiency of rtPA-NP thrombus targeted administration on branch retinal vein occlusion reached 85.64%. The successful construction of the rtPA-NP thrombus targeted drug delivery system provides a new way for thrombosis treatment and lays the foundation for the future combination of anticoagulants and vascular protection drugs to achieve the combined treatment of thrombosis and the development of safe and efficient thrombolytic drugs.