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#32746501   2020/08/03 To Up

Assessment of sexuality information needs in haemophilia: Evaluation of a multi-ethnic patient cohort.


Gianluca Sottilotta, Dora Messina, Andrea Buzzi

2486 related Products with: Assessment of sexuality information needs in haemophilia: Evaluation of a multi-ethnic patient cohort.



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#32746500   2020/08/03 To Up

Colonoscopy-guided therapy for the prevention of post-operative recurrence of Crohn's disease.

About half of patients with Crohn's disease (CD) require surgery within 10 years of diagnosis. Resection of the affected segment is highly effective, however the majority of patients experience clinical recurrence after surgery. Most of these patients have asymptomatic endoscopic recurrence weeks or months before starting with symptoms. This inflammation can be detected by colonoscopy and is a good predictor of poor prognosis.Therapy guided by colonoscopy could tailor the management and improve the prognosis of postoperative CD.
Roberto Candia, Gonzalo A Bravo-Soto, Hugo Monrroy, Cristian Hernandez, Geoffrey C Nguyen

2985 related Products with: Colonoscopy-guided therapy for the prevention of post-operative recurrence of Crohn's disease.

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#32746498   2020/08/03 To Up

Donor-Transmitted Cancers in Transplanted Livers: Analysis of Clinical Outcomes.

The risk of transmission of malignancy from donor to recipient is low; however, this occurrence has dramatic consequences. Many reports of donor derived cancers in liver transplant recipients have been published, but they have not been a systematically summarized into a lucid and unified analysis. The present study is an attempt to provide clarity to this unusual, but clinically important problem. We systematically reviewed all case reports, case series, and registries published on cancer transmission events through the end of December 2019. We identified a total of 67 publications with 92 transmission events. The most frequently transmitted cancers were lymphomas (30 [32.6%]), melanomas (8 [8.7%]), and neuroendocrine tumors (8 [8.7%]). Most of the melanomas were metastasizing, while most of the lymphomas were localized to the graft. The median time to cancer diagnosis after transplantation was 7 months, with 78% of diagnoses established in the first year. Melanoma carried the worst prognosis, with no recipients alive at 1 year after cancer diagnosis. Lymphoma recipients had a better outcome, with more than 75% surviving at 2 years. Conclusion: A metastatic cancer carries a worse prognosis for recipients, also because recipients with localized cancer can benefit from the chance to undergo transplantation again. The findings confirm the need to pay attention to donors with a history of melanoma but also suggest the need for a more careful evaluation of groups of donors, such as those dying from cerebral hemorrhage. Finally, recipients of organs from donors with cancer should be carefully followed to detect potential transmission.
Albino Eccher, Ilaria Girolami, Stefano Marletta, Matteo Brunelli, Amedeo Carraro, Umberto Montin, Ugo Boggi, Claudia Mescoli, Luca Novelli, Deborah Malvi, Letizia Lombardini, Massimo Cardillo, Desley Neil, Antonietta D'Errico

2975 related Products with: Donor-Transmitted Cancers in Transplanted Livers: Analysis of Clinical Outcomes.



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#32746395   // To Up

Do Social Threat Cognitions Decrease With School-Based CBT and Predict Treatment Outcome in Adolescents With Social Anxiety Disorder?

Evidence suggests that Social Anxiety Disorder (SAD) is less responsive to cognitive behavioral treatment (CBT) compared to other anxiety disorders. Therefore, exploring what might facilitate clinical benefit is essential. Social threat cognitions, characterized by exaggerated perceptions of negative evaluation by others, may be one important avenue to examine. The current study investigated whether youths' social threat cognitions decreased with Skills for Academic and Social Success (SASS), a group, school-based CBT designed for SAD, and whether decreases predicted SAD severity and treatment response. Participants included 138 high school students with SAD randomly assigned to SASS, or a nonspecific school counseling intervention. SASS participants showed significantly decreased social threat cognitions at 5-month follow-up. Treatment responders had significantly greater reductions in social threat cognitions compared to nonresponders at post-intervention and follow-up. These findings suggest that social threat cognitions may be important to assess and monitor when treating youth with SAD.
Julie L Ryan, Jeremy K Fox, Sarah R Lowe, Carrie Masia Warner

2281 related Products with: Do Social Threat Cognitions Decrease With School-Based CBT and Predict Treatment Outcome in Adolescents With Social Anxiety Disorder?

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#32746368   2020/07/07 To Up

Machine Learning for Clinical Outcome Prediction.

Clinical decision-making in healthcare is already being influenced by predictions or recommendations made by data-driven machines. Numerous machine learning applications have appeared in the latest clinical literature, especially for outcome prediction models, with outcomes ranging from mortality and cardiac arrest to acute kidney injury and arrhythmia. In this review article, we summarize the stateof- the-art in related works covering data processing, inference, and model evaluation, in the context of outcome prediction models developed using data extracted from electronic health records.We also discuss limitations of prominent modeling assumptions and highlight opportunities for future research.
Farah Shamout, Tingting Zhu, David A Clifton

2865 related Products with: Machine Learning for Clinical Outcome Prediction.

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#32746365   2020/06/24 To Up

Segmentation of White Blood Cell, Nucleus and Cytoplasm in Digital Haematology Microscope Images: A Review-Challenges, Current and Future Potential Techniques.

Segmentation of white blood cells in digital haematology microscope images represents one of the major tools in the diagnosis and evaluation of blood disorders. Pathological examinations are being the gold standard in many haematology and histophathology, and also play a key role in the diagnosis of diseases. In clinical diagnosis, white blood cells are analysed by pathologists from peripheral blood smears samples of patients. This analysis is mainly based on morphological features and characteristics of the white blood cells and their nuclei and cytoplasm, including, shapes, sizes, colours, textures, maturity stages and staining processes. Recently, Computer Aided Diagnosis techniques have been rapidly growing in the digital haematology area related to white blood cells, and their nuclei and cytoplasm detection, as well as their segmentation and classification techniques. In digital haematology image analysis, these techniques have played and will continue to play, a vital role for providing traceable clinical information, consolidating pertinent second opinions, and minimizing human intervention. This study outlines, discusses, and introduces the major trends from a particular review of detection and segmentation methods for white blood cells and their nuclei and cytoplasm from digital haematology microscope images.
Khamael Al-Dulaimi, Jasmine Banks, Kien Nguyen, Aiman Al-Sabaawi, Inmaculada Tomeo-Reyes, Vinod Chandran

2914 related Products with: Segmentation of White Blood Cell, Nucleus and Cytoplasm in Digital Haematology Microscope Images: A Review-Challenges, Current and Future Potential Techniques.

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#32746361   2020/07/27 To Up

Study of Real-Time Spatial and Temporal Behavior of Bacterial Biolms Using 2D Impedance Spectroscopy.

The purpose of this paper is to demonstrate the use of 2D impedance spectroscopy to identify biofilm growth on a CMOS biosensor microelectrode-array.
Caleb Begly, David Ackart, Julian Mylius, Randell Basaraba, Adam J Chicco, Thomas Chen

2006 related Products with: Study of Real-Time Spatial and Temporal Behavior of Bacterial Biolms Using 2D Impedance Spectroscopy.

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#32746351   2020/07/07 To Up

A Chip Integrity Monitor for Evaluating Moisture/Ion Ingress in mm-Sized Single-Chip Implants.

For mm-sized implants incorporating silicon integrated circuits, ensuring life-time operation of the chip within the corrosive environment of the body still remains a critical challenge. For the chips packaging, various polymeric and thin ceramic coatings have been reported, demonstrating high biocompatibility and barrier properties. Yet, for the evaluation of the final packaging and lifetime prediction, the conventional helium leak test method can no longer be used due to the mm-size of such implants. Alternatively, accelerated soak studies are typically used instead. For such studies, early detection of moisture/ion ingress using an in-situ platform may result in a better prediction of lifetime functionality. In this work, we have developed such a platform on a CMOS chip. The changes in the inter layer dielectric resistance within the chip represent the ingress, and are tracked by the implemented chip, which consists of a sensing array and an on-chip measurement engine. The measurement system uses a novel charge/discharge based time-mode resistance sensor that can be implemented using simple yet highly robust circuitry. The sensor array is implemented together with the measurement engine in a standard 0.18 m 6-metal CMOS process. The platform was validated through a series of dry and wet measurements. Wet measurements in saline demonstrated the sensitivity of the platform in detecting moisture/ion ingress. Such a platform could be used both in accelerated soak studies and during the implant's life-time for monitoring the integrity of the chips packaging.
Omer Can Akgun, Kambiz Nanbakhsh, Vasiliki Giagka, Wouter Serdijn

1812 related Products with: A Chip Integrity Monitor for Evaluating Moisture/Ion Ingress in mm-Sized Single-Chip Implants.

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#32746333   2020/08/03 To Up

Biogenic Synthesis of Zinc Oxide Nanoparticles by Bryophyllum pinnatum and its Acute Oral Toxicity Evaluation in Wistar Rats.

The evaluation of toxic effects of nanoparticles (NPs) has become an important aspect of Nanotechnology research in the 21st century. The present investigation deals with the green synthesis of biogenic zinc oxide nanoparticles (ZnO-NPs) using Bryophyllum pinnatum leaves, their characterization and evaluation of acute oral toxicity in Wistar rats. The characterization of synthesized ZnO-NPs revealed maximum absorbance at 307 nm on UV-Vis spectrophotometric analysis, NTA showed mean size of particles and mode of the particles distribution as 128.2 nm and 12.6 nm, respectively. Zeta potential was found to be - 0.369 mV. The absorbance shown by FTIR at 3469, 1644, 1355 and 887 cm-1 indicates the involvement of biomolecules that are accountable for capping and stabilization of ZnO-NPs. The XRD assessment further demonstrated the crystalline nature of the ZnO-NP. The TEM analysis of the synthesized ZnO-NPs revealed the presence of spherical NPs with the mean size of 3.7 nm. The acute oral toxicity evaluation in rat showed an approximate median lethal dose to be more than 2000 mg/kg body weight. It is thus concluded that biogenic ZnO-NPs showed absence of acute oral toxicity symptoms at the doses employed in the present study.
Abhilash D Jadhao, Sudhir Shende, Pramod Ingle, Aniket Gade, Sunil W Hajare, Ranjit S Ingole

1782 related Products with: Biogenic Synthesis of Zinc Oxide Nanoparticles by Bryophyllum pinnatum and its Acute Oral Toxicity Evaluation in Wistar Rats.

96tests100 100 μg5 mg100 μg100 assays100ug Lyophilized100ug Lyophilized

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#32746328   2020/07/31 To Up

A New Framework For Automatic Detection of Patients With Mild Cognitive Impairment Using Resting-State EEG Signals.

Mild cognitive impairment (MCI) can be an indicator representing the early stage of Alzheimier's disease (AD). AD, which is the most common form of dementia, is a major public health problem worldwide. Efficient detection of MCI is essential to identify the risks of AD and dementia. Currently Electroencephalography (EEG) is the most popular tool to investigate the presenence of MCI biomarkers. This study aims to develop a new framework that can use EEG data to automatically distinguish MCI patients from healthy control subjects. The proposed framework consists of noise removal (baseline drift and power line interference noises), segmentation, data compression, feature extraction, classification, and performance evaluation. This study introduces Piecewise Aggregate Approximation (PAA) for compressing massive volumes of EEG data for reliable analysis. Permutation entropy (PE) and auto-regressive (AR) model features are investigated to explore whether the changes in EEG signals can effectively distinguish MCI from healthy control subjects. Finally, three models are developed based on three modern machine learning techniques: Extreme Learning Machine (ELM); Support Vector Machine (SVM) and K-Nearest Neighbours (KNN) for the obtained feature sets. Our developed models are tested on a publicly available MCI EEG database and the robustness of our models is evaluated by using a 10-fold cross validation method. The results show that the proposed ELM based method achieves the highest classification accuracy (98.78%) with lower execution time (0.281 seconds) and also outperforms the existing methods. The experimental results suggest that our proposed framework could provide a robust biomarker for efficient detection of MCI patients.
Siuly Siuly, Omer Faruk Alcin, Enamul Kabir, Abdulkadir Sengur, Hua Wang, Yanchun Zhang, Frank Whittaker

2542 related Products with: A New Framework For Automatic Detection of Patients With Mild Cognitive Impairment Using Resting-State EEG Signals.

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