Sensor Array for Detection of Early Stage Parkinson's Disease before Medication

Volatile organic compounds analysis as promising biomarkers for Parkinson's disease diagnosis: A systematic review and meta-analysis

OBJECTIVE

Researchers are investigating the potential of volatile organic compounds (VOCs) obtained from exhaled breath and sebum as non-invasive tools for early Parkinson's disease (PD) diagnosis. The present study aims to assess the feasibility of using VOC analysis for PD diagnosis and determine the overall diagnostic accuracy of the proposed tests.

METHODS

We performed systematic searches based on the PRISMA guidelines to identify relevant studies on VOCs in PD diagnosis using exhaled breath or sebum samples. The selected articles were described, and meta-analysis was conducted on those that provided the sensitivity and specificity data.

RESULTS

Out of 1268 articles initially identified, 8 met the inclusion criteria and provided specific sensitivity and specificity data for PD, which were included in the current meta-analysis. The pooled analysis of these findings showed a mean area under the receiver operating characteristic curve of 0.85, a sensitivity of 0.81 (95% confidence interval (CI): 0.72, 0.88), and a specificity of 0.76 (95% CI: 0.66, 0.84).

CONCLUSION

The analysis of VOCs in exhaled breath and sebum has shown promise as a new avenue for non-invasive diagnosis of PD. VOCs' ability to distinguish PD from healthy controls suggests their potential clinical application in screening for the disease. Consequently, VOCs hold significant potential as biomarkers for PD diagnosis and offer a promising novel approach to identifying and diagnosing the condition.

Sensitivity of Sniffer Dogs for a Diagnosis of Parkinson's Disease: A Diagnostic Accuracy Study

BACKGROUND

The diagnostic criteria for Parkinson's disease (PD) remain complex, which is especially problematic for nonmovement disorder experts. A test is required to establish a diagnosis of PD with improved accuracy and reproducibility.

OBJECTIVE

The study aimed to investigate the sensitivity and specificity of tests using sniffer dogs to diagnose PD.

METHODS

A prospective, diagnostic case-control study was conducted in four tertiary medical centers in China to evaluate the accuracy of sniffer dogs to distinguish between 109 clinically established medicated patients with PD, 654 subjects without PD, 37 drug-naïve patients with PD, and 185 non-PD controls. The primary outcomes were sensitivity and specificity of sniffer dog's identification.

RESULTS

In the study with patients who were medicated, when two or all three sniffer dogs yielded positive detection results in a sample tested, the index test sensitivity, specificity, and positive and negative likelihood ratios were 91% (95% CI: 84%-96%), 95% (95% CI: 93%-97%), and 19.16 (95% CI: 13.52-27.16) and 0.10 (95% CI: 0.05-0.17), respectively. The corresponding sensitivity, specificity, and positive and negative likelihood ratios in patients who were drug-naïve were 89% (95% CI: 75%-96%), 86% (95% CI: 81%-91%), and 6.6 (95% CI: 4.51-9.66) and 0.13 (95% CI: 0.05-0.32), respectively.

CONCLUSIONS

Tests using sniffer dogs may be a useful, noninvasive, fast, and cost-effective method to identify patients with PD in community screening and health prevention checkups as well as in neurological practice. © 2022 International Parkinson and Movement Disorder Society.

The Utility of Breath Analysis in the Diagnosis and Staging of Parkinson's Disease

BACKGROUND

The analysis of volatile organic compounds (VOCs) collected in breath samples has the potential to be a rapid, non-invasive test to aid in the clinical diagnosis and tracking of chronic conditions such as Parkinson's disease (PD).

OBJECTIVE

To assess the feasibility and utility of breath sample analysis done, both at point of collection in clinic and when sent away to be analyzed remotely, to diagnose, stratify and monitor disease course in a moderately large cohort of patients with PD.

METHODS

Breath samples were collected from 177 people with PD and 37 healthy matched control individuals followed over time. Standard clinical data (MDS-UPDRS & cognitive assessments) from the PD patients were collected at the same time as the breath sample was taken, these measures were then correlated with the breath test analysis of exhaled VOCs.

RESULTS

The breath test was able to distinguish patients with PD from healthy control participants and correlated with disease stage. The off-line system (remote analysis) gave good results with overall classification accuracies across a range of clinical measures of between 73.6% to 95.6%. The on-line (in clinic) system showed comparable results but with lower levels of correlation, varying between 33.5% to 82.4%. Chemical analysis identified 29 potential molecules that were different and which may relate to pathogenic pathways in PD.

CONCLUSION

Breath analysis shows potential for PD diagnostics and monitoring. Both off-line and on-line sensor systems were easy to do and provided comparable results which will enable this technique to be easily adopted in clinic if larger studies confirm our findings.

Smell tests can discriminate Parkinson's disease patients from healthy individuals: A meta-analysis

BACKGROUND

Olfactory impairment is common in Parkinson's disease (PD). The authors aimed to identify the clinical tests used to assess olfactory function and examine their ability to distinguish PD with different disease duration from healthy individuals with physiological aging.

METHODS

Cross-sectional studies published until May 2020 that assessed the olfaction of individuals with PD using search terms related to PD, olfactory function, and assessment were searched on PubMed, PsycInfo, Cinahl, and Web of Science databases.

RESULTS

Twelve smell tests were identified from the reviewed studies (n = 125) that assessed 8776 individuals with PD. Data of 6593 individuals with PD and 8731 healthy individuals were included in the meta-analyses. Individuals with PD presented worse performance than healthy individuals, regardless of the smell test used. The University of Pennsylvania Smell Identification Test (UPSIT) was used by most studies (n = 2310 individuals with PD) and presented smaller heterogeneity. When the studies were subclassified according to the years of PD duration, there were no significant differences.

CONCLUSION

All smell tests were able to discriminate the olfactory function of PD from that of healthy individuals, although the UPSIT was widely used. The abnormal olfaction was not related to the disease duration. Systematic review protocol registration (PROSPERO/2020-CRD42020160878).

Carbon nanomaterials for cardiovascular theranostics: Promises and challenges

Cardiovascular diseases (CVDs) are the leading cause of death worldwide. Heart attack and stroke cause irreversible tissue damage. The currently available treatment options are limited to "damage-control" rather than tissue repair. The recent advances in nanomaterials have offered novel approaches to restore tissue function after injury. In particular, carbon nanomaterials (CNMs) have shown significant promise to bridge the gap in clinical translation of biomaterial based therapies. This family of carbon allotropes (including graphenes, carbon nanotubes and fullerenes) have unique physiochemical properties, including exceptional mechanical strength, electrical conductivity, chemical behaviour, thermal stability and optical properties. These intrinsic properties make CNMs ideal materials for use in cardiovascular theranostics. This review is focused on recent efforts in the diagnosis and treatment of heart diseases using graphenes and carbon nanotubes. The first section introduces currently available derivatives of graphenes and carbon nanotubes and discusses some of the key characteristics of these materials. The second section covers their application in drug delivery, biosensors, tissue engineering and immunomodulation with a focus on cardiovascular applications. The final section discusses current shortcomings and limitations of CNMs in cardiovascular applications and reviews ongoing efforts to address these concerns and to bring CNMs from bench to bedside.

Biodiagnostics in an era of global pandemics-From biosensing materials to data management

The novel corona virus SARS‐CoV‐2 (COVID‐19) has exposed the world to challenges never before seen in fast diagnostics, monitoring, and prevention of the outbreak. As a result, different approaches for fast diagnostic and screening are made and yet to find the ideal way. The current mini‐review provides and examines evidence‐based innovative and rapid chemical sensing and related biodiagnostic solutions to deal with infectious disease and related pandemic emergencies, which could offer the best possible care for the general population and improve the approachability of the pandemic information, insights, and surrounding contexts. The review discusses how integration of sensing devices with big data analysis, artificial Intelligence or machine learning, and clinical decision support system, could improve the accuracy of the recorded patterns of the disease conditions within an ocean of information. At the end, the mini‐review provides a prospective on the requirements to improve our coping of the pandemic‐related biodiagnostics as well as future opportunities.

Fabricating and printing chemiresistors based on monolayer-capped metal nanoparticles

Chemiresistors that are based on monolayer-capped metal nanoparticles (MCNPs) have been used in a wide variety of innovative sensing applications, including detection and monitoring of diagnostic markers in body fluids, explosive materials, environmental contaminations and food quality control. The sensing mechanism is based on reversible swelling or aggregation and/or changes in dielectric constant of the MCNPs. In this protocol, we describe a procedure for producing MCNP-based chemiresistive sensors that is reproducible from device to device and from batch to batch. The approach relies on three main steps: (i) controlled synthesis of gold MCNPs, (ii) fabrication of electrodes that are surrounded with a microbarrier ring to confine the deposited MCNP solution and (iii) a tailor-made drying process to enable evaporation of solvent residues from the MCNP sensing layer to prevent a coffee-ring effect. Application of this approach has been shown to produce devices with ±1.5% variance-a value consistent with the criterion for commercial sensors-as well as long shelf life and stability. Fabrication of chemical sensors based on dodecanethiol- or 2-ethylhexanethiol-capped MCNPs with this approach provides high sensitivity and accuracy in the detection of volatile organic compounds (e.g., octane and decane), toxic gaseous species (e.g., HCl and NH₃) in air and simulated mixtures of lung and gastric cancer from exhaled breath.

Responsive Thin-Film Interference Colors from Polaronic Conjugated Block Copolymers

Colors responsive to the chemical environment can form the basis for simple and highly accessible diagnostic tools. Herein, the charge modulation of conjugated polymers is demonstrated as a new mechanism for chemically responsive structural colors based on thin-film interference. A liquid-liquid interfacial self-assembly is employed to create a conjugated block copolymer film that is flexible, transferable, and highly homogeneous in thickness over a large area. Gold (Au) complexes are introduced in the self-assembly process for in situ oxidation of conjugated polymers into a hole-polaronic state that renders the polymer film responsive to the chemical environment. When transferred onto a reflective substrate, the film shows thickness-dependent tunable reflective colors due to the optical interference. Furthermore, it experiences drastic changes in its dielectric behavior upon switching of the polaronic state, thereby enabling large modulations to the interferometric colors. Such responsive thin-film colors, in turn, can be used as a simple and intuitive multicolor readout for the recognition of reductive vapors including biological decomposition products.

Respiratory Function and Dysfunction in Parkinson-Type Neurodegeneration

Parkinson's disease (PD) is most commonly manifested by the presence of motor symptoms. However, non-motor symptoms occur several years before the onset of motor symptoms themselves. Hallmarks of dysfunction of the respiratory system are still outside the main focus of interest, whether by clinicians or scientists, despite their indisputable contribution to the morbidity and mortality of patients suffering from PD. In addition, many of the respiratory symptoms are already present in the early stages of the disease and efforts to utilize these parameters in the early diagnosis of PD are now intensifying. Mechanisms that lead to the development and progression of respiratory symptoms are only partially understood. This review focuses mainly on the comparison of respiratory problems observed in clinical studies with available findings obtained from experimental animal models. It also explains pathological changes observed in non-neuronal tissues in subjects with PD.

Screening for gastric cancer using exhaled breath samples

BACKGROUND

The aim was to derive a breath-based classifier for gastric cancer using a nanomaterial-based sensor array, and to validate it in a large screening population.

METHODS

A new training algorithm for the diagnosis of gastric cancer was derived from previous breath samples from patients with gastric cancer and healthy controls in a clinical setting, and validated in a blinded manner in a screening population.

RESULTS

The training algorithm was derived using breath samples from 99 patients with gastric cancer and 342 healthy controls, and validated in a population of 726 people. The calculated training set algorithm had 82 per cent sensitivity, 78 per cent specificity and 79 per cent accuracy. The algorithm correctly classified all three patients with gastric cancer and 570 of the 723 cancer-free controls in the screening population, yielding 100 per cent sensitivity, 79 per cent specificity and 79 per cent accuracy. Further analyses of lifestyle and confounding factors were not associated with the classifier.

CONCLUSION

This first validation of a nanomaterial sensor array-based algorithm for gastric cancer detection from breath samples in a large screening population supports the potential of this technology for the early detection of gastric cancer.

From radioactive ligands to biosensors: binding methods with olfactory proteins

In this paper, we critically review the binding protocols currently reported in the literature to measure the affinity of odorants and pheromones to soluble olfactory proteins, such as odorant-binding proteins (OBPs), chemosensory proteins (CSPs) and Niemann-Pick class C2 (NPC2) proteins. The first part contains a brief introduction on the principles of binding and a comparison of the techniques adopted or proposed so far, discussing advantages and problems of each technique, as well as their suitable application to soluble olfactory proteins. In the second part, we focus on the fluorescent binding assay, currently the most widely used approach. We analyse advantages and drawbacks, trying to identify the causes of anomalous behaviours that have been occasionally observed, and suggest how to interpret the experimental data when such events occur. In the last part, we describe the state of the art of biosensors for odorants, using soluble olfactory proteins immobilised on biochips, and discuss the possibility of using such approach as an alternative way to measure binding events and dissociation constants.