- Contributions from the 2018 Literature on Bioinformatics and Translational Informatics. [Journal Article]Yearb Med Inform 2019; 28(1):190-193YM
- CONCLUSIONS: Thanks to the normalization of open data and open science practices, research in BTI continues to develop and mature. Noteworthy achievements are sophisticated applications of leading edge machine-learning methods dedicated to personalized medicine.
- Formal Medical Knowledge Representation Supports Deep Learning Algorithms, Bioinformatics Pipelines, Genomics Data Analysis, and Big Data Processes. [Journal Article]Yearb Med Inform 2019; 28(1):152-155YM
- CONCLUSIONS: In the KRM selection for 2018, research on semantic representations demonstrated their added value for enhanced deep learning approaches in text mining and for designing novel bioinformatics pipelines based on graph databases. In addition, the ontology structure can enrich the analyses of whole genome expression data. Finally, semantic representations demonstrated promising results to process phenotypic big data.
- Contributions on Clinical Decision Support from the 2018 Literature. [Journal Article]Yearb Med Inform 2019; 28(1):135-137YM
- CONCLUSIONS: Three of the four best papers rely on data-driven methods, and one builds on a knowledge-based approach. While there is currently a trend for data-driven decision support, the promising results of such approaches still need to be confirmed by the adoption of these systems and their routine use.
- A Broader Look: Camera-Based Vital Sign Estimation across the Spectrum. [Journal Article]Yearb Med Inform 2019; 28(1):102-114YM
- CONCLUSIONS: Although some general trends and frequent shortcomings are obvious, the spectrum of publications related to camera-based vital sign estimation is broad. While many creative solutions and unique approaches exist, the lack of standardization hinders comparability of these techniques and of their performance. We believe that sharing algorithms and/ or datasets will alleviate this and would allow the application of newer techniques such as deep learning.
- A multicenter, open-label, controlled trial on acceptance, convenience, and complications of rechargeable internal pulse generators for deep brain stimulation: the Multi Recharge Trial. [Journal Article]J Neurosurg 2019; :1-9JN
- CONCLUSIONS: Overall, patients with movement disorders rated recharging as easy, with low complication rates and acceptable charge burden.
- Deep brain stimulation of the posterior limb of the internal capsule in the treatment of central poststroke neuropathic pain of the lower limb: case series with long-term follow-up and literature review. [Journal Article]J Neurosurg 2019; :1-9JN
- CONCLUSIONS: This series suggests that stimulation of the posterior limb of the internal capsule is safe and effective in treating patients with chronic neuropathic pain affecting the lower limb. The procedure may be a more targeted treatment method than motor cortex stimulation or other neuromodulation techniques in the subset of patients whose pain and spasticity are referred to the lower limbs.
- Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks. [Journal Article]Eur J Cancer 2019; 119:57-65EJ
- CONCLUSIONS: Our findings show that automated classification of dermoscopic melanoma and nevi images is extendable to a multiclass classification problem, thus better reflecting clinical differential diagnoses, while still outperforming dermatologists at a significant level (p < 0.001).
New Search Next
- Laser-triggered polymeric lipoproteins for precision tumor penetrating theranostics. [Journal Article]Biomaterials 2019; 221:119413B
- Natural particles ranging from various cell membranes to nascent proteins are highly optimized for their specific functions in vivo and possess features that are desired in drug delivery carriers. However, the current endeavor in research on bioparticles is still seeking the appropriate strategy to shield multiple agents and circumvent biological hurdles. These issues have propelled the advanceme…
Natural particles ranging from various cell membranes to nascent proteins are highly optimized for their specific functions in vivo and possess features that are desired in drug delivery carriers. However, the current endeavor in research on bioparticles is still seeking the appropriate strategy to shield multiple agents and circumvent biological hurdles. These issues have propelled the advancement of lipid-polymer hybrid nanocarriers, which could be employed as drug reservoirs and strive to meet these expectations. We thereby proposed functionalized biopeptide-lipid hybrid particles, which were applied to encapsulating a PLGA polymeric core together with indocyanine green (ICG) and packaged by a lipoprotein-inspired structural shell. To initiate precision tumor-penetrating performance, tLyP-1-fused apolipoprotein A-I-mimicking peptides (D4F) were exploited to impart tumor-homing and tumor-penetrating biological functions. The sub-100 nm drug vehicle possessed a long circulation time with uniform mono-dispersity but was stable enough to navigate freely, penetrate deeply into tumors and deliver its cargoes to the targeted sites. Moreover, ICG-encapsulated penetrable polymeric lipoprotein particles (PPL/ICG) could realize real-time fluorescence/photoacoustic imaging for monitoring in vivo dynamic distribution. Upon near-infrared (NIR) laser irradiation, PPL/ICG demonstrated a highly efficient phototherapeutic effect to eradicate orthotopic xenografted tumors, resulting in an 88.77% decrease from the initial tumor volume and inhibited tumor metastasis with good biosafety. Therefore, the described bio-strategy opens new avenues for creating polymeric lipoproteins with varied hybrid functionalities, which may be applied to provide a basis and inspiration for improved nanoparticle-based precision theranostic nanoplatforms.