Biomedicine Technology Research Articles

CRISPR/Cas-mediated DNA base editing technology and its application in biomedicine and agriculture

In recent years, the genome editing technologies based on the clustered regularly interspaced short palindromic repeats/CRISPR-associated protein (CRISPR/Cas) have developed rapidly. The system can use homologous directed recombination (HDR) to achieve precise editing that it medicated, but the efficiency is extremely low, which limits its application in agriculture and biomedical fields. As an emerging genome editing technology, the CRISPR/Cas-mediated DNA base editing technologies can achieve targeted mutations of bases without generating double-strand breaks, and has higher editing efficiency and specificity compared with CRISPR/Cas-mediated HDR editing. At present, cytidine base editors (CBEs) that can mutate C to T, adenine base editors (ABEs) that can mutate A to G, and prime editors (PEs) that enable arbitrary base conversion and precise insertion and deletion of small fragments, have been developed. In addition, glycosylase base editors (GBEs) capable of transitioning from C to G and double base editors capable of editing both A and C simultaneously, have been developed. This review summarizes the development, advances, advantages and limitations of several DNA base editors. The successful applications of DNA base editing technology in biomedicine and agriculture, together with the prospects for further optimization and selection of DNA base editors, are discussed.

The principle, data analysis methods, and its applications for brain research into positron emission tomography

<p indent="0mm">Positron emission tomography (PET) is a typical application for nuclear science and technology in biomedicine. A positron-labeled compound is used as a tracer during PET imaging, which traces the corresponding physiological or biochemical processes in the organ being studied. The distribution of the tracer in the organ is displayed via tomographic imaging, which reflects the biological functional status of the organ under certain conditions. This paper will systematically introduce the principles of PET imaging, progress in the data processing methods, and applications for brain imaging.

Sech-Shape Time-Stretched Dissipative Solitons in Anomalous Dispersion Cavity Fiber Lasers

New pulse dynamics, which generates time-stretched dissipative soliton, has been analyzed in theory and demonstrated in experiment. With introducing non-equilibrium saturable absorber (SA) into the laser cavity, the time-dependent loss of SA can balance the intracavity dispersion, while gain and nonlinearity assist to stabilize the pulse. The pulse envelop is in exact sech-shape and the duration can be stretched to sub-microsecond by the cavity dispersion. To verify the dynamics, a mode-locked Er-doped fiber laser (EDFL) is fabricated, in which a piece of Tm-doped fiber (TDF) serves as the non-equilibrium SA. The laser delivers stable nanosecond pulse and its temporal intensity is in exact sech 2 shape. The pulse duration is invariant with the pump power but determined by the cavity length. As large as 155nJ mode-locked pulse has been generated. Furthermore, such mode-locked pulse can serve as ideal pump source to optical parametric oscillators, and will have wide applications in optical communication, material processing and biomedicine technology.

Cover: Special Issue. Laser and optical technologies in biomedicine and ecology

Cover: Special Issue. Laser and optical technologies in biomedicine and ecology

Foreword to the Special Issue on Laser and optical technologies in biomedicine and ecology

Foreword to the Special Issue on Laser and optical technologies in biomedicine and ecology

Digital systems for improving outcomes in patients with primary immune defects.

Healthcare has already been impacted by the fourth industrial revolution exemplified by tip of spear technology, such as artificial intelligence and quantum computing. Yet, there is much to be accomplished as systems remain suboptimal, and full interoperability of digital records is not realized. Given the footprint of technology in healthcare, the field of clinical immunology will certainly see improvements related to these tools. Biomedical informatics spans the gamut of technology in biomedicine. Within this distinct field, advances are being made, which allow for engineering of systems to automate disease detection, create computable phenotypes and improve record portability. Within clinical immunology, technologies are emerging along these lines and are expected to continue. This review highlights advancements in digital health including learning health systems, electronic phenotyping, artificial intelligence and use of registries. Technological advancements for improving diagnosis and care of patients with primary immunodeficiency diseases is also highlighted.

Application of mathematical modelling for the evaluation of the results of systemiс-pulmonary shunts formation

Surgical treatment of congenital heart defects with the obstruction of the outflow tract of the right ventricle can be performed in several stages. The first stage of surgical correction is the creation of a systemic-pulmonary shunt, followed by radical correction. The main complications of systemic-pulmonary shunts are associated with the development of shunt thrombosis and hypervolemia of the pulmonary circulation. Currently, considering the importance of individual selection of a shunt for effective functioning, the main scientific search is aimed at creating optimal methods that consider all the hemodynamic features of a particular patient. Recently, the direction of mathematical modelling and biomechanical analysis in medicine has been actively developing, facilitating the objective evaluation of the accumulated clinical experience and is one of the main tools in evidence-based medicine. The use of computational fluid dynamics methods for modified Blalock–Taussig shunt analysis allows us evaluate the hemodynamic parameters for various configurations of shunts and anastomosis angles and improve the understanding of pathophysiological processes in the cardiovascular system before or after an application of the modified Blalock–Taussig shunt. Here, we provide an overview of the work related to the use of modelling for the calculation of the currents in the aorta–shunt–pulmonary artery system. It is noteworthy that most studies consider the personalised characteristics of the patients and are therefore highly likely to be used in clinical practice. The main hemodynamic parameters that are analysed with the computer calculations are described. Part of the work is devoted to the stages of computer modelling and the limitations in the implementation of these stages. We believe that this manuscript will be of interest to specialists in cardiovascular surgery and to the several scholars working in areas related to the use of digital technologies in medicine, mathematical modelling in medicine and biomechanics. Received 30 January 2020. Revised 25 May 2020. Accepted 9 June 2020. Conflict of interest: Authors declare no conflict of interest. Funding: The work is supported by the program for the development of the Scientific and Educational Mathematical Center of the Volga Federal District (No. 075-02-2020-1478) and a grant for the development of the scientific school of the Perm Region “Computer biomechanics and digital technologies in biomedicine”. Author contributionsConception and design: Yu.S. Sinelnikov, V.B. Arutunyan, A.A. Porodikov, A.N. Biyanov, V.S. Tuktamyshev, M.I. Shmurak, A.R. KhairulinDrafting the article: A.A. Porodikov, A.N. Biyanov, A.G. KuchumovCritical revision of the article: A.N. Biyanov, A.G. KuchumovFinal approval of the version to be published: Yu.S. Sinelnikov, V.B. Arutunyan, A.A. Porodikov, A.N. Biyanov, V.S. Tuktamyshev, M.I. Shmurak, A.R. Khairulin, A.G. Kuchumov

Ethics parallel research: an approach for (early) ethical guidance of biomedical innovation

BackgroundOur human societies and certainly also (bio) medicine are more and more permeated with technology. There seems to be an increasing awareness among bioethicists that an effective and comprehensive approach to ethically guide these emerging biomedical innovations into society is needed. Such an approach has not been spelled out yet for bioethics, while there are frequent calls for ethical guidance of biomedical innovation, also by biomedical researchers themselves. New and emerging biotechnologies require anticipation of possible effects and implications, meaning the scope is not evaluative after a technology has been fully developed or about hypothetical technologies, but real-time for a real biotechnology.Main textIn this paper we aim to substantiate and discuss six ingredients that we increasingly see adopted by ethicists and that together constitute “ethics parallel research”. This approach allows to fulfil two aims: guiding the development process of technologies in biomedicine and providing input for the normative evaluation of such technologies. The six ingredients of ethics parallel research are: (1) disentangling wicked problems, (2) upstream or midstream ethical analysis, (3) ethics from within, (4) inclusion of empirical research, (5) public participation and (6) mapping societal impacts, including hard and soft impacts. We will draw on gene editing, organoid technology and artificial intelligence as examples to illustrate these six ingredients.ConclusionEthics parallel research brings together these ingredients to ethically analyse and proactively or parallel guide technological development. It widens the roles and judgements from the ethicist to a more anticipatory and constructively guiding role. Ethics parallel research is characterised by a constructive, rather than a purely critical perspective, it focusses on developing best-practices rather than outlining worst practice, and draws on insights from social sciences and philosophy of technology.

Cover: Special Issue. Laser and optical technologies in biomedicine and ecology

Cover: Special Issue. Laser and optical technologies in biomedicine and ecology

Foreword to the Special Issue on Laser and optical technologies in biomedicine and ecology

Foreword to the Special Issue on Laser and optical technologies in biomedicine and ecology

Is Big Data the New Stethoscope? Perils of Digital Phenotyping to Address Mental Illness

Advances in applications of artificial intelligence and the use of data analytics technology in biomedicine are creating optimism, as many believe these technologies will fill the need-availability gap by increasing resources for mental health care. One resource considered especially promising is smartphone psychotherapy chatbots, i.e., artificially intelligent bots that offer cognitive behavior therapy to their users with the aim of helping them improve their mental health. While a number of studies have highlighted the positive outcomes of using smartphone psychotherapy chatbots to handle various anxiety related problems no conclusive data illustrate their effectiveness or warrant their use in mental illness diagnosis and treatment settings. Yet smartphone psychotherapy is highly endorsed by experts in the field of mental health research. In this paper, I focus on the specific features of smartphone psychotherapy chatbots intended for the diagnosis and treatment of mental illness and criticize three popular promises; i.e., (i) they enable early diagnosis and intervention through digital phenotyping; (ii) they defy the stigma of mental illness diagnosis and treatment; (iii) they offer increased access to mental health treatment globally. Going against the popular enthusiasm, I argue smartphone psychotherapy chatbots have epistemic and ethical limitations in the diagnosis and treatment of illnesses. In light of these, I encourage researchers, clinicians, policy makers, patients, and caregivers to pause before jumping on the artificial intelligence bandwagon to seek solutions for mental illness on the grounds of these three promises.

The utilization of perspective quantum technologies in biomedicine

Currently, there is a widespread introduction of quantum technologies in human activity. The prospects of quantum technologies use for the needs of biomedicine are considered. The necessity of the development of new quantum technologies and methods for organizing the processing and analysis of large biomedical data is substantiated. Opportunities and prospects of using modern quantum computers for the needs of biomedicine are being analyzed. The prospects for the use of quantum sensors in biomedicine are discussed. The possibility of using quantum communication lines in the near future to transmit confidential personalized biomedical information is being considered. Prospects for using quantum dots for the purpose of killing both multidrug-resistant bacteria and cancer cells are discussed.

The ICTBioMed NCIP Hub: Cancer research in a science gateway consortium

ICTBioMed, the International Consortium for Technology in Biomedicine is a consortium for biomedical collaborative research and the consortium partners believe in decentralization and democratization of science. The consortium works on strategies to develop ready-to-use research initiatives bridging the gap between research, implementation and ready-to-use science. The consortium has identified real science use cases with the help of the collaborative partners to get access of shared data and methods using the principles of science gateways. ICTBioMed has set up an NCIP Hub instance based upon the HUBzero framework and started using it for community research activities. It is an environment for scientific collaboration where researchers can access and take advantage of a variety of resources shared by others. The NCIP Hub supports members with shared access to data, tools, and standards across the cancer research community. Cancer researchers, in principle, have access to a wide range of data and software tools but in practice, however, they make limited use of these resources. Barriers that restrict access include the need to install software locally, inconsistent user interfaces, security concerns and poor documentation. ICTBioMed is developing a cancer science gateway that will greatly simplify analysis in cancer imaging research by offering a single point of entry and a unified interface for multiple tools, databases, and image repositories widely used by the community. The consortium aims at borderless research with a common goal to solve real life biomedical problems by facilitating collaborative research.

Sputtered Mg100-xZnx (0 ≤ x ≤ 100) systems as anode materials for a biodegradable battery aimed for transient bioelectronics

Transient implantable medical devices are gaining research enthusiasm as an emerging technology in biomedicine. To provide on-board powering for such devices, a biodegradable battery is a promising choice. However, the anode material in such batteries, usually Mg or its alloys, suffer from parasitic corrosion and faster discharge kinetics, that limits the lifetime of these devices. In the pursuit of finding a better anode material, herein, the idea of combinatorial development is employed to fabricate a material having a good combination of corrosion resistance and discharge characteristics, by exploring a wider Mg100-xZnx (0 ≤ x ≤ 100 at.%) system. Using magnetron co-sputtering of Mg and Zn, six Mg100-xZnx (x = 0, 6, 20, 34, 41, 100) systems are synthesized. Structural characterization of these systems via X-Ray Diffraction manifests range of microstructures, from fully crystalline to fully amorphous, governed by alloy composition and sputtering conditions. The corrosion investigation of the six systems manifests a generally improving trend upon higher addition of Zn content. Additionally, the discharge performances of the systems are investigated in Phosphate Buffered Saline (PBS) solution, an in-vitro surrogate of physiological fluid, which demonstrates that discharge performances of the sputtered anode materials can be effectively tailored via a prudent design of alloy composition and microstructure.

Cover: Special Issue. Laser and optical technologies in biomedicine and ecology

Cover: Special Issue. Laser and optical technologies in biomedicine and ecology

Foreword to the Special Issue on Laser and optical technologies in biomedicine and ecology

Foreword to the Special Issue on Laser and optical technologies in biomedicine and ecology

A hybrid approach for named entity recognition in Chinese electronic medical record

BackgroundWith the rapid spread of electronic medical records and the arrival of medical big data era, the application of natural language processing technology in biomedicine has become a hot research topic.MethodsIn this paper, firstly, BiLSTM-CRF model is applied to medical named entity recognition on Chinese electronic medical record. According to the characteristics of Chinese electronic medical records, obtain the low-dimensional word vector of each word in units of sentences. And then input the word vector to BiLSTM to realize automatic extraction of sentence features. And then CRF performs sentence-level word tagging. Secondly, attention mechanism is added between the BiLSTM and the CRF to construct Attention-BiLSTM-CRF model, which can leverage document-level information to alleviate tagging inconsistency. In addition, this paper proposes an entity auto-correct algorithm to rectify entities according to historical entity information. At last, a drug dictionary and post-processing rules are well-built to rectify entities, to further improve performance.ResultsThe final F1 scores of the BiLSTM-CRF and Attention-BiLSTM-CRF model on given test dataset are 90.15 and 90.82% respectively, both of which are higher than 89.26%, which is the best F1 score on the test dataset except ours.ConclusionOur approach can be used to recognize medical named entity on Chinese electronic medical records and achieves the state-of-the-art performance on the given test dataset.

Advances and Future Perspectives in 4D Bioprinting.

Three-dimensionally printed constructs are static and do not recapitulate the dynamic nature of tissues. Four-dimensional (4D) bioprinting has emerged to include conformational changes in printed structures in a predetermined fashion using stimuli-responsive biomaterials and/or cells. The ability to make such dynamic constructs would enable an individual to fabricate tissue structures that can undergo morphological changes. Furthermore, other fields (bioactuation, biorobotics, and biosensing) will benefit from developments in 4D bioprinting. Here, the authors discuss stimuli-responsive biomaterials as potential bioinks for 4D bioprinting. Natural cell forces can also be incorporated into 4D bioprinted structures. The authors introduce mathematical modeling to predict the transition and final state of 4D printed constructs. Different potential applications of 4D bioprinting are also described. Finally, the authors highlight future perspectives for this emerging technology in biomedicine.

Visible light sensorless adaptive optics for retinal structure and fluorescence imaging.

Optical coherence tomography (OCT) has emerged as a powerful imaging instrument and technology in biomedicine. OCT imaging is predominantly performed using wavelengths in the near infrared; however, visible light (VIS) has been recently employed in OCT systems with encouraging results for high-resolution retinal imaging. Using a broadband supercontinuum VIS source, we present a sensorless adaptive optics (SAO) multimodal imaging system driven by VIS-OCT for volumetric retinal structural imaging, followed by the acquisition of fluorescence emission. The coherence-gated, depth-resolved VIS-OCT images used for image-guided SAO aberration correction enable high-resolution structural and fluorescence imaging.

The estimation of probability distribution for factor variables with many categorical values.

With recent developments of data technology in biomedicine, factor data such as diagnosis codes and genomic features, which can have tens to hundreds of discrete and unorderable categorical values, have emerged. While considered as a fundamental problem in statistical analyses, the estimation of probability distribution for such factor variables has not studied much because the previous studies have mainly focused on continuous variables and discrete factor variables with a few categories such as sex and race. In this work, we propose a nonparametric Bayesian procedure to estimate the probability distribution of factors with many categories. The proposed method was demonstrated through simulation studies under various conditions and showed significant improvements on the estimation errors from the previous conventional methods. In addition, the method was applied to the analysis of diagnosis data of intensive care unit patients, and generated interesting medical hypotheses. The overall results indicate that the proposed method will be useful in the analysis of biomedical factor data.