scholarly journals Prediction of Ovarian Follicular Dominance by MRI Phenotyping of Hormonally Induced Vascular Remodeling

2021 ◽  
Vol 8 ◽  
Author(s):  
Liat Fellus-Alyagor ◽  
Inbal E. Biton ◽  
Hagit Dafni ◽  
Filip Bochner ◽  
Ron Rotkopf ◽  
...  
Keyword(s):  
Blood Vessel ◽  
Blood Volume ◽  
Early Stage ◽  
Ovarian Follicles ◽  
Small Subset ◽  
Dce Mri ◽  
Stage Of Development ◽  
Vessel Growth ◽  
Mammalian Female ◽  
Area Product

In the mammalian female, only a small subset of ovarian follicles, known as the dominant follicles (DFs), are selected for ovulation in each reproductive cycle, while the majority of the follicles and their resident oocytes are destined for elimination. This study aimed at characterizing early changes in blood vessel properties upon the establishment of dominance in the mouse ovary and application of this vascular phenotype for prediction of the follicles destined to ovulate. Sexually immature mice, hormonally treated for induction of ovulation, were imaged at three different stages by dynamic contrast-enhanced (DCE) MRI: prior to hormonal administration, at the time of DF selection, and upon formation of the corpus luteum (CL). Macromolecular biotin-bovine serum albumin conjugated with gadolinium-diethylenetriaminepentaacetic acid (b-BSA-GdDTPA) was intravenously injected, and the dynamics of its extravasation from permeable vessels as well as its accumulation in the antral cavity of the ovarian follicles was followed by consecutive T1-weighted MRI. Permeability surface area product (permeability) and fractional blood volume (blood volume) were calculated from b-BSA-GdDTPA accumulation. We found that the neo-vasculature during the time of DF selection was characterized by low blood volume and low permeability values as compared to unstimulated animals. Interestingly, while the vasculature of the CL showed higher blood volume compared to the DF, it exhibited a similar permeability. Taking advantage of immobilized ovarian imaging, we combined DCE-MRI and intravital light microscopy, to reveal the vascular properties of follicles destined for dominance from the non-ovulating subordinate follicles (SFs). Immediately after their selection, permeability of the vasculature of DF was attenuated compared to SF while the blood volume remained similar. Furthermore, DFs were characterized by delayed contrast enhancement in the avascular follicular antrum, reflecting interstitial convection, whereas SFs were not. In this study, we showed that although DF selection is accompanied by blood vessel growth, the new vasculature remained relatively impermeable compared to the vasculature in control animal and compared to SF. Additionally, DFs show late signal enhancement in their antrum. These two properties may aid in clinical prediction of follicular dominance at an early stage of development and help in their diagnosis for possible treatment of infertility.

The Application of UX Research in New Energy Vehicle Innovation

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Menghan TAO ◽  
Ning XIAO ◽  
Xingfu ZHAO ◽  
Wenbin LIU
Keyword(s):  
Early Stage ◽  
Rapid Expansion ◽  
The Other ◽  
Innovative Product ◽  
Stage Of Development ◽  
New Energy ◽  
New Energy Vehicle ◽  
The One ◽  
New Energy Vehicles ◽  
Degree Of Innovation

New energy vehicles(NEV) as a new thing for sustainable development, in China, on the one hand has faced the rapid expansion of the market; the other hand, for the new NEV users, the current NEVs cannot keep up with the degree of innovation. This paper demonstrates the reasons for the existence of this systematic challenge, and puts forward the method of UX research which is different from the traditional petrol vehicles research in the early stage of development, which studies from the user's essence level, to form the innovative product programs which meet the needs of users and being real attractive.

scholarly journals Learning health systems in primary care: a systematic scoping review

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Danielle M. Nash ◽  
Zohra Bhimani ◽  
Jennifer Rayner ◽  
Merrick Zwarenstein
Keyword(s):  
Primary Care ◽  
Quality Improvement ◽  
Health Systems ◽  
Scoping Review ◽  
Early Stage ◽  
Point Of Care ◽  
The United States ◽  
Stage Of Development ◽  
Integrated Health ◽  
Google Search

Abstract Background Learning health systems have been gaining traction over the past decade. The purpose of this study was to understand the spread of learning health systems in primary care, including where they have been implemented, how they are operating, and potential challenges and solutions. Methods We completed a scoping review by systematically searching OVID Medline®, Embase®, IEEE Xplore®, and reviewing specific journals from 2007 to 2020. We also completed a Google search to identify gray literature. Results We reviewed 1924 articles through our database search and 51 articles from other sources, from which we identified 21 unique learning health systems based on 62 data sources. Only one of these learning health systems was implemented exclusively in a primary care setting, where all others were integrated health systems or networks that also included other care settings. Eighteen of the 21 were in the United States. Examples of how these learning health systems were being used included real-time clinical surveillance, quality improvement initiatives, pragmatic trials at the point of care, and decision support. Many challenges and potential solutions were identified regarding data, sustainability, promoting a learning culture, prioritization processes, involvement of community, and balancing quality improvement versus research. Conclusions We identified 21 learning health systems, which all appear at an early stage of development, and only one was primary care only. We summarized and provided examples of integrated health systems and data networks that can be considered early models in the growing global movement to advance learning health systems in primary care.

scholarly journals Open Research Data and Open Peer Review: Perceptions of a Medical and Health Sciences Community in Greece

Publications ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 14
Author(s):  
Eirini Delikoura ◽  
Dimitrios Kouis
Keyword(s):  
Peer Review ◽  
Evaluation System ◽  
Early Stage ◽  
Open Science ◽  
Health Sciences ◽  
Research Data ◽  
Stage Of Development ◽  
Open Research ◽  
Proper Training ◽  
To Receive

Recently significant initiatives have been launched for the dissemination of Open Access as part of the Open Science movement. Nevertheless, two other major pillars of Open Science such as Open Research Data (ORD) and Open Peer Review (OPR) are still in an early stage of development among the communities of researchers and stakeholders. The present study sought to unveil the perceptions of a medical and health sciences community about these issues. Through the investigation of researchers` attitudes, valuable conclusions can be drawn, especially in the field of medicine and health sciences, where an explosive growth of scientific publishing exists. A quantitative survey was conducted based on a structured questionnaire, with 179 valid responses. The participants in the survey agreed with the Open Peer Review principles. However, they ignored basic terms like FAIR (Findable, Accessible, Interoperable, and Reusable) and appeared incentivized to permit the exploitation of their data. Regarding Open Peer Review (OPR), participants expressed their agreement, implying their support for a trustworthy evaluation system. Conclusively, researchers need to receive proper training for both Open Research Data principles and Open Peer Review processes which combined with a reformed evaluation system will enable them to take full advantage of the opportunities that arise from the new scholarly publishing and communication landscape.

scholarly journals Primary Care Networks and Starfield’s 4Cs: A Case for Enhanced Chronic Disease Management

2021 ◽  
Vol 18 (6) ◽  
pp. 2926
Author(s):  
Chuan De Foo ◽  
Shilpa Surendran ◽  
Geronimo Jimenez ◽  
John Pastor Ansah ◽  
David Bruce Matchar ◽  
...  
Keyword(s):  
Primary Care ◽  
Chronic Disease ◽  
Disease Management ◽  
Chronic Disease Management ◽  
Early Stage ◽  
Healthcare Delivery ◽  
Stage Of Development ◽  
Facilitators And Barriers ◽  
Design Options ◽  
First Contact

The primary care network (PCN) was implemented as a healthcare delivery model which organises private general practitioners (GPs) into groups and furnished with a certain level of resources for chronic disease management. A secondary qualitative analysis was conducted with data from an earlier study exploring facilitators and barriers GPs enrolled in PCN’s face in chronic disease management. The objective of this study is to map features of PCN to Starfield’s “4Cs” framework. The “4Cs” of primary care—comprehensiveness, first contact access, coordination and continuity—offer high-quality design options for chronic disease management. Interview transcripts of GPs (n = 30) from the original study were purposefully selected. Provision of ancillary services, manpower, a chronic disease registry and extended operating hours of GP practices demonstrated PCN’s empowering features that fulfil the “4Cs”. On the contrary, operational challenges such as the lack of an integrated electronic medical record and disproportionate GP payment structures limit PCNs from maximising the “4Cs”. However, the enabling features mentioned above outweighs the shortfalls in all important aspects of delivering optimal chronic disease care. Therefore, even though PCN is in its early stage of development, it has shown to be well poised to steer GPs towards enhanced chronic disease management.

Diagnosing breast cancer tumors using stacked ensemble model

2021 ◽  
pp. 1-9
Author(s):  
Ahmet Haşim Yurttakal ◽  
Hasan Erbay ◽  
Türkan İkizceli ◽  
Seyhan Karaçavuş ◽  
Cenker Biçer
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
Medical Imaging ◽  
Early Stage ◽  
False Negative ◽  
Gradient Boosting ◽  
Physical Sign ◽  
Ensemble Model ◽  
Learning Methods ◽  
Dce Mri

Breast cancer is the most common cancer that progresses from cells in the breast tissue among women. Early-stage detection could reduce death rates significantly, and the detection-stage determines the treatment process. Mammography is utilized to discover breast cancer at an early stage prior to any physical sign. However, mammography might return false-negative, in which case, if it is suspected that lesions might have cancer of chance greater than two percent, a biopsy is recommended. About 30 percent of biopsies result in malignancy that means the rate of unnecessary biopsies is high. So to reduce unnecessary biopsies, recently, due to its excellent capability in soft tissue imaging, Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has been utilized to detect breast cancer. Nowadays, DCE-MRI is a highly recommended method not only to identify breast cancer but also to monitor its development, and to interpret tumorous regions. However, in addition to being a time-consuming process, the accuracy depends on radiologists’ experience. Radiomic data, on the other hand, are used in medical imaging and have the potential to extract disease characteristics that can not be seen by the naked eye. Radiomics are hard-coded features and provide crucial information about the disease where it is imaged. Conversely, deep learning methods like convolutional neural networks(CNNs) learn features automatically from the dataset. Especially in medical imaging, CNNs’ performance is better than compared to hard-coded features-based methods. However, combining the power of these two types of features increases accuracy significantly, which is especially critical in medicine. Herein, a stacked ensemble of gradient boosting and deep learning models were developed to classify breast tumors using DCE-MRI images. The model makes use of radiomics acquired from pixel information in breast DCE-MRI images. Prior to train the model, radiomics had been applied to the factor analysis to refine the feature set and eliminate unuseful features. The performance metrics, as well as the comparisons to some well-known machine learning methods, state the ensemble model outperforms its counterparts. The ensembled model’s accuracy is 94.87% and its AUC value is 0.9728. The recall and precision are 1.0 and 0.9130, respectively, whereas F1-score is 0.9545.

The magic bullet for rural development? Exploring the impacts of community telecenters in Bangladesh

2021 ◽  
pp. 026666692199750
Author(s):  
Noore Alam Siddiquee ◽  
Md Gofran Faroqi
Keyword(s):  
Service Delivery ◽  
Rural Areas ◽  
Early Stage ◽  
Rural Livelihoods ◽  
Value Added ◽  
Magic Bullet ◽  
Government Information ◽  
Individual Interviews ◽  
Stage Of Development ◽  
Marginalized Groups

This paper explores the impacts of Bangladesh’s Union Digital Centers (UDCs) as government information and service delivery hubs in rural areas. Drawing on user-surveys and semi-structured individual interviews it demonstrates that the UDCs have produced generally positive yet modest impacts on governance of service delivery. It shows that the UDCs are at an early stage of development, and that they offer only a limited set of services. While they helped extend ICT-enabled services to sections of population that would otherwise have missed them, the UDCs do not have much to do with rural livelihoods and empowerment of the poor and marginalized groups. These findings point to current inadequacies and pitfalls of the UDC approach to development. We argue that enhanced viability and effectiveness of the UDC experiment would warrant embedding more value-added governmental services and further strengthening of their capacity, mandate, and connectivity with government agencies at various levels, among others.

Targets, triggers, and directionality in non-local and local place assimilation in child and adult language

2014 ◽  
Vol 50 (3) ◽  
pp. 273-307
Author(s):  
Mi-Hui Cho ◽  
Shinsook Lee
Keyword(s):  
Longitudinal Study ◽  
Early Development ◽  
Early Stage ◽  
Decisive Role ◽  
Diary Study ◽  
Consonant Harmony ◽  
Stage Of Development ◽  
Place Assimilation ◽  
Korean Child ◽  
Non Local

Abstract Data collected from one Korean child in a longitudinal diary study present novel patterns of consonant harmony in that labials, coronals, and velars can be triggers and targets of both progressive and regressive non-local place assimilation in an early stage of development. The same child also shows some cases of local regressive place assimilation. In another study where 4 children's data were gathered from a naturalistic longitudinal study, local regressive place assimilation as well as conso-nant harmony is witnessed regardless of place features. In adult Korean, however, only coronal to labial/velar and labial to velar local regressive assimilation occurs. This paper argues that the non-local and local place assimilation is connected and shows that the connection can be accounted for in terms of different constraint rankings within the Optimality-theoretic framework. More specifically, it is shown that the Ident-Onset(place) constraint plays a decisive role even in the early stage of acquisition, unlike child English, accounting for the predominant regressive assimilation. Also, the Agree-Place constraint is exploded into two sub-constraints in Stage 3, capturing the asymmetrical behavior of assimilation. Further, the unranking of place features in early development gradually evolves to the fixed ranking which reflects the universal markedness hierarchy in adult Korean.

Genera coelomycetarum. I. Urohendersonia

1971 ◽  
Vol 49 (11) ◽  
pp. 1853-1862 ◽  
Author(s):  
T. R. Nag Raj ◽  
Bryce Kendrick
Keyword(s):  
Early Stage ◽  
Type Material ◽  
Stage Of Development

Study of type material of Urohendersonia platensis, U. indica, and U. stipae reveals that structures described by their original authors as ‘basidia’ or ‘pedicels’ (in contemporary parlance, conidiophores) are, in fact, apical conidium appendages. The true conidiophores and the processes of conidiogenesis are described and illustrated. Urohendersonia has unilocular, ostiolate pycnidia producing three-septate, colored conidia that are enclosed from an early stage of development in a sheath which extends apically as a hyaline, filiform process. Urohendersonia and Hendersonia are delineated. Revised descriptions are given for Urohendersonia and its four species. A fifth species, U. mysorensis, is described as new. A key to the five species is given.

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