Materials for Dentoalveolar Bioprinting: Current State of the Art

Although current treatments can successfully address a wide range of complications in the dentoalveolar region, they often still suffer from drawbacks and limitations, resulting in sub-optimal treatments for specific problems. In recent decades, significant progress has been made in the field of tissue engineering, aiming at restoring damaged tissues via a regenerative approach. Yet, the translation into a clinical product is still challenging. Novel technologies such as bioprinting have been developed to solve some of the shortcomings faced in traditional tissue engineering approaches. Using automated bioprinting techniques allows for precise placement of cells and biological molecules and for geometrical patient-specific design of produced biological scaffolds. Recently, bioprinting has also been introduced into the field of dentoalveolar tissue engineering. However, the choice of a suitable material to encapsulate cells in the development of so-called bioinks for bioprinting dentoalveolar tissues is still a challenge, considering the heterogeneity of these tissues and the range of properties they possess. This review, therefore, aims to provide an overview of the current state of the art by discussing the progress of the research on materials used for dentoalveolar bioprinting, highlighting the advantages and shortcomings of current approaches and considering opportunities for further research.

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Bio-Based Alternatives to Phenol and Formaldehyde for the Production of Resins

Polymers ◽

10.3390/polym12102237 ◽

2020 ◽

Vol 12 (10) ◽

pp. 2237 ◽

Cited By ~ 2

Author(s):

P. R. Sarika ◽

Paul Nancarrow ◽

Abdulrahman Khansaheb ◽

Taleb Ibrahim

Keyword(s):

Raw Materials ◽

Phenol Formaldehyde ◽

Raw Material ◽

Wood Industry ◽

Suitable Material ◽

The Past ◽

Wide Range ◽

Recent Developments ◽

Sustainable Materials ◽

Materials Used

Phenol–formaldehyde (PF) resin continues to dominate the resin industry more than 100 years after its first synthesis. Its versatile properties such as thermal stability, chemical resistance, fire resistance, and dimensional stability make it a suitable material for a wide range of applications. PF resins have been used in the wood industry as adhesives, in paints and coatings, and in the aerospace, construction, and building industries as composites and foams. Currently, petroleum is the key source of raw materials used in manufacturing PF resin. However, increasing environmental pollution and fossil fuel depletion have driven industries to seek sustainable alternatives to petroleum based raw materials. Over the past decade, researchers have replaced phenol and formaldehyde with sustainable materials such as lignin, tannin, cardanol, hydroxymethylfurfural, and glyoxal to produce bio-based PF resin. Several synthesis modifications are currently under investigation towards improving the properties of bio-based phenolic resin. This review discusses recent developments in the synthesis of PF resins, particularly those created from sustainable raw material substitutes, and modifications applied to the synthetic route in order to improve the mechanical properties.

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Introduction to redundancy rules: the continuous wavelet transform comes of age

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2017.0258 ◽

2018 ◽

Vol 376 (2126) ◽

pp. 20170258 ◽

Cited By ~ 8

Author(s):

Paul S. Addison

Keyword(s):

Wavelet Transform ◽

Continuous Wavelet Transform ◽

State Of The Art ◽

Structural Characteristics ◽

Continuous Wavelet ◽

Theme Issue ◽

Current State ◽

Analysis Methods ◽

Wide Range ◽

New Form

Redundancy: it is a word heavy with connotations of lacking usefulness. I often hear that the rationale for not using the continuous wavelet transform (CWT)—even when it appears most appropriate for the problem at hand—is that it is ‘redundant’. Sometimes the conversation ends there, as if self-explanatory. However, in the context of the CWT, ‘redundant’ is not a pejorative term, it simply refers to a less compact form used to represent the information within the signal. The benefit of this new form—the CWT—is that it allows for intricate structural characteristics of the signal information to be made manifest within the transform space, where it can be more amenable to study: resolution over redundancy. Once the signal information is in CWT form, a range of powerful analysis methods can then be employed for its extraction, interpretation and/or manipulation. This theme issue is intended to provide the reader with an overview of the current state of the art of CWT analysis methods from across a wide range of numerate disciplines, including fluid dynamics, structural mechanics, geophysics, medicine, astronomy and finance. This article is part of the theme issue ‘Redundancy rules: the continuous wavelet transform comes of age’.

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Fused filament printing of specialized biomedical devices: a state-of-the art review of technological feasibilities with PEEK

Rapid Prototyping Journal ◽

10.1108/rpj-06-2020-0139 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Erfan Rezvani Ghomi ◽

Saeideh Kholghi Eshkalak ◽

Sunpreet Singh ◽

Amutha Chinnappan ◽

Seeram Ramakrishna ◽

...

Keyword(s):

High Performance ◽

State Of The Art ◽

Three Dimensional ◽

Patient Specific ◽

Biomedical Devices ◽

Fused Filament Fabrication ◽

Content Type ◽

Patient Specific Implants ◽

Complex Design ◽

Wide Range

Purpose The potential implications of the three-dimensional printing (3DP) technology are growing enormously in the various health-care sectors, including surgical planning, manufacturing of patient-specific implants and developing anatomical models. Although a wide range of thermoplastic polymers are available as 3DP feedstock, yet obtaining biocompatible and structurally integrated biomedical devices is still challenging owing to various technical issues. Design/methodology/approach Polyether ether ketone (PEEK) is an organic and biocompatible compound material that is recently being used to fabricate complex design geometries and patient-specific implants through 3DP. However, the thermal and rheological features of PEEK make it difficult to process through the 3DP technologies, for instance, fused filament fabrication. The present review paper presents a state-of-the-art literature review of the 3DP of PEEK for potential biomedical applications. In particular, a special emphasis has been given on the existing technical hurdles and possible technological and processing solutions for improving the printability of PEEK. Findings The reviewed literature highlighted that there exist numerous scientific and technical means which can be adopted for improving the quality features of the 3D-printed PEEK-based biomedical structures. The discussed technological innovations will help the 3DP system to enhance the layer adhesion strength, structural stability, as well as enable the printing of high-performance thermoplastics. Originality/value The content of the present manuscript will motivate young scholars and senior scientists to work in exploring high-performance thermoplastics for 3DP applications.

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Mosaic Super-resolution via Sequential Feature Pyramid Networks

10.36227/techrxiv.11402130 ◽

2019 ◽

Author(s):

Mehrdad Shoeiby ◽

Mohammad Ali Armin ◽

Sadegh Aliakbarian ◽

Saeed Anwar ◽

Lars petersson

Keyword(s):

State Of The Art ◽

Super Resolution ◽

Autonomous Driving ◽

Single Shot ◽

Current State ◽

Wide Range ◽

Feature Pyramid ◽

Novel Method ◽

Convolutional Lstm ◽

Mosaic Images

<div>Advances in the design of multi-spectral cameras have</div><div>led to great interests in a wide range of applications, from</div><div>astronomy to autonomous driving. However, such cameras</div><div>inherently suffer from a trade-off between the spatial and</div><div>spectral resolution. In this paper, we propose to address</div><div>this limitation by introducing a novel method to carry out</div><div>super-resolution on raw mosaic images, multi-spectral or</div><div>RGB Bayer, captured by modern real-time single-shot mo-</div><div>saic sensors. To this end, we design a deep super-resolution</div><div>architecture that benefits from a sequential feature pyramid</div><div>along the depth of the network. This, in fact, is achieved</div><div>by utilizing a convolutional LSTM (ConvLSTM) to learn the</div><div>inter-dependencies between features at different receptive</div><div>fields. Additionally, by investigating the effect of different</div><div>attention mechanisms in our framework, we show that a</div><div>ConvLSTM inspired module is able to provide superior at-</div><div>tention in our context. Our extensive experiments and anal-</div><div>yses evidence that our approach yields significant super-</div><div>resolution quality, outperforming current state-of-the-art</div><div>mosaic super-resolution methods on both Bayer and multi-</div><div>spectral images. Additionally, to the best of our knowledge,</div><div>our method is the first specialized method to super-resolve</div><div>mosaic images, whether it be multi-spectral or Bayer.</div><div><br></div>

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Climate-dependent propagation of precipitation uncertainty into the water cycle

10.5194/hess-2019-660 ◽

2020 ◽

Author(s):

Ali Fallah ◽

Sungmin O ◽

Rene Orth

Keyword(s):

Hydrological Model ◽

Water Cycle ◽

State Of The Art ◽

Rain Gauge ◽

Multiple Sources ◽

Current State ◽

Wide Range ◽

The Impact ◽

Conceptual Hydrological Model

Abstract. Precipitation is a crucial variable for hydro-meteorological applications. Unfortunately, rain gauge measurements are sparse and unevenly distributed, which substantially hampers the use of in-situ precipitation data in many regions of the world. The increasing availability of high-resolution gridded precipitation products presents a valuable alternative, especially over gauge-sparse regions. Nevertheless, uncertainties and corresponding differences across products can limit the applicability of these data. This study examines the usefulness of current state-of-the-art precipitation datasets in hydrological modelling. For this purpose, we force a conceptual hydrological model with multiple precipitation datasets in > 200 European catchments. We consider a wide range of precipitation products, which are generated via (1) interpolation of gauge measurements (E-OBS and GPCC V.2018), (2) combination of multiple sources (MSWEP V2) and (3) data assimilation into reanalysis models (ERA-Interim, ERA5, and CFSR). For each catchment, runoff and evapotranspiration simulations are obtained by forcing the model with the various precipitation products. Evaluation is done at the monthly time scale during the period of 1984–2007. We find that simulated runoff values are highly dependent on the accuracy of precipitation inputs, and thus show significant differences between the simulations. By contrast, simulated evapotranspiration is generally much less influenced. The results are further analysed with respect to different hydro-climatic regimes. We find that the impact of precipitation uncertainty on simulated runoff increases towards wetter regions, while the opposite is observed in the case of evapotranspiration. Finally, we perform an indirect performance evaluation of the precipitation datasets by comparing the runoff simulations with streamflow observations. Thereby, E-OBS yields the best agreement, while furthermore ERA5, GPCC V.2018 and MSWEP V2 show good performance. In summary, our findings highlight a climate-dependent propagation of precipitation uncertainty through the water cycle; while runoff is strongly impacted in comparatively wet regions such as Central Europe, there are increasing implications on evapotranspiration towards drier regions.

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Bladder Substitution: The Role of Tissue Engineering and Biomaterials

Processes ◽

10.3390/pr9091643 ◽

2021 ◽

Vol 9 (9) ◽

pp. 1643

Author(s):

Martina Casarin ◽

Alessandro Morlacco ◽

Fabrizio Dal Moro

Keyword(s):

Tissue Engineering ◽

Urinary Diversion ◽

Mucus Production ◽

Reconstructive Procedures ◽

Suitable Material ◽

Orthotopic Urinary Diversion ◽

Bladder Substitution ◽

Materials Used ◽

Bowel Segments

Tissue engineering could play a major role in the setting of urinary diversion. Several conditions cause the functional or anatomic loss of urinary bladder, requiring reconstructive procedures on the urinary tract. Three main approaches are possible: (i) incontinent cutaneous diversion, such as ureterocutaneostomy, colonic or ileal conduit, (ii) continent pouch created using different segments of the gastrointestinal system and a cutaneous stoma, and (iii) orthotopic urinary diversion with an intestinal segment with spherical configuration and anastomosis to the urethra (neobladder, orthotopic bladder substitution). However, urinary diversions are associated with numerous complications, such as mucus production, electrolyte imbalances and increased malignant transformation potential. In this context, tissue engineering would have the fundamental role of creating a suitable material for urinary diversion, avoiding the use of bowel segments, and reducing complications. Materials used for the purpose of urinary substitution are biological in case of acellular tissue matrices and naturally derived materials, or artificial in case of synthetic polymers. However, only limited success has been achieved so far. The aim of this review is to present the ideal properties of a urinary tissue engineered scaffold and to examine the results achieved so far. The most promising studies have been highlighted in order to guide the choice of scaffolds and cells type for further evolutions.

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AI-driven deep CNN approach for multi-label pathology classification using chest X-Rays

PeerJ Computer Science ◽

10.7717/peerj-cs.495 ◽

2021 ◽

Vol 7 ◽

pp. e495

Author(s):

Saleh Albahli ◽

Hafiz Tayyab Rauf ◽

Abdulelah Algosaibi ◽

Valentina Emilia Balas

Keyword(s):

Neural Networks ◽

Data Augmentation ◽

State Of The Art ◽

Synthetic Data ◽

X Rays ◽

Deep Convolutional Neural Networks ◽

Current State ◽

Pathology Classification ◽

Wide Range ◽

Multi Class Classification

Artificial intelligence (AI) has played a significant role in image analysis and feature extraction, applied to detect and diagnose a wide range of chest-related diseases. Although several researchers have used current state-of-the-art approaches and have produced impressive chest-related clinical outcomes, specific techniques may not contribute many advantages if one type of disease is detected without the rest being identified. Those who tried to identify multiple chest-related diseases were ineffective due to insufficient data and the available data not being balanced. This research provides a significant contribution to the healthcare industry and the research community by proposing a synthetic data augmentation in three deep Convolutional Neural Networks (CNNs) architectures for the detection of 14 chest-related diseases. The employed models are DenseNet121, InceptionResNetV2, and ResNet152V2; after training and validation, an average ROC-AUC score of 0.80 was obtained competitive as compared to the previous models that were trained for multi-class classification to detect anomalies in x-ray images. This research illustrates how the proposed model practices state-of-the-art deep neural networks to classify 14 chest-related diseases with better accuracy.

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Tissue engineering

Oxford Textbook of Rheumatology ◽

10.1093/med/9780199642489.003.0086 ◽

2013 ◽

pp. 664-668

Author(s):

Andrew McCaskie ◽

Paul Genever ◽

Cosimo De Bari

Keyword(s):

Tissue Engineering ◽

Host Tissue ◽

Target Tissue ◽

Cell Therapies ◽

Cell Matrix ◽

Wide Range ◽

Regenerative Approach ◽

Great Relevance ◽

Functional Interface

The field of tissue engineering has developed rapidly over the last few decades and is of great relevance to musculoskeletal therapy and intervention. Tissue engineering strategies are often considered in a simplified form in terms of cells, scaffolds, and additional factors, although it should be noted that successful translation of such a strategy is more complex. There are many variations of usage and combination and it is not necessary for all three to be provided by the proposed treatment. However, the regenerative approach must produce both the quantity and quality of target tissue at the level of the cell, matrix, and environment. Moreover, the regenerated tissue must interact with the host tissue with a seamless biological and functional interface. Tissue engineering, regenerative medicine, and cell therapies have developed significantly over the last few decades and are applicable to a wide range of musculoskeletal applications. Many strategies have been identified that would potentially benefit patients but the future will require successful translation from the laboratory into clinical practice. It is important to identify clinical targets where there is both clinical need and an informed view that the approach is likely to be successful.

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