Biomedical Objects Research Articles

A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities

A foundation model for joint segmentation, detection and recognition of biomedical objects across nine modalities

Brillouin spectroscopy of medically relevant samples of bovine jugular vein and pericardium

There is the rapid growth in application of Brillouin scattering spectroscopy to biomedical objects in order to characterize their mechanoelastic properties in this way. However, the possibilities and limitations of the method when applied to tissues have not yet been clarified. Here, applicability of Brillouin spectroscopy for testing the elastic response of medically relevant tissues of bovine jugular vein and pericardium was considered. Parameters of the Brillouin peak were studied for samples untreated, diepoxide-fixed, and preserved after treatment in alcohol solutions. It was found that diepoxide cross-linking resulted to a slight tendency to increase the Brillouin position for hydrated tissues. The variations in the position and width of the Brillouin peaks, associated with local fluctuations in water concentration, were reduced after diepoxide treatment in the case of the pericardium, but not in the case of the vein wall. To obtain more information about the elastic response of the protein scaffold without the participation of water, dried samples were also studied. Brillouin spectra of the dried pericardium and vein wall revealed a significant increase in the Brillouin peak position (elastic modulus) after conservation in alcohol. In the case of the vein wall, this effect was found for both collagen and elastin-related peaks, which were identified in the Brillouin spectrum. This result corresponds to a denser packing of fibrous proteins after preservation in alcohol solutions. The ability of Brillouin spectroscopy to independently characterize the effect of treatment on the instantaneous elastic modulus of various tissue components is also attractive for its application in the development of new materials for bioimplants. A comparison of the Brillouin longitudinal and Young’s elastic moduli determined for the hydrated samples of the vein and pericardium showed that there is no clear correspondence between these material parameters. The usefulness of using both experimental methods to obtain new information about the elastic response of the material is discussed.

Image Processing in L1-Norm-Based Discrete Cartesian and Polar Coordinates

This paper proposes a radial image processing method performed in an L1-norm-based discrete polar coordinate system. For this purpose, we address the problem that polar coordinates based on the L2-norm cannot exist in discrete systems and then develop a method for converting Cartesian coordinates to L1-norm-based discrete polar coordinates. The proposed method greatly reduces the directional variance occurring in the Cartesian coordinate system and so processes radial directional images along the directions of the local image signal flows. To verify the usages of the proposed method, it was applied to the stabilization of mass-type breast cancer images, a segmentation of extremely deformable objects such as biomedical objects. In all cases, the proposed method produced superior results compared to the processing in the Cartesian coordinate systems. The proposed method is useful for processing or analyzing diffusing and deformable images such as bio-cell and smoke images.

Techniques and applications of 3D bioprinting

3D bioprinting is an emerging technology that uses computer printing technology and unique bio-ink components to create artificial organs and biomedical objects. It is an interdisciplinary development technology integrating biology, chemistry, materials science, life science and other disciplines, and the technology behind biological 3D printing has improved in its development over the past few decades. Precisely printed biomaterials could benefit both tissue engineering and regenerative medicine. 3D bioprinting technology makes it possible to print tissues and organs, providing favorable conditions for organ transplantation and medical experiments. This paper mainly reviews the development of bioprinting technology and related concepts. According to the morphological change and chemical composition, the commonly used bioprinting materials (bio-inks) and their characteristics are described. The main methods of bioprinting are summarized, including traditional inkjet 3D bioprinting, extrusion 3D bioprinting, laser-assisted 3D bioprinting, photocuring 3D bioprinting and emerging 4D bioprinting and in situ bioprinting technologies. Finally, the paper introduces the development trend of bioprinting in the transplantation of skin, blood vessels and complex organs, as well as the precision research of tumors. In addition, current research challenges and prospects for future bioprinted 3D printing materials are discussed.

Application of a Stochastic Extension of the Analytical Design of Aggregated Regulators to a Multidimensional Biomedical Object

The results of the application of the methods of the synergetic control theory to a high-dimensional immunology object with uncertainty in its descriptions are reported. The control here is the therapy treated as a problem for constructing an optimal cure program. The control object is presented in continuous and discrete forms, i.e., mathematical models given by a system of ordinary differential equations with a bounded disturbance and a system of stochastic difference equations, respectively. Two algorithms for deriving robust regulators applicable to a 10-dimensional nonlinear multi-loop system with unstable limit states, which models an immune response to the hepatitis B infection, are obtained. Analytical control design for a continuous model relies on the method of nonlinear adaptation on the target manifold. The second algorithm represents a stochastic extension of the method of analytical design of aggregated discrete regulators minimizing the variance of the target macro variable. The numerical simulation of the developed control systems indicates the performance of the designed control algorithms. The results of this study can be used as a component part of the mathematical tools of expert systems and decision support systems.

A computable biomedical knowledge object for calculating in-hospital mortality for patients admitted with acute myocardial infarction.

Quality indicators play an essential role in a learning health system. They help healthcare providers to monitor the quality and safety of care delivered and to identify areas for improvement. Clinical quality indicators, therefore, need to be based on real world data. Generating reliable and actionable data routinely is challenging. Healthcare data are often stored in different formats and use different terminologies and coding systems, making it difficult to generate and compare indicator reports from different sources. The Observational Health Sciences and Informatics community maintains the Observational Medical Outcomes Partnership Common Data Model (OMOP). This is an open data standard providing a computable and interoperable format for real world data. We implemented a Computable Biomedical Knowledge Object (CBK) in the Piano Platform based on OMOP. The CBK calculates an inpatient quality indicator and was illustrated using synthetic electronic health record (EHR) data in the open OMOP standard. The CBK reported the in-hospital mortality of patients admitted for acute myocardial infarction (AMI) for the synthetic EHR dataset and includes interactive visualizations and the results of calculations. Value sets composed of OMOP concept codes for AMI and comorbidities used in the indicator calculation were also created. Computable biomedical knowledge (CBK) objects that operate on OMOP data can be reused across datasets that conform to OMOP. With OMOP being a widely used interoperability standard, quality indicators embedded in CBKs can accelerate the generation of evidence for targeted quality and safety management, improving care to benefit larger populations.

Which computable biomedical knowledge objects will be regulated? Results of a UK workshop discussing the regulation of knowledge libraries and software as a medical device.

To understand when knowledge objects in a computable biomedical knowledge library are likely to be subject to regulation as a medical device in the United Kingdom. A briefing paper was circulated to a multi-disciplinary group of 25 including regulators, lawyers and others with insights into device regulation. A 1-day workshop was convened to discuss questions relating to our aim. A discussion paper was drafted by lead authors and circulated to other authors for their comments and contributions. This article reports on those deliberations and describes how UK device regulators are likely to treat the different kinds of knowledge objects that may be stored in computable biomedical knowledge libraries. While our focus is the likely approach of UK regulators, our analogies and analysis will also be relevant to the approaches taken by regulators elsewhere. We include a table examining the implications for each of the four knowledge levels described by Boxwala in 2011 and propose an additional level. If a knowledge object is described as directly executable for a medical purpose to provide decision support, it will generally be in scope of UK regulation as "software as a medical device." However, if the knowledge object consists of an algorithm, a ruleset, pseudocode or some other representation that is not directly executable and whose developers make no claim that it can be used for a medical purpose, it is not likely to be subject to regulation. We expect similar reasoning to be applied by regulators in other countries.

High-Speed Current Switching of Inverted-Staggered Bottom-Gate a-IGZO-Based Thin-Film Transistors with Highly Stable Logic Circuit Operations

High-speed electronic (HSE) systems are an emerging technology with potential applications in various fields, including biomedical imaging devices, display systems, ultrasound detectors, and object recognition. This report presents a study on low-temperature processed inverted-staggered bottom-gate a-IGZO thin-film transistors (TFTs) for measuring fast current switching at higher frequencies. The IGZO TFT exhibits an excellent mobility of 10.51 cm2/(V·s) and a higher on/off ratio of 3.2 × 105. Additionally, it displays highly stable and reliable gate-pulse switching at different frequencies ranging from 1 kHz to 0.2 MHz. Furthermore, logic operations such as inverter, NAND, and NOR gates were successfully performed using the enhancement-type device configuration. The results show stable and reliable voltage transfer responses with respect to the device configurations. Thus, this study not only enables the development of the applicability of the IGZO material in logic operations but also in HSE systems.

Sticky Biomedical Objects: Affective Circulations in Twitter Discussions about Medicinal Cannabis

This article combines qualitative and quantitative methods to examine affectivity in discussions on Twitter about the first years of a pilot programme for medicinal cannabis in Denmark. Starting in 2018, the pilot programme has been the object of much public discussion, including on social media. Drawing on data from the platform Twitter and affect theory from Sara Ahmed (2010 , 2014 ), the article uses a combination of computational methods and close readings to locate and analyse which topics in the debate are particularly affectively charged and what the implications of this affectivity are. The article argues that the circulation of affect here is rooted in wider negotiations and hierarchies of knowledge as this relates to medicine and bodies. In particular, ideas and discourses relating to evidence are circulated in the debate as an object of varying articulations of hopes, dreams, and frustration.

Optofluidic identification of single microorganisms using fiber‐optical‐tweezer‐based Raman spectroscopy with artificial neural network

AbstractRapid and accurate detection of microorganisms is critical to clinical diagnosis. As Raman spectroscopy promises label‐free and culture‐free detection of biomedical objects, it holds the potential to rapidly identify microorganisms in a single step. To stabilize the microorganism for spectrum collection and to increase the accuracy of real‐time identification, we propose an optofluidic method for single microorganism detection in microfluidics using optical‐tweezing‐based Raman spectroscopy with artificial neural network. A fiber optical tweezer was incorporated into a microfluidic channel to generate optical forces that trap different species of microorganisms at the tip of the tweezer and their Raman spectra were simultaneously collected. An artificial neural network was designed and employed to classify the Raman spectra of the microorganisms, and the identification accuracy reached 94.93%. This study provides a promising strategy for rapid and accurate diagnosis of microbial infection on a lab‐on‐a‐chip platform.

Two-Level 3D Column-like Nanofilms with Hexagonally-Packed Tantalum Fabricated via Anodizing of Al/Nb and Al/Ta Layers-A Potential Nano-Optical Biosensor.

Reanodizing metal underlayers through porous anodic alumina has already been used extensively to fabricate ordered columns of different metal oxides. Here, we present similar 3D multilayered nanostructures with unprecedented complexity. Two-level 3D column-like nanofilms have been synthesized by anodizing an Al/Nb metal layer in aqueous oxalic acid for forming the first level, and an Al/Ta layer in aqueous tartaric acid for forming the second level of the structure. Both levels were then reanodized in aqueous boric acid. The Ta layer deposited on partially dissolved porous anodic alumina of the first level, with protruding tops of niobia columns, acquired a unique hexagonally-packed structure. The morphology of the first and second levels was determined using scanning electron microscopy. Prolonged etching for 24 h in a 50%wt aqueous phosphoric acid was used to remove the porous anodic alumina. The formation mechanism of aluminum phosphates on the second-level columns in the process of long-time cold etching is considered. The model for the growth of columns on a Ta hexagonally-packed structure of the second level is proposed and described. The described approach can be applied to create 3D two- or three-level column-like systems from various valve metals (Ta, Nb, W, Hf, V, Ti), their combinations and alloys, with adjustable column sizes and scaling. The results of optical simulation show a high sensitivity of two-level column-like 3D nanofilms to biomedical objects and liquids. Among potential applications of these two-level column-like 3D nanofilms are photonic crystals for full-color displays, chemical sensors and biosensor, solar cells and thermoresponsive shape memory polymers.

Analyzing Overlaid Foreign Objects in Chest X-rays-Clinical Significance and Artificial Intelligence Tools.

The presence of non-biomedical foreign objects (NBFO), such as coins, buttons and jewelry, and biomedical foreign objects (BFO), such as medical tubes and devices in chest X-rays (CXRs), make accurate interpretation difficult, as they do not indicate known biological abnormalities like excess fluids, tuberculosis (TB) or cysts. Such foreign objects need to be detected, localized, categorized as either NBFO or BFO, and removed from CXR or highlighted in CXR for effective abnormality analysis. Very specifically, NBFOs can adversely impact the process, as typical machine learning algorithms would consider these objects to be biological abnormalities producing false-positive cases. It holds true for BFOs in CXRs. This paper examines detailed discussions on numerous clinical reports in addition to computer-aided detection (CADe) with diagnosis (CADx) tools, where both shallow learning and deep learning algorithms are applied. Our discussion reflects the importance of accurately detecting, isolating, classifying, and either removing or highlighting NBFOs and BFOs in CXRs by taking 29 peer-reviewed research reports and articles into account.

Flow-injection amperometric determination of adrenalin, melatonin, and Cortisol on the electrode modified by gold - palladium binary system and Nation film

Pharmaceuticals containing steroid hormones and their synthetic analogues are widely used in medicine. Accurate determination of the hormone content in biomedical objects is an urgent problem in modem analytical chemistry. A method for the selective and highly sensitive amperometric determination of adrenaline, melatonin, and cortisol in a flow-injection system has been developed. A scheme of a two-detector flow-injection system was proposed for the simultaneous determination of the adrenaline, melatonin, and cortisol content. Screen-printed carbon electrodes (SPE) with one or two working electrodes modified by gold-palladium binary system, which exhibited catalytic activity upon electrooxidation of organic compounds under study were used as detectors. A high sensitivity of the determination is attributed to the catalytic properties of the metal modifier: the transition between the metal and binary system leads to an increase in the catalytic current of hormones oxidation. The selectivity of the adrenaline determination in the presence of melatonin and cortisol is provided by the difference in the potentials of hormone oxidation at the developed electrode. For the selective determination of melatonin and cortisol the surface of the working electrode was modified by the Nation film. The potential difference between the oxidation peaks of adrenaline, melatonin and cortisol on the modified electrode was 300 mV. The proposed method was tested in analysis of real urine samples. The flow-injection scheme was supplemented with a dialyzer and a chromatographic mini-column to eliminate the interfering effect of electrophilic compounds. The linear logarithmic dependence of the analytical signal on the concentration of adrenaline, melatonin and cortisol is observed in the range from 5.0 x 10-10 to 5.0 x 10-3 M, from 5.0 x 10-11 to 5.0 x 10-3 M, and from 5.0 x 10-12 to 5.0 x 10-3 M, respectively. Amperometric determination of hormones in a flow-injection system leads to an increase in the productivity of analysis, decrease in the sample consumption and provides for automation of the process.

How Medical Students Apply Their Biomedical Science Knowledge to Patient Care in the Family Medicine Clerkship.

The online version contains supplementary material available at 10.1007/s40670-022-01697-5.

TP-DDI: A Two-Pathway Deep Neural Network for Drug-Drug Interaction Prediction.

Adverse drug-drug interactions (DDIs) can severely damage the body. Thus, it is essential to accurately predict DDIs. DDIs are complex processes in which many factors can cause interactions. Rather than merely considering one or two of the factors, we design a two-pathway drug-drug interaction framework named TP-DDI that uses multimodal data for DDI prediction. TP-DDI effectively explores the combined effect of a topological structure-based pathway and a biomedical object similarity-based pathway to obtain multimodal drug representations. For the topology-based pathway, we focus on drug chemistry structures through the self-attention mechanism, which can capture hidden critical relationships, especially between pairs of atoms at remote topological distances. For the similarity-based pathway, our model can emphasize useful biomedical objects according to the channel weights. Finally, the fusion of multimodal data provides a holistic view of DDIs by learning the complementary features. On a real-world dataset, experiments show that TP-DDI can achieve better performance than the state-of-the-art models. Moreover, we can find the most critical substructures with certain interpretability in the newly predicted DDIs.

Circle Representation for Medical Object Detection.

Box representation has been extensively used for object detection in computer vision. Such representation is efficacious but not necessarily optimized for biomedical objects (e.g., glomeruli), which play an essential role in renal pathology. In this paper, we propose a simple circle representation for medical object detection and introduce CircleNet, an anchor-free detection framework. Compared with the conventional bounding box representation, the proposed bounding circle representation innovates in three-fold: (1) it is optimized for ball-shaped biomedical objects; (2) The circle representation reduced the degree of freedom compared with box representation; (3) It is naturally more rotation invariant. When detecting glomeruli and nuclei on pathological images, the proposed circle representation achieved superior detection performance and be more rotation-invariant, compared with the bounding box. The code has been made publicly available: https://github.com/hrlblab/CircleNet.

AMPEROMETRIC IMMUNOSENSORS BASED ON CARBON NANOMATERIALS AND RHENIUM CLUSTERS FOR THE DETERMINATION OF TRICYCLIC ANTIDEPRESSANTS IN A SEQUENTIAL INJECTION SYSTEM

A method of sequential injection determination of tricyclic antidepressants (amitriptyline, desipramine, imipramine) using amperometric immunosensors based on screen-printed graphite electrodes modified by carbon nanomaterials (carbon nanotubes, graphene oxide or fullerene) in combination with hexarhenium chalcogenide clusters is proposed. Sequential injection analysis was performed at a sweep rate of 10 mV/s; the flow rate (supporting electrolyte – phosphate buffer solution with pH 7.0) was also varied from 20 to 40 µl/s. Composition of the modifier affects the analytical capability of immunosensors. Screening of various types of modifiers showed that the immunosensor based on graphene oxide and cyanide complexes of rhenium chalcogenide clusters exhibited the highest sensitivity of 23.9±0.9 with a range of working concentrations of 1·10–10–1·10–5 M, and even wider range of detectable concentrations, 1·10–10–1·10–4 M was observed for the immunosensor based on fullerene and cyanide complexes of rhenium chalcogenide clusters. The lowest limit of the determined contents was (4–7)·10–11 M. Relative standard deviation of repeatability (Sr) did not exceed 0.046. The results obtained show that the proposed immunosensors can be used in sequential injection determination of trace amounts of medicinal compounds (antidepressants) in biomedical objects.

The problem of brief interaction of two amorphous bodies

The author has proposed a model of brief interaction of two amorphous bodies with boundary conditions of the third and fourth kind in the amorphous body without a convective massflux. Consideration has been given to the thermophysical aspect of formation of the temperature sensation of a biomedical object (BMO) on contact with the amorphous body with a different temperature. The procedure of short measurements in the stage of irregular thermal regime (pulse method) was applied to investigation of thermal conductivity of various anatomical sections of the BMO skin as a function of its temperature. It has been shown experimentally that thermal conductivity grows with temperature and is within 0.29–0.48 W/(m K). The total relative error of the method of thermal conductivity measurements amounted to ∼ 5%. It has been proposed that analytical calculation of the surface temperature of the BMO on contact be modeled as a combination of the temperatures in liquid and solid media by using the criterion of moisture-content percentage in the BMO.

A Biomedical Knowledge Graph System to Propose Mechanistic Hypotheses for Real-World Environmental Health Observations: Cohort Study and Informatics Application.

BackgroundKnowledge graphs are a common form of knowledge representation in biomedicine and many other fields. We developed an open biomedical knowledge graph–based system termed Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP). ROBOKOP consists of both a front-end user interface and a back-end knowledge graph. The ROBOKOP user interface allows users to posit questions and explore answer subgraphs. Users can also posit questions through direct Cypher query of the underlying knowledge graph, which currently contains roughly 6 million nodes or biomedical entities and 140 million edges or predicates describing the relationship between nodes, drawn from over 30 curated data sources.ObjectiveWe aimed to apply ROBOKOP to survey data on workplace exposures and immune-mediated diseases from the Environmental Polymorphisms Registry (EPR) within the National Institute of Environmental Health Sciences.MethodsWe analyzed EPR survey data and identified 45 associations between workplace chemical exposures and immune-mediated diseases, as self-reported by study participants (n= 4574), with 20 associations significant at P<.05 after false discovery rate correction. We then used ROBOKOP to (1) validate the associations by determining whether plausible connections exist within the ROBOKOP knowledge graph and (2) propose biological mechanisms that might explain them and serve as hypotheses for subsequent testing. We highlight the following three exemplar associations: carbon monoxide-multiple sclerosis, ammonia-asthma, and isopropanol-allergic disease.ResultsROBOKOP successfully returned answer sets for three queries that were posed in the context of the driving examples. The answer sets included potential intermediary genes, as well as supporting evidence that might explain the observed associations.ConclusionsWe demonstrate real-world application of ROBOKOP to generate mechanistic hypotheses for associations between workplace chemical exposures and immune-mediated diseases. We expect that ROBOKOP will find broad application across many biomedical fields and other scientific disciplines due to its generalizability, speed to discovery and generation of mechanistic hypotheses, and open nature.

Fused Filament Fabrication Three-Dimensional Printing Multi-Functional of Polylactic Acid/Carbon Black Nanocomposites

Conductive Polymer Composites (CPCs) have recently gained an extensive scientific interest as feedstock materials in Fused Filament Fabrication (FFF) Three-dimensional (3D) printing. Polylactic Acid (PLA), widely used in FFF 3D printing, as well as its Carbon Black (CB) nanocomposites at different weight percentage (wt.%) filler loadings (0.5, 1.0, 2.5 and 5.0 wt.%), were prepared via a melt mixing filament extrusion process in this study and utilized to manufacture FFF 3D printed specimens. The nanocomposites were examined for their electrical conductivity. The highest loaded 3D printed CPC (5.0 wt.%) was tested as an electrothermal Joule heating device. Static tensile, flexural, Charpy’s impact and Vickers microhardness mechanical properties were investigated for the neat and PLA/CB 3D printed nanocomposites. Dynamic Mechanical Analysis (DMA) revealed a stiffening mechanism for the PLA/CB nanocomposites. Scanning Electron Microscopy (SEM) elucidated the samples’ internal and external microstructural characteristics. The PLA/CB 5.0 wt.% nanocomposite demonstrated also antibacterial properties, when examined with a screening process, against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). It can be envisaged that the 3D printed PLA/CB CPCs exhibited a multi-functional performance, and could open new avenues towards low-cost personalized biomedical objects with complex geometry, amongst others, i.e., surgery tools, splints, wearables, etc.