Applications In Disease Diagnostics Research Articles

Transient shuttle for a widespread neural probe with minimal perturbation

Bioelectronic implants in the deep brain provide the opportunity to monitor deep brain activity with potential applications in disease diagnostics and treatment. However, mechanical mismatch between a probe and brain tissue can cause surgical trauma in the brain and limit chronic probe-based monitoring, leading to performance degradation. Here, we report a transient shuttle-based probe consisting of a PVA and a mesh-type probe. A rigid shuttle based on PVA implants an ultrathin mesh probe in the target deep brain without a tangle, while creating both a sharp edge for facile penetration into the brain and an anti-friction layer between the probe and brain tissue through dissolving its surface. The capability to shuttle dissolved materials can exclude the retracted process of the shuttle in the brain. Complete dissolution of the shuttle provides a dramatic decrease (~1078-fold) in the stiffness of the probe, which can therefore chronically monitor a wide area of the brain. These results indicate the ability to use a simplistic design for implantation of wide and deep brain probes while preventing unnecessary damage to the brain and probe degradation during long-term use.

ATPSpin: A Single Microfluidic Platform that Produces Diversified ATPS-Alginate Microfibers.

Microfluidic spinning is emerging as a useful technique in the fabrication of alginate fibers, enabling applications in drug screening, disease modeling, and disease diagnostics. In this paper, by capitalizing on the benefits of aqueous two-phase systems (ATPS) to produce diverse alginate fiber forms, we introduce an ATPS-Spinning platform (ATPSpin). This ATPS-enabled method efficiently circumvents the rapid clogging challenges inherent to traditional fiber production techniques by regulating the interaction between alginate and cross-linking agents like Ba2+ ions. By varying system parameters under the guidance of a regime map, our system produces several fiber forms─solid, hollow, and droplet-filled─consistently and reproducibly from a single device. We demonstrate that the resulting alginate fibers possess distinct features, including biocompatibility. We also encapsulate HEK293 cells in the microfibers as a proof-of-concept that this versatile microfluidic fiber generation platform may have utility in tissue engineering and regenerative medicine applications.

Charge-Based Isolation of Extracellular Vesicles from Human Plasma.

Extracellular vesicles (EVs) have garnered significant attention due to their potential applications in disease diagnostics and management. However, the process of isolating EVs, primarily from blood samples, is still suboptimal. This is mainly attributed to the abundant nature of soluble proteins and lipoproteins, which are often separated together with EVs in the end products of conventional isolation methods. As such, we devise a single-step charge-based EV isolation method by utilizing positively charged beads to selectively remove negatively charged major impurities from human plasma via electrostatic interaction. By carefully controlling the buffer pH, we successfully collected EVs from undesired plasma components with superior purity and yield compared to conventional EV collection methods. Moreover, the developed process is rapid, taking only about 20 min for overall EV isolation. The charge-based isolation can ultimately benefit the EV-based liquid biopsy field for the early diagnosis of various diseases.

A review of self-supervised, generative, and few-shot deep learning methods for data-limited magnetic resonance imaging segmentation.

Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with applications in disease diagnostics, intervention, and treatment planning. Accurate MRI segmentation is critical for diagnosing abnormalities, monitoring diseases, and deciding on a course of treatment. With the advent of advanced deep learning frameworks, fully automated and accurate MRI segmentation is advancing. Traditional supervised deep learning techniques have advanced tremendously, reaching clinical-level accuracy in the field of segmentation. However, these algorithms still require a large amount of annotated data, which is oftentimes unavailable or impractical. One way to circumvent this issue is to utilize algorithms that exploit a limited amount of labeled data. This paper aims to review such state-of-the-art algorithms that use a limited number of annotated samples. We explain the fundamental principles of self-supervised learning, generative models, few-shot learning, and semi-supervised learning and summarize their applications in cardiac, abdomen, and brain MRI segmentation. Throughout this review, we highlight algorithms that can be employed based on the quantity of annotated data available. We also present a comprehensive list of notable publicly available MRI segmentation datasets. To conclude, we discuss possible future directions of the field-including emerging algorithms, such as contrastive language-image pretraining, and potential combinations across the methods discussed-that can further increase the efficacy of image segmentation with limited labels.

Toxicological Effects of Metal Nanoparticles Employed in Biomedicine: Biocompatibility, Clinical Trials, and Future Perspective

AbstractMetal nanoparticles play a crucial role in the medical industry due to its desirable properties such as antimicrobial activity, anti‐cancer property, and its application in disease diagnostics. These properties enable the nanoparticles to be used as efficient medical devices for various treatments as well as drug delivery systems. Despite all the positives, metal nanoparticles are known for causing toxicity in the living system. The toxicological effects of metal nanoparticles are due to their size, surface*e coating, and the dose administered. Therefore, it is important to study the toxic effects of these nanoparticles before they are used as medical devices for various treatments. This review focuses on the five major metal nanoparticles used in the medical field, namely; silver, gold, iron oxide, zinc oxide, and titanium dioxide nanoparticles. The non‐exhaustive review consists of an introduction to the toxicological effects of these nanoparticles, the biocompatibility, and the current and future clinical perspective on metal nanoparticles.

Viscoelastic microfluidics for enhanced separation resolution of submicron particles and extracellular vesicles.

Manipulation, focusing, and separation of submicron- and nanoparticles such as extracellular vesicles (EVs), viruses and bacteria have broad applications in disease diagnostics and therapeutics. Viscoelastic microfluidic technology emerges as a promising technique, and it shows an unparalleled capacity to manipulate and separate submicron particles in a high resolution based on the elastic effects of non-Newtonian mediums. The maximum particle separation resolution for the reported state-of-the-art viscoelastic microfluidics is around 200 nm. To further enhance the reseparation resolution, this work develops a viscoelastic microfluidic device that can achieve a finer separation resolution up to 100 nm, by optimising the operating conditions such as flow rate, flow rate ratio and polyethylene oxide (PEO) concentration. With these optimised conditions, we separated a ternary mixture of 100 nm, 200 nm and 500 nm polystyrene particles, with purities above 90%, 70% and 82%, respectively. Furthermore, we also applied the developed viscoelastic microfluidic device for the separation of cancer cell-secreted extracellular vesicles (EVs) into three different size groups. After single processing, the separation efficiencies for small EVs (sEVs, <150 nm), medium EVs (mEVs, 150-300 nm), and large EVs (>300 nm) were 86%, 80% and 50%, respectively. The enrichment factors for the three EV groups were 2.4, 1.1 and 1.3, respectively. Moreover, we observed an unexpected effect of high PEO concentrations (2000-5000 ppm) on the lateral migration of nanoparticles where nanoparticles of up to 50 nm surprisingly can migrate and concentrate at the middle of the microchannel. This simple and label-free viscoelastic microfluidic device possesses excellent potential for sorting submicron particles for various chemical, biological, medical and environmental applications.

Low fouling electrochemical sensing interfaces based on Bovine serum albumin hydrogel for the detection of protein biomarkers in human serum

The development of electrochemical biosensor capable of detecting specific biomarkers in real complex biological samples remains a challenge significantly relevant to a range of disease diagnostic applications. Herein an antifouling electrochemical biosensor suitable for biomarker detection in human serum was constructed based on protein hydrogels. A typical protein bovine serum albumin (BSA) was crosslinked with glutaraldehyde to form a hydrogel, which was freeze-dried and re-swollen to exhibit excellent antifouling capability. The rheological testing revealed that the prepared BSA hydrogel possessed good elasticity with a critical strain value of about 600 %, which is important for the construction of stable hydrogel-based biosensors. Following the immobilization of CA125 antibodies onto the BSA hydrogel modified electrode, an electrochemical biosensor for the detection of CA125 was constructed, with a linear range of 0.1 ∼ 1000 U mL−1 and a limit of detection of 0.026 U mL−1. Owing to the unique properties of the BSA hydrogel, the biosensor exhibited good stability and excellent antifouling performances, and it was able to detect CA125 in human serum with acceptable accuracy. The strategy of constructing low fouling biosensors based on hydrogels prepared from BSA with biocompatibility and widespread availability represented a very promising advance along the road to develop biosensing devices with robust operation in complex biological fluids.

(Invited) Magnetofluidic Platforms for Point-of-Care Detection of Infectious Diseases

Commercialized rapid POC PCR technologies are either too slow, lack antimicrobial resistance data, or are too costly for widespread adoption in resource-limited settings. This talk discusses the use of magnetofluidic platforms coupled with inexpensive disposable assay cartridges to automate, accelerate, and simplify PCR tests of infectious diseases. Instead of traditional fluidic strategies for sample handling and assay automation, magnetofluidic technologies use the movement of magnetic beads through discrete droplets of reagents to capture, purify, and transfer analytes for amplification and/or detection, eliminating the need for large, complex instrumentation and fluidics typically associated with clinical laboratory PCR tests. Miniaturized and focused thermal cycling enabled by magnetofluidic PCR significantly shortens the turnaround time of a DNA/RNA test to <15 min. We demonstrated the versatile use of portable magnetofluidic platforms for various infectious disease diagnostic applications, including POC detection of sexually transmitted infections and antimicrobial susceptibility, multiplex detection of SARS-CoV-2 and respiratory pathogens, and HIV viral load testing.

Laccase-Conjugated Nanostructured ZnFe2O4/rGO-Modified Electrode-Based Interfaces for Electrochemical Impedance Monitoring of Adrenaline: A Promising Biosensor for Management of Neurodegenerative Disorders.

A propitious biosensor for adrenaline (AD) detection in bovine serum albumin (BSA) real samples, which can be used for diagnosis and treatment of neurodegenerative disorders, is reported here. The biosensor consists of a La/ZF/rGO/ITO bioelectrode, which is fabricated by electrophoretic deposition of zinc ferrite/reduced graphene oxide (ZF/rGO) nanohybrid followed by drop casting of laccase (La) enzymes. The material characterization and electrochemical studies revealed that the ZF/rGO nanohybrid enhanced the electroactive surface and facilitated direct electron transfer between the electrode and electrolyte interface, resulting in enhanced electrocatalytic performance. The cyclic voltammetry and electrochemical impedance spectroscopy results asserted that the ZF/rGO nanohybrid decreased the charge-transfer resistance (Rct) and increased the surface adsorption, leading to a high diffusion coefficient (D) of 0.192 cm2/s. The biosensor exhibited a high sensitivity of 0.71 Ω/μM cm2, a good linear range (0.1 to 140 μM with R2 = 0.98), and a low limit of detection (LOD) is 12.5 μM, demonstrating the synergic effect of ZF and rGO in the La/ZF/rGO/ITO bioelectrode with AD. The biosensor also exhibited high selectivity and stability (55 days) in the presence of interfering substances and in BSA samples, with a recovery percentage close to 100 ± 5% RSD, indicating its potential biosensing applications for real-world applications in disease diagnostics, monitoring, and treatment.

Three-Dimensional Fractal Analysis of the Interstitial Cells of Cajal Networks of Gastrointestinal Tissue Specimens.

Several functional gastrointestinaldisorders (FGIDs) have been associated with the degradation or remodeling of the network of interstitial cells of Cajal (ICC). Introducing fractal analysis to the field of gastroenterology as a promising data analytics approach to extract key structural characteristics that may provide insightful features for machine learning applications in disease diagnostics. Fractal geometry has advantages over several physically based parameters (or classical metrics) for analysis of intricate and complex microstructures that could be applied to ICC networks. In this study, three fractal structural parameters: Fractal Dimension, Lacunarity, and Succolarity were employed to characterize scale-invariant complexity, heterogeneity, and anisotropy; respectively of three types of gastric ICC network structures from a flat-mount transgenic mouse stomach. The Fractal Dimension of ICC in the longitudinal muscle layer was found to be significantly lower than ICC in the myenteric plexus and circumferential muscle in the proximal, and distal antrum, respectively (both p < 0.0001). Conversely, the Lacunarity parameters for ICC-LM and ICC-CM were found to be significantly higher than ICC-MP in the proximal and in the distal antrum, respectively (both p < 0.0001). The Succolarity measures of ICC-LM network in the aboral direction were found to be consistently higher in the proximal than in the distal antrum (p < 0.05). The fractal parameters presented here could go beyond the limitation of classical metrics to provide better understanding of the structural-functional relationship between ICC networks and the conduction of gastric bioelectrical slow waves.

Enzymatic DNA repairing amplification-powered construction of an Au nanoparticle-based nanosensor for single-molecule monitoring of cytosine deaminase activity in cancer cells

APOBEC3A (A3A) is a cytidine deaminase with critical roles in molecular diagnostics. Herein, we demonstrate the enzymatic DNA repairing amplification-powered construction of an Au nanoparticle-based nanosensor for single-molecule monitoring of A3A activity in cancer cells. Target A3A can convert cytosine (C) in substrate probe to uracil (U), and then the template binds with substrate probe to form a dsDNA containing U/A base pairs. Uracil DNA glycosylase (UDG) excises the U base to produce an apurinic/apyrimidinic (AP) site that can be cleaved by apurinic/apyrimidic endonuclease 1 (APE1) to obtain the substrate fragment with 3′-OH end. Subsequently, the substrate fragment initiates cyclic enzymatic repairing amplification (ERA), releasing trigger-1 and trigger-2. The resultant trigger-1 can act as the primer to induce multiple cycles of cyclic ERA, producing numerous trigger-1 and trigger-2. The hybridization of trigger-2 with signal probe forms the dsDNA duplexes with an AP site, inducing the cyclic cleavage of signal probes by APE1 to release abundant Cy5 molecules from the AuNPs. Released Cy5 molecules can be easily quantified by single-molecule imaging. This nanosensor allows for specific and sensitive detection of A3A activity with a detection limit of 0.855 aM, and it can further measure kinetic parameters, screen inhibitors, and quantify endogenous A3A activity at the single-cell level, with prospect application in disease diagnostics and therapy.

Amplification-Free Detection of Sars-Cov-2 and Respiratory Syncytial Virus Using CRISPR Cas13a and Graphene Field-Effect Transistors

The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) systems have recently received notable attention for their applications in nucleic acid detection. Despite many attempts, the majority of current CRISPR-based biosensors in infectious respiratory disease diagnostic applications still require target preamplifications. This study reports a new biosensor for amplification-free nucleic acid detection via harnessing the trans-cleavage mechanism of Cas13a and ultrasensitive graphene field-effect transistors (gFETs). CRISPR Cas13a-gFET achieves the detection of SARS-CoV-2 and respiratory syncytial virus (RSV) genome down to 1 attomolar without target preamplifications. Additionally, we validate the detection performance using clinical SARS-CoV-2 samples, including those with low viral loads (Ct value >30). Overall, these findings establish our CRISPR Cas13a-gFET among the most sensitive amplification-free nucleic acid diagnostic platforms to date.

Self-assembly of molecular beacons through metal ion coordination for fluorescence imaging of miRNA in living cells.

Fluorescence nanosensors based on functional nucleic acids have been explored as a powerful sensing platform for disease-relevant miRNAs. This work developed a new hybrid nanosensor (Zr-B) through coordination-driven self-assembly of Zr ions and beacons. The prepared nanosensor exhibited high loading efficiency of beacons and could achieve sensitive and specific detection for miRNAs. The hybrid nanosensor could transfer beacons into living cells efficiently and maintain high stability and biocompatibility in the biological environment, achieving effective miRNA fluorescence imaging in living cells. Therefore, the resultant nanosensor holds potential for applications in disease diagnostics.

Retrospective on molecular assay design for detecting pan-orthopox viruses and prospective on mpox laboratory preparedness and readiness

The landscape of in vitro diagnostic (IVD) devices encompasses a broad range of tests that have been used to detect and diagnose pathogens, especially tropical diseases, for decades. The COVID-19 pandemic exemplified the greater need for bringing IVDs from the laboratory directly to the consumer, and recent outbreaks such as mpox, Sudan ebolavirus, and Marburg virus further reinforce this need. The increased emergence of tropical disease outbreaks requires more agile development, higher performance, and mass production of IVD devices. Furthermore, lessons learned in previous device developments can sometimes be used to accelerate new disease diagnostic applications. As an example, we describe one case history of an earlier pan-orthopox viral assay that detected smallpox variola and vaccinia strains, and also discerned related strains including mpox. This work established the foundation for the molecular detection of orthopox viruses, which could be mobilized to address public health needs once an emergency declaration was made that opened the FDA pathway for issuing an emergency use authorization for the use of these assays. Thus, the utilization of knowledge from earlier investments was shown to enhance preparedness and readiness. Here in this retrospective, we elaborate on the processes that enable this approach, including multi-disciplinary and multisectoral collaborations to accomplish a holistic, one health world.

Diagnostic Molecular Markers for Identification of Different Races and a Pathotype of Columbia Root Knot Nematode

Columbia root-knot nematode, Meloidogyne chitwoodi, parasitizes potato plants and causes visible small brown dots in the tuber flesh that dramatically reduce the market value of the crop. In the Pacific Northwest, two races of M. chitwoodi, Race 1 and Race 2, and a pathotype, Race 1Roza, exist. The races and pathotype of M. chitwoodi are primarily differentiated based on host tests. Currently, M. chitwoodi can be differentiated from M. hapla and other Meloidogyne spp. based on morphology and molecular markers; however, the different pathotypes of M. chitwoodi cannot be differentiated using the aforementioned techniques. Based on the in silico genome comparison of M. chitwoodi Race 1, Race 2, and Race 1Roza, we developed diagnostic molecular markers that could successfully differentiate between M. chitwoodi races and the pathotype. We also developed three race-specific markers that can specifically amplify Race 1, Race 2, or Race 1Roza. Overall, we have potential markers that can successfully differentiate the two races and one pathotype of M. chitwoodi through simplex PCR, which has a potential application in plant disease diagnostics. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Engineering of catalytic hairpin-rigidified Y-shaped DNA-functionalized nanomachine to rapidly detect mRNA.

The catalytic hairpin-rigidified Y-shaped DNA through layer-by-layer assembly has beenfixed on the surface of copper sulfide nanoparticles for the detection of survivin mRNA. The distance between the CHA probes fixed on the Y-shaped DNA is significantly shortened. The results show that the fluorescence of this nanomachine reached the maximum value in 50 min (excitation wavelength at 488 nm and emission wavelength 526 nm), and its reaction rate is more than 5-fold faster than that of the free-CHA control system. In addition, the nanomachine showed high sensitivity (LOD of 3.5 pM) and high specificity for the survivin mRNA detection. Given its fast response time and excellent detection performance, we envision that the catalytic hairpin-rigidified Y-shaped DNA-functionalized nanomachine will offer potential applications in disease diagnostics and clinical applications.

Deamination-triggered exponential signal amplification for chemiluminescent detection of cytosine deaminase at the single-cell level.

We construct a sensitive chemiluminescent biosensor for sensitive detection of cytosine deaminase APOBEC3A based on deamination-triggered exponential signal amplification. This biosensor displays good specificity and high sensitivity, and it can screen APOBEC3A inhibitors and measure endogenous APOBEC3A at the single-cell level, with prospective applications in disease diagnostics and therapy.

Metagenomics and Whole Genome Sequencing in Clinical Microbiology: A Narrative Review

The role of Whole Genome Sequencing (WGS) in clinical microbiology is increasing and is not restricted to molecular epidemiology alone. With the advent of third-generation sequencing technologies, its applications in infectious disease diagnostics have further expanded to include the direct identification of microorganisms from primary clinical samples, prediction of antimicrobial resistance (including antiviral resistance) by detecting resistance genes, and detection of virulence genes. Untargeted metagenomic sequencing of clinical samples can provide a promising platform for the comprehensive diagnosis of infections. This article outlines the applications and scope of WGS and metagenomic sequencing in routine clinical microbiology, along with the challenges and practical issues in their implementation.

Single-cell transcriptional and functional analysis of dopaminergic neurons in organoid-like cultures derived from human fetal midbrain.

Significant efforts are ongoing to develop refined differentiation protocols to generate midbrain dopamine (DA) neurons from pluripotent stem cells (PSCs) for application in disease modeling, diagnostics, drug screening, and cell-based therapies for Parkinson's Disease (PD). An increased understanding of the timing and molecular mechanisms promoting the generation of distinct subtypes of human midbrain DA during development will be essential for guiding future efforts to generate molecularly defined and subtype-specific DA neurons from PSCs. Here, we used droplet-based single-cell RNA sequencing to transcriptionally profile the developing human ventral midbrain (VM) when the DA neurons are generated (6-11 weeks post-conception) and their subsequent differentiation into functional mature DA neurons in primary fetal 3D organoid-like cultures. This approach revealed that 3D cultures are superior to monolayer conditions for their ability to generate and maintain mature DA neurons; hence they have the potential to be used for studying human VM development. These results provide a unique transcriptional profile of the developing human fetal VM and functionally mature human DA neurons, which can be used to guide stem cell-based therapies and disease modeling approaches in PD.

BepiPred-3.0: Improved B-cell epitope prediction using protein language models.

B-cell epitope prediction tools are of great medical and commercial interest due to their practical applications in vaccine development and disease diagnostics. The introduction of protein language models (LMs), trained on unprecedented large datasets of protein sequences and structures, tap into a powerful numeric representation that can be exploited to accurately predict local and global protein structural features from amino acid sequences only. In this paper, we present BepiPred-3.0, a sequence-based epitope prediction tool that, by exploiting LM embeddings, greatly improves the prediction accuracy for both linear and conformational epitope prediction on several independent test sets. Furthermore, by carefully selecting additional input variables and epitope residue annotation strategy, performance was further improved, thus achieving unprecedented predictive power. Our tool can predict epitopes across hundreds of sequences in minutes. It is freely available as a web server and a standalone package at https://services.healthtech.dtu.dk/service.php?BepiPred-3.0 with a user-friendly interface to navigate the results.